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Speaker 1: Broadcasting live from the Abraham Lincoln Radio Studio the George

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Speaker 1: Washington Broadcast Center, Jack Armstrong and Joe Getty.

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Speaker 2: Arm Strong and Jetty and he.

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Speaker 3: Armstrong and Yetty.

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Speaker 4: Allergies are brutal apparently nationwide, more states with high allergy.

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Speaker 3: Alert than I've ever been at one time. Climate change

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Speaker 3: or who knows?

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Speaker 2: What?

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Speaker 3: Can we get? A giant national hepafilter? Is that possible?

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Speaker 3: To ask me about that?

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Speaker 1: Wow? And make Mexico pay for it? I don't know.

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Speaker 1: Something like that would be nice, yes, or just a yeah?

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Speaker 1: A gigantic series of fans on the border with the

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Speaker 1: filters to recirculate the air. Yeah, why not? So last

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Speaker 1: night on Special Report with Brett Bear, Brett sat down

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Speaker 1: and talked with gosh was it seven guys? Seven? Oh

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Speaker 1: my lord? With six or seven of the guys who

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Speaker 1: are heading up the DOGE efforts, including Elon Musk. Of course,

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Speaker 1: executive producer Hanson has done a fabulous job of getting

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Speaker 1: us many many highlights, many more than we could play

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Speaker 1: on air. Meeting time, Jack, I say, I want to

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Speaker 1: hear a couple from Elon Musk because the interview begins

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Speaker 1: with him. But i'd really, really like to highlight at

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Speaker 1: least a little bit from each of the guys because

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Speaker 1: to me, the great takeaway and Elon is a brilliant

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Speaker 1: guy and interesting, but between his overexposure and his halting

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Speaker 1: speaking style, and as a parent of an autistic kid,

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Speaker 1: I get it, and I'm used to it more or less,

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Speaker 1: but it can be distracting. And my big takeaway from

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Speaker 1: it was this is an amazing collection of brilliant people

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Speaker 1: who are a dead serious about doing what's right for

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Speaker 1: the American people, not within a thousand miles of the

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Speaker 1: haphazard monster that the mainstream media is portrayed. So what

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Speaker 1: do you think of a little touch on all the fellas?

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Speaker 3: Then why the Hitler salute?

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Speaker 1: Well, yeah, we were kicking around a picture on the

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Speaker 1: Private Well, Jeffrey Goldberg was probably on it. But the

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Speaker 1: private show thread last night of Musk waving with two hands,

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Speaker 1: we called it the double Hitler. So obviously we're dabbling

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Speaker 1: with Nazism here to even play it. But so here's

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Speaker 1: Brett Bear with Elon Musk talking about when they took

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Speaker 1: a look at the government books, what they found. We'll

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Speaker 1: start with fifty one Michael and.

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Speaker 5: Talk to all the guys here about the specifics. But

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Speaker 5: for you, what's the most astonishing thing you've found out

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Speaker 5: in this process?

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Speaker 6: The sheer amount of waste and ford in the government.

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Speaker 6: It is astonishing, It's mind blowing. Just we routinely encounter

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Speaker 6: wastes of a billion dollars or more casually. You know,

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Speaker 6: for example, like the simple survey that was literally ten

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Speaker 6: questions survey that you could do with survey monkey quashed

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Speaker 6: about ten thousand dollars. Was the government was being charged

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Speaker 6: almost a billion dollars for that for just the survey.

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Speaker 6: A billion dollars for a simple online survey do you

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Speaker 6: like the National Park? And then there pays me no

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Speaker 6: feedback loop for what will be done with that survey?

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Speaker 6: Sole say, we would just go to nothing. It's like

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Speaker 6: you're saying you tacking.

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Speaker 2: That's nice.

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Speaker 1: Yeah. And then to the criticism that they are making

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Speaker 1: mistakes and running rough shot over the federal bureaucracy fifty

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Speaker 1: three Michael.

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Speaker 5: There obviously are dose critics who are reading all kinds

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Speaker 5: of stuff. Obviously lawmakers on the other side of the

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Speaker 5: aisle are attacking you, and they characterize the approach is

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Speaker 5: this fire ready and then aim and.

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Speaker 3: How do you approach that. How do you respond to that.

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Speaker 2: Well, I do agree that we act.

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Speaker 6: We want to be careful in the cuts, so we

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Speaker 6: want to measure twice if not thrice, and cut once.

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Speaker 2: And actually that is our approach.

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Speaker 6: They may characterize it as shooting from the hip, but

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Speaker 6: it is anything at that which is not saying that

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Speaker 6: we don't make mistakes.

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Speaker 2: If we were to approach this with the.

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Speaker 6: Standard of making no mistakes at all, that would be

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Speaker 6: like saying someone in baseball's got a bat a thousand

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Speaker 6: as impossible. So when we do make mistakes, we correct

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Speaker 6: them quickly and we move on.

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Speaker 4: I think it's interesting that so the crowd that's angry

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Speaker 4: at DOGE, they don't get angry when they hear the

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Speaker 4: government spent a billion dollars on a ten thousand dollars survey.

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Speaker 4: And then it's not even for anything anyway. I mean,

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Speaker 4: that's all money that could be going to programs you

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Speaker 4: like that eventually won't happen because we'll be broke, or

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Speaker 4: you should be angry that they're taking your money at

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Speaker 4: all that you earned, not letting you and spending on that.

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Speaker 4: You have no anger about that, only about when they

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Speaker 4: get it wrong now and then before they can fix it.

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Speaker 1: I'm reminded of Thomas Sole's epic book of Conflict of Visions.

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Speaker 1: People have just gotten the message that in our tribe

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Speaker 1: we are anti this, so shout that it's evil and

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Speaker 1: they say, okay, I will. That's part of all the

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Speaker 1: rational thought that goes into it, and that's part of it.

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Speaker 4: I think there is the rational thought of there's endless

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Speaker 4: government money, or it's not my money, or I don't

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Speaker 4: pay taxes or whatever, that you just don't care about waste,

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Speaker 4: fraud and abuse.

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Speaker 3: I think true, a lot of people just don't care

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Speaker 3: about it.

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Speaker 1: And as I've said a million times, that's actually part

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Speaker 1: of the progressive playbook is to narrow the tax base

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Speaker 1: as much as possible so there aren't enough votes to

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Speaker 1: vote against the graft that you spread to your cronies. Anyway,

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Speaker 1: moving on from Elon Musk Brett now turns to Steve Davis,

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Speaker 1: and I should have jotted down all these guys credentials.

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Speaker 1: They touch on some of it, but he's the first

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Speaker 1: of the many, very very impressive, serious people who is

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Speaker 1: helping Elon head up the doge thing. Fifty four Michael.

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Speaker 5: Some people say this shouldn't take a rocket scientist, Steve Davis,

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Speaker 5: you are a rocket scientist.

