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Speaker 1: Al Zone Media. Oh my goodness, it's it could happen here,

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Speaker 1: a podcast that is about things falling apart are Dystopian

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Speaker 1: now and tomorrow, And for the last several days has

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Speaker 1: been heavily about the Consumer Electronics Show, which is a

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Speaker 1: huge event every year where one hundred and twenty to

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Speaker 1: one hundred and fifty thousand people flood into Las Vegas

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Speaker 1: to show off all of the new gadgets and to

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Speaker 1: have big, fancy panels on the future of technology. And

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Speaker 1: this has been a particularly good year for the Dystopia beat.

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Speaker 1: Part of that because the entire industry is obsessed right

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Speaker 1: now with artificial intelligence. Now there's a couple reasons for this.

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Speaker 1: Every laptop manufacturer is basically throwing out laptops with AI assistance.

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Speaker 1: Microsoft's is Copilot, and they're doing this because laptop sales

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Speaker 1: have stalled a lot of people, like the pandemic was

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Speaker 1: great for laptop sales, and then people stopped buying them

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Speaker 1: because most people don't need to replace their laptops very often.

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Speaker 1: So there's this death spread hope that by scaring everybody

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Speaker 1: into thinking they need AI immediately, they can get folks

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Speaker 1: to buy a new raft of machines, and outside of that,

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Speaker 1: it's just as I'm sure you're aware, with interest rates

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Speaker 1: where they are companies, Tech companies, particularly startups, are having

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Speaker 1: trouble getting VC money venture capital money invested in them.

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Speaker 1: So there's this kind of desperate hope that by plugging

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Speaker 1: AI constantly they can fill in the gap. So today

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Speaker 1: we have probably in a week or two, we're going

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Speaker 1: to have be putting out a long investigation based on

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Speaker 1: number of panels we went to with executives from Google,

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Speaker 1: from weirdly enough McDonald's, from Adobe, from Nvidia, from the

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Speaker 1: Consumer Electronics Association, in multiple government agencies including DHS, on

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Speaker 1: what they see as the future of AI. That's going

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Speaker 1: to be some pretty in depth reporting. But today we

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Speaker 1: want to talk about the AI products that we've been

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Speaker 1: seeing and as a spoiler, they're basically all the dumbest

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Speaker 1: shit you've ever heard of. So I want to introduce

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Speaker 1: our panel today. Coming back after catching a horrible, horrible

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Speaker 1: lung infection, throat infection, some kind of infection. Yeah, Garrison

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Speaker 1: got strep throat and despite the fact that we've been

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Speaker 1: hanging out together, I did not, which does prove I'm

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Speaker 1: genetically superior. We also have Tavia Mora coming back our

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Speaker 1: technical expert. Hello Tavia, Howdy everybody, and for the first

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Speaker 1: time on well, no, not for the first time, for

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Speaker 1: the third time on It could happen here. The upcoming

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Speaker 1: host of the cool Zone media tech focused show Better

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Speaker 1: Offline ed zitron.

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Speaker 2: Ed Wi Guan Hello, Hey, yeah, sorry, Hi, Yeah, hit

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Speaker 2: my head on the way, and yeah.

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Speaker 3: It's a truly awful show this year.

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Speaker 2: The thing that I said to Robert yesterday when we

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Speaker 2: were talking about the show, and this really stood out

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Speaker 2: to me, is if you had told me this was

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Speaker 2: twenty twenty one, I'd have believed you. It doesn't feel

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Speaker 2: despite the use of the word AI, it does not

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Speaker 2: feel like tech has actually moved that far.

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Speaker 3: And it's very strange.

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Speaker 1: Yeah, there was this period of time after the iPhone

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Speaker 1: came out where every year there would be really big

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Speaker 1: lead in the tech you saw. And this part of

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Speaker 1: I think why they're leaning on AI so heavily is

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Speaker 1: otherwise it's just the same laptop, smartphones, speakers, connected gadgets,

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Speaker 1: you know, autonomous cars and shit that we've been seeing

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Speaker 1: for years and they really haven't jumped forward much. But

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Speaker 1: you know, the downside of that is a lot of things.

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Speaker 1: But the upside of that is people are increasingly cramming

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Speaker 1: AI into insane shit in the hopes that somebody will

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Speaker 1: want to buy it. And so I want to start

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Speaker 1: off ed since you're you are not just our newest

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Speaker 1: host but also a Las Vegas native. I think people

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Speaker 1: could probably assume that from your Vegas accents. Yes, natural, Yeah,

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Speaker 1: what is your favorite or the first AI product do

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Speaker 1: you want to get into today?

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Speaker 3: I want to talk about the rabbit. The rabbit on

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Speaker 3: one Oh God.

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Speaker 1: Yes.

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Speaker 2: So this thing is a square box and I can't

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Speaker 2: tell if it acts without your phone or with your phone,

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Speaker 2: but it uses AI. You you speak into it, look

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Speaker 2: a walk, dooky, and it does a series of actions

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Speaker 2: what you say. So it can do all the things

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Speaker 2: that Siri could do five years ago, like change music

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Speaker 2: and start. But it also has like a three hundred

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Speaker 2: and sixty degree camera, which can based on the extremely

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Speaker 2: awkward and agonizing how a long demo twenty five minutes

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Speaker 2: but on me it felt like an hour. It can

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Speaker 2: look at a picture of rick Castle and start very

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Speaker 2: and after several agonizing seconds stop playing never give you up.

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Speaker 2: It can also it claims do a series of nuanced

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Speaker 2: actions like you can say, get me a cab home

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Speaker 2: and also put on my tunes and also change the

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Speaker 2: air conditioned at seventy four degrees, all in one one sentence.

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Speaker 2: Now you may think, why do I need to spend

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Speaker 2: two hundred dollars on a device to do this? And

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Speaker 2: the answer is you don't. You do not need to.

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Speaker 2: This thing looks cool and on some level, I'm just

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Speaker 2: glad we're getting new tat.

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Speaker 1: Yeah, the design is not bad. It's like a square.

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Speaker 1: It looks like it's maybe two to two and a

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Speaker 1: half inches by two and a half inches or so

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Speaker 1: something like that. Yeah, a little screen. It's like well

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Speaker 1: designed from an industrial design standpoint, and I think the

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Speaker 1: big Yeah, it looks like it's just that it's a

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Speaker 1: It's a basically a seri that can use app It

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Speaker 1: can use uber, It could book a flight for you.

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Speaker 1: One of the things they show is it like planning

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Speaker 1: a vacation in London for you, which does seem to

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Speaker 1: kind of go against the point of like going somewhere

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Speaker 1: new and like figuring out what you want to do there,

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Speaker 1: as opposed to it's basically pulling from a list. I'm

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Speaker 1: sure in the AI wrote of like top ten things

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Speaker 1: to do in London.

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Speaker 2: And it's just very weird because all of these tech guys,

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Speaker 2: who they very loudly claim their free spirits. They're independent,

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Speaker 2: they're not controlled by any authority, they cannot be manipulated,

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Speaker 2: all desperately want a machine to tell them exactly what

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Speaker 2: the hell to do with their lives. And it's so

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Speaker 2: bizarre because they we were discussing the different articles about

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Speaker 2: this and people trying to argue other thing these three exists.

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Speaker 2: It's like, oh, it takes out the friction between all

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Speaker 2: of these apps. I'm sorry, I just don't think there's

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Speaker 2: that much friction.

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Speaker 1: Pull up my phone. I'm on a yes, right, I

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Speaker 1: pull out my phone, I pull up grub Hub, I

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Speaker 1: order food. It's very simple. It's remarkably easy. I don't

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Speaker 1: see how talking to a square is better, Like it's

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Speaker 1: the same, Like I could call someone on the phone

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Speaker 1: and do it hands free, or I could text them,

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Speaker 1: and I always text them because that's more pleasant.

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Speaker 4: I mean, like, I have my phone open to signal

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Speaker 4: right now, I can swipe up go to Uber in

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Speaker 4: less than a second, saying the words move from signal

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Speaker 4: to the Uber app. Takes a whole lot longer than

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Speaker 4: just doing it with my thumb.

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Speaker 1: I also do love the idea of like completely ruining

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Speaker 1: the point of signal, which is an encrypted, extremely secure

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Speaker 1: messaging app, to be like, hey, random box, I want

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Speaker 1: to feed my private messages through you and have you

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Speaker 1: read them out to me as I go about my day.

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Speaker 1: I don't know what your data retention policy is or

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Speaker 1: what you'll be doing with it.

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Speaker 3: They sold down and they made two million dollars.

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Speaker 1: Like ten million of them ten thousand.

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Speaker 2: Sorry, it's just and it's I've read. I read like

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Speaker 2: eleven articles about this thing, because I occasionally drive myself

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Speaker 2: insane with these things when I see everyone excited about something,

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Speaker 2: but I can't read a single article that tells me

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Speaker 2: why I should buy it, even though my rap brain says, oh,

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Speaker 2: take with screen I want, but then I want to

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Speaker 2: use it.

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Speaker 3: But I'll have to explain this to.

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Speaker 2: The normal people in my life why I have this,

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Speaker 2: And I don't want to do that if it's useless.

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Speaker 2: But on top of that, I just don't think controlling

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Speaker 2: my life with voice is that useful.

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Speaker 3: Yeah, I don't like that.

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Speaker 1: I'm already and I think a lot of people are

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Speaker 1: already kind of fed up with the extent to which

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Speaker 1: my smartphone is a part of my life. Yeah, but

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Speaker 1: like it does irreplaceable tasks at the moment for me.

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Speaker 1: So I have it this thing is number one, adding

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Speaker 1: a device because I think it does require your phone.

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Speaker 1: But it's also, like you know, in addition to the

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Speaker 1: current problems I have with privacy on my smartphone, I

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Speaker 1: am adding another company and another device and another set

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Speaker 1: of security potential security flaws to it.

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Speaker 2: But on top of that, the thing they have failed

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Speaker 2: to explain anywhere no jealous apparently is interrogate them about

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Speaker 2: this is they claim this thing can log onto your

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Speaker 2: Uber and make a flight booking, ostensibly having your passport information,

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Speaker 2: your date of birth, and all this stuff. First and foremost, that's,

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Speaker 2: like you mentioned, the data retention policy is very strange.

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Speaker 2: But where is this crap all happening? Is it happening

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Speaker 2: on my phone? Is my phone just doing all this?

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Speaker 2: I refuse to believe that. So you're doing this in

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Speaker 2: the kind of virtual machine environment. How is that possible?

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Speaker 2: Surely these companies are going to have a problem with that.

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Speaker 2: Mark Sullivan for Fast Company. Actually, I think ask them

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Speaker 2: this and they were like, oh, yeah, they'll be fine

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Speaker 2: with it. They just want people using their apps. I

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Speaker 2: do not think they're going to be fine with this.

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Speaker 2: Companies hate it when they hand off power from the user,

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Speaker 2: who will still be liable to another computer.

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Speaker 1: Yeah. Well, the other thing is just that, like part

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Speaker 1: of me kind of suspects And when you watch the video,

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Speaker 1: we'll play a clip from it in a second. The

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Speaker 1: CEO of Rabbit very clearly, like a lot of guys

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Speaker 1: in tech, wants to be Steve Jobs. And I will

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Speaker 1: say one thing I kind of suspect that might actually

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Speaker 1: be that would be a Steve Jobs move, is he

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Speaker 1: may have just been hoping that this thing coming out

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Speaker 1: selling a shitload on free order and getting huge buzz

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Speaker 1: would force these companies after the fact to allow integration.

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Speaker 1: Like he may just be gambling, like if I get

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Speaker 1: enough buzz behind me, Uber and whatnot will come to

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Speaker 1: the table and be willing to work with me, because

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Speaker 1: suddenly this is like the Hippus new gadget.

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Speaker 2: Except ten thousand customers is actually not that many. And

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Speaker 2: I actually look forward to I really can't wait for

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Speaker 2: two months to pass people to get this and someone

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Speaker 2: to end up like sending the word penis to their

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Speaker 2: or company slack because they wanted to order pizza, and

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Speaker 2: on top of that, ordering a fly, ordering an uber.

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Speaker 2: These are actually really nuanced actions. Coming to mandelay, baitenit

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Speaker 2: Uber took me to the wrong place because it decided

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Speaker 2: it wanted to go to the convention center. I did

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Speaker 2: not select that. If you go to the airport, you

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Speaker 2: need to put in Southwest Airlines and what have you.

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Speaker 2: With grub hub, you need to do little bits. It's

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Speaker 2: just most people don't order lunch. They order something for lunch,

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Speaker 2: and I just don't. Ah, this whole thing just feels useless.

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Speaker 5: Yeah. See, for me, it's the additional level of abstraction

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Speaker 5: on top of these already abstracted apps that we use

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Speaker 5: to order our basic necessities like eating and things like that.

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Speaker 5: It worries me in sort of like a fantasy dystopic way.

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Speaker 5: What happens when people suddenly don't use that after getting

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Speaker 5: used to using it, Like what are they going to know?

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Speaker 5: Are they going to know how to operate a door

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Speaker 5: dash app? Are they going to know how to book

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Speaker 5: a flight? That kind of thing.

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Speaker 1: Yeah, it is kind of because one of the things

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Speaker 1: there was a c neet review that said, like, well,

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Speaker 1: the potential of this is that it completely removes physical

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Speaker 1: use of a device. So you're using these apps, but

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Speaker 1: they're just a part of your life. Uber's just a

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Speaker 1: thing you talk to. You never look at anything when

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Speaker 1: you do it, And like, is that better? Like I

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Speaker 1: don't like the idea that you basically have a robot

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Speaker 1: that you treat as like your nanny that plans your

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Speaker 1: life for you. Like the amount of hype over there

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Speaker 1: will be a more concerted piece about this coming out.

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Speaker 1: But the first thing I thought when I looked at

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Speaker 1: all these guys talking about how cool it was to

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Speaker 1: be able to just tell a robot to book your

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Speaker 1: flight and plan your travel and book your hotels for you.

