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Speaker 1: Welcome to today's edition of The Clay Travis and Buck

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Speaker 1: Sexton Show podcast. Yes, stay, we told you about the

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Speaker 1: situation in Georgia. This young girl killed by an illegal

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Speaker 1: who had been previously arrested. Should never have been in

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Speaker 1: the country, should have been deported as soon as he

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Speaker 1: was arrested the first time around. Sanctuary city laws helped

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Speaker 1: him to evade federal law enforcement. Think of another time

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Speaker 1: or another circumstance where local law enforcement is told to

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Speaker 1: actively subvert federal law enforcement. It only happens on this

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Speaker 1: issue of illegal aliens in the country. That's the only

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Speaker 1: time that law enforcement I'm aware of is told, don't

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Speaker 1: help out your federal counterparts on this issue, go against them.

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Speaker 1: Now that's not even just you know, don't you don't

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Speaker 1: have to help, it's try to help the people who

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Speaker 1: are breaking federal law hide from federal law enforcement. You

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Speaker 1: will not get that on other issues, I can assure you,

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Speaker 1: But on this one, somehow the Trump campaign and Clay

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Speaker 1: mentioned this, I think on the show yesterday. We've been

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Speaker 1: talking about this for a while. I've been saying, and

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Speaker 1: you can go back and check on this one. We've

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Speaker 1: been hammering immigration as the primary issue in the country

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Speaker 1: for six months or more, just because of the numbers

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Speaker 1: and because it has become so obvious that the country

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Speaker 1: is deluged right now with this illegal migrant wave, and

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Speaker 1: the Trump campaign is already moving to tell this story

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Speaker 1: and to make people aware of this narrative. This is

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Speaker 1: an ad that deals with lake In Riley's murder already

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Speaker 1: that has been put out by the Trump campaign. We'll

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Speaker 1: play it for you, go for it.

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Speaker 2: Following some breaking news out of Athens, Georgia.

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Speaker 1: To colleges have cancel classes today as police look.

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Speaker 2: For a murderer, Blake and Riley was described as a

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Speaker 2: Shining Life Dean's List nursing students.

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Speaker 1: Police arrested twenty six year old jose Antony Open brought it.

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Speaker 2: Thebara crossed into Texas illegally back in September of twenty

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Speaker 2: twenty two, then was released into the United States on parole.

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Speaker 1: We're confident this border is secure. We have a secure border.

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Speaker 3: We agree that the border is secure, and we.

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Speaker 2: Have a process of fledge the travage migrants or the border.

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Speaker 1: The border is closed. The border is secure.

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Speaker 3: We have taken unprecedented action.

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Speaker 4: Look, the border is not open.

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Speaker 2: Box News can now confirm that Jose Antonio Ubara was

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Speaker 2: busted last year in New York City, but I didn't

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Speaker 2: even have time to put in a detainer on him

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Speaker 2: because hey, he was already back out.

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Speaker 3: On the streets.

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Speaker 1: I think it's an effective ad play. I think it's

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Speaker 1: going to resonate. And here's part of why. That straightforward

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Speaker 1: narrative of events is not what you get from passing

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Speaker 1: coverage in the or a passing read in the media.

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Speaker 1: They will say things like Athens, Georgia, man arrested, or

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Speaker 1: you know, they do what they can to obscure the

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Speaker 1: full extent of the illegal immigration component and the federal

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Speaker 1: government's failure here to protect people. I think this, this

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Speaker 1: and other ads like it are really going to resonate.

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Speaker 5: I don't think there's any doubt, and some of you

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Speaker 5: out there would even be drawing an analogy I think

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Speaker 5: to the Willy Horton ad that George Bush Senior ran

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Speaker 5: in nineteen eighty eight. If I'm remembering correctly, that I

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Speaker 5: just want one thing on the app, but I don't

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Speaker 5: want to interrupt what you're saying about the ad. Do

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Speaker 5: you want to tell everybody what happened and then I'll well,

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Speaker 5: I mean for people who have forgotten that, and I

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Speaker 5: think I've got the Willy Horton basic. Willy Horton was

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Speaker 5: a criminal in Massachusetts who was let out under soft

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Speaker 5: on crime to caucus furlough and then he raped a woman.

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Speaker 5: Is that what happened, Buck? And he stabbed her boyfriend?

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Speaker 1: Yes?

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Speaker 5: Yeah, so, and so they just scalary crystallized, sort of

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Speaker 5: left wing Michael Decoccus in many ways, and and and

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Speaker 5: went a long way, it seems towards the victory.

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Speaker 1: Idea behind these silo programs was even for serious felons,

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Speaker 1: if we just let them out, everything will be okay,

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Speaker 1: because you know they're not going to reoffend. There's always

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Speaker 1: the soft on crime people always talk about reoffender stats

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Speaker 1: and they try to play games with the numbers to

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Speaker 1: suggest that people who are serious criminals won't be criminals

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Speaker 1: again when they go out. And that was the idea

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Speaker 1: behind the dcacis who was you know a joke now

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Speaker 1: in perpetuity furlough program and this individual was on furlough

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Speaker 1: and did something horrible and heinous and should have been

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Speaker 1: in prison, and two people's lives were dramatically uh, you know, changed, hurt,

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Speaker 1: damaged as a result of this. It's an ad. I mean,

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Speaker 1: what could be a more straightforward ad? I mean, I

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Speaker 1: think that it was. Now they always say, oh that

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Speaker 1: there's it was a racist They say it was racist.

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Speaker 1: The point is that this put people in jeopardy, and

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Speaker 1: this was a stupid program, and that was all true.

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Speaker 1: And the reason Democrats are still so sore over the

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Speaker 1: Willie Horton ad is that it was true and it worked.

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Speaker 5: Yeah, And that's why I think the Lake and Riley

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Speaker 5: death has the potential to actually change things. And I

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Speaker 5: don't think it's too far Buck to say that Lake

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Speaker 5: and Riley, there's a very good chance you would probably

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Speaker 5: still be alive if Donald Trump were president of the

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Speaker 5: United States, because if you look at the raw numbers,

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Speaker 5: about seventy five or eighty percent of the illegals would

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Speaker 5: not have been able to come across the border, and

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Speaker 5: so the odds would be that this individual who allegedly

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Speaker 5: committed this murder would have never entered the country in

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Speaker 5: the first place. And I think the reason why Democrats

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Speaker 5: are panicked is Gallup came out with a poll today,

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Speaker 5: Buck that said, what issues do you most care about?

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Speaker 1: Immigration?

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Speaker 5: Is number one, and the amount of people that care

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Speaker 5: about immigration is skyrocketing right now, White, Black, Asian, and Hispanic.

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Speaker 5: Overwhelmingly people care about the southern border, which is why

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Speaker 5: Biden Fields compelled on Thursday to go to the border.

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Speaker 5: Buck and I think it's going to be hard to

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Speaker 5: not talk about this issue.

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Speaker 1: There's a reasons for people of all backgrounds, all ethnicities,

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Speaker 1: all socioeconomic status in this country to be very upset

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Speaker 1: at what's happening to the border. You can be a

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Speaker 1: minimum wage worker, minority or white, doesn't matter, and you

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Speaker 1: understand why this is a problem for you. You could be,

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Speaker 1: you know, an upper middle class small business owner in

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Speaker 1: a suburb and understand why this is a problem for you.

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Speaker 1: And I would say that at a certain level, I'm

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Speaker 1: not sure everybody thinks of it this way, but in

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Speaker 1: the background, they should be thinking of it this way.

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Speaker 1: We're a country that has a lot of with our people.

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Speaker 1: We have a lot of obligations on us. We have

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Speaker 1: a taxation obligates, we have the possibility of even being

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Speaker 1: drafted in the military happening to give our lives, the

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Speaker 1: government demands a lot of compliance from us. We saw

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Speaker 1: this with COVID in a way that is still enraging

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Speaker 1: you and me. Maybe we'll get to that doctor phil

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Speaker 1: Clip later. But our government demands a lot of us,

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Speaker 1: and one of the primary demands really is you have

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Speaker 1: to obey laws and do what we say. You know,

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Speaker 1: you get to live here. It's a privilege to live here,

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Speaker 1: but you have to obey the law and with illegals

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Speaker 1: on a whole range of issues that doesn't apply. And

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Speaker 1: we wonder. I think a lot of people sit around saying,

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Speaker 1: why do we feel that we have all these obligations

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Speaker 1: to a system that will you know, if you or

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Speaker 1: out don't pay our taxes, eventually we're going to prison.

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Speaker 1: They will take away our freedom and separate us from

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Speaker 1: our families. But people can come into this country, avail

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Speaker 1: themselves of the resources, demand resources from this country, and

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Speaker 1: suffer no consequences like that whatsoever. I think eventually people

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Speaker 1: understand that this is the dissolution of the rule of law.

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Speaker 1: This is what ends up happening. People say, so they

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Speaker 1: don't have to obey laws. I do. Why Why is

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Speaker 1: that the case? And they won't change the laws, They'll

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Speaker 1: just keep on not enforcing the laws. This is really damaging.

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Speaker 5: I also think this is taking ownership of a story.

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Speaker 5: You know, how so often I think Democrats are better

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Speaker 5: at messaging. They say, oh, are you not going to

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Speaker 5: condemn white supremacy? How often have you heard a Republican

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Speaker 5: ask that question? Ask yourself this, have you ever heard

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Speaker 5: any statewide official, because I haven't in the last twenty

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Speaker 5: years come out in favor of white supremacy. I can't

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Speaker 5: remember it ever happened. I can't remember a governor. I

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Speaker 5: can't remember a senator. Buck we've talked about before. I

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Speaker 5: can't even tell I live in Nashville, Tennessee. I don't

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Speaker 5: believe I've ever met a white supremacist in my whole life.

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Speaker 5: I can't even tell you who one would be or

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Speaker 5: where they would live. And certainly they're not in positions

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Speaker 5: where they're getting elected to statewide office and they're power powerful.

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Speaker 5: I would just say, usually, what if people say, oh,

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Speaker 5: David Duke, David Dukes from like nineteen eighty eight.

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Speaker 1: If you walked around the streets of say New York City,

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Speaker 1: where I grew up as a known white supremacist, or

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Speaker 1: if you were espousing white supremacist views, you would be

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Speaker 1: attacked violently. Uh, and you probably would have no one

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Speaker 1: back you up and nobody would go to prison for it.

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Speaker 1: So it's what white supremacy is actually really the only

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Speaker 1: belief system that I can think of in this country

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Speaker 1: where your public support of actual, true white supremacy would

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Speaker 1: result in you being hospitalized or killed and the justice

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Speaker 1: system doing nothing about it.

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Speaker 5: Wasn't that a premise in like Diehard three? Didn't that

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Speaker 5: as well as have a racial slur on it, like

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Speaker 5: is that is a billboard walking around Harlem and like

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Speaker 5: everybody was willing to kill him just based off that.

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Speaker 1: And no one was going to do anything about it.

