WEBVTT - Chinese Humanoid Robots Aren’t Welcome Here, US Says - Week in Tech

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<v Speaker 1>Read, Taylor, I want to ask you to open this

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<v Speaker 1>week's episode. Would you shop online if you didn't actually

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<v Speaker 1>get anything in the mail. But I'm asking because I've

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<v Speaker 1>recently read about these dopamine sites out of South Korea

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<v Speaker 1>that let you look through non existent products with made

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<v Speaker 1>up reviews and promotions that you can add to your cart,

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<v Speaker 1>click buy, track your packages and never receive a thing,

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<v Speaker 1>No money spent, just the satisfaction of buying something online.

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<v Speaker 2>No you got, Taylor.

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<v Speaker 3>I think I already do this with Zillo every night

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<v Speaker 3>where I'm you know, perusing multimillion dollar houses in Pasadena

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<v Speaker 3>adding them to my favorites.

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<v Speaker 2>Like I don't do the Zilla thing because there's nothing

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<v Speaker 2>on the market here in the day area, but I

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<v Speaker 2>would know. Like what I would do, though, is could

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<v Speaker 2>I order stuff but not have the package just show

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<v Speaker 2>up at my front door, so that, like all my

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<v Speaker 2>neighbors know that we're just like those horrible people who

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<v Speaker 2>order like twenty things on Amazon every.

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<v Speaker 4>Day that the note packages thing.

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<v Speaker 2>For sure, I still want the product stuff.

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<v Speaker 4>Welcome to Tech Stuff.

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<v Speaker 1>I'm as Volocian and this is the week in Tech

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<v Speaker 1>where I'm joined by the world's most clubs and reporters.

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<v Speaker 4>To break down what's really happening in tech right now.

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<v Speaker 1>Today, we're joined by Taylor Lorenzo use a mag and

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<v Speaker 1>Read Albergotti, tech editor at Centophore.

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<v Speaker 2>Welcome both, great to be here, Thanks for having us.

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<v Speaker 1>Great to have you both, As always read, the FCC

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<v Speaker 1>moved to ban Chinese humanoid robots and quadrupeds from entering

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<v Speaker 1>the US, which I can't read without laughing. But I mean,

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<v Speaker 1>what's what's going on here?

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<v Speaker 3>Like?

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<v Speaker 4>How serious is this story?

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<v Speaker 1>What what does it have to do with US robot

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<v Speaker 1>makers lobbying efforts?

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<v Speaker 4>And what's gonna happen next?

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<v Speaker 2>Yeah, I mean this is this is another sort of

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<v Speaker 2>it's its industrial policy protectionism. I guess we shouldn't be surprised.

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<v Speaker 2>I mean, they're already are no buy D Chinese cars

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<v Speaker 2>in the US and it and on its face, you're

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<v Speaker 2>you're you'd sort of put into that box and you say, okay,

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<v Speaker 2>this this makes sense. We want US robot makers to

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<v Speaker 2>to kind of have a clear run at this. But

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<v Speaker 2>I think there's a there and and granted like there

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<v Speaker 2>will be exceptions to this, right, this is not like

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<v Speaker 2>this is not a law. This is you know, this

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<v Speaker 2>is this is policy coming out of the White House essentially,

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<v Speaker 2>but like on its face, you there are these big

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<v Speaker 2>questions like a bunch if you go into any sort

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<v Speaker 2>of like AI company that's doing anything in the physical

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<v Speaker 2>world and in the Bay Area right now, they've got

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<v Speaker 2>these Chinese robots like sitting around from all these different companies,

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<v Speaker 2>and they're you know, some of them are cheap, like

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<v Speaker 2>ten thousand apiece, and they're doing all sorts of testing

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<v Speaker 2>on these things, right They're they're essentially building software and

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<v Speaker 2>the and the hardware is what they use to you know,

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<v Speaker 2>to gather data or just test out their their algorithm.

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<v Speaker 2>So I think it's actually like potentially detrimental to innovation.

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<v Speaker 2>So this is all and it's the same thing with

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<v Speaker 2>like the same issue with these Chinese open source models.

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<v Speaker 1>Right It's like, I want to talk about the open

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<v Speaker 1>source models, but let's stay with the robots for a

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<v Speaker 1>little bit. I mean, the detail about the quadrupeds was

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<v Speaker 1>the one that really really caught my eye because I

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<v Speaker 1>kind of thought the four legged robots were only for

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<v Speaker 1>YouTube videos that I didn't realized they were threat to America.

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<v Speaker 2>I saw I was in Boston a couple of weeks

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<v Speaker 2>ago and I saw some people walking their their robot

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<v Speaker 2>dicers that looked like, yeah, they looked like they were

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<v Speaker 2>sort of like MIT researchers or something. But no, I

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<v Speaker 2>mean it's it's like the same issue though. It's the

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<v Speaker 2>same principle, which is like you try to you try

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<v Speaker 2>to stop the you know, the Chinese from encroaching in

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<v Speaker 2>the US market, and then you sort of like also

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<v Speaker 2>hinder your own innovation. So these things always come at

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<v Speaker 2>a cost. So I think that the trick is going

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<v Speaker 2>to be figuring out how to thread that needle right, Like,

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<v Speaker 2>do what you need to do, you know, if you're

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<v Speaker 2>the White House, to to sort of protect US companies,

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<v Speaker 2>stop the Chinese from i don't know, dumping robots if

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<v Speaker 2>that's even a thing, but then also allow US researchers

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<v Speaker 2>to still, you know, to still be able to innovate

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<v Speaker 2>and come. You know, you don't want like a situation

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<v Speaker 2>where there's like one or two robotics companies in the

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<v Speaker 2>US and if they don't, if they don't just happen

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<v Speaker 2>to win this race outright, you know, the US is

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<v Speaker 2>way behind.

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<v Speaker 1>This will be like the cause in the Soviet Union

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<v Speaker 1>when the when in nineteen eighteen nine, Right, the US

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<v Speaker 1>will have all of these like Dusty Treban style robots

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<v Speaker 1>call the Tita. Have you been following the robot element

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<v Speaker 1>of this story.

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<v Speaker 3>Yes, I've been following. And does this mean that rumbas

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<v Speaker 3>are banned? I saw some headline basically implying.

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<v Speaker 2>That I have a Chinese I have a Chinese robot vacuum.

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<v Speaker 2>That's really really good. I think it's a way outperforms

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<v Speaker 2>the rumba. So I hope, I hope that's not the case. Look,

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<v Speaker 2>I think this is like all of these policies. It's

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<v Speaker 2>just the thing to remember is that you can do

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<v Speaker 2>whatever you want to try to stop China these tech

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<v Speaker 2>and you know, stop them from i don't know, catching

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<v Speaker 2>up or ripping off American technology. The US will not

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<v Speaker 2>win unless it can move faster than China on innovation.

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<v Speaker 2>That is the most important thing about this race, and

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<v Speaker 2>I think it often. I think it often gets sort

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<v Speaker 2>of forgotten or pushed to the side.

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<v Speaker 3>I totally agree with Red and yeah, I mean I

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<v Speaker 3>was just reading this article on the Verge talking about

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<v Speaker 3>like what's actually sort of included in this span and

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<v Speaker 3>it's significantly broader than you would think. I mean, Obviously

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<v Speaker 3>we're talking about the humanoid robots and the quadrupeds, but

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<v Speaker 3>it's not just that, it's it's far broader. This ban

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<v Speaker 3>covers basically any new software controlled robot that travels over

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<v Speaker 3>the ground or weighs more than four point four pounds,

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<v Speaker 3>including the DOC, and that can perceive its own environment

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<v Speaker 3>and has wireless which is basically any robot vacuum like

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<v Speaker 3>it's it's a lot of like household devices. Like I

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<v Speaker 3>think people don't realize as well just how much stuff

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<v Speaker 3>comes from China, Like how like automated I have this

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<v Speaker 3>like automated you know, like watering system thing that I

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<v Speaker 3>got from Amazon. I'm sure it's some Chinese little robot thing.

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<v Speaker 4>Oh you did.

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<v Speaker 1>We were talking about the garden last week and you

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<v Speaker 1>were talking about wanting a gunting robot. And now you've

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<v Speaker 1>now you filled the trigger.

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<v Speaker 3>Exactly and I've ordered a Chinese gardening you know, watering thing.

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<v Speaker 3>Probably that's potentially going to be illegal, legal, but but

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<v Speaker 3>I know I snuck in right under the van. I

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<v Speaker 3>just think, like, I mean, what Reid said is true.

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<v Speaker 3>I think this is ridiculous. Like I understand from a

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<v Speaker 3>consumer perspective, you know, with the electric cars. Okay, protecting

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<v Speaker 3>our car industry in some way, but you know, at

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<v Speaker 3>some point, robotics are becoming so pervasive, and this just

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<v Speaker 3>seems like, you know, we we need to compete harder,

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<v Speaker 3>like we can't. We're I feel like we're the declining

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<v Speaker 3>and we're just trying to like protect this declining industry

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<v Speaker 3>and we need to allow our researchers to compete. And

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<v Speaker 3>and that means that you know, giving technologists access to

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<v Speaker 3>this cutting.

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<v Speaker 1>Head technology on the kind of robotspan Is this like

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<v Speaker 1>kind of a thing that people expect to be in

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<v Speaker 1>forced or is this kind of like a staking of

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<v Speaker 1>some political kind of pulturing.

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<v Speaker 4>Do we do we have any idea?

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<v Speaker 2>Well, I like I was sort of getting at earlier.

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<v Speaker 2>I mean, this is this is just you know, these

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<v Speaker 2>are just orders coming out of the White House. So

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<v Speaker 2>it's not like this is not a law. And I

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<v Speaker 2>think they always they you know, like I think at

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<v Speaker 2>some point they're going to go, oh my god, like

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<v Speaker 2>this is way too broad. We got to find loop.

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<v Speaker 2>You know, there's gonna be loopholes or or carve outs

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<v Speaker 2>for specific areas, like you know, this is what always happens.