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Speaker 1: That's like part of the experience of traveling, and like

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Speaker 1: choosing things to do is like one of the things

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Speaker 1: that traveling is, and the desire so many people have

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Speaker 1: to hand off elements of choice really reminds me of

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Speaker 1: like cult dynamics, And I don't think this is a

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Speaker 1: consumer thing. I think this is specifically a weird subculture

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Speaker 1: of tech people of AI people, a lot of the

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Speaker 1: same folks who got into NFTs. But this desire, like

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Speaker 1: life is so complex and scary, I want to hand

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Speaker 1: over all of my agency to a robot. It's the

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Speaker 1: same thing that is behind a lot of like why

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Speaker 1: people join cults. And I don't think this is a

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Speaker 1: pro societal problem, but I think it is a weird

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Speaker 1: problem with the group of people who are most excited

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Speaker 1: to have a fucking rabbit.

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Speaker 5: It seems like a sad thing to me that folks

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Speaker 5: might only attend bars or restaurants that are rated like

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Speaker 5: four point five and above that's decided by something else. Yeah,

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Speaker 5: and they don't get to have this like experience of

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Speaker 5: walking into like the sedious bar you've ever seen in

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Speaker 5: your life and have like maybe possibly like a life

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Speaker 5: changing experience.

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Speaker 2: I was just in South Korea and we went to

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Speaker 2: this fried chicken place that ended up being close actually

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Speaker 2: was like we opened, but nobody was there, which made

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Speaker 2: me just want to leave before getting killed. And so

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Speaker 2: I just went to a random chicken place across the

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Speaker 2: road from my hotel, and I thought, well, it'll feed me.

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Speaker 2: It was wonderful, it was delightful.

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Speaker 3: And it was I could not find any reviews for it.

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Speaker 2: It was just a flipping place, and I don't I

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Speaker 2: think these people who were desperate for a device like this,

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Speaker 2: this kind of weird nanny device. First of all, I

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Speaker 2: don't think they think about the practicalities of this. I

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Speaker 2: don't think this is quicker or easier or better. But

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Speaker 2: also they're like, oh, I wish I could just say

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Speaker 2: one thing and all of these things could happen for me.

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Speaker 2: Same people, by the way, who were saying that people

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Speaker 2: need to pull themselves up by their bootstraps and do

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Speaker 2: things for themselves. It's just I don't know if they'd

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Speaker 2: even call it the stopian. It's just weird and sad

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Speaker 2: to me.

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Speaker 1: Speaking of weird and sad, We're going to move on

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Speaker 1: to the next product in a second, but first I

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Speaker 1: gotta play everybody, in case you haven't seen it or

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Speaker 1: heard it, the CEO of Rabbit trying to rickroll the

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Speaker 1: audience with his Hell device. Have you seen this, Garrison? Oh? Okay,

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Speaker 1: eyes on the screen. Everybody to activate the eye, just

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Speaker 1: double tap the button. Oh funny seeing you here, Rick.

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Speaker 6: Let me take a look. You're never gonna give you up.

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Speaker 6: Enjoy it?

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Speaker 3: What am I getting rickrolled?

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Speaker 2: In my own?

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Speaker 3: Kenots. Let's move on to the next one.

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Speaker 2: All right, I have a question real quick. So what

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Speaker 2: is the functionality he just activated? Is it that you

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Speaker 2: just put you point the eye at something and it

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Speaker 2: chooses an Actually the.

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Speaker 1: I automatically see Rick Astley and choose to play one

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Speaker 1: specific song of his, Because that actually doesn't seem like

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Speaker 1: a feature. That seems like a bug.

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Speaker 2: Yeah, that seems like what happens if it sees certain people.

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Speaker 1: Yeah, Jeffrey Epstein, Yeah, what happens if it sees Jeffrey Yeah,

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Speaker 1: plays children screaming like what is how is this thing work?

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Speaker 2: Booking trips to Florida.

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Speaker 1: I maybe it's respectable that they showed how bad the

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Speaker 1: lag is because that moment where there's quiet after he

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Speaker 1: like clicks on, it is like it's loading, it's processing

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Speaker 1: for a considerable period of time, and.

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Speaker 2: It's just Also I feel for the bloke because I

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Speaker 2: know he was probably so excited to do this and

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Speaker 2: he's like, I'm going to be Steve Jobs. But man,

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Speaker 2: when you can't perform, you don't perform, Like.

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Speaker 1: Yeah, that's bad delivery.

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Speaker 2: The did I just get Rick Rold in my own video?

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Speaker 2: It was like that I forget what the movie's Oh

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Speaker 2: hi mock.

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Speaker 1: Yeah, it is and obviously like English is the reverse language,

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Speaker 1: but like it's a performance. You like you practice, right,

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Speaker 1: you get coached and stuff because you're trying to represent

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Speaker 1: your company.

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Speaker 2: Oh I tell you this from experiences I've run a

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Speaker 2: the off. Yeah, that guy actually did practice because all

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Speaker 2: of that was He's actual timing wasn't bad. He just

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Speaker 2: does not have that dog in him.

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Speaker 1: Yeah. Yeah, you bring in other people to do like that. Anyway, everybody, anyone,

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Speaker 1: anyone's mind on the rabbit changed having seen that. Absolutely

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Speaker 1: not Garrison has a look on their face.

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Speaker 4: No, it's just like what I've always wanted in a

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Speaker 4: tech gadget is be able to point at three to

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Speaker 4: sixty five degree camera at a picture of a musician

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Speaker 4: and then wait thirty seconds and then have an AI

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Speaker 4: pick a random song of theirs. That's always what I

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Speaker 4: wanted for the future.

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Speaker 1: Yeah, yeah, that's that's the dream of fucking Archimedes had.

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Speaker 4: That's right.

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Speaker 1: It was when he was building his laser that we

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Speaker 1: all saw in the most recent Indiana Jones film. Speaking

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Speaker 1: of the most recent Indiana Jones film, this podcast is

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Speaker 1: entirely sponsored by that movie. So here's some other ads.

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Speaker 4: Why are we giving free advertising to Disney.

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Speaker 3: Why are we.

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Speaker 1: Why because that movie was so close to being worth it.

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Speaker 1: That last twenty minutested no Nazis machine gunning Roman legionnaires

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Speaker 1: pretty funny.

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Speaker 4: Well, do you know who would have loved the s

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Speaker 4: our Comedies? Probably? Yes, he probably would have would have

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Speaker 4: had a great time. What what Nextarrison? The product do

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Speaker 4: we want to talk about?

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Speaker 1: How about the pet one? Garrison? You saw that?

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Speaker 4: All right? So I think I think I think me

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Speaker 4: and Ed saw chat GPT for animals.

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Speaker 1: Oh yeah, damn it.

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Speaker 4: Which is not really what it is saying. It's like

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Speaker 4: it scans a picture of your dog and then tries

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Speaker 4: to tell you if it has any health problem. It's

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Speaker 4: based on that picture. It's it's. It's You're not You're

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Speaker 4: not actually talking to your dog or anything. It just

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Speaker 4: it takes pictures of animals and then it analyzes it

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Speaker 4: to tell you how the dog is feeling. Blah blah

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Speaker 4: blah blah blah. It's it's. I saw a product like

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Speaker 4: this earlier at CES. I saw a product. I saw

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Speaker 4: a product like this last year. They're just calling it

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Speaker 4: chat GPT because it's an AI name. It's it's it's

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Speaker 4: it's it's.

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Speaker 1: It's hip like because people people, they're hoping that that

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Speaker 1: will make people spend money up.

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Speaker 2: It was every ces I see something that begins to

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Speaker 2: make me disassociate and I walk I walked past there

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Speaker 2: and Blovo the chat GPT for and my brain was

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Speaker 2: just like, could she just like start like glitching out?

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Speaker 2: And then when I went to look it up as

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Speaker 2: Garrison did, I was so disappointed because I hope that

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Speaker 2: these would just crackpots are like, yep, you put the

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Speaker 2: microphone to your dog. Now you know your dog's saying

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Speaker 2: that I would respect even if it didn't work, just

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Speaker 2: if you're like, yeah, fuck it. Yeah, your cat's said

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Speaker 2: he hates here. Your cat's been radicalized them Afraight.

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Speaker 1: See, there's a fun product in here, which is you

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Speaker 1: sell to Rubes and a product that you're like it

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Speaker 1: translates your dog's micro expressions into language. And then the

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Speaker 1: actual paying customers are sickos like us, and you just

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Speaker 1: take control of somebody's pets voice.

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Speaker 4: That would be so cool.

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Speaker 1: You can have their like yeah, your cat's racist, now

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Speaker 1: your dog's are Nazi like.

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Speaker 4: This is this is the perfect product for HP. Lovecraft

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Speaker 4: would have loved this.

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Speaker 2: No, if you gave me like the show light to me,

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Speaker 2: but for dogs on my phone, I would spend whatever

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Speaker 2: you want A thousand dollars, I will geah.

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Speaker 1: I wouldn't pay like average West Coast rent prices to

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Speaker 1: be able to like gaslight some family into thinking their

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Speaker 1: dog is a terrorist.

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Speaker 2: See a friend of mine, Oh, what's what's wrong? Ed

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Speaker 2: chat GPT said the I said that my dogs joined

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Speaker 2: ISIS and I don't know. I don't know how he

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Speaker 2: did it, but he's been He's talking about a caliphate

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Speaker 2: according to the app. I don't know what this app

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Speaker 2: is bankrupting me. I paid four and a half thousand

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Speaker 2: dollars for this app a month.

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Speaker 3: I don't know why I need it.

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Speaker 4: So because so I unfortunately had to miss yesterday. So

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Speaker 4: there was probably an endless number of tech innovations that

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Speaker 4: I was unable to see because I had to miss

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Speaker 4: one day. But with the help of penicil and I

399
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Speaker 4: was able to return today to do one final.

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Speaker 1: Chat GPT of antibiotics.

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00:19:37,400 --> 00:19:40,520
Speaker 4: That's that is exactly what my doctor said. Actually, but

402
00:19:40,840 --> 00:19:43,240
Speaker 4: I did. I did swear revenge on cees. So I

403
00:19:43,280 --> 00:19:48,000
Speaker 4: just walked around most mostly mostly the Venetian just seeing

404
00:19:48,080 --> 00:19:50,280
Speaker 4: all of the worst things I could find in documenting

405
00:19:50,359 --> 00:19:53,679
Speaker 4: them so I could get revenge from that twink poisoning

406
00:19:53,760 --> 00:19:57,240
Speaker 4: me with strap throat. So the first really good thing

407
00:19:57,480 --> 00:20:00,840
Speaker 4: is this. I mostly walked around the award winning sections

408
00:20:00,880 --> 00:20:04,320
Speaker 4: because that's where you find only the best. There was

409
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Speaker 4: an award winning speaker called Audio Cu that all of

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Speaker 4: their marketing was built from this horrible, horrible uh Ai

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Speaker 4: image generation of this like extremely busty blonde woman in

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Speaker 4: a latex suit, but if you zoom it onto her fingernails,

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Speaker 4: her her fingernails are like sticking through the wrong side

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Speaker 4: of her fingers.

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Speaker 3: There, my god, oh my god.

416
00:20:29,800 --> 00:20:35,080
Speaker 2: It's the woman's from that one movie for oh damn it,

417
00:20:35,240 --> 00:20:37,520
Speaker 2: not skin the one. The other it was the woman

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00:20:37,560 --> 00:20:39,480
Speaker 2: where the alien was sexy and then she killed people

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00:20:39,480 --> 00:20:43,000
Speaker 2: when she had sex with them. It's the same thing, Yes, terrifying. Yes,

420
00:20:43,480 --> 00:20:45,560
Speaker 2: rita's cool in and say what that is?

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00:20:46,359 --> 00:20:49,080
Speaker 4: Yeah, it looks just like that. It says relaxed, stick

422
00:20:49,119 --> 00:20:51,439
Speaker 4: it in, which is pretty funny. So that that was

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00:20:51,480 --> 00:20:52,080
Speaker 4: pretty bad.

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Speaker 1: Now I respect that. I respect That's that's a baller

425
00:20:57,840 --> 00:20:58,520
Speaker 1: move right there.

426
00:21:00,080 --> 00:21:02,879
Speaker 4: Again. This is this is for a speaker company like.

427
00:21:02,960 --> 00:21:06,399
Speaker 5: DJ Girlfriend in the shape it's a speaker in the

428
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Speaker 5: shape of a girlfriend.

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Speaker 4: No, it's just home theater speakers.

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Speaker 1: It just have a horrible AI generated woman as their spokesperson.

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Speaker 5: I mean I would buy it if it was DJ Girlfriend. Though.

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Speaker 1: DJ Girlfriend is a great idea for a product and

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Speaker 1: might stop several shows.

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Speaker 3: AI has brought back sexism.

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00:21:22,840 --> 00:21:26,239
Speaker 1: If you do DJ girlfriend right, you could stop at

436
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Speaker 1: least one mass shooting.

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Speaker 5: Finally, we have a real solution now.

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Speaker 4: Another product that won the CEES twenty twenty four Innovation

439
00:21:33,440 --> 00:21:39,199
Speaker 4: Awards is an AI powered coffee brewer and grinder system.

440
00:21:39,040 --> 00:21:42,560
Speaker 4: I'm just gonna read the description from Coffee's been missing,

441
00:21:42,760 --> 00:21:46,080
Speaker 4: That's right. I know we wake up every morning make

442
00:21:46,119 --> 00:21:48,200
Speaker 4: our little French press coffee. That's fine. But you know

443
00:21:48,240 --> 00:21:50,600
Speaker 4: what could be better? An AI system that does it

444
00:21:50,640 --> 00:21:54,560
Speaker 4: for you. I'm going to read the award the award

445
00:21:54,800 --> 00:21:59,320
Speaker 4: description for this product. Okay, introducing Barista Brew Coffee Brewer

446
00:21:59,359 --> 00:22:03,240
Speaker 4: and Grinders System, a smart coffee system that tailors your

447
00:22:03,320 --> 00:22:07,919
Speaker 4: brew to perfection with AI guided personalization. Easily adjust brewing

448
00:22:07,960 --> 00:22:11,560
Speaker 4: parameters for a custom cup. New expertise needed rate to

449
00:22:11,680 --> 00:22:15,840
Speaker 4: track and refine your bruise brew iq AI suggestions for

450
00:22:15,880 --> 00:22:20,280
Speaker 4: your ideal taste, simplify with one touch favorites, elevate your

451
00:22:20,320 --> 00:22:21,359
Speaker 4: coffee experience.