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Speaker 2: It used to be yeah.

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Speaker 5: Now essentially you're the chief operating officer of dough day

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Speaker 5: to day operations.

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Speaker 7: Fair to say, yeah, part of part of the Dose team.

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Speaker 2: So how did you end up here?

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Speaker 3: What's the biggest challenge?

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Speaker 5: You see?

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Speaker 7: The reason I'm here, which is probably for many, is

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Speaker 7: that I think the goal is incredibly inspiring. I think

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Speaker 7: most of the taxpayers in the country would agree that

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Speaker 7: in order to have the country going bankrupt would be

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Speaker 7: a very bad thing, and therefore the country going not

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Speaker 7: bankrupt is a good thing that all of us are

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Speaker 7: willing to kind of put our lives on hold in

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Speaker 7: order to do. I think the thing that's special right

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Speaker 7: now is we actually believe there's a chance to succeed,

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Speaker 7: that there's an administration that's supportive and a great cabinet

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Speaker 7: and just a great group that will actually make success

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Speaker 7: a possible outcome. And I think that's given the inspiring

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Speaker 7: mission and given the non zero chance of success, it was.

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Speaker 1: Worth h Obviously the voice of a monster, right, and

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Speaker 1: one principle that hung over in a good way all

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Speaker 1: of the discussions that was repeated many times is we

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Speaker 1: need to be adults and recognize the country is going broke.

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Speaker 1: We need to get serious about this before the train

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Speaker 1: wreck occurs or the beloved social programs that everybody's screaming about,

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Speaker 1: even though they're not talking about touching them, really will

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Speaker 1: go away. The outcome you are screaming about will happen

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Speaker 1: unless we do this very very serious. Do you think

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Speaker 1: it's worth resetting the retirement mind? I think that's covered

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Speaker 1: pretty thoroughly. I was surprised they got into that the

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Speaker 1: way they did. Yeah, just a great story.

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Speaker 4: We played a whole bunch of clips on that several

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Speaker 4: weeks ago when Elon first started talking about it, that

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Speaker 4: they still do it paper like it's the fifties down

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Speaker 4: in a mine.

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Speaker 3: For all.

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Speaker 4: The retirement paperwork for government employees is just unbelievable.

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Speaker 1: Right, and they're trying to modernize that to make it

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Speaker 1: easier for federal employees to do everything they need to do,

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Speaker 1: including to retire. They mentioned you have to take a

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Speaker 1: seminar to teach you how to retire as a federal

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Speaker 1: government employee. Let's see, all right, let's skip ahead to

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Speaker 1: Arab Mogadasi, who is a software engineer as he explains

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Speaker 1: who's a major part of the effort. After a quick

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Speaker 4: And we're also in the drive to the playoffs for

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Speaker 1: Yep, basketball playoffs are a coming. That's when they actually

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Speaker 1: The coat is armstrong, Prize Picks run your game. So

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Speaker 1: the computer systems of the government are a terrible, sad

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Speaker 1: joke and far from irresponsible frat boys. The DOGE team

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Speaker 1: is taking a serious look about how to make the

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Speaker 1: government more responsive to us. Let's start with sixty Michael.

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Speaker 5: Parham Moganasi DOJE engineer go into these places, one of

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Speaker 5: the more than a dozen engineers. First people to go

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Speaker 5: into the agencies and view the computer data sets. Tell

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Speaker 5: me what you're finding, and for people who don't understand

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Speaker 5: how that process works, explain it for them.

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Speaker 8: Yeah, I'll say the first thing that got me really

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Speaker 8: excited about DOGE was learning basically the state of government computers.

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Speaker 8: By some estimates, government it costs about one hundred billion

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Speaker 8: dollars and it's funding systems that are over fifty years

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Speaker 8: old in the case of something like Social Security or

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Speaker 8: the IRS. So really critical systems are old, they cost

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Speaker 8: a lot of money to maintain, and they can be

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Speaker 8: the efforts to improve them are often very delayed. So

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Speaker 8: I thought, I'm a software engineer that that maybe can

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Speaker 8: make a difference here, and.

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Speaker 2: That's that's really what.

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Speaker 1: Inspired me at a high level.

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Speaker 4: That's going to be something when you come out of

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Speaker 4: the tech world where you're probably using the very latest,

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Speaker 4: greatest of its last week, to come into government and

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Speaker 4: realize you're using stuff that's fifty years old and figure

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Speaker 4: out what that even was.

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Speaker 1: Right, And here's another incredibly successful guy who answered the

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Speaker 1: call and said, yeah, you know what, we might be

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Speaker 1: able to actually do this for the American people. I'm in.

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Speaker 1: I'm going to give it a try. I like the

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Speaker 1: way the next part is framed sixty one sixty two

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Speaker 1: back to back. Please the first a montage of Democrats

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Speaker 1: with their messaging over Doge.

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Speaker 9: It's absurd that Elon Musk is trying to eliminate billions

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Speaker 9: of dollars from Social Security.

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Speaker 10: Elon Musk and President Trump have set their sites on

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Speaker 10: cutting Social Security.

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Speaker 11: Their goal is clear, destroy social Security from within.

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Speaker 5: You're in the building, I mean, you're in the computers.

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Speaker 2: What's happening there?

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Speaker 1: What are you doing?

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Speaker 8: Yeah, it doesn't line up with my experience on the ground.

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Speaker 2: And I'll say the two.

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Speaker 8: Improvements that we're trying to make to Social Security are

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Speaker 8: helping people that legitimately get benefits protect them from fraud

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Speaker 8: that they experience every day on a routine basis, and

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Speaker 8: also make the experience better.

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Speaker 3: And I'll give.

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Speaker 8: You one example is at Social Security. One of the

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Speaker 8: first things we learned is that they get phone calls

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Speaker 8: every day of people trying to change direct positive information.

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Speaker 8: So when you want to change your bank account, you

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Speaker 8: can call Social Security. We learned forty percent of the

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Speaker 8: phone calls that they get are from fraudsters.

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Speaker 10: That's right, almost half.

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Speaker 2: Yes, And they steal people's social security. Is what happens

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Speaker 2: is they call in, they say they claim to be

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Speaker 2: a retiree.

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Speaker 6: Then they and they convinced the post the Social Security

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Speaker 6: posts on the phone to change where the money is flowing,

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Speaker 6: it actually goes to some fraudster. Is this happening all

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Speaker 6: day every day and then and then somebody doesn't receive

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Speaker 6: their social security is because of all the fraud loopholes

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Speaker 6: in the social security system.

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Speaker 3: They're trying to destroy social Security from within.

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Speaker 1: And then Musk makes the point, we're trying to make

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Speaker 1: sure people get more money, not less.

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Speaker 3: Not politics is awful.

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Speaker 1: The appalling dishonesty is problem number one. Secondly, standing in

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Speaker 1: the way of actual improvement is a second evil, unforgivable.