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<v Speaker 2>It's like this this shoot from the hip sort of

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<v Speaker 2>you know, proclamation policy, I guess strategy, and then and

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<v Speaker 2>then you go back and make all it. And the

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<v Speaker 2>same thing happened with tariffs, right It's like, oh my god,

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<v Speaker 2>we have all these tariffs. And then it's like, well,

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<v Speaker 2>this thing's carved out and that thing's carved out, and

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<v Speaker 2>you eventually get to like, I don't know someplace where

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<v Speaker 2>it's where it's logical. So I just take all of

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<v Speaker 2>it with a grain of salt and just figure it's

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<v Speaker 2>all going to change.

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<v Speaker 3>I just think in the meantime, the damage is done.

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<v Speaker 3>I mean, the tariffs are good example, that was like

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<v Speaker 3>a huge economic shock. It caused prices to increase for consumers,

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<v Speaker 3>like it did cause a lot of I would argue

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<v Speaker 3>harm to our economy. And I think when we do

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<v Speaker 3>things like this as well, like yeah, maybe you're right

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<v Speaker 3>read and I agree, like it will have to be

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<v Speaker 3>rolled back in some way because it's nonsensical. But in

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<v Speaker 3>the meantime, it's hurt innovation in the meantime, it slowed

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<v Speaker 3>us down. In the meantime, it's created liability for startups

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<v Speaker 3>that don't want to take on any liability. So it

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<v Speaker 3>just seems bad.

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<v Speaker 2>Yeah, I mean, it'd be one thing if they did

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<v Speaker 2>this and they're like, and we're going to put you know,

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<v Speaker 2>more money into academic research.

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<v Speaker 4>That was my next question.

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<v Speaker 1>So is there going to be is there any commensurate

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<v Speaker 1>effort to stimulate the American robotics industry. I so Deep

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<v Speaker 1>Mind had an announcement today about some some new kind

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<v Speaker 1>of robotics program and obviously read you we talked about

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<v Speaker 1>robotics with applied intuition last week on the show. So

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<v Speaker 1>it seems like there is like some action in the

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<v Speaker 1>American robotics sphere.

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<v Speaker 2>Of course, this is a huge industry. There's tons of

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<v Speaker 2>private money going into it. But I think if you're

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<v Speaker 2>the US, like the private sectors going to do what

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<v Speaker 2>it's going to do, the levers that they can pull,

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<v Speaker 2>I think are an academic research. Right. That's where like

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<v Speaker 2>if you think the robotics race is over, like I

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<v Speaker 2>think that's insane. Like I think there's still a lot

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<v Speaker 2>of innovation that's going to happen, and it's maybe not

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<v Speaker 2>all going to come from the private sector. Like if

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<v Speaker 2>you want to do something policy wise, like you know,

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<v Speaker 2>push forward research, right, basic research that's going to you know,

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<v Speaker 2>help advance this industry. There's so many different areas that

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<v Speaker 2>would speed things up. It's it's long term thinking, though,

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<v Speaker 2>right and I think that's what Washington is really short

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<v Speaker 2>on right now.

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<v Speaker 3>I mean, I also just think of like the drama

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<v Speaker 3>over the H one B visas and the way that

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<v Speaker 3>we're treating immigrants. And there are so many talented scientists, engineers,

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<v Speaker 3>roboticists that you know, might be from India, might be

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<v Speaker 3>from other places that we've also pushed out of our country,

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<v Speaker 3>and I think, I mean, I know that's affected startup's

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<v Speaker 3>ability to recruit. I was just talking to somebody last

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<v Speaker 3>night who is living in Canada and what is has

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<v Speaker 3>a job in a Mameric can start up but can't

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<v Speaker 3>start because of this visa process. This is just it's

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<v Speaker 3>really ridiculous.

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<v Speaker 2>Yeah, I mean, it's a it's a this is like

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<v Speaker 2>such a challenge because I mean, what you really want

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<v Speaker 2>to do is like is not sort of bam the

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<v Speaker 2>Chinese robots, but find the people who are really the

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<v Speaker 2>most talented people in China building the robots, bring them

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<v Speaker 2>to the US, have them build the robots here. But

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<v Speaker 2>then there's this worry that they're all spies. Or they

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<v Speaker 2>all will be spies, right, and and there is I mean,

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<v Speaker 2>these are legitimate concerns, but I think there's like a

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<v Speaker 2>I mean this happened in that you mentioned the Soviet

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<v Speaker 2>era too. I mean this happened in the Soviet era

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<v Speaker 2>like the US because of its system, because of its

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<v Speaker 2>open system, you know. There it makes you know, spying easier,

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<v Speaker 2>and so that's just a downside. But then that open

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<v Speaker 2>system leads to like massive innovation, so it's always a

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<v Speaker 2>trade off.

0:10:51.480 --> 0:10:53.920
<v Speaker 1>I got of liked on that word open. Let's talk

0:10:53.920 --> 0:10:55.800
<v Speaker 1>about open source models. I think for the third week

0:10:55.800 --> 0:10:58.679
<v Speaker 1>in a row this is a textuff record, but the

0:10:58.720 --> 0:11:03.079
<v Speaker 1>news keeps rumbling on. So another Chinese export, of course

0:11:03.280 --> 0:11:07.240
<v Speaker 1>is open source models from Chinese companies like Zai and

0:11:07.320 --> 0:11:08.199
<v Speaker 1>moonshot Ai.

0:11:09.720 --> 0:11:11.439
<v Speaker 4>Why is it study in the news for so long?

0:11:11.520 --> 0:11:15.319
<v Speaker 1>And also read you wrote about this concern about censorship

0:11:15.480 --> 0:11:18.760
<v Speaker 1>an Ai models Chinese models that may be unfounded.

0:11:19.520 --> 0:11:22.559
<v Speaker 2>Yeah, there was this research study I wrote about yesterday

0:11:23.040 --> 0:11:27.160
<v Speaker 2>from CTGT which does this interpretability research, like looking at

0:11:27.240 --> 0:11:30.680
<v Speaker 2>how these models actually work so they can build you know,

0:11:30.800 --> 0:11:33.400
<v Speaker 2>products for the private sector that are sort of harnessed

0:11:33.440 --> 0:11:36.920
<v Speaker 2>and don't go off the rails. They did this experiment

0:11:36.960 --> 0:11:40.480
<v Speaker 2>where they took a deep seek model and they fine

0:11:40.520 --> 0:11:43.800
<v Speaker 2>tuned from that model and then tested the before and

0:11:43.840 --> 0:11:47.960
<v Speaker 2>after Chinese censorship and found that the censorship was essentially

0:11:48.000 --> 0:11:50.959
<v Speaker 2>gone once they once they built this new model, the

0:11:51.280 --> 0:11:54.800
<v Speaker 2>base of it was was an open ai OSS like

0:11:54.920 --> 0:11:57.719
<v Speaker 2>open weights model, and then it was fine tuned or

0:11:57.800 --> 0:12:01.200
<v Speaker 2>taught from deep Seek. And so there have been this

0:12:01.200 --> 0:12:04.880
<v Speaker 2>this talk of like subliminal messages being passed on from

0:12:04.920 --> 0:12:09.160
<v Speaker 2>the teacher model to the student model. It gets it

0:12:09.200 --> 0:12:11.679
<v Speaker 2>gets pretty technical and you can get into weeds. But

0:12:11.760 --> 0:12:14.160
<v Speaker 2>like the long story short is like we need more

0:12:14.200 --> 0:12:17.120
<v Speaker 2>research on this. But what it looks like is I

0:12:17.160 --> 0:12:21.559
<v Speaker 2>think these these Chinese models are actually like not as

0:12:21.640 --> 0:12:24.400
<v Speaker 2>much of a propaganda risk as you think because they

0:12:24.440 --> 0:12:28.320
<v Speaker 2>will get changed and filtered through all these different techniques.

0:12:28.920 --> 0:12:30.840
<v Speaker 2>And it also goes to this research point. I mean,

0:12:30.880 --> 0:12:34.360
<v Speaker 2>this is like really interesting research that wouldn't happen unless

0:12:34.400 --> 0:12:37.600
<v Speaker 2>there were these Chinese open source models. So it's another

0:12:38.720 --> 0:12:42.319
<v Speaker 2>I guess point in favor of the pro open source people.

0:12:42.960 --> 0:12:47.200
<v Speaker 3>Yeah. Absolutely, I mean I just think that like it's

0:12:47.240 --> 0:12:50.880
<v Speaker 3>it's really concerning to me that like our response is

0:12:50.920 --> 0:12:54.000
<v Speaker 3>to ban things like I you know, I watched everything

0:12:54.040 --> 0:12:57.320
<v Speaker 3>that happened with TikTok. I covered the musically sale to

0:12:57.360 --> 0:13:00.080
<v Speaker 3>Bite dance, which the government was totally fine with, and

0:13:00.080 --> 0:13:02.280
<v Speaker 3>then they turned around five years later and they were like, actually,

0:13:02.320 --> 0:13:06.200
<v Speaker 3>we're gonna ban TikTok, you know, based on nothing really

0:13:06.280 --> 0:13:11.280
<v Speaker 3>except that they it was keep challenging meta products, you know,

0:13:11.440 --> 0:13:13.600
<v Speaker 3>like there were all these like sort of like made

0:13:13.679 --> 0:13:17.280
<v Speaker 3>up concerns about China that never came to fruition. And

0:13:17.320 --> 0:13:19.640
<v Speaker 3>similar to the Chinese open source models. I mean, we

0:13:19.720 --> 0:13:21.679
<v Speaker 3>did have a lot of research on TikTok and there

0:13:21.760 --> 0:13:25.920
<v Speaker 3>ultimately was just no evidence of anything that the government

0:13:26.040 --> 0:13:30.800
<v Speaker 3>was claiming. And I just it's like if they had

0:13:30.920 --> 0:13:33.199
<v Speaker 3>proof of these things and if they were doing these

0:13:33.240 --> 0:13:35.959
<v Speaker 3>research and showing wow, the Chinese open source models are

0:13:36.080 --> 0:13:38.760
<v Speaker 3>really like biased. So this could be really dangerous for

0:13:38.800 --> 0:13:41.560
<v Speaker 3>American companies because if X Y z all right, then

0:13:41.600 --> 0:13:43.240
<v Speaker 3>I think, you know, we could have a talk about it.