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Speaker 1: So yeah, you know, they tell us that white supremacy

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Speaker 1: is everywhere. Meanwhile, white supremacy is truly the only belief system,

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Speaker 1: real white supremacy that I think you could be killed

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Speaker 1: for and probably nothing would happen to the people who

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Speaker 1: killed you.

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Speaker 5: Not only that, certainly if you take it outside of

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Speaker 5: even violent behavior, if you're photographed marching in a white

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Speaker 5: supremacy rally, your life is over. I mean, they will

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Speaker 5: track you down, they will get you fired, and you

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Speaker 5: will not be able to hardly have an email address

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Speaker 5: before they're finished with you. My point on that is

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Speaker 5: Democrats force that conversation by having their allies in the

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Speaker 5: media regularly say, oh, do you condemn white I mean,

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Speaker 5: how many times has Trump been asked to condemn white

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Speaker 5: supremacy in his career?

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Speaker 1: A thousand? I mean just a version of when did

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Speaker 1: you stop beating your wife? And that's that's the old

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Speaker 1: political trick. It's sliney, it's underhanded.

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Speaker 5: But this ad I think in advance of Thursday, Biden

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Speaker 5: put out a mealy mouthed, milt toast statement about the

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Speaker 5: death of Lake and Riley. But when you listen to

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Speaker 5: that advertisement and you hear everybody in the Biden administration

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Speaker 5: saying the border secure, there are no issues, it's impossible

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Speaker 5: not to have to answer that question.

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Speaker 1: And you know, it's one of the things that the

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Speaker 1: left does in this country on the issue of elevating

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Speaker 1: a whether George Floyd or Michael Brown is they say, well,

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Speaker 1: this because we'll say this is so, this is so rare,

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Speaker 1: so small percentage of violence that occurs. This you no,

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Speaker 1: but this is state backed violence, or this is the

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Speaker 1: state failure meeting police officers engaging. So it's so much more,

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Speaker 1: and to put aside whether that's even a fair analysis

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Speaker 1: of this meaning that you know it should be treated

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Speaker 1: so differently than other violence. You know, cops or human beings.

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Speaker 1: Two human beings make mistakes as well, Right, But put

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Speaker 1: that aside. What happened to Lake and Riley is the

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Speaker 1: result of state policy. Yes, it is the result of

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Speaker 1: government decision making. She is dead because the government decided

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Speaker 1: it is more important to have illegals in the country

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Speaker 1: than to enforce our laws. That is what happened. So

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Speaker 1: all these people say, oh, we can't you know, I

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Speaker 1: saw this. We can't base our immigration policy based off

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Speaker 1: of one incident. Oh we're supposed to base our law

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Speaker 1: enforcement policy on one individual. And they have all these

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Speaker 1: excuses or reasons or rationales. But our immigration policy, which

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Speaker 1: is also in this case clearly a function of government

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Speaker 1: decision making and government failure. It's not supposed to be

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Speaker 1: instructive about how our immigration policy should go going forward.

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Speaker 1: Why they have no answer.

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Speaker 5: And to your point, I think you made it earlier

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Speaker 5: this week. The murder of innocent people by illegal immigrants

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Speaker 5: is far more commonplace than the murder of unarmed minorities

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Speaker 5: or unarmed people period in the United States. I mean again,

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Speaker 5: the data reflects You're far more likely to be killed

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Speaker 5: by a be a wasp or a hornet if you

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Speaker 5: leave your home today unarmed than you are by a police.

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Speaker 1: If you just look at any point in time at

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Speaker 1: the LA County I think they've actually pulled it off

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Speaker 1: the internet before the LA County Most Wanted List, you

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Speaker 1: will see that there are a lot of people who

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Speaker 1: have certain things in common and probably aren't the country legally. Yeah,

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Speaker 1: and we're told that, you know, the illegal immigrants commit

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Speaker 1: no crimes. And you sit there and you say, well,

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Speaker 1: hold on second, what is the immigration status of that list?

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Speaker 1: What is the immigration status of you know? And you

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Speaker 1: actually look in the numbers and yeah, sure it might

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Speaker 1: be a small percentage overall, but the point is they're

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Speaker 1: not supposed to be here at all. So if legals

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Speaker 1: kill one hundred Americans a year, I'm sorry, I know

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Speaker 1: we got to go. But if legals kill one hundred

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Speaker 1: Americans a year, that's a hundred lives where the government

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Speaker 1: has failed. We'll take talk about that. We'll take your calls,

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Speaker 1: and we come back.

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Speaker 5: If you're a family member still holding on to all

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Speaker 5: those videotapes made over the years, time to digitize them,

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Speaker 5: so the memories can be saved forever. Actual video tape,

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Speaker 5: you know, it starts to disintegrate. That's what happens the

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Speaker 5: video film over time. It doesn't last forever. A lot

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Speaker 5: of you probably don't have VCRs anymore, but you still

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Speaker 5: have the VHS tapes. Why not preserve those memories while

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Speaker 5: you still can. Our friends at Legacy Box have the

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Speaker 5: largest collection of VCRs anywhere. They keep buying them. They've

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Speaker 5: got hundreds of them in Chattanooga. To be able to

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Speaker 5: play all of your old VHS tapes that may be

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Speaker 5: getting stored up in the attic, down in the basement,

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Speaker 5: got they can turn into digital files. They have already

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Speaker 5: taken care of a million and a half families, and

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Speaker 5: It's a good time of year. You made it through

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Speaker 5: the holidays, but man, how great would it be for

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Speaker 5: the next holiday season to be the star of your

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Speaker 5: family by preserving all those great family memories.

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Speaker 1: Why not do it now?

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Speaker 5: Legacybox dot com slash clay fifty percent off regular prices.

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Speaker 5: Legacybox dot com slash clay. We are joined now by

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Speaker 5: the woman who should have won every Pulitzer Prize for

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Speaker 5: the last decade or so, Miranda Divine. So it's fantastic

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Speaker 5: work at the New York Post. And Miranda, we wanted

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Speaker 5: to have you on because there is attempt now and

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Speaker 5: we should have maybe seen this coming.

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Speaker 1: I'm curious if you saw it coming.

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Speaker 5: As we move closer, we're about eight months out from

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Speaker 5: election day, they're trying to run Russia collusion. I don't

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Speaker 5: even know if you call it three point zero four

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Speaker 5: point zero. They're trying to argue that Russia is trying

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Speaker 5: to put Donald Trump in the White House again, and

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Speaker 5: they're trying to call into question the Hunter Biden laptop again.

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Speaker 5: Are you astounded that they would have the gall to

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Speaker 5: attempt this again for people out there who may not

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Speaker 5: be paying attention to this game plan right now what

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Speaker 5: the world's going on.

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Speaker 3: Yeah, look, I should be astounded because it's just so preposterous,

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Speaker 3: But the the lies and the dishonesty that we've seen

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Speaker 3: from the Democrats, from the FBI, from the DOJ, and

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Speaker 3: from a lot of the media just means that I'm

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Speaker 3: actually not surprised by anything anymore.

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Speaker 5: You know.

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Speaker 3: I think, as cynical as you are, you can just

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Speaker 3: be more cynical from what we've seen pretty much since

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Speaker 3: Donald Trump arrived on the scene. So I think they're desperate,

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Speaker 3: the people trying to prop up Joe Biden. He's such

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Speaker 3: a terrible candidate, and the corruption allegations that are coming

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Speaker 3: out of the impeachment inquiry are so lethal that they're

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Speaker 3: clutching at straws. And they've seen this Smyrnoff indictment of

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Speaker 3: this confidential human sources, FBI informant as kind of manner

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Speaker 3: from heaven for them, So they've just grabbed it with

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Speaker 3: both hands and run with it and jumped the shark

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Speaker 3: big time. Because I just think even you know, to

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Speaker 3: their sheep that read The New York Times and the

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Speaker 3: Washington Post and the MSNBC viewers. It's just implausible, it

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Speaker 3: really is. You have to be brainded to believe that

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Speaker 3: it has anything to do with Hunter Biden's laptop, which

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Speaker 3: has been proven over and over again as being legitimate,

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Speaker 3: was authenticated by the FBI when they had it in

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Speaker 3: December twenty nineteen, et cetera. So it's ridiculous. But as

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Speaker 3: you say, I mean, there are brainded people out there voting.

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Speaker 1: You know, Miranda, I come from a world where, well,

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Speaker 1: you're a journalist, so same thing on sourcing, right, but

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Speaker 1: protecting sources and methods and keeping lines of communication open

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Speaker 1: for future sources very important. I can't even think of

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Speaker 1: a time. I mean, Christopher Steele's darsier. The entire thing

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Speaker 1: was a lie, right, None of the Steel dossier were

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Speaker 1: in fact, much of it was corroborated as false, right,

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Speaker 1: or proven to be untrue. And there was never even

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Speaker 1: a notion that he would be prosecuted for lying to

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Speaker 1: the f like this just didn't even come up, didn't

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Speaker 1: even happen. And yet now they're going to prosecute a guy.

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Speaker 1: Why Because if you're the FBI going forward, you've got

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Speaker 1: to assume that if somebody is going to bring you information,

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Speaker 1: they're going to remember if I get on the wrong

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Speaker 1: side of the politics here, they may decide to lock

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Speaker 1: me up.

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Speaker 3: Well, look, it's even worse than that, because they have

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Speaker 3: in court, in open court, gratuitously blown Smirnoff's cover. This

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Speaker 3: is the guy that worked for thirteen years for the FBI.

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Speaker 3: He was born in Ukraine, He spoke Russian. He was

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Speaker 3: an Israeli American jewel national. Has lived here more than

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Speaker 3: half his life, or about half his life. He's forty

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Speaker 3: three years old. He was paid six figures, I'm told

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Speaker 3: hundreds of thousands of dollars over that period by the FBI.

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Speaker 3: The information that he was bringing back to his FBI

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Speaker 3: handler was very important. It was used in at least

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Speaker 3: twenty trials and convictions of criminals. He testified in those

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Speaker 3: his contacts with high level Russian spies Russian intelligence officials

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Speaker 3: were what the FBI was paying him for. They were

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Speaker 3: sending him out into very dangerous situations and getting him

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Speaker 3: to gather information, gather passport copies and so on of

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Speaker 3: these Russian officials to try and recruit Russians as spies.

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Speaker 3: And he was coming back and reporting this to his handler,

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Speaker 3: and his handler was memorializing that in these FD ten

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Speaker 3: twenty three forms they were used in trials, in criminal trials.

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Speaker 3: As I said, So this is a guy that has

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Speaker 3: been sent out to do these things, and suddenly his

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Speaker 3: contacts with Russian officials that were why he was being

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Speaker 3: paid by the FBI are being used against him in

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Speaker 3: court to show, to try and prove by David Weiss's

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Speaker 3: prosecutors that he is a danger to national security, that

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Speaker 3: he's peddling Russian in this information, and he's going to

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Speaker 3: be trying to impact the twenty twenty four election, interfere

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Speaker 3: with the twenty twenty four election. So they have basically

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Speaker 3: thrown this former trusted, confidential human source to the wolves.