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Speaker 4: Yeah, we got more of this and other stuff too.

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Speaker 4: But man, how much of America had heard this take

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Speaker 4: on Doge. Not very much, Not very many people stay here.

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Speaker 4: We got a text from somebody listening to this stuff,

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Speaker 4: the Doge stuff about the computers being out of date,

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Speaker 4: and he used to work in that world, and he

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Speaker 4: said a lot of it was they have this stupid

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Speaker 4: requirement where the new system has to integrate with the

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Speaker 4: old system so that end users don't notice a difference

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Speaker 4: during transitions, which means you have to hold on to

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Speaker 4: all the stuff from the old system for the new system.

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Speaker 4: And it just doesn't work in any way to try to,

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Speaker 4: you know, move forward with new technology, so you just

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Speaker 4: end up sticking with the old stuff, sometimes fifty years.

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Speaker 3: Down the line apparently, if.

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Speaker 1: You're just tuning in. Brettbair did a fabulous series of

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Speaker 1: interviews with the leaders of the Doge effort last night,

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Speaker 1: including Brad Smith, who is a health care entrepreneur and

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Speaker 1: is working on the Department of Health and Human Services stuff.

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Speaker 1: You may have heard in the various lefty media that

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Speaker 1: they're trying to gut scientific research and causing damage to

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Speaker 1: our elite. You know universities blah blah blah. Here's Brad

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Speaker 1: Smith talking about their efforts sixty five Michael Brett.

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Speaker 5: Smith working at HHS, And obviously another element is Medicare

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Speaker 5: and Medicaid NIH.

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Speaker 10: What do you find it?

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Speaker 12: Yeah, Well, I'd say there's a couple of things we're

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Speaker 12: really committed to in our work at AHHS. Number one,

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Speaker 12: making sure we continue to have the best biomedical research

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Speaker 12: in the world. And number two making sure which President

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Speaker 12: Trump has said over and over again, that we one

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Speaker 12: protect Medicare and Medicaid. But there's a lot of opportunity.

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Speaker 12: So if I take NIH as an example today, if

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Speaker 12: you're a NIH researcher and you get one hundred dollars

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Speaker 12: grant at your university today, you get to spend sixty

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Speaker 12: of that and your university spends forty of that. The

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Speaker 12: policy that we're proposing to make is that you get

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Speaker 12: to spend eighty five of that and your university spends fifteen.

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Speaker 12: So that's more money going directly to the scientists who

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Speaker 12: are discovering new cures. Another example at NIH is today

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Speaker 12: they have twenty seven different centers. They got created over

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Speaker 12: time by Congress, and they're typically by disease state or

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Speaker 12: body system. There's seven hundred different IT systems today at NIH.

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Speaker 5: Seven hundred different ITS software systems.

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Speaker 2: They can't speak to each other, so they don't talk

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Speaker 2: to them.

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Speaker 12: They have twenty seven different CIOs. And so when you

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Speaker 12: think about making great medical discoveries, you have to connect

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Speaker 12: the data.

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Speaker 8: Time.

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Speaker 5: Yeah, time, twenty seven different chief information officers correct, correct,

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Speaker 5: and most.

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Speaker 2: Of your non technical. So there's a lot there.

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Speaker 12: There's a lot of opportunity. It will make science better,

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Speaker 12: not yours.

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Speaker 1: No, No, they're derailing important research. This is Elon is

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Speaker 1: a Nazi. They need to be stopped.

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Speaker 4: I live in a university town and a lot of

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Speaker 4: people have been really upset about this aspect of it.

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Speaker 4: And I mean just like sad and scared for America

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Speaker 4: And how are we going to weather the next three years?

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Speaker 3: Well, how about this, how about.

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Speaker 4: Make it even slightly more efficient and you can have

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Speaker 4: more money to use for your research.

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Speaker 1: Yeah, let's squeeze in sixty six. Michael, you're quite right.

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Speaker 6: Yes, when I say that our job is tech support,

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Speaker 6: I really mean it.

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Speaker 2: Yeah, we have to fix the computers.

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Speaker 6: If the computers can't talk to each other, you can't

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Speaker 6: get research done. If the computers can't stay online, people won't.

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Speaker 2: Receive as social security.

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Speaker 6: So what we have here are a bunch of failing

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Speaker 6: computer systems that are preventing people from receiving their benefits,

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Speaker 6: that are preventing people from preventing research from happening, that

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Speaker 6: are extremely vulnerable to fraud.

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Speaker 2: And we're fixing it.

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Speaker 5: And does that include AI does that include kind of

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Speaker 5: changing the system overall? That's what I guess what people

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Speaker 5: are afraid of is they don't know what this is

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Speaker 5: all looking like and is it going to affect me

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Speaker 5: in the long term.

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Speaker 6: It's going to affect them, It's going to affect people

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Speaker 6: very positively. So the changes that we're doing here will

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Speaker 6: ensure the solvency of the American Government, of the American

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Speaker 6: of the United States of America. This is what we're

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Speaker 6: trying to do, is ensure that people do receive their

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Speaker 6: benefits in the future. And you can all receive your

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Speaker 6: benefits if the country is operating in a healthy and

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Speaker 6: competent way.

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Speaker 4: I like elon always bringing it back to that, because

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Speaker 4: that's what drives the whole thing. We're going to become insolvent,

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Speaker 4: We're going to have no money we're not going to.

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Speaker 3: Be able to do anything if we don't change it.

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Speaker 1: Course right right next, we'd like to feature Anthony Armstrong,

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Speaker 1: who's a banking giant who's trying to get a hold

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Speaker 1: of federal personnel and duplicated efforts and redundancy and waste

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Speaker 1: in that way, another very serious person doing serious work

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Speaker 1: for you, not against you.

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Speaker 3: Yeah, so that's on the way.

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Speaker 4: If you missed a segment at the podcast Armstrong and

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Speaker 4: Getty on demand, but stick around Armstrong and Getty.

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Speaker 2: But it is.

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Speaker 13: Very important to recognize that that the people who work

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Speaker 13: in government who are working on health.

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Speaker 3: Are dedicated public servants.

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Speaker 13: There are neighbors, there are friends, There are people in

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Speaker 13: our family who are committed to improving the lives of

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Speaker 13: people across our country. A lot of them are going

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Speaker 13: to be losing their jobs and we're all going to

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Speaker 13: suffer because of it.

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Speaker 1: That's CNN had this doctor on who is a former

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Speaker 1: CDC staffer explaining how cuts and restructuring like Doge is doing.

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Speaker 1: It's just a terrible idea. We must not improve anything

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Speaker 1: because there's a huge human cost.

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Speaker 4: Welling back to the thing I've been complaining about for

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Speaker 4: a long time, that the idea of somebody losing their

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Speaker 4: job in government is just something that can't happen.

