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Speaker 1: Hey, guys, Saga and Crystal here.

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Speaker 2: Independent media just played a truly massive role in this election,

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Speaker 2: and we are so excited about what that means for

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Speaker 2: the future of the show.

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Speaker 3: This is the only place where you can find honest

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Speaker 3: perspectives from the left and the right that simply does

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Speaker 3: not exist anywhere else.

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Speaker 2: So if that is something that's important to you, please

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Speaker 2: go to Breakingpoints dot com. Become a member today and

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Speaker 2: and all put together for you every morning in your inbox.

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Speaker 3: We need your help to build the future of independent

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Speaker 3: news media and we hope to see you at Breakingpoints

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Speaker 3: dot com. Turning now to censorship, there's a lot of

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Speaker 3: stuff going on whenever it comes to censorship of anybody

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Speaker 3: who's remotely challenges the Israel consensus here in the US,

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Speaker 3: The CEO of the ADL, Jonathan Greenblatt, now saying that

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Speaker 3: there are AI automatic versions to try and to monitor

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Speaker 3: any alleged act of anti Semitism, using AI to report

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Speaker 3: it to lawyers, to prosecute, to criminalize, and to go

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Speaker 3: after anybody who criticizes the state of Israel.

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Speaker 1: Here's what he had to say.

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Speaker 4: We created something called the Legal Action Network. We've assembled

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Speaker 4: fifty of the top law firms in the United States

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Speaker 4: to create a pro bono cortery of literally like fifty

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Speaker 4: thousand lawyers. And so now when you enter in an

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Speaker 4: incident at ADL, it instantly gets evaluated by our AI systems.

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Speaker 4: Is there a litigation opportunity? And we feed it to

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Speaker 4: the lawyers to evaluate and to find someone to take

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Speaker 4: the case. So it used to be there again, if

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Speaker 4: you had a problem, you picked up the phone and

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Speaker 4: called ADL, and it took us days and days to

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Speaker 4: get back to you. Remember I told you thirty one

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Speaker 4: thousand reports. Now, using generative AI, I am responding instantly.

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Speaker 4: And if you enter that something happened to you. For example,

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Speaker 4: say your kid got bullied at middle or your kid

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Speaker 4: had a teacher at middle school, a social studies teacher

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Speaker 4: who again this oppress or oppressed craziness and held out

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Speaker 4: your kid. You enter it in and our GENAI can

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Speaker 4: literally on the spot generate a letter for you to say,

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Speaker 4: send to LAUSD. That will automatically. Okay, this is the

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Speaker 4: chairman of the Board of Education, This is the Superintendent

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Speaker 4: of schools. This is the name of the principle of

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Speaker 4: that specific school will generate the letter real time and

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Speaker 4: send it out for you and at the same time

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Speaker 4: launch a petition that we can push to the city

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Speaker 4: council and so on and so forth.

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Speaker 1: Wow.

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Speaker 3: Jenai working with lawyers, fifty thousand lawyers, the Legal Action Network,

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Speaker 3: the Panopticon, Yeah, the literal Panopticon, Surveillance, private surveillance state,

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Speaker 3: which is working behind the scenes, and just to go

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Speaker 3: and show everybody. We just had a long debate about

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Speaker 3: the role of you know, public life, law enforcement, and churches.

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Speaker 3: One of the things that we at least generally kind

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Speaker 3: of agreed on was this idea of the First Amendment

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Speaker 3: and of expressing yourself without being visited, without being visited

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Speaker 3: by police officers. As we often look at videos in

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Speaker 3: the UK or in Germany when people privately post something,

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Speaker 3: let's say, on Facebook and gives it visits from the authority,

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Speaker 3: You're never like you truly will not leave where you're

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Speaker 3: about to see. The mayor of Miami Beach sent police officers,

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Speaker 3: taxpayer dollar police officers to the home of a private

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Speaker 3: US citizen after she criticized the mayor on Facebook over

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Speaker 3: his pro Israel stance.

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Speaker 1: Let's watch the video.

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Speaker 4: Picture to make sure it's your order.

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Speaker 3: Not sure, okay, all right?

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Speaker 1: Thanks?

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Speaker 4: Is that your account?

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Speaker 1: I refuse to answer questions without my lawyer president, so

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Speaker 1: I really don't know how to answer that.

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Speaker 2: Like I said, America, I agree, we're just trying to

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Speaker 2: see that you we're not talking to the right person.

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Speaker 2: We want to go see the right help you.

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Speaker 4: So pretty much, it's just a statement that was made

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Speaker 4: as far as you know, uh.

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Speaker 5: Says the guy who consistently calls for the death of

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Speaker 5: all Palestinians, tried to shut down the theater for showing

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Speaker 5: a movie that hurt his feelings and refuses to stand

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Speaker 5: up for.

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Speaker 1: The ol g bt Q community in any way.

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Speaker 5: Even leave the room when they vote, and on related matters,

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Speaker 5: one to know that you're all welcome clown face, clown

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Speaker 5: face confidence. Pretty you know, I'm not going to answer

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Speaker 5: whether that's me or not. Okay, the concerning part and

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Speaker 5: not concerning for the person who's posting it. Well, we're

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Speaker 5: just trying to preventage somebody else getting agitated or or

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Speaker 5: or agreeing with the statement. We're not saying it's true

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Speaker 5: or not. That guy who consistently calls for the death

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Speaker 5: of our Palestinians that can probably intact somebody to do

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Speaker 5: something radical. That's all we're here to talk about, and

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Speaker 5: we wanted to get your side of it. Was you

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Speaker 5: that posted that to I would think to refrain from

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Speaker 5: posting things like that because that could get something. I

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Speaker 5: appreciate your concern. I appreciate you coming out here. We're

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Speaker 5: going to maintain my Amendment rights to.

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Speaker 1: Not answer the question.

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Speaker 6: I appreciate it.

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Speaker 7: You you as well.

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Speaker 3: Thank you, take care shout out to this She handled

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Speaker 3: that exactly. Nothing to say to you without in the

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Speaker 3: presence of a lawyer. Let's can we reiterate this post.

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Speaker 3: This is the post that she was sent a police

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Speaker 3: officer to her door. The guy who consistently calls for

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Speaker 3: the death of all Palestidians, tried to shut down a

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Speaker 3: theater for showing a movie that hurt his feelings and

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Speaker 3: refuses to stand up for the LGBTQ community in any way,

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Speaker 3: even leaves the room when they vote on related matters.

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Speaker 1: Wants you to know that you are all welcome here.

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Speaker 3: Clown clown clown, that is what she said, standard shit

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Speaker 3: lib stuff, and I just.

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Speaker 2: Sent It's just a lefty post, that's it. I mean,

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Speaker 2: there's no even implied threat and nothing.

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Speaker 1: It's just a post.

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Speaker 3: And I just made a whole diatribe about liberal protest

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Speaker 3: culture and all that. However, what I do accept is

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Speaker 3: we do need to live together in some respect, and yes,

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Speaker 3: even cringe posting on the Internet in any respect is

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Speaker 3: deeply accepted, especially whenever it is about a mayor. I mean,

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Speaker 3: it's just so insane because this, this, and this. You know,

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Speaker 3: I just talked about the normalization of crazy norms. This

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Speaker 3: is the part of the issue we are watching. The

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Speaker 3: normalization just is rapidly getting stepped up.

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Speaker 1: Here.

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Speaker 3: We can all debate on when it all started, but

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Speaker 3: especially whenever it comes to politically sensitive speech targeted at

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Speaker 3: public officials, and by breaking open that you have created

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Speaker 3: an environment here where I mean, even being visited by

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Speaker 3: a police officer is the definition of chilling. Whenever it

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Speaker 3: comes to political space, there's no getting around it.

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Speaker 1: Like period, end of story. This is a local matter.

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Speaker 3: Where as a citizen you have every right to be

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Speaker 3: able to criticize your public officials. And this is the

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Speaker 3: fundamental problem is that with AI and you have like

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Speaker 3: let's say corporate censorship legal let's say harassment was probably

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Speaker 3: call it that. On top of multiple locality, state and

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Speaker 3: now federal whenever it comes to the Trump administration of

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Speaker 3: the DOJ, well, this becomes like a full on entity.

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Speaker 3: I just spent all this time criticizing BLM, which I

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Speaker 3: believed embodied that for multiple times during the Biden years

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Speaker 3: and under democratic presidencies. Well, I think this has now

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Speaker 3: effectively happen with the so called anti Semitism industrial complex,

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Speaker 3: where the DOJ, the ADL, and these mayors, local cops,

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Speaker 3: and lawyers all together are creating the exact same effect here. Yeah,

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Speaker 3: and that's really dangerous.

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Speaker 2: And once you accept it. For so they the way

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Speaker 2: they started was with pro Palestinian protesters who were immigrancy

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Speaker 2: had mak Mukhalil, who was a Green card holder, but

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Speaker 2: you know, he was the first high profile one that

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Speaker 2: they went after, and they felt like the combination of

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Speaker 2: pro Palestine speech plus immigrant status was like the lowest

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Speaker 2: hanging fruit. And they've expanded out from there, so it

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Speaker 2: doesn't stay with pro Palestinian speech. And that's why you

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Speaker 2: know this memo that Ken Klipstein is reported on that

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Speaker 2: classifies anyone who is anti capitalist, anti Christian protests that

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Speaker 2: they're all considered domestic terrorists. What is to stop them

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Speaker 2: from coming to your door? If you just post something critical,

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Speaker 2: anti capitalist about the administration, that is the predicate that's

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Speaker 2: being set to your point though, I mean, this is

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Speaker 2: the way the federal government has focused on this. Pam

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Speaker 2: Bondi spoke at this Israeli American Council proudly telling the

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Speaker 2: story of how she got involved in this school matter

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Speaker 2: at Florida State where I don't know if you guys

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Speaker 2: remember this. I think we played it and talked about

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Speaker 2: it on the Shoe There's School of the School the

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Speaker 2: show There we go. There was a guy who had

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Speaker 2: an IDF T shirt on in the gym. There was

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Speaker 2: a lady who came up to him. I think she did,

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Speaker 2: you know, put her hand on him. But they made

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Speaker 2: it like, oh my god, he was assaulted. Blah blah

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Speaker 2: blah blah blah. And the federal government got involved in

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Speaker 2: this frickin thing. And now Pam Bondi is out lying

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Speaker 2: about the incident and bragging about it. Let's take a

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Speaker 2: listen to that.

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Speaker 6: I want to tell you a story right here in Florida.

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Speaker 6: You've probably heard of it. It's not a crime of

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Speaker 6: great violence, but in my opinion, it's a crime of

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Speaker 6: great significance. I give college presidents my personal self and

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Speaker 6: I say, if you need anything, call me. My phone

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Speaker 6: rang one day. I was sitting in an office and

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Speaker 6: it was the president of Florida State University and he said,

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Speaker 6: something just happened. Yeah, a young woman, a student, through

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Speaker 6: her phone cursed attacked a young student, a young man,

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Speaker 6: a male student, who was playing basketball because he was

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Speaker 6: wearing an id up shirt. She was a student, he

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Speaker 6: was a student. I spent the next few hours on

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Speaker 6: the phone. I call my US attorney, I call the

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Speaker 6: state attorney, call law enforcement. And I guess she saw

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Speaker 6: it went through the system as it should, and she

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Speaker 6: now has kicked out a Florida State University. But little

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Speaker 6: things are the big things, and do sends a strong

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Speaker 6: message that you can't behave that way anymore in our country.

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Speaker 2: So rather than working on I don't know, maybe like

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Speaker 2: releasing that ein files, instead, the Attorney General of the

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Speaker 2: United States of America is spending hours of her time

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Speaker 2: to get this college student kicked out for this genuinely

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Speaker 2: minor incident. And in fraction, she.

