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Speaker 1: Okay, a team, it's Patrick, it's Harps, it's no. If

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Speaker 1: it's it's a tipless it's a tipless episode. But I

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Speaker 1: tell you what, Nonetheless, we will put on our big

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Speaker 1: boy pants, Patrick and Soldier on might't we I'm.

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Speaker 2: Not wearing any pants.

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Speaker 1: Well are you just? Are you free balling or what

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Speaker 1: are you doing? D I really don't, I really don't.

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Speaker 1: But here is straight off the bat.

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Speaker 2: Straight off the bat, it doesn't take to hit the

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Speaker 2: kind of belw the belt. Literally, it certainly doesn't if

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Speaker 2: you were wearing a belt. I always wear a belt.

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Speaker 1: Well, I wear a belt on the cargoes because one

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Speaker 1: of the problems with having huge legs and are not

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Speaker 1: so huge waist is that you've always got to have

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Speaker 1: pants are a little bit looser in the waist unless

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Speaker 1: you take your cargo shorts to the lady slash man

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Speaker 1: who fixes all that stuff. But I can't be bothered.

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Speaker 2: I'm not sure how personal I should get with our conversation,

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Speaker 2: and it's kind of a serious personal thing. My family

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Speaker 2: doesn't listen to this, so I know we've spoken about this,

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Speaker 2: but never on air. We're having family issues where I'm

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Speaker 2: looking after my younger disabled brother every weekend and then

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Speaker 2: coming up November it'll be for three days every weekend

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Speaker 2: and it's great and it's good spending time with him

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Speaker 2: because we haven't really done a lot of that. But

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Speaker 2: Jason's very short and he has an unusual body shape.

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Speaker 2: He's got a bit of a belly, but he's got

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Speaker 2: zero ass, so he's got to wear races. And I've

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Speaker 2: been spending my time and he's great. He loves trains,

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Speaker 2: so he took a train trip the last time he

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Speaker 2: was here, just a Ballarat and back. He had the

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Speaker 2: best time and the conductor was amazing. It's great. I

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Speaker 2: think conductors on those vline trains they're so considerate. They're

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Speaker 2: just wonderful to speak to. But one of the biggest challenges,

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Speaker 2: and I know if anybody out there has been a

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Speaker 2: care for an elderly parent or someone, the biggest challenges

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Speaker 2: is using the bathroom and being a bad shot.

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Speaker 3: And I can imagine on a moving Oh it's not

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Speaker 3: on the train, this is even station, right, Okay, Okay.

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Speaker 2: My sister in law has been so good because they've

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Speaker 2: taken in my brother who can't live with my dad anymore,

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Speaker 2: at the retirement village and so she's been amazing. She's

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Speaker 2: washing his clothes every day and doing stuff for him,

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Speaker 2: and so what they are doing is probably ten times

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Speaker 2: harder than what I'm doing. But you do have to

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Speaker 2: clean the bathroom every time he goes, and so I've

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Speaker 2: been trying to convince him to sit down to go.

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Speaker 2: But the problem is, because of his unfortunate body shape,

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Speaker 2: is he has to wear braces to keep his pants

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Speaker 2: up right. So have you got braces, Craig, Yes, yes,

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Speaker 2: I can imagine the problem with braces is they're not

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Speaker 2: practical in an emergency situation. No, no, yeah, but he's

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Speaker 2: the dar. He's really been trying hard enough, kind of

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Speaker 2: said to him, Look, when you're living at my place,

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Speaker 2: maybe we can get you to sit down when you

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Speaker 2: go to the toilet. Oh no, no, no, Dad says,

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Speaker 2: I have to stand up. Yeah I know that, but

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Speaker 2: when you're at my place, maybe you can sit down.

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Speaker 2: So it's taken a few months and now he's I'm

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Speaker 2: with dad.

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Speaker 1: I'm with Dad. Don't you dare? After? How old is

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Speaker 1: he fifty?

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Speaker 2: He's fifty two.

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Speaker 1: After fifty two years of standing, let him fucking stand.

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Speaker 1: Don't try and reinvent the wheel, just because you're worried

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Speaker 1: about a bit of we on your floor.

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Speaker 2: It's not.

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Speaker 1: Okay the walls, the floor, it's not just about you

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Speaker 1: and you. He're home beautiful.

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Speaker 2: But you know it's funny, isn't it? How simple requirements?

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Speaker 2: You know, we've been watching train trips on v line,

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Speaker 2: just on the TV on the big screen. I'm going

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Speaker 2: to fill right TV. So we just plug in the

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Speaker 2: laptop and we watch trips from Melbourne to Bendigo and

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Speaker 2: Melbourne to Ballarat and it just you know, I shouldn't

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Speaker 2: say nerdy people. I'm a nerd, but those train spotters

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Speaker 2: they just get a camera and they just record the

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Speaker 2: whole trip something that hour of footage and he loves it.

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Speaker 2: It's been really good.

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Speaker 1: You know, there's a show on is it SBS? Maybe

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Speaker 1: this is what you're talking about, but there's a show

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Speaker 1: I think it's on SBS, and they literally do. They

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Speaker 1: have these like three hour docos which are silent. There's

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Speaker 1: no commentary. It's just the sounds of the train or

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Speaker 1: the ship or the whatever. But I think, is it

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Speaker 1: the gan that goes across.

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Speaker 2: He's desperate for me to take him on the gang.

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Speaker 1: Yeah, So I watched one and it's just like it

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Speaker 1: just obviously it's days and days of footage kind of

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Speaker 1: condensed and edited into this beautiful kind of three hour

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Speaker 1: but you would think. I remember turning it on and

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Speaker 1: thinking what is this? Then I had to look it

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Speaker 1: up and it's like it's a three hour silent doco

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Speaker 1: of Miko the fuck would watch this? And then an

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Speaker 1: hour later I'm still watching it. Transfixed train trips.

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Speaker 2: I did a train trip my last trip to Canada

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Speaker 2: through the Canadian Rockies, and I was on the train

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Speaker 2: for three days and I'm going to tell you, no

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Speaker 2: Internet amazing views of the just the the stunning, the

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Speaker 2: beautiful Canadian wild wilderness. And it's great. And you go

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Speaker 2: to a little reading car or a dining car, you

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Speaker 2: go to the bar and sit there and they have

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Speaker 2: these perspect perspects viewing roofs in something where you can

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Speaker 2: sit back watch the sky go past. It is and

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Speaker 2: there's something about train travel that is meditative that that

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Speaker 2: kind of and and I love sleeping on the train

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Speaker 2: as well, you know, so if you if you can

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Speaker 2: get a little cabin and mine was tiny. It was

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Speaker 2: a fold down bed and had a little toy and

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Speaker 2: all that sort of stuff and it was just great

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Speaker 2: if you look for specials and you know, because they

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Speaker 2: can be quite expensive. But I just kind of jumped

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Speaker 2: online and found some deals and had a great time.

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Speaker 1: Can I ask, what's your brother's name again?

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Speaker 2: Jason?

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Speaker 1: How old is Jason? Intellectually?

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Speaker 2: Like?

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Speaker 1: What's his kind of functional? IQ? Kind? Not IQ? But

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Speaker 1: you know he's age five or six? Yeah? Okay, So

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Speaker 1: I have a cute story. So last night I did

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Speaker 1: a gig for the eighty nine point nine Light FM,

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Speaker 1: Melbourne's Positive alternative. They were running two big, two big

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Speaker 1: mental health events. One one last night. Hundreds I don't know,

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Speaker 1: five or six hundred people won the night before, six

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Speaker 1: or seven hundred. I spoke at both events. Anyway, last night,

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Speaker 1: Oh my goodness, I had the best night, right I was.

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Speaker 1: I was talking at quarter to nine and I was

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Speaker 1: up yesterday at five. So I was driving there thinking,

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Speaker 1: I don't know how I'm going to do this. I'm

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Speaker 1: probably going to be rubbish. Fortunately, when I got to

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Speaker 1: to the place, they had a cafe in the boyer

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Speaker 1: and I got some caffeine on board, and I'm like, okay,

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Speaker 1: I'm started to perk up. Anyway, two people spoke before

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Speaker 1: me doctor Jody Richardson and doctor Ken I forget his surname,

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Speaker 1: but brilliant. Anyway, I'm on last, and I get up

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Speaker 1: and I start tom gunn Okay, I'm riffing, you know,

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Speaker 1: like I'm a bit. The other two are very very

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Speaker 1: professional and slide show and very grown up, and you know,

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Speaker 1: I'm like the dog with three dicks up there in

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Speaker 1: the flannel shirt and the jeans and like different, not

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Speaker 1: better or not worse, just different energy and different vibe

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Speaker 1: and having fun. And then I'm about three minutes in

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Speaker 1: and this young lady who I don't know how old

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Speaker 1: she is, but I would say sixteen to eight en,

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Speaker 1: but I could be totally wrong on that, just starts

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Speaker 1: laughing hysterically at my not particularly funny joke, like really loud.

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Speaker 1: And then and then you're like, yeah, and clearly a

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Speaker 1: young girl with a disability sitting next to her mum.

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Speaker 1: And she was awesome, right, And then I was talking

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Speaker 1: about a few minutes later or I don't know, and

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Speaker 1: she kept yelling out and so I just went with

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Speaker 1: it and I would say something mildly funny and she

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Speaker 1: would crack up hysterically, and I'm like, what's your name,

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Speaker 1: and she goes mal like, I'm Mel, can you come

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Speaker 1: to all of my events because you're amazing. I've got

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Speaker 1: a gig with some old stuffy corporates next Monday. Are

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Speaker 1: you available? You know, I'd love you, you know. So

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Speaker 1: there was this whole banter, right, and then then I

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Speaker 1: was telling the story about Jumbo, the fat kid at

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Speaker 1: the swimming sports. Then she goes Jumbo and then she

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Speaker 1: starts screaming out, hey, he jumpbo all through my thing, right,

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Speaker 1: Oh my god. And so I was up there with

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Speaker 1: like six hundred or five hundred people and Mel screaming

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Speaker 1: in the front, and she was just awesome. She was

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Speaker 1: such a good kid and such good energy, and it

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Speaker 1: could have potentially derailed everything, but it actually made it better.

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Speaker 1: And I finished and her mom came up with her

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Speaker 1: and we all took a photo together, and her mom

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Speaker 1: was like, thank you. So I'm like, she is. I

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Speaker 1: genuinely mean, she's fantastic.

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Speaker 2: You know.

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Speaker 1: It's like when imagine not caring that much, in fact,

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Speaker 1: not even knowing that not that she should be embarrassed

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Speaker 1: or not that she should be awkward, but just not

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Speaker 1: that's not even a thought. So free and so liberated

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Speaker 1: and she had the best time. I had the best time,

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Speaker 1: and the audience loved it as well. You know, it

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Speaker 1: could have been a clunky experience, but it just turned

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Speaker 1: out great. I loved it.

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Speaker 2: I think people who have special needs really can teach

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Speaker 2: us a lot, and it may be different things. You know,

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Speaker 2: the people who formerly owned my house, I've kept in

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Speaker 2: contact with beautiful people. And the husband is blind and

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Speaker 2: he taught me so much about the world when you

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Speaker 2: are devoid of one sense. Now he's a petrol head.

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Speaker 2: He loves car racing, loves cars, and just having conversations

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Speaker 2: with David is so much fun because it makes you

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Speaker 2: think about how you can interact with someone with a

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Speaker 2: disability when it even comes to simple things like you know,

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Speaker 2: I saw this yesterday. Well he can't, you know, he's

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Speaker 2: very used to this, and he's a really smart guy.