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Speaker 1: Well, these are our friends, Jack, these are neighbors. These

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Speaker 1: are nice people.

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Speaker 4: So before we get back to more Elon Doge stuff

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Speaker 4: that is so interesting and not being heard any were

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Speaker 4: in America. You know the doctor who tried to push

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Speaker 4: his wife off the cliff and killer. The latest is

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Speaker 4: he tried to hit her in the head with a

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Speaker 4: rock ten times an injector with syringes. Oh so more

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Speaker 4: details to come on that it was definitely premeditated.

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Speaker 1: She money insanity. So the interesting part, well, one of

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Speaker 1: the interesting parts of Brett Bear's interview with a bunch

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Speaker 1: of Doge leaders last night was that it wasn't just

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Speaker 1: Elon Musk, who's a lovely fellow and brilliant, but it

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Speaker 1: was the group of extremely smart, capable, accomplished people who

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Speaker 1: had been assembled who are working as hard as they

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Speaker 1: can on improving the federal government how it functions and

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Speaker 1: it's you know, it's benefits for American taxpayers. Having been

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Speaker 1: portrayed is as this loose band of frat boy lunatics

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Speaker 1: in most of the media, these are dead serious people.

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Speaker 1: For instance, Anthony Armstrong, Morgan Stanley Banker. He is working

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Speaker 1: for DOJE at the Office of Personnel Management, trying to

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Speaker 1: modernize and make more efficient that huge part of the

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Speaker 1: federal government. Clips sixty seven.

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Speaker 5: Michael Anthony Armstrong, DOZE, Office of Personnel Management.

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Speaker 10: You're Morgan Stanley Banker, M.

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Speaker 5: And a guy you know money, And this is a

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Speaker 5: lot of money slashing around.

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Speaker 14: There's a lot of money slashing around. It's a lot

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Speaker 14: of money slashing out the door. And if you look

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Speaker 14: at the federal government in the way the workforce works,

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Speaker 14: it's really a one way ratchet over decades.

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Speaker 10: So it's all going up. It's only going up. You

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Speaker 10: never you never take it away.

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Speaker 14: So that leads you with duplicative functions, It leaves you

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Speaker 14: with overstaffing, and it leaves you with functions in the

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Speaker 14: wrong places. So a couple of examples duplicative functions Brad

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Speaker 14: mentioned twenty seven CIOs. If you had kept going with Brady,

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Speaker 14: probably even talk about the communications office.

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Speaker 10: I think you've got forty forty distinct.

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Speaker 14: Communications offices in HIHS, right, wow forty yeah, yeah, And

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Speaker 14: that's not unusual, by the way, multiple offices like another

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Speaker 14: a healthy wow.

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Speaker 4: If you had three, you'd think you need three different

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Speaker 4: communications offices for one agency.

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Speaker 1: No, forty Wow, it's a one way ratchet. It just grows.

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Speaker 1: Next to Michael, this.

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Speaker 10: Is not about the employees there.

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Speaker 14: There's been many, many hard working, well meeting people who

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Speaker 14: took these jobs. These jobs were out there, they applied

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Speaker 14: for them, they took them.

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Speaker 10: They're doing what's there. It's just that they're.

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Speaker 14: Duplicating the effort of forty offices. So you've got that,

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Speaker 14: you've got overstaffing. A good example of overstaffing would be

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Speaker 14: the IRS has got fourteen hundred people who are dedicated

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Speaker 14: to provisioning laptops and cell phones. So if you join

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Speaker 14: the RS, you get a laptop and a cell phone.

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Speaker 14: You're provisioned. So if each of those IRS officers or

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Speaker 14: employees provisioned two employees per day, you could provision the

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Speaker 14: entire IRS in a little more than a month, so

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Speaker 14: twelve times a year.

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Speaker 2: You can read this.

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Speaker 6: Why would you have fourteen hundred people whose only job

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Speaker 6: it is to give out a laptop on the phone.

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Speaker 10: Right, The whole IRS could be hand once on a month.

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Speaker 10: So that doesn't make any sense.

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Speaker 14: And President trump'son very clear it's scalpel, not hatchet, and

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Speaker 14: that's the way it's getting done.

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Speaker 1: And of course that's all being portrayed as you will

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Speaker 1: not be able to get the irs to answer the phone,

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Speaker 1: which they never have, or get good tax advice from

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Speaker 1: you never have, and these suedus are trying to get

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Speaker 1: to those outcomes. Anyway. One more fell at a feature.

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Speaker 1: This is Tom Krause, who is the CEO of the

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Speaker 1: Cloud Software Group. He is working at the Treasury Department.

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Speaker 1: We'll start with seventy Michael.

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Speaker 5: Tom Crass working at Treasury, you are having access to

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Speaker 5: the payment system oversees all the outgoing payments. Essentially those

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Speaker 5: payments were going places we didn't know where they were going, right, Yeah.

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Speaker 3: Unfortunately that's the case right.

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Speaker 9: As an XCFO of a big public tech company. Really,

445
00:22:54,680 --> 00:22:58,199
Speaker 9: what we're doing is we're applying public company standards to

446
00:22:58,240 --> 00:22:59,000
Speaker 9: the federal government.

447
00:22:59,560 --> 00:23:00,159
Speaker 1: And it is.

448
00:23:00,080 --> 00:23:05,280
Speaker 9: Alarming how the financial operations and financial management is set

449
00:23:05,359 --> 00:23:05,840
Speaker 9: up today.

450
00:23:06,840 --> 00:23:10,639
Speaker 1: Michael, let's continue on with this frat boy doge boy

451
00:23:10,840 --> 00:23:11,400
Speaker 1: loose camp.

452
00:23:12,440 --> 00:23:16,359
Speaker 9: There is actually really only one bank account that's used

453
00:23:16,359 --> 00:23:20,400
Speaker 9: to disburse all monies that go out of the federal government.

454
00:23:20,040 --> 00:23:22,520
Speaker 2: Time about one blank account it's a big one. It's

455
00:23:22,520 --> 00:23:23,440
Speaker 2: a it's a big one.

456
00:23:23,440 --> 00:23:24,000
Speaker 1: It's a big one.

457
00:23:24,640 --> 00:23:26,080
Speaker 9: A couple of weeks ago, I had eight hundred million

458
00:23:26,119 --> 00:23:29,439
Speaker 9: dollars in it. But it's the treasury gedital account. So

459
00:23:30,160 --> 00:23:32,399
Speaker 9: when you hear, you know, some of my colleagues here

460
00:23:32,400 --> 00:23:34,840
Speaker 9: what they're talking about in terms of the fraud, you

461
00:23:34,920 --> 00:23:38,359
Speaker 9: have to ask, well, why is this allowed to happen

462
00:23:38,520 --> 00:23:41,880
Speaker 9: at a financial level. Well, it's actually quite simple but alarming.

