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Speaker 1: Also media.

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Speaker 2: This is it could happen here a podcast about things

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Speaker 2: falling apart, and today the things falling apart are consumer

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Speaker 2: electronics as an industry. We are at CS twenty twenty six,

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Speaker 2: the trade show where the tech industry shows us everything

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Speaker 2: that's going to sell us in the next year. And

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Speaker 2: we've seen some cool stuff and a lot of bloat wear,

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Speaker 2: a lot of crap, a lot of AI enabled stuff

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Speaker 2: that doesn't need to be AI enabled. Here to talk

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Speaker 2: about it is our panel of experts.

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Speaker 3: Needs experts is a strong word, but okay.

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Speaker 2: Yeah, panel is a strong word. Is even a strong word.

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Speaker 2: I'm Robert Evans. Garrison Davis is also with me.

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Speaker 1: And I'm Ben rose Porter.

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Speaker 4: And you know, Ben, you're an academic, right you do

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Speaker 4: you do college?

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Speaker 1: Yeah?

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Speaker 4: Your college.

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Speaker 1: I'm a teach sociology.

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Speaker 4: That's right, that's right, as a sociopath. How a trade shift.

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Speaker 1: It's fascinating, love, I mean, you know, it's a fascinating

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Speaker 1: world sociologically. You can learn a lot of the maladies

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Speaker 1: of society at this place.

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Speaker 4: Yeah, it's most of them are on display here.

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Speaker 3: We are now going to walk you through a bunch

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Speaker 3: of the largely non AI products that we were able

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Speaker 3: to find after sorting through the gunk.

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Speaker 2: Yeah, it's kind of like like you know how people

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Speaker 2: like pan for gold. Yes, if instead of like panning

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Speaker 2: for gold and like a beautiful mountain stream, like you

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Speaker 2: were panning for gold and like a pile of used condoms.

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Speaker 5: Gold is also generous. This is panning for pennies in

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Speaker 5: a pile of used condoms.

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Speaker 2: Right right now? What was the best used condom you

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Speaker 2: saw it? Twenty twenty six, Garrison?

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Speaker 5: I think you mean, what's the best penny good products?

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Speaker 5: Did we see any good products? Yeah, there's some good ones.

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Speaker 5: Did I I don't know if I saw any good

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Speaker 5: products this year?

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Speaker 4: The translation stuff is still around, and some of it's really.

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Speaker 5: Cool now, I mean, yeah, we've in other episodes we've

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Speaker 5: talked about the glasses in the earbuds. Most of the

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Speaker 5: product sheets I have out now are at the very

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Speaker 5: least mixed if if if not, it's not bad. At

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Speaker 5: Eureka Park there was this product called Nodi which is

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Speaker 5: a smartphone replacement for for kids, like kids like six

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Speaker 5: to twelve if you don't want them having a smartphone,

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Speaker 5: and it allows them to send voice messages to a

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Speaker 5: parent and who like you know, has like this approoved

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Speaker 5: contact list, so you can you can also listen to music,

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Speaker 5: listen to like some like radio, like like you know, radio, dramas,

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Speaker 5: price and books.

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Speaker 3: It connects to Spotify.

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Speaker 5: You can learn languages allegedly, or you can you can

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Speaker 5: learn words, right, you can learn words from other languages,

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Speaker 5: and you can communicate with your parents. And this was

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Speaker 5: like fine, right, it's the stuff that we've kind of

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Speaker 5: seen before, but it was this little like you know,

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Speaker 5: silicon kind of looks like like a elf bar. If

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Speaker 5: you're familiar with an elf bar, it kind of looks

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Speaker 5: like that. And it's if yeah, if you don't want

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Speaker 5: to give your like, you know, six year old an iPhone,

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Speaker 5: but you know, want them to have a way to

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Speaker 5: contact you, right, And.

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Speaker 3: That's like fine, right. So there's there's a lot of

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Speaker 3: like basic stuff like that.

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Speaker 5: I guess that is like kind of okay, I don't

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Speaker 5: want to be cynical for the sake of being cynical.

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Speaker 3: That kind of stuff bores me.

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Speaker 5: But there really wasn't that many good products this year

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Speaker 5: because so many of them just wre lm rappers, as

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Speaker 5: we discussed in our previous episode.

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Speaker 2: And there's another there were products that were good and

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Speaker 2: I could tell we're good products on their own that

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Speaker 2: they had still thrown AI functionality that I don't want

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Speaker 2: that I know will blow itt the price and also

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Speaker 2: makes it me less want to buy it. LG was

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Speaker 2: advertising their new OLED television that has like the most

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Speaker 2: vibrant colors, the best OLED screen that's ever been on

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Speaker 2: a TV. I'm sure it looked fucking great. Yeah, video

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Speaker 2: of it. The colors, the darks are amazing, are really good.

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Speaker 2: But it's also with AI, with Evo AI, and to

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Speaker 2: show if it's vibrant colors and what's capable of they

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Speaker 2: had a loop of videos that were inspired by the

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Speaker 2: Hubbled Space Telescope and you can see it if if

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Speaker 2: you ever watched Deep Space nine. It's about the quality

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Speaker 2: of the Deep Space nine intro.

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Speaker 3: It does look very Star Trek intro.

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Speaker 2: Yeah, which is frustrating because again we have images show

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Speaker 2: the actual image show they look cool because you know

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Speaker 2: what they are is real, Like they're real products of

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Speaker 2: one of the most impressive things human beings ever made.

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Speaker 2: And you're bragging that, like we have an AI generating

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Speaker 2: images inspired by this thing that look worse.

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Speaker 3: Yeah, it's just a lot of those things that are

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Speaker 3: kind of mixed.

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Speaker 4: I wanted the TV I want.

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Speaker 2: I was like, Wow, I might like a TV like

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Speaker 2: that until you displayed that part of it, and now

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Speaker 2: I just kind of feel dirty about even the prospect

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Speaker 2: of wanting one of your products.

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Speaker 5: This is an interesting product I saw the like the

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Speaker 5: Innovation Awards showcases, is the Acoustic Eye, which is kind

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Speaker 5: of just off.

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Speaker 4: That's an ear.

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Speaker 3: That's an ear, Like, right, that's an ear. We don't

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Speaker 3: need to do that.

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Speaker 5: But this is a specifically a security system that tries

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Speaker 5: to detect very small drones. And this is like for

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Speaker 5: you know, high profile people's houses. Mostly you can put

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Speaker 5: that on your roof or your window and it'll detect

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Speaker 5: very small drones that cameras would not be able to detect.

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Speaker 5: So it's trying to like listen for drones. It provides

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Speaker 5: three hundred and sixty degree omnidirectional aerial surveillance, detecting invisible

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Speaker 5: aerial threats. So I would assume that they're trying to

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Speaker 5: excel these to like, you know, like executives, like CEOs, politicians,

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Speaker 5: people who are at risk of either you know, drones

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Speaker 5: filming around their house or more like kinetic drone based attacks, right,

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Speaker 5: and this is an interesting product that's like very current,

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Speaker 5: the very current product like this is this is a

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Speaker 5: reflection of some of the times that we're in. And yeah,

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Speaker 5: I found I found that to be one of an

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Speaker 5: interesting thing. I guess we should discuss the exoskeleton, which

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Speaker 5: is maybe, yes, the best part of the show for me.

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Speaker 2: Yes, there's a lot more exoskeletons this year. The technology

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Speaker 2: is clearly matured and mature to the point that not

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Speaker 2: only is it, do they have viable versions for like

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Speaker 2: industrial use for people working in factories and whatnot, right,

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Speaker 2: which two years ago is what they were always advertising

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Speaker 2: is that these are things that you buy at an

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Speaker 2: enterprise level. And I know they're not primarily concerned with

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Speaker 2: the health and well being of their workers, but actually

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Speaker 2: these do improve health and well being of workers.

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Speaker 3: Right.

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Speaker 2: It reduces the felt load and the felt strain, it

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Speaker 2: reduces the damaged knees and back, right.

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Speaker 3: And that does affect their productivity, right.

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Speaker 2: And it also affects a profit because you're not you're

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Speaker 2: less likely to have workmen's comp claims.

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Speaker 4: Right.

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Speaker 2: It's one of those it's one of those things where

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Speaker 2: it's a really good idea and the product's work. There's

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Speaker 2: a number of very good exoskeletons we received from a

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Speaker 2: company called hyper Shell, an exoskeleton before the convention this

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Speaker 2: year that you and I both wore on the floor.

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Speaker 2: I have some data on it, which is that I

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Speaker 2: timed my normal walking pace when I'm not particularly trying

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Speaker 2: to get anywhere about nineteen minutes a mile, right, if

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Speaker 2: I'm just kind of like walking casually. When I put

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Speaker 2: the Hypershell on and had it at seventy five percent

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Speaker 2: power mode, my walking pace was fifteen to sixteen minutes

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Speaker 2: a mile, about fifteen and a half, I think is

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Speaker 2: what I generally advertised. And my heart rate didn't change meaningfully.

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Speaker 2: It was like one or two higher than it normally.

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Speaker 2: Is not really a significant change and heart rate, right,

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Speaker 2: And I felt like at the end of the day,

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Speaker 2: my feet heard about a normal amount for a day

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Speaker 2: at Cees, but my lower back and my knees felt

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Speaker 2: less strained.

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Speaker 4: Right. That was my experience with hyper Shell.

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Speaker 5: It's like an external hip almost attatches around your waist.

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Speaker 2: Yeah, there's a belt around your hip and it goes

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Speaker 2: up to right above your knees. Is kind of the

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Speaker 2: and so it's not a huge footprint.

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Speaker 3: No, it's a very small device. And yeah, it goes,

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Speaker 3: it goes around your hip.

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Speaker 5: Then another strap like goes above your knee and it

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Speaker 5: kind of assists or guides your like leg and your

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Speaker 5: hip up and down.

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Speaker 4: Yeah.

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Speaker 2: And for the record, folks, the basic version of this

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Speaker 2: product is about a thousand dollars. The version we had

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Speaker 2: was about twenty one hundred dollars, right, and the battery

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Speaker 2: will last about thirty kilometers. They say, I didn't have

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Speaker 2: any trouble getting about an eight hour day out of it.

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Speaker 3: Ben, you wore it much more than I did. I

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Speaker 3: wore it a little bit. Do you want to just

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Speaker 3: talk about your experience with hyper Shell.

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Speaker 1: Yeah, I was impressed with it. It was first of all, Hypershell,

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Speaker 1: very funny name. I like that name. It was pretty

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Speaker 1: comfortable to wear, which is I always see the exoskeletons

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Speaker 1: and I'm like, it looks kind of but it was

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Speaker 1: like it was very easy to take on and pull off.

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Speaker 1: I was, And it was comfortable and it was pretty simple.

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Speaker 1: And it basically just has two motors that sort of

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Speaker 1: assist when you move your leg, it pushes your leg

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Speaker 1: and when it comes back in the step, it pushes

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Speaker 1: it back down and so it's just assisting and it

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Speaker 1: tracks your leg pretty well, so there's just very little

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Speaker 1: time when you're pushing against the machine. It's coordinated very well.

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Speaker 1: I mean, it just functioned. It worked, and you could

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Speaker 1: walk a long time.

