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Speaker 1: I'll get a team. It's to you, projectivity and Cook, Patrick,

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Speaker 1: James Bonello, Craig, Anthony Harper, just reporting in on a Friday,

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Speaker 1: well as Friday as we record. Whenever you hear this

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Speaker 1: is whenever you hear it. Let's start with the boy

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Speaker 1: in the room. Hi Patrick, it's just going to you.

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Speaker 1: TIF didn't you?

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Speaker 2: Yeah?

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Speaker 1: I did? I was ready, Hi Patrick?

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Speaker 2: Last episode do you ask for the girl in the room?

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Speaker 2: And then came to me and I just thought, you're

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Speaker 2: going to be smart again, or try to be I.

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Speaker 1: Was going to be more respectful this time. How's the

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Speaker 1: land space station where you're currently residing.

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Speaker 2: I kind of feel like we need to do a

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Speaker 2: screenshot or something so people get a sense of my

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Speaker 2: backdrop being a giant space station looking out on a

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Speaker 2: planet just hovering.

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Speaker 1: Do you know what I mean? I know this sounds silly,

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Speaker 1: but it like if my mum looked at that and

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Speaker 1: I told my mum Patrick's in space, she would believe it.

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Speaker 1: It looks literally like you're in space, like you got

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Speaker 1: this big round window just looking at it. I don't

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Speaker 1: know whatever it is is that the Earth below you

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Speaker 1: and the moon in the distance.

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Speaker 2: Yeah, yep, yep.

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Speaker 1: Yeah.

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Speaker 2: The other thing too is you know, when you and this,

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Speaker 2: I've started to this sounds like a real foible of mine,

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Speaker 2: but I've started to get annoyed at having zoom meetings

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Speaker 2: with people turning on fake backgrounds.

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Speaker 1: It is, what do you mean that's a photo of

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Speaker 1: the studio. Well, it's not real.

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Speaker 2: It's a fake background.

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Speaker 1: And you know what a fake background. It's a photo

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Speaker 1: of my real studio.

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Speaker 2: Exactly, it's a photo. It's fake. And his hair kind

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Speaker 2: of starts to disappear. Well, actually that's just age. No,

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Speaker 2: but you know, look at his shoulders disappearing and.

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Speaker 1: Straight out of the gate. Everyone straight out of the gate,

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Speaker 1: attack ups. This is this is what they do. Okay,

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Speaker 1: when they're insecure, they just go, let's attack him. Keep going,

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Speaker 1: keep going, do your best, not me, keep going, do

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Speaker 1: your best. If you can't say anything nice about people,

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Speaker 1: don't say any thing. That's what Mary would tell you.

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Speaker 1: That's him. He's just that out. Okay. So I'll talk

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Speaker 1: to you, Tiff. Tiff, how's your day going.

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Speaker 3: It's really good. Thank you, thanks for asking. And I

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Speaker 3: think your shoulders look great with the background.

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Speaker 1: Yeah. Thanks. I don't know what's wrong with my background.

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Speaker 2: When you put your arm up, and.

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Speaker 1: Now's interrupting because he's trying to get back in the

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Speaker 1: good books.

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Speaker 2: I'm not getting back any good books. Hey, Now what

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Speaker 2: I mean by you know, when you're hit in a

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Speaker 2: zoom meeting or a teams meeting and the people have

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Speaker 2: fake backgrounds and they just start to shimmy in and

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Speaker 2: out and disappear and re materialize and deep materialize. It's

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Speaker 2: like watching an episode of Star Trek and they're all

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Speaker 2: about to go on away mission. That's that's started to

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Speaker 2: annoy me. Just have your background. And so I decided

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Speaker 2: to buy some backdrops. And obviously, because I took like

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Speaker 2: tech stuff, I thought a space station scene would be good.

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Speaker 2: And that's why it looks more not realistic. You were

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Speaker 2: talking about fooling Mary, But the reality of it is,

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Speaker 2: I'm not shimming in and out because it's not a

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Speaker 2: superimposed background, because it's actually a material picture that's hanging

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Speaker 2: on the wall behind me. And that's why it looks

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Speaker 2: more authentic.

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Speaker 1: All Right, you're better than us. Well done, next Tiff,

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Speaker 1: all right you win? Yeah great, I'll tell you what

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Speaker 1: when that's your biggest problem is fucking worrying about people's

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Speaker 1: backgrounds on Zoom. Your life's good, Champ. Yeah, true, you

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Speaker 1: probably find you had to find a real problem. Uh, tiff,

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Speaker 1: how are you? What is going on on planet Tiffany?

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Speaker 2: Oh? Great stuff, Harts.

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Speaker 3: I got up at the crack of dawn. I had

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Speaker 3: a seven am appointment with my body magician, as I

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Speaker 3: call him, and I got the tick of approval. Things

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Speaker 3: are all tracking well, I'd had that tennis or golfers

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Speaker 3: elbow rubbish. I've already rehabbed it myself. You give me

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Speaker 3: a little pat on the back and sent me on

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Speaker 3: my way.

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Speaker 2: How was that?

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Speaker 1: A couple of things I want to chat about, and

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Speaker 1: one is relates to might relate to Patrick, because you

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Speaker 1: sent me a gift voucher that we're going to talk about.

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Speaker 1: When you say your your magician, what is it? A

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Speaker 1: he or she? Doesn't matter? But before it he Okay?

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Speaker 1: Is he a cairo, a physio, an osteo, or mio?

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Speaker 1: Is he any of the things ending in?

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Speaker 3: Oh? Yeah, he's a sports chiropractic, but he works in

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Speaker 3: a thing called neuro something rehabilitation. He does a lot

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Speaker 3: of it, does a lot of work with the brain

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Speaker 3: and how the brain communicates with the body. He's just

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Speaker 3: I just call him a magician because I don't know.

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Speaker 3: He never does chiropractic adjustments ever.

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Speaker 1: Does he need any more work? Because I'm feeling if

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Speaker 1: you share his name, he's going to be inundated. So

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Speaker 1: I don't know whether or not weishul.

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Speaker 3: He already is in undated. He's hard to get into.

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Speaker 3: All my clients get sent to him at some point

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Speaker 3: because he is the superior being.

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Speaker 1: Well, if he's treating you at seven am, he's busy.

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Speaker 1: He's busy. Patrick, do you have a mechanic of sorts

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Speaker 1: who works on your your sor like? Do you like

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Speaker 1: massage or physio or cairo? Do you like any of

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Speaker 1: that stuff?

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Speaker 2: Not really. I tend to only do it if I'm

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Speaker 2: really falling apart, which luckily not much. I'm so my

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Speaker 2: tai chi. I do tai cheese so often now I

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Speaker 2: teach it, I participate in it, doing lots of core work.

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Speaker 2: We were chatting before the show, so I feel like

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Speaker 2: I'm in pretty good nettle at the moment. Does anyone

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Speaker 2: say that I'm in good nettle at the moment?

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Speaker 4: You and Mary feeling pretty good.

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Speaker 2: I used to get some really chronic pain. When I

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Speaker 2: was at the gym with you, I used to get

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Speaker 2: bad shoulder pain, but that was because.

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Speaker 1: It's a shout out, that's a good ad for my work.

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Speaker 2: Was it as a result of training with you? Was

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Speaker 2: it as a result of sitting in a bloody desk

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Speaker 2: on a stool our radio station when I was working

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Speaker 2: in news at a company Trip and Fox. When I

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Speaker 2: was working for them in the newsroom, he sat on stools,

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Speaker 2: unsupported feet, and the keyboard was sitting in front of you,

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Speaker 2: and the monitors were sunk into the desk, so you hunched.

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Speaker 2: Your natural sitting position was hunched over the monitors. It

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Speaker 2: was horrendously bad ergonomics. So I had chronic shoulder pain

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Speaker 2: for such a long time and went to lots of

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Speaker 2: different people. I don't know if you remember. There was

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Speaker 2: an amazing South African lady who was a Cairo and

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Speaker 2: a physio. I'm trying to think that name.

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Speaker 5: Yeah, it worked at my place, Yeah, absolutely, And what

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Speaker 5: I love about her was that she took a very

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Speaker 5: broad approach, you know, a holistic approach to looking at

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Speaker 5: what was causing your ailments.

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Speaker 2: Because I've been to lots of people and she fixed it.

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Speaker 1: She was good. I should remember her name. She did

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Speaker 1: work in my business. But yeah, no, figure that was

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Speaker 1: twenty five years ago.

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Speaker 2: It was a while, but I and you know what

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Speaker 2: fixed it for me. And this is going to sound weird.

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Speaker 2: She gave me a home traction kit where you put

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Speaker 2: this neck brace on. You had a clip that was

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Speaker 2: fixed to the top of the door, and you put

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Speaker 2: water in a bag, so say three leads of water,

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Speaker 2: so three kilos and it stretched your neck.

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Speaker 1: Well, are you sure that was meant to be rehab

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Speaker 1: or something else?

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Speaker 2: It?

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Speaker 1: Yeah, that's that. Actually, neck traction is a real thing.

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Speaker 1: It's just a it's a be careful thing.

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Speaker 2: Pretty of a professional. Yeah, yeah, yeah, yeah.

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Speaker 1: Don't get your kid to yank on your neck while

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Speaker 1: you're lying on the kitchen table or something.

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Speaker 2: Now, it was under quite strict medical supervision, but it

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Speaker 2: fixed everything. Just stretching the old neck was great.

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Speaker 1: Now, before we jump into the show proper, I'll go on.

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Speaker 2: No, it's just gonna because it was very you know me,

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Speaker 2: I give a very long winded answer. So no, I

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Speaker 2: don't have a regular person who manipulates my joints and

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Speaker 2: touches me all over. But I'm taking applications after the show.

