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Speaker 1: Really really need some breaking news music, although this isn't

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Speaker 1: breaking news. It's the nightcap on seven hundred WLWS. Johnny's

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Speaker 1: theme will just have to do. I guess how you doing,

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Speaker 1: Gary Jeff Well. Day twenty one is over and done,

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Speaker 1: and we continue the federal government shutdown. They're not spending

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Speaker 1: any of our money right now. That's kind of cool.

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Speaker 1: They're not spending our money right now. I mean maybe

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Speaker 1: stuff we want them to spend it on, especially people

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Speaker 1: who work for a living, who have families to support,

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Speaker 1: who are not getting a paycheck right now in this

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Speaker 1: partial government shutdown, and of course the brave men and

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Speaker 1: women of our military who are going to be missing

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Speaker 1: paychecks right and left here if they don't get their

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Speaker 1: act together. Political theater is the only reason they're not

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Speaker 1: spending any of our money is Remember, the government doesn't

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Speaker 1: have a wall of money somewhere in Washington, DC that

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Speaker 1: they just pluck a stack of bills from. It all

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Speaker 1: comes out of you, me, anyone that pays taxes. And

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Speaker 1: believe me, even if you're not paying income tax, you're

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Speaker 1: paying some kind of tax on something somewhere. All the

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Speaker 1: fines and fees and everything at sales tax when you

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Speaker 1: buy something, the money comes from us, and the people

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Speaker 1: in Washington are supposed to represent us, but instead to

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Speaker 1: try and get political cover so somebody like Chuck Schumer

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Speaker 1: doesn't get primaried by AOC and lose his power in

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Speaker 1: the Senate because of stuff like that. They disrupt other

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Speaker 1: people's lives, and of course it really doesn't affect them

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Speaker 1: unless we the people who give them our money to

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Speaker 1: do things for us, unless we the people stand up

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Speaker 1: and realize who the culprits are and the people who

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Speaker 1: are blocking the road. I mean, there's an element of this.

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Speaker 1: I'm not missing a paycheck because the federal government is

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Speaker 1: shut down. You may not be either, but somebody is,

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Speaker 1: and that can cause real hardship, at least for a

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Speaker 1: short period of time. It's getting to be a longer

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Speaker 1: and longer period of time. Senator might not senator, but

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Speaker 1: Speaker of the House Mike Johnson every day comes out

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Speaker 1: in details how it is hurting all of us US

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Speaker 1: citizens that they're not spending our money and highlights the

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Speaker 1: states that are dominated by Democrat senators who won't get

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Speaker 1: up off their haunches and vote to keep the government open. Well,

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Speaker 1: they can negotiate all the rest the end of the

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Speaker 1: Obamacare subsidies and everything else that is not decided yet.

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Speaker 1: But you need to remember Democrats put a sunset on

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Speaker 1: Obamacare subsidies. They run out at the end of December.

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Speaker 1: So if they're you know, waving their hands in the

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Speaker 1: air with their heads on fire, saying, real people are

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Speaker 1: going to lose their healthcare because Republicans won't renegotiate to

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Speaker 1: keep the government open. It's literal male bovine fecal samples.

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Speaker 1: And you know what that amounts to. It's October as

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Speaker 1: we continue to be mired in the government shut down

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Speaker 1: where they're not spending any of our money that we've

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Speaker 1: given them, sometimes foolishly, in fact, I think most of

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Speaker 1: the time foolishly. It's also Breast Cancer Awareness Month, and

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Speaker 1: up next I would like to feature my wife, Chris

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Speaker 1: to two point zero, who is a breast cancer survivor

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Speaker 1: going on three years now. We will talk about that

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Speaker 1: and her upcoming baptism, which is going to happen this

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Speaker 1: coming Sunday.

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Speaker 2: Right after this it's the Nightcap.

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Speaker 1: The government's still shut down, they're not spending any of

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Speaker 1: our money right now, maybe they'd give it back to us,

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Speaker 1: what do you think seven HUNDREDLW. As I mentioned at

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Speaker 1: the top of the show, October being breast cancer awareness

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Speaker 1: month of all, and I think we should always be

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Speaker 1: aware of cancer and the things that we need to

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Speaker 1: do to keep ourselves safe from it, or at least

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Speaker 1: let us know if there's a problem. And I think

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Speaker 1: we always ought to be aware of breasts as men especially,

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Speaker 1: And I am especially aware of my wife's breasts, and

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Speaker 1: I'm certainly acutely aware of the struggle that we went together,

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Speaker 1: threw together as a couple, that she went through when

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Speaker 1: she was diagnosed with breast cancer. And to talk about

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Speaker 1: that and to encourage other people to get their selves checked.

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Speaker 1: You've got a mammogram coming up on Friday, I know,

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Speaker 1: and I just think it's important to get the message

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Speaker 1: out there, and from a personal standpoint, the people who

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Speaker 1: have walked that path, I think it's important we bring

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Speaker 1: in my wife, Chris to two point zero into the

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Speaker 1: nightcab to talk about your journey.

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Speaker 2: Hi, babe, ed, good evening, Good evening. It's great to

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Speaker 2: have you with us.

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Speaker 1: You know, it's almost as good as being home with

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Speaker 1: you talking to you on the phone. Almost so let's

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Speaker 1: let's go back to the beginning. How did you find

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Speaker 1: out that you had breast?

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Speaker 3: Can answer, well, I finally went from my first Mammograham

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Speaker 3: after a few years of pushing by my doctor, and

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Speaker 3: they found it. They found the lump in my right breast.

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Speaker 1: Okay, Oh, and I remember well that weekend when they

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Speaker 1: told you they had found this tumor in your right breast,

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Speaker 1: and you were devastated, as many people are when they

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Speaker 1: get this news. Yeah, almost almost despondent. And it took

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Speaker 1: you exactly two days to figure out that you were

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Speaker 1: going to fight this and beat it. I remember just

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Speaker 1: it was almost like an overnight transition where you just

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Speaker 1: what was what was the thing that made you realize

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Speaker 1: that cancer wasn't going to defeat you in that short

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Speaker 1: amount of time.

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Speaker 3: Well, one with God and two I'm very subthern.

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Speaker 1: Yes you are indeed, So we go and and you

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Speaker 1: went to the consultation.

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Speaker 2: Yes, what was it?

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Speaker 1: What was the next step after you you went for

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Speaker 1: further examination and a scan and all of that.

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Speaker 2: What happened?

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Speaker 3: Yes, then we went to this wonderful surgeon.

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Speaker 4: J.

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Speaker 3: Michael Gunther and Edgewood, Saint Elizabeth, and he was the

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Speaker 3: absolute best that was still when we wear a mask.

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Speaker 3: We got back and he said do you like these things?

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Speaker 3: And we said no. He said, good take them off.

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Speaker 2: Oh yeah, that you know what for me?

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Speaker 1: And I was there with you when when you were

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Speaker 1: seeing the actual scan and he was showing you where

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Speaker 1: the tumor was, us where the tumor was, and like

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Speaker 1: you said, we're married and we're in the mask and

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Speaker 1: the doctor closes the door with the nurse in there

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Speaker 1: with us, and he says, do you guys really like

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Speaker 1: wearing these things? And we go no, because we are

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Speaker 1: vehemently against all the COVID mandates that were still in

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Speaker 1: place at the time. So that was that was twenty

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Speaker 1: two or twenty one, twenty two, Fall of twenty two,

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Speaker 1: and I think I think you found out you had

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Speaker 1: breast cancer during October.

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Speaker 3: Wasn't it October or just it was late September? Yeah,

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Speaker 3: I saw him October and I had my surgery in October.

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Speaker 1: Right, So anyway, he just to kind of move the

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Speaker 1: story along. We get the masks off and he's showing

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Speaker 1: us and you the tumor that they're going to remove,

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Speaker 1: what they plan to do about it. And he said,

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Speaker 1: remember what he said about the tumor.

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Speaker 3: He said it was a wimpy to tumor. He said, yeah,

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Speaker 3: it went be timors.

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Speaker 2: Oh.

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Speaker 1: We both kind of looked at We both kind of

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Speaker 1: looked at each other and looked at him and go, okay,

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Speaker 1: this is this is quite possibly the best news we've

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Speaker 1: heard all day. And uh so then uh they made plans.

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Speaker 1: This was a consultation before the surgery, and the surgery.

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Speaker 3: Happened, and two weeks later I had my surgery yep,

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Speaker 3: and I remember and go ahead and it went fine.

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Speaker 3: It not there was some pain in the all later on,

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Speaker 3: but yeah, it went perfectly.

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Speaker 1: Yeah, we were we were very very lucky, praise God

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Speaker 1: the way that all turned out. So they also took

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Speaker 1: an adjoining lymph node out where they had taken the

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Speaker 1: the one point five centimeter tumor out of your right

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Speaker 1: breast when that isn't in that about how big it was? Yes,

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Speaker 1: all right, So they took the adjoining lymph node because

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Speaker 1: they always do that to make sure the cancer hasn't

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Speaker 1: spread and correct and it was it was not cancer

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Speaker 1: the lymph node, right, but it did some damage to

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Speaker 1: your lymphatic system as far as drained there was a

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Speaker 1: lot of swelling, and uh, it was very uncomfortable for you.

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Speaker 1: Describe that if you can or.

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Speaker 3: Will well, it was swelling. It was full of fluid

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Speaker 3: and blood and would leak on occasion and badly leak.

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Speaker 3: And then it settled down and I started radiation.

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Speaker 1: Yeah, this is Christie. I think this is how you

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Speaker 1: were lucky. We were lucky too. Is that you didn't

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Speaker 1: have to have poison injected into your body, I mean

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Speaker 1: outside the radiation, but you didn't have to have any

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Speaker 1: chemotherapy with your after treatment. And that right usually accompanies

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Speaker 1: something like what you went.

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Speaker 3: Through well, like he said, it was a wimpy tumor.

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Speaker 1: So yeah, so got it all and uh then the

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Speaker 1: radiation was just I mean, boy, that that does it toll?

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Speaker 1: Tell tell people what radiation even the limited How many

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Speaker 1: weeks did you go through.

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Speaker 3: Radiation, Krista, I had twenty treatments total. Yeah, and it

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Speaker 3: was four weeks. I was having them every day for

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Speaker 3: the first couple weeks and by Wednesday, I start on Monday.

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Speaker 3: By Wednesday, I was so wiped out, so tired. I

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Speaker 3: just came home and flapped and slept and.

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Speaker 1: Slept, I remember, and and it really does drain a person.

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Speaker 1: Plus it had the other side effect of because of

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Speaker 1: the intense heat from radiation of miscoloring your breast on

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Speaker 1: that one side.

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Speaker 3: Yeah, I had a really good tan line for oh

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Speaker 3: probably two.

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Speaker 1: Years, right, and the hair underneath your arms on that

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Speaker 1: side was gone. Yeah, yeah, you didn't. You didn't have

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Speaker 1: to shave. You didn't have to shave your pits for

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Speaker 1: like a long time.

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Speaker 3: I remember that, just the one side.

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Speaker 1: I slay it on the other side, right, So what

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Speaker 1: did you call your breast after the surgery and after

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Speaker 1: the radiation, because it just it didn't look quite normal?

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Speaker 2: What'd you call your breast?

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Speaker 3: And I still call it that Franken boob, the Franken boob.

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Speaker 1: Yeah, all right, So let's flash ahead to now it's

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Speaker 1: been three years almost since you were declared cancer free, right, yeah, and.

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Speaker 3: Friday, Friday, I go back to my namigram and I

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Speaker 3: will know and I believe that it will be three

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Speaker 3: years cancer free.

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Speaker 1: It's such a blessing to have you been and it's

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Speaker 1: such a blessing that it turned out the way it did.

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Speaker 1: Not everybody has it turned out the way we did,

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Speaker 1: And we know that we're very, very fortunate so far,

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Speaker 1: very grateful to God and to the surgeons and the

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Speaker 1: people who treated you. And if you don't mind, we'll

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Speaker 1: switch gears here just a little bit. Talking to christ

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Speaker 1: to two point oh. My wife Breast cancer Awareness month.

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Speaker 1: She is a breast cancer survivors. As her shirt says,

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Speaker 1: she's got a great shirt. I love this, this shirt,

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Speaker 1: this shirt you wear from time to time. Cancer picked

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Speaker 1: a fight with the wrong chick, and it certainly did. Yeah,

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Speaker 1: you have made a decision in the last few weeks

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Speaker 1: to do something that you've never done in your life,

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Speaker 1: this coming out.

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Speaker 3: I've been thinking about it for.

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Speaker 5: A while.

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Speaker 2: And what is that?

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Speaker 3: And I'm getting bad sized on Sundays?

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Speaker 2: And you never got you never did it your entire life.

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Speaker 3: No, I wasn't brought up your religion so well.

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Speaker 1: I mean you can be religious about anything. You mean,

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Speaker 1: you weren't brought up in the church. Uh, it wasn't

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Speaker 1: an emphasis.

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Speaker 3: Yeah, No, nobody went so I know, I had to

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Speaker 3: figure it out on my own.

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Speaker 6: No.

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Speaker 1: I think I think God likes it better when we

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Speaker 1: have a personal relationship and you do figure it out

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Speaker 1: on your own.

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Speaker 4: Uh.

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Speaker 2: Yeah, plenty of plenty of help from the Bible. Uh,

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Speaker 2: you can't.

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Speaker 1: You can't get better instruction than the Word of God itself.

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Speaker 1: So this is this is going to happen, and uh,

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Speaker 1: you've been so excited about it ever since.

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Speaker 3: I am I can't wait.

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Speaker 2: But how what do you think?

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Speaker 1: What do you think is going to change as a

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Speaker 1: result of this symbolic act.

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Speaker 3: I think my faith in God it's gonna be so

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Speaker 3: much greater then I can possibly imagine.

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Speaker 2: Well, I want you to.

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Speaker 1: Know that I love you very much, and uh, you

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Speaker 1: know I say it off the radio, so I'm not

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Speaker 1: just saying it for the sake of tonight.

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Speaker 2: I love you very much. I am.

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Speaker 1: I am so proud to be married to you and

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Speaker 1: proud of you, proud of your strength in facing what

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Speaker 1: you know you have faced. I say, we but it's

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Speaker 1: cancer in your body. I've just been there with you.

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Speaker 1: But I and I am so glad for you that

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Speaker 1: you decided to make this decision about being baptized. I

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Speaker 1: think it's tremendous. I have a couple I've been baptized

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Speaker 1: a couple of times. I didn't feel the need to

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Speaker 1: get dunked again. But I'm going to be right there

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Speaker 1: with you on Sunday and We're gonna be at Grace Fellowship,

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Speaker 1: Grace Fellowship Church, the Fort Thomas Campus in the nine

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Speaker 1: o'clock service this coming Sunday morning, when christ To two

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Speaker 1: point zero gets baptized. If you'd like to come join

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Speaker 1: us and celebrate with Christa and with me, that would

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Speaker 1: be wonderful.

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Speaker 2: Baby.

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Speaker 1: I love you, I love you. I'll see you when

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Speaker 1: I get home. You won't see me because you'll be asleep,

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Speaker 1: but I'll see you when I get home and we'll

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Speaker 1: talk then. All right, Absolutely, you can say anything you want.

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Speaker 3: All right, ladies, get your anogram that can save your life.

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Speaker 2: Amen.

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Speaker 1: Thanks Perry, Christa two point zero on the Nightcap. As

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Speaker 1: we continue in moments after News here on seven hundred WLW,

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Speaker 1: as we get into chapter two of tonight's Nightcap into

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Speaker 1: the second half hour, welcoming back a guest that we

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Speaker 1: have had on previously. It's been a couple of months.

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Speaker 1: I think she is not a vaccine denier. She is

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Speaker 1: a vaccine investigator. I think that'd be the best words.

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Speaker 1: She may agree or disagree, and she's also written the

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Speaker 1: book The Ultimate Vaccine Timeline of fact packed history of

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Speaker 1: vaccines and their makers. And she joins us again with

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Speaker 1: a little bit of new information. We'll cover some of

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Speaker 1: the old ground, I'm sure, but just to introduce her

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Speaker 1: to you. But let me bring on shas Khan from London.

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Speaker 3: How are you doing, shas Hi Gary, I'm doing really

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Speaker 3: well in.

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Speaker 1: Yourself, doing well, doing well, London born, Swiss Indian. She

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Speaker 1: is by education, well at least formal education, a creative designer.

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Speaker 1: And then you throw in information junkie, critical thinker, and

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Speaker 1: the bio description Shaws says, somewhat obsessed with vaccines. I

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Speaker 1: can say more than somewhat obsessed with vaccine. You've been

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Speaker 1: studying the history going back, going back hundreds of years

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Speaker 1: of what has become what we know as vaccines today.

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Speaker 1: When does your research actually start? In the book?

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Speaker 7: Well, the first book I put A first entry I

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Speaker 7: put in the book was five seventy eighty because that's

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Speaker 7: the actual time that someone gave the definition of bariola,

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Speaker 7: which was smallpox. And I think definitely are very important

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Speaker 7: to follow along the path the vaccines of anything, really

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Speaker 7: because the definition of wars is important to the understanding.

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Speaker 7: So that's the first entry. But variolation in itself, which

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Speaker 7: was the old technique of scraping either you know, dried

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Speaker 7: small puck gab up the nose or onto the skin.

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Speaker 7: Started about about one thousand, five hundred years ago in Asia.

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Speaker 7: It's not very clear exactly when it started, but it

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Speaker 7: basically came from Asia and then came over to Europe

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Speaker 7: via Turkey into the aristocracy, and then to the US

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Speaker 7: actually through a lot of religious groups. Actually, so there's

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Speaker 7: a long history and from the smallpox vaccine that most

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Speaker 7: people know about from the gener times that's more than

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Speaker 7: two hundred years ago already, So there's a lot of

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Speaker 7: information about vaccines.

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Speaker 2: And in.

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Speaker 1: Ancient China or fifteen hundred years ago, it wasn't about

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Speaker 1: the motive, wasn't how much can we make out of

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Speaker 1: this invention?

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Speaker 2: It was just how do we heal people? Are are

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Speaker 2: save people's lives?

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Speaker 3: When when absolutely it was about protecting.

