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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 3: Well are you just? Are you free balling or what

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Speaker 3: are you doing? I really don't, I really don't. But

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Speaker 3: 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 the low the belt. Literally, it certainly doesn't

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Speaker 2: if 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.

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Speaker 3: 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 4: And I can imagine on a moving Oh it's not

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Speaker 4: 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.

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Speaker 1: Braces, Craig, Yes, yes, I can imagine the problem with

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Speaker 1: braces is they're not practical in an emergency situation.

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Speaker 2: No, no, yeah, but he's the dar. He's really been

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Speaker 2: trying hard enough, kind of said to him, Look, when

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Speaker 2: you're living at my place, maybe we can get you

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Speaker 2: to sit down when you go to the toilet. Oh no, no, no,

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

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Speaker 2: but 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 3: I'm with Dad. Don't you dare? After? How old is

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Speaker 3: he fifty?

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Speaker 2: He's fifty two.

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Speaker 3: After fifty two years of standing, let him fucking stand.

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Speaker 3: Don't try and reinvent the wheel just because you're worried

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Speaker 3: about a bit of we on your floor.

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Speaker 2: It's not.

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Speaker 3: Okay, the walls, the floor, it's not just about you

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Speaker 3: 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's meditative, that that kind

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Speaker 2: of and and I love sleeping on the train as well,

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Speaker 2: you know, so if you if you can get a

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

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Speaker 2: down bed and had a little toy and all that

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Speaker 2: sort of stuff. And it was just great. If you

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

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Speaker 2: quite expensive. But I just kind of jumped online and

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

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Speaker 3: 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? Like, what's his kind of functional?

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Speaker 3: IQ? Kind? Not IQ? But you know he's age five

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Speaker 3: or six? Yeah? Okay, So I have a cute story.

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Speaker 1: So last night I did a gig for the eighty

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Speaker 1: nine point nine Light FM, Melbourne's Positive alternative. They were

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Speaker 1: running two big, two big mental health events. One one

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Speaker 1: last night. Hundreds I don't know, five or six hundred

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Speaker 1: people won the night before, six or seven hundred. I

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Speaker 1: spoke at both events. Anyway, last night, Oh my goodness,

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

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

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Speaker 1: at five. So I was driving there thinking, I don't

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Speaker 1: know how I'm going to do this. I'm probably going

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Speaker 1: to be rubbish. Fortunately, when I got to to the place,

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Speaker 1: they had a cafe in the boyer and I got

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

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Speaker 1: to perk up. Anyway, two people spoke before me doctor

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Speaker 1: Jody Richardson and doctor Ken I forget his surname, but brilliant. Anyway,

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Speaker 1: I'm on last, and I get up and I start

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Speaker 1: tom gunn Okay, I'm riffing, you know, like I'm a bit.

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Speaker 3: The other two are very very professional and slide show

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Speaker 3: and very grown up, and you know, I'm like.

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Speaker 1: The dog with three dicks up there in the flannel

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Speaker 1: shirt and the jeans and like different, not better or

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Speaker 1: not worse, just different energy and different vibe and having fun.

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Speaker 1: And then I'm about three minutes in and this young

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Speaker 1: lady who I don't know how old she is, but

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

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Speaker 1: be totally wrong on that, just starts laughing hysterically at

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Speaker 1: my not particularly funny.

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Speaker 3: Joke, like really loud. And then and then you're like, yeah,

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Speaker 3: and clearly a young girl with a disability sitting next

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Speaker 3: 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 3: Oh my god.

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Speaker 1: And so I was up there with like six hundred

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Speaker 1: or five hundred people and Mel screaming in the front,

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Speaker 1: and she was just awesome. She was such a good

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Speaker 1: kid and such good energy, and it could have potentially

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Speaker 1: derailed everything, but it actually made it better. And I

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Speaker 1: finished and her mom came up with her and we

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

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Speaker 1: thank you.

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Speaker 3: So I'm like, she is. I genuinely mean, she's fantastic.

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Speaker 2: You know.

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Speaker 3: It's like when imagine not caring that much, in fact,

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Speaker 3: not even knowing that not that she should be embarrassed

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Speaker 3: or not that she should be awkward, but just not

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Speaker 3: that's not even a thought. So free and so liberated

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Speaker 3: and she had the best time.

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Speaker 1: I had the best time, and the audience loved it

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Speaker 1: as well. You know, it could have been a clunky experience,

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Speaker 1: but it just turned out great.

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Speaker 3: 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

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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 3: Yeah, that one hundredsent agree. And also.

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Speaker 1: That's very smart of you, Like, that's very naturally socially

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Speaker 1: and emotionally intelligent of you, Like trying to understand the

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Speaker 1: world through someone else's perception or through someone else's window experiences.

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

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Speaker 1: see in inverted commas what he sees in inverted commas,

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

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

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

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Speaker 1: world or sees the situation or see the conversation. In

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Speaker 1: other words, trying to put yourself in their psychological and

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Speaker 1: or emotional experience, and that a lot of people are

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Speaker 1: terrible at that, and a lot of people don't think

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Speaker 1: about that. So, you know, realizing what you're doing in

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Speaker 1: real time is that you and him might be in

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Speaker 1: the same conversation but clearly not the same experience, or

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Speaker 1: you might be in the same situation or circumstance or environment,

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Speaker 1: but just understanding that, you know, the way that you

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

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

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Speaker 1: to somebody who who has vision. But that's yeah, that's

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

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Speaker 3: So 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 therest out 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 3: 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 3: Well, I mean, that's a good question, but I guess

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Speaker 3: 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 3: Yeah, I mean, I agree with you.

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

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Speaker 1: growing up around or being around or having friends with disabilities.

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Speaker 1: And you know, as you know, I've been working with

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Speaker 1: Johnny in the gym for the last six years, who's

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

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Speaker 1: a wheelchair and then eventually to a frame and now

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Speaker 1: he's walking with a stick. But you know, it's an

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Speaker 1: undertaking for him to walk twenty feet, you know, And

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Speaker 1: so I mean he can, but it just it takes

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Speaker 1: him ten times longer than it would take you to

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Speaker 1: walk twenty feet, and so I'm often walking around the.

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Speaker 3: Gym with him and I'm helping him, and I'm.

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Speaker 1: Either holding his hand or holding his arm or kind

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Speaker 1: of lifting him half lifting him up and down off

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Speaker 1: a bench. And I don't even think about it when

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Speaker 1: I'm not saying a great bloke. I'm saying, it's just

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Speaker 1: a byproduct of being around someone. And sometimes I'll be

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Speaker 1: through the gym where I'm helping him from one bench

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Speaker 1: to another exercise, and here's these two you know, old blokes,

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Speaker 1: and one of them's holding the other bloke's hand, and

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Speaker 1: I don't even I'm not aware of it until I

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Speaker 1: see a seventeen year old staring at me, like what

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Speaker 1: the fuck are they doing? You know, it's like, no,

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Speaker 1: well it's okay, mate, you know, and it's like and

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Speaker 1: there's no, it's just not a typical thing. But then

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Speaker 1: you don't because it's so automatic now because I've trained

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Speaker 1: him probably thousands of times, where it's just you know, like,

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Speaker 1: you know, I'm constantly and the crab is the same.

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Speaker 1: Mark's amazing as well, my training partner and everyone. It's

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Speaker 1: like you're just naturally doing these things without drawing attention

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Speaker 1: to it or without overthinking it. But I definitely think

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Speaker 1: you know, and it's beautiful the relationship you've got with

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Speaker 1: your brother mate, and it's and your friend who's you know,

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Speaker 1: doesn't have sight. I think for us as humans, it's

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Speaker 1: I'm very at the risk of sounding naf and lame,

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Speaker 1: and you know, I don't know trite. I'm very grateful

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Speaker 1: for all of the interactions I have with people whose

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Speaker 1: life and situation is tougher than mine, because I think

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Speaker 1: I could be a pain in the ass unless I

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Speaker 1: had that gratitude and that awareness that I'm very, very

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Speaker 1: lucky and very privileged to have what I have. And

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Speaker 1: I don't just mean things, I mean physically, mentally and emotionally,

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

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

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Speaker 1: and 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 it

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Speaker 1: pretty good.

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

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Speaker 5: 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 3: All Right, I'm ready.

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Speaker 1: Let's let's let's get out of human behavior and into technology.

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Speaker 1: I've got no notes in front of me, so you

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

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Speaker 3: 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 3: 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 3: Is it a megawatch shit tone?

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Speaker 2: Yeah? Well probably Gigawa shit tone?

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Speaker 3: How many?

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Speaker 1: How many killer wat's per megawatch ship tone? I don't know,

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Speaker 1: just I'm just trying to get the metrics right.

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Speaker 3: I'm just taking professor. Now, can I just ask a question.

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Speaker 1: When you said they've ordered seven nuclear reactors, I don't

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Speaker 1: exactly know what that means. What do you mean they're

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Speaker 1: buying their own fucking dedicated nuclear energy?

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Speaker 3: Yeah?

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Speaker 2: I know, but what is that?

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Speaker 3: 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 3: I don't know what the fuck it's what. I'm not physics.

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Speaker 3: 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 3: Hell, by the way, everyone, do not listen to us

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Speaker 3: to I'm the biggest dickhead, but maybe don't listen to

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Speaker 3: 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 3: That's okay, that's all right. So there, so you're doing it,

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Speaker 3: are you?

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Speaker 2: Yeah?

393
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Speaker 3: All right, here we go explain. You just go into

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Speaker 3: chatters chat GPT and say, simply explain.

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Speaker 2: Comes from nuclear fission. Nuclear power reactors use heat produced

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

397
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Speaker 2: is routed through the reactor steam system to spin a

398
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Speaker 2: large turbine blade drives mechnetic generators to produce electricity.