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Speaker 2: But I love looking through the world through his ears

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Speaker 2: and through interactions and through sense and touch and making

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Speaker 2: sure that I'm really descriptive when I talk to him,

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Speaker 2: and that I'm really mindful and respectful of where he

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Speaker 2: or how he takes in the world. And I love that.

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Speaker 2: And that's the same with my brother. You know, the

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Speaker 2: simple enjoyment of just getting on a train and there

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Speaker 2: and watching the countryside speed past and going up to Ballarat,

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Speaker 2: and then we hung around in the cafe and had

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Speaker 2: a dream can then wait for the train to turn

202
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Speaker 2: around and come back again, and then we jump back

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Speaker 2: on the train again and came home. But it was

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Speaker 2: a lot of fun. And again, those simple things that

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Speaker 2: we sometimes don't think about or take for granted, sometimes

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Speaker 2: through the eyes of somebody else, can make us really

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Speaker 2: reevaluate what is important or the things that the little

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Speaker 2: things in life.

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Speaker 1: Yeah, that one hundredsent agree. And also that's very smart

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Speaker 1: of you, Like, that's very naturally socially and emotionally intelligent

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Speaker 1: of you, Like trying to understand the world through someone

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Speaker 1: else's perception or through someone else's window experiences. You know,

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Speaker 1: like you can't see, but you're trying to see in

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Speaker 1: inverted commas what he sees in inverted commas, and that,

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Speaker 1: you know, in psych that's called theory of mind. Is

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Speaker 1: trying to understand how someone else perceives things, or how

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Speaker 1: someone else thinks, or how someone else sees the world

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Speaker 1: or sees the situation or see the conversation. In other words,

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Speaker 1: trying to put yourself in their psychological and or emotional experience,

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Speaker 1: and that a lot of people are terrible at that,

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Speaker 1: and a lot of people don't think about that. So,

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Speaker 1: you know, realizing what you're doing in real time is

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Speaker 1: that you and him might be in the same conversation

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Speaker 1: but clearly not the same experience, or you might be

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Speaker 1: in the same situation or circumstance or environment, but just

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Speaker 1: understanding that, you know, the way that you need to

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Speaker 1: connect with him and understand him and communicate with him

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Speaker 1: is very him specific, you know, versus talking to somebody

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Speaker 1: who who has vision. But that's yeah, that's very high

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Speaker 1: order kind of social intelligence that you naturally do. So

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Speaker 1: well done.

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Speaker 2: You thanks mate. You know I went to the twenty

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Speaker 2: first birthday of one of his sons recently, who jumps

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Speaker 2: online as part of our online gaming group, and you know,

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Speaker 2: I was there the lunch. It was insteat of winery,

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Speaker 2: and you know, because I've known the family for years,

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Speaker 2: it's really great, you know, they were you know, when

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Speaker 2: you buy a house, sometimes the real estate agent leaves

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Speaker 2: a bottle of champagne or something. Well, that doesn't happen

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Speaker 2: very often, but the family who were vacating the house

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Speaker 2: left a gift pack for me, like with brochures on

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Speaker 2: things to do, you know, champagne flutes and bottle of

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Speaker 2: champagne and chocolates and coffee sachets and you know, and

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Speaker 2: come and you know, make sure you come and have

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Speaker 2: dinner with us once you've got settled in. Just amazing people,

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Speaker 2: which is back up a friendship, and we've become good friends.

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Speaker 2: The only thing that really Alex, who is there son

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Speaker 2: who turned twenty one, has got to stop saying to

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Speaker 2: people that Patrick sleeps in my bedroom because it's his

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Speaker 2: old room is my room. And it's like, ah, nah,

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Speaker 2: just really uncomfortable with that.

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Speaker 1: Ah, just let him go. How old is twenty one?

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Speaker 2: He does it deliberately, of course, to take the piss

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Speaker 2: and knows that I find it really creepy. He says that.

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Speaker 2: But what I was getting at is when we're at

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Speaker 2: the twenty first now his younger brother is seventeen, and

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Speaker 2: you know what's about their family. His father needed to

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Speaker 2: go to the toilet, and so his youngest son just

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Speaker 2: got up and said, yeah, come on, dad, let's go.

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Speaker 2: How many seventeen year old boys would feel comfortable taking

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Speaker 2: their father to the toilet.

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Speaker 1: Well, I mean, that's a good question, but I guess

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Speaker 1: that's really because you've just grown up around that, right.

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Speaker 2: That's just what has that taught them about being people

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Speaker 2: who are considerate young people who are considerate of people

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Speaker 2: around them. And how much better a person has that

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Speaker 2: made them understanding that they need to contribute to the

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Speaker 2: family and that they can feel comfortable in themselves to

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Speaker 2: be a part of that dynamic. I think it's made

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Speaker 2: them much more rounded people. I think it's lovely to

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Speaker 2: see people who don't have reservations about being caring about

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Speaker 2: a parent who has a disability.

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Speaker 1: Yeah, I mean, I agree with you. I think I

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Speaker 1: think being around, whether or not it's growing up around

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Speaker 1: or being around or having friends with disabilities. And you know,

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Speaker 1: as you know, I've been working with Johnny in the

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Speaker 1: gym for the last six years, who's got a spinal

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Speaker 1: cord injury, and he started training in a wheelchair and

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Speaker 1: then eventually to a frame and now he's walking with

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Speaker 1: a stick. But you know, it's an undertaking for him

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Speaker 1: to walk twenty feet, you know, And so I mean

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Speaker 1: he can, but it just it takes him ten times

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Speaker 1: longer than it would take you to walk twenty feet,

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Speaker 1: and so I'm often walking around the gym with him

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Speaker 1: and I'm helping him, and I'm either holding his hand

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Speaker 1: or holding his arm or kind of lifting him half

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Speaker 1: lifting him up and down off a bench. And I

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Speaker 1: don't even think about it when I'm not saying a

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Speaker 1: great bloke. I'm saying, it's just a byproduct of being

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Speaker 1: around someone. And sometimes I'll be through the gym where

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Speaker 1: I'm helping him from one bench to another exercise, and

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Speaker 1: here's these two you know, old blokes, and one of

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Speaker 1: them's holding the other bloke's hand, and I don't even

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Speaker 1: I'm not aware of it until I see a seventeen

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Speaker 1: year old staring at me, like what the fuck are

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Speaker 1: they doing? You know, it's like, no, well it's okay, mate,

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Speaker 1: you know, and it's like and there's no, it's just

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Speaker 1: not a typical thing. But then you don't because it's

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Speaker 1: so automatic now because I've trained him probably thousands of times,

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Speaker 1: where it's just you know, like, you know, I'm constantly

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Speaker 1: and the crab is the same. Mark's amazing as well,

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Speaker 1: my training partner and everyone. It's like you're just naturally

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Speaker 1: doing these things without drawing attention to it or without

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Speaker 1: overthinking it. But I definitely think you know, and it's

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Speaker 1: beautiful the relationship you've got with your brother mate, and

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Speaker 1: it's and your friend who's you know, doesn't have sight.

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Speaker 1: I think for us as humans, it's I'm very at

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Speaker 1: the risk of sounding naf and lame, and you know,

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Speaker 1: I don't know trite. I'm very grateful for all of

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Speaker 1: the interactions I have with people whose life and situation

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Speaker 1: is tougher than mine, because I think I could be

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Speaker 1: a pain in the ass unless I had that gratitude

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Speaker 1: and that awareness that I'm very, very lucky and very

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Speaker 1: privileged to have what I have. And I don't just

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Speaker 1: mean things, I mean physically, mentally and emotionally, you know,

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Speaker 1: to be able to as we've spoken about before, but

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Speaker 1: to be able to get out of a chair and

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Speaker 1: go and turn on a tap and there's cold water,

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Speaker 1: and push a button and there's some heat, and open

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Speaker 1: a door and there's food inside that door. And then

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Speaker 1: you know, it's like we live in especially you and

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Speaker 1: me anyway, and privileged Australia. Not that everyone's privileged in Australia,

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Speaker 1: but a lot of us, you know, we've got a pretty.

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Speaker 2: Good Yeah, very very very much, so very much.

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Speaker 4: So.

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Speaker 2: Hey, I know we generally talk about tech stuff, and

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Speaker 2: I think when you asked me to do the potty

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Speaker 2: a little bit earlier than usual, I said, I've got

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Speaker 2: much together. But you know what, I did, throw some

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Speaker 2: stuff together for us.

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Speaker 1: All Right, I'm ready. Let's let's let's get out of

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Speaker 1: human behavior and into technology. I've got no notes in

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Speaker 1: front of me, so you need to be the host

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Speaker 1: for the next half hour. You need to host.

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Speaker 2: All right, it sounds good. I found this fascinating. Google,

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Speaker 2: with all the data processing due to AI, is now

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Speaker 2: put an order in to buy nuclear power like so

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Speaker 2: they need more power for their data centers. This is

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Speaker 2: a world's first deal. It was an article that was

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Speaker 2: in the Guardian newspaper yesterday or the day before. So

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Speaker 2: they've ordered six or seven small nuclear reactors from a

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Speaker 2: Californian power supplier and they need it to power all

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Speaker 2: the data processing, the staggering amount of data that's getting

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Speaker 2: processed now due to AI. Because every time you do

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Speaker 2: an AI search as opposed to a normal Google search,

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Speaker 2: you're exponentially doing needing a data center that can do

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Speaker 2: a lot more processing power. So these AI data centers

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Speaker 2: are running twenty four to seven. They're absolutely going off

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Speaker 2: tap at the moment. And it's exponential in terms of

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Speaker 2: the growth as well, because what's happening is more and

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Speaker 2: more companies are getting onto the AI bandwagon, and as

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Speaker 2: a consequence, they're needing bigger, more processing power, and that,

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Speaker 2: as a consequence means not just power, but water as

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Speaker 2: well cooling systems. So they use water and they use

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Speaker 2: a lot of electricity. And we're talking a shit ton.

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Speaker 2: That's a technical term, by the way.

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Speaker 1: Yeah, sure, I've just wrote that down.

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Speaker 2: Yeah, yeah, yeah, it's actually a tangible figure.

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Speaker 1: Is it a megawatch shit tone?

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Speaker 2: Yeah? Well probably Gigawa shit tone?

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Speaker 1: How many? How many killer wat's per megawatch ship tone?

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Speaker 1: I don't know, just I'm just trying to get the

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Speaker 1: metrics right. I'm just taking professor. Now, can I just

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Speaker 1: ask a question when you said they've ordered seven nuclear reactors,

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Speaker 1: I don't exactly know what that means. What do you

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Speaker 1: mean they're buying their own fucking dedicated nuclear energy? Yeah?

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Speaker 2: I know, but what is that?

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Speaker 1: What's a nuclear reactor? Does that create nuclear energy?

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Speaker 2: Well, it uses nuclear I mean effectively, it uses nuclear

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Speaker 2: power or nuclear the you know you're harnessing the atom.

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Speaker 2: It's a nuclear power plant that generates life.

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Speaker 1: I don't know what the fuck it's what I'm not physics.

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Speaker 1: Oh no, I can't only tell you about humans.

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Speaker 2: Well, in the nuclear power plant plant process, what they

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Speaker 2: do is they split the atom that creates energy, and

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Speaker 2: then they use that energy to hit water, and water

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Speaker 2: spins a turbine, and a turbine then generates electricity. That

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Speaker 2: I think that's the rudimentary and.

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Speaker 1: Hell, by the way, everyone, do not listen to us

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Speaker 1: to I'm the biggest stickhead, but maybe don't listen to

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Speaker 1: him either, because that could be all bullshit.