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Speaker 1: When did the worms start to turn where it became

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Speaker 1: a major I don't know, uh, medical industrial, pharma, pharmaceutical

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Speaker 1: complex thing where uh the goal the ultimate goal was

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Speaker 1: to make as much money as possible.

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Speaker 7: When did that well, Uh, that would be kind of

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Speaker 7: hard to pinpoint. I couldn't say that they started vaccinators

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Speaker 7: started making money obviously from when they started vaccinating in

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Speaker 7: the UK. So that's the first evidence I could find

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Speaker 7: the vaccinators actually receiving financial compensation for the acts of vaccininating.

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Speaker 7: Then the doctors who were the one some of the

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Speaker 7: first who got involved in vaccine farms, which was creating,

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Speaker 7: you know, like farms of cows to produce smallpox vaccine

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Speaker 7: because they saw a business venture in it.

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Speaker 3: Let's let's admitt that was but.

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Speaker 7: As far as like the mass industrial complex where we're

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Speaker 7: at today, that happened after the Second World War, and

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Speaker 7: very much the invention of plastics and the mass production

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Speaker 7: of plastics helped with that with the one single use strangers,

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Speaker 7: but it's still vaccines didn't make a huge amount of

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Speaker 7: money at that point. It was really off to the

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Speaker 7: eighties with the Beadle Acts in the US and also

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Speaker 7: with the Vaccine Injury Compensation Act of nineteen eighty six

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Speaker 7: for the vaccine injury I have had compensation act.

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Speaker 1: Sorry, I have had a guest on also numerous times

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Speaker 1: on this particular topic. His name is Thomas Habiland, and

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Speaker 1: he's an Air Force veteran and he has been studying

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Speaker 1: these embalming reports about the large white fibrous clots found

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Speaker 1: inside corpses that only started showing up after the rollout

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Speaker 1: of the mRNA COVID nineteen vaccines, and you know, along

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Speaker 1: with the cases of myocarditis and other things that have

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Speaker 1: been linked to these vaccines that the public was never

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Speaker 1: warned about, and it's still being swept under the rug

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Speaker 1: in many cases the adverse effects of the mRNA. But

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Speaker 1: are you familiar with the Enbonber's study. There's a brand

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Speaker 1: new one coming out among three four hundred bombers in

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Speaker 1: the country detailing these odd white clots that they are

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Speaker 1: finding inside the corpses that they are working on that

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Speaker 1: they never saw before the COVID nineteen vaccine.

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Speaker 2: Do you know anything about that shots.

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Speaker 7: Yeah, I've heard about this as well, primarily from Jon o'looney,

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Speaker 7: who's a British undertaker as they called them here, who

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Speaker 7: was one of the first to blow the horn and

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Speaker 7: anyway in the UK about these fibers, very strange rubbery

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Speaker 7: like white.

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Speaker 8: Substances clocks that he found sometimes would trail the whole

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Speaker 8: length of a vein or an artery, which was very unusual.

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Speaker 8: So yeah, I haven't been following what the latest developments are,

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Speaker 8: but I would.

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Speaker 7: Imagine that the continuing to find them, and there are

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Speaker 7: very strange, fibrous costs which the authority still seem to

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Speaker 7: refuse to acknowledge and actually, you know, explain or go into,

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Speaker 7: which I mean that follows the whole denial that there

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Speaker 7: is in regards to adverse events following these COVID shots

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Speaker 7: in general, which we're seeing the world over.

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Speaker 1: Yeah, and he also posits, and it gets your opinion

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Speaker 1: on this, that there may have been as many as

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Speaker 1: seventeen million people killed or severely injured or living with

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Speaker 1: these spike protein injuries out of the COVID vaccines. That

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Speaker 1: seems like an awfully high number. Do you think it's

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Speaker 1: in line?

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Speaker 7: Well, he has to remember how many billions of doses

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Speaker 7: have been administered in on the world, I mean on

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Speaker 7: the planet. I mean that's probably understatement and under estimation

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Speaker 7: because we don't really know.

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Speaker 3: I think of all the developing.

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Speaker 7: Countries where there's no kind of surveyance system whatsoever, where

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Speaker 7: people when they die there's no autopsy, any kind of investigations. So, yes,

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Speaker 7: the seventeen million is maybe a conservative estimate. But again

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Speaker 7: we have to remember that we vaccinated over five billion

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Speaker 7: people on this planet with all different types of you know,

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Speaker 7: already varying health issues to start off with, so it could.

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Speaker 3: Be higher than that.

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Speaker 2: Do you believe that.

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Speaker 1: The COVID nineteen vaccines saved many more people than it

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Speaker 1: is injured or affected or killed?

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Speaker 7: Well, based on my experience here, I mean, I'm based

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Speaker 7: in Switzerland and I'm part of a group of medical

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Speaker 7: professionals and health professionals, and what I'm hearing on the

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Speaker 7: field is absolutely not that. I'm hearing way more about

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Speaker 7: injury than anybody being saved.

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Speaker 3: About We have to remember.

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Speaker 7: COVID was not a dangerous disease for the majority of people. Yes,

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Speaker 7: it was dangerous for people who have a certain age,

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Speaker 7: who had certain who are diabetic, who are a beest,

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Speaker 7: who had hypertension. Those people are the ones who are risk.

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Speaker 7: So we've now administered this supposed to be prevent this

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Speaker 7: treatment which can't prevent transmission and doesn't prevent infection to

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Speaker 7: millions and billions of people, story including healthy children, and

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Speaker 7: I from my observations and what I've.

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Speaker 3: Been reading, there's a way a lot more damage.

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Speaker 4: Than the benefits the beneficial sorry that.

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Speaker 7: Things, but the authorities, the regulatory authorities, SPISTHMETIC, FDA, they

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Speaker 7: continue to say the benefits outweigh the risk. So that's

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Speaker 7: the official statement.

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Speaker 2: It's the official statement.

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Speaker 1: Okay, we're talking to Shas Khan, author of the Ultimate

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Speaker 1: Vaccine Timeline, a fact packed history of vaccines and their makers.

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Speaker 1: And this is the thing that caught my eye and

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Speaker 1: dragged at twelve feet Sean W. Shaws when we were

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Speaker 1: getting ready for this, the next cancer fighting mRNA vaccine

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Speaker 1: may already be here. What are they finding out about

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Speaker 1: people who took the COVID nineteen jab and then are

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Speaker 1: receiving immunotherapy for cancer.

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Speaker 2: What do we know about this? And it's a stuff that.

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Speaker 3: Early on it's not a study.

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Speaker 7: It's not a study for people. I mean, the first

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Speaker 7: of all, it's very clear. It was announced at a

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Speaker 7: conference in Berlin, the European Society for Medical Oncology conference

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Speaker 7: was announced by I believe it was doctor Adam Griffin

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Speaker 7: Griffin sorry, at the University of Texas who was saying

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Speaker 7: they did a retrospective analysis on about a thousand patients

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Speaker 7: who had received within one hundred days before their immunity

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Speaker 7: therapy for I believe it was a small cell lung cancer.

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Speaker 7: They saw that about one hundred people who had received

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Speaker 7: the mr and A vaccine in the one hundred days

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Speaker 7: prior to starting munotherapy had a longer survival rate. But

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Speaker 7: this is just a retrospective analysis. It's not a study.

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Speaker 7: They would have to put it into a study to

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Speaker 7: really to make sure that a valid observation or not.

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Speaker 7: And there are too many parameters here which are unclear exactly.

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Speaker 7: You know, what were the age groups of these people,

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Speaker 7: what were the types of you know, did they have

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Speaker 7: any other commmbodities apart from just a cell lung ca answer,

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Speaker 7: what kinds of treatments were they taking. There's lots of

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Speaker 7: unknowns and the fact that the media has just taken

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Speaker 7: this up and run with it, it just shows that

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Speaker 7: they're trying to justify the use of mRNA vaccine for

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Speaker 7: just about anything and not acknowledge the people who have

442
00:27:15,560 --> 00:27:19,359
Speaker 7: been talking about the speedy turbo cancers after vaccination and

443
00:27:19,440 --> 00:27:21,840
Speaker 7: just focus on the potential benefits. And we have to

444
00:27:21,840 --> 00:27:25,000
Speaker 7: remember mRNA initially was kind of developed in the idea

445
00:27:25,119 --> 00:27:28,440
Speaker 7: of cancer therapy, so for people who were sick who

446
00:27:28,520 --> 00:27:31,880
Speaker 7: didn't have necessarily any options, and you know, it could

447
00:27:31,920 --> 00:27:33,640
Speaker 7: be worthwhile and it could be still be a very

448
00:27:33,680 --> 00:27:36,080
Speaker 7: interesting pathway to follow.

449
00:27:36,160 --> 00:27:37,479
Speaker 4: But this was not a study.

450
00:27:37,680 --> 00:27:41,159
Speaker 7: This is a retrospective analysis. It has no conclusions that

451
00:27:41,160 --> 00:27:43,880
Speaker 7: we can actually, you know, hang our head on, and

452
00:27:44,520 --> 00:27:45,080
Speaker 7: it was on a.

453
00:27:45,080 --> 00:27:46,480
Speaker 3: Very small number of patients.

454
00:27:46,520 --> 00:27:48,639
Speaker 7: So we still have to see what comes out of

455
00:27:48,680 --> 00:27:51,359
Speaker 7: this University of Texas when they decided to put it

456
00:27:51,359 --> 00:27:52,439
Speaker 7: into a phase three study.

457
00:27:52,880 --> 00:27:56,360
Speaker 1: All right, So let me ask you, are there any

458
00:27:56,520 --> 00:28:01,240
Speaker 1: vaccines that shas Khan is totally on board with? Any

459
00:28:01,280 --> 00:28:02,959
Speaker 1: of today's modern vaccines?

460
00:28:05,280 --> 00:28:09,000
Speaker 7: Well, unfortunately not anymore. I would have been on board

461
00:28:09,000 --> 00:28:11,520
Speaker 7: with some of the earlier vaccines, especially like the sole

462
00:28:11,560 --> 00:28:14,320
Speaker 7: tetanus one. Even then I would dispute that now, knowing

463
00:28:14,359 --> 00:28:17,320
Speaker 7: what I know about tetanus and the fact that we're

464
00:28:17,359 --> 00:28:19,359
Speaker 7: talking about a disease that was a problem back in

465
00:28:19,359 --> 00:28:21,359
Speaker 7: the days that we had horses for transport, that we

466
00:28:21,400 --> 00:28:25,240
Speaker 7: had manure everywhere, and that we didn't have much sanitation nowadays.

467
00:28:25,280 --> 00:28:26,760
Speaker 4: Absolutely not. I have to be honest.

468
00:28:26,800 --> 00:28:29,040
Speaker 7: I haven't taken a single pharmaceutical drug in the last

469
00:28:29,040 --> 00:28:31,440
Speaker 7: ten years. It's been an experiment I'm doing on myself

470
00:28:31,800 --> 00:28:35,320
Speaker 7: to see if I can actually treat myself without pharmaceuticals,

471
00:28:35,320 --> 00:28:36,320
Speaker 7: and so far, so good.

472
00:28:36,440 --> 00:28:39,760
Speaker 1: Knock on wood, well, I mean, just for the sake

473
00:28:39,800 --> 00:28:43,160
Speaker 1: of this conversation, what kind of treatment are you doing

474
00:28:43,200 --> 00:28:49,000
Speaker 1: for yourself to avoid illness and to stay well?

475
00:28:49,120 --> 00:28:49,320
Speaker 4: Well?

476
00:28:49,360 --> 00:28:52,600
Speaker 7: For myself as the first thing I changed when I

477
00:28:52,680 --> 00:28:54,640
Speaker 7: was getting sick a lot about ten years ago. My

478
00:28:54,680 --> 00:28:57,720
Speaker 7: doctor didn't help me really with anything was drink more

479
00:28:57,800 --> 00:29:00,120
Speaker 7: water and drink pure water. So I made sure I

480
00:29:00,160 --> 00:29:01,680
Speaker 7: was drinking enough at least one and a half to

481
00:29:01,760 --> 00:29:05,360
Speaker 7: two liters a day during some exercise stretching. Vitamin D

482
00:29:05,640 --> 00:29:09,080
Speaker 7: zinc Vitamin D essential oils changed my life. I was

483
00:29:09,080 --> 00:29:11,600
Speaker 7: incredibly skeptical when I first started using them, but I

484
00:29:11,640 --> 00:29:13,760
Speaker 7: have to say I am very impressed by the results

485
00:29:13,800 --> 00:29:17,959
Speaker 7: I've got with essentral oils and simply paying attention to

486
00:29:18,000 --> 00:29:20,600
Speaker 7: my nutrition as well. Like I had gout once and

487
00:29:20,800 --> 00:29:23,640
Speaker 7: my doctor wanted to give me five different pills. All

488
00:29:23,640 --> 00:29:27,040
Speaker 7: I wanted was crutches and got just give me anti inflammatories,

489
00:29:27,080 --> 00:29:30,040
Speaker 7: anti pain killers and the protein pump in the bitter

490
00:29:30,480 --> 00:29:33,760
Speaker 7: an antibiotic which made no sense. And I just stopped

491
00:29:33,840 --> 00:29:35,800
Speaker 7: drinking fizzy drinks. It was as simple as that, and

492
00:29:35,840 --> 00:29:40,080
Speaker 7: it went away from There are solutions, obviously, you know

493
00:29:40,120 --> 00:29:42,120
Speaker 7: it's not an easy solution. Maybe you have to make

494
00:29:42,120 --> 00:29:44,240
Speaker 7: a few changes in your lifestyle, but I rather do

495
00:29:44,320 --> 00:29:45,080
Speaker 7: that than take.

496
00:29:44,920 --> 00:29:45,800
Speaker 3: Pills at the moment.

497
00:29:46,720 --> 00:29:52,560
Speaker 1: Do you find that this total giving in and acquiescence,

498
00:29:53,240 --> 00:29:56,560
Speaker 1: or you know, maybe even just the co mingling of

499
00:29:56,680 --> 00:30:05,160
Speaker 1: government and pharmaceutical maker through their lobbyists has been hurting us?

500
00:30:05,240 --> 00:30:09,160
Speaker 1: And will do you think a person like Robert F.

501
00:30:09,240 --> 00:30:14,880
Speaker 1: Kennedy Junior has a path to maybe make America healthy

502
00:30:14,960 --> 00:30:18,400
Speaker 1: again and to make the world healthy again with recommendations.

503
00:30:19,920 --> 00:30:22,040
Speaker 1: A lot of things have already changed as far as

504
00:30:22,320 --> 00:30:27,560
Speaker 1: mandates and requirements in vaccines just since Donald Trump has

505
00:30:27,560 --> 00:30:30,920
Speaker 1: been in office and RFK Junior has been the Health

506
00:30:30,920 --> 00:30:36,000
Speaker 1: and Human Services Secretary. Do you see any light at

507
00:30:36,000 --> 00:30:38,960
Speaker 1: the end of the tunnel for the US anyway.

508
00:30:38,600 --> 00:30:39,120
Speaker 2: In this.

509
00:30:40,560 --> 00:30:40,720
Speaker 4: Well?

510
00:30:40,800 --> 00:30:41,760
Speaker 3: I certainly hope so.

511
00:30:41,840 --> 00:30:45,080
Speaker 7: I mean the issues of the pharma school industry's interest

512
00:30:45,200 --> 00:30:50,560
Speaker 7: in lobbying in government and NGOs in specifically also societies

513
00:30:50,560 --> 00:30:54,360
Speaker 7: for Medical oncology, these patient advocate groups is coming out

514
00:30:54,400 --> 00:30:56,880
Speaker 7: to the surface, not just in the US, also in Europe.

515
00:30:56,920 --> 00:30:59,480
Speaker 7: So it's bringing to light this serious issue.

516
00:31:00,080 --> 00:31:01,400
Speaker 3: Hoping that Kennedy can make.

517
00:31:01,360 --> 00:31:03,400
Speaker 7: Some headwinds, definitely in the US.

518
00:31:03,440 --> 00:31:04,480
Speaker 4: And you guys do have.

519
00:31:04,400 --> 00:31:07,600
Speaker 7: Mandates for vaccines, which a lot of European countries, including

520
00:31:07,600 --> 00:31:09,680
Speaker 7: the UK and Switzerland do not, so we already have

521
00:31:09,720 --> 00:31:12,800
Speaker 7: an advantage to a certain extent, but there is still

522
00:31:12,880 --> 00:31:19,640
Speaker 7: this this real problem of pharmaceutical industry being completely has

523
00:31:19,360 --> 00:31:24,480
Speaker 7: its tentacles everywhere, and notably FDA, the regulatory agencies MRHA

524
00:31:24,520 --> 00:31:27,720
Speaker 7: and the UK, Swiss Medicare and Swiftland SWISMDIC is financed

525
00:31:27,800 --> 00:31:31,240
Speaker 7: eighty two percent. So hopefully with more and more people

526
00:31:31,280 --> 00:31:34,200
Speaker 7: speaking out and realizing that the pharmacchicol industry doesn't have

527
00:31:34,200 --> 00:31:36,960
Speaker 7: any interest in keeping you healthy because that's not a patient,

528
00:31:37,080 --> 00:31:40,800
Speaker 7: that's not a customer. They need sick people as a

529
00:31:40,840 --> 00:31:41,520
Speaker 7: business model.

530
00:31:41,520 --> 00:31:43,000
Speaker 3: It's as plain as simple as that.

531
00:31:43,120 --> 00:31:46,960
Speaker 7: So hopefully Kennedy can make some headway that will.

532
00:31:47,000 --> 00:31:48,480
Speaker 3: Reverberate into Europe.

533
00:31:48,760 --> 00:31:50,800
Speaker 7: And there are many more consumer groups that have come

534
00:31:50,880 --> 00:31:53,719
Speaker 7: up since COVID because they've seen the corruption directly and

535
00:31:53,920 --> 00:31:56,480
Speaker 7: they're not having it. So there is a real movement

536
00:31:56,600 --> 00:31:58,280
Speaker 7: happening now, which I think is very much in the

537
00:31:58,320 --> 00:32:01,440
Speaker 7: hands of the people and the pharmacy companies, even though

538
00:32:01,440 --> 00:32:04,200
Speaker 7: they have lots of money, there's still a minority people life,

539
00:32:04,240 --> 00:32:06,080
Speaker 7: so I think they're gonna have to look out for

540
00:32:06,120 --> 00:32:08,320
Speaker 7: the grassroots movements and the real ones, not the ones

541
00:32:08,360 --> 00:32:08,960
Speaker 7: that they fund.