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Speaker 1: Okay, just shout out to Patrick if you feel like

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Speaker 1: you might be that guy TIV. You sent me a

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Speaker 1: message this week to say that you put on some

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Speaker 1: inordinate amount of muscle over the last month. You've got

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Speaker 1: an inbody or a body contest done. Are you feeling

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Speaker 1: quite powerful and strong?

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Speaker 3: I'm feeling quite good doing strength training and I'm loving it.

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Speaker 3: And it's such a nice shift. And you know, as

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Speaker 3: a female that's always been very athletic and very borderline obsessive.

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Speaker 3: But you know, I loved that high intensity, calorie burning,

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Speaker 3: sweatfesting type of training. It's been a real nice switch.

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Speaker 3: And what comes with that is kind of wanting to

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Speaker 3: see the scales go up knock down.

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Speaker 1: That's hilarious. We watch your I would not ask any

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Speaker 1: other woman this but you, because I know you're happy

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Speaker 1: with it. What what's your current weight?

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Speaker 3: Sixty three?

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Speaker 1: How do you feel it that? Yeah?

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Speaker 2: Good?

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Speaker 3: Good. And the thing is like, I want to I

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Speaker 3: want to put lower body muscle on and the reality

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Speaker 3: is I can't do that staying at the same weight

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Speaker 3: because it's just physiologically not possible. I can't lose that

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Speaker 3: amount of weight to put it on in fat in

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Speaker 3: body fat, it'd be too lower body fat.

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Speaker 1: Yeah, well you can't. Yeah, I mean, what's that?

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Speaker 2: Sorry, Greg, I had to all aids.

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Speaker 3: If one sixty just under one sixty eight.

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Speaker 2: Oh wow, I'm trying to do this s stare because

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Speaker 2: I'm one sixty nine and seventy kilos. It's just yeah,

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Speaker 2: that's that's that seems really light to me. But obviously

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Speaker 2: your shape is totally different. Yeah.

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Speaker 1: No, she doesn't look I mean not, I mean she

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Speaker 1: looks jacked, you know. She looks like an athlete, which

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Speaker 1: is it's good because that's what she wants to look like.

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Speaker 1: So up and Grandpa in the middle of the screen.

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Speaker 1: My screen anyway, is eighty kilos, which for me is

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Speaker 1: borderline anorexic. I haven't been this light since I was

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Speaker 1: about twelve, not even probably eleven. How funny is that?

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Speaker 1: People are going, Oh, that's funny. I got No, that's

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Speaker 1: actually true. I probably weighed this when I was about

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Speaker 1: eleven or twelve.

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Speaker 2: But do you remember sitting in a boardroom in an

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Speaker 2: advertising agency with me when we were working on a

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Speaker 2: project that didn't quite get off the ground, but it

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Speaker 2: was just helping people lose weights, and there were a

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Speaker 2: number of people, and one of the directors of the

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Speaker 2: agency was a kind of a bit of a bigger guy,

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Speaker 2: and we were all talking about, you know, collectively losing weight.

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Speaker 2: So the idea of the project was instead of losing

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Speaker 2: weight individually, you set up a team of people and

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Speaker 2: you collectively lost weight, and that way it was more

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Speaker 2: of a team effort to help encourage people. But I

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Speaker 2: remember saying whilst we were sitting there, saying, yeah, I

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Speaker 2: like to lose a couple of kilos, and I was,

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Speaker 2: and this guy got kind of really tore shreds off me, saying, oh,

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Speaker 2: that's ridiculous. You don't need to lose any ways. But

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Speaker 2: it's a very personal journey when we look at weight

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Speaker 2: loss and one kilo to me is saying, oh, man,

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Speaker 2: I just wish I could lose one or two kilos

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Speaker 2: in the grand scale of things. Because a good friend

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Speaker 2: of mine we were talking about losing weight and he's

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Speaker 2: lost about forty kilos. He's a very big person and

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Speaker 2: it's a massive amount to lose for him, but relative

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Speaker 2: to his size, he's got a little bit more of

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Speaker 2: a journey to go, and he's doing really, really well

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Speaker 2: because he's losing it over a span of time, but

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Speaker 2: it is a personal journey and it's and you know,

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Speaker 2: sometimes people forget that, you know, and you almost face

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Speaker 2: ridicule if you say, if you if you present to

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Speaker 2: somebody who looks quite fit, but you feel that you'd

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Speaker 2: like to lose a little bit, without being obsessive, it

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Speaker 2: still is how you feel in your own skin.

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Speaker 1: Yeah, yeah, I mean it's I remember exactly what you're

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Speaker 1: talking about and who you're talking about. And what's tricky is,

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Speaker 1: especially in twenty twenty five, you can't almost talk about weight.

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Speaker 1: You know, I can, and I do. But the problem

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Speaker 1: is that when we are talking about physiology and health

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Speaker 1: and body composition and subcutaneous fat and visceral fat and

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Speaker 1: diabetes and all of the things that kind of float

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Speaker 1: around how your body works and what your body is

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Speaker 1: made up of, and you know, people almost take that

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Speaker 1: as an emotional or psychological judgment or attack. Whereas I'm

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Speaker 1: speaking as an exercise scientist and I'm talking about data

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Speaker 1: and science, and so without being rude, I don't give

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Speaker 1: a fuck what people way. I don't give a fuck

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Speaker 1: what they look like. I care about how well their

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Speaker 1: body works. But like it or not, there is a

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Speaker 1: relationship between weight and how much body fat a person

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Speaker 1: is carrying, and they're likely health outcomes. Now that's not

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Speaker 1: a guess or a stab or an insult, but when

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Speaker 1: you point that out, people would rather find a way

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Speaker 1: to get insulted than enlightened, right, And they're like, oh,

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Speaker 1: you're fucking fat shaming. I'm like, I was the fattest

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Speaker 1: kid in my school. I know what it's like to

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Speaker 1: be obese. I know what it's like to be called jumbo.

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Speaker 1: I am not fat shaming. I'm fucking talking about health

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Speaker 1: and wellness and coming from a place of literal personal experience,

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Speaker 1: you know. And there's that kind of trying to navigate

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Speaker 1: that road at the moment publicly when you're talking. It's

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Speaker 1: tricky because in many ways it's easier to find a

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Speaker 1: way to be offended than it is to take it

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Speaker 1: on board as just you know, science or information and

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Speaker 1: do something positive with it.

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Speaker 2: The AMA, the Australian Medical Association, a few years ago

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Speaker 2: were trying to encourage doctors to be more blunts with

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Speaker 2: the language they were using and not to gloss over

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Speaker 2: the notion that someone might be morbidly obese. And the

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Speaker 2: thing is it's such a difficult journey for different people,

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Speaker 2: for lots and lots and lots of reasons. And I

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Speaker 2: guess that the how do you walk that tight rope

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Speaker 2: of glossing over it to protect the person's mental well

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Speaker 2: being but also to you know, to say to them

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Speaker 2: that you potentially are putting your life at risk by

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Speaker 2: maintaining the current status status quo. So I don't know

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Speaker 2: that I'd want to be in that space, but it's

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Speaker 2: certainly a challenge in every GP and health professional faces.

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Speaker 1: Yeah, and I think, I mean, it is tough because

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Speaker 1: of course you care about people, and you have empathy

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Speaker 1: and awareness, and you don't want to make people feel bad.

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Speaker 1: But also I don't want people that I care about,

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Speaker 1: or even people that I don't know that matter. I

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Speaker 1: don't want them to wake up in five or ten

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Speaker 1: years and have life threatening health conditions because everyone was

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Speaker 1: too concerned with their their feelings for the next thirty seconds.

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Speaker 1: It's like, I care about your feelings, but it's not

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Speaker 1: my job to manage your feelings or work around your emotions.

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Speaker 1: I'm literally sharing practical, real world information with you, and

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Speaker 1: if you don't want to listen, that's fine. If you

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Speaker 1: get upset. That's also fine. I don't want you to

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Speaker 1: be upset. But I'm not going to apologize for just

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Speaker 1: saying what I know. Like, I've literally worked with tens

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Speaker 1: of thousands of bodies, so I'm not guessing you know.

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Speaker 1: This is not some random theory and it's it's funny.

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Speaker 1: We live in that time where where did Tiff go?

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Speaker 1: By the way, Patrick, can hear?

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Speaker 2: We can hear, yeah, we can. We're missing you. What's

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Speaker 2: going on?

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Speaker 3: Well, my screen has frozen, so everything and I can't

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Speaker 3: move the cursor or anything, so I can hear you,

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Speaker 3: but everything's frozen on my computer screen.

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Speaker 2: Don't touch anything. Was doing what you're doing?

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Speaker 3: Yeah?

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Speaker 1: Yeah, you just talk from behind that black curtain. I

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Speaker 1: don't know what I was going to say, but let's

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Speaker 1: talk about Let's talk about the stuff that you're the

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Speaker 1: best at, Patrick James.

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Speaker 2: I've got a nice segue to that. Because a lot

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Speaker 2: more people are turning to AI for health advice, And

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Speaker 2: there was a really interesting story about a man who

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Speaker 2: became hospitalized with psychiatric psychiatric symptoms following getting after getting

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Speaker 2: advice from AI. So this guy was wanting to reduce

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Speaker 2: his salt intake. Okay, so he started this whole chat

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Speaker 2: with the chatbot, and he decided to set up his

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Speaker 2: own health plan and thought, I've got to reduce my

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Speaker 2: salt intake. So he basically found a substitute by talking

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Speaker 2: to chat JPT and it suggested sodium instead of sodium

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Speaker 2: chloride and you can swap them around if you're going

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Speaker 2: to be cleaning a bath tub but yesting it. So yeah,

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Speaker 2: he went and bought this stuff online and thought, oh,

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Speaker 2: I'm going to reduce my salting take with it, but

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Speaker 2: with different sort of salt. So he's just eating this

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Speaker 2: over three months he's decided to take this on and

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Speaker 2: then after that time he started, he ended up in

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Speaker 2: the emergency department with paranoid delusions and he believed that

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Speaker 2: his neighbor was trying to poison him. In fact, he

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Speaker 2: was poisoning himself. And that's because he'd listened to advice

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Speaker 2: health advice, and that the chatbot didn't really discern that

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Speaker 2: it was about him taking it. It's just well, what's

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Speaker 2: an alternative to salt, and that's what ended up happening.