0:13:43.280 --> 0:13:46.040
<v Speaker 3>But in this case, it just it's it seems like

0:13:46.120 --> 0:13:48.959
<v Speaker 3>these speculative fears and as read mentioned earlier, it feels

0:13:49.080 --> 0:13:52.440
<v Speaker 3>very cold war. It feels very like punching at ghosts,

0:13:52.480 --> 0:13:55.800
<v Speaker 3>and I just I really worry about the damage that

0:13:55.840 --> 0:13:58.440
<v Speaker 3>we're doing to our own tech landscape.

0:13:58.480 --> 0:14:02.120
<v Speaker 1>In the meantime you mentioned, I think Markackerberg did two

0:14:02.160 --> 0:14:03.960
<v Speaker 1>interviews this week, with one of the New York Times

0:14:03.960 --> 0:14:06.960
<v Speaker 1>and one with the Journal, his first first media appearances

0:14:07.040 --> 0:14:10.560
<v Speaker 1>since since his uh since his feed me guest lecture

0:14:10.640 --> 0:14:11.840
<v Speaker 1>a few weeks ago.

0:14:12.720 --> 0:14:12.800
<v Speaker 2>And.

0:14:14.360 --> 0:14:17.560
<v Speaker 1>He was basically complaining about the dominance of of open

0:14:17.600 --> 0:14:18.599
<v Speaker 1>a and ionanthropic.

0:14:18.720 --> 0:14:18.840
<v Speaker 2>Right.

0:14:19.000 --> 0:14:21.040
<v Speaker 4>Is that? Is that a fair summary of what the

0:14:21.080 --> 0:14:21.960
<v Speaker 4>media tour was about.

0:14:22.480 --> 0:14:25.600
<v Speaker 2>Yeah, I think there's two minds of this. I mean, one,

0:14:26.480 --> 0:14:29.000
<v Speaker 2>you know, Meta or Facebook has always been sort of

0:14:29.000 --> 0:14:32.120
<v Speaker 2>a pro open source company. They've developed a bunch of

0:14:32.320 --> 0:14:35.880
<v Speaker 2>open source you know, protocols, and but on the other hand,

0:14:35.960 --> 0:14:38.400
<v Speaker 2>I mean you have to sort of take this as like, yeah,

0:14:38.400 --> 0:14:40.240
<v Speaker 2>I mean they're behind in the air raight, so like

0:14:40.400 --> 0:14:41.960
<v Speaker 2>of course, I mean they're going to just be in

0:14:42.000 --> 0:14:45.400
<v Speaker 2>favor of whatever slows their competitors down. So you know,

0:14:45.640 --> 0:14:46.080
<v Speaker 2>there's that.

0:14:46.840 --> 0:14:48.360
<v Speaker 1>There was a headline in the in the New York

0:14:48.360 --> 0:14:51.960
<v Speaker 1>Times Silicon Valley splits over closing the borders to Chinese AI.

0:14:52.640 --> 0:14:54.560
<v Speaker 1>So read is what you're saying that people who want

0:14:54.560 --> 0:14:56.360
<v Speaker 1>to close the borders to Chinese AI are the ones

0:14:56.360 --> 0:14:58.120
<v Speaker 1>who are currently winning and the ones who don't want

0:14:58.160 --> 0:14:59.920
<v Speaker 1>to close the borders of Chinese AI, the ones who

0:15:00.120 --> 0:15:01.200
<v Speaker 1>only losing a no note.

0:15:01.280 --> 0:15:03.920
<v Speaker 3>To me, it's you know, that's a kind of misleading headline.

0:15:04.080 --> 0:15:07.320
<v Speaker 3>To me, it feels very like Anthropic versus everyone else

0:15:07.440 --> 0:15:12.560
<v Speaker 3>in tech. I mean, you had Google, like every single

0:15:12.600 --> 0:15:15.440
<v Speaker 3>tech company kind of signed this open letter right against

0:15:15.440 --> 0:15:17.400
<v Speaker 3>that sort of I felt like was a big subtweet

0:15:17.400 --> 0:15:20.240
<v Speaker 3>of Anthropic. Dario comes out, He's like, Oh no, we

0:15:20.280 --> 0:15:22.160
<v Speaker 3>don't like really want to be an open source models,

0:15:22.160 --> 0:15:23.600
<v Speaker 3>but also we kind of think they're dangerous and we

0:15:24.000 --> 0:15:26.680
<v Speaker 3>kind of I think like dark to me, like I

0:15:26.760 --> 0:15:31.200
<v Speaker 3>see Anthropic running the meta playbook exactly where they have

0:15:31.320 --> 0:15:33.440
<v Speaker 3>this dominance in the market right now and they're trying

0:15:33.480 --> 0:15:36.760
<v Speaker 3>to sort of do regulatory capture to maintain it.

0:15:38.200 --> 0:15:40.120
<v Speaker 4>More about the letter, Taylor, just before we go too far?

0:15:40.640 --> 0:15:44.880
<v Speaker 3>Sure so that So Jensen Wang, CEO of Nvidia, joins

0:15:44.920 --> 0:15:47.040
<v Speaker 3>Twitter big. By the way, I just have to say

0:15:47.080 --> 0:15:49.920
<v Speaker 3>Mark Zuckerberg's on Twitter promoting his Wall Street Journal op

0:15:50.040 --> 0:15:52.600
<v Speaker 3>ed like Jensen's on Twitter. I feel like Twitter has

0:15:52.640 --> 0:15:55.920
<v Speaker 3>gotten peak lately. I love to see all these tech

0:15:55.960 --> 0:15:59.880
<v Speaker 3>CEOs on there. But so Jensen joins Twitter and po

0:16:00.360 --> 0:16:03.120
<v Speaker 3>this open letter, which obviously is you know, shared to

0:16:03.160 --> 0:16:07.280
<v Speaker 3>the website whatever, and it is a defensive open source

0:16:07.600 --> 0:16:11.040
<v Speaker 3>open weight models. Obviously Nvidia has a strong you know,

0:16:11.120 --> 0:16:14.440
<v Speaker 3>business interest in this as well, but it becomes this letter,

0:16:14.520 --> 0:16:16.680
<v Speaker 3>this open letter becomes this sort of like rallying cry,

0:16:16.800 --> 0:16:20.000
<v Speaker 3>and you have just dozens and dozens of tech companies

0:16:20.000 --> 0:16:23.080
<v Speaker 3>sign on to it, you know, by the by the weekend,

0:16:23.280 --> 0:16:25.840
<v Speaker 3>like every almost every major tech company it'd signed on

0:16:25.840 --> 0:16:28.520
<v Speaker 3>to it, including all these startup you know why, y Combinator,

0:16:28.520 --> 0:16:31.360
<v Speaker 3>et cetera, a bunch of startups. So it felt like

0:16:32.200 --> 0:16:36.160
<v Speaker 3>basically the entire tech industry had united to advocate for

0:16:36.400 --> 0:16:39.359
<v Speaker 3>open weight AI models to be accept to remain accessible.

0:16:39.920 --> 0:16:43.920
<v Speaker 3>And then Anthropic came out. Dario issued this this blog

0:16:43.960 --> 0:16:48.560
<v Speaker 3>post saying basically like trying again doing the meta thing

0:16:48.600 --> 0:16:51.040
<v Speaker 3>where it's like, oh, we don't really want to ban TikTok.

0:16:51.080 --> 0:16:53.080
<v Speaker 3>We just think it's a national security thread and it

0:16:53.080 --> 0:16:55.600
<v Speaker 3>should be eliminated and probably we shouldn't be able to

0:16:55.600 --> 0:16:57.960
<v Speaker 3>download the United States and so like That's kind of

0:16:57.960 --> 0:16:59.960
<v Speaker 3>how his letter read to me. I don't know what

0:17:00.040 --> 0:17:01.720
<v Speaker 3>read thought, but it was like, oh no, no, no, we

0:17:02.080 --> 0:17:05.080
<v Speaker 3>don't mind open Wait we just think it's incredibly dangerous

0:17:05.119 --> 0:17:07.040
<v Speaker 3>and you know, I don't like to you know, that's

0:17:07.040 --> 0:17:08.359
<v Speaker 3>probably not worth the resk or whatever.

0:17:08.440 --> 0:17:10.600
<v Speaker 1>So read on Smiley, I want to hear your tape

0:17:10.600 --> 0:17:12.560
<v Speaker 1>of first. Can one of you help us under sound

0:17:12.560 --> 0:17:14.200
<v Speaker 1>difference between open source and open weight?

0:17:14.600 --> 0:17:16.879
<v Speaker 2>Yeah, I mean it's just a this is just a

0:17:16.920 --> 0:17:21.399
<v Speaker 2>semantics thing really because these models don't reveal their underlying

0:17:21.480 --> 0:17:24.640
<v Speaker 2>data sets. And so people in the open source community

0:17:24.640 --> 0:17:26.640
<v Speaker 2>took issue with that term because it's like, well, it's

0:17:26.640 --> 0:17:30.480
<v Speaker 2>not totally open, but you know, you can still for

0:17:30.520 --> 0:17:34.199
<v Speaker 2>all intents and purposes, they're open. I use yeah, I

0:17:34.320 --> 0:17:36.840
<v Speaker 2>use open source all the time because I think it

0:17:37.000 --> 0:17:39.080
<v Speaker 2>just confuses people to a lot of people to say

0:17:39.119 --> 0:17:41.840
<v Speaker 2>open weights. But but you know, there's a there's a

0:17:42.000 --> 0:17:44.480
<v Speaker 2>sort of debate there. There was a big debate about

0:17:44.480 --> 0:17:47.840
<v Speaker 2>this in the open source community. But no, I mean,

0:17:47.920 --> 0:17:51.399
<v Speaker 2>I basically agree with Taylor on this. I think the

0:17:51.480 --> 0:17:53.320
<v Speaker 2>one thing I would sort of take issue with is

0:17:53.359 --> 0:17:56.760
<v Speaker 2>like I actually think that anthropic people in Dario, like

0:17:56.800 --> 0:17:59.680
<v Speaker 2>they're like true believers and they really are scared of

0:18:00.640 --> 0:18:03.119
<v Speaker 2>like AI and what's going to happen if you know,

0:18:03.200 --> 0:18:05.760
<v Speaker 2>you have these open models that can have all the

0:18:05.800 --> 0:18:09.800
<v Speaker 2>guardrails and protection stripped away from them that eventually We're

0:18:09.800 --> 0:18:13.560
<v Speaker 2>not there yet, but eventually, I think pose like a

0:18:13.640 --> 0:18:17.800
<v Speaker 2>large amount of risk in cybersecurity or bioterrorism.

