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Speaker 1: I get a team, Patrick, James Mean Andlla Craig, Anthony Harper,

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Speaker 1: our Fortnightly get together and you are part of that.

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Speaker 1: In fact, we get here together for you because you're

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Speaker 1: loved by us. Hi, Patrick, how are you doing?

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Speaker 2: I have such an exciting day today, Craigo.

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Speaker 3: Remember what I'm doing today?

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Speaker 1: Thirty three on a Friday. As we record this everyone today,

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Speaker 1: when did you tell me?

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Speaker 2: I don't know, middle of the week.

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Speaker 1: Today, I'm a shit friend Forretney.

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Speaker 2: You laughed at me.

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Speaker 1: What tell me again?

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Speaker 2: I'm waiting for a chimney sweep to come over.

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Speaker 1: Oh, that's right, the chimney sweep. And I said, what

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Speaker 1: is this? Eighteen ten? Are you fucking Oliver? Please? Sir?

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Speaker 1: I want more now. All of our young audience members

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Speaker 1: will not know who Oliver Twist is. Just google it, kids.

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Speaker 1: Why do you have a chimney sweep coming? Well, I

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Speaker 1: guess it's obvious, but I didn't even know that they

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Speaker 1: still existed.

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Speaker 3: People still have chimneys, and they still have flues that

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Speaker 3: connect to their fireplaces. And mine isn't working properly. So

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Speaker 3: the port Fritz, the schnauzer, who's very needy this morning.

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Speaker 3: He and I well, he stood there looking at me

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Speaker 3: while I tried to light the fireplace the other day

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Speaker 3: when it got down to two degrees and smoke started

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Speaker 3: billowing out out of the fire, I thought that flu.

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Speaker 2: Isn't working, first time I've used it this year, so

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Speaker 2: it must be blocked.

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Speaker 3: And all the smoke alarms went off, and I'm running

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Speaker 3: around upstairs with a tea towel and trying to stop

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Speaker 3: the smoke, which wasn't helping. So yeah, I thought, I'm

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Speaker 3: going to have to get desperate now. So I call

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Speaker 3: the local hardware store and yes, they knew a chimney sweep,

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Speaker 3: and he's coming over today.

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Speaker 2: Three weeks later. Wow, in high demand.

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Speaker 1: What's a good thing? It's been unseasonally warm for you? Well,

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Speaker 1: probably not up in the land, but it's been bloody.

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Speaker 1: There's twenty or twenty one the other day down here

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Speaker 1: in I mean, well, I not winter, but nelly winter.

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Speaker 2: Oh for sure. And look we have really chilly, chilly mornings.

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Speaker 3: I have a wheat bag that I put in the

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Speaker 3: microwave to put in my pocket so that my hands

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Speaker 3: don't get cold with that is that is?

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Speaker 2: Oh?

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Speaker 1: I can't say what I was going to say, but

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Speaker 1: fucking ninety eight percent of people would have laughed in

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Speaker 1: two percent would have sent an email. But you know,

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Speaker 1: you know, you know what that is? All right? Apart

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Speaker 1: from that, have you been good? Everything? All right? Why

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Speaker 1: is Fritz a underdog so needy?

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Speaker 3: By the way, because he normally goes through a walk

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Speaker 3: at seven am, we go out for an hour, and

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Speaker 3: because he woke me up at two am and I

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Speaker 3: didn't get back to sleep till three point thirty, I

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Speaker 3: had something of a sleep in.

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Speaker 1: Well, there you go.

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Speaker 2: I haven't taken him out yet. I'm gonna have to

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Speaker 2: take him out after the show.

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Speaker 1: You're in the bad books, but in about an hour

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Speaker 1: you'll be in the good books. It's right. Hey. There's

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Speaker 1: been a bit of chat in the media about some

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Speaker 1: parents and experts wanting to raise the age for social

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Speaker 1: media for teenagers to like sixteen or something, and that's

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Speaker 1: one What are your thoughts on that? And too, how

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Speaker 1: the fuck would you ever enforce that?

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Speaker 2: Yeah, it's a tough one.

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Speaker 3: It's one of those generational things where well, I've got one,

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Speaker 3: all my friends have one. I don't want to not

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Speaker 3: have a phone. I don't want to have access to

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Speaker 3: social media. It's really difficult because a lot of children's

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Speaker 3: identities are also kind of included in that they connect

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Speaker 3: by devices. You know, friends of mine have a fourteen

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Speaker 3: year old and from the age of about eleven or twelve,

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Speaker 3: he was chatting to his mates using his iPad. So

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Speaker 3: how do you rule out social media as opposed to

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Speaker 3: just direct connection, You know, it's really hard. But the

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Speaker 3: reasoning behind this, And look, I'm in two minds and

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Speaker 3: I don't have children, so but I do see friends'

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Speaker 3: kids and I wonder whether there is a problem when

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Speaker 3: people are looking for likes, and that's the big thing

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Speaker 3: that seems to be coming up. It's a and this

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Speaker 3: is an Australian mind you they're saying that the like

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Speaker 3: button the kids.

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Speaker 2: This is specifically about social media.

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Speaker 3: So you put a post up whatever the platform happens

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Speaker 3: to be, and someone likes it. Now, how many likes

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Speaker 3: you get can play a very big part in how

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Speaker 3: you feel about yourself and what you've posted, particularly if

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Speaker 3: you're posting a selfie. You know, think about you at

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Speaker 3: the gym and how many times you post pictures of

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Speaker 3: yourself and you know you.

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Speaker 2: Can one like? You know that must being to you.

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Speaker 1: Yeah, it's fucking I'm straight from here to my therapist

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Speaker 1: because yesterday I only got two Yeah, and what was mum?

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Speaker 1: And the other was Arnie Marge, So.

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Speaker 2: I like you last week yesterday. Oh sorry, I think

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Speaker 2: it was the bear rug.

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Speaker 1: It was slightly out of position.

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Speaker 2: That could have been it. Well, see, there is there

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Speaker 2: is a name for this. It's a new mental kind

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Speaker 2: of health condition.

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Speaker 3: They're calling it problem Internet use or p I you

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Speaker 3: And this this is not just kind of abstract statements

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Speaker 3: being made by people in general. These are quite a

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Speaker 3: few renowned researchers, experts, you know, clinicians who work in

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Speaker 3: the area of child mental health. And that's what they're

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Speaker 3: trying to draw on to discuss ways. You know that

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Speaker 3: this generation of children who potentially are being lost to

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Speaker 3: the likes of you know, meta which is Facebook and Instagram,

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Speaker 3: TikTok and all of those engaging, keep scrolling, keep engaging

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Speaker 3: platforms that just do everything they possibly can to try

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Speaker 3: to keep you online. That's what the whole aim of

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Speaker 3: social media is. So this is coming from the Royal

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Speaker 3: College of Psychiatrists and they're talking about the impact of

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Speaker 3: technology on teenagers and they really are the guinea pigs

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Speaker 3: of this generation, aren't they when you think about it,

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Speaker 3: because they're saying more than four in ten austraeteens, so

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Speaker 3: forty percent suffer from mental health distress, with experts saying

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Speaker 3: that you know, the case are now on the rise,

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Speaker 3: and this is being attributed to social media. But what

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Speaker 3: is even more scary is they're saying the rate of

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Speaker 3: hospitalization for intentional self harm has surged. We're talking by

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Speaker 3: seventy percent in young young women between the age of

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Speaker 3: fifteen and nineteen, and that's from two thousand and eight,

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Speaker 3: two thousand and nine to twenty twenty one, twenty two.

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Speaker 3: So in a very very short amount of time, the

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Speaker 3: warning flags are being raised. And so I mean, it's

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Speaker 3: a long winded answer, but I'm not an expert, but

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Speaker 3: if kids are harming more and there's more distress, then

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Speaker 3: you know, there's got to.

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Speaker 2: Be a way to do it.

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Speaker 3: I mean, I think technology is such an intrinsic part

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Speaker 3: of the lives of everybody, but we as adults can

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Speaker 3: be discerning enough to put it away sometimes.

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Speaker 1: Well, I think, you know, it's like for me, it's

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Speaker 1: a little bit like, you know, cigarettes kill lots of people,

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Speaker 1: but then I've never had a cigarette you either.

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Speaker 3: Right, No, No, I had a we will them two

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Speaker 3: cigar once mate when we were fourteen, and we almost

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Speaker 3: choked the death and that did it for me.

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Speaker 1: Now, well, thanks for interrupting for that. You know, you know,

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Speaker 1: whether or not it's well, I don't think that's a cigarette,

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Speaker 1: whether or not it's booze or cigarettes or technology or

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Speaker 1: pawn or you know, like it's we don't have to

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Speaker 1: use social media, like it's not a rule. But as

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Speaker 1: you and I have spoken about before, if you're fourteen

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Speaker 1: years old, you've never had a world without technology. You know,

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Speaker 1: it's like it's well, maybe a few kids in Australia

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Speaker 1: who grew up in you know, on farms in rural wherever,

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Speaker 1: or in the outback or whatever, but the vast majority

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Speaker 1: of fourteen year old Australian kids have pretty much had

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Speaker 1: their whole life interwoven with technology in one shape or form.

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Speaker 1: And I guess yeah, it's like do we get rid

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Speaker 1: of it? Do we ban it? Or do we teach

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Speaker 1: them how to you know, it's like do we teach

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Speaker 1: kids how to eat well? Do we teach kids how

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Speaker 1: to move their body well? And look after their irreplaceable

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Speaker 1: gift that is their body, do we I don't know.

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Speaker 1: It's like when you just I feel like if you

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Speaker 1: just ban it, I don't know that you're teaching them anything,

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Speaker 1: and I don't know that that is going to be

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Speaker 1: a solution. And at the same time, you think about, well,

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Speaker 1: if not for social media and technology and you and

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Speaker 1: I wouldn't be doing this and we wouldn't have, you

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Speaker 1: know whatever, half a million listeners a month and all

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Speaker 1: the great things that we have. So I don't know

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Speaker 1: that of themselves that all of these things are good

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Speaker 1: or bad, but the rather the way that they are

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Speaker 1: used and experienced and I guess exploited. And you're right,

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Speaker 1: like Meta is a for profit company. It's not a

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Speaker 1: charity metas you know, despite what they'll say, which is

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Speaker 1: all pr and as is it. Of course, every company

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Speaker 1: wants to be seen to be morally conscious and ethical,

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Speaker 1: of course because that's good for the brand. But the

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Speaker 1: bottom line is the bottom line for most companies, like

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Speaker 1: their bottom line is their profit. And if you can

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Speaker 1: the longer that you can keep people on their sites

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Speaker 1: or on their apps or whatever it is, as we've

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Speaker 1: said before, the more profitable it is for them. Right.

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Speaker 3: Look, you know, It's funny whilst you were talking, two

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Speaker 3: things popped into mind. You know, you make that mental

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Speaker 3: ledger the pros and cons. And I'm going to ask

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Speaker 3: you a question. When you were thirteen, fourteen, fifteen, living

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Speaker 3: where you were was out MOOI wait, you know, out

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Speaker 3: in the bush, would you if I sit to you

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Speaker 3: now you can go back in time, would you want

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Speaker 3: social media and to be able to actively actively be

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Speaker 3: a part of it as a kid?

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Speaker 1: Yeow, one hundred percent. No. However, look, I think I

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Speaker 1: think old people and I'm going to not put you

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Speaker 1: in that category, but me in that category. I think

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Speaker 1: we tend to romanticize the past and we go, oh,

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Speaker 1: back in my day, I want to punch people in

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Speaker 1: the face. I'm like, back in your day, it was

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Speaker 1: shit sometimes, you know what I mean. It's like you

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Speaker 1: know that it's everyone thinks that now is shit and

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Speaker 1: then was better, and like, I don't believe that. Like

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Speaker 1: I think that they're being alive now, although there's a

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Speaker 1: lot of shit going on. I think that being alive

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Speaker 1: now depending on where you are, of course, I'm talking

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Speaker 1: about you know, you and me living in first world

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Speaker 1: luxury really in Australia, anyway, it's like it's never been

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Speaker 1: a better time, Like it's never been We've never been

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Speaker 1: more fortunate. Is there bad shit going on? Yes? Was

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Speaker 1: there bad shit going on back then? I think a

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Speaker 1: lot of the current dilemmas that we're dealing with are

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Speaker 1: self created. But for me, I loved my childhood. But

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Speaker 1: then there were kids in the same era as me

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Speaker 1: who had terrible childhoods. But me personally, I wouldn't change it.

