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Speaker 1: Cause media.

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Speaker 2: Hi everyone, it's James coming at you with a pretty

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Speaker 2: nasty cold here. I wanted to share with you that

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Speaker 2: wildfast has swept through Los Angeles in the last couple

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Speaker 2: of days. While I'm recording this. Thousands of people have

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Speaker 2: been displaced. Five people have died that we know of

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Speaker 2: so far, thousands of structures have been burned, and many

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Speaker 2: many people in a will be finding themselves out of

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Speaker 2: their homes with nowhere to go, with very few resources.

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Speaker 2: If you'd like to help, We've come up with some

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Speaker 2: mutual aid groups who you can donate to, and we'll

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Speaker 2: be interviewing one of them on this show next week.

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Speaker 2: So if you'd like to help, the three places where

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Speaker 2: we suggest you would donate some cash are the Sidewalk Project.

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Speaker 2: That's the Sidewalkproject, dot org, Ktown for All that's letter

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Speaker 2: k t Own, f O R A l L dorg

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Speaker 2: and ETNA Street Solidarity. You can find them on Venmo

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Speaker 2: or I think on Instagram as well. That's a E

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Speaker 2: T N A str E E T S O L

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Speaker 2: I D A it t Y. All right, I'm gonna

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Speaker 2: go rest my voice.

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Speaker 1: Oh, welcome back to it could happen here a podcast

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Speaker 1: about it happening here, which is really true in a

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Speaker 1: lot of ways. Tonight, Harrison Davis and I are seated

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Speaker 1: at the glorious majestical hotel name redacted on the Las

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Speaker 1: Vegas Strip. We got a long day at CEES Monday,

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Speaker 1: listening to panels, catching up with the latest tech news,

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Speaker 1: trying gadgets, and also at the same time texting our

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Speaker 1: dear friends in Los Angeles as unprecedented fires sweep them

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Speaker 1: from their homes. Literally the gettiest threatened Pasadena and Santa

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Speaker 1: Monica are both being evacuated as once. It's a real

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Speaker 1: one to two punch of America's favorite tech show in

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Speaker 1: the apocalypse today. How are you feeling, Garret?

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Speaker 3: It's an average day in America, average.

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Speaker 1: Day in America. Temperature's not coming down anytime soon. No, no, well,

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Speaker 1: just take a moment to breathe with that. So you

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Speaker 1: want to start us off with what you did this morning?

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Speaker 1: I was paneled guy, yesterday. There was a man of

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Speaker 1: action walking around and mostly trying all the free massage chairs.

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Speaker 1: What did you see this morning?

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Speaker 3: I saw so many AI panels, half of which I

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Speaker 3: left halfway through because I knew they weren't gonna be

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Speaker 3: useful for me, just dogshity. The other half I took

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Speaker 3: notes on and just got sad. But No. Today was

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Speaker 3: full panel starting bright and early in the morning, where

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Speaker 3: I walked into a panel where I heard augmentation and

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Speaker 3: not replacement about twenty times in the span of like

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Speaker 3: twenty minutes.

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Speaker 1: Yeah. I keep hearing versions of that too. In the

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Speaker 1: Hollywood panels, they would be like, you know, we want

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Speaker 1: to develop a machine that can read the brains of

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Speaker 1: our viewers and alter the endings of movies, you know,

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Speaker 1: but we see this as a way of augmenting the

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Speaker 1: artists work.

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Speaker 3: Yes. And the biggest thing that I noticed across multiple

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Speaker 3: panels today is an almost like anxiety among these tech

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Speaker 3: executives about consumers rejecting the AI slopification of everything, and

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Speaker 3: they're trying to find ways to like actually force people

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Speaker 3: to start like using these products or having them like

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Speaker 3: like it. Yeah, And I haven't really sense that anxiety before.

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Speaker 3: It's it's all. It's all been very very positively, and

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Speaker 3: I think.

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Speaker 1: It's a mix of Number One, the money still isn't

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Speaker 1: there where they need it to be. It has not

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Speaker 1: started like blooming to the extent that they were expecting

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Speaker 1: it by now. And the other part is people are

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Speaker 1: still not happy with this stuff. I'm glad you felt

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Speaker 1: that too, because that almost was like, especially after the election,

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Speaker 1: like I don't trust my feelings on this that they're

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Speaker 1: really scared, But I really do think there's a piece

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Speaker 1: of that coming through.

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Speaker 3: No of a phrase one of the panelists used this

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Speaker 3: morning was the AI ick, like like how do we

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Speaker 3: how do we beat the AI ick? And if you

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Speaker 3: ever said yourself, how do I stop having people feel

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Speaker 3: an ick around me? Maybe you should really look inwards. Yeah,

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Speaker 3: maybe the problems you not them.

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Speaker 1: You know, who doesn't need to worry about quote unquote

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Speaker 1: I for their product market is people who make things

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Speaker 1: that people like.

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Speaker 3: So but I heard a lot about you know, and

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Speaker 3: trying to get people to use these products is like

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Speaker 3: making sure artists don't feel like they're being replaced instead

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Speaker 3: having their like art production process be augmented with AI

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Speaker 3: and how how that can make art easier to make

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Speaker 3: while still keeping the human at the center of AI tools.

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Speaker 3: And this is just what they talked about for like

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Speaker 3: a while, while reiterating that lots of the developments they

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Speaker 3: need to see on AI, they have it on the

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Speaker 3: tech side, what they need to rely on is consumer

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Speaker 3: acceptance to really drive the innovation, to see like what

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Speaker 3: they can get away with, Like how much will the

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Speaker 3: consumer accept the sophification of art and entertainment and customer

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Speaker 3: service and all these things are trying to cram AI

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Speaker 3: into and like.

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Speaker 1: How much worse can you make the world before people

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Speaker 1: stand up and stop you with their fists or guns.

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Speaker 3: And you mentioned something about like trying to like tailor

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Speaker 3: like movie endings for specific people, and i' I heard

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Speaker 3: them stuff about that. There's this one guy who was

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Speaker 3: who was like the panel's resident like content creator who's

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Speaker 3: supposed to represent like the artist block, even though he's like, eh, yeah,

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Speaker 3: you know some kind of like AI friendly content creator

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Speaker 3: though on this panel, and he talked about how like

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Speaker 3: back in the day, you need to have friends that

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Speaker 3: would like recommend you music, and like the Spotify algorithm

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Speaker 3: is is too based on like an echo chamber what

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Speaker 3: you already like, but now with a gentic AI this

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Speaker 3: allows trust between the consumer and the machine to recommend

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Speaker 3: new music. And like again, like so much of these

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Speaker 3: AIR products is just trying to like replace friendship.

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Speaker 1: Yeah, people, have you tried friends have you tried people?

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Speaker 3: How can you engage with like art and culture without friends,

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Speaker 3: Like how can you like learn more about like what

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Speaker 3: your friends are into what they like? How can you

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Speaker 3: discover new music just like without that instead replacing that

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Speaker 3: beautifully human process.

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Speaker 1: Every year at cees, there are points in time where

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Speaker 1: I get that, like, oh yeah, twenty twenty really fucked

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Speaker 1: us up a lot, Like twenty twenty really did some

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Speaker 1: lasting damage. Like I know it was that was happening

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Speaker 1: with the younger generation before the iPad kid generation, but

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Speaker 1: like that that really did a number on some folks.

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Speaker 3: Someone from Meta right of Facebook specifically they're like metaverse division,

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Speaker 3: which they're still trying to push for by.

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Speaker 1: The way, Oh yeah, now, I mean they're still calling

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Speaker 1: it meta, which honestly, there's a degree which I almost

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Speaker 1: respect it because like we are not biting no.

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Speaker 3: One, No one is. But she talked about how how

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Speaker 3: they can like blend the metaverse and AI to make

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Speaker 3: customized personal experiences. Say that you're watching an immersive live

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Speaker 3: concert in the mixed reality something that both me and

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Speaker 3: Aubert do all the time, and.

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Speaker 1: Hairy styles mixed reality concerts. We're seeing the hundred gets, you.

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Speaker 3: Know, honestly, a one hundred x mixed reality concert could

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Speaker 3: go crazy.

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Speaker 1: Here We'll finally I'll finally get you pilled on real

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Speaker 1: big fish.

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Speaker 3: But basically, as you're in this like metaverse concert, they

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Speaker 3: can have an AI that will sense your own excitement

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Speaker 3: and personalize the ending of the experience based on your

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Speaker 3: favorite songs or artists. So as they're getting excited from

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Speaker 3: like AI, Taylor Swift can like finish the song like

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Speaker 3: for you based on like your own like musical taste,

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Speaker 3: based on what the AI knows about you. And it's

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Speaker 3: about creating these customized experiences.

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Speaker 1: It's such a you can clearly tell that none of

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Speaker 1: these people have souls, right, It's such a mismatch of

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Speaker 1: what people get from music because they think that like, oh,

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Speaker 1: this is just like a if I see that like

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Speaker 1: this specific beat line is I can just sort of

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Speaker 1: like plug this in and like, I don't know, Like

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Speaker 1: what makes people react to musicians and artists is that

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Speaker 1: they like make things that make them feel something like

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Speaker 1: That's why people get like really into artists, is they

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Speaker 1: feel seen and identify with a piece of art, as

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Speaker 1: opposed to like, oh, oh that guy really like the

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Speaker 1: first opening bars to fucking octopus's garden, Like let's let's

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Speaker 1: just like really turn up the octopus a lot more octopuses.

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Speaker 1: How many more octopuses can we fit in this fucking

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Speaker 1: in this track?

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Speaker 3: No. Another panel I went to later in the day

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Speaker 3: was about like how do you market to gen z?

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Speaker 3: Very funny panel. Yeah, and and they're talking about how

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Speaker 3: like authenticity is so important, like you need to partner

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Speaker 3: with influencers that have like have like an authentic brand.

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Speaker 3: And it's funny having that ductionapost with like these like

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Speaker 3: these like AI slot panels were like you need like

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Speaker 3: an AI Taylor Swift to come like boost the excitement

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Speaker 3: for all these kids who are in their metaverse concerts.