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Speaker 3: Exactly what I just said. The fucking nothing like what

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Speaker 3: I did. Come on, come on, all right, So all right,

401
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Speaker 3: the bottom line is Google are going nuclear.

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

403
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Speaker 1: all things tech, there's also an exponential expanse of requirement

404
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Speaker 1: for 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,

406
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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

410
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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.

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Speaker 3: Fucking slightly. But to me it would seem that move

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Speaker 3: I mean an obvious statement.

435
00:24:02,480 --> 00:24:07,359
Speaker 1: But you know, energy moving forward is just not just

436
00:24:07,640 --> 00:24:12,399
Speaker 1: energy for electricity and day to day operation, but energy

437
00:24:12,520 --> 00:24:15,879
Speaker 1: for humans in terms of the quality of energy, calories, food,

438
00:24:16,400 --> 00:24:17,960
Speaker 1: micro and macro nutrients.

439
00:24:18,040 --> 00:24:21,480
Speaker 3: So energy to make you know, computers and.

440
00:24:21,600 --> 00:24:26,200
Speaker 1: Cars and organizations work, but also energy to make humans work.

441
00:24:26,280 --> 00:24:29,399
Speaker 1: I think there's a kind of a dual kind of

442
00:24:30,240 --> 00:24:32,760
Speaker 1: energetic issue that's looming.

443
00:24:32,960 --> 00:24:34,080
Speaker 3: Well, it's already here.

444
00:24:34,160 --> 00:24:37,040
Speaker 2: I guess you know how my brain works, which is

445
00:24:37,080 --> 00:24:40,240
Speaker 2: a bit confusing for anybody listening to our podcast, but

446
00:24:40,240 --> 00:24:42,040
Speaker 2: a litt alone for me who has to cope with

447
00:24:42,080 --> 00:24:44,399
Speaker 2: it on a day to day basis. But yes, to

448
00:24:44,520 --> 00:24:47,480
Speaker 2: go through my mind sometimes. When I was hiking this morning,

449
00:24:47,520 --> 00:24:50,200
Speaker 2: I went to a place called Bosstoc Reservoir, so I

450
00:24:50,320 --> 00:24:54,160
Speaker 2: probably not very far, maybe went about five kilometers this morning.

451
00:24:54,480 --> 00:24:57,440
Speaker 2: Out in the bush, Fritz saw a wallaby and chase

452
00:24:57,520 --> 00:25:00,600
Speaker 2: the wallaby, but he didn't get close to because there's

453
00:25:00,600 --> 00:25:02,800
Speaker 2: no way a miniature now is going to catch a wallaby,

454
00:25:02,840 --> 00:25:04,280
Speaker 2: and he wouldn't want to do anyway, but.

455
00:25:04,600 --> 00:25:06,479
Speaker 3: If he did, the wallaby would kick the fuck out

456
00:25:06,520 --> 00:25:06,760
Speaker 3: of him.

457
00:25:06,800 --> 00:25:09,520
Speaker 2: But okay, yeah, but you know what fascinates me about

458
00:25:09,520 --> 00:25:13,560
Speaker 2: You were talking about the biomechanics, and I'm pretty good

459
00:25:13,640 --> 00:25:16,640
Speaker 2: with my feeding of Fritz. He gets usually a half

460
00:25:16,680 --> 00:25:18,880
Speaker 2: a cup of food or a cup of dry food

461
00:25:18,960 --> 00:25:21,160
Speaker 2: and then something else, so I supplement it with bits

462
00:25:21,200 --> 00:25:23,639
Speaker 2: and pieces and a few vegetables and things. But what

463
00:25:23,800 --> 00:25:26,040
Speaker 2: blows my mind is he gets fed once a day

464
00:25:26,080 --> 00:25:28,600
Speaker 2: and maybe gets a treat after the walk. How the

465
00:25:28,760 --> 00:25:31,480
Speaker 2: hell is he able to run in the bush? Probably

466
00:25:31,640 --> 00:25:34,200
Speaker 2: four or five times the distance that I do. He

467
00:25:34,320 --> 00:25:36,359
Speaker 2: does all the things that he does. He's so active.

468
00:25:36,400 --> 00:25:39,720
Speaker 2: We do the zuomies, we throw toys. The fact that

469
00:25:39,880 --> 00:25:44,040
Speaker 2: that machine, that biological machine, can do so much with

470
00:25:44,760 --> 00:25:48,639
Speaker 2: main feed a day blows my mind.

471
00:25:49,680 --> 00:25:55,399
Speaker 3: Well, they're very metabolically efficient. But also, I mean, you

472
00:25:55,680 --> 00:26:01,560
Speaker 3: weigh probably twenty to thirty times what he weighs. Yeah, right,

473
00:26:01,760 --> 00:26:04,200
Speaker 3: so you think, what does he way? Five ks?

474
00:26:05,000 --> 00:26:07,480
Speaker 2: No, he's about eight eight and a half.

475
00:26:08,240 --> 00:26:12,880
Speaker 1: Okay, and what are you about? Sixty five sixty eight? Yeah,

476
00:26:13,040 --> 00:26:16,240
Speaker 1: so you're about six and a half times his weight. Yeah,

477
00:26:16,440 --> 00:26:19,159
Speaker 1: so you put if you figured out his calories and

478
00:26:19,320 --> 00:26:22,520
Speaker 1: times by six and a half, it's probably about the same.

479
00:26:22,880 --> 00:26:25,680
Speaker 3: But you don't do zoomies and you don't chase wallabies.

480
00:26:26,359 --> 00:26:27,760
Speaker 3: So you do make a good point.

481
00:26:28,080 --> 00:26:31,480
Speaker 1: But I mean, the beauty of dogs is I mean, well,

482
00:26:31,520 --> 00:26:33,440
Speaker 1: I was going to say dogs don't eat junk food,

483
00:26:33,480 --> 00:26:36,160
Speaker 1: but that's not true depending on the owner. By the way,

484
00:26:36,359 --> 00:26:39,320
Speaker 1: owners who feed their dogs junk fuck. It makes me mad,

485
00:26:40,160 --> 00:26:42,720
Speaker 1: Like when you see dogs that are just morbidly obese

486
00:26:42,800 --> 00:26:47,240
Speaker 1: because their owners literally make them fat by fucking makes

487
00:26:47,280 --> 00:26:49,720
Speaker 1: me mad because you don't see that you don't see

488
00:26:49,760 --> 00:26:52,320
Speaker 1: that with any other animals except animals who are genetically

489
00:26:52,440 --> 00:26:54,000
Speaker 1: required to be fat for survival.

490
00:26:54,080 --> 00:26:56,840
Speaker 3: But anyway, no, he doesn't need that much food. That's

491
00:26:56,880 --> 00:27:02,160
Speaker 3: the point. But also I feel like dogs miss out

492
00:27:02,240 --> 00:27:05,639
Speaker 3: because you know how we get so much pleasure from food.

493
00:27:06,640 --> 00:27:09,400
Speaker 2: Yeah, but you know what, they get so much pleasure

494
00:27:09,520 --> 00:27:15,080
Speaker 2: from being off lead, running around, exploring, sniffing. They smell everything.

495
00:27:15,119 --> 00:27:18,280
Speaker 2: It's like social media. They love it. They pee on things,

496
00:27:18,320 --> 00:27:21,399
Speaker 2: they smell other dogs pee, They sniff bums. They do

497
00:27:21,560 --> 00:27:22,240
Speaker 2: so many fun.

498
00:27:22,160 --> 00:27:25,480
Speaker 3: Things, letting them go different ways. So hang on, tiff,

499
00:27:25,520 --> 00:27:27,879
Speaker 3: can you make that a real please? They sniff bums.

500
00:27:27,920 --> 00:27:31,080
Speaker 3: They do so many fun things. Let's just capture that,

501
00:27:31,320 --> 00:27:35,280
Speaker 3: will we They sniff bums, They do so many fun things.

502
00:27:36,119 --> 00:27:39,200
Speaker 3: They smell pee. The fuck is wrong with you? What

503
00:27:39,320 --> 00:27:42,320
Speaker 3: makes you think any of that compares to a pizza

504
00:27:42,960 --> 00:27:44,080
Speaker 3: or fucking cheesecake?

505
00:27:44,600 --> 00:27:48,280
Speaker 1: Like, oh, yeah, sure, sure, they're diets boring, but they

506
00:27:48,400 --> 00:27:51,240
Speaker 1: get to sniff asses and we oh wow, that fuck

507
00:27:51,280 --> 00:27:51,879
Speaker 1: you sold me.

508
00:27:52,520 --> 00:27:57,720
Speaker 3: I'm changing. I'm going to become a greyhound. Oh, I am.

509
00:27:58,119 --> 00:28:00,760
Speaker 2: Putting myself in the realm of the dog because I'm

510
00:28:00,800 --> 00:28:02,600
Speaker 2: trying to look at it from a dog's perspective?

511
00:28:02,720 --> 00:28:05,640
Speaker 1: Are you using theory of mind with canine's Canine theory

512
00:28:05,720 --> 00:28:09,360
Speaker 1: of mind with Patrick? Welcome back to today's episode Through

513
00:28:09,440 --> 00:28:13,120
Speaker 1: the Eyes of a Dog. I'm Patricks.

514
00:28:14,720 --> 00:28:17,879
Speaker 2: Someone told me that today that dogs aren't self aware.

515
00:28:19,359 --> 00:28:20,239
Speaker 2: So elephants are.

516
00:28:21,119 --> 00:28:21,239
Speaker 5: Are?

517
00:28:21,320 --> 00:28:23,600
Speaker 2: Some animals are. But if a dog looks at a mirror,

518
00:28:23,680 --> 00:28:26,240
Speaker 2: it doesn't see itself, it just sees another dog.

519
00:28:26,800 --> 00:28:27,280
Speaker 5: Is that's true?

520
00:28:29,040 --> 00:28:31,479
Speaker 3: It's I think dogs are.