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Speaker 3: No, So it's interesting you say that because on the

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Speaker 3: flip side, for me, I had, for the most part,

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Speaker 3: I had a pretty good upbringing. I had a lot

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Speaker 3: of freedom, got on my bike, got up in the

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Speaker 3: morning on a Saturday, and didn't come home till nighttime,

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Speaker 3: you know, stayed at the mate's place. But as an

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Speaker 3: older teen, and I'm thinking about this demographic we're talking about,

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Speaker 3: I felt sad and isolated a lot of the time,

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Speaker 3: psychologically mentally unconnected, and I it was Yeah, it was

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Speaker 3: a really tough time. And if I had been able

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Speaker 3: to connect with peers online, if I'd been able to

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Speaker 3: realize that I was okay and that there were other

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Speaker 3: people like me, then my negative thoughts self harm probably

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Speaker 3: wouldn't have happened, so I.

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Speaker 1: Think, and that's a beautiful example of there is no

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Speaker 1: right or wrong, but it's right and wrong for the individual.

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Speaker 1: And it's like, for you, I agree, it probably would

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Speaker 1: have made your life better. I don't think it would

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Speaker 1: have made my life better, but it may it may have.

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Speaker 1: I don't know, but I think for you that's a

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Speaker 1: and I think, like when we extrapolate this, mate, you think, well,

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Speaker 1: there are lots of kids who use social media without problems,

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Speaker 1: and there are lots that probably more that have. You know,

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Speaker 1: I don't know what the percentage is, but yeah, I

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Speaker 1: sometimes I think we need to figure out what is

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Speaker 1: the underlying cause, because it's like technology can be used

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Speaker 1: for great stuff, but not so great stuff.

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Speaker 2: Can I throw some stats at you?

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Speaker 1: Sure?

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Speaker 3: So there's a campaign called let Them Be Kids, and

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Speaker 3: they did a serve a recently of over three thousand

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Speaker 3: social media users and this is what their pole come

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Speaker 3: up with. Seventy percent of teens have had a negative

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Speaker 3: experience on social media, three has been exposed to disturbing

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Speaker 3: or traumatic content, Forty five percent have been abused or harassed,

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Speaker 3: one in four have been cyber bullied or sexually harassed.

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Speaker 3: Fifty nine percent have been scammed and one in ten

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Speaker 3: have been the victim of revenge porn. So when those

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Speaker 3: statistics are thrown out, it's frighteningly high. And I guess,

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Speaker 3: you know, it's three thousand social media users. Now I'd

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Speaker 3: want to dig further into those stats, to be honest,

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Speaker 3: I'd want to know, you know, the demographic spread, all

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Speaker 3: that sort of thing. But those seem like pretty worrying

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Speaker 3: statistics to me. And I guess we have to rely

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Speaker 3: on the experts and not rely on knee jerk, not

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Speaker 3: rely on you know, the media blowing things out of proportion.

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Speaker 3: And I guess what you do is you set up

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Speaker 3: working groups with psychologists, with people who understand the industry,

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Speaker 3: and you get the brains into the building. And that's

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Speaker 3: how you make those decisions. You know, often you think

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Speaker 3: about politics, where I certainly think about politics, and you think,

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Speaker 3: I wonder how many politicians actually did science and have doctorates,

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Speaker 3: And they don't because generally, the pool of people, the

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Speaker 3: talent pool of people who want to get into politics

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Speaker 3: generally don't come from the science and technology background.

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Speaker 2: But that's why you employ experts.

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Speaker 3: From the CSIRO and other organizations to be advisors. So

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Speaker 3: I guess my response to all of this is we

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Speaker 3: can speculate as much as we like and kind of

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Speaker 3: look back and reminisce and they wouldn't have been nice.

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Speaker 2: But the reality is, I guess it's out of our hands.

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Speaker 3: And I hope that whoever does make the decisions is

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Speaker 3: asking the right questions of the right people.

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Speaker 1: Yeah, yeah, no, I think that's very valid. There's also

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Speaker 1: there's also another component that I think of, which is

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Speaker 1: is teaching people to be able to self regulate and

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Speaker 1: make good decisions. And what doors do I open? You know,

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Speaker 1: what metaphoric doors do I open? If I choose to

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Speaker 1: go and watch porn? You know that can become problematic. Well,

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Speaker 1: nobody put a gun to my head. But I'm doing it.

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Speaker 1: I'm going back each day or if I choose to.

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Speaker 1: You know, I'm not saying that the kids are at fault.

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Speaker 1: I'm saying, you know, we stick like we For me,

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Speaker 1: I find this a little bit. What's the words. I'm

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Speaker 1: curious and fascinated around being a teenager now, the experience

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Speaker 1: of being a teenager, because in a minute they're going

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Speaker 1: to be adults, right, and the world doesn't give a

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Speaker 1: fuck about your emotions or your feelings, right, and so

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Speaker 1: when you step out of the nest, you know, the

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Speaker 1: bubble where everyone's like you okay, And we need that.

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Speaker 1: Of course, we need love, care, compassion, of course, but

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Speaker 1: also at the same time, we need to build kids

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Speaker 1: to be able to or to help empower them to

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Speaker 1: be able to be strong and resilient and make good

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Speaker 1: decisions and be aware and be in charge of their

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Speaker 1: own life. And you know, because the fourteen year old

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Speaker 1: in a minute is going to be an adult with

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Speaker 1: a job or at university and driving a car and

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Speaker 1: legally drinking booze and socializing with other adults. And so

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Speaker 1: while we need to protect them, of course, I think

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Speaker 1: we also need to from a sociological, psychological, emotional point

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Speaker 1: of view, help equip them so that they are independently thinking,

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Speaker 1: critically making decisions, and that they can build emotional and

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Speaker 1: psychological resilience. Because the only person who can ultimately manage

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Speaker 1: your life is you. So like, let's yes, let's do

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Speaker 1: all of these things, let's make decisions. But you know,

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Speaker 1: like I would want if I And of course this

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Speaker 1: is just an old white guy with no children, so

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Speaker 1: whatever it means, But I know a little bit about

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Speaker 1: human behavior. But if I had kids, I would want

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Speaker 1: them to come out the other side of their teenage

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Speaker 1: years as a really well prepared adult for life. So

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Speaker 1: I think there's a big emphasis on don't let them

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Speaker 1: do this, do let them do that, all of that,

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Speaker 1: but also how do we help them self regulate so

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Speaker 1: that we're not running the show and we're empowering them

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Speaker 1: as well.

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Speaker 3: My friends, I've got a great couple of friends who

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Speaker 3: live now near you, as you know, and they've got

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Speaker 3: two boys, young ones a young man now, the other

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Speaker 3: one's still about turn fifteen. But what's always impressed me

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Speaker 3: about them is they've never been shoved in the corner

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Speaker 3: while adults are present.

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Speaker 2: What they do is encourage dialogue.

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Speaker 3: So we play board games, they sit at the table,

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Speaker 3: they join into the discussions, so there's no taboo subjects.

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Speaker 3: They're pretty open about whatever discussion happens to come up,

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Speaker 3: and they'll answer questions. And I think that approach leads

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Speaker 3: to a more worldly and sometimes we underestimate young people

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Speaker 3: the intellect, the sense for wanting to know and understand,

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Speaker 3: and so I think in a lot of ways, the

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Speaker 3: approach that individuals take, whether you happen to be a

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Speaker 3: parent or a grandparent or a friend of so always

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Speaker 3: being open to have discussion, and so maybe that's the approach.

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Speaker 3: I'm going to change the topic a little bit, if

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Speaker 3: that's okay with you, because this is something that I

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Speaker 3: was really really wondering about. When you go to a shop,

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Speaker 3: do you ask for a receipt? You know they've got

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Speaker 3: the button sometimes receipt you ask do you get the receipt?

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Speaker 1: I know I probably should say it depends on what

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Speaker 1: it is, but in general terms, no, Well.

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Speaker 3: That's interesting because generally the fact that you ask for

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Speaker 3: a receipt can sometimes work out whether you're a millennial

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Speaker 3: or you're older.

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Speaker 2: Evidently, so really older people always.

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Speaker 3: Ask for receipts, and young people can't understand why we

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Speaker 3: use receipts. My caveat on that is if I'm getting

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Speaker 3: anything that I might potentially need to take back, and

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Speaker 3: I have an electronic version because you know, I do

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Speaker 3: my JB shop and I always get it sent to

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Speaker 3: my phone because we all remember remember the old I

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Speaker 3: think they still do that thermal paper where the receipt

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Speaker 3: ends up fading anyway, so there's not really much point

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Speaker 3: to it.

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Speaker 1: Yeah, yeah, and then like one side was shiny.

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Speaker 2: Yeah, yeah, that's right.

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Speaker 3: Yeah, And look, my bookkeeper always gives me a hard

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Speaker 3: time about not keeping receipts, but I do the I

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Speaker 3: just snap a photo of them with quick books on

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Speaker 3: my phone, and that way I don't get in trouble

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Speaker 3: every week, which I normally do for spending stuff and

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Speaker 3: buying stuff I shouldn't have.

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Speaker 2: But I thought it was interesting that you don't keep receipts.

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Speaker 3: But evidently gen Z generation Z doesn't have wallets or

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Speaker 3: time for paper.

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Speaker 2: I mean that's true too.

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Speaker 3: I mean my wallet, I should admit this sits in

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Speaker 3: my car never ever ever is in my pack?

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Speaker 1: Could you not say that ship on a podcast?

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Speaker 2: Did I leave my walk in my car? I do

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Speaker 2: lock my car most of the time.

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Speaker 1: Well, geez, because nobody can get into a car ever,

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Speaker 1: so well, that's totally secure.

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Speaker 2: I don't even have to break a window.

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Speaker 3: The other day, I let the window open, got back

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Speaker 3: after shopping at the local supermarket and thought, well, yeah,

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Speaker 3: I opened the window.

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Speaker 1: There's I don't yeah, I'm I'm I just paid for

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Speaker 1: everything through my phone, like I don't. I don't even

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Speaker 1: take money. I don't even take my wallet.

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Speaker 2: Yeah, and as you know, when we've gone out anywhere,

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Speaker 2: I use my watch. But it's interesting.

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Speaker 3: I just was curious as to whether or not you

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Speaker 3: fell into that category as an old fogie.

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Speaker 1: But well, I am probably, I'm probably. I don't know that,

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Speaker 1: you know. In some ways, I'm probably an old fogy. Probably.

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Speaker 1: Otherwise I'm a little bit atypical. You know, I could

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Speaker 1: literally be a granddad, which is fucking hilarious. Tell me

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Speaker 1: about neural link one of my favorite things in the

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Speaker 1: world of technology. I'm so fascinated with this thing and

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Speaker 1: what's going to happen with it over the next year

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Speaker 1: or ten.

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Speaker 3: Okay, one bloke's got it so far, and there's now

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Speaker 3: pushed to get two more people. So it's been given

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Speaker 3: FDA approval in the United States, the medical authority that

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Speaker 3: basically says you can do real life experimentation.

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Speaker 2: I suppose.

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Speaker 1: Now.

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Speaker 3: The thing is, what we need to understand is the

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Speaker 3: person who has had the implant has now been able

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Speaker 3: to they're totally incapacitated, and they're able to play video

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Speaker 3: games and do a whole lot of stuff on a

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Speaker 3: computer that they weren't.

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Speaker 2: Able to previously.

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Speaker 3: So it's given them a level of freedom that they

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Speaker 3: hadn't previously experienced.

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Speaker 2: And you know, we've spoken about this. I would hate

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Speaker 2: to have anything implanted in my head.