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Speaker 3: Tweeted about it instantly whenever it happened. Yeah, we covered

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Speaker 3: it all here at the time. You're exactly right whenever

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Speaker 3: it comes to the Epstein's story and why so many

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Speaker 3: people are so upset about their handling of it. They

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Speaker 3: can do whatever they want when they want to. Don't

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Speaker 3: forget that coffee shop incident. That actually that one really

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Speaker 3: gets me more than anyone, because we're talking about they

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Speaker 3: had whatever right.

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Speaker 1: It was a distasteful name. I wouldn't have done the name.

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Speaker 3: We can criticize the tactic, Okay, however, you're a private business.

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Speaker 3: And what ended up happening was like some alleged discrimination,

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Speaker 3: and the DOJ was like, we're going to sue this

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Speaker 3: coffee shop down into the ground, right using federal civil

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Speaker 3: rights raw, federal civil rights rights law over what is

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Speaker 3: obviously a local incident. And in that case, in particular,

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Speaker 3: what they were doing is trying to make this message

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Speaker 3: that it's only going to be on the side of

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Speaker 3: pro Israel activism. The one thing that we did also

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Speaker 3: want to show everybody is this Miriam Adelson question where

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Speaker 3: she was asked at this conference, how do you buy

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Speaker 3: an exercise influence over politicians in the US, And she

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Speaker 3: gets very squarely.

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Speaker 1: Let's take a lesson Miri.

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Speaker 7: You and Sheldon created a lot of relationship over the

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Speaker 7: years with politicians at the state level, especially at the

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Speaker 7: federal level. I want you to share with everyone why

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Speaker 7: is it so important? And how do you do it? Again,

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Speaker 7: writing checks is part of it, but there is more

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Speaker 7: than writing just checks. So how do you do it?

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Speaker 1: Can you allow me not to answer?

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Speaker 7: You choose?

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Speaker 4: I want to be truthful, and there are so many

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Speaker 4: things that I don't want to talk about.

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Speaker 7: Yeah, I mean, we don't want specific but that's okay.

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Speaker 2: Wow, incredible, that all incredible. He asked the same question

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Speaker 2: the other guys sitting there. Who's a billionaire? Heim Saban

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Speaker 2: I think is his name, And he also was like, yeah,

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Speaker 2: I don't really want to get into that, yeah, because.

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Speaker 3: You know, it would be too distasteful for us to

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Speaker 3: all hear out of the mouth of what kind of.

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Speaker 1: People our leaders are.

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Speaker 3: It's disgusting, terrible to me, it's just amazing they still

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Speaker 3: hold these conferences if cameras don't cameras and microphones don't exist,

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Speaker 3: So it's just it's it's I don't know. At the

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Speaker 3: same time, it's crazy and it feels crushing on the other.

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Speaker 3: At the you know, we do have a moment of

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Speaker 3: more heightened awareness and people around this issue that the

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Speaker 3: propaganda has never worked more than ever, So maybe in

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Speaker 3: the long run it will all work out.

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Speaker 2: So John Sapiro, who is the governor of Pennsylvania and

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Speaker 2: who was famously vetted to be a potential VP pick

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Speaker 2: for Kamala Harris, and there's been all kinds of talk

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Speaker 2: of him potential twenty twenty eight contender. He's popular in

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Speaker 2: the state of Pennsylvania, Will you know, certainly give him that.

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Speaker 2: He is now out with the book where he talks

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Speaker 2: about how upset he was about the VP vetting process.

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Speaker 2: And by the way, for context here, what the Harris

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Speaker 2: people had put out about why they didn't want Josh

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Speaker 2: Shapiro on the ticket was that he seemed more about

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Speaker 2: like himself. He was like measuring the drapes, very way

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Speaker 2: too ambitious and not a team player. And I have

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Speaker 2: to say that they look pretty vindicated with these with

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Speaker 2: what he's putting out now about how this process went.

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Speaker 2: In any case, what he was particularly upset about put

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Speaker 2: this up on the screen is they apparently asked him

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Speaker 2: if he had been a double agent for Israel. Quote

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Speaker 2: was she kidding? I told her how offensive the question was. Okay,

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Speaker 2: So let's keep in mind that Josh Shapiro, by his

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Speaker 2: own words, volunteered with the IDF, wrote, you know, has

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Speaker 2: written all kinds of like pretty wild anti Palestinian stuff.

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Speaker 2: He also worked for a while in information, like in

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Speaker 2: public affairs at the Israeli embassy. So it would honestly

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Speaker 2: be irresponsible not to ask whether it was Israel or

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Speaker 2: any other country. You worked for their military and you

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Speaker 2: worked for their embassy. It is incumbent on you. If

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Speaker 2: you're going to be Vice president of the United States,

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Speaker 2: you have to answer that question. We also have now

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Speaker 2: gotten information that they asked Tim Wallas the same question,

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Speaker 2: by the way, about China, because he had had extensive

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Speaker 2: time in China and some you know, I can't remember

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Speaker 2: all there was like an entanglement with someone who was

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Speaker 2: a Chinese official.

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Speaker 1: Whatever, or it was genuinely weird, like he did spend

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Speaker 1: a lot of time in China.

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Speaker 2: Yeah, he did. He spent a lot of time, So

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Speaker 2: they asked him the same question. So it's not like

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Speaker 2: they were just like picking on Josh Shapiro. But that

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Speaker 2: is the way that he took it. Let's put d

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Speaker 2: two up on the screen, so he says their discussion

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Speaker 2: was especially tense when Harris asked Shapiro if he would

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Speaker 2: apologize for some of his comments about protesters at the

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Speaker 2: University of Pennsylvania, ho had built encampments to decry Israel's

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Speaker 2: military campaign in Gaza. He was very aggressive in terms

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Speaker 2: of the democratic side and like, you know, condemning the

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Speaker 2: protester and cracking down on them as governor of the state.

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Speaker 2: This one also just like sort of cracked me up.

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Speaker 2: The other thing he complained about was that their questions

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Speaker 2: were not substantive. Put the next one up on the screen.

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Speaker 2: He said, it nagged at me that their questions weren't

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Speaker 2: really about substance, he wrote, Rather, they were questioning my ideology,

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Speaker 2: my approach, and my worldview. That seems pretty substantive, Like

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Speaker 2: what are we talking about? Weren't about substance? What was

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Speaker 2: he expecting them to ask? It was out of bounds

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Speaker 2: that they wanted to know about his ideology, his approach,

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Speaker 2: and his worldview. Kind of kind of wild. And then

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Speaker 2: let's put the last one up on the screen. So

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Speaker 2: this is Harris, he wrote, described her own experience as

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Speaker 2: vice president, Stark term saying she had a rough time

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Speaker 2: in a position that had little autonomy or executive authority.

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Speaker 2: I was surprised by how much she seemed to dislike

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Speaker 2: the role, he wrote. She noted her chief of staff

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Speaker 2: would be giving me my directions, lamented that the vice

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Speaker 2: president didn't have a private bathroom in their office, and

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Speaker 2: how difficult it was for her at times not to

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Speaker 2: have a voice in the decision. And I believe that

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Speaker 2: that Kamala was not happy in that role. And you

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Speaker 2: know there were lots of leaks to that effect during

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Speaker 2: the Biden administration. But pretty, I mean, this is pretty.

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Speaker 1: There's no heroes.

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Speaker 2: Incredibly, of course not. Yeah, I mean this is incredibly

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Speaker 2: lame from Josh Shapiro though, and like I said, really

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Speaker 2: does sort of validate the reasons that the Hairs team

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Speaker 2: had given for why he wasn't ultimately picked.

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Speaker 3: Well, yeah, I don't know, because at the same time,

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Speaker 3: I think, in retrospect, I think Walts was a disastrous pick.

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Speaker 3: He was a horrible debate. He basically brought nothing to

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Speaker 3: the ticket.

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Speaker 1: Look at him.

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Speaker 3: I mean he's so weak that he has to basically

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Speaker 3: drop out of the race. Immediately and can't even defend

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Speaker 3: his own record in the state. And even now with

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Speaker 3: the way he's handling Minnesota, I don't think any even

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Speaker 3: the Libs are mad at him, and the right is

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Speaker 3: mad at him. He's got nobody who was standing up.

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Speaker 1: So he was a joke. I always thought he was

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Speaker 1: an idiot.

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Speaker 3: But you know, whenever you look at Josh Shapiro, the

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Speaker 3: appealing part was not only the state of Pennsylvania, which

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Speaker 3: you know she did lose by relatively small margin. It

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Speaker 3: wasn't like it was a blowout. Whenever it came to

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Speaker 3: the statewide election. It may have actually been worth putting

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Speaker 3: up with if you had thought that it was going

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Speaker 3: to do anything.

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Speaker 1: I think, though, the.

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Speaker 3: Case being made is that look at how these people

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Speaker 3: are all.

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Speaker 1: Divas, you know, in the way that they act.

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Speaker 3: And like they have the victim comp Like even Kamala

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Speaker 3: she's bitching about how the vice president's office doesn't have.

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Speaker 8: A bathroom, like oh yeah, like I give a fuck

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Speaker 8: whether you'd be to go to the bathroom in your

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Speaker 8: private office or not, all right, And then whenever it

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Speaker 8: comes to Josh Shapiro, he's like, oh, well, they were

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Speaker 8: so mean to me because he's mad that they didn't

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Speaker 8: come and try to offer him the role on a

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Speaker 8: silver right in a way, like he wanted them to

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Speaker 8: beg for him to take the job, and what they.

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Speaker 2: Said is he was like measuring the drapes basically and

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Speaker 2: like being very assertive about like what he wanted the

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Speaker 2: vice presidential role to be, and they we'll, like, screw you.

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Speaker 3: But you know, in a way I sympathize in that,

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Speaker 3: like he they needed him, I think a little bit

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Speaker 3: more than she needed or she needed him more than

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Speaker 3: he needed her.

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Speaker 1: Like he's still fine enough, governor.

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Speaker 2: I mean, honestly, it kind of dodged a bullet.

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Speaker 1: Yeah, he obviously because look at Wallt's Walts's a disast, right,

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Speaker 1: he looks like a joke is out now.

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Speaker 2: I mean, listen, I don't think Shapiro is going to

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Speaker 2: win a twenty twenty eight primary, but he's still in

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Speaker 2: his head, is holding onto that hope.

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Speaker 3: For sure, for sure, but you know, at the very least,

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Speaker 3: like he gets to survive, you know, if you if

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Speaker 3: you take it out four years, like the fact that

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Speaker 3: the sitting the vice presidential Democratic candidate who previously was

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Speaker 3: like somebody you know who actually had some sort of

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Speaker 3: political juice had to not run for reelection should make

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Speaker 3: you seriously reassess, like the way that that entire thing

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Speaker 3: went down from a pure political talent perspective, and the

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Speaker 3: fact now that you know, for him dodging the bullet.

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Speaker 3: What I think, though, is so bad about this book

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Speaker 3: is it's all personal, and it just reveals that these

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Speaker 3: people don't care about really anything.

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Speaker 1: It's for him, It's.

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Speaker 3: All about the slights that are all perceived, etc. Even

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Speaker 3: Kamala's book was just the gallery of all of the

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Speaker 3: perceived slights and how people let her down, and she

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Speaker 3: was never in a position where she actually failed the public. Like,

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Speaker 3: if you're a Democrat, you should be serious with this woman,

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Speaker 3: like actually furious for the way she ran her campaign.

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Speaker 1: If you're like, oh my god, Trump is so bad,

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Speaker 1: it's like it's her fault, guys, I just don't get it.

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Speaker 2: I mean, listen, I don't. It's not all her fault, right,

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Speaker 2: but you cannot avoid laying some blame at her feet.