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Speaker 4: Yeah.

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Speaker 2: The fact that it's like, yes, it's a product that

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Speaker 2: works and it does a thing that has utility, it

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Speaker 2: feels increasingly rare.

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Speaker 4: At Cees.

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Speaker 1: I was a little disappointed that the product did not

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Speaker 1: pay attention to my emotions and build a relationship of

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Speaker 1: empathy with me. That was, but the walking was got Yeah.

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Speaker 2: I asked the hyper Rochelle about its opinions on Proust,

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Speaker 2: and it had very little to say.

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Speaker 3: It is it is like two main mode.

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Speaker 5: It has like this Eco mode, then it's this hypermode,

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Speaker 5: which can get really aggressive.

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Speaker 4: If you turn up hyper model kind of lifting your legs,

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Speaker 4: you can.

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Speaker 3: You can you could be bounding, yeah, and you you can.

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Speaker 3: You can.

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Speaker 5: You can addres like the torque, you can address like

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Speaker 5: how how much delay it has.

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Speaker 3: You have a lot of different settings.

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Speaker 5: The one thing that I had a lot of fun

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Speaker 5: with is that there's this other experimental mode. I don't

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Speaker 5: know if you turned it on yet called called fitness mode.

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Speaker 5: Fitness mode is cool. It does the opposite. It adds

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Speaker 5: resistance to like so it's it's for like working out.

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Speaker 5: If you want like a harder hike, right then you

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Speaker 5: can you can. You can turn on fitness mode and

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Speaker 5: then it'll be it's more work.

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Speaker 4: Like how Goku trained to walk.

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Speaker 5: Sure, but something I I I that's an anime thing.

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Speaker 4: By the way.

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Speaker 5: Now, one thing that I've found out through through my

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Speaker 5: own my my, my own cunning is that if you

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Speaker 5: have hyper mode turned on all the way, which which

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Speaker 5: it was when when Ben was wearing the exoskeleton on

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Speaker 5: my phone, I can switch from hyper mode to fitness

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Speaker 5: Mode immediately, which completely halts any movement.

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Speaker 3: So you can be walking like seven.

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Speaker 4: Fuck up your friends if they don't have the app

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Speaker 4: had seven.

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Speaker 5: You're walking with like seven miles an hour, really fast

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Speaker 5: speed walking, and then I press a button and your

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Speaker 5: legs are going to an immediate halt. And it was

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Speaker 5: really fun to do that for about seven hours.

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Speaker 1: Yeah, I almost crashed into several people just scare to

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Speaker 1: get his kicks.

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Speaker 4: Oh, I'm glad you found the terrorize your friend option.

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Speaker 3: On that It was really fun.

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Speaker 4: It was most of the time I used it.

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Speaker 2: I had installed the app when I got it, but

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Speaker 2: I didn't think about it after that because there you

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Speaker 2: can do everything on device, or at least you can.

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Speaker 3: Do a lot a lot of analyze device.

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Speaker 2: You get a lot more options when you're using the app,

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Speaker 2: but you don't have the app to handle the basic functionality.

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Speaker 4: Right.

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Speaker 5: I loved adjusting the the like the intensity of how

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Speaker 5: much how much doing, and it shows a munch of

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Speaker 5: like applications. Or you can wear this hiking like running,

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Speaker 5: doing you know, lifting your.

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Speaker 4: Work, and I like the thoughtfulness in there.

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Speaker 2: You don't need the app to use this, but the

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Speaker 2: app vastly The app allows you, gives you a lot

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Speaker 2: of control that you're not going to get off of

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Speaker 2: a simple like button.

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Speaker 1: Right.

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Speaker 4: Yeah, It's just struck me as good design.

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Speaker 3: It has a lot of like fidelity.

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Speaker 2: Yeah yeah, so that's the hypershell, folks. Good exoskeleton. I've

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Speaker 2: used a few at various cess and this one certainly

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Speaker 2: strikes me as like a very good like consumer option,

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Speaker 2: like if you as an individual want one. And I'm

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Speaker 2: sure still most of the sales are going to be

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Speaker 2: like enterprise different companies that have like you know, want

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Speaker 2: these for people who are doing like loading and unloading

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Speaker 2: and like a loading.

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Speaker 4: Dock or whatever.

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Speaker 2: But I think the price prices will continue to go

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Speaker 2: down and they are now hitting the point where this

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Speaker 2: is like a thing that individuals can afford if they

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Speaker 2: want one. And there is a lot of and Hypershell

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Speaker 2: focused on this in some of their advertising, but there's

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Speaker 2: a lot of utility for people with disabilities for stuff

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Speaker 2: like this, right Like, that's part of the point of

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Speaker 2: all of these different products, and in general, when it

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Speaker 2: came to the stuff where like the because there's AI

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Speaker 2: in this too, Hypershell talks about it, and it's mostly

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Speaker 2: just like how it learns and reacts to your motions,

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Speaker 2: right that.

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Speaker 4: That's like machine learning.

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Speaker 2: When we talk about AI, usually the useful applications you

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Speaker 2: could also just call machine learning.

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Speaker 4: That's what we used to say.

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Speaker 2: But in general, the products that impressed me most and

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Speaker 2: scared me most at CEES were healthcare related products.

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Speaker 4: Right where we.

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Speaker 2: Have a towel that reads your sweat and can tell

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Speaker 2: if you have like vitamin deficiencies or if you're if

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Speaker 2: you're if you're not hydrated enough, or all of these

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Speaker 2: different like the number of products where it's both like, yes,

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Speaker 2: this thing can tell if you've like fatty liver disease

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Speaker 2: like based on without needing to go to a doctor,

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Speaker 2: and I'm sure that is useful and will help a

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Speaker 2: lot of people.

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Speaker 4: And also all of these products are.

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Speaker 2: Selling your data to the highest bedder, your health data,

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Speaker 2: you're biometrics.

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Speaker 3: You ask them about that.

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Speaker 2: Sorry not, I am not aware of that being the

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Speaker 2: specific thing for the fatty liver people. That was my

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Speaker 2: problem with all of the health wearables. I should just

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Speaker 2: to be sure, I should clarify the wearables are all

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Speaker 2: on the cloud and every one of the ones I

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Speaker 2: saw has deals with the LLLM companies that they're working

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Speaker 2: with and are are handing your data over.

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Speaker 5: Yeah, because that's how they get quote unquote smarter through

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Speaker 5: a massive data data collection.

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Speaker 2: And so there's this thing where there is this kind

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Speaker 2: of baseline expectation here that everyone is fine with handing

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Speaker 2: over all of their data, all of their physical data,

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Speaker 2: all their biometrics, which I they're like, the utility is

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Speaker 2: undeniable of things that can diagnose that you need to

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Speaker 2: go to the to a doctor, or can at least

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Speaker 2: suggest the existence of problems combined with and we are

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Speaker 2: not at all interested in keeping that information secure. I

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Speaker 2: find the kind of casual and no one will because

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Speaker 2: I don't think people will. I think people will buy

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Speaker 2: these products and not think about who's getting access to

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Speaker 2: their biometric data. And I wish that people cared about that.

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Speaker 5: And we've seen that specifically be a problem like around

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Speaker 5: like pregnancy. Yeah, and with states restricting abortion and the

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Speaker 5: ways in which these companies are aware of people's bodies

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Speaker 5: even before the actual people are.

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Speaker 2: Here's an AD break. All right, we're back from ADS.

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Speaker 2: So I went to Lenovo's booth. It was a bunch

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Speaker 2: of laptops. I use Lenovo laptops. They make good products.

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Speaker 2: It was every product there was either here is a

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Speaker 2: new update to the line of laptops we've been making

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Speaker 2: for thirty years. This is the latest one, this is

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Speaker 2: the latest think pad carbon, this is the latest you know,

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Speaker 2: idea pad or whatever. And then they had a couple

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Speaker 2: of like the big thing they were showing was the

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Speaker 2: Lenovo Twist, which is a laptop that has a screen

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Speaker 2: that can twist around and so it can lay flat

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Speaker 2: like a tablet, but it can also the thing that

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Speaker 2: we're really showing is that it's motorized and it has

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Speaker 2: AI enabled, so it can follow your face and you

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Speaker 2: can set it to track an individual's face and as

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Speaker 2: you move, it will move with you. Now, it has

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Speaker 2: two different modes. One of them is also you can

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Speaker 2: like gesture to it, or you can command it by

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Speaker 2: voice and you can say go into laptop mode, go

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Speaker 2: into tablet mode, turn left, turn right. That did not

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Speaker 2: work well about half the time in the demo that

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Speaker 2: I saw, it did not respond, maybe because the room

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Speaker 2: was loud, maybe because the data was bad. But then

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Speaker 2: he put it into face tracking mode and when you

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Speaker 2: have multiple faces, you can pick which face it tracks

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Speaker 2: and it swiveled to meet your face and it was

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Speaker 2: cool and it did work very well. That was like,

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Speaker 2: this is impressive, Like what is the use case? Why

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Speaker 2: would you want it? And he was like, well, say

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Speaker 2: you're doing a presentation, like you're a CEO or something

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Speaker 2: doing a presentation. This way the screen with your text

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Speaker 2: on it or the PowerPoint on it will follow you

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Speaker 2: as you move around. And I was like, that could

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Speaker 2: be useful. I don't feel like many people are in

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Speaker 2: that situation often. I've never been in that situation in

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Speaker 2: my life, and I speak in public for a living sometimes,

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Speaker 2: so I guess, yeah, there probably is a CEO who

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Speaker 2: would benefit for there's like five of those guys. Like

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Speaker 2: what is the there's a whole laptop product line. You

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Speaker 2: have multiple versions, and I didn't get a single reason

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Speaker 2: why you would want this other than that, other than

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Speaker 2: for presentations. And it's genuinely impressive that it can track

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Speaker 2: your face and move as you move. But why And

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Speaker 2: another product they had that was in the bolt y

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Speaker 2: category was the Lenovo Legion and this is not a

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Speaker 2: product that's ever going to come out, but it was

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Speaker 2: like a proof of concept. So it's their gaming laptop

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Speaker 2: line and it has a normal screen that can widen

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Speaker 2: to be three times as long and it unfolds. They

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Speaker 2: have screens that unfold, and it's cool that they could

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Speaker 2: do that, and it looked neat, and it's neat that

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Speaker 2: a screen has that capability. I don't want it because

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Speaker 2: it also it doesn't look I could see like obviously

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Speaker 2: I can see utility and like you can have a

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Speaker 2: screen that gets bigger without it being a bigger footprint

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Speaker 2: for the laptop. But when the screen is unfolded, there's huge,

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Speaker 2: like speed bump size, looking like wads of screen that

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Speaker 2: are bigger and like bulge out, and it doesn't look

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Speaker 2: good like it's a bad screen.

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Speaker 3: It's like a little like bubbly.

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Speaker 4: Yeah, when it's fully extended, it's not like a good screen.

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Speaker 5: You said, it's a proven concept piece, Like there's this thing.

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Speaker 5: I mean, like they're.

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Speaker 4: Showing that they've they're working on folding screen technology.

