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Speaker 1: This is the primal scream of a dying regime. Pray

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Speaker 1: for our enemies because we're going to medieval.

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Speaker 2: On these people.

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Speaker 1: You've not got a free shot. All these networks lying

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Speaker 1: about the people, the people have had a belly full

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Speaker 1: of it. I know you don't like hearing that. I

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Speaker 1: know you tried to do everything in the world to

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Speaker 1: stop that, but you're not going to stop it. It's

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Speaker 1: going to happen. And where do people like that go

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Speaker 1: to share the big line?

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Speaker 3: Mega media?

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Speaker 1: I wish in my soul, I wish that any of

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Speaker 1: these people had a conscience. Ask yourself, what is my

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Speaker 1: task and what is my purpose? If that answer is

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Speaker 1: to save my country, this country will be saved.

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Speaker 3: War Room, use your host, Stephen Kvan.

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Speaker 1: Saturday eight March in The Arveler twenty twenty five, Rosemary

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Speaker 1: Jinks one of the greatest warriors this movement's ever produced,

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Speaker 1: been doing this for years. And the reason that we're

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Speaker 1: finally getting our hands around it and now getting ready

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Speaker 1: to mass deportations and we will get to that of

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Speaker 1: timmy and folks and stop at the blind becers are

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Speaker 1: years at numbers USA to make people and there was

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Speaker 1: many lonely years in the wilderness. I remember this. Years

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Speaker 1: that you guys were blocked to go in a seapac

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Speaker 1: There were years that people didn't want you're talking to conferences.

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Speaker 1: They treated you like lepers, right because you spoke truth

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Speaker 1: to power and eventually punched through and President Trump rode

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Speaker 1: that truth to the presidency. Remember that, against all odds

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Speaker 1: and against what the establishment, the established ordered had to say.

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Speaker 1: Then she shifted to go on offense. We have to

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Speaker 1: go on offense. We cannot continue like this. We're not

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Speaker 1: going to be a country and you're going to have

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Speaker 1: so many dispirited people that you know, we're just not

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Speaker 1: gonna be able to go forward. We can't. Part of

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Speaker 1: this is we cannot invite the world here to compete

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Speaker 1: against American citizens, competing on a global basis with American companies,

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Speaker 1: with American works, no problem, competitive people, we can take

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Speaker 1: on anybody. But that's not what's happening. What's happening is

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Speaker 1: a total con and a scam. And people say, Steve,

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Speaker 1: you know Republicans christ and it's so pro corporation, you're

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Speaker 1: anti corporation. You damn right on anti corporation. You see

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Speaker 1: what they did in DEI Hey, I went to Harvard

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Speaker 1: Business School. Okay, I worked at Goldman Sachs. I seen it, okay,

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Speaker 1: up close and personal. I see what's taught. I see

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Speaker 1: how they act. I see what their priorities are. It's

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Speaker 1: not the United States of America, and it's certainly not

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Speaker 1: American citizens. Rosemarie Jenks, I want to go put through

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Speaker 1: the value chain of this con and the value chain

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Speaker 1: is all for the companies and the corporations who do

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Speaker 1: not give a damn about American citizens unless the Schmendrick

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Speaker 1: taxpayers are underwriting their con. So walk us through it, ma'am.

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Speaker 4: Yeah.

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Speaker 5: So the universities are heavily involved in this as well,

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Speaker 5: because they get full tuition from foreign students, so they

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Speaker 5: bring in foreign students on an f visa.

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Speaker 4: And then the actually President George W.

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Speaker 5: Bush created a program out of whole cloth called the

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Speaker 5: Optional Practical Training Program OPT, which allows employers to hire

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Speaker 5: foreign student graduates over Americans and get a subsidy because

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Speaker 5: they don't have to pay Social Security taxes for the

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Speaker 5: foreign students, so they actually save seven to eight percent

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Speaker 5: on hiring foreigners over Americans. And then from OPT, the

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Speaker 5: employer sponsors them for an h one B, and then

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Speaker 5: from H one B the employer sponsors them for a

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Speaker 5: green card, they go into a backlog and they can

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Speaker 5: remain here for twenty thirty forty fifty years until a

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Speaker 5: green card becomes available, and that entire time American STEM

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Speaker 5: workers are blocked, literally excluded from those jobs.

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Speaker 4: So this is a pipeline that we have to break.

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Speaker 5: First of all, we have to eliminate OPT immediately, which

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Speaker 5: the President could do with a stroke of his pen.

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Speaker 5: The second thing is, if I mean, if America first

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Speaker 5: actually means Americans first, then we should just eliminate the

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Speaker 5: H one V program altogether. If you are the you know,

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Speaker 5: seriously best and brightest genius.

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Speaker 1: To hang on, hang on, hang on, hang on, hang on,

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Speaker 1: hang on. I have begged these guys to show, and

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Speaker 1: there's hundreds of thousands, not to eighty. There's eighty five thousand,

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Speaker 1: plus another twenty thousand for graduate schools, which also you know,

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Speaker 1: takes the graduate schools off for American citizens getting into.

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Speaker 1: So there's twenty third's one hundred five thousand, one hundred

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Speaker 1: and fifteen thousand I get to or one hundred five thousand.

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Speaker 1: Then there's unlimited number coming out of college and that's

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Speaker 1: just on an annual basis. So there's hundreds of thousands,

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Speaker 1: are over one hundred thousand on an annual basis. You

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Speaker 1: owed it up. There's millions here. I have asked a

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Speaker 1: million and a half, pleaded for them to come to

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Speaker 1: come to how many? How many?

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Speaker 4: Did you just say, ma'am, that's one point five million?

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Speaker 1: One point five million. I think that's a low count,

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Speaker 1: but I'll take that number. One point five million, all

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Speaker 1: of whom have to go home immediately. And I'm not

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Speaker 1: being a nativist. I'm not being a xenophobe. This is practical.

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Speaker 1: And here's why I have not They have not shown

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Speaker 1: us one person in a billet that that billet either

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Speaker 1: has a professional, academic or professional rank that an American

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Speaker 1: citizen can't fill. That the entire program is a lie.

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Speaker 1: It is a bald faced lie. I understand. I worked

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Speaker 1: at Goldman Sachs, I went to Harvard Business School. I

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Speaker 1: get the math. You want to have all these these

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Speaker 1: companies are it's the labor that's the cost. In the

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Speaker 1: age of the algorithm, it's it's in by and large

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Speaker 1: that there's some others have production capability, but labor costs

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Speaker 1: is everything. If you cut your labor costs by a

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Speaker 1: third to fifty per and that's what they pay these

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Speaker 1: people less. Of course, and they're going to be compliant.

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Speaker 1: They're gonna be compliant. They're gonna be compliant because they

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Speaker 1: want to stick around and get a green card. Of course,

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Speaker 1: it makes sense. The logic of capitalism drives it to

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Speaker 1: make sense. I got that. But it destroys American citizens.

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Speaker 1: This is why Silicon Valley is in an apartheight state.

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Speaker 1: You have no African Americans, you have no Hispanics, and

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Speaker 1: now you have virtually no white working class. Why because

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Speaker 1: the game is rigged against you. And here's the Greek

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Speaker 1: tragedy part of it. You underwrite it both. You're with

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Speaker 1: your tax dollars because they don't charge Social Security and

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Speaker 1: your pension funds are the private equiin venture capital. Of

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Speaker 1: the finances, you finance all of it. I want that,

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Speaker 1: I want that wound. I want to take that salt.

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Speaker 1: I'm gonna rub that salt right in it. Right, I

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Speaker 1: want to burn. I want to burn. So you understand

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Speaker 1: how you're being conned and destroyed and your children are

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Speaker 1: being destroyed. Rosemary jinks. This is and what they're trying

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Speaker 1: to do and Semophore has got this story Mark Andresen.

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Speaker 1: They think you're an idiot. They're going to pat us

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Speaker 1: on the head and have some changes on the margin.

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Speaker 3: Screw you.

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Speaker 1: We want the whole fricking program gone. We want OPT gone.

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Speaker 1: If it's America first, it's got to be American citizens first,

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Speaker 1: Rosemary jinks.

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Speaker 5: Yeah, that's absolutely right. And you know the proof. First

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Speaker 5: of all, I can tell you what Congress is going

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Speaker 5: to do. You're going to see a push to address

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Speaker 5: the H one B dependent employers like the body shops.

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Speaker 4: That's not good enough.

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Speaker 5: Yes, we need to end the body shops, which means

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Speaker 5: you eliminate third party employment altogether. They need to go.

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Speaker 5: But that is not enough. We have American workers there.

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Speaker 5: According to the Center for Immigration Studies, there are almost

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Speaker 5: twelve million US STEM workers STEM graduates who are not

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Speaker 5: working in STEM because they have been blocked from STEM

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Speaker 5: by foreign workers by this pipeline.

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Speaker 4: That has to end.

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Speaker 5: And that the employers are using this to replace Americans obviously,

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Speaker 5: is that they're taking experienced US tech workers and firing

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Speaker 5: them because they're expensive and replacing them with entry level

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Speaker 5: H one B workers so they can pay you know,

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Speaker 5: significantly less a fraction of the cost that they were

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Speaker 5: to experienced Americans. It's not about qualifications, it's not about skills.