0:18:17.080 --> 0:18:20.159
<v Speaker 3>Doesn't it make us safer? Like, isn't the argument, like

0:18:20.200 --> 0:18:22.879
<v Speaker 3>the argument that I've seen from security people and Alex

0:18:22.960 --> 0:18:25.480
<v Speaker 3>Damos was talking about this sort of a long time

0:18:25.480 --> 0:18:30.360
<v Speaker 3>security guy at Metali. Actually it strengthens everyone to have

0:18:30.480 --> 0:18:33.040
<v Speaker 3>these open source models out there and available because it

0:18:33.080 --> 0:18:35.240
<v Speaker 3>allows I mean the Hugging Face incident is a perfect

0:18:35.240 --> 0:18:37.280
<v Speaker 3>example of this, Like when you have these guard bills

0:18:37.320 --> 0:18:39.040
<v Speaker 3>and you have these restrictions and we're only allowed to

0:18:39.119 --> 0:18:41.800
<v Speaker 3>use anthropic robe and ai basically like it actually made

0:18:41.800 --> 0:18:43.400
<v Speaker 3>it makes it more dangerous.

0:18:43.680 --> 0:18:48.320
<v Speaker 1>Yeah, the hugging Face example was when open Aiy's cyber

0:18:48.440 --> 0:18:51.800
<v Speaker 1>tool kind of went semi rogue in a non properly

0:18:51.920 --> 0:18:55.600
<v Speaker 1>send boxed environment and hecked hugging Face and Hugging Face

0:18:55.640 --> 0:18:58.040
<v Speaker 1>couldn't defend themselves within the US models because of the

0:18:58.040 --> 0:19:00.399
<v Speaker 1>god rails, and so they used a chiny models to

0:19:00.400 --> 0:19:02.040
<v Speaker 1>defend themselves, which we talked about last week.

0:19:02.160 --> 0:19:05.000
<v Speaker 2>Yeah, I mean that's where I would also agree with you,

0:19:05.040 --> 0:19:08.000
<v Speaker 2>like I just my only point was, like, my only

0:19:08.000 --> 0:19:10.400
<v Speaker 2>point of disagreement with you was, like, I actually think

0:19:10.440 --> 0:19:13.840
<v Speaker 2>it's not just some sort of cynical regulatory capture point.

0:19:13.920 --> 0:19:16.400
<v Speaker 2>I think they actually believe in this stuff. I don't

0:19:16.400 --> 0:19:19.440
<v Speaker 2>think their conclusion though, is always right. Like I agree

0:19:19.480 --> 0:19:23.040
<v Speaker 2>with you that, like you can't plug this dam. Like

0:19:23.119 --> 0:19:26.520
<v Speaker 2>these models, these open source models will you know, find

0:19:26.560 --> 0:19:29.280
<v Speaker 2>their way into the country. The Chinese will continue to

0:19:29.440 --> 0:19:33.160
<v Speaker 2>distill from American AI unless there's some new breakthrough that

0:19:33.800 --> 0:19:37.600
<v Speaker 2>you know, allows AI frontier models companies to stop that.

0:19:38.200 --> 0:19:40.919
<v Speaker 2>So yeah, I mean, I think the only answer is, like,

0:19:41.400 --> 0:19:45.040
<v Speaker 2>if these open source models are a threat to cybersecurity,

0:19:45.440 --> 0:19:49.800
<v Speaker 2>we better be plugging as many cybersecurity holes as we can, right, Like,

0:19:49.880 --> 0:19:54.080
<v Speaker 2>we have to protect against this reality rather than try to,

0:19:54.520 --> 0:19:57.199
<v Speaker 2>you know, I don't know, like plug the dam or

0:19:57.240 --> 0:19:58.920
<v Speaker 2>just bury our heads in the sand and hope that

0:19:59.040 --> 0:20:02.280
<v Speaker 2>somehow we can ban this and stop you know, technology

0:20:02.280 --> 0:20:03.240
<v Speaker 2>from marching forward.

0:20:03.680 --> 0:20:05.920
<v Speaker 3>I just want to say, though, like on the true

0:20:05.920 --> 0:20:09.280
<v Speaker 3>believer point, like I totally agree with you. I think

0:20:09.359 --> 0:20:11.439
<v Speaker 3>Dario and a lot of people they're effective ault as

0:20:11.480 --> 0:20:15.640
<v Speaker 3>true believers, but it is also very convenient for their

0:20:15.680 --> 0:20:19.639
<v Speaker 3>business interest And I do think that, like, you know,

0:20:19.880 --> 0:20:22.880
<v Speaker 3>in a lot of ways like Meta, where there were

0:20:22.920 --> 0:20:24.840
<v Speaker 3>true believers in the sense that they thought that it

0:20:24.880 --> 0:20:27.480
<v Speaker 3>was like a dangerous open internet and connecting the world

0:20:27.520 --> 0:20:30.240
<v Speaker 3>would be dangerous, and that's how it was like before Meta,

0:20:30.240 --> 0:20:32.440
<v Speaker 3>it was all sort of like chaotic and the chaos

0:20:32.480 --> 0:20:35.600
<v Speaker 3>of like forums and blogs, there's disinformation. So Meta's whole

0:20:35.600 --> 0:20:37.200
<v Speaker 3>thing was like, we're going to clean it up. We're

0:20:37.200 --> 0:20:40.119
<v Speaker 3>going to provide this standardized experience, like we're going to

0:20:40.119 --> 0:20:42.119
<v Speaker 3>be the one to connect the world and it's going

0:20:42.200 --> 0:20:44.520
<v Speaker 3>to be amazing. And I think part of it is,

0:20:44.560 --> 0:20:47.359
<v Speaker 3>like I mean, and maybe I'm more cynical about all

0:20:47.359 --> 0:20:49.560
<v Speaker 3>of it, but I do think there's this like paternalistic

0:20:49.720 --> 0:20:52.800
<v Speaker 3>power fantasy as well, where it's very much like I'm

0:20:52.880 --> 0:20:56.240
<v Speaker 3>the one that can bring artificial intelligence. I'm the responsible

0:20:56.280 --> 0:20:59.720
<v Speaker 3>one that can oversee it. And I just reject that,

0:21:00.440 --> 0:21:01.920
<v Speaker 3>especially from people like Dario.

0:21:02.440 --> 0:21:04.840
<v Speaker 2>There's a lot of Yeah, there's a lot of paternalistic

0:21:04.920 --> 0:21:08.600
<v Speaker 2>fantasies and tech for sure, I mean, and it is, yeah,

0:21:08.640 --> 0:21:10.760
<v Speaker 2>I mean, it's like trying to boil the ocean. Really,

0:21:11.000 --> 0:21:15.040
<v Speaker 2>it's just like no one person, no one company is

0:21:15.119 --> 0:21:18.280
<v Speaker 2>going to be in charge of safeguarding all of this right,

0:21:18.359 --> 0:21:20.400
<v Speaker 2>And I don't even think I mean, I think even

0:21:20.480 --> 0:21:24.760
<v Speaker 2>government is just like almost moving too fast. And I

0:21:24.840 --> 0:21:27.520
<v Speaker 2>think this partially is because like we don't legislate anymore,

0:21:27.560 --> 0:21:31.200
<v Speaker 2>we just write executive orders. But it's like the people

0:21:31.200 --> 0:21:36.600
<v Speaker 2>are talking about, you know, distillation being and being ip theft, right, Well,

0:21:36.720 --> 0:21:40.760
<v Speaker 2>that essentially means that like when these Chinese models do

0:21:40.840 --> 0:21:42.920
<v Speaker 2>make it to the US and people start using these

0:21:42.960 --> 0:21:46.680
<v Speaker 2>open source models, they won't be allowed to distill them,

0:21:46.720 --> 0:21:49.040
<v Speaker 2>which back to this research study, is how you get

0:21:49.119 --> 0:21:52.360
<v Speaker 2>rid of all this censorship which is real in these models,

0:21:52.359 --> 0:21:55.480
<v Speaker 2>like they are very biased toward you know, the CCP

0:21:55.880 --> 0:21:58.840
<v Speaker 2>point of view. So I mean you're like in all

0:21:58.880 --> 0:22:02.240
<v Speaker 2>these every move that you make, you're like cutting off

0:22:02.280 --> 0:22:04.480
<v Speaker 2>one of your options to deal with this problem, which

0:22:04.480 --> 0:22:06.879
<v Speaker 2>I think is a you know, is a problem.

0:22:06.640 --> 0:22:10.280
<v Speaker 3>Which could be solved by competing. Like I just I'm like,

0:22:10.440 --> 0:22:13.600
<v Speaker 3>why don't we actually try to compete. Why don't we

0:22:13.640 --> 0:22:16.480
<v Speaker 3>invest in research? Why don't we invest Like China has

0:22:16.520 --> 0:22:22.040
<v Speaker 3>this long term vision and has really facilitated innovation and

0:22:22.200 --> 0:22:25.879
<v Speaker 3>prioritize their you know, education system to build you know,

0:22:25.920 --> 0:22:29.040
<v Speaker 3>the skills necessary to build the next generation technology, and

0:22:29.119 --> 0:22:31.520
<v Speaker 3>I just feel like America, it's like, what are we doing?

0:22:31.560 --> 0:22:34.439
<v Speaker 3>We're making gambling apps? And what is Andreas and Horwitz funding?

0:22:34.440 --> 0:22:37.320
<v Speaker 3>Are they funding next generation technology? I don't know, you

0:22:37.400 --> 0:22:40.280
<v Speaker 3>know what I mean. I just like America feels like

0:22:41.240 --> 0:22:44.680
<v Speaker 3>just it's like rickety old cart that's like falling apart,

0:22:44.840 --> 0:22:46.639
<v Speaker 3>and I'm just like, is anyone going to fix it?

0:22:47.000 --> 0:22:49.399
<v Speaker 2>Well? I think that I think the rickety old cart

0:22:49.560 --> 0:22:53.320
<v Speaker 2>is is like actually fine, Like there's there's a America's

0:22:53.359 --> 0:22:56.000
<v Speaker 2>never been perfect, right, and it happens in that like

0:22:56.320 --> 0:22:59.720
<v Speaker 2>innovation happens in a very sort of like haphazard and

0:22:59.760 --> 0:23:03.360
<v Speaker 2>just rebated way. And my point is just get out

0:23:03.440 --> 0:23:03.840
<v Speaker 2>of the way.