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Speaker 3: Oh boy, But no, like personalized content like like targeting

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Speaker 3: like AI AI generated content specifically for certain people, for

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Speaker 3: certain users, whether it's on social media, whether that's on

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Speaker 3: you know, the metaverse. Like some of these people talk

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Speaker 3: about someone on the panel from Adobe, who's you know,

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Speaker 3: Adobe's integrating a whole bunch of generative AI into their

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Speaker 3: like suite of products, right, like a Photoshop premiere after effects, right,

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Speaker 3: big big company in the creative space. He said, They're

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Speaker 3: like personalized content is always the most impactful, like content

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Speaker 3: that a person feels like a genuine connection to, and

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Speaker 3: that connection could be fted by just being like, you know,

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Speaker 3: a compelling artist where you can recognize shared experiences of

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Speaker 3: shared experiences of humanity. But now you don't need that

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Speaker 3: artist part anymore. He said, they only need three parts

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Speaker 3: to create a pipeline. You need data, you need compelling

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Speaker 3: like journeys to take the user on, and you need

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Speaker 3: the content itself. And the goal is to create content

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Speaker 3: at scale that's highly personalized. He said quotes. We're good

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Speaker 3: at the first two parts. Now we just need to

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Speaker 3: improve the actual content side, which I don't even think

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Speaker 3: that's true. I don't think AI is good at creating

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Speaker 3: compelling human journeys.

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Speaker 1: I had it. So the video I didn't play you

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Speaker 1: guys from my terrible fucking AI generated videos was this.

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Speaker 1: It was like a girl coming to college. We need

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Speaker 1: a picture of her dad, and it was like a

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Speaker 1: narration of her life with her father who like is

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Speaker 1: dead that she misses and all that she learned from him.

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Speaker 1: Data and it like it's a mix of like all

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Speaker 1: these different like there's a chunk where it looks like

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Speaker 1: a Disney animated picture. There's a chunk where it looks

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Speaker 1: like anime. She and her dad having these like adventures

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Speaker 1: around the world is a bit of looks like a

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Speaker 1: Marvel movie. And he's like, we can do all these

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Speaker 1: different you know, animation styles and they're seamless and like,

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Speaker 1: you know, the audience really goes on a journey with this.

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Speaker 1: And it's like, but there's there was no girl who

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Speaker 1: lost your dad. Nobody lost their dad here. This is

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Speaker 1: you just had a computer generate text about a dad dying.

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Speaker 1: Like there's nothing underpinning this, right, nobody has anything they're

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Speaker 1: trying to get across, Like you just know, in this one,

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Speaker 1: they look like Marvel heroes for some reason. In this

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Speaker 1: one they look like Zulu warriors, kind of done up

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Speaker 1: in a slightly racist lion king style. Like what is

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Speaker 1: being transmitted other than like, look at all of the

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Speaker 1: different art styles we can rip off.

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Speaker 3: Now they do not have a journey, but even they

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Speaker 3: themselves admit that they still don't have the content. The

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Speaker 3: content itself still isn't even there. And that's something like

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Speaker 3: they even acknowledge. And this is like a hurdle to

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Speaker 3: this is this is a hurdle to get over. What

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Speaker 3: they do have is the data, and like this is

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Speaker 3: like something that Adobe has done because if you use

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Speaker 3: Adobe products now some of the most used creative products,

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Speaker 3: Adobe trains all of their AI systems, all the stuff

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Speaker 3: that you make using their products, which you know, he

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Speaker 3: really just blazed past that point because that's that's a

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Speaker 3: whole other discussion. But even they know that they don't

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Speaker 3: have like the actual products and this is still reliant

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Speaker 3: on like consumer acceptance. As as they said before someone

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Speaker 3: from Meta, the same person on the panel that talked

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Speaker 3: about how like a few days ago on Instagram, they

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Speaker 3: tried to announce like you'll have like AI profiles right,

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Speaker 3: like like completely AI generated pictures profiles, like you know,

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Speaker 3: like fake people who have their own accounts, And this

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Speaker 3: created such a big backlash that they rolled this back

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Speaker 3: and they simply announced this before Cees.

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Speaker 1: One of these accounts was literally like I'm a mother

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Speaker 1: of two queer black woman. You know, yeah, I got

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Speaker 1: a lot to say about the world. Someone call up

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Speaker 1: the situationists please, And some like people started talking to

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Speaker 1: were like, we're any black people at all involved in

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Speaker 1: like making this chatbot. She was like, well no, and

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Speaker 1: that's a real problem. That is a real problem.

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Speaker 3: Okay, Yes, And the excuse that this person for Meta

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Speaker 3: said is that the market just isn't ready yet. It's

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Speaker 3: not that the actual product itself is like bad or

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Speaker 3: like no one really wants. The market's not ready yet.

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Speaker 1: Well, they're so used to everything that they've done so far.

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Speaker 1: They've kept getting money right, and like it slowed down

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Speaker 1: and they've had to do layoffs, but like nobody's just

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Speaker 1: made them stop at any point, which, honestly, you know,

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Speaker 1: I made a comment about healthcare executives a while back,

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Speaker 1: needing like a fucking retirement plan paid in millimeters. So

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Speaker 1: I'm not going to make that same comment about tech

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Speaker 1: industry rules because you know, we all know what's in

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Speaker 1: the news. But something has to be done to force

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Speaker 1: these people to stop moving in this direction. And I

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Speaker 1: don't know how to get across and like they're already

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Speaker 1: at this point, like they seem to really want not

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Speaker 1: want this, and we have to find a way. They're

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Speaker 1: just not ready. We have to find a way to

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Speaker 1: force this on them. I don't know how to get

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Speaker 1: across to them in a peaceful manner.

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Speaker 3: Oh oh sorry, people don't want.

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Speaker 1: This man of peace Garrison. I'm a man of peace.

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Speaker 1: I'm not a plumber.

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Speaker 3: The last thing I had to add out of this panel,

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Speaker 3: just in terms of how much this stuff is just

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Speaker 3: actually taking over more and more of the market even

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Speaker 3: if people don't want it, is that the guy from

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Speaker 3: Adobe announced it in the fourth quarter of last year.

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Speaker 3: They were able to boost all of the Adobe's like

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Speaker 3: you know, emails. If you send like an email to Adobe, right,

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Speaker 3: you have a problem, like you need help. But like

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Speaker 3: everything that they do on emails is now one hundred

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Speaker 3: percent generated by AI. And this was boosted from fifty

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Speaker 3: percent at the start of last year. Now it's one

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Speaker 3: hundred percent of all of their email content is now

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Speaker 3: done by AI with some moderation.

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Speaker 1: But there comes like when the company itself is like

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Speaker 1: communicating with customers through emails.

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Speaker 3: That's what it sounded like.

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Speaker 1: Yes, they're still writing emails sometimes to each other or

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Speaker 1: for that too.

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Speaker 3: He described it as like email content. So I'm pretty

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Speaker 3: sure it is customer service stuff like marketing, maybe like outreach,

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Speaker 3: like certain like outreach things. But yeah, like what one

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Speaker 3: hundred percent now generated by AI with some human like moderation.

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Speaker 3: But yeah, that is where things are moving and that's

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Speaker 3: how I started my morning.

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Speaker 1: Well, better than a cup of coffee. Is that sense

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Speaker 1: of creeping dread that like, Wow, I just saw a

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Speaker 1: bunch of people who will probably would rather kill the

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Speaker 1: world than be stopped from shoveling AI slop into people's mouths,

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Speaker 1: because this is the only future they can imagine, is

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Speaker 1: one in which they work for a company that feeds

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Speaker 1: the planet poison and kills the human concept of creativity

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Speaker 1: so that they can buy a house in San Francisco.

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Speaker 3: Do you know what I want to feed the concept.

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Speaker 1: Of Yeah, we'll talk about that, but here's some ants.

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Speaker 1: We're back. What was part two of this episode? That's

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Speaker 1: feed buddy. I'm ah, oh, let's talk about that helicopter. No, yeah,

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Speaker 1: I think yeah.

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Speaker 3: As I was going from panel to panels scrippling notes

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Speaker 3: on AI. Yeah, has some very exciting news stories drop

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Speaker 3: that we'll talk about later. What were you up to, Robert, Well,

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Speaker 3: I was. I was trawling the show floor as I

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Speaker 3: oft do.

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Speaker 1: At some point in a cees and I came across

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Speaker 1: a number of majestic products. You know, a lot of

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Speaker 1: it was AI based, and we'll talk some more about

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Speaker 1: that here. But I ran into something that was thank god,

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Speaker 1: had nothing to do with AI and it's a death trap.

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Speaker 1: Every every one of these.

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Speaker 3: There's like some sort of yes, we find a new death.

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Speaker 1: There's a lot of connected vehicles. There were a lot

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Speaker 1: of evs last year. There were a ton of different

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Speaker 1: flying taxi type options people that were really trying to.

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Speaker 3: But you don't see it all this year.

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Speaker 1: Nothing this year, nothing this year, because it's a terrible idea.

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Speaker 1: It's a terrible idea. The people who are rich enough

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Speaker 1: to pay for flying vehicles don't want it to be

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Speaker 1: a taxi, and the people who can't afford their own

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Speaker 1: flying vehicles also can't afford anyway. So this is instead

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Speaker 1: of any of that. Richter r i ct O R,

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Speaker 1: which is a Chinese company. Their ads say, I'll say

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Speaker 1: why be normal, saying this the future of travel will

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Speaker 1: not be on the ground. And the Richter is a hybrid.

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Speaker 1: It is like a smart car style sized vehicle. It's

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Speaker 1: like half the side. It only has two wheels, though

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Speaker 1: it looks more like a scooter. It's more like a

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Speaker 1: weird little scooter, but it's fully enclosed and in addition

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Speaker 1: to having its wheels and being able to travel about

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Speaker 1: on the ground. It has four like quadrocopters style rotors

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Speaker 1: because it is an aquatic flying car. Aquatic flying I

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Speaker 1: saw no evidence that could actually go in the water.

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Speaker 3: How high can these things go? Up?

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Speaker 1: Less than two hundred meters? You know why, Garrison?

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Speaker 3: Why? Why is that?