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Speaker 2: So yeah, it's a really timely reminded that everything that

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Speaker 2: you see may not necessarily be the right sort of

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Speaker 2: advice when you jump into a you know, you chat,

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Speaker 2: GPTs or whatever it is that you're using. So that

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Speaker 2: was a very vivid ex you.

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Speaker 1: Know, that's that's bloody amazing. I mean imagine, yeah, well

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Speaker 1: that that's one of the dangers, isn't it. I mean,

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Speaker 1: that's a danger of I think how much, how much

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Speaker 1: we pay attention to rely on trust and I think

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Speaker 1: everything even though you know, I think we both agree

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Speaker 1: that AI has got unbelievable potential and unbelievable capacity to

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Speaker 1: be of value. It's also you know, it can also

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Speaker 1: do untold harm if not used the right way, and

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Speaker 1: if perhaps trusted in inverted commas when it shouldn't be trusted.

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Speaker 2: So oh yeah, And there's a lot of AI slop

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Speaker 2: out there as well. And in fact Wikipedia, I don't

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Speaker 2: know if you use Wikipedia much, but I tend to

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Speaker 2: find it still pops up and I have a bit

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Speaker 2: of a read, you know, whether it's a profile or

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Speaker 2: something like that. But they're battling AI at the moment

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Speaker 2: because Wikipedia is managed by a whole stack of volunteers,

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Speaker 2: and a lot of them a pandemics. So these people

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Speaker 2: who are really passionate about keeping the content out there.

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Speaker 2: So I guess it's like the Internet version of the

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Speaker 2: Encyclopedia Britannica. You know, it's the traditional encyclopedic format to

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Speaker 2: be able to give you information on a whole host

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Speaker 2: of things. But what they've always taken a lot of

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Speaker 2: pride in is the way that they fact check and

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Speaker 2: the way that the volunteers try to make sure that

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Speaker 2: the content that's on Wikipedia is proper, you know, whether

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Speaker 2: it's scientifically based or information based, it's you know, it's

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Speaker 2: a rigid way to kind of you know, keep the

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Speaker 2: system in place. But the problem now is that this

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Speaker 2: AI slop is being pushed out and anybody can contribute,

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Speaker 2: but then there's the fact checking that goes with it.

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Speaker 2: So they call the people who moderator called wikipedians, and

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Speaker 2: they go through all of this and what they're trying

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Speaker 2: they literally have to read the written articles, they have

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Speaker 2: to go through and they're trying to monitor what's being

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Speaker 2: proposed and they're getting good at finding the crap stuff

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Speaker 2: and there's a process that they go through, but they

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Speaker 2: are really working hard and typically articles that get flagged

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Speaker 2: then have a seven day discussion period. So it's a

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Speaker 2: pierce peer thing goes out other people in the community,

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Speaker 2: members who moderators, and they determine whether or not the

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Speaker 2: sites should be you know, should they should delete the article.

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Speaker 2: So they feel it's quite robust, but they're kind of

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Speaker 2: fighting a bit of an uphill battle at the moment

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Speaker 2: to try to keep Wikipedia as you know, AI free

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Speaker 2: as possible. But there's so much slop. I read an

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Speaker 2: article a little while ago that said fifty one percent

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Speaker 2: of all content on the Internet now is AI generated.

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Speaker 2: That scared the shit out of me. That's pretty scary

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Speaker 2: to think of that sort of content. But maybe at

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Speaker 2: the moment, Wikipedia seems like they're doing what they can

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Speaker 2: through a whole horde of volunteers.

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Speaker 1: Overall, just one word or the other. Are you pro

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Speaker 1: or anti AI? Just overall? P Yeah? Cool, Tiff, where

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Speaker 1: you've been?

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Speaker 3: I fell fell off My Carl computer just shut down

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Speaker 3: and said we've needed to shut you down.

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Speaker 2: You didn't.

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Speaker 1: Patrick was just we've been talking about you for three minutes.

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Speaker 1: Tiff actually fell off the podcast. Now she's gone, I'll

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Speaker 1: tell you what. She's having Internet problems. She actually dropped

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Speaker 1: right out. There was just Patrick and I on the

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Speaker 1: screen for the moment. It's a good thing I'm recording

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Speaker 1: from this end, isn't it.

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Speaker 2: Yeah, that's true, it certainly is. Tif's flashing in my window.

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Speaker 1: Well, there's a thought I'm not even gonna. I'm not

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Speaker 1: even gonna. I don't I reckon yep, Oh, so many things,

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Speaker 1: you know, Like I have this thing where I play

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Speaker 1: this verbal scenario out in my head on fast forward

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Speaker 1: before I'm going to say it, and on rare occasions

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Speaker 1: I choose not to say it.

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Speaker 2: Today's that well, except for the stuff we've had to

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Speaker 2: edit out of the show. At the start of the

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Speaker 2: show because it's been heavily edited listeners, it started off

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Speaker 2: pretty well.

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Speaker 1: That's because I went very dark, and I'm like, I

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Speaker 1: self edited.

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Speaker 2: Actually talking about dark. I think I feel I need

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Speaker 2: to work this into the conversation now scenes we're talking

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Speaker 2: about AI and Dark. You know the problem with AI,

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Speaker 2: and we talked about this in a previous show where

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Speaker 2: I did some testing with AI and I asked to

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Speaker 2: get some image generation and you might recall that I

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Speaker 2: wanted to see what would happen if I asked AI

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Speaker 2: to generate a picture of Alexander the Great with his lover,

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Speaker 2: and the initial pictures were of Alexander the Great with

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Speaker 2: a female and then we now know except for Gemini,

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Speaker 2: which was interesting because Gemini is Google's AI, and it

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Speaker 2: pulled up a whole lot of factual information about the

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Speaker 2: fact that it's thought that Alexander the Great had a

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Speaker 2: male lover. And then when I got Meta to try

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Speaker 2: to generate the picture, when I corrected it and said

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Speaker 2: I no, no, I don't want a female lover, I

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Speaker 2: want a male lover, it refused to generate it, saying

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Speaker 2: it was inappropriate content. So it's interesting because when we

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Speaker 2: think about who programs these AI and what are the

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Speaker 2: biases that are built into it. You know, if you

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Speaker 2: just type in you know young female or young male,

435
00:23:21,760 --> 00:23:25,040
Speaker 2: or you type in you know man working, generally, it's

436
00:23:25,080 --> 00:23:27,639
Speaker 2: going to be a white person. It's not going to

437
00:23:27,680 --> 00:23:30,199
Speaker 2: be a person of Asian origin or a person with

438
00:23:30,560 --> 00:23:33,840
Speaker 2: dark skin. So sometimes there's been a lot of biases

439
00:23:33,880 --> 00:23:36,120
Speaker 2: that have been picked up. But what creeped me out

440
00:23:36,160 --> 00:23:40,200
Speaker 2: a lot reading this article is Meta had some rules

441
00:23:40,320 --> 00:23:41,800
Speaker 2: that they've been picked up on. So there was an

442
00:23:41,840 --> 00:23:45,120
Speaker 2: internal investor in an investigation by Reuters, the news service,

443
00:23:45,480 --> 00:23:48,439
Speaker 2: and they reckon that the social media giant had a

444
00:23:48,520 --> 00:23:52,840
Speaker 2: rule for their chatbots, which permitted them to have a

445
00:23:53,400 --> 00:23:59,560
Speaker 2: provocative kind of behavior when talking to children, including issues

446
00:23:59,560 --> 00:24:05,000
Speaker 2: around sex. And so there were documents talking about what

447
00:24:05,160 --> 00:24:09,920
Speaker 2: was appropriate behavior and what wasn't and they were condoning, effectively,

448
00:24:11,160 --> 00:24:14,400
Speaker 2: the notion that the the the AI chatbot could engage

449
00:24:14,440 --> 00:24:19,879
Speaker 2: in child conversations with romantic or sensual information related to that.

450
00:24:20,000 --> 00:24:23,440
Speaker 2: So Reuters said that basically the document that it saw

451
00:24:23,480 --> 00:24:27,679
Speaker 2: from Meta discussed the standards that its guidelines were based on,

452
00:24:28,280 --> 00:24:32,800
Speaker 2: and the chatbot this is we're talking Facebook, WhatsApp, Instagram,

453
00:24:33,160 --> 00:24:38,400
Speaker 2: And they confirmed the document's authenticity and said that effectively,

454
00:24:39,040 --> 00:24:42,280
Speaker 2: it could say things to children about how so an

455
00:24:42,280 --> 00:24:45,919
Speaker 2: eight year old could have the chatbot say your body

456
00:24:46,200 --> 00:24:50,679
Speaker 2: looks in a certain way, it could in a sensual way. Effectively,

457
00:24:50,760 --> 00:24:53,439
Speaker 2: is how it was looking at And so if an

458
00:24:53,480 --> 00:24:56,000
Speaker 2: eight year old asked how its body, how their body looked,

459
00:24:56,240 --> 00:24:58,639
Speaker 2: they could say it looks like a masterpiece, you know,

460
00:24:58,720 --> 00:25:01,600
Speaker 2: a sensual masterpiece. There was some really creepy kind of

461
00:25:01,680 --> 00:25:06,320
Speaker 2: terminology in there. And the concern is that this was

462
00:25:06,440 --> 00:25:11,040
Speaker 2: vetted internally by the people who are providing the chatbots,

463
00:25:11,080 --> 00:25:13,840
Speaker 2: and they're saying, well, yeah, it's okay for the AI

464
00:25:13,960 --> 00:25:17,760
Speaker 2: chatbot to talk to children about sexual things or sensual things,

465
00:25:18,280 --> 00:25:23,159
Speaker 2: but then when it was flagged by Reuters, they removed it.