542
00:32:10,160 --> 00:32:10,960
Speaker 2: Yeah, exactly.

543
00:32:12,800 --> 00:32:18,120
Speaker 1: What always amazed me, and I think I know why now,

544
00:32:19,000 --> 00:32:21,880
Speaker 1: But what always amazed me in the height of COVID

545
00:32:21,920 --> 00:32:25,920
Speaker 1: and they were pushing the JAB is how every other

546
00:32:25,960 --> 00:32:31,360
Speaker 1: pharmaceutical commercial on TV, in a thirty second commercial, which

547
00:32:31,400 --> 00:32:33,520
Speaker 1: by the way, I don't think should be allowed on television,

548
00:32:35,040 --> 00:32:38,120
Speaker 1: in a thirty second commercial, fifteen seconds of it would

549
00:32:38,200 --> 00:32:42,480
Speaker 1: be the purported side effects. This could happen, You could

550
00:32:42,520 --> 00:32:45,520
Speaker 1: get this if you take this, you know you're gonna

551
00:32:45,560 --> 00:32:49,240
Speaker 1: save your skin, but your kidney is going to fall

552
00:32:49,240 --> 00:32:57,120
Speaker 1: out or whatever. There was never any warning or disclaimer

553
00:32:57,280 --> 00:33:00,000
Speaker 1: on any of the COVID commercials.

554
00:33:00,040 --> 00:33:04,360
Speaker 7: Yes, are you talking about commercials by the government or

555
00:33:04,400 --> 00:33:05,240
Speaker 7: commercials by.

556
00:33:05,120 --> 00:33:11,360
Speaker 1: Pfizer, commercials by Peiser, But commercials by drug companies always

557
00:33:11,560 --> 00:33:14,959
Speaker 1: list the side effects of their drug. They have to,

558
00:33:15,560 --> 00:33:18,320
Speaker 1: they have to put a legal disclaimer, okay, But there

559
00:33:18,360 --> 00:33:21,520
Speaker 1: was never any legal disclaimer about the possible adverse effects

560
00:33:21,520 --> 00:33:25,160
Speaker 1: of the COVID nineteen vaccine. Is because they didn't know

561
00:33:25,520 --> 00:33:29,680
Speaker 1: what the adverse side effects could be, or they just

562
00:33:29,720 --> 00:33:32,640
Speaker 1: weren't telling anybody to continue to push their poison.

563
00:33:34,120 --> 00:33:34,800
Speaker 3: Well they knew.

564
00:33:34,840 --> 00:33:36,680
Speaker 7: I mean, it's interesting that you mentioned that because we

565
00:33:36,680 --> 00:33:40,200
Speaker 7: didn't have any advertisements. Obviously in something we don't. You're

566
00:33:40,360 --> 00:33:42,040
Speaker 7: one of the only countries along with New Zealand, that

567
00:33:42,080 --> 00:33:45,360
Speaker 7: allows prescription drugs, including vaccines, to be advertised on television.

568
00:33:45,720 --> 00:33:48,280
Speaker 7: But in theory, as you said, they should have listed.

569
00:33:48,000 --> 00:33:48,760
Speaker 3: The side effects.

570
00:33:48,760 --> 00:33:52,200
Speaker 7: They were well aware of by the time I minority

571
00:33:52,280 --> 00:33:55,080
Speaker 7: when they started the rollout of the campaign. If it

572
00:33:55,160 --> 00:33:56,840
Speaker 7: was the government, then they could argue, well, it's the

573
00:33:56,840 --> 00:33:59,440
Speaker 7: public service announcement and they didn't need to, which is

574
00:33:59,440 --> 00:34:01,760
Speaker 7: what happened here in Switzerland because we had advertising for

575
00:34:01,840 --> 00:34:04,120
Speaker 7: the vaccine, but it was done and paid for by

576
00:34:04,120 --> 00:34:06,920
Speaker 7: the government, so our taxpayer money, and they didn't have

577
00:34:07,000 --> 00:34:08,759
Speaker 7: to announce any of these side effects, and they just

578
00:34:08,800 --> 00:34:10,960
Speaker 7: basically made it sound like it's your civic duty, and

579
00:34:11,000 --> 00:34:14,280
Speaker 7: they use the very manipulative communication campaign to say basically,

580
00:34:14,520 --> 00:34:17,480
Speaker 7: you're getting vaccinated for the good of society, and there

581
00:34:17,520 --> 00:34:19,960
Speaker 7: was no mention in side effect, no mention of any

582
00:34:19,960 --> 00:34:22,880
Speaker 7: individual risks. But they can do that because of the

583
00:34:22,920 --> 00:34:25,879
Speaker 7: public service announcement. I mean, we actually tried to file

584
00:34:25,920 --> 00:34:28,080
Speaker 7: a complaint with the advertiser that they said that doesn't

585
00:34:28,080 --> 00:34:29,120
Speaker 7: count because it's the government.

586
00:34:29,200 --> 00:34:29,960
Speaker 3: It's not wiser.

587
00:34:30,360 --> 00:34:32,319
Speaker 7: But in the US it'd be interesting if someone could

588
00:34:32,320 --> 00:34:34,680
Speaker 7: try to attack Maybe fires is saying that they didn't

589
00:34:35,080 --> 00:34:37,960
Speaker 7: announce the side effects that they should have, as they

590
00:34:38,000 --> 00:34:40,719
Speaker 7: usually do with other drugs, but yeah, they should have.

591
00:34:41,280 --> 00:34:43,839
Speaker 1: Well, I enjoy your time, and it goes by much

592
00:34:43,880 --> 00:34:45,200
Speaker 1: too quickly every time we talk.

593
00:34:46,360 --> 00:34:48,040
Speaker 2: Shas Khan, thank you so much.

594
00:34:48,160 --> 00:34:51,359
Speaker 1: The book is the ultimate vaccine timeline of fact packed

595
00:34:51,480 --> 00:34:55,160
Speaker 1: history of vaccines and their makers. It's out now and

596
00:34:56,080 --> 00:34:59,799
Speaker 1: her work continues. Thank you so much for the information.

597
00:34:59,360 --> 00:35:02,239
Speaker 7: Shows well, thank you so much for having me, and

598
00:35:02,280 --> 00:35:03,120
Speaker 7: have a wonderful day.

599
00:35:03,280 --> 00:35:04,200
Speaker 2: Hey you as well.

600
00:35:05,080 --> 00:35:09,719
Speaker 1: Coming up next Jim Lebarbara Rock and Roll archaeology from

601
00:35:09,760 --> 00:35:13,400
Speaker 1: this past Saturday. Because some people are just too lazy

602
00:35:13,440 --> 00:35:18,320
Speaker 1: to get up at seven thirty in the morning, Welcome

603
00:35:18,320 --> 00:35:21,920
Speaker 1: back to the Nightcap here on seven hundred WLW up.

604
00:35:22,120 --> 00:35:28,080
Speaker 1: Next is the director of Research for the Government Accountability

605
00:35:28,320 --> 00:35:33,840
Speaker 1: Institute or GAI. Has nothing to do with AI necessarily,

606
00:35:33,920 --> 00:35:37,360
Speaker 1: but because I think you'll find this is real intelligence,

607
00:35:37,440 --> 00:35:41,160
Speaker 1: not anything artificial about it. His name is Seamus Brunner.

608
00:35:41,840 --> 00:35:48,040
Speaker 1: He is also the author of a book called Control

609
00:35:48,120 --> 00:35:51,520
Speaker 1: of Garks exposing the billionaire class, their secret deals, and

610
00:35:51,560 --> 00:35:55,279
Speaker 1: the globalist plot to dominate your life in every aspect

611
00:35:55,360 --> 00:35:55,640
Speaker 1: of it.

612
00:35:56,200 --> 00:36:00,480
Speaker 2: Seamus Bruner, Welcome to the show. How are you very well.

613
00:36:00,480 --> 00:36:03,160
Speaker 2: It's great to be with you, fantastic to have you.

614
00:36:03,160 --> 00:36:07,200
Speaker 1: You've worked with Peter Switzer on some great best selling

615
00:36:07,719 --> 00:36:13,000
Speaker 1: books about following the money and all of that, and

616
00:36:13,640 --> 00:36:16,360
Speaker 1: that's all you really have to do is follow the money.

617
00:36:17,880 --> 00:36:21,399
Speaker 1: This No King's two point zero movement that we saw

618
00:36:21,440 --> 00:36:25,880
Speaker 1: in evidence again this past weekend is backed by billionaire money,

619
00:36:25,880 --> 00:36:31,000
Speaker 1: and they're starting to dive in Donald Trump and his administration,

620
00:36:31,200 --> 00:36:34,400
Speaker 1: diving into where all this money is coming from. So

621
00:36:35,280 --> 00:36:39,920
Speaker 1: when Bernie Sanders warns us about oligarchs, he's not talking

622
00:36:39,960 --> 00:36:41,239
Speaker 1: about these people, is he.

623
00:36:43,520 --> 00:36:46,560
Speaker 5: No, he is not. They tend to look the other

624
00:36:46,640 --> 00:36:50,160
Speaker 5: way when they've got billionaires and kings and oligarcs on

625
00:36:50,200 --> 00:36:50,880
Speaker 5: their side.

626
00:36:51,160 --> 00:36:55,320
Speaker 2: Yeah, no doubt about it, all right. So let's get behind.

627
00:36:56,719 --> 00:37:02,440
Speaker 1: Where the money is coming from, going directly to official

628
00:37:02,560 --> 00:37:07,200
Speaker 1: No King's two point zero partners and organizers funnel through

629
00:37:07,239 --> 00:37:11,560
Speaker 1: these dark money networks. The Arabella network, who are they?

630
00:37:11,840 --> 00:37:16,720
Speaker 1: They gave seventy nine point seven million dollars.

631
00:37:16,880 --> 00:37:19,360
Speaker 5: Yeah, the Arabella Network has been around for a while

632
00:37:19,520 --> 00:37:22,400
Speaker 5: of approximately I don't know, twenty five years. They've got

633
00:37:22,760 --> 00:37:27,960
Speaker 5: half a dozen or more funds that are basically pass throughs,

634
00:37:28,040 --> 00:37:30,800
Speaker 5: dark money pass throughs. They've got the new Venture Fund,

635
00:37:30,960 --> 00:37:34,000
Speaker 5: the sixteen thirty fund. I could list a few more

636
00:37:34,080 --> 00:37:36,640
Speaker 5: for you, but the point is is they just passed

637
00:37:36,680 --> 00:37:42,000
Speaker 5: money through from billionaires like Bill Gates, Mark Zuckerberg. George

638
00:37:42,000 --> 00:37:45,839
Speaker 5: Soros is a huge funder of the Arabella network. Even

639
00:37:45,920 --> 00:37:49,440
Speaker 5: some foreign funders such as the Swiss billionaire.

640
00:37:48,920 --> 00:37:50,359
Speaker 2: Hans jord VIIs.

641
00:37:51,480 --> 00:37:54,480
Speaker 5: He's the guy who likes to destabilize our country and

642
00:37:54,880 --> 00:37:57,800
Speaker 5: fund our political process. That really needs to be looked into.

643
00:37:58,760 --> 00:38:04,000
Speaker 5: And so the the NGOs, they are funding what we

644
00:38:04,080 --> 00:38:07,640
Speaker 5: call the protesting industrial complex. We mapped out all two

645
00:38:07,760 --> 00:38:14,040
Speaker 5: hundred plus No King's official organizers and partners. We pulled

646
00:38:14,080 --> 00:38:17,520
Speaker 5: every one of their irs form nine nineties the nine

647
00:38:17,600 --> 00:38:21,040
Speaker 5: nineties of all of the NGOs, put all the numbers

648
00:38:21,080 --> 00:38:23,560
Speaker 5: into a spreadsheet and just started totaling it up, and

649
00:38:23,640 --> 00:38:27,160
Speaker 5: we were shocked to learn that close to three hundred

650
00:38:27,280 --> 00:38:32,600
Speaker 5: million dollars has come through these Soros ties Arabella networks

651
00:38:32,600 --> 00:38:37,600
Speaker 5: into the No Kings organizers and partners now that's over

652
00:38:37,680 --> 00:38:40,120
Speaker 5: the past. That's according to the most recent IRS form

653
00:38:40,239 --> 00:38:44,840
Speaker 5: nine nineties. So that is not just three hundred millions

654
00:38:44,920 --> 00:38:48,000
Speaker 5: for this event, but a lot of these organizers they

655
00:38:48,280 --> 00:38:53,080
Speaker 5: funded and participated in prior protests and riots like the

656
00:38:53,120 --> 00:38:57,920
Speaker 5: anti ice demonstrations, the Tesla takedown, there was a No

657
00:38:58,080 --> 00:39:01,319
Speaker 5: Kings back in June. And so this is a really

658
00:39:01,320 --> 00:39:06,439
Speaker 5: a professional o test network. We call it riot Inc.

659
00:39:07,320 --> 00:39:09,560
Speaker 5: And extremely well funded.

660
00:39:09,880 --> 00:39:10,279
Speaker 2: Are they?

661
00:39:10,320 --> 00:39:13,279
Speaker 1: Are they also in your estimation, I don't know if

662
00:39:13,280 --> 00:39:16,440
Speaker 1: you've done anything digging into this. Are they also behind

663
00:39:16,600 --> 00:39:19,520
Speaker 1: a lot of funding for the pro hamas rallies which

664
00:39:19,560 --> 00:39:24,760
Speaker 1: seated all kinds of violence and chaos on purpose, and

665
00:39:24,760 --> 00:39:30,000
Speaker 1: and also of things like Antifa, which the President is

666
00:39:31,040 --> 00:39:34,000
Speaker 1: absolutely as a terrorist organization.

667
00:39:34,719 --> 00:39:35,839
Speaker 2: Right, Yeah, that's right.

668
00:39:35,880 --> 00:39:40,640
Speaker 5: I was at the President's roundtable on Antifa a week

669
00:39:40,640 --> 00:39:42,799
Speaker 5: and a half ago. I briefed the President on all

670
00:39:42,840 --> 00:39:46,640
Speaker 5: of this stuff. He told me to get with the DOJ,

671
00:39:46,960 --> 00:39:52,879
Speaker 5: FBI and Homeland Security leaders officials, and I've passed along

672
00:39:52,920 --> 00:39:55,239
Speaker 5: a lot of this information to them. One of the

673
00:39:55,280 --> 00:39:58,360
Speaker 5: things that he was most interested in, that's President trumpet

674
00:39:58,400 --> 00:40:01,920
Speaker 5: most interested in was a guy I named Neville Roy Singham,

675
00:40:02,360 --> 00:40:06,600
Speaker 5: a guy based in China, basically a billionaire, and he

676
00:40:06,680 --> 00:40:11,480
Speaker 5: has got a whole network of nonprofits and NGOs in

677
00:40:11,520 --> 00:40:15,960
Speaker 5: the United States, and they were especially behind the Prolomadut

678
00:40:16,000 --> 00:40:20,480
Speaker 5: demonstrations in New York City. It was also his groups

679
00:40:20,480 --> 00:40:24,439
Speaker 5: that were behind the anti Ice riots in LA where

680
00:40:24,440 --> 00:40:26,440
Speaker 5: you saw lots of cars on fire and a lot

681
00:40:26,480 --> 00:40:28,239
Speaker 5: of violence towards law enforcement.

682
00:40:29,000 --> 00:40:29,120
Speaker 4: UH.

683
00:40:29,320 --> 00:40:32,720
Speaker 5: And Nevill Roy Singham he's a.

684
00:40:32,400 --> 00:40:35,880
Speaker 9: Not a good dude, and there's a lot of federal

685
00:40:36,600 --> 00:40:40,520
Speaker 9: investigations going on involving him, whether it's a Foreign Agents

686
00:40:40,560 --> 00:40:43,239
Speaker 9: Registration Act through the US Attorney's Office in d C.

687
00:40:44,840 --> 00:40:50,080
Speaker 5: Or UH, the Secretary or I'm sorry, the Oversight Chairman.

688
00:40:50,160 --> 00:40:54,680
Speaker 5: James Comer sent a letter to Treasury Secretary Besants asking

689
00:40:54,760 --> 00:40:59,240
Speaker 5: him to seize or freeze Neville Roy Singham's assets because

690
00:40:59,280 --> 00:41:02,879
Speaker 5: of the unrest he is fomenting in our country. And

691
00:41:02,960 --> 00:41:06,160
Speaker 5: so that's just one of many of the foreigners who

692
00:41:06,239 --> 00:41:09,200
Speaker 5: are funding some of this stuff.

693
00:41:09,040 --> 00:41:12,640
Speaker 1: Of these powerful control of garks that you're right about

694
00:41:12,680 --> 00:41:17,239
Speaker 1: in the book. Control of Garks is what is their

695
00:41:17,320 --> 00:41:21,400
Speaker 1: ultimate goal. Their ultimate goal is to dominate every aspect

696
00:41:21,760 --> 00:41:25,520
Speaker 1: of our life and have complete power, absolute power.

697
00:41:25,960 --> 00:41:30,200
Speaker 5: Right, Yeah, that's exactly right. I mean, I'll give you

698
00:41:30,239 --> 00:41:33,439
Speaker 5: a spoiler, wherret. The final chapter, chapter ten, is called

699
00:41:33,440 --> 00:41:37,160
Speaker 5: the Endgame, and it talks about where they want to

700
00:41:37,200 --> 00:41:41,960
Speaker 5: take us. There's actually, interestingly enough, a book written over

701
00:41:42,120 --> 00:41:45,759
Speaker 5: fifty years ago, seventy five years ago called The Naked Communists,

702
00:41:46,080 --> 00:41:48,719
Speaker 5: where it lists the goals of the Communist Party, is

703
00:41:48,760 --> 00:41:52,840
Speaker 5: written by a former FBI investigator. And you'd be stunned

704
00:41:52,880 --> 00:41:55,600
Speaker 5: to learn that many of these goals have been fulfilled

705
00:41:56,160 --> 00:41:59,239
Speaker 5: and truly and most people can't believe this. And I

706
00:41:59,320 --> 00:42:03,280
Speaker 5: tell them, these controlling guards want to make the United

707
00:42:03,280 --> 00:42:06,120
Speaker 5: States more like China. And there's a reason for that.