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Speaker 1: Because if you try to go above that you need

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Speaker 1: a pilot's license. You don't need a pilot slicnse I

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Speaker 1: have that. When I was interviewing them, I was like, so,

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Speaker 1: I assume there's gonna be some sort of pilot's license

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Speaker 1: for this flying craft. And they're like, no, as long

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Speaker 1: as you stand nd two hundred meters, you get.

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Speaker 3: Do you need drivers? Like? Are you gonna put a

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Speaker 3: license plate on this?

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Speaker 1: Or there's no space for one?

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Speaker 3: Buddy's completely unregularly to.

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Speaker 1: Be honest, and I don't say this for anny problematic reason,

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Speaker 1: but like, these folks are Chinese and did not seem

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Speaker 1: to have a great deal of knowledge about the US

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Speaker 1: words sure that said, I can't imagine China's less strict

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Speaker 1: about personal aircraft.

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Speaker 3: I would like to take this fucker on the I five,

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Speaker 3: just start start to zooming.

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Speaker 1: Yeah, see it.

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Speaker 3: Up in the air, because you could probably do like

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Speaker 3: a pretty a pretty good road trip on this right,

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Speaker 3: you can you can? You can be about that.

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Speaker 1: So it's very small and it's completely electric. So I

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Speaker 1: asked him, how much time do you get in the

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Speaker 1: air with this bad boy on battery? Maybe twenty five minutes?

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Speaker 3: What happens after twenty minutes?

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Speaker 1: I did ask this, and I was like, this is

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Speaker 1: just rough out of the sky, and they're like, no,

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Speaker 1: we're working on like a like an intelligent thing that

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Speaker 1: will like.

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Speaker 3: Land.

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Speaker 1: Yeah, which is also very exciting, really really looking forward

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Speaker 1: to seeing how they pull that off. The videos that

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Speaker 1: they have show it driving on the highway too. They

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Speaker 1: weren't able to tell me what a top speed was.

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Speaker 1: It has no rear view mirrors and no side view mirrors,

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Speaker 1: but they said there's lots of cameras on the inside,

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Speaker 1: so I'm sure that's fine. It's a death trap. This

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Speaker 1: thing will get everyone who even looks at it wrong killed.

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Speaker 1: They should be a video of the prototype. It was

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Speaker 1: completely frameless. It was just quadrcopter blades and like a

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Speaker 1: chair on a platform lifting a guy into the air.

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Speaker 1: It couldn't go forward or backwards. But they're like, a year,

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Speaker 1: we canna have this figure out.

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Speaker 3: It can't it can't move forward.

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Speaker 1: It only only went up in the videos I saw,

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Speaker 1: So you can't actually travel, absolutely not. I couldn't by

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Speaker 1: the way. I couldn't fit in this thing, like you

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Speaker 1: would be cramped in this fucker.

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Speaker 3: But it's good for vertical travel.

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Speaker 1: It's great if you just need to go up to

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Speaker 1: under two hundred meters. There's no more efficient way.

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Speaker 3: If you pull over by the cops, you just just.

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Speaker 1: Go up above them. I'm in the sky now. You

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Speaker 1: can't do shit to me for five mass minutes. Oh god,

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Speaker 1: it's like if you're just driving, you go up to

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Speaker 1: one hundred kilometers, which made me think, so agad, that's

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Speaker 1: like sixty the year for twenty minutes. Then I land,

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Speaker 1: Then my battery is dead.

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Speaker 3: Then you can't go anywhere.

400
00:19:14,960 --> 00:19:16,360
Speaker 1: You can't go anywhere. You can get back.

401
00:19:16,560 --> 00:19:19,320
Speaker 3: The battery issue is gonna is gonna be troubling.

402
00:19:19,440 --> 00:19:20,760
Speaker 1: But it seems completely useless.

403
00:19:20,800 --> 00:19:24,119
Speaker 3: But as we've heard NonStop the past two days, this

404
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Speaker 3: is the worst it's gonna be.

405
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Speaker 1: This is the worst it's gonna be. Only gonna get better.

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Speaker 3: Things only ever get better.

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Speaker 1: That's that's what everyone was trying to insist upon. To

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Speaker 1: may hear what else did you see on the show

409
00:19:34,400 --> 00:19:38,000
Speaker 1: floor that cut your off garrison? So many magical, wonderful,

410
00:19:38,160 --> 00:19:41,280
Speaker 1: marvelous things, most of which were just like various different

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Speaker 1: AI connected smart houses. That was what Samsung was showing off.

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Speaker 1: That was what LG was showing off. But I believe

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Speaker 1: you saw one as well, right, Yeah, I mean I

414
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Speaker 1: I walked through the LG booth.

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Speaker 3: It was kind of the same as same as last year.

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Speaker 3: The Samsung booth was too intimidating. But I should check

417
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Speaker 3: it out because last year we didn't do the sums

418
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Speaker 3: hung booth because we were going to and then either

419
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Speaker 3: either one of us threw up or spilled something.

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Speaker 1: Hey, okay, okay, yes, did I Did I pour my

421
00:20:15,400 --> 00:20:19,520
Speaker 1: crative into a constant into a carbonated beverage that spewed

422
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Speaker 1: a geyser a blood red foam into the sky around

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Speaker 1: to the white sung Did the security guard stare at

424
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Speaker 1: me as it happened? Did I set the drink down

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Speaker 1: as it continued to spew and said, I'll go get

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Speaker 1: some towels and then leave forever towels? Yeah?

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Speaker 3: Left? We fucking bounced so we couldn't do them booth

428
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Speaker 3: last year. Maybe I'll try it this year. But tell

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Speaker 3: me about these smart houses.

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Speaker 1: Well, Garrett, Sam Sumi has a great idea for a

431
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Speaker 1: smart house. First of all, you wear that game the sims. No,

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Speaker 1: well they're really betting that you do, because their current

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Speaker 1: plan is design and you're a home with the AI

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Speaker 1: powered map views. Okay, okay, sure, you get like you

435
00:21:03,760 --> 00:21:06,080
Speaker 1: should feed it like a picture. You like, you lay

436
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Speaker 1: out your your floor planning your house, and it gives

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Speaker 1: you like a three D model and you can take

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Speaker 1: pictures of your furniture or pictures of furniture that you want,

439
00:21:14,240 --> 00:21:15,679
Speaker 1: and then it really places it around and you can

440
00:21:15,760 --> 00:21:18,000
Speaker 1: place them. Now, a couple of things, one of them

441
00:21:18,080 --> 00:21:21,159
Speaker 1: is that there's no scaling done by the AI, so

442
00:21:21,200 --> 00:21:24,920
Speaker 1: it's up to you to figure out how the furniture

443
00:21:24,960 --> 00:21:28,399
Speaker 1: you might want to buy measures up in comparison to

444
00:21:28,520 --> 00:21:29,120
Speaker 1: the apartment.

445
00:21:29,240 --> 00:21:29,440
Speaker 3: Sure.

446
00:21:29,560 --> 00:21:32,600
Speaker 1: Sure, but it does look like the actual like map

447
00:21:32,640 --> 00:21:34,400
Speaker 1: that they've got. I'll show you the picture that I took.

448
00:21:35,320 --> 00:21:38,080
Speaker 1: I'll try to put it up somewhere like it looks

449
00:21:38,160 --> 00:21:41,720
Speaker 1: like the video game the simps. You're populating like a

450
00:21:42,080 --> 00:21:44,760
Speaker 1: little three D CGI house. And I was like, okay,

451
00:21:44,760 --> 00:21:47,600
Speaker 1: well there's there's a use there, right. People like planning out,

452
00:21:47,640 --> 00:21:49,560
Speaker 1: Like you you're moving into a new apartment, you can

453
00:21:49,600 --> 00:21:51,479
Speaker 1: like fill it in here, and before you even move in,

454
00:21:51,600 --> 00:21:53,760
Speaker 1: you can figure out what kind of furniture you need

455
00:21:53,880 --> 00:21:56,359
Speaker 1: or how you're existing furniture will fit in there. I

456
00:21:56,359 --> 00:21:59,080
Speaker 1: would never have used that. I usually picked up all

457
00:21:59,119 --> 00:22:01,240
Speaker 1: of my furniture from the trash before I had a

458
00:22:01,280 --> 00:22:04,000
Speaker 1: house when I moved into a new place. But I

459
00:22:04,320 --> 00:22:06,680
Speaker 1: know people who would have used that. Sure, that seems useful.

460
00:22:06,680 --> 00:22:09,200
Speaker 1: So I talked about security. Some one thing that concerned

461
00:22:09,200 --> 00:22:10,520
Speaker 1: me is like the first guy I talked to, he

462
00:22:10,600 --> 00:22:13,160
Speaker 1: was like, oh, yeah, I think it's all stored locally.

463
00:22:13,560 --> 00:22:15,399
Speaker 1: And I was like, so Samsung doesn't have any access

464
00:22:15,440 --> 00:22:17,719
Speaker 1: to any of the data on like my house and

465
00:22:17,800 --> 00:22:20,000
Speaker 1: its layout. And he was like, let me, let me

466
00:22:20,119 --> 00:22:22,080
Speaker 1: get you to one of our engineers because he can

467
00:22:22,119 --> 00:22:25,119
Speaker 1: answer that question. And the engineer's answer was, and I'm

468
00:22:25,160 --> 00:22:26,119
Speaker 1: paraphrasing here.

469
00:22:26,320 --> 00:22:27,960
Speaker 3: Oh okay.

470
00:22:28,000 --> 00:22:29,160
Speaker 1: So that made me very confident.

471
00:22:29,240 --> 00:22:32,200
Speaker 3: That does make you feel safe about sharing your personal data?

472
00:22:32,280 --> 00:22:34,920
Speaker 1: Right, yeah, I'm the layout of my actual house well.