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Speaker 4: It is about cheap labor. Period.

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Speaker 1: Sure, indentured servants. We fought wars in the nineteenth century

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Speaker 1: and had massive union in labor fights as bloody as

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Speaker 1: almost a civil war. Part of them about slavery and

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Speaker 1: about indentured servitude. It's got to end, and we're going

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Speaker 1: to end it. Rosemard jinks, where can people go. We're

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Speaker 1: going to weaponize people on this. We're going to weaponize them.

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Speaker 1: This cannot go on. And we're not going to be

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Speaker 1: padded on the head by the market reasons of the

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Speaker 1: world and all your conferences and oh we'll get the

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Speaker 1: body shops and know, the whole thing's got to go.

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Speaker 1: It's a con and a scam, and it's offensive defensive

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Speaker 1: because it's destroying the people that put to get through

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Speaker 1: engineering school and to become STEM and learn a computer

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Speaker 1: and program. I can't do it. I'm a frickin moron.

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Speaker 1: It's too hard for me, way too hard. People have

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Speaker 1: done that in sacrifice and then not to have opportunities

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Speaker 1: when you promise it, if you work hard, the promise

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Speaker 1: of America. You work hard, you have grit and diligence,

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Speaker 1: and you get through and you dedicate your life to

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Speaker 1: this profession, this skill, and then it's blocked because you're

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Speaker 1: an American citizen, is blocked in your own country. And

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Speaker 1: you don't think that's outrageous. If we can't take care

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Speaker 1: of this, then we can't take care of anything. And

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Speaker 1: any politician it sets up there and gives the happy talk.

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Speaker 1: It's outrageous, Rosemary jinks. How do people get more information

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Speaker 1: on it? This is a crusade. Where do people get

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Speaker 1: more information?

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Speaker 5: We actually have a fact sheet up on our website,

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Speaker 5: which is iaproject dot org.

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Speaker 4: We're also extremely active on.

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Speaker 5: This on x All of our social media is linked

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Speaker 5: from our website iaproject dot org. We need the support

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Speaker 5: of the posse to get this done because members of

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Speaker 5: Congress are afraid, and we need to break their fear

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Speaker 5: and make them understand that America first is Americans first.

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Speaker 1: Yeah, well, we're going to make them. They're afraid of

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Speaker 1: big teching, the donors and all that. I got it.

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Speaker 1: They should be afraid of that, But we're going to

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Speaker 1: make the more afraid of an enraged population that says

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Speaker 1: this has to end, this has to stop, and we're

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Speaker 1: prepared to put political muscle in make in getting into

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Speaker 1: your district and making sure you're one of the bums

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Speaker 1: are going to throw out. So we don't care how

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Speaker 1: much money Mark in Dresen gives you. Thank you, I

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Speaker 1: appreciate you.

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Speaker 5: I hope everyone would call the members of the Judiciary

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Speaker 5: Committee in the House and the Senate, and the members

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Speaker 5: of House and Senate leadership and tell them, do not

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Speaker 5: play around with us on this in the Reconciliation Bill.

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Speaker 5: We are not going to accept any half measures. You

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Speaker 5: fix it, eliminate it, or we're coming.

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Speaker 1: For you, or the vote is no. And the big

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Speaker 1: beautiful bill. This is what they're trying to do. They're

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Speaker 1: going to play kind of games, mister President. They're going

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Speaker 1: to lie to you. Rosemarie Jenks, thank you, ma'am. Appreciate you,

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Speaker 1: very special, very special warrior. She's given up a lot

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Speaker 1: and then she caught a lot of grief for years.

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Speaker 1: You can't believe what was stown with these people. Now,

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Speaker 1: me Wolf joins us from India to say, so we've

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Speaker 1: got a rigg system. But it gets worse because artificial

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Speaker 1: intelligence is coming. For all that keeps saying, the managerial, tech,

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Speaker 1: administrative jobs, for anybody's kind of entry level jobs under

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Speaker 1: third they're all going to get eviscerated immediately. So you're

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Speaker 1: not going to have that coming out of college. For

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Speaker 1: the skill set. We don't know anything practically and you

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Speaker 1: got to learn that's all about to go. You're over

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Speaker 1: in India right now getting an eye opening and awakening experience.

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Speaker 1: I take it, ma'am. And artificial intelligence.

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Speaker 6: Yeah, it's revelatory. I thought I understood the gist of it,

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Speaker 6: and of course I have a tech company, so it's

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Speaker 6: important to understand. But what I've seen in the last

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Speaker 6: two days here at the India Today conclave in Delhi

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Speaker 6: is pretty stunning. Because of course there's always such a difference, Steve,

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Speaker 6: between what is messaged like, oh, chatchipt will help you

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Speaker 6: write about Romeo and Juliet without reading the original text,

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Speaker 6: versus what you hear when you actually go behind the

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Speaker 6: curtain and listen to.

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Speaker 7: The people the heart of the belly of the beast

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Speaker 7: and hear what their plans are.

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Speaker 6: So, to be more specific, what I learned about AI

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Speaker 6: and this conference has largely focused on AI with sixty speakers.

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Speaker 6: It includes some of the most distinguished pioneers in AI

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Speaker 6: out of Deloitte and Harvard and Microsoft.

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Speaker 7: Is that they're planning for a completely other world for us.

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Speaker 6: And I just want to walk through three points. And

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Speaker 6: again we've heard variations of some of these, but to

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Speaker 6: hear that, I.

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Speaker 1: Tell you what hang on. Second, I want to start

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Speaker 1: at the top of the next segment with the brave

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Speaker 1: new world that awaits. Naomi Wolf went behind the curtain

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Speaker 1: and it takes something pretty horrific to shock. Naomi Wolf

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Speaker 1: seen a lot, knows a lot, been in the power

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Speaker 1: centers of culture, government, politics globally. When she's tells you

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Speaker 1: you've got no the idea of what's coming down the track,

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Speaker 1: you better sit up pay attention. The great fight of

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Speaker 1: our time. I'm on the side of the Homo sapiens.

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Speaker 1: I'm on the side of the human race. I don't

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Speaker 1: know about you. If we got to go down fighting,

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Speaker 1: if we've got to go down, we're gonna go down fighting.

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Speaker 1: We'll give them one for the ages, right. But I

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Speaker 1: don't think we're going down. I think we break this

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Speaker 1: whole thing. I don't think they're that strong. I don't

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Speaker 1: think they're that tough, and I don't think they're that courageous.

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Speaker 1: But it is going to be a fight. If you

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Speaker 1: don't think so, you're kidding yourself. Because it's about money

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Speaker 1: and power. These people have no ethics, they have no morality.

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Speaker 1: It's going to be quite Darwinian short break, confuse your host.

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Speaker 3: Stephen came back, you.

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Speaker 1: Know, beside my Warpath coffee, which gets because we're up

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Speaker 1: When I say pre dawn, I mean really pre down

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Speaker 1: middle of the night to get ready for the show

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Speaker 1: every day, get all jacked up with the war Path coffee.

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Speaker 1: You know, Tays used to be the head of my

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Speaker 1: security detail and then he told me one day he

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Speaker 1: was working on this one to do something else, to

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Speaker 1: get out of that business, because he's been in it

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Speaker 1: for you know, twenty years of his life, deploying all

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Speaker 1: the time over to Iraq in Afghanistan, and then with

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Speaker 1: us start the coffee company. And look when he's made

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Speaker 1: it seven five star reviews, Warpath Dot Coffee slash Warm

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Speaker 1: twenty percent off. And I'm so proud of this guy

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Speaker 1: because a guy had an idea and he made it.

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Speaker 1: And I people know, I'm very picky about my coffee,

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Speaker 1: and I told him you got to do a dark roast,

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Speaker 1: and he took a year and a half to get

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Speaker 1: it right. It's the Champagne of coffee. You can drink

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Speaker 1: it black, and coffee should be consume black with no cream,

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Speaker 1: no sugar. That's all to cut the acidity. You don't

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Speaker 1: want to say something, and I know some people have

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Speaker 1: been texting me, some of the war room, the engine

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Speaker 1: room about the whole thing of getting into colleges. We're

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Speaker 1: going to deal with that also, because you're right, Chinese oligarchs,

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Speaker 1: not just oligarchs about the world's kids are getting priority

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Speaker 1: in these universities. They're getting priorities. It's not acceptable. We

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Speaker 1: got to vet that whole thing. These universities are cesspools,

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Speaker 1: so we're having to barrow it the other day. That's

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Speaker 1: their back already on the Jewish kids. It's just it's

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Speaker 1: not right. It's not right. We got to clean these

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Speaker 1: things are cesspoles. I mean, you saw when Naomi went

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Speaker 1: back to Yale, remember the thing with the with to

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Speaker 1: think about what Nazis they were about putting the vaccine kids.

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Speaker 1: They're out of control. What's even worse and the moral

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Speaker 1: dilimma you're going to have, Naomi, is that folks. You

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Speaker 1: know like you went to Yale, I went to Harvard.