466
00:25:23,520 --> 00:25:26,800
Speaker 2: So the thing is they have ethicists who work for them,

467
00:25:27,240 --> 00:25:29,679
Speaker 2: and they vetted this and said it was okay, and

468
00:25:29,720 --> 00:25:33,800
Speaker 2: then Reuters pulls out an article and they say, well, actually,

469
00:25:34,000 --> 00:25:37,280
Speaker 2: what you've got here isn't good. So the term that

470
00:25:37,400 --> 00:25:40,919
Speaker 2: was used this is a shirtless eight year old. Every

471
00:25:41,000 --> 00:25:45,400
Speaker 2: inch ofview is a masterpiece. Is the terminology that they

472
00:25:45,440 --> 00:25:48,479
Speaker 2: said was okay as far as Meta was concerned. And

473
00:25:48,520 --> 00:25:50,800
Speaker 2: now of course it's been picked up by Reuters and

474
00:25:50,960 --> 00:25:53,280
Speaker 2: they're going a little bit more strict on that policy.

475
00:25:53,640 --> 00:25:57,560
Speaker 2: But this is the frightening thought that who is training

476
00:25:57,600 --> 00:26:01,119
Speaker 2: the AI and what's the background, what are their standards,

477
00:26:01,160 --> 00:26:04,560
Speaker 2: what are their morals, what are their values? And you know,

478
00:26:04,640 --> 00:26:07,480
Speaker 2: when you're pulling all this information in and then you

479
00:26:07,520 --> 00:26:10,800
Speaker 2: know there's a bias that then gets adapted to the AI,

480
00:26:11,320 --> 00:26:14,000
Speaker 2: which is then born out in the results that it's

481
00:26:14,040 --> 00:26:15,719
Speaker 2: giving us.

482
00:26:16,160 --> 00:26:22,440
Speaker 1: Yeah, it's like who, as you alluded, Like who says

483
00:26:22,840 --> 00:26:26,760
Speaker 1: that that's okay? Like ultimately there must be someone somewhere

484
00:26:27,760 --> 00:26:30,159
Speaker 1: giving the green light or the thumbs up or whatever.

485
00:26:30,200 --> 00:26:34,679
Speaker 1: The whatever the equivalent is, the virtual equivalent, say this

486
00:26:34,840 --> 00:26:39,760
Speaker 1: is that stuff? It actually makes me angry. It makes

487
00:26:39,840 --> 00:26:44,679
Speaker 1: me quite fucked off that that's even a thing that

488
00:26:45,720 --> 00:26:48,800
Speaker 1: needs to or not needs to, but that exists. Is

489
00:26:49,480 --> 00:26:56,240
Speaker 1: anything anything around the abuse or exploitation or of kids.

490
00:26:56,359 --> 00:26:58,400
Speaker 1: I don't know why, I just have this. It fucking

491
00:26:58,440 --> 00:27:02,520
Speaker 1: annoys me a lot. And adults who perpetuate that or

492
00:27:02,520 --> 00:27:07,840
Speaker 1: facilitate or allow or promote that, fuck you, all of you,

493
00:27:07,920 --> 00:27:09,320
Speaker 1: like I just don't like it.

494
00:27:09,800 --> 00:27:13,840
Speaker 2: And on the flip side, there's a few Australian businesses

495
00:27:13,840 --> 00:27:15,840
Speaker 2: I don't know if you've seen this in the media recently,

496
00:27:16,160 --> 00:27:21,600
Speaker 2: where businesses that potentially might do say early childhood photography,

497
00:27:22,200 --> 00:27:25,400
Speaker 2: so they take photos of kids with mums and babes

498
00:27:25,400 --> 00:27:27,879
Speaker 2: and things like that. Well, there's been a couple of

499
00:27:27,880 --> 00:27:31,360
Speaker 2: instances where businesses have been shut out of their social

500
00:27:31,440 --> 00:27:36,200
Speaker 2: media because the imagery has been flagged by the AI

501
00:27:36,520 --> 00:27:40,600
Speaker 2: as inappropriate and potentially child pornography, when in fact it wasn't.

502
00:27:41,000 --> 00:27:44,000
Speaker 2: But there's no appeal process that seems to be robust

503
00:27:44,080 --> 00:27:46,239
Speaker 2: enough to have a real human look at it. So

504
00:27:46,280 --> 00:27:50,080
Speaker 2: there have been businesses that have been said that they

505
00:27:50,119 --> 00:27:53,679
Speaker 2: do all their promotion to all of their customers online

506
00:27:53,760 --> 00:27:56,960
Speaker 2: and they rely on Facebook, they rely on Instagram, and

507
00:27:57,000 --> 00:27:59,680
Speaker 2: they've been booted off for having inappropriate images. And I

508
00:27:59,680 --> 00:28:02,760
Speaker 2: guess that's where you know, Wikipedia is doing it right

509
00:28:02,880 --> 00:28:07,480
Speaker 2: with the human oversight. But as these mega companies just

510
00:28:07,520 --> 00:28:10,040
Speaker 2: get bigger and bigger and bigger and are using AI

511
00:28:10,359 --> 00:28:15,320
Speaker 2: to decide whether TIFF's photograph as a child, because she

512
00:28:15,440 --> 00:28:17,280
Speaker 2: wants to show what she looked like as a kid

513
00:28:17,280 --> 00:28:19,440
Speaker 2: and what she looks like as an adult, may be

514
00:28:19,480 --> 00:28:23,359
Speaker 2: flagged as inappropriate. Well, your social media could be switched off,

515
00:28:23,520 --> 00:28:25,520
Speaker 2: you know, if it's a day at the beach and

516
00:28:25,600 --> 00:28:28,560
Speaker 2: Tiff shows herself as a kid, you know of running

517
00:28:28,600 --> 00:28:30,159
Speaker 2: into the water or running out of the water with

518
00:28:30,280 --> 00:28:33,000
Speaker 2: dad holding her hand, or something that could potentially be

519
00:28:33,040 --> 00:28:35,320
Speaker 2: flagged and then your social media will be switched off

520
00:28:35,359 --> 00:28:39,880
Speaker 2: instantly overnight. And then what's the process to then go through?

521
00:28:40,280 --> 00:28:43,080
Speaker 2: And in fact, the a Triple C is looking that

522
00:28:43,160 --> 00:28:48,200
Speaker 2: the Australian Competition and Consumer Commission is looking at putting

523
00:28:48,280 --> 00:28:53,600
Speaker 2: pressure and potentially calling for legislation to force these big

524
00:28:53,640 --> 00:28:57,040
Speaker 2: tech companies to have a better and more robust system

525
00:28:57,040 --> 00:29:00,400
Speaker 2: of appeal that's not going just through an automated system,

526
00:29:00,480 --> 00:29:04,479
Speaker 2: but where there is rapid response, not weeks and months

527
00:29:04,480 --> 00:29:07,120
Speaker 2: of response time to try to get your social media

528
00:29:07,160 --> 00:29:10,160
Speaker 2: back up again if it accidentally gets flagged. So I mean,

529
00:29:10,200 --> 00:29:13,240
Speaker 2: it's problematic on both sides. And that's the challenge, isn't it.

530
00:29:13,360 --> 00:29:15,560
Speaker 2: When you take humans out of the equation and you're

531
00:29:15,600 --> 00:29:19,800
Speaker 2: relying on an algorithm, then that's where it becomes a problem.

532
00:29:19,880 --> 00:29:22,000
Speaker 2: And if they're taking you, I mean, and the other

533
00:29:22,040 --> 00:29:24,720
Speaker 2: thing I guess is, you know, at the moment, Facebook

534
00:29:24,760 --> 00:29:29,680
Speaker 2: is pushing businesses to pay now to have a you know,

535
00:29:29,800 --> 00:29:31,640
Speaker 2: to be able to have a kind of a subscription

536
00:29:31,760 --> 00:29:36,560
Speaker 2: process to make it easier for them to validate their business.

537
00:29:36,840 --> 00:29:38,840
Speaker 2: So if you want to validate your business, you can

538
00:29:38,880 --> 00:29:41,560
Speaker 2: pay for that to happen now. And I guess there

539
00:29:41,680 --> 00:29:43,240
Speaker 2: was going to be a point at which they wanted

540
00:29:43,280 --> 00:29:45,880
Speaker 2: to get some money for you know, all those hundreds

541
00:29:45,920 --> 00:29:49,959
Speaker 2: of millions of sites out there that rely on social

542
00:29:50,000 --> 00:29:53,360
Speaker 2: media for marketing. The reality of it is when we

543
00:29:53,440 --> 00:29:55,920
Speaker 2: get something for free, we lose control of our data

544
00:29:55,960 --> 00:29:58,880
Speaker 2: and information. Because you know, everything we think is free,

545
00:29:58,880 --> 00:30:02,920
Speaker 2: whether it's Gmail or whatever it is, Facebook and Instagram,

546
00:30:03,360 --> 00:30:05,600
Speaker 2: it's not really free. It's just giving them all the

547
00:30:05,640 --> 00:30:07,520
Speaker 2: content that we put up there.