521
00:28:31,800 --> 00:28:34,200
Speaker 1: That is a very good question, and if I'm being

522
00:28:34,520 --> 00:28:37,000
Speaker 1: totally honest, I don't know the answer. But that makes

523
00:28:37,080 --> 00:28:39,920
Speaker 1: sense to me. But I think that they look at

524
00:28:40,000 --> 00:28:43,520
Speaker 1: you googling. I think that they are definitely aware of

525
00:28:43,840 --> 00:28:48,640
Speaker 1: other people's needs and emotions, and I think they are

526
00:28:49,080 --> 00:28:52,520
Speaker 1: especially with dogs that are very very bonded with their

527
00:28:52,680 --> 00:28:54,800
Speaker 1: human I was going to say owner.

528
00:28:54,920 --> 00:28:56,120
Speaker 3: I hate the word owner.

529
00:28:56,400 --> 00:28:58,040
Speaker 2: I don't use it. I don't use the word owner.

530
00:28:58,400 --> 00:29:01,760
Speaker 1: I think they're human, they're person and yep, their dad,

531
00:29:01,880 --> 00:29:06,280
Speaker 1: their mum, there, whatever. I think they are very attuned

532
00:29:06,480 --> 00:29:12,400
Speaker 1: to the needs and emotions and even mental states of

533
00:29:13,280 --> 00:29:18,440
Speaker 1: they're human. But self awareness is a slippery slope in general.

534
00:29:18,480 --> 00:29:20,040
Speaker 1: But it doesn't surprise me that.

535
00:29:20,880 --> 00:29:23,440
Speaker 2: But then, how do you know, well, like looked at

536
00:29:23,480 --> 00:29:27,600
Speaker 2: two articles, one from the Smithsonian magazine that says dogs

537
00:29:27,760 --> 00:29:31,040
Speaker 2: may be more self aware than experts thought, and then

538
00:29:31,080 --> 00:29:35,240
Speaker 2: the second one is from an article on the website

539
00:29:35,360 --> 00:29:38,720
Speaker 2: earth dot com, and it says that although dogs can't

540
00:29:38,920 --> 00:29:42,520
Speaker 2: identify themselves in the mirror, they still have some levels

541
00:29:42,560 --> 00:29:46,080
Speaker 2: of self awareness. They ace other self recognition tests, they

542
00:29:46,120 --> 00:29:49,440
Speaker 2: can recognize their own odor, and they can recall memories

543
00:29:49,480 --> 00:29:51,680
Speaker 2: of specific events. So there you go.

544
00:29:52,280 --> 00:29:54,560
Speaker 3: Should we ask Chap GPT go for it?

545
00:29:55,160 --> 00:29:55,400
Speaker 1: All? Right?

546
00:29:55,640 --> 00:29:55,680
Speaker 3: On?

547
00:29:56,120 --> 00:29:56,320
Speaker 2: Yep?

548
00:29:57,040 --> 00:29:59,840
Speaker 3: On are dogs self aware?

549
00:30:01,960 --> 00:30:04,720
Speaker 5: Dogs have a level of self awareness, but it's not

550
00:30:04,840 --> 00:30:08,000
Speaker 5: quite like human self awareness. They show signs of understanding

551
00:30:08,000 --> 00:30:10,800
Speaker 5: their own bodies and movements, and they can recognize their

552
00:30:10,840 --> 00:30:14,680
Speaker 5: own scent. However, in tests like the mirror test, which

553
00:30:14,760 --> 00:30:19,760
Speaker 5: measures self recognition, dogs generally don't recognize themselves. They might

554
00:30:19,800 --> 00:30:22,760
Speaker 5: see their reflection as another dog or just ignore it.

555
00:30:23,280 --> 00:30:26,280
Speaker 5: So while they have some degree of self awareness, it's

556
00:30:26,360 --> 00:30:28,080
Speaker 5: more limited compared to humans.

557
00:30:29,960 --> 00:30:33,240
Speaker 1: Thanks shatters here you get well, yeah, I think also,

558
00:30:33,560 --> 00:30:35,640
Speaker 1: And also you got to remember, even with chat JPT,

559
00:30:35,840 --> 00:30:38,680
Speaker 1: they're just drawing on whatever's on the Internet that they

560
00:30:38,800 --> 00:30:39,680
Speaker 1: access at the time.

561
00:30:39,760 --> 00:30:42,800
Speaker 3: Too. But interesting, all right, what else you got for

562
00:30:42,920 --> 00:30:43,480
Speaker 3: us tech boy.

563
00:30:43,920 --> 00:30:46,760
Speaker 2: While we're talking about AI and we know it's a

564
00:30:46,880 --> 00:30:50,160
Speaker 2: billion dollar industry. Now here's an article that I read

565
00:30:50,280 --> 00:30:53,760
Speaker 2: recently that actually frightened me a little bit in terms

566
00:30:53,880 --> 00:30:57,240
Speaker 2: of what it means in the implications. So this article

567
00:30:57,400 --> 00:31:02,680
Speaker 2: was in published on the Conversation and it's stated that

568
00:31:03,240 --> 00:31:08,920
Speaker 2: that AI is being underpinned by an exploited workforce. So

569
00:31:09,040 --> 00:31:11,760
Speaker 2: what does that actually mean? There are you know, we

570
00:31:11,880 --> 00:31:16,760
Speaker 2: think about people working putting garments together and working in sweatshops.

571
00:31:18,040 --> 00:31:21,320
Speaker 2: There's one part of AI we don't think about, and

572
00:31:21,400 --> 00:31:27,160
Speaker 2: it's data labeling. So data comes in and the human

573
00:31:27,240 --> 00:31:31,480
Speaker 2: operator has to label that data to explain what it is.

574
00:31:31,840 --> 00:31:35,400
Speaker 2: So if it's a picture of Craig, it's said handsome,

575
00:31:35,520 --> 00:31:39,160
Speaker 2: middle aged man, big guns. You know, it's got to

576
00:31:39,200 --> 00:31:42,640
Speaker 2: come up with something, right. But the interesting thing is that,

577
00:31:43,720 --> 00:31:48,120
Speaker 2: you know, with the AI industry expected to be worth

578
00:31:48,160 --> 00:31:51,160
Speaker 2: about four hundred and seven billion US dollars by twenty

579
00:31:51,240 --> 00:31:55,000
Speaker 2: twenty seven, right, that's not a long way away. The

580
00:31:55,120 --> 00:31:59,520
Speaker 2: problem is that there's up to one hundred data labelers

581
00:31:59,760 --> 00:32:02,840
Speaker 2: for each AI and all these AI workers are in

582
00:32:02,920 --> 00:32:06,720
Speaker 2: places like Kenya and they work for these companies like Facebook,

583
00:32:06,800 --> 00:32:10,160
Speaker 2: Scale AI, Open AI, all that sort of stuff, and

584
00:32:11,120 --> 00:32:15,480
Speaker 2: the thing is that they're on really crap conditions and wages.

585
00:32:15,720 --> 00:32:18,480
Speaker 2: So data abeling, So this is the basically you take

586
00:32:18,520 --> 00:32:22,800
Speaker 2: the raw data, images, video, text, and then you say

587
00:32:22,880 --> 00:32:25,440
Speaker 2: to AI, this is what you are seeing, this is

588
00:32:25,520 --> 00:32:27,920
Speaker 2: what you are hearing, so that AI can understand what

589
00:32:28,040 --> 00:32:34,440
Speaker 2: it is and whether it's self driving cars, smart devices, chat, GPT,

590
00:32:34,680 --> 00:32:37,880
Speaker 2: all that stuff has to be labeled because AI thrives

591
00:32:38,080 --> 00:32:41,560
Speaker 2: on data and these data models that they have to

592
00:32:41,760 --> 00:32:45,680
Speaker 2: keep updating. So for AI to continue to be as

593
00:32:45,720 --> 00:32:48,000
Speaker 2: smart as it is, you've got to keep updating it.

594
00:32:48,200 --> 00:32:51,880
Speaker 2: So these data sets need to be updated and refreshed regularly.

595
00:32:51,960 --> 00:32:57,600
Speaker 2: They cannot work without them. So tech giants so Meta, Google, OpenAI, Microsoft,

596
00:32:57,920 --> 00:33:04,080
Speaker 2: They outsource all of this stuff to the Filmilippines, Kenya, India, Pakistan, Venezuela, Colombia,

597
00:33:04,440 --> 00:33:06,920
Speaker 2: and now China of course is jumping on the bandwagon

598
00:33:07,120 --> 00:33:11,120
Speaker 2: as well. So this has become an ethical thing that

599
00:33:11,640 --> 00:33:13,880
Speaker 2: I guess we in the Western world, sitting on the

600
00:33:13,920 --> 00:33:17,160
Speaker 2: other end of a phone or a computer or a tablet,

601
00:33:17,880 --> 00:33:22,720
Speaker 2: just don't think about the implications. And look, there's moves.

602
00:33:23,360 --> 00:33:26,080
Speaker 2: I think Joe Biden was looking at some sort of

603
00:33:26,160 --> 00:33:29,120
Speaker 2: international agreement. But the reality of it is, I don't

604
00:33:29,160 --> 00:33:31,200
Speaker 2: know what we can do. I mean, we're getting we're

605
00:33:31,320 --> 00:33:34,080
Speaker 2: using it as we speak, you know, we've just within

606
00:33:34,160 --> 00:33:36,960
Speaker 2: the last ten minutes. So well, it's good to be

607
00:33:37,000 --> 00:33:37,480
Speaker 2: aware of it.

608
00:33:38,280 --> 00:33:42,280
Speaker 1: Yeah, but also you I mean, wow, I find that

609
00:33:42,720 --> 00:33:46,480
Speaker 1: not hard to believe, but I find that curious that

610
00:33:47,760 --> 00:33:52,120
Speaker 1: you know, on some level, there's people sitting in some

611
00:33:52,440 --> 00:33:56,520
Speaker 1: third world country, potentially third world country, looking at images

612
00:33:57,040 --> 00:34:00,680
Speaker 1: and describing that image, and that's part of the very

613
00:34:00,920 --> 00:34:03,960
Speaker 1: very very high tech evolved.