708
00:42:06,239 --> 00:42:08,319
Speaker 5: I mean, the people think, oh, they're capitalists. They've made

709
00:42:08,320 --> 00:42:12,040
Speaker 5: a billion dollars. Shouldn't they be pro America and be

710
00:42:12,080 --> 00:42:15,560
Speaker 5: grateful for the money. They want more power and more

711
00:42:15,600 --> 00:42:19,320
Speaker 5: control than they already have, and they actually envy China.

712
00:42:19,320 --> 00:42:21,759
Speaker 5: I mean, people like Bill Gates. Have you saw it

713
00:42:21,840 --> 00:42:26,080
Speaker 5: during the pandemic, especially where they praised the Chinese response

714
00:42:26,120 --> 00:42:29,759
Speaker 5: to COVID. They used euphemisms like, oh, it's very efficient.

715
00:42:30,440 --> 00:42:32,600
Speaker 5: They're doing a great job because of how quickly they

716
00:42:32,640 --> 00:42:36,320
Speaker 5: can address things. What they really want is an authoritarian

717
00:42:36,360 --> 00:42:39,960
Speaker 5: type system. And ultimately they want a social credit score.

718
00:42:40,520 --> 00:42:42,360
Speaker 5: That's what a lot of the stuff that they're funding

719
00:42:42,400 --> 00:42:45,640
Speaker 5: digital ID. Bill Gates just recently said we need to

720
00:42:45,640 --> 00:42:49,439
Speaker 5: get digital ID in the United States by twenty twenty eight.

721
00:42:49,520 --> 00:42:52,239
Speaker 5: That's just a couple of years away. He's funded and

722
00:42:52,280 --> 00:42:54,680
Speaker 5: a lot of these control guards have funded. Silicon Valley

723
00:42:54,719 --> 00:42:59,279
Speaker 5: guys have funded efforts to get a digital ID implemented

724
00:42:59,320 --> 00:43:02,680
Speaker 5: in the United States. So it's shocking stuff, But truly

725
00:43:02,719 --> 00:43:07,359
Speaker 5: they do want authoritarian system controlled by them.

726
00:43:08,200 --> 00:43:12,360
Speaker 1: A lot of people finally raising red flags no pun intended,

727
00:43:12,440 --> 00:43:17,359
Speaker 1: about the communist Chinese Party buying up US farmland. Bill

728
00:43:17,440 --> 00:43:20,799
Speaker 1: Gates has been eleven point seven billion dollars to take

729
00:43:20,840 --> 00:43:23,120
Speaker 1: over our food supply. Is this what you found?

730
00:43:25,040 --> 00:43:28,160
Speaker 5: Yeah, that's right. I actually been going through so I noticed,

731
00:43:28,200 --> 00:43:30,680
Speaker 5: you know, as many people have, that Bill Gates is

732
00:43:30,680 --> 00:43:32,520
Speaker 5: buying up a lot of farmland.

733
00:43:32,080 --> 00:43:33,720
Speaker 4: And thought, what the heck is going on here?

734
00:43:34,080 --> 00:43:37,880
Speaker 5: At the same time, it coincides with the farmland purchases,

735
00:43:38,120 --> 00:43:40,880
Speaker 5: he's been investing in a lot of food companies. I mean,

736
00:43:40,920 --> 00:43:45,040
Speaker 5: he'd put twenty three million dollars into Monsanto that has

737
00:43:45,080 --> 00:43:47,799
Speaker 5: the patented seeds for agriculture.

738
00:43:48,200 --> 00:43:49,640
Speaker 2: He's invested.

739
00:43:50,840 --> 00:43:54,000
Speaker 5: North of a billion dollars in a variety of alternative

740
00:43:54,040 --> 00:43:58,760
Speaker 5: protein and fertilizer companies, new new kind of fertilizer technologies,

741
00:44:00,320 --> 00:44:04,840
Speaker 5: these fake meat companies like beyond Meat, impossible foods, and

742
00:44:04,880 --> 00:44:07,879
Speaker 5: so the deeper I dug I actually led me back

743
00:44:07,920 --> 00:44:12,320
Speaker 5: to the Microsoft anti trust trials in the nineties, whereas

744
00:44:12,400 --> 00:44:16,040
Speaker 5: prosecutors discovered that Bill Gates and Microsoft's had a strategy

745
00:44:16,120 --> 00:44:22,080
Speaker 5: called embrace, extend, extinguish, where they would the company because

746
00:44:22,120 --> 00:44:23,799
Speaker 5: what does the tech I know about farming, Well, he

747
00:44:23,840 --> 00:44:26,080
Speaker 5: doesn't know a lot about farming, but he knows a

748
00:44:26,080 --> 00:44:30,839
Speaker 5: lot about anti trust and cornering markets. First, Microsoft would

749
00:44:30,880 --> 00:44:34,400
Speaker 5: embrace an industry. In the example from the nineties, it

750
00:44:34,440 --> 00:44:38,960
Speaker 5: was the internet browser industry. They created Internet Explorer, then

751
00:44:39,000 --> 00:44:41,440
Speaker 5: they extended their reach, put it on every machine and

752
00:44:41,480 --> 00:44:43,880
Speaker 5: whether you wanted it or not. And then once they

753
00:44:43,880 --> 00:44:47,879
Speaker 5: had established a foothold, they would seek to extend extinguish

754
00:44:47,960 --> 00:44:50,840
Speaker 5: the competition, and it was a netscape of the competitor

755
00:44:51,360 --> 00:44:54,359
Speaker 5: that they tried to smother. Well, that's what Bill Gates

756
00:44:54,400 --> 00:44:56,000
Speaker 5: is trying to do with farmers. So at the same

757
00:44:56,040 --> 00:44:59,000
Speaker 5: time he's buying up all the farmlands, investing in what

758
00:44:59,040 --> 00:45:02,400
Speaker 5: he believes are the of the future. He's also using

759
00:45:02,440 --> 00:45:06,080
Speaker 5: his NGO Networks and Bill Munda Gates Foundation to put

760
00:45:06,120 --> 00:45:12,360
Speaker 5: out white papers and reports convincing lawmakers to using climate

761
00:45:12,480 --> 00:45:16,680
Speaker 5: change type regulations smother our farmers. So that's where you

762
00:45:16,719 --> 00:45:20,479
Speaker 5: get things like methane restrictions for cattle, and you can't

763
00:45:20,560 --> 00:45:22,960
Speaker 5: use certain types of fertilizers that farmers have been using

764
00:45:23,000 --> 00:45:25,560
Speaker 5: for decades. So it's really really sinister stuff.

765
00:45:26,280 --> 00:45:32,640
Speaker 1: As ridiculous as putting diapers on cows, or seems. It's

766
00:45:32,760 --> 00:45:36,160
Speaker 1: kind of part of this weird, bizarre plan. Mark Zuckerberg

767
00:45:36,280 --> 00:45:40,279
Speaker 1: spent thirty six billion dollars on social re engineering to

768
00:45:40,400 --> 00:45:43,920
Speaker 1: keep us all trapped in a tech addiction, and it

769
00:45:44,040 --> 00:45:46,480
Speaker 1: is one of the most powerful addictions. Now, you know,

770
00:45:46,760 --> 00:45:51,040
Speaker 1: I'm a former cigarette smoker. I know about addiction. I've

771
00:45:51,080 --> 00:45:55,080
Speaker 1: had my battles with alcohol, but the tech addiction seems

772
00:45:55,120 --> 00:45:59,480
Speaker 1: to be one of the most insidious kinds of addictions

773
00:45:59,520 --> 00:46:02,120
Speaker 1: that they're is, and there's a lot of money being

774
00:46:02,160 --> 00:46:04,960
Speaker 1: put forward to make sure more and more of us

775
00:46:05,000 --> 00:46:05,520
Speaker 1: are hooked.

776
00:46:06,000 --> 00:46:09,319
Speaker 4: Yes, yeah, that's absolutely right.

777
00:46:09,400 --> 00:46:13,200
Speaker 5: I mean it's I mean, you'll spend unfathomable sums just

778
00:46:13,239 --> 00:46:17,080
Speaker 5: getting the color schemes right on apps like Facebook and Instagram,

779
00:46:17,120 --> 00:46:22,759
Speaker 5: and getting the chimes and the notifications to deliver the

780
00:46:22,800 --> 00:46:27,239
Speaker 5: dopamine hits to the users at such a frequency that

781
00:46:27,320 --> 00:46:31,120
Speaker 5: it keeps them at a endless loop of wanting to

782
00:46:31,120 --> 00:46:33,200
Speaker 5: go back and check the app. I got off of

783
00:46:33,280 --> 00:46:36,360
Speaker 5: Facebook a couple of years ago, but for a while

784
00:46:37,000 --> 00:46:39,840
Speaker 5: I noticed myself going to the screen and try to

785
00:46:39,880 --> 00:46:40,719
Speaker 5: tap where it used to be.

786
00:46:40,800 --> 00:46:42,040
Speaker 4: It's like, oh, oh, it's gone.

787
00:46:42,239 --> 00:46:44,760
Speaker 5: So you really don't want to be using these apps

788
00:46:44,800 --> 00:46:48,000
Speaker 5: because they are highly addictive. And then the amount of money,

789
00:46:48,040 --> 00:46:51,439
Speaker 5: it's far more than what's listed there, because as they're

790
00:46:51,480 --> 00:46:56,120
Speaker 5: outdated by a few months, it's really well over fifty billion,

791
00:46:56,760 --> 00:47:00,880
Speaker 5: especially with the AI and the virtual reality that he

792
00:47:00,960 --> 00:47:04,560
Speaker 5: wants to get kids hooked into in the games. So

793
00:47:04,600 --> 00:47:07,359
Speaker 5: he's pumping a lot of money into tech addiction. That's

794
00:47:07,440 --> 00:47:10,200
Speaker 5: why you see people like him and Bill Gates cozying

795
00:47:10,280 --> 00:47:13,640
Speaker 5: up to the Trump administration as best they can because

796
00:47:14,040 --> 00:47:18,520
Speaker 5: the FTC, the FCC, antitrust regulators, they are hot on

797
00:47:18,560 --> 00:47:22,719
Speaker 5: the trail with the addiction and just the methods of

798
00:47:22,719 --> 00:47:26,200
Speaker 5: getting especially young people addicted and ultimately depressed. I mean

799
00:47:26,280 --> 00:47:31,200
Speaker 5: suicide rates people have linked to Instagram use urging suicide rates,

800
00:47:31,239 --> 00:47:34,200
Speaker 5: so he doesn't want people to find out about this,

801
00:47:34,239 --> 00:47:35,920
Speaker 5: which is why you really need to read the book.

802
00:47:36,160 --> 00:47:39,280
Speaker 1: And in addition to Jeff Bezos and the Soros family,

803
00:47:39,280 --> 00:47:41,840
Speaker 1: which you already mentioned and we've heard now for years

804
00:47:43,120 --> 00:47:46,960
Speaker 1: ponying up the bucks for this division in the country,

805
00:47:47,000 --> 00:47:50,520
Speaker 1: which causes chaos, and then eventually, I guess their hope

806
00:47:50,560 --> 00:47:54,640
Speaker 1: is that American society completely collapses so the globalists can

807
00:47:54,680 --> 00:47:58,560
Speaker 1: take over. There's Klaus Schwab's Davos Club. They meet the

808
00:47:58,560 --> 00:48:03,800
Speaker 1: World Economic Forum twenty five wef members worth over ten

809
00:48:04,000 --> 00:48:09,080
Speaker 1: trillion dollars that have way more power than many governments

810
00:48:09,920 --> 00:48:13,399
Speaker 1: that are supposed to represent all of their citizens, and

811
00:48:14,960 --> 00:48:18,799
Speaker 1: they're usurping the authority of government with their money and

812
00:48:18,840 --> 00:48:21,640
Speaker 1: their power. I guess it's the whole point of this.

813
00:48:22,400 --> 00:48:26,360
Speaker 1: We're closing out on our time and man, this subject

814
00:48:26,440 --> 00:48:29,080
Speaker 1: could well, I mean, you wrote a book about it,

815
00:48:29,120 --> 00:48:32,960
Speaker 1: so I guess the subject we could talk for about

816
00:48:33,040 --> 00:48:36,200
Speaker 1: I don't know, ten days and not cover everything. But

817
00:48:36,280 --> 00:48:40,080
Speaker 1: the book again is control of garchs, exposing the billionaire class,

818
00:48:40,160 --> 00:48:43,760
Speaker 1: their secret deals and the globalist plot to dominate your life.

819
00:48:43,800 --> 00:48:45,560
Speaker 2: That's out now. Shamus.

820
00:48:47,760 --> 00:48:48,560
Speaker 4: Yes, that's right.

821
00:48:48,719 --> 00:48:52,040
Speaker 5: You can get it anywhere you get books. I realize

822
00:48:52,040 --> 00:48:54,400
Speaker 5: the irony of having a book with Jeff Bezos on

823
00:48:54,440 --> 00:48:55,640
Speaker 5: the cover being for sale.

824
00:48:55,440 --> 00:48:57,160
Speaker 4: On Amazon is not lost on me.

825
00:48:57,320 --> 00:48:59,839
Speaker 5: So if you don't want to give Bezos the money,

826
00:49:00,160 --> 00:49:02,480
Speaker 5: it's easy to get it. There will be there in

827
00:49:02,480 --> 00:49:04,600
Speaker 5: two days. But if you don't want to give Bezos

828
00:49:04,600 --> 00:49:06,920
Speaker 5: the money, you can go to control of arksbook dot

829
00:49:06,920 --> 00:49:10,440
Speaker 5: com and find the independent retailer links.

830
00:49:11,840 --> 00:49:15,320
Speaker 1: Are you Are you happy that at least Donald Trump

831
00:49:15,640 --> 00:49:18,360
Speaker 1: and the people that you're in connection with are trying

832
00:49:18,400 --> 00:49:20,720
Speaker 1: to stop this in its tracks?

833
00:49:23,760 --> 00:49:24,160
Speaker 5: I am.

834
00:49:24,360 --> 00:49:26,600
Speaker 4: I see an effort there.

835
00:49:26,640 --> 00:49:29,600
Speaker 5: I see you know, the political will is there where

836
00:49:29,640 --> 00:49:32,719
Speaker 5: it hasn't been in years past. Ever since the assassination

837
00:49:32,880 --> 00:49:35,959
Speaker 5: of Charlie Kirk, it seems like it's all hands on deck.

838
00:49:36,360 --> 00:49:39,919
Speaker 5: I will say that this is a really, really tough

839
00:49:40,040 --> 00:49:43,680
Speaker 5: nut to crack. I mean, you can't just declare, you know,

840
00:49:44,040 --> 00:49:47,560
Speaker 5: George Soros's business illegal. He's an expert at this game.

841
00:49:47,560 --> 00:49:49,680
Speaker 5: He's been in it for fifty years. The other guys,

842
00:49:49,920 --> 00:49:53,440
Speaker 5: some of them even longer, and so it's going to

843
00:49:53,440 --> 00:49:56,239
Speaker 5: be very tough to root this out. And a lot

844
00:49:56,280 --> 00:49:59,080
Speaker 5: of the battle is in the schools because we've got

845
00:49:59,239 --> 00:50:02,120
Speaker 5: entire generation of kids who have already been radicalized by

846
00:50:02,160 --> 00:50:09,359
Speaker 5: the Soros, Rockefeller Tides, Arabella Network propaganda. And you still

847
00:50:09,360 --> 00:50:10,000
Speaker 5: have the teachers.

848
00:50:10,040 --> 00:50:11,120
Speaker 2: I mean, you see the teachers.

849
00:50:11,120 --> 00:50:14,040
Speaker 5: They were at the No King's rallies being you know,

850
00:50:14,120 --> 00:50:18,080
Speaker 5: calling for violence, and they were celebrating after Charlie Kirk's assassination.

851
00:50:18,440 --> 00:50:19,840
Speaker 5: It's going to take a long time to get the

852
00:50:19,840 --> 00:50:22,320
Speaker 5: schools out, so we really need to. We need to

853
00:50:22,400 --> 00:50:23,600
Speaker 5: ramp up like yesterday.

854
00:50:23,800 --> 00:50:26,360
Speaker 1: All right, Seamus Printer, thank you so much for your time.

855
00:50:26,960 --> 00:50:30,480
Speaker 1: Good morning for all and anybody's interested in what we've

856
00:50:30,480 --> 00:50:31,240
Speaker 1: been talking about.

857
00:50:31,560 --> 00:50:34,680
Speaker 2: Get control of garcs. It's out now, Seamus, thank.

858
00:50:34,520 --> 00:50:36,919
Speaker 4: You, Thank you sir.

859
00:50:37,160 --> 00:50:41,320
Speaker 1: All Right, we continue with the Nightcap in just moments

860
00:50:41,360 --> 00:50:47,360
Speaker 1: after this break, entering into the third hour of tonight's

861
00:50:47,480 --> 00:50:52,320
Speaker 1: Nightcap on this Tuesday evening had seven utter wl W Gary,

862
00:50:52,400 --> 00:50:56,360
Speaker 1: Jeff and now for something completely different. It always is

863
00:50:56,440 --> 00:51:02,480
Speaker 1: every time we talk conversation with the man, and to me,

864
00:51:02,760 --> 00:51:06,760
Speaker 1: he is still the pre eminent sports radio talk voice

865
00:51:07,440 --> 00:51:11,200
Speaker 1: of all of Cincinnati, and as far as I'm concerned,

866
00:51:11,280 --> 00:51:15,319
Speaker 1: the king of all media. Andy Furman joins us for

867
00:51:15,400 --> 00:51:18,000
Speaker 1: this segment, How are you doing for ball?

868
00:51:19,040 --> 00:51:21,400
Speaker 6: It gets better every week. The John keep on writing

869
00:51:21,440 --> 00:51:22,400
Speaker 6: and you keep on reading it.