0:23:04.080 --> 0:23:06.280
<v Speaker 1>There was a great book called Breakneck, which I'm not

0:23:06.320 --> 0:23:08.640
<v Speaker 1>sure if either you read. A big guy called Dan Wong,

0:23:08.720 --> 0:23:13.000
<v Speaker 1>and he basically counterposed the Chinese Communist Party with the

0:23:13.080 --> 0:23:16.760
<v Speaker 1>history of American presidents and basically as a huge preponderance

0:23:16.800 --> 0:23:19.760
<v Speaker 1>of engineers in the who became you know, supreme leaders

0:23:19.840 --> 0:23:23.960
<v Speaker 1>versus lawyers who became presidents. And you know, his point was,

0:23:24.000 --> 0:23:25.359
<v Speaker 1>if you live in China and you look out the

0:23:25.359 --> 0:23:27.280
<v Speaker 1>window and a year has gone by, you might see

0:23:27.280 --> 0:23:29.439
<v Speaker 1>a new city out of the window and if you

0:23:29.480 --> 0:23:31.200
<v Speaker 1>live in the US, like the best you can hope

0:23:31.240 --> 0:23:33.600
<v Speaker 1>for is a new coffee shop. And I don't know,

0:23:33.600 --> 0:23:37.359
<v Speaker 1>I think there is something. There's something to there's a

0:23:37.400 --> 0:23:40.040
<v Speaker 1>conversation which is bigger than the technology conversation, really about

0:23:40.040 --> 0:23:41.919
<v Speaker 1>like how do you, like, how do you create a

0:23:42.160 --> 0:23:46.119
<v Speaker 1>national culture that promotes innovation without but also without the

0:23:46.280 --> 0:23:47.240
<v Speaker 1>all of the bad things.

0:23:47.119 --> 0:23:48.040
<v Speaker 4>That happen in China.

0:23:48.240 --> 0:23:49.600
<v Speaker 1>Just before we go to the break there, I wanted

0:23:49.640 --> 0:23:51.800
<v Speaker 1>to ask you both. You know, we live in an

0:23:51.800 --> 0:23:54.159
<v Speaker 1>attention economy and we're all you know, all three of

0:23:54.240 --> 0:23:58.639
<v Speaker 1>us work in it. But it's very rare that a

0:23:58.720 --> 0:24:01.040
<v Speaker 1>story rumbles on for three weeks, Like why why is

0:24:01.080 --> 0:24:04.480
<v Speaker 1>everyone still talking about these Chinese open source models and distillations?

0:24:04.720 --> 0:24:07.200
<v Speaker 1>Is just because it's the behind the story is questions

0:24:07.240 --> 0:24:10.560
<v Speaker 1>about like the next open Ai ipo and the anthropic

0:24:10.600 --> 0:24:13.480
<v Speaker 1>ipo or is it about the China US Great Palace struggle?

0:24:13.520 --> 0:24:16.000
<v Speaker 1>Story is always fascinating, like why people still own this?

0:24:16.960 --> 0:24:21.240
<v Speaker 2>Well my one theory and okay, I'm kind I'm kind

0:24:21.240 --> 0:24:23.199
<v Speaker 2>of just going off the cuff here, but like I

0:24:23.200 --> 0:24:27.040
<v Speaker 2>think it's a great question. This AI conversation has sucked

0:24:27.119 --> 0:24:29.760
<v Speaker 2>all of our attention into it, right, It's become everything.

0:24:29.880 --> 0:24:33.040
<v Speaker 2>And so you know, when you have a controversy like

0:24:33.040 --> 0:24:37.000
<v Speaker 2>this and there isn't some major breakthrough that's drawing our

0:24:37.000 --> 0:24:39.720
<v Speaker 2>attention away, like we're going to focus on this stuff

0:24:39.760 --> 0:24:42.639
<v Speaker 2>for longer. But I think as soon as, like, you know,

0:24:42.760 --> 0:24:45.879
<v Speaker 2>we see some new corner turned and there's a shiny

0:24:45.960 --> 0:24:48.679
<v Speaker 2>new thing to go after, we will like that. That

0:24:48.720 --> 0:24:52.840
<v Speaker 2>will that will be the thing everybody talks about. Maybe

0:24:52.880 --> 0:24:56.480
<v Speaker 2>it'll happen later this year, maybe in January. It seems

0:24:56.480 --> 0:25:01.280
<v Speaker 2>like January is it just has some major breakthrough every year, right,

0:25:01.400 --> 0:25:03.600
<v Speaker 2>I wasn't thinking of c yes, but just like every

0:25:03.760 --> 0:25:05.880
<v Speaker 2>like January it was like it was like the reasoning

0:25:05.960 --> 0:25:08.359
<v Speaker 2>models happened, and then like last January it was like

0:25:08.480 --> 0:25:10.960
<v Speaker 2>all of a sudden, the harnesses were just working and

0:25:11.040 --> 0:25:13.960
<v Speaker 2>you could build, you know, build all this technology. I

0:25:13.960 --> 0:25:16.439
<v Speaker 2>think something like that's going to happen, and you know,

0:25:16.760 --> 0:25:18.119
<v Speaker 2>we'll forget about this for a while.

0:25:18.320 --> 0:25:21.160
<v Speaker 3>I hope so. But I feel I'm scared that we're

0:25:21.160 --> 0:25:23.320
<v Speaker 3>going to get distracted by that shiny new object and

0:25:24.359 --> 0:25:26.639
<v Speaker 3>fundamentally not fix all the issues. That sort of reads

0:25:26.720 --> 0:25:29.359
<v Speaker 3>mentioning this idea of not investing in research, Like I

0:25:29.400 --> 0:25:31.879
<v Speaker 3>do think the US has as a major problem with

0:25:31.960 --> 0:25:34.399
<v Speaker 3>long term vision and maybe that's how our political system

0:25:34.480 --> 0:25:37.399
<v Speaker 3>set up, I don't know, but or sort of our

0:25:37.440 --> 0:25:51.080
<v Speaker 3>economic system, but certainly it's it's a problem.

0:25:45.440 --> 0:25:46.280
<v Speaker 4>When we come back.

0:25:46.680 --> 0:25:50.040
<v Speaker 1>Substock has pushed back against a new AI detection feature.

0:25:50.440 --> 0:26:06.840
<v Speaker 1>Stay with us, Welcome back, Taylor. Subset recently launched a

0:26:06.920 --> 0:26:09.359
<v Speaker 1>feature on that app which acts like a kind of

0:26:09.400 --> 0:26:12.120
<v Speaker 1>AI detective fit us in.

0:26:12.600 --> 0:26:17.160
<v Speaker 3>Yeah, So, Substack partnered with this company called Pangram, which

0:26:17.200 --> 0:26:20.600
<v Speaker 3>is a startup that is basically they build themselves as

0:26:20.760 --> 0:26:23.600
<v Speaker 3>like the slop detector of the web, and so they

0:26:23.640 --> 0:26:28.800
<v Speaker 3>have probably the most sophisticated AI detection tools and they've

0:26:28.880 --> 0:26:32.080
<v Speaker 3>just actually they're working on visual AI detection tools in

0:26:32.160 --> 0:26:36.040
<v Speaker 3>terms of images, but they're really good at detecting AI

0:26:36.600 --> 0:26:40.760
<v Speaker 3>use in writing and so basically substack is trying to

0:26:40.800 --> 0:26:45.560
<v Speaker 3>make it easier to click and determine how much of

0:26:45.640 --> 0:26:49.640
<v Speaker 3>an article is written by AI or it's really good

0:26:49.640 --> 0:26:52.159
<v Speaker 3>at determining if one hundred percent of the article is

0:26:52.200 --> 0:26:55.680
<v Speaker 3>AI generated, which I think is valuable because I did

0:26:55.680 --> 0:26:58.159
<v Speaker 3>a partnership with Pangram myself actually where they gave me

0:26:58.200 --> 0:27:02.840
<v Speaker 3>access early access to their API last year or well

0:27:02.880 --> 0:27:04.640
<v Speaker 3>it wasn't even last year, it's like four months ago.

0:27:05.000 --> 0:27:08.960
<v Speaker 3>And tech moves fast, and you know, up to forty

0:27:09.040 --> 0:27:11.960
<v Speaker 3>percent of articles in the tech category, which is what

0:27:12.000 --> 0:27:12.800
<v Speaker 3>my newsletter is in.

0:27:13.480 --> 0:27:16.480
<v Speaker 4>We're fully AI generated, fully AI generated.

0:27:16.200 --> 0:27:18.920
<v Speaker 3>Fully AI generated, So it's really taking over.

0:27:19.280 --> 0:27:20.919
<v Speaker 4>Is this in response to consumer demand?

0:27:21.080 --> 0:27:23.560
<v Speaker 1>Is like this of a substac leadership concern that if

0:27:23.560 --> 0:27:26.200
<v Speaker 1>they let AI proliferate for too long on substack, ultimately

0:27:26.240 --> 0:27:28.119
<v Speaker 1>people will migrate away from substack Like where was it

0:27:28.240 --> 0:27:30.000
<v Speaker 1>was a demand signal kind of driving this?

0:27:30.280 --> 0:27:33.800
<v Speaker 3>You know, I don't know the total thinking behind it.

0:27:33.840 --> 0:27:35.480
<v Speaker 3>I did interview Chris Best, and.

0:27:36.080 --> 0:27:38.200
<v Speaker 4>What he said is like the CEO of subsc right.