548
00:30:10,160 --> 00:30:14,640
Speaker 1: Wow, that was quite the monologue. Fucking hell. I could

549
00:30:14,640 --> 00:30:16,640
Speaker 1: have gone and made lunch, hat it grown a beard

550
00:30:16,680 --> 00:30:17,920
Speaker 1: out of shave and come back.

551
00:30:18,160 --> 00:30:22,000
Speaker 2: You actually listen at all, Like I was listening.

552
00:30:22,080 --> 00:30:23,640
Speaker 1: I was waiting for a break.

553
00:30:25,200 --> 00:30:25,600
Speaker 2: It's good.

554
00:30:26,880 --> 00:30:30,400
Speaker 1: No, no, no, it's all good. It's you know, here's

555
00:30:30,480 --> 00:30:31,600
Speaker 1: the absolute truth.

556
00:30:31,720 --> 00:30:31,880
Speaker 2: Right.

557
00:30:31,920 --> 00:30:35,560
Speaker 1: I shouldn't say this, but everything you said makes sense. One,

558
00:30:38,240 --> 00:30:42,440
Speaker 1: but this kind of exploitation. I don't know why, but

559
00:30:42,480 --> 00:30:48,000
Speaker 1: there's something in me. It makes me fucking angry the

560
00:30:48,040 --> 00:30:52,080
Speaker 1: way that people it's not just kids, but it's anyone

561
00:30:52,120 --> 00:30:56,160
Speaker 1: who can't really protect themselves and anyone you know, like

562
00:30:56,240 --> 00:30:59,280
Speaker 1: my mum who like people wring my mum regularly and

563
00:30:59,360 --> 00:31:03,239
Speaker 1: try and scammer. It makes me so angry, which I

564
00:31:03,240 --> 00:31:05,360
Speaker 1: know is not a solution, and it's probably a flow

565
00:31:05,440 --> 00:31:09,680
Speaker 1: of mine, but I just get incensed and I just

566
00:31:09,760 --> 00:31:12,760
Speaker 1: want to, Like, honestly, I want to change the fucking topic.

567
00:31:12,880 --> 00:31:15,360
Speaker 1: That's what I feel like. But I think it's good

568
00:31:15,360 --> 00:31:18,320
Speaker 1: that we talk about it. That's the truth. But yeah,

569
00:31:18,360 --> 00:31:22,040
Speaker 1: that stuff that kind of pushes a button in me,

570
00:31:22,800 --> 00:31:23,840
Speaker 1: you Patrick or no.

571
00:31:24,400 --> 00:31:26,720
Speaker 2: Oh, absolutely it does, absolutely.

572
00:31:27,640 --> 00:31:30,840
Speaker 1: Yeah, I know I'm the problem. But yeah, it's like if.

573
00:31:30,720 --> 00:31:34,160
Speaker 2: You ask me the question earlier, AI good or bad?

574
00:31:34,480 --> 00:31:36,200
Speaker 2: So I'm going to post it to you and Tiff

575
00:31:36,600 --> 00:31:38,320
Speaker 2: Crago AI good or bad?

576
00:31:38,720 --> 00:31:41,440
Speaker 1: Yeah, that is a good question that I asked it you.

577
00:31:43,360 --> 00:31:48,440
Speaker 1: I think overall, I think overall it's an amazing tool.

578
00:31:48,480 --> 00:31:51,160
Speaker 1: So I'm going to say good. But my caveat is

579
00:31:51,720 --> 00:31:55,000
Speaker 1: I don't think AI of itself is good or bad

580
00:31:55,160 --> 00:31:58,400
Speaker 1: in the sense that it depends what we do with it. See,

581
00:31:58,440 --> 00:32:01,640
Speaker 1: I know that I can give you a bunch of

582
00:32:01,680 --> 00:32:04,720
Speaker 1: tools and resources, and because I know you, you're going

583
00:32:04,800 --> 00:32:06,560
Speaker 1: to do You're either not going to use them or

584
00:32:06,600 --> 00:32:09,080
Speaker 1: you're going to do something positive with them, right because

585
00:32:09,120 --> 00:32:11,640
Speaker 1: I know you and I trust you, and I know

586
00:32:11,760 --> 00:32:15,520
Speaker 1: your values. But give those same tools and resources like

587
00:32:15,600 --> 00:32:18,880
Speaker 1: your knowledge, right, You've You've got pretty expansive knowledge in

588
00:32:18,920 --> 00:32:22,320
Speaker 1: their space. Somebody with your knowledge who doesn't have your

589
00:32:22,400 --> 00:32:26,160
Speaker 1: values or internal sat NAV, they could do some horrible shit.

590
00:32:26,720 --> 00:32:29,640
Speaker 1: So it's not so much about the AI or the tools,

591
00:32:30,160 --> 00:32:34,480
Speaker 1: or the technical capacity of whatever, or the technological capacity.

592
00:32:34,880 --> 00:32:38,840
Speaker 1: It's about who's doing what with it. Like I would gladly,

593
00:32:39,000 --> 00:32:41,240
Speaker 1: I would trust you with pretty much anything. I would

594
00:32:41,280 --> 00:32:44,320
Speaker 1: go well, Patrick's doing it, So I'm fine, But there

595
00:32:44,320 --> 00:32:46,520
Speaker 1: are most people or many people that I wouldn't, you

596
00:32:46,520 --> 00:32:49,160
Speaker 1: know what I mean. So I still think it comes

597
00:32:49,200 --> 00:32:52,800
Speaker 1: back to the user. And as you said, nothing's for nothing.

598
00:32:52,920 --> 00:32:56,000
Speaker 1: So when people are letting you have this resource or

599
00:32:56,000 --> 00:32:59,280
Speaker 1: this tool or whatever for free, it ain't for free.

600
00:33:00,080 --> 00:33:02,600
Speaker 2: There's a tech company in the US called in Vision

601
00:33:03,040 --> 00:33:06,560
Speaker 2: and they work with kind of disability technology and using

602
00:33:06,600 --> 00:33:09,400
Speaker 2: tech to help people with disabilities. And they've partnered with

603
00:33:09,640 --> 00:33:12,840
Speaker 2: a company that makes glasses called Solos and they've just

604
00:33:12,920 --> 00:33:16,880
Speaker 2: launched a new camera equipped called the Alley's Solos Glasses.

605
00:33:17,280 --> 00:33:20,520
Speaker 2: And what they they've made is a set of glasses

606
00:33:20,520 --> 00:33:22,480
Speaker 2: with cameras built into them for people who are vision

607
00:33:22,520 --> 00:33:26,280
Speaker 2: impaired and blind. And what they do is they can

608
00:33:26,680 --> 00:33:30,800
Speaker 2: translate text, they can describe the surroundings in real time,

609
00:33:30,960 --> 00:33:35,080
Speaker 2: search the web, recognize people object signs, so if you're

610
00:33:35,160 --> 00:33:38,080
Speaker 2: vision impaired, and they have speakers built into the arms

611
00:33:38,200 --> 00:33:42,080
Speaker 2: of the glasses, so someone who's vision impaired can effectively

612
00:33:42,200 --> 00:33:44,680
Speaker 2: use these to decode the life around them. You know,

613
00:33:44,720 --> 00:33:46,520
Speaker 2: they can be walking down the street, they can use

614
00:33:46,520 --> 00:33:49,440
Speaker 2: a navigation it's three meters away, but watch out as

615
00:33:49,440 --> 00:33:51,479
Speaker 2: a fire hydrant on the right hand side, you know,

616
00:33:51,560 --> 00:33:55,719
Speaker 2: to your right. It's literally describing the world around them

617
00:33:55,800 --> 00:33:59,240
Speaker 2: and it recognizes like all these Craig Harper quick change over,

618
00:33:59,360 --> 00:34:01,600
Speaker 2: go to the other side out of the street, all

619
00:34:01,640 --> 00:34:07,719
Speaker 2: these tears hurtful. But isn't that amazing? And so there's

620
00:34:07,880 --> 00:34:10,920
Speaker 2: the practical example of this tech. Now they've got a

621
00:34:11,000 --> 00:34:14,640
Speaker 2: they're doing a limited release US about four hundred bucks

622
00:34:14,640 --> 00:34:17,000
Speaker 2: at the moment. They're going to end up being I

623
00:34:17,000 --> 00:34:20,680
Speaker 2: think seven hundred dollars US and a couple of different

624
00:34:20,719 --> 00:34:23,320
Speaker 2: frame sizes and all that sort of stuff. But that

625
00:34:23,520 --> 00:34:27,440
Speaker 2: uses chet chepte before and they use an AI assistant

626
00:34:27,840 --> 00:34:31,840
Speaker 2: called Ali, and it's just going to be a groundbreaker

627
00:34:31,880 --> 00:34:34,319
Speaker 2: for people who are vision impaired, and I think more

628
00:34:34,360 --> 00:34:37,520
Speaker 2: so I know people. You know a friend of mine

629
00:34:37,640 --> 00:34:41,320
Speaker 2: who went blind progressively in his late teenage years, and

630
00:34:42,280 --> 00:34:44,960
Speaker 2: he's a real uh you know, he's a real petrol

631
00:34:45,000 --> 00:34:47,759
Speaker 2: head too, So it's it's amazing he's got these He's

632
00:34:47,800 --> 00:34:50,800
Speaker 2: got this amazing car that he's helping or he's getting,

633
00:34:51,440 --> 00:34:54,680
Speaker 2: you know, fixed up, and it's looking phenomenal, but he

634
00:34:54,719 --> 00:34:58,680
Speaker 2: can't see the car abscribed to him. But to lose

635
00:34:58,680 --> 00:35:02,480
Speaker 2: your vision progressively. But then again, when I have interacted

636
00:35:02,480 --> 00:35:04,919
Speaker 2: with people who have been blind all their lives, they

637
00:35:04,960 --> 00:35:08,320
Speaker 2: say that they don't necessarily want to have smart glasses

638
00:35:08,360 --> 00:35:10,719
Speaker 2: that will describe the world around them because they've grown

639
00:35:10,800 --> 00:35:14,400
Speaker 2: up in that world of having no visions. So I

640
00:35:14,400 --> 00:35:16,440
Speaker 2: guess it depends on the stage of life that you're

641
00:35:16,480 --> 00:35:18,279
Speaker 2: in whether these would be useful. But I think for

642
00:35:18,360 --> 00:35:21,680
Speaker 2: most people who could potentially navigate the world and be

643
00:35:21,760 --> 00:35:24,560
Speaker 2: more autonomous, that would be fantastic, wouldn't it.