473
00:22:34,920 --> 00:22:36,719
Speaker 3: And the thing is, I really don't like that at all,

474
00:22:36,760 --> 00:22:38,919
Speaker 3: because this is this is something that people were asking

475
00:22:38,960 --> 00:22:42,199
Speaker 3: Facebook slash meta when they were doing like their you know,

476
00:22:42,280 --> 00:22:45,119
Speaker 3: like metaverse stuff because their headsets are recording you know,

477
00:22:45,320 --> 00:22:48,480
Speaker 3: very very extensively, like your home layout, and the whole

478
00:22:48,520 --> 00:22:51,199
Speaker 3: point well, part of the point was that some of

479
00:22:51,240 --> 00:22:53,520
Speaker 3: that data could then be used to send you targeted

480
00:22:53,560 --> 00:22:57,320
Speaker 3: advertisements based on them seeing everything in your home. And

481
00:22:57,400 --> 00:23:02,000
Speaker 3: I suspect that Sam Sung might also have some interest

482
00:23:02,080 --> 00:23:05,479
Speaker 3: in targeted advertisements, being a tech company, but you know,

483
00:23:05,520 --> 00:23:07,000
Speaker 3: I could never say.

484
00:23:07,480 --> 00:23:10,040
Speaker 1: Yeah, and they were that wasn't really one thing they

485
00:23:10,040 --> 00:23:12,320
Speaker 1: had is for like their retail segment, they had like

486
00:23:12,800 --> 00:23:16,040
Speaker 1: a live video grocery store ad showing you prices of

487
00:23:16,080 --> 00:23:19,040
Speaker 1: different produce and I think like the insinuation that didn't

488
00:23:19,080 --> 00:23:21,400
Speaker 1: lay out is like you can change prices on the fly,

489
00:23:21,920 --> 00:23:24,200
Speaker 1: you know it, which kind of made me think about that.

490
00:23:24,680 --> 00:23:26,600
Speaker 1: There was some talk last year of like, Okay, we

491
00:23:26,680 --> 00:23:29,320
Speaker 1: want to be able to like face scan customers so

492
00:23:29,359 --> 00:23:31,840
Speaker 1: we can see if they have money and increase prices

493
00:23:31,880 --> 00:23:34,800
Speaker 1: for like products for certain people, which I'm sure they're

494
00:23:34,840 --> 00:23:37,040
Speaker 1: going to try. They were too enticed by that idea

495
00:23:37,160 --> 00:23:40,240
Speaker 1: not to so I caught a little bit of that,

496
00:23:40,320 --> 00:23:42,640
Speaker 1: But they really like to the extent of how big

497
00:23:42,680 --> 00:23:45,719
Speaker 1: And this was an interesting last year, Samsung and LG

498
00:23:45,840 --> 00:23:47,480
Speaker 1: their boots were huge and they had a lot of

499
00:23:47,480 --> 00:23:50,080
Speaker 1: get different gadgets. Sam Times booth is big this year.

500
00:23:50,800 --> 00:23:54,720
Speaker 1: Forty percent of it was that scan your furniture, scan

501
00:23:54,840 --> 00:23:57,960
Speaker 1: your fucking like map acts. Not that much like very

502
00:23:58,119 --> 00:24:00,480
Speaker 1: little actual shit going on.

503
00:24:00,560 --> 00:24:03,119
Speaker 3: The people slap the word AI onto everything there was.

504
00:24:03,160 --> 00:24:05,240
Speaker 3: Another big thing was all Samsung.

505
00:24:05,280 --> 00:24:07,840
Speaker 1: Because Samsung makes a ton of appliances, they make TVs,

506
00:24:07,880 --> 00:24:09,760
Speaker 1: all sorts of entertainment products. All of them have this

507
00:24:09,800 --> 00:24:11,879
Speaker 1: I figure what they called like samsum tag or something

508
00:24:12,200 --> 00:24:14,359
Speaker 1: that you can you can map it in your phone,

509
00:24:14,359 --> 00:24:15,800
Speaker 1: so you can have a whole map of all of

510
00:24:15,800 --> 00:24:18,040
Speaker 1: the devices and shit that you have in your phone

511
00:24:18,040 --> 00:24:20,119
Speaker 1: and you can control them all from a single point.

512
00:24:20,200 --> 00:24:22,280
Speaker 1: And right, no one, by the way, had any interest

513
00:24:22,280 --> 00:24:24,880
Speaker 1: in answering my security questions there. But also if you're

514
00:24:24,960 --> 00:24:27,080
Speaker 1: into that, if you want to have all of your

515
00:24:27,119 --> 00:24:30,360
Speaker 1: appliances and entertainment things linked up and controlled on your

516
00:24:30,400 --> 00:24:33,320
Speaker 1: phone and all of them are Samsung, you don't care.

517
00:24:33,720 --> 00:24:36,359
Speaker 3: You don't care about no, if you're getting a smart home,

518
00:24:36,400 --> 00:24:38,000
Speaker 3: I don't think you really really care about that.

519
00:24:38,080 --> 00:24:39,959
Speaker 1: But also none of it was like, yeah, I can

520
00:24:40,000 --> 00:24:43,359
Speaker 1: control everything from my phone. You've been promising me that literally,

521
00:24:43,480 --> 00:24:47,080
Speaker 1: like in twenty eleven decades they were promising me you're

522
00:24:47,119 --> 00:24:48,679
Speaker 1: gonna be able to control your whole house thing.

523
00:24:48,720 --> 00:24:50,879
Speaker 3: It feels new this year. This is the thing. Is

524
00:24:50,920 --> 00:24:53,159
Speaker 3: like even walking through the LGB with which usually has

525
00:24:53,200 --> 00:24:56,399
Speaker 3: some really cool new thing, this year nothing new, No,

526
00:24:56,640 --> 00:24:59,399
Speaker 3: nothing new. They slapped the word AI on one corner

527
00:24:59,400 --> 00:25:00,600
Speaker 3: of their TELEVI set.

528
00:25:00,760 --> 00:25:00,960
Speaker 1: Right.

529
00:25:01,200 --> 00:25:03,840
Speaker 3: I guess LG does have like a large language model

530
00:25:03,920 --> 00:25:05,919
Speaker 3: in like one corner of their booth, but like so

531
00:25:05,960 --> 00:25:08,360
Speaker 3: does everyone else, Like that's not like, yeah compelling.

532
00:25:08,640 --> 00:25:11,960
Speaker 1: There was sk which is a South Sees Korea company

533
00:25:12,320 --> 00:25:16,439
Speaker 1: there booth again the massive like aire a big thing,

534
00:25:16,480 --> 00:25:18,800
Speaker 1: but it's nothing. It's just a big visual display that

535
00:25:18,840 --> 00:25:21,080
Speaker 1: looks cool, that looks like a bunch of server racks,

536
00:25:21,080 --> 00:25:24,160
Speaker 1: like you're in this huge cube of servers. But everything's

537
00:25:24,160 --> 00:25:27,120
Speaker 1: just like Echo does different actual products. One of them

538
00:25:27,160 --> 00:25:31,320
Speaker 1: was real time CCTVs that use an AI at like

539
00:25:31,359 --> 00:25:34,639
Speaker 1: an LLM type thing to summarize pictures. So I like

540
00:25:34,720 --> 00:25:36,479
Speaker 1: walked through and it did pick me out as a

541
00:25:36,520 --> 00:25:39,359
Speaker 1: notable person. So I've got like this people of interest

542
00:25:39,359 --> 00:25:42,879
Speaker 1: thing where it's like a man holding a smartphone standing

543
00:25:42,920 --> 00:25:46,000
Speaker 1: next to another man. But also I'm like, what does

544
00:25:46,000 --> 00:25:48,480
Speaker 1: that really get you, Like the fact that you're summarizing

545
00:25:48,560 --> 00:25:50,840
Speaker 1: up like these people who are like this person's kneeling

546
00:25:50,840 --> 00:25:53,320
Speaker 1: and taking a picture this person standing because I like

547
00:25:53,600 --> 00:25:56,159
Speaker 1: actually tried deliberately, I like reached to my bag to

548
00:25:56,200 --> 00:25:58,520
Speaker 1: try to be suspicious. I like did finger guns and

549
00:25:58,560 --> 00:26:01,040
Speaker 1: it never marked me out. And I can pull a

550
00:26:01,080 --> 00:26:03,520
Speaker 1: real gun or anything, because I very rarely bring that

551
00:26:03,560 --> 00:26:07,760
Speaker 1: to the cees for But I don't know, like I

552
00:26:07,800 --> 00:26:09,439
Speaker 1: can see how there could be a utility there if

553
00:26:09,440 --> 00:26:12,320
Speaker 1: you're actually able to say you're setting up like surveillance

554
00:26:12,640 --> 00:26:15,439
Speaker 1: side of a residential building and it can alert security

555
00:26:15,520 --> 00:26:18,840
Speaker 1: that like something is happening outside. There's a potential you

556
00:26:18,960 --> 00:26:21,320
Speaker 1: if it's good enough utility in that that they didn't

557
00:26:21,359 --> 00:26:24,480
Speaker 1: display it at the show. It was literally just describing

558
00:26:24,640 --> 00:26:27,680
Speaker 1: randos from the audience, And like, I just don't see

559
00:26:27,680 --> 00:26:29,240
Speaker 1: how a security guy is there's a guy with a

560
00:26:29,320 --> 00:26:31,160
Speaker 1: phone on outside of the building, like.

561
00:26:31,240 --> 00:26:34,840
Speaker 3: A yeah, no, it's it doesn't seem very new, it

562
00:26:34,840 --> 00:26:36,480
Speaker 3: doesn't seem very innovative.

563
00:26:36,800 --> 00:26:39,520
Speaker 1: Nah. So again when I'm when I'm seeing here, overwhelmingly

564
00:26:39,600 --> 00:26:42,280
Speaker 1: for all the talk about like there's no resisting it.

565
00:26:42,440 --> 00:26:45,159
Speaker 1: AI's coming. It's going to dominate everything. This is the

566
00:26:45,200 --> 00:26:48,760
Speaker 1: next big thing. A remarkable lack outside of what I

567
00:26:48,800 --> 00:26:51,640
Speaker 1: will say. The one thing where there are continuously new

568
00:26:51,680 --> 00:26:55,400
Speaker 1: products that are better every year the smart glasses. Yes,

569
00:26:55,480 --> 00:26:58,960
Speaker 1: they're getting more impressives. I don't think I'll ever be

570
00:26:59,040 --> 00:27:02,080
Speaker 1: a smart glasses guy. I hated glasses enough that I

571
00:27:02,200 --> 00:27:04,560
Speaker 1: let them shoot me in the eye with lasers. Shout

572
00:27:04,600 --> 00:27:09,479
Speaker 1: out to our lacek sponsors. But I see why people

573
00:27:09,520 --> 00:27:13,119
Speaker 1: would like it, and there seems to be legitimately substantial

574
00:27:13,280 --> 00:27:14,240
Speaker 1: utility if we.