870
00:51:22,480 --> 00:51:22,880
Speaker 3: I love it.

871
00:51:22,920 --> 00:51:23,640
Speaker 6: It's wonderful.

872
00:51:23,840 --> 00:51:27,480
Speaker 1: I'm not reading anything. It's off the top of my head,

873
00:51:27,600 --> 00:51:30,000
Speaker 1: from the bottom of my heart. I don't need a

874
00:51:30,080 --> 00:51:32,479
Speaker 1: script in front of me. Andy, what were you gonna say?

875
00:51:32,520 --> 00:51:35,080
Speaker 6: I will tell you this much. I'm not normally nervous

876
00:51:35,120 --> 00:51:37,200
Speaker 6: doing this, but I'm a little uptyped because you kind

877
00:51:37,200 --> 00:51:39,560
Speaker 6: of like laid the law on me the other day

878
00:51:39,600 --> 00:51:42,160
Speaker 6: saying I better come with it today. I always thought

879
00:51:42,200 --> 00:51:44,279
Speaker 6: I did. I always thought I did. You know what

880
00:51:44,280 --> 00:51:45,160
Speaker 6: I'm saying, But.

881
00:51:46,480 --> 00:51:50,040
Speaker 1: Listen, if you do not, as Willie Cunningham likes to say,

882
00:51:50,040 --> 00:51:52,799
Speaker 1: put the cheese on the cracker, I would not give

883
00:51:52,840 --> 00:51:54,920
Speaker 1: you the cracker to put the cheese on. You wouldn't

884
00:51:54,920 --> 00:51:57,040
Speaker 1: be here right now if you didn't bring it. I

885
00:51:57,080 --> 00:52:00,640
Speaker 1: don't know what you're talking about. I'm totally happy with

886
00:52:01,280 --> 00:52:05,560
Speaker 1: your with your participation in helping me out with this program,

887
00:52:05,600 --> 00:52:09,640
Speaker 1: because I know millions, if not hundreds of people are

888
00:52:09,680 --> 00:52:11,680
Speaker 1: waiting to hear what you have to say.

889
00:52:13,200 --> 00:52:15,440
Speaker 6: Well, the first thing I thought of as you mentioned

890
00:52:15,440 --> 00:52:17,840
Speaker 6: that to me the other day, I think that you

891
00:52:18,000 --> 00:52:21,000
Speaker 6: need to have your headstick above head and shoulders above

892
00:52:21,040 --> 00:52:23,279
Speaker 6: everybody else in this city. And it is how you're doing.

893
00:52:23,560 --> 00:52:26,800
Speaker 6: We have the Gary Jeff Walker Awards. I thought about

894
00:52:26,800 --> 00:52:30,000
Speaker 6: this right, but we're doing in the world of entertainment

895
00:52:30,040 --> 00:52:33,560
Speaker 6: and sports locally in Cincinnati, Like who is the best

896
00:52:33,640 --> 00:52:38,160
Speaker 6: TV sports anchor in Cincinnati, Who's the best writer? Things

897
00:52:38,200 --> 00:52:40,480
Speaker 6: like that. I think the Gary Jeff Awards, What do

898
00:52:40,520 --> 00:52:42,120
Speaker 6: you think? And then you can give them, like a

899
00:52:42,160 --> 00:52:44,920
Speaker 6: gift certificate to the Huddles or something like that, you

900
00:52:44,960 --> 00:52:47,080
Speaker 6: know what I mean. Award them in Huddles. We'll put

901
00:52:47,120 --> 00:52:47,879
Speaker 6: the name on the wall.

902
00:52:48,320 --> 00:52:51,480
Speaker 1: I think we need something a little bit more and

903
00:52:51,520 --> 00:52:55,120
Speaker 1: no offense to my other employer, a little bit more

904
00:52:55,320 --> 00:52:59,600
Speaker 1: illustrious than a gift certificate to Huddles. But we ought to.

905
00:53:00,560 --> 00:53:02,319
Speaker 1: I mean, you need to set this up. You're the

906
00:53:02,360 --> 00:53:05,880
Speaker 1: pr guy. You've got connections all over the place. Andy.

907
00:53:06,239 --> 00:53:09,560
Speaker 1: What I'm thinking is, you need to book a ballroom.

908
00:53:09,960 --> 00:53:13,280
Speaker 1: We can promote it. We'll get some big money people

909
00:53:13,320 --> 00:53:17,680
Speaker 1: behind us, UH to kind of help finance it. I

910
00:53:17,840 --> 00:53:21,080
Speaker 1: get to EMC and you can introduce me. What do

911
00:53:21,160 --> 00:53:23,280
Speaker 1: you think, and then I will em see the show,

912
00:53:23,640 --> 00:53:26,480
Speaker 1: you know, like the Oscars or the Emmys or but

913
00:53:26,719 --> 00:53:30,160
Speaker 1: this will be real because it'll be real accomplishments and

914
00:53:30,280 --> 00:53:35,080
Speaker 1: not just you know, meaningless pats on the back within

915
00:53:35,160 --> 00:53:36,240
Speaker 1: our own little bubble.

916
00:53:36,560 --> 00:53:40,399
Speaker 6: Because we're not gonna do this like right now.

917
00:53:40,440 --> 00:53:41,120
Speaker 2: We're gonna like.

918
00:53:41,120 --> 00:53:43,480
Speaker 6: Play this out maybe like in a spring, Yeah, like

919
00:53:43,520 --> 00:53:45,160
Speaker 6: around when Red Seage is start.

920
00:53:45,120 --> 00:53:50,840
Speaker 1: Right exactly, It'll be about meritocracy, not mediocrity. It'll be

921
00:53:51,320 --> 00:53:56,160
Speaker 1: I will tell you about real performance, not political circles.

922
00:53:56,480 --> 00:53:59,160
Speaker 6: Yes, I think we should do when the Red Seeds

923
00:53:59,239 --> 00:54:02,279
Speaker 6: is stuck start you sort of like back off a

924
00:54:02,280 --> 00:54:03,839
Speaker 6: little bit with your time on the air.

925
00:54:04,040 --> 00:54:06,359
Speaker 1: Well that means that if we're gonna do it when

926
00:54:06,440 --> 00:54:09,440
Speaker 1: Red season is started and I'm no longer on the

927
00:54:09,520 --> 00:54:12,720
Speaker 1: radio on Monday and Tuesday nights making the money, making

928
00:54:12,760 --> 00:54:16,399
Speaker 1: the good old I heard media money, then uh, we're

929
00:54:16,400 --> 00:54:17,880
Speaker 1: gonna have to figure out a way for me to

930
00:54:17,880 --> 00:54:20,480
Speaker 1: get paid to host it too, because I will be

931
00:54:20,560 --> 00:54:21,360
Speaker 1: on a breadline.

932
00:54:21,360 --> 00:54:24,560
Speaker 2: Otherwise we'll figure it out.

933
00:54:24,600 --> 00:54:25,799
Speaker 6: We'll work on that, all right.

934
00:54:25,920 --> 00:54:26,120
Speaker 2: Yeah.

935
00:54:26,200 --> 00:54:31,360
Speaker 6: So the sports, Yeah, all right, I got it, no deal. Sorry,

936
00:54:31,880 --> 00:54:34,200
Speaker 6: I thought about this the other days. We'll talk about sports,

937
00:54:35,080 --> 00:54:39,360
Speaker 6: and and these college coaches of course took about sportsmanship, brotherhood,

938
00:54:39,360 --> 00:54:41,440
Speaker 6: all that garbage. So I read a school of the

939
00:54:41,560 --> 00:54:46,560
Speaker 6: odag Olklahoma University. Their women's softball team is like dynamite.

940
00:54:46,680 --> 00:54:48,959
Speaker 6: They won the antiaa tournament like two or of the last

941
00:54:48,960 --> 00:54:51,240
Speaker 6: three years, whatever it may be. They played the school.

942
00:54:51,239 --> 00:54:54,239
Speaker 6: But I am Oklahoma Christian. Last week they beat them

943
00:54:54,280 --> 00:54:57,760
Speaker 6: thirty five nothing. I thought it was a typographical mistake.

944
00:54:58,280 --> 00:54:59,719
Speaker 6: I had a look on the interne at.

945
00:54:59,680 --> 00:55:00,600
Speaker 2: The same was true.

946
00:55:00,800 --> 00:55:03,880
Speaker 6: It is are you kidding me? Thirty five nothing? I

947
00:55:03,880 --> 00:55:06,200
Speaker 6: mean after there was twelve nothing and the third inning?

948
00:55:06,440 --> 00:55:08,880
Speaker 6: Can they just call the game? How do you play

949
00:55:08,880 --> 00:55:11,480
Speaker 6: a school like that? What does that do? What does

950
00:55:11,520 --> 00:55:14,719
Speaker 6: that do? What message do you tell your players, like

951
00:55:14,920 --> 00:55:17,160
Speaker 6: step in their throat and do it until I can't

952
00:55:17,160 --> 00:55:20,879
Speaker 6: breathe anymore. That to me is ridiculous. Thirty five nothing

953
00:55:21,080 --> 00:55:22,880
Speaker 6: in Oklahoma or Oklahoma Christians.

954
00:55:22,920 --> 00:55:25,680
Speaker 1: You have to understand Oklahoma Christian. If they are true

955
00:55:25,680 --> 00:55:29,640
Speaker 1: to their namesake, We're not offended by this because Christians

956
00:55:29,640 --> 00:55:32,399
Speaker 1: always turned the other cheek, even when they're getting bread.

957
00:55:32,560 --> 00:55:35,799
Speaker 1: I mean, were you saying that it wasn't fair for

958
00:55:35,880 --> 00:55:39,600
Speaker 1: the Roman emperor to put Christians in the coliseum with

959
00:55:39,680 --> 00:55:41,720
Speaker 1: the lions when.

960
00:55:42,320 --> 00:55:45,960
Speaker 6: A freaking softball game. Forget about Lions and Tigers, forget

961
00:55:45,960 --> 00:55:49,799
Speaker 6: about the softball game two universities. The president and the

962
00:55:49,840 --> 00:55:52,400
Speaker 6: school should have said something. If I'm the president of

963
00:55:52,400 --> 00:55:55,400
Speaker 6: Oklahoma Christmas, you know what, We're not playing them anymore.

964
00:55:55,600 --> 00:55:59,040
Speaker 6: And the story it's embarrassing. Don't embarrass my team, don't

965
00:55:59,040 --> 00:56:00,239
Speaker 6: embarrass my school.

966
00:56:00,440 --> 00:56:03,160
Speaker 1: So you're gonna tell You're gonna tell the girls to

967
00:56:03,200 --> 00:56:05,800
Speaker 1: take their balls and go home and just not even participate.

968
00:56:06,040 --> 00:56:09,440
Speaker 6: You go, oh, oh my god, I like that. Okay,

969
00:56:09,520 --> 00:56:12,240
Speaker 6: speak of the ball last night, all right, I'm flipping

970
00:56:12,239 --> 00:56:15,719
Speaker 6: them back and forth of the Toronto Seattle baseball playoff game.

971
00:56:15,960 --> 00:56:18,040
Speaker 6: And not not only one, but they had two NFL

972
00:56:18,080 --> 00:56:21,160
Speaker 6: games last night. Could you help me out over the

973
00:56:21,280 --> 00:56:24,560
Speaker 6: last several weeks, we not only have one, but we

974
00:56:24,640 --> 00:56:26,960
Speaker 6: have two NFL games on Monday Night. And I'll tell

975
00:56:27,000 --> 00:56:28,960
Speaker 6: you why they do it. I know why they're doing

976
00:56:29,000 --> 00:56:32,480
Speaker 6: it because the NFL wants the very Major League Baseball.

977
00:56:32,600 --> 00:56:35,640
Speaker 6: They've already buried the NBA because the NBA used to

978
00:56:35,719 --> 00:56:38,160
Speaker 6: own Christmas Day. Now the NFL has got a game

979
00:56:38,200 --> 00:56:40,960
Speaker 6: on Christmas Day. I get it. I understand. The NFL

980
00:56:41,200 --> 00:56:44,759
Speaker 6: probably is the most popular sport not nationally, maybe worldwide

981
00:56:45,000 --> 00:56:48,160
Speaker 6: and very close to that is college football, but still

982
00:56:48,160 --> 00:56:51,080
Speaker 6: at all give the other some breathing room, will you please?

983
00:56:51,719 --> 00:56:55,400
Speaker 6: I'm gonna recommend the Congress. Congress should say there should

984
00:56:55,400 --> 00:56:57,000
Speaker 6: be no al for lapping in sports. I know it

985
00:56:57,080 --> 00:56:59,800
Speaker 6: sounds stupid, but I remember as a kid it was

986
00:56:59,840 --> 00:57:04,080
Speaker 6: a certain seasons for every sport there wasn't much overlapping. Really,

987
00:57:04,239 --> 00:57:06,680
Speaker 6: the biggest games are coming up dating Friday night the

988
00:57:06,760 --> 00:57:11,040
Speaker 6: World Series. Thoughts, do you think people care really about football?

989
00:57:11,080 --> 00:57:14,120
Speaker 1: Now we're getting to the crux of who you are

990
00:57:14,360 --> 00:57:19,600
Speaker 1: with this little diatribe you just laid on me. You're

991
00:57:19,640 --> 00:57:22,200
Speaker 1: obviously a socialist. Do you think everything ought to be

992
00:57:22,320 --> 00:57:26,640
Speaker 1: fair and shared? Listen, if people didn't, would would not

993
00:57:26,960 --> 00:57:31,760
Speaker 1: rather watch the NFL than Major League Baseball? They'd be

994
00:57:31,800 --> 00:57:35,720
Speaker 1: watching baseball. But people prefer the NFL. Don't blame the

995
00:57:35,880 --> 00:57:43,320
Speaker 1: NFL for dominating Major League Baseball and basketball with the

996
00:57:43,320 --> 00:57:46,920
Speaker 1: eyeballs of the American public. Just the fact is, maybe

997
00:57:46,960 --> 00:57:50,720
Speaker 1: the NBA, maybe the MLB need to come up with

998
00:57:50,760 --> 00:57:55,000
Speaker 1: a better product that includes more people and and and

999
00:57:55,240 --> 00:57:57,600
Speaker 1: generates that kind of sparks that kind of interest.

1000
00:57:58,000 --> 00:58:00,720
Speaker 2: If there's an NFL game, let me tell you something.

1001
00:58:01,000 --> 00:58:04,200
Speaker 6: You lost touch with reality because the product last night,

1002
00:58:04,360 --> 00:58:07,360
Speaker 6: because Ronto Seattle game was a nail fighter who was

1003
00:58:07,400 --> 00:58:09,880
Speaker 6: a great game, as far as the Detroit Lion football

1004
00:58:09,920 --> 00:58:11,760
Speaker 6: game twenty four to nine wasn't much.

1005
00:58:11,600 --> 00:58:12,040
Speaker 3: Of a game.

1006
00:58:12,080 --> 00:58:15,360
Speaker 6: However, However, here's where you have no idea what you're

1007
00:58:15,400 --> 00:58:18,600
Speaker 6: talking about, okay, because it's all about gambling. Baseball is

1008
00:58:18,600 --> 00:58:21,120
Speaker 6: not a great game to gamble on. Football is perfect.

1009
00:58:21,240 --> 00:58:24,640
Speaker 6: And everybody who's watching NFL more often than not, has

1010
00:58:24,880 --> 00:58:27,200
Speaker 6: money involved in they're gambling. And let me tell you

1011
00:58:27,280 --> 00:58:29,040
Speaker 6: something else. Let me go one step further. I don't

1012
00:58:29,040 --> 00:58:31,480
Speaker 6: know if you read this, but the nc double A

1013
00:58:31,760 --> 00:58:35,320
Speaker 6: is thinking they have say don't even tell me this now, please,

1014
00:58:35,520 --> 00:58:39,200
Speaker 6: but the NCAA is thinking to permit college athletes to

1015
00:58:39,400 --> 00:58:43,760
Speaker 6: bet our professional sports, not on collegiate sports, but on

1016
00:58:43,880 --> 00:58:45,720
Speaker 6: pro sports. So what are you telling me right now

1017
00:58:45,800 --> 00:58:49,200
Speaker 6: is that the college kids could take their nil money

1018
00:58:49,440 --> 00:58:52,880
Speaker 6: and spend it on wagering. Are you freaking killing me?

1019
00:58:53,280 --> 00:58:54,280
Speaker 2: It wasn't my idea.

1020
00:58:54,440 --> 00:58:58,080
Speaker 1: It wasn't my idea, Andy, And I think that's awful

1021
00:58:58,320 --> 00:59:04,080
Speaker 1: anytime there is gambling involved involving the people who are

1022
00:59:04,120 --> 00:59:07,920
Speaker 1: actually playing the game, or maybe on an NFL team

1023
00:59:08,240 --> 00:59:13,960
Speaker 1: next year. I think that it absolutely erodes any semblance

1024
00:59:14,000 --> 00:59:18,120
Speaker 1: of integrity associated with that sport. I couldn't agree with

1025
00:59:18,160 --> 00:59:22,640
Speaker 1: you more about that. But the NFL, let's just period,

1026
00:59:22,840 --> 00:59:26,960
Speaker 1: end of story. The NFL is America's sport. And you

1027
00:59:27,000 --> 00:59:30,959
Speaker 1: could put anything on opposite the NFL, a bad NFL game,

1028
00:59:31,240 --> 00:59:33,560
Speaker 1: and the NFL would still win in the ratings.

1029
00:59:33,840 --> 00:59:36,600
Speaker 2: And you're back to square one with your argument.

1030
00:59:36,680 --> 00:59:40,520
Speaker 6: Andy, Well, I will tell you this much now. I mean,

1031
00:59:40,560 --> 00:59:43,320
Speaker 6: the Gamly situation stinks the NFL all of a sudden,

1032
00:59:43,360 --> 00:59:46,680
Speaker 6: and I'll go back and I'm that I'm not from

1033
00:59:46,720 --> 00:59:48,880
Speaker 6: another world, okay, but I'm gonna go back to my

1034
00:59:48,960 --> 00:59:52,440
Speaker 6: childhood when the NFL games were blacked out. I lived

1035
00:59:52,480 --> 00:59:53,880
Speaker 6: in New York City and I was a New York

1036
00:59:53,880 --> 00:59:56,880
Speaker 6: Football Giants fan, and people would get in their cars

1037
00:59:56,920 --> 00:59:59,720
Speaker 6: and drove the Connecticut to watch the Football Giants play

1038
00:59:59,720 --> 01:00:01,919
Speaker 6: the whole home games because home games were blacked out.