644
00:35:25,239 --> 00:35:27,759
Speaker 1: Oh mate, that's at the very very positive end of

645
00:35:27,840 --> 00:35:30,120
Speaker 1: the AI scale. Yeah, I'm with you. That's amazing. I

646
00:35:30,160 --> 00:35:32,359
Speaker 1: have a selfish question I want to ask you, which

647
00:35:32,400 --> 00:35:33,279
Speaker 1: is not on your list?

648
00:35:33,680 --> 00:35:33,960
Speaker 2: Yep.

649
00:35:35,520 --> 00:35:40,120
Speaker 1: So, my internet at the moment is shit, and every day,

650
00:35:40,280 --> 00:35:41,840
Speaker 1: like I've been trying to get someone out here to

651
00:35:41,920 --> 00:35:44,800
Speaker 1: fix my internet and every day so I'm having to

652
00:35:45,080 --> 00:35:47,920
Speaker 1: hotspot from my phone. So my internet in my house

653
00:35:47,960 --> 00:35:51,960
Speaker 1: now is my phone. Like right now we're running, the

654
00:35:52,000 --> 00:35:57,839
Speaker 1: internet is coming from my phone. Starlink. Tell me what

655
00:35:57,960 --> 00:36:00,520
Speaker 1: starlink is? I can't know your shape, Can your head

656
00:36:00,520 --> 00:36:01,359
Speaker 1: tell me what it is?

657
00:36:01,440 --> 00:36:02,080
Speaker 2: Do we like it?

658
00:36:02,120 --> 00:36:05,200
Speaker 1: Do we not like it? Firstly, just explain to people

659
00:36:05,239 --> 00:36:07,759
Speaker 1: what Starlink is if you would and then give us

660
00:36:07,800 --> 00:36:11,040
Speaker 1: the pros and cons, and you've only got three minutes,

661
00:36:11,080 --> 00:36:11,520
Speaker 1: not ten.

662
00:36:11,800 --> 00:36:17,360
Speaker 2: Go Elon Musk launches his Starlink satellite network low orbit

663
00:36:17,480 --> 00:36:21,440
Speaker 2: satellites which mean that your point of contact is directly

664
00:36:21,480 --> 00:36:23,839
Speaker 2: above you, but they're in low Earth orbit, which means

665
00:36:23,840 --> 00:36:28,040
Speaker 2: it's created effectively and a whole network around the planet.

666
00:36:28,480 --> 00:36:32,600
Speaker 2: So potentially Starlink could allow you to be able to

667
00:36:32,680 --> 00:36:34,879
Speaker 2: if you're in a camper trailer in the middle of Australia,

668
00:36:34,920 --> 00:36:37,719
Speaker 2: there's no phone signal, but you'll have Starlink because it's

669
00:36:37,760 --> 00:36:41,080
Speaker 2: low orbit satellites, so that's basically getting your Internet. And

670
00:36:41,120 --> 00:36:44,440
Speaker 2: it's really good as an alternative to the NBN's Skymuster

671
00:36:44,960 --> 00:36:48,759
Speaker 2: because Skymuster is just a big ass like satellite that

672
00:36:48,880 --> 00:36:52,279
Speaker 2: beams it down, whereas this is lots of little micro satellites.

673
00:36:52,320 --> 00:36:56,000
Speaker 2: That's where starlink works. The only disadvantage I guess is

674
00:36:56,000 --> 00:36:58,920
Speaker 2: starlink isn't so good in built up areas. If you've

675
00:36:58,960 --> 00:37:01,960
Speaker 2: got buildings around you, it doesn't work as well. And

676
00:37:02,000 --> 00:37:06,440
Speaker 2: also you know you should be on really good Internet

677
00:37:06,520 --> 00:37:09,960
Speaker 2: through the NBN. So Starlink is totally independent of our

678
00:37:10,000 --> 00:37:14,040
Speaker 2: current terrestrial I guess network here. So when you deal

679
00:37:14,080 --> 00:37:17,600
Speaker 2: with Telstra, Optus and all the other local providers, you're

680
00:37:17,640 --> 00:37:21,480
Speaker 2: getting the NBN to the National Broadband Network, which is

681
00:37:21,520 --> 00:37:24,600
Speaker 2: the backbone of all the Internet services that we get

682
00:37:24,640 --> 00:37:28,480
Speaker 2: in Australia. Star is totally separate. It's an independent company

683
00:37:28,600 --> 00:37:32,360
Speaker 2: and you're buying the Internet through Elon Musk effectively. And

684
00:37:32,400 --> 00:37:34,560
Speaker 2: that's right. So it's good if you're in a wide

685
00:37:34,600 --> 00:37:37,799
Speaker 2: open spaces, if you're in rural areas, but it's not

686
00:37:38,000 --> 00:37:41,080
Speaker 2: as good in city areas, in built up areas, it

687
00:37:41,160 --> 00:37:43,640
Speaker 2: may not be as good for you. I certainly wouldn't

688
00:37:43,680 --> 00:37:46,839
Speaker 2: be looking at that as an alternative, particularly because at

689
00:37:46,840 --> 00:37:49,840
Speaker 2: the moment in September, if people are listening to this

690
00:37:50,200 --> 00:37:53,960
Speaker 2: around about this time, all the speeds NBN is going

691
00:37:54,000 --> 00:37:58,120
Speaker 2: to increase, all the speeds to home Internet users, depending

692
00:37:58,160 --> 00:38:01,440
Speaker 2: on what sort of Internet connection you've got at your house. Crago,

693
00:38:01,719 --> 00:38:03,799
Speaker 2: did that kind of makes about what starling you?

694
00:38:03,800 --> 00:38:06,400
Speaker 1: No, that's great, that's great. I mean that answers my question.

695
00:38:07,160 --> 00:38:08,839
Speaker 1: I knew you. I knew you wouldn't know the answer

696
00:38:08,920 --> 00:38:12,680
Speaker 1: to that. Tell me about the Chinese researchers who have

697
00:38:12,800 --> 00:38:16,520
Speaker 1: unveiled the world's larger scale brain like computer called the

698
00:38:16,600 --> 00:38:17,440
Speaker 1: Darwin Monkey.

699
00:38:17,640 --> 00:38:20,319
Speaker 2: I love that they've called it the Darwin Monkey, don't you.

700
00:38:21,080 --> 00:38:22,200
Speaker 1: I love it. I love it.

701
00:38:22,600 --> 00:38:26,400
Speaker 2: So they've built a massive computer, but they've tried to

702
00:38:26,560 --> 00:38:31,120
Speaker 2: use what they're calling a brain like interface, and that

703
00:38:31,239 --> 00:38:35,160
Speaker 2: they call it newomorphic brain like computer. So they're trying

704
00:38:35,280 --> 00:38:39,279
Speaker 2: to simulate the neurons of the human brain, and they're

705
00:38:39,320 --> 00:38:42,160
Speaker 2: saying this has got too bigger neurons, so this can

706
00:38:42,239 --> 00:38:45,600
Speaker 2: mimic the workings of Now they're not saying human being

707
00:38:45,600 --> 00:38:47,560
Speaker 2: because they're nowhere near what a human being is, but

708
00:38:47,640 --> 00:38:51,520
Speaker 2: they reckon that they can they can mimic basically a

709
00:38:51,600 --> 00:38:55,160
Speaker 2: monkey's brain in the way that it works, and that's

710
00:38:55,320 --> 00:38:58,360
Speaker 2: that's why they've called it the Darwin Monkey, which I

711
00:38:58,360 --> 00:39:00,640
Speaker 2: thought was kind of cute. Nothing to do with up North,

712
00:39:01,160 --> 00:39:05,239
Speaker 2: we're talking a different Darwin, yep. But I thought that's

713
00:39:05,280 --> 00:39:08,880
Speaker 2: really interesting because you know, computers traditionally work off a

714
00:39:08,920 --> 00:39:12,239
Speaker 2: totally different system of processing, whereas this is going to

715
00:39:12,280 --> 00:39:15,160
Speaker 2: try to mimic what a brain in the functioning of

716
00:39:15,200 --> 00:39:17,360
Speaker 2: a brain. So that's what I thought was kind of

717
00:39:17,840 --> 00:39:20,000
Speaker 2: is interesting about this. You know, who knows in the

718
00:39:20,040 --> 00:39:22,960
Speaker 2: future if they could, you know, would you upload your

719
00:39:22,960 --> 00:39:25,600
Speaker 2: brain to a computer crago if they could mimic all

720
00:39:25,600 --> 00:39:27,439
Speaker 2: the neurons and that would that really be you?