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Speaker 1: Other people went to ivans are Ivy League equivalent or

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Speaker 1: just to the Great State University of the University of

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Speaker 1: Michigan and UCLA and you know University of Arizona and

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Speaker 1: Tennessee and Alabama. All this In the future, the dilemma

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Speaker 1: of people under forty are going to have is do

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Speaker 1: I chip my kid? I do I enhance? Do they

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Speaker 1: have to be enhanced to compete? Because this is where

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Speaker 1: it's going and you look behind the curtain on artificial intelligence,

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Speaker 1: and it takes a lot to shock Naomi Wolf, but

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Speaker 1: when I talk to her, when we make contact, she says,

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Speaker 1: I want to make sure people understand where this is headed.

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Speaker 1: So Naomi Wolf, give it to us, as we say,

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Speaker 1: down south with the bark on ma'am.

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Speaker 7: Yeah.

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Speaker 6: So first, like, being here in India and hearing this

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Speaker 6: conversation is very sobering because it's so clear that the

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Speaker 6: conversation is so much more advanced here and more people

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Speaker 6: understand it than they're allowing us to understand it in

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Speaker 6: the United States. And that's scary headline I want to

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Speaker 6: give you is these tech insiders who are handling and planning.

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Speaker 6: AI are so happy and so cheerful and empowered about

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Speaker 6: what they're planning for the rest of us, because in

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Speaker 6: their mind, the battles already won, and they're the ones

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Speaker 6: who hold all the power. And they stress that it's

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Speaker 6: not a matter of years, which is how we tend

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Speaker 6: to think of it. Oh, this is coming down the pike,

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Speaker 6: you know, we can prepare for it. No, they're saying,

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Speaker 6: it's not even a matter of months. The changes are

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Speaker 6: so fast with his technology, it's a matter of weeks

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Speaker 6: and days for the changes. And so number one, what

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Speaker 6: they're preparing for and planning for now is a world

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Speaker 6: almost without workers. And I can't stress this enough because

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Speaker 6: it ties in with what ms Jenks was saying, It

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Speaker 6: ties in with what Joe Allen has been saying.

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Speaker 7: I think it even ties in with.

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Speaker 6: The lethal effects of the vaccine and the whole rollout

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Speaker 6: of the vaccine. This is what one of these commentators

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Speaker 6: from Microsoft is I experts said. He said, they're planning

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Speaker 6: for a world in which there's a factory floor and

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Speaker 6: he used to have one hundred workers and now it's

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Speaker 6: got fifteen.

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Speaker 7: Everything else has been done by robots and all the

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Speaker 7: other jobs are gone.

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Speaker 6: And maybe some people that were laid off or have

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Speaker 6: no more social import He didn't say this.

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Speaker 7: This is me elucidating the implications.

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Speaker 6: You know, maybe a handful of them will retrain to

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Speaker 6: oversee the networking of the robots, but everyone else is

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Speaker 6: over there's no more use for them. They're useless eaters.

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Speaker 6: They have no more social value. And that's not just

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Speaker 6: in one field, it's in every field. We heard presentations

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Speaker 6: about AI kind of replacing teachers and graduate students at Harvard,

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Speaker 6: you know, chatbots replacing pedagogy, replacing the learning process. You know,

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Speaker 6: we heard about AI in healthcare replacing nurses essentially, and

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Speaker 6: I'll get to that in a minute. But what people

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Speaker 6: really have to understand is they're not thinking futuristically. It's

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Speaker 6: more like the day after tomorrow, eighty five percent of

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Speaker 6: the workers in job after job after job, including coding

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Speaker 6: and you know, FAA and real estate and healthcare, will

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Speaker 6: not have any purpose. So you've really got to think

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Speaker 6: about that. You know, if I'm hearing it behind the scenes,

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Speaker 6: it means that the World Economic Forum has heard this.

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Speaker 6: It means that, you know, the Biden administration heard it.

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Speaker 6: It means that governments around the world have heard that

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Speaker 6: eighty five percent of the workers won't have a role

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Speaker 6: or a purpose in society. So you've really got to think,

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Speaker 6: if you're a policymaker, what does that mean?

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Speaker 7: You know, is this going to be a revolution of.

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Speaker 6: Laid off, angry, pointless people, or do you have to

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Speaker 6: manage things differently?

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Speaker 7: And I honestly went right to the lethal effects of

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Speaker 7: the vaccine.

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Speaker 6: I'm not saying there's a cause and effect that I

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Speaker 6: can point to, but these insiders are looking at a

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Speaker 6: world in which most people don't have a soul role

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Speaker 6: as workers anymore.

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Speaker 7: Shall I go on to the next two points?

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Speaker 6: Oh?

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Speaker 1: Yes, continue on, all right.

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Speaker 6: So I guess what I want to really stress is

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Speaker 6: the cheerfulness of these people. They don't say it like,

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Speaker 6: oh my god, this is going to be a huge

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Speaker 6: social problem all over the world.

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Speaker 7: We're to deal with people.

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Speaker 6: Who have no point, no role, no reason to have

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Speaker 6: an income, no professional self respect, no occupation, no purpose

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Speaker 6: in society.

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Speaker 7: They're really like, Okay, all right, that's in the past.

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Speaker 7: Workers are in the past. We've got the robots.

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Speaker 6: And by the way, they rolled down a robot at

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Speaker 6: one point in this conference, So the robots are already there.

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Speaker 7: People in China and.

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Speaker 6: India, you know, all these countries that are out piecing

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Speaker 6: us for reasons that you've also described, have produced the robots,

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Speaker 6: and everyone's kind of getting ready behind the scenes for

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Speaker 6: a robot filled humanless world in which you know, there's

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Speaker 6: fifteen people left on the shop floor. The next thing

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Speaker 6: is they're so cheerful because the people who run the AI,

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Speaker 6: meaning Microsoft, in Deloitte and Harvard, are going to be

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Speaker 6: far more powerful than anyone else.

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Speaker 7: And I've been warning about this in my essays.

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Speaker 6: More powerful than presidents, more powerful than prime ministers. So

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Speaker 6: something else we should really understand, which I hadn't fullyp grasped,

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Speaker 6: is that there's an arms racer now globally for states

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Speaker 6: to create sovereign AI. Like everyone on the inside understands

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Speaker 6: that the ownership of the AI is so critical that

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Speaker 6: you can't just leave it to the private sector. Whoever

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Speaker 6: has the best AI owns everything, right, wins all the wars.

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Speaker 6: So what we haven't heard in the United States is

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Speaker 6: that there's an arms race for nations and governments to

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Speaker 6: create and own their own artificial intelligence. This is really important, Steve,

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Speaker 6: Sovereign AI. It's especially important for your wonderful posse, your

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Speaker 6: populist nationalist audience, to understand we in the United States.

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Speaker 7: Don't have our own sovereign AI. We don't have it.

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Speaker 7: We were starting to.

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Speaker 6: Build it, and I don't mean to, you know, bring

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Speaker 6: up something awkward or.

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Speaker 7: You know, difficult.

433
00:24:11,880 --> 00:24:14,359
Speaker 6: I'm getting lots of angry emails about the fact that

434
00:24:14,359 --> 00:24:17,760
Speaker 6: I keep, you know, sounding this alarm. We were building it,

435
00:24:17,880 --> 00:24:22,520
Speaker 6: and Elon Musk replaced that with his own AI, which

436
00:24:22,680 --> 00:24:26,960
Speaker 6: is now being set upon our government data sets. The

437
00:24:27,040 --> 00:24:31,320
Speaker 6: point is when AI eats really good data sets, like

438
00:24:31,359 --> 00:24:35,560
Speaker 6: government data sets or other really pure, pristine, you know,

439
00:24:35,920 --> 00:24:40,080
Speaker 6: real fact based data sets that are not publicly available,

440
00:24:40,400 --> 00:24:43,000
Speaker 6: it then becomes the most valuable AI.

441
00:24:43,400 --> 00:24:48,120
Speaker 7: Right. So the point is our AI, our government AI. Everyone.

442
00:24:48,160 --> 00:24:50,480
Speaker 7: It's easy to hate the government, but this is our

443
00:24:50,600 --> 00:24:51,360
Speaker 7: tax dollars.

444
00:24:51,440 --> 00:24:51,640
Speaker 4: Right.

445
00:24:51,720 --> 00:24:55,119
Speaker 6: We should be owning the AI that is let loose

446
00:24:55,160 --> 00:24:58,159
Speaker 6: on our own government data sets, getting richer and richer

447
00:24:58,240 --> 00:25:00,199
Speaker 6: as it learns no.

448
00:25:00,800 --> 00:25:02,439
Speaker 7: Right that the plug got pulled.

449
00:25:02,640 --> 00:25:04,879
Speaker 6: So the point I want to make to everybody is

450
00:25:05,119 --> 00:25:07,560
Speaker 6: to win this arms race, or even compete in it,

451
00:25:07,840 --> 00:25:11,880
Speaker 6: we need our own sovereign AI, right, just like other

452
00:25:12,040 --> 00:25:13,919
Speaker 6: nations China, no doubt.

453
00:25:14,200 --> 00:25:16,800
Speaker 7: You know, certainly India, certainly.