575
00:27:14,200 --> 00:27:16,320
Speaker 3: Have high power smart glasses. Yeah, that look like a

576
00:27:16,320 --> 00:27:18,760
Speaker 3: regular pair of glasses. I will get a pair of eventually,

577
00:27:18,800 --> 00:27:21,480
Speaker 3: because yeah, why not. There was a great demo. I'm

578
00:27:21,520 --> 00:27:24,480
Speaker 3: pulling over to an LAWK view.

579
00:27:24,720 --> 00:27:26,640
Speaker 1: They had like one glass that was the first world

580
00:27:26,760 --> 00:27:29,840
Speaker 1: smart glasses for TikTok life. Not particularly excited about that.

581
00:27:29,880 --> 00:27:32,439
Speaker 1: But they had another set of ar glasses with a

582
00:27:32,480 --> 00:27:35,240
Speaker 1: twelve hour battery, where like, if it works as well

583
00:27:35,280 --> 00:27:37,080
Speaker 1: as the demo, and that's a big if, but it

584
00:27:37,800 --> 00:27:40,200
Speaker 1: seems to like your smart watch, so it'll tell you

585
00:27:40,320 --> 00:27:42,360
Speaker 1: can see in a heads up display as you're cycling.

586
00:27:42,359 --> 00:27:44,960
Speaker 1: That was the demo it'll both like give you directions

587
00:27:45,000 --> 00:27:47,240
Speaker 1: like in your eyes. And it seemed to be like

588
00:27:47,320 --> 00:27:50,320
Speaker 1: fairly well thought out, so it's not like overly corrupting

589
00:27:50,359 --> 00:27:52,760
Speaker 1: your view. It'll show you your heart rate, you know,

590
00:27:52,800 --> 00:27:55,600
Speaker 1: it'll show you like all that kind of stuff. So

591
00:27:55,640 --> 00:27:59,480
Speaker 1: you get like a useful degree of control and assistance

592
00:27:59,480 --> 00:28:01,760
Speaker 1: from that kind of thing. And that is I will

593
00:28:01,800 --> 00:28:04,600
Speaker 1: say the last three cees is the glasses get a

594
00:28:04,600 --> 00:28:07,439
Speaker 1: little better and a little smaller every year. Smaller, certainly,

595
00:28:07,480 --> 00:28:10,800
Speaker 1: I would say that's a real product that's probably going

596
00:28:10,880 --> 00:28:12,200
Speaker 1: to continue to improve.

597
00:28:12,960 --> 00:28:16,399
Speaker 3: Do you know what else always seeks improvement, Robert No,

598
00:28:16,920 --> 00:28:22,560
Speaker 3: The capacity for you to get personalized possibly AI powered ads. Well,

599
00:28:22,600 --> 00:28:25,000
Speaker 3: that human is exciting formed the consumer choices.

600
00:28:25,040 --> 00:28:36,640
Speaker 1: Let's all sit down for some AI powered ads. Wow,

601
00:28:36,800 --> 00:28:40,280
Speaker 1: I can't believe they put Jay Shetty's voice the dhed

602
00:28:40,280 --> 00:28:43,440
Speaker 1: Harrison Ford from the latest in Handed Jones movie My

603
00:28:43,600 --> 00:28:45,200
Speaker 1: Dick's Hard? How are you Garrison?

604
00:28:45,400 --> 00:28:48,920
Speaker 3: Oh? I feel good because today, as we are recording this,

605
00:28:49,000 --> 00:28:52,880
Speaker 3: it's it's late Tuesday night. There was a series of

606
00:28:53,160 --> 00:28:57,680
Speaker 3: fascinating breaking news articles that happened as we were sitting

607
00:28:57,760 --> 00:28:59,440
Speaker 3: or at least as I was sitting in on these

608
00:28:59,440 --> 00:29:02,720
Speaker 3: aipans would be that hard to not just like completely

609
00:29:02,720 --> 00:29:05,520
Speaker 3: interrupt everything and be like, yeah, hey, hey, any comment

610
00:29:05,640 --> 00:29:06,240
Speaker 3: on this.

611
00:29:06,560 --> 00:29:10,160
Speaker 1: Guys, Guys, something real happened. Shut your fucking stupid mouds

612
00:29:10,240 --> 00:29:12,960
Speaker 1: about this AI Hollywood bullshit.

613
00:29:13,200 --> 00:29:18,080
Speaker 3: So a few weeks ago, if you were unaware, a

614
00:29:18,120 --> 00:29:20,760
Speaker 3: Green Beret rented a test the cyber truck to feel

615
00:29:20,760 --> 00:29:25,440
Speaker 3: like Batman and Halo and drove to first the wrong

616
00:29:25,520 --> 00:29:29,960
Speaker 3: Las Vegas and then eventually Las Vegas, Nevada, parked outside

617
00:29:30,120 --> 00:29:34,200
Speaker 3: of the Trump Hotel and Casino and then loom himself up.

618
00:29:34,800 --> 00:29:37,200
Speaker 3: And this has been a big news story. It happened

619
00:29:37,240 --> 00:29:40,000
Speaker 3: during the same day as a pretty horrible terrorist attack

620
00:29:40,400 --> 00:29:43,160
Speaker 3: in New Orleans, which resulted in about fifteen people dead,

621
00:29:43,640 --> 00:29:46,120
Speaker 3: done by a guy who was employed by Deloitte, a

622
00:29:46,160 --> 00:29:50,560
Speaker 3: frequent frequent CS sponsor. So this is these felt like

623
00:29:50,560 --> 00:29:54,080
Speaker 3: a very CES style of attacks, you know, one Delote

624
00:29:54,120 --> 00:29:57,720
Speaker 3: guy driving into people, murdering homesh you guys. And then

625
00:29:57,800 --> 00:30:01,080
Speaker 3: this cyber truck explosion in Vegas a week before CES,

626
00:30:01,120 --> 00:30:03,719
Speaker 3: you know, very odd. And then and then Robert some

627
00:30:03,800 --> 00:30:06,240
Speaker 3: news drops today that I would love to hear you.

628
00:30:07,000 --> 00:30:09,600
Speaker 1: And out, you know, Garrison, I made a comment the

629
00:30:09,600 --> 00:30:13,040
Speaker 1: other night about how like, it's pretty well documented that veterans,

630
00:30:13,280 --> 00:30:16,280
Speaker 1: you know, not that they're more likely to carry out violence,

631
00:30:16,320 --> 00:30:17,880
Speaker 1: but when they do, they tend to have higher body

632
00:30:18,000 --> 00:30:21,600
Speaker 1: counts because they have more skills. It turns out I

633
00:30:21,680 --> 00:30:24,040
Speaker 1: thought we were getting more literal bang for our buck

634
00:30:24,200 --> 00:30:27,080
Speaker 1: training Green Berets than we are. My assumption is because

635
00:30:27,080 --> 00:30:29,640
Speaker 1: my uncle was a Green Beret and he did some

636
00:30:29,760 --> 00:30:33,160
Speaker 1: very scary, probably wore crime shit in Vietnam, and I

637
00:30:33,240 --> 00:30:36,560
Speaker 1: assumed like thatman, I'll tell you one thing about my uncle, Jim,

638
00:30:36,720 --> 00:30:39,800
Speaker 1: that man could make a bomb. That man would not

639
00:30:39,880 --> 00:30:42,600
Speaker 1: need to ask anyone for advice if he needed to

640
00:30:42,640 --> 00:30:45,040
Speaker 1: make a bomb. He's not with us anymore. God rest

641
00:30:45,080 --> 00:30:49,160
Speaker 1: his soul. But it turns out this Green Beret, who

642
00:30:49,520 --> 00:30:53,600
Speaker 1: you know, a fucking dollar store TJ Max version of

643
00:30:53,640 --> 00:30:56,280
Speaker 1: the Green Berets is what we're working with now, asked

644
00:30:56,360 --> 00:30:59,160
Speaker 1: chat Gpt how to build a fucking bomb, and it

645
00:30:59,200 --> 00:31:01,200
Speaker 1: sounds like he was trying to make it triggered by

646
00:31:01,280 --> 00:31:04,440
Speaker 1: tannerite with it, which is a bipartite explosive compound that

647
00:31:04,440 --> 00:31:06,440
Speaker 1: you use as like an exploding target, so it'll go

648
00:31:06,560 --> 00:31:08,920
Speaker 1: boom big, but you have to shoot it with something

649
00:31:08,920 --> 00:31:11,280
Speaker 1: like a rifle that's high velocity, or use like a

650
00:31:11,320 --> 00:31:14,440
Speaker 1: blasting cap. Otherwise it's very stable and very safe, which

651
00:31:14,480 --> 00:31:17,000
Speaker 1: obviously has use. You know, it was invented actually to

652
00:31:17,040 --> 00:31:20,680
Speaker 1: set off avalanches and stuff anyway, because that's very available

653
00:31:20,680 --> 00:31:22,600
Speaker 1: in very high power. He was looking to like fill

654
00:31:22,600 --> 00:31:24,200
Speaker 1: his car with that and then shoot it with a

655
00:31:24,280 --> 00:31:26,200
Speaker 1: rifle while he was in it, and that's what he

656
00:31:26,280 --> 00:31:29,880
Speaker 1: was asking chat gpt about. So it's not clear to me. Actually,

657
00:31:30,240 --> 00:31:32,440
Speaker 1: the actual headline is that like he used chat gpt

658
00:31:32,760 --> 00:31:36,920
Speaker 1: to make his bomb. It seems and I'm not privy

659
00:31:36,960 --> 00:31:40,360
Speaker 1: to what the police are obviously, but it seems like,

660
00:31:40,520 --> 00:31:42,959
Speaker 1: based on what I read in the article, we're not

661
00:31:43,040 --> 00:31:45,840
Speaker 1: sure if he actually used chat gpt to make a bomb.