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Speaker 5: The Twist was was like a previous version of that. Yes,

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Speaker 5: the proof of concept called the Swivel was at CES

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Speaker 5: last year. Yes, and they improved it and now it's

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Speaker 5: a real product called the Twist. Right, and maybe this

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Speaker 5: could be the case for this like unrolling unfolding.

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Speaker 4: Eventually it will be.

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Speaker 2: In products, right, Yeah, But I also don't think I

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Speaker 2: don't see how you cannot have the bulge kind of

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Speaker 2: out and a girl to how the screen work.

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Speaker 3: The folding screens have come along way the past five years.

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Speaker 4: I used one.

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00:17:32,760 --> 00:17:36,399
Speaker 2: Yeah, they also do have some pixels dying in the

402
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Speaker 2: fold area.

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Speaker 3: I mean yeah, if you're trying.

404
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Speaker 5: To buy products for longevity, probably not the thing for you.

405
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Speaker 5: If you like it for the novelty and for some

406
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Speaker 5: reason have enough cash to burn, then maybe it's something

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Speaker 5: someone will be interested in.

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Speaker 2: As I was watching an unfold, there were two guys

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Speaker 2: behind me and talking about it, and one of them

410
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Speaker 2: was like, yeah, it's not a real it's not going

411
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Speaker 2: to actually come out like that's even like the old

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Speaker 2: version of the chassis.

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Speaker 4: And I said, I just don't really see a use.

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Speaker 4: I don't think people.

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Speaker 2: Want a product like this, Like I'm looking at it,

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Speaker 2: the screen's not great, and I just don't see who's

417
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Speaker 2: gonna buy this.

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Speaker 4: And the guy behind.

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Speaker 2: Me said, well, I think like the the use case

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Speaker 2: is like billionaire CEOs and other people have a lot

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Speaker 2: of money.

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Speaker 4: And I looked at it. It was a Lenovo rep

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Speaker 4: and I was.

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Speaker 2: Like, hahh, that's not that's the use Why who are

425
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Speaker 2: like that's not?

426
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Speaker 4: Like did you just say that to me?

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Speaker 3: A Lenovo rep said that.

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Speaker 4: Yeah, yeah, he's one of the guys doing the demos.

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Speaker 2: He had a wild Lenovo badge on and I, yeah,

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Speaker 2: that was weird to me, that's wild.

431
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Speaker 4: But again, at least it was a thing.

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Speaker 3: No, it was it was a physical productcause the.

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Speaker 2: Other thing they had they had the workstation, which the

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Speaker 2: thing they were showing was there was an app on

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Speaker 2: it that looks at your face and said shows you

436
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Speaker 2: how fatigued you are by percent, and how fatigued your

437
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Speaker 2: eyes are, and like other data. And I was like, oh,

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Speaker 2: that's creepy and kind of impressive. But then I walked

439
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Speaker 2: away and I came back and it gave me a

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Speaker 2: totally different set of numbers for my fatigue.

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Speaker 3: Where you're differently fatigued.

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Speaker 2: No, I was a second leg and I did it

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Speaker 2: four times, and every time the set of numbers was

444
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Speaker 2: like different enough that the only assumption I can make

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Speaker 2: is that it was those aren't real numbers. It's just

446
00:19:09,080 --> 00:19:11,760
Speaker 2: generating a number and telling you that. And it's full

447
00:19:11,800 --> 00:19:14,360
Speaker 2: of shit because it wouldn't have been so different if

448
00:19:14,359 --> 00:19:17,560
Speaker 2: it was actually measuring anything. It's just random numbers that

449
00:19:17,600 --> 00:19:20,000
Speaker 2: it's putting on to make you think it's me measuring something.

450
00:19:20,000 --> 00:19:21,520
Speaker 3: It's probably trying to it.

451
00:19:21,520 --> 00:19:25,600
Speaker 5: There might be just subtle things that dramatically changed the numbers.

452
00:19:26,000 --> 00:19:26,359
Speaker 4: I tried.

453
00:19:26,400 --> 00:19:28,320
Speaker 2: I specifically once I noticed that tried to keep my

454
00:19:28,359 --> 00:19:30,600
Speaker 2: face flat, and I did notice when you move closer

455
00:19:30,640 --> 00:19:33,680
Speaker 2: and further it changes. But I think it's just programmed

456
00:19:33,680 --> 00:19:36,080
Speaker 2: to as you move, alter the numbers so that you

457
00:19:36,119 --> 00:19:38,639
Speaker 2: see the number moving but every time I came on

458
00:19:38,760 --> 00:19:40,520
Speaker 2: new it was a different number. It went from like

459
00:19:40,800 --> 00:19:42,960
Speaker 2: when I started was like point oh two, and the

460
00:19:43,040 --> 00:19:44,840
Speaker 2: second time I came back it was point five to ozho.

461
00:19:45,240 --> 00:19:48,320
Speaker 2: And again I did nothing. I was specifically keeping my

462
00:19:48,400 --> 00:19:51,280
Speaker 2: face neutral interest like it's just this, it's not a

463
00:19:51,280 --> 00:19:52,080
Speaker 2: big I think.

464
00:19:52,080 --> 00:19:53,840
Speaker 5: I think that type of stuff will will get better,

465
00:19:53,840 --> 00:19:57,240
Speaker 5: Like we've seen versions of that before that have actually

466
00:19:57,280 --> 00:20:00,239
Speaker 5: done like Okay, yeah, well there could be a lot

467
00:20:00,240 --> 00:20:03,360
Speaker 5: of factors into like into why why the demo goes

468
00:20:03,400 --> 00:20:03,960
Speaker 5: a certain way.

469
00:20:04,040 --> 00:20:07,280
Speaker 2: The face tracking and facial recognition were but I went

470
00:20:07,320 --> 00:20:08,959
Speaker 2: to this booth that like the big thing they were

471
00:20:08,960 --> 00:20:11,560
Speaker 2: doing was like uh, driving assistant robots that would like

472
00:20:11,640 --> 00:20:13,560
Speaker 2: yell at you if you fell asleep or if you

473
00:20:13,600 --> 00:20:16,600
Speaker 2: like looked away and were like texting or something. It

474
00:20:16,640 --> 00:20:18,399
Speaker 2: would say like look away from your phone, look at

475
00:20:18,400 --> 00:20:22,920
Speaker 2: the screen please. And there's definitely like utility there, right,

476
00:20:23,040 --> 00:20:24,840
Speaker 2: Like that is probably a good idea.

477
00:20:24,920 --> 00:20:27,160
Speaker 5: I mean we saw that last year at Samsung's section

478
00:20:27,200 --> 00:20:30,359
Speaker 5: of Eurka Park for like like test taking to make

479
00:20:30,400 --> 00:20:33,560
Speaker 5: sure students aren't cheating at tests, right, So it like

480
00:20:33,640 --> 00:20:37,000
Speaker 5: sends an alert every time the students' eyes goes away

481
00:20:37,040 --> 00:20:39,240
Speaker 5: from like the computer screen, like if they keep like

482
00:20:39,280 --> 00:20:42,120
Speaker 5: looking down like like under if they could be checking

483
00:20:42,160 --> 00:20:43,080
Speaker 5: like their phone or notes.

484
00:20:43,240 --> 00:20:44,680
Speaker 4: Smart Eye is the company.

485
00:20:45,040 --> 00:20:47,400
Speaker 2: One thing I did appreciate was that the little device

486
00:20:47,440 --> 00:20:49,080
Speaker 2: that they put in was just like a circle with

487
00:20:49,119 --> 00:20:51,639
Speaker 2: two eyes on it as opposed to like a whole dashboard.

488
00:20:52,320 --> 00:20:54,320
Speaker 2: So that seemed nice. But the thing, the thing that

489
00:20:54,359 --> 00:20:56,280
Speaker 2: they had, the first thing I used was this optical

490
00:20:56,320 --> 00:20:58,640
Speaker 2: recognition system where it learned my eyes and then when

491
00:20:58,640 --> 00:21:00,359
Speaker 2: I came on, it would give my name time I

492
00:21:00,359 --> 00:21:02,399
Speaker 2: walked up to it, and so like, yeah, it definitely

493
00:21:02,480 --> 00:21:06,800
Speaker 2: like recognizes at least your eyes. That's it could switch

494
00:21:06,840 --> 00:21:09,600
Speaker 2: between different people. But it was also it can tell

495
00:21:09,640 --> 00:21:13,480
Speaker 2: when you're drunk, they claim, And I couldn't tell that.

496
00:21:13,760 --> 00:21:16,680
Speaker 4: I couldn't. I was high on kratum and I had.

497
00:21:16,880 --> 00:21:21,679
Speaker 2: Smoked Delta aid, but so I was definitely not sober.

498
00:21:21,720 --> 00:21:23,639
Speaker 2: It didn't recognize me as not sober, so it couldn't

499
00:21:23,640 --> 00:21:27,359
Speaker 2: measure those things. Maybe it can tell if you're drunk. Yeah, demo,

500
00:21:27,480 --> 00:21:29,280
Speaker 2: it's it. They said it could. And they showed a

501
00:21:29,320 --> 00:21:30,920
Speaker 2: woman when she was sober and when she was drunk,

502
00:21:30,920 --> 00:21:33,280
Speaker 2: and they explained to me it was actually really difficult

503
00:21:33,280 --> 00:21:34,919
Speaker 2: because we did this on a close track and she

504
00:21:35,040 --> 00:21:37,080
Speaker 2: is really drunk and we had to jump through a

505
00:21:37,119 --> 00:21:38,960
Speaker 2: lot of hoops for them to let us have a

506
00:21:39,000 --> 00:21:39,880
Speaker 2: person drunk driving.

507
00:21:39,960 --> 00:21:41,680
Speaker 4: That's just And I did find that kind of funny.

508
00:21:42,119 --> 00:21:43,600
Speaker 3: You response that his how you test that would be

509
00:21:43,680 --> 00:21:45,000
Speaker 3: kind of a hard thing to test. Yeah, you can

510
00:21:45,000 --> 00:21:46,479
Speaker 3: test like simulations.

511
00:21:46,200 --> 00:21:48,200
Speaker 2: Right, but they wanted like this was supposed to be

512
00:21:48,200 --> 00:21:50,720
Speaker 2: a perfect concept in vehicle and it'll shut down the car.

513
00:21:51,080 --> 00:21:53,240
Speaker 2: I did have some people posting when I posted a

514
00:21:53,320 --> 00:21:55,760
Speaker 2: video of that that like, I have this condition with

515
00:21:55,800 --> 00:21:57,639
Speaker 2: my eyes or that condition with my eyes, and normal

516
00:21:57,720 --> 00:22:00,720
Speaker 2: optical recognition stuff doesn't work with me. Is this going

517
00:22:00,760 --> 00:22:02,760
Speaker 2: to show that I'm drunk or is it going to

518
00:22:02,840 --> 00:22:04,760
Speaker 2: like be able to And I actually don't know. Again,

519
00:22:04,800 --> 00:22:06,320
Speaker 2: I'm not I was not able to test the product

520
00:22:06,359 --> 00:22:09,760
Speaker 2: that that does seem like a concern. I would hope

521
00:22:09,760 --> 00:22:12,360
Speaker 2: they've dealt with. But also I kind of doubt they

522
00:22:12,400 --> 00:22:15,800
Speaker 2: did because usually there's gaps.