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Speaker 2: And this was the thing I never understood with the

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Speaker 2: Hillary either. It's like, I mean that one really is

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Speaker 2: all her fault. By and large, you are the most

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Speaker 2: proximate cause of the Trump era, and I just never

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Speaker 2: felt like there was a reckoning with that, and it's

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Speaker 2: that's becas you know, accountability. So let's put let's put

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Speaker 2: D six up on the screen because this gets to

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Speaker 2: what you're speaking about with this Kamala Harris situation. So

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Speaker 2: she's still imagining that she's going to run for president.

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Speaker 2: And the headline here from Axios is Dems divide over

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Speaker 2: Harris surfaces as she looks like twenty twenty eight contender.

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Speaker 2: One top Democrat told Axios, Kamala has not accepted that

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Speaker 2: she's not running yet. And I mean the that is

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Speaker 2: wild to me. That is wild to me because and

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Speaker 2: I know where it comes from. It's because number one,

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Speaker 2: she has whoever around her that you know, when you

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Speaker 2: have consultants and aids around you, they stand a financially

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Speaker 2: profit off of your run, even if you'd lose, because

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Speaker 2: Kamala Harris would raise money and she'd do a thing

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Speaker 2: and they'd get a cut of her adviys and whatever.

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Speaker 2: So they have a vested interest. And then genuinely, there's

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Speaker 2: a lot of affection for her in the black community.

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Speaker 2: So when she travels around and she sees these crowds

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Speaker 2: of people who are you know, like genuinely admire her

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Speaker 2: and appreciate her and all of that that continues to

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Speaker 2: sort of like fill her head with I am the one,

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Speaker 2: and you know what, you look at the polling and

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Speaker 2: there still is a significant chunk of the Democratic base

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Speaker 2: that will say, yeah, if in this primary field, she's

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Speaker 2: the one that I would choose. But that ignores the

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Speaker 2: fact that we have not one, but two presidential campaigns

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Speaker 2: that we can look at with Kamala Harris, where you know,

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Speaker 2: in the Democratic primary she couldn't even get off the ground, right,

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Speaker 2: she had to drop out before the votes read and cast.

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Speaker 2: And then in this past election, look, she failed. I mean,

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Speaker 2: we ran the experiment. It didn't work. She wasn't able

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Speaker 2: to win. And you can chalk that up to any

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Speaker 2: number of factors that you want to, but that is reality.

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Speaker 2: And so it's just it's just wild to me. And

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Speaker 2: then the other part of it that is wow to

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Speaker 2: me is if you still want to be part of

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Speaker 2: if you want to be a leader in the Democratic Party,

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Speaker 2: like there is a massive void to fill. But she

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Speaker 2: is very she put on a thing now and then,

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Speaker 2: but in terms of really taking the lead and like

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Speaker 2: being a leader in this moment when they desperately need it.

438
00:21:35,000 --> 00:21:39,480
Speaker 2: She's not there, so still continuing to demonstrate that she

439
00:21:39,520 --> 00:21:42,000
Speaker 2: doesn't understand where the base is, she doesn't understand what

440
00:21:42,480 --> 00:21:44,639
Speaker 2: the moment is, what the moment calls for, she doesn't

441
00:21:44,680 --> 00:21:46,600
Speaker 2: know what she really believes in. That's always been kind

442
00:21:46,640 --> 00:21:48,920
Speaker 2: of the core problem with her, and all of those

443
00:21:48,960 --> 00:21:50,520
Speaker 2: issues are continued.

444
00:21:50,160 --> 00:21:52,600
Speaker 3: To right, Meanwhile, she's just about an eight million dollar

445
00:21:52,640 --> 00:21:55,360
Speaker 3: house in Malibu, if anybody's wondering, that's nice for her.

446
00:21:55,359 --> 00:21:58,320
Speaker 3: A couple of days ago off the proceeds at the book. Yeah,

447
00:21:58,320 --> 00:21:59,800
Speaker 3: I mean, here's a structural prison.

448
00:22:00,119 --> 00:22:03,000
Speaker 1: So yeah, right, yeah, through dubious means.

449
00:22:03,000 --> 00:22:05,560
Speaker 3: But yeah, but here's the thing with Kamala, and here's

450
00:22:05,560 --> 00:22:09,080
Speaker 3: a structural problem for Democrats. They rigged the primary for

451
00:22:09,119 --> 00:22:11,680
Speaker 3: Biden and have now made it South Carolina is a

452
00:22:11,680 --> 00:22:15,000
Speaker 3: first date, that's right, And remember the proving And I

453
00:22:15,040 --> 00:22:17,119
Speaker 3: had a lot of Christism of Iowa and New Hampshire

454
00:22:17,560 --> 00:22:20,359
Speaker 3: like not to be woke, but they actually are ironically

455
00:22:20,400 --> 00:22:23,840
Speaker 3: too white, as in like not and it's not about

456
00:22:23,880 --> 00:22:27,240
Speaker 3: them being white. It's not representative of a general electorate

457
00:22:27,600 --> 00:22:30,080
Speaker 3: and or a swing state. I always thought the first

458
00:22:30,080 --> 00:22:33,040
Speaker 3: state should be Michigan or some sort of battleground state

459
00:22:33,200 --> 00:22:35,080
Speaker 3: to be able to prove like the ability to get

460
00:22:35,080 --> 00:22:37,119
Speaker 3: people out where the demographics are going to look a

461
00:22:37,119 --> 00:22:38,760
Speaker 3: lot more like the general election, but.

462
00:22:38,720 --> 00:22:41,520
Speaker 2: They swing state, yeah, or noth Carolina is not.

463
00:22:41,560 --> 00:22:42,240
Speaker 1: How about Nevada?

464
00:22:42,359 --> 00:22:45,240
Speaker 3: Right, Bada was a perfect everyone, Yeah, Nevada is a

465
00:22:45,240 --> 00:22:48,320
Speaker 3: good one. Michigan and or maybe even Super Tuesday. It's

466
00:22:48,359 --> 00:22:50,800
Speaker 3: not a horrible idea, just to see how you play nationally.

467
00:22:51,000 --> 00:22:53,359
Speaker 3: But the fact is they rigged it so that South

468
00:22:53,400 --> 00:22:55,320
Speaker 3: Carolina is going to be first, and whoever wins that

469
00:22:55,359 --> 00:22:57,280
Speaker 3: gets the momentum. And this is going to be a

470
00:22:57,359 --> 00:23:01,840
Speaker 3: huge uphill challenge if Kamalon does running, because she doesn't

471
00:23:01,840 --> 00:23:05,000
Speaker 3: have to prove electability in Iowa and New Hampshire ahead

472
00:23:05,000 --> 00:23:07,920
Speaker 3: of South Carolina, and she can immediately win a primary,

473
00:23:08,040 --> 00:23:10,320
Speaker 3: which will flood the donation inbox and make her look

474
00:23:10,440 --> 00:23:13,240
Speaker 3: more like the left has a huge uphill back.

475
00:23:13,280 --> 00:23:14,800
Speaker 1: That's true to climb primary.

476
00:23:15,080 --> 00:23:18,720
Speaker 2: To be clear, I don't think they've actually set the

477
00:23:18,880 --> 00:23:22,239
Speaker 2: order of the states for twenty twenty eight, but I

478
00:23:22,320 --> 00:23:25,320
Speaker 2: do think it would be difficult. New Hampshire has that

479
00:23:25,359 --> 00:23:27,800
Speaker 2: thing where it's in their constitute whatever. Anyway, I do

480
00:23:27,840 --> 00:23:30,720
Speaker 2: think it will be difficult to push South Carolina back in.

481
00:23:30,880 --> 00:23:33,280
Speaker 2: It's certainly still going to be an incredibly consequential state,

482
00:23:33,480 --> 00:23:35,880
Speaker 2: and it continues to be the biggest dumbling block for

483
00:23:36,080 --> 00:23:38,560
Speaker 2: left wing candidates. There's simply no doubt about it that

484
00:23:38,960 --> 00:23:42,119
Speaker 2: older black, young, young black voters left wing candidates do

485
00:23:42,280 --> 00:23:44,199
Speaker 2: fine with, But older black voters that make up the

486
00:23:44,200 --> 00:23:47,000
Speaker 2: base of the Democratic Party in southern states like South Carolina,

487
00:23:47,359 --> 00:23:50,960
Speaker 2: I don't think that left wing candidates have figured that out.

488
00:23:51,160 --> 00:23:53,680
Speaker 1: And it's not representative though. That's why it drives me crazy.

489
00:23:53,720 --> 00:23:56,760
Speaker 2: It's not it and because I mean again in state,

490
00:23:56,800 --> 00:23:59,640
Speaker 2: it is a Republican state, so this is not emblematic

491
00:23:59,680 --> 00:24:03,840
Speaker 2: of the like. Those voters are the most reliable block

492
00:24:04,000 --> 00:24:08,239
Speaker 2: of Democratic Party voters, So whoever the nominee is is

493
00:24:08,280 --> 00:24:10,440
Speaker 2: going to get the backing of those voters. So you're

494
00:24:10,440 --> 00:24:13,840
Speaker 2: not really demonstrating anything in terms of your certainly in

495
00:24:13,920 --> 00:24:16,840
Speaker 2: terms of your electability and anyway, I mean, the whole

496
00:24:16,880 --> 00:24:18,879
Speaker 2: idea that this was all about some like, oh, we

497
00:24:18,920 --> 00:24:21,120
Speaker 2: need to be inclusive is just bullshit. They just did

498
00:24:21,119 --> 00:24:23,080
Speaker 2: it because they thought it would be best for Joe Biden.

499
00:24:23,119 --> 00:24:25,240
Speaker 2: That is the bottom line of what happened there, because

500
00:24:25,440 --> 00:24:28,320
Speaker 2: you know, I'll never forget in twenty twenty when you

501
00:24:28,400 --> 00:24:32,600
Speaker 2: had you know, Bernie running and he wins Iowa, Pete

502
00:24:32,800 --> 00:24:35,160
Speaker 2: whatever you know, ties in Iowa. How do you want

503
00:24:35,160 --> 00:24:38,200
Speaker 2: to say that does very well in Iowa, wins New Hampshire,

504
00:24:38,560 --> 00:24:41,920
Speaker 2: wins Nevada, which you can say Iowa, New Hampshire, Yes,

505
00:24:42,000 --> 00:24:46,960
Speaker 2: very white. Nevada extremely diverse, extremely extremely diverse in all

506
00:24:47,000 --> 00:24:49,199
Speaker 2: of the pundit class that none of that really counts.

507
00:24:49,720 --> 00:24:53,800
Speaker 2: That doesn't count as diversity. Only South Carolina accounts as diversity.

508
00:24:54,080 --> 00:24:56,320
Speaker 2: And so in any case, I don't know what the

509
00:24:56,440 --> 00:24:59,679
Speaker 2: order will be, but that regardless, that is something that

510
00:24:59,800 --> 00:25:01,359
Speaker 2: you a left wing candidate is going to have to

511
00:25:01,359 --> 00:25:04,760
Speaker 2: figure on or they have to hope that there is

512
00:25:05,600 --> 00:25:09,400
Speaker 2: there are a variety of like establishment lane candidates who

513
00:25:09,520 --> 00:25:14,520
Speaker 2: divide that vote in South Carolina because that you know,

514
00:25:14,600 --> 00:25:17,040
Speaker 2: that would be the other hope. And I think that's possible.

515
00:25:17,080 --> 00:25:18,920
Speaker 1: It is possible. But don't forget about Cliburn.

516
00:25:18,960 --> 00:25:20,760
Speaker 3: If he's around, all he has to do is endorse

517
00:25:20,840 --> 00:25:22,800
Speaker 3: you in the like Apparently forty percent of the people

518
00:25:22,840 --> 00:25:24,359
Speaker 3: in South Carolina will just vote for you.

519
00:25:25,000 --> 00:25:26,400
Speaker 1: I think it's I think it's really bad.