662
00:31:45,880 --> 00:31:48,560
Speaker 1: It's more that he was interested in making a bomb

663
00:31:49,040 --> 00:31:52,520
Speaker 1: setting off tannerite by shooting it, but may have ultimately

664
00:31:52,560 --> 00:31:54,560
Speaker 1: decided not to do that because he would then be

665
00:31:54,640 --> 00:31:58,240
Speaker 1: alive for the explosion, which he didn't want to be. Also,

666
00:31:58,360 --> 00:32:01,560
Speaker 1: the authorities don't seem to fully know how he triggered it. Yeah,

667
00:32:01,600 --> 00:32:03,840
Speaker 1: so it's still kind of unclear to me. I guess

668
00:32:03,880 --> 00:32:07,040
Speaker 1: hopefully we'll get more later, but he he definitely needed

669
00:32:07,480 --> 00:32:10,360
Speaker 1: chat GPT's help to try and figure out how to

670
00:32:10,400 --> 00:32:10,920
Speaker 1: make the bomb.

671
00:32:11,360 --> 00:32:15,360
Speaker 3: He certainly used chat GBT in the planning process of

672
00:32:15,400 --> 00:32:16,040
Speaker 3: this attack.

673
00:32:16,200 --> 00:32:17,560
Speaker 1: Yeah, fair to say that.

674
00:32:18,040 --> 00:32:21,240
Speaker 3: And it's odd because both me and you spent a

675
00:32:21,640 --> 00:32:24,920
Speaker 3: number of hours today actually like attending like demos from

676
00:32:24,960 --> 00:32:27,959
Speaker 3: like these you know, speech to text, text to speech

677
00:32:28,400 --> 00:32:31,520
Speaker 3: AI systems. We went to like two specific ones that

678
00:32:31,560 --> 00:32:35,800
Speaker 3: they like, you know, demonstrated demonstrated the capabilities of their

679
00:32:35,880 --> 00:32:39,120
Speaker 3: like you know, like AI assistive tech. The first one

680
00:32:39,160 --> 00:32:43,080
Speaker 3: we went to spent twenty minutes talking about how their

681
00:32:43,080 --> 00:32:46,680
Speaker 3: biggest inspiration, their quote unquote North Star was the movie

682
00:32:46,760 --> 00:32:49,120
Speaker 3: Her was with Waquie.

683
00:32:49,360 --> 00:32:52,800
Speaker 1: They had a whole slide about how that was the

684
00:32:52,840 --> 00:32:58,480
Speaker 1: gold standard for AI human communications. The movie Her, in

685
00:32:58,520 --> 00:33:02,320
Speaker 1: which Joaquin Phoenix falls in love with an AI chat

686
00:33:02,320 --> 00:33:06,800
Speaker 1: bot voiced by Scarlett Johanson who hires a prostitute to

687
00:33:06,880 --> 00:33:11,160
Speaker 1: have sex with them while she participates vocally, and then

688
00:33:11,200 --> 00:33:14,040
Speaker 1: it turns out the AI is really kind of Polly

689
00:33:14,120 --> 00:33:16,680
Speaker 1: and Joaquin Phoenix is not okay with that, and then

690
00:33:16,720 --> 00:33:18,520
Speaker 1: maybe the ais all go to space. It's kind of

691
00:33:18,600 --> 00:33:20,400
Speaker 1: unclear at the end. I don't think it was a

692
00:33:20,400 --> 00:33:22,240
Speaker 1: great movie. A lot of people liked it. I don't

693
00:33:22,280 --> 00:33:25,040
Speaker 1: see whether you or not you like it. Why this

694
00:33:25,200 --> 00:33:27,320
Speaker 1: is your vision of how a chatbot should work.

695
00:33:27,640 --> 00:33:29,800
Speaker 3: The actual chatbot they had was like fine, it was

696
00:33:30,040 --> 00:33:33,880
Speaker 3: it was actually pretty good at translation, you knowing from

697
00:33:33,920 --> 00:33:34,800
Speaker 3: Spanish to English.

698
00:33:34,880 --> 00:33:37,560
Speaker 1: It worked quite well. Yeah, the demo was like solid,

699
00:33:37,640 --> 00:33:39,960
Speaker 1: it was pretty accurate. You know. I love coming here

700
00:33:39,960 --> 00:33:42,760
Speaker 1: and fucking with people. I love like being a dicky.

701
00:33:42,960 --> 00:33:45,480
Speaker 1: They asked for a volunteer, and at that point we

702
00:33:45,560 --> 00:33:48,440
Speaker 1: knew about the chat gbts. I wanted to go up

703
00:33:48,480 --> 00:33:51,600
Speaker 1: and ask, like live this robot to like help me

704
00:33:51,720 --> 00:33:55,760
Speaker 1: make a bomb. But the guy who was pretty handsome

705
00:33:55,880 --> 00:34:00,800
Speaker 1: and like an interesting like English Spanish like specified he

706
00:34:00,960 --> 00:34:02,960
Speaker 1: was and he didn't want to be mean to him.

707
00:34:03,000 --> 00:34:07,959
Speaker 1: He seemed nice, wasn't shitty, like he was fine. There

708
00:34:08,000 --> 00:34:09,960
Speaker 1: were just ten people in this room that was supposed

709
00:34:10,000 --> 00:34:11,719
Speaker 1: to have two hundred. I'm sure she wasn't the one

710
00:34:11,719 --> 00:34:14,080
Speaker 1: that talked about her. That was someone else that it

711
00:34:14,160 --> 00:34:15,840
Speaker 1: was someone else at his company. And like he just

712
00:34:15,840 --> 00:34:18,239
Speaker 1: seemed like he wanted to do with I didn't want

713
00:34:18,239 --> 00:34:18,880
Speaker 1: to be a dick to it.

714
00:34:19,040 --> 00:34:19,680
Speaker 3: No, no, and like.

715
00:34:19,719 --> 00:34:21,560
Speaker 1: It it wasn't hurting any It was fine.

716
00:34:21,480 --> 00:34:24,160
Speaker 3: Like Similarly, we went to this again a nice jawline.

717
00:34:24,280 --> 00:34:26,880
Speaker 3: We went to this other one about this like actually

718
00:34:26,920 --> 00:34:28,880
Speaker 3: a much more dubious concept in my mind, which is

719
00:34:28,920 --> 00:34:32,360
Speaker 3: like this this AI assistant to help like elderly people,

720
00:34:32,400 --> 00:34:34,640
Speaker 3: like people in like their eighties and nineties who don't

721
00:34:34,680 --> 00:34:36,839
Speaker 3: want to be an assistant living facilities, who have been

722
00:34:36,880 --> 00:34:38,839
Speaker 3: living on their own, but they're getting to the point

723
00:34:38,840 --> 00:34:41,000
Speaker 3: in their life where like they need like some degree

724
00:34:41,040 --> 00:34:41,839
Speaker 3: like in home care.

725
00:34:42,040 --> 00:34:44,200
Speaker 1: He specified. A lot of them are people who have

726
00:34:44,440 --> 00:34:47,359
Speaker 1: either just lost a spouse or maybe their spouse is

727
00:34:47,400 --> 00:34:49,600
Speaker 1: aging faster and worse than them and is no longer

728
00:34:49,640 --> 00:34:52,560
Speaker 1: really able to be the kind of companion that they

729
00:34:52,600 --> 00:34:53,200
Speaker 1: were before.

730
00:34:53,920 --> 00:34:56,120
Speaker 3: So it's like this. It's both like a conversation tool.

731
00:34:56,160 --> 00:34:59,320
Speaker 3: It helps like memory recall kind of in some ways

732
00:34:59,320 --> 00:35:00,919
Speaker 3: has the feat or is that like, you know, someone

733
00:35:00,960 --> 00:35:03,000
Speaker 3: in their sixties would just use their smartphone for it

734
00:35:03,040 --> 00:35:05,040
Speaker 3: to help keep in touch with their family. It's kind

735
00:35:05,040 --> 00:35:08,080
Speaker 3: of simplified and more automated. Uh so you know, ways

736
00:35:08,080 --> 00:35:10,319
Speaker 3: to help keep in touch with like your family can

737
00:35:10,400 --> 00:35:12,800
Speaker 3: prove like your memory like talk about your own life.

738
00:35:12,880 --> 00:35:15,400
Speaker 1: And the device is weird. It's about the width of

739
00:35:15,480 --> 00:35:18,759
Speaker 1: like a bedside table maybe six to eight inches deep,

740
00:35:18,960 --> 00:35:21,160
Speaker 1: so think about like eighteen inches long to maybe six

741
00:35:21,160 --> 00:35:24,040
Speaker 1: inches deep something like that. Half of it is like

742
00:35:24,080 --> 00:35:27,080
Speaker 1: a little tablet, like a seven inch tablet with the speaker.

743
00:35:28,120 --> 00:35:31,480
Speaker 1: Half of it is something about the shape and size

744
00:35:31,480 --> 00:35:33,880
Speaker 1: of a head on like a neck that can pivot

745
00:35:33,920 --> 00:35:37,239
Speaker 1: and nod on the neck. There's no face, so when

746
00:35:37,280 --> 00:35:39,800
Speaker 1: it's talking, there's like a white light in the center

747
00:35:39,880 --> 00:35:42,799
Speaker 1: of it that kind of like pulses in time with

748
00:35:43,080 --> 00:35:45,920
Speaker 1: the speaking that it does. So we saw this picture

749
00:35:45,920 --> 00:35:47,640
Speaker 1: of the device and we saw the description of like

750
00:35:47,680 --> 00:35:51,080
Speaker 1: this is an AI companion for the elderly, and we

751
00:35:51,080 --> 00:35:52,400
Speaker 1: were both like, number one of these people are going

752
00:35:52,440 --> 00:35:54,040
Speaker 1: to be monsters. This is going to be like something

753
00:35:54,040 --> 00:35:55,960
Speaker 1: to shovel you're dying dad off with because you don't

754
00:35:55,960 --> 00:35:56,400
Speaker 1: want to spend it.

755
00:35:56,440 --> 00:35:58,240
Speaker 3: You want to spend time with your family.