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Speaker 2: Google, if Tip was here, should be googling this right now.

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Speaker 1: That's okay, that's all right. So there, so you're doing it,

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Speaker 1: are you?

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Speaker 2: Yeah?

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Speaker 1: All right, here we go explain. You just go into

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Speaker 1: chatters chat GPT and say, simply.

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Speaker 2: Explain comes from nuclear fission. Nuclear power reactors use heat

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Speaker 2: produced during atomic fission to boil water produce pressurized steam.

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Speaker 2: Steam is routed through the reactor steam system to spin

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Speaker 2: a large turbine blade drives mechnetic generators to produce electricity.

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Speaker 1: Exactly what I just said. The fucking nothing like what

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Speaker 1: I did.

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Speaker 2: Come on, come on, all right, So all.

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Speaker 1: Right, the bottom line is Google are going nuclear. I

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Speaker 1: worry about with the exponential kind of acceleration of all

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Speaker 1: things tech, there's also an exponential expanse of requirement for

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Speaker 1: more and more power. As you've already said, you know,

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Speaker 1: I wonder when we get to that point of you know,

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Speaker 1: energy extinction, like the can't be.

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Speaker 2: I mean, it's not infinite now were the worrying is

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Speaker 2: at the moment that at presently there's more demand on

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Speaker 2: cold fire generating of power because what I mean here

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Speaker 2: in Australia we don't have there's only one nuclear reactor

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Speaker 2: and it's used for medical purposes, but of it is

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Speaker 2: there's a lot more pressure, so it's putting pressure across

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Speaker 2: the entire system. In the United States, they're turning to

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Speaker 2: nuclear because obviously for them, it's a cleaner alternative. And

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Speaker 2: I know people there's a lot of arguments for and

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Speaker 2: against nuclear power plants. They've been around for a long

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Speaker 2: time and so a good example is the fact that Westinghouse,

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Speaker 2: the company that may have made your fridge, also makes

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Speaker 2: the e Vincy. Now the e Vinchy is a micro

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Speaker 2: nuclear reactor and they're being built and they claim to

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Speaker 2: be able to deliver five megawatts of power up to

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Speaker 2: one hundred months, So that's eight years of power, right,

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Speaker 2: That's a staggering amount of power to be able to

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Speaker 2: And these are specifically being designed for lots of different purposes.

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Speaker 2: They're even talking about sending one of these to the Moon,

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Speaker 2: so potentially lunar missions could use these micro nuclear reactors.

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Speaker 2: So there's a lot of research being done specifically to

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Speaker 2: combat the issue of this demand on power.

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Speaker 1: Yeah, I think, I mean, I'm I'm not even close

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Speaker 1: to an expert in any of this stuff, of course,

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Speaker 1: I'm just a bloke listening to someone who knows slightly

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Speaker 1: more than me, I say, fucking slightly. But to me

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Speaker 1: it would seem that move I mean an obvious statement.

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Speaker 1: But you know, energy moving forward is just not just

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Speaker 1: energy for electricity and day to day operation, but energy

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Speaker 1: for humans in terms of the quality of energy, calories, food,

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Speaker 1: micro and macro nutrients. So energy to make you know,

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Speaker 1: computers and cars and organizations work, but also energy to

433
00:24:25,280 --> 00:24:27,359
Speaker 1: make humans work. I think there's a kind of a

434
00:24:28,520 --> 00:24:32,760
Speaker 1: dual kind of energetic issue that's looming.

435
00:24:32,960 --> 00:24:36,000
Speaker 2: Well, it's already here, I guess you know how my

436
00:24:36,119 --> 00:24:39,320
Speaker 2: brain works, which is a bit confusing for anybody listening

437
00:24:39,400 --> 00:24:41,240
Speaker 2: to our podcast, but a litt alone for me who

438
00:24:41,280 --> 00:24:43,280
Speaker 2: has to cope with it on a day to day basis.

439
00:24:43,720 --> 00:24:46,240
Speaker 2: But yes, to go through my mind sometimes. When I

440
00:24:46,320 --> 00:24:48,400
Speaker 2: was hiking this morning, I went to a place called

441
00:24:48,400 --> 00:24:52,320
Speaker 2: Bosstoc Reservoir, so I probably not very far, maybe went

442
00:24:52,400 --> 00:24:56,160
Speaker 2: about five kilometers this morning. Out in the bush, Fritz

443
00:24:56,200 --> 00:24:59,480
Speaker 2: saw a wallaby and chase the wallaby, but he didn't

444
00:24:59,520 --> 00:25:01,679
Speaker 2: get close to because there's no way a miniature now

445
00:25:01,760 --> 00:25:03,439
Speaker 2: is going to catch a wallaby, and he wouldn't want

446
00:25:03,440 --> 00:25:04,280
Speaker 2: to do anyway, but.

447
00:25:04,600 --> 00:25:06,479
Speaker 1: If he did, the wallaby would kick the fuck out

448
00:25:06,520 --> 00:25:06,760
Speaker 1: of him.

449
00:25:06,800 --> 00:25:09,520
Speaker 2: But okay, yeah, but you know what fascinates me about

450
00:25:09,520 --> 00:25:13,560
Speaker 2: You were talking about the biomechanics, and I'm pretty good

451
00:25:13,640 --> 00:25:16,640
Speaker 2: with my feeding of Fritz. He gets usually a half

452
00:25:16,680 --> 00:25:18,880
Speaker 2: a cup of food or a cup of dry food

453
00:25:18,960 --> 00:25:21,160
Speaker 2: and then something else, so I supplement it with bits

454
00:25:21,200 --> 00:25:23,639
Speaker 2: and pieces and a few vegetables and things. But what

455
00:25:23,800 --> 00:25:26,040
Speaker 2: blows my mind is he gets fed once a day

456
00:25:26,080 --> 00:25:28,600
Speaker 2: and maybe gets a treat after the walk. How the

457
00:25:28,760 --> 00:25:31,480
Speaker 2: hell is he able to run in the bush? Probably

458
00:25:31,640 --> 00:25:34,200
Speaker 2: four or five times the distance that I do. He

459
00:25:34,320 --> 00:25:36,359
Speaker 2: does all the things that he does. He's so active.

460
00:25:36,400 --> 00:25:39,720
Speaker 2: We do the zuomies, we throw toys. The fact that

461
00:25:39,880 --> 00:25:44,040
Speaker 2: that machine, that biological machine, can do so much with

462
00:25:44,760 --> 00:25:48,639
Speaker 2: main feed a day blows my mind.

463
00:25:49,680 --> 00:25:55,399
Speaker 1: Well, they're very metabolically efficient. But also, I mean, you

464
00:25:55,680 --> 00:26:01,560
Speaker 1: weigh probably twenty to thirty times what he weighs. Yeah, right,

465
00:26:01,760 --> 00:26:04,200
Speaker 1: so you think, what does he wait? Five ks?

466
00:26:05,000 --> 00:26:07,480
Speaker 2: No, he's about eight eight and a half.

467
00:26:08,240 --> 00:26:12,880
Speaker 1: Okay, and what are you about? Sixty five sixty eight? Yeah,

468
00:26:13,040 --> 00:26:16,240
Speaker 1: so you're about six and a half times his weight. Yeah,

469
00:26:16,440 --> 00:26:19,159
Speaker 1: so you put if you figured out his calories and

470
00:26:19,320 --> 00:26:22,520
Speaker 1: times by six and a half, it's probably about the same.

471
00:26:22,600 --> 00:26:25,680
Speaker 1: But you don't do zoomies and you don't chase wallabies.

472
00:26:26,359 --> 00:26:28,840
Speaker 1: So you do make a good point. But I mean,

473
00:26:28,920 --> 00:26:31,720
Speaker 1: the beauty of dogs is I mean, well, I was

474
00:26:31,760 --> 00:26:33,800
Speaker 1: going to say dogs don't eat junk food, but that's

475
00:26:33,880 --> 00:26:36,679
Speaker 1: not true depending on the owner. By the way, owners

476
00:26:36,680 --> 00:26:39,320
Speaker 1: who feed their dogs junk fuck. It makes me mad,

477
00:26:40,160 --> 00:26:42,720
Speaker 1: Like when you see dogs that are just morbidly obese

478
00:26:42,800 --> 00:26:47,240
Speaker 1: because their owners literally make them fat by fucking makes

479
00:26:47,280 --> 00:26:49,720
Speaker 1: me mad because you don't see that. You don't see

480
00:26:49,760 --> 00:26:52,320
Speaker 1: that with any other animals except animals who are genetically

481
00:26:52,440 --> 00:26:55,399
Speaker 1: required to be fat for survival. But anyway, no, he

482
00:26:55,480 --> 00:26:59,440
Speaker 1: doesn't need that much food. That's the point. But also

483
00:27:00,760 --> 00:27:03,719
Speaker 1: I feel like dogs miss out because you know how

484
00:27:03,800 --> 00:27:05,639
Speaker 1: we get so much pleasure from food.

485
00:27:06,640 --> 00:27:09,400
Speaker 2: Yeah, but you know what, they get so much pleasure

486
00:27:09,520 --> 00:27:15,080
Speaker 2: from being off lead, running around, exploring, sniffing. They smell everything.

487
00:27:15,119 --> 00:27:18,280
Speaker 2: It's like social media. They love it. They pee on things,

488
00:27:18,320 --> 00:27:21,399
Speaker 2: they smell other dogs pee, They sniff bums. They do

489
00:27:21,560 --> 00:27:22,240
Speaker 2: so many fun.

490
00:27:22,160 --> 00:27:25,480
Speaker 1: Things, letting them go different ways. So hang on, tiff,

491
00:27:25,520 --> 00:27:27,879
Speaker 1: can you make that a real please? They sniff bums.

492
00:27:27,920 --> 00:27:31,080
Speaker 1: They do so many fun things. Let's just capture that,

493
00:27:31,320 --> 00:27:35,280
Speaker 1: will we They sniff bums, They do so many fun things.

494
00:27:36,119 --> 00:27:39,200
Speaker 1: They smell pee. The fuck is wrong with you? What

495
00:27:39,320 --> 00:27:42,320
Speaker 1: makes you think any of that compares to a pizza

496
00:27:42,960 --> 00:27:47,960
Speaker 1: or fucking cheesecake? Like, oh, yeah, sure, sure, they're diets boring,

497
00:27:48,040 --> 00:27:50,760
Speaker 1: but they get to sniff asses and we oh wow,

498
00:27:50,840 --> 00:27:54,040
Speaker 1: that fuck you sold me. I'm changing. I'm going to

499
00:27:54,080 --> 00:27:57,720
Speaker 1: become a greyhound. Oh, I am.

500
00:27:58,119 --> 00:28:00,760
Speaker 2: Putting myself in the realm of the dog because I'm

501
00:28:00,800 --> 00:28:02,600
Speaker 2: trying to look at it from a dog's perspective.

502
00:28:02,720 --> 00:28:05,640
Speaker 1: Are you using theory of mind with canine's Canine Theory

503
00:28:05,720 --> 00:28:09,360
Speaker 1: of Mind with Patrick? Welcome back to today's episode Through

504
00:28:09,440 --> 00:28:13,120
Speaker 1: the Eyes of a Dog. I'm Patricks.

505
00:28:14,720 --> 00:28:17,879
Speaker 2: Someone told me that today that dogs aren't self aware.

506
00:28:19,359 --> 00:28:20,239
Speaker 2: So elephants are.

507
00:28:21,119 --> 00:28:21,239
Speaker 1: Are?