721
00:39:28,440 --> 00:39:34,000
Speaker 1: Ah? That well? See that's the philosophical six thousand dollars

722
00:39:34,480 --> 00:39:39,239
Speaker 1: spiritual question, isn't It's like who knows? Who knows? But

723
00:39:39,680 --> 00:39:42,520
Speaker 1: I don't know. I don't think so. But that would

724
00:39:42,560 --> 00:39:45,040
Speaker 1: be interesting. But something I am interested in, which I've

725
00:39:45,080 --> 00:39:48,480
Speaker 1: thought about a lot, which you've written this question. I

726
00:39:48,480 --> 00:39:52,760
Speaker 1: didn't read the actual story. But humans keep building robots

727
00:39:52,800 --> 00:39:56,560
Speaker 1: that are shaped like us. So robots that are shaped

728
00:39:56,640 --> 00:39:59,440
Speaker 1: like humans? What's the point? And I've always thought this.

729
00:39:59,560 --> 00:40:03,720
Speaker 1: I've thought, like to try to build a robot that's

730
00:40:03,880 --> 00:40:09,000
Speaker 1: bipedal and walks and is six foot tall? And why

731
00:40:09,040 --> 00:40:12,879
Speaker 1: would you? I get it because humans identify goa kind

732
00:40:12,880 --> 00:40:14,759
Speaker 1: of looks like me, and it can talk, and it's

733
00:40:14,760 --> 00:40:17,920
Speaker 1: got in inverted commas eyes and arms and legs, And

734
00:40:18,480 --> 00:40:21,080
Speaker 1: I get it from a psychology point of view that

735
00:40:21,680 --> 00:40:24,600
Speaker 1: humans might relate better to something that looks like it.

736
00:40:24,800 --> 00:40:28,080
Speaker 1: But I would think from a function and an engineering

737
00:40:28,120 --> 00:40:31,400
Speaker 1: point of view, it'd be much easier to have something

738
00:40:31,480 --> 00:40:38,120
Speaker 1: that's much more practical and functional that isn't shaped like

739
00:40:38,160 --> 00:40:40,560
Speaker 1: a human like I don't know, a little box that

740
00:40:40,920 --> 00:40:44,160
Speaker 1: ain't going to fall over or you know what I mean, Oh,

741
00:40:44,239 --> 00:40:46,919
Speaker 1: a dog, I'd go four legs, I reckon that would

742
00:40:46,920 --> 00:40:49,000
Speaker 1: be a much better option if you're going to design

743
00:40:49,040 --> 00:40:51,880
Speaker 1: a robot to go up and down hills and navigate.

744
00:40:52,040 --> 00:40:55,319
Speaker 1: I mean, think about a wheelchair system that had four

745
00:40:55,400 --> 00:40:59,239
Speaker 1: legs as opposed to two legs. The balance that goes

746
00:40:59,280 --> 00:41:04,000
Speaker 1: into kind of coordinating bipedle as opposed to well they exist. Yeah,

747
00:41:04,040 --> 00:41:06,400
Speaker 1: but also you think about the dog. You think about

748
00:41:06,440 --> 00:41:09,560
Speaker 1: you know that MIT motherfucker that they built. You know,

749
00:41:09,719 --> 00:41:12,040
Speaker 1: have you seen that tip that to look at the

750
00:41:12,360 --> 00:41:18,160
Speaker 1: MIT Capital MIT robot dog that they're that they're using

751
00:41:18,239 --> 00:41:23,400
Speaker 1: for warfare, And yeah, these things are as you suggest,

752
00:41:23,520 --> 00:41:26,399
Speaker 1: just the fact that they've got four legs not two,

753
00:41:26,840 --> 00:41:28,760
Speaker 1: they're much more stable.

754
00:41:29,320 --> 00:41:34,239
Speaker 2: Cleo, Cleo, the robot dog. But look, it does make it.

755
00:41:34,480 --> 00:41:38,760
Speaker 2: You're ponder this because you've heard the term the uncanny valley,

756
00:41:38,840 --> 00:41:43,040
Speaker 2: have you, Yeah? Yeah, So the uncanny valley was coined

757
00:41:43,080 --> 00:41:46,960
Speaker 2: by a Japanese robot research and robotics research in the

758
00:41:47,000 --> 00:41:51,120
Speaker 2: nineteen seventies, and what he discovered was the more you

759
00:41:51,239 --> 00:41:54,719
Speaker 2: make a robot look like a human being, it gets

760
00:41:54,760 --> 00:41:58,120
Speaker 2: to a point where the fakeness of it, so you

761
00:41:58,120 --> 00:42:00,680
Speaker 2: put eye lashes on it. You have a mouth moves,

762
00:42:01,080 --> 00:42:04,120
Speaker 2: but you know instinctively that it's not a human being.

763
00:42:04,160 --> 00:42:06,560
Speaker 2: But the mouth is moving, but the you know, this

764
00:42:06,640 --> 00:42:09,360
Speaker 2: doesn't have proper skin texture, or the muscles don't the

765
00:42:09,440 --> 00:42:12,439
Speaker 2: musculature isn't the same, and it gets to a point

766
00:42:12,440 --> 00:42:14,359
Speaker 2: where it starts to look creepy. So if you've got

767
00:42:14,400 --> 00:42:17,759
Speaker 2: a screen on a robot with a smiley emoji, then

768
00:42:17,920 --> 00:42:20,280
Speaker 2: I can deal with that. But if you've got lips

769
00:42:20,320 --> 00:42:24,360
Speaker 2: that are moving and fake skin, that's the uncanny valley.

770
00:42:24,360 --> 00:42:26,759
Speaker 2: That's where it looks that little bit creepy because it's

771
00:42:26,800 --> 00:42:27,280
Speaker 2: not real.

772
00:42:28,320 --> 00:42:33,720
Speaker 1: Yeah yeah, and but we know that it's not real.

773
00:42:34,200 --> 00:42:37,680
Speaker 1: But in another thing, which I know you know, and

774
00:42:37,719 --> 00:42:40,520
Speaker 1: I'm sure Tiff knows and our listeners know, but more

775
00:42:40,560 --> 00:42:47,040
Speaker 1: and more people are having relationships in inverted commas with

776
00:42:47,040 --> 00:42:50,200
Speaker 1: with bots, you know, and people are marrying them. I

777
00:42:50,239 --> 00:42:57,160
Speaker 1: saw a Japanese dude marrying his Japanese bride, yeah, and

778
00:42:57,320 --> 00:42:59,880
Speaker 1: the whole bunch of people at the wedding, and I'm like, okay,

779
00:43:00,760 --> 00:43:03,799
Speaker 1: so yeah, I don't know how that's going to work.

780
00:43:04,160 --> 00:43:06,839
Speaker 2: The ABC had an article that I read a couple

781
00:43:06,880 --> 00:43:08,880
Speaker 2: of days ago, and you could probably find it pretty

782
00:43:08,920 --> 00:43:13,640
Speaker 2: easily about a woman who has got some emotional problems

783
00:43:13,719 --> 00:43:16,839
Speaker 2: and she'd been in a relationship with a chatbot for

784
00:43:16,920 --> 00:43:20,319
Speaker 2: four years. And I think she was on the NDIS

785
00:43:20,360 --> 00:43:22,719
Speaker 2: and her care a talked to the chatbot as well,

786
00:43:22,840 --> 00:43:25,319
Speaker 2: so she had a conversation, but she felt she was

787
00:43:25,320 --> 00:43:29,080
Speaker 2: in an authentic relationship with the chatbot, and she lives

788
00:43:29,080 --> 00:43:31,120
Speaker 2: her daily life. She gets up in the morning, starts

789
00:43:31,160 --> 00:43:34,239
Speaker 2: talking to her chatbot, and then when people come in

790
00:43:34,360 --> 00:43:37,440
Speaker 2: to visit her, they interact with the chat bot as well.

791
00:43:37,719 --> 00:43:40,040
Speaker 2: And there's no question, and I know we've spoken about

792
00:43:40,080 --> 00:43:43,400
Speaker 2: this many times, but developing a relationship with an AI,

793
00:43:43,640 --> 00:43:46,839
Speaker 2: with a chatbot or a robot, as that happens. If

794
00:43:46,880 --> 00:43:51,920
Speaker 2: you finally do have an autonomous bipedal robot in your

795
00:43:51,960 --> 00:43:55,400
Speaker 2: home making you your soup for lunch, there's no question

796
00:43:55,440 --> 00:43:57,160
Speaker 2: that you would probably interact with. I mean, God, the

797
00:43:57,160 --> 00:43:59,680
Speaker 2: amount that I talked to my dog, I can imagine

798
00:43:59,680 --> 00:44:01,520
Speaker 2: what it be like if I had a robot walking

799
00:44:01,560 --> 00:44:03,840
Speaker 2: around the house talking to me. I mean, Fritz doesn't

800
00:44:03,840 --> 00:44:06,000
Speaker 2: even talk back to me that I know, just a

801
00:44:06,040 --> 00:44:08,799
Speaker 2: monologue for me. Which is really hard to do.

802
00:44:10,200 --> 00:44:12,839
Speaker 1: Oh yeah, I can imagine you must really struggle with that.

803
00:44:12,840 --> 00:44:15,520
Speaker 1: That poor dog. Has he ever jump under the fucking

804
00:44:15,600 --> 00:44:18,440
Speaker 1: couch and put a cushion over his head?

805
00:44:19,360 --> 00:44:24,279
Speaker 2: Wow? No, dogs are amazingly resilient and of coase it.

806
00:44:24,320 --> 00:44:26,440
Speaker 2: Don't forget I'm the person who walks and feeds him

807
00:44:26,480 --> 00:44:28,440
Speaker 2: and plays with him, so you know he knows on

808
00:44:28,480 --> 00:44:29,120
Speaker 2: which side.

809
00:44:28,960 --> 00:44:35,040
Speaker 1: He's bread has butted? What's what's his vocabulary? How many

810
00:44:35,239 --> 00:44:38,000
Speaker 1: actual words? We're digressing, We'll get back on track. But

811
00:44:38,040 --> 00:44:41,520
Speaker 1: how many actual words do you reckon he understands?