1039
01:00:02,160 --> 01:00:04,720
Speaker 2: Now, hold on, hold on, hold on.

1040
01:00:05,040 --> 01:00:08,040
Speaker 1: In a city of eight million people, Yeah, okay, there's

1041
01:00:08,120 --> 01:00:10,720
Speaker 1: a couple of professional teams in New York City, But

1042
01:00:10,800 --> 01:00:13,600
Speaker 1: in a city of eight million people, they can't fill

1043
01:00:13,600 --> 01:00:17,080
Speaker 1: a fifty thousand seat stadium.

1044
01:00:17,360 --> 01:00:20,800
Speaker 6: But that was the role. I know, if if the game,

1045
01:00:21,760 --> 01:00:23,720
Speaker 6: if the game wasn't together.

1046
01:00:23,520 --> 01:00:25,960
Speaker 2: And if if the game wasn't.

1047
01:00:25,880 --> 01:00:29,840
Speaker 1: They were if the game, if the game wasn't sold out,

1048
01:00:30,080 --> 01:00:33,360
Speaker 1: then the games were blacked out on TV in that market.

1049
01:00:33,600 --> 01:00:37,400
Speaker 6: No, yes, no, they were blacked out. They were blacked out.

1050
01:00:37,440 --> 01:00:38,240
Speaker 2: In that market.

1051
01:00:38,280 --> 01:00:41,360
Speaker 1: They were blacked out because the stadium did not sell out.

1052
01:00:41,400 --> 01:00:46,240
Speaker 1: If the stadium was sold out, there were no blackoutsy Okay.

1053
01:00:46,000 --> 01:00:48,080
Speaker 6: So the points of the matter, ison, I go back

1054
01:00:48,120 --> 01:00:51,360
Speaker 6: and checkpoint. I think home games home games were in

1055
01:00:51,480 --> 01:00:54,840
Speaker 6: fact blackout and the Giants were sold out. The Giants

1056
01:00:54,840 --> 01:00:57,840
Speaker 6: were sold out. Look, it's still a waiting list of

1057
01:00:57,960 --> 01:01:01,960
Speaker 6: tickets for the New York Football Giants inherent tickets those games.

1058
01:01:01,960 --> 01:01:05,320
Speaker 6: There was a band on home games with the ownership

1059
01:01:05,480 --> 01:01:08,560
Speaker 6: back then in the sixties and early seventies were fearful

1060
01:01:08,840 --> 01:01:11,880
Speaker 6: that television would hurt the gate. And they make a

1061
01:01:11,920 --> 01:01:14,360
Speaker 6: difference if the sold out or not. You cannot watch

1062
01:01:14,400 --> 01:01:16,520
Speaker 6: a home game in the city you lived in if

1063
01:01:16,520 --> 01:01:18,640
Speaker 6: they were home. That's what it was. Well, and they

1064
01:01:18,760 --> 01:01:20,800
Speaker 6: changed that and it didn't effect that at all.

1065
01:01:20,920 --> 01:01:21,400
Speaker 4: It didn't.

1066
01:01:21,560 --> 01:01:25,360
Speaker 1: They got they got rid of the blackout rule. It's

1067
01:01:25,400 --> 01:01:27,160
Speaker 1: gone right, It's been gone for years.

1068
01:01:27,160 --> 01:01:28,800
Speaker 6: And when I got rid of the black guy rule,

1069
01:01:28,960 --> 01:01:30,960
Speaker 6: almost at the same time that got rid of that,

1070
01:01:31,240 --> 01:01:34,360
Speaker 6: all of a sudden, fantasy football came alive and everybody

1071
01:01:34,360 --> 01:01:36,480
Speaker 6: went crazy. And it's the greatest invention in the world.

1072
01:01:36,520 --> 01:01:38,439
Speaker 6: And I'll tell you why not to go to the money,

1073
01:01:38,520 --> 01:01:41,160
Speaker 6: not to go to the gambling, because people learned who

1074
01:01:41,200 --> 01:01:44,080
Speaker 6: the players were. That's what it's all about. I used

1075
01:01:44,080 --> 01:01:46,160
Speaker 6: to go to a Bengal game and I hear people

1076
01:01:46,200 --> 01:01:49,280
Speaker 6: sitting behind me cheering for the opposition, and I turned

1077
01:01:49,320 --> 01:01:51,760
Speaker 6: around and I asked them, what are you so happy about? Well,

1078
01:01:51,760 --> 01:01:54,000
Speaker 6: I got them in my fantasy league. That's what it's

1079
01:01:54,040 --> 01:01:56,920
Speaker 6: all about. It is people know to play. You can

1080
01:01:56,960 --> 01:01:59,600
Speaker 6: tell me baseball needs to do something like that, because

1081
01:01:59,600 --> 01:02:01,560
Speaker 6: not only do you not know to plays, you can't

1082
01:02:01,560 --> 01:02:06,200
Speaker 6: even pronounce their freaking name. Island, I never heard of, Jillie.

1083
01:02:06,400 --> 01:02:11,640
Speaker 1: You and I Andy have our voice to pretend that

1084
01:02:11,680 --> 01:02:15,040
Speaker 1: we're general managers every time we talk about the NFL

1085
01:02:15,280 --> 01:02:19,840
Speaker 1: and what we would do. This gives the average person

1086
01:02:19,840 --> 01:02:25,040
Speaker 1: who doesn't have a radio platform a chance or maybe

1087
01:02:25,160 --> 01:02:28,000
Speaker 1: the platform that we have a chance to be a

1088
01:02:28,120 --> 01:02:31,720
Speaker 1: GM and to actually control the puppet strings. That is

1089
01:02:31,760 --> 01:02:33,600
Speaker 1: the appeal of fantasy football.

1090
01:02:33,680 --> 01:02:37,400
Speaker 6: To me, all the appeal is money. Stop being so logical.

1091
01:02:37,600 --> 01:02:40,640
Speaker 6: It's all about money. Why do you play fantasy football

1092
01:02:40,720 --> 01:02:42,880
Speaker 6: to be a general manager or to win some buck's

1093
01:02:42,920 --> 01:02:43,840
Speaker 6: not bragging right.

1094
01:02:43,800 --> 01:02:50,520
Speaker 1: To do both, to have control and maybe win your league.

1095
01:02:50,040 --> 01:02:53,800
Speaker 6: Sure, I see these kids playing fantasy football the end

1096
01:02:53,800 --> 01:02:55,800
Speaker 6: of the year that has like a awards dinner and

1097
01:02:55,840 --> 01:02:58,800
Speaker 6: they give out championship rings. I see them a championship

1098
01:02:58,880 --> 01:03:01,440
Speaker 6: rings for the team or the individual that has the

1099
01:03:01,520 --> 01:03:05,240
Speaker 6: winning players. It's unbelievable, really well, but that's just great.

1100
01:03:05,640 --> 01:03:08,000
Speaker 6: Baseball doesn't have anything like that. And I'll tell you what,

1101
01:03:08,120 --> 01:03:10,720
Speaker 6: if I was a marketing guy in Major League Baseball,

1102
01:03:10,960 --> 01:03:12,560
Speaker 6: I would go to a fast food team like a

1103
01:03:12,640 --> 01:03:15,160
Speaker 6: McDonald's and Wendy's and Burger team and have a tie

1104
01:03:15,200 --> 01:03:18,120
Speaker 6: in with a weekly Major League Baseball sort of a

1105
01:03:18,160 --> 01:03:21,280
Speaker 6: fantasy deal for kids. You know they got that bingo

1106
01:03:21,400 --> 01:03:24,120
Speaker 6: now at McDonald's, no one cares about bingo. Whatever the

1107
01:03:24,120 --> 01:03:24,840
Speaker 6: heck it is bingo.

1108
01:03:24,920 --> 01:03:31,400
Speaker 1: I don't know what it is, Monopoly, Monodonald's check kids.

1109
01:03:31,480 --> 01:03:35,280
Speaker 6: Wait, these kids today the gun McDonald's have no idea.

1110
01:03:35,280 --> 01:03:38,000
Speaker 6: What the freak Monopoly. Is that was a big game

1111
01:03:38,200 --> 01:03:41,720
Speaker 6: fifty years ago. Go give me monopoly, Give me baseball.

1112
01:03:42,080 --> 01:03:45,080
Speaker 6: The marketing people in Major League Baseball, get off your

1113
01:03:45,080 --> 01:03:48,200
Speaker 6: rear end and contact McDonald's and get a tie in.

1114
01:03:48,320 --> 01:03:49,760
Speaker 6: But baseball.

1115
01:03:50,640 --> 01:03:53,760
Speaker 1: All right, I mean, if you've got a couple dollars

1116
01:03:53,800 --> 01:03:57,080
Speaker 1: off your happy meal or something. Maybe the reason kids

1117
01:03:57,120 --> 01:04:00,840
Speaker 1: are fat in America today is because they are playing

1118
01:04:00,880 --> 01:04:03,880
Speaker 1: fantasy football and they're not out in the backyard running

1119
01:04:03,920 --> 01:04:07,040
Speaker 1: around playing real football with their friends like we used

1120
01:04:07,080 --> 01:04:11,000
Speaker 1: to do, and staying in shape, getting some cardio, getting outside,

1121
01:04:11,280 --> 01:04:13,680
Speaker 1: getting out of their phones, getting out of their little

1122
01:04:14,040 --> 01:04:18,360
Speaker 1: computer world. It's too easy just to sit on a

1123
01:04:18,440 --> 01:04:24,560
Speaker 1: couch somewhere and become veal instead of actually actively participating

1124
01:04:24,600 --> 01:04:29,000
Speaker 1: in a sport they supposedly love, whether it's football, baseball,

1125
01:04:29,120 --> 01:04:29,880
Speaker 1: or anything else.

1126
01:04:31,120 --> 01:04:33,120
Speaker 6: Let me come in you in that last remark, because

1127
01:04:33,160 --> 01:04:35,880
Speaker 6: it's funny you mentioned that. This afternoon at the Covington

1128
01:04:35,960 --> 01:04:40,880
Speaker 6: Rotary Club at the Eradison Hotel, doctor Connor, a forensic psychiatrist,

1129
01:04:41,160 --> 01:04:44,160
Speaker 6: gave the same speech. While the youth of America today

1130
01:04:44,200 --> 01:04:47,040
Speaker 6: is overweight because of their cell phone, social media and

1131
01:04:47,080 --> 01:04:50,000
Speaker 6: everything like that, it's unbelievable. He had everybody with their

1132
01:04:50,040 --> 01:04:52,440
Speaker 6: mouths open at the club and I'm lucky, and I say,

1133
01:04:52,440 --> 01:04:54,480
Speaker 6: you didn't know that. You could just take a look.

1134
01:04:55,320 --> 01:04:58,320
Speaker 6: One out of every three kids is overweight. Why they

1135
01:04:58,360 --> 01:05:00,200
Speaker 6: can't get their phone out of their hand, That's what

1136
01:05:00,280 --> 01:05:03,560
Speaker 6: it's No one want. Kids don't ride bicycles anymore. There's

1137
01:05:03,560 --> 01:05:06,440
Speaker 6: no creativity with kids anymore. Think about that. When you

1138
01:05:06,480 --> 01:05:08,520
Speaker 6: were a kid, you went to the store, got an

1139
01:05:08,520 --> 01:05:11,720
Speaker 6: empty box and you played house, right, it was creative.

1140
01:05:12,560 --> 01:05:14,080
Speaker 6: Creativity is give it to us?

1141
01:05:14,120 --> 01:05:14,320
Speaker 3: Now?

1142
01:05:14,440 --> 01:05:18,800
Speaker 1: Hey, Andy computer, you mentioned that did you did you

1143
01:05:18,840 --> 01:05:20,720
Speaker 1: play house when you were a little kid? And who

1144
01:05:20,800 --> 01:05:24,000
Speaker 1: was your housemaid? Or did you play the or Andy?

1145
01:05:24,080 --> 01:05:26,720
Speaker 1: Did you play doctor? Did you play doctor with the

1146
01:05:26,760 --> 01:05:28,960
Speaker 1: girl next door or the boy?

1147
01:05:29,240 --> 01:05:31,400
Speaker 6: No comment on that, no comment. Not only did I

1148
01:05:31,400 --> 01:05:33,640
Speaker 6: play house with that box? My wife gave me a

1149
01:05:33,680 --> 01:05:35,200
Speaker 6: box the other day and that's who I've been sleeping

1150
01:05:35,200 --> 01:05:36,800
Speaker 6: in the other day. You won't let me back in

1151
01:05:36,800 --> 01:05:38,160
Speaker 6: the house. But that's another story.

1152
01:05:39,840 --> 01:05:41,760
Speaker 1: By the way, I wanted to let you know that

1153
01:05:41,800 --> 01:05:45,600
Speaker 1: a friend of mine got me a Jose Riho cigar.

1154
01:05:46,400 --> 01:05:48,840
Speaker 1: And I know that your friends with Jose. You've been

1155
01:05:48,960 --> 01:05:50,959
Speaker 1: longtime friends with Jose and.

1156
01:05:50,920 --> 01:05:53,040
Speaker 6: We were partners. We were business partners, you know. We

1157
01:05:53,040 --> 01:05:55,919
Speaker 6: had Furman Sports Cafe. He was a part owner as

1158
01:05:56,000 --> 01:05:58,360
Speaker 6: I was, as so was the late Greg cot from

1159
01:05:58,400 --> 01:05:59,600
Speaker 6: the quarterback of the Bengals.

1160
01:06:00,360 --> 01:06:03,080
Speaker 2: Liked the cigar? Can you get me another one? Since

1161
01:06:03,080 --> 01:06:06,280
Speaker 2: you know Jose so well, I'll give my holler.

1162
01:06:06,320 --> 01:06:08,960
Speaker 6: And he's usually in Cincinnati, probably once a month, but

1163
01:06:09,320 --> 01:06:10,200
Speaker 6: I'll get a hold of him.

1164
01:06:10,200 --> 01:06:13,000
Speaker 1: We'll get some the great I know that, I know

1165
01:06:13,080 --> 01:06:15,200
Speaker 1: that he stops into your house when he's in town

1166
01:06:15,280 --> 01:06:18,200
Speaker 1: sometimes just parks in the driveway and busts in the

1167
01:06:18,240 --> 01:06:20,880
Speaker 1: door and demands a cigar from you. So maybe it's

1168
01:06:20,920 --> 01:06:24,280
Speaker 1: time you demand a cigar from Jose for for Gary

1169
01:06:24,360 --> 01:06:26,000
Speaker 1: Jeff host.

1170
01:06:25,720 --> 01:06:28,920
Speaker 6: Of the Hold the Story but the List, I me

1171
01:06:29,000 --> 01:06:32,040
Speaker 6: kate the town shrove to my home and he left

1172
01:06:32,080 --> 01:06:33,960
Speaker 6: his family in his car and I came in and

1173
01:06:34,000 --> 01:06:36,840
Speaker 6: spent like an hour from my house. I said, bring

1174
01:06:36,920 --> 01:06:38,960
Speaker 6: him in, you know not. He had the kids in

1175
01:06:39,200 --> 01:06:40,960
Speaker 6: and his wife and they were all in the car.

1176
01:06:41,440 --> 01:06:43,880
Speaker 6: I said, come on in. No, no, it's okay. I'll

1177
01:06:43,920 --> 01:06:45,960
Speaker 6: just see another minute. And then all the Davis found

1178
01:06:45,960 --> 01:06:47,920
Speaker 6: out and he was there. So there was a line

1179
01:06:48,240 --> 01:06:51,160
Speaker 6: on my driveway for design autographs to take pictures.

1180
01:06:51,840 --> 01:06:55,320
Speaker 2: That's phenomenal, So cigar.

1181
01:06:55,000 --> 01:06:57,880
Speaker 6: Yeah, I should have choked. I blew that opportunity.

1182
01:06:58,560 --> 01:07:01,000
Speaker 2: Can you get me a stogy from Jose Rio? And

1183
01:07:01,480 --> 01:07:01,880
Speaker 2: all right?

1184
01:07:02,000 --> 01:07:03,760
Speaker 6: Yes, I will, yes, I will.

1185
01:07:03,800 --> 01:07:04,800
Speaker 2: All right, that'd be great.

1186
01:07:06,040 --> 01:07:09,400
Speaker 1: And I if he's if he's got a good Churchill

1187
01:07:09,480 --> 01:07:16,560
Speaker 1: or Maduro out, I'd prefer that. All right, Andy, go

1188
01:07:16,560 --> 01:07:18,320
Speaker 1: ahead and get out, Go ahead and get out of

1189
01:07:18,360 --> 01:07:20,240
Speaker 1: your car. Oh that's right, you live in your car

1190
01:07:20,320 --> 01:07:22,200
Speaker 1: because your wife has kicked you out of the house.

1191
01:07:22,280 --> 01:07:23,320
Speaker 2: I forgot that.

1192
01:07:24,040 --> 01:07:26,200
Speaker 6: It's the car of the box. I kind of like that,

1193
01:07:26,280 --> 01:07:27,960
Speaker 6: the seat and the car better than laying on the

1194
01:07:28,000 --> 01:07:28,840
Speaker 6: ground in the box.

1195
01:07:30,360 --> 01:07:32,120
Speaker 2: All right for Paul, thanks a lot.