508
00:28:21,320 --> 00:28:23,600
Speaker 2: Some animals are. But if a dog looks at a mirror,

509
00:28:23,680 --> 00:28:26,240
Speaker 2: it doesn't see itself, it just sees another dog.

510
00:28:26,800 --> 00:28:27,280
Speaker 4: Is that's true?

511
00:28:29,040 --> 00:28:32,960
Speaker 1: It's I think dogs are. That is a very good question,

512
00:28:33,280 --> 00:28:36,280
Speaker 1: and if I'm being totally honest, I don't know the answer.

513
00:28:36,359 --> 00:28:38,840
Speaker 1: But that makes sense to me. But I think that

514
00:28:38,960 --> 00:28:42,120
Speaker 1: they look at you googling. I think that they are

515
00:28:42,280 --> 00:28:47,880
Speaker 1: definitely aware of other people's needs and emotions, and I

516
00:28:48,040 --> 00:28:51,560
Speaker 1: think they are especially with dogs that are very very

517
00:28:51,680 --> 00:28:54,800
Speaker 1: bonded with their human I was going to say owner.

518
00:28:54,920 --> 00:28:56,120
Speaker 1: I hate the word owner.

519
00:28:56,400 --> 00:28:58,040
Speaker 2: I don't use it. I don't use the word owner.

520
00:28:58,400 --> 00:29:01,760
Speaker 1: I think they're human, they're person and yep, their dad,

521
00:29:01,880 --> 00:29:06,280
Speaker 1: their mum, there, whatever. I think they are very attuned

522
00:29:06,480 --> 00:29:12,400
Speaker 1: to the needs and emotions and even mental states of

523
00:29:13,280 --> 00:29:18,440
Speaker 1: they're human. But self awareness is a slippery slope in general.

524
00:29:18,480 --> 00:29:20,040
Speaker 1: But it doesn't surprise me that.

525
00:29:20,880 --> 00:29:23,440
Speaker 2: But then, how do you know, well, like looked at

526
00:29:23,480 --> 00:29:27,600
Speaker 2: two articles, one from the Smithsonian magazine that says dogs

527
00:29:27,760 --> 00:29:31,040
Speaker 2: may be more self aware than experts thought, and then

528
00:29:31,080 --> 00:29:35,240
Speaker 2: the second one is from an article on the website

529
00:29:35,360 --> 00:29:38,720
Speaker 2: earth dot com, and it says that although dogs can't

530
00:29:38,920 --> 00:29:42,520
Speaker 2: identify themselves in the mirror, they still have some levels

531
00:29:42,560 --> 00:29:46,080
Speaker 2: of self awareness. They ace other self recognition tests, They

532
00:29:46,120 --> 00:29:49,440
Speaker 2: can recognize their own odor, and they can recall memories

533
00:29:49,480 --> 00:29:51,680
Speaker 2: of specific events. So there you go.

534
00:29:52,240 --> 00:29:55,680
Speaker 1: Should we ask Chap GPT go for it? All right? On?

535
00:29:56,120 --> 00:29:56,320
Speaker 2: Yep?

536
00:29:57,040 --> 00:29:59,840
Speaker 1: On are dogs self aware?

537
00:30:01,960 --> 00:30:04,720
Speaker 4: Dogs have a level of self awareness, but it's not

538
00:30:04,840 --> 00:30:08,000
Speaker 4: quite like human self awareness. They show signs of understanding

539
00:30:08,000 --> 00:30:10,800
Speaker 4: their own bodies and movements, and they can recognize their

540
00:30:10,840 --> 00:30:14,680
Speaker 4: own scent. However, in tests like the mirror test, which

541
00:30:14,760 --> 00:30:19,760
Speaker 4: measures self recognition, dogs generally don't recognize themselves. They might

542
00:30:19,800 --> 00:30:22,760
Speaker 4: see their reflection as another dog or just ignore it.

543
00:30:23,280 --> 00:30:26,280
Speaker 4: So while they have some degree of self awareness, it's

544
00:30:26,360 --> 00:30:28,080
Speaker 4: more limited compared to humans.

545
00:30:29,960 --> 00:30:33,240
Speaker 1: Thanks shatters here you get well, yeah, I think also,

546
00:30:33,560 --> 00:30:35,640
Speaker 1: And also you got to remember, even with chat JPT,

547
00:30:35,840 --> 00:30:38,680
Speaker 1: they're just drawing on whatever's on the Internet that they

548
00:30:38,800 --> 00:30:39,680
Speaker 1: access at the time.

549
00:30:39,760 --> 00:30:39,920
Speaker 4: Too.

550
00:30:40,160 --> 00:30:43,040
Speaker 1: But interesting, all right, what else you got for US

551
00:30:43,080 --> 00:30:43,480
Speaker 1: tech boy.

552
00:30:43,920 --> 00:30:46,760
Speaker 2: While we're talking about AI and we know it's a

553
00:30:46,880 --> 00:30:50,160
Speaker 2: billion dollar industry. Now here's an article that I read

554
00:30:50,280 --> 00:30:53,760
Speaker 2: recently that actually frightened me a little bit in terms

555
00:30:53,880 --> 00:30:57,240
Speaker 2: of what it means in the implications. So this article

556
00:30:57,400 --> 00:31:02,680
Speaker 2: was in published on the Conversation and it's stated that

557
00:31:03,240 --> 00:31:08,920
Speaker 2: that AI is being underpinned by an exploited workforce. So

558
00:31:09,040 --> 00:31:11,760
Speaker 2: what does that actually mean? There are you know, we

559
00:31:11,880 --> 00:31:16,760
Speaker 2: think about people working putting garments together and working in sweatshops.

560
00:31:18,040 --> 00:31:21,320
Speaker 2: There's one part of AI we don't think about, and

561
00:31:21,400 --> 00:31:27,160
Speaker 2: it's data labeling. So data comes in and a human

562
00:31:27,240 --> 00:31:31,480
Speaker 2: operator has to label that data to explain what it is.

563
00:31:31,840 --> 00:31:35,400
Speaker 2: So if it's a picture of Craig, it's said handsome,

564
00:31:35,520 --> 00:31:39,160
Speaker 2: middle aged man, big guns. You know, it's got to

565
00:31:39,200 --> 00:31:42,640
Speaker 2: come up with something, right. But the interesting thing is that,

566
00:31:43,720 --> 00:31:48,120
Speaker 2: you know, with the AI industry expected to be worth

567
00:31:48,160 --> 00:31:51,160
Speaker 2: about four hundred and seven billion US dollars by twenty

568
00:31:51,240 --> 00:31:55,000
Speaker 2: twenty seven, right, that's not a long way away. The

569
00:31:55,120 --> 00:31:59,520
Speaker 2: problem is that there's up to one hundred data labelers

570
00:31:59,760 --> 00:32:02,840
Speaker 2: for each AI and all these AI workers are in

571
00:32:02,920 --> 00:32:06,720
Speaker 2: places like Kenya and they work for these companies like Facebook,

572
00:32:06,800 --> 00:32:11,160
Speaker 2: SCALEAI Open AI all that sort of stuff. And the

573
00:32:11,280 --> 00:32:15,480
Speaker 2: thing is that they're on really crap conditions and wages.

574
00:32:15,720 --> 00:32:18,480
Speaker 2: So data abeling, So this is the basically you take

575
00:32:18,520 --> 00:32:22,800
Speaker 2: the raw data, images, video, text, and then you say

576
00:32:22,880 --> 00:32:25,440
Speaker 2: to AI, this is what you are seeing, this is

577
00:32:25,520 --> 00:32:27,920
Speaker 2: what you are hearing, so that AI can understand what

578
00:32:28,040 --> 00:32:34,440
Speaker 2: it is and whether it's self driving cars, smart devices, chat, GPT,

579
00:32:34,680 --> 00:32:37,880
Speaker 2: all that stuff has to be labeled because AI thrives

580
00:32:38,080 --> 00:32:41,560
Speaker 2: on data and these data models that they have to

581
00:32:41,760 --> 00:32:45,680
Speaker 2: keep updating. So for AI to continue to be as

582
00:32:45,720 --> 00:32:48,000
Speaker 2: smart as it is, you've got to keep updating it.

583
00:32:48,200 --> 00:32:51,880
Speaker 2: So these data sets need to be updated and refreshed regularly.

584
00:32:51,960 --> 00:32:57,600
Speaker 2: They cannot work without them. So tech giants so Meta, Google, OpenAI, Microsoft,

585
00:32:57,920 --> 00:33:02,840
Speaker 2: They outsource all of this stuff to the Filmilippines, Kenya, India, Pakistan, Venezuela,

586
00:33:03,520 --> 00:33:06,240
Speaker 2: Colombia and now China of course is jumping on the

587
00:33:06,280 --> 00:33:10,640
Speaker 2: bandwagon as well. So this has become an ethical thing

588
00:33:11,080 --> 00:33:13,800
Speaker 2: that I guess we in the Western world, sitting on

589
00:33:13,840 --> 00:33:16,520
Speaker 2: the other end of a phone or a computer or

590
00:33:16,560 --> 00:33:21,720
Speaker 2: a tablet, just don't think about the implications. And look,

591
00:33:21,880 --> 00:33:25,600
Speaker 2: there's moves. I think Joe Biden was looking at some

592
00:33:25,840 --> 00:33:28,760
Speaker 2: sort of international agreement. But the reality of it is,

593
00:33:28,880 --> 00:33:30,640
Speaker 2: I don't know what we can do. I mean, we're

594
00:33:30,640 --> 00:33:33,040
Speaker 2: getting we're using it as we speak, you know, we've

595
00:33:33,120 --> 00:33:36,800
Speaker 2: just within the last ten minutes. So well, it's good

596
00:33:36,840 --> 00:33:37,480
Speaker 2: to be aware of it.

597
00:33:38,280 --> 00:33:42,280
Speaker 1: Yeah, but also you I mean, wow, I find that

598
00:33:42,720 --> 00:33:46,480
Speaker 1: not hard to believe. But I find that curious that

599
00:33:47,760 --> 00:33:52,120
Speaker 1: you know, on some level there's people sitting in some

600
00:33:52,440 --> 00:33:56,520
Speaker 1: third world country, potentially third world country, looking at images

601
00:33:57,040 --> 00:34:00,680
Speaker 1: and describing that image and that's part of the very

602
00:34:00,920 --> 00:34:06,360
Speaker 1: very very high tech evolved, you know system that we're

603
00:34:06,400 --> 00:34:09,560
Speaker 1: in the middle. How is that happening in twenty twenty four?

604
00:34:10,080 --> 00:34:14,920
Speaker 1: Like and not? Can't AI itself? Hasn't it been trained

605
00:34:14,960 --> 00:34:16,960
Speaker 1: and developed to a point where it can look at

606
00:34:17,000 --> 00:34:20,720
Speaker 1: me and go, you know, middle aged I can white

607
00:34:20,760 --> 00:34:23,839
Speaker 1: bloke with a bad attitude. Can't it do that all

608
00:34:23,880 --> 00:34:25,239
Speaker 1: by itself? Now? No?

609
00:34:25,400 --> 00:34:27,759
Speaker 2: The problem with that is if you're using AI to

610
00:34:27,880 --> 00:34:30,600
Speaker 2: train AI, that's your AI cannibalism. Isn't it.

611
00:34:32,560 --> 00:34:35,960
Speaker 1: Not to train AI? But surely surely it can look

612
00:34:36,000 --> 00:34:39,480
Speaker 1: at pretty much anything now and figure out what it is. Like,

613
00:34:39,600 --> 00:34:42,319
Speaker 1: do we still need people to be going, oh, that's

614
00:34:42,360 --> 00:34:44,960
Speaker 1: a train, that's a yellow train with red wheels.