523
00:22:15,280 --> 00:22:17,240
Speaker 5: I mean, I can see a company like this partnering

524
00:22:17,320 --> 00:22:19,520
Speaker 5: with like an insurance company, yeah, or partnering with like

525
00:22:19,560 --> 00:22:22,040
Speaker 5: certain cars that would like, yeah, stop the car from

526
00:22:22,040 --> 00:22:24,440
Speaker 5: being able to be moved if it detects the driver

527
00:22:24,560 --> 00:22:27,600
Speaker 5: as drunk, yes, and how like false positives what play

528
00:22:27,600 --> 00:22:29,200
Speaker 5: into that? And then you just like are like locked

529
00:22:29,240 --> 00:22:31,520
Speaker 5: out of your car right because this robot thinks you're

530
00:22:31,520 --> 00:22:33,639
Speaker 5: intoxicated and actually you're fine.

531
00:22:33,680 --> 00:22:34,600
Speaker 3: You just like look like that.

532
00:22:35,000 --> 00:22:37,000
Speaker 2: And I could also see them like rolling this product

533
00:22:37,080 --> 00:22:39,080
Speaker 2: out and it hits like Thailand or something, and then

534
00:22:39,119 --> 00:22:41,359
Speaker 2: there being a big store where it's like they didn't

535
00:22:41,400 --> 00:22:44,359
Speaker 2: test this on any people of like Thaie ancestry, and

536
00:22:44,359 --> 00:22:46,720
Speaker 2: it actually sees all of them as drunk because of

537
00:22:46,720 --> 00:22:48,639
Speaker 2: like an error in the coding. Sure, and being like

538
00:22:48,680 --> 00:22:52,440
Speaker 2: oh great, like like I'm not again smart Eye. From

539
00:22:52,480 --> 00:22:55,560
Speaker 2: what I can tell, their technology worked, but in order

540
00:22:55,600 --> 00:22:59,720
Speaker 2: to adequately like review and test it, you do need

541
00:23:00,320 --> 00:23:01,840
Speaker 2: you need more access to it than they're giving it

542
00:23:01,840 --> 00:23:03,840
Speaker 2: the show. I can't actually tell you if it works

543
00:23:03,840 --> 00:23:05,600
Speaker 2: a determined when people are drunk. I can just show

544
00:23:05,600 --> 00:23:07,280
Speaker 2: you they had a video claiming it does.

545
00:23:07,960 --> 00:23:08,080
Speaker 4: So.

546
00:23:08,400 --> 00:23:13,080
Speaker 5: One product that I feel at best mixed about I

547
00:23:13,440 --> 00:23:17,040
Speaker 5: first saw in the CS Innovation Awards section. This is

548
00:23:17,080 --> 00:23:21,960
Speaker 5: called Self Insight Therapy Resolve x R from South Korea.

549
00:23:22,320 --> 00:23:24,160
Speaker 2: Oh, one of my two favorite Koreas. By the way,

550
00:23:24,240 --> 00:23:25,439
Speaker 2: just since we're talking Korea.

551
00:23:25,880 --> 00:23:30,399
Speaker 5: This is a VR therapy program that is supposed to

552
00:23:30,560 --> 00:23:34,800
Speaker 5: give give you a final goodbye with the deceased loved

553
00:23:34,800 --> 00:23:38,480
Speaker 5: one in VR. Yes, this was my initial reaction as well.

554
00:23:39,080 --> 00:23:41,399
Speaker 5: And like I've seen version I've seen versions of this

555
00:23:41,440 --> 00:23:45,440
Speaker 5: before where it's like an LLLM or like an AI. Yeah,

556
00:23:46,040 --> 00:23:48,679
Speaker 5: pretending to be your like dead wife that you like

557
00:23:49,000 --> 00:23:52,200
Speaker 5: hug in VR, sure, and that type of stuff. I've

558
00:23:52,280 --> 00:23:55,959
Speaker 5: generally felt bad about some of the people who've used it,

559
00:23:56,000 --> 00:23:58,040
Speaker 5: like in like you know, like the promotional videos are

560
00:23:58,119 --> 00:24:00,520
Speaker 5: you know, crying, And I feel and like the product

561
00:24:00,520 --> 00:24:01,080
Speaker 5: in a way.

562
00:24:01,200 --> 00:24:03,680
Speaker 2: As a friend, I will promise you if that moment

563
00:24:03,680 --> 00:24:06,000
Speaker 2: ever comes for you all pretend to be your dead wife.

564
00:24:06,040 --> 00:24:08,119
Speaker 3: I don't even know what to say that I've.

565
00:24:09,480 --> 00:24:14,960
Speaker 5: But what I found interesting about Resolve XR is that

566
00:24:15,640 --> 00:24:18,239
Speaker 5: the the avatar of your deceased loved one is not

567
00:24:18,880 --> 00:24:23,480
Speaker 5: that the b is not actually an AI, nor is

568
00:24:23,520 --> 00:24:28,399
Speaker 5: it a fully pre recorded, like prescripted like simulation. It

569
00:24:28,520 --> 00:24:31,879
Speaker 5: is being puppeted by a therapist that you are working

570
00:24:31,920 --> 00:24:36,760
Speaker 5: with as a part of the Gestalt empty Chair therapy technique.

571
00:24:36,880 --> 00:24:39,000
Speaker 5: And this this is what the product is. So you're

572
00:24:39,000 --> 00:24:41,560
Speaker 5: working with a therapist who is using text to speech,

573
00:24:42,040 --> 00:24:45,720
Speaker 5: that is, talking as your deceased as your deceased loved

574
00:24:45,720 --> 00:24:48,320
Speaker 5: one as a part of this therapy exercise, if you

575
00:24:48,320 --> 00:24:51,359
Speaker 5: have if you have recordings of their voice, the AI

576
00:24:51,400 --> 00:24:53,359
Speaker 5: will try to replicate their voice. That's something I feel

577
00:24:53,400 --> 00:24:55,840
Speaker 5: a little bit odd about. But like that is like

578
00:24:55,880 --> 00:24:57,760
Speaker 5: the one like aspect of like qute unquote AI that's

579
00:24:57,800 --> 00:25:00,000
Speaker 5: being used here is for is for the voice clone.

580
00:25:00,720 --> 00:25:03,399
Speaker 5: And then there's like a pre a prerecorded set of

581
00:25:03,440 --> 00:25:06,199
Speaker 5: like gestures that someone does in like motion capture. But

582
00:25:06,280 --> 00:25:08,520
Speaker 5: the actual like like live puppeting of this thing is

583
00:25:08,520 --> 00:25:10,800
Speaker 5: done by a therapist that you were sitting across from.

584
00:25:10,920 --> 00:25:14,199
Speaker 5: But you have you know the VR goggle song mm hm.

585
00:25:14,760 --> 00:25:16,880
Speaker 5: And this is this is not supposed to be something

586
00:25:16,880 --> 00:25:18,960
Speaker 5: that you do like routinely. It's not like, oh, I'm

587
00:25:19,320 --> 00:25:22,119
Speaker 5: like I'm talking to my wife like my wife.

588
00:25:21,880 --> 00:25:22,240
Speaker 4: Is in VR.

589
00:25:22,320 --> 00:25:25,280
Speaker 5: It's this is a therapeutic exercise meant for people dealing

590
00:25:25,280 --> 00:25:28,360
Speaker 5: with extreme grief, specifically when loved ones have been taken

591
00:25:28,400 --> 00:25:32,080
Speaker 5: away during like like like accidents, like they specifically mentioned

592
00:25:32,119 --> 00:25:34,800
Speaker 5: like a plane crash that happened a year ago. And

593
00:25:34,880 --> 00:25:36,760
Speaker 5: so this is for people like an extreme extreme grief

594
00:25:36,840 --> 00:25:40,560
Speaker 5: to give them like closure through this therapeutic exercise, and

595
00:25:40,600 --> 00:25:41,800
Speaker 5: this is this is this is the this is the

596
00:25:41,800 --> 00:25:42,359
Speaker 5: pam slet.

597
00:25:43,800 --> 00:25:46,159
Speaker 2: I went through a lot of whiplash because obviously my

598
00:25:46,200 --> 00:25:48,960
Speaker 2: first assumption was this is an evil product where you

599
00:25:49,000 --> 00:25:51,040
Speaker 2: like feed your loved one's social media data and it

600
00:25:51,080 --> 00:25:53,600
Speaker 2: pretends to be them, and it's not that, and it's

601
00:25:53,600 --> 00:25:55,520
Speaker 2: good that it's not that, But then it's like a

602
00:25:56,000 --> 00:25:59,640
Speaker 2: it's being basically a therapist puppeting your dead loved one.

603
00:26:00,720 --> 00:26:03,720
Speaker 2: There's a couple of conclusions I have. First off, these

604
00:26:03,760 --> 00:26:07,119
Speaker 2: people are trying to be ethical. It does seem it

605
00:26:07,200 --> 00:26:11,400
Speaker 2: seems like they care, and they are attempting to provide

606
00:26:11,520 --> 00:26:14,600
Speaker 2: something that is useful to people who are suffering. I

607
00:26:14,640 --> 00:26:18,119
Speaker 2: also think this might fundamentally, this idea might be fundamentally

608
00:26:18,160 --> 00:26:20,240
Speaker 2: unethical and impossible to do well. So I think this

609
00:26:20,359 --> 00:26:22,399
Speaker 2: might be a case of someone trying to do the

610
00:26:22,440 --> 00:26:24,920
Speaker 2: most ethical version of something that cannot be done ethically,

611
00:26:25,200 --> 00:26:27,680
Speaker 2: which is a category of AI device that I've seen

612
00:26:27,720 --> 00:26:28,080
Speaker 2: this year.

613
00:26:28,760 --> 00:26:32,359
Speaker 1: It's tricky because on one hand, you know, as I

614
00:26:32,440 --> 00:26:36,119
Speaker 1: was talking to the woman at the booth and reading

615
00:26:36,160 --> 00:26:39,240
Speaker 1: through the materials they had, it seemed like they were

616
00:26:39,320 --> 00:26:43,159
Speaker 1: selling this as this is just sort of augmentation to

617
00:26:43,280 --> 00:26:46,720
Speaker 1: a therapeutic practice that has already done. Yeah, we're just

618
00:26:46,840 --> 00:26:50,159
Speaker 1: putting a you know, a digitally generated face and voice

619
00:26:50,200 --> 00:26:53,719
Speaker 1: to it. But it's so I mean, it's so easy

620
00:26:53,720 --> 00:27:00,000
Speaker 1: to imagine just this company seems somewhat ethically focused. But yeah,

621
00:27:01,240 --> 00:27:03,640
Speaker 1: all kinds of directions you could go in this. It's

622
00:27:03,760 --> 00:27:06,440
Speaker 1: a Pandora's box, a little bit of like, yeah, where

623
00:27:06,520 --> 00:27:12,040
Speaker 1: where we're starting to venture into creating replicas of the dead? Yeah,

624
00:27:12,080 --> 00:27:12,720
Speaker 1: and that is.