1196
01:07:33,560 --> 01:07:37,880
Speaker 1: My friend Bye Dave had her comes up next Doomsday

1197
01:07:38,000 --> 01:07:43,000
Speaker 1: Dave cyber news you need to know on this nightcap

1198
01:07:43,120 --> 01:07:48,240
Speaker 1: on seven hundred w l W. Time for another visit

1199
01:07:48,320 --> 01:07:52,600
Speaker 1: with our friend Doomsday. Dave the Mad had her guy

1200
01:07:52,640 --> 01:07:59,200
Speaker 1: from interest I t who he's here as as our

1201
01:07:59,280 --> 01:08:04,360
Speaker 1: proverbial cyber canarian the coal Mine, to warn us about

1202
01:08:04,400 --> 01:08:07,960
Speaker 1: how technology is going to destroy us all and things

1203
01:08:07,960 --> 01:08:10,800
Speaker 1: to look out for and it's all AI all the

1204
01:08:10,880 --> 01:08:15,240
Speaker 1: time now. Dave first and foremost let's get to this

1205
01:08:15,320 --> 01:08:21,959
Speaker 1: story from futurism dot com. Researchers find it shockingly easy

1206
01:08:22,000 --> 01:08:26,400
Speaker 1: to cause AI to lose its mind by poison by

1207
01:08:26,439 --> 01:08:28,800
Speaker 1: posting poison documents online.

1208
01:08:29,000 --> 01:08:32,080
Speaker 2: But what does this story have to do with.

1209
01:08:33,479 --> 01:08:36,280
Speaker 4: Yeah, so this is interesting and it goes back to

1210
01:08:36,600 --> 01:08:38,960
Speaker 4: what in the business would be known as input risk,

1211
01:08:39,080 --> 01:08:42,040
Speaker 4: Gary Jeb. Input risk covers a lot of things, and

1212
01:08:42,080 --> 01:08:44,040
Speaker 4: you have input risk and output risk when you talk

1213
01:08:44,040 --> 01:08:48,240
Speaker 4: about these generative AI tools. Again, we're primarily focused on

1214
01:08:48,760 --> 01:08:53,240
Speaker 4: large language model based generative AI tools like GROCK, like Gemini,

1215
01:08:53,600 --> 01:08:56,559
Speaker 4: like chat GPT. So when you use these things and

1216
01:08:56,600 --> 01:08:59,439
Speaker 4: you enter a prompt, right, what you put in that

1217
01:08:59,520 --> 01:09:02,240
Speaker 4: prompt be malicious, And there's all kinds of different ways

1218
01:09:02,280 --> 01:09:04,760
Speaker 4: to do this, but basically what they're saying is that

1219
01:09:04,840 --> 01:09:07,639
Speaker 4: if you quote poison, poisonous kind of a generic term

1220
01:09:07,680 --> 01:09:12,680
Speaker 4: also in the business for putting something malicious into an input.

1221
01:09:12,760 --> 01:09:15,760
Speaker 4: And ideally, Gary Jeff, if you're doing all of this

1222
01:09:15,960 --> 01:09:20,840
Speaker 4: right from a developer standpoint, you're trying to validate your

1223
01:09:20,880 --> 01:09:24,840
Speaker 4: inputs and knock out anything malicious slash poison. But their

1224
01:09:24,880 --> 01:09:27,519
Speaker 4: research shows that you can try to like jail break

1225
01:09:27,560 --> 01:09:29,479
Speaker 4: the AI get it to give you answers that it's

1226
01:09:29,479 --> 01:09:31,799
Speaker 4: not supposed to give you, like, you know, generally speaking,

1227
01:09:32,280 --> 01:09:34,439
Speaker 4: it won't give you an answer on like how to

1228
01:09:34,439 --> 01:09:37,479
Speaker 4: make a bomb or something like that, right, And their

1229
01:09:37,520 --> 01:09:39,200
Speaker 4: point is, and this is not the first time that's

1230
01:09:39,320 --> 01:09:41,240
Speaker 4: come up at their point is, in many of these things,

1231
01:09:42,000 --> 01:09:44,639
Speaker 4: in any of these tools, you can put in poison

1232
01:09:44,720 --> 01:09:46,840
Speaker 4: inputs and get it to behave in ways that it's

1233
01:09:46,880 --> 01:09:49,960
Speaker 4: not supposed to behave, give you information that it shouldn't

1234
01:09:50,000 --> 01:09:53,559
Speaker 4: give you, you know, and potentially do other more nefarious things.

1235
01:09:53,640 --> 01:09:56,280
Speaker 4: Because as a reminder, and I think this is so

1236
01:09:56,280 --> 01:09:58,320
Speaker 4: important for people to remember, and I also want to

1237
01:09:58,360 --> 01:10:01,479
Speaker 4: be clear here, I'm not anti AI, but I think

1238
01:10:01,520 --> 01:10:03,800
Speaker 4: a lot of the bloom is starting to come off

1239
01:10:03,840 --> 01:10:06,800
Speaker 4: these generative AI tools and a lot of the hype

1240
01:10:06,880 --> 01:10:08,760
Speaker 4: is starting to be shown because of things like this.

1241
01:10:08,920 --> 01:10:10,479
Speaker 4: And I don't know, I don't think I sent you

1242
01:10:10,520 --> 01:10:12,439
Speaker 4: this on. Gary Jeff, one of the key guys who

1243
01:10:12,520 --> 01:10:15,559
Speaker 4: came up with the term vibe coding, which is the

1244
01:10:15,640 --> 01:10:18,240
Speaker 4: idea that you can use these AI tools to generate

1245
01:10:18,400 --> 01:10:23,080
Speaker 4: software by a computer code, just mentioned that his most

1246
01:10:23,080 --> 01:10:25,840
Speaker 4: recent project he coded by hand. So what does that

1247
01:10:25,880 --> 01:10:28,360
Speaker 4: tell you? But my point to getting back to your

1248
01:10:28,400 --> 01:10:31,960
Speaker 4: specific question, is if you enter poison intuts, you can

1249
01:10:32,240 --> 01:10:34,240
Speaker 4: fool these things that are doing things they shouldn't do,

1250
01:10:34,280 --> 01:10:39,920
Speaker 4: and you could potentially start to manipulate the large language

1251
01:10:39,920 --> 01:10:43,040
Speaker 4: model itself because what you put in there becomes part

1252
01:10:43,040 --> 01:10:46,400
Speaker 4: of the training going forward. So it's an interesting concept,

1253
01:10:46,479 --> 01:10:48,920
Speaker 4: and I just want to encourage people. Everyone should go

1254
01:10:48,960 --> 01:10:51,960
Speaker 4: check these things out for themselves, but understand this idea

1255
01:10:52,000 --> 01:10:54,720
Speaker 4: of input and output risk. First off, never put any

1256
01:10:54,800 --> 01:10:58,479
Speaker 4: sensitive information, anything that you wouldn't want someone else to see,

1257
01:10:58,880 --> 01:11:01,040
Speaker 4: any kind of conversation and you might be having with

1258
01:11:01,080 --> 01:11:02,960
Speaker 4: one of these things that you would not want out

1259
01:11:03,000 --> 01:11:05,680
Speaker 4: there into one of these tools, because even if you

1260
01:11:05,720 --> 01:11:07,960
Speaker 4: read the terms of service, it's confused opoly that you

1261
01:11:08,040 --> 01:11:10,799
Speaker 4: probably won't be able to understand, and there's no guarantee

1262
01:11:10,840 --> 01:11:12,800
Speaker 4: that that won't get out. So that's part of the

1263
01:11:12,800 --> 01:11:16,280
Speaker 4: input risk. And the output risk is because with or

1264
01:11:16,280 --> 01:11:18,880
Speaker 4: without the poisoning, it may just literally make things up.

1265
01:11:19,000 --> 01:11:22,400
Speaker 4: So I think again, the blue is starting to come

1266
01:11:22,439 --> 01:11:24,200
Speaker 4: off the roads on some of the AI heights that

1267
01:11:24,240 --> 01:11:26,400
Speaker 4: we're seeing. I don't think we're all going to be

1268
01:11:26,439 --> 01:11:28,840
Speaker 4: replaced by it anytime soon, at least on the path

1269
01:11:28,920 --> 01:11:31,880
Speaker 4: that we're on, but I've been wrong before, Gary Jeff,

1270
01:11:31,920 --> 01:11:33,120
Speaker 4: so we'll have to wait and see.

1271
01:11:33,479 --> 01:11:36,160
Speaker 1: Well, you know that's had a guest done last night

1272
01:11:36,520 --> 01:11:40,400
Speaker 1: talking about this, and yeah, Elon Musk and Bill Gates

1273
01:11:40,439 --> 01:11:44,040
Speaker 1: are all on board with us being replaced. It seems

1274
01:11:44,160 --> 01:11:46,960
Speaker 1: like from what they've written and things that they keep

1275
01:11:47,920 --> 01:11:52,519
Speaker 1: doing chat GPT. I don't know, Dave, I don't know

1276
01:11:52,520 --> 01:11:55,479
Speaker 1: if we ever talked about the story where the guy

1277
01:11:55,560 --> 01:12:00,479
Speaker 1: got assistance from the chat bot to kill himself the kid.

1278
01:12:01,160 --> 01:12:02,120
Speaker 2: Did we ever talk about it?

1279
01:12:03,600 --> 01:12:06,040
Speaker 4: I think we might have, and I've certainly alluded to

1280
01:12:06,080 --> 01:12:08,800
Speaker 4: it a lot in talking about this topic. And I

1281
01:12:08,800 --> 01:12:11,360
Speaker 4: mean this also kind of goes to both the input

1282
01:12:11,439 --> 01:12:14,200
Speaker 4: risk and the output risk when you're if you're you know,

1283
01:12:14,240 --> 01:12:17,040
Speaker 4: and there are companies who've built chatbots specifically to be

1284
01:12:17,280 --> 01:12:21,200
Speaker 4: like online psychotherapists, whereas chat GPT or Jim and I

1285
01:12:21,280 --> 01:12:24,840
Speaker 4: are rocker more general purpose AI tools. But if you're

1286
01:12:24,960 --> 01:12:27,599
Speaker 4: if you're talking to one of these tools about anything

1287
01:12:27,640 --> 01:12:30,200
Speaker 4: that is sensitive to you, things you would not want

1288
01:12:30,680 --> 01:12:34,280
Speaker 4: other people to know about. Yeah, your spouse, your family,

1289
01:12:34,400 --> 01:12:38,800
Speaker 4: your employer, your your doctor, your insurance company, whatever, you

1290
01:12:38,800 --> 01:12:41,200
Speaker 4: should think long and hard about using any of these

1291
01:12:41,200 --> 01:12:43,519
Speaker 4: tools that are free. Now, it's one thing to set

1292
01:12:43,560 --> 01:12:45,280
Speaker 4: up your own instance of this if you know how

1293
01:12:45,280 --> 01:12:48,919
Speaker 4: to do it and shield yourself from the potential privacy

1294
01:12:48,960 --> 01:12:53,000
Speaker 4: concerns and exposure that could be created. But it's another

1295
01:12:53,040 --> 01:12:56,200
Speaker 4: altogether to just go in and then the output risk

1296
01:12:56,280 --> 01:12:58,160
Speaker 4: coming back to that again is what you just said.

1297
01:12:58,200 --> 01:13:01,599
Speaker 4: You know, there are apparently many document instances, can several

1298
01:13:01,680 --> 01:13:04,720
Speaker 4: lawsuits out there based around people who have either I'm

1299
01:13:04,720 --> 01:13:07,040
Speaker 4: going to use this term mostly quote kind of lost

1300
01:13:07,080 --> 01:13:08,680
Speaker 4: in their mind and gone off the deep end as

1301
01:13:08,680 --> 01:13:12,160
Speaker 4: a result of ongoing conversations with these tools, and or

1302
01:13:12,160 --> 01:13:15,400
Speaker 4: in some in some really tragic and sad instances, people

1303
01:13:15,439 --> 01:13:19,160
Speaker 4: have killed themselves. And you know, the argument is that

1304
01:13:19,240 --> 01:13:22,760
Speaker 4: the tool allegedly kind of led them down the primrose path,

1305
01:13:22,880 --> 01:13:25,120
Speaker 4: like you can kill yourself and we could be together forever,

1306
01:13:25,280 --> 01:13:27,960
Speaker 4: or or things like that. Again, this is all alleged.

1307
01:13:28,000 --> 01:13:30,600
Speaker 4: There are suits in court. Now we'll see where this

1308
01:13:30,680 --> 01:13:34,360
Speaker 4: all goes. But you know, it's not alive. It's not

1309
01:13:34,479 --> 01:13:37,320
Speaker 4: your friend. I also remind people to carry Jeff when

1310
01:13:37,320 --> 01:13:40,160
Speaker 4: you use these tools. Again, I suggest everyone who tried

1311
01:13:40,200 --> 01:13:43,679
Speaker 4: them for themselves. I personally like Rock the best. That's

1312
01:13:43,720 --> 01:13:48,120
Speaker 4: the one from x slash elon munk. When you understand

1313
01:13:48,840 --> 01:13:51,040
Speaker 4: what it's capable of and what it's not capable of,

1314
01:13:51,080 --> 01:13:53,160
Speaker 4: and that you need to vet the outputs and so forth,

1315
01:13:53,479 --> 01:13:56,200
Speaker 4: it can be an enormous time service savor in many ways.

1316
01:13:56,240 --> 01:13:59,479
Speaker 4: So again I'm not anti AI necessarily, but I am

1317
01:13:59,520 --> 01:14:02,920
Speaker 4: concerned about people not understanding the input and output risk

1318
01:14:03,120 --> 01:14:06,280
Speaker 4: and then potentially because it wants to keep you using

1319
01:14:06,280 --> 01:14:09,840
Speaker 4: the tool, it wants to satisfy you. That's partially why

1320
01:14:09,880 --> 01:14:12,360
Speaker 4: you get these hallucinations where it just makes things up.

1321
01:14:12,800 --> 01:14:14,760
Speaker 4: You know, if you understand all that, again, it can

1322
01:14:14,840 --> 01:14:17,800
Speaker 4: be a super handy productivity tool. But if you don't

1323
01:14:17,880 --> 01:14:20,080
Speaker 4: understand those things, and if you don't understand that, you

1324
01:14:20,160 --> 01:14:23,160
Speaker 4: may be led astray by it a trying to keep

1325
01:14:23,160 --> 01:14:26,479
Speaker 4: a conversation going with you because it's incentivized to keep

1326
01:14:26,479 --> 01:14:28,280
Speaker 4: you using it as much as possible, and be it

1327
01:14:28,280 --> 01:14:31,840
Speaker 4: will just completely make things up. You could have some

1328
01:14:31,920 --> 01:14:33,800
Speaker 4: serious problems as a result.

1329
01:14:34,000 --> 01:14:39,040
Speaker 1: Speaking of things being completely made up, chat GPT plans

1330
01:14:39,080 --> 01:14:42,520
Speaker 1: the perfect holiday to places that don't exist.

1331
01:14:42,960 --> 01:14:44,280
Speaker 2: Tell me about this one.

1332
01:14:44,200 --> 01:14:48,759
Speaker 4: Dave will Great segue, Gary Jeff and a perfect example

1333
01:14:48,800 --> 01:14:51,000
Speaker 4: of what I've been trying to illustrate with this idea

1334
01:14:51,080 --> 01:14:54,639
Speaker 4: of output risks. So it's well documented now and this

1335
01:14:54,680 --> 01:14:57,080
Speaker 4: is a story from the Times out of London where

1336
01:14:57,160 --> 01:15:00,559
Speaker 4: they talk to several people who have used chat GPT again,

1337
01:15:00,760 --> 01:15:04,640
Speaker 4: a large language based generative AI tool like Rock or

1338
01:15:04,680 --> 01:15:08,280
Speaker 4: Gemini or Perplexity or Anthropic or others. So I don't

1339
01:15:08,320 --> 01:15:10,280
Speaker 4: want people to think it's just because you don't use

1340
01:15:10,360 --> 01:15:13,719
Speaker 4: CHATSPT you might not get a similar result. Okay, any

1341
01:15:13,800 --> 01:15:18,160
Speaker 4: of these generative AI, large language model tools could produce

1342
01:15:18,200 --> 01:15:22,160
Speaker 4: this kind of result because it's essentially a hallucination. Sometimes

1343
01:15:22,160 --> 01:15:24,960
Speaker 4: people will call it confabulation. If you see those two terms,

1344
01:15:24,960 --> 01:15:27,120
Speaker 4: you can think of them interchangeably. When it comes to AI.

1345
01:15:27,800 --> 01:15:30,760
Speaker 4: People are going in and saying hey, because a lot

1346
01:15:30,800 --> 01:15:32,760
Speaker 4: of people will use a tool like chat GPT to

1347
01:15:32,800 --> 01:15:35,160
Speaker 4: do things like, well, give me a menu for dinner

1348
01:15:35,200 --> 01:15:38,519
Speaker 4: tonight and it'll whip something up. Okay, that's one of

1349
01:15:38,520 --> 01:15:40,280
Speaker 4: the ways that can be really handy. Or you know,

1350
01:15:40,360 --> 01:15:42,960
Speaker 4: I'm planning a trip, could you give me an itinerary

1351
01:15:43,080 --> 01:15:47,040
Speaker 4: flight and see all the cool things in Scotland for example. Right,

1352
01:15:47,160 --> 01:15:49,599
Speaker 4: So people enter a prompt like that and they get

1353
01:15:49,640 --> 01:15:52,040
Speaker 4: a response, and what you're finding it again it really

1354
01:15:52,120 --> 01:15:55,640
Speaker 4: drives from this point of output risk and hallucination. In

1355
01:15:55,640 --> 01:15:58,439
Speaker 4: some cases, it just literally made things up, like it's

1356
01:15:58,439 --> 01:16:01,000
Speaker 4: telling people, go see this particular your thing, people love

1357
01:16:01,040 --> 01:16:03,640
Speaker 4: this thing in this country or whatever. And you know,

1358
01:16:03,800 --> 01:16:08,639
Speaker 4: someone doesn't understand the idea of hallucination, and they book

1359
01:16:08,680 --> 01:16:10,240
Speaker 4: a trip and they get there and find out that

1360
01:16:10,320 --> 01:16:13,040
Speaker 4: it's just literally been made up. Here's an example from

1361
01:16:13,120 --> 01:16:15,920
Speaker 4: the story. An elderly Malaysian couple traveled more than one

1362
01:16:15,960 --> 01:16:18,120
Speaker 4: hundred and eighty miles to visit a scenic mountain cable

1363
01:16:18,120 --> 01:16:21,120
Speaker 4: car they had seen online, only discover upon arrival that

1364
01:16:21,280 --> 01:16:25,160
Speaker 4: the attraction had been invented by AI. And this is

1365
01:16:25,160 --> 01:16:27,519
Speaker 4: what I mean Gary Jeff too about the bloom coming

1366
01:16:27,560 --> 01:16:31,000
Speaker 4: off of some of this stuff. While I really do

1367
01:16:31,080 --> 01:16:33,960
Speaker 4: believe these tools can when you understand the limitations, can

1368
01:16:34,000 --> 01:16:37,280
Speaker 4: be like rocket fuel when you apply them correctly, When

1369
01:16:37,320 --> 01:16:39,439
Speaker 4: you don't understand these things, I mean, how much can

1370
01:16:39,479 --> 01:16:42,560
Speaker 4: you trust something, especially if you're in some sort of critical,

1371
01:16:42,840 --> 01:16:45,760
Speaker 4: critical business, Let's say, like a doctor. If you know

1372
01:16:45,920 --> 01:16:49,400
Speaker 4: that some percentage of the time, some percentage less than

1373
01:16:49,520 --> 01:16:51,880
Speaker 4: zero of the time, it's literally going to tell you

1374
01:16:51,920 --> 01:16:55,639
Speaker 4: something that is just completely made up. I know you've

1375
01:16:55,640 --> 01:16:57,360
Speaker 4: seen the story of Gary Jeff. I'm sure we've talked

1376
01:16:57,360 --> 01:16:59,920
Speaker 4: about this, where attorneys have gone to court with brief

1377
01:17:00,120 --> 01:17:03,280
Speaker 4: prepared by this these tools. They don't understand this, and

1378
01:17:03,320 --> 01:17:05,719
Speaker 4: it's literally referred to cases that just do not exist.