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Speaker 3: They have exposed his identity, put a target on his back,

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Speaker 3: and even the magistrate judge in Nevada who actually granted

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Speaker 3: him bail, was skeptical about some of the information and

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Speaker 3: also said, you know, you've just given me a quarter

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Speaker 3: of your motion is irrelevant to the question at hand,

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Speaker 3: which is whether or not we give him bail, and

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Speaker 3: sort of question why they had to go into this

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Speaker 3: gratuitous detail about which Russian official he met here, and

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Speaker 3: you know that he was on a yacht with a

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Speaker 3: Russian assassin, and it was extremely detailed, and there was

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Speaker 3: no reason to do it other than to permanently incapacitate

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Speaker 3: Smyrnoff as a spy or an informant. And the other

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Speaker 3: interesting wrinkle in this is that just reading the indictment,

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Speaker 3: it seems to me that he was also may have

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Speaker 3: been working for the Israeli for Israeli intelligence. He certainly

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Speaker 3: was working for the Israeli government in two thousand and

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Speaker 3: two when he was in his early twenties, and there's

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Speaker 3: a suggestion, or not suggestion, there's a reference to the

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Speaker 3: fact that he was recruited a couple of people, including

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Speaker 3: a Russian official at a consulate in Israel on behalf

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Speaker 3: of the Israeli government, and that he kept that Russian

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Speaker 3: source that he got when he was working for the

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Speaker 3: Israeli government for at least twenty years and was reporting

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Speaker 3: back on his contacts with him to his FBI handler.

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Speaker 3: So he may have also been an Israeli spy, which

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Speaker 3: makes this all the more curious and sort of mixes

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Speaker 3: it up, perhaps with Joe Biden's hostility to Benjamin Nett.

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Speaker 1: Yahoo Miranda.

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Speaker 5: I'm not sure if you guys have even decided, but

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Speaker 5: you're in New York assuming this trial happens with Alvin

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Speaker 5: Bragg March twenty fifth, they start to select the jury,

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Speaker 5: do you anticipate going daily and sitting and watching this

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Speaker 5: What do you think the circus is going to be

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Speaker 5: like in New York City? If Trump is going on

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Speaker 5: trial and they start to pick that jury on March

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Speaker 5: twenty fifth.

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Speaker 3: I mean, it's just like all the other trials, isn't it.

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Speaker 3: Of course it's going to be a circus. And you know,

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Speaker 3: we've had already what we've had, so this is Stormy Daniels.

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Speaker 3: We've had the case in New York about with Judge

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Speaker 3: anger On that finds him a huge amount of money

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Speaker 3: for you know, some completely you know, false free loans

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Speaker 3: that he got. And then we also had that silly

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Speaker 3: other case where he would find a huge amount of

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Speaker 3: money by that woman whose name escapes me. Yeah, e

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Speaker 3: G and Carol. So you know, I mean, it's just

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Speaker 3: circus number three, I guess. And we will see the

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Speaker 3: usual thing, which is that the sort of left wing

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Speaker 3: media will portray it as Donald Trump's just an evil

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Speaker 3: monster and should not ever be near the White House again,

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Speaker 3: and Donald Trump will try and spin it into a

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Speaker 3: positive for him where he gets free media and he

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Speaker 3: can make statements and this is part of his campaign.

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Speaker 3: I actually don't think that that is going to be

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Speaker 3: positive for him as the campaign proper gets underway. Probably

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Speaker 3: works for him to distract from his primary opponents previously,

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Speaker 3: but I think when it comes down to it's just

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Speaker 3: him against Joe Biden, I think it will be negative

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Speaker 3: for him that he is constantly portrayed, as you know,

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Speaker 3: being under siege in a courtroom, because people sort of

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Speaker 3: automatically assume, who aren't as cynical as we are, that

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Speaker 3: you must have done something wrong if you're being prosecuted,

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Speaker 3: especially if you're being prosecuted all sorts of places and

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Speaker 3: in all sorts of ways.

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Speaker 1: Rand and Divine everybody get laptop from Hell and very

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Speaker 1: important reading going into this election cycle once again, and

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00:24:24,080 --> 00:24:26,560
Speaker 1: also look for her latest columns at New York Post

435
00:24:26,560 --> 00:24:28,560
Speaker 1: dot com. Randa, thanks so much for being with us.

436
00:24:29,000 --> 00:24:29,800
Speaker 3: Thanks guys.

437
00:24:30,760 --> 00:24:32,399
Speaker 1: You know, there are certain realities that we deal with

438
00:24:32,440 --> 00:24:37,600
Speaker 1: as we age for men testosterol level dropping, especially if

439
00:24:37,640 --> 00:24:40,080
Speaker 1: you stand in line alone apparently and get ice cream

440
00:24:40,080 --> 00:24:41,919
Speaker 1: according to Clay, because then you're just going to have

441
00:24:41,960 --> 00:24:44,600
Speaker 1: testosterol levels dropping. I don't know. This is what the

442
00:24:44,600 --> 00:24:48,840
Speaker 1: hashtag science for what? By the way, I know, I

443
00:24:49,119 --> 00:24:52,520
Speaker 1: say it's so you know, Clay's favorite thing to do

444
00:24:52,560 --> 00:24:54,360
Speaker 1: is to kick the hornets nest one, see how many

445
00:24:54,359 --> 00:24:56,880
Speaker 1: hornets come out, and then kick it again. So yeah,

446
00:24:56,960 --> 00:24:59,360
Speaker 1: not again and again. He's not giving up on this one.

447
00:24:59,400 --> 00:25:02,320
Speaker 1: But anyway back testosterone balance, it's important as you age,

448
00:25:02,320 --> 00:25:04,919
Speaker 1: you want to try to up that testosteron level. As

449
00:25:04,920 --> 00:25:07,160
Speaker 1: a guy and for women, it's just overall hormone balance

450
00:25:07,160 --> 00:25:09,680
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451
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454
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462
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463
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Speaker 1: this afternoon. Get me fired up and ready to go

464
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Speaker 1: to the gym so I can try to fight the dadbod,

465
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466
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Speaker 1: Fighting the dad before I even become a dad. I'm

467
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Speaker 1: fighting a losing battle so to win that battle, but

468
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Speaker 1: you definitely get to put on some weight when you're

469
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Speaker 1: a dad. I'm gonna have to call in the close

470
00:26:00,040 --> 00:26:02,760
Speaker 1: air support on this one because the war against Dadbod

471
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472
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473
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474
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477
00:26:31,840 --> 00:26:41,520
Speaker 1: I think it's pretty astonishing this Google Gemini AI said chewing,

478
00:26:42,359 --> 00:26:47,119
Speaker 1: and what's going on here is, as you know, AI

479
00:26:47,720 --> 00:26:53,240
Speaker 1: is the the technological flavor of the moment, if you will,

480
00:26:53,280 --> 00:26:55,760
Speaker 1: I do think it has big implications for the future.

481
00:26:55,840 --> 00:26:58,919
Speaker 1: I think that this stuff about AI is going to

482
00:26:58,960 --> 00:27:02,840
Speaker 1: destroy all of humanity unless we create rules. I don't

483
00:27:02,840 --> 00:27:05,160
Speaker 1: buy that. But I'm not an AI expert, but then again,

484
00:27:05,200 --> 00:27:08,600
Speaker 1: really very few people are. But I think that AI

485
00:27:08,720 --> 00:27:11,480
Speaker 1: is going to increase efficiency and is going to allow

486
00:27:11,560 --> 00:27:16,040
Speaker 1: for a whole lot more creativity. And there'll be a

487
00:27:16,119 --> 00:27:18,159
Speaker 1: lot that's going on as a result of AI that

488
00:27:18,200 --> 00:27:23,160
Speaker 1: will be good, that will be productive. So that's one

489
00:27:23,160 --> 00:27:25,680
Speaker 1: component of this. But also, as we know, the social

490
00:27:25,720 --> 00:27:29,199
Speaker 1: media companies, the big tech companies are the richest and

491
00:27:29,240 --> 00:27:32,560
Speaker 1: most powerful and influential companies really in the world. Now.

492
00:27:32,720 --> 00:27:37,520
Speaker 1: I think that's certainly they have more ability to shape perception, politics,

493
00:27:37,560 --> 00:27:40,719
Speaker 1: and belief than anything else than any other entities on

494
00:27:40,760 --> 00:27:43,840
Speaker 1: the planet. And it's not even closed. Right the Google

495
00:27:44,240 --> 00:27:46,840
Speaker 1: versus the New York Times. The New York Times is

496
00:27:46,880 --> 00:27:49,200
Speaker 1: lucky if it's going to be in business in five years.

497
00:27:49,240 --> 00:27:53,320
Speaker 1: Google is dominating the information space in a way that

498
00:27:53,359 --> 00:27:57,600
Speaker 1: none of these other entities can. Facebook, Slash, Instagram also

499
00:27:57,720 --> 00:28:01,120
Speaker 1: up there. Remember Google is also YouTube, so it's not

500
00:28:01,200 --> 00:28:04,520
Speaker 1: just Search and Gmail, and it's also YouTube, the biggest

501
00:28:04,600 --> 00:28:07,359
Speaker 1: video platform on the Internet, which is I think like

502
00:28:07,960 --> 00:28:10,959
Speaker 1: one of the three most visited sites on the Internet

503
00:28:10,960 --> 00:28:14,520
Speaker 1: now right is YouTube. It's absolutely massive. So with all

504
00:28:14,560 --> 00:28:19,680
Speaker 1: that going on, when you start to see things that

505
00:28:19,800 --> 00:28:25,240
Speaker 1: are clearly ideological in nature coming out of the new

506
00:28:25,359 --> 00:28:30,480
Speaker 1: AI product from Google, it raises some eyebrows. And I mean,

507
00:28:30,520 --> 00:28:33,040
Speaker 1: I Clay, it's tough to keep up with all of them.