625
00:27:12,960 --> 00:27:15,399
Speaker 2: And I went to a panel kind of in the

626
00:27:15,400 --> 00:27:19,280
Speaker 2: same tone on mental health and AI that I thought

627
00:27:19,359 --> 00:27:22,240
Speaker 2: was going to be an opportunity for me to harass

628
00:27:22,640 --> 00:27:25,200
Speaker 2: an executive during a Q and A because which is

629
00:27:25,200 --> 00:27:27,480
Speaker 2: which is one of your favorite the activity everything to

630
00:27:27,480 --> 00:27:31,200
Speaker 2: do at CES and there literally is like AI. There's

631
00:27:31,320 --> 00:27:33,560
Speaker 2: ample data that it is a disaster for mental health,

632
00:27:33,680 --> 00:27:35,600
Speaker 2: not just AI psychosis, but there are a lot of

633
00:27:35,640 --> 00:27:38,080
Speaker 2: things that it makes worse, and a lot of problems

634
00:27:38,080 --> 00:27:40,199
Speaker 2: that it causes people and a lot of problems that

635
00:27:40,240 --> 00:27:42,880
Speaker 2: it exacerbates, including like suicidal ideation.

636
00:27:43,200 --> 00:27:45,960
Speaker 4: This is documented, there's data on it. So that's what

637
00:27:46,040 --> 00:27:46,280
Speaker 4: I was.

638
00:27:46,359 --> 00:27:48,320
Speaker 2: I was showing up prepared to do that, And what

639
00:27:48,359 --> 00:27:51,639
Speaker 2: I actually got was an actual clinical therapist who was

640
00:27:51,720 --> 00:27:55,639
Speaker 2: trying to talk about who first started by kind of

641
00:27:55,640 --> 00:27:59,399
Speaker 2: by very much admitting the dangers with AI and the

642
00:27:59,440 --> 00:28:01,440
Speaker 2: things that it harms in terms of mental health, and

643
00:28:01,480 --> 00:28:04,080
Speaker 2: then was trying to say, what would a responsible and

644
00:28:04,200 --> 00:28:09,920
Speaker 2: ethical like therapeutic AI do. And her argument was, we

645
00:28:10,000 --> 00:28:12,439
Speaker 2: know how many people need therapy and don't have access

646
00:28:12,440 --> 00:28:14,640
Speaker 2: to it, both in the United States and worldwide, and

647
00:28:14,760 --> 00:28:19,119
Speaker 2: some sort of automated BOT system that handles aspects of

648
00:28:19,160 --> 00:28:22,800
Speaker 2: therapy might be the only way to provide affordable therapy

649
00:28:22,880 --> 00:28:24,879
Speaker 2: to the number of people who needed who can't currently

650
00:28:24,880 --> 00:28:29,560
Speaker 2: afford it. And I disagree, or at least I don't

651
00:28:29,600 --> 00:28:32,240
Speaker 2: think that. I don't disagree. It's accurate that there's way

652
00:28:32,240 --> 00:28:35,480
Speaker 2: more people who need mental health than can afford it, right,

653
00:28:35,480 --> 00:28:40,280
Speaker 2: that's undeniable, undebatable. I disagree that AI can help this

654
00:28:40,320 --> 00:28:42,440
Speaker 2: problem in any meaningful way, and in fact, I think

655
00:28:42,480 --> 00:28:45,680
Speaker 2: it will only make it worse. But I understand that

656
00:28:45,720 --> 00:28:47,920
Speaker 2: she was coming at this from a I am attempting

657
00:28:47,960 --> 00:28:52,680
Speaker 2: to define what a responsible, a therapeutic AI might do,

658
00:28:53,480 --> 00:28:55,720
Speaker 2: and through the course of that I believe she is

659
00:28:55,920 --> 00:28:58,000
Speaker 2: partially because I talked to her about this afterwards too.

660
00:28:58,400 --> 00:29:01,640
Speaker 2: She thinks it might be possis, but is not convinced

661
00:29:01,680 --> 00:29:03,920
Speaker 2: that it is in fact possible for there to be

662
00:29:04,360 --> 00:29:09,800
Speaker 2: an AI therapy system that is actually useful. And one

663
00:29:09,800 --> 00:29:12,720
Speaker 2: of the things she brought up was that in traditional

664
00:29:12,800 --> 00:29:17,280
Speaker 2: AI chatbots, the big ones are all programmed to gas

665
00:29:17,320 --> 00:29:19,479
Speaker 2: you up in order to keep you using them, right,

666
00:29:19,520 --> 00:29:21,640
Speaker 2: the program to make you want to continue to interact

667
00:29:21,640 --> 00:29:23,240
Speaker 2: with them, and so it does things that are really

668
00:29:23,240 --> 00:29:25,680
Speaker 2: bad for your mental health and that can exacerbate and

669
00:29:25,800 --> 00:29:28,440
Speaker 2: cause new problems, right because of the way these are programmed.

670
00:29:28,680 --> 00:29:32,680
Speaker 2: So any responsible AI therapy chatbot would have to not

671
00:29:32,880 --> 00:29:35,800
Speaker 2: do that, which I'm like, that is true, that you

672
00:29:35,920 --> 00:29:38,520
Speaker 2: can't be a useful therapy to tool that.

673
00:29:38,520 --> 00:29:40,920
Speaker 4: Only praises people, right, that's just not a thing.

674
00:29:41,280 --> 00:29:43,080
Speaker 2: But when I came to afterwards, I was like, my

675
00:29:43,640 --> 00:29:45,280
Speaker 2: issue is I think you're right about that, but I

676
00:29:45,320 --> 00:29:49,560
Speaker 2: also think if you're saying the AI therapy bot is

677
00:29:49,600 --> 00:29:51,520
Speaker 2: going to be a separate product that does not do

678
00:29:51,640 --> 00:29:54,719
Speaker 2: these things. Number one, it's a high bar to get

679
00:29:54,760 --> 00:29:57,120
Speaker 2: people to pay money for a tool when they already

680
00:29:57,120 --> 00:29:59,640
Speaker 2: have the chatbot. And number two, if the chatbot that

681
00:29:59,720 --> 00:30:02,080
Speaker 2: is good for them, doesn't do the thing that makes

682
00:30:02,120 --> 00:30:05,480
Speaker 2: it addictive, people will continue to use the addictive one

683
00:30:05,480 --> 00:30:08,640
Speaker 2: for therapy. And she said, yeah, that's my worry too.

684
00:30:09,120 --> 00:30:11,440
Speaker 2: And so I came away from being like, she's trying

685
00:30:11,480 --> 00:30:14,040
Speaker 2: to explore if this can be done, and my conclusion,

686
00:30:14,080 --> 00:30:15,640
Speaker 2: based on her exploration.

687
00:30:15,200 --> 00:30:15,680
Speaker 4: Is it can't.

688
00:30:15,960 --> 00:30:19,040
Speaker 1: But it's so interesting that she said that because she

689
00:30:19,320 --> 00:30:22,240
Speaker 1: and this is I mean me hearing you talk about her,

690
00:30:22,320 --> 00:30:24,520
Speaker 1: she sounds like the only person who is thinking about

691
00:30:24,520 --> 00:30:25,920
Speaker 1: this at all. Yes, that's the convention.

692
00:30:26,000 --> 00:30:28,120
Speaker 2: She was the only person on the panel. Yeah, of

693
00:30:28,640 --> 00:30:30,120
Speaker 2: just it was a speech, not a panel.

694
00:30:30,160 --> 00:30:33,480
Speaker 1: Really, Yeah, of thinking about that, what are the social

695
00:30:33,520 --> 00:30:36,840
Speaker 1: relations behind these technologies, because of course that's the main question.

696
00:30:36,920 --> 00:30:37,080
Speaker 5: Here.

697
00:30:37,160 --> 00:30:40,760
Speaker 1: Is a technology that can generate that can have a

698
00:30:40,800 --> 00:30:44,440
Speaker 1: conversation with you? Is one thing it's not that really

699
00:30:44,440 --> 00:30:46,040
Speaker 1: doesn't seem like the war of the problem so much

700
00:30:46,040 --> 00:30:49,000
Speaker 1: as will all the machines that are having conversations are

701
00:30:49,040 --> 00:30:52,920
Speaker 1: driven by very specific incentives, you know, to interact with

702
00:30:52,960 --> 00:30:55,320
Speaker 1: their users in a particular way that has everything to

703
00:30:55,360 --> 00:30:59,000
Speaker 1: do with the social relationships of their production and use,

704
00:30:59,640 --> 00:31:04,560
Speaker 1: and and the notion that technology would have any connection

705
00:31:04,680 --> 00:31:08,640
Speaker 1: to social relations at all is completely absent from any

706
00:31:08,640 --> 00:31:11,040
Speaker 1: discussion of any product I've seen here.

707
00:31:11,360 --> 00:31:17,560
Speaker 2: Speaking of social relations between products and human beings, here's

708
00:31:17,600 --> 00:31:31,480
Speaker 2: some ads. We're back and God, I really love those

709
00:31:31,560 --> 00:31:35,680
Speaker 2: Chumba casino ads. They remind me that whenever I'm out

710
00:31:35,680 --> 00:31:38,360
Speaker 2: in the world, sitting down with my loved ones, you know,

711
00:31:38,840 --> 00:31:42,680
Speaker 2: watching the big Game, I could be gambling, and kind

712
00:31:42,680 --> 00:31:44,360
Speaker 2: of every other moment of my life that I'm not

713
00:31:44,440 --> 00:31:45,440
Speaker 2: gambling is wasted.

714
00:31:45,720 --> 00:31:48,600
Speaker 5: Robert, have you heard of how She No? So you

715
00:31:48,680 --> 00:31:51,040
Speaker 5: know about politics, right, I love politics, and you know

716
00:31:51,040 --> 00:31:53,400
Speaker 5: about insider trading, right, I love insider te What if

717
00:31:53,400 --> 00:31:56,320
Speaker 5: you could do insider trading about all of politics on

718
00:31:56,400 --> 00:31:58,800
Speaker 5: the exclusive evasion that you will learn as a journalist.

719
00:31:59,040 --> 00:32:00,880
Speaker 4: Wow, sounds legal.

720
00:32:01,360 --> 00:32:02,400
Speaker 3: It shockingly is.

721
00:32:02,880 --> 00:32:07,719
Speaker 5: There's actually zero federal or state regulation affecting this whatsoever.

722
00:32:07,920 --> 00:32:09,240
Speaker 4: That's the CALCI guarantee.

723
00:32:09,280 --> 00:32:11,560
Speaker 5: There is no regulatory mechanism that exists on a state

724
00:32:11,640 --> 00:32:13,120
Speaker 5: level to regulate this behavior.

725
00:32:13,240 --> 00:32:14,880
Speaker 4: Now years and you say that, but that's literally just

726
00:32:14,880 --> 00:32:16,000
Speaker 4: what's printed above their booth.

727
00:32:18,080 --> 00:32:21,280
Speaker 5: Let's talk about maybe the worst product that I saw

728
00:32:21,320 --> 00:32:24,080
Speaker 5: at CEES child Free trust.

729
00:32:24,200 --> 00:32:28,360
Speaker 3: Boy, So, what is it like a software that lets

730
00:32:28,360 --> 00:32:29,120
Speaker 3: you make a trust?