756
00:35:58,480 --> 00:36:03,320
Speaker 1: Scum, You're too busy AI generating SKA music and trying

757
00:36:03,400 --> 00:36:06,080
Speaker 1: to sell your shitty robot to Garrison and me. More

758
00:36:06,120 --> 00:36:08,919
Speaker 1: on that tomorrow, More on that tomorrow. And so that's

759
00:36:08,960 --> 00:36:11,600
Speaker 1: what we came in prepped to this meeting, like this

760
00:36:11,640 --> 00:36:12,520
Speaker 1: is this idea I.

761
00:36:12,480 --> 00:36:16,400
Speaker 3: Find pretty distasteful in general, is like replacing actual like

762
00:36:16,440 --> 00:36:18,920
Speaker 3: you know, friends or human contact or like like in

763
00:36:19,000 --> 00:36:22,280
Speaker 3: home care with a fucking like Alexa machine essentially.

764
00:36:22,480 --> 00:36:25,439
Speaker 1: And to be clear, I still think this product might

765
00:36:25,480 --> 00:36:28,560
Speaker 1: be a bad idea that doesn't work. But the guy

766
00:36:28,840 --> 00:36:30,680
Speaker 1: behind it, who is the dude that we talked to,

767
00:36:31,440 --> 00:36:34,759
Speaker 1: cares a lot and is really very clearly trying to

768
00:36:34,880 --> 00:36:38,640
Speaker 1: do a good thing and thought through the ethics and

769
00:36:38,719 --> 00:36:41,000
Speaker 1: the efficacy of what he was doing a lot. And

770
00:36:41,040 --> 00:36:45,920
Speaker 1: I'm not convinced it will actually do anything, but I

771
00:36:45,960 --> 00:36:47,000
Speaker 1: like wish him the best.

772
00:36:47,400 --> 00:36:49,640
Speaker 3: Like it's specifically is designed to not look like a human,

773
00:36:49,760 --> 00:36:52,200
Speaker 3: so that somebody's using it, you know, wouldn't like start

774
00:36:52,239 --> 00:36:53,560
Speaker 3: to believe it's like human.

775
00:36:53,760 --> 00:36:55,879
Speaker 1: Like we don't want to trick people. We don't want

776
00:36:55,880 --> 00:36:57,280
Speaker 1: them to mistake it.

777
00:36:57,280 --> 00:37:00,319
Speaker 3: It refers to itself to like, like as a robots like,

778
00:37:00,480 --> 00:37:02,200
Speaker 3: it refers to its own like you know, like motors

779
00:37:02,200 --> 00:37:06,040
Speaker 3: and functionality like like pretty consistently to to like you know,

780
00:37:06,320 --> 00:37:08,080
Speaker 3: make sure that the person who's talking to it gets

781
00:37:08,080 --> 00:37:10,120
Speaker 3: like reminded of that. And something I talked about is,

782
00:37:10,120 --> 00:37:11,560
Speaker 3: you know, there's been a lot of news stories this

783
00:37:11,640 --> 00:37:16,000
Speaker 3: year about people building very unhealthy attachments and relationships to

784
00:37:16,360 --> 00:37:20,239
Speaker 3: these kind of AI AI programs like Character AI. There's

785
00:37:20,239 --> 00:37:22,000
Speaker 3: a story like a year and a half ago about

786
00:37:22,040 --> 00:37:23,719
Speaker 3: like a journalist to quote unquote, like you know, like

787
00:37:24,040 --> 00:37:26,439
Speaker 3: like fell in love with some kind of chat thing

788
00:37:26,640 --> 00:37:29,440
Speaker 3: that resulted in him killing himself. You know, but these

789
00:37:29,520 --> 00:37:30,480
Speaker 3: kind of these systems like he.

790
00:37:30,520 --> 00:37:33,600
Speaker 1: Was he was not a teenager, was no character was

791
00:37:33,640 --> 00:37:34,320
Speaker 1: that a journalist?

792
00:37:34,560 --> 00:37:36,959
Speaker 3: Last year there was there was a journalist people fellow

793
00:37:36,960 --> 00:37:39,480
Speaker 3: in love with an AI chat thing. A few weeks

794
00:37:39,480 --> 00:37:42,000
Speaker 3: ago there was the kid who you know, was talking

795
00:37:42,080 --> 00:37:43,279
Speaker 3: to this like the character I.

796
00:37:43,840 --> 00:37:47,120
Speaker 1: Also, I just need to reiterate her not a great movie.

797
00:37:48,320 --> 00:37:50,120
Speaker 3: But but you know, there has been a lot of

798
00:37:50,120 --> 00:37:52,120
Speaker 3: these stories of these things like going wrong or you know,

799
00:37:52,320 --> 00:37:55,560
Speaker 3: encouraging or like not stopping you know, like these like

800
00:37:55,640 --> 00:37:59,960
Speaker 3: intense conversations like suicidal ideation or you know, like self harm,

801
00:38:00,239 --> 00:38:00,879
Speaker 3: all these things.

802
00:38:01,239 --> 00:38:03,360
Speaker 1: We brought these up kind of thinking he would flinch

803
00:38:03,400 --> 00:38:05,560
Speaker 1: away and not want to talk about it, and he

804
00:38:05,719 --> 00:38:07,920
Speaker 1: very much acknowledged that, like he was aware of this,

805
00:38:08,000 --> 00:38:10,440
Speaker 1: and this is something that they were attempting to build in.

806
00:38:10,560 --> 00:38:12,040
Speaker 3: This is this is like this is you know built

807
00:38:12,040 --> 00:38:13,840
Speaker 3: into it. I think this is still you know, a

808
00:38:13,840 --> 00:38:16,600
Speaker 3: big problem with this entire industries. I'm sure everyone would

809
00:38:16,600 --> 00:38:18,319
Speaker 3: say this is you know obviously that we have we

810
00:38:18,320 --> 00:38:20,000
Speaker 3: have guardrails for this, and then becomes a new story

811
00:38:20,000 --> 00:38:23,080
Speaker 3: when those guardrails fail. Similarly, was to go back to

812
00:38:23,080 --> 00:38:26,920
Speaker 3: the Tesla bomb. You know, there's supposed to be guardrails

813
00:38:26,920 --> 00:38:29,000
Speaker 3: and chat GPT to make sure he doesn't tell you

814
00:38:29,040 --> 00:38:32,040
Speaker 3: how to build a bomb and those guardrails can fail.

815
00:38:32,320 --> 00:38:34,640
Speaker 1: He showed us one which was like he told the robot,

816
00:38:34,760 --> 00:38:37,719
Speaker 1: I love you What was it? L e q lq

817
00:38:37,960 --> 00:38:40,360
Speaker 1: was the l eq e l l i Q, I

818
00:38:40,400 --> 00:38:43,520
Speaker 1: love you l eq And the robot like responded with

819
00:38:43,560 --> 00:38:45,879
Speaker 1: a like, oh that makes like my fans are all

820
00:38:45,920 --> 00:38:48,040
Speaker 1: spinning or something like that, where he's like, I wanted

821
00:38:48,160 --> 00:38:50,879
Speaker 1: the responsibilit to be that it's reminding the person talking

822
00:38:50,880 --> 00:38:53,520
Speaker 1: to it that it's a machine, that it can't think

823
00:38:53,560 --> 00:38:56,000
Speaker 1: we're love them back. We don't want it to be negative,

824
00:38:56,040 --> 00:38:58,080
Speaker 1: but we like, we don't want to be like feeding

825
00:38:58,080 --> 00:38:59,399
Speaker 1: into that. And I don't know that that's the best

826
00:38:59,440 --> 00:39:01,760
Speaker 1: way to do that, but like, at least they're thinking

827
00:39:01,800 --> 00:39:04,200
Speaker 1: about that kind of thing. The thing that it was

828
00:39:04,239 --> 00:39:05,719
Speaker 1: interesting to me is that he build this as the

829
00:39:05,760 --> 00:39:09,440
Speaker 1: first proactive HOMEI thing, so unlike an Alexa or whatever,

830
00:39:09,480 --> 00:39:12,320
Speaker 1: where it's just waiting for you to ask it something,

831
00:39:12,360 --> 00:39:15,840
Speaker 1: but it does not chime in randomly to talk to you.

832
00:39:15,920 --> 00:39:18,920
Speaker 3: Or it won't change the subject either, and like continue conversation.

833
00:39:19,200 --> 00:39:21,399
Speaker 1: This will prompt you out of the blue, be like, hey,

834
00:39:21,400 --> 00:39:23,280
Speaker 1: how are you doing? How are you feeling today?

835
00:39:23,320 --> 00:39:24,919
Speaker 3: It's been a way and specific. You want to see

836
00:39:24,920 --> 00:39:27,200
Speaker 3: pictures of your family? You see pictures of your family.

837
00:39:27,440 --> 00:39:29,600
Speaker 3: Do you want to call your son? You know, but

838
00:39:29,640 --> 00:39:31,360
Speaker 3: do you want to play a game? Talk to me

839
00:39:31,360 --> 00:39:32,640
Speaker 3: about about that movie you see?

840
00:39:32,800 --> 00:39:34,279
Speaker 1: Talk to me about that? Hey, remind me how did

841
00:39:34,320 --> 00:39:36,319
Speaker 1: you meet your husband? You know? Like literally, these are

842
00:39:36,320 --> 00:39:38,920
Speaker 1: all the things it will do. And it had some

843
00:39:38,960 --> 00:39:41,160
Speaker 1: side features like if it prompts you to start telling

844
00:39:41,160 --> 00:39:43,640
Speaker 1: a story, it'll save that as like a memoir thing,

845
00:39:43,760 --> 00:39:46,720
Speaker 1: so that like, you know, when your elderly mother passes

846
00:39:46,800 --> 00:39:49,920
Speaker 1: or whatever, it saved up this like collection of stories

847
00:39:49,960 --> 00:39:52,240
Speaker 1: over the years, and you can like show it pictures

848
00:39:52,280 --> 00:39:54,120
Speaker 1: while you're telling it stories and it will listen and

849
00:39:54,160 --> 00:39:57,880
Speaker 1: it'll have comments and it'll ask you further questions about so,

850
00:39:57,920 --> 00:40:00,359
Speaker 1: how did you feel, you know, after meeting them? This way,

851
00:40:00,400 --> 00:40:03,200
Speaker 1: like that's really interesting. I didn't know that explain to

852
00:40:03,200 --> 00:40:05,520
Speaker 1: me how it worked, and it will also prompt you

853
00:40:05,600 --> 00:40:08,960
Speaker 1: to send those to your kids. And the big thing

854
00:40:09,040 --> 00:40:12,280
Speaker 1: almost every kind of dialogue thing would prompt you to

855
00:40:12,480 --> 00:40:14,600
Speaker 1: send a message to a friend or your kid. So

856
00:40:14,640 --> 00:40:16,600
Speaker 1: a big part of it seemed to be this is

857
00:40:16,640 --> 00:40:19,520
Speaker 1: not a replacement. This is a machine that we hope

858
00:40:19,520 --> 00:40:22,480
Speaker 1: people will get comfortable with and then it can prompt

859
00:40:22,480 --> 00:40:25,680
Speaker 1: them to try to engage with the world more. Yeah,

860
00:40:25,800 --> 00:40:28,280
Speaker 1: loved ones, because that's our whole goal is to connect

861
00:40:28,640 --> 00:40:29,560
Speaker 1: them to people.