615
00:34:46,280 --> 00:34:49,480
Speaker 2: People are better at it. People are much better at it.

616
00:34:49,560 --> 00:34:52,920
Speaker 2: We adapt. You know, the reality of it is that

617
00:34:53,200 --> 00:34:57,640
Speaker 2: it's a good thing. That there's an oversight in some ways,

618
00:34:58,400 --> 00:35:01,040
Speaker 2: but at this stage it appears is not. It appears

619
00:35:01,120 --> 00:35:03,799
Speaker 2: that the industry needs this, and when people are being

620
00:35:03,880 --> 00:35:07,360
Speaker 2: paid between say you're in Venezuela, you're being paid between

621
00:35:07,480 --> 00:35:10,480
Speaker 2: ninety cents and two dollars US an hour to do

622
00:35:10,640 --> 00:35:12,360
Speaker 2: this generally mindless work.

623
00:35:13,080 --> 00:35:15,640
Speaker 1: Do you know what I think? I don't know. I

624
00:35:15,680 --> 00:35:17,880
Speaker 1: don't think we've ever We've kind of spoken about this,

625
00:35:18,040 --> 00:35:22,440
Speaker 1: but not in any great detail. I think there's a vast,

626
00:35:23,080 --> 00:35:30,040
Speaker 1: vast chasmhole in the in what's happening right now in

627
00:35:30,160 --> 00:35:32,239
Speaker 1: terms of the role out and the I guess the

628
00:35:32,480 --> 00:35:37,359
Speaker 1: overwhelm of technology. You know, we've spoken about my mum

629
00:35:37,400 --> 00:35:40,080
Speaker 1: and dad a bit with tech, and you know that

630
00:35:40,360 --> 00:35:42,319
Speaker 1: now I've taken over the paying of all of their

631
00:35:42,400 --> 00:35:45,720
Speaker 1: bills electronically because mum and dad were freaked out, because

632
00:35:46,520 --> 00:35:48,360
Speaker 1: you know, I mean, the truth is that there are

633
00:35:48,480 --> 00:35:51,600
Speaker 1: even in Australia, there are millions of people who are

634
00:35:51,640 --> 00:35:59,719
Speaker 1: not tech savvy who are constantly having problems with navigating

635
00:36:00,120 --> 00:36:02,920
Speaker 1: world that is very very very different to the one

636
00:36:03,080 --> 00:36:06,000
Speaker 1: twenty years ago. And of course technology brings with it

637
00:36:06,480 --> 00:36:11,200
Speaker 1: great advantages, but it also brings potential or many potential problems.

638
00:36:12,520 --> 00:36:15,520
Speaker 1: What I mean, there's no answer to this, but or

639
00:36:15,560 --> 00:36:20,600
Speaker 1: there's no immediate answer. But being able to create technology

640
00:36:20,800 --> 00:36:25,279
Speaker 1: that is truly user friendly, truly user friendly for people

641
00:36:25,320 --> 00:36:28,680
Speaker 1: who don't understand technology, I mean, I think that's the

642
00:36:28,800 --> 00:36:32,640
Speaker 1: next great bloody opportunity or the great the next great

643
00:36:32,719 --> 00:36:36,200
Speaker 1: problem to be solved, because you know, even for me

644
00:36:36,320 --> 00:36:38,839
Speaker 1: and I use technology all day every day, we're using

645
00:36:38,920 --> 00:36:42,960
Speaker 1: it right now, I've got multiple computers, phones. You know,

646
00:36:43,480 --> 00:36:46,759
Speaker 1: I'm my life, my business, my career is dependent on it.

647
00:36:48,200 --> 00:36:51,320
Speaker 1: And I'm still a complete fucking dummy compared to you,

648
00:36:52,320 --> 00:36:55,840
Speaker 1: and you're a complete dummy compared to someone else. But

649
00:36:55,960 --> 00:36:58,400
Speaker 1: then you take at one level beyond me and you

650
00:36:58,520 --> 00:37:00,799
Speaker 1: go then there are like my mum and dad who

651
00:37:00,840 --> 00:37:02,719
Speaker 1: do not know how to pay a bill unless it's

652
00:37:02,760 --> 00:37:05,880
Speaker 1: with a check or cash. You know, how do we

653
00:37:06,000 --> 00:37:09,360
Speaker 1: look after those people moving forward? Because it seems like

654
00:37:10,320 --> 00:37:12,880
Speaker 1: they're not really being hated.

655
00:37:12,600 --> 00:37:17,600
Speaker 2: For the digital haves and have nots. I guess it's

656
00:37:17,719 --> 00:37:22,920
Speaker 2: probably people maybe fifty up because they didn't grow up

657
00:37:22,960 --> 00:37:27,000
Speaker 2: in a schooling environment with technology. They may have not

658
00:37:27,200 --> 00:37:29,480
Speaker 2: adopted technology because they didn't need it for their job

659
00:37:29,560 --> 00:37:31,760
Speaker 2: if they were in a trade or they did something

660
00:37:31,840 --> 00:37:34,520
Speaker 2: that didn't require them to be on computers. And I mean,

661
00:37:34,560 --> 00:37:37,640
Speaker 2: do you remember when they started rolling out atm machines,

662
00:37:38,120 --> 00:37:40,600
Speaker 2: how lot people just didn't know how to use them

663
00:37:40,640 --> 00:37:42,640
Speaker 2: and struggled with them. And there's still concerns for a

664
00:37:42,680 --> 00:37:46,399
Speaker 2: lot of older people. For me, you asked two kind

665
00:37:46,400 --> 00:37:49,080
Speaker 2: of really pertinent questions there. One is how do we

666
00:37:49,160 --> 00:37:52,360
Speaker 2: support and help the people right now who are in

667
00:37:52,480 --> 00:37:54,799
Speaker 2: that digital divide, who are part of the other side

668
00:37:54,840 --> 00:37:59,600
Speaker 2: of the digital divide? And I guess it's compassion from

669
00:37:59,760 --> 00:38:02,879
Speaker 2: the banking system, from those services, you know, whether you're

670
00:38:02,920 --> 00:38:05,959
Speaker 2: going to my other account and being able to still

671
00:38:06,480 --> 00:38:09,480
Speaker 2: have face to face contact and saying, well, you know,

672
00:38:09,560 --> 00:38:11,920
Speaker 2: the reality of it is, if someone's over the age

673
00:38:11,960 --> 00:38:15,200
Speaker 2: of sixty or seventy, they may still need to walk

674
00:38:15,239 --> 00:38:16,799
Speaker 2: into a bank and sit down and talk to their

675
00:38:16,880 --> 00:38:20,080
Speaker 2: bank teller, their bank manager, and we need to not

676
00:38:20,440 --> 00:38:24,080
Speaker 2: force them onto technology because maybe beyond them, we need

677
00:38:24,160 --> 00:38:27,200
Speaker 2: to understand that some people a they may not be willing,

678
00:38:27,320 --> 00:38:30,319
Speaker 2: but be they may be frightened. They may have many

679
00:38:30,480 --> 00:38:33,560
Speaker 2: reasons for being part of the digital divide. So I think,

680
00:38:34,040 --> 00:38:35,719
Speaker 2: first of all, as a society, we need to be

681
00:38:35,800 --> 00:38:38,360
Speaker 2: more compassionate to those people and not force them to

682
00:38:38,400 --> 00:38:40,920
Speaker 2: do something. COVID forced a little of people to work

683
00:38:40,960 --> 00:38:43,239
Speaker 2: out what a Q code was, but a lot of

684
00:38:43,280 --> 00:38:47,319
Speaker 2: people stressed over that, so it's difficult for those people.

685
00:38:47,400 --> 00:38:49,640
Speaker 2: But the secondary thing is, and I think the exciting

686
00:38:49,719 --> 00:38:52,279
Speaker 2: thing from the next level up and it won't help

687
00:38:52,360 --> 00:38:56,240
Speaker 2: your parents, but it may help us and people younger

688
00:38:56,280 --> 00:38:59,320
Speaker 2: than us as we get older. Is as technology and

689
00:38:59,400 --> 00:39:03,560
Speaker 2: AIS in implemented, is getting technology that doesn't just have

690
00:39:03,719 --> 00:39:06,279
Speaker 2: a this one way to turn something on and off.

691
00:39:06,719 --> 00:39:10,040
Speaker 2: If you think about it, if you ask different ways,

692
00:39:10,400 --> 00:39:12,759
Speaker 2: you know, you can use different phrases to say the

693
00:39:12,840 --> 00:39:15,040
Speaker 2: same thing to try to get the same results. But

694
00:39:15,239 --> 00:39:19,480
Speaker 2: generally most computers are binary. It's yes or no, it's

695
00:39:19,560 --> 00:39:24,240
Speaker 2: off or on. But with the deployment of things like AI,

696
00:39:24,640 --> 00:39:29,200
Speaker 2: it will make technology easier because you know, I envisited

697
00:39:29,239 --> 00:39:32,560
Speaker 2: a time where we won't be using phones anymore. We'll

698
00:39:32,600 --> 00:39:36,640
Speaker 2: have a pair of our glasses will project the information

699
00:39:36,840 --> 00:39:39,200
Speaker 2: we need hovering in front of us like a heads

700
00:39:39,239 --> 00:39:41,319
Speaker 2: up display. Your car has a heads up display, doesn't

701
00:39:41,320 --> 00:39:41,920
Speaker 2: it your new car?

702
00:39:42,080 --> 00:39:42,279
Speaker 1: Yeah?

703
00:39:42,640 --> 00:39:45,880
Speaker 2: Yeah, okay, So it's not obtrusive at all, and in

704
00:39:46,040 --> 00:39:48,960
Speaker 2: fact it helps with the road experience because you're not

705
00:39:49,040 --> 00:39:51,800
Speaker 2: looking down at your speedo. But I could imagine a

706
00:39:51,920 --> 00:39:54,400
Speaker 2: future where I would just say, you know, what's the

707
00:39:54,480 --> 00:39:58,040
Speaker 2: weather going to be today, and tell me that without

708
00:39:58,160 --> 00:40:01,680
Speaker 2: searching for an app, without going going to a Google

709
00:40:01,760 --> 00:40:04,439
Speaker 2: search bar and typing that in. So I think as

710
00:40:04,600 --> 00:40:08,000
Speaker 2: technology becomes more used friendly, then hopefully for us and

711
00:40:08,160 --> 00:40:12,640
Speaker 2: people who's substantly come along, you won't have the barriers.

712
00:40:12,680 --> 00:40:16,359
Speaker 2: We won't have keyboards to worry about. We will have conversations.

713
00:40:16,600 --> 00:40:19,000
Speaker 2: You just had a conversation with chat GPT and that

714
00:40:19,160 --> 00:40:21,719
Speaker 2: was very natural. And the thing about a lot of

715
00:40:21,800 --> 00:40:24,800
Speaker 2: these searches now is they remember what we previously spoke about.