731
00:32:29,720 --> 00:32:35,440
Speaker 1: This software was marketed towards child free people. They lead

732
00:32:35,520 --> 00:32:39,000
Speaker 1: with twenty five percent of Americans don't have children and

733
00:32:39,280 --> 00:32:42,840
Speaker 1: don't intend to have them, tell you, yeah, and so

734
00:32:43,000 --> 00:32:45,920
Speaker 1: their idea is that they right here. Child Free Trust

735
00:32:46,000 --> 00:32:49,680
Speaker 1: is the first comprehensive nationwide solution providing medical and financial

736
00:32:49,720 --> 00:32:53,840
Speaker 1: poa executor and trustee representation for child free and permanently

737
00:32:53,880 --> 00:32:57,920
Speaker 1: childless people. So if you are childless and you don't

738
00:32:57,920 --> 00:33:02,960
Speaker 1: want to burden your loved ones, that's their wording with

739
00:33:03,320 --> 00:33:06,040
Speaker 1: you know, your estate plan when you die. Uh, this

740
00:33:06,200 --> 00:33:09,360
Speaker 1: is a company that will do that for you. What's

741
00:33:09,400 --> 00:33:12,480
Speaker 1: interesting though, is that I asked them, I said, well, look,

742
00:33:12,560 --> 00:33:16,240
Speaker 1: you know this presumably already happens. What is in place?

743
00:33:16,520 --> 00:33:17,959
Speaker 4: I have a trust in no children?

744
00:33:18,080 --> 00:33:21,840
Speaker 1: Yes, yeah, well does state appoints someone to handle this.

745
00:33:21,920 --> 00:33:25,120
Speaker 1: They'll they will first see if that you have, if

746
00:33:25,120 --> 00:33:28,280
Speaker 1: you have any loved ones who would want to take

747
00:33:28,280 --> 00:33:28,880
Speaker 1: on these duties.

748
00:33:28,920 --> 00:33:30,800
Speaker 4: And obviously people with that kids aren't capable of love.

749
00:33:30,880 --> 00:33:33,600
Speaker 1: So yeah, yeah, they they a little bit I mean

750
00:33:33,720 --> 00:33:36,960
Speaker 1: strangely like it. So it's it's an it's a product

751
00:33:36,960 --> 00:33:40,000
Speaker 1: that is for we already have a public service that

752
00:33:40,280 --> 00:33:43,600
Speaker 1: searches for people loved ones that could take on these responsibilities,

753
00:33:43,640 --> 00:33:45,640
Speaker 1: and if it cannot find those, it takes it on

754
00:33:45,760 --> 00:33:48,160
Speaker 1: as a as a public good. So it was it

755
00:33:48,200 --> 00:33:51,200
Speaker 1: was a product completely without purpose. It was like you,

756
00:33:51,280 --> 00:33:53,560
Speaker 1: in order to use this, you just have to be

757
00:33:53,680 --> 00:33:57,520
Speaker 1: intent on separating yourself from society in this way. You

758
00:33:57,560 --> 00:34:00,160
Speaker 1: have no loved ones presumably or you don't want them

759
00:34:00,200 --> 00:34:03,320
Speaker 1: involved in your estate planning. You also don't want the

760
00:34:03,320 --> 00:34:07,160
Speaker 1: state involved, so it requires this third party company. It

761
00:34:07,240 --> 00:34:10,120
Speaker 1: is just a very strange product the way they present it.

762
00:34:10,160 --> 00:34:12,560
Speaker 4: Well, I mean it's again, I have a trust and

763
00:34:12,600 --> 00:34:13,040
Speaker 4: a will.

764
00:34:13,520 --> 00:34:16,600
Speaker 2: If you don't have a kid, and you don't have

765
00:34:17,120 --> 00:34:18,960
Speaker 2: like a you're not like married, or you don't have

766
00:34:18,960 --> 00:34:22,360
Speaker 2: a surviving spouse, like, yes, the state will appoint somebody,

767
00:34:22,400 --> 00:34:25,080
Speaker 2: but that process is slower and more expensive. If you

768
00:34:25,120 --> 00:34:26,920
Speaker 2: want to avoid the cost, or if you want to

769
00:34:26,920 --> 00:34:29,480
Speaker 2: avoid like, having a trust and a will is not

770
00:34:29,520 --> 00:34:31,640
Speaker 2: an unreasonable thing, especially if you want to make sure

771
00:34:31,680 --> 00:34:33,239
Speaker 2: if you have assets and you want to make sure

772
00:34:33,520 --> 00:34:35,520
Speaker 2: they go a specific place, you want to donate them

773
00:34:35,520 --> 00:34:36,200
Speaker 2: somewhere or whatever.

774
00:34:36,560 --> 00:34:39,040
Speaker 3: Well, and like a lawyer can handle that, a lawyer.

775
00:34:38,719 --> 00:34:41,600
Speaker 4: Should handle that is what I'm saying, is you shouldn't

776
00:34:41,680 --> 00:34:42,240
Speaker 4: use an app.

777
00:34:42,360 --> 00:34:45,160
Speaker 5: Specifically, what they do that the lawyer can't is they

778
00:34:45,400 --> 00:34:48,680
Speaker 5: provide a service for the corporation to execute power of attorney.

779
00:34:49,640 --> 00:34:51,680
Speaker 3: And that is the main thing.

780
00:34:52,800 --> 00:34:55,920
Speaker 5: So this is the most anti social This is the

781
00:34:55,920 --> 00:34:57,880
Speaker 5: most anti social service I've seen it all of ces

782
00:34:57,920 --> 00:34:59,520
Speaker 5: because it's building this idea that if you have no

783
00:34:59,640 --> 00:35:02,120
Speaker 5: kids and you are so separated from the rest of

784
00:35:02,200 --> 00:35:04,960
Speaker 5: your family, like you don't trust any siblings, you don't

785
00:35:05,000 --> 00:35:07,640
Speaker 5: trust a spouse, a partner maybe you don't have one,

786
00:35:07,760 --> 00:35:09,840
Speaker 5: you don't trust parents, you don't even trust a friend

787
00:35:10,320 --> 00:35:14,520
Speaker 5: to like do this for you. Instead that you turn

788
00:35:14,680 --> 00:35:17,600
Speaker 5: to a company, a private company. You don't even trust

789
00:35:17,640 --> 00:35:19,920
Speaker 5: the state, right because the state can handle this. It

790
00:35:20,000 --> 00:35:22,839
Speaker 5: is a private corporation that it's going to handle your will,

791
00:35:22,920 --> 00:35:28,280
Speaker 5: your estate and power of attorneys. And that that's what really,

792
00:35:28,920 --> 00:35:30,759
Speaker 5: that's what really got me because I asked them, it's like, yeah,

793
00:35:30,800 --> 00:35:32,799
Speaker 5: like a lawyer can handle all this, and like, well, no,

794
00:35:32,920 --> 00:35:36,040
Speaker 5: regular lawyer can't be power of attorney. And I was like, oh,

795
00:35:36,080 --> 00:35:38,160
Speaker 5: this is the core of your product actually is that

796
00:35:38,200 --> 00:35:40,719
Speaker 5: it's it's for people who are so anti social, who

797
00:35:40,760 --> 00:35:42,919
Speaker 5: have so separated themselves that they don't trust.

798
00:35:43,080 --> 00:35:46,560
Speaker 3: They don't trust anyone with this. They don't have any

799
00:35:46,560 --> 00:35:48,799
Speaker 3: loved ones. Really, it's not just about being child free.

800
00:35:48,880 --> 00:35:52,800
Speaker 5: No, it's like it's about you do not exist in

801
00:35:52,840 --> 00:35:54,320
Speaker 5: a social network whatsoever.

802
00:35:54,440 --> 00:35:56,000
Speaker 2: Because I can see the kind of people who might

803
00:35:56,080 --> 00:35:58,920
Speaker 2: need this are people or might want this, are not

804
00:35:58,960 --> 00:36:00,880
Speaker 2: the people kind of people who do apps, because the

805
00:36:01,320 --> 00:36:04,120
Speaker 2: actual the group of people who definitely don't have kids

806
00:36:04,120 --> 00:36:06,160
Speaker 2: and also may not have any living friends are people

807
00:36:06,200 --> 00:36:08,640
Speaker 2: who are incredibly elderly. But it's not even a factor

808
00:36:08,680 --> 00:36:10,319
Speaker 2: of like their life is bleak that it's just you

809
00:36:10,400 --> 00:36:12,560
Speaker 2: lived way too long. You literally don't have anyone left

810
00:36:12,600 --> 00:36:15,080
Speaker 2: that you knew. But they're not going to use an app,

811
00:36:15,920 --> 00:36:18,600
Speaker 2: like that's just not how they think about. If they

812
00:36:18,600 --> 00:36:20,759
Speaker 2: don't have a lawyer, they'll let have the state handle it.

813
00:36:20,840 --> 00:36:23,120
Speaker 2: But like they're not they're not going to download the

814
00:36:23,239 --> 00:36:25,560
Speaker 2: child free app. That's one hundred and four year old

815
00:36:25,560 --> 00:36:29,520
Speaker 2: okanawent woman to like handle this for them. There's like

816
00:36:29,560 --> 00:36:32,080
Speaker 2: a graph on the bottom that here's like features and

817
00:36:32,120 --> 00:36:35,520
Speaker 2: like which different versions have which features, And the three

818
00:36:35,520 --> 00:36:38,279
Speaker 2: features are child free, trust, trust, and will and then

819
00:36:38,600 --> 00:36:41,239
Speaker 2: free will as one word, but the w's capitalized. I

820
00:36:41,320 --> 00:36:43,520
Speaker 2: just like seeing free well and then checks and exes

821
00:36:43,640 --> 00:36:45,400
Speaker 2: at the bottom. You don't get free well on all

822
00:36:45,440 --> 00:36:48,320
Speaker 2: of the options. Sorry, what is free will as a service?

823
00:36:48,360 --> 00:36:50,719
Speaker 2: S Garrison? Are they saying the machine has it? Or

824
00:36:50,760 --> 00:36:53,400
Speaker 2: is it literally a free will making service? It's I

825
00:36:53,400 --> 00:36:55,680
Speaker 2: think I think it's creating a will and they're calling

826
00:36:55,760 --> 00:36:56,200
Speaker 2: it free will.

827
00:36:56,239 --> 00:36:57,040
Speaker 3: I think that's what I think.

828
00:36:57,040 --> 00:37:00,399
Speaker 4: That's what they're doing. Okay, I mean, but yeah, right now.

829
00:37:00,960 --> 00:37:03,640
Speaker 3: And this was in this was in Eureka part.

830
00:37:03,560 --> 00:37:07,480
Speaker 4: Yeah, which is where the cool little products are. That's bad.

831
00:37:07,719 --> 00:37:09,240
Speaker 3: Yeah, it was really bizarre.

832
00:37:09,960 --> 00:37:12,040
Speaker 2: Yeah, there's a fun bit that you could do if

833
00:37:12,040 --> 00:37:13,320
Speaker 2: you had the money to show up and just do

834
00:37:13,400 --> 00:37:16,400
Speaker 2: bits at CEES where it's like this company can handle

835
00:37:16,440 --> 00:37:19,279
Speaker 2: all of your end of life care and decisions and

836
00:37:19,280 --> 00:37:21,240
Speaker 2: it's just a booth with a handgun on a table.