463
00:23:42,840 --> 00:23:45,280
Speaker 9: The Treasury up until now, and thanks to President Trump,

464
00:23:45,920 --> 00:23:48,120
Speaker 9: we're fixing this. In fact, there's an executive order that

465
00:23:48,200 --> 00:23:51,240
Speaker 9: he just signed the other day which is protecting America's

466
00:23:51,240 --> 00:23:54,040
Speaker 9: bank account because it really is the taxpayer's money, you know.

467
00:23:54,080 --> 00:23:55,320
Speaker 1: One, we're changing the culture.

468
00:23:55,400 --> 00:23:59,840
Speaker 9: The culture is been not a lot of caring and

469
00:24:00,240 --> 00:24:02,960
Speaker 9: not a lot of commitment to doing what's right. Relative

470
00:24:02,960 --> 00:24:06,199
Speaker 9: to financial operations. There's a five hundred million dollars a

471
00:24:06,200 --> 00:24:08,520
Speaker 9: fraud every year. There's one hundreds of billion dollars of

472
00:24:08,520 --> 00:24:12,680
Speaker 9: improper payments, and we can't pass it on it. The

473
00:24:13,320 --> 00:24:16,479
Speaker 9: Consolidated Financial Report is produced by Treasury, and we cannot

474
00:24:16,480 --> 00:24:16,879
Speaker 9: pass it on.

475
00:24:16,960 --> 00:24:19,560
Speaker 1: We have material weaknesses. What that means is.

476
00:24:19,520 --> 00:24:22,080
Speaker 9: That if I was a public company, CFO, I would

477
00:24:22,080 --> 00:24:25,719
Speaker 9: effectively be removed. I couldn't file financial statements, I couldn't

478
00:24:25,720 --> 00:24:26,440
Speaker 9: issue securities.

479
00:24:26,480 --> 00:24:29,200
Speaker 2: Such a question can't pass it on right, the federal

480
00:24:29,240 --> 00:24:31,000
Speaker 2: government cannot pass it in ordered.

481
00:24:34,400 --> 00:24:36,800
Speaker 1: And you know one more. He makes a great point here.

482
00:24:37,200 --> 00:24:40,159
Speaker 9: We're serving five hundred and eighty plus agencies, and up

483
00:24:40,200 --> 00:24:44,359
Speaker 9: until very recently, effectively they could say make the payment

484
00:24:44,400 --> 00:24:46,480
Speaker 9: and Treasury just sent it out as fast as possible,

485
00:24:47,280 --> 00:24:50,840
Speaker 9: no verification. And so what we're doing is what any

486
00:24:50,960 --> 00:24:53,480
Speaker 9: household would do. But imagine you're a household. You have

487
00:24:53,480 --> 00:24:56,679
Speaker 9: a bank account. Everyone has an ATM card connect to

488
00:24:56,680 --> 00:24:59,280
Speaker 9: that account, everyone has a check book that account. It's

489
00:24:59,280 --> 00:25:01,840
Speaker 9: not just your children, it's not just your parents at

490
00:25:01,840 --> 00:25:04,160
Speaker 9: you're in LASS, it's your extended family, and they all

491
00:25:04,200 --> 00:25:07,320
Speaker 9: can go to the account and disperse funds, no questions asked,

492
00:25:07,359 --> 00:25:09,639
Speaker 9: no justification, no verification.

493
00:25:09,920 --> 00:25:12,200
Speaker 3: Yeah, it's not surprising to me. It's horrifying.

494
00:25:12,240 --> 00:25:14,399
Speaker 1: But I missed the part where they admitted that they're

495
00:25:14,520 --> 00:25:17,280
Speaker 1: just trying to slap Social Security benefits out of the

496
00:25:17,280 --> 00:25:20,040
Speaker 1: mouth of a ninety year old woman who's starving and blind.

497
00:25:20,640 --> 00:25:23,200
Speaker 1: They didn't get to that part, I guess. And then

498
00:25:23,280 --> 00:25:26,000
Speaker 1: finally to put a cap on it bear wrapping up

499
00:25:26,240 --> 00:25:28,320
Speaker 1: ret bear with Elon Musk.

500
00:25:29,480 --> 00:25:32,320
Speaker 5: We didn't talk about any plans to approach cuts at

501
00:25:32,320 --> 00:25:32,960
Speaker 5: the Pentagon.

502
00:25:33,440 --> 00:25:34,159
Speaker 3: You're in there.

503
00:25:34,560 --> 00:25:36,640
Speaker 6: The Pentagon has not passed the orders in a very

504
00:25:36,640 --> 00:25:40,560
Speaker 6: long time. I mean, as crazy as it sounds, they

505
00:25:40,560 --> 00:25:43,960
Speaker 6: will lose twenty thirty billion dollars a year and they

506
00:25:44,000 --> 00:25:45,960
Speaker 6: don't know where They literally don't know where it went.

507
00:25:48,320 --> 00:25:50,359
Speaker 6: I mean, Senator Collins was telling me about how she

508
00:25:51,560 --> 00:25:55,040
Speaker 6: gave the Navy twelve billion dollars for extra submarines, got

509
00:25:55,160 --> 00:25:58,960
Speaker 6: zero extra submarines, and then when she held a hearing said,

510
00:25:59,000 --> 00:26:00,919
Speaker 6: web the twelve billion dollars they didn't know.

511
00:26:04,960 --> 00:26:10,280
Speaker 1: We have howled for years about the idiotic, gigantic theft

512
00:26:10,480 --> 00:26:14,440
Speaker 1: that is the bullet train in California, and the other

513
00:26:15,080 --> 00:26:19,919
Speaker 1: of the twin towers to government squandering taxpayer money is

514
00:26:19,960 --> 00:26:23,679
Speaker 1: the homeless programs in kel Unicornia, billions and billions and

515
00:26:23,680 --> 00:26:26,480
Speaker 1: billions of dollars given out. And we all found out

516
00:26:26,520 --> 00:26:29,200
Speaker 1: last year that not only do they not know if

517
00:26:29,240 --> 00:26:31,720
Speaker 1: any of them have borne any fruit, have been successful,

518
00:26:31,840 --> 00:26:33,919
Speaker 1: they don't even have a means to ask the question.

519
00:26:34,840 --> 00:26:37,560
Speaker 1: And whether it was that little screed about the Pentagon

520
00:26:37,800 --> 00:26:40,760
Speaker 1: or Tyler Hassen, who don't have time to play that tape.