716
00:40:25,200 --> 00:40:29,040
Speaker 2: So if you can think about your experiences of using

717
00:40:29,120 --> 00:40:32,280
Speaker 2: a phone and then putting it all into smart glasses,

718
00:40:32,600 --> 00:40:35,200
Speaker 2: it's hovering there. Quite often. We don't need to look

719
00:40:35,200 --> 00:40:37,520
Speaker 2: at our phone. If you want to call me and

720
00:40:37,600 --> 00:40:40,560
Speaker 2: you say call Patrick Bonello, you don't need to go

721
00:40:40,800 --> 00:40:44,000
Speaker 2: through your contact list. It verifies it's you and then

722
00:40:44,040 --> 00:40:47,480
Speaker 2: the call gets initiated. So for me Hopefully we'll get

723
00:40:47,480 --> 00:40:49,799
Speaker 2: a hybrid of this that will help your parents down

724
00:40:49,840 --> 00:40:52,480
Speaker 2: the track, maybe, you know, if they get more and

725
00:40:52,600 --> 00:40:55,600
Speaker 2: more comfortable, at least with using voice activation. It takes

726
00:40:55,640 --> 00:40:59,200
Speaker 2: screens and keyboards and mice away from people who may

727
00:40:59,239 --> 00:40:59,880
Speaker 2: have problems with it.

728
00:41:01,320 --> 00:41:03,359
Speaker 1: Even my little old car that I get around then,

729
00:41:03,480 --> 00:41:06,200
Speaker 1: which is a five year old Suzuki. It's not that old,

730
00:41:06,280 --> 00:41:08,360
Speaker 1: but you know what I mean, it's and it's just

731
00:41:08,520 --> 00:41:11,680
Speaker 1: really it's a Suzuki Swift that's super basic. There's a

732
00:41:11,719 --> 00:41:13,960
Speaker 1: button on the thing which is like a bloke talking

733
00:41:14,120 --> 00:41:16,920
Speaker 1: or a person talking. I press that and I go

734
00:41:18,239 --> 00:41:23,560
Speaker 1: call Patrick, and the lady goes calling Patrick Bonello, you know,

735
00:41:23,800 --> 00:41:25,800
Speaker 1: and then it rings you. I don't even I know

736
00:41:25,920 --> 00:41:28,720
Speaker 1: where that button is without even looking at the steering wheel.

737
00:41:29,520 --> 00:41:32,120
Speaker 1: I can just watch the road, press that button with

738
00:41:32,280 --> 00:41:34,600
Speaker 1: my thumb and tell my car to call you when

739
00:41:34,680 --> 00:41:37,279
Speaker 1: it does. And I mean that's five or six year

740
00:41:37,280 --> 00:41:41,040
Speaker 1: old technology. But I mean everything you're saying I agree with,

741
00:41:41,800 --> 00:41:43,759
Speaker 1: and I think moving forward it's great. And I'm a

742
00:41:43,800 --> 00:41:47,040
Speaker 1: little bit selfish and I'm a little bit biased with

743
00:41:47,200 --> 00:41:49,760
Speaker 1: this because of my eighty four and five year old parents.

744
00:41:50,520 --> 00:41:54,560
Speaker 1: But like, hands down, at the moment. Hands down, my

745
00:41:54,719 --> 00:41:59,880
Speaker 1: mum's biggest source of anxiety is technology because it's scarce

746
00:42:00,080 --> 00:42:03,000
Speaker 1: a shit out of her and she doesn't know, you know,

747
00:42:03,120 --> 00:42:07,040
Speaker 1: in my mom Like my mum's got an iPhone, she

748
00:42:07,200 --> 00:42:10,480
Speaker 1: literally doesn't know how to use it other than to

749
00:42:10,640 --> 00:42:13,360
Speaker 1: make a call and get a call, you know, and

750
00:42:13,480 --> 00:42:16,040
Speaker 1: even I could, you know, I've tried to teach her

751
00:42:16,239 --> 00:42:19,880
Speaker 1: so many times how to do that. She can she

752
00:42:20,000 --> 00:42:23,680
Speaker 1: can send texts, but even then it's pretty clunky. But

753
00:42:24,239 --> 00:42:26,880
Speaker 1: I will send her a text and she it'll go,

754
00:42:27,280 --> 00:42:29,560
Speaker 1: she'll get it, but she doesn't get it because she

755
00:42:29,680 --> 00:42:32,400
Speaker 1: never thinks to look or that little sign in the

756
00:42:32,480 --> 00:42:35,560
Speaker 1: window or whatever. You know. It's like, I don't know.

757
00:42:35,760 --> 00:42:39,160
Speaker 1: I guess there's no answer. But it's like we're so brilliant,

758
00:42:39,200 --> 00:42:42,680
Speaker 1: we're so advanced at solving problems, and we can do

759
00:42:42,880 --> 00:42:46,480
Speaker 1: you know, we can we can do pretty much anything now,

760
00:42:46,560 --> 00:42:50,040
Speaker 1: but we can't create a way for old people who

761
00:42:50,200 --> 00:42:55,880
Speaker 1: aren't technologically minded or trained. It'd be great if we

762
00:42:55,960 --> 00:42:58,960
Speaker 1: could produce something which for them is just as easy

763
00:42:59,000 --> 00:43:02,080
Speaker 1: as talking to a human or having a human interaction.

764
00:43:02,800 --> 00:43:06,440
Speaker 1: Because you think about the percentage of people in Australia

765
00:43:06,520 --> 00:43:09,479
Speaker 1: who are say older than sixty and that's the group

766
00:43:09,560 --> 00:43:12,440
Speaker 1: we're talking about. I don't know what it is, but

767
00:43:12,560 --> 00:43:14,600
Speaker 1: I would guess it would be somewhere in the three

768
00:43:14,840 --> 00:43:17,920
Speaker 1: four million range. I mean, that's a lot of humans,

769
00:43:17,960 --> 00:43:21,160
Speaker 1: and we're not a massive population. Then you think globally,

770
00:43:21,320 --> 00:43:24,440
Speaker 1: you extrapolate that it might be a billion people who

771
00:43:24,480 --> 00:43:28,000
Speaker 1: are sixty year older. You know, that's a big that's

772
00:43:28,040 --> 00:43:28,720
Speaker 1: a big market.

773
00:43:29,400 --> 00:43:32,640
Speaker 2: There are some companies that are servicing that market. I

774
00:43:32,760 --> 00:43:35,600
Speaker 2: was thinking about your mum and the iPhone, and then

775
00:43:35,840 --> 00:43:37,800
Speaker 2: I kind of thought, well, my little brother has a

776
00:43:37,920 --> 00:43:40,640
Speaker 2: phone that doesn't have a screen on it. All it has,

777
00:43:40,880 --> 00:43:43,240
Speaker 2: if you can imagine, you know, it's a bit smaller

778
00:43:43,280 --> 00:43:46,040
Speaker 2: than a standard mobile phone, a bit bigger than card

779
00:43:46,400 --> 00:43:49,120
Speaker 2: and all it has is you pre program. It's got

780
00:43:49,160 --> 00:43:51,480
Speaker 2: a big, chunky name next to it, so it's Patrick,

781
00:43:52,080 --> 00:43:55,239
Speaker 2: it's Dad, it's all the various contacts. I think about

782
00:43:55,280 --> 00:43:58,200
Speaker 2: eight or ten on it, maybe only eight, and you

783
00:43:58,320 --> 00:44:00,799
Speaker 2: just button and it calls them. That's it. All you've

784
00:44:00,840 --> 00:44:03,000
Speaker 2: got is a call and a hang up. Doesn't even

785
00:44:03,040 --> 00:44:05,960
Speaker 2: have a keypad to dial numbers. You just have emergency

786
00:44:06,040 --> 00:44:07,960
Speaker 2: contacts or people you want to speak to, and he

787
00:44:08,120 --> 00:44:10,760
Speaker 2: just press the button, it calls them, and he presses

788
00:44:10,800 --> 00:44:12,920
Speaker 2: the hang up button most of the time to hang up.

789
00:44:13,600 --> 00:44:15,759
Speaker 1: And how does he know who's ringing?

790
00:44:15,840 --> 00:44:21,399
Speaker 2: If someone rings, Oh, I guess that lights up next

791
00:44:21,440 --> 00:44:21,640
Speaker 2: to them.

792
00:44:21,719 --> 00:44:25,160
Speaker 1: I don't know, amen, because I'm just thinking what efforts,

793
00:44:25,160 --> 00:44:27,640
Speaker 1: you know, one of those fucking annoying people trying to

794
00:44:27,719 --> 00:44:29,680
Speaker 1: sell your shit. You don't want to be answering those

795
00:44:29,680 --> 00:44:30,160
Speaker 1: all the time.

796
00:44:30,760 --> 00:44:33,400
Speaker 2: I just realized that the contact details that I've got

797
00:44:33,440 --> 00:44:36,120
Speaker 2: in my phone for his phone is Jason's lego phone.

798
00:44:37,360 --> 00:44:38,200
Speaker 1: That's hilarious.

799
00:44:38,400 --> 00:44:40,200
Speaker 2: Yeah, but I don't know. I'll have to try that

800
00:44:40,360 --> 00:44:42,840
Speaker 2: next time. I'm not sure what it does when you

801
00:44:43,000 --> 00:44:45,080
Speaker 2: ring in and how he knows where it's coming from.

802
00:44:45,400 --> 00:44:47,239
Speaker 2: That's a really good question. I need to follow that up.

803
00:44:48,400 --> 00:44:52,839
Speaker 1: Oh wow, oh wow, all right, let's do another one

804
00:44:52,960 --> 00:44:55,120
Speaker 1: or two if you've got anything on your list.

805
00:44:55,760 --> 00:44:58,960
Speaker 2: Well, this is an interesting one. The government's getting really proactive.

806
00:44:59,000 --> 00:45:01,239
Speaker 2: When I say the government, this trading. Government's getting really

807
00:45:01,280 --> 00:45:06,920
Speaker 2: proactive with a first ever standalone Cybersecurity Act. So what

808
00:45:07,120 --> 00:45:10,680
Speaker 2: this means there's two cybersecurity bills that are currently being

809
00:45:10,760 --> 00:45:14,440
Speaker 2: reviewed by a parliamentary committee and what they're looking at

810
00:45:14,719 --> 00:45:20,000
Speaker 2: is a mandatory minimum cyber security standard for smart devices

811
00:45:20,080 --> 00:45:25,879
Speaker 2: because things like speakers, vacuums, doorbells, fridges, all that sort

812
00:45:25,920 --> 00:45:29,320
Speaker 2: of smart connectivity because they're there now. They want to

813
00:45:29,440 --> 00:45:34,040
Speaker 2: have an absolute minimum that that security means. Because there

814
00:45:34,160 --> 00:45:37,640
Speaker 2: was a brand of vacuum cleaners recently that they found

815
00:45:37,719 --> 00:45:40,839
Speaker 2: out that because they have cameras built into them, these

816
00:45:41,000 --> 00:45:44,680
Speaker 2: robo vACC You don't have a robovac, dear, no so,

817
00:45:45,040 --> 00:45:45,880
Speaker 2: but there's been a.

818
00:45:45,880 --> 00:45:49,000
Speaker 1: Bit of stuff in the news about robo vax fucking

819
00:45:49,280 --> 00:45:52,080
Speaker 1: doing like attacking dogs.