454
00:25:16,840 --> 00:25:18,960
Speaker 6: You know other nation states around the world are building

455
00:25:19,000 --> 00:25:22,719
Speaker 6: their own sovereign, state owned AI. We don't have it,

456
00:25:22,840 --> 00:25:26,880
Speaker 6: we need it. When other privately owned AI is unleashed

457
00:25:26,960 --> 00:25:30,919
Speaker 6: on our data, it just enriches other people's AI. And

458
00:25:31,280 --> 00:25:34,760
Speaker 6: I can't stress the smoothness of these insiders as they

459
00:25:35,200 --> 00:25:37,879
Speaker 6: know that they will become the most powerful people on

460
00:25:37,920 --> 00:25:39,280
Speaker 6: the planet when they own the AI.

461
00:25:40,080 --> 00:25:42,960
Speaker 1: And the last thing I want to talk about, but

462
00:25:43,040 --> 00:25:44,439
Speaker 1: hang on and hang on and hang on, don't go

463
00:25:44,440 --> 00:25:47,720
Speaker 1: to the last point. Let skip This is this why

464
00:25:49,200 --> 00:25:52,560
Speaker 1: people are thinking this through says really technologies the new

465
00:25:52,600 --> 00:25:57,320
Speaker 1: political order that political governments and the established order we've

466
00:25:57,320 --> 00:26:01,119
Speaker 1: thought about for you know, a millennial yea or two

467
00:26:01,440 --> 00:26:03,879
Speaker 1: is now going to be overwhelmed by answer to this.

468
00:26:03,960 --> 00:26:05,320
Speaker 1: On the other side, we're gonna take a break. But

469
00:26:06,240 --> 00:26:12,919
Speaker 1: becomes the technology itself, becomes both a presser and the

470
00:26:13,000 --> 00:26:20,080
Speaker 1: new order. Wow, what a Saturday morning. Maybe it's time

471
00:26:20,119 --> 00:26:24,359
Speaker 1: to get another cup of coffee. Hey, you got to

472
00:26:24,400 --> 00:26:27,719
Speaker 1: face it, right, That's why you are a vanguard. That's

473
00:26:27,720 --> 00:26:29,919
Speaker 1: why you're a cadre. That's where you've already changed the

474
00:26:29,960 --> 00:26:33,520
Speaker 1: direction of the country. We wouldn't lay this on you

475
00:26:33,640 --> 00:26:35,640
Speaker 1: if it wasn't important, and we didn't think you could

476
00:26:35,640 --> 00:26:39,480
Speaker 1: handle it, and we didn't think you could fight on

477
00:26:39,560 --> 00:26:44,880
Speaker 1: the side of the righteous. Short commercial break. We are

478
00:26:44,880 --> 00:26:46,360
Speaker 1: in a modern day Holy Ward.

479
00:27:00,200 --> 00:27:02,440
Speaker 3: Use your host, Stephen k Bah.

480
00:27:06,359 --> 00:27:09,199
Speaker 1: Patriot Mobile. You know how great they are. You know

481
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Speaker 1: how they support your values. You know the work they're

482
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Speaker 1: doing in Texas, throughout the country. Glenn Starring's team is everywhere.

483
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Speaker 1: Now it's all about trying the service out. Do the switch.

484
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485
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487
00:27:28,920 --> 00:27:32,920
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488
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489
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Speaker 1: layered on top of every major platform. You're gonna have

490
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Speaker 1: incredible service. And when you speak to somebody in one

491
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Speaker 1: of these customer service it's an American citizen support companies

492
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Speaker 1: that support the Patriot movement. This is this Patriot economy

493
00:27:51,480 --> 00:27:55,160
Speaker 1: we're building. We got another issue about dbanking. I'm gonna

494
00:27:55,160 --> 00:27:58,160
Speaker 1: talk to you on Monday. Another fight. Hey, I would

495
00:27:58,160 --> 00:28:00,280
Speaker 1: love to wave a magic wand and say it's all better.

496
00:28:00,440 --> 00:28:02,880
Speaker 1: It ain't better. I mean it's much better. Don't care.

497
00:28:02,920 --> 00:28:06,000
Speaker 1: It's much much better. But there's no magic wand to

498
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Speaker 1: take care of her. It's going to take grit, determination

499
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Speaker 1: and down the trenches. Patriot Mobile ninety seven two. Patriot.

500
00:28:14,000 --> 00:28:16,560
Speaker 1: You'll love the service and you'll love the company. You'll

501
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Speaker 1: feel good about supporting something that does good by you.

502
00:28:22,400 --> 00:28:24,560
Speaker 1: Naimi Wolf, I want to go back for a second.

503
00:28:24,800 --> 00:28:31,280
Speaker 1: This hit rewind to sovereign AI. This. I'm totally confused.

504
00:28:31,840 --> 00:28:34,520
Speaker 1: All these companies are running around, they're getting capital, their

505
00:28:34,880 --> 00:28:37,640
Speaker 1: market caps two trellion dollars, are doing this, they're doing that.

506
00:28:38,040 --> 00:28:40,680
Speaker 1: I thought the companies had the AI. Are you arguing

507
00:28:40,720 --> 00:28:43,600
Speaker 1: for something different, ma'am? And why are you arguing that?

508
00:28:45,080 --> 00:28:50,080
Speaker 6: Okay, well, the companies, different companies do have different AI.

509
00:28:50,280 --> 00:28:50,880
Speaker 7: They own it.

510
00:28:51,000 --> 00:28:51,160
Speaker 1: Right.

511
00:28:51,160 --> 00:28:54,480
Speaker 6: People have to understand, it's not like air or water

512
00:28:54,520 --> 00:28:57,760
Speaker 6: in the ocean that's just out there. AI is a

513
00:28:57,920 --> 00:29:04,280
Speaker 6: technology that is owned by different companies, different shareholders. It's

514
00:29:04,440 --> 00:29:07,640
Speaker 6: patented and we're in an arms race right for who

515
00:29:07,680 --> 00:29:12,080
Speaker 6: has the best AI. Now, AI doesn't get better all

516
00:29:12,720 --> 00:29:17,640
Speaker 6: by itself in a company with you know coders and engineers,

517
00:29:17,800 --> 00:29:21,640
Speaker 6: it requires data sets, right, It's this voracious kind of

518
00:29:21,680 --> 00:29:24,640
Speaker 6: I always say, imagine an artificial giant fish eating a

519
00:29:24,640 --> 00:29:27,440
Speaker 6: lot of tiny reelfish, right and always needs more and

520
00:29:27,480 --> 00:29:29,280
Speaker 6: more and more tiny reel fish to get.

521
00:29:29,160 --> 00:29:32,520
Speaker 7: Better and better. So what it eats is data.

522
00:29:32,600 --> 00:29:34,840
Speaker 6: Right, data sets, so that data sets that are out

523
00:29:34,840 --> 00:29:38,080
Speaker 6: there in the world already are kind of okay. You know,

524
00:29:38,120 --> 00:29:39,840
Speaker 6: they've got a lot of errors, they've got a lot

525
00:29:39,880 --> 00:29:45,560
Speaker 6: of misinformation. Publicly available data is okay. But the government data,

526
00:29:45,600 --> 00:29:52,160
Speaker 6: our census information, our tax returns, our contracts, our payment systems,

527
00:29:52,600 --> 00:29:56,040
Speaker 6: you know, our IP, the software that we, our own

528
00:29:56,200 --> 00:29:59,680
Speaker 6: tax payer funded engineers have developed for the use of

529
00:29:59,720 --> 00:30:03,920
Speaker 6: the our cantaxpayer. That's I know, people love to hate

530
00:30:03,920 --> 00:30:05,480
Speaker 6: on the government. There are a lot of things to

531
00:30:05,520 --> 00:30:08,040
Speaker 6: do better, but that as a data set is the

532
00:30:08,040 --> 00:30:14,040
Speaker 6: most pristine, detailed, accurate, unmonetized data set in the world.

533
00:30:14,240 --> 00:30:14,440
Speaker 8: Right.

534
00:30:14,880 --> 00:30:18,840
Speaker 6: So if you're going to we should be building our

535
00:30:18,880 --> 00:30:23,800
Speaker 6: own sovereign AI owned by our government, owned by the people,

536
00:30:24,200 --> 00:30:29,959
Speaker 6: paid for by the people, patented, copyrighted, locked down by

537
00:30:30,160 --> 00:30:33,640
Speaker 6: the federal government. The way other IP intellectual property for

538
00:30:33,720 --> 00:30:38,360
Speaker 6: other software that the government developed is owned by the government,

539
00:30:38,400 --> 00:30:39,200
Speaker 6: belongs to us.

540
00:30:39,640 --> 00:30:42,640
Speaker 7: But that's not what's happening, right, That's the arms race.