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Speaker 3: However, that's all a relative decision, because if you were

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Speaker 3: trapped in your body, you probably would. So the neural

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Speaker 3: link now they're talking about the next two people are

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Speaker 3: potentially going to be implanted with Elon Musk's chip. The

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Speaker 3: only thing that would worry me is that, I don't know.

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Speaker 3: I don't know if you know this, but there are

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Speaker 3: certain features in Tesla's that don't get turned on unless

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Speaker 3: you pay a subscription, So you know, could you imagine

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Speaker 3: if and that's even speed limiting I heard recently. Could

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Speaker 3: you imagine if you bought, you know, one of your

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Speaker 3: great bikes that you've got, if they said, oh, you

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Speaker 3: buy subscription, it could go faster.

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Speaker 2: It's like, what's I mean, I own I paid for it,

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Speaker 2: now you want to make me unlock.

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Speaker 1: That's what scares me about about Essentially, cars that are

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Speaker 1: a computer on air on wheels, and you think about

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Speaker 1: the fact that they can literally from from wherever in

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Speaker 1: the world, they can program your car to do different stuff,

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Speaker 1: to have more power, to to be able to access

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Speaker 1: different features or whatever. Well, if they can do that,

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Speaker 1: surely they can make the brakes not work or somebody.

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Speaker 1: You know, it's like, obviously Tesla wouldn't do that, but

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Speaker 1: but imagine if somebody like things get hacked all the time.

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Speaker 1: And I just I just I am. I'm not as

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Speaker 1: optimistic about the cars. And I love cars on my

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Speaker 1: car head, but I'm not as optimistic about all the

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Speaker 1: technology that's happening in cars right now, even EV's. I

436
00:23:11,359 --> 00:23:16,440
Speaker 1: think theoretically electronic electric vehicles are a good idea, but

437
00:23:16,600 --> 00:23:19,720
Speaker 1: I don't know that practically that's going to work out.

438
00:23:19,840 --> 00:23:23,679
Speaker 1: We know that EV price is secondhand prices are plummeting

439
00:23:24,359 --> 00:23:29,040
Speaker 1: and second hand and new sales are dropping. I don't know.

440
00:23:29,920 --> 00:23:33,760
Speaker 1: There's something to be said for like a basic car

441
00:23:33,840 --> 00:23:39,080
Speaker 1: that runs well, that doesn't that isn't completely technologically dependent.

442
00:23:39,960 --> 00:23:42,159
Speaker 1: I don't know. I don't know. It just makes me

443
00:23:42,200 --> 00:23:42,840
Speaker 1: a little nervous.

444
00:23:42,960 --> 00:23:45,040
Speaker 3: Imagine that you never have to go to a petrol

445
00:23:45,040 --> 00:23:48,199
Speaker 3: station ever again, that you get in your car and

446
00:23:48,240 --> 00:23:51,480
Speaker 3: it's fully charged, You drive off, get home, plug it

447
00:23:51,520 --> 00:23:53,280
Speaker 3: back in again, and it's ready to go again.

448
00:23:53,880 --> 00:23:56,800
Speaker 1: But imagine imagine I'm driving to Ron and Mary's and

449
00:23:56,840 --> 00:24:01,160
Speaker 1: I run out and there's no EV station like this

450
00:24:01,240 --> 00:24:03,119
Speaker 1: is I mean, this is happening to a lot of

451
00:24:03,160 --> 00:24:08,439
Speaker 1: people because there's there's the limitation of they can't and

452
00:24:08,480 --> 00:24:10,320
Speaker 1: then when you've got to charge, you've got to wait

453
00:24:10,440 --> 00:24:15,040
Speaker 1: minimum forty five minutes for it to charge. So I

454
00:24:15,119 --> 00:24:18,640
Speaker 1: know what you're saying, but it's not all that positive,

455
00:24:18,720 --> 00:24:22,600
Speaker 1: and you're very pro ev and I understand it, and

456
00:24:22,680 --> 00:24:25,840
Speaker 1: I'm not pro ORAENTTI. I'm just I'm like, I'm interested

457
00:24:25,880 --> 00:24:29,880
Speaker 1: in the reality of Look, I could be completely wrong.

458
00:24:29,880 --> 00:24:31,840
Speaker 1: I'm going to go on the record, I don't think

459
00:24:32,320 --> 00:24:34,440
Speaker 1: electric vehicles are going to take off.

460
00:24:34,560 --> 00:24:39,040
Speaker 3: All right, I respond to that, no, Go okay. First

461
00:24:39,040 --> 00:24:41,880
Speaker 3: thing is, if you're planning to go and visit your

462
00:24:41,920 --> 00:24:45,119
Speaker 3: folks and you had an electric vehicle, you would be

463
00:24:45,160 --> 00:24:48,000
Speaker 3: able to instantly know what the range is and how

464
00:24:48,000 --> 00:24:51,280
Speaker 3: many charging stations there are between there. So cars are

465
00:24:51,280 --> 00:24:53,160
Speaker 3: now smart enough to know whether you've got the range

466
00:24:53,160 --> 00:24:54,760
Speaker 3: to get there, and if you don't have the range,

467
00:24:54,960 --> 00:24:57,840
Speaker 3: where you can get to and then charge up accordingly.

468
00:24:57,920 --> 00:25:00,199
Speaker 3: So it is planned around it to have brunch or

469
00:25:00,320 --> 00:25:03,439
Speaker 3: a lunch or something on the way there, but.

470
00:25:03,320 --> 00:25:04,920
Speaker 1: Not if you don't want to have brunch or lunch.

471
00:25:05,000 --> 00:25:07,160
Speaker 1: Like you go, oh wow, I can fill up at Warrigal,

472
00:25:07,160 --> 00:25:10,960
Speaker 1: but it's fucking an hour to fill up. Like I

473
00:25:11,000 --> 00:25:13,640
Speaker 1: know you're trying to do the sales pitch. I get it.

474
00:25:14,720 --> 00:25:18,560
Speaker 1: But also it doesn't know the exact driving range because

475
00:25:18,560 --> 00:25:20,879
Speaker 1: there are so many variables. How many people are in

476
00:25:20,880 --> 00:25:26,240
Speaker 1: the car, the weight of the passengers affects the range,

477
00:25:26,240 --> 00:25:30,920
Speaker 1: how fast you drive affects the range. It's not perfect technology,

478
00:25:30,960 --> 00:25:34,960
Speaker 1: that's for sure. But I think they're you know, I

479
00:25:35,000 --> 00:25:37,920
Speaker 1: think there's a case for them. I'm not anti them

480
00:25:37,960 --> 00:25:42,800
Speaker 1: at all. In fact, the idea excites me. But I

481
00:25:42,840 --> 00:25:47,600
Speaker 1: think there's so many natural resources that are actually being

482
00:25:47,760 --> 00:25:52,040
Speaker 1: used in production it's almost ironic. And we've even got

483
00:25:52,119 --> 00:25:57,080
Speaker 1: electric charging stations in remote areas that are being fueled

484
00:25:57,119 --> 00:26:01,280
Speaker 1: by diesel generators, which is the fucking height of irony.

485
00:26:01,359 --> 00:26:03,879
Speaker 1: And it's not a few, it's it's a lot. So

486
00:26:05,119 --> 00:26:07,240
Speaker 1: is it? Look, I could be wrong, and if I'm wrong,

487
00:26:07,240 --> 00:26:09,520
Speaker 1: I'll be the first to go I'm wrong, But I

488
00:26:10,160 --> 00:26:13,159
Speaker 1: don't think. I don't think e these are the magic

489
00:26:13,240 --> 00:26:14,840
Speaker 1: pill that we think they might be.

490
00:26:15,280 --> 00:26:19,000
Speaker 3: Yeah, so you know how I said, I have two points? Yeah, Okay, cold,

491
00:26:19,000 --> 00:26:20,480
Speaker 3: I say my second one.

492
00:26:20,840 --> 00:26:26,840
Speaker 1: No, you, you and your two points? All right?

493
00:26:28,280 --> 00:26:31,399
Speaker 3: You did you actually rightly mentioned that the uptake of

494
00:26:31,400 --> 00:26:35,200
Speaker 3: electric vehicles and we're just saying Australia is an ecosystem

495
00:26:35,520 --> 00:26:37,639
Speaker 3: has been a little bit slow, so they you know,

496
00:26:37,640 --> 00:26:41,280
Speaker 3: there was this initial burst and that's been fairly consistent.

497
00:26:41,640 --> 00:26:44,199
Speaker 3: But I think that the limiting factor has been the

498
00:26:44,400 --> 00:26:48,440
Speaker 3: entry level price. And you know, I have come out

499
00:26:48,440 --> 00:26:50,800
Speaker 3: and said many times that I couldn't afford an electric

500
00:26:50,840 --> 00:26:53,600
Speaker 3: car when I needed a car just after COVID, so

501
00:26:53,680 --> 00:26:55,359
Speaker 3: I didn't get we've got a hybrid instead.

502
00:26:55,640 --> 00:26:58,240
Speaker 2: However, that's said, we are soon going.

503
00:26:58,040 --> 00:27:02,240
Speaker 3: To see a big flood of electric Chinese cars hitting

504
00:27:02,240 --> 00:27:05,560
Speaker 3: the market, which will be under forty thousand dollars. And

505
00:27:05,600 --> 00:27:09,520
Speaker 3: I think that may be the additional hurdle because you know,

506
00:27:09,680 --> 00:27:11,040
Speaker 3: you're right, going.

507
00:27:10,800 --> 00:27:13,040
Speaker 2: From where you live and doing.

508
00:27:12,920 --> 00:27:16,600
Speaker 3: Long distance tripping can be problematic, but if you could

509
00:27:16,720 --> 00:27:20,560
Speaker 3: drive just in a city, electric vehicles are fantastic.

510
00:27:20,800 --> 00:27:23,280
Speaker 2: Think of the reduction in pollution. And there are some

511
00:27:23,320 --> 00:27:24,720
Speaker 2: really great little cars.

512
00:27:25,160 --> 00:27:28,000
Speaker 3: There's an amazing car that Reno put out which was

513
00:27:28,119 --> 00:27:30,840
Speaker 3: termed as a buggy and not allowed in Australia.

514
00:27:30,920 --> 00:27:34,280
Speaker 2: It was a one seater and it had goal wing doors.

515
00:27:34,400 --> 00:27:38,160
Speaker 3: This is like the ultimate mrdy little electric car maximum

516
00:27:38,200 --> 00:27:41,359
Speaker 3: speed maybe fifty clicks. If I could have bought one

517
00:27:41,880 --> 00:27:44,800
Speaker 3: for I think it was maybe fifteen grand I would

518
00:27:44,800 --> 00:27:47,000
Speaker 3: be driving that around my little town and doing my

519
00:27:47,080 --> 00:27:49,000
Speaker 3: shopping and put Fritzy on my lap and we'd just

520
00:27:49,000 --> 00:27:52,280
Speaker 3: be driving around, pottering around in my little electric vehicle.

521
00:27:52,440 --> 00:27:53,920
Speaker 2: I saw it in Europe when I was over there

522
00:27:53,920 --> 00:27:56,359
Speaker 2: in Malta, and it's like, I love this car. It

523
00:27:56,480 --> 00:27:57,320
Speaker 2: was so cool.

524
00:27:57,520 --> 00:28:00,320
Speaker 3: But Reno weren't allowed to bring it into Australia because

525
00:28:00,359 --> 00:28:02,879
Speaker 3: it was classified as a buggy, not as a car.

526
00:28:03,200 --> 00:28:05,520
Speaker 3: And that's why this little electric vehicle, it may have

527
00:28:05,520 --> 00:28:07,480
Speaker 3: had a range of maybe one hundred and twenty k's

528
00:28:07,520 --> 00:28:09,440
Speaker 3: not far and you wouldn't put on a highway.

529
00:28:09,840 --> 00:28:10,520
Speaker 2: But what a.