820
00:45:51,840 --> 00:45:56,320
Speaker 2: And dog yeah. No, well, in this instance, recording everything

821
00:45:56,680 --> 00:45:58,600
Speaker 2: so they can send to the cloud and they can

822
00:45:58,680 --> 00:46:01,319
Speaker 2: basically look through through the cameras. I mean for your

823
00:46:01,360 --> 00:46:04,839
Speaker 2: own personal security. This is scary to think that your

824
00:46:04,920 --> 00:46:08,880
Speaker 2: own devices could be spying on you. So your robot

825
00:46:09,000 --> 00:46:11,040
Speaker 2: vacuum cleaner has a camera in it, and if you

826
00:46:11,120 --> 00:46:14,280
Speaker 2: think that it's vacuuming around the house and you've got kids,

827
00:46:14,360 --> 00:46:17,279
Speaker 2: and you've got older people, and it could be seeing

828
00:46:17,360 --> 00:46:20,440
Speaker 2: and watching and then recording that information. There was one brand,

829
00:46:20,520 --> 00:46:22,279
Speaker 2: and I can't think of it at the moment. It's

830
00:46:22,360 --> 00:46:24,680
Speaker 2: not one of the big popular ones, but certainly was

831
00:46:24,719 --> 00:46:28,520
Speaker 2: a reasonably popular one. They didn't have protections in place,

832
00:46:28,600 --> 00:46:31,880
Speaker 2: so that data was being captured, including camera footage and

833
00:46:32,120 --> 00:46:35,600
Speaker 2: audio being recorded. So you've got this digital spy that's

834
00:46:35,680 --> 00:46:38,239
Speaker 2: running around your house. So I think it's a good

835
00:46:38,320 --> 00:46:42,120
Speaker 2: step in the right direction with this kind of cyber

836
00:46:42,200 --> 00:46:46,400
Speaker 2: security legislation that hopefully will go to Parliament. It's a

837
00:46:46,480 --> 00:46:49,160
Speaker 2: security bill they're talking about putting it through, and then

838
00:46:49,200 --> 00:46:52,319
Speaker 2: it puts the onus back on the companies to make

839
00:46:52,400 --> 00:46:55,840
Speaker 2: sure that the devices that we use, the smart things.

840
00:46:56,120 --> 00:46:58,480
Speaker 2: You know, we call it the Internet of things. So

841
00:46:58,600 --> 00:47:01,680
Speaker 2: a device that's Internet enable and can be right in

842
00:47:01,760 --> 00:47:05,080
Speaker 2: our digital ecosystem, it's referred to as the Internet of things.

843
00:47:05,600 --> 00:47:08,879
Speaker 2: And I think that more companies need to be put

844
00:47:08,960 --> 00:47:12,640
Speaker 2: under pressure to make sure these devices are secures. That's

845
00:47:12,640 --> 00:47:15,400
Speaker 2: a real problem. If you've ever installed a router in

846
00:47:15,440 --> 00:47:18,160
Speaker 2: your home, you know, when you connect the internet, generally

847
00:47:18,640 --> 00:47:23,000
Speaker 2: the standard username and password is either admin admin or

848
00:47:23,080 --> 00:47:27,360
Speaker 2: admin password or admin one two three four. You know

849
00:47:27,440 --> 00:47:33,560
Speaker 2: it's it's it's mind blowingly ridiculous that standard that comes out.

850
00:47:33,560 --> 00:47:35,640
Speaker 2: I mean, you should be forced when you install a

851
00:47:35,760 --> 00:47:38,279
Speaker 2: router or a modem, it should be found to create

852
00:47:38,360 --> 00:47:41,600
Speaker 2: a password and a username that's unique to you, not

853
00:47:41,760 --> 00:47:44,600
Speaker 2: the standard because it means that all these off the

854
00:47:44,680 --> 00:47:47,239
Speaker 2: shelf devices could be potentially hacked into.

855
00:47:48,200 --> 00:47:53,920
Speaker 1: Hey, David gillespian I did an episode on October eleven,

856
00:47:54,000 --> 00:47:58,000
Speaker 1: What's that six days ago? Episode sixteen seventy one called

857
00:47:58,280 --> 00:48:04,480
Speaker 1: is your car spying on you? And he wrote wanted

858
00:48:04,600 --> 00:48:06,480
Speaker 1: or not aware of it or not? If you have

859
00:48:06,560 --> 00:48:08,959
Speaker 1: a relatively late model car, there's a very high chance

860
00:48:09,000 --> 00:48:10,800
Speaker 1: that much of what you're doing when you're behind the

861
00:48:10,800 --> 00:48:14,840
Speaker 1: wheel is being recorded. Henry Ford would be horrified his

862
00:48:15,000 --> 00:48:18,359
Speaker 1: model T once a symbol of freedom, has morphed into

863
00:48:18,440 --> 00:48:22,920
Speaker 1: a rolling surveillance device tracking our every move and eavesdropping

864
00:48:23,000 --> 00:48:28,960
Speaker 1: on our conversations. Some cars Tesla for example, even turning

865
00:48:29,080 --> 00:48:34,640
Speaker 1: into rolling CCTV cameras capturing every move Grimace and nose Pick,

866
00:48:35,520 --> 00:48:40,719
Speaker 1: So there are Choice Magazine did like an expose on that.

867
00:48:41,320 --> 00:48:45,399
Speaker 1: They did and then Gillespo wrote about it. But yeah,

868
00:48:45,480 --> 00:48:49,080
Speaker 1: that's that. That's fucking terrifying, Like they're not just audio

869
00:48:49,280 --> 00:48:53,680
Speaker 1: recording but video recording you in your car and then

870
00:48:54,040 --> 00:48:57,520
Speaker 1: keeping that. And I said to him, what about But

871
00:48:57,680 --> 00:49:00,879
Speaker 1: surely they need approval or they need and it's like, yeah,

872
00:49:00,920 --> 00:49:03,520
Speaker 1: well when you buy whatever or you of course you

873
00:49:03,719 --> 00:49:08,120
Speaker 1: just go accept and he said, like trying to what

874
00:49:08,239 --> 00:49:11,360
Speaker 1: did he say? He said, trying to read and understand

875
00:49:11,840 --> 00:49:16,480
Speaker 1: what you're agreeing to is like trying to read a

876
00:49:16,560 --> 00:49:18,520
Speaker 1: ten thousand word document in Klingon.

877
00:49:20,040 --> 00:49:24,920
Speaker 2: You know, that's right. I know that in Europe, the

878
00:49:25,040 --> 00:49:29,200
Speaker 2: EU is trying to force companies to make their terms

879
00:49:29,280 --> 00:49:32,640
Speaker 2: of service and agreements to be a lot clearer, to

880
00:49:32,760 --> 00:49:35,120
Speaker 2: spell them out, to put more kind of you know,

881
00:49:35,239 --> 00:49:37,720
Speaker 2: to make the more succinct as to what they're storing

882
00:49:37,800 --> 00:49:39,920
Speaker 2: and what they're keeping from you. By the way, I

883
00:49:40,000 --> 00:49:43,880
Speaker 2: remember I found the article about that vacuum cleaner that

884
00:49:44,000 --> 00:49:47,239
Speaker 2: collects photos and audio to train AI. It's called the

885
00:49:47,400 --> 00:49:52,600
Speaker 2: d Bot dwbot robot vacuum and they're saying, and this

886
00:49:52,719 --> 00:49:55,360
Speaker 2: was an article on the ABC by the way, ABC Australia.

887
00:49:55,840 --> 00:49:59,880
Speaker 2: So they've been found to suffer from critical cybersecurity flaws

888
00:50:00,040 --> 00:50:04,200
Speaker 2: and they're collecting photos, videos and voice recordings has taken

889
00:50:04,360 --> 00:50:07,640
Speaker 2: inside customers' houses and what they're using that data for

890
00:50:07,840 --> 00:50:11,000
Speaker 2: is to train the company's AI model. So they're taking it.

891
00:50:11,280 --> 00:50:15,000
Speaker 2: This is a Chinese home robotics company and they sell

892
00:50:15,080 --> 00:50:17,680
Speaker 2: the debot, which is a lot of people illustrated him

893
00:50:17,680 --> 00:50:20,480
Speaker 2: may have one of these. I'm going to tell you

894
00:50:20,560 --> 00:50:22,279
Speaker 2: a story. A friend of mine just brought himself a

895
00:50:22,360 --> 00:50:25,160
Speaker 2: Chinese car. It's called the Tank. Have you heard of

896
00:50:25,239 --> 00:50:25,560
Speaker 2: the Tank?

897
00:50:26,239 --> 00:50:30,200
Speaker 1: Yeah? Yeah, it's made by GWM Havelet's there's a three

898
00:50:30,320 --> 00:50:32,680
Speaker 1: hundred and a five hundred, so he probably bought the

899
00:50:32,719 --> 00:50:33,240
Speaker 1: three hundred.

900
00:50:33,360 --> 00:50:36,520
Speaker 2: Coincidence two one of my friends bought the three hundred.

901
00:50:36,560 --> 00:50:38,759
Speaker 2: One bought the five hundred. But I had to laugh.

902
00:50:38,800 --> 00:50:40,239
Speaker 2: I got into his car the other day. He's only

903
00:50:40,280 --> 00:50:43,640
Speaker 2: had it for about two weeks, and there's a camera

904
00:50:43,760 --> 00:50:47,440
Speaker 2: that faces you to crack whether you fall asleep or

905
00:50:47,600 --> 00:50:50,160
Speaker 2: I mean, it's about effectively that's what it's supposed to do.

906
00:50:50,560 --> 00:50:53,359
Speaker 2: He's put a sticker over it because he does looking

907
00:50:53,400 --> 00:50:55,200
Speaker 2: at him. I don't know if I could be in

908
00:50:55,280 --> 00:50:58,600
Speaker 2: a car that's looking back at me constantly. That's his frame.

909
00:50:59,000 --> 00:50:59,920
Speaker 1: Mine's got the same thing.

910
00:51:00,600 --> 00:51:01,719
Speaker 2: Oh really yeah yeah.

911
00:51:01,880 --> 00:51:04,040
Speaker 1: If you blink for too long, it tells you to

912
00:51:04,200 --> 00:51:07,920
Speaker 1: pull over and have a rest. Yeah wow, I mean,

913
00:51:08,600 --> 00:51:12,920
Speaker 1: but just quickly jumping back to the vaxspying vacuum, think

914
00:51:13,000 --> 00:51:17,040
Speaker 1: about the fact that what a genius way to get

915
00:51:17,239 --> 00:51:22,680
Speaker 1: a mobile microphone and camera into your house where imagine

916
00:51:22,719 --> 00:51:26,480
Speaker 1: if you know, like it looked like a microphone and camera.

917
00:51:26,640 --> 00:51:30,120
Speaker 1: You wouldn't let it anywhere near your fucking property. But

918
00:51:30,280 --> 00:51:34,120
Speaker 1: because oh it's a vacuum, it's a vacuum that happens

919
00:51:34,200 --> 00:51:37,440
Speaker 1: to have a camera and a microphone. And you go

920
00:51:37,600 --> 00:51:39,360
Speaker 1: into room and all of a sudden, there it is

921
00:51:39,600 --> 00:51:43,200
Speaker 1: listening and filming, you know, And now I'm in the shower.

922
00:51:43,719 --> 00:51:47,160
Speaker 1: I'm not sure why it's in the bathroom, you know.

923
00:51:48,000 --> 00:51:54,600
Speaker 1: I'm like, that is potentially fucking terrifying. Well, not potentially,

924
00:51:54,719 --> 00:51:55,560
Speaker 1: it is terrifying.

925
00:51:55,760 --> 00:51:58,239
Speaker 2: Well, they also do a two D and sometimes even

926
00:51:58,280 --> 00:52:01,480
Speaker 2: a three D map of your house. And the concern

927
00:52:01,640 --> 00:52:04,920
Speaker 2: is this company may legitimately be collecting the data to

928
00:52:04,960 --> 00:52:08,200
Speaker 2: try to map their vacuum cleaners better, but what they

929
00:52:08,320 --> 00:52:11,320
Speaker 2: can't guarantee is that they're not going to be hacked.

930
00:52:11,360 --> 00:52:14,160
Speaker 2: Could you think about a crime syndicate hacking your vacuum

931
00:52:14,200 --> 00:52:17,400
Speaker 2: cleaner moving around knowing where you are, when you are,

932
00:52:17,560 --> 00:52:19,680
Speaker 2: when you're off to work, and where all the valuables

933
00:52:19,719 --> 00:52:20,319
Speaker 2: are in the house.