452
00:22:22,320 --> 00:22:23,879
Speaker 2: Yeah, well, I hear all that. The one thing I

453
00:22:23,960 --> 00:22:27,719
Speaker 2: think is simplify. That's that's simple. The Movie's Spacies, by

454
00:22:27,720 --> 00:22:29,440
Speaker 2: the way, I.

455
00:22:29,440 --> 00:22:31,960
Speaker 4: Love that movie. One of one of one of the

456
00:22:32,000 --> 00:22:34,560
Speaker 4: best hr Geiger art utilizations.

457
00:22:34,720 --> 00:22:37,800
Speaker 1: Yeah yeah, and easily the horniest movie of the nineteen nineties.

458
00:22:37,960 --> 00:22:38,879
Speaker 1: Like this, which is a lot of.

459
00:22:39,040 --> 00:22:44,600
Speaker 4: Which is which is a high high bar, so on on.

460
00:22:44,600 --> 00:22:46,960
Speaker 4: On this AI coffee maker on the front, there's a

461
00:22:47,040 --> 00:22:49,920
Speaker 4: little control panel with nine different settings that you can

462
00:22:50,080 --> 00:22:52,679
Speaker 4: you can change because they're all in a graph. We

463
00:22:52,720 --> 00:22:59,240
Speaker 4: have we have citrus, spice, nutty, fruity, balanced, cocoa, floral, herbal,

464
00:22:59,480 --> 00:23:02,960
Speaker 4: and honey. So you can you can with your with

465
00:23:03,000 --> 00:23:05,560
Speaker 4: the with the ease of a touchpad, start to customize

466
00:23:05,600 --> 00:23:08,480
Speaker 4: your own AI coffee. So that that is revolutionary. I'm

467
00:23:08,480 --> 00:23:10,280
Speaker 4: going to be getting one for Robert this Christmas.

468
00:23:10,280 --> 00:23:12,760
Speaker 1: Thank you, Garrison. I know I've always thought, you know,

469
00:23:12,800 --> 00:23:17,399
Speaker 1: what I hate is the experience of exploring new flavors

470
00:23:17,400 --> 00:23:21,480
Speaker 1: on my own and learning new ways of brewing coffee,

471
00:23:21,480 --> 00:23:23,960
Speaker 1: a beverage I consume every day. So I'm glad to

472
00:23:24,000 --> 00:23:26,480
Speaker 1: be handing that whole experience off to a machine.

473
00:23:26,560 --> 00:23:29,160
Speaker 4: That's right, And I know a lot of people used.

474
00:23:29,760 --> 00:23:32,560
Speaker 1: Tavia just brought something up that I think is relevant here.

475
00:23:33,560 --> 00:23:36,240
Speaker 5: It's a Guardian article about an AI smoothie shop that

476
00:23:36,280 --> 00:23:39,800
Speaker 5: opened in San Francisco well before ce S. That is

477
00:23:40,040 --> 00:23:42,960
Speaker 5: a combination of uh it's being driven forward with AI

478
00:23:43,080 --> 00:23:46,280
Speaker 5: technology as well as five G stuff that I think

479
00:23:46,359 --> 00:23:48,640
Speaker 5: had opened up and then like three weeks later had

480
00:23:48,640 --> 00:23:49,200
Speaker 5: shut down.

481
00:23:49,520 --> 00:23:52,040
Speaker 1: Oh that's too They were like, a robot will pick

482
00:23:52,080 --> 00:23:53,560
Speaker 1: the perfect smoothie for you.

483
00:23:53,960 --> 00:23:56,440
Speaker 2: Well, I actually want to bring work. I want to

484
00:23:56,440 --> 00:24:00,360
Speaker 2: bring something up. So I love smoking me I pelosmokers

485
00:24:00,359 --> 00:24:02,720
Speaker 2: at home. And I saw a few times on this

486
00:24:02,800 --> 00:24:05,960
Speaker 2: show AI grills and I just looked up one called

487
00:24:06,520 --> 00:24:09,320
Speaker 2: a brisk It smart grill, and I was like, how

488
00:24:09,320 --> 00:24:12,920
Speaker 2: could you possibly make a thing which is basically maintaining

489
00:24:12,960 --> 00:24:15,720
Speaker 2: hot air in a tube long enough until the food's done?

490
00:24:15,720 --> 00:24:17,560
Speaker 2: And what it is is it has a thing. You

491
00:24:17,560 --> 00:24:20,480
Speaker 2: can ask the grill what seasoning should I add to

492
00:24:20,480 --> 00:24:22,879
Speaker 2: make my chicken skew a spicy or how do I

493
00:24:22,920 --> 00:24:25,399
Speaker 2: see a medium rest eak? I don't fucking know. Why

494
00:24:25,440 --> 00:24:26,679
Speaker 2: don't you learn to cook.

495
00:24:26,440 --> 00:24:30,640
Speaker 1: You twat, it's just like.

496
00:24:32,200 --> 00:24:35,679
Speaker 2: The enjoyable part of cooking is the experimentation and learning taste.

497
00:24:35,680 --> 00:24:39,040
Speaker 2: But no, thank you, just like that goddamn coffee thing. Oh,

498
00:24:39,080 --> 00:24:41,280
Speaker 2: I don't want to learn anything. I don't want to

499
00:24:41,280 --> 00:24:42,359
Speaker 2: have a human experience.

500
00:24:42,840 --> 00:24:45,160
Speaker 5: That's the thing with a lot of these AI solutions,

501
00:24:45,200 --> 00:24:47,639
Speaker 5: will call them, is I feel like they're robbing people

502
00:24:47,640 --> 00:24:49,080
Speaker 5: of real experiences.

503
00:24:49,359 --> 00:24:53,359
Speaker 1: Yeah, for like no bit, Like there's some stuff that like,

504
00:24:53,680 --> 00:24:56,960
Speaker 1: you know, the ability of a smartphone to once you

505
00:24:57,080 --> 00:24:59,239
Speaker 1: had to be like in a building in order to

506
00:24:59,280 --> 00:25:01,840
Speaker 1: like access a phone or like use a payphone. Now

507
00:25:01,840 --> 00:25:04,920
Speaker 1: you can connect with people everywhere. That's that's a clear benefit, right,

508
00:25:05,119 --> 00:25:07,920
Speaker 1: there's downsides to it, obviously, but it's a clear benefit.

509
00:25:08,240 --> 00:25:11,080
Speaker 1: But like now you don't have to learn. Now, now

510
00:25:11,080 --> 00:25:13,199
Speaker 1: you don't have to cook. You can let a robot

511
00:25:13,240 --> 00:25:17,400
Speaker 1: do it for you. It's like, well, but why cooking

512
00:25:17,520 --> 00:25:19,960
Speaker 1: is pleasurable? And if I don't want to cook, I

513
00:25:20,000 --> 00:25:22,480
Speaker 1: will go to a restaurant or order food, and it's

514
00:25:22,560 --> 00:25:25,600
Speaker 1: cheaper than buying several thousand dollars AI device.

515
00:25:25,720 --> 00:25:29,040
Speaker 4: I mean, some things are hard to learn, which brings

516
00:25:29,080 --> 00:25:30,280
Speaker 4: me to the next product.

517
00:25:29,960 --> 00:25:30,600
Speaker 3: That's smoking me.

518
00:25:30,840 --> 00:25:34,120
Speaker 1: But hard word.

519
00:25:34,160 --> 00:25:36,360
Speaker 4: Kind of like like like.

520
00:25:36,400 --> 00:25:39,760
Speaker 7: Parenting, right, so good, okay, nice, you know what, Garrison,

521
00:25:39,760 --> 00:25:41,480
Speaker 7: I'm proud of you. That was a good SEXUA so

522
00:25:42,040 --> 00:25:46,080
Speaker 7: AI parenting, especially with your infant child. This was also

523
00:25:46,240 --> 00:25:49,000
Speaker 7: in the CEES Awards section, so you know it's going

524
00:25:49,040 --> 00:25:51,399
Speaker 7: to be legit. I was able to see an demonstration

525
00:25:51,480 --> 00:25:54,560
Speaker 7: of an AI baby crib that will shake your baby

526
00:25:54,680 --> 00:25:58,919
Speaker 7: up and down based on facial expression analysis done by

527
00:25:58,960 --> 00:25:59,399
Speaker 7: an AI.

528
00:26:00,359 --> 00:26:02,359
Speaker 4: Yeah, that's what you do is I'm gonna show you

529
00:26:02,400 --> 00:26:05,479
Speaker 4: show it here. So here is the cutting edge facial

530
00:26:05,480 --> 00:26:08,760
Speaker 4: expressions we have anger discussed fear, happiness, sadness, and surprise,

531
00:26:09,320 --> 00:26:13,520
Speaker 4: and that basically that data will go into this little

532
00:26:13,600 --> 00:26:15,880
Speaker 4: crib which will start shaking and moving up and down

533
00:26:15,920 --> 00:26:17,920
Speaker 4: based on what they skin on your baby's face.

534
00:26:18,280 --> 00:26:21,399
Speaker 2: So to be clear, there is a product snow that

535
00:26:21,520 --> 00:26:25,440
Speaker 2: exists where it drop my phone there. There's a product

536
00:26:25,440 --> 00:26:28,040
Speaker 2: called the Snow which is like a for infants and

537
00:26:28,080 --> 00:26:30,000
Speaker 2: it notices when they're fussing and it kind of like

538
00:26:30,040 --> 00:26:32,520
Speaker 2: lightly rocks them, but the way it rocks them is

539
00:26:32,560 --> 00:26:35,719
Speaker 2: so very light. It is very much a This is

540
00:26:35,960 --> 00:26:37,800
Speaker 2: this is what a mother would do with a brand

541
00:26:37,840 --> 00:26:40,800
Speaker 2: new baby, freshly baked. You don't want to move into much.

542
00:26:41,000 --> 00:26:43,760
Speaker 2: That one has like six pictures from the intro of

543
00:26:43,840 --> 00:26:47,720
Speaker 2: light to me and a heart rate monitor, and it's like, yeah,

544
00:26:47,960 --> 00:26:49,840
Speaker 2: hand over your baby to AI.

545
00:26:50,480 --> 00:26:50,800
Speaker 3: Great.

546
00:26:51,920 --> 00:26:54,600
Speaker 5: Yeah, this product looks like a baby Morocca the pace

547
00:26:54,760 --> 00:26:56,720
Speaker 5: that you've shaken it, which is dependent on what pretty

548
00:26:56,760 --> 00:26:57,960
Speaker 5: much you make pretty much.

549
00:26:58,040 --> 00:26:58,200
Speaker 4: Well.

550
00:26:58,200 --> 00:27:01,359
Speaker 1: I love it also because like a real scandal I

551
00:27:01,359 --> 00:27:03,280
Speaker 1: think from the I think it was in the eighties,

552
00:27:03,400 --> 00:27:08,719
Speaker 1: is like Nanny's shaking babies to death, like the idea

553
00:27:08,760 --> 00:27:12,119
Speaker 1: that like again a machine that can only go at

554
00:27:12,160 --> 00:27:13,760
Speaker 1: a certain pace that's very light.

555
00:27:14,720 --> 00:27:14,919
Speaker 8: You know.

556
00:27:14,960 --> 00:27:16,720
Speaker 1: I get that's a labor stave, especially for like a

557
00:27:16,760 --> 00:27:19,119
Speaker 1: single parent or whatnot. Like you know, some some people

558
00:27:19,160 --> 00:27:24,399
Speaker 1: will need that. But I just worry. I worry that

559
00:27:24,440 --> 00:27:26,440
Speaker 1: we're not all that far from our first and AI

560
00:27:26,600 --> 00:27:27,800
Speaker 1: killed my baby.

561
00:27:27,600 --> 00:27:29,400
Speaker 4: You know, I think I think that. I I think

562
00:27:29,400 --> 00:27:31,600
Speaker 4: the real beauty of this product is usually when you

563
00:27:31,600 --> 00:27:33,080
Speaker 4: have a newber, maybe you have to like watch it

564
00:27:33,119 --> 00:27:34,560
Speaker 4: all night becas it'll wake up, you have to like

565
00:27:34,600 --> 00:27:36,400
Speaker 4: pick it up, pat it, make sure it gets back

566
00:27:36,400 --> 00:27:38,240
Speaker 4: to sleep. You can just leave that baby in the bed.

567
00:27:38,320 --> 00:27:40,320
Speaker 4: You can you can like go to the club. Yeah,

568
00:27:40,440 --> 00:27:42,560
Speaker 4: just leave the baby in the bed. If it starts crying,

569
00:27:42,640 --> 00:27:45,320
Speaker 4: don't worry. The AI will take the will take over.

570
00:27:45,440 --> 00:27:47,840
Speaker 1: We are on the verge of beds that can raise

571
00:27:47,840 --> 00:27:50,040
Speaker 1: our children, just like the Venture Brothers.

572
00:27:50,160 --> 00:27:54,159
Speaker 4: That's right, and and those and those kids turned out fine,

573
00:27:54,880 --> 00:28:02,159
Speaker 4: they turned out great, perfect, But I think luckily, luckily

574
00:28:02,280 --> 00:28:04,360
Speaker 4: for you, because I know none of us are babies anymore.

575
00:28:04,400 --> 00:28:10,399
Speaker 4: But we are all you know, eventually going to get old, hopefully, hopefully,

576
00:28:11,200 --> 00:28:14,320
Speaker 4: And there is air products that will also assist us

577
00:28:14,359 --> 00:28:17,360
Speaker 4: as we get older using the same AI baby tech.

578
00:28:17,359 --> 00:28:17,560
Speaker 3: Here.