0:27:38.200 --> 0:27:41.400
<v Speaker 3>The CEO of Substack, who said, you know, we want

0:27:41.440 --> 0:27:45.480
<v Speaker 3>consumers to basically have more information and know and like

0:27:45.520 --> 0:27:48.359
<v Speaker 3>this is our way of kind of not doing like

0:27:48.359 --> 0:27:50.680
<v Speaker 3>trust and safety, but kind of like making our platform

0:27:50.680 --> 0:27:53.719
<v Speaker 3>more transparent. I think there's a lot of scams and

0:27:53.800 --> 0:27:56.199
<v Speaker 3>spam kind of info. I mean, as I wrote in

0:27:56.200 --> 0:27:59.240
<v Speaker 3>my piece, like one of the most popular subsacts in

0:27:59.280 --> 0:28:03.240
<v Speaker 3>the past year was this like fake conversation between Elon

0:28:03.359 --> 0:28:07.200
<v Speaker 3>Musk and Keanu Reeves. It literally never happened, but it

0:28:07.240 --> 0:28:10.680
<v Speaker 3>was AI generated slop that went megaviral that people still

0:28:10.720 --> 0:28:13.440
<v Speaker 3>share to this day as if it was real. The

0:28:13.520 --> 0:28:19.439
<v Speaker 3>politics category is overrun with AI generated content, so I

0:28:19.440 --> 0:28:23.439
<v Speaker 3>think it's about giving consumers more transparency. I don't know

0:28:23.480 --> 0:28:25.280
<v Speaker 3>that it's totally led to that. I feel like it's

0:28:25.280 --> 0:28:29.280
<v Speaker 3>caused a bit of chaos, but that's certainly the goal.

0:28:29.800 --> 0:28:32.919
<v Speaker 4>So this is not just the detective, It's not X.

0:28:33.000 --> 0:28:35.359
<v Speaker 4>It's that this is more sophisticated.

0:28:35.640 --> 0:28:37.280
<v Speaker 1>Do you think I'm curious for both of your take

0:28:37.320 --> 0:28:40.640
<v Speaker 1>as people who write newsletters, like is all AI writing

0:28:40.720 --> 0:28:41.440
<v Speaker 1>AI slop?

0:28:42.920 --> 0:28:45.760
<v Speaker 3>I get a few AI generated newsletters that I really love.

0:28:46.840 --> 0:28:49.120
<v Speaker 3>There's like a social listening tool that I get the

0:28:49.120 --> 0:28:51.680
<v Speaker 3>newsletter up, and it basically gives me like a roundup

0:28:51.720 --> 0:28:56.280
<v Speaker 3>of trending posts and automatically sort of pulls yeah, like

0:28:56.360 --> 0:28:59.840
<v Speaker 3>trending content in I like Vibe coded my own one

0:29:00.120 --> 0:29:03.240
<v Speaker 3>that like it's mostly it's I trust AI for like

0:29:03.280 --> 0:29:06.720
<v Speaker 3>analysis and scraping, and it's honestly better than like a

0:29:06.720 --> 0:29:08.240
<v Speaker 3>lot of the ones that I subscribe to. I mean,

0:29:08.240 --> 0:29:10.200
<v Speaker 3>I subscribe to a lot of human newsletters as well,

0:29:10.200 --> 0:29:13.120
<v Speaker 3>but I think that like AI can pick up these

0:29:13.680 --> 0:29:18.720
<v Speaker 3>small detections, you know, in sort of trends. I At

0:29:18.720 --> 0:29:21.080
<v Speaker 3>the same time, I think it's all about transparency, right,

0:29:21.240 --> 0:29:23.880
<v Speaker 3>and what does the consumer think they're getting. Do they

0:29:23.880 --> 0:29:26.760
<v Speaker 3>think that they're getting one hundred percent human No, AI

0:29:27.120 --> 0:29:29.280
<v Speaker 3>used it all, but they're actually getting slop. Okay, that's

0:29:29.280 --> 0:29:32.600
<v Speaker 3>going to cause a negative experience. But I think increasingly

0:29:33.360 --> 0:29:35.320
<v Speaker 3>it's somewhere in the middle. And that's kind of where

0:29:35.360 --> 0:29:36.040
<v Speaker 3>things get tricky.

0:29:36.840 --> 0:29:38.920
<v Speaker 2>Yeah, I don't think it's all slop, but I do.

0:29:39.800 --> 0:29:41.480
<v Speaker 2>I don't know about you guys. I mean I can

0:29:41.480 --> 0:29:44.440
<v Speaker 2>tell when something's like AI generated.

0:29:44.760 --> 0:29:46.440
<v Speaker 3>I can to Most people can't.

0:29:46.680 --> 0:29:48.840
<v Speaker 2>Yeah, most people can't, but you get it. There's a

0:29:48.920 --> 0:29:52.520
<v Speaker 2>rhythm to it that sort of like becomes familiar, especially claude,

0:29:52.560 --> 0:29:56.040
<v Speaker 2>like if there's a specially exactly style and you read

0:29:56.400 --> 0:29:59.200
<v Speaker 2>X and sometimes I'm like, well, this is actually an

0:29:59.200 --> 0:30:01.960
<v Speaker 2>interesting point that this person's making. It's also just this

0:30:02.120 --> 0:30:04.880
<v Speaker 2>is just AI generated, and like, I don't know what

0:30:04.960 --> 0:30:05.640
<v Speaker 2>to think about it.

0:30:06.000 --> 0:30:08.959
<v Speaker 3>So one thing that I thought was interesting is this

0:30:09.000 --> 0:30:11.040
<v Speaker 3>person on ax has been doing and I want to

0:30:11.040 --> 0:30:15.200
<v Speaker 3>write about this myself and I haven't. But the big

0:30:15.200 --> 0:30:17.920
<v Speaker 3>thing on YouTube right now is AI generated scripts. So

0:30:18.080 --> 0:30:20.880
<v Speaker 3>Almost every big YouTuber is using AI to auto generate

0:30:20.920 --> 0:30:23.040
<v Speaker 3>their scripts. They're not even tweaking them. They're literally just

0:30:23.120 --> 0:30:25.360
<v Speaker 3>generating the script and reading it. But they're a human

0:30:25.840 --> 0:30:30.600
<v Speaker 3>reading it. So audiences, this person was tweeting out the

0:30:30.640 --> 0:30:33.000
<v Speaker 3>response to your audiences and what I've noticed as well

0:30:33.200 --> 0:30:36.320
<v Speaker 3>one hundred percent positive. They seem to prefer it. Actually

0:30:36.800 --> 0:30:42.480
<v Speaker 3>they are saying incredible analysis, phenomenal. Wow, I can't believe it.

0:30:42.720 --> 0:30:44.840
<v Speaker 2>And how do you know those aren't bots?

0:30:45.000 --> 0:30:47.360
<v Speaker 3>No, no, no, I trust me. I have gone deep

0:30:47.400 --> 0:30:49.840
<v Speaker 3>and I have used AI on one of my own

0:30:49.960 --> 0:30:53.240
<v Speaker 3>multiple of my own scripts, and people praise those AI

0:30:53.320 --> 0:30:56.600
<v Speaker 3>scripts far more than my human scripts. So and I

0:30:56.640 --> 0:30:59.040
<v Speaker 3>didn't use AI like one hundred percent, But like people

0:30:59.280 --> 0:31:03.440
<v Speaker 3>seem there's something about the AI cadence that, like normally

0:31:03.520 --> 0:31:06.280
<v Speaker 3>people online seem to really like. And if you look

0:31:06.320 --> 0:31:11.920
<v Speaker 3>at these like viral articles as well read I generated,

0:31:12.000 --> 0:31:14.760
<v Speaker 3>So there is something And I don't think most most

0:31:14.800 --> 0:31:16.920
<v Speaker 3>of those people do not realize that they're consuming AI.

0:31:17.000 --> 0:31:18.920
<v Speaker 3>And I think that was the issue with substack as well,

0:31:18.960 --> 0:31:22.160
<v Speaker 3>like and I think, but that's the thing they I

0:31:22.160 --> 0:31:24.719
<v Speaker 3>don't know that they want to know that it's they

0:31:24.720 --> 0:31:27.200
<v Speaker 3>get kind of they won't believe it, you know, when

0:31:27.240 --> 0:31:29.160
<v Speaker 3>you say, hey, this is one hundred percent AI generated,

0:31:29.200 --> 0:31:31.400
<v Speaker 3>like they kind of don't want to accept that.

0:31:31.840 --> 0:31:35.200
<v Speaker 1>Did you follow the moment with the Canadian politician this week, Yes,

0:31:35.880 --> 0:31:38.400
<v Speaker 1>here's a more natural, flowing version of that section that

0:31:38.480 --> 0:31:40.480
<v Speaker 1>reads like legislative speech rather than.

0:31:40.400 --> 0:31:42.920
<v Speaker 4>A series of short points. Madam speaker. One of my

0:31:43.000 --> 0:31:43.880
<v Speaker 4>concerns who.

0:31:43.680 --> 0:31:47.480
<v Speaker 1>Went viral reading the instructions from Clode a Loud in

0:31:47.480 --> 0:31:48.440
<v Speaker 1>his political speech.

0:31:48.960 --> 0:31:50.160
<v Speaker 4>I mean, but it's funny.

0:31:50.200 --> 0:31:51.600
<v Speaker 1>I think it's one of those things where it's like,

0:31:52.520 --> 0:31:54.480
<v Speaker 1>oh my god, he was caught with his pants down.

0:31:54.800 --> 0:31:57.840
<v Speaker 1>But on the other hand, like probably ninety nine point

0:31:57.880 --> 0:32:01.240
<v Speaker 1>nine percent of politicians used AI to enhance their speeches

0:32:01.520 --> 0:32:03.640
<v Speaker 1>or even write them, So it's a funny, like funny

0:32:03.680 --> 0:32:07.720
<v Speaker 1>that people were so like panicked or like captivated. I

0:32:07.720 --> 0:32:09.960
<v Speaker 1>guess it's very embarrassing for him, but it was also like.

0:32:10.000 --> 0:32:12.680
<v Speaker 3>Well, it's also like, is AI writing our policy? Like

0:32:13.040 --> 0:32:14.880
<v Speaker 3>this is my stance on all of it. It's like

0:32:15.000 --> 0:32:19.400
<v Speaker 3>I think that by doing like, I think that there's

0:32:19.440 --> 0:32:22.440
<v Speaker 3>not enough transparency. I think there's not enough discussion. I mean,

0:32:22.480 --> 0:32:25.000
<v Speaker 3>I did a Q and A with Substack about this yesterday,

0:32:25.080 --> 0:32:28.040
<v Speaker 3>Like I think we Joe Wisenthal had a good tweet

0:32:28.080 --> 0:32:30.000
<v Speaker 3>a while ago. A while ago he was basically like,

0:32:30.480 --> 0:32:32.680
<v Speaker 3>this is all happening, and we're not going to put

0:32:32.760 --> 0:32:34.560
<v Speaker 3>the genie back in the bottle. We need to accept

0:32:34.600 --> 0:32:36.280
<v Speaker 3>that AI is being used in all these ways and

0:32:36.320 --> 0:32:39.040
<v Speaker 3>we should have discussions about sort of what that means.