530
00:28:10,440 --> 00:28:13,520
Speaker 3: Great little vehicle just to be you whizzing around And

531
00:28:13,560 --> 00:28:16,200
Speaker 3: if you think about where you live parking, you park

532
00:28:16,320 --> 00:28:19,600
Speaker 3: straight into the right into the curb because the car

533
00:28:19,720 --> 00:28:23,600
Speaker 3: is so small, it's it's as long as a standard

534
00:28:23,600 --> 00:28:27,320
Speaker 3: car is wide, so you know, you would have many

535
00:28:27,359 --> 00:28:30,800
Speaker 3: more parking spaces, potentially two to three more parking spaces

536
00:28:30,840 --> 00:28:35,359
Speaker 3: per parking space, and for zipping around in suburbia. They'd

537
00:28:35,359 --> 00:28:36,120
Speaker 3: be fantastic.

538
00:28:36,680 --> 00:28:39,560
Speaker 1: You know what, it'd be better a scooter that you

539
00:28:39,640 --> 00:28:42,600
Speaker 1: park on the footpath out of everyone's.

540
00:28:42,080 --> 00:28:43,840
Speaker 2: Way, which I have, which I have.

541
00:28:44,680 --> 00:28:45,760
Speaker 1: No, you have a scooter.

542
00:28:45,840 --> 00:28:46,440
Speaker 2: No you don't have it.

543
00:28:46,520 --> 00:28:51,240
Speaker 1: You are a toy. That's not a scooter. That's a

544
00:28:51,440 --> 00:28:54,600
Speaker 1: fucking that's something from kmart. That's seven year olds.

545
00:28:54,680 --> 00:29:00,920
Speaker 3: Rightlome is an hour downhill with the hell what do

546
00:29:00,960 --> 00:29:02,960
Speaker 3: you get in the fucking the race position?

547
00:29:03,080 --> 00:29:05,760
Speaker 1: Do you flection your these? Get your head down behind

548
00:29:05,800 --> 00:29:06,680
Speaker 1: the handlebars.

549
00:29:06,880 --> 00:29:08,320
Speaker 2: I bought a new helmet the other day.

550
00:29:08,400 --> 00:29:13,480
Speaker 3: Well, it's black, it's kind of it's kind of gun

551
00:29:13,520 --> 00:29:14,120
Speaker 3: metal gray.

552
00:29:14,280 --> 00:29:16,960
Speaker 2: It looks a bit cool, and it's got the fate. Yeah,

553
00:29:17,000 --> 00:29:17,760
Speaker 2: you know I'm not gonna win you.

554
00:29:17,960 --> 00:29:20,560
Speaker 1: It looks a bit cool. He's the guy who rides

555
00:29:20,560 --> 00:29:22,160
Speaker 1: a scooter that goes twenty segway.

556
00:29:22,240 --> 00:29:24,120
Speaker 2: Scooter that folds down flat.

557
00:29:24,160 --> 00:29:26,200
Speaker 3: It's pretty. It's got lights on it. I can make

558
00:29:26,240 --> 00:29:27,480
Speaker 3: it flash lights as well.

559
00:29:28,120 --> 00:29:30,800
Speaker 1: I've done. By the way, you can't drive with a

560
00:29:30,880 --> 00:29:33,960
Speaker 1: dog on your lap. It's illegal. You're welcome, all right.

561
00:29:34,000 --> 00:29:36,200
Speaker 1: So you're very excited about a new gadget, which is

562
00:29:36,200 --> 00:29:39,400
Speaker 1: not uncommon for you because you get easily excited about gadgets,

563
00:29:39,400 --> 00:29:40,280
Speaker 1: But what is it?

564
00:29:40,840 --> 00:29:42,560
Speaker 2: AI headphones?

565
00:29:44,240 --> 00:29:45,280
Speaker 1: What does that even mean?

566
00:29:45,480 --> 00:29:48,400
Speaker 2: Okay, you've got noise canceling headphones, haven't you?

567
00:29:48,920 --> 00:29:49,280
Speaker 1: I do?

568
00:29:49,640 --> 00:29:52,280
Speaker 2: Okay, So noise canceling headphones are fantastic.

569
00:29:52,360 --> 00:29:55,760
Speaker 3: I wear them on public transport and flying because they

570
00:29:55,800 --> 00:29:59,440
Speaker 3: can listen to a sound and wipe out a consistent sound,

571
00:29:59,480 --> 00:30:01,800
Speaker 3: so an noise, which means you get a.

572
00:30:01,840 --> 00:30:02,800
Speaker 2: Much better trip.

573
00:30:03,440 --> 00:30:07,760
Speaker 3: Whereas these new noise canceling headphones are out of sight.

574
00:30:07,880 --> 00:30:10,480
Speaker 3: These are amazing. If you can imagine putting on noise

575
00:30:10,520 --> 00:30:14,080
Speaker 3: canceling headphones, being in a crowded room and I look

576
00:30:14,080 --> 00:30:17,240
Speaker 3: at you for three or four seconds, the AI built

577
00:30:17,240 --> 00:30:20,280
Speaker 3: into the noise canceling system will wipe out all the

578
00:30:20,360 --> 00:30:25,280
Speaker 3: other voices, all the other noises except your voice, and

579
00:30:25,360 --> 00:30:28,719
Speaker 3: even if you walk around, it will still continue to

580
00:30:28,800 --> 00:30:29,280
Speaker 3: listen to.

581
00:30:29,480 --> 00:30:30,600
Speaker 2: Just your voice.

582
00:30:30,800 --> 00:30:33,280
Speaker 3: So particularly, I've got a good friend of mine who

583
00:30:33,320 --> 00:30:37,000
Speaker 3: has hearing problems. They had an infection and an illness

584
00:30:37,040 --> 00:30:40,160
Speaker 3: and was similar to tenatus. And admit that he's now

585
00:30:40,240 --> 00:30:43,360
Speaker 3: very socially isolated if in large groups, and we've had

586
00:30:43,360 --> 00:30:44,000
Speaker 3: this discussion.

587
00:30:44,040 --> 00:30:46,040
Speaker 2: He doesn't even have big birthday parties.

588
00:30:46,280 --> 00:30:49,120
Speaker 3: Generally it's small gathering because he just can't cope with

589
00:30:49,160 --> 00:30:53,040
Speaker 3: all these voices. So these headphones that they're they're developing

590
00:30:53,080 --> 00:30:56,600
Speaker 3: at the University of Washington, so researchers are currently working

591
00:30:56,600 --> 00:31:00,560
Speaker 3: on these. They're an adaptive noise canceling so you can

592
00:31:00,640 --> 00:31:03,720
Speaker 3: isolate a single person that you're having a conversation with

593
00:31:03,800 --> 00:31:06,720
Speaker 3: in a room and cancel every other sound out. That

594
00:31:06,840 --> 00:31:09,880
Speaker 3: to me is fantastic, Isn't that? That's so cool?

595
00:31:10,480 --> 00:31:11,920
Speaker 1: How's your memory, Grandpa?

596
00:31:12,720 --> 00:31:13,360
Speaker 2: Yeah?

597
00:31:13,480 --> 00:31:16,240
Speaker 1: Was that I spoke to you about this last episode?

598
00:31:16,640 --> 00:31:17,320
Speaker 2: Did you really?

599
00:31:17,800 --> 00:31:21,280
Speaker 1: Yeah? I told you, Yeah, I told you. I just

600
00:31:21,360 --> 00:31:25,280
Speaker 1: watched a video. There was a dude and he was

601
00:31:25,320 --> 00:31:28,520
Speaker 1: sitting at a table and everyone was talking and it

602
00:31:28,640 --> 00:31:32,000
Speaker 1: was crazy, and then he was talking to another guy.

603
00:31:32,080 --> 00:31:34,120
Speaker 1: Then all of the other noise drowned out and you

604
00:31:34,160 --> 00:31:37,200
Speaker 1: could just hear his voice. So thanks for repeating that

605
00:31:37,280 --> 00:31:39,800
Speaker 1: story that I broke last time. You're welcome.

606
00:31:39,920 --> 00:31:43,040
Speaker 2: Oh geez, I really pay attention to you, don't I.

607
00:31:43,080 --> 00:31:47,400
Speaker 1: You really should. But having said that is it is

608
00:31:47,440 --> 00:31:51,200
Speaker 1: a really good idea, And I mean, imagine that's one

609
00:31:51,240 --> 00:31:55,000
Speaker 1: of my things. I just, you know, old person alert.

610
00:31:56,360 --> 00:31:59,400
Speaker 1: But yeah, being in really you know where you know,

611
00:31:59,400 --> 00:32:01,720
Speaker 1: We're in unim environment and a million people are talking,

612
00:32:01,760 --> 00:32:04,000
Speaker 1: which is not good or bad. But then trying to

613
00:32:04,040 --> 00:32:07,240
Speaker 1: actually have a meaningful dialogue with somebody where you're essentially

614
00:32:07,240 --> 00:32:10,120
Speaker 1: got to yell into their ear to it's not really

615
00:32:10,120 --> 00:32:13,440
Speaker 1: optimal for me, but being able to. But are these

616
00:32:13,480 --> 00:32:16,640
Speaker 1: actual headphones that you are they you've got to wear

617
00:32:16,800 --> 00:32:20,640
Speaker 1: over your ears or are they ones that you stick

618
00:32:20,720 --> 00:32:21,160
Speaker 1: in your ear?

619
00:32:21,680 --> 00:32:24,160
Speaker 3: They're still developing them, and I guess there's also the

620
00:32:24,160 --> 00:32:29,240
Speaker 3: bone conducting ones as well. Because noise cancelation is just

621
00:32:29,280 --> 00:32:32,640
Speaker 3: a negative wave, isn't it. So what happens is when

622
00:32:32,720 --> 00:32:35,760
Speaker 3: you put the headphones on, if you've got a consistent frequency,

623
00:32:36,240 --> 00:32:39,080
Speaker 3: they then invert that frequency and it cancels it out

624
00:32:39,560 --> 00:32:40,760
Speaker 3: so effectively.

625
00:32:40,960 --> 00:32:41,680
Speaker 2: If it can do.

626
00:32:41,720 --> 00:32:43,840
Speaker 3: That, it wouldn't Why if you just put your headphones on,

627
00:32:44,760 --> 00:32:45,720
Speaker 3: are you blocking me out?

628
00:32:46,040 --> 00:32:47,920
Speaker 1: I just put on the noise canceling My.

629
00:32:47,760 --> 00:32:49,480
Speaker 2: God, that is so rude.

630
00:32:52,360 --> 00:32:54,520
Speaker 1: Do you know when I put on I have Sony

631
00:32:54,600 --> 00:32:57,200
Speaker 1: I think they're called one thousand W X or X.

632
00:32:57,280 --> 00:33:02,440
Speaker 1: You know they're really good? Break dad, I press the button. Yeah,

633
00:33:02,480 --> 00:33:05,680
Speaker 1: I press the button and the lady goes noise canceling

634
00:33:06,000 --> 00:33:09,560
Speaker 1: on and all of a sudden the room just like

635
00:33:10,120 --> 00:33:12,719
Speaker 1: it's like now I'm in a vacuum. It's so fucking

636
00:33:12,760 --> 00:33:13,480
Speaker 1: effective that.

637
00:33:14,040 --> 00:33:16,920
Speaker 3: Yeah, noise cancelation's really cool. So in answer to your question,

638
00:33:17,000 --> 00:33:18,480
Speaker 3: I don't know that they've got to the point where

639
00:33:18,800 --> 00:33:22,200
Speaker 3: I mean headphones as opposed to earbuds infer that they

640
00:33:22,200 --> 00:33:25,880
Speaker 3: go over your ears. So, but you can get inner

641
00:33:25,920 --> 00:33:28,960
Speaker 3: ear noise canceling headphones as well. And I guess if

642
00:33:29,000 --> 00:33:30,880
Speaker 3: you're going to be in a social setting, you do

643
00:33:31,080 --> 00:33:33,480
Speaker 3: want to be able to be as subtle as possible

644
00:33:33,560 --> 00:33:36,080
Speaker 3: rather than you know, the old chunky headphones. But have

645
00:33:36,200 --> 00:33:39,800
Speaker 3: you noticed kids are wearing them down the street now more? Yes,

646
00:33:39,880 --> 00:33:42,640
Speaker 3: over ear headphones have become really popular that you know that.