579
00:28:17,920 --> 00:28:19,479
Speaker 4: One of the one of the one of the places

580
00:28:19,480 --> 00:28:22,720
Speaker 4: that me and Robert stopped by was called Blue Sky AI.

581
00:28:22,760 --> 00:28:28,200
Speaker 4: It's spelled ridiculously offensively, and they refused to do an interview.

582
00:28:28,320 --> 00:28:30,440
Speaker 1: They were not happy.

583
00:28:32,080 --> 00:28:35,600
Speaker 4: But I was able to get a pamphlet and they

584
00:28:35,600 --> 00:28:37,920
Speaker 4: have an AI that I think they're mostly targeted to

585
00:28:37,960 --> 00:28:41,440
Speaker 4: get at like older people. But quote by comparing the

586
00:28:41,480 --> 00:28:44,520
Speaker 4: way your facial and vocal behavior changes over time, using

587
00:28:44,520 --> 00:28:47,560
Speaker 4: your facial expressions, facial muscle actions, as well as where

588
00:28:47,600 --> 00:28:49,880
Speaker 4: you are looking, your body posts, and the tone of

589
00:28:49,880 --> 00:28:52,400
Speaker 4: your voice, we have the potential to identify and monitor

590
00:28:52,480 --> 00:28:55,120
Speaker 4: all kinds of medical conditions that manifest in the face

591
00:28:55,240 --> 00:28:59,240
Speaker 4: or voice, So it's it's a facial scanning and voice

592
00:28:59,280 --> 00:29:02,320
Speaker 4: scanning uses AI to try to diagnose you with medical

593
00:29:02,360 --> 00:29:06,840
Speaker 4: conditions specific specifically, the guy told us that it's it's

594
00:29:06,920 --> 00:29:09,400
Speaker 4: useful for Alzheimer's. Then he realized we were journalists and

595
00:29:09,400 --> 00:29:12,959
Speaker 4: the nasses to go away.

596
00:29:14,000 --> 00:29:17,120
Speaker 1: It also, but yeah, that's how you know you've got

597
00:29:17,120 --> 00:29:19,120
Speaker 1: a good medical device.

598
00:29:18,840 --> 00:29:23,080
Speaker 4: A good product. At CES Blue Sky uses a continuous

599
00:29:23,120 --> 00:29:28,560
Speaker 4: approach apparent valiance and arousal to measure to measure expressed emotion.

600
00:29:28,960 --> 00:29:31,600
Speaker 4: This better fits the real human experience of emotional states.

601
00:29:31,720 --> 00:29:34,680
Speaker 4: This approach allows emotion regions to be defined and to

602
00:29:34,680 --> 00:29:38,040
Speaker 4: measure the transitions away from and towards these regions. This

603
00:29:38,080 --> 00:29:41,000
Speaker 4: continuous approach, where appropriate, can be mapped back to a

604
00:29:41,040 --> 00:29:46,160
Speaker 4: much less exact categorical representation. For example, excited, calm or angry?

605
00:29:46,800 --> 00:29:47,640
Speaker 5: Did he have horny?

606
00:29:48,160 --> 00:29:50,440
Speaker 4: They do not have horny, not that I can see.

607
00:29:50,480 --> 00:29:53,600
Speaker 1: Look, if you know old people, one thing they never

608
00:29:53,720 --> 00:29:54,800
Speaker 1: stop doing is fun.

609
00:29:54,840 --> 00:29:58,480
Speaker 4: Now, they do have a list of all human emotions

610
00:29:58,520 --> 00:30:01,920
Speaker 4: here that char you turn it on a map. Finally

611
00:30:02,200 --> 00:30:05,440
Speaker 4: that using AI, we can finally figure out what emotions

612
00:30:05,440 --> 00:30:07,800
Speaker 4: you're feeling based on your face, so you can use

613
00:30:07,800 --> 00:30:10,240
Speaker 4: this just with your with your phone camera, with your

614
00:30:10,480 --> 00:30:13,760
Speaker 4: with your iPad camera. They do data collection, data analysis.

615
00:30:14,080 --> 00:30:16,040
Speaker 4: One of the weird use cases that we saw was,

616
00:30:16,520 --> 00:30:19,160
Speaker 4: I know we saw something similar to this already, but

617
00:30:19,520 --> 00:30:21,880
Speaker 4: just scanning your face when driving to tell you how

618
00:30:21,920 --> 00:30:24,000
Speaker 4: you're feeling, which is just quite fun.

619
00:30:24,160 --> 00:30:26,520
Speaker 1: Yeah, it's a I could talk about that a second.

620
00:30:26,520 --> 00:30:28,640
Speaker 1: What this reminds me of there was a product a

621
00:30:28,640 --> 00:30:31,400
Speaker 1: few years ago. It was like a robot for the military,

622
00:30:31,440 --> 00:30:34,280
Speaker 1: and the idea was this robot can run in dangerous

623
00:30:34,320 --> 00:30:36,400
Speaker 1: situations and pick up troops that have been injured and

624
00:30:36,480 --> 00:30:38,600
Speaker 1: run them out, which is probably a thing that will

625
00:30:38,600 --> 00:30:40,880
Speaker 1: exist at some point and might even save lives. Right,

626
00:30:40,920 --> 00:30:42,280
Speaker 1: I can see how that would be a useful thing

627
00:30:42,280 --> 00:30:44,480
Speaker 1: in the military can be very dangerous to retrieve people.

628
00:30:44,720 --> 00:30:46,920
Speaker 1: Much better for a robot to get shot or blown

629
00:30:46,960 --> 00:30:50,200
Speaker 1: up in that situation than another person. But to try

630
00:30:50,240 --> 00:30:53,600
Speaker 1: and comfort the soldiers, they gave the robot the head

631
00:30:53,600 --> 00:30:56,560
Speaker 1: of a Teddy Bear, like a metal Teddy Bear head.

632
00:30:57,160 --> 00:31:01,200
Speaker 1: It looked like a fucking nightmare. It's just like, what

633
00:31:01,200 --> 00:31:04,360
Speaker 1: what do you think did you talk to There's all

634
00:31:04,440 --> 00:31:06,720
Speaker 1: sorts of guys who have been shot in combat. Did

635
00:31:06,760 --> 00:31:08,800
Speaker 1: you talk to one of them? Did you go with

636
00:31:08,920 --> 00:31:11,920
Speaker 1: the experience of having your arm blown off? Corporal have

637
00:31:12,040 --> 00:31:15,640
Speaker 1: been more pleasurable if a giant metal teddy bear it.

638
00:31:16,080 --> 00:31:18,040
Speaker 2: So my first job was working on the characters and

639
00:31:18,040 --> 00:31:23,440
Speaker 2: twisted metal, but then I moved into robotics. It's so

640
00:31:23,640 --> 00:31:28,240
Speaker 2: cool that how many of these products are very clearly made, funded, prototyped,

641
00:31:28,440 --> 00:31:31,600
Speaker 2: r and D, hired PR teams. Everyone's done these big

642
00:31:31,640 --> 00:31:34,320
Speaker 2: presentations without talking to a single fucking human being.

643
00:31:34,720 --> 00:31:35,640
Speaker 3: It's so cool.

644
00:31:35,920 --> 00:31:38,400
Speaker 2: It's so cool how much waste there is at this

645
00:31:38,520 --> 00:31:42,240
Speaker 2: show where not a single human soul there is a

646
00:31:42,280 --> 00:31:46,240
Speaker 2: completely different subject. There was like an AI powered nail

647
00:31:46,280 --> 00:31:49,440
Speaker 2: salon thing as well. I saw, and I'm like, that's

648
00:31:49,480 --> 00:31:52,600
Speaker 2: definitely one where you didn't talk to talk to any

649
00:31:52,640 --> 00:32:00,200
Speaker 2: woman though. Yeah, first and foremost in my experience, one

650
00:32:00,280 --> 00:32:02,280
Speaker 2: is scared of a new nail place for fucking up

651
00:32:02,320 --> 00:32:05,120
Speaker 2: their hands. So are they going to spend eight hundred

652
00:32:05,200 --> 00:32:07,880
Speaker 2: goddamn dollars on this thing to maybe get burned? And

653
00:32:07,920 --> 00:32:10,440
Speaker 2: I saw in this article about it just now that

654
00:32:10,520 --> 00:32:12,400
Speaker 2: their thing they said was, oh, yeah, it's like an

655
00:32:12,480 --> 00:32:16,280
Speaker 2: espresso at home. I've had an espressos break multiple times,

656
00:32:16,960 --> 00:32:18,920
Speaker 2: and I realized it may sound weird. How can you

657
00:32:18,920 --> 00:32:21,040
Speaker 2: break an espresso? I'm just built different.

658
00:32:21,240 --> 00:32:23,080
Speaker 1: But if I can break it in just like me

659
00:32:23,160 --> 00:32:26,480
Speaker 1: and strep throat, unbelievable.

660
00:32:27,560 --> 00:32:30,200
Speaker 4: So I do have one more product, and then I'm and.

661
00:32:30,240 --> 00:32:32,880
Speaker 1: Well, first, Garrison, I know you have one more product,

662
00:32:32,960 --> 00:32:47,360
Speaker 1: but we also have one more ad break. Ah, we're back, Garrison.

663
00:32:47,600 --> 00:32:48,640
Speaker 1: What's your next product?

664
00:32:48,760 --> 00:32:52,200
Speaker 4: So we already talked about the Handy, which is you know,

665
00:32:52,240 --> 00:32:56,440
Speaker 4: like sure did, which is by all accounts actually like

666
00:32:56,840 --> 00:32:57,760
Speaker 4: works as intended.

667
00:32:57,840 --> 00:33:00,480
Speaker 1: It's a good product. The people, the PR people, and

668
00:33:00,520 --> 00:33:03,320
Speaker 1: we talked to the CEO. We're not just knowledgeable, but

669
00:33:03,520 --> 00:33:07,000
Speaker 1: like remarkably good at keeping a straight face while talking

670
00:33:07,040 --> 00:33:10,240
Speaker 1: about their jack Well, that's professionalism. You have to respect it.

671
00:33:10,600 --> 00:33:13,200
Speaker 5: Honestly, that was the most professional booth I saw the

672
00:33:13,360 --> 00:33:15,640
Speaker 5: entirety of cees. They were really on point.

673
00:33:15,960 --> 00:33:18,360
Speaker 1: If you are looking for a jack off machine, I

674
00:33:18,400 --> 00:33:20,680
Speaker 1: can't recommend anything more highly.

675
00:33:20,480 --> 00:33:24,040
Speaker 4: Well, Robert, except for our next product, which is an

676
00:33:24,080 --> 00:33:26,280
Speaker 4: AI power to jack off machine.

677
00:33:26,880 --> 00:33:27,680
Speaker 1: Thank god.

678
00:33:28,840 --> 00:33:32,240
Speaker 4: So this is called my Hixel. It is the first

679
00:33:32,480 --> 00:33:34,000
Speaker 4: it's the first app.

680
00:33:33,760 --> 00:33:37,120
Speaker 1: That's an appealing names that's a name that sounds like sex.

681
00:33:37,800 --> 00:33:42,480
Speaker 4: It is the first app for climax Control to incorporate AI.

682
00:33:43,200 --> 00:33:46,160
Speaker 4: Now I'm gonna I'm gonna read through their.

683
00:33:46,720 --> 00:33:49,400
Speaker 5: Really redefines edge technology. Huh.

684
00:33:49,600 --> 00:33:51,280
Speaker 1: I want to make a note before you get into it.

685
00:33:51,640 --> 00:33:53,400
Speaker 1: The thing that they're claiming this is useful for. There

686
00:33:53,400 --> 00:33:56,000
Speaker 1: are devices for and it is a real use case,

687
00:33:56,000 --> 00:33:59,200
Speaker 1: which is that like premature ejaculation, this is a serious

688
00:33:59,240 --> 00:34:01,080
Speaker 1: problem for a lot of it. It's like a quality

689
00:34:01,080 --> 00:34:04,920
Speaker 1: of life issue, right, like it stops people from feeling confident.

690
00:34:04,960 --> 00:34:08,600
Speaker 1: It's a serious problem. There are prosthetic devices people can

691
00:34:08,680 --> 00:34:13,440
Speaker 1: use to train themselves. That's fine, they already exist. This

692
00:34:13,600 --> 00:34:16,120
Speaker 1: is basically like what if an AI could teach you

693
00:34:16,200 --> 00:34:17,200
Speaker 1: how to come slower?

694
00:34:17,400 --> 00:34:23,120
Speaker 4: Yes, and we have a six step layout here describing

695
00:34:23,480 --> 00:34:27,080
Speaker 4: why why my hixel is right for you. For the

696
00:34:27,200 --> 00:34:32,239
Speaker 4: first step is secure and anonymonized data collection, so you

697
00:34:32,280 --> 00:34:35,080
Speaker 4: can get o good all of your coming data stored,

698
00:34:35,200 --> 00:34:36,800
Speaker 4: but don't worry, it's secure.

699
00:34:37,040 --> 00:34:37,279
Speaker 8: See.

700
00:34:37,320 --> 00:34:39,560
Speaker 1: My first question to that is why is data on

701
00:34:39,640 --> 00:34:42,240
Speaker 1: me masturbating being collected at all?

702
00:34:42,400 --> 00:34:45,000
Speaker 4: Well, it could be because they're putting it towards an

703
00:34:45,040 --> 00:34:47,799
Speaker 4: eight week training program.

704
00:34:49,000 --> 00:34:51,799
Speaker 2: No, So, first and foremost, one of the first things

705
00:34:51,800 --> 00:34:53,880
Speaker 2: on the website for this is just the words happy

706
00:34:53,920 --> 00:34:57,360
Speaker 2: sex here, save sixty dollars in my Hixel Control. But

707
00:34:57,520 --> 00:34:59,120
Speaker 2: happy sex here is going to be something I think

708
00:34:59,160 --> 00:35:01,719
Speaker 2: about for a while. But also it says it has

709
00:35:02,280 --> 00:35:05,720
Speaker 2: my Hixel Care and my Hixel Control, two different things,

710
00:35:05,719 --> 00:35:08,600
Speaker 2: and then my hicksl Academy, and sadly you can't click

711
00:35:08,640 --> 00:35:10,680
Speaker 2: on that because I've never wanted to know more about

712
00:35:11,040 --> 00:35:13,160
Speaker 2: what how much material could that be?