614
00:34:04,360 --> 00:34:07,680
Speaker 3: You know system that we're in the middle. How is

615
00:34:07,800 --> 00:34:09,560
Speaker 3: that happening in twenty twenty four?

616
00:34:10,080 --> 00:34:10,960
Speaker 2: Like and not?

617
00:34:12,200 --> 00:34:13,560
Speaker 3: Can't AI itself?

618
00:34:13,920 --> 00:34:16,239
Speaker 1: Hasn't it been trained and developed to a point where

619
00:34:16,320 --> 00:34:19,040
Speaker 1: it can look at me and go, you know, middle

620
00:34:19,080 --> 00:34:23,319
Speaker 1: aged I can white bloke with a bad attitude. Can't

621
00:34:23,320 --> 00:34:24,440
Speaker 1: it do that all by itself?

622
00:34:24,520 --> 00:34:27,000
Speaker 2: Now? No? The problem with that is if you're using

623
00:34:27,120 --> 00:34:30,600
Speaker 2: AI to train AI, that's your AI cannibalism. Isn't it.

624
00:34:32,760 --> 00:34:33,600
Speaker 3: Not to train AI?

625
00:34:33,800 --> 00:34:37,160
Speaker 1: But surely surely it can look at pretty much anything

626
00:34:37,280 --> 00:34:39,800
Speaker 1: now and figure out what it is. Like, do we

627
00:34:39,880 --> 00:34:42,880
Speaker 1: still need people to be going, Oh, that's a train,

628
00:34:43,040 --> 00:34:44,960
Speaker 1: that's a yellow train with red wheels.

629
00:34:46,280 --> 00:34:49,480
Speaker 2: People are better at it. People are much better at it.

630
00:34:49,560 --> 00:34:52,920
Speaker 2: We adapt. You know, the reality of it is that

631
00:34:53,200 --> 00:34:57,640
Speaker 2: it's a good thing. That there's an oversight in some ways,

632
00:34:58,400 --> 00:35:01,040
Speaker 2: but at this stage it appears is not. It appears

633
00:35:01,120 --> 00:35:03,799
Speaker 2: that the industry needs this, and when people are being

634
00:35:03,880 --> 00:35:07,360
Speaker 2: paid between say you're in Venezuela, you're being paid between

635
00:35:07,480 --> 00:35:10,480
Speaker 2: ninety cents and two dollars US an hour to do

636
00:35:10,640 --> 00:35:12,360
Speaker 2: this generally mindless work.

637
00:35:13,080 --> 00:35:15,480
Speaker 3: Do you know what I think? I don't know.

638
00:35:15,600 --> 00:35:17,880
Speaker 1: I don't think we've ever We've kind of spoken about this,

639
00:35:18,040 --> 00:35:22,440
Speaker 1: but not in any great detail. I think there's a vast,

640
00:35:23,080 --> 00:35:30,040
Speaker 1: vast chasmhole in the in what's happening right now in

641
00:35:30,160 --> 00:35:32,239
Speaker 1: terms of the role out and the I guess the

642
00:35:32,480 --> 00:35:37,359
Speaker 1: overwhelm of technology. You know, we've spoken about my mum

643
00:35:37,400 --> 00:35:40,080
Speaker 1: and dad a bit with tech, and you know that

644
00:35:40,360 --> 00:35:42,319
Speaker 1: now I've taken over the paying of all of their

645
00:35:42,400 --> 00:35:45,720
Speaker 1: bills electronically because mum and dad were freaked out, because

646
00:35:46,520 --> 00:35:48,360
Speaker 1: you know, I mean, the truth is that there are

647
00:35:48,480 --> 00:35:51,600
Speaker 1: even in Australia, there are millions of people who are

648
00:35:51,640 --> 00:35:59,719
Speaker 1: not tech savvy, who are constantly having problems with navigating

649
00:36:00,120 --> 00:36:02,920
Speaker 1: world that is very, very very different to the one

650
00:36:03,080 --> 00:36:06,000
Speaker 1: twenty years ago. And of course technology brings with it

651
00:36:06,480 --> 00:36:11,200
Speaker 1: great advantages, but it also brings potential or many potential problems.

652
00:36:12,520 --> 00:36:15,520
Speaker 1: What I mean, there's no answer to this, but or

653
00:36:15,560 --> 00:36:20,600
Speaker 1: there's no immediate answer. But being able to create technology

654
00:36:20,800 --> 00:36:25,279
Speaker 1: that is truly user friendly, truly user friendly for people

655
00:36:25,320 --> 00:36:28,680
Speaker 1: who don't understand technology, I mean, I think that's the

656
00:36:28,800 --> 00:36:32,640
Speaker 1: next great bloody opportunity or the great the next great

657
00:36:32,719 --> 00:36:36,200
Speaker 1: problem to be solved, because you know, even for me

658
00:36:36,320 --> 00:36:38,839
Speaker 1: and I use technology all day every day, we're using

659
00:36:38,920 --> 00:36:42,960
Speaker 1: it right now, I've got multiple computers, phones. You know,

660
00:36:43,480 --> 00:36:46,759
Speaker 1: I'm my life, my business, my career is dependent on it.

661
00:36:48,200 --> 00:36:51,320
Speaker 1: And I'm still a complete fucking dummy compared to you,

662
00:36:52,320 --> 00:36:55,840
Speaker 1: and you're a complete dummy compared to someone else. But

663
00:36:55,960 --> 00:36:58,400
Speaker 1: then you take at one level beyond me and you

664
00:36:58,520 --> 00:37:00,799
Speaker 1: go then there are like my mum and dad who

665
00:37:00,840 --> 00:37:02,719
Speaker 1: do not know how to pay a bill unless it's

666
00:37:02,760 --> 00:37:05,880
Speaker 1: with a check or cash. You know, how do we

667
00:37:06,000 --> 00:37:09,360
Speaker 1: look after those people moving forward? Because it seems like

668
00:37:10,320 --> 00:37:12,880
Speaker 1: they're not really being hated.

669
00:37:12,600 --> 00:37:17,600
Speaker 2: For the digital haves and have nots. I guess it's

670
00:37:17,719 --> 00:37:22,920
Speaker 2: probably people maybe fifty up because they didn't grow up

671
00:37:22,960 --> 00:37:27,000
Speaker 2: in a schooling environment with technology. They may have not

672
00:37:27,200 --> 00:37:29,480
Speaker 2: adopted technology because they didn't need it for their job

673
00:37:29,560 --> 00:37:31,760
Speaker 2: if they were in a trade or they did something

674
00:37:31,840 --> 00:37:34,520
Speaker 2: that didn't require them to be on computers. And I mean,

675
00:37:34,560 --> 00:37:37,640
Speaker 2: do you remember when they started rolling out atm machines,

676
00:37:38,120 --> 00:37:40,600
Speaker 2: how lot people just didn't know how to use them

677
00:37:40,640 --> 00:37:42,640
Speaker 2: and struggled with them. And there's still concerns for a

678
00:37:42,680 --> 00:37:46,399
Speaker 2: lot of older people. For me, you asked two kind

679
00:37:46,400 --> 00:37:49,080
Speaker 2: of really pertinent questions there. One is how do we

680
00:37:49,160 --> 00:37:52,360
Speaker 2: support and help the people right now who are in

681
00:37:52,480 --> 00:37:54,799
Speaker 2: that digital divide, who are part of the other side

682
00:37:54,840 --> 00:37:59,600
Speaker 2: of the digital divide? And I guess it's compassion from

683
00:37:59,760 --> 00:38:02,879
Speaker 2: the banking system, from those services, you know, whether you're

684
00:38:02,920 --> 00:38:05,959
Speaker 2: going to my other account and being able to still

685
00:38:06,480 --> 00:38:09,480
Speaker 2: have face to face contact and saying, well, you know,

686
00:38:09,560 --> 00:38:11,920
Speaker 2: the reality of it is, if someone's over the age

687
00:38:11,960 --> 00:38:15,200
Speaker 2: of sixty or seventy, they may still need to walk

688
00:38:15,239 --> 00:38:16,799
Speaker 2: into a bank and sit down and talk to their

689
00:38:16,880 --> 00:38:20,080
Speaker 2: bank teller, their bank manager, and we need to not

690
00:38:20,440 --> 00:38:24,080
Speaker 2: force them onto technology because maybe beyond them, we need

691
00:38:24,160 --> 00:38:27,200
Speaker 2: to understand that some people a they may not be willing,

692
00:38:27,320 --> 00:38:30,319
Speaker 2: but be they may be frightened. They may have many

693
00:38:30,480 --> 00:38:33,560
Speaker 2: reasons for being part of the digital divide. So I think,

694
00:38:34,040 --> 00:38:35,719
Speaker 2: first of all, as a society, we need to be

695
00:38:35,800 --> 00:38:38,360
Speaker 2: more compassionate to those people and not force them to

696
00:38:38,400 --> 00:38:40,920
Speaker 2: do something. COVID forced a little of people to work

697
00:38:40,960 --> 00:38:43,239
Speaker 2: out what a Q code was, but a lot of

698
00:38:43,280 --> 00:38:47,319
Speaker 2: people stressed over that, so it's difficult for those people.

699
00:38:47,400 --> 00:38:49,640
Speaker 2: But the secondary thing is, and I think the exciting

700
00:38:49,719 --> 00:38:52,279
Speaker 2: thing from the next level up and it won't help

701
00:38:52,360 --> 00:38:56,240
Speaker 2: your parents, but it may help us and people younger

702
00:38:56,280 --> 00:38:59,320
Speaker 2: than us as we get older. Is as technology and

703
00:38:59,400 --> 00:39:03,560
Speaker 2: AIS in implemented, is getting technology that doesn't just have

704
00:39:03,719 --> 00:39:06,279
Speaker 2: a this one way to turn something on and off.