934
00:52:21,320 --> 00:52:23,600
Speaker 1: Well, it's funny you say this, and this is not

935
00:52:23,719 --> 00:52:25,560
Speaker 1: a very good way. You and I have been quite

936
00:52:26,200 --> 00:52:29,799
Speaker 1: you know, unprofessional today. But I'm just having a look

937
00:52:29,840 --> 00:52:44,040
Speaker 1: at vacuum, vacuum threatening. I read this thing person, excuse me, No,

938
00:52:44,520 --> 00:52:48,759
Speaker 1: I can't find it. But this this one of those

939
00:52:48,880 --> 00:52:52,759
Speaker 1: vacuums was basically somebody, I don't know what the word

940
00:52:52,880 --> 00:52:54,800
Speaker 1: is hijacked it. You know the word. I don't know

941
00:52:54,880 --> 00:52:58,480
Speaker 1: the word, but took and they have speakers in them,

942
00:52:59,120 --> 00:53:03,239
Speaker 1: and somebody was abusing. Somebody had had hacked it and

943
00:53:03,440 --> 00:53:07,719
Speaker 1: was abusing the homeowner was abusing that. So obviously not

944
00:53:07,840 --> 00:53:10,920
Speaker 1: the company was doing, but somebody had had that particular

945
00:53:11,120 --> 00:53:15,040
Speaker 1: let's call it what it is, robot, and yeah, they

946
00:53:15,520 --> 00:53:20,600
Speaker 1: they were just abusing this person who was in the home. Yeah.

947
00:53:22,239 --> 00:53:22,439
Speaker 4: Yeah.

948
00:53:23,200 --> 00:53:27,000
Speaker 2: It is a worrying thing that we allow technology into

949
00:53:27,080 --> 00:53:29,319
Speaker 2: our homes. And we talked in an episode not long

950
00:53:29,360 --> 00:53:34,320
Speaker 2: ago about how some apps owned by Facebook Meta and

951
00:53:35,040 --> 00:53:38,800
Speaker 2: they were tracking people in conversations. So once you have

952
00:53:39,000 --> 00:53:41,440
Speaker 2: the Facebook app on your phone, potentially they could be

953
00:53:41,480 --> 00:53:44,120
Speaker 2: listening into your conversation so they can serve up ads.

954
00:53:44,400 --> 00:53:48,200
Speaker 2: So there was an advertising agency that ran ads for

955
00:53:48,400 --> 00:53:50,960
Speaker 2: the likes of Meta, and what they were doing was

956
00:53:51,120 --> 00:53:56,080
Speaker 2: they were tracking conversations for keywords and then serving up ads.

957
00:53:56,480 --> 00:53:58,839
Speaker 2: They've been caught out, but they were serving up ads

958
00:53:58,920 --> 00:54:02,000
Speaker 2: related to the conversation. So we're talking about robot vacuum cleaner.

959
00:54:02,560 --> 00:54:05,040
Speaker 2: Potentially you could jump back on your phone and suddenly

960
00:54:05,080 --> 00:54:07,200
Speaker 2: an ad for a robot vacuum cleaner would appear.

961
00:54:08,640 --> 00:54:12,600
Speaker 1: Yeah, yep. I have that happen all the time, where

962
00:54:13,160 --> 00:54:16,040
Speaker 1: I'll be talking about something, my phone's not even near me,

963
00:54:16,200 --> 00:54:19,040
Speaker 1: and then I start getting ads. Hey, listen to this

964
00:54:22,000 --> 00:54:26,120
Speaker 1: South Korean woman's hair eaten by robot vacuum cleaner as

965
00:54:26,200 --> 00:54:30,360
Speaker 1: she slept. Oh my god, there's a photo. When a

966
00:54:30,440 --> 00:54:33,440
Speaker 1: South Korean woman invested in a robot vacuum cleaner, the

967
00:54:33,520 --> 00:54:36,359
Speaker 1: idea was to leave her trustworthy gadget to do its

968
00:54:36,440 --> 00:54:39,920
Speaker 1: work while she took a break from household chores. Instead,

969
00:54:39,960 --> 00:54:42,520
Speaker 1: the fifty two year old resident of chang Wan City

970
00:54:42,719 --> 00:54:45,400
Speaker 1: ended up being a victim of what many believe is

971
00:54:45,440 --> 00:54:49,920
Speaker 1: a peek into a dystopian future in which supposedly benign

972
00:54:50,040 --> 00:54:54,120
Speaker 1: robots against their human masters. The woman, whose name is

973
00:54:54,160 --> 00:54:59,000
Speaker 1: been with was taking a nap on the floor at

974
00:54:59,080 --> 00:55:02,080
Speaker 1: home when the vacuum cleaner locked onto her hair and

975
00:55:02,280 --> 00:55:06,320
Speaker 1: sucked it up, apparently mistaking it for dust. The agony

976
00:55:06,400 --> 00:55:09,279
Speaker 1: of having her hair entangled in the boughs of the

977
00:55:09,400 --> 00:55:12,800
Speaker 1: contraption raised her from a slumber, and then there's a

978
00:55:12,880 --> 00:55:19,440
Speaker 1: photo of what looks like ambos. Oh my god. Yeah, firefighters,

979
00:55:19,440 --> 00:55:22,480
Speaker 1: so you found it trying to rescue the woman. Yeah,

980
00:55:22,760 --> 00:55:23,480
Speaker 1: that's going to hurt.

981
00:55:23,640 --> 00:55:25,560
Speaker 2: Can I just say, I'm going to take the side

982
00:55:25,600 --> 00:55:27,040
Speaker 2: of the vacuum cleaner on this one.

983
00:55:28,040 --> 00:55:30,399
Speaker 1: Well, that's because you've got no fucking hair, so you're

984
00:55:30,480 --> 00:55:32,240
Speaker 1: not You're number anybody.

985
00:55:32,840 --> 00:55:36,240
Speaker 2: Can I just say if you have a robot vacuum

986
00:55:36,280 --> 00:55:39,840
Speaker 2: cleaner in your home and you lay down on the

987
00:55:40,000 --> 00:55:43,960
Speaker 2: ground with your hair spread out on the floor, which

988
00:55:44,040 --> 00:55:47,360
Speaker 2: is pretty gross as it happens, and the innocent robot

989
00:55:47,480 --> 00:55:50,680
Speaker 2: vacuum cleaner happens to be doing their job and they

990
00:55:50,920 --> 00:55:53,360
Speaker 2: find some dirt on the ground that happens to be

991
00:55:53,520 --> 00:55:56,600
Speaker 2: someone's hair, it will vacuum it up. It didn't know

992
00:55:56,680 --> 00:55:57,960
Speaker 2: it was attached to a human.

993
00:55:59,239 --> 00:56:01,400
Speaker 1: Well, that's an that therein lies the problem.

994
00:56:02,960 --> 00:56:06,280
Speaker 2: When you first told that story, I envisaged the vacuum

995
00:56:06,280 --> 00:56:09,399
Speaker 2: cleaner jumping onto the bed and attacking her because that's

996
00:56:09,400 --> 00:56:11,720
Speaker 2: what you made it sound like. And then the actual

997
00:56:11,840 --> 00:56:15,520
Speaker 2: story was that she was naively laying on the floor

998
00:56:15,600 --> 00:56:18,840
Speaker 2: while the vacuum cleaner was innocently doing its job. It

999
00:56:18,960 --> 00:56:21,600
Speaker 2: doesn't it has to work times.

1000
00:56:21,400 --> 00:56:24,120
Speaker 1: Have I told you off air, don't let the facts

1001
00:56:24,160 --> 00:56:26,239
Speaker 1: get in the way of a fucking good story. So you,

1002
00:56:28,200 --> 00:56:33,399
Speaker 1: you and your bloody reality check can fuck off, mate.

1003
00:56:33,480 --> 00:56:35,560
Speaker 1: How can people connect with you and find you and

1004
00:56:35,680 --> 00:56:36,879
Speaker 1: follow you? Where are you at?

1005
00:56:37,680 --> 00:56:41,040
Speaker 2: Well? They can go to websites now, dot com, dot

1006
00:56:41,200 --> 00:56:45,080
Speaker 2: au and as it suggests, we actually build websites when

1007
00:56:45,120 --> 00:56:49,000
Speaker 2: I'm not on podcast talking crap, but we do all

1008
00:56:49,040 --> 00:56:51,040
Speaker 2: sorts of marketing and stuff like that. So go to

1009
00:56:51,440 --> 00:56:52,920
Speaker 2: if you want to ask questions, if you want us

1010
00:56:52,920 --> 00:56:55,120
Speaker 2: to talk about something in particular, So just go to

1011
00:56:55,200 --> 00:56:58,000
Speaker 2: websites now, dot com today you They can then jump

1012
00:56:58,040 --> 00:57:02,240
Speaker 2: online and send us sends a note, email me, contact

1013
00:57:02,280 --> 00:57:03,120
Speaker 2: me and I'll happily.

1014
00:57:03,360 --> 00:57:04,719
Speaker 1: Can I tell you if you do want to get

1015
00:57:04,760 --> 00:57:06,800
Speaker 1: a web and this is not a paid endorsement, but

1016
00:57:06,840 --> 00:57:08,680
Speaker 1: if you do want to get a website built, for

1017
00:57:08,800 --> 00:57:11,200
Speaker 1: God's sake, go to Patrick. Because one, there's a whole

1018
00:57:11,239 --> 00:57:14,960
Speaker 1: lot of fucking people who overcharge and under deliver, Like really,

1019
00:57:15,000 --> 00:57:18,960
Speaker 1: I've experienced it, He's not one. And there's a lot

1020
00:57:19,000 --> 00:57:20,880
Speaker 1: of people who try and keep you on the hook

1021
00:57:21,080 --> 00:57:24,800
Speaker 1: forever with a range of things you don't need, so

1022
00:57:25,000 --> 00:57:27,320
Speaker 1: save yourself a bit of time and energy and just

1023
00:57:27,680 --> 00:57:29,120
Speaker 1: start with someone who's good at it.

1024
00:57:29,440 --> 00:57:31,160
Speaker 2: Well, thanks, mate, that's really nice of you to say.

1025
00:57:31,440 --> 00:57:33,160
Speaker 2: Looking at what I love about what we do with

1026
00:57:33,240 --> 00:57:35,680
Speaker 2: our clients is we have such a diversity, and I

1027
00:57:35,800 --> 00:57:38,600
Speaker 2: love getting to know people and their businesses. I never

1028
00:57:38,720 --> 00:57:42,640
Speaker 2: knew that I would know anything about delivering a baby,

1029
00:57:43,320 --> 00:57:46,960
Speaker 2: but I do. Wow, that's because one of our clients

1030
00:57:47,200 --> 00:57:50,760
Speaker 2: does the most amazing obstetrics and gynological training models in

1031
00:57:51,040 --> 00:57:53,520
Speaker 2: the world. And they may just rand the corner from you,

1032
00:57:53,600 --> 00:57:55,200
Speaker 2: actually just down the road from your house.

1033
00:57:55,680 --> 00:57:56,680
Speaker 1: Well, the babies or.

1034
00:57:56,680 --> 00:57:59,800
Speaker 2: The everything, well, I guess they're happening all around you.

1035
00:58:00,040 --> 00:58:04,800
Speaker 1: It makes everybody everywhere appreciate you, mate, Thank you.

1036
00:58:05,280 --> 00:58:06,120
Speaker 2: Jeez. I