520
00:25:26,480 --> 00:25:29,040
Speaker 3: I think a lot of Democrats, people like you guys

521
00:25:29,040 --> 00:25:32,000
Speaker 3: should get involved or try to get into a primary process,

522
00:25:32,000 --> 00:25:34,600
Speaker 3: because like this is bad for the country, to make

523
00:25:34,640 --> 00:25:37,880
Speaker 3: it so that it is effectively rigged, you know, by

524
00:25:37,920 --> 00:25:41,320
Speaker 3: the Democratic establishment from the get go, to make it

525
00:25:41,359 --> 00:25:44,560
Speaker 3: so that any sort of upstart candidate basically has no

526
00:25:44,720 --> 00:25:48,239
Speaker 3: shot whatsoever. And especially how this will play in the

527
00:25:48,280 --> 00:25:51,280
Speaker 3: midst of where likely to be some insurgent victories in

528
00:25:51,320 --> 00:25:54,960
Speaker 3: twenty twenty six Oh, that's horrible, right to basically betray

529
00:25:55,240 --> 00:25:57,119
Speaker 3: a huge part and then that would could lead to

530
00:25:57,600 --> 00:25:59,640
Speaker 3: you know, the feelings of betrayal or replay the whole

531
00:25:59,640 --> 00:26:03,000
Speaker 3: twenty s sixteen candidacy, which is I mean, I would

532
00:26:03,000 --> 00:26:05,040
Speaker 3: say that's like the modal outcome right now, is that

533
00:26:05,080 --> 00:26:06,120
Speaker 3: there's going to be a huge fight.

534
00:26:06,560 --> 00:26:07,359
Speaker 1: Who knows.

535
00:26:07,680 --> 00:26:11,280
Speaker 3: I never count out the democratic establishment or the ability

536
00:26:11,320 --> 00:26:12,959
Speaker 3: for a lot of people to just like go along.

537
00:26:13,280 --> 00:26:15,919
Speaker 3: Trump JD will be the boogeyman of the you know,

538
00:26:16,000 --> 00:26:19,400
Speaker 3: he's Trump, but actually he's worse, and everybody will kind

539
00:26:19,400 --> 00:26:21,360
Speaker 3: of come together and then who knows, you know, from

540
00:26:21,400 --> 00:26:24,760
Speaker 3: there there may be enough people who are not willing

541
00:26:24,760 --> 00:26:27,200
Speaker 3: to buy the boogeyman argument and you could potentially see

542
00:26:27,200 --> 00:26:29,240
Speaker 3: some sort of close election all over again.

543
00:26:29,400 --> 00:26:33,520
Speaker 1: I have no idea. Let's get to Epstein.

544
00:26:33,720 --> 00:26:37,879
Speaker 2: Yeah, so this is I think a very noteworthy development.

545
00:26:37,920 --> 00:26:40,280
Speaker 2: So podcaster Sean Ryan, who I think had Trump and

546
00:26:40,400 --> 00:26:43,520
Speaker 2: Jade Vans on in advanceity election, you know, has been

547
00:26:43,680 --> 00:26:47,919
Speaker 2: outspoken about he voted for them. You know, he truly believed,

548
00:26:47,960 --> 00:26:49,760
Speaker 2: I mean what I give him this, You've truly believed

549
00:26:49,880 --> 00:26:52,280
Speaker 2: the hype that they would they would reveal the secrets,

550
00:26:52,280 --> 00:26:54,679
Speaker 2: they would release the Epstein. Vaz clearly something that he

551
00:26:54,760 --> 00:27:00,520
Speaker 2: feels passionate about, and he is thoroughly disgusted with the

552
00:27:00,680 --> 00:27:04,560
Speaker 2: cover up. Had an extraordinary conversation with Rocana. Of course

553
00:27:04,600 --> 00:27:06,960
Speaker 2: spent at the forefront of pushing to get the Epstein

554
00:27:06,960 --> 00:27:09,760
Speaker 2: files released, and in the context of that, you know,

555
00:27:09,800 --> 00:27:12,240
Speaker 2: went aggressively after the Trump White House. Let's go ahead

556
00:27:12,240 --> 00:27:12,919
Speaker 2: and take a listen to that.

557
00:27:13,320 --> 00:27:17,399
Speaker 9: Why is the White House protecting pedophiles? Why is the

558
00:27:17,400 --> 00:27:21,439
Speaker 9: White House protecting pedophiles? I just don't understand it. Bro,

559
00:27:21,800 --> 00:27:24,119
Speaker 9: I can't fucking get it through my head. Why we

560
00:27:24,119 --> 00:27:27,640
Speaker 9: would protect pedophiles. I mean, I fucking voted for this shit.

561
00:27:27,840 --> 00:27:31,240
Speaker 9: I voted to get these damn files released, and it's

562
00:27:31,320 --> 00:27:35,400
Speaker 9: like a total one eighty just happened. They are legitimately

563
00:27:36,359 --> 00:27:42,200
Speaker 9: proactively protecting pedophiles. They are protecting pedophiles at this point.

564
00:27:42,040 --> 00:27:48,399
Speaker 10: By redacting the abuser's name by the White House. Listen up, everybody,

565
00:27:48,800 --> 00:27:55,520
Speaker 10: the fucking White House is protecting pedophiles. You hear that

566
00:27:56,000 --> 00:27:59,680
Speaker 10: they're fucking protecting pedophiles. That's what the fuck they're doing.

567
00:28:00,440 --> 00:28:04,600
Speaker 2: So making sure that everybody heard. Hey, just so you

568
00:28:04,680 --> 00:28:07,560
Speaker 2: know what these people are doing, let's put the next

569
00:28:07,600 --> 00:28:09,480
Speaker 2: one up on the screen, because he's been going in

570
00:28:09,560 --> 00:28:13,080
Speaker 2: on Twitter as well. So this guy, Donald Trump's quote

571
00:28:13,080 --> 00:28:16,680
Speaker 2: spiritual leader Robert Morris was just sentenced to a pathetic,

572
00:28:16,720 --> 00:28:19,600
Speaker 2: by the way, six months in prison after pleading guilty

573
00:28:19,640 --> 00:28:23,080
Speaker 2: to five counts of sexually abusing a twelve year old child.

574
00:28:23,920 --> 00:28:26,359
Speaker 2: And Sean Ryan Wison and says, yeah, and he'll probably

575
00:28:26,359 --> 00:28:29,240
Speaker 2: get a pardon with this administration. So he's you know,

576
00:28:29,480 --> 00:28:33,800
Speaker 2: pretty aggressive going after them year and rightfully so and

577
00:28:33,880 --> 00:28:36,199
Speaker 2: we have, you know, to back him up. We have

578
00:28:36,280 --> 00:28:39,640
Speaker 2: some new legal moves from this administration as well. They

579
00:28:39,640 --> 00:28:42,600
Speaker 2: are telling the courts the dj is arguing that no

580
00:28:42,720 --> 00:28:45,880
Speaker 2: court can actually force the release of the Epstein files.

581
00:28:46,200 --> 00:28:48,520
Speaker 2: According to Brian Allen, he says their position is basically,

582
00:28:48,560 --> 00:28:51,640
Speaker 2: the Epstein Transparency Act doesn't create an enforcable path in

583
00:28:51,680 --> 00:28:55,440
Speaker 2: federal courts, so judges cannot compel compliance. Translation will release

584
00:28:55,440 --> 00:28:57,800
Speaker 2: what we want when we want, and you can't stop us.

585
00:28:57,960 --> 00:29:00,920
Speaker 2: It has now been a month sent they were supposed

586
00:29:00,920 --> 00:29:05,800
Speaker 2: to have released everything, and there is a tiny sliver

587
00:29:06,520 --> 00:29:08,960
Speaker 2: of files that have come out, and you know, I

588
00:29:09,000 --> 00:29:10,560
Speaker 2: thought we were going to get a drip drip drip.

589
00:29:10,600 --> 00:29:13,080
Speaker 2: We got like a drip drip and that was it.

590
00:29:13,280 --> 00:29:16,520
Speaker 2: Nothing else since what December is the last time we

591
00:29:16,560 --> 00:29:20,360
Speaker 2: got any sort of release. And those releases, even though

592
00:29:20,400 --> 00:29:23,640
Speaker 2: they were redacted, even though they were insufficient, they were

593
00:29:23,720 --> 00:29:28,840
Speaker 2: still very damaging to Trump and very revelatory in general

594
00:29:29,080 --> 00:29:32,080
Speaker 2: about you know, what Epstein was doing and you know,

595
00:29:32,200 --> 00:29:36,480
Speaker 2: implicating all sorts of people. So even with this very

596
00:29:36,800 --> 00:29:41,120
Speaker 2: constrained tiny amount of information that we got, there was

597
00:29:41,160 --> 00:29:46,320
Speaker 2: still noteworthy information contained there. So they're completely stonewalling. They

598
00:29:46,360 --> 00:29:48,000
Speaker 2: want to wash their hands of it, they want to

599
00:29:48,080 --> 00:29:50,120
Speaker 2: argue in court, they don't have to do anything else,

600
00:29:50,400 --> 00:29:53,720
Speaker 2: and they're flagrantly violating the law that was passed by

601
00:29:53,720 --> 00:29:56,280
Speaker 2: Commerce and signed into law by the President himself.

602
00:29:56,360 --> 00:29:57,880
Speaker 3: One of the things that makes me hopeful about the

603
00:29:57,880 --> 00:29:59,360
Speaker 3: shoon Ryan, I mean, Sean, you know you got a

604
00:29:59,360 --> 00:30:00,000
Speaker 3: good guy credit.

605
00:30:00,040 --> 00:30:01,080
Speaker 1: You actually talked a lot about this.

606
00:30:01,120 --> 00:30:03,840
Speaker 3: He just had on a child protection person on his show,

607
00:30:03,920 --> 00:30:06,680
Speaker 3: Like he cares really, really deeply about this issue. And

608
00:30:06,800 --> 00:30:09,600
Speaker 3: this is somebody who is I mean, he's got millions

609
00:30:09,640 --> 00:30:13,120
Speaker 3: of subscribers on YouTube and in general. The way that

610
00:30:13,120 --> 00:30:15,640
Speaker 3: you could assess this is part of an overall let's

611
00:30:15,640 --> 00:30:18,360
Speaker 3: call it vibe shift if you will, If you'll take

612
00:30:18,400 --> 00:30:21,960
Speaker 3: the totality of like Tim Dillon, Andrew Schaltz, Joe Rogan,

613
00:30:22,200 --> 00:30:25,240
Speaker 3: Sean Ryan. If we accept that all of those people

614
00:30:25,360 --> 00:30:29,120
Speaker 3: were vital conduits for Donald Trump or Trump thought theovon

615
00:30:29,320 --> 00:30:32,640
Speaker 3: another one of them, Trump's to Trump permission structure in

616
00:30:32,680 --> 00:30:35,760
Speaker 3: twenty twenty four, then we have to accept that their

617
00:30:35,840 --> 00:30:39,760
Speaker 3: criticism is also a permission structure against Trump and the

618
00:30:39,760 --> 00:30:43,520
Speaker 3: Republicans in twenty twenty six and potentially in twenty twenty eight.

619
00:30:43,640 --> 00:30:46,600
Speaker 3: And that's why I actually think that this issue remains

620
00:30:46,680 --> 00:30:49,840
Speaker 3: so important, not only because of the substance, which again

621
00:30:49,880 --> 00:30:52,880
Speaker 3: we've covered since here from day one, but it matters

622
00:30:52,960 --> 00:30:55,960
Speaker 3: because when it comes to a cover up and the

623
00:30:56,000 --> 00:30:58,400
Speaker 3: way that they act. Let's say, as we just pointed

624
00:30:58,400 --> 00:31:02,800
Speaker 3: out in the censorship block, that there immediately will come

625
00:31:02,840 --> 00:31:07,080
Speaker 3: to the defense of some Florida State student who apparently

626
00:31:07,120 --> 00:31:09,720
Speaker 3: got yelled at because he's wearing an IDF T shirt.