521
00:26:41,480 --> 00:26:43,719
Speaker 1: He's working at the Department of the Interior. They were

522
00:26:43,760 --> 00:26:47,720
Speaker 1: talking about how they have many, many, many programs that

523
00:26:47,760 --> 00:26:51,639
Speaker 1: they are now looking into auditing and realizing nobody knows

524
00:26:51,880 --> 00:26:54,639
Speaker 1: who signed this contract, where the money's going. We're not

525
00:26:54,680 --> 00:26:57,600
Speaker 1: getting anything out of it, but the checks keep getting

526
00:26:57,640 --> 00:27:00,639
Speaker 1: written month after month, year after year. Even so nobody

527
00:27:00,640 --> 00:27:04,560
Speaker 1: has any idea what this is. It's just shocking. And

528
00:27:04,600 --> 00:27:07,840
Speaker 1: again the effort to rain this in is being portrayed

529
00:27:08,320 --> 00:27:14,120
Speaker 1: as the stormtroopers marching across Poland slaughtering the innocent by

530
00:27:14,359 --> 00:27:18,000
Speaker 1: you know, Chuck Schumer and Hakim Jeffreys and aoc Well.

531
00:27:18,000 --> 00:27:20,440
Speaker 4: And half the country doesn't pay federal taxes. You can't

532
00:27:20,480 --> 00:27:21,840
Speaker 4: count on that half to be too mad.

533
00:27:23,119 --> 00:27:23,720
Speaker 2: It's true.

534
00:27:25,160 --> 00:27:26,280
Speaker 3: That's really frustrating.

535
00:27:27,920 --> 00:27:30,919
Speaker 4: Uh, you know, different topic. It's it's interesting to me

536
00:27:31,119 --> 00:27:36,840
Speaker 4: for some reason. It's popping into my head. I can't

537
00:27:36,840 --> 00:27:39,439
Speaker 4: imagine what Elon's work day is. I've thought about this

538
00:27:39,520 --> 00:27:43,760
Speaker 4: many times. But people always want to.

539
00:27:43,760 --> 00:27:44,359
Speaker 3: Win the lottery.

540
00:27:44,400 --> 00:27:46,560
Speaker 4: You know, the lottery gets up to a billion dollars

541
00:27:46,640 --> 00:27:48,479
Speaker 4: or whatever, and it makes national news and people are

542
00:27:48,480 --> 00:27:50,720
Speaker 4: buying tickets and everything like that, and everybody who wants

543
00:27:50,760 --> 00:27:53,520
Speaker 4: to win most everybody hear about who wants to win

544
00:27:53,560 --> 00:27:55,320
Speaker 4: the lottery. It's just and so they can live this

545
00:27:55,400 --> 00:27:59,120
Speaker 4: incredible life of pleasure. And it's like, you know which

546
00:27:59,240 --> 00:28:02,800
Speaker 4: yacht which, how switch car? You know how much pleasure

547
00:28:02,840 --> 00:28:04,840
Speaker 4: can you get free? Billain does, Yes, that is my dream.

548
00:28:04,960 --> 00:28:06,720
Speaker 4: Go on, and then you got all these guys here

549
00:28:06,760 --> 00:28:08,680
Speaker 4: Elon at the head of them who've got that kind

550
00:28:08,720 --> 00:28:10,920
Speaker 4: of money, and they're doing the exact opposite.

551
00:28:11,000 --> 00:28:12,640
Speaker 3: They're working. They're busting their ass.

552
00:28:12,440 --> 00:28:16,960
Speaker 4: All day long with mind numbing, frustrating, possibly dead end

553
00:28:17,080 --> 00:28:21,800
Speaker 4: work because they that's what they do. They care about

554
00:28:21,840 --> 00:28:25,199
Speaker 4: their country. They just they like working. It's interesting, an

555
00:28:25,320 --> 00:28:28,760
Speaker 4: enormous challenge. Yeah, it's interesting, and that's why they have money,

556
00:28:28,800 --> 00:28:31,280
Speaker 4: because they're built that way to have earned the money

557
00:28:31,280 --> 00:28:33,040
Speaker 4: in the first place, as opposed to so many people

558
00:28:33,040 --> 00:28:34,560
Speaker 4: who you know, when they think about having that kind

559
00:28:34,560 --> 00:28:37,160
Speaker 4: of money, it's oh, man, I'd get up at noon,

560
00:28:37,359 --> 00:28:40,000
Speaker 4: I'd go to my yacht, I'd have a ferrari. And

561
00:28:40,040 --> 00:28:41,880
Speaker 4: that's not what these guys are thinking. I just find

562
00:28:41,880 --> 00:28:43,360
Speaker 4: that interesting. The way they're good at.

563
00:28:43,280 --> 00:28:45,200
Speaker 1: The golf course. Before I went to my yacht. But anyway,

564
00:28:45,360 --> 00:28:49,000
Speaker 1: I don't mean to quibble. I've got it right day, Monday, Tuesday,

565
00:28:49,200 --> 00:28:54,440
Speaker 1: Wednesday and so on. Yeah, yeah, well, there you have it.

566
00:28:54,600 --> 00:28:59,560
Speaker 1: I would love to see somehow elon and more particularly

567
00:28:59,640 --> 00:29:06,680
Speaker 1: it's Eve Davis, Joe Jibeiah Brad Smith, Anthony Armstrong, Aaron Moga,

568
00:29:06,720 --> 00:29:12,080
Speaker 1: Don Dasi Moganasi. I would love to have them get

569
00:29:12,120 --> 00:29:14,880
Speaker 1: out and explain this, but they will not be welcomed

570
00:29:14,960 --> 00:29:19,720
Speaker 1: at most media outlets because it doesn't go with the

571
00:29:19,840 --> 00:29:21,280
Speaker 1: narrative of their tribe.

572
00:29:21,920 --> 00:29:25,360
Speaker 3: Now, you combine the left's love of.

573
00:29:26,880 --> 00:29:29,640
Speaker 4: Big government and government workers and all that sort of

574
00:29:29,640 --> 00:29:31,880
Speaker 4: stuff with just hatred of Trump, Trump's sport, you got

575
00:29:31,920 --> 00:29:33,320
Speaker 4: to be against it. We know all that how the

576
00:29:33,320 --> 00:29:35,239
Speaker 4: whole thing works. So it's just yeah, it's tough. It's

577
00:29:35,240 --> 00:29:36,600
Speaker 4: stuf sletting well.