837
00:37:21,920 --> 00:37:24,560
Speaker 5: So let's talk about to clothes. Let's just discuss like

838
00:37:24,600 --> 00:37:27,400
Speaker 5: what this Cees kind of means in general. We already

839
00:37:27,480 --> 00:37:29,880
Speaker 5: kind of discussed like the AI angle of this, and

840
00:37:29,920 --> 00:37:32,560
Speaker 5: that's something that we've seen throughout this show, is these

841
00:37:32,640 --> 00:37:37,000
Speaker 5: these massive banners hanging everywhere about how Cees is where.

842
00:37:36,719 --> 00:37:37,799
Speaker 3: Innovators show up.

843
00:37:37,800 --> 00:37:41,000
Speaker 5: Sure, yeah, absolutely, And and how everything's based around innovation

844
00:37:41,120 --> 00:37:44,080
Speaker 5: and creativity, and this is where everything descends from. And

845
00:37:44,080 --> 00:37:47,120
Speaker 5: this sort of like like tech idealism that the world

846
00:37:47,239 --> 00:37:51,560
Speaker 5: is based around these concepts of innovation and creativity. And

847
00:37:51,960 --> 00:37:55,600
Speaker 5: they do not mention any any physical way that actually

848
00:37:55,600 --> 00:37:57,800
Speaker 5: comes into the world or the sort of mechanisms of

849
00:37:57,840 --> 00:38:03,040
Speaker 5: the world that allow innovation to take And then we've

850
00:38:03,080 --> 00:38:05,760
Speaker 5: been talking a lot about this the past like two days.

851
00:38:06,200 --> 00:38:08,920
Speaker 1: I mean, it's all we're solving all the problems of

852
00:38:08,960 --> 00:38:12,840
Speaker 1: the world and we're fixing everything, and it's all eternal sunshine.

853
00:38:13,360 --> 00:38:17,319
Speaker 1: And where that comes from is innovation and creativity. But

854
00:38:17,360 --> 00:38:20,879
Speaker 1: those are just yeah, totally abstract quantities. There's not even

855
00:38:20,880 --> 00:38:24,680
Speaker 1: a subject given of like innovators. Well, who who is that?

856
00:38:24,800 --> 00:38:26,440
Speaker 4: Ye are the product you're innovating?

857
00:38:26,560 --> 00:38:29,879
Speaker 1: Yeah, if you is that? The owner? Is that the

858
00:38:30,080 --> 00:38:32,560
Speaker 1: workers who make it? I mean, no mention of labor

859
00:38:32,640 --> 00:38:34,440
Speaker 1: at any point in any of this, which I mean

860
00:38:34,480 --> 00:38:35,319
Speaker 1: that's a given, but.

861
00:38:35,200 --> 00:38:36,880
Speaker 4: Well that's not true. They talked about all the labories

862
00:38:36,920 --> 00:38:37,239
Speaker 4: you can.

863
00:38:37,200 --> 00:38:40,359
Speaker 1: Replace, Yeah, all right, you can. We don't need them.

864
00:38:40,920 --> 00:38:43,719
Speaker 1: It's the innovation is is drawn the full circle, it

865
00:38:43,760 --> 00:38:48,080
Speaker 1: produces itself. Now, yeah, just this abstract quantum of I mean,

866
00:38:48,120 --> 00:38:50,319
Speaker 1: it really is kind of interesting. It does become a

867
00:38:50,360 --> 00:38:54,440
Speaker 1: blur of like who is the magical font producing all

868
00:38:54,480 --> 00:38:56,960
Speaker 1: of this stuff? It almost it's sometimes it almost seems

869
00:38:56,960 --> 00:38:59,719
Speaker 1: like it's the consumer. It's sort of suggesting is like

870
00:39:00,400 --> 00:39:03,800
Speaker 1: it's actually you who creates all of this. It was

871
00:39:03,920 --> 00:39:05,120
Speaker 1: very vague, very strange.

872
00:39:05,280 --> 00:39:05,680
Speaker 3: Mm hmm.

873
00:39:06,560 --> 00:39:08,759
Speaker 5: We went to that one panel about like trying to

874
00:39:08,840 --> 00:39:12,399
Speaker 5: address underserved people who are who are like cut out

875
00:39:12,400 --> 00:39:14,960
Speaker 5: of tech and like cut out of cut out of

876
00:39:15,000 --> 00:39:16,160
Speaker 5: all of these industries.

877
00:39:16,560 --> 00:39:19,440
Speaker 1: Yeah, I mean it was very nondescript about who exactly

878
00:39:19,520 --> 00:39:22,640
Speaker 1: that was. Yeah, they had people talking for that are

879
00:39:22,920 --> 00:39:28,239
Speaker 1: paralyzed veterans, someone from the NAACP, and I mean it

880
00:39:28,320 --> 00:39:32,000
Speaker 1: was just one again, there was no actual discussion of

881
00:39:32,040 --> 00:39:35,320
Speaker 1: the social relationships behind technology. It was just entirely about

882
00:39:35,880 --> 00:39:40,000
Speaker 1: this technology is here, it is the first priority, so

883
00:39:40,040 --> 00:39:44,120
Speaker 1: everything else has to follow after. And yeah, very very

884
00:39:44,239 --> 00:39:46,960
Speaker 1: unclear about they They would all talk about what technology

885
00:39:47,040 --> 00:39:50,920
Speaker 1: could be used for, but entirely nondescript about where that

886
00:39:50,960 --> 00:39:53,920
Speaker 1: process comes from, who's making those decisions, where those centers

887
00:39:53,920 --> 00:39:54,600
Speaker 1: of power are.

888
00:39:54,960 --> 00:39:57,920
Speaker 2: The reach to have an for existing brands and companies

889
00:39:57,920 --> 00:40:00,960
Speaker 2: that make real things to have an AI angle was

890
00:40:01,280 --> 00:40:04,279
Speaker 2: the most obvious and tortured thing that I saw, And

891
00:40:04,560 --> 00:40:06,000
Speaker 2: like one of my favorite booths every year is the

892
00:40:06,080 --> 00:40:09,239
Speaker 2: Jackery booth. Jacquery makes batteries and solar panels, and they

893
00:40:09,280 --> 00:40:12,200
Speaker 2: make pretty good batteries and solar panels for like expeditions

894
00:40:12,400 --> 00:40:14,200
Speaker 2: for camping, like the rugged that they can and I

895
00:40:14,320 --> 00:40:14,600
Speaker 2: use them.

896
00:40:14,640 --> 00:40:15,680
Speaker 4: They're good products.

897
00:40:16,200 --> 00:40:18,000
Speaker 2: And this year they had the new addition of all

898
00:40:18,040 --> 00:40:20,400
Speaker 2: their batteries and the new edition of all their solar panels,

899
00:40:20,400 --> 00:40:23,439
Speaker 2: and as generally happens with technology, everything's a little better

900
00:40:23,440 --> 00:40:26,120
Speaker 2: than it was last year. But there's not much room

901
00:40:26,200 --> 00:40:29,239
Speaker 2: for AI aside from like the batteries have AI, by

902
00:40:29,280 --> 00:40:32,080
Speaker 2: which they mean there's like a learning algorithm that can

903
00:40:32,120 --> 00:40:35,160
Speaker 2: determine like how to optimize aspects.

904
00:40:34,719 --> 00:40:36,200
Speaker 4: Of like power draw or whatever.

905
00:40:36,280 --> 00:40:38,520
Speaker 2: Like Sure, that's not really AI in the way that

906
00:40:38,560 --> 00:40:41,479
Speaker 2: the AI industry means it, but I'm sure sounds real.

907
00:40:42,200 --> 00:40:44,520
Speaker 2: But because that wasn't enough, they had this thing that

908
00:40:44,560 --> 00:40:47,040
Speaker 2: they called their Mars rover, which was not a Mars rover.

909
00:40:47,520 --> 00:40:49,000
Speaker 2: I don't think we'll ever go on Mars. Does not

910
00:40:49,040 --> 00:40:50,960
Speaker 2: look like it could survive on Mars, but it is

911
00:40:51,000 --> 00:40:54,880
Speaker 2: a rover that is a big battery on wheels that

912
00:40:55,120 --> 00:40:57,960
Speaker 2: is intelligent and can drive itself and has solar panels

913
00:40:57,960 --> 00:41:00,680
Speaker 2: that slide out, and the use case for this it

914
00:41:00,719 --> 00:41:03,040
Speaker 2: will travel around and can go to where the sun

915
00:41:03,120 --> 00:41:05,000
Speaker 2: is in order to charge itself up and then head

916
00:41:05,040 --> 00:41:07,080
Speaker 2: to you to offer you outlets when you're doing work.

917
00:41:07,120 --> 00:41:11,360
Speaker 4: And it's like, is a robot that moves? Really? I

918
00:41:11,360 --> 00:41:13,400
Speaker 4: can see like two points in my life where I

919
00:41:13,480 --> 00:41:15,560
Speaker 4: might have gotten used. Who's gonna buy this for?

920
00:41:15,680 --> 00:41:15,759
Speaker 5: What?

921
00:41:16,280 --> 00:41:17,400
Speaker 4: Where will it be deployed?

922
00:41:17,440 --> 00:41:21,200
Speaker 2: It just roams around outside, this expensive machine that does

923
00:41:21,200 --> 00:41:23,000
Speaker 2: not look like it should get rained on too much,

924
00:41:23,640 --> 00:41:26,560
Speaker 2: and finds the sun to charge itself up and then

925
00:41:26,640 --> 00:41:29,080
Speaker 2: heads over to you to charge device. It can't charge

926
00:41:29,080 --> 00:41:31,840
Speaker 2: a home. It doesn't power a house. It's like a

927
00:41:31,840 --> 00:41:32,520
Speaker 2: little robot.

928
00:41:33,920 --> 00:41:34,760
Speaker 3: Is it really camping?

929
00:41:35,000 --> 00:41:36,600
Speaker 4: I don't know. That was unclear.

930
00:41:36,680 --> 00:41:38,399
Speaker 2: They showed it being used and they showed it as

931
00:41:38,440 --> 00:41:40,520
Speaker 2: like I'm outside and using power tools.

932
00:41:40,520 --> 00:41:42,400
Speaker 4: The robot came up to me so I could plug

933
00:41:42,400 --> 00:41:43,760
Speaker 4: in and like, I guess.

934
00:41:43,719 --> 00:41:45,360
Speaker 3: You could take like the park. You could take it

935
00:41:45,400 --> 00:41:45,960
Speaker 3: to the park.

936
00:41:46,280 --> 00:41:46,960
Speaker 4: But it's big.

937
00:41:47,120 --> 00:41:47,839
Speaker 3: It is pretty big.

938
00:41:47,920 --> 00:41:51,520
Speaker 2: It's like a sizeable machine. It probably weighed eighty pounds

939
00:41:51,960 --> 00:41:55,600
Speaker 2: and again like, it's impressive that it can go seek

940
00:41:55,640 --> 00:41:58,360
Speaker 2: out the sun to charge itself up. It's impressive that

941
00:41:58,400 --> 00:42:00,320
Speaker 2: you could like call it or like call it with

942
00:42:00,360 --> 00:42:01,840
Speaker 2: an app and it will come over to you. And

943
00:42:01,880 --> 00:42:05,000
Speaker 2: there's an outlet. Who what is the Who will buy this?