705
00:39:06,719 --> 00:39:10,040
Speaker 2: If you think about it, if you ask different ways,

706
00:39:10,400 --> 00:39:12,759
Speaker 2: you know, you can use different phrases to say the

707
00:39:12,840 --> 00:39:15,040
Speaker 2: same thing to try to get the same results. But

708
00:39:15,239 --> 00:39:19,480
Speaker 2: generally most computers are binary. It's yes or no, it's

709
00:39:19,560 --> 00:39:24,240
Speaker 2: off or on. But with the deployment of things like AI,

710
00:39:24,640 --> 00:39:29,200
Speaker 2: it will make technology easier because you know, I envisited

711
00:39:29,239 --> 00:39:32,560
Speaker 2: a time where we won't be using phones anymore. We'll

712
00:39:32,600 --> 00:39:36,640
Speaker 2: have a pair of our glasses will project the information

713
00:39:36,840 --> 00:39:39,200
Speaker 2: we need hovering in front of us like a heads

714
00:39:39,239 --> 00:39:41,319
Speaker 2: up display. Your car has a heads up display, doesn't

715
00:39:41,320 --> 00:39:41,920
Speaker 2: it your new car?

716
00:39:42,080 --> 00:39:42,279
Speaker 3: Yeah?

717
00:39:42,640 --> 00:39:45,880
Speaker 2: Yeah, okay, So it's not obtrusive at all, and in

718
00:39:46,040 --> 00:39:48,960
Speaker 2: fact it helps with the road experience because you're not

719
00:39:49,040 --> 00:39:51,800
Speaker 2: looking down at your speedo. But I could imagine a

720
00:39:51,920 --> 00:39:54,400
Speaker 2: future where I would just say, you know, what's the

721
00:39:54,480 --> 00:39:58,040
Speaker 2: weather going to be today, and tell me that without

722
00:39:58,160 --> 00:40:01,680
Speaker 2: searching for an app, without going going to a Google

723
00:40:01,760 --> 00:40:04,439
Speaker 2: search bar and typing that in. So I think as

724
00:40:04,600 --> 00:40:08,000
Speaker 2: technology becomes more used friendly, then hopefully for us and

725
00:40:08,160 --> 00:40:12,640
Speaker 2: people who's substantly come along, you won't have the barriers.

726
00:40:12,680 --> 00:40:16,359
Speaker 2: We won't have keyboards to worry about. We will have conversations.

727
00:40:16,600 --> 00:40:19,000
Speaker 2: You just had a conversation with chat GPT and that

728
00:40:19,160 --> 00:40:21,719
Speaker 2: was very natural. And the thing about a lot of

729
00:40:21,800 --> 00:40:24,800
Speaker 2: these searches now is they remember what we previously spoke about.

730
00:40:25,200 --> 00:40:29,040
Speaker 2: So if you can think about your experiences of using

731
00:40:29,120 --> 00:40:32,280
Speaker 2: a phone and then putting it all into smart glasses,

732
00:40:32,600 --> 00:40:35,200
Speaker 2: it's hovering there. Quite often. We don't need to look

733
00:40:35,200 --> 00:40:37,520
Speaker 2: at our phone. If you want to call me and

734
00:40:37,600 --> 00:40:40,560
Speaker 2: you say call Patrick Bonello, you don't need to go

735
00:40:40,800 --> 00:40:44,000
Speaker 2: through your contact list. It verifies it's you and then

736
00:40:44,040 --> 00:40:47,480
Speaker 2: the call gets initiated. So for me Hopefully we'll get

737
00:40:47,480 --> 00:40:49,799
Speaker 2: a hybrid of this that will help your parents down

738
00:40:49,840 --> 00:40:52,480
Speaker 2: the track, maybe, you know, if they get more and

739
00:40:52,600 --> 00:40:55,600
Speaker 2: more comfortable, at least with using voice activation. It takes

740
00:40:55,640 --> 00:40:59,200
Speaker 2: screens and keyboards and mice away from people who may

741
00:40:59,239 --> 00:40:59,880
Speaker 2: have problems with it.

742
00:41:01,320 --> 00:41:03,359
Speaker 1: Even my little old car that I get around then,

743
00:41:03,480 --> 00:41:06,200
Speaker 1: which is a five year old Suzuki. It's not that old,

744
00:41:06,280 --> 00:41:08,360
Speaker 1: but you know what I mean, it's and it's just

745
00:41:08,520 --> 00:41:11,680
Speaker 1: really it's a Suzuki Swift that's super basic. There's a

746
00:41:11,719 --> 00:41:13,960
Speaker 1: button on the thing which is like a bloke talking

747
00:41:14,120 --> 00:41:16,920
Speaker 1: or a person talking. I press that and I go

748
00:41:18,239 --> 00:41:23,560
Speaker 1: call Patrick, and the lady goes calling Patrick Bonello, you know,

749
00:41:23,800 --> 00:41:25,800
Speaker 1: and then it rings you. I don't even I know

750
00:41:25,920 --> 00:41:28,720
Speaker 1: where that button is without even looking at the steering wheel.

751
00:41:29,520 --> 00:41:32,120
Speaker 1: I can just watch the road, press that button with

752
00:41:32,280 --> 00:41:34,600
Speaker 1: my thumb and tell my car to call you when

753
00:41:34,680 --> 00:41:37,279
Speaker 1: it does. And I mean that's five or six year

754
00:41:37,280 --> 00:41:41,040
Speaker 1: old technology. But I mean everything you're saying I agree with,

755
00:41:41,800 --> 00:41:43,759
Speaker 1: and I think moving forward it's great. And I'm a

756
00:41:43,800 --> 00:41:47,040
Speaker 1: little bit selfish and I'm a little bit biased with

757
00:41:47,200 --> 00:41:49,760
Speaker 1: this because of my eighty four and five year old parents.

758
00:41:50,520 --> 00:41:54,560
Speaker 1: But like, hands down, at the moment. Hands down, my

759
00:41:54,719 --> 00:41:59,880
Speaker 1: mum's biggest source of anxiety is technology because it's scarce

760
00:42:00,080 --> 00:42:03,000
Speaker 1: a shit out of her and she doesn't know, you know,

761
00:42:03,120 --> 00:42:07,040
Speaker 1: in my mom Like my mum's got an iPhone, she

762
00:42:07,200 --> 00:42:10,480
Speaker 1: literally doesn't know how to use it other than to

763
00:42:10,640 --> 00:42:13,360
Speaker 1: make a call and get a call, you know, and

764
00:42:13,480 --> 00:42:16,040
Speaker 1: even I could, you know, I've tried to teach her

765
00:42:16,239 --> 00:42:19,880
Speaker 1: so many times how to do that. She can she

766
00:42:20,000 --> 00:42:23,680
Speaker 1: can send texts, but even then it's pretty clunky. But

767
00:42:24,239 --> 00:42:26,880
Speaker 1: I will send her a text and she it'll go,

768
00:42:27,280 --> 00:42:29,560
Speaker 1: she'll get it, but she doesn't get it because she

769
00:42:29,680 --> 00:42:32,400
Speaker 1: never thinks to look or that little sign in the

770
00:42:32,480 --> 00:42:33,320
Speaker 1: window or whatever.

771
00:42:33,440 --> 00:42:36,279
Speaker 3: You know. It's like, I don't know. I guess there's

772
00:42:36,360 --> 00:42:36,920
Speaker 3: no answer.

773
00:42:37,080 --> 00:42:40,239
Speaker 1: But it's like we're so brilliant, we're so advanced at

774
00:42:40,320 --> 00:42:43,520
Speaker 1: solving problems, and we can do you know, we can

775
00:42:44,640 --> 00:42:47,280
Speaker 1: we can do pretty much anything now, but we can't

776
00:42:47,440 --> 00:42:53,400
Speaker 1: create a way for old people who aren't technologically minded

777
00:42:53,719 --> 00:42:57,000
Speaker 1: or trained. It'd be great if we could produce something

778
00:42:57,080 --> 00:42:59,520
Speaker 1: which for them is just as easy as talking to

779
00:42:59,600 --> 00:43:00,120
Speaker 1: a human.

780
00:43:00,640 --> 00:43:02,080
Speaker 3: Or having a human interaction.

781
00:43:02,800 --> 00:43:06,440
Speaker 1: Because you think about the percentage of people in Australia

782
00:43:06,520 --> 00:43:09,239
Speaker 1: who are say older than sixty and that's the.

783
00:43:09,239 --> 00:43:10,400
Speaker 3: Group we're talking about.

784
00:43:11,200 --> 00:43:13,120
Speaker 1: I don't know what it is, but I would guess

785
00:43:13,160 --> 00:43:16,120
Speaker 1: it would be somewhere in the three four million range.

786
00:43:16,680 --> 00:43:18,400
Speaker 1: I mean, that's a lot of humans, and we're not

787
00:43:18,480 --> 00:43:22,320
Speaker 1: a massive population. Then you think globally, you extrapolate that

788
00:43:22,840 --> 00:43:25,520
Speaker 1: it might be a billion people who are sixty year older.

789
00:43:26,840 --> 00:43:28,720
Speaker 1: You know, that's a big that's a big market.