713
00:35:14,080 --> 00:35:16,160
Speaker 5: Unless a masturbation academy.

714
00:35:16,680 --> 00:35:18,680
Speaker 1: Yeah, I thought they just called that eton. I was

715
00:35:18,680 --> 00:35:19,960
Speaker 1: a British public school joke.

716
00:35:20,239 --> 00:35:22,400
Speaker 5: It's okay, I made an edging joke earlier and nobody

717
00:35:22,480 --> 00:35:22,799
Speaker 5: caught it.

718
00:35:23,840 --> 00:35:24,120
Speaker 3: Yeah.

719
00:35:24,280 --> 00:35:27,400
Speaker 2: I there's one thing the eating boys do and they

720
00:35:27,440 --> 00:35:28,400
Speaker 2: don't have sex.

721
00:35:29,120 --> 00:35:30,000
Speaker 1: No masturbation.

722
00:35:30,320 --> 00:35:30,520
Speaker 4: Yeah.

723
00:35:30,719 --> 00:35:31,239
Speaker 3: Sorry.

724
00:35:32,680 --> 00:35:34,799
Speaker 1: Part of what I hate about this is its name

725
00:35:34,920 --> 00:35:37,719
Speaker 1: is so clearly like trying to be respectful and like

726
00:35:37,840 --> 00:35:40,840
Speaker 1: respectable and a tech product name as opposed to like

727
00:35:40,880 --> 00:35:42,840
Speaker 1: one of the things that I respect about the Handy

728
00:35:42,840 --> 00:35:45,240
Speaker 1: people is they just went ahead and called it handy.

729
00:35:45,360 --> 00:35:47,680
Speaker 4: I mean it's weird because like some of their some

730
00:35:47,719 --> 00:35:51,080
Speaker 4: of their free merch were labeled with stuff like download

731
00:35:51,120 --> 00:35:58,440
Speaker 4: the app to control your loads, we bring the game,

732
00:35:58,640 --> 00:36:03,520
Speaker 4: you bring the joystick. The first day you went for

733
00:36:03,560 --> 00:36:06,280
Speaker 4: a run, you couldn't last more than three minutes either.

734
00:36:07,360 --> 00:36:09,640
Speaker 4: So it's weird how they Yeah, I had this very

735
00:36:09,640 --> 00:36:13,680
Speaker 4: like sanitized branding except for their like free merch but yeah,

736
00:36:13,719 --> 00:36:17,040
Speaker 4: it has. It has Bluetooth connection, interactive and personalized settings.

737
00:36:17,239 --> 00:36:20,319
Speaker 4: You can monitor your user evolution, and it is it

738
00:36:20,400 --> 00:36:23,439
Speaker 4: is marked as a medical device. But on on their

739
00:36:23,480 --> 00:36:28,080
Speaker 4: brochure there's just two really really good sentences. There's video

740
00:36:28,200 --> 00:36:31,160
Speaker 4: feedback from our sexual health professionals. So after you come,

741
00:36:31,480 --> 00:36:34,200
Speaker 4: you can get on a video chat and talk about

742
00:36:34,200 --> 00:36:37,200
Speaker 4: there we go, there we go looking good.

743
00:36:37,840 --> 00:36:41,239
Speaker 5: It's the pillow talking. Add on, I'd.

744
00:36:40,960 --> 00:36:43,399
Speaker 2: Love to be one of those people as a gun man.

745
00:36:43,560 --> 00:36:45,800
Speaker 2: Three minutes. You can do better than that. Come on,

746
00:36:46,040 --> 00:36:47,640
Speaker 2: So they are you meant to encourage them?

747
00:36:47,920 --> 00:36:48,160
Speaker 1: Yeah?

748
00:36:48,440 --> 00:36:48,640
Speaker 4: Yeah?

749
00:36:48,840 --> 00:36:50,600
Speaker 3: Are you meant to commiserate with them? Yeah?

750
00:36:50,640 --> 00:36:52,160
Speaker 1: What is the goal here?

751
00:36:52,320 --> 00:36:52,680
Speaker 3: Yeah?

752
00:36:52,719 --> 00:36:55,239
Speaker 2: But also I cannot think of a single person i'd

753
00:36:55,239 --> 00:36:56,320
Speaker 2: want to talk about that with.

754
00:36:56,760 --> 00:36:59,200
Speaker 1: Yeah, I'm just imagining like the guy in the other

755
00:36:59,200 --> 00:37:00,799
Speaker 1: and be like no, no, no, no, zoom me the camera

756
00:37:00,800 --> 00:37:02,600
Speaker 1: a little more. I want to see those ropes. No,

757
00:37:02,920 --> 00:37:05,000
Speaker 1: that's not bad, that's not bad. Good consistency.

758
00:37:05,080 --> 00:37:07,160
Speaker 5: Okay, let's move that over. Let's see his O face again.

759
00:37:07,239 --> 00:37:10,840
Speaker 3: Wow, you play that, my friend? That your load management

760
00:37:10,920 --> 00:37:11,920
Speaker 3: is very consistent.

761
00:37:14,840 --> 00:37:18,560
Speaker 4: And I think I think we're really missing is how

762
00:37:18,680 --> 00:37:21,359
Speaker 4: much how much AI will assist in this because they

763
00:37:21,400 --> 00:37:26,640
Speaker 4: claim that using cutting edge technology? Eh eh my hixel

764
00:37:26,719 --> 00:37:29,480
Speaker 4: Control is the first solution to include AI and machine

765
00:37:29,560 --> 00:37:34,440
Speaker 4: learning for climax controlled treatment, which is just really really reassuring.

766
00:37:34,960 --> 00:37:37,080
Speaker 4: So yeah, it basically looks like a flashlight that connects

767
00:37:37,080 --> 00:37:42,920
Speaker 4: to your phone and it's an app with anatomical realistic

768
00:37:42,920 --> 00:37:47,840
Speaker 4: interior design and AI and secured it and and adanemonized data.

769
00:37:47,960 --> 00:37:49,480
Speaker 5: I think this is really going to open up some

770
00:37:49,520 --> 00:37:50,840
Speaker 5: avenues for sex workers.

771
00:37:51,600 --> 00:37:54,440
Speaker 4: Yeah, hope, hopefully, hopefully, Tafia.

772
00:37:54,160 --> 00:37:57,479
Speaker 1: It's It's also like the design the handy is very

773
00:37:57,560 --> 00:38:00,520
Speaker 1: clearly a robot. You stick your dick inside and it

774
00:38:00,960 --> 00:38:05,280
Speaker 1: jacks you off. This looks like a flesh light except

775
00:38:05,680 --> 00:38:07,840
Speaker 1: the back and like the front end that we unscrewed

776
00:38:07,840 --> 00:38:09,520
Speaker 1: the top and it's like a fake vagina looks like

777
00:38:09,520 --> 00:38:13,600
Speaker 1: a fleshlight. The back end looks like an incense diffuser,

778
00:38:14,080 --> 00:38:18,440
Speaker 1: Like like someone decided these two products needed to be

779
00:38:18,680 --> 00:38:22,240
Speaker 1: Like what if you could fuck your your aromatherapy bot.

780
00:38:23,680 --> 00:38:27,560
Speaker 4: Finally, So that is that is most of the the

781
00:38:27,560 --> 00:38:30,240
Speaker 4: the just the groundbreaking AI products that I was able

782
00:38:30,280 --> 00:38:33,400
Speaker 4: to see today. Does anyone else have any AI products

783
00:38:33,400 --> 00:38:34,319
Speaker 4: they would love to talk about?

784
00:38:34,400 --> 00:38:39,200
Speaker 1: It's time to talk about ganert I okayert obvious you

785
00:38:39,239 --> 00:38:41,440
Speaker 1: want to start us off about ganert.

786
00:38:41,560 --> 00:38:45,080
Speaker 5: Okay I guess We attended a panel. Which panel was it, y'all?

787
00:38:45,160 --> 00:38:48,440
Speaker 8: That was the dhs AI Yeah, that was That was

788
00:38:48,480 --> 00:38:50,960
Speaker 8: the AI panel with one of the heads of the

789
00:38:51,000 --> 00:38:54,440
Speaker 8: Department of Homeland Security, who I can confirm because he

790
00:38:54,520 --> 00:38:57,440
Speaker 8: turned around to take a selfie has a Hank Hill ass.

791
00:38:58,360 --> 00:38:59,640
Speaker 5: He was very insistent on that.

792
00:39:00,160 --> 00:39:03,520
Speaker 1: No but absolutely no. But and I'm saying this not

793
00:39:03,600 --> 00:39:06,239
Speaker 1: to shame him, but because there are ORTHOTICX for that

794
00:39:06,640 --> 00:39:10,080
Speaker 1: you can get help, sir. That's even a whole episode

795
00:39:10,520 --> 00:39:14,600
Speaker 1: of King of the Hill, one of the better EPISODESOD times.

796
00:39:15,040 --> 00:39:19,479
Speaker 5: Soert AI was announced before this talk that we had,

797
00:39:19,960 --> 00:39:23,840
Speaker 5: and it was a I think the guy announcing both

798
00:39:24,000 --> 00:39:28,520
Speaker 5: this this event as well as the panel had taken

799
00:39:28,560 --> 00:39:30,200
Speaker 5: some time to really focus on the fact that this

800
00:39:30,360 --> 00:39:31,640
Speaker 5: was his quote unquote.

801
00:39:31,280 --> 00:39:34,840
Speaker 4: Opis his his opis opus. He said the word opus

802
00:39:34,920 --> 00:39:37,640
Speaker 4: like five times Ganert's what I'll be remembered by.

803
00:39:38,920 --> 00:39:42,200
Speaker 5: This is my legacy. Yeah, and then I guess two

804
00:39:42,239 --> 00:39:44,520
Speaker 5: of the designers had come up who stuck out like

805
00:39:44,560 --> 00:39:47,200
Speaker 5: a sore thumb compared to like the sea of khaki

806
00:39:47,280 --> 00:39:48,839
Speaker 5: and blazers and things like that.

807
00:39:50,120 --> 00:39:53,160
Speaker 1: Yeah. Yeah, they had clearly never ordered a drone strike,

808
00:39:53,280 --> 00:39:55,360
Speaker 1: unlike our hero and Homelands security.

809
00:39:55,840 --> 00:39:58,120
Speaker 4: One of them had a wide brimmed hat that was

810
00:39:58,239 --> 00:40:01,040
Speaker 4: color matched to the Gert logo, which is pretty cool.

811
00:40:01,480 --> 00:40:02,799
Speaker 1: What does Genert stand for?

812
00:40:03,480 --> 00:40:07,000
Speaker 4: Ganert stands for generate, So I think it's actually just

813
00:40:07,600 --> 00:40:12,319
Speaker 4: called it generate. They just took out the vowels. But

814
00:40:12,480 --> 00:40:15,840
Speaker 4: this is going to be a three day event or

815
00:40:15,960 --> 00:40:21,960
Speaker 4: a conference held in Arlington, Virginia's they're claiming that it's

816
00:40:21,960 --> 00:40:24,560
Speaker 4: gonna have like two hundred speakers, one hundred and fifty

817
00:40:24,600 --> 00:40:28,320
Speaker 4: AI sessions, more than five hundred startups, one hundred fifty partners,

818
00:40:28,320 --> 00:40:32,439
Speaker 4: one hundred investors, and around five thousand attendees. They're trying

819
00:40:32,480 --> 00:40:38,600
Speaker 4: to target enterprise governments, platforms, AI tools, AI builders, services, investors, startups,

820
00:40:38,640 --> 00:40:42,640
Speaker 4: and media that it's it's these three events held simultaneously,

821
00:40:42,760 --> 00:40:47,080
Speaker 4: ones just called Gennert or Generate AI, which is about

822
00:40:47,280 --> 00:40:53,120
Speaker 4: just AI AI tech. It's about like AI companies, classes, keynotes, funding,

823
00:40:53,120 --> 00:40:55,760
Speaker 4: blah blah blah blah blah. There is then Voice and AI,

824
00:40:56,160 --> 00:41:00,359
Speaker 4: which is about AI language services. And there's also for

825
00:41:00,480 --> 00:41:03,279
Speaker 4: gov ai, which is about public sector and how the

826
00:41:03,320 --> 00:41:06,040
Speaker 4: government's gonna start integrating AI or regulating AI. And they

827
00:41:06,080 --> 00:41:10,839
Speaker 4: also have one for coding called code Forward, and it's

828
00:41:11,000 --> 00:41:13,359
Speaker 4: it's a bummer. We can't just play the opening video

829
00:41:13,400 --> 00:41:16,680
Speaker 4: because opening video had no like voice here.

830
00:41:16,719 --> 00:41:18,880
Speaker 1: But there's yeah, there's no voice. I can read it though.

831
00:41:19,440 --> 00:41:22,880
Speaker 1: Ninety seven million new jobs in AI, five hundred billion

832
00:41:22,920 --> 00:41:25,520
Speaker 1: in annual AI spend by twenty twenty seven, two hundred

833
00:41:25,520 --> 00:41:26,840
Speaker 1: and fifty billion in VC.

834
00:41:27,360 --> 00:41:29,320
Speaker 3: Funding by twenty twenty five.

835
00:41:29,760 --> 00:41:33,160
Speaker 1: Conert generate for a new world in a new market.

836
00:41:33,440 --> 00:41:37,560
Speaker 1: Gonert connects and forms, elevates and inspires. It all happens

837
00:41:37,600 --> 00:41:39,320
Speaker 1: at Ganerts.

838
00:41:39,760 --> 00:41:42,160
Speaker 4: And we cannot emphasize it enough. How they hyped up

839
00:41:42,560 --> 00:41:46,720
Speaker 4: VC cash there, there was there was so much build

840
00:41:46,800 --> 00:41:48,040
Speaker 4: up for VC cash.