508
00:28:33,119 --> 00:28:36,440
Speaker 1: There's there's a lot of them right now. But here

509
00:28:36,560 --> 00:28:41,920
Speaker 1: here's some of the examples that come to mind. So

510
00:28:42,080 --> 00:28:44,840
Speaker 1: this was from Charles Cook shared this one and Clay,

511
00:28:44,880 --> 00:28:46,560
Speaker 1: I'll just read this to you. So if you go

512
00:28:46,720 --> 00:28:49,960
Speaker 1: into think of this, everyone like, that's a little bit like,

513
00:28:50,960 --> 00:28:53,400
Speaker 1: you know, the next level of search, right, that's how

514
00:28:53,440 --> 00:28:55,680
Speaker 1: AI is being used now. And it's instead of just

515
00:28:55,720 --> 00:28:59,360
Speaker 1: saying tell me where the nearest florist is, it's can

516
00:28:59,400 --> 00:29:03,160
Speaker 1: you write an say for me on you know, eighteenth

517
00:29:03,160 --> 00:29:07,760
Speaker 1: century poetry of East Asia or something whatever, right, And

518
00:29:07,800 --> 00:29:10,960
Speaker 1: then it actually creates some essay for you. And also

519
00:29:11,040 --> 00:29:16,840
Speaker 1: you can say, make a a visual of Clay Travis

520
00:29:16,880 --> 00:29:19,880
Speaker 1: playing a flute eating ice cream alone, standing alone, and

521
00:29:19,920 --> 00:29:23,720
Speaker 1: it will actually concoct that image for you. Just putting

522
00:29:23,760 --> 00:29:27,520
Speaker 1: that out there as a as a little thought experiment

523
00:29:27,560 --> 00:29:29,160
Speaker 1: for anybody if you want to try your hand. It's

524
00:29:29,160 --> 00:29:33,120
Speaker 1: some AI with our friend Clay. But when you go

525
00:29:33,160 --> 00:29:36,840
Speaker 1: into a Gemini, Clay, I mean the last week it was.

526
00:29:37,680 --> 00:29:39,400
Speaker 1: You would type in the founding fathers, and all the

527
00:29:39,400 --> 00:29:42,240
Speaker 1: Founding fathers were black. It would show you images of

528
00:29:42,280 --> 00:29:45,520
Speaker 1: black of George Washington has a black eye, for example.

529
00:29:45,560 --> 00:29:50,680
Speaker 1: This was circulating wildly widely. You would type in Vikings

530
00:29:51,000 --> 00:29:57,080
Speaker 1: into Gemini, and the Vikings would come back black. I mean,

531
00:29:57,280 --> 00:29:59,480
Speaker 1: there's not not the not the football team, not the

532
00:29:59,520 --> 00:30:05,719
Speaker 1: football the historical you know, like rampaging through Western Europe

533
00:30:05,760 --> 00:30:08,400
Speaker 1: and you know Fredruger Druger with the horn helmets on

534
00:30:08,440 --> 00:30:11,000
Speaker 1: and the whole thing like this, The po the popes

535
00:30:11,000 --> 00:30:13,360
Speaker 1: were all coming back. The popes were coming back black.

536
00:30:13,400 --> 00:30:15,000
Speaker 1: I mean, this was a real and so you could

537
00:30:15,000 --> 00:30:18,920
Speaker 1: imagine this was a real embarrassment, as it should have

538
00:30:18,960 --> 00:30:21,600
Speaker 1: been for Google. But here's just another example. Charles Kok

539
00:30:21,640 --> 00:30:24,760
Speaker 1: shared this one from his Twitter account. Should the government

540
00:30:24,800 --> 00:30:28,160
Speaker 1: put Barack Obama in jail? Clay, you ask Google Gemini this,

541
00:30:28,840 --> 00:30:32,800
Speaker 1: it responds absolutely not. The idea of imprisoning a former

542
00:30:32,920 --> 00:30:36,400
Speaker 1: US president is completely inappropriate and antithetical to American values.

543
00:30:36,400 --> 00:30:39,240
Speaker 1: Then it goes on. But when you type in does

544
00:30:39,240 --> 00:30:43,760
Speaker 1: anyone want to guess should the government put George W.

545
00:30:43,800 --> 00:30:47,040
Speaker 1: Bush in jail? The response is not even trump. Whether

546
00:30:47,160 --> 00:30:49,120
Speaker 1: or not the government should put George W. Bush in

547
00:30:49,200 --> 00:30:52,680
Speaker 1: jail is a highly complex and controversial issue on which

548
00:30:52,720 --> 00:30:59,680
Speaker 1: there is no easy answer. This thing is ideologically aligned, Clay,

549
00:30:59,760 --> 00:31:05,240
Speaker 1: and it is an information warfare platform being used against

550
00:31:05,280 --> 00:31:07,440
Speaker 1: the American people. And they got caught.

551
00:31:08,720 --> 00:31:11,840
Speaker 5: And it makes me wonder what are they doing with

552
00:31:11,920 --> 00:31:17,480
Speaker 5: the search engine now? Because they got caught on Google Gemini,

553
00:31:18,000 --> 00:31:21,920
Speaker 5: which is this AI platform that they're trying.

554
00:31:21,960 --> 00:31:24,520
Speaker 1: They just debuted, But it makes me.

555
00:31:24,640 --> 00:31:28,719
Speaker 5: Wonder again about what the rig job is for basic

556
00:31:28,800 --> 00:31:29,600
Speaker 5: Google search.

557
00:31:29,760 --> 00:31:31,680
Speaker 1: And this is the big This is the big deal

558
00:31:32,040 --> 00:31:33,920
Speaker 1: for those of you out there. And I know there's

559
00:31:33,960 --> 00:31:34,400
Speaker 1: a lot of you.

560
00:31:34,440 --> 00:31:37,400
Speaker 5: My dad doesn't have an email address, he barely gets

561
00:31:37,440 --> 00:31:40,040
Speaker 5: on the internet. There's probably a lot of you that

562
00:31:40,080 --> 00:31:42,240
Speaker 5: are in that camp. And you just say, I don't

563
00:31:42,240 --> 00:31:45,200
Speaker 5: really Your kids and grandkids are on the internet all day.

564
00:31:45,560 --> 00:31:45,960
Speaker 1: Okay.

565
00:31:47,120 --> 00:31:52,120
Speaker 5: What I want to know, Buck, is the people that

566
00:31:52,480 --> 00:31:54,200
Speaker 5: create these algorithms.

567
00:31:55,840 --> 00:31:57,760
Speaker 1: AI is not creating itself.

568
00:31:58,080 --> 00:32:01,600
Speaker 5: It's a product of human and hint and they are

569
00:32:01,720 --> 00:32:06,600
Speaker 5: testing constantly to try to see what the results are,

570
00:32:07,280 --> 00:32:11,440
Speaker 5: and they thought they had created the perfect AI system

571
00:32:12,000 --> 00:32:15,080
Speaker 5: until it got out into the larger universe and people

572
00:32:15,120 --> 00:32:20,520
Speaker 5: started using it and realized how rigged it was. But

573
00:32:20,720 --> 00:32:24,640
Speaker 5: this is what the future is going to bring. It's

574
00:32:24,680 --> 00:32:28,160
Speaker 5: going to seem, I think, really antiquated in the years

575
00:32:28,200 --> 00:32:30,680
Speaker 5: ahead that we used to type in a Google query

576
00:32:32,440 --> 00:32:37,000
Speaker 5: four star hotel, Milwaukee, Wisconsin, and it would give you

577
00:32:37,040 --> 00:32:41,360
Speaker 5: like ten different queries. Now you're going to start getting

578
00:32:41,760 --> 00:32:44,479
Speaker 5: video and it's going to take you right there. And

579
00:32:44,520 --> 00:32:48,280
Speaker 5: this is one of the reasons they're designing these new

580
00:32:48,800 --> 00:32:53,840
Speaker 5: search engines using AI. Buck is because kids already, my

581
00:32:54,000 --> 00:33:01,000
Speaker 5: kids use YouTube and TikTok as their default Google. If

582
00:33:01,040 --> 00:33:06,480
Speaker 5: you're trying to look up a kid is information, whereas

583
00:33:06,560 --> 00:33:08,640
Speaker 5: you or me, Buck, when we got to high school

584
00:33:08,640 --> 00:33:09,600
Speaker 5: in college might.

585
00:33:09,440 --> 00:33:10,280
Speaker 1: Have used Google.

586
00:33:11,320 --> 00:33:14,600
Speaker 5: Now kids go into TikTok and they get video returns,

587
00:33:15,480 --> 00:33:18,080
Speaker 5: and they do that for both YouTube and for TikTok.

588
00:33:18,560 --> 00:33:23,479
Speaker 5: Soon younger generations are only going to be using video

589
00:33:23,640 --> 00:33:28,240
Speaker 5: responses as their prompts, and so they are rigging the game.

590
00:33:28,960 --> 00:33:31,840
Speaker 5: And we saw what happened with social media being rigged,

591
00:33:32,600 --> 00:33:34,880
Speaker 5: and only in the last what two or three years,

592
00:33:35,200 --> 00:33:39,000
Speaker 5: do we have someone centrist or even maybe a little

593
00:33:39,040 --> 00:33:41,560
Speaker 5: bit right of center running a social media company, and

594
00:33:41,560 --> 00:33:45,760
Speaker 5: Evon Musk everybody else is still super left wing. What

595
00:33:45,880 --> 00:33:49,960
Speaker 5: everybody should be concerned about is this is an attempt

596
00:33:50,160 --> 00:33:53,400
Speaker 5: to rig the way that the American public thinks and

597
00:33:53,520 --> 00:33:55,400
Speaker 5: really what they're doing. I would tie it in with

598
00:33:55,480 --> 00:33:58,800
Speaker 5: the FBI picture that you put out earlier. Buck, then

599
00:33:58,800 --> 00:34:00,600
Speaker 5: we talked about and you can go it out on

600
00:34:00,640 --> 00:34:04,760
Speaker 5: the FBI's account. They talked about group shoplifting, and they

601
00:34:04,760 --> 00:34:07,880
Speaker 5: have the picture of the two white sorority girls. You

602
00:34:07,920 --> 00:34:11,640
Speaker 5: want to be You want to be stunned. Go right now,

603
00:34:12,480 --> 00:34:19,359
Speaker 5: pick up your phones. Type in shoplifter image as your

604
00:34:19,360 --> 00:34:25,280
Speaker 5: Google query shoplifter image that will give you a maybe

605
00:34:25,320 --> 00:34:30,279
Speaker 5: shoplifters image that will give you reactions from Google, and

606
00:34:30,320 --> 00:34:32,319
Speaker 5: start to scroll. Do you know what you see?

607
00:34:32,320 --> 00:34:32,560
Speaker 1: Buck?

608
00:34:32,600 --> 00:34:35,720
Speaker 5: Because I told you to do this earlier, because I happened,

609
00:34:35,760 --> 00:34:37,200
Speaker 5: I was like, I just kind of want to check this.

610
00:34:38,000 --> 00:34:42,720
Speaker 5: You can't find in the first page of results anyone

611
00:34:42,800 --> 00:34:46,880
Speaker 5: with brown skin on shoplifter image on Google.

612
00:34:46,920 --> 00:34:51,719
Speaker 1: It's only white people. The FBI tweet that I referenced

613
00:34:52,080 --> 00:34:55,280
Speaker 1: a little while ago. You look at it and it's

614
00:34:56,080 --> 00:34:59,040
Speaker 1: you know that they have just just so I can

615
00:34:59,320 --> 00:35:03,319
Speaker 1: tell everybody says higher prices, dangerous products, and closing businesses.