790
00:43:29,400 --> 00:43:32,640
Speaker 2: There are some companies that are servicing that market. I

791
00:43:32,760 --> 00:43:35,600
Speaker 2: was thinking about your mum and the iPhone, and then

792
00:43:35,840 --> 00:43:37,800
Speaker 2: I kind of thought, well, my little brother has a

793
00:43:37,920 --> 00:43:40,640
Speaker 2: phone that doesn't have a screen on it. All it has,

794
00:43:40,880 --> 00:43:43,240
Speaker 2: if you can imagine, you know, it's a bit smaller

795
00:43:43,280 --> 00:43:46,040
Speaker 2: than a standard mobile phone, a bit bigger than card

796
00:43:46,400 --> 00:43:49,120
Speaker 2: and all it has is you pre program. It's got

797
00:43:49,160 --> 00:43:51,480
Speaker 2: a big, chunky name next to it, so it's Patrick,

798
00:43:52,080 --> 00:43:55,239
Speaker 2: it's Dad, it's all the various contacts. I think about

799
00:43:55,280 --> 00:43:58,200
Speaker 2: eight or ten on it, maybe only eight, and you

800
00:43:58,320 --> 00:44:00,799
Speaker 2: just button and it calls them. That's it. All you've

801
00:44:00,840 --> 00:44:03,000
Speaker 2: got is a call and a hang up. Doesn't even

802
00:44:03,040 --> 00:44:05,960
Speaker 2: have a keypad to dial numbers. You just have emergency

803
00:44:06,040 --> 00:44:07,960
Speaker 2: contacts or people you want to speak to, and he

804
00:44:08,120 --> 00:44:10,760
Speaker 2: just press the button, it calls them, and he presses

805
00:44:10,800 --> 00:44:12,920
Speaker 2: the hang up button most of the time to hang up.

806
00:44:13,600 --> 00:44:15,759
Speaker 3: And how does he know who's ringing?

807
00:44:15,840 --> 00:44:21,399
Speaker 2: If someone rings, Oh, I guess that lights up next

808
00:44:21,440 --> 00:44:21,640
Speaker 2: to them.

809
00:44:21,719 --> 00:44:25,160
Speaker 3: I don't know, amen, because I'm just thinking what efforts,

810
00:44:25,160 --> 00:44:27,640
Speaker 3: you know, one of those fucking annoying people trying to

811
00:44:27,719 --> 00:44:29,680
Speaker 3: sell your shit. You don't want to be answering those

812
00:44:29,680 --> 00:44:30,160
Speaker 3: all the time.

813
00:44:30,760 --> 00:44:33,400
Speaker 2: I just realized that the contact details that I've got

814
00:44:33,440 --> 00:44:36,120
Speaker 2: in my phone for his phone is Jason's lego phone.

815
00:44:37,360 --> 00:44:38,200
Speaker 3: That's hilarious.

816
00:44:38,400 --> 00:44:40,200
Speaker 2: Yeah, but I don't know. I'll have to try that

817
00:44:40,360 --> 00:44:42,840
Speaker 2: next time. I'm not sure what it does when you

818
00:44:43,000 --> 00:44:45,080
Speaker 2: ring in and how he knows where it's coming from.

819
00:44:45,400 --> 00:44:47,239
Speaker 2: That's a really good question. I need to follow that up.

820
00:44:48,400 --> 00:44:52,839
Speaker 1: Oh wow, oh wow, all right, let's do another one

821
00:44:52,960 --> 00:44:55,120
Speaker 1: or two if you've got anything on your list.

822
00:44:55,760 --> 00:44:58,960
Speaker 2: Well, this is an interesting one. The government's getting really proactive.

823
00:44:59,000 --> 00:45:01,239
Speaker 2: When I say the government, this trading. Government's getting really

824
00:45:01,280 --> 00:45:06,920
Speaker 2: proactive with a first ever standalone Cybersecurity Act. So what

825
00:45:07,120 --> 00:45:10,680
Speaker 2: this means there's two cybersecurity bills that are currently being

826
00:45:10,760 --> 00:45:14,440
Speaker 2: reviewed by a parliamentary committee and what they're looking at

827
00:45:14,719 --> 00:45:20,000
Speaker 2: is a mandatory minimum cyber security standard for smart devices

828
00:45:20,080 --> 00:45:25,879
Speaker 2: because things like speakers, vacuums, doorbells, fridges, all that sort

829
00:45:25,920 --> 00:45:29,320
Speaker 2: of smart connectivity because they're there now. They want to

830
00:45:29,440 --> 00:45:34,040
Speaker 2: have an absolute minimum that that security means. Because there

831
00:45:34,160 --> 00:45:37,640
Speaker 2: was a brand of vacuum cleaners recently that they found

832
00:45:37,719 --> 00:45:40,839
Speaker 2: out that because they have cameras built into them, these

833
00:45:41,000 --> 00:45:44,680
Speaker 2: robo vACC You don't have a robovac, dear, no so,

834
00:45:45,040 --> 00:45:45,880
Speaker 2: but there's been a.

835
00:45:45,880 --> 00:45:49,000
Speaker 3: Bit of stuff in the news about robo vax fucking

836
00:45:49,280 --> 00:45:52,080
Speaker 3: doing like attacking dogs.

837
00:45:51,840 --> 00:45:56,320
Speaker 2: And dog yeah. No, well, in this instance, recording everything

838
00:45:56,680 --> 00:45:58,600
Speaker 2: so they can send to the cloud and they can

839
00:45:58,680 --> 00:46:01,319
Speaker 2: basically look through through the cameras. I mean for your

840
00:46:01,360 --> 00:46:04,839
Speaker 2: own personal security. This is scary to think that your

841
00:46:04,920 --> 00:46:08,880
Speaker 2: own devices could be spying on you. So your robot

842
00:46:09,000 --> 00:46:11,040
Speaker 2: vacuum cleaner has a camera in it, and if you

843
00:46:11,120 --> 00:46:14,280
Speaker 2: think that it's vacuuming around the house and you've got kids,

844
00:46:14,360 --> 00:46:17,279
Speaker 2: and you've got older people, and it could be seeing

845
00:46:17,360 --> 00:46:20,440
Speaker 2: and watching and then recording that information. There was one brand,

846
00:46:20,520 --> 00:46:22,279
Speaker 2: and I can't think of it at the moment. It's

847
00:46:22,360 --> 00:46:24,680
Speaker 2: not one of the big popular ones, but certainly was

848
00:46:24,719 --> 00:46:28,520
Speaker 2: a reasonably popular one. They didn't have protections in place,

849
00:46:28,600 --> 00:46:31,880
Speaker 2: so that data was being captured, including camera footage and

850
00:46:32,120 --> 00:46:35,600
Speaker 2: audio being recorded. So you've got this digital spy that's

851
00:46:35,680 --> 00:46:38,239
Speaker 2: running around your house. So I think it's a good

852
00:46:38,320 --> 00:46:42,120
Speaker 2: step in the right direction with this kind of cyber

853
00:46:42,200 --> 00:46:46,400
Speaker 2: security legislation that hopefully will go to Parliament. It's a

854
00:46:46,480 --> 00:46:49,160
Speaker 2: security bill they're talking about putting it through, and then

855
00:46:49,200 --> 00:46:52,319
Speaker 2: it puts the onus back on the companies to make

856
00:46:52,400 --> 00:46:55,840
Speaker 2: sure that the devices that we use, the smart things.

857
00:46:56,120 --> 00:46:58,480
Speaker 2: You know, we call it the Internet of things. So

858
00:46:58,600 --> 00:47:01,680
Speaker 2: a device that's Internet enable and can be right in

859
00:47:01,760 --> 00:47:05,080
Speaker 2: our digital ecosystem, it's referred to as the Internet of things.

860
00:47:05,600 --> 00:47:08,879
Speaker 2: And I think that more companies need to be put

861
00:47:08,960 --> 00:47:12,640
Speaker 2: under pressure to make sure these devices are secure. That's

862
00:47:12,640 --> 00:47:15,400
Speaker 2: a real problem. If you've ever installed a router in

863
00:47:15,440 --> 00:47:18,160
Speaker 2: your home, you know, when you connect the internet, generally

864
00:47:18,640 --> 00:47:23,000
Speaker 2: the standard username and password is either admin admin or

865
00:47:23,080 --> 00:47:27,360
Speaker 2: admin password or admin one two three four. You know

866
00:47:27,440 --> 00:47:33,560
Speaker 2: it's it's it's mind blowingly ridiculous that standard that comes out.

867
00:47:33,560 --> 00:47:35,640
Speaker 2: I mean, you should be forced when you install a

868
00:47:35,760 --> 00:47:38,279
Speaker 2: router or a modem, it should be found to create

869
00:47:38,360 --> 00:47:41,600
Speaker 2: a password and a username that's unique to you, not

870
00:47:41,760 --> 00:47:44,600
Speaker 2: the standard because it means that all these off the

871
00:47:44,680 --> 00:47:47,239
Speaker 2: shelf devices could be potentially hacked into.

872
00:47:48,200 --> 00:47:53,920
Speaker 1: Hey, David Gillespie and I did an episode on October eleven,

873
00:47:54,000 --> 00:47:58,000
Speaker 1: what's that six days ago? Episode sixteen seventy one called

874
00:47:58,280 --> 00:48:04,480
Speaker 1: is your car spying on you? And he wrote wanted

875
00:48:04,600 --> 00:48:05,719
Speaker 1: or not aware of it or not?

876
00:48:06,160 --> 00:48:08,200
Speaker 3: If you have a relatively late model car, there's a

877
00:48:08,239 --> 00:48:10,239
Speaker 3: very high chance that much of what you're doing when

878
00:48:10,239 --> 00:48:14,000
Speaker 3: you're behind the wheel is being recorded. Henry Ford would

879
00:48:14,040 --> 00:48:16,960
Speaker 3: be horrified his model T once a symbol of freedom,

880
00:48:17,440 --> 00:48:21,160
Speaker 3: has morphed into a rolling surveillance device tracking our every

881
00:48:21,280 --> 00:48:26,719
Speaker 3: move and eavesdropping on our conversations. Some cars Tesla for example,

882
00:48:27,560 --> 00:48:33,320
Speaker 3: even turning into rolling CCTV cameras capturing every move Grimace

883
00:48:33,760 --> 00:48:39,360
Speaker 3: and nose Pick, So there are Choice Magazine did like

884
00:48:39,480 --> 00:48:43,319
Speaker 3: an expose on that. They did and then Gillespo wrote

885
00:48:43,320 --> 00:48:45,800
Speaker 3: about it. But yeah, that's that.