841
00:41:48,239 --> 00:41:51,840
Speaker 1: I have I have watched people who are dope sick

842
00:41:52,360 --> 00:41:57,200
Speaker 1: by heroin with less jittery excitement in their hands and eyes.

843
00:41:58,120 --> 00:42:00,880
Speaker 3: All right, So but about shit like this?

844
00:42:01,000 --> 00:42:03,440
Speaker 2: So I just did a brief cursory look up Ganert

845
00:42:04,040 --> 00:42:10,640
Speaker 2: and it's and it's it's connected, Confidence, Voice I and

846
00:42:10,680 --> 00:42:14,160
Speaker 2: Gove and code Forward, and all of them are claiming

847
00:42:14,200 --> 00:42:20,480
Speaker 2: the following. They're featuring GitHub, Microsoft, open Ai, Codium tab nine.

848
00:42:21,320 --> 00:42:24,040
Speaker 2: Their thing on LinkedIn has twenty eight followers, and their

849
00:42:24,040 --> 00:42:27,640
Speaker 2: engagement is like when I post the word twitter on Twitter,

850
00:42:28,120 --> 00:42:29,879
Speaker 2: it's not very good at all. I can get more

851
00:42:29,880 --> 00:42:31,520
Speaker 2: on that doing any of the Pocht picture of my

852
00:42:31,520 --> 00:42:34,000
Speaker 2: asshole and get more than that. But also I cannot

853
00:42:34,040 --> 00:42:38,319
Speaker 2: find a single person claiming to attend this. Despite them

854
00:42:38,320 --> 00:42:40,600
Speaker 2: claiming two hundred bus speakers, one hundred and fifty plus sessions,

855
00:42:40,640 --> 00:42:43,080
Speaker 2: five hundred stars, one hundred fifty part one hundred investors,

856
00:42:43,080 --> 00:42:46,080
Speaker 2: five thousand attendees, I can't find a single bit of

857
00:42:46,120 --> 00:42:49,680
Speaker 2: evidence that anyone is ganerting around at all. And also

858
00:42:49,760 --> 00:42:52,840
Speaker 2: they claim to have three different conferences, code Forward, Gove, AI,

859
00:42:52,960 --> 00:42:57,440
Speaker 2: Voice AI and of course Connert AI and I, and

860
00:42:57,640 --> 00:43:00,520
Speaker 2: of course all of these are part of the AI

861
00:43:00,760 --> 00:43:01,840
Speaker 2: beta experience.

862
00:43:01,920 --> 00:43:03,680
Speaker 3: I don't know why you put beta.

863
00:43:03,800 --> 00:43:06,640
Speaker 2: People are beta as hell, But also why have you

864
00:43:06,680 --> 00:43:08,160
Speaker 2: got beta on a conference?

865
00:43:08,239 --> 00:43:10,040
Speaker 3: What are you doing? But also.

866
00:43:11,280 --> 00:43:14,440
Speaker 2: Featuring open AI and video Microsoft, Google, and Verituan. I'm

867
00:43:14,480 --> 00:43:17,560
Speaker 2: gonna guess that they've got like chat, GPT, open on

868
00:43:17,560 --> 00:43:22,319
Speaker 2: a computer, an Nvidio GPU and something Microsoft Word and

869
00:43:22,360 --> 00:43:28,000
Speaker 2: they've used Google. And it's very strange because I don't

870
00:43:28,040 --> 00:43:29,080
Speaker 2: know what this thing.

871
00:43:29,160 --> 00:43:32,160
Speaker 1: Is, you know. I think what it is is some

872
00:43:32,440 --> 00:43:37,080
Speaker 1: guys who have a degree of like nay like like

873
00:43:37,160 --> 00:43:40,480
Speaker 1: some guys who are hoping that they don't have any

874
00:43:40,480 --> 00:43:42,359
Speaker 1: actual ideas for it to do with AI, so they're

875
00:43:42,360 --> 00:43:44,719
Speaker 1: hoping that if they create a conference and make that

876
00:43:44,800 --> 00:43:47,279
Speaker 1: be like the Cees of AI, they can kind of

877
00:43:47,280 --> 00:43:50,080
Speaker 1: force a place for themselves and also attract a bunch

878
00:43:50,080 --> 00:43:51,239
Speaker 1: of suction up a bunch of money.

879
00:43:51,280 --> 00:43:53,440
Speaker 2: I also found some I found some of the speakers.

880
00:43:53,440 --> 00:43:56,760
Speaker 2: You've got fellow called Adam Goldberg, who's an account director

881
00:43:56,800 --> 00:43:58,880
Speaker 2: and head of a is your open Ai enablement on

882
00:43:58,920 --> 00:44:01,200
Speaker 2: the go to market team open Ai. They found a

883
00:44:01,239 --> 00:44:03,319
Speaker 2: sales guy from open ai and then said they got

884
00:44:03,320 --> 00:44:06,320
Speaker 2: someone from open Ai. They got someone from JP Morgan,

885
00:44:06,400 --> 00:44:10,080
Speaker 2: Chile's data and AI design. These are all fake jobs.

886
00:44:10,640 --> 00:44:14,480
Speaker 2: These aren't real jobs. And I think that these conferences

887
00:44:14,520 --> 00:44:16,560
Speaker 2: are amazing as well, because all people do at them

888
00:44:16,600 --> 00:44:18,719
Speaker 2: is they go they watch these things where people go

889
00:44:18,800 --> 00:44:21,560
Speaker 2: up on stage and go, you know, generative AI is

890
00:44:21,600 --> 00:44:24,760
Speaker 2: going to create maybe even trillions of dollars of value

891
00:44:24,760 --> 00:44:28,200
Speaker 2: at some point, and you know, the synergy between generative

892
00:44:28,280 --> 00:44:33,319
Speaker 2: AI and data collection but also data silos is going

893
00:44:33,400 --> 00:44:37,560
Speaker 2: to be truly, truly innovative. And everyone's like, holy fucking shit,

894
00:44:37,960 --> 00:44:41,520
Speaker 2: whoa holy shit, piss no, and then they all post

895
00:44:41,520 --> 00:44:44,120
Speaker 2: it on Twitter and they all forget it. Ever happened immediately.

896
00:44:44,360 --> 00:44:46,680
Speaker 5: Yeah, we call that the dividend.

897
00:44:47,800 --> 00:44:50,480
Speaker 4: We do call that the dividend. So Gert's being put

898
00:44:50,520 --> 00:44:54,200
Speaker 4: on by this guy who runs this like panel collection

899
00:44:54,360 --> 00:44:57,040
Speaker 4: called brands gpt at ces.

900
00:44:56,800 --> 00:44:57,160
Speaker 2: With a Z.

901
00:44:58,440 --> 00:45:00,840
Speaker 1: No, it's not Pear and Gar with a Z.

902
00:45:01,080 --> 00:45:04,200
Speaker 4: Should it should be. I think me and Robert both

903
00:45:04,239 --> 00:45:07,640
Speaker 4: went to like one or two of these brands GPT panels.

904
00:45:07,840 --> 00:45:10,040
Speaker 4: This is the one where Robert got to yell at

905
00:45:10,080 --> 00:45:11,680
Speaker 4: Google and Microsoft and get them mad.

906
00:45:12,400 --> 00:45:15,960
Speaker 1: No Google and McDonald's McDon donald's ahead of AI, which

907
00:45:16,000 --> 00:45:16,479
Speaker 1: is a thing.

908
00:45:17,640 --> 00:45:22,600
Speaker 4: So they look to basically just focus on like convention programming.

909
00:45:22,840 --> 00:45:24,520
Speaker 4: So now they're trying to put on their own convention

910
00:45:24,600 --> 00:45:28,840
Speaker 4: that they're calling Ganert instead of just running this brand's

911
00:45:28,920 --> 00:45:33,279
Speaker 4: gpt at CES. So that's that's the background. It's it's

912
00:45:33,320 --> 00:45:37,759
Speaker 4: done by Mode v events. That's Mode and the letter VD.

913
00:45:37,840 --> 00:45:40,600
Speaker 4: But one word that's like the parent company for this.

914
00:45:41,200 --> 00:45:43,839
Speaker 4: I'll be interested once we get closer to October. I'll

915
00:45:43,880 --> 00:45:45,480
Speaker 4: be interested to see if this is looking more like

916
00:45:45,480 --> 00:45:47,560
Speaker 4: a real event. It's it's not going to be that

917
00:45:47,600 --> 00:45:50,520
Speaker 4: far for me to travel. But no, they're they're promising

918
00:45:51,120 --> 00:45:54,640
Speaker 4: five hundred billion dollars in annual AI spending with two

919
00:45:54,800 --> 00:45:59,000
Speaker 4: hundred and fifty billion new VC cash investments, which is

920
00:45:59,040 --> 00:45:59,920
Speaker 4: which is quite promised.

921
00:46:00,360 --> 00:46:04,160
Speaker 1: Yeah, so hopefully this beta test goes like the last

922
00:46:04,239 --> 00:46:07,000
Speaker 1: video game beta test that I went to and everybody

923
00:46:07,040 --> 00:46:12,040
Speaker 1: clips through the floor and disappears into avoid Well, I

924
00:46:12,080 --> 00:46:14,800
Speaker 1: think that's gonna do it for us in this episode.

925
00:46:14,800 --> 00:46:17,320
Speaker 1: And I want to leave you all with well, before

926
00:46:17,680 --> 00:46:19,879
Speaker 1: we've got one more thing. But before we get into that,

927
00:46:19,960 --> 00:46:22,120
Speaker 1: which which will be fun, I want to talk about

928
00:46:22,120 --> 00:46:24,560
Speaker 1: something sobering, which is that, as you may get from this,

929
00:46:25,080 --> 00:46:27,719
Speaker 1: nearly one hundred percent of the AI use cases that

930
00:46:27,760 --> 00:46:31,080
Speaker 1: we saw presented were either nonsense or incredibly vague. At

931
00:46:31,080 --> 00:46:33,520
Speaker 1: these different that where you had people from like Nvidia

932
00:46:33,560 --> 00:46:36,000
Speaker 1: and Adobe and whatnot that like they wouldn't say like,

933
00:46:36,080 --> 00:46:38,359
Speaker 1: we're going to use AI for this specific task. They

934
00:46:38,360 --> 00:46:41,200
Speaker 1: would say we're going to use AI to get more nimble,

935
00:46:41,280 --> 00:46:42,880
Speaker 1: which I think means firing people.

936
00:46:43,360 --> 00:46:43,600
Speaker 3: You know.

937
00:46:43,920 --> 00:46:46,840
Speaker 1: Outside of that, the only real specific use cases that

938
00:46:46,840 --> 00:46:50,160
Speaker 1: were not clearly nonsense. We're stuff like replacing you know,

939
00:46:50,360 --> 00:46:53,360
Speaker 1: customer service workers with chatbots, which is bad, and to

940
00:46:53,400 --> 00:46:56,080
Speaker 1: be fair, some also really good stuff like that telescope

941
00:46:56,080 --> 00:46:58,279
Speaker 1: that used kind of machine learning in order to like

942
00:46:58,280 --> 00:47:00,440
Speaker 1: clean up images so that you can get better, better

943
00:47:00,480 --> 00:47:02,320
Speaker 1: images and whatnot when you're in an area with a

944
00:47:02,360 --> 00:47:04,600
Speaker 1: lot of light pollution. There was some stuff like that,

945
00:47:04,920 --> 00:47:08,640
Speaker 1: but usually very vague. The use cases for AI was

946
00:47:08,680 --> 00:47:12,480
Speaker 1: always extremely clear were the harms and the very first

947
00:47:13,040 --> 00:47:15,759
Speaker 1: panel we attended, there's a company called Deloitte. They're a

948
00:47:15,920 --> 00:47:18,680
Speaker 1: huge consulting firm. If you know about McKenzie because they're

949
00:47:18,680 --> 00:47:21,759
Speaker 1: currently somewhat rightfully so a bit of a bugbear on

950
00:47:21,800 --> 00:47:24,839
Speaker 1: the left, Deloitte is a similar kind of organization, right

951
00:47:24,880 --> 00:47:27,960
Speaker 1: I think they're a bit less toxic, but to a

952
00:47:28,000 --> 00:47:31,839
Speaker 1: marginal degree. They're like a massive consulting firm. Companies bring

953
00:47:31,880 --> 00:47:34,120
Speaker 1: them in in order to help them streamline and make

954
00:47:34,440 --> 00:47:38,080
Speaker 1: processes more efficient and stuff, and one of their people

955
00:47:38,120 --> 00:47:41,680
Speaker 1: said that according to their internal metrics, they expected half

956
00:47:41,719 --> 00:47:46,759
Speaker 1: a trillion dollars in fraud this year in one year

957
00:47:47,239 --> 00:47:52,920
Speaker 1: due just to voice cloning AI. And that was a

958
00:47:52,960 --> 00:47:56,680
Speaker 1: more specific statement of what AI is going to do

959
00:47:56,760 --> 00:48:00,279
Speaker 1: to change people's lives than absolutely any positive use case

960
00:48:00,320 --> 00:48:01,760
Speaker 1: I heard presented at this conference.

961
00:48:02,040 --> 00:48:05,120
Speaker 4: Could you like explain what you mean by voice cloning

962
00:48:05,440 --> 00:48:06,120
Speaker 4: so AI.

963
00:48:06,400 --> 00:48:08,720
Speaker 1: You know, we did a couple of Bastards episodes talking

964
00:48:08,719 --> 00:48:12,200
Speaker 1: about scams and like how they've contributed to the decline

965
00:48:12,200 --> 00:48:14,640
Speaker 1: of trust in our society. One of the things that

966
00:48:14,760 --> 00:48:16,880
Speaker 1: is in the last year or so become a massive

967
00:48:16,920 --> 00:48:19,840
Speaker 1: problem is there are now AI things that can generate

968
00:48:19,920 --> 00:48:23,960
Speaker 1: a human voice near perfectly to the point where, especially

969
00:48:23,960 --> 00:48:26,120
Speaker 1: if it is a voice of say your kid calls

970
00:48:26,120 --> 00:48:27,720
Speaker 1: you and they're telling you that they have been fucking

971
00:48:27,800 --> 00:48:30,440
Speaker 1: kidnapped or you know, something else has happened and they

972
00:48:30,440 --> 00:48:32,439
Speaker 1: need you to wire them money desperately and you send

973
00:48:32,440 --> 00:48:34,839
Speaker 1: them the money, it's a fucking scam, right that is.