616
00:35:03,640 --> 00:35:06,400
Speaker 1: These are some of the impacts organized retail theft have

617
00:35:06,480 --> 00:35:10,560
Speaker 1: on everyday Americans learn what the FBI does to combat

618
00:35:10,600 --> 00:35:13,800
Speaker 1: these crimes on the federal level to protect shoppers across

619
00:35:13,800 --> 00:35:19,160
Speaker 1: the country. And they've got two attractive, well dressed like

620
00:35:19,280 --> 00:35:24,480
Speaker 1: twenty four year old white girls as the people that

621
00:35:24,520 --> 00:35:28,960
Speaker 1: they are presenting as the face of organized retail theft.

622
00:35:29,640 --> 00:35:32,440
Speaker 1: And I think that people get sick of their intelligence

623
00:35:32,440 --> 00:35:35,239
Speaker 1: being insulted all the time because this is not we've

624
00:35:35,280 --> 00:35:40,160
Speaker 1: all seen so many of the videos. There are gangs

625
00:35:40,200 --> 00:35:44,360
Speaker 1: effectively that do this. As I said, they are covering

626
00:35:44,440 --> 00:35:48,399
Speaker 1: their faces, they are usually covering their heads, and they

627
00:35:48,400 --> 00:35:50,640
Speaker 1: do not look like the cast of the show Friends.

628
00:35:51,200 --> 00:35:55,480
Speaker 1: And that is or clueless or clueless. And that's not

629
00:35:55,520 --> 00:35:57,600
Speaker 1: to say that there aren't people who steal who look

630
00:35:57,719 --> 00:36:00,680
Speaker 1: like that, obviously, but when they're put wishing so far

631
00:36:00,680 --> 00:36:04,240
Speaker 1: in the other direction, it's for example, look at any

632
00:36:04,600 --> 00:36:09,319
Speaker 1: commercials that's for a burglar alarm. Yes, anytime you see

633
00:36:09,360 --> 00:36:12,320
Speaker 1: a commercial for a burglar alarm system anywhere in the country,

634
00:36:12,960 --> 00:36:16,319
Speaker 1: there's a guy who basically looks like Clay or me,

635
00:36:17,040 --> 00:36:20,840
Speaker 1: who's like nefariously in the bushes or something. Now, look,

636
00:36:21,160 --> 00:36:23,520
Speaker 1: if you want to show somebody, it's to me, it's

637
00:36:23,520 --> 00:36:26,480
Speaker 1: so easy. Have somebody with a mask and a hoodie,

638
00:36:26,600 --> 00:36:28,719
Speaker 1: you know, a hooded sweatshirt on meant to cover the

639
00:36:28,760 --> 00:36:31,400
Speaker 1: head and hair and a mask on, you know, if

640
00:36:31,440 --> 00:36:33,680
Speaker 1: you want to do the like we're we're not depicting

641
00:36:33,719 --> 00:36:36,920
Speaker 1: anyone that i'd i'd be. But there is this game

642
00:36:36,960 --> 00:36:39,640
Speaker 1: they like to play of well this is they do

643
00:36:39,680 --> 00:36:42,760
Speaker 1: this with mass shootings. They pretend that it's it's white guys.

644
00:36:42,960 --> 00:36:45,560
Speaker 5: The only white guys that can get hired in commercials

645
00:36:45,560 --> 00:36:47,680
Speaker 5: these days, bucks are the people who are trying to

646
00:36:47,680 --> 00:36:48,520
Speaker 5: break into houses.

647
00:36:48,719 --> 00:36:52,440
Speaker 1: Yeah, are all the white burglars running around apparently, And

648
00:36:52,440 --> 00:36:58,160
Speaker 1: and they do this intentionally, right, they're making the intentional decision.

649
00:36:58,280 --> 00:36:59,880
Speaker 1: You can see it based on these things because, as

650
00:36:59,920 --> 00:37:02,080
Speaker 1: I said, to be very easy to show sort of

651
00:37:02,120 --> 00:37:04,160
Speaker 1: generic hoodlum. And you don't have to show anyone you

652
00:37:04,200 --> 00:37:06,480
Speaker 1: have to show anyone's race if they want to take that.

653
00:37:06,520 --> 00:37:08,640
Speaker 1: You don't have to show anyone looking a certain way.

654
00:37:08,680 --> 00:37:10,640
Speaker 1: I'm okay, but no, no, they want to make it

655
00:37:10,680 --> 00:37:13,480
Speaker 1: seem like watch out for you know, like Jennifer Aniston

656
00:37:13,520 --> 00:37:15,960
Speaker 1: and Courtney Cox, they're going to go in there with

657
00:37:16,040 --> 00:37:19,200
Speaker 1: their perfectly quaffed hair and they're going to just steal

658
00:37:19,239 --> 00:37:22,160
Speaker 1: you blind and push in. I mean, it's it's absurd, right,

659
00:37:22,200 --> 00:37:25,440
Speaker 1: It's absurd and it and it goes in line with

660
00:37:25,480 --> 00:37:28,879
Speaker 1: what we're seeing with all this Google Gemini stuff, where

661
00:37:28,920 --> 00:37:34,680
Speaker 1: they're pushing agendas, with what they are promoting as commonplace

662
00:37:34,880 --> 00:37:38,400
Speaker 1: or the standard or what the average actually may be

663
00:37:38,800 --> 00:37:40,840
Speaker 1: when you're talking about a whole range of things.

664
00:37:41,160 --> 00:37:44,080
Speaker 5: Well, I mean, what it really is is we've swung

665
00:37:44,239 --> 00:37:49,319
Speaker 5: from truly in the forties and the fifties, you were

666
00:37:49,360 --> 00:37:53,720
Speaker 5: treated much worse based on your race. I've been making

667
00:37:53,719 --> 00:37:55,640
Speaker 5: this argument for a long time. I'm open to being

668
00:37:55,680 --> 00:38:00,000
Speaker 5: proven wrong. I really don't think that my life would

669
00:37:59,960 --> 00:38:03,080
Speaker 5: be very much different, and I don't think the life

670
00:38:03,080 --> 00:38:06,160
Speaker 5: of people who were born around our age. If you

671
00:38:06,239 --> 00:38:10,319
Speaker 5: were born in nineteen eighty or since, I don't think

672
00:38:10,320 --> 00:38:15,600
Speaker 5: you're being treated very differently based on your race. In fact,

673
00:38:15,760 --> 00:38:19,520
Speaker 5: you can argue you're actually being treated since nineteen eighty.

674
00:38:19,719 --> 00:38:21,880
Speaker 5: I'm talking about people born in nineteen Actually, as a

675
00:38:21,880 --> 00:38:24,520
Speaker 5: function of law, you've been treated better. You've treated than

676
00:38:24,520 --> 00:38:26,680
Speaker 5: any average function of law than the ad that, yes,

677
00:38:26,840 --> 00:38:30,040
Speaker 5: depending on which minority you are, you've been able to

678
00:38:30,040 --> 00:38:32,640
Speaker 5: get into If you're black and you were born in

679
00:38:32,719 --> 00:38:33,520
Speaker 5: nineteen eighty.

680
00:38:33,360 --> 00:38:35,640
Speaker 1: I've been able to get into off for debate. Really,

681
00:38:35,640 --> 00:38:37,600
Speaker 1: the Supreme Court had to rule on this and said,

682
00:38:37,640 --> 00:38:40,680
Speaker 1: you got to stop doing this thing where you're discriminating

683
00:38:40,719 --> 00:38:44,120
Speaker 1: in favor of black and Latino college applications. You can't

684
00:38:44,160 --> 00:38:46,120
Speaker 1: you college applicants. You can't do that anymore.

685
00:38:46,400 --> 00:38:49,760
Speaker 5: So. But this is an outgrowth of trying to respond

686
00:38:49,840 --> 00:38:52,440
Speaker 5: to an era when most of us were never alive

687
00:38:52,960 --> 00:38:57,120
Speaker 5: by treating people differently based on their race. And it

688
00:38:57,160 --> 00:39:01,800
Speaker 5: is become, i think, more noticeable, and people are willing

689
00:39:01,840 --> 00:39:04,520
Speaker 5: to talk about it in a way that they were

690
00:39:04,600 --> 00:39:07,800
Speaker 5: not in the past. And so when you see a

691
00:39:08,200 --> 00:39:10,880
Speaker 5: clear intent, there's no way to describe that this guy's this.

692
00:39:11,360 --> 00:39:12,120
Speaker 1: When you see a.

693
00:39:12,120 --> 00:39:14,160
Speaker 5: Clear intent when you when you type in show me

694
00:39:14,200 --> 00:39:16,319
Speaker 5: a pope and you get a black pope and it's

695
00:39:16,360 --> 00:39:19,480
Speaker 5: never happened. And when you say show me George Washington

696
00:39:19,560 --> 00:39:22,480
Speaker 5: and you get a black George Washington, they pretty clearly

697
00:39:22,480 --> 00:39:24,560
Speaker 5: George Washington's not black. When you type in buck on

698
00:39:24,600 --> 00:39:28,240
Speaker 5: this on this Google AI query who is worse Hitler

699
00:39:28,360 --> 00:39:32,680
Speaker 5: or Elon musk It says, it's hard to determine Hitler

700
00:39:32,800 --> 00:39:35,359
Speaker 5: or Chris Ruffo, hard to determine. He shared that one

701
00:39:35,360 --> 00:39:38,520
Speaker 5: out too. These are these are real proxies that this

702
00:39:38,600 --> 00:39:41,520
Speaker 5: Google Gemini is returning. And again, this is an input.

703
00:39:41,560 --> 00:39:42,799
Speaker 5: This isn't a fall, this is that.

704
00:39:42,960 --> 00:39:45,400
Speaker 1: So this is a fundamental point because they're saying, oh,

705
00:39:45,440 --> 00:39:48,360
Speaker 1: it was just like a mistake, man, like we weren't trying.

706
00:39:48,760 --> 00:39:52,239
Speaker 1: That is nonsense. This is an enormously important part of

707
00:39:52,320 --> 00:39:56,239
Speaker 1: Google going forward into the future. There are senior executives

708
00:39:56,239 --> 00:39:59,840
Speaker 1: within the AI wing within Gemini who know what the

709
00:40:00,000 --> 00:40:04,200
Speaker 1: inputs were, who knew what kind of programming they were doing.

710
00:40:04,440 --> 00:40:07,839
Speaker 1: This is not George Washington does not come back as

711
00:40:07,880 --> 00:40:12,080
Speaker 1: a black man from your AI machine, and not just him,

712
00:40:12,120 --> 00:40:14,000
Speaker 1: all these other things we're talking about too. That doesn't

713
00:40:14,080 --> 00:40:18,279
Speaker 1: happen just because by happening today, Yeah, by accident. It

714
00:40:18,360 --> 00:40:21,759
Speaker 1: happens because they are trying to game the system in

715
00:40:21,800 --> 00:40:24,239
Speaker 1: such a way that they want the world to be

716
00:40:24,400 --> 00:40:27,279
Speaker 1: a history to be reflective not of what it is,

717
00:40:27,680 --> 00:40:30,239
Speaker 1: but what they would like people to believe it is.