886
00:48:46,080 --> 00:48:49,880
Speaker 1: That's fucking terrifying, Like they're not just audio recording but

887
00:48:50,239 --> 00:48:54,480
Speaker 1: video recording you in your car and then keeping that.

888
00:48:54,800 --> 00:48:58,160
Speaker 1: And I said to him, what about But surely they

889
00:48:58,280 --> 00:49:01,040
Speaker 1: need approval or they need and it's like, yeah, well

890
00:49:01,080 --> 00:49:03,759
Speaker 1: when you buy whatever or you of course you just

891
00:49:03,840 --> 00:49:08,359
Speaker 1: go accept and he said, like trying to what did

892
00:49:08,440 --> 00:49:11,880
Speaker 1: he say? He said, trying to read and understand what

893
00:49:12,080 --> 00:49:16,719
Speaker 1: you're agreeing to is like trying to read a ten

894
00:49:16,800 --> 00:49:18,520
Speaker 1: thousand word document in Klingon.

895
00:49:20,040 --> 00:49:24,920
Speaker 2: You know, that's right. I know that in Europe, the

896
00:49:25,040 --> 00:49:29,200
Speaker 2: EU is trying to force companies to make their terms

897
00:49:29,280 --> 00:49:32,640
Speaker 2: of service and agreements to be a lot clearer, to

898
00:49:32,760 --> 00:49:35,120
Speaker 2: spell them out, to put more kind of you know,

899
00:49:35,239 --> 00:49:37,720
Speaker 2: to make the more succinct as to what they're storing

900
00:49:37,800 --> 00:49:39,920
Speaker 2: and what they're keeping from you. By the way, I

901
00:49:40,000 --> 00:49:43,880
Speaker 2: remember I found the article about that vacuum cleaner that

902
00:49:44,000 --> 00:49:47,239
Speaker 2: collects photos and audio to train AI. It's called the

903
00:49:47,400 --> 00:49:52,600
Speaker 2: d Bot dwbot robot vacuum and they're saying, and this

904
00:49:52,719 --> 00:49:55,360
Speaker 2: was an article on the ABC by the way, ABC Australia.

905
00:49:55,840 --> 00:49:59,880
Speaker 2: So they've been found to suffer from critical cybersecurity flaws

906
00:50:00,040 --> 00:50:04,200
Speaker 2: and they're collecting photos, videos and voice recordings has taken

907
00:50:04,360 --> 00:50:07,640
Speaker 2: inside customers' houses and what they're using that data for

908
00:50:07,840 --> 00:50:11,000
Speaker 2: is to train the company's AI model. So they're taking it.

909
00:50:11,280 --> 00:50:15,000
Speaker 2: This is a Chinese home robotics company and they sell

910
00:50:15,080 --> 00:50:17,680
Speaker 2: the debot, which is a lot of people illustrated him

911
00:50:17,680 --> 00:50:20,480
Speaker 2: may have one of these. I'm going to tell you

912
00:50:20,560 --> 00:50:22,279
Speaker 2: a story. A friend of mine just brought himself a

913
00:50:22,360 --> 00:50:25,160
Speaker 2: Chinese car. It's called the Tank. Have you heard of

914
00:50:25,239 --> 00:50:25,560
Speaker 2: the Tank?

915
00:50:26,239 --> 00:50:26,399
Speaker 3: Yeah?

916
00:50:26,480 --> 00:50:30,680
Speaker 1: Yeah, it's made by GWM Havelet's there's a three hundred

917
00:50:30,800 --> 00:50:33,240
Speaker 1: and a five hundred, so he probably bought the three hundred.

918
00:50:33,400 --> 00:50:36,520
Speaker 2: Coincidence two one of my friends bought the three hundred.

919
00:50:36,560 --> 00:50:38,759
Speaker 2: One bought the five hundred. But I had to laugh.

920
00:50:38,800 --> 00:50:40,239
Speaker 2: I got into his car the other day. He's only

921
00:50:40,280 --> 00:50:43,640
Speaker 2: had it for about two weeks and there's a camera

922
00:50:43,760 --> 00:50:47,440
Speaker 2: that faces you to crack whether you fall asleep or

923
00:50:47,600 --> 00:50:50,160
Speaker 2: I mean, it's about effectively that's what it's supposed to do.

924
00:50:50,560 --> 00:50:53,359
Speaker 2: He's put a sticker over it because he does looking

925
00:50:53,400 --> 00:50:55,200
Speaker 2: at him. I don't know if I could be in

926
00:50:55,280 --> 00:50:58,600
Speaker 2: a car that's looking back at me constantly. That's his frame.

927
00:50:59,000 --> 00:50:59,920
Speaker 3: Mine's got the same thing.

928
00:51:00,600 --> 00:51:01,719
Speaker 2: Oh really yeah yeah.

929
00:51:01,880 --> 00:51:04,040
Speaker 3: If you blink for too long, it tells you to

930
00:51:04,200 --> 00:51:07,920
Speaker 3: pull over and have a rest. Yeah wow, I mean,

931
00:51:08,600 --> 00:51:10,040
Speaker 3: but just quickly.

932
00:51:09,840 --> 00:51:13,840
Speaker 1: Jumping back to the vaxspying vacuum, think about the fact

933
00:51:13,920 --> 00:51:19,000
Speaker 1: that what a genius way to get a mobile microphone

934
00:51:19,120 --> 00:51:23,600
Speaker 1: and camera into your house where imagine if you know,

935
00:51:24,080 --> 00:51:27,120
Speaker 1: like it looked like a microphone and camera. You wouldn't

936
00:51:27,239 --> 00:51:30,960
Speaker 1: let it anywhere near your fucking property. But because oh

937
00:51:31,080 --> 00:51:34,400
Speaker 1: it's a vacuum, it's a vacuum that happens to have

938
00:51:34,560 --> 00:51:38,080
Speaker 1: a camera and a microphone. And you go into room

939
00:51:38,120 --> 00:51:40,560
Speaker 1: and all of a sudden, there it is listening and filming,

940
00:51:41,440 --> 00:51:44,040
Speaker 1: you know, And now I'm in the shower. I'm not

941
00:51:44,160 --> 00:51:48,320
Speaker 1: sure why it's in the bathroom, you know. I'm like,

942
00:51:49,239 --> 00:51:51,400
Speaker 1: that is potentially fucking.

943
00:51:52,760 --> 00:51:55,560
Speaker 3: Terrifying. Well, not potentially, it is terrifying.

944
00:51:55,760 --> 00:51:58,239
Speaker 2: Well, they also do a two D and sometimes even

945
00:51:58,280 --> 00:52:01,480
Speaker 2: a three D map of your house. And the concern

946
00:52:01,640 --> 00:52:04,920
Speaker 2: is this company may legitimately be collecting the data to

947
00:52:04,960 --> 00:52:08,200
Speaker 2: try to map their vacuum cleaners better, but what they

948
00:52:08,320 --> 00:52:11,320
Speaker 2: can't guarantee is that they're not going to be hacked.

949
00:52:11,360 --> 00:52:14,160
Speaker 2: Could you think about a crime syndicate hacking your vacuum

950
00:52:14,200 --> 00:52:17,400
Speaker 2: cleaner moving around knowing where you are, when you are,

951
00:52:17,560 --> 00:52:19,680
Speaker 2: when you're off to work, and where all the valuables

952
00:52:19,719 --> 00:52:20,319
Speaker 2: are in the house.

953
00:52:21,320 --> 00:52:23,600
Speaker 1: Well, it's funny you say this, and this is not

954
00:52:23,719 --> 00:52:25,560
Speaker 1: a very good way. You and I have been quite

955
00:52:26,200 --> 00:52:29,799
Speaker 1: you know, unprofessional today. But I'm just having a look

956
00:52:29,840 --> 00:52:44,040
Speaker 1: at vacuum vacuum threatening I read this thing person, excuse me, No,

957
00:52:44,520 --> 00:52:48,759
Speaker 1: I can't find it. But this this one of those

958
00:52:48,880 --> 00:52:52,759
Speaker 1: vacuums was basically somebody, I don't know what the word

959
00:52:52,880 --> 00:52:53,640
Speaker 1: is hijacked it.

960
00:52:53,840 --> 00:52:54,399
Speaker 2: You know the word.

961
00:52:54,440 --> 00:52:57,480
Speaker 1: I don't know the word, but took and they have

962
00:52:57,680 --> 00:53:02,160
Speaker 1: speakers in them, and somebody was abusing. Somebody had had

963
00:53:02,280 --> 00:53:06,400
Speaker 1: hacked it and was abusing the homeowner was abusing that.

964
00:53:06,840 --> 00:53:10,320
Speaker 3: So obviously not the company was doing, but somebody had had.

965
00:53:10,280 --> 00:53:14,759
Speaker 1: That particular let's call it what it is, robot, and yeah,

966
00:53:14,920 --> 00:53:19,320
Speaker 1: they they were just abusing this person who was in

967
00:53:19,400 --> 00:53:19,759
Speaker 1: the home.

968
00:53:20,400 --> 00:53:22,439
Speaker 5: Yeah. Yeah.

969
00:53:23,200 --> 00:53:27,000
Speaker 2: It is a worrying thing that we allow technology into

970
00:53:27,080 --> 00:53:29,319
Speaker 2: our homes. And we talked in an episode not long

971
00:53:29,360 --> 00:53:34,320
Speaker 2: ago about how some apps owned by Facebook Meta and

972
00:53:35,040 --> 00:53:38,800
Speaker 2: they were tracking people in conversations. So once you have

973
00:53:39,000 --> 00:53:41,440
Speaker 2: the Facebook app on your phone, potentially they could be

974
00:53:41,480 --> 00:53:44,120
Speaker 2: listening into your conversation so they can serve up ads.