647
00:33:42,680 --> 00:33:45,160
Speaker 3: I've got this a teenager who works for me, who

648
00:33:45,240 --> 00:33:48,840
Speaker 3: works after schools sixteen, and he walks in. He's got

649
00:33:48,920 --> 00:33:50,480
Speaker 3: his headphones on. Hi, how you doing?

650
00:33:50,720 --> 00:33:53,600
Speaker 2: Yeah? Hi, sits down, does his work with his headphones on?

651
00:33:54,520 --> 00:33:57,920
Speaker 1: Yeah, it's well. At the gym, it's it's like it's

652
00:33:57,960 --> 00:34:00,280
Speaker 1: the thing like if you are in the gym, or

653
00:34:00,920 --> 00:34:04,920
Speaker 1: if you're in the gym where I train at four thirty,

654
00:34:06,160 --> 00:34:08,680
Speaker 1: you will be the odd one out if you're not

655
00:34:08,719 --> 00:34:11,959
Speaker 1: wearing over ear headphones. If there's twenty people in there,

656
00:34:12,840 --> 00:34:16,160
Speaker 1: seventeen people have got headphones. If they're not on their head,

657
00:34:16,160 --> 00:34:17,200
Speaker 1: they're around their neck.

658
00:34:17,719 --> 00:34:20,200
Speaker 3: How do you train with headphones on? A You'll get

659
00:34:20,200 --> 00:34:23,239
Speaker 3: sweaty and that would be really uncomfortable. And B it's

660
00:34:23,320 --> 00:34:25,920
Speaker 3: impractical if you're doing you know, any of the exos.

661
00:34:26,120 --> 00:34:26,960
Speaker 2: I don't understand.

662
00:34:27,200 --> 00:34:30,000
Speaker 1: I can't, man, man, it's all they do. Like there's

663
00:34:30,040 --> 00:34:33,680
Speaker 1: young dudes who are doing you know, squats, deadlifts, chins,

664
00:34:33,840 --> 00:34:37,319
Speaker 1: like all of it. And they, in fact, they I

665
00:34:37,360 --> 00:34:40,120
Speaker 1: think they train better with them on. It's like they

666
00:34:40,239 --> 00:34:44,640
Speaker 1: almost can't train unless they have How about something blaring.

667
00:34:44,520 --> 00:34:46,799
Speaker 2: Watch out the smith Machine's falling on you.

668
00:34:49,840 --> 00:34:53,000
Speaker 1: Yeah, yeah, I mean, and that's one.

669
00:34:52,880 --> 00:34:56,560
Speaker 2: Of the fact surely that is dangerous as well.

670
00:34:57,120 --> 00:35:00,120
Speaker 1: I think we should call our episodes grumpy old pricks

671
00:35:00,120 --> 00:35:04,439
Speaker 1: like just. But it's like it is sometimes frustrating when

672
00:35:04,440 --> 00:35:09,120
Speaker 1: someone's well. One of the consequences, potential consequences and very

673
00:35:09,200 --> 00:35:15,160
Speaker 1: common consequences in a gym, usually young dudes banging weights

674
00:35:15,200 --> 00:35:19,680
Speaker 1: like a fucking cyclone, like just, and they don't know

675
00:35:20,480 --> 00:35:24,280
Speaker 1: because they've either got noise canceling and or loud music

676
00:35:25,160 --> 00:35:28,000
Speaker 1: so they can't hear the noise that they're making in

677
00:35:28,040 --> 00:35:32,040
Speaker 1: the gym, and when you go over and politely suggest

678
00:35:32,160 --> 00:35:34,920
Speaker 1: that they don't drop or bang weights or make they

679
00:35:34,960 --> 00:35:39,360
Speaker 1: look at you quizzically like what. But then, you know,

680
00:35:39,920 --> 00:35:42,680
Speaker 1: old old grumpy guy in the gym, Maybe I should

681
00:35:42,800 --> 00:35:45,800
Speaker 1: just put on noise canceling headphones and then I can't

682
00:35:45,800 --> 00:35:46,600
Speaker 1: talk to the crab.

683
00:35:47,200 --> 00:35:50,400
Speaker 3: Yeah, well, you know, remember the good old days when

684
00:35:50,600 --> 00:35:53,759
Speaker 3: astronauts met cats on the moon and played with them

685
00:35:53,800 --> 00:35:56,759
Speaker 3: and provided care to them. Do you remember that? Do

686
00:35:56,800 --> 00:35:58,680
Speaker 3: you remember that when the cats went to the moon

687
00:35:58,760 --> 00:36:00,000
Speaker 3: and it helped us.

688
00:36:00,320 --> 00:36:01,960
Speaker 1: I don't know how you got there from what I

689
00:36:02,000 --> 00:36:04,520
Speaker 1: was talking about, But why what are you talking about?

690
00:36:04,520 --> 00:36:06,759
Speaker 3: It's about the good old days, you know, when you

691
00:36:06,800 --> 00:36:11,040
Speaker 3: didn't overhear earheadphones at the gym and cats went to

692
00:36:11,080 --> 00:36:16,360
Speaker 3: the moon. So Google's AI has been criticized in the past,

693
00:36:16,719 --> 00:36:19,920
Speaker 3: right because they're trying to incorporate Google AI into their

694
00:36:19,960 --> 00:36:23,560
Speaker 3: search algorithm, which means you use AI and at summarizes information.

695
00:36:24,040 --> 00:36:25,680
Speaker 2: However, it's pulled up.

696
00:36:25,840 --> 00:36:28,760
Speaker 3: Well, initially they got in trouble because people were typing

697
00:36:28,800 --> 00:36:31,400
Speaker 3: in Nazis and they had people of color and Asian

698
00:36:31,440 --> 00:36:35,560
Speaker 3: people wearing you know, Nazi uniforms and it went one way.

699
00:36:35,920 --> 00:36:39,400
Speaker 3: So visually it was just crazy, you know, vikings that

700
00:36:39,480 --> 00:36:43,320
Speaker 3: had really good hands. And now they've done some searches

701
00:36:43,360 --> 00:36:46,160
Speaker 3: and they found that the AI picked up things like

702
00:36:46,840 --> 00:36:49,640
Speaker 3: you know, Neil Armstrong said one small step for man

703
00:36:50,000 --> 00:36:53,080
Speaker 3: because it was a cat size step and buzz Aldron

704
00:36:53,120 --> 00:36:56,680
Speaker 3: also deployed cats on the Apollo eleven miss mission. So

705
00:36:57,160 --> 00:36:59,520
Speaker 3: because there's so much stuff about cats on the Internet,

706
00:36:59,640 --> 00:37:03,600
Speaker 3: somehow the AI algorithm has picked up this connection between

707
00:37:03,920 --> 00:37:09,799
Speaker 3: the moon landings and ma and cats. And what's problematic

708
00:37:09,960 --> 00:37:12,239
Speaker 3: is that there are lots of errors coming up with

709
00:37:12,320 --> 00:37:16,919
Speaker 3: this search algorithm, so it's generating flawed responses. And that's

710
00:37:17,080 --> 00:37:20,680
Speaker 3: really been a big criticism because you know, obviously we

711
00:37:20,680 --> 00:37:23,279
Speaker 3: we've got to a point where we take a lot

712
00:37:23,280 --> 00:37:26,520
Speaker 3: of for granted, you know, doctor Google, if we've got

713
00:37:26,520 --> 00:37:29,920
Speaker 3: a concern. I mean, I would probably be more inclined

714
00:37:29,920 --> 00:37:31,880
Speaker 3: if I had a I don't know, a skin condition

715
00:37:31,920 --> 00:37:33,719
Speaker 3: and I jumped online and I wanted to find out

716
00:37:33,719 --> 00:37:34,239
Speaker 3: what it was.

717
00:37:34,520 --> 00:37:36,359
Speaker 2: I would look at those results and say, oh, yeah,

718
00:37:36,400 --> 00:37:38,840
Speaker 2: Mayo clinic. I probably think that would be okay.

719
00:37:39,000 --> 00:37:41,840
Speaker 3: Well, a government service, you know, I look at the

720
00:37:41,920 --> 00:37:44,360
Speaker 3: u UR l I look at the website. But you know,

721
00:37:44,480 --> 00:37:47,600
Speaker 3: another example is that what an eerror recently that got

722
00:37:47,600 --> 00:37:51,080
Speaker 3: pulled up by this AI search function was put glue

723
00:37:51,080 --> 00:37:55,520
Speaker 3: on a pizza like and that you know, there was

724
00:37:56,239 --> 00:37:59,600
Speaker 3: I think it was asked how many presidents of the

725
00:37:59,680 --> 00:38:04,319
Speaker 3: United States were Muslim and it came up with Barack Obama.

726
00:38:04,680 --> 00:38:07,000
Speaker 2: So that's wrong and we know it's wrong.

727
00:38:07,360 --> 00:38:12,800
Speaker 3: So this misinformation is really kind of broading the trust

728
00:38:13,080 --> 00:38:15,920
Speaker 3: in a search engine that we've invested a lot of

729
00:38:15,960 --> 00:38:20,280
Speaker 3: faith in. We'll think about it the term googling something well.

730
00:38:20,360 --> 00:38:24,120
Speaker 1: Also when you don't know, when you you know, when

731
00:38:24,120 --> 00:38:26,920
Speaker 1: you don't know that it's wrong, but it sounds like,

732
00:38:26,960 --> 00:38:29,600
Speaker 1: oh that reads well and it's from the Mayo whatever,

733
00:38:29,680 --> 00:38:32,960
Speaker 1: or it's from a Harvard Medical review or but it's not.

734
00:38:33,680 --> 00:38:35,839
Speaker 1: It's not though, and you don't know that. And then

735
00:38:35,880 --> 00:38:39,840
Speaker 1: all of a sudden that becomes you're in inverted Comma's truth.

736
00:38:40,400 --> 00:38:43,080
Speaker 1: Now you're evangelizing that, oh, I guess what, but this

737
00:38:43,280 --> 00:38:46,200
Speaker 1: is how that works, and then you're actually saying something

738
00:38:46,239 --> 00:38:51,640
Speaker 1: that it is flawed or you know, improbable at the

739
00:38:51,800 --> 00:38:56,560
Speaker 1: very least. I mean, and that's I asked chat GPT,

740
00:38:56,800 --> 00:38:58,719
Speaker 1: I've got the four point zero the burger with the

741
00:38:58,760 --> 00:39:02,880
Speaker 1: lot to does me a logo? I just wanted to

742
00:39:02,920 --> 00:39:05,120
Speaker 1: see what it would come up with the other day.

743
00:39:05,440 --> 00:39:07,320
Speaker 1: I don't have a logo, I don't need a logo,

744
00:39:07,880 --> 00:39:12,600
Speaker 1: but I just went, designed me a logo with my

745
00:39:12,760 --> 00:39:19,279
Speaker 1: name Craig Harper, and you know, basically, I'm going to

746
00:39:19,440 --> 00:39:22,160
Speaker 1: I'm going to be working as a neuropsychologist, which I'm not,

747
00:39:22,400 --> 00:39:24,200
Speaker 1: by the way, but I just wanted to see, you know,

748
00:39:24,280 --> 00:39:27,279
Speaker 1: so I thought, brain mind, so it designs this thing,

749
00:39:27,680 --> 00:39:33,200
Speaker 1: and it misspelled my name, so Craig Harper's it left

750
00:39:33,200 --> 00:39:37,640
Speaker 1: out the eye so it had Crag Harper. I'm like yeah,

751
00:39:37,760 --> 00:39:40,960
Speaker 1: and and then I went then I typed it in

752
00:39:41,280 --> 00:39:44,600
Speaker 1: again you misspelled my name, and then it got the

753
00:39:44,680 --> 00:39:48,640
Speaker 1: Craig right and fucked something else up. Like it is.

754
00:39:49,239 --> 00:39:52,400
Speaker 1: These are far from perfect tools, and I think the

755
00:39:52,480 --> 00:39:56,000
Speaker 1: problem is when you're dealing with something that you know.