578
00:29:36,640 --> 00:29:39,440
Speaker 1: And you need to remember always that a big part

579
00:29:39,480 --> 00:29:44,480
Speaker 1: of the patchwork that is the Democrat coalition is government employees,

580
00:29:45,440 --> 00:29:48,640
Speaker 1: and they are It's a fore alarm fire at the

581
00:29:48,640 --> 00:29:52,840
Speaker 1: government employee unions right now because if you have one

582
00:29:52,920 --> 00:29:55,760
Speaker 1: thousand workers, three hundred and forty three of whom are

583
00:29:55,800 --> 00:30:00,200
Speaker 1: completely redundant, unnecessary, and taxpayer money is being squandered on them. Well,

584
00:30:00,240 --> 00:30:02,520
Speaker 1: losing those three hundred and forty three is just purely

585
00:30:03,720 --> 00:30:08,440
Speaker 1: a loss to the government unions. They despise the idea

586
00:30:09,080 --> 00:30:12,680
Speaker 1: of making government more efficient for tax payers. And so

587
00:30:12,960 --> 00:30:15,520
Speaker 1: why do you have a quote unquote civil rights leader

588
00:30:15,600 --> 00:30:21,000
Speaker 1: yelling about this, or up with Palestine person yelling about this. Well,

589
00:30:21,040 --> 00:30:27,160
Speaker 1: it's that whole intersectionality, the NATO of grievances. You're all

590
00:30:27,200 --> 00:30:29,720
Speaker 1: together in this. So yeah, okay, when it comes time

591
00:30:29,760 --> 00:30:32,080
Speaker 1: to yell for us, you're gonna yell for us, rightee

592
00:30:32,160 --> 00:30:34,280
Speaker 1: government employees, and they say, yeah, of course we will,

593
00:30:34,320 --> 00:30:36,600
Speaker 1: So okay. So everybody on the left side of the

594
00:30:36,600 --> 00:30:40,840
Speaker 1: aisle acts like making the government better is an unspeakable

595
00:30:40,880 --> 00:30:45,479
Speaker 1: horror at the cost of the of the American people.

596
00:30:45,920 --> 00:30:48,800
Speaker 1: It's all born by the American people. It's obscene, end

597
00:30:48,840 --> 00:30:49,600
Speaker 1: of screed.

598
00:30:50,640 --> 00:30:53,360
Speaker 4: So I got the latest details on that job doctor

599
00:30:53,400 --> 00:30:55,240
Speaker 4: who luckily was arrested to is trying to push his

600
00:30:55,280 --> 00:30:57,520
Speaker 4: wife off the cliff. Also one of the worst New

601
00:30:57,600 --> 00:31:01,200
Speaker 4: York Post headlines I've ever seen, certainly not for the kids,

602
00:31:01,640 --> 00:31:04,520
Speaker 4: among certainly among other things.

603
00:31:04,560 --> 00:31:08,960
Speaker 3: On the way stay here.

604
00:31:09,080 --> 00:31:11,920
Speaker 11: The Dodgers got to jump on everybody. They started the

605
00:31:11,920 --> 00:31:13,880
Speaker 11: season last week at a two game sweep of the

606
00:31:13,960 --> 00:31:17,120
Speaker 11: Cubs in Tokyo. That's how loaded the Dodgers are this year.

607
00:31:17,240 --> 00:31:20,320
Speaker 11: On opening date, they're already two games ahead of everyone else,

608
00:31:20,960 --> 00:31:24,560
Speaker 11: and they're only spending three hundred and ninety eight point

609
00:31:24,640 --> 00:31:27,360
Speaker 11: two million dollars this year to do it, so they

610
00:31:27,360 --> 00:31:30,480
Speaker 11: don't even need to steal bases, they just buy them from.

611
00:31:30,320 --> 00:31:35,560
Speaker 4: The other team. You're Dodger fan, it's awesome. If you're not,

612
00:31:35,720 --> 00:31:36,760
Speaker 4: it's very annoying.

613
00:31:37,480 --> 00:31:39,640
Speaker 1: Yeah, the owners are going to be saying we need

614
00:31:39,680 --> 00:31:42,880
Speaker 1: a salary cap very very soon, and the players Association

615
00:31:42,960 --> 00:31:46,480
Speaker 1: has been staunchly against it. So hello strike or lockout

616
00:31:46,560 --> 00:31:47,320
Speaker 1: or something. Someday.

617
00:31:48,320 --> 00:31:51,160
Speaker 4: I want to talk about my ongoing sleep problems and

618
00:31:51,280 --> 00:31:55,560
Speaker 4: things I've learned and I'm realizing based on texts we

619
00:31:55,600 --> 00:31:57,800
Speaker 4: get and statistics a lot.

620
00:31:57,840 --> 00:31:58,880
Speaker 3: Do you have trouble sleeping?

621
00:31:58,880 --> 00:32:01,760
Speaker 4: In fact, over half of people say they have trouble

622
00:32:01,760 --> 00:32:03,760
Speaker 4: sleeping on a regular basis, half of adults.

623
00:32:03,760 --> 00:32:04,160
Speaker 1: Anyway.

624
00:32:04,960 --> 00:32:05,880
Speaker 3: Anyway, more on that a.

625
00:32:05,880 --> 00:32:08,720
Speaker 4: Little bit later, and then in a few minutes the

626
00:32:08,840 --> 00:32:11,040
Speaker 4: one of the worst New York Post headlines I've ever seen,

627
00:32:11,280 --> 00:32:14,960
Speaker 4: but ongoing story of the doctor who tried to kill

628
00:32:15,000 --> 00:32:17,640
Speaker 4: his wife at the cliff in Hawaii on the hiking trail.

629
00:32:18,040 --> 00:32:19,920
Speaker 3: That story seems to get a lot of attention. I'm

630
00:32:19,920 --> 00:32:21,640
Speaker 3: not exactly sure why.

631
00:32:23,160 --> 00:32:27,000
Speaker 1: It good looking, rich people murder love.

632
00:32:27,480 --> 00:32:29,880
Speaker 3: Remember I told his story the other day.

633
00:32:30,600 --> 00:32:32,440
Speaker 4: I told the story the other day of someone I

634
00:32:32,520 --> 00:32:36,640
Speaker 4: personally know who broke up with a guy, very serious relationship.

635
00:32:36,640 --> 00:32:38,640
Speaker 4: Broke up with a guy because they were hiking along

636
00:32:38,680 --> 00:32:40,480
Speaker 4: a cliff and he said, man, I could push you

637
00:32:40,520 --> 00:32:42,239
Speaker 4: off this cliff right now, and nobody to ever know.

638
00:32:44,320 --> 00:32:46,520
Speaker 3: She was so come out, she's so grouped out about it.

639
00:32:46,600 --> 00:32:47,160
Speaker 1: She broke up.

640
00:32:48,640 --> 00:32:52,400
Speaker 4: Same hiking trail is this guy. So there must be

641
00:32:52,480 --> 00:32:54,680
Speaker 4: something about this cliff that makes you think, wow, there

642
00:32:54,720 --> 00:32:57,440
Speaker 4: is nobody around, and that is straight down. They should

643
00:32:57,440 --> 00:32:59,560
Speaker 4: rename that trail. You know you got you're tired of

644
00:32:59,560 --> 00:33:01,920
Speaker 4: your husband, take your micing on that trail, just to

645
00:33:01,920 --> 00:33:03,000
Speaker 4: give him a little elbow.

646
00:33:03,520 --> 00:33:09,160
Speaker 1: The old Hawaiian divorce, right, it's gonna get a name anyway.

647
00:33:09,560 --> 00:33:10,280
Speaker 3: It's gruesome.