944
00:42:05,680 --> 00:42:07,520
Speaker 2: Why when that is not one?

945
00:42:07,680 --> 00:42:07,919
Speaker 4: Again?

946
00:42:07,960 --> 00:42:11,120
Speaker 2: I can think working in my yard, working out, you know,

947
00:42:11,120 --> 00:42:13,319
Speaker 2: when I'm shearing the goats or whatever, I have had

948
00:42:13,320 --> 00:42:15,319
Speaker 2: to carry a battery with me because there's not an

949
00:42:15,360 --> 00:42:18,759
Speaker 2: outlet out there and the shears need a battery. And yeah,

950
00:42:18,840 --> 00:42:20,960
Speaker 2: I guess it would be easier if the robot moved there.

951
00:42:21,000 --> 00:42:24,160
Speaker 2: But this has to be like twenty thousand dollars. I'm

952
00:42:24,160 --> 00:42:27,279
Speaker 2: not gonna buy a robot to do that. I can

953
00:42:27,360 --> 00:42:30,120
Speaker 2: just pick up a battery and walk with it one

954
00:42:30,200 --> 00:42:34,120
Speaker 2: hundred feet. Who will use this? Why it's not going

955
00:42:34,120 --> 00:42:37,480
Speaker 2: to Mars? I assure you it's not going to Mars. Again,

956
00:42:37,920 --> 00:42:39,759
Speaker 2: I wouldn't want it to be left out in the rain.

957
00:42:40,320 --> 00:42:43,960
Speaker 2: And I love the Jaggery products. They make good stuff.

958
00:42:44,440 --> 00:42:46,880
Speaker 2: And the fact that like, yeah, you clearly scrambled to

959
00:42:46,960 --> 00:42:49,640
Speaker 2: make this, that you had a thing that can compete

960
00:42:49,640 --> 00:42:52,360
Speaker 2: with all the other AI things, And I wish you

961
00:42:52,360 --> 00:42:55,360
Speaker 2: were just devoting your lifes to making better solar panels,

962
00:42:55,680 --> 00:42:56,920
Speaker 2: which is what I want from you.

963
00:42:58,160 --> 00:43:02,960
Speaker 1: Anyway, I'm just curious are the companies here. Are they profitable?

964
00:43:03,320 --> 00:43:04,319
Speaker 1: Like do they?

965
00:43:04,480 --> 00:43:04,680
Speaker 4: Yeah?

966
00:43:04,680 --> 00:43:06,759
Speaker 1: I mean some of them, some of them, but a lot.

967
00:43:06,840 --> 00:43:09,279
Speaker 2: I mean some of them are funded with VC money

968
00:43:09,280 --> 00:43:11,080
Speaker 2: and have not made a profit. Some of them are

969
00:43:11,080 --> 00:43:13,399
Speaker 2: funded from VC money and have been losing money for years.

970
00:43:13,440 --> 00:43:15,640
Speaker 2: And then there's also like like Lenovo makes it's a company,

971
00:43:15,640 --> 00:43:17,640
Speaker 2: it makes a profit. They make products people buy, you know,

972
00:43:18,000 --> 00:43:19,640
Speaker 2: Jaggery makes products people buy.

973
00:43:19,800 --> 00:43:21,680
Speaker 5: There's also a lot of startups like the Eureka Park

974
00:43:21,719 --> 00:43:24,239
Speaker 5: section that we've been referring to, like the stuff in

975
00:43:24,280 --> 00:43:27,520
Speaker 5: the bottom floor of the Venetian that there's you know,

976
00:43:27,520 --> 00:43:29,840
Speaker 5: a lot of startup companies who are looking for investors

977
00:43:29,920 --> 00:43:30,319
Speaker 5: as well.

978
00:43:30,760 --> 00:43:32,080
Speaker 3: So yeah, it is definitely a mix.

979
00:43:32,160 --> 00:43:33,799
Speaker 5: Some of them are trying to do like business business sales,

980
00:43:33,840 --> 00:43:35,400
Speaker 5: some of them are more consumer facing, some of them

981
00:43:35,400 --> 00:43:38,239
Speaker 5: are looking for investors. Some of them are profitable, and

982
00:43:38,719 --> 00:43:41,000
Speaker 5: other ones are trying to boost their sacer price by

983
00:43:41,000 --> 00:43:42,080
Speaker 5: being here, kind of like.

984
00:43:42,480 --> 00:43:44,520
Speaker 3: Kloyd at LG.

985
00:43:44,880 --> 00:43:48,319
Speaker 5: But I think what's really important is that everyone here

986
00:43:48,360 --> 00:43:50,560
Speaker 5: is an innovator, and you know, why we know that

987
00:43:50,520 --> 00:43:53,320
Speaker 5: they're an innovators because they've shown up and only innovators

988
00:43:53,360 --> 00:43:56,399
Speaker 5: show up here and they're the real the driving force

989
00:43:56,440 --> 00:43:57,040
Speaker 5: of the economy.

990
00:43:57,080 --> 00:43:59,279
Speaker 2: And I was feeling bad about myself until I saw

991
00:43:59,280 --> 00:44:01,239
Speaker 2: that band in realize that I am an innovator.

992
00:44:01,760 --> 00:44:03,280
Speaker 3: You know you are an innovator.

993
00:44:03,600 --> 00:44:03,960
Speaker 4: Thank you.

994
00:44:04,040 --> 00:44:06,360
Speaker 2: I showed up and I figured out how to be

995
00:44:06,400 --> 00:44:09,280
Speaker 2: the guy on the most kratim at the at the

996
00:44:09,320 --> 00:44:10,320
Speaker 2: CEO show floor.

997
00:44:10,480 --> 00:44:12,080
Speaker 5: No, I mean CS is so is so interesting to

998
00:44:12,120 --> 00:44:15,480
Speaker 5: be innovated, Like it runs on both on this like

999
00:44:15,719 --> 00:44:20,520
Speaker 5: technology idealism where everything is based on people geniuses. You know,

1000
00:44:20,600 --> 00:44:23,319
Speaker 5: your Steve Jobs having like an id Staates job, and

1001
00:44:23,440 --> 00:44:26,480
Speaker 5: he is the innovator and everything descends from the idea

1002
00:44:26,520 --> 00:44:29,400
Speaker 5: that is like the thing is like this like tech platonism,

1003
00:44:29,680 --> 00:44:31,399
Speaker 5: so like this is one side of it. You also

1004
00:44:31,480 --> 00:44:34,120
Speaker 5: have like the tech accelerationists at CES, where it's like

1005
00:44:34,480 --> 00:44:38,400
Speaker 5: they occupy this position of being so pro technology no

1006
00:44:38,600 --> 00:44:42,400
Speaker 5: matter whatever downsides is the current iteration might have because

1007
00:44:42,440 --> 00:44:45,120
Speaker 5: they need someone to hold that position in order for

1008
00:44:45,200 --> 00:44:47,360
Speaker 5: this thing to move forward. They know that there's concerns

1009
00:44:47,400 --> 00:44:51,440
Speaker 5: around data protection, but their opinion is that it doesn't

1010
00:44:51,520 --> 00:44:55,240
Speaker 5: matter there is problems there, but we we the people

1011
00:44:55,239 --> 00:44:57,800
Speaker 5: here at CES, the innovators, need to ignore them because

1012
00:44:57,840 --> 00:45:00,200
Speaker 5: we have to push forward. And this is like, this

1013
00:45:00,239 --> 00:45:03,040
Speaker 5: is what like the Austrian Secretary of State said that

1014
00:45:03,080 --> 00:45:04,879
Speaker 5: at that one panel I went to. It's like data

1015
00:45:04,880 --> 00:45:07,080
Speaker 5: protection is a problem, but in a but like it

1016
00:45:07,120 --> 00:45:08,120
Speaker 5: gets in the way of innovation.

1017
00:45:08,320 --> 00:45:10,640
Speaker 3: Yeah, and that's that's literally literally what he said.

1018
00:45:10,760 --> 00:45:13,160
Speaker 5: Yeah, and so you have you have this like this

1019
00:45:13,160 --> 00:45:17,120
Speaker 5: this like tech optimistic like acceleration like viewpoint of like

1020
00:45:17,239 --> 00:45:19,560
Speaker 5: technology will be better, but in order for it's to

1021
00:45:19,680 --> 00:45:21,879
Speaker 5: be better and safe. Essentially, it's it's it's gonna g's

1022
00:45:21,960 --> 00:45:23,520
Speaker 5: kind of shitty and has some problems now, but we

1023
00:45:23,560 --> 00:45:25,600
Speaker 5: need to push forward through that all the way, Like

1024
00:45:25,640 --> 00:45:27,920
Speaker 5: we can't, we can't, we can't go slowly.

1025
00:45:28,520 --> 00:45:30,000
Speaker 3: It has it has to go forward.

1026
00:45:30,040 --> 00:45:33,000
Speaker 5: So they adopt this this viewpoint because like they need

1027
00:45:33,040 --> 00:45:36,160
Speaker 5: someone to hold this like tech optimism viewpoint in order

1028
00:45:36,239 --> 00:45:37,840
Speaker 5: for the process to like unfold.

1029
00:45:38,320 --> 00:45:41,360
Speaker 1: Yeah, there's something strangely clear eyed about that in the

1030
00:45:41,400 --> 00:45:43,680
Speaker 1: way that it's like, yeah, if I mean, if you're

1031
00:45:43,719 --> 00:45:48,239
Speaker 1: limiting your view to the system of capitalism, yeah, the

1032
00:45:48,239 --> 00:45:50,680
Speaker 1: whole thing goes into crisis. If you are not squeezing

1033
00:45:50,680 --> 00:45:53,560
Speaker 1: a little more juice out of the orange. Uh And

1034
00:45:53,640 --> 00:45:55,479
Speaker 1: if this is what it takes to do that, then

1035
00:45:55,680 --> 00:45:57,839
Speaker 1: then full steam ahead. They're lucid about that.

1036
00:45:57,960 --> 00:46:00,879
Speaker 2: Yeah, yeah, you know what else is lucid us saying

1037
00:46:00,880 --> 00:46:02,799
Speaker 2: it's time to end this fucking podcast.

1038
00:46:03,320 --> 00:46:07,680
Speaker 5: Goodbye, another CES miracle. We have kind of survived.

1039
00:46:12,040 --> 00:46:14,520
Speaker 6: It Could Happen Here is a production of cool Zone Media.

1040
00:46:14,680 --> 00:46:17,760
Speaker 6: For more podcasts from cool Zone Media, visit our website

1041
00:46:17,840 --> 00:46:21,399
Speaker 6: Coolzonemedia dot com, or check us out on the iHeartRadio app,

1042
00:46:21,480 --> 00:46:23,480
Speaker 6: Apple Podcasts, or wherever.

1043
00:46:23,200 --> 00:46:24,520
Speaker 3: You listen to podcasts.

1044
00:46:24,800 --> 00:46:26,759
Speaker 6: You can now find sources for It Could Happen here

1045
00:46:26,760 --> 00:46:29,760
Speaker 6: listed directly in episode descriptions. Thanks for listening.