756
00:39:56,040 --> 00:40:00,400
Speaker 1: It's like like the amount of pseudo experts. I'm not

757
00:40:00,440 --> 00:40:03,960
Speaker 1: an expert by any on any kind of level, but

758
00:40:04,160 --> 00:40:08,360
Speaker 1: who come out and say things that sounds scientifically valid

759
00:40:09,280 --> 00:40:12,640
Speaker 1: and they're convincing, and they use terminology and people go, oh,

760
00:40:12,640 --> 00:40:14,760
Speaker 1: I guess what if you do this, then that happens.

761
00:40:16,120 --> 00:40:19,480
Speaker 1: Maybe maybe not, you know, like, I think that's the

762
00:40:19,640 --> 00:40:23,200
Speaker 1: danger or one of the dangers of getting all of

763
00:40:23,239 --> 00:40:26,399
Speaker 1: your information on the internet. Which is even why even

764
00:40:26,400 --> 00:40:29,399
Speaker 1: when I have actual experts on the show that I'm

765
00:40:29,440 --> 00:40:34,080
Speaker 1: not sure not, oh you kind of are? You know,

766
00:40:34,160 --> 00:40:35,840
Speaker 1: when we have like I have someone who's got a

767
00:40:35,840 --> 00:40:39,040
Speaker 1: fucking doctorate in this or that and we're talking about,

768
00:40:39,200 --> 00:40:45,240
Speaker 1: you know, something that is really a multi dimensional, complicated topic,

769
00:40:46,200 --> 00:40:49,319
Speaker 1: I never I mean I always tell people this is

770
00:40:49,360 --> 00:40:53,319
Speaker 1: not advice. This is not a personal prescription, This is

771
00:40:53,440 --> 00:40:56,840
Speaker 1: not a recommendation. This is too even you and me,

772
00:40:56,920 --> 00:41:00,520
Speaker 1: it's two blokes talking about stuff. Don't can use that

773
00:41:00,760 --> 00:41:05,160
Speaker 1: with individual advice. You know, if we bring up something

774
00:41:05,200 --> 00:41:09,239
Speaker 1: that kind of resonates and it might be something that

775
00:41:09,360 --> 00:41:11,959
Speaker 1: is an important topic for you, then go and see

776
00:41:12,000 --> 00:41:15,640
Speaker 1: the relevant person and then make decisions off the back

777
00:41:15,680 --> 00:41:19,080
Speaker 1: of that. You know. That's why. And I think, well,

778
00:41:19,120 --> 00:41:22,600
Speaker 1: we're fifteen hundred and nearly fifteen hundred and fifty episodes

779
00:41:22,600 --> 00:41:28,239
Speaker 1: in how many things have I got wrong? Thousands? You know,

780
00:41:28,840 --> 00:41:32,319
Speaker 1: because I'm human and normal, you know, so yeah, you

781
00:41:32,400 --> 00:41:36,520
Speaker 1: got to you got to expose yourself to whatever you want.

782
00:41:36,560 --> 00:41:38,080
Speaker 1: But think critically.

783
00:41:38,719 --> 00:41:42,520
Speaker 3: Yeah, this recent this AI researcher from Santa Fe Institute

784
00:41:42,560 --> 00:41:44,520
Speaker 3: in New Mexico by the name of Melandy Mitchell.

785
00:41:44,600 --> 00:41:47,000
Speaker 2: She she explained it really succinctly.

786
00:41:47,080 --> 00:41:51,960
Speaker 3: She said, what's happening is that Google's AI isn't smart

787
00:41:52,080 --> 00:41:55,440
Speaker 3: enough to figure out the difference between a citation and

788
00:41:56,320 --> 00:41:59,640
Speaker 3: actual research. So if there's a citation and a reference

789
00:41:59,680 --> 00:42:03,120
Speaker 3: to something, it doesn't necessarily mean that's true or factual

790
00:42:03,239 --> 00:42:06,200
Speaker 3: or accurate. So, you know, if you've written a paper

791
00:42:06,360 --> 00:42:10,160
Speaker 3: and there've been claims, you know it's remember the Mandala effect.

792
00:42:10,560 --> 00:42:11,880
Speaker 2: You've heard the Mandala effect.

793
00:42:12,320 --> 00:42:13,440
Speaker 1: I've heard of it. What is it?

794
00:42:13,760 --> 00:42:14,719
Speaker 2: So effectively?

795
00:42:15,000 --> 00:42:18,719
Speaker 3: You ask someone, do you remember when Nelson Mandela died

796
00:42:18,760 --> 00:42:19,200
Speaker 3: in prison?

797
00:42:19,680 --> 00:42:21,520
Speaker 2: And people say, yeah, that's right, he died in prison.

798
00:42:21,600 --> 00:42:24,480
Speaker 3: Well, he didn't die in prison, was the president and

799
00:42:24,680 --> 00:42:28,640
Speaker 3: you know of South Africa. So but it was the

800
00:42:28,719 --> 00:42:31,320
Speaker 3: phrase was coined as the Mandala effect because we know

801
00:42:31,400 --> 00:42:34,440
Speaker 3: that he was in jail for decades and he was

802
00:42:34,480 --> 00:42:36,480
Speaker 3: in a very poor condition when he came out of jail.

803
00:42:36,560 --> 00:42:39,080
Speaker 3: But for some reason, and the reason was called the

804
00:42:39,120 --> 00:42:42,640
Speaker 3: Mandala effect is because people actually believed that and they

805
00:42:42,760 --> 00:42:46,960
Speaker 3: false remembered that situation. So we're frail enough as it

806
00:42:47,080 --> 00:42:50,320
Speaker 3: is with false memories and the way that our memory

807
00:42:50,360 --> 00:42:54,560
Speaker 3: reconstructs itself. And sometimes it's great when you have siblings

808
00:42:54,880 --> 00:42:58,560
Speaker 3: recounting a story and looking at the different ways that

809
00:42:58,680 --> 00:42:59,760
Speaker 3: story was remembered.

810
00:43:00,400 --> 00:43:01,200
Speaker 2: I don't have had that.

811
00:43:01,280 --> 00:43:02,640
Speaker 3: You know, you talk to one of your mates, haven't

812
00:43:02,640 --> 00:43:05,920
Speaker 3: caught up with you, and you misremember and your brains

813
00:43:06,120 --> 00:43:07,719
Speaker 3: within the blanks.

814
00:43:08,320 --> 00:43:13,240
Speaker 1: Well, and it's the same with eyewitness testimony. It's held

815
00:43:13,440 --> 00:43:16,520
Speaker 1: in not very high regard because oh, well, where were

816
00:43:16,560 --> 00:43:19,440
Speaker 1: your eyes on the other side of the street. Okay, Well,

817
00:43:19,880 --> 00:43:22,879
Speaker 1: so this happened inside the shop, and you were outside

818
00:43:22,880 --> 00:43:25,960
Speaker 1: the shop on the other side of the street, and

819
00:43:26,000 --> 00:43:29,000
Speaker 1: it was dusk, and the person had their back, you know,

820
00:43:29,080 --> 00:43:32,520
Speaker 1: then all of a sudden, it's like, well, like there

821
00:43:32,600 --> 00:43:34,680
Speaker 1: was the thing that happened, and then there was what

822
00:43:34,800 --> 00:43:38,680
Speaker 1: you think happened. Like sometimes they're pretty desparate, you know.

823
00:43:39,840 --> 00:43:41,520
Speaker 3: I was always I was saying to someone recently, there

824
00:43:41,560 --> 00:43:43,400
Speaker 3: are always three sides to every story.

825
00:43:43,560 --> 00:43:45,680
Speaker 2: Your side, my side, and the truth.

826
00:43:45,960 --> 00:43:51,600
Speaker 1: Yeah. Hey, one of my favorite actresses, Scarlett Johanson, been

827
00:43:51,640 --> 00:43:52,520
Speaker 1: in the news lately.

828
00:43:53,040 --> 00:43:55,120
Speaker 2: Well, you you were a victim of this, I know

829
00:43:55,280 --> 00:43:58,440
Speaker 2: recently you were the victim of someone copying your voice.

830
00:43:58,520 --> 00:44:01,279
Speaker 2: Go listen to the last episode, did you Was there

831
00:44:01,320 --> 00:44:04,799
Speaker 2: any comments about that it would be Yeah, yeah it was.

832
00:44:05,040 --> 00:44:08,200
Speaker 1: It was actually funny, like it got worse through the

833
00:44:08,239 --> 00:44:10,839
Speaker 1: show because you were making it up on the spot. Yes,

834
00:44:10,880 --> 00:44:13,200
Speaker 1: but the stuff that you pre prepared in it, I

835
00:44:13,200 --> 00:44:15,080
Speaker 1: think you told me it took about three minutes, but

836
00:44:16,120 --> 00:44:18,000
Speaker 1: I listened. I didn't listen to the whole show, but

837
00:44:18,040 --> 00:44:20,960
Speaker 1: I listened to that because I wanted to listen as

838
00:44:21,000 --> 00:44:25,000
Speaker 1: a listener to see how the if you weren't if

839
00:44:25,000 --> 00:44:28,680
Speaker 1: you didn't listen to it, everyone Patrick basically used took

840
00:44:28,840 --> 00:44:30,680
Speaker 1: my fuck. I don't know. Can you tell people what

841
00:44:30,719 --> 00:44:31,000
Speaker 1: you did?

842
00:44:31,040 --> 00:44:33,800
Speaker 3: You took my voice and uploaded it to an AI

843
00:44:33,960 --> 00:44:35,759
Speaker 3: to copy it, and then I was able to type

844
00:44:35,840 --> 00:44:38,759
Speaker 3: in some text a statement by Craig on how much

845
00:44:38,760 --> 00:44:40,719
Speaker 3: he liked me, how much better I was at him,

846
00:44:40,760 --> 00:44:43,720
Speaker 3: how much the more handsome, And I did the intro

847
00:44:43,840 --> 00:44:47,640
Speaker 3: to the show as Craig's voice mimicked by an AI,

848
00:44:48,320 --> 00:44:49,120
Speaker 3: which was kind of fun.

849
00:44:49,280 --> 00:44:49,759
Speaker 2: Actually was.

850
00:44:49,800 --> 00:44:51,880
Speaker 3: It was fun doing it, and it was interesting as

851
00:44:51,880 --> 00:44:55,400
Speaker 3: an exercise because we've spoken about it before and we

852
00:44:55,480 --> 00:44:57,160
Speaker 3: know that the tools are out there, but I'd never

853
00:44:57,160 --> 00:44:58,640
Speaker 3: done it, so I thought it'd be a nice little

854
00:44:58,640 --> 00:45:00,880
Speaker 3: experiment to the show.

855
00:45:01,360 --> 00:45:03,000
Speaker 2: But it was. It was kind of cool.

856
00:45:03,040 --> 00:45:05,160
Speaker 3: And you know what I really wanted to know was

857
00:45:05,239 --> 00:45:09,440
Speaker 3: has anybody sent you five bucks? No, because one of

858
00:45:09,480 --> 00:45:12,319
Speaker 3: the other things we asked was for everybody send five

859
00:45:12,400 --> 00:45:17,480
Speaker 3: dollars for me, and that you'd match whatever amount we raised. Yeah, yeah,

860
00:45:17,560 --> 00:45:18,640
Speaker 3: it was. It was worth a try.

861
00:45:18,680 --> 00:45:22,160
Speaker 1: I reckon, No, that's not happening. Hey, as we're winding up,

862
00:45:23,360 --> 00:45:26,600
Speaker 1: it was worth a try. Self balancing motorcycles. That's kind

863
00:45:26,640 --> 00:45:28,360
Speaker 1: of annoy I think it's funny.

864
00:45:28,960 --> 00:45:31,600
Speaker 2: Well, funny, you reckon. I thought this was really cool.