975
00:53:44,400 --> 00:53:48,200
Speaker 2: So there was an advertising agency that ran ads for

976
00:53:48,400 --> 00:53:50,960
Speaker 2: the likes of Meta, and what they were doing was

977
00:53:51,120 --> 00:53:56,080
Speaker 2: they were tracking conversations for keywords and then serving up ads.

978
00:53:56,480 --> 00:53:58,839
Speaker 2: They've been caught out, but they were serving up ads

979
00:53:58,920 --> 00:54:02,000
Speaker 2: related to the conversation. So we're talking about robot vacuum cleaner.

980
00:54:02,560 --> 00:54:05,040
Speaker 2: Potentially you could jump back on your phone and suddenly

981
00:54:05,080 --> 00:54:07,200
Speaker 2: an ad for a robot vacuum cleaner would appear.

982
00:54:08,640 --> 00:54:09,879
Speaker 3: Yeah, yep.

983
00:54:11,120 --> 00:54:13,440
Speaker 1: I have that happen all the time, where I'll be

984
00:54:13,680 --> 00:54:16,239
Speaker 1: talking about something, my phone's not even near me, and

985
00:54:16,320 --> 00:54:18,080
Speaker 1: then I start getting ads.

986
00:54:18,360 --> 00:54:19,080
Speaker 3: Hey, listen to this.

987
00:54:22,000 --> 00:54:26,120
Speaker 1: South Korean woman's hair eaten by robot vacuum cleaner as

988
00:54:26,200 --> 00:54:26,800
Speaker 1: she slept.

989
00:54:27,040 --> 00:54:29,520
Speaker 3: Oh my god, there's a photo.

990
00:54:30,120 --> 00:54:33,320
Speaker 1: When a South Korean woman invested in a robot vacuum cleaner,

991
00:54:33,400 --> 00:54:36,040
Speaker 1: the idea was to leave her trustworthy gadget to do

992
00:54:36,200 --> 00:54:39,920
Speaker 1: its work while she took a break from household chores. Instead,

993
00:54:39,960 --> 00:54:42,520
Speaker 1: the fifty two year old resident of chang Wan City

994
00:54:42,719 --> 00:54:45,400
Speaker 1: ended up being a victim of what many believe is

995
00:54:45,440 --> 00:54:49,920
Speaker 1: a peek into a dystopian future in which supposedly benign

996
00:54:50,040 --> 00:54:54,120
Speaker 1: robots against their human masters. The woman, whose name is

997
00:54:54,160 --> 00:54:59,000
Speaker 1: been with was taking a nap on the floor at

998
00:54:59,080 --> 00:55:02,080
Speaker 1: home when the vacuum cleaner locked onto her hair and

999
00:55:02,280 --> 00:55:06,320
Speaker 1: sucked it up, apparently mistaking it for dust. The agony

1000
00:55:06,400 --> 00:55:09,279
Speaker 1: of having her hair entangled in the boughs of the

1001
00:55:09,400 --> 00:55:12,800
Speaker 1: contraption raised her from a slumber, and then there's a

1002
00:55:12,880 --> 00:55:15,480
Speaker 1: photo of what looks like ambos.

1003
00:55:15,880 --> 00:55:16,560
Speaker 2: Oh my god.

1004
00:55:18,440 --> 00:55:22,480
Speaker 3: Yeah, firefighters, so you found it trying to rescue the woman. Yeah,

1005
00:55:22,760 --> 00:55:23,480
Speaker 3: that's going to hurt.

1006
00:55:23,640 --> 00:55:25,560
Speaker 2: Can I just say, I'm going to take the side

1007
00:55:25,600 --> 00:55:27,040
Speaker 2: of the vacuum cleaner on this one.

1008
00:55:28,040 --> 00:55:30,399
Speaker 3: Well, that's because you've got no fucking hair, so you're

1009
00:55:30,480 --> 00:55:32,240
Speaker 3: not You're number anybody.

1010
00:55:32,840 --> 00:55:36,240
Speaker 2: Can I just say if you have a robot vacuum

1011
00:55:36,280 --> 00:55:39,840
Speaker 2: cleaner in your home and you lay down on the

1012
00:55:40,000 --> 00:55:43,960
Speaker 2: ground with your hair spread out on the floor, which

1013
00:55:44,040 --> 00:55:47,360
Speaker 2: is pretty gross as it happens, and the innocent robot

1014
00:55:47,480 --> 00:55:50,680
Speaker 2: vacuum cleaner happens to be doing their job and they

1015
00:55:50,920 --> 00:55:53,360
Speaker 2: find some dirt on the ground that happens to be

1016
00:55:53,520 --> 00:55:56,600
Speaker 2: someone's hair, it will vacuum it up. It didn't know

1017
00:55:56,680 --> 00:56:00,160
Speaker 2: it was attached to a human. Well, that's an that

1018
00:56:00,280 --> 00:56:04,480
Speaker 2: therein lies the problem. When you first told that story,

1019
00:56:04,719 --> 00:56:07,640
Speaker 2: I envisaged the vacuum cleaner jumping onto the bed and

1020
00:56:07,760 --> 00:56:10,400
Speaker 2: attacking her because that's what you made it sound like.

1021
00:56:10,800 --> 00:56:14,320
Speaker 2: And then the actual story was that she was naively

1022
00:56:14,560 --> 00:56:17,240
Speaker 2: laying on the floor while the vacuum cleaner was innocently

1023
00:56:17,360 --> 00:56:18,120
Speaker 2: doing its job.

1024
00:56:18,800 --> 00:56:22,000
Speaker 3: It doesn't it has to work times have I told

1025
00:56:22,040 --> 00:56:24,440
Speaker 3: you off air, don't let the facts get in the

1026
00:56:24,480 --> 00:56:28,440
Speaker 3: way of a fucking good story. So you, you and

1027
00:56:28,560 --> 00:56:33,799
Speaker 3: your bloody reality check can fuck off, mate. How can

1028
00:56:33,880 --> 00:56:36,040
Speaker 3: people connect with you and find you and follow you?

1029
00:56:36,160 --> 00:56:36,879
Speaker 3: Where are you at?

1030
00:56:37,680 --> 00:56:41,040
Speaker 2: Well? They can go to websites now, dot com, dot

1031
00:56:41,200 --> 00:56:45,080
Speaker 2: au and as it suggests, we actually build websites when

1032
00:56:45,120 --> 00:56:49,000
Speaker 2: I'm not on podcast talking crap, but we do all

1033
00:56:49,040 --> 00:56:51,040
Speaker 2: sorts of marketing and stuff like that. So go to

1034
00:56:51,440 --> 00:56:52,920
Speaker 2: if you want to ask questions, if you want us

1035
00:56:52,920 --> 00:56:55,120
Speaker 2: to talk about something in particular, So just go to

1036
00:56:55,200 --> 00:56:58,000
Speaker 2: websites now, dot com today you They can then jump

1037
00:56:58,040 --> 00:57:02,240
Speaker 2: online and send us sends a note, email me, contact

1038
00:57:02,280 --> 00:57:03,120
Speaker 2: me and I'll happily.

1039
00:57:03,360 --> 00:57:04,719
Speaker 1: Can I tell you if you do want to get

1040
00:57:04,760 --> 00:57:06,800
Speaker 1: a web and this is not a paid endorsement, but

1041
00:57:06,840 --> 00:57:08,680
Speaker 1: if you do want to get a website built, for

1042
00:57:08,800 --> 00:57:10,000
Speaker 1: God's sake, go to Patrick.

1043
00:57:10,080 --> 00:57:11,400
Speaker 3: Because one, there's a whole.

1044
00:57:11,239 --> 00:57:14,960
Speaker 1: Lot of fucking people who overcharge and under deliver, Like really,

1045
00:57:15,000 --> 00:57:18,960
Speaker 1: I've experienced it, He's not one. And there's a lot

1046
00:57:19,000 --> 00:57:20,880
Speaker 1: of people who try and keep you on the hook

1047
00:57:21,080 --> 00:57:24,800
Speaker 1: forever with a range of things you don't need, so

1048
00:57:25,000 --> 00:57:27,320
Speaker 1: save yourself a bit of time and energy and just

1049
00:57:27,680 --> 00:57:29,120
Speaker 1: start with someone who's good at it.

1050
00:57:29,440 --> 00:57:31,160
Speaker 2: Well, thanks, mate, that's really nice of you to say.

1051
00:57:31,440 --> 00:57:33,160
Speaker 2: Looking at what I love about what we do with

1052
00:57:33,240 --> 00:57:35,680
Speaker 2: our clients is we have such a diversity, and I

1053
00:57:35,800 --> 00:57:38,600
Speaker 2: love getting to know people and their businesses. I never

1054
00:57:38,720 --> 00:57:42,640
Speaker 2: knew that I would know anything about delivering a baby,

1055
00:57:43,320 --> 00:57:46,960
Speaker 2: but I do. Wow, that's because one of our clients

1056
00:57:47,200 --> 00:57:50,760
Speaker 2: does the most amazing obstetrics and gynological training models in

1057
00:57:51,040 --> 00:57:53,520
Speaker 2: the world. And they may just rand the corner from you,

1058
00:57:53,600 --> 00:57:55,200
Speaker 2: actually just down the road from your house.

1059
00:57:55,680 --> 00:57:56,680
Speaker 3: Well, the babies or.

1060
00:57:56,680 --> 00:57:59,800
Speaker 2: The everything, well, I guess they're happening all around you.

1061
00:58:00,040 --> 00:58:04,800
Speaker 3: It makes everybody everywhere appreciate you, mate, Thank you.

1062
00:58:05,280 --> 00:58:06,120
Speaker 2: Jeez. I