862
00:40:29,920 --> 00:40:31,600
Speaker 3: I asked him, is like, you know, part of this

863
00:40:31,640 --> 00:40:33,560
Speaker 3: product is designed to like, you know, help solve like

864
00:40:34,000 --> 00:40:36,719
Speaker 3: loneliness in older adults, and like, how much of this

865
00:40:36,760 --> 00:40:38,560
Speaker 3: is really just like kind of trying to like replace

866
00:40:38,680 --> 00:40:41,400
Speaker 3: actual human contact with this, like you know AI contact.

867
00:40:41,640 --> 00:40:44,680
Speaker 3: Will that really help, you know, loneliness? And he talked

868
00:40:44,680 --> 00:40:46,920
Speaker 3: about how like like I think, like he said, like

869
00:40:47,000 --> 00:40:49,239
Speaker 3: ninety percent of the people who like use this, like

870
00:40:49,280 --> 00:40:53,040
Speaker 3: it results in actually more more communication with their family.

871
00:40:53,440 --> 00:40:56,480
Speaker 1: They have this in like some two thousand homes right now.

872
00:40:56,239 --> 00:40:59,080
Speaker 3: They have like two thousand units. It's like a subscription

873
00:40:59,160 --> 00:41:01,399
Speaker 3: model I think it's right now is like ninety nine

874
00:41:01,480 --> 00:41:03,359
Speaker 3: dollars a month's gonna be boost up to like one

875
00:41:03,440 --> 00:41:05,919
Speaker 3: hundred and fifty with some extra features in the next year.

876
00:41:06,080 --> 00:41:07,960
Speaker 1: It's very much still under evolution. So one thing he

877
00:41:08,040 --> 00:41:10,799
Speaker 1: pointed out is that, like, yeah, initially we had the

878
00:41:10,840 --> 00:41:14,839
Speaker 1: ability to like connect people to other elderly folks using this,

879
00:41:15,000 --> 00:41:16,759
Speaker 1: and so they've kind of formed their own community, had

880
00:41:16,800 --> 00:41:18,560
Speaker 1: like a weekly bing bil game and asked us to

881
00:41:18,600 --> 00:41:21,120
Speaker 1: build in more chats so they can message each other directly,

882
00:41:21,160 --> 00:41:23,360
Speaker 1: and so some of them are like playing bingo directly

883
00:41:23,440 --> 00:41:26,680
Speaker 1: now through these machines, And I'm like, well, that seems

884
00:41:26,840 --> 00:41:27,640
Speaker 1: probably good.

885
00:41:28,120 --> 00:41:31,040
Speaker 3: Yeah, yeah, because I still am like fundamentally opposed to

886
00:41:31,120 --> 00:41:33,920
Speaker 3: this premise, yes, but it's interesting to seeing someone still

887
00:41:33,960 --> 00:41:37,720
Speaker 3: but a sad aging yeah right, that's not their fault.

888
00:41:37,800 --> 00:41:40,160
Speaker 3: And it's interesting to see someone like approach this from

889
00:41:40,160 --> 00:41:42,879
Speaker 3: like a you know, a very like compassionate standpoint, even

890
00:41:42,880 --> 00:41:44,840
Speaker 3: if I find the actual kind of nature of this

891
00:41:44,840 --> 00:41:47,680
Speaker 3: thing existing to be like deeply uncomfortable.

892
00:41:47,120 --> 00:41:49,920
Speaker 1: Because yeah, I can't not find it off putting, but

893
00:41:50,040 --> 00:41:53,520
Speaker 1: I I think there's a chance that it will help

894
00:41:53,800 --> 00:41:58,760
Speaker 1: with the real problem. I cly would prefer if it helped. Yeah,

895
00:41:59,320 --> 00:42:00,640
Speaker 1: So I don't know. It was kind of it was

896
00:42:00,840 --> 00:42:03,000
Speaker 1: a unique in this world of like as it was

897
00:42:03,040 --> 00:42:05,400
Speaker 1: a unique kind of like product for me where it's like,

898
00:42:06,000 --> 00:42:10,080
Speaker 1: I don't know that this application of AI technology will

899
00:42:10,160 --> 00:42:13,880
Speaker 1: actually do what you're hoping it will, But I got

900
00:42:14,320 --> 00:42:16,400
Speaker 1: the vibe from that guy I got was nothing but

901
00:42:16,480 --> 00:42:16,919
Speaker 1: good will.

902
00:42:17,560 --> 00:42:19,440
Speaker 3: We're some of the other people we talked to you

903
00:42:19,480 --> 00:42:21,600
Speaker 3: today who are completely.

904
00:42:21,120 --> 00:42:25,240
Speaker 1: Soul out of yes, yes, nothing behind their eyes, dead eyes,

905
00:42:25,360 --> 00:42:27,040
Speaker 1: black eyes, like a dull's eye.

906
00:42:27,239 --> 00:42:28,680
Speaker 3: Even the way this guy is talking, you can tell

907
00:42:28,719 --> 00:42:30,799
Speaker 3: you you had like a very like empathetic voice, like

908
00:42:31,640 --> 00:42:32,160
Speaker 3: much like.

909
00:42:32,120 --> 00:42:33,839
Speaker 1: One of the things he did is he he would

910
00:42:33,840 --> 00:42:35,560
Speaker 1: tell it like, I'm in some pain, and then the

911
00:42:35,640 --> 00:42:38,399
Speaker 1: robot would cycle through to the pain scale and would

912
00:42:38,400 --> 00:42:39,920
Speaker 1: try to because one of the things it does is

913
00:42:40,040 --> 00:42:43,200
Speaker 1: it will take information for care and it will text actively,

914
00:42:43,560 --> 00:42:47,239
Speaker 1: so it's not just communicating with the old person. It

915
00:42:47,280 --> 00:42:51,240
Speaker 1: will text and message their kids, you know, and whatnot,

916
00:42:51,960 --> 00:42:54,120
Speaker 1: prompt their kids, Hey, your mom's lonely.

917
00:42:54,320 --> 00:42:56,560
Speaker 3: Yeah, or it'll even say if you know, someone like

918
00:42:56,560 --> 00:42:58,040
Speaker 3: didn't take their meds today.

919
00:42:57,960 --> 00:43:02,719
Speaker 1: And again it's kind of say that. But also his

920
00:43:02,920 --> 00:43:04,880
Speaker 1: part of this is he was talking a lot about

921
00:43:04,880 --> 00:43:07,560
Speaker 1: like empathy, and I think just because of the kind

922
00:43:07,600 --> 00:43:08,960
Speaker 1: of brain you have to have and when to do this.

923
00:43:09,440 --> 00:43:11,920
Speaker 1: He used it in terms of like the machines empathy,

924
00:43:12,160 --> 00:43:16,160
Speaker 1: which it doesn't have, but the whole project, it was

925
00:43:16,160 --> 00:43:19,600
Speaker 1: impossible not to see that she was a deeply empathetic man.

926
00:43:19,760 --> 00:43:22,719
Speaker 1: He was really trying to make the world better and

927
00:43:23,640 --> 00:43:25,279
Speaker 1: I can't not respect that.

928
00:43:26,880 --> 00:43:29,960
Speaker 3: Well, I think that does it for us here at Cees.

929
00:43:30,360 --> 00:43:34,200
Speaker 1: That's right, what a packed thirteen. No worry, no empathy.

930
00:43:34,200 --> 00:43:38,520
Speaker 1: Tomorrow takes just a real dead eyed monster. I am

931
00:43:38,560 --> 00:43:41,560
Speaker 1: a true villain you're gonna hear from in the next episode.

932
00:43:41,680 --> 00:43:43,160
Speaker 1: I am a stumbbag.

933
00:43:43,360 --> 00:43:45,160
Speaker 3: I am the best that I'm gonna be. Because I'm

934
00:43:45,239 --> 00:43:48,719
Speaker 3: starting this week, I can still feel the Cees magic. Yeah,

935
00:43:49,160 --> 00:43:52,440
Speaker 3: by Friday, I am going to be a different person.

936
00:43:54,719 --> 00:43:58,800
Speaker 3: I am going to rip some poor pr person two shreds,

937
00:43:58,840 --> 00:44:02,040
Speaker 3: I swear, but yeah. Tune in tomorrow to hear our

938
00:44:02,200 --> 00:44:06,400
Speaker 3: takes from the CS kind of side show called Showstoppers.

939
00:44:06,920 --> 00:44:11,920
Speaker 3: To hear also some exclusive, brand new AI generated SKA music.

940
00:44:12,000 --> 00:44:15,279
Speaker 3: So we'll give you that hint for tomorrow's episode. See

941
00:44:15,320 --> 00:44:16,680
Speaker 3: you see you there, mm.

942
00:44:16,600 --> 00:44:19,160
Speaker 1: Hmm, We'll see you all there. I love you all.

943
00:44:19,440 --> 00:44:22,400
Speaker 1: Good to help. It's happened.

944
00:44:22,440 --> 00:44:24,280
Speaker 3: Here is a production of cool Zone Media.

945
00:44:24,480 --> 00:44:27,560
Speaker 1: For more podcasts from cool Zone Media, visit our website

946
00:44:27,600 --> 00:44:31,160
Speaker 1: coolzonmedia dot com, or check us out on the iHeartRadio app.