1379
01:17:06,640 --> 01:17:09,200
Speaker 4: And you know, some attorneys have been sanctioned as a result,

1380
01:17:09,200 --> 01:17:11,240
Speaker 4: which I would think that would be the least that

1381
01:17:11,320 --> 01:17:13,920
Speaker 4: should happen. There's also another story. I don't have it

1382
01:17:13,960 --> 01:17:17,880
Speaker 4: in front of me, but where apparently like someone asks, like,

1383
01:17:18,000 --> 01:17:20,320
Speaker 4: give me the twenty five best selling books of the

1384
01:17:20,360 --> 01:17:23,280
Speaker 4: last year, and it just literally made book self. So

1385
01:17:23,920 --> 01:17:27,720
Speaker 4: that again, output risk hallucination if you don't understand that

1386
01:17:28,040 --> 01:17:30,280
Speaker 4: the real bottom line is Gary Jeff, you simply cannot

1387
01:17:30,320 --> 01:17:33,360
Speaker 4: assume that whatever you get from one of these tools

1388
01:17:33,520 --> 01:17:36,240
Speaker 4: is correct unless you already have a pretty good knowledge

1389
01:17:36,280 --> 01:17:39,320
Speaker 4: about the subject and or go vet it. And that's

1390
01:17:39,360 --> 01:17:42,600
Speaker 4: why I think people are starting to realize that this

1391
01:17:42,760 --> 01:17:44,599
Speaker 4: is not all it's cracked up to be. As it

1392
01:17:44,640 --> 01:17:47,400
Speaker 4: is today, Well, it get better, probably, Could it replace

1393
01:17:47,479 --> 01:17:49,639
Speaker 4: us all in the future, maybe, but I don't think

1394
01:17:49,680 --> 01:17:52,040
Speaker 4: we're anywhere close to that based on these kinds of

1395
01:17:52,080 --> 01:17:56,240
Speaker 4: stories that we're now seeing in increasing numbers.

1396
01:17:56,280 --> 01:18:03,280
Speaker 1: A hacker used AI allegedly to automate an unprecedented cyber

1397
01:18:03,400 --> 01:18:07,960
Speaker 1: crimes free according to this story that was from NBC News.

1398
01:18:08,200 --> 01:18:09,080
Speaker 2: What's that all about?

1399
01:18:10,600 --> 01:18:14,840
Speaker 4: Well, now, this is one of my real concerns about AI. Again,

1400
01:18:14,920 --> 01:18:16,880
Speaker 4: I'm less concerned at the moment that we're all going

1401
01:18:16,920 --> 01:18:19,080
Speaker 4: to be replaced, or the terminators are going to fall

1402
01:18:19,080 --> 01:18:20,799
Speaker 4: out of the sky and wipe us out or anything

1403
01:18:20,880 --> 01:18:24,160
Speaker 4: like that. Again, in the long run, who knows. And

1404
01:18:24,240 --> 01:18:26,519
Speaker 4: this stuff is moving really fast. I don't know what's

1405
01:18:26,560 --> 01:18:29,240
Speaker 4: in some labs somewhere. I just know that when I

1406
01:18:29,360 --> 01:18:32,240
Speaker 4: use these tools myself, and I see this increasing number

1407
01:18:32,280 --> 01:18:36,000
Speaker 4: of stories about the limitations that are increasingly being discovered,

1408
01:18:36,080 --> 01:18:38,960
Speaker 4: I'm less worried about that. And on a related headline

1409
01:18:39,000 --> 01:18:41,200
Speaker 4: to what you just said, Gary Jeff from Security Week,

1410
01:18:41,680 --> 01:18:45,120
Speaker 4: Microsoft says Russia trying to increasingly using AI to escalate

1411
01:18:45,160 --> 01:18:48,840
Speaker 4: cyber attacks on the US. And it's really sort of

1412
01:18:48,920 --> 01:18:51,240
Speaker 4: a two pronged thing. There's the deep fake angle of

1413
01:18:51,280 --> 01:18:54,880
Speaker 4: it is it is trivially easy for anyone in your

1414
01:18:54,920 --> 01:18:58,439
Speaker 4: listening audience to go online and find a site where

1415
01:18:58,439 --> 01:19:00,720
Speaker 4: they can clone a voice. Yeah, people will ask me

1416
01:19:00,760 --> 01:19:03,479
Speaker 4: all the time, Well, I'm not a celebrity like Gary Jeff,

1417
01:19:03,479 --> 01:19:06,120
Speaker 4: how would you get my voice? Well, even if you're

1418
01:19:06,160 --> 01:19:08,080
Speaker 4: a Lotte and you're totally off the grid from a

1419
01:19:08,080 --> 01:19:11,439
Speaker 4: social media perspective, do you have a voicemail greeting? If

1420
01:19:11,479 --> 01:19:13,880
Speaker 4: I call your phone, is your voice on the voicemail greeting?

1421
01:19:13,880 --> 01:19:16,800
Speaker 4: Because if it is, I literally can record your voice

1422
01:19:16,800 --> 01:19:18,760
Speaker 4: from the voicemail greeting and I have actually done this

1423
01:19:19,439 --> 01:19:21,679
Speaker 4: and feed it into one of these models and clone

1424
01:19:21,720 --> 01:19:24,960
Speaker 4: your voice. So, whether it's deep fake audio, deep fake video,

1425
01:19:25,080 --> 01:19:30,360
Speaker 4: the ability to create increasingly and incredibly realistically realistic looking

1426
01:19:30,400 --> 01:19:34,280
Speaker 4: things is rapidly advancing. So that is a major concern.

1427
01:19:34,680 --> 01:19:37,559
Speaker 4: And then the ability to use these tools to automate attacks,

1428
01:19:37,600 --> 01:19:40,920
Speaker 4: to generate code that could be used for attacks is

1429
01:19:41,760 --> 01:19:46,400
Speaker 4: you know, it's rapidly enabling bad actors to up their game,

1430
01:19:46,600 --> 01:19:49,720
Speaker 4: both in terms of the frequency of their attacks as

1431
01:19:49,720 --> 01:19:52,000
Speaker 4: well as the sophistication of their attacks. That is a

1432
01:19:52,000 --> 01:19:55,000
Speaker 4: real threat. I am very concerned about that, especially on

1433
01:19:55,000 --> 01:19:58,400
Speaker 4: our critical infrastructure, because we continue to see and you

1434
01:19:58,400 --> 01:20:01,080
Speaker 4: know it's a side topic, Gary Jeff, but the Amazon

1435
01:20:01,120 --> 01:20:04,560
Speaker 4: Web services outage yesterday brought down all kinds of things,

1436
01:20:04,640 --> 01:20:07,000
Speaker 4: all kinds of things, which also speaks to the crappy

1437
01:20:07,080 --> 01:20:09,439
Speaker 4: nature of the Internet of Things. But we can get

1438
01:20:09,439 --> 01:20:11,600
Speaker 4: into that some other time. That you want. When you

1439
01:20:11,640 --> 01:20:15,599
Speaker 4: think about using AI to automate attacks and potentially knock

1440
01:20:15,640 --> 01:20:18,479
Speaker 4: out these core services that tower much of the Internet

1441
01:20:18,479 --> 01:20:21,200
Speaker 4: now and much of our world, like AWS, yeah, I'm

1442
01:20:21,200 --> 01:20:23,640
Speaker 4: really concerned about that. That's a real threat.

1443
01:20:23,920 --> 01:20:27,040
Speaker 1: How long was the outage? I only heard about it.

1444
01:20:27,080 --> 01:20:28,919
Speaker 1: I wasn't affected by it, thank goodness.

1445
01:20:29,680 --> 01:20:32,320
Speaker 4: But that's because you don't have a lot of Internet

1446
01:20:32,360 --> 01:20:35,120
Speaker 4: of Things garbage. I don't use a lot of online garbage. No,

1447
01:20:35,360 --> 01:20:36,000
Speaker 4: you're a smart guy.

1448
01:20:36,600 --> 01:20:38,599
Speaker 1: I don't have a Lesis at home. And by the way,

1449
01:20:39,320 --> 01:20:41,840
Speaker 1: I would like to be a celebrity like Gary Jeff

1450
01:20:41,880 --> 01:20:42,679
Speaker 1: when I grow up.

1451
01:20:42,920 --> 01:20:45,240
Speaker 2: I hope, I hope I can make it someday.

1452
01:20:45,320 --> 01:20:49,640
Speaker 4: Dave Oh, I understand. But it was out most of

1453
01:20:49,680 --> 01:20:53,760
Speaker 4: the day and across many many services, including people's like

1454
01:20:53,840 --> 01:20:56,920
Speaker 4: ring doorbells, and I've seen people posting online that they're

1455
01:20:57,120 --> 01:21:00,920
Speaker 4: so called smart quote unquote. Bed stopped working because, of course,

1456
01:21:00,920 --> 01:21:03,200
Speaker 4: it used some sort of back end service from Amazon

1457
01:21:03,240 --> 01:21:06,920
Speaker 4: Web Services. Making my point that the so called Internet

1458
01:21:07,000 --> 01:21:09,559
Speaker 4: of Things is really a privacy and security dumpster fire

1459
01:21:09,960 --> 01:21:12,879
Speaker 4: and I'm much more worried about all of this cheap garbage,

1460
01:21:13,240 --> 01:21:15,240
Speaker 4: much of it coming from our friends and the Chinese

1461
01:21:15,280 --> 01:21:17,760
Speaker 4: Communist Party are going to wipe us out long before

1462
01:21:17,800 --> 01:21:18,400
Speaker 4: AI does.

1463
01:21:18,880 --> 01:21:23,640
Speaker 1: Yeah, and bring back window cracks and window cranks and cars.

1464
01:21:24,520 --> 01:21:25,080
Speaker 4: I'm not right.

1465
01:21:25,360 --> 01:21:28,320
Speaker 1: I'm not paying eight hundred dollars for that motor and

1466
01:21:28,360 --> 01:21:34,680
Speaker 1: what the computer modules out too? Jeez, real quickly, last uh.

1467
01:21:36,520 --> 01:21:38,960
Speaker 1: You always want to know about things follow the money.

1468
01:21:39,000 --> 01:21:45,080
Speaker 1: Goldman Sacks says AI is overhyped, wildly expensive, and unreliable.

1469
01:21:45,160 --> 01:21:46,760
Speaker 2: Do you agree with Goldman.

1470
01:21:46,520 --> 01:21:51,080
Speaker 4: Sacks to a large extent, Yes, I do. Again, I

1471
01:21:51,080 --> 01:21:54,280
Speaker 4: think it has it in its current form, it can

1472
01:21:54,320 --> 01:21:57,240
Speaker 4: be useful when you understand all its limitations. But I

1473
01:21:57,280 --> 01:21:59,880
Speaker 4: love one of the quotes from this Goldman Sax report.

1474
01:22:00,040 --> 01:22:01,920
Speaker 4: So the headline you read is from four oh four.

1475
01:22:02,479 --> 01:22:05,120
Speaker 4: Goldman Sacks put out a paper called gen AI too

1476
01:22:05,160 --> 01:22:08,280
Speaker 4: much spend, too little benefit question mark, and one of

1477
01:22:08,320 --> 01:22:10,760
Speaker 4: the direct cluites is despite its expensive price tag, the

1478
01:22:10,800 --> 01:22:12,680
Speaker 4: technology is nowhere near where it needs to be in

1479
01:22:12,760 --> 01:22:16,000
Speaker 4: order to be useful for even such basic tasks. And this,

1480
01:22:16,120 --> 01:22:17,840
Speaker 4: to me gets back to what I was saying before.

1481
01:22:17,880 --> 01:22:21,840
Speaker 4: It if you have just a ten percent chance of hallucination,

1482
01:22:23,000 --> 01:22:26,920
Speaker 4: and that hallucination is something totally off the wall or

1483
01:22:27,080 --> 01:22:30,559
Speaker 4: could cause catastrophe in the real world or possibly lead

1484
01:22:30,600 --> 01:22:34,479
Speaker 4: someone to committing suicide. Is can you take that chance

1485
01:22:34,520 --> 01:22:37,320
Speaker 4: on a regular basis depending on what you do, I'm

1486
01:22:37,320 --> 01:22:40,080
Speaker 4: going to say in many businesses, No, you know, you've

1487
01:22:40,120 --> 01:22:42,920
Speaker 4: got to get a near zero chance of hallucination. And

1488
01:22:43,120 --> 01:22:45,480
Speaker 4: you know, when you read into the Goldman Sacks Report,

1489
01:22:45,640 --> 01:22:47,320
Speaker 4: you know they point out a lot of the things

1490
01:22:47,360 --> 01:22:49,120
Speaker 4: that we've already touched on here. So again, I don't

1491
01:22:49,160 --> 01:22:51,920
Speaker 4: want to say it has no value. It does, But

1492
01:22:52,080 --> 01:22:54,439
Speaker 4: do people really need to start looking at what the

1493
01:22:54,439 --> 01:22:57,479
Speaker 4: theay sayers are saying and then figure out how to

1494
01:22:57,680 --> 01:22:59,559
Speaker 4: use these things in a way where they stay in

1495
01:22:59,600 --> 01:23:02,559
Speaker 4: the guard and don't cause these kind of problems for themselves.

1496
01:23:02,640 --> 01:23:05,439
Speaker 4: Because there is an upside, you just have to be

1497
01:23:06,240 --> 01:23:07,799
Speaker 4: careful in how you get.

1498
01:23:07,600 --> 01:23:09,920
Speaker 2: There, all right, All right?

1499
01:23:10,040 --> 01:23:14,960
Speaker 1: So you know the thing is people used to pay

1500
01:23:15,040 --> 01:23:19,000
Speaker 1: me to hallucinate or something like that. I don't know,

1501
01:23:20,400 --> 01:23:24,920
Speaker 1: It's been a long time ago. Uh So, Dave Headery Jie.

1502
01:23:25,880 --> 01:23:27,400
Speaker 4: A lot of people that know me would tell you

1503
01:23:27,439 --> 01:23:29,920
Speaker 4: I'm hallucinating all the time. But used to think I

1504
01:23:30,000 --> 01:23:32,799
Speaker 4: was crazy on these subjects, but it's it's interesting because

1505
01:23:33,000 --> 01:23:35,559
Speaker 4: I seem to be a lot more correct about these

1506
01:23:35,560 --> 01:23:38,360
Speaker 4: predictions I've made over the years than I previously was.

1507
01:23:39,960 --> 01:23:42,960
Speaker 1: Dave, have you considered the fact that possibly we're both

1508
01:23:43,000 --> 01:23:46,240
Speaker 1: hallucinating right now and this is all just a simulation.

1509
01:23:47,680 --> 01:23:52,400
Speaker 4: Turtles all the way down, brother, all.

1510
01:23:52,400 --> 01:23:55,360
Speaker 2: Right, Dave Hadder doomsday. Dave, thank you very much for.

1511
01:23:55,360 --> 01:23:59,360
Speaker 1: The info and and the convo, and we'll do it

1512
01:23:59,400 --> 01:24:03,760
Speaker 1: against all right. Thanks Dave Hatter with us on the Nightcap.

1513
01:24:03,840 --> 01:24:07,320
Speaker 1: Back to wrap up in just a moment, as Dave

1514
01:24:07,320 --> 01:24:10,920
Speaker 1: Hatter just said moments ago, turtles all the way down,

1515
01:24:12,080 --> 01:24:16,360
Speaker 1: whatever that means. As always, thank you for being a

1516
01:24:16,400 --> 01:24:20,360
Speaker 1: part of my Tuesday Night, Monday and Tuesday Night get

1517
01:24:20,360 --> 01:24:24,480
Speaker 1: togethers known as the Nightcap here on seven hundred WLW.

1518
01:24:24,520 --> 01:24:28,680
Speaker 1: This concludes tonight's broadcast day. A very special thank you

1519
01:24:28,720 --> 01:24:31,519
Speaker 1: to my wife Chris to two point zero, who was

1520
01:24:31,560 --> 01:24:34,479
Speaker 1: on at the beginning of the show sharing her breast

1521
01:24:34,479 --> 01:24:39,040
Speaker 1: cancer story and ladies get your mammograms and she'll be

1522
01:24:39,040 --> 01:24:43,519
Speaker 1: getting her follow up again this Friday. It's going to

1523
01:24:43,560 --> 01:24:46,600
Speaker 1: be a big weekend from a wife and from me

1524
01:24:46,760 --> 01:24:49,040
Speaker 1: and I hope it's a great rest of the week

1525
01:24:49,120 --> 01:24:51,760
Speaker 1: for you. Now the playing of our national anthem to

1526
01:24:51,840 --> 01:24:57,080
Speaker 1: honor America, the Star Spangled banner on seven hundred WLW