0:32:39.600 --> 0:32:41.840
<v Speaker 3>And I think that's much better than the sort of

0:32:41.840 --> 0:32:44.160
<v Speaker 3>witch hunting, which I also see happening and I think

0:32:44.160 --> 0:32:46.200
<v Speaker 3>has sort of happened with Pan Graham now, where it's

0:32:46.200 --> 0:32:47.959
<v Speaker 3>like people just go around like, oh my god, oh

0:32:47.960 --> 0:32:49.520
<v Speaker 3>my god, this AI was used to I was used

0:32:49.520 --> 0:32:51.200
<v Speaker 3>and I was like, okay, but what does it matter

0:32:51.240 --> 0:32:53.240
<v Speaker 3>if AI was used for this like niche thing, you

0:32:53.280 --> 0:32:55.280
<v Speaker 3>know what I mean, Like, let's have a real discussion

0:32:55.280 --> 0:32:55.640
<v Speaker 3>about it.

0:32:55.880 --> 0:32:57.760
<v Speaker 4>How it creators On substeck reacting to.

0:32:58.240 --> 0:33:02.800
<v Speaker 3>Pangram, it runs the gamute. Some people are like so

0:33:03.040 --> 0:33:07.080
<v Speaker 3>mad because again they use AI and they weren't disclosing it.

0:33:08.720 --> 0:33:10.520
<v Speaker 3>I think a lot of consumers, it really depends on

0:33:10.560 --> 0:33:13.440
<v Speaker 3>your audience. You know, ironically, no one really cares about

0:33:13.440 --> 0:33:16.800
<v Speaker 3>the tech, like the tech the tech newsletterspace like tramas

0:33:16.880 --> 0:33:20.520
<v Speaker 3>posted like that full AI generated like you know, article

0:33:20.600 --> 0:33:23.000
<v Speaker 3>basically on X everyone knew it was AI generated and

0:33:23.000 --> 0:33:25.120
<v Speaker 3>Elon Musk was a great article. Like people were like,

0:33:25.160 --> 0:33:27.160
<v Speaker 3>as kind of as read said, people were like, Okay,

0:33:27.560 --> 0:33:30.120
<v Speaker 3>Tamath is colo siding this analysis, and so I find

0:33:30.120 --> 0:33:33.280
<v Speaker 3>it valuable. So but people in the politics category, and

0:33:33.320 --> 0:33:36.920
<v Speaker 3>it's more like the lifestyle things like food and sort

0:33:36.960 --> 0:33:39.479
<v Speaker 3>of lifestyle influencers that have been relying on AI, like

0:33:39.680 --> 0:33:42.200
<v Speaker 3>their audiences are not taking kindly to it. And I

0:33:42.600 --> 0:33:46.160
<v Speaker 3>have a very left leaning audience that rulently hates AI,

0:33:46.720 --> 0:33:48.680
<v Speaker 3>so I've been tried to be very transparent with them.

0:33:48.760 --> 0:33:50.760
<v Speaker 4>Is that a point of tension between you and your audience.

0:33:51.240 --> 0:33:54.640
<v Speaker 3>Yeah, I've lost like a significant amount of subscribers just

0:33:54.640 --> 0:33:57.600
<v Speaker 3>by saying, hey, I'm a tech reporter, so I'm going

0:33:57.680 --> 0:34:00.000
<v Speaker 3>to use these tools for research, and I will alway

0:34:00.000 --> 0:34:03.400
<v Speaker 3>always write my articles like human but I will always

0:34:03.440 --> 0:34:05.680
<v Speaker 3>be transparent. But just so you know, I report on

0:34:05.720 --> 0:34:09.000
<v Speaker 3>technology that means using technology, and this has gotten me

0:34:09.040 --> 0:34:10.600
<v Speaker 3>canceled on Blue Sky multiple times.

0:34:11.760 --> 0:34:13.719
<v Speaker 2>I think in the in the end, though, this is

0:34:14.080 --> 0:34:17.520
<v Speaker 2>in some sense positive because there's always been sort of

0:34:17.600 --> 0:34:21.600
<v Speaker 2>an inauthentic nature to you know, social media to politics,

0:34:22.160 --> 0:34:25.040
<v Speaker 2>and I think this is actually driving people more towards

0:34:25.160 --> 0:34:28.799
<v Speaker 2>like a yearning for authenticity, and that's like part of

0:34:28.840 --> 0:34:31.840
<v Speaker 2>what the anti a AI hate is, right, And we

0:34:31.880 --> 0:34:35.040
<v Speaker 2>saw this with the latest you know, Christopher Nolan movie, right,

0:34:35.080 --> 0:34:39.319
<v Speaker 2>who's sort of rejected CGI and filmed this movie in

0:34:39.440 --> 0:34:42.719
<v Speaker 2>seventy millimeter IMAX like that, and people, I still can't

0:34:42.760 --> 0:34:45.920
<v Speaker 2>get tickets to the seventy millimeter right for months, And

0:34:45.960 --> 0:34:49.160
<v Speaker 2>it's like, you know, I think that's I sort of

0:34:49.200 --> 0:34:51.760
<v Speaker 2>think that's a positive, Like this is this is moving

0:34:51.880 --> 0:34:55.440
<v Speaker 2>us in the right direction for humanity. It's it's and

0:34:55.480 --> 0:34:57.799
<v Speaker 2>it's and it's like I even sort of like the

0:34:57.840 --> 0:35:01.640
<v Speaker 2>fact that even if something's AIG generated, like people can say, well,

0:35:01.960 --> 0:35:04.840
<v Speaker 2>the ideas behind this and the messenger here, I know,

0:35:05.480 --> 0:35:07.400
<v Speaker 2>and I'm gonna take it at face value. I'm not

0:35:07.440 --> 0:35:09.719
<v Speaker 2>going to worry about like what tools were used to

0:35:09.760 --> 0:35:11.920
<v Speaker 2>generate this. I'm gonna actually think about it as long

0:35:11.920 --> 0:35:15.440
<v Speaker 2>as there are people who are thinking critically, like in

0:35:15.560 --> 0:35:19.000
<v Speaker 2>policy and positions of power. That's good read.

0:35:19.000 --> 0:35:21.360
<v Speaker 1>Do you think your sem how would your semaphoe audience

0:35:21.480 --> 0:35:25.160
<v Speaker 1>feel if if you said, Okay, starting next week, I'm

0:35:25.160 --> 0:35:27.360
<v Speaker 1>going to use AI to as like as like a

0:35:27.400 --> 0:35:29.120
<v Speaker 1>full partner to write this newsletter.

0:35:30.160 --> 0:35:32.640
<v Speaker 2>I don't know. I don't think people would really care

0:35:32.680 --> 0:35:35.279
<v Speaker 2>as long as it's ultimately like I'm signing off on

0:35:35.480 --> 0:35:39.520
<v Speaker 2>every part of it, right, the writing of the writing

0:35:39.600 --> 0:35:42.200
<v Speaker 2>part of journalism is like a tiny part of journalism.

0:35:42.239 --> 0:35:46.040
<v Speaker 2>Like I actually would love if AI could just take

0:35:46.600 --> 0:35:50.239
<v Speaker 2>all of my interviews and my notes and my ideas

0:35:50.400 --> 0:35:54.279
<v Speaker 2>or you know, maybe my brains my verbal brainstorming to

0:35:54.520 --> 0:35:57.600
<v Speaker 2>my AI agent and just make like an amazing article

0:35:57.680 --> 0:36:00.480
<v Speaker 2>that's you know, perfectly edited. Like that would be great.

0:36:00.520 --> 0:36:03.680
<v Speaker 2>They'd be huge time saver, right, And I think, you know,

0:36:03.800 --> 0:36:05.960
<v Speaker 2>but you have to think critically about it, like you

0:36:05.960 --> 0:36:09.320
<v Speaker 2>you can't just you know, put stuff out there without

0:36:09.600 --> 0:36:13.120
<v Speaker 2>without like actually going through. It's not good enough yet, right,

0:36:13.200 --> 0:36:15.960
<v Speaker 2>Like I'm sure Taylor agrees. Like I've tried, you know,

0:36:16.000 --> 0:36:20.080
<v Speaker 2>I'm constantly trying. And it's good at some stuff, like

0:36:20.120 --> 0:36:22.439
<v Speaker 2>we use it for copy editing, et cetera. Like it's

0:36:22.520 --> 0:36:24.840
<v Speaker 2>it could be a time saver, but like it's not

0:36:24.960 --> 0:36:29.280
<v Speaker 2>there yet. It can't it can't generate you know, full articles.

0:36:29.600 --> 0:36:31.680
<v Speaker 3>I think AI is also very good at sort of

0:36:31.760 --> 0:36:34.399
<v Speaker 3>optimizing for AI, And I think, like when I talk

0:36:34.440 --> 0:36:37.640
<v Speaker 3>to YouTubers, about why so many YouTubers use it for scripts.

0:36:37.880 --> 0:36:40.319
<v Speaker 3>They're like, well, because the algorithm I'm playing for the

0:36:40.320 --> 0:36:44.720
<v Speaker 3>YouTube algorithm, the algorithm is ingesting my script and making

0:36:44.760 --> 0:36:47.359
<v Speaker 3>a determination about it. And if I say optimize it,

0:36:47.400 --> 0:36:51.120
<v Speaker 3>include these keywords include this cay to like, do include

0:36:51.160 --> 0:36:53.480
<v Speaker 3>these things that perform well for this algorithm, Like I

0:36:53.719 --> 0:36:57.320
<v Speaker 3>I think that's where it, you know, shines.

0:36:57.360 --> 0:36:59.040
<v Speaker 4>I guess it's so interesting.