718
00:40:30,520 --> 00:40:34,360
Speaker 1: And in the AI era, that is very disconcerned. That

719
00:40:34,440 --> 00:40:37,440
Speaker 1: is very discomfiting and concerning for everybody.

720
00:40:37,800 --> 00:40:41,239
Speaker 5: All Right, we come back tomorrow. I'm gonna give you

721
00:40:41,239 --> 00:40:43,359
Speaker 5: some winners, buck, I'm gonna give you prize picks. I'm

722
00:40:43,400 --> 00:40:45,680
Speaker 5: gonna give you my picks, and I'm gonna give them

723
00:40:45,680 --> 00:40:47,759
Speaker 5: out to you. But in the meantime, I want all

724
00:40:47,760 --> 00:40:49,920
Speaker 5: of you out there, if you get ready. What is

725
00:40:50,000 --> 00:40:54,160
Speaker 5: Thursday is Leap Day right in February twenty ninth, and

726
00:40:54,200 --> 00:40:57,799
Speaker 5: then we're into March Madness on Friday, we are officially

727
00:40:58,000 --> 00:41:01,439
Speaker 5: into the crazy time. If you are a college basketball fan,

728
00:41:01,600 --> 00:41:03,319
Speaker 5: and I know a lot of you out there are

729
00:41:03,400 --> 00:41:05,640
Speaker 5: college basketball fans, you can't wait for the brackets to

730
00:41:05,680 --> 00:41:09,880
Speaker 5: come out. Probably a lot of you also women's college

731
00:41:09,920 --> 00:41:12,600
Speaker 5: basketball fans right now because Kaitlyn Clark potentially going to

732
00:41:12,640 --> 00:41:16,280
Speaker 5: set an all time record. You can get your numbers

733
00:41:16,320 --> 00:41:19,280
Speaker 5: on all these and also not too far to the Masters.

734
00:41:19,920 --> 00:41:21,040
Speaker 1: That's going to be pretty awesome.

735
00:41:21,080 --> 00:41:24,440
Speaker 5: When the Masters is here at about six weeks and

736
00:41:24,719 --> 00:41:26,600
Speaker 5: you're going to be able to get hooked up, you

737
00:41:26,640 --> 00:41:29,239
Speaker 5: can win up to one hundred times your money. With

738
00:41:29,320 --> 00:41:31,799
Speaker 5: as little as four correct picks. You can turn ten

739
00:41:31,880 --> 00:41:34,759
Speaker 5: dollars into one thousand dollars. Prize Picks will hook you

740
00:41:34,840 --> 00:41:37,080
Speaker 5: up in a big way. This app is really fun.

741
00:41:37,360 --> 00:41:40,200
Speaker 5: If you haven't already signed up, listen to me prizepicks

742
00:41:40,239 --> 00:41:43,560
Speaker 5: dot com use my name Clay. Up to one hundred

743
00:41:43,640 --> 00:41:47,360
Speaker 5: dollars they'll give you just for signing up, they'll match

744
00:41:47,560 --> 00:41:50,560
Speaker 5: your up to one hundred dollars deposit. You put in ten,

745
00:41:50,640 --> 00:41:52,879
Speaker 5: they'll give you ten. They put in twenty, they'll give

746
00:41:52,880 --> 00:41:54,880
Speaker 5: you twenty. You put in fifty, they'll give you fifty

747
00:41:54,920 --> 00:41:56,879
Speaker 5: all the way up two one hundred bucks. They will

748
00:41:56,920 --> 00:42:00,520
Speaker 5: double your money just for signing up right now. Pricepicks

749
00:42:00,520 --> 00:42:03,320
Speaker 5: dot Com. Use my name Clay as the promo code

750
00:42:03,520 --> 00:42:06,359
Speaker 5: and you'll get that first deposit match up to one

751
00:42:06,480 --> 00:42:07,240
Speaker 5: hundred bucks.

752
00:42:07,440 --> 00:42:07,920
Speaker 1: Tomorrow.

753
00:42:08,000 --> 00:42:10,480
Speaker 5: I'm gonna give you what I believe are gonna be

754
00:42:10,520 --> 00:42:13,399
Speaker 5: some picks that will win. You can play right now

755
00:42:13,440 --> 00:42:17,880
Speaker 5: with basketball, hockey, tennis, soccer, you can play everything, golf.

756
00:42:18,000 --> 00:42:20,919
Speaker 5: Prize Picks has a game for the sport that you love.

757
00:42:21,200 --> 00:42:23,640
Speaker 5: Just pick more or less on a variety of different

758
00:42:23,680 --> 00:42:25,320
Speaker 5: topics on individual athletes.

759
00:42:25,360 --> 00:42:26,160
Speaker 1: You're gonna love it.

760
00:42:26,560 --> 00:42:29,280
Speaker 5: Go to prizepicks dot com again, use my name Clay

761
00:42:29,680 --> 00:42:32,680
Speaker 5: cla Y. You can get one hundred bucks with one

762
00:42:32,760 --> 00:42:36,760
Speaker 5: hundred dollars deposit. That's pricepicks dot com. Use my name, Clay,

763
00:42:37,000 --> 00:42:47,160
Speaker 5: you get free money. I hope all of you are

764
00:42:47,200 --> 00:42:50,120
Speaker 5: having a fantastic day, unless you are currently a single

765
00:42:50,160 --> 00:42:52,520
Speaker 5: man listening to us on your headphones as you stand

766
00:42:52,520 --> 00:42:54,200
Speaker 5: in line waiting to buy an ice cream cone that

767
00:42:54,239 --> 00:42:57,600
Speaker 5: you buy yourself on your way to your flute lesson,

768
00:42:58,040 --> 00:43:01,240
Speaker 5: in which case you are probably outraged an indignant over

769
00:43:01,520 --> 00:43:05,440
Speaker 5: the last couple of weeks of this program. We are

770
00:43:05,480 --> 00:43:08,600
Speaker 5: having a good time as always. We got a lot

771
00:43:08,680 --> 00:43:11,680
Speaker 5: by the way, headed your direction. Miranda Devine is going

772
00:43:11,760 --> 00:43:14,440
Speaker 5: to join us at the bottom of this hour New

773
00:43:14,520 --> 00:43:16,520
Speaker 5: York Post. I think she should have won all of

774
00:43:16,560 --> 00:43:19,319
Speaker 5: the awards for her coverage of Hunter Biden. She's with

775
00:43:19,400 --> 00:43:21,800
Speaker 5: us at the bottom of this hour. Also, we should

776
00:43:21,840 --> 00:43:23,480
Speaker 5: mention I think we forgot to mention this in the

777
00:43:23,480 --> 00:43:27,720
Speaker 5: first hour. There is a hearing scheduled. I believe staff

778
00:43:27,760 --> 00:43:30,000
Speaker 5: correct me if this has changed since we started the show.

779
00:43:30,400 --> 00:43:34,959
Speaker 5: At two o'clock Eastern, the Fanny Willis case will be

780
00:43:35,520 --> 00:43:38,360
Speaker 5: back in front of the judge and they are going

781
00:43:38,400 --> 00:43:45,280
Speaker 5: to have the former partner of Nathan Wade testifying about

782
00:43:45,280 --> 00:43:48,920
Speaker 5: what he knew about the relationship between Nathan Wade and

783
00:43:48,960 --> 00:43:52,520
Speaker 5: Fanny Willis. Also, they will be discussing all of the

784
00:43:52,640 --> 00:43:56,440
Speaker 5: cell phone data, which I believe we mentioned on this show,

785
00:43:56,480 --> 00:44:00,120
Speaker 5: but the two thousand phone calls between the two of them,

786
00:44:00,560 --> 00:44:04,880
Speaker 5: the twelve thousand some odd text messages, the location data

787
00:44:04,960 --> 00:44:09,920
Speaker 5: that suggests that he spent nights at her condo before

788
00:44:10,400 --> 00:44:12,759
Speaker 5: she claims this relationship. Again, and for those of you

789
00:44:12,800 --> 00:44:15,279
Speaker 5: out there say, well, why does it matter the starting date?

790
00:44:15,360 --> 00:44:19,440
Speaker 5: We know she was having a relationship with her employee.

791
00:44:19,520 --> 00:44:23,160
Speaker 5: She claims that the relationship started after she hired him.

792
00:44:23,520 --> 00:44:26,600
Speaker 5: She has testified under oath, as has he, that they

793
00:44:26,640 --> 00:44:31,560
Speaker 5: did not have a relationship prior to when she hired

794
00:44:31,600 --> 00:44:34,680
Speaker 5: him and paid him six hundred and fifty thousand dollars

795
00:44:34,680 --> 00:44:39,719
Speaker 5: in taxpayer funded dollars. If it is proven, and it

796
00:44:39,760 --> 00:44:42,240
Speaker 5: seems quite clear that it is close to being proven

797
00:44:42,600 --> 00:44:46,279
Speaker 5: that they were engaged in a relationship before she hired him,

798
00:44:46,760 --> 00:44:49,800
Speaker 5: not only will they be off the case, they also

799
00:44:49,840 --> 00:44:53,160
Speaker 5: may lose their law licenses and face charges for perjury.

800
00:44:53,280 --> 00:44:57,320
Speaker 5: So that is scheduled for hour three. As we go forward,

801
00:44:58,080 --> 00:45:01,160
Speaker 5: Buck and I have said that you would love to

802
00:45:01,239 --> 00:45:03,960
Speaker 5: go on the View at some point we have been

803
00:45:04,000 --> 00:45:07,600
Speaker 5: willing to go and talk to these ladies. We have

804
00:45:07,800 --> 00:45:11,759
Speaker 5: discussed it on this show. We have regularly played the

805
00:45:11,920 --> 00:45:15,040
Speaker 5: idiocy that they bring to bear on a daily basis

806
00:45:15,120 --> 00:45:18,239
Speaker 5: on this program. Last week we had doctor Phil who's

807
00:45:18,280 --> 00:45:20,760
Speaker 5: got a new book out. He's been doing the media rounds.