865
00:45:31,680 --> 00:45:34,800
Speaker 3: So having only ever been a passenger on a bike

866
00:45:35,040 --> 00:45:38,879
Speaker 3: and being told sternly by you, you need to lean

867
00:45:38,920 --> 00:45:42,359
Speaker 3: into the same direction that I'm leaning into. Why why

868
00:45:42,360 --> 00:45:44,400
Speaker 3: do I need to lean into the same direction that

869
00:45:44,440 --> 00:45:46,560
Speaker 3: you're leaning to, Craig when you're at speed?

870
00:45:48,840 --> 00:45:50,960
Speaker 1: Well, because we don't want to well what people try

871
00:45:51,000 --> 00:45:53,560
Speaker 1: and do who are inexperienced on moti So say you're

872
00:45:53,600 --> 00:45:56,799
Speaker 1: going into a left hand turn, well, and so your

873
00:45:56,800 --> 00:45:59,640
Speaker 1: motorbike is leaning to the left because you're going into

874
00:45:59,680 --> 00:46:02,640
Speaker 1: the car, and so you lean with it because you're

875
00:46:02,640 --> 00:46:05,880
Speaker 1: one with a bike. But what some people do is

876
00:46:05,920 --> 00:46:10,200
Speaker 1: they go, oh, I better counterbalance this, and so they

877
00:46:10,239 --> 00:46:12,800
Speaker 1: try and hang off the other side like a fucking

878
00:46:12,880 --> 00:46:18,280
Speaker 1: idiot and nearly kill everyone. So you lean into the corner.

879
00:46:18,400 --> 00:46:22,239
Speaker 1: But but I mean, I can't imagine because I've been

880
00:46:22,360 --> 00:46:25,280
Speaker 1: riding for so long, but I guess I could hypothetically

881
00:46:25,320 --> 00:46:28,360
Speaker 1: imagine that. It feels like that's a dumb thing to

882
00:46:28,400 --> 00:46:31,920
Speaker 1: do when you're on the back. Can intuitive Yeah, it

883
00:46:32,080 --> 00:46:35,440
Speaker 1: seemed correct, And you're like, fuck, my knee is about

884
00:46:35,440 --> 00:46:38,239
Speaker 1: three inches from the ground and my elbows about eight

885
00:46:38,280 --> 00:46:41,040
Speaker 1: inches from the ground. I really should maybe lean the

886
00:46:41,080 --> 00:46:42,799
Speaker 1: other way just to help crag out.

887
00:46:43,080 --> 00:46:45,600
Speaker 2: Yeah, how is the heaviest bike you've got?

888
00:46:47,200 --> 00:46:49,640
Speaker 1: So, one of the bikes I've got is three hundred

889
00:46:49,640 --> 00:46:53,360
Speaker 1: and sixty two kilos what they call dry, So with

890
00:46:53,480 --> 00:46:58,160
Speaker 1: motorbikes they say dry or wet, So without drying, yeah,

891
00:46:58,200 --> 00:47:01,960
Speaker 1: without oil, without fuel, so so probably wet. It's about

892
00:47:02,000 --> 00:47:04,720
Speaker 1: three hundred and eighty k's before I put my fat

893
00:47:04,719 --> 00:47:05,279
Speaker 1: ass on it.

894
00:47:05,800 --> 00:47:08,000
Speaker 3: So now, when you get to a set of lights

895
00:47:08,320 --> 00:47:11,360
Speaker 3: and stop, rather than running the light, what's you do?

896
00:47:12,600 --> 00:47:13,880
Speaker 1: Well, you've got to put your feet.

897
00:47:13,640 --> 00:47:18,880
Speaker 3: Down obviously, No you don't, No, you don't, Okay, okay,

898
00:47:19,000 --> 00:47:24,719
Speaker 3: Honda wait for this. Honda has unveiled riding assist technology,

899
00:47:25,160 --> 00:47:28,760
Speaker 3: and what they demonstrated was a bloke with the bike stopped,

900
00:47:29,239 --> 00:47:33,120
Speaker 3: standing on the bike, so standing actually on the bike

901
00:47:33,719 --> 00:47:35,920
Speaker 3: headily things I don't know what they are, and with

902
00:47:36,080 --> 00:47:39,160
Speaker 3: his arms out right, so his feet on the footpegs

903
00:47:39,360 --> 00:47:44,080
Speaker 3: and his fully stretched out and the bike maintained it's up.

904
00:47:44,880 --> 00:47:46,000
Speaker 2: How awesome is that?

905
00:47:46,920 --> 00:47:49,359
Speaker 1: Well? How unnecessary is that? Because if you can't put

906
00:47:49,360 --> 00:47:53,880
Speaker 1: your fucking feet on the ground, what's wrong with you? No?

907
00:47:53,960 --> 00:47:56,239
Speaker 3: No, but what about when you're stuck in traffic you

908
00:47:56,280 --> 00:47:58,839
Speaker 3: can't weave around and you're going you're going slight.

909
00:47:59,040 --> 00:48:00,960
Speaker 2: The slower you go, the harder it is to balance.

910
00:48:01,040 --> 00:48:07,439
Speaker 1: Yeah, yeah, Are you trying to tell me about motorbikes? Now?

911
00:48:08,600 --> 00:48:10,680
Speaker 1: I try and tell you about technology.

912
00:48:10,840 --> 00:48:14,120
Speaker 2: Okay? Can I ask you a question? At the beginner's side.

913
00:48:13,880 --> 00:48:16,040
Speaker 1: You know when you say can I ask you a question,

914
00:48:16,440 --> 00:48:19,359
Speaker 1: that is of itself a question, So you should say,

915
00:48:19,440 --> 00:48:20,920
Speaker 1: can I ask you another question?

916
00:48:21,080 --> 00:48:22,440
Speaker 2: Did I ask you another question?

917
00:48:23,000 --> 00:48:23,239
Speaker 1: Yes?

918
00:48:23,920 --> 00:48:26,840
Speaker 3: What do you think is the biggest hurdle to young

919
00:48:27,040 --> 00:48:32,000
Speaker 3: drivers or young riders when they're driving in slow traffic.

920
00:48:32,040 --> 00:48:34,120
Speaker 3: What's the hardest thing for them to accomplish if they're

921
00:48:34,120 --> 00:48:36,000
Speaker 3: slowing down to say five k's an hour.

922
00:48:37,840 --> 00:48:40,880
Speaker 1: Well, what the inhibiting factor is their lack of skill

923
00:48:40,920 --> 00:48:43,080
Speaker 1: and they can only get good by riding more.

924
00:48:43,560 --> 00:48:48,720
Speaker 3: Ah, you deliberately didn't say balance as a contributing problem

925
00:48:48,760 --> 00:48:50,400
Speaker 3: for younger riders or people.

926
00:48:50,120 --> 00:48:51,160
Speaker 2: Who are in experience.

927
00:48:51,520 --> 00:48:53,640
Speaker 3: Don't you think this would be great to have this

928
00:48:53,760 --> 00:48:55,960
Speaker 3: rider assist writing technology.

929
00:48:56,040 --> 00:49:01,640
Speaker 1: No bullshit, we're becoming so fucked and fragile. Now we

930
00:49:01,719 --> 00:49:05,480
Speaker 1: need a self balancing fuck off with yourself balancing motorbike.

931
00:49:06,280 --> 00:49:08,000
Speaker 2: I was so excited when I saw that.

932
00:49:08,120 --> 00:49:11,200
Speaker 3: I thought Crago is going to get really happy and

933
00:49:11,280 --> 00:49:12,040
Speaker 3: excited about this.

934
00:49:12,400 --> 00:49:12,480
Speaker 2: Now.

935
00:49:12,520 --> 00:49:14,440
Speaker 1: I'll tell you what I do want, though, I want

936
00:49:14,520 --> 00:49:19,120
Speaker 1: a robot dog that blow shit up. That's what I want.

937
00:49:19,360 --> 00:49:20,360
Speaker 2: China's done it.

938
00:49:20,480 --> 00:49:22,960
Speaker 3: So China seems to have been the first they got

939
00:49:22,960 --> 00:49:25,160
Speaker 3: one of those robot dogs. We've seen them all, the

940
00:49:25,160 --> 00:49:28,640
Speaker 3: Boston Dynamics dogs, and there's some weapon on the back

941
00:49:28,719 --> 00:49:31,239
Speaker 3: of them. So now they've got who knows what they're

942
00:49:31,239 --> 00:49:35,680
Speaker 3: going to be using them for urban warfare or just

943
00:49:35,800 --> 00:49:41,319
Speaker 3: knows what. That's really pretty frightening, actually, you know I'd

944
00:49:41,320 --> 00:49:43,279
Speaker 3: hate to think that they're autonomous. I could kind of

945
00:49:43,360 --> 00:49:45,920
Speaker 3: understand if they were under remote control. But the idea

946
00:49:46,520 --> 00:49:49,920
Speaker 3: of some sort of autonomous four legged, very fast, very

947
00:49:49,960 --> 00:49:54,040
Speaker 3: agile upstairs, downstairs, round corners with a gun on top,

948
00:49:54,920 --> 00:49:56,120
Speaker 3: we're just frightening to see.

949
00:49:56,120 --> 00:49:57,759
Speaker 2: I don't know if you saw the photos of it, but.

950
00:49:58,960 --> 00:50:03,320
Speaker 3: Actually has deployed a dog, robot dog with a weapon

951
00:50:03,360 --> 00:50:04,000
Speaker 3: on the back of it.

952
00:50:04,320 --> 00:50:09,320
Speaker 1: I know, imagine sending that into bloody warfare, like into

953
00:50:09,920 --> 00:50:14,200
Speaker 1: yeah exactly, I mean that, yeah, I mean the technology

954
00:50:14,239 --> 00:50:19,360
Speaker 1: in that space is Yeah, that that that scares me

955
00:50:19,400 --> 00:50:22,000
Speaker 1: a little bit, I mean, war scares me. Like fuck,

956
00:50:23,080 --> 00:50:25,799
Speaker 1: that's a whole episode. Why can't we humans figure that

957
00:50:25,880 --> 00:50:30,080
Speaker 1: shit out? Where allegedly the smartest species fuck, I don't know,

958
00:50:30,160 --> 00:50:31,799
Speaker 1: have a look at some of the ship that we do,

959
00:50:31,920 --> 00:50:34,200
Speaker 1: like some of the incredible shit we do and some

960
00:50:34,239 --> 00:50:37,440
Speaker 1: of the horrible shit we do. I reckon dolphins and

961
00:50:37,680 --> 00:50:41,759
Speaker 1: OCTOPI have got us covered. And elephants. Yeah, you know,

962
00:50:41,840 --> 00:50:43,719
Speaker 1: elephants are super smart. Did you know that?

963
00:50:45,120 --> 00:50:47,759
Speaker 2: I yeah, you just told me so.

964
00:50:47,800 --> 00:50:53,360
Speaker 1: They must be and also quite emotionally evolved. Yeah.

965
00:50:53,480 --> 00:50:58,160
Speaker 3: Look, I love seeing the videos of elephants when they

966
00:50:58,480 --> 00:51:02,960
Speaker 3: nurture and protect, and they really have quite strong family ties,

967
00:51:03,080 --> 00:51:06,320
Speaker 3: don't they community sense of how they.

968
00:51:06,480 --> 00:51:10,440
Speaker 1: They like dolphins too. They have language like they actually

969
00:51:10,680 --> 00:51:16,839
Speaker 1: have like their version of you know, verbal communication obviously

970
00:51:17,040 --> 00:51:20,680
Speaker 1: vastly different to us, but you know, all right, have

971
00:51:20,719 --> 00:51:25,319
Speaker 1: you got a big fucking highlight to close something out on?

972
00:51:25,680 --> 00:51:28,080
Speaker 1: We didn't talk about Scarlet, but we can discard her

973
00:51:28,120 --> 00:51:30,799
Speaker 1: if you want. Have you got a banger that you

974
00:51:30,840 --> 00:51:31,680
Speaker 1: want to finish with?

975
00:51:32,400 --> 00:51:35,000
Speaker 3: So a lot of us use our browsers, and think

976
00:51:35,160 --> 00:51:37,239
Speaker 3: when I talk about browsers, I'm talking about you know,

977
00:51:37,440 --> 00:51:41,680
Speaker 3: using Google Chrome or Edge or one of the other browsers.