0:36:59.080 --> 0:37:00.759
<v Speaker 1>I mean it shows up when you look at when

0:37:00.760 --> 0:37:03.840
<v Speaker 1>you look at like the top performing stuff on YouTube,

0:37:03.880 --> 0:37:06.440
<v Speaker 1>by the way the headlines are done, and the and

0:37:06.560 --> 0:37:10.040
<v Speaker 1>the thumbnails and the titling and like the kind of

0:37:10.040 --> 0:37:13.280
<v Speaker 1>like scrunged express like curious expression and stuff like. It's

0:37:13.560 --> 0:37:15.799
<v Speaker 1>it does feel like as I'm not a I have

0:37:15.840 --> 0:37:18.560
<v Speaker 1>to confess to I'm not like a super user review too,

0:37:18.600 --> 0:37:20.560
<v Speaker 1>but like when I look at those thumbnails, I'm like, wow,

0:37:20.600 --> 0:37:23.360
<v Speaker 1>this is like this has been so optimized.

0:37:22.719 --> 0:37:24.400
<v Speaker 4>For something that I am not. It's kind of an

0:37:24.400 --> 0:37:25.440
<v Speaker 4>interesting experience.

0:37:26.200 --> 0:37:28.960
<v Speaker 2>Well, if you think about the way that these models

0:37:29.000 --> 0:37:32.600
<v Speaker 2>were built with reinforcement learning, they had you know, thousands

0:37:32.640 --> 0:37:35.520
<v Speaker 2>of people sitting there just clicking. I like this version

0:37:35.640 --> 0:37:38.279
<v Speaker 2>more than that version. You know, they put a lot

0:37:38.320 --> 0:37:41.759
<v Speaker 2>of money into essentially like finding the common denominator of

0:37:41.880 --> 0:37:45.040
<v Speaker 2>reader listeners. So it sort of makes sense that they

0:37:45.080 --> 0:37:48.600
<v Speaker 2>prefer the AI generated content, which I think it's back

0:37:48.640 --> 0:37:51.480
<v Speaker 2>to this like thing that a lot of journalists and

0:37:51.480 --> 0:37:54.960
<v Speaker 2>and maybe even creators forget, which is like you're you're

0:37:55.000 --> 0:37:58.120
<v Speaker 2>writing this for the reader, not for yourself, right, And

0:37:58.160 --> 0:38:01.919
<v Speaker 2>I think another thing people get really upset about that's

0:38:01.920 --> 0:38:05.000
<v Speaker 2>not AI is when like you just take forever to

0:38:05.040 --> 0:38:07.880
<v Speaker 2>get to the point, and you know, there's certain publications

0:38:07.920 --> 0:38:10.560
<v Speaker 2>that are really bad about this, and like I just

0:38:10.680 --> 0:38:13.240
<v Speaker 2>end up skipping the first three paragraphs of every article

0:38:13.280 --> 0:38:16.240
<v Speaker 2>they write because it's all just you know, basically written

0:38:16.280 --> 0:38:19.160
<v Speaker 2>for the satisfaction of the writer, not for the reader.

0:38:19.200 --> 0:38:21.600
<v Speaker 2>And so we could probably all learn something from me.

0:38:21.840 --> 0:38:23.799
<v Speaker 1>With that in mind, I think we better wrap up

0:38:23.840 --> 0:38:25.200
<v Speaker 1>this episode, but I want to get I want to

0:38:25.200 --> 0:38:27.760
<v Speaker 1>get the last word to Taylor, because I saw you

0:38:27.760 --> 0:38:31.160
<v Speaker 1>you nodding about read saying that writing's only a small

0:38:31.200 --> 0:38:34.000
<v Speaker 1>fraction of journalism, like what's your what's your final word

0:38:34.040 --> 0:38:34.239
<v Speaker 1>on that?

0:38:34.880 --> 0:38:39.200
<v Speaker 3>So I you know, I'm a bad writer, I'm dyslexic.

0:38:39.360 --> 0:38:42.200
<v Speaker 3>I'm a much better writer now than I was. But

0:38:42.400 --> 0:38:46.319
<v Speaker 3>a huge reason, I mean, it was like it was

0:38:46.360 --> 0:38:48.720
<v Speaker 3>really hard for me to even consider being a reporter

0:38:48.760 --> 0:38:49.879
<v Speaker 3>because I thought you had to be a good writer.

0:38:49.960 --> 0:38:52.800
<v Speaker 3>And this really well known editor told me at one point,

0:38:53.520 --> 0:38:56.000
<v Speaker 3>you know, basically there are journalists like the job of

0:38:56.000 --> 0:38:59.200
<v Speaker 3>a journalist is to expose new information, and no one

0:38:59.280 --> 0:39:01.880
<v Speaker 3>will care if you're a bad writer if you can

0:39:01.920 --> 0:39:05.120
<v Speaker 3>get scoops. Like, if you can expose new information, editors

0:39:05.120 --> 0:39:07.480
<v Speaker 3>will hire you no matter what because they'll rewrite your

0:39:07.480 --> 0:39:10.680
<v Speaker 3>stuff and it's fine. And I started to do that

0:39:10.840 --> 0:39:13.560
<v Speaker 3>and that's what got me hired in media, and my

0:39:13.600 --> 0:39:15.640
<v Speaker 3>writing got better over the years, and I think it's

0:39:15.680 --> 0:39:17.719
<v Speaker 3>like good now. But I'm never going to write for

0:39:17.760 --> 0:39:20.759
<v Speaker 3>the like the New Yorker long Form or some you know,

0:39:20.800 --> 0:39:24.000
<v Speaker 3>Like I'm not really that kind of journalist. And there

0:39:24.000 --> 0:39:26.359
<v Speaker 3>are journalists that are amazing writers, right, But I think,

0:39:26.440 --> 0:39:28.960
<v Speaker 3>like what Reid said, I feel the same way. I'm like,

0:39:29.000 --> 0:39:30.759
<v Speaker 3>I wish I could just feed all this stuff in

0:39:31.239 --> 0:39:33.640
<v Speaker 3>have the AI kind of put it together. The goal

0:39:33.800 --> 0:39:36.160
<v Speaker 3>to me is to like get that new information out

0:39:36.200 --> 0:39:41.120
<v Speaker 3>there and kind of let that inform inform the world.

0:39:41.560 --> 0:39:44.400
<v Speaker 1>I feel that's always the deepest cut against the Stannyokagen

0:39:44.520 --> 0:39:47.160
<v Speaker 1>that still hear like rumors that they always hand in

0:39:47.200 --> 0:39:51.000
<v Speaker 1>the shoddiest copy and like the most successful ones to

0:39:51.080 --> 0:39:53.040
<v Speaker 1>do the least good job of handing in good drafts.

0:39:53.080 --> 0:39:54.839
<v Speaker 1>But maybe that's maybe that's what you're getting.

0:39:55.000 --> 0:39:57.600
<v Speaker 2>I am just maybe you can still give Taylor the

0:39:57.680 --> 0:39:59.239
<v Speaker 2>last word, and you can edit this out if you

0:39:59.280 --> 0:40:02.359
<v Speaker 2>want to. But I I wish more journalists would take

0:40:02.400 --> 0:40:05.919
<v Speaker 2>their article before sending it to their editor and run

0:40:05.960 --> 0:40:08.399
<v Speaker 2>it through whatever their favorite chat butt is and say

0:40:08.400 --> 0:40:10.360
<v Speaker 2>what am I missing here? What are my blind spots?

0:40:10.400 --> 0:40:13.399
<v Speaker 2>Where are my biases? And like, actually take that because

0:40:13.440 --> 0:40:15.360
<v Speaker 2>that is I find super helpful.

0:40:15.600 --> 0:40:17.920
<v Speaker 3>Totally. I think, like I mean, I just think like

0:40:18.880 --> 0:40:21.440
<v Speaker 3>we should embrace these tools if they can help us

0:40:21.640 --> 0:40:25.279
<v Speaker 3>improve our jobs. And also we need to understand these

0:40:25.320 --> 0:40:28.160
<v Speaker 3>tools to report on them, especially as technology reporters. And

0:40:28.200 --> 0:40:31.319
<v Speaker 3>I said this in my interview with Substack, but there's

0:40:31.360 --> 0:40:34.640
<v Speaker 3>a lot of people that I see, especially online, that

0:40:35.080 --> 0:40:39.440
<v Speaker 3>are very performative about AI. I will say, and I

0:40:39.520 --> 0:40:41.520
<v Speaker 3>know that they're using it in their personal lives. I

0:40:41.560 --> 0:40:43.600
<v Speaker 3>know that they're using it and they're getting online all

0:40:43.680 --> 0:40:46.640
<v Speaker 3>day and saying all this slop. And I just I

0:40:47.080 --> 0:40:49.080
<v Speaker 3>to me, that bothers me because I'm like let's just

0:40:49.120 --> 0:40:51.080
<v Speaker 3>be on and say that you use it sometimes it's

0:40:51.120 --> 0:40:53.600
<v Speaker 3>not the n to the world, Like let's have a

0:40:53.640 --> 0:40:55.719
<v Speaker 3>discussion about it, but don't just get online all day

0:40:55.719 --> 0:40:58.320
<v Speaker 3>and stoke the sort of fires of the AI hate

0:40:58.360 --> 0:41:00.520
<v Speaker 3>and then like sort of quietly try already lose it

0:41:00.560 --> 0:41:03.799
<v Speaker 3>on the side, like that's silly.

0:41:04.400 --> 0:41:07.920
<v Speaker 4>That's all we have time for this week, Taylor read, thank.

0:41:07.760 --> 0:41:10.480
<v Speaker 2>You great to be here as always, thanks for having us.

0:41:20.239 --> 0:41:20.920
<v Speaker 4>For tech stuff.

0:41:21.040 --> 0:41:24.360
<v Speaker 1>I'm mos Voloshian. This episode was produced by Eliza Dennis.

0:41:24.800 --> 0:41:27.520
<v Speaker 1>It was executive produced by me and Julian Nutter The

0:41:27.600 --> 0:41:32.400
<v Speaker 1>Kaleidoscope and Katrina norvelve iHeart Podcasts. Jack intlument to this

0:41:32.520 --> 0:41:35.840
<v Speaker 1>episode and Kyle Murdoch wrote our theme song. A special

0:41:35.880 --> 0:41:39.359
<v Speaker 1>thank you to Taylor Lorenz and Read Albergotti. Please check

0:41:39.360 --> 0:41:41.280
<v Speaker 1>out all the work be put out into the world.

0:41:41.560 --> 0:41:43.400
<v Speaker 1>We're lucky to call them friends of the Pod.