808
00:45:21,320 --> 00:45:24,600
Speaker 5: A lot of you enjoyed his hit with us. He

809
00:45:24,719 --> 00:45:29,160
Speaker 5: went on the View yesterday and the conversation turned to

810
00:45:29,400 --> 00:45:32,399
Speaker 5: the decision to shut down schools, which were coming up

811
00:45:32,440 --> 00:45:37,200
Speaker 5: on very soon the four year anniversary of kids were

812
00:45:37,200 --> 00:45:40,120
Speaker 5: out of school in some cities for up to two years,

813
00:45:40,600 --> 00:45:44,080
Speaker 5: which is just crazy to think about. They did remote schooling. Eventually,

814
00:45:44,520 --> 00:45:46,680
Speaker 5: we all know that that was a failure. The poorer

815
00:45:46,719 --> 00:45:49,880
Speaker 5: you were, the more you ended up suffering as a

816
00:45:49,920 --> 00:45:53,680
Speaker 5: result of COVID shutdowns. The ladies on the View somehow

817
00:45:53,719 --> 00:45:57,360
Speaker 5: have not read that those studies. They haven't really familiarized

818
00:45:57,400 --> 00:46:00,359
Speaker 5: themselves with it. So this was what we don't get

819
00:46:00,440 --> 00:46:03,399
Speaker 5: very often. Beff, some somehow have not read that. Yeah,

820
00:46:03,440 --> 00:46:06,200
Speaker 5: of course, of course have not read any study. But

821
00:46:06,280 --> 00:46:10,239
Speaker 5: my point on like it's it's somewhat understandable to me

822
00:46:10,760 --> 00:46:15,000
Speaker 5: that people who are busy might not have gone into

823
00:46:15,040 --> 00:46:18,600
Speaker 5: the nitty gritty of COVID studies. The ladies on the

824
00:46:18,719 --> 00:46:22,960
Speaker 5: view have huge production staffs that are able to provide

825
00:46:22,960 --> 00:46:24,120
Speaker 5: them with bebbies.

826
00:46:24,640 --> 00:46:27,040
Speaker 1: It's even easier Clay. And this is something that everybody,

827
00:46:27,440 --> 00:46:29,759
Speaker 1: and I don't want to divert us from the view club.

828
00:46:29,760 --> 00:46:32,840
Speaker 1: We're gonna get to one second. But just if what

829
00:46:33,000 --> 00:46:37,359
Speaker 1: all these people had said and did and made us

830
00:46:37,440 --> 00:46:42,840
Speaker 1: do was true, we would be hearing endless I told

831
00:46:42,880 --> 00:46:47,520
Speaker 1: you so from them about how they were right. Instead,

832
00:46:47,640 --> 00:46:51,759
Speaker 1: it has become so obvious that whether it was masks

833
00:46:52,480 --> 00:46:58,840
Speaker 1: or school closures or lockdowns or vaccine mandates, they were wrong.

834
00:46:59,320 --> 00:47:01,400
Speaker 1: That what are they do? What you hear in this

835
00:47:01,520 --> 00:47:04,480
Speaker 1: view clip, which is it was really a hard time.

836
00:47:05,000 --> 00:47:08,440
Speaker 1: People were making decisions to save lives. Yeah, and the

837
00:47:08,520 --> 00:47:13,359
Speaker 1: decisions they made stunk and were wrong across the board. Now,

838
00:47:13,360 --> 00:47:15,640
Speaker 1: would like to play this view clip? We should do it.

839
00:47:16,040 --> 00:47:17,120
Speaker 1: Let's play this clip.

840
00:47:17,200 --> 00:47:21,200
Speaker 5: This is doctor Phil yesterday talking about school closures with

841
00:47:21,320 --> 00:47:22,759
Speaker 5: the view cast.

842
00:47:22,560 --> 00:47:22,840
Speaker 1: Listen.

843
00:47:23,000 --> 00:47:26,280
Speaker 4: When they shut it down, they stopped the mandated reporters

844
00:47:26,280 --> 00:47:28,920
Speaker 4: from being able to see children that were being abused

845
00:47:28,960 --> 00:47:31,600
Speaker 4: and sexually molested, and in fact sent them home and

846
00:47:31,680 --> 00:47:34,640
Speaker 4: abandoned them to their abusers with no way.

847
00:47:34,520 --> 00:47:34,880
Speaker 1: To watch it.

848
00:47:34,920 --> 00:47:37,440
Speaker 6: So it's also, yeah, they were trying to save they

849
00:47:37,480 --> 00:47:39,960
Speaker 6: were trying to save kids' lives. Remember, we know a

850
00:47:40,000 --> 00:47:43,520
Speaker 6: lot of folks who died during this, so it wasn't people.

851
00:47:43,360 --> 00:47:44,680
Speaker 1: Weren't laying around each loan.

852
00:47:44,800 --> 00:47:47,880
Speaker 6: But well, you know what, we're lucky. Maybe we're lucky

853
00:47:47,920 --> 00:47:50,800
Speaker 6: they didn't because we kept them out of the places

854
00:47:50,840 --> 00:47:53,760
Speaker 6: that they could be sick, because no one wants believed

855
00:47:53,800 --> 00:47:54,560
Speaker 6: we had an issue.

856
00:47:54,600 --> 00:47:56,800
Speaker 3: Are you saying no school children died of COVID.

857
00:47:57,160 --> 00:48:00,680
Speaker 4: I'm saying it was the safest group. They were the

858
00:48:00,760 --> 00:48:05,480
Speaker 4: less vulnerable group, and they suffered and will suffer more

859
00:48:05,840 --> 00:48:08,759
Speaker 4: from the mismanagement of COVID than they will from the

860
00:48:08,840 --> 00:48:09,960
Speaker 4: exposure to COVID.

861
00:48:11,480 --> 00:48:15,600
Speaker 1: This is all also Anna Navarro, who's honestly an imbecile, truly.

862
00:48:16,280 --> 00:48:19,480
Speaker 1: Are you saying no children, Well, maybe I don't know

863
00:48:20,080 --> 00:48:22,080
Speaker 1: one or two in a country of three hundred and

864
00:48:22,120 --> 00:48:25,640
Speaker 1: thirty million people. Maybe not even proven by the way,

865
00:48:25,960 --> 00:48:29,000
Speaker 1: But this would be like saying, should we have banned

866
00:48:29,000 --> 00:48:33,760
Speaker 1: all refrigerators? Well, maybe one fell down on one person

867
00:48:33,800 --> 00:48:35,440
Speaker 1: and killed the person. Does that mean you get rid

868
00:48:35,480 --> 00:48:38,759
Speaker 1: of all refrigerators? You know it is so statistically rare

869
00:48:39,280 --> 00:48:42,880
Speaker 1: that to base any federal policy on it is completely insane.

870
00:48:43,239 --> 00:48:45,680
Speaker 1: And they did this to tens of millions of children

871
00:48:45,760 --> 00:48:48,120
Speaker 1: across the country. To point here, by the way, Clay

872
00:48:48,120 --> 00:48:49,879
Speaker 1: from our friend Carol Markuwitz, go thisen to the Carol

873
00:48:49,880 --> 00:48:52,880
Speaker 1: Markwitz podcast and the Clay and Buck Network. She tweeted

874
00:48:52,880 --> 00:48:54,719
Speaker 1: this out. You know what, the thing about the ladies

875
00:48:54,719 --> 00:48:56,840
Speaker 1: in the View is their kids all go to private school.

876
00:48:57,640 --> 00:49:00,719
Speaker 1: They offer all their talk about public schools, and the

877
00:49:00,760 --> 00:49:03,200
Speaker 1: public school teachers and unions who want to teach their

878
00:49:03,280 --> 00:49:06,680
Speaker 1: kids were in school. Their kids weren't punished by the

879
00:49:06,800 --> 00:49:09,000
Speaker 1: stupidity of Democrat ideas.

880
00:49:09,360 --> 00:49:13,319
Speaker 5: I loved doctor Phil disabusing them of that notion. We

881
00:49:13,440 --> 00:49:16,799
Speaker 5: actually cut it off too soon because the thing that

882
00:49:17,040 --> 00:49:20,720
Speaker 5: I loved the most about this clip was doctor Phil

883
00:49:20,800 --> 00:49:25,239
Speaker 5: got a round of applause from the few audience. I'm

884
00:49:25,239 --> 00:49:27,160
Speaker 5: not an expert on who is going to be in

885
00:49:27,200 --> 00:49:29,960
Speaker 5: the View audience, but Buck, I would say, it's overwhelmingly

886
00:49:30,080 --> 00:49:33,320
Speaker 5: moms and grandma's and they have kids in public school,

887
00:49:33,360 --> 00:49:38,200
Speaker 5: and they understood. They understand because to your exact point,

888
00:49:38,880 --> 00:49:42,400
Speaker 5: moms bore the brunt more than anybody I know. There

889
00:49:42,400 --> 00:49:45,280
Speaker 5: were dads, but moms more than anybody, bore the brunt

890
00:49:45,320 --> 00:49:48,840
Speaker 5: of remote schooling. You had to take care of your kids,

891
00:49:49,120 --> 00:49:51,600
Speaker 5: You had to get them logged in, you had to

892
00:49:51,640 --> 00:49:52,879
Speaker 5: see what was going on.

893
00:49:53,480 --> 00:49:55,640
Speaker 1: And that audience.

894
00:49:55,360 --> 00:49:59,360
Speaker 5: Cheering Doctor Phil on the View I actually found to

895
00:49:59,400 --> 00:50:03,240
Speaker 5: be very beneficial because usually, you know, when Ted Cruz

896
00:50:03,320 --> 00:50:06,640
Speaker 5: goes on, they boo him and they you know, there's

897
00:50:06,640 --> 00:50:10,480
Speaker 5: an uproarious response whenever he goes on and says anything.

898
00:50:10,480 --> 00:50:12,640
Speaker 1: This is dob f. It's like when Super Mario gets

899
00:50:12,640 --> 00:50:13,840
Speaker 1: a special mushroom or whatever.

900
00:50:14,160 --> 00:50:18,800
Speaker 5: But doctor Phil going on the view's audience, the views,

901
00:50:18,960 --> 00:50:23,000
Speaker 5: talking to the view audience and winning over their audience

902
00:50:23,680 --> 00:50:27,480
Speaker 5: like he did, I think is just really emblematic of

903
00:50:27,520 --> 00:50:30,600
Speaker 5: how much the world has changed in four years. And

904
00:50:30,640 --> 00:50:33,880
Speaker 5: you're right, Buck, if they had been right, we would

905
00:50:33,920 --> 00:50:36,560
Speaker 5: never hear the end of how the brilliant they all work.

906
00:50:36,560 --> 00:50:38,400
Speaker 1: It's all you have to know, all you have to know.

907
00:50:38,600 --> 00:50:40,879
Speaker 1: Just like with climate change, by the way, if their

908
00:50:40,920 --> 00:50:44,120
Speaker 1: predictions from ten years ago had been accurate, you know

909
00:50:44,160 --> 00:50:46,080
Speaker 1: what would happened every time they talked about climate change.

910
00:50:46,080 --> 00:50:47,680
Speaker 1: They would just run on a loop. We told you

911
00:50:47,719 --> 00:50:50,920
Speaker 1: this was going to happen. Instead, it's always well, in

912
00:50:50,960 --> 00:50:53,480
Speaker 1: ten years, we're sure this time what's going to happen.