627
00:31:10,000 --> 00:31:11,840
Speaker 3: But then you see them dragging their feet for a

628
00:31:11,960 --> 00:31:15,120
Speaker 3: month whenever it comes to Epstein. I mean, you should

629
00:31:15,160 --> 00:31:17,640
Speaker 3: freak out about that, Like, you really should be upset

630
00:31:17,680 --> 00:31:20,640
Speaker 3: about that, And then you see the way that they

631
00:31:20,720 --> 00:31:24,160
Speaker 3: act for multiple other high profile cases.

632
00:31:24,280 --> 00:31:25,360
Speaker 1: By the way, if you're super.

633
00:31:25,160 --> 00:31:27,000
Speaker 3: Right wing, shouldn't you be upset about the way that

634
00:31:27,040 --> 00:31:29,680
Speaker 3: the Charlie Kirk thing went down. It's nuts, right, the

635
00:31:29,760 --> 00:31:32,719
Speaker 3: way that cash Betel and the FBI botched that investigation

636
00:31:33,000 --> 00:31:35,120
Speaker 3: from day one, you should be furious.

637
00:31:35,360 --> 00:31:36,320
Speaker 1: I mean, even.

638
00:31:37,600 --> 00:31:40,760
Speaker 3: Oh my god, the shooter remember the Brown University thing.

639
00:31:41,120 --> 00:31:44,000
Speaker 3: What a shit show, And they had no idea where

640
00:31:44,000 --> 00:31:45,960
Speaker 3: the person was. He ended up killing himself in a

641
00:31:45,960 --> 00:31:49,040
Speaker 3: storage locker, right, That's how it all eventually went out.

642
00:31:49,040 --> 00:31:50,840
Speaker 3: By the way, still haven't heard much about that. We

643
00:31:50,920 --> 00:31:53,160
Speaker 3: got the transcripts of his video, and apparently it's just

644
00:31:53,160 --> 00:31:55,320
Speaker 3: because he was crazy. Maybe, I mean, I don't know

645
00:31:55,320 --> 00:31:57,480
Speaker 3: it seem pretty weird to me, going to assassinate the

646
00:31:57,480 --> 00:32:00,640
Speaker 3: head of a nuclear science program. But yeah, so like

647
00:32:01,120 --> 00:32:05,840
Speaker 3: at every step they're either incompetent and or acting as

648
00:32:05,840 --> 00:32:08,800
Speaker 3: if there is something to cover up and they have

649
00:32:08,920 --> 00:32:10,920
Speaker 3: nothing to say about it. And then the president the

650
00:32:11,000 --> 00:32:13,240
Speaker 3: DJ and all of their behavior. Look at the way

651
00:32:13,240 --> 00:32:15,440
Speaker 3: I mean Trump literally flipped that guy off, the forward

652
00:32:15,480 --> 00:32:19,880
Speaker 3: worker because and then even inside the administration, they're furious

653
00:32:19,920 --> 00:32:22,800
Speaker 3: with Pam Bondi for blaming her, and it is like

654
00:32:22,880 --> 00:32:25,400
Speaker 3: kind of centrally her and Cash's fault because from the

655
00:32:25,480 --> 00:32:28,920
Speaker 3: day one they handed out all of that Epstein files transparency,

656
00:32:29,200 --> 00:32:31,920
Speaker 3: they made it into a thing which makes their retrenchment

657
00:32:31,920 --> 00:32:33,400
Speaker 3: and their cover up like so much worse.

658
00:32:33,480 --> 00:32:33,680
Speaker 9: Yeah.

659
00:32:33,680 --> 00:32:35,080
Speaker 1: Completely, That's why I think.

660
00:32:35,400 --> 00:32:37,840
Speaker 3: You know, there's this whole theory on the right called

661
00:32:37,920 --> 00:32:43,040
Speaker 3: no you're not This will not be unfamiliar to you.

662
00:32:42,920 --> 00:32:46,280
Speaker 3: You never criticize your own side. And I have always

663
00:32:46,320 --> 00:32:49,720
Speaker 3: found first no enemy, no enemies to the right, which

664
00:32:49,800 --> 00:32:51,840
Speaker 3: on the left as the statement right, anyone who's part

665
00:32:51,840 --> 00:32:54,080
Speaker 3: of the revolution is part of the revolution, all right. So,

666
00:32:54,400 --> 00:32:57,080
Speaker 3: but in this case, it is so clear to me

667
00:32:57,360 --> 00:33:01,160
Speaker 3: that people who criticize get more results because if it's

668
00:33:01,200 --> 00:33:03,640
Speaker 3: something that you actually care about. Look at Roe and

669
00:33:03,720 --> 00:33:07,800
Speaker 3: Thomas Massey. They brute force this bill, which the administration

670
00:33:07,880 --> 00:33:11,959
Speaker 3: tried to kill through all of Congress and made Donald

671
00:33:12,040 --> 00:33:15,520
Speaker 3: Trump sign the bill, which was to his own detriment.

672
00:33:15,760 --> 00:33:19,080
Speaker 3: That was only made possible because I mean, a small

673
00:33:19,120 --> 00:33:21,560
Speaker 3: part show like ours, which is part of like this

674
00:33:21,960 --> 00:33:24,960
Speaker 3: vast conduit which keeps the issue alive and to this

675
00:33:25,080 --> 00:33:28,600
Speaker 3: day is forcing like continued transparency. If you want to

676
00:33:28,680 --> 00:33:30,840
Speaker 3: have something be done, the worst thing you can be

677
00:33:30,920 --> 00:33:33,320
Speaker 3: is sycophantic, Which is why I think it's really good

678
00:33:33,520 --> 00:33:35,680
Speaker 3: that somebody like Sean Ryan or any of these other

679
00:33:35,720 --> 00:33:38,400
Speaker 3: people continue to speak up about the issue, because something

680
00:33:38,400 --> 00:33:41,760
Speaker 3: in the zeitgeist is genuinely the only way that this

681
00:33:41,800 --> 00:33:45,480
Speaker 3: will ever like where we even remotely come to some

682
00:33:45,520 --> 00:33:48,000
Speaker 3: sort of transparency, even though I will still never believe,

683
00:33:48,240 --> 00:33:49,800
Speaker 3: you know, most of what they put out yea, and

684
00:33:49,880 --> 00:33:52,000
Speaker 3: I don't really think that that's you know, where it is.

685
00:33:52,040 --> 00:33:53,960
Speaker 3: I do hope though, we can normalize this so when

686
00:33:54,000 --> 00:33:56,840
Speaker 3: the Democrats, if they eventually come into power, actually just

687
00:33:56,880 --> 00:33:59,320
Speaker 3: release the entire thing, and then you know, perhaps we

688
00:33:59,320 --> 00:34:00,360
Speaker 3: will get closure day.

689
00:34:00,480 --> 00:34:00,720
Speaker 5: Yeah.

690
00:34:01,280 --> 00:34:03,360
Speaker 2: Put E four just last piece up on the screen.

691
00:34:03,440 --> 00:34:10,200
Speaker 2: To your point about sickofancy so courageously you had, you

692
00:34:10,280 --> 00:34:13,920
Speaker 2: needed four Republicans to sign on to, you know, to

693
00:34:13,960 --> 00:34:16,200
Speaker 2: get this discharge petition through, to get this law passed.

694
00:34:16,239 --> 00:34:19,000
Speaker 2: You had Thomas Massey, you had Marjorie Taylor Green, you

695
00:34:19,080 --> 00:34:21,840
Speaker 2: had Lauren Bobert, and you had Nancy Mace. And the

696
00:34:21,880 --> 00:34:26,360
Speaker 2: White House aggressively went after Nancy Mace and Lauren Bobert

697
00:34:26,400 --> 00:34:28,879
Speaker 2: in particular, and which one of them was that they

698
00:34:28,960 --> 00:34:31,040
Speaker 2: pulled into the situation. One of them just didn't answer

699
00:34:31,040 --> 00:34:33,719
Speaker 2: the phone. Bobert. They like pulled in the situation where

700
00:34:33,719 --> 00:34:36,680
Speaker 2: they do the whole thing, like full pressure campaign. And

701
00:34:36,680 --> 00:34:38,799
Speaker 2: to her credit, she did not cave. She signed on

702
00:34:38,840 --> 00:34:41,440
Speaker 2: to it. And that's that is the reason why this

703
00:34:41,560 --> 00:34:44,520
Speaker 2: law was ultimately passed. Well, now they are all just

704
00:34:44,600 --> 00:34:46,880
Speaker 2: trying to, you know, move on. They don't want to

705
00:34:46,880 --> 00:34:51,680
Speaker 2: talk about it anymore. Lauren Bobert in particular said, quote,

706
00:34:51,960 --> 00:34:55,200
Speaker 2: I don't give a rip about Epstein, Like, there's so

707
00:34:55,320 --> 00:34:57,759
Speaker 2: many other things we need to be working on. I've

708
00:34:57,800 --> 00:35:00,160
Speaker 2: done what I had to do for Epstein. Talk to

709
00:35:00,200 --> 00:35:02,960
Speaker 2: somebody else about that. It's no longer in my hands.

710
00:35:03,320 --> 00:35:06,279
Speaker 2: So outside of Massy and then Marjorie tillergreen is on

711
00:35:06,400 --> 00:35:09,400
Speaker 2: in Congress now, so outside of mass on the Republican side,

712
00:35:09,440 --> 00:35:12,240
Speaker 2: they really are all just hoping this sort of goes away,

713
00:35:12,280 --> 00:35:15,600
Speaker 2: Like they're probably hoping the administration wins in court that

714
00:35:15,800 --> 00:35:19,560
Speaker 2: you know that the courts can't actually compel them to

715
00:35:19,600 --> 00:35:21,680
Speaker 2: do anything, and they just continue to sit on it

716
00:35:21,760 --> 00:35:23,600
Speaker 2: and there's no drip drip drip, drip drip that they

717
00:35:23,640 --> 00:35:25,759
Speaker 2: have to deal with. They're just hoping this all goes

718
00:35:25,800 --> 00:35:26,520
Speaker 2: away at this point.

719
00:35:26,560 --> 00:35:29,520
Speaker 3: And look, it could be right because I mean, even

720
00:35:29,600 --> 00:35:33,640
Speaker 3: we are subject to global affairs, this is our what

721
00:35:33,760 --> 00:35:34,520
Speaker 3: is it e block?

722
00:35:34,719 --> 00:35:34,919
Speaker 1: Right?

723
00:35:35,600 --> 00:35:39,520
Speaker 3: What do we have to leave lead with Davos Greenland? Yeah, Ice,

724
00:35:39,680 --> 00:35:42,040
Speaker 3: I mean, look, I mean it's not that you're falling

725
00:35:42,160 --> 00:35:45,399
Speaker 3: for their game, but like we do have to quite

726
00:35:45,520 --> 00:35:49,719
Speaker 3: literally order the news in terms of relative importance, and

727
00:35:49,760 --> 00:35:52,240
Speaker 3: you can't be on top of everything at all times.

728
00:35:52,360 --> 00:35:54,719
Speaker 3: That's part of the tragedy of their strategy is it

729
00:35:54,800 --> 00:35:57,640
Speaker 3: usually does work whenever they're in power. I do hope

730
00:35:57,640 --> 00:36:00,560
Speaker 3: if the Democrats, let's say, take the House in midterms,

731
00:36:00,560 --> 00:36:03,239
Speaker 3: that they just you know, create a Bengazi level shit

732
00:36:03,280 --> 00:36:06,319
Speaker 3: storm which makes them which constantly keeps it in the

733
00:36:06,360 --> 00:36:10,040
Speaker 3: news constantly forces you know, reckoning or pressure on the

734
00:36:10,040 --> 00:36:13,440
Speaker 3: administration because as they've already shown, they had to fold

735
00:36:13,719 --> 00:36:15,239
Speaker 3: on this issue. I would say this is probably the

736
00:36:15,239 --> 00:36:19,080
Speaker 3: biggest legislative loss that happened in Trump's entire presidency, even

737
00:36:19,080 --> 00:36:20,600
Speaker 3: going back to two thousand.