541
00:30:42,680 --> 00:30:44,880
Speaker 6: You know, all these other countries around the world are

542
00:30:44,960 --> 00:30:48,640
Speaker 6: racing to develop their own state owned IP. That's not

543
00:30:48,680 --> 00:30:51,040
Speaker 6: what's happening. A lot of people are mad at me

544
00:30:51,200 --> 00:30:53,000
Speaker 6: for beating this drum, but I'm going to beat it

545
00:30:53,120 --> 00:30:57,200
Speaker 6: till I see that these questions are answered correctly. Elon Musk,

546
00:30:57,320 --> 00:30:59,959
Speaker 6: I fear the trumpet. You know, Trump advisors don't really

547
00:31:00,240 --> 00:31:05,520
Speaker 6: understand the technological issues raised by the way Elon Musk

548
00:31:05,640 --> 00:31:08,960
Speaker 6: is going about handling our data. Right, and so one

549
00:31:09,000 --> 00:31:12,040
Speaker 6: of the many things that I'm very worried about in

550
00:31:12,120 --> 00:31:16,640
Speaker 6: terms of cybersecurity and our own well being. In terms

551
00:31:16,640 --> 00:31:19,720
Speaker 6: of how Elon Musk and his team are handling our data,

552
00:31:20,520 --> 00:31:26,200
Speaker 6: is that he's using his AI, meaning his shareholders own it,

553
00:31:26,920 --> 00:31:30,960
Speaker 6: they are enriched by it. He has the patents. It's

554
00:31:31,000 --> 00:31:36,000
Speaker 6: not our AI, it's his company's AI. To us set

555
00:31:36,040 --> 00:31:40,400
Speaker 6: it onto our government data sets, these Christine beautiful pure

556
00:31:40,480 --> 00:31:43,360
Speaker 6: data sets that everyone in the tech world has been

557
00:31:43,480 --> 00:31:44,160
Speaker 6: lusting after.

558
00:31:44,680 --> 00:31:46,280
Speaker 7: So what does that do?

559
00:31:47,400 --> 00:31:51,080
Speaker 6: It enriches his AI beyond his competitors, right, It makes

560
00:31:51,120 --> 00:31:54,120
Speaker 6: it better immediately than his competitor's AI.

561
00:31:54,600 --> 00:31:56,040
Speaker 7: That's not the worst problem.

562
00:31:56,440 --> 00:31:59,000
Speaker 6: Now you've got to really understand that what AI does

563
00:31:59,160 --> 00:32:05,320
Speaker 6: is it liberates information a from any security, any privacy,

564
00:32:05,560 --> 00:32:10,000
Speaker 6: any restrictions, and B it makes it unaccountable.

565
00:32:10,640 --> 00:32:13,520
Speaker 7: Right liberates and there's no one accountable.

566
00:32:13,800 --> 00:32:17,160
Speaker 6: So what that means is if he eats, if his

567
00:32:17,360 --> 00:32:22,800
Speaker 6: AI consumes our government data sets at a at a touch.

568
00:32:23,200 --> 00:32:26,400
Speaker 7: He can see or the people with.

569
00:32:26,320 --> 00:32:31,240
Speaker 6: Whom he shares access to his AI can see at

570
00:32:31,240 --> 00:32:35,719
Speaker 6: a touch. You know, especially if the FBI, for instance,

571
00:32:35,760 --> 00:32:39,280
Speaker 6: answers his five questions, what are the undercover operations against

572
00:32:39,360 --> 00:32:41,480
Speaker 6: Chinese sleeper sells in the United States of America?

573
00:32:41,720 --> 00:32:43,240
Speaker 7: Boom, He can get that file.

574
00:32:43,360 --> 00:32:46,280
Speaker 6: He can hand it theoretically to China, or put it

575
00:32:46,320 --> 00:32:49,720
Speaker 6: in the dark web, or hand it over to our adversaries.

576
00:32:50,040 --> 00:32:52,000
Speaker 1: It well, we know, but hang up. But we know

577
00:32:52,160 --> 00:32:54,479
Speaker 1: we know that hang but we know that Cash brottel

578
00:32:54,800 --> 00:33:00,520
Speaker 1: at at at FBI, We know that John Recliffe CIA,

579
00:33:00,600 --> 00:33:02,600
Speaker 1: we know that Tulca gabbertt D and I, and we

580
00:33:02,680 --> 00:33:05,760
Speaker 1: know that Pete Hesith at Defense have not allowed that.

581
00:33:05,760 --> 00:33:09,040
Speaker 1: They've been pretty adamant about that. So this one I

582
00:33:09,120 --> 00:33:12,480
Speaker 1: understanding to go back hang on hang on. I want

583
00:33:12,480 --> 00:33:14,680
Speaker 1: to make sure people understand it. It's the if you

584
00:33:14,760 --> 00:33:19,120
Speaker 1: understand the construct, then you can understand the specifics. What

585
00:33:19,160 --> 00:33:22,360
Speaker 1: do you mean? Because this is kind of definitional right

586
00:33:23,520 --> 00:33:26,760
Speaker 1: the and you and I did not talk about this beforehand.

587
00:33:26,840 --> 00:33:28,920
Speaker 1: It was AI conference thing, So this is not and

588
00:33:29,040 --> 00:33:32,360
Speaker 1: people know I have severe disagreements with brother Musk and

589
00:33:32,440 --> 00:33:35,880
Speaker 1: it's it's along this line. But when you say liberate

590
00:33:36,120 --> 00:33:39,800
Speaker 1: and then what was your second term to unaccountable? Just

591
00:33:39,880 --> 00:33:42,560
Speaker 1: go back and hang on, you're moving to just just

592
00:33:42,560 --> 00:33:45,520
Speaker 1: go back? What do you mean by liberate data sets

593
00:33:45,600 --> 00:33:48,200
Speaker 1: or liberate information? What is that? What does that even mean?

594
00:33:49,280 --> 00:33:49,520
Speaker 7: Well?

595
00:33:49,720 --> 00:33:53,400
Speaker 6: I think we first identified one of the really scary

596
00:33:54,120 --> 00:33:58,280
Speaker 6: critical things, which is national security. Right. I mean, there

597
00:33:58,280 --> 00:34:00,600
Speaker 6: are a lot of reasons to keep information private in

598
00:34:00,600 --> 00:34:04,600
Speaker 6: the federal government, a lot of reasons like, for instance,

599
00:34:05,520 --> 00:34:06,960
Speaker 6: when the AI in chess.

600
00:34:07,000 --> 00:34:08,759
Speaker 1: Okay, but hang on, but hang but hang it, but

601
00:34:08,760 --> 00:34:11,480
Speaker 1: hang on hand but hang it. But let's assume it's

602
00:34:11,600 --> 00:34:14,879
Speaker 1: let's say, the national security I say not that. Let's say,

603
00:34:14,880 --> 00:34:18,200
Speaker 1: but if they get into hell. Bobby Kennedy has been

604
00:34:18,239 --> 00:34:23,279
Speaker 1: pretty open, surprisingly about HHS and complying and working with it.

605
00:34:23,320 --> 00:34:25,840
Speaker 1: What about HHS that's an era of expertise yours. What

606
00:34:25,880 --> 00:34:29,319
Speaker 1: about HHS. If Bobby Kennedy allows the AI guys in

607
00:34:29,360 --> 00:34:31,879
Speaker 1: the in the in the Doge guys, who on one hand,

608
00:34:31,880 --> 00:34:34,280
Speaker 1: I think are doing a very good job about exposing

609
00:34:34,280 --> 00:34:36,440
Speaker 1: a lot of stuff. Now my big complaint is, but

610
00:34:36,560 --> 00:34:39,120
Speaker 1: I haven't seen any numbers of what this waste, fraud

611
00:34:39,160 --> 00:34:42,520
Speaker 1: and abuse WFA really means. And as we come down

612
00:34:42,520 --> 00:34:45,239
Speaker 1: to the fourteenth that we don't see a hard number. Hey,

613
00:34:45,280 --> 00:34:47,799
Speaker 1: I'll put my investment banker head on. Then maybe it

614
00:34:47,800 --> 00:34:50,600
Speaker 1: doesn't exist. We need to see that number. But when

615
00:34:50,600 --> 00:34:54,319
Speaker 1: Bobby Kennedy, when Bobby Kennedy and Bobby's I think, has

616
00:34:54,320 --> 00:34:57,200
Speaker 1: said hey, come on over, you can help us out,

617
00:34:57,400 --> 00:34:59,120
Speaker 1: what does that mean If they're into a if they're

618
00:34:59,160 --> 00:35:01,640
Speaker 1: into health and humans services in NIH and all the

619
00:35:01,719 --> 00:35:04,000
Speaker 1: various apparatus of big pharm.

620
00:35:04,320 --> 00:35:05,920
Speaker 4: Ma'am right.

621
00:35:06,800 --> 00:35:08,799
Speaker 6: Well, I mean, first I want to stress there's a

622
00:35:08,840 --> 00:35:11,239
Speaker 6: way for Doge and Musk to do all of this

623
00:35:11,320 --> 00:35:15,200
Speaker 6: in a way that CyberSecure and avoids conflicts of interest,

624
00:35:15,360 --> 00:35:20,440
Speaker 6: has non competes and non disclosure agreements and proper cybersecurity protocols,

625
00:35:20,520 --> 00:35:24,000
Speaker 6: and also uses our AI which again we were building

626
00:35:24,080 --> 00:35:26,160
Speaker 6: I believe he pulled the plug on it as opposed

627
00:35:26,160 --> 00:35:26,879
Speaker 6: to his own AI.

628
00:35:27,120 --> 00:35:28,840
Speaker 7: Right, that's not what's happening.

629
00:35:28,880 --> 00:35:30,520
Speaker 6: So I just want to stress you could get all

630
00:35:30,520 --> 00:35:33,480
Speaker 6: the good headlines of musk finding the waste, fraud and

631
00:35:33,520 --> 00:35:37,840
Speaker 6: abuse and not put our national security and our Fourth Amendment,

632
00:35:37,960 --> 00:35:42,399
Speaker 6: privacy and other huge concerns at risk.