648
00:33:10,320 --> 00:33:13,600
Speaker 4: Obviously, this is horrible, and thank god somebody who's around

649
00:33:13,680 --> 00:33:16,760
Speaker 4: to intervene when she started screaming, help, Elpie's trying to

650
00:33:16,880 --> 00:33:20,880
Speaker 4: kill me. Two people in their forties. This is what

651
00:33:20,960 --> 00:33:25,520
Speaker 4: the testimony is now from her. They're on this trail

652
00:33:25,560 --> 00:33:28,120
Speaker 4: in Honolulu, up on a cliff and everything like that.

653
00:33:28,880 --> 00:33:31,520
Speaker 4: He stood next to her and said, hey, let's take

654
00:33:31,520 --> 00:33:34,880
Speaker 4: a selfie, and then was like edging closer to the

655
00:33:35,040 --> 00:33:37,120
Speaker 4: end of the cliff, and she said no, no, we're

656
00:33:37,120 --> 00:33:39,080
Speaker 4: too close to the cliff, and like walked away, kind

657
00:33:39,120 --> 00:33:42,400
Speaker 4: of freaked out. He then grabs a rock and starts

658
00:33:42,400 --> 00:33:45,880
Speaker 4: beating her on the head with the rock. He'd given

659
00:33:46,000 --> 00:33:48,239
Speaker 4: up on the hole. This will I'm gonna make it

660
00:33:48,240 --> 00:33:50,000
Speaker 4: seem like an accident. I don't know what are you doing,

661
00:33:50,000 --> 00:33:51,280
Speaker 4: but it's just.

662
00:33:51,320 --> 00:33:53,400
Speaker 1: Trying to get her near the edge. And she backed off,

663
00:33:53,400 --> 00:33:55,840
Speaker 1: and he thought, well, I'm all intent on killing her.

664
00:33:55,920 --> 00:33:57,160
Speaker 1: Let's see what do we have at hand.

665
00:33:57,400 --> 00:33:59,520
Speaker 4: Starts bashing around the head with a rock, gets her

666
00:33:59,520 --> 00:34:03,360
Speaker 4: on the ground, then grabs his bag and gets two

667
00:34:03,480 --> 00:34:06,880
Speaker 4: syringes from the bag. So this wasn't a all of

668
00:34:06,920 --> 00:34:09,560
Speaker 4: a sudden he thought of this sort of plan. He

669
00:34:09,640 --> 00:34:13,400
Speaker 4: certainly not he had had this plan in mind. She

670
00:34:13,440 --> 00:34:14,319
Speaker 4: starts yelling and help.

671
00:34:14,400 --> 00:34:14,680
Speaker 3: Help.

672
00:34:15,080 --> 00:34:17,759
Speaker 4: Luckily, he's kind of a weedy guy, apparently, because he

673
00:34:17,840 --> 00:34:19,640
Speaker 4: keeps fighting and hitting herund the head with a rock

674
00:34:19,680 --> 00:34:22,200
Speaker 4: and she's fine. Well she's not fine, but she ain't dead,

675
00:34:22,560 --> 00:34:25,920
Speaker 4: and she's yelling in somebody seasons, somebody runs that direction,

676
00:34:26,000 --> 00:34:28,040
Speaker 4: and then he stops, and then he makes up the

677
00:34:28,080 --> 00:34:31,200
Speaker 4: whole story of she's lying and she fell and all

678
00:34:31,200 --> 00:34:33,840
Speaker 4: that sort of stuff. He's being charged with currently second

679
00:34:33,840 --> 00:34:36,080
Speaker 4: degree murder. But what a weird story.

680
00:34:36,600 --> 00:34:37,640
Speaker 3: It's a freaking doctor.

681
00:34:38,000 --> 00:34:39,840
Speaker 4: I guess you're right. That is part of the appeal.

682
00:34:39,880 --> 00:34:43,720
Speaker 4: It's you know, rich, successful white people.

683
00:34:44,640 --> 00:34:45,040
Speaker 3: Whatever.

684
00:34:45,680 --> 00:34:48,240
Speaker 1: Yeah, no offense to anybody. But if a messy trailer

685
00:34:48,360 --> 00:34:51,240
Speaker 1: park couple tries to kill each other, nobody pays much attention.

686
00:34:51,760 --> 00:34:54,680
Speaker 3: Yeah, it happens on a fair early regular basis.

687
00:34:55,200 --> 00:34:59,440
Speaker 4: And then this headline I don't like. Man says he

688
00:34:59,600 --> 00:35:03,000
Speaker 4: im had luck improving this is not for the children.

689
00:35:03,400 --> 00:35:05,359
Speaker 1: Oh boy too boy.

690
00:35:05,480 --> 00:35:09,160
Speaker 4: Man says he had luck improving nighttime erections by thirty

691
00:35:09,200 --> 00:35:13,960
Speaker 4: four percent with shockwave therapy and botox to his penis.

692
00:35:14,600 --> 00:35:18,279
Speaker 4: Couple things about this headline I find interesting. First of all,

693
00:35:19,719 --> 00:35:24,239
Speaker 4: improving nighttime erections is that the thing, like you mean

694
00:35:24,280 --> 00:35:25,839
Speaker 4: while I'm asleep in the middle line, I don't know.

695
00:35:26,000 --> 00:35:29,680
Speaker 4: And thirty four percent seems like a very specific number from.

696
00:35:29,520 --> 00:35:33,520
Speaker 1: The Department of the weirdly specific Yes, well, let's bye

697
00:35:33,640 --> 00:35:36,879
Speaker 1: bye golly. My nighttime erections seem to have improved by

698
00:35:36,880 --> 00:35:40,240
Speaker 1: a third. Wait a moment, let me recal your thirty four.

699
00:35:40,239 --> 00:35:45,680
Speaker 4: Percent night after night shockwave therapy. What are you shocking?

700
00:35:48,120 --> 00:35:54,160
Speaker 4: And then botox? Oh okay, the botox. Why congratulations on

701
00:35:54,280 --> 00:35:59,000
Speaker 4: improving your ntes, which apparently had been letting you down.

702
00:35:59,480 --> 00:36:04,080
Speaker 1: Give me botox, not botox, says I, No, inappropriate, I

703
00:36:04,160 --> 00:36:06,560
Speaker 1: apologize thirty four percent?

704
00:36:06,680 --> 00:36:10,319
Speaker 3: You say, that's pretty successful. We got more news of

705
00:36:10,320 --> 00:36:10,960
Speaker 3: the day on the way.

706
00:36:10,960 --> 00:36:12,680
Speaker 4: If you miss the second, we get the podcast Armstrong

707
00:36:12,719 --> 00:36:13,640
Speaker 4: and Getty on demand

708
00:36:16,400 --> 00:36:17,560
Speaker 1: Armstrong and Getty