738
00:36:20,360 --> 00:36:21,720
Speaker 1: Ex pol, which is shocked.

739
00:36:22,239 --> 00:36:24,600
Speaker 3: Is shocking that it actually was able to come to

740
00:36:24,680 --> 00:36:27,239
Speaker 3: fruit and that they didn't bruce force it and eventually

741
00:36:27,600 --> 00:36:31,200
Speaker 3: veto So that shows the crack that people can continue

742
00:36:31,239 --> 00:36:33,480
Speaker 3: to work through. So anyway, I think I think it's

743
00:36:33,520 --> 00:36:38,640
Speaker 3: a positive development. We would be remiss if we didn't

744
00:36:38,640 --> 00:36:40,759
Speaker 3: give our flowers here to Ben Affleck and to Matt

745
00:36:40,840 --> 00:36:43,680
Speaker 3: Damon in their recent appearance on Joe Rogan dropping several

746
00:36:43,680 --> 00:36:46,520
Speaker 3: truth bombs, not just about AI, but also about our

747
00:36:46,520 --> 00:36:49,280
Speaker 3: movie industry and the way it currently works. Here's Ben's

748
00:36:49,360 --> 00:36:52,160
Speaker 3: rumination on AI. You could have taken it straight out

749
00:36:52,200 --> 00:36:53,799
Speaker 3: of like a Bloomberg analysis.

750
00:36:53,920 --> 00:36:54,640
Speaker 1: Let's take a listen.

751
00:36:55,080 --> 00:36:57,200
Speaker 11: What I see is, for example, if you try to

752
00:36:57,200 --> 00:37:01,200
Speaker 11: get chat Ebt or Claude or Gemin to write you something,

753
00:37:01,280 --> 00:37:05,360
Speaker 11: it's really shitty. And it's shitty because by its nature

754
00:37:05,400 --> 00:37:08,320
Speaker 11: it goes to the mean, to the average, and it's

755
00:37:08,440 --> 00:37:11,319
Speaker 11: and it's not reliable, and it's I mean, I just

756
00:37:11,360 --> 00:37:14,000
Speaker 11: can't stand to see what writes. Now. It's a useful

757
00:37:14,000 --> 00:37:16,600
Speaker 11: tool if you're a writer and you're going, ah, what's

758
00:37:16,640 --> 00:37:18,960
Speaker 11: the thing. I'm trying to set something up where somebody

759
00:37:19,000 --> 00:37:21,080
Speaker 11: sends someone a letter but it's delayed two days and

760
00:37:21,120 --> 00:37:23,000
Speaker 11: gets and it can give you some examples of that.

761
00:37:23,680 --> 00:37:26,600
Speaker 11: I actually don't think it's very likely that it can

762
00:37:26,719 --> 00:37:29,080
Speaker 11: it's going to be able to write anything meaningful or

763
00:37:29,120 --> 00:37:32,680
Speaker 11: and in particular that it's going to be making movies

764
00:37:32,760 --> 00:37:34,880
Speaker 11: like from Hoole Cloth like Tilly normal, Like that's bullshit.

765
00:37:34,920 --> 00:37:37,080
Speaker 11: I don't think that's going to happen. I think it's not.

766
00:37:37,160 --> 00:37:39,319
Speaker 11: I think it actually turns out the technology is not

767
00:37:39,400 --> 00:37:42,879
Speaker 11: progressing in exactly the same way they sort of presented it.

768
00:37:43,400 --> 00:37:44,680
Speaker 11: And really what it is is going to be a

769
00:37:44,719 --> 00:37:47,719
Speaker 11: tool just like sort of visual facts, and yeah, it

770
00:37:47,800 --> 00:37:49,600
Speaker 11: needs to have language around it. You need to protect

771
00:37:49,600 --> 00:37:51,560
Speaker 11: your name and likeness. You can do that. You can

772
00:37:51,600 --> 00:37:54,480
Speaker 11: water market your those laws already exist. You can't. I

773
00:37:54,520 --> 00:37:56,759
Speaker 11: can't sell your fucking picture for money. I can't you

774
00:37:56,800 --> 00:37:59,400
Speaker 11: consume me. Period. It kind of feels to me like

775
00:37:59,680 --> 00:38:02,840
Speaker 11: things earlier where there's a lot more fear because we

776
00:38:02,880 --> 00:38:05,839
Speaker 11: have the sense that's existential dread, it's gonna wipe everything out.

777
00:38:06,400 --> 00:38:09,160
Speaker 11: But that actually runs counter, in my view, to what

778
00:38:09,560 --> 00:38:12,440
Speaker 11: history seems to show, which is a adoption is slow,

779
00:38:12,920 --> 00:38:17,160
Speaker 11: it's incremental. I think a lot of that rhetoric comes

780
00:38:17,160 --> 00:38:21,120
Speaker 11: from people who are trying to justify valuations around companies,

781
00:38:21,320 --> 00:38:23,279
Speaker 11: where they go, we're gonna change everything in two years.

782
00:38:23,280 --> 00:38:25,319
Speaker 11: There's gonna be no more work. But the reason they're

783
00:38:25,320 --> 00:38:28,719
Speaker 11: saying that is because they need to ascribe evaluation for

784
00:38:28,840 --> 00:38:31,759
Speaker 11: investment that can warrant the cape spend they're gonna make

785
00:38:31,760 --> 00:38:34,480
Speaker 11: on these data centers, with the argument that like, oh,

786
00:38:34,680 --> 00:38:36,560
Speaker 11: you know, as soon as we do the next model,

787
00:38:36,560 --> 00:38:38,520
Speaker 11: it's gonna scale up. It can be three times as good,

788
00:38:39,040 --> 00:38:42,600
Speaker 11: except that actually chat Chap five about twenty five times

789
00:38:42,800 --> 00:38:46,480
Speaker 11: percent better than chatchipp four and costs about four times

790
00:38:46,480 --> 00:38:49,120
Speaker 11: as much in the way of electricity and data. So

791
00:38:49,400 --> 00:38:53,000
Speaker 11: those and they say that it's like plateauing the early AI.

792
00:38:53,440 --> 00:38:56,160
Speaker 11: The line went up very steeply and it's now sort

793
00:38:56,160 --> 00:38:58,839
Speaker 11: of leveling off. I think it's because and yes, it'll

794
00:38:58,840 --> 00:39:01,680
Speaker 11: get better, but it's gonna be really expensive to get better,

795
00:39:02,120 --> 00:39:03,640
Speaker 11: and a lot of people were like, fuck this, we

796
00:39:03,680 --> 00:39:06,120
Speaker 11: want chat GP four because it turned out like the

797
00:39:06,200 --> 00:39:09,239
Speaker 11: vast majority of people who use AI are using it

798
00:39:09,280 --> 00:39:13,080
Speaker 11: to like as like companion bots to chat with at night,

799
00:39:13,120 --> 00:39:15,360
Speaker 11: and so there's no work, there's no productivity, there's no

800
00:39:15,480 --> 00:39:16,480
Speaker 11: value to it.

801
00:39:16,520 --> 00:39:19,240
Speaker 1: Has he been watching Breaking points like this guy's so good?

802
00:39:19,440 --> 00:39:21,840
Speaker 3: But the reason why I thought it was important was

803
00:39:21,880 --> 00:39:24,840
Speaker 3: because there is quite a bit of concern still around

804
00:39:25,040 --> 00:39:28,360
Speaker 3: AI and it's creative endeavors in Hollywood, and there absolutely

805
00:39:28,360 --> 00:39:30,440
Speaker 3: should be because of the potential. I mean, look at

806
00:39:30,440 --> 00:39:33,000
Speaker 3: the New Avatar movie, like it's insane what people are

807
00:39:33,040 --> 00:39:35,960
Speaker 3: able to create literally like out of nothing is CGI

808
00:39:36,040 --> 00:39:38,880
Speaker 3: technology and all of that, et cetera. But what I

809
00:39:38,880 --> 00:39:41,239
Speaker 3: think he actually hit the nail on the head though,

810
00:39:41,520 --> 00:39:44,520
Speaker 3: is that while in the long run there remains quite

811
00:39:44,520 --> 00:39:47,680
Speaker 3: a bit of danger, in the immediate term, many of

812
00:39:47,719 --> 00:39:53,000
Speaker 3: these companies are lying. Much of their behavior indicates that

813
00:39:53,080 --> 00:39:57,080
Speaker 3: there's nothing that great or new coming chat GBT putting

814
00:39:57,080 --> 00:40:00,520
Speaker 3: in ads into the feed means we're kind of there

815
00:40:00,719 --> 00:40:03,480
Speaker 3: for the interim period and we just need to monetize

816
00:40:03,520 --> 00:40:05,680
Speaker 3: the shit out of this to continue pumping all of

817
00:40:05,680 --> 00:40:08,520
Speaker 3: these data centers. And actually the difference between you know,

818
00:40:08,600 --> 00:40:11,880
Speaker 3: chat GPT five and four point eight or whatever really

819
00:40:11,880 --> 00:40:14,959
Speaker 3: only matters in like a few select cases. And though

820
00:40:15,040 --> 00:40:18,600
Speaker 3: the data crunch is like immense, but at the consumer level,

821
00:40:18,880 --> 00:40:21,080
Speaker 3: like he said, we're talking about companion bots and all

822
00:40:21,080 --> 00:40:24,200
Speaker 3: this other parasocial weirdo stuff which is causing all these

823
00:40:24,239 --> 00:40:27,160
Speaker 3: social pathologies. So I actually think he just like really

824
00:40:27,200 --> 00:40:28,840
Speaker 3: eloquently kind of put it together.

825
00:40:29,200 --> 00:40:31,400
Speaker 2: I'm a little skeptical now. I need to be honest

826
00:40:31,440 --> 00:40:33,839
Speaker 2: with you, because here's why. It is because of the

827
00:40:33,880 --> 00:40:37,239
Speaker 2: economics of Yes, to run all the data centers is

828
00:40:37,320 --> 00:40:40,880
Speaker 2: very expensive, but to be the studio that says, you know,

829
00:40:40,960 --> 00:40:43,200
Speaker 2: give me a plot that hits X, y and z

830
00:40:43,520 --> 00:40:45,920
Speaker 2: points and there it is, it's extremely cheap.

831
00:40:46,080 --> 00:40:47,359
Speaker 1: Yeah, extremely cheap.

832
00:40:47,719 --> 00:40:51,279
Speaker 2: And so there's an assumption that they're going to care

833
00:40:51,320 --> 00:40:54,680
Speaker 2: about quality that I just don't think is really true.

834
00:40:54,880 --> 00:40:57,080
Speaker 2: I think when you have that level, there's going to

835
00:40:57,120 --> 00:41:02,279
Speaker 2: be some large number of you know, studios that push

836
00:41:02,320 --> 00:41:04,360
Speaker 2: in the direction of we're just going to do quantity

837
00:41:04,440 --> 00:41:07,160
Speaker 2: over quality. I mean, you already see this YouTube is

838
00:41:07,200 --> 00:41:09,200
Speaker 2: in some ways kind of like a good place to

839
00:41:09,239 --> 00:41:11,840
Speaker 2: see the way that these things will take off. You

840
00:41:11,920 --> 00:41:14,600
Speaker 2: already have these channels that will just put out like

841
00:41:14,800 --> 00:41:18,160
Speaker 2: endless numbers of AI songs I have right for some

842
00:41:18,200 --> 00:41:21,759
Speaker 2: of these there we've got Yannis faa Faucus came on

843
00:41:21,800 --> 00:41:25,080
Speaker 2: and talked about how there's all these channels that deep

844
00:41:25,080 --> 00:41:29,400
Speaker 2: fake him and some of the videos genuinely hit, you know.