633
00:35:43,600 --> 00:35:47,120
Speaker 7: Let's go to HHS to here example. One of the

634
00:35:47,160 --> 00:35:48,880
Speaker 7: things I fully expect is.

635
00:35:48,800 --> 00:35:53,680
Speaker 6: That our Medicare and Medicaid records will be fed into

636
00:35:53,840 --> 00:36:00,799
Speaker 6: his AI application. So what that means is, certainly you

637
00:36:00,840 --> 00:36:05,160
Speaker 6: can see, you know, big trends.

638
00:36:05,200 --> 00:36:07,160
Speaker 7: You can do good modeling.

639
00:36:07,480 --> 00:36:10,640
Speaker 6: Again, that should be our AI that's enriched by those

640
00:36:10,920 --> 00:36:14,759
Speaker 6: what's called PII blind.

641
00:36:13,800 --> 00:36:16,839
Speaker 1: Hang on, hang on, slow slow down, slow down, slow down.

642
00:36:17,200 --> 00:36:20,160
Speaker 1: When you say our AI, when you say ARA, you

643
00:36:20,239 --> 00:36:24,120
Speaker 1: mean the United States government that theoretically is controlled by,

644
00:36:24,320 --> 00:36:28,680
Speaker 1: although not really American taxpayers. You're saying the Biden moonshot

645
00:36:28,760 --> 00:36:31,480
Speaker 1: when he changed the entire focus of the government onto

646
00:36:31,680 --> 00:36:34,640
Speaker 1: uh onto AI that Joe Allen went through. I think

647
00:36:34,640 --> 00:36:36,879
Speaker 1: it was two years ago when they signed the executive order.

648
00:36:36,920 --> 00:36:39,719
Speaker 1: They called it the cancer moonshot. That was a lie.

649
00:36:39,840 --> 00:36:43,360
Speaker 1: It was really about changing hol of government to supporting

650
00:36:43,440 --> 00:36:44,920
Speaker 1: artificial intelligence. Correct.

651
00:36:46,160 --> 00:36:48,920
Speaker 7: I don't know enough about that specifically.

652
00:36:49,400 --> 00:36:52,600
Speaker 6: What I do know is that developers in our government

653
00:36:52,640 --> 00:36:55,680
Speaker 6: were building our AI and that was put on pause,

654
00:36:56,040 --> 00:36:59,120
Speaker 6: as I understand by Elon Musk, and he applied his

655
00:36:59,160 --> 00:36:59,600
Speaker 6: own AI.

656
00:36:59,600 --> 00:37:01,920
Speaker 1: I don't know by the by hang on, hang on,

657
00:37:02,000 --> 00:37:03,719
Speaker 1: hang on. I don't know where you saw that. I

658
00:37:03,760 --> 00:37:06,360
Speaker 1: have no earthy idea. Is that is that publicly reported?

659
00:37:06,360 --> 00:37:09,560
Speaker 1: Can you cite a reference on that? Because the weapons

660
00:37:09,680 --> 00:37:11,960
Speaker 1: labs and the national labs, and yeah, I don't think

661
00:37:12,000 --> 00:37:14,719
Speaker 1: that's actually I don't think that's a fact. If it is,

662
00:37:14,880 --> 00:37:16,080
Speaker 1: come back to me, I want to have you on

663
00:37:16,080 --> 00:37:18,000
Speaker 1: Monday to talk about that. But I don't think that's

664
00:37:18,040 --> 00:37:20,120
Speaker 1: a fact at all. I have not heard at all

665
00:37:20,840 --> 00:37:23,960
Speaker 1: that we've paused any development on our own artificial intelligence

666
00:37:24,000 --> 00:37:25,759
Speaker 1: yet his so I don't want to. I want to

667
00:37:25,800 --> 00:37:29,080
Speaker 1: make sure you're you're inside the guardrails here, because people

668
00:37:29,200 --> 00:37:31,960
Speaker 1: just dismiss it out of hand. You may be cracked.

669
00:37:32,000 --> 00:37:34,719
Speaker 1: But I'm fairly close to this situation. I haven't heard

670
00:37:34,800 --> 00:37:36,520
Speaker 1: that at all, and I haven't heard any stand down

671
00:37:37,120 --> 00:37:38,640
Speaker 1: of any of the national labs.

672
00:37:38,640 --> 00:37:44,160
Speaker 9: The the the the oligarchs have said because of this

673
00:37:44,360 --> 00:37:48,200
Speaker 9: between Deep Seek and between UH and between it looks

674
00:37:48,200 --> 00:37:52,040
Speaker 9: like the fiasco of the of the of the blunt

675
00:37:52,160 --> 00:37:55,200
Speaker 9: force AI that we've had really with.

676
00:37:55,239 --> 00:37:57,600
Speaker 1: Chat GBT and all that. And really if Deep Seeks

677
00:37:57,719 --> 00:38:00,680
Speaker 1: not a Chinese SI out, but actually this is NI moment.

678
00:38:01,400 --> 00:38:04,480
Speaker 1: The Ola Garks and Silicon Valley, led by Indries and

679
00:38:04,560 --> 00:38:07,719
Speaker 1: led by others, have said they need essentially a bailout.

680
00:38:08,000 --> 00:38:12,319
Speaker 1: They need either a new Mercury program or a Marshall plan,

681
00:38:12,480 --> 00:38:15,040
Speaker 1: but they're talking about five hundred billion dollars. As part

682
00:38:15,120 --> 00:38:18,560
Speaker 1: of that, they are requesting that we turn over essentially

683
00:38:18,560 --> 00:38:21,120
Speaker 1: the weapons laboratories that make all the nuclear weapons at

684
00:38:21,160 --> 00:38:23,920
Speaker 1: San Dia and Laurence Livermore. You see, if you remember

685
00:38:23,960 --> 00:38:27,239
Speaker 1: the movie Oppenheimer r. Livermore is they want to turn

686
00:38:27,320 --> 00:38:29,560
Speaker 1: they want to turn the labs over where our most

687
00:38:29,600 --> 00:38:34,319
Speaker 1: advanced AI is being developed to their control of partnership

688
00:38:34,400 --> 00:38:36,360
Speaker 1: or joint venture or whatever. But that that is a

689
00:38:36,360 --> 00:38:38,440
Speaker 1: long way that has not been done. It's a long way,

690
00:38:38,440 --> 00:38:40,560
Speaker 1: and that's going to be a huge public debate. But continue,

691
00:38:40,600 --> 00:38:42,799
Speaker 1: We've got a couple of minutes here, and continue on

692
00:38:42,880 --> 00:38:43,840
Speaker 1: what you finish your argument.

693
00:38:46,640 --> 00:38:51,640
Speaker 6: So if it ingests our midicary and Medicaid data. Then

694
00:38:52,600 --> 00:38:57,160
Speaker 6: then our personal records are no longer private. Those two

695
00:38:57,440 --> 00:39:02,239
Speaker 6: are now part of externally privately owned AI and the

696
00:39:02,360 --> 00:39:06,040
Speaker 6: access you know, through that AI contracts.

697
00:39:06,120 --> 00:39:08,799
Speaker 7: Right, whoever owns the AI.

698
00:39:08,680 --> 00:39:11,680
Speaker 6: That is applied to the American government data set is

699
00:39:11,719 --> 00:39:14,960
Speaker 6: going to be more powerful than anyone in the economy

700
00:39:15,000 --> 00:39:18,840
Speaker 6: because they'll have the ownership of all of the contract

701
00:39:19,440 --> 00:39:23,040
Speaker 6: that are housed within the federal government. So that's the

702
00:39:23,200 --> 00:39:27,200
Speaker 6: kind of liberation of information outside of privacy and national

703
00:39:27,239 --> 00:39:32,600
Speaker 6: security guard rails that this implies or involves, as well

704
00:39:32,600 --> 00:39:35,680
Speaker 6: as just an incredible enrichment of that privately owned AI

705
00:39:35,840 --> 00:39:37,880
Speaker 6: compared to all of the AI. And then let me

706
00:39:37,880 --> 00:39:42,200
Speaker 6: talk about not accountable. The example that the Deloitte and

707
00:39:42,360 --> 00:39:45,799
Speaker 6: Microsoft people gave of the deployment of AI and how

708
00:39:46,280 --> 00:39:49,520
Speaker 6: awesome it would be included the deployment, you know, removal

709
00:39:49,520 --> 00:39:52,719
Speaker 6: of human nurses in a drug trial, right and the

710
00:39:52,760 --> 00:39:56,640
Speaker 6: replacement of those human nurses by digital nurses AI. And

711
00:39:56,719 --> 00:39:59,720
Speaker 6: the AI nurses would tell, you know, hundreds of people

712
00:39:59,719 --> 00:40:02,919
Speaker 6: in drug protocol, uh, how you know when to take

713
00:40:02,960 --> 00:40:07,440
Speaker 6: the pill, how much to take a monitor there ingesting

714
00:40:07,480 --> 00:40:09,560
Speaker 6: of the pill. So they were thrilled about this you

715
00:40:09,600 --> 00:40:11,680
Speaker 6: can do thousands and thousands of people in drug trial

716
00:40:11,680 --> 00:40:13,680
Speaker 6: with a digital nurse or an a I nurse as

717
00:40:13,719 --> 00:40:15,520
Speaker 6: opposed to a human nurse.