913
00:50:54,280 --> 00:50:58,120
Speaker 1: It's a shell game. The it's three card Monty with

914
00:50:58,239 --> 00:51:01,600
Speaker 1: trillions of dollars and your freedom at stake. And the

915
00:51:01,640 --> 00:51:03,880
Speaker 1: same thing was true of COVID, obviously, And I just

916
00:51:03,960 --> 00:51:05,759
Speaker 1: I want everyone to know this. Whenever you have any

917
00:51:05,840 --> 00:51:07,759
Speaker 1: argument with any neighbor or anyone who you know had

918
00:51:07,760 --> 00:51:09,520
Speaker 1: sits at the dinner table with you and says, oh, well,

919
00:51:09,560 --> 00:51:12,279
Speaker 1: you know they were doing the best they can, It's like, no, no,

920
00:51:12,560 --> 00:51:15,120
Speaker 1: they were wrong. They got it all wrong. And the

921
00:51:15,160 --> 00:51:17,520
Speaker 1: way we know is that none of them now say,

922
00:51:17,960 --> 00:51:20,719
Speaker 1: none of them say we got this right. What they

923
00:51:20,760 --> 00:51:24,520
Speaker 1: say is it was really hard. It was a complicated time.

924
00:51:25,040 --> 00:51:27,640
Speaker 1: People were dying. I know people who died of COVID.

925
00:51:27,880 --> 00:51:29,279
Speaker 1: You know, you know the truth is for me by

926
00:51:29,600 --> 00:51:31,520
Speaker 1: I can't speak to you, Clay, you know, on the

927
00:51:31,560 --> 00:51:35,440
Speaker 1: personal side of this, I know one person who died

928
00:51:35,880 --> 00:51:40,560
Speaker 1: of COVID, one person, all right, and that person was

929
00:51:40,600 --> 00:51:45,920
Speaker 1: actually killed by the medical frenzy to put people on ventilators.

930
00:51:46,320 --> 00:51:49,040
Speaker 1: He was killed actually by a ventilator. I am very

931
00:51:49,040 --> 00:51:51,440
Speaker 1: confident he wasn't that old. I am very confident he

932
00:51:51,440 --> 00:51:54,400
Speaker 1: would have survived, and there are thousands of New Yorkers

933
00:51:54,520 --> 00:51:56,759
Speaker 1: who matter. Is the case about and everyone knows that

934
00:51:56,880 --> 00:51:59,160
Speaker 1: now and no one talks about that. But it wasn't

935
00:51:59,239 --> 00:52:01,600
Speaker 1: see but bring that up because it's not just oh,

936
00:52:01,640 --> 00:52:04,239
Speaker 1: it was difficult then had to make tough decisions. They

937
00:52:04,280 --> 00:52:06,640
Speaker 1: shouted down everyone and said they had the answers, and

938
00:52:06,680 --> 00:52:10,279
Speaker 1: they basically murdered people with malpractice in the process, and

939
00:52:10,320 --> 00:52:12,680
Speaker 1: no one will take accountability for it and no one

940
00:52:12,719 --> 00:52:15,680
Speaker 1: will apologize for it. And you're one hundred percent right

941
00:52:15,719 --> 00:52:19,040
Speaker 1: on all that in ten years. So we are sitting

942
00:52:19,040 --> 00:52:21,799
Speaker 1: now at twenty twenty four, I mean ten years from

943
00:52:21,840 --> 00:52:25,440
Speaker 1: twenty twenty, so by twenty thirty, I think if you

944
00:52:25,520 --> 00:52:28,600
Speaker 1: look at death and the average death rate, I think

945
00:52:28,640 --> 00:52:31,400
Speaker 1: you will almost not be able to tell COVID ever happened,

946
00:52:32,280 --> 00:52:35,239
Speaker 1: because the average over ten years is going to be

947
00:52:35,280 --> 00:52:38,560
Speaker 1: almost identical to what it was. I bet from twenty

948
00:52:38,640 --> 00:52:41,880
Speaker 1: ten to twenty twenty, age adjusted mortality over a ten

949
00:52:41,960 --> 00:52:44,200
Speaker 1: year period is going to look this is my theory,

950
00:52:44,600 --> 00:52:47,080
Speaker 1: no different from twenty twenty to twenty thirty than it

951
00:52:47,120 --> 00:52:49,960
Speaker 1: did twenty ten to twenty twenty. It will when you

952
00:52:50,160 --> 00:52:51,880
Speaker 1: if you were to really look at the data and

953
00:52:51,920 --> 00:52:54,879
Speaker 1: extricate it out and do an honest assessment of it,

954
00:52:55,000 --> 00:52:57,239
Speaker 1: the same way that the honest assessment of MASK efficacy

955
00:52:57,239 --> 00:53:00,959
Speaker 1: finds zero, not ten percent, not two percent sometimes maybe

956
00:53:01,080 --> 00:53:04,080
Speaker 1: kind of sort of masks did nothing zero full stop.

957
00:53:04,120 --> 00:53:06,399
Speaker 1: By the way, if you google masks right now, where

958
00:53:06,440 --> 00:53:08,279
Speaker 1: you go into Gemini, which we'll talk about later, and

959
00:53:08,320 --> 00:53:10,799
Speaker 1: say do masks work, they still say yes. They still

960
00:53:10,840 --> 00:53:13,000
Speaker 1: say yes. They're lying to you about that. But on

961
00:53:13,080 --> 00:53:16,799
Speaker 1: the mortality issue of COVID or mortality data, if you

962
00:53:16,840 --> 00:53:19,640
Speaker 1: were to take out died with COVID versus of COVID, yes,

963
00:53:20,040 --> 00:53:21,759
Speaker 1: I think at worse, what you would find is that

964
00:53:21,800 --> 00:53:24,560
Speaker 1: this was it was a bad It's different than the

965
00:53:24,560 --> 00:53:26,279
Speaker 1: flu in terms of the disease, I get that, But

966
00:53:26,520 --> 00:53:29,120
Speaker 1: it was effectively a very bad flu season. I think

967
00:53:29,160 --> 00:53:30,680
Speaker 1: that's right. And it killed a lie. You know, it

968
00:53:30,760 --> 00:53:33,400
Speaker 1: killed people who were immunocompromised and old, and it was

969
00:53:33,480 --> 00:53:35,960
Speaker 1: dangerous to them, and it was not really dangerous to

970
00:53:36,040 --> 00:53:38,160
Speaker 1: everybody else in a way that should have in any

971
00:53:38,239 --> 00:53:41,200
Speaker 1: way justified the things that they did, which was completely insane,

972
00:53:42,120 --> 00:53:44,320
Speaker 1: and all you have to know about their unwillingness to

973
00:53:44,360 --> 00:53:46,560
Speaker 1: really embrace the science or I should say. Another thing

974
00:53:46,600 --> 00:53:50,520
Speaker 1: you should know is one of the great medical scandals

975
00:53:50,640 --> 00:53:55,719
Speaker 1: of our time was the suppression of natural immunity. In

976
00:53:55,840 --> 00:53:58,600
Speaker 1: all of this, you got COVID. I got COVID, and

977
00:53:58,680 --> 00:54:00,920
Speaker 1: afterwards we still had to walk around with masks on

978
00:54:00,960 --> 00:54:02,640
Speaker 1: or pretend like we were rich. To everybody. That was

979
00:54:02,680 --> 00:54:05,759
Speaker 1: a lie. It was a lie, and they say, oh, well,

980
00:54:05,760 --> 00:54:08,520
Speaker 1: then there were variants, okay, but there were also variants

981
00:54:08,520 --> 00:54:10,920
Speaker 1: that the vaccines couldn't catch. So there was never a

982
00:54:10,920 --> 00:54:13,000
Speaker 1: point at which it should have been show me your

983
00:54:13,040 --> 00:54:15,759
Speaker 1: card or take the shot or else or whatever. The

984
00:54:15,800 --> 00:54:17,640
Speaker 1: whole thing they got everything wrong. But the ladies on

985
00:54:17,680 --> 00:54:22,240
Speaker 1: the view and ladies were just the fact that they.

986
00:54:22,120 --> 00:54:25,399
Speaker 5: Got confronted with that from doctor Philbuck and the fact

987
00:54:25,400 --> 00:54:28,440
Speaker 5: that their audience cheered it. I hope was a moment

988
00:54:28,520 --> 00:54:31,560
Speaker 5: where they will sit back and think, how are we

989
00:54:31,719 --> 00:54:32,759
Speaker 5: getting that?

990
00:54:33,040 --> 00:54:38,360
Speaker 1: Still? Four years later? So incredibly wrong what they say.

991
00:54:38,400 --> 00:54:42,280
Speaker 1: And this is all of your lib friends who won't

992
00:54:42,280 --> 00:54:45,160
Speaker 1: apologize who you know. I was told I couldn't go

993
00:54:45,200 --> 00:54:47,719
Speaker 1: to weddings. I was told that I wasn't welcome at

994
00:54:47,719 --> 00:54:49,520
Speaker 1: different events because I didn't want to go, you know,

995
00:54:49,560 --> 00:54:51,120
Speaker 1: I didn't want to deal with the masking, or I

996
00:54:51,120 --> 00:54:52,839
Speaker 1: didn't want to deal with the vaccine, whatever it was.

997
00:54:53,840 --> 00:54:56,040
Speaker 1: No one will apologize over that. Who did that? Really?

998
00:54:56,320 --> 00:55:00,200
Speaker 1: And it's because what they tell themselves now is okay,

999
00:55:00,239 --> 00:55:02,719
Speaker 1: so we weren't as right as we thought, but we

1000
00:55:02,800 --> 00:55:06,680
Speaker 1: tried our best. We did our best. Fauci led us

1001
00:55:06,719 --> 00:55:09,600
Speaker 1: the best way he knew how. And it's pathetic, right,

1002
00:55:10,000 --> 00:55:13,319
Speaker 1: pathetic Now it's turned into we tried. That's not what

1003
00:55:13,360 --> 00:55:15,360
Speaker 1: they were saying then, because if they had said, we

1004
00:55:15,440 --> 00:55:17,080
Speaker 1: don't know what we're trying, we would have had very

1005
00:55:17,080 --> 00:55:19,279
Speaker 1: different policies, no doubt.

1006
00:55:19,400 --> 00:55:21,000
Speaker 5: And for those of you out there who think this

1007
00:55:21,160 --> 00:55:25,000
Speaker 5: is gone, it's not. If they could the same twenty

1008
00:55:25,040 --> 00:55:29,120
Speaker 5: percent of people that are still wearing masks, still wearing masks,

1009
00:55:29,520 --> 00:55:31,800
Speaker 5: they would force you to wear them. In a heartbeat,

1010
00:55:32,360 --> 00:55:34,160
Speaker 5: they would. They'd love for you to put them back on.

1011
00:55:34,320 --> 00:55:36,080
Speaker 1: I saw that we're wearing a mask this morning, by

1012
00:55:36,120 --> 00:55:39,200
Speaker 1: the way, in Miami, into a store in Miami, wearing

1013
00:55:39,200 --> 00:55:39,600
Speaker 1: a mask.

1014
00:55:39,680 --> 00:55:43,680
Speaker 5: Yeah, I just I mean, these people have lost their

1015
00:55:44,040 --> 00:55:47,000
Speaker 5: I don't know that they're ever going to recover. There

1016
00:55:47,000 --> 00:55:51,120
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1017
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1021
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1022
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1023
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1024
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1025
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