978
00:51:41,840 --> 00:51:45,000
Speaker 3: But Microsoft's Edge browser, which is not as used as

979
00:51:45,080 --> 00:51:47,560
Speaker 3: much as Chrome. And I guess if you're on an

980
00:51:47,560 --> 00:51:49,640
Speaker 3: Apple device, you've got what safari?

981
00:51:49,760 --> 00:51:53,560
Speaker 2: Is that what people know? Yeah, that's right, But this

982
00:51:53,680 --> 00:51:55,800
Speaker 2: is a new feature that's kind of cool.

983
00:51:56,040 --> 00:51:59,440
Speaker 3: And I like to watch lots of videos, and a

984
00:51:59,440 --> 00:52:04,920
Speaker 3: lot of independ and producers publish videos online. So foreign

985
00:52:04,960 --> 00:52:09,920
Speaker 3: films smart small niche kind of five, ten, twelve, fifteen

986
00:52:10,000 --> 00:52:13,080
Speaker 3: minute docos or whatever. But if there are in other

987
00:52:13,200 --> 00:52:16,320
Speaker 3: languages and they don't have subtitles, that's really frustrating because

988
00:52:16,400 --> 00:52:20,600
Speaker 3: they don't always have English subtitles. However, now Microsoft Edge

989
00:52:20,880 --> 00:52:24,919
Speaker 3: will be able to translate and dub on the fly.

990
00:52:26,320 --> 00:52:26,600
Speaker 1: Wow.

991
00:52:27,080 --> 00:52:28,160
Speaker 2: Yeah, it's really good.

992
00:52:28,200 --> 00:52:32,680
Speaker 3: So real time video translation on anything from YouTube, LinkedIn,

993
00:52:33,400 --> 00:52:35,600
Speaker 3: you name it. And this is something that's going to

994
00:52:35,600 --> 00:52:38,640
Speaker 3: be built into the browsers. So as you're watching, it

995
00:52:38,680 --> 00:52:42,600
Speaker 3: could be from German, Hindi, Italian, Russian, Spanish, and it

996
00:52:42,640 --> 00:52:45,200
Speaker 3: can convert it on the fly into English or the

997
00:52:45,239 --> 00:52:47,520
Speaker 3: other way around if you happen to be a German speaker.

998
00:52:48,120 --> 00:52:49,560
Speaker 2: So I thought that's kind of.

999
00:52:49,520 --> 00:52:52,840
Speaker 3: Cool that now it's going to make that sort of

1000
00:52:52,880 --> 00:52:55,040
Speaker 3: content more accessible to people.

1001
00:52:55,640 --> 00:52:57,560
Speaker 2: Do you watch much YouTube or do you look at

1002
00:52:57,600 --> 00:52:58,240
Speaker 2: foreign films?

1003
00:52:58,239 --> 00:53:00,719
Speaker 1: Do you like, Yeah, I watched too much. I go

1004
00:53:00,840 --> 00:53:03,120
Speaker 1: down the old YouTube rabbit hole when I should be

1005
00:53:03,160 --> 00:53:06,160
Speaker 1: reading a research paper or something because I've got the

1006
00:53:06,200 --> 00:53:10,360
Speaker 1: attention of a four year old. But yeah, it's yeah.

1007
00:53:10,680 --> 00:53:13,000
Speaker 1: But satally, I mean, that's amazing though, that you can

1008
00:53:13,040 --> 00:53:15,880
Speaker 1: watch something that is in a foreign language and have

1009
00:53:15,920 --> 00:53:17,080
Speaker 1: it convert in real time.

1010
00:53:17,400 --> 00:53:20,799
Speaker 2: So it's called co pilot. And my dream for this

1011
00:53:21,120 --> 00:53:23,760
Speaker 2: is to have smart glasses and travel around the world

1012
00:53:23,800 --> 00:53:26,920
Speaker 2: where someone talks to you in Chinese and you get

1013
00:53:26,960 --> 00:53:29,400
Speaker 2: the real time translation floating in front of you, like

1014
00:53:29,440 --> 00:53:32,640
Speaker 2: a little talk bubble. You know, you can imagine talk

1015
00:53:32,680 --> 00:53:35,440
Speaker 2: bubble appearing over the person as they're talking, and it's

1016
00:53:35,480 --> 00:53:37,560
Speaker 2: translating in real time. And if they were wearing the

1017
00:53:37,600 --> 00:53:42,239
Speaker 2: same smart glasses with this real time translation, then you

1018
00:53:42,239 --> 00:53:45,320
Speaker 2: you know, all the barriers to communication can be dropped.

1019
00:53:45,600 --> 00:53:48,280
Speaker 2: It would make life so fun and interesting.

1020
00:53:49,040 --> 00:53:53,160
Speaker 1: You know how there's always been talk about that eventually

1021
00:53:53,160 --> 00:53:57,279
Speaker 1: we're not going to have to verbally speak, because we'll

1022
00:53:57,320 --> 00:53:59,720
Speaker 1: just be able to read each other's minds or thoughts

1023
00:53:59,840 --> 00:54:01,400
Speaker 1: or whatever, which who knows.

1024
00:54:01,400 --> 00:54:03,680
Speaker 2: Frightening. I would not want to read your mind and

1025
00:54:03,719 --> 00:54:04,640
Speaker 2: you don't want to read it.

1026
00:54:05,520 --> 00:54:08,759
Speaker 1: I would not want anyone to like that's I'll be

1027
00:54:08,800 --> 00:54:14,000
Speaker 1: put in an asylum. But I wonder if like you go, okay,

1028
00:54:14,040 --> 00:54:17,759
Speaker 1: so now I can Elon Musk and Joe Rogan talk

1029
00:54:17,800 --> 00:54:21,520
Speaker 1: about this a lot, this idea. They're fucking infatuated with it.

1030
00:54:21,560 --> 00:54:24,239
Speaker 1: But I wonder if they ever got to that, if

1031
00:54:24,280 --> 00:54:26,920
Speaker 1: you go to another country, if you could understand, because

1032
00:54:26,920 --> 00:54:30,120
Speaker 1: they don't they don't think in English, like I wonder

1033
00:54:30,160 --> 00:54:33,880
Speaker 1: if do you know what I'm saying? It's like like

1034
00:54:33,920 --> 00:54:36,720
Speaker 1: when you're just thinking about something, Like when I'm thinking

1035
00:54:36,719 --> 00:54:39,800
Speaker 1: about something, it's not like there are words in my head.

1036
00:54:41,360 --> 00:54:44,680
Speaker 1: I this is a stupid conversation. Do you know what

1037
00:54:44,680 --> 00:54:48,839
Speaker 1: I mean? For people's mind if you could read them

1038
00:54:48,840 --> 00:54:49,800
Speaker 1: in different countries.

1039
00:54:50,120 --> 00:54:53,160
Speaker 3: Some people have a condition where they can't verbalize in

1040
00:54:53,200 --> 00:54:56,800
Speaker 3: their head. They don't have the internal dialogue or internal narrator.

1041
00:54:57,320 --> 00:55:00,480
Speaker 3: So wow, that's yeah, that's a that's an ext condition

1042
00:55:00,560 --> 00:55:03,640
Speaker 3: that some people have. But I guess do we think

1043
00:55:03,640 --> 00:55:06,359
Speaker 3: in those arbitrary thoughts? You know, if I'm hungry, if

1044
00:55:06,400 --> 00:55:08,160
Speaker 3: I look at something and think that looks great.

1045
00:55:08,800 --> 00:55:10,640
Speaker 2: That's a really interesting question.

1046
00:55:10,400 --> 00:55:13,680
Speaker 3: As to whether on a deeper level, even though we

1047
00:55:13,760 --> 00:55:17,319
Speaker 3: may be applying words to that thought process, whether there

1048
00:55:17,640 --> 00:55:22,839
Speaker 3: is on a deeper level is translatable across languages if

1049
00:55:22,840 --> 00:55:25,680
Speaker 3: it was just the emotion that's built into that. So

1050
00:55:25,719 --> 00:55:27,560
Speaker 3: if I look at my dog and I look at

1051
00:55:27,600 --> 00:55:29,800
Speaker 3: him and I think of fondness and love because I

1052
00:55:29,840 --> 00:55:30,399
Speaker 3: love my dog.

1053
00:55:30,760 --> 00:55:32,080
Speaker 2: We're'm about to take him for a walk.

1054
00:55:32,480 --> 00:55:36,200
Speaker 3: I said the word, but in those senses, then, you know,

1055
00:55:36,480 --> 00:55:38,279
Speaker 3: I don't even understand how we do that.

1056
00:55:38,280 --> 00:55:41,759
Speaker 2: On a you know, kind of neurological I.

1057
00:55:41,680 --> 00:55:44,400
Speaker 1: Think the thought is just like we don't think in

1058
00:55:44,480 --> 00:55:47,520
Speaker 1: words like I'm not I'm not. I'm not looking out

1059
00:55:47,560 --> 00:55:50,880
Speaker 1: my window now at the beautiful trees in my yard

1060
00:55:51,400 --> 00:55:53,960
Speaker 1: thinking in my mind the words are, oh, they are

1061
00:55:54,000 --> 00:55:57,440
Speaker 1: beautiful grand trees. What a nice outlook like that's not happening,

1062
00:55:58,040 --> 00:56:01,279
Speaker 1: like there's just the I what that'll do? You've killed

1063
00:56:01,320 --> 00:56:03,920
Speaker 1: it again. For people who want to come and start

1064
00:56:03,920 --> 00:56:06,839
Speaker 1: your joint or you know, connect with you in some way,

1065
00:56:06,920 --> 00:56:09,160
Speaker 1: or take Fritz for a walk, or steal your wallet

1066
00:56:09,200 --> 00:56:11,799
Speaker 1: from your car, that's there. Watch your home address, watch

1067
00:56:11,800 --> 00:56:13,520
Speaker 1: your web address. How do people do that?

1068
00:56:13,840 --> 00:56:15,200
Speaker 2: Okay, our west of Melbourne.

1069
00:56:15,200 --> 00:56:17,160
Speaker 3: If you just drive on the highway for an hour

1070
00:56:17,239 --> 00:56:18,759
Speaker 3: and then pull off at the first time you get

1071
00:56:18,800 --> 00:56:20,000
Speaker 3: to that will be where I live.

1072
00:56:23,000 --> 00:56:23,800
Speaker 2: Traffic situation.

1073
00:56:23,880 --> 00:56:27,040
Speaker 3: I guess you could be end up Betty where no websites, NOOW,

1074
00:56:27,080 --> 00:56:30,200
Speaker 3: dot com, dot au. So that's I guess my business

1075
00:56:30,239 --> 00:56:32,840
Speaker 3: website building part of it. We do lots of that

1076
00:56:32,880 --> 00:56:36,080
Speaker 3: sort of stuff, and I don't really do the social

1077
00:56:36,120 --> 00:56:38,920
Speaker 3: thing very much in terms of connecting online. So if

1078
00:56:38,920 --> 00:56:41,360
Speaker 3: you want to contact me about stuff, you could just

1079
00:56:41,400 --> 00:56:42,600
Speaker 3: go to them and.

1080
00:56:42,480 --> 00:56:45,240
Speaker 2: Tie cheer at home. I do have some online tie.

1081
00:56:45,160 --> 00:56:48,440
Speaker 3: Cheat courses that Craig refuses to take part in and

1082
00:56:49,160 --> 00:56:50,919
Speaker 3: go to ty chair at home and do some free

1083
00:56:50,960 --> 00:56:53,919
Speaker 3: time chat classes or as I said, websites now, dot Com,

1084
00:56:53,920 --> 00:56:56,560
Speaker 3: tod au and check out what we do and all

1085
00:56:56,560 --> 00:56:57,320
Speaker 3: that sort of stuff.

1086
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Speaker 1: Well, if I could, if I was more flexible than

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Speaker 1: a fucking cricket bat, i'd get involved. But let me

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Speaker 1: let me work on that. Patrick, Thank you, thanks Crego,

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Speaker 1: Thanks Mat