845
00:41:29,560 --> 00:41:32,640
Speaker 2: And so if you're just able to easily churn out

846
00:41:32,800 --> 00:41:35,640
Speaker 2: a ton of content that some of it's going to

847
00:41:35,680 --> 00:41:37,920
Speaker 2: be so shitty no one watches it, but some of

848
00:41:37,920 --> 00:41:41,600
Speaker 2: it will be good enough that it does garner an audience,

849
00:41:41,920 --> 00:41:43,560
Speaker 2: there are going to be a lot of people who

850
00:41:43,600 --> 00:41:46,760
Speaker 2: go in that direction of like of just slop creation

851
00:41:47,000 --> 00:41:49,879
Speaker 2: because the economics of it are everything, and they don't

852
00:41:49,880 --> 00:41:52,719
Speaker 2: give a shit about like artistic creation, and you know,

853
00:41:52,800 --> 00:41:54,759
Speaker 2: and so the fact that it's low quality is right.

854
00:41:54,840 --> 00:41:57,960
Speaker 2: That it's low quality, there's no doubt about it. But

855
00:41:58,680 --> 00:42:01,520
Speaker 2: and it's improving, Mark that I do think he's right

856
00:42:01,560 --> 00:42:04,960
Speaker 2: too about the acceleration has slowed down in terms of

857
00:42:05,000 --> 00:42:07,319
Speaker 2: the improvement curve, and it kind of is at a

858
00:42:07,320 --> 00:42:09,680
Speaker 2: bit of a stasis right now, at least for the moment.

859
00:42:10,000 --> 00:42:12,279
Speaker 2: But that to me doesn't rule out the possibility that

860
00:42:12,280 --> 00:42:14,520
Speaker 2: it's going to come to dominate the sort of like

861
00:42:14,640 --> 00:42:18,760
Speaker 2: creative space simply because of the way that the economics.

862
00:42:18,320 --> 00:42:18,640
Speaker 1: Of it were.

863
00:42:18,760 --> 00:42:21,719
Speaker 3: Yeah, maybe I've made the great mistake of thinking that

864
00:42:21,760 --> 00:42:25,200
Speaker 3: people value anything of artistic high talent and that slop

865
00:42:25,239 --> 00:42:28,319
Speaker 3: will always win, which is usually the case, I guess

866
00:42:28,400 --> 00:42:30,120
Speaker 3: right now in our current system.

867
00:42:30,160 --> 00:42:30,760
Speaker 1: You're not wrong.

868
00:42:31,040 --> 00:42:33,200
Speaker 3: And at the end of the day, one thing that

869
00:42:33,239 --> 00:42:36,919
Speaker 3: I thought was really important and illuminating from what they said,

870
00:42:36,920 --> 00:42:38,640
Speaker 3: because they made this whole case for why they are

871
00:42:38,719 --> 00:42:41,719
Speaker 3: new movies on Netflix. But they eventually kind of gave

872
00:42:41,760 --> 00:42:44,120
Speaker 3: the game away about the executives and how they talk,

873
00:42:44,440 --> 00:42:47,080
Speaker 3: and I'd never heard words put to it.

874
00:42:47,120 --> 00:42:49,359
Speaker 1: But I had watched the first.

875
00:42:49,120 --> 00:42:51,920
Speaker 3: Episode of this New Stranger Things just you know whatever,

876
00:42:52,000 --> 00:42:54,319
Speaker 3: it's something to do during Christmas, and I was like,

877
00:42:54,480 --> 00:42:57,160
Speaker 3: this is the shittiest written show I have ever seen

878
00:42:57,320 --> 00:42:59,680
Speaker 3: in my entire life. Where they would gather around the

879
00:42:59,680 --> 00:43:03,880
Speaker 3: table and consistently reiterate the plot and like bang you

880
00:43:03,920 --> 00:43:05,960
Speaker 3: over the face, which is the opposite of good writing.

881
00:43:05,960 --> 00:43:08,680
Speaker 3: Good writing is when you're able to say all of

882
00:43:08,719 --> 00:43:11,440
Speaker 3: these different just to be like, you remember our brother John,

883
00:43:11,760 --> 00:43:14,560
Speaker 3: he died five years ago, right, just like you need

884
00:43:14,600 --> 00:43:16,840
Speaker 3: to try and engineer in a script to give that

885
00:43:16,920 --> 00:43:19,319
Speaker 3: away without the characteristics, saying.

886
00:43:19,040 --> 00:43:22,400
Speaker 2: The central tension it works Gloring there is his breakup

887
00:43:22,440 --> 00:43:23,239
Speaker 2: with Jamie.

888
00:43:23,080 --> 00:43:26,680
Speaker 3: Exactly correct. That is what all Netflix slop now currently

889
00:43:26,719 --> 00:43:31,040
Speaker 3: sounds like. They revealed why that is because people are

890
00:43:31,040 --> 00:43:33,399
Speaker 3: on their phones and you have to be banged over

891
00:43:33,400 --> 00:43:35,400
Speaker 3: the head with the plot over and over again or

892
00:43:35,480 --> 00:43:36,399
Speaker 3: you're going to lose track.

893
00:43:36,520 --> 00:43:38,799
Speaker 1: Here's what they had to say, aperience of watching at home.

894
00:43:38,840 --> 00:43:41,239
Speaker 12: I think you know, you're watching in a room, the

895
00:43:41,320 --> 00:43:43,480
Speaker 12: lights are on, other shit's going on, the kids are

896
00:43:43,560 --> 00:43:45,320
Speaker 12: running around, the dogs are running around, whatever it is,

897
00:43:45,360 --> 00:43:47,160
Speaker 12: you know what I mean. It's just a very different

898
00:43:47,480 --> 00:43:50,600
Speaker 12: level of attention that you're willing to or that you're

899
00:43:50,600 --> 00:43:53,040
Speaker 12: able to give to it. And that has a big effect,

900
00:43:53,080 --> 00:43:54,840
Speaker 12: and it also ends up having an effect or is

901
00:43:54,840 --> 00:43:58,200
Speaker 12: starting to have an effect on how you make movies,

902
00:43:58,280 --> 00:44:02,719
Speaker 12: like for instance, Netflix, you know, the standard way to

903
00:44:02,719 --> 00:44:05,200
Speaker 12: make an action movie that we learned was, you know,

904
00:44:05,239 --> 00:44:07,680
Speaker 12: you usually have like three set pieces, one in the

905
00:44:07,680 --> 00:44:09,520
Speaker 12: first act one and the second one and the third

906
00:44:09,560 --> 00:44:11,319
Speaker 12: and you know you kind of they kind of ramp

907
00:44:11,400 --> 00:44:13,080
Speaker 12: up and the big one with all the explosions, and

908
00:44:13,120 --> 00:44:14,640
Speaker 12: you spend most of your money on that one in

909
00:44:14,680 --> 00:44:18,040
Speaker 12: the third act that's your kind of finale. And now

910
00:44:18,040 --> 00:44:20,080
Speaker 12: they're you know, they're like, can we get a big

911
00:44:20,080 --> 00:44:22,279
Speaker 12: one in the first five minutes to get somebody? You know,

912
00:44:22,360 --> 00:44:25,480
Speaker 12: we want people to stay yeah, tuned in and ken

913
00:44:26,000 --> 00:44:29,040
Speaker 12: and you know, it wouldn't be terrible if you reiterated

914
00:44:29,040 --> 00:44:31,640
Speaker 12: the plot three or four times in the dialogue because

915
00:44:31,760 --> 00:44:34,160
Speaker 12: people are on their phones while they're watching, you know

916
00:44:34,200 --> 00:44:36,799
Speaker 12: what I mean. So then it's gonna really start to

917
00:44:36,840 --> 00:44:39,200
Speaker 12: infringe on creatively.

918
00:44:39,239 --> 00:44:41,160
Speaker 11: Yeah, we're telling, but then you look at our lessons.

919
00:44:41,280 --> 00:44:43,480
Speaker 11: Didn't do anything, didn't do any of the fucking great

920
00:44:43,520 --> 00:44:44,000
Speaker 11: you know what I mean.

921
00:44:44,560 --> 00:44:47,160
Speaker 3: See, that's why I was like, I was like, Wow,

922
00:44:47,239 --> 00:44:50,399
Speaker 3: that is why Netflix slop sounds the way that it does.

923
00:44:50,520 --> 00:44:54,120
Speaker 3: It's because it's purely regression to the mean, as he

924
00:44:54,239 --> 00:44:59,120
Speaker 3: just said with Ai, where anything, even even great concept shows,

925
00:44:59,560 --> 00:45:02,480
Speaker 3: they you know, I don't think it's deniable, like Stranger

926
00:45:02,560 --> 00:45:04,600
Speaker 3: Things season one, like that was a phenomenon. People really

927
00:45:04,600 --> 00:45:06,480
Speaker 3: love that show, but what it ended up being like,

928
00:45:06,520 --> 00:45:09,360
Speaker 3: oh my god, it's horrific. And there are multiple of

929
00:45:09,400 --> 00:45:12,000
Speaker 3: these kind of over the years, and they just keep

930
00:45:12,040 --> 00:45:15,800
Speaker 3: pumping out multiple seasons of this absolute nonsense, which just

931
00:45:15,840 --> 00:45:18,560
Speaker 3: continues to get worse and worse and worse and worse,

932
00:45:18,560 --> 00:45:21,000
Speaker 3: And I didn't realize how much of this like second

933
00:45:21,000 --> 00:45:25,040
Speaker 3: screen phenomenon is now being directly pressured into the very

934
00:45:25,080 --> 00:45:26,760
Speaker 3: content which is now dominating.

935
00:45:26,920 --> 00:45:27,840
Speaker 1: And so I don't know.

936
00:45:27,920 --> 00:45:30,120
Speaker 3: Sometimes this may be a long winded way of saying

937
00:45:30,160 --> 00:45:33,280
Speaker 3: like I'm now afraid. Originally I was generally supportive of

938
00:45:33,280 --> 00:45:37,680
Speaker 3: of Netflix buying Warner Brothers and HBO over Paramount Skuydance,

939
00:45:37,680 --> 00:45:39,800
Speaker 3: But now I'm like, wait, we don't want this nonsense

940
00:45:39,840 --> 00:45:42,600
Speaker 3: to come to HBO either. Like I'm currently watching the

941
00:45:42,600 --> 00:45:45,680
Speaker 3: show industry, I've never seen anything like it where it

942
00:45:45,719 --> 00:45:46,400
Speaker 3: is now currently.

943
00:45:46,840 --> 00:45:49,160
Speaker 1: Only they could do that, Like, only they could.

944
00:45:49,000 --> 00:45:51,000
Speaker 3: Do that, and it would never be able to exist

945
00:45:51,040 --> 00:45:53,560
Speaker 3: in the sloppy list world of where we are right

946
00:45:53,600 --> 00:45:56,320
Speaker 3: now on Netflix. So maybe you're correct that the AI

947
00:45:56,400 --> 00:45:58,359
Speaker 3: slop is ultimately which just what's going to take over.