974
00:48:35,120 --> 00:48:37,359
Speaker 1: We had a person from Deloitte, and I think it

975
00:48:37,400 --> 00:48:39,640
Speaker 1: was a person from Adobe, say that they had been

976
00:48:39,719 --> 00:48:43,800
Speaker 1: called by a colleague who had gotten like a call

977
00:48:43,960 --> 00:48:47,000
Speaker 1: thinking it was that seemed to be them asking them

978
00:48:47,000 --> 00:48:49,640
Speaker 1: to buy a bunch of Apple gift cards like shit,

979
00:48:49,800 --> 00:48:51,799
Speaker 1: Like this is extreme and it's only going to get

980
00:48:51,800 --> 00:48:55,080
Speaker 1: more common. You can automate to the writing of the

981
00:48:55,120 --> 00:48:57,960
Speaker 1: scams and the sending of the scams using these AI tools,

982
00:48:58,280 --> 00:49:02,840
Speaker 1: and that is absolutely, in my opinion, much more of

983
00:49:02,880 --> 00:49:05,680
Speaker 1: a direct way in which AI is going to affect

984
00:49:05,680 --> 00:49:09,279
Speaker 1: people than any single product or even cumulatively, all of

985
00:49:09,280 --> 00:49:10,840
Speaker 1: the AI products we saw at CE.

986
00:49:13,600 --> 00:49:17,000
Speaker 4: All that uplifting note Yeah, yeah.

987
00:49:16,719 --> 00:49:19,359
Speaker 1: So that's a bummer, and well, we will be going

988
00:49:19,400 --> 00:49:21,480
Speaker 1: into more depth about that, but I wanted to end.

989
00:49:21,560 --> 00:49:25,560
Speaker 1: Tavia took notes at all of the buzzwords, particularly the

990
00:49:25,560 --> 00:49:29,200
Speaker 1: AI buzzwords that we heard during the convention, and she's

991
00:49:29,239 --> 00:49:30,680
Speaker 1: going to read that to us now.

992
00:49:31,200 --> 00:49:33,520
Speaker 5: You gotta tell you, this list is incredible. I've worked

993
00:49:33,560 --> 00:49:36,040
Speaker 5: in and out of corporate America, and much like a cult,

994
00:49:36,040 --> 00:49:39,520
Speaker 5: they have their own internal vocabulary that they use, and

995
00:49:39,560 --> 00:49:44,279
Speaker 5: this convention we went to was just filthy with these buzzwords.

996
00:49:44,320 --> 00:49:46,759
Speaker 5: So I'm just going to dig in. The ones that

997
00:49:46,800 --> 00:49:50,120
Speaker 5: I've written down are double down, love that one. That

998
00:49:50,120 --> 00:49:54,480
Speaker 5: one comes up a lot. Versioning, versioning, versioning, which is

999
00:49:54,560 --> 00:49:57,240
Speaker 5: like a legitimate term in software, but I was hearing

1000
00:49:57,239 --> 00:49:59,520
Speaker 5: it used in places where it didn't make much sense

1001
00:49:59,560 --> 00:50:03,320
Speaker 5: to do it. Then our favorite liar's.

1002
00:50:02,960 --> 00:50:06,040
Speaker 4: Dividend by by by far the best term that we've

1003
00:50:06,040 --> 00:50:08,520
Speaker 4: heard at the conference, So flexible.

1004
00:50:08,840 --> 00:50:11,000
Speaker 1: Yeah, I'm using versions of that and everything. You know,

1005
00:50:11,040 --> 00:50:13,080
Speaker 1: it makes me think a lot about the murderer's dividend,

1006
00:50:13,120 --> 00:50:14,560
Speaker 1: which is when you know, I longer I have to

1007
00:50:14,560 --> 00:50:15,760
Speaker 1: deal with an annoying person.

1008
00:50:16,480 --> 00:50:19,399
Speaker 5: We got content credential, which is coming up a lot,

1009
00:50:19,480 --> 00:50:22,439
Speaker 5: especially around the topic of AI. We have data rich

1010
00:50:22,640 --> 00:50:26,520
Speaker 5: and it's sister term problem rich core values, which I

1011
00:50:26,600 --> 00:50:29,279
Speaker 5: heard in every single panel that we were in.

1012
00:50:29,560 --> 00:50:32,520
Speaker 1: Yeah. Usually the context of this was we don't need

1013
00:50:32,600 --> 00:50:36,480
Speaker 1: regulations around how AI can be made and put together.

1014
00:50:37,000 --> 00:50:39,759
Speaker 1: The core values of the companies is what we'll make

1015
00:50:39,800 --> 00:50:43,080
Speaker 1: sure that AI isn't used in a harmful way.

1016
00:50:43,120 --> 00:50:45,960
Speaker 3: Great, that's that's gonna happen.

1017
00:50:47,320 --> 00:50:51,960
Speaker 5: No, very trustworthy, very trustworthy groups. Got risk model. And

1018
00:50:52,000 --> 00:50:54,239
Speaker 5: then my next term is the favorite one. It's so good,

1019
00:50:54,400 --> 00:50:55,640
Speaker 5: I think I'm gonna give this one to you.

1020
00:50:56,200 --> 00:50:58,280
Speaker 1: Yeah, because I don't think we talked about this. Guardian

1021
00:50:58,480 --> 00:51:01,360
Speaker 1: MM or something like that was then it's MM guardian

1022
00:51:01,680 --> 00:51:05,440
Speaker 1: MM Guardian, which is an app you put on It's

1023
00:51:05,520 --> 00:51:07,080
Speaker 1: not it used to be an app. Now it is

1024
00:51:07,120 --> 00:51:09,880
Speaker 1: a phone you buy for your child. It's a modified

1025
00:51:09,920 --> 00:51:15,759
Speaker 1: Samsung Galaxy something or other that there's no seven. It

1026
00:51:15,880 --> 00:51:19,080
Speaker 1: gives your It gives you, as the parent, complete access

1027
00:51:19,120 --> 00:51:21,080
Speaker 1: to your kid's phone and everything they're doing. And it

1028
00:51:21,120 --> 00:51:25,160
Speaker 1: automatically monitors, monitors all of their not just their conversations,

1029
00:51:25,200 --> 00:51:28,400
Speaker 1: but their browsing history, and sends you alerts. So like,

1030
00:51:28,520 --> 00:51:31,279
Speaker 1: if someone sends your kid a text that says you

1031
00:51:31,280 --> 00:51:33,720
Speaker 1: should kys you know, kill yourself. This is the example

1032
00:51:33,719 --> 00:51:36,040
Speaker 1: he showed us. You get a message that like there's

1033
00:51:36,080 --> 00:51:40,640
Speaker 1: this suicidal discussion or whatnot going on, we ask them,

1034
00:51:40,920 --> 00:51:44,680
Speaker 1: you know. Hey. Garrison particularly was like, what if this

1035
00:51:44,719 --> 00:51:48,480
Speaker 1: is a situation where a parent is abusive and like

1036
00:51:48,880 --> 00:51:52,480
Speaker 1: using this in order to keep tabs on their kids

1037
00:51:52,600 --> 00:51:55,120
Speaker 1: or like hates you know, is like a child is

1038
00:51:55,120 --> 00:51:58,399
Speaker 1: gay or trans and their parents are not accepting of that.

1039
00:51:58,600 --> 00:52:01,279
Speaker 1: Like does this still can parents still like spy on

1040
00:52:01,320 --> 00:52:03,680
Speaker 1: them over that stuff? Are there any limitations? Are there

1041
00:52:03,680 --> 00:52:06,279
Speaker 1: any sort of safeguards built in in case a parent

1042
00:52:06,400 --> 00:52:09,200
Speaker 1: is being abusive right to like monitor or sin to

1043
00:52:09,239 --> 00:52:11,120
Speaker 1: the authorities of a parent is using this in an

1044
00:52:11,160 --> 00:52:14,680
Speaker 1: abusive way. And their answer was no, We're purely about

1045
00:52:14,719 --> 00:52:18,399
Speaker 1: giving parents more power. And yeah, the term that they

1046
00:52:18,600 --> 00:52:21,400
Speaker 1: used was tech contracts with children.

1047
00:52:23,640 --> 00:52:25,520
Speaker 5: I can't think of anything more dismal.

1048
00:52:26,120 --> 00:52:29,799
Speaker 1: Yeah, that is one of the most dystopian assemblies of

1049
00:52:29,920 --> 00:52:31,000
Speaker 1: words I've ever heard.

1050
00:52:31,080 --> 00:52:35,040
Speaker 4: Should you should you should never say the phrase contracts

1051
00:52:35,080 --> 00:52:38,439
Speaker 4: with children. That's just that's just like if you find

1052
00:52:38,480 --> 00:52:42,360
Speaker 4: yourself ever ever hearing the phrase contracts with children spoken

1053
00:52:42,440 --> 00:52:44,600
Speaker 4: by anyone, run away from that person as fast as

1054
00:52:44,640 --> 00:52:47,279
Speaker 4: you can, maybe maybe maybe punch them in the face first,

1055
00:52:47,560 --> 00:52:49,399
Speaker 4: and then run away as fast as you can.

1056
00:52:50,760 --> 00:52:52,120
Speaker 1: So that's a good one.

1057
00:52:52,760 --> 00:52:54,840
Speaker 3: That's that's some shit you just keep in Florida. I

1058
00:52:54,880 --> 00:52:55,600
Speaker 3: guess now.

1059
00:52:57,360 --> 00:52:58,759
Speaker 1: It's a super Florida app.

1060
00:52:58,920 --> 00:52:59,200
Speaker 4: That is.

1061
00:52:59,280 --> 00:53:00,960
Speaker 1: That is the scent of this business.

1062
00:53:01,920 --> 00:53:05,080
Speaker 5: Moving on, We've got other terms called like visionary and

1063
00:53:05,120 --> 00:53:07,400
Speaker 5: thought leaders, which comes up a lot in these types.

1064
00:53:07,200 --> 00:53:10,680
Speaker 2: Of I mean, the pr shit people love saying thought leader.

1065
00:53:11,000 --> 00:53:11,480
Speaker 1: I love it.

1066
00:53:12,680 --> 00:53:18,160
Speaker 5: Eat it up. We also have Edge Computing I know.

1067
00:53:19,200 --> 00:53:21,400
Speaker 1: Yeah again handy, great company.

1068
00:53:21,200 --> 00:53:25,479
Speaker 5: Incredible company, very very excellent product. We have Digital Twin

1069
00:53:26,080 --> 00:53:27,040
Speaker 5: Horizon Scan.

1070
00:53:27,360 --> 00:53:31,000
Speaker 2: So Digital Twin's really good because it means like eight

1071
00:53:31,040 --> 00:53:35,000
Speaker 2: different things. It can mean literally a copy of something,

1072
00:53:35,280 --> 00:53:37,840
Speaker 2: or it can mean a digital version of something. It

1073
00:53:37,840 --> 00:53:40,399
Speaker 2: can mean like a metaverse thing. And these are all

1074
00:53:40,480 --> 00:53:42,719
Speaker 2: different industries using it, and no one can agree on

1075
00:53:42,760 --> 00:53:43,160
Speaker 2: the meaning.

1076
00:53:43,480 --> 00:53:45,680
Speaker 5: Yeah, that's just tradition. That's just like what they do.

1077
00:53:46,560 --> 00:53:49,120
Speaker 5: They have horizon scan. I actually kind of liked that one.

1078
00:53:49,239 --> 00:53:51,120
Speaker 5: Was the first time I heard that one. When they're

1079
00:53:51,160 --> 00:53:53,279
Speaker 5: just like looking into the future, I think they're calling

1080
00:53:53,360 --> 00:53:57,239
Speaker 5: that horizon scan use case, which came up a lot

1081
00:53:57,320 --> 00:54:00,759
Speaker 5: because everyone was groping for use cases for their technology

1082
00:54:00,800 --> 00:54:03,319
Speaker 5: and didn't seem to have any that they could bring up.

1083
00:54:04,040 --> 00:54:08,880
Speaker 4: The next one I heard way more than I wanted

1084
00:54:08,960 --> 00:54:12,520
Speaker 4: to hear, which was accelerate. Yes, always always a great

1085
00:54:12,640 --> 00:54:16,440
Speaker 4: term to hear in tech. There was there was so

1086
00:54:16,680 --> 00:54:20,759
Speaker 4: much accelerate and accelerating relating to their tech development and

1087
00:54:20,800 --> 00:54:24,520
Speaker 4: their tech use cases. For another one of those terms

1088
00:54:24,520 --> 00:54:25,719
Speaker 4: that Tavia just read off.

1089
00:54:25,800 --> 00:54:27,920
Speaker 1: Now, this next term is a real thing and an

1090
00:54:27,960 --> 00:54:30,520
Speaker 1: important thing, and not a thing that anyone in the

1091
00:54:30,520 --> 00:54:34,000
Speaker 1: tech industry wants or cares about the right to be forgotten.

1092
00:54:34,480 --> 00:54:36,520
Speaker 1: This has actually been legislated. The reason they have to

1093
00:54:36,560 --> 00:54:38,879
Speaker 1: care about this to some extent is it's been legislated

1094
00:54:38,880 --> 00:54:41,480
Speaker 1: in the EU right, and it should be everywhere. I

1095
00:54:41,520 --> 00:54:44,759
Speaker 1: actually think this is an incredibly important concept, and it's

1096
00:54:44,760 --> 00:54:48,040
Speaker 1: basically the you know, we have people go viral that

1097
00:54:48,200 --> 00:54:51,279
Speaker 1: become a main character on whatever app for being a

1098
00:54:51,280 --> 00:54:54,040
Speaker 1: piece of shit sometimes or sometimes doing something stupid or

1099
00:54:54,080 --> 00:54:56,719
Speaker 1: sometimes doing something innocuous that for no reason at all

1100
00:54:57,040 --> 00:54:57,799
Speaker 1: makes a huge number.