718
00:40:15,880 --> 00:40:18,240
Speaker 7: Well, that's the kind of refraction.

719
00:40:18,880 --> 00:40:21,600
Speaker 1: Naomi, Naomi, just just hang over for one second. We're

720
00:40:21,680 --> 00:40:23,600
Speaker 1: take a short break. We'll have you back over. In

721
00:40:23,680 --> 00:40:26,480
Speaker 1: the last segment, Naomi Wolf joins us from India. She's

722
00:40:26,520 --> 00:40:31,360
Speaker 1: at a major AI conference and uh, she's pretty shocked

723
00:40:31,360 --> 00:40:34,839
Speaker 1: what she's seeing behind the curtain. As one if your

724
00:40:34,960 --> 00:40:39,240
Speaker 1: rational human being would be shocked. Birch gold dot com

725
00:40:39,280 --> 00:40:42,480
Speaker 1: take your phone out right now. Text Bannon b A

726
00:40:42,600 --> 00:40:44,839
Speaker 1: n n O at nine eight nine eight nine eight,

727
00:40:45,239 --> 00:40:48,600
Speaker 1: get the free brochure investing in Gold in the Aero

728
00:40:48,719 --> 00:40:51,840
Speaker 1: Trump the Ultimate Guide, and you can talk to Philip

729
00:40:51,880 --> 00:40:54,880
Speaker 1: Patrick and the team short break back in the month, God.

730
00:41:00,920 --> 00:41:03,000
Speaker 3: Use your host Stephen k Back.

731
00:41:06,200 --> 00:41:09,120
Speaker 1: Okay, Naomi is going to put up on social media

732
00:41:09,160 --> 00:41:11,440
Speaker 1: all weekend. She's going to join us back here on Monday.

733
00:41:11,480 --> 00:41:13,280
Speaker 1: I take here, still be in India at that time.

734
00:41:13,440 --> 00:41:16,120
Speaker 1: We want obviously much more on this conference. It sounds

735
00:41:16,160 --> 00:41:19,600
Speaker 1: like and you were the very first ahead of it.

736
00:41:19,640 --> 00:41:22,520
Speaker 1: On the on the vaccine, on the on the on

737
00:41:22,560 --> 00:41:25,239
Speaker 1: the on the pandemic all of it. And uh, I

738
00:41:25,280 --> 00:41:27,440
Speaker 1: know you're head of the curve here. Where do people

739
00:41:27,480 --> 00:41:29,239
Speaker 1: go over the weekend to get to social media? And

740
00:41:29,239 --> 00:41:30,719
Speaker 1: then you're going to come back on Monday and we're

741
00:41:30,760 --> 00:41:33,520
Speaker 1: going to do this again because this is a massive

742
00:41:33,600 --> 00:41:36,960
Speaker 1: issue in the court. Obviously it has to be dealt

743
00:41:37,000 --> 00:41:39,520
Speaker 1: with now. So where do people go, Naomi to get

744
00:41:39,600 --> 00:41:41,920
Speaker 1: all your stuff you put up and to follow you

745
00:41:41,960 --> 00:41:43,000
Speaker 1: over the weekend? Ma'am?

746
00:41:43,960 --> 00:41:46,120
Speaker 7: Thank you so And I.

747
00:41:46,040 --> 00:41:48,880
Speaker 6: Do want to credit Cash Bettel and Telsea Gabbard and

748
00:41:48,920 --> 00:41:51,000
Speaker 6: the people including President Trump.

749
00:41:51,040 --> 00:41:53,920
Speaker 7: Who are you know standing up for.

750
00:41:53,960 --> 00:41:56,600
Speaker 6: Confidentiality and security of our of our data and our

751
00:41:56,680 --> 00:42:00,960
Speaker 6: national security secrets. I am at Daily out dot io.

752
00:42:01,200 --> 00:42:07,040
Speaker 6: Please support independent journalism. And I'm also over on substack.

753
00:42:07,400 --> 00:42:10,560
Speaker 6: My substack is Outspoken and you can find me at

754
00:42:10,640 --> 00:42:14,440
Speaker 6: naomere wolf, on x and on social media.

755
00:42:14,560 --> 00:42:17,080
Speaker 1: Are you are you outspoken? I didn't know that real quickly,

756
00:42:17,160 --> 00:42:20,200
Speaker 1: just give me sixty seconds. Why are data sets like

757
00:42:20,360 --> 00:42:22,839
Speaker 1: oxygen when you talk about artificial intelligence? Just want make

758
00:42:22,840 --> 00:42:25,200
Speaker 1: sure that we've done the war room a lot of

759
00:42:25,280 --> 00:42:28,760
Speaker 1: number two pencil work today. Why you keep saying data sets?

760
00:42:28,840 --> 00:42:32,120
Speaker 1: Why are data sets like oxygen when it comes to

761
00:42:32,200 --> 00:42:34,040
Speaker 1: artificial intelligence, ma'am.

762
00:42:34,400 --> 00:42:36,960
Speaker 6: Yeah, like oxygen are like gold as the metaphor people

763
00:42:37,000 --> 00:42:37,439
Speaker 6: are using.

764
00:42:37,560 --> 00:42:40,960
Speaker 7: Okay, so it's AI.

765
00:42:41,440 --> 00:42:46,600
Speaker 6: Is learns, right, and it gets better and better by learning,

766
00:42:47,080 --> 00:42:49,200
Speaker 6: and it learns from the data.

767
00:42:48,960 --> 00:42:53,480
Speaker 7: That it eats or ingests essentially right. So if it's.

768
00:42:53,640 --> 00:42:58,080
Speaker 6: Reading blogs and gossip online, it's only going to be

769
00:42:58,120 --> 00:43:01,520
Speaker 6: as good or as factual as the and gossip online, right.

770
00:43:01,520 --> 00:43:05,399
Speaker 6: It can't get better or smarter than that, even as

771
00:43:05,440 --> 00:43:11,840
Speaker 6: it evolves. However, if it's reading this pristine, beautiful, mostly

772
00:43:11,880 --> 00:43:16,000
Speaker 6: accurate that the United States government holds like Fort Knox,

773
00:43:16,440 --> 00:43:21,359
Speaker 6: you know, with a lot of late security than it,

774
00:43:21,360 --> 00:43:25,360
Speaker 6: it becomes the most powerful superman.

775
00:43:24,719 --> 00:43:29,520
Speaker 1: A super super a ma'am. Thank you very much. We'll

776
00:43:29,520 --> 00:43:32,560
Speaker 1: look for you, sticking to you all weekend on your

777
00:43:32,560 --> 00:43:34,759
Speaker 1: sub stack and on Twitter, and we look forward to

778
00:43:34,760 --> 00:43:38,359
Speaker 1: having you back here on Monday, and we will live

779
00:43:38,400 --> 00:43:40,680
Speaker 1: from India. Thank you, ma'am, and say hi to our

780
00:43:40,800 --> 00:43:44,279
Speaker 1: favorite Mari Monahan who knows over there with you.

781
00:43:45,120 --> 00:43:46,520
Speaker 7: Thank you so much, Steve Right.

782
00:43:46,440 --> 00:43:50,680
Speaker 1: India, Love you guys, Love you guys. Uh comstock brother

783
00:43:50,719 --> 00:43:53,239
Speaker 1: Comstock you were a home run your state. People have

784
00:43:53,280 --> 00:43:54,920
Speaker 1: blown my phone up all day they want to know

785
00:43:54,960 --> 00:43:58,600
Speaker 1: more about Sacred Human health hit it brother, Sure.

786
00:43:58,520 --> 00:44:01,000
Speaker 8: Yeah, I appreciate you having me on once again, Steve, And

787
00:44:01,160 --> 00:44:03,120
Speaker 8: today I just wanted to highlight one of our more

788
00:44:03,160 --> 00:44:06,080
Speaker 8: popular products that we've also had great.

789
00:44:05,920 --> 00:44:08,240
Speaker 2: Feedback on, which is our natural Sleep formula.

790
00:44:09,000 --> 00:44:12,080
Speaker 8: And what's unique about this product is that it's derived

791
00:44:12,080 --> 00:44:15,799
Speaker 8: from four natural elements and completely free of melatonin, So

792
00:44:16,360 --> 00:44:19,040
Speaker 8: all four of our ingredients actually work together to naturally

793
00:44:19,080 --> 00:44:22,120
Speaker 8: commune before bed as well as keep you asleep during

794
00:44:22,120 --> 00:44:24,959
Speaker 8: the night, So it will also prevent you from waking

795
00:44:25,040 --> 00:44:28,160
Speaker 8: up without that groggy feeling that people often get when

796
00:44:28,200 --> 00:44:34,400
Speaker 8: taking melatonin or prescription type medications. And when we created

797
00:44:34,400 --> 00:44:37,839
Speaker 8: this product, we were really searching for or at least

798
00:44:37,840 --> 00:44:39,720
Speaker 8: within the market, to see what else was out there

799
00:44:40,480 --> 00:44:43,680
Speaker 8: that was natural, and unfortunately, most of what we found

800
00:44:43,760 --> 00:44:47,279
Speaker 8: were products that were advertised as natural sleep formulas, but

801
00:44:47,560 --> 00:44:51,440
Speaker 8: most of them had melatonin added or just other preservatives

802
00:44:51,480 --> 00:44:53,520
Speaker 8: and chemicals that aren't ideal for health.