948
00:45:58,600 --> 00:46:02,040
Speaker 2: These guys were very like they were very optimistic, and

949
00:46:02,080 --> 00:46:05,400
Speaker 2: they were very like, you know, they were talking about how, look,

950
00:46:05,480 --> 00:46:08,440
Speaker 2: we've experienced these changes in your own history, and people

951
00:46:08,440 --> 00:46:11,160
Speaker 2: every time are upset about what's lost, but ultimately, you know,

952
00:46:11,200 --> 00:46:13,600
Speaker 2: it's more convenient for people to be at home on there,

953
00:46:13,680 --> 00:46:16,040
Speaker 2: like you know, watching them have usually got a big,

954
00:46:16,160 --> 00:46:19,879
Speaker 2: nice flat screen TV, and it's a convenient experience. And

955
00:46:20,040 --> 00:46:22,880
Speaker 2: they did talk about how you do lose something that

956
00:46:23,000 --> 00:46:26,440
Speaker 2: is a different experience when you have the distractions contained

957
00:46:26,440 --> 00:46:28,399
Speaker 2: in your house, whether it's your kids or your dog,

958
00:46:28,480 --> 00:46:31,200
Speaker 2: or your tours or whatever it is, that that is

959
00:46:31,239 --> 00:46:33,680
Speaker 2: a different experience from being in the theater together. But

960
00:46:33,719 --> 00:46:35,840
Speaker 2: they were sort of like ambivalent and they're like, that's fine,

961
00:46:36,000 --> 00:46:38,080
Speaker 2: but you know, I've kind of come to view things

962
00:46:38,120 --> 00:46:42,240
Speaker 2: a little bit differently of that all of the people

963
00:46:42,280 --> 00:46:45,560
Speaker 2: in the past who warned about like the radio was

964
00:46:45,640 --> 00:46:48,560
Speaker 2: going to take away from family time or the TV

965
00:46:49,320 --> 00:46:52,719
Speaker 2: is going to create this like homogeneous culture and we're

966
00:46:52,719 --> 00:46:54,879
Speaker 2: going to be you know, and the warnings they had

967
00:46:54,880 --> 00:46:56,360
Speaker 2: about that and the way that it would turn you

968
00:46:56,400 --> 00:46:59,759
Speaker 2: into a zombie, like, they weren't wrong. They were you know,

969
00:47:00,080 --> 00:47:02,439
Speaker 2: they were all correct, and they were correct about that

970
00:47:02,480 --> 00:47:05,000
Speaker 2: there would be things that would be lost that come

971
00:47:05,040 --> 00:47:07,879
Speaker 2: along with that technology. And the fact that we grew

972
00:47:07,920 --> 00:47:09,480
Speaker 2: up with it and that was just the only world

973
00:47:09,520 --> 00:47:11,600
Speaker 2: that we knew and we were fine with it doesn't

974
00:47:11,600 --> 00:47:15,320
Speaker 2: mean that they were incorrect about the parts of life

975
00:47:15,400 --> 00:47:17,800
Speaker 2: that would be pushed to the Margins by the advent

976
00:47:17,840 --> 00:47:18,520
Speaker 2: of that technology.

977
00:47:18,560 --> 00:47:20,200
Speaker 3: Yeah, one of my friends just recommended this book to me.

978
00:47:20,239 --> 00:47:21,640
Speaker 3: I think it's called like Tech Exit.

979
00:47:22,000 --> 00:47:22,520
Speaker 1: I love this.

980
00:47:23,440 --> 00:47:28,879
Speaker 3: She quit television's she like deleted all social media, which

981
00:47:28,960 --> 00:47:31,560
Speaker 3: you know, that's like step one. Yea, she quit TV period.

982
00:47:31,760 --> 00:47:34,919
Speaker 3: She does not watch television dinner. She's a mom of two.

983
00:47:35,000 --> 00:47:36,880
Speaker 1: And I was like, man, that's like I kind of

984
00:47:36,920 --> 00:47:37,799
Speaker 1: want to I want to try it.

985
00:47:37,800 --> 00:47:40,080
Speaker 3: A little bit, you know, as somebody, because exactly what

986
00:47:40,120 --> 00:47:43,720
Speaker 3: you're talking about is, you know, the original or started

987
00:47:43,760 --> 00:47:46,640
Speaker 3: with the TV dinner in the fifties and the sixties,

988
00:47:46,800 --> 00:47:49,200
Speaker 3: which took people away from the dinner table, and then

989
00:47:49,520 --> 00:47:52,520
Speaker 3: what it became is now people will they may even

990
00:47:52,560 --> 00:47:54,879
Speaker 3: be sitting you know, how many times have you gone

991
00:47:54,880 --> 00:47:56,600
Speaker 3: out to dinner and somebody across the table from me

992
00:47:56,760 --> 00:47:58,719
Speaker 3: was like this on their phone, right, Yeah, And so

993
00:47:58,840 --> 00:48:02,320
Speaker 3: now we created the device which is now here everywhere.

994
00:48:02,320 --> 00:48:04,080
Speaker 3: And you know, not to be like a crazy ludited,

995
00:48:04,120 --> 00:48:06,160
Speaker 3: especially for two people to make their career on the internet,

996
00:48:06,560 --> 00:48:09,120
Speaker 3: but it's one of those where in your own personal

997
00:48:09,120 --> 00:48:11,319
Speaker 3: life you're right in that you do have to ask

998
00:48:11,600 --> 00:48:14,960
Speaker 3: and say that many of the most vicious critics like

999
00:48:15,160 --> 00:48:18,080
Speaker 3: when we think back about the television and what people

1000
00:48:18,120 --> 00:48:21,160
Speaker 3: said about that. Maybe, like in the late eighties and nineties,

1001
00:48:21,239 --> 00:48:23,680
Speaker 3: especially with cable TV, there was a real reckoning in

1002
00:48:23,680 --> 00:48:25,719
Speaker 3: the same way are talking about AI. They're like, this

1003
00:48:25,760 --> 00:48:28,799
Speaker 3: is a disaster, it's actually going to destroy you know,

1004
00:48:28,960 --> 00:48:31,080
Speaker 3: at that time, people were watching seven hours of TV

1005
00:48:31,480 --> 00:48:35,719
Speaker 3: per day, family unit. It'll make everybody dumber. I think

1006
00:48:35,760 --> 00:48:39,560
Speaker 3: they're probably right. You know, it did kill critical thinking

1007
00:48:39,840 --> 00:48:42,480
Speaker 3: if you want to look, really, the most disastrous statistics

1008
00:48:42,719 --> 00:48:46,400
Speaker 3: around phones and AI is books. The amount of Americans

1009
00:48:46,400 --> 00:48:48,319
Speaker 3: now who read even one book a year is like

1010
00:48:48,360 --> 00:48:52,359
Speaker 3: a record all time low. The bookstore industry is only

1011
00:48:52,400 --> 00:48:54,719
Speaker 3: prospering at the high end for people who make it

1012
00:48:54,760 --> 00:48:58,200
Speaker 3: like a social currency and value to read, and professors

1013
00:48:58,200 --> 00:49:01,080
Speaker 3: across the country are talking about all people do is

1014
00:49:01,120 --> 00:49:04,880
Speaker 3: just chat shept summarize books and readings instead of actually

1015
00:49:04,920 --> 00:49:07,239
Speaker 3: engaging or reading with the text. I think it's a

1016
00:49:07,480 --> 00:49:09,319
Speaker 3: I mean, obviously not only in terms of people making

1017
00:49:09,320 --> 00:49:11,759
Speaker 3: people dumber, but then you create a culture, just like

1018
00:49:11,840 --> 00:49:14,200
Speaker 3: you're talking about with TV and radio, where if your

1019
00:49:14,280 --> 00:49:16,319
Speaker 3: kids don't even see you reading, Like my kid is

1020
00:49:16,320 --> 00:49:17,800
Speaker 3: now this age where she wants to eat what I

1021
00:49:17,840 --> 00:49:19,719
Speaker 3: want to eat, which is a very powerful thing because

1022
00:49:19,719 --> 00:49:22,359
Speaker 3: you're like, wow, mimicry is literally the way that these

1023
00:49:22,440 --> 00:49:25,560
Speaker 3: children develop and learn in the world. Well, she would

1024
00:49:25,640 --> 00:49:27,879
Speaker 3: never see me, you know. I famously have only listened

1025
00:49:27,880 --> 00:49:29,920
Speaker 3: to audiobooks for ten years. I started breaking out the real

1026
00:49:29,960 --> 00:49:31,799
Speaker 3: books again because I'm like, she needs to see me

1027
00:49:31,840 --> 00:49:33,520
Speaker 3: read because then she'll want to read. That's the only

1028
00:49:33,560 --> 00:49:35,400
Speaker 3: way to normalize the type of behavior. But you have

1029
00:49:35,440 --> 00:49:36,440
Speaker 3: to be very intentional about it.

1030
00:49:36,440 --> 00:49:39,720
Speaker 2: Because my eight year old Ida, We're talking about reading

1031
00:49:39,800 --> 00:49:41,440
Speaker 2: and how much I enjoy and where she's like, you

1032
00:49:41,480 --> 00:49:43,920
Speaker 2: never read, was like, what are you talking about? But

1033
00:49:44,040 --> 00:49:46,360
Speaker 2: it's because she Yeah, she doesn't see me with the book.

1034
00:49:46,719 --> 00:49:49,200
Speaker 2: And even if I am reading a physical book, it's

1035
00:49:49,320 --> 00:49:53,600
Speaker 2: usually on like my phone right and then, but mostly

1036
00:49:53,640 --> 00:49:56,560
Speaker 2: what I do is listen to audiobooks. Yeah, same, So yeah,

1037
00:49:56,600 --> 00:49:59,479
Speaker 2: I had that realization recently of like, oh, like, even

1038
00:49:59,520 --> 00:50:01,400
Speaker 2: though I I am a reader and it is an

1039
00:50:01,440 --> 00:50:03,759
Speaker 2: important part of my life, she actually is not.

1040
00:50:03,880 --> 00:50:05,160
Speaker 1: She has no clue witnessing that.

1041
00:50:06,239 --> 00:50:07,520
Speaker 2: But in any case, to go back to it, I

1042
00:50:07,560 --> 00:50:11,200
Speaker 2: mean we also have to acknowledge like even as obviously

1043
00:50:11,280 --> 00:50:15,680
Speaker 2: the drawbacks blah blah blah, we also we like we

1044
00:50:15,840 --> 00:50:18,239
Speaker 2: like having the thing, you know, I mean there are

1045
00:50:18,560 --> 00:50:20,960
Speaker 2: obviously there are positive things about it too, which is

1046
00:50:21,000 --> 00:50:24,160
Speaker 2: why it is so widespread and why it has you know,

1047
00:50:24,200 --> 00:50:27,000
Speaker 2: completely taken into the culture. But in any case, the

1048
00:50:27,040 --> 00:50:29,880
Speaker 2: two guys very thoughtful, very interesting conversation.

1049
00:50:29,480 --> 00:50:32,279
Speaker 1: People, especially the first half. Yeah, it was very good. Yeah.

1050
00:50:32,600 --> 00:50:34,680
Speaker 3: I will listen to them talk anytime any day. Also,

1051
00:50:34,719 --> 00:50:37,960
Speaker 3: Matt Ben if you're listening, man would love to talk.

1052
00:50:38,239 --> 00:50:39,840
Speaker 1: We can talk all week. We don't even have to

1053
00:50:39,840 --> 00:50:41,680
Speaker 1: talk about new movies. We can only do old that

1054
00:50:41,680 --> 00:50:43,960
Speaker 1: would be even better. All right, thank you everybody for listening.

1055
00:50:44,000 --> 00:50:44,600
Speaker 1: We appreciate it.

1056
00:50:44,600 --> 00:50:46,439
Speaker 3: I know we went very long today, so the show

1057
00:50:46,480 --> 00:50:48,040
Speaker 3: is going to be late. It is what it is.

1058
00:50:48,280 --> 00:50:51,720
Speaker 3: I hope you enjoy it. Nonetheless, and counter no, Ryan

1059
00:50:51,760 --> 00:50:53,239
Speaker 3: and Emily will see you all tomorrow. There is no

1060
00:50:53,320 --> 00:50:53,799
Speaker 3: count of the show.

1061
00:50:53,840 --> 00:50:56,080
Speaker 2: Formerly, I don't know why I like to call.

1062
00:50:55,960 --> 00:50:58,880
Speaker 1: It Ryan and Emily will see you all tomorrow.

1063
00:51:01,440 --> 00:51:05,719
Speaker 10: Put tagotu