1101
00:54:58,160 --> 00:54:59,320
Speaker 3: He's actually a really good example.

1102
00:54:59,360 --> 00:55:01,680
Speaker 2: There was a kid who posted a video of himself

1103
00:55:01,960 --> 00:55:05,080
Speaker 2: and it was like four point zero gpa had a job,

1104
00:55:05,239 --> 00:55:08,280
Speaker 2: brais money didn't get into Harvard or something. He didn't

1105
00:55:08,320 --> 00:55:10,239
Speaker 2: mean it in this way, but someone took it and

1106
00:55:10,280 --> 00:55:12,480
Speaker 2: then turned it into ay why kids are being kept

1107
00:55:12,520 --> 00:55:14,839
Speaker 2: off Harvard thing? And he dm them was like, you're

1108
00:55:14,920 --> 00:55:18,120
Speaker 2: ruining my fucking life. Yeah, this is how this, like

1109
00:55:18,160 --> 00:55:20,360
Speaker 2: the right to be forgotten, should be everywhere.

1110
00:55:20,440 --> 00:55:21,000
Speaker 3: Yeah, is not.

1111
00:55:21,320 --> 00:55:24,560
Speaker 1: It is a hugely important thing, and you know, I

1112
00:55:24,880 --> 00:55:26,680
Speaker 1: actually give the EU a lot of credit for the

1113
00:55:26,719 --> 00:55:29,279
Speaker 1: fact that that has to some extent been legislated. All

1114
00:55:29,280 --> 00:55:31,600
Speaker 1: of that needs to be more common in other countries

1115
00:55:31,680 --> 00:55:36,120
Speaker 1: and more vigorously enforced. I don't I say that I

1116
00:55:36,160 --> 00:55:37,880
Speaker 1: have no idea how you do it with the internet.

1117
00:55:37,920 --> 00:55:40,200
Speaker 1: Working the way it does. Some of this, I actually

1118
00:55:40,280 --> 00:55:43,080
Speaker 1: do think is a values thing where we all need

1119
00:55:43,120 --> 00:55:45,760
Speaker 1: to be more okay with the fact that people, even

1120
00:55:45,800 --> 00:55:49,600
Speaker 1: people who can do something shitty online, deserve to not

1121
00:55:49,680 --> 00:55:53,560
Speaker 1: have that necessarily define the rest of their lives, especially

1122
00:55:54,120 --> 00:55:55,399
Speaker 1: you know, teenagers.

1123
00:55:56,800 --> 00:55:59,000
Speaker 2: And the next one is one that I like to

1124
00:55:59,040 --> 00:56:03,480
Speaker 2: associate with my posts, data poisoning. I believe every time

1125
00:56:03,520 --> 00:56:06,839
Speaker 2: I interact with Twitter or blue Sky, that is what

1126
00:56:06,880 --> 00:56:09,640
Speaker 2: I am doing. I have some data poisoning gap, or

1127
00:56:09,719 --> 00:56:13,120
Speaker 2: I am data poisoning as a verb, or I am

1128
00:56:13,239 --> 00:56:14,480
Speaker 2: data poisoning myself.

1129
00:56:14,560 --> 00:56:16,920
Speaker 1: Yeah.

1130
00:56:17,400 --> 00:56:17,680
Speaker 5: Uh.

1131
00:56:17,719 --> 00:56:20,640
Speaker 1: And then we've got oh, Garrison, you want to do

1132
00:56:20,680 --> 00:56:21,080
Speaker 1: this one?

1133
00:56:21,160 --> 00:56:21,440
Speaker 3: Sure?

1134
00:56:21,640 --> 00:56:23,480
Speaker 4: These these are the last three that I got from

1135
00:56:23,520 --> 00:56:27,640
Speaker 4: an AI ethics panel. We have data silos, how data

1136
00:56:27,719 --> 00:56:31,200
Speaker 4: is all separated. We have data harmonization, kind of the

1137
00:56:31,239 --> 00:56:32,640
Speaker 4: opposite of data silos.

1138
00:56:32,719 --> 00:56:35,560
Speaker 1: Yeah, that's basically using AI to generate pictures of dan

1139
00:56:35,600 --> 00:56:36,319
Speaker 1: harmon Right.

1140
00:56:37,400 --> 00:56:42,239
Speaker 4: Yes, Then we have the last term, which I will

1141
00:56:42,360 --> 00:56:48,000
Speaker 4: I will describe for you the speed capacity gap. So

1142
00:56:48,760 --> 00:56:50,240
Speaker 4: the speed capacity.

1143
00:56:49,800 --> 00:56:51,680
Speaker 1: Gap, I know I can answer that for you. So

1144
00:56:51,800 --> 00:56:55,920
Speaker 1: sometimes when I'm doing a shitload of amphetamines that I

1145
00:56:56,000 --> 00:56:59,640
Speaker 1: purchased from some Turkish website via the dark web. You know,

1146
00:56:59,680 --> 00:57:02,320
Speaker 1: I'm doing them with a friend and they od because

1147
00:57:02,360 --> 00:57:04,920
Speaker 1: there's a day there's a speed capacity gap, which we

1148
00:57:05,040 --> 00:57:05,759
Speaker 1: need two of us.

1149
00:57:06,560 --> 00:57:09,480
Speaker 4: Yeah, that's what that uh, that's what that DHS guy

1150
00:57:09,560 --> 00:57:11,919
Speaker 4: was talking about. For using AI to monitor dark web

1151
00:57:11,960 --> 00:57:15,480
Speaker 4: purchases is going to really get on that one. No

1152
00:57:15,800 --> 00:57:19,440
Speaker 4: speed capacity gap the gap between tech acceleration and the

1153
00:57:19,480 --> 00:57:22,760
Speaker 4: capacity of society to keep up and make informed decisions

1154
00:57:22,800 --> 00:57:27,120
Speaker 4: about that technology, which is actually kind of a useful terms.

1155
00:57:27,160 --> 00:57:28,880
Speaker 4: It's it's just one of those you know, it sounds

1156
00:57:28,880 --> 00:57:31,040
Speaker 4: like a silly tech term, but when the win it's

1157
00:57:31,040 --> 00:57:32,919
Speaker 4: actually explained like, oh, that's actually a really good way

1158
00:57:32,920 --> 00:57:36,040
Speaker 4: to think about the way AI is being pushed in

1159
00:57:36,080 --> 00:57:38,760
Speaker 4: all of these new ways, and are we actually as

1160
00:57:38,800 --> 00:57:41,440
Speaker 4: a society, whether that's like as a government or just

1161
00:57:41,480 --> 00:57:44,160
Speaker 4: like culturally, able to actually make inform decisions about how

1162
00:57:44,160 --> 00:57:46,480
Speaker 4: we want this tech to be integrated into our lives.

1163
00:57:47,120 --> 00:57:49,640
Speaker 4: And now the dark side of this term, the speed

1164
00:57:49,720 --> 00:57:53,320
Speaker 4: capacity gap. For the to to kind of solve this gap,

1165
00:57:53,320 --> 00:57:56,520
Speaker 4: we can either slow down a development or we can

1166
00:57:56,560 --> 00:58:00,440
Speaker 4: speed up our capacity. And the panelists obviously we preferred

1167
00:58:00,480 --> 00:58:04,040
Speaker 4: the latter, and so we should just speed up our

1168
00:58:04,080 --> 00:58:05,080
Speaker 4: cultural capacity.

1169
00:58:05,760 --> 00:58:07,240
Speaker 5: Did they propose a solution for.

1170
00:58:07,240 --> 00:58:12,920
Speaker 4: That, Well, kind of, but it's it's a little unclear.

1171
00:58:12,960 --> 00:58:15,080
Speaker 4: We can go through my recording at a later date

1172
00:58:15,080 --> 00:58:18,720
Speaker 4: once we do our full AI episode. But they're rationale

1173
00:58:18,760 --> 00:58:21,240
Speaker 4: for why we should instead of instead of slowing down

1174
00:58:21,240 --> 00:58:24,560
Speaker 4: tech development instead speed up our cultural capacity is because

1175
00:58:24,640 --> 00:58:28,640
Speaker 4: of the many benefits that tech improvements can be made

1176
00:58:29,360 --> 00:58:32,520
Speaker 4: via tech iterations. Right, the more iterations you get of

1177
00:58:32,520 --> 00:58:35,320
Speaker 4: technology that the more benefits are able to get from

1178
00:58:35,360 --> 00:58:39,440
Speaker 4: said technology. A versioning y version exactly, which brings us

1179
00:58:39,480 --> 00:58:41,120
Speaker 4: all the way back to versioning there we go.

1180
00:58:41,280 --> 00:58:43,840
Speaker 1: Yeah, which brings us all the way back to turkisham fetamines.

1181
00:58:43,880 --> 00:58:46,520
Speaker 1: Because I've been for the last twenty years trying different

1182
00:58:46,760 --> 00:58:51,840
Speaker 1: versions of turkisham fetamines and the blue pills. Man. You know,

1183
00:58:51,960 --> 00:58:55,720
Speaker 1: normally you don't hallucinate on speed, but when you take enough,

1184
00:58:55,800 --> 00:58:58,320
Speaker 1: it turns out you can. And so I think what

1185
00:58:58,360 --> 00:59:01,240
Speaker 1: I'd like to leave everyone with is the knowledge that

1186
00:59:01,360 --> 00:59:03,600
Speaker 1: Turkish shamphetamines are a thing you can purchase on the

1187
00:59:03,680 --> 00:59:06,160
Speaker 1: dark web and should there's no health consequences to it

1188
00:59:06,200 --> 00:59:06,480
Speaker 1: at all.

1189
00:59:07,480 --> 00:59:11,200
Speaker 2: I'm not part of this off line does not support

1190
00:59:11,240 --> 00:59:12,520
Speaker 2: illegal drug purchases.

1191
00:59:12,680 --> 00:59:13,880
Speaker 3: Respectful podcast.

1192
00:59:14,520 --> 00:59:17,600
Speaker 1: They're not illegal if they're so new that the DEA

1193
00:59:17,760 --> 00:59:21,680
Speaker 1: hasn't banned them yet, that's innovation exactly exactly.

1194
00:59:21,960 --> 00:59:29,000
Speaker 2: That's versioning, and that is the speed capacity gap, folks, that.

1195
00:59:32,120 --> 00:59:34,800
Speaker 4: The DA can't keep up with the tech improvements.

1196
00:59:36,400 --> 00:59:38,440
Speaker 1: All right, everybody that's going to do it for us

1197
00:59:38,480 --> 00:59:40,840
Speaker 1: here at cool Zone. Before we leave, I want to

1198
00:59:40,840 --> 00:59:44,600
Speaker 1: give Tabia and Ed both chances to plug their pluggables. Ed,

1199
00:59:44,600 --> 00:59:46,200
Speaker 1: people are going to be hearing from you every week

1200
00:59:46,240 --> 00:59:48,520
Speaker 1: on your new show, Better off Line, which is launching

1201
00:59:48,880 --> 00:59:51,680
Speaker 1: in a what I'm sure you'll agree is a frighteningly

1202
00:59:51,760 --> 00:59:52,600
Speaker 1: short time raace.

1203
00:59:52,720 --> 00:59:52,959
Speaker 4: Soon.

1204
00:59:53,720 --> 00:59:56,160
Speaker 2: It is going to be the best weekly tech show.

1205
00:59:56,560 --> 00:59:58,280
Speaker 2: It is going to do the job that no one

1206
00:59:58,360 --> 01:00:00,880
Speaker 2: is strong enough to do, which is a questions. Listen

1207
01:00:00,920 --> 01:00:03,919
Speaker 2: to the answers, then actually make a question that follows them.

1208
01:00:04,320 --> 01:00:06,680
Speaker 2: I'm very much looking forward to this and very excited

1209
01:00:06,680 --> 01:00:10,720
Speaker 2: to work with the cool Zone team and Tabia.

1210
01:00:11,360 --> 01:00:15,400
Speaker 5: Oh. You can find me on Twitter at cutma and

1211
01:00:15,440 --> 01:00:17,360
Speaker 5: if you want to learn a little bit more about

1212
01:00:17,400 --> 01:00:20,120
Speaker 5: my interactive and immersive work, you can see that at

1213
01:00:20,160 --> 01:00:22,080
Speaker 5: Tabimora dot com.

1214
01:00:22,120 --> 01:00:23,760
Speaker 2: Now you may wonder why I didn't give you any

1215
01:00:23,840 --> 01:00:28,160
Speaker 2: links to anything, and that was a deliberate thing called subterfuge.

1216
01:00:28,160 --> 01:00:29,840
Speaker 2: But you can find me at where's your ed dot

1217
01:00:29,880 --> 01:00:34,800
Speaker 2: at at Edzeitron, on Twitter, x rateminutes, dot bierz, and

1218
01:00:34,880 --> 01:00:37,680
Speaker 2: of course plue sky Zetron, dobisky stot dot social.

1219
01:00:37,880 --> 01:00:44,520
Speaker 1: Yeah, and you can find my profile on here. All right,

1220
01:00:44,560 --> 01:00:45,480
Speaker 1: We're fucking done here.

1221
01:00:51,240 --> 01:00:53,600
Speaker 3: It could happen here as a production of cool Zone Media.

1222
01:00:53,840 --> 01:00:56,480
Speaker 3: For more podcasts from cool Zone Media, visit our website

1223
01:00:56,560 --> 01:00:58,720
Speaker 3: cool zonemedia dot com, or check us out on the

1224
01:00:58,800 --> 01:01:02,200
Speaker 3: iHeartRadio app podcasts, or wherever you listen to podcasts.

1225
01:01:02,640 --> 01:01:04,720
Speaker 4: You can find sources for It could Happen here, updated

1226
01:01:04,840 --> 01:01:07,800
Speaker 4: monthly at coolzonemedia dot com slash sources.

1227
01:01:08,040 --> 01:01:08,840
Speaker 5: Thanks for listening.