803
00:44:54,239 --> 00:44:57,359
Speaker 2: So also the issue with regular.

804
00:44:57,120 --> 00:44:59,680
Speaker 8: Use of melatonin is that it can actually reduce your

805
00:44:59,680 --> 00:45:04,800
Speaker 8: bodies ability to naturally produce malotonin, making you more dependent

806
00:45:04,840 --> 00:45:08,480
Speaker 8: on the supplement over time. So Sacred Human we really

807
00:45:08,520 --> 00:45:11,280
Speaker 8: just wanted to stick with the natural elements that benefit

808
00:45:11,320 --> 00:45:14,799
Speaker 8: your sleep, but don't get you hooked on them. So again,

809
00:45:14,840 --> 00:45:21,799
Speaker 8: these foreign ingredients include magnesium, glycinate, glycine, alteening apogenin which

810
00:45:21,880 --> 00:45:25,640
Speaker 8: synergistically work together to naturally upgrade your sleep. So if

811
00:45:25,680 --> 00:45:28,240
Speaker 8: you are struggling with sleep, I always recommend this product,

812
00:45:28,280 --> 00:45:29,719
Speaker 8: and I know a lot of our customers have had

813
00:45:29,760 --> 00:45:33,319
Speaker 8: great success with it as well. So and of course

814
00:45:33,480 --> 00:45:36,880
Speaker 8: our promises will always provide these products and an affordable price.

815
00:45:36,760 --> 00:45:39,319
Speaker 2: And make sure that everything's produced right here in the USA.

816
00:45:39,719 --> 00:45:44,560
Speaker 1: So on top of everything everything we do. Yeah, yeah, no,

817
00:45:44,600 --> 00:45:46,799
Speaker 1: I was just sure committed to do when you guys

818
00:45:47,000 --> 00:45:48,440
Speaker 1: go ahead, sir, Yeah.

819
00:45:48,320 --> 00:45:49,759
Speaker 8: Yeah, no, it's been mean to cut you off, but

820
00:45:49,840 --> 00:45:51,400
Speaker 8: I did really just want to say thank you to

821
00:45:51,480 --> 00:45:53,600
Speaker 8: the war room because we did get our start here

822
00:45:53,600 --> 00:45:56,400
Speaker 8: as a business. We wouldn't be here without you, and

823
00:45:57,480 --> 00:45:59,560
Speaker 8: the MAHA movements really starting to come alive, and we're

824
00:45:59,600 --> 00:46:00,520
Speaker 8: excited to be a part of it.

825
00:46:03,000 --> 00:46:05,239
Speaker 1: I want read all the reviews where do they go

826
00:46:05,480 --> 00:46:07,800
Speaker 1: right now? Because I know it's gonna be interesting yesterday

827
00:46:07,880 --> 00:46:10,200
Speaker 1: to pile into here and see all the different products,

828
00:46:10,200 --> 00:46:12,720
Speaker 1: including the grass fed beef liver, which is my baby.

829
00:46:13,200 --> 00:46:14,000
Speaker 1: Where do they go? Sir?

830
00:46:14,520 --> 00:46:16,640
Speaker 8: Yeah, of course you can go to Sacred Humanhealth dot

831
00:46:16,760 --> 00:46:19,759
Speaker 8: com or just plug in Sacred humanto Google. You can

832
00:46:19,880 --> 00:46:22,560
Speaker 8: use code warm for ten percent off any one time purchase.

833
00:46:22,800 --> 00:46:25,200
Speaker 8: If you do subscribe, you're locked into that ten percent

834
00:46:25,320 --> 00:46:28,239
Speaker 8: discount and you can cancel it anytime as well, so

835
00:46:28,280 --> 00:46:28,920
Speaker 8: don't worry about that.

836
00:46:29,920 --> 00:46:31,399
Speaker 2: But yeah, a ton of information on the site.

837
00:46:31,400 --> 00:46:33,520
Speaker 8: You can sip through the reviews, click on each product

838
00:46:33,520 --> 00:46:36,360
Speaker 8: and see the different ingredients and what value they provide

839
00:46:36,360 --> 00:46:38,000
Speaker 8: as well as of overall benefits.

840
00:46:40,000 --> 00:46:44,719
Speaker 1: Thank you, sir, Trevor Comstock found you and CEO of

841
00:46:44,840 --> 00:46:48,000
Speaker 1: Sacred Human Health, Thank you, sir. You guys will love it.

842
00:46:48,080 --> 00:46:50,000
Speaker 1: Go check it out today. Get on the site, check

843
00:46:50,080 --> 00:46:52,880
Speaker 1: out all the information the reviews, particularly from war Imposse.

844
00:46:53,760 --> 00:46:55,279
Speaker 1: The best thing to sell is to make sure you

845
00:46:55,360 --> 00:46:57,319
Speaker 1: talk to warrem possible and say, hey, how was that thing?

846
00:46:57,560 --> 00:47:01,239
Speaker 1: Was great? Okay cool, let me check it out. We're

847
00:47:01,280 --> 00:47:03,200
Speaker 1: going to be up all weekend on social media. I'll

848
00:47:03,239 --> 00:47:06,160
Speaker 1: be on get her Grace, the Queen of the Trolls,

849
00:47:06,160 --> 00:47:09,160
Speaker 1: will be up on Twitter and other platforms. She's also

850
00:47:09,239 --> 00:47:12,359
Speaker 1: on getter Moby up all weekend we're working all weekend here.

851
00:47:12,480 --> 00:47:15,520
Speaker 1: President Trump's working all weekend. Check it out. Another guy's

852
00:47:15,560 --> 00:47:19,399
Speaker 1: twenty four to seven is Mike Lindell, and he's still

853
00:47:19,440 --> 00:47:21,400
Speaker 1: in business. They ain't shut him down now, so he's

854
00:47:21,400 --> 00:47:23,279
Speaker 1: still got pillows of What do you got for us?

855
00:47:23,360 --> 00:47:23,600
Speaker 3: Brother?

856
00:47:24,320 --> 00:47:27,239
Speaker 10: You guys, this is this last weekend here where all

857
00:47:27,320 --> 00:47:29,120
Speaker 10: the all our specials collide.

858
00:47:29,160 --> 00:47:30,880
Speaker 3: And it's only for the Warmorm polse.

859
00:47:31,360 --> 00:47:34,800
Speaker 10: It's the warm Room free free sales, so you're getting

860
00:47:34,880 --> 00:47:36,560
Speaker 10: free shipping on your entire order.

861
00:47:37,200 --> 00:47:39,760
Speaker 1: We still the nine to ninety eight pillows, you guys.

862
00:47:40,280 --> 00:47:42,799
Speaker 1: When they're gone, they're gone. Nine dollars and ninety cents.

863
00:47:42,880 --> 00:47:45,520
Speaker 10: That's to my pillow two point zero your choice of

864
00:47:45,640 --> 00:47:48,719
Speaker 10: pillow case a limit of fifteen. Now, if you go

865
00:47:48,800 --> 00:47:52,359
Speaker 10: to the website, remember free shipping on your entire order

866
00:47:52,440 --> 00:47:55,120
Speaker 10: promo code Warroom. You have the blanket sale up to

867
00:47:55,200 --> 00:47:58,440
Speaker 10: eighty percent of but if your orders going one hundred

868
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Speaker 10: dollars or more, I'm going to ship you two free

869
00:48:00,640 --> 00:48:03,560
Speaker 10: my pillow bed pillows. So it's the free pre all

870
00:48:03,600 --> 00:48:06,520
Speaker 10: these specials have collided. I'm gonna be making a new

871
00:48:06,600 --> 00:48:09,879
Speaker 10: commercial this week, going back to Minnesota. The Warroom gets

872
00:48:09,920 --> 00:48:13,880
Speaker 10: all the old specials, news specials, and exclusive specials. So

873
00:48:14,040 --> 00:48:17,640
Speaker 10: you guys check get the beds and the mattress coppers

874
00:48:18,000 --> 00:48:20,960
Speaker 10: made in the USA. Get them now with the free

875
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Speaker 10: shipping promo Code war Room.

876
00:48:24,760 --> 00:48:27,960
Speaker 1: He's got other media guys and podcasters bitching at him.

877
00:48:27,960 --> 00:48:30,520
Speaker 1: Why are you giving the war room posse all the

878
00:48:30,640 --> 00:48:35,760
Speaker 1: deals MyPillow dot com promo Code Warroom get the best deals.

879
00:48:35,840 --> 00:48:39,600
Speaker 1: Mike Lindale has love your brother. See you Monday. Have

880
00:48:39,680 --> 00:48:43,120
Speaker 1: a great weekend. I'll be up on Getter non stop.

881
00:48:43,239 --> 00:48:46,319
Speaker 1: There's so much going on. We'll see you Monday morning

882
00:48:46,520 --> 00:48:49,640
Speaker 1: ten am Eastern Standard Time, when you will be back

883
00:48:51,160 --> 00:48:51,759
Speaker 1: in the war Room