812
00:44:42,160 --> 00:44:44,080
Speaker 2: That's a really good question. I've often thought about that

813
00:44:44,120 --> 00:44:45,640
Speaker 2: because I was reading a book and I can't think

814
00:44:45,640 --> 00:44:47,480
Speaker 2: of the name of it a little while ago, where

815
00:44:47,880 --> 00:44:50,439
Speaker 2: the character in the book was determined to teach their

816
00:44:50,480 --> 00:44:53,520
Speaker 2: dog six hundred words. It was a very cute story,

817
00:44:53,760 --> 00:44:56,440
Speaker 2: and the dog was really smart. I don't know how

818
00:44:56,520 --> 00:44:59,359
Speaker 2: many words he knows? I think t if you could

819
00:44:59,360 --> 00:45:01,640
Speaker 2: probably answer the as well. Having got a dog yourself,

820
00:45:01,719 --> 00:45:04,440
Speaker 2: do you give Luna other names? Like the most pet

821
00:45:04,520 --> 00:45:06,680
Speaker 2: owners have about three or four names for their dogs.

822
00:45:07,440 --> 00:45:11,400
Speaker 2: She Yeah, mine does too, Yeah does as well, So

823
00:45:11,400 --> 00:45:13,480
Speaker 2: I've got multiple names. But as far as what he

824
00:45:13,520 --> 00:45:17,160
Speaker 2: can understand. I mean, he certainly what really staggers me.

825
00:45:17,360 --> 00:45:20,680
Speaker 2: And I remember a friend of mine, her father had

826
00:45:20,760 --> 00:45:24,400
Speaker 2: a sheep farm and he was ill and had to

827
00:45:24,400 --> 00:45:26,880
Speaker 2: go to hospital, and they had a working dog that

828
00:45:26,920 --> 00:45:29,440
Speaker 2: would round up the sheep in the bottom paddock and

829
00:45:29,440 --> 00:45:32,319
Speaker 2: bring them up to the top paddock. And they were

830
00:45:32,360 --> 00:45:34,960
Speaker 2: trying to get the dog to bring the sheep up,

831
00:45:35,000 --> 00:45:36,920
Speaker 2: and they didn't know what the command was. They know

832
00:45:36,960 --> 00:45:39,839
Speaker 2: the dog was really smart, but they couldn't work out

833
00:45:39,840 --> 00:45:42,080
Speaker 2: what the command was. And eventually they got a message

834
00:45:42,080 --> 00:45:44,480
Speaker 2: to the father and he said, oh, no, it's not

835
00:45:44,520 --> 00:45:47,040
Speaker 2: a verbal command. I just flick my eyes to the

836
00:45:47,120 --> 00:45:49,759
Speaker 2: left and the dog knows to go up the hill

837
00:45:50,000 --> 00:45:52,880
Speaker 2: and bring the sheep up. So that's how subtle the

838
00:45:52,880 --> 00:45:55,640
Speaker 2: interaction was. And I know with Fritz, I can just

839
00:45:55,680 --> 00:45:58,000
Speaker 2: point to the ground in a certain way, or put

840
00:45:58,040 --> 00:46:00,359
Speaker 2: my palm flat to the ground and he'll drop. And

841
00:46:00,360 --> 00:46:02,640
Speaker 2: then I turned my palm and he rolls over. So

842
00:46:02,760 --> 00:46:05,800
Speaker 2: those sorts of things. So when it comes to words,

843
00:46:06,560 --> 00:46:08,719
Speaker 2: it probably knows a few of them, but he certainly

844
00:46:09,200 --> 00:46:13,480
Speaker 2: knows actions and movements as well, and hand gestures. So

845
00:46:14,000 --> 00:46:15,719
Speaker 2: I guess if you wanted to spend a lot of time.

846
00:46:15,760 --> 00:46:19,440
Speaker 2: Friends of mine just found these little electronic tiles at

847
00:46:19,480 --> 00:46:22,960
Speaker 2: the opshop and you can there buttons that you record

848
00:46:23,040 --> 00:46:24,879
Speaker 2: you on your voice, So it might be I want

849
00:46:24,880 --> 00:46:27,520
Speaker 2: to go outside, and then you train your dog to

850
00:46:27,600 --> 00:46:30,440
Speaker 2: hit the button to send you the message I want

851
00:46:30,480 --> 00:46:32,399
Speaker 2: to go outside, I want to go outside, I want

852
00:46:32,400 --> 00:46:34,480
Speaker 2: to treat, and you can train the dog to hit

853
00:46:34,520 --> 00:46:36,440
Speaker 2: the buttons for the different things that it wants you

854
00:46:36,480 --> 00:46:36,759
Speaker 2: to do.

855
00:46:38,120 --> 00:46:40,239
Speaker 1: That wouldn't be annoying at three am at all, I

856
00:46:40,320 --> 00:46:51,279
Speaker 1: want to treat. Your phone is covered in germs. I'm like, like,

857
00:46:51,400 --> 00:46:54,239
Speaker 1: this is one of the stories, just quickly before you

858
00:46:54,280 --> 00:46:56,040
Speaker 1: tell us about it. I was talking to a lady

859
00:46:56,080 --> 00:46:59,800
Speaker 1: who's a microbiologist and she's like, you know what creates

860
00:46:59,840 --> 00:47:04,480
Speaker 1: more more sickness than all the germs on whatever is

861
00:47:04,920 --> 00:47:09,400
Speaker 1: the propensity that we now have to try to sanitize

862
00:47:09,440 --> 00:47:13,920
Speaker 1: the whole world? And who was it someone on the

863
00:47:13,920 --> 00:47:16,799
Speaker 1: show they were talking about we need germs, like we

864
00:47:16,840 --> 00:47:19,640
Speaker 1: need germs, We need you know, we need a level

865
00:47:19,719 --> 00:47:23,000
Speaker 1: of germs so that our immune system has to deal

866
00:47:23,080 --> 00:47:26,080
Speaker 1: and cope and adapt. And when we put ourselves in

867
00:47:26,160 --> 00:47:29,080
Speaker 1: our kids and in a completely or close as we

868
00:47:29,120 --> 00:47:34,160
Speaker 1: can sanitized environment. Then when we do get exposed to something,

869
00:47:34,239 --> 00:47:37,560
Speaker 1: which inevitably we will, we have no resistance, like we

870
00:47:37,680 --> 00:47:41,839
Speaker 1: have no immunity because we're always nerfing the world. So

871
00:47:41,920 --> 00:47:44,959
Speaker 1: I reckon, let your phone be dirty, That's what I think.

872
00:47:45,360 --> 00:47:48,560
Speaker 2: Okay, well, we've had this conversation, and it's the pre

873
00:47:48,719 --> 00:47:53,520
Speaker 2: flush or pre wipe and post wipe phone use. So

874
00:47:53,680 --> 00:47:55,839
Speaker 2: you know when you go to the toilet. We all

875
00:47:55,880 --> 00:47:57,879
Speaker 2: know we take our phones to the toilet. Don't lie,

876
00:47:58,080 --> 00:48:01,680
Speaker 2: you know you do, right, my popuy is the pre

877
00:48:01,800 --> 00:48:05,400
Speaker 2: wipe policy, so the second that I start wiping, the

878
00:48:05,440 --> 00:48:07,719
Speaker 2: phone doesn't get touched again until I've washed my hand.

879
00:48:09,040 --> 00:48:13,720
Speaker 2: So pre wipe you can use your phone. Post post wipe,

880
00:48:14,000 --> 00:48:16,160
Speaker 2: you can't touch your vote until you've washed your hair.

881
00:48:17,040 --> 00:48:20,000
Speaker 1: I saw a show on your favorite station, the ab C,

882
00:48:20,200 --> 00:48:22,560
Speaker 1: a couple of years ago, and it was talking about this,

883
00:48:22,640 --> 00:48:25,480
Speaker 1: and it was talking about one of the you know

884
00:48:25,560 --> 00:48:29,239
Speaker 1: what fecal matter is is bits of pooh. They were

885
00:48:29,280 --> 00:48:32,839
Speaker 1: talking about you know what has pooh on it? And

886
00:48:32,880 --> 00:48:35,280
Speaker 1: one of the things that's got a pretty liberal smattering

887
00:48:35,360 --> 00:48:40,280
Speaker 1: of pooh on it is your toothbrush. Because yeah, because

888
00:48:40,280 --> 00:48:42,520
Speaker 1: it's generally or for a lot of people it's within

889
00:48:42,560 --> 00:48:46,600
Speaker 1: a meter or two of the toilet, so and a

890
00:48:46,640 --> 00:48:51,319
Speaker 1: pretty simple way to offset that is to I don't know.

891
00:48:51,400 --> 00:48:54,120
Speaker 1: I don't because I've never watched anyone else. Let's not

892
00:48:54,200 --> 00:48:57,680
Speaker 1: go there. But I always shut the lid when I flush.

893
00:48:57,800 --> 00:49:00,799
Speaker 1: Do you shut the lid when you flush? Tip, Yes, yep,

894
00:49:00,840 --> 00:49:03,520
Speaker 1: because if you don't, you kind of just spray shit

895
00:49:03,719 --> 00:49:05,520
Speaker 1: literally around the room.

896
00:49:05,960 --> 00:49:08,480
Speaker 2: Did I talk about the next level of paranoia? My

897
00:49:08,800 --> 00:49:12,520
Speaker 2: toothbrush sits in a cupboard, so I close the cupboard

898
00:49:12,680 --> 00:49:16,520
Speaker 2: and that way it's not exposed to any flushing potential. Well,

899
00:49:16,560 --> 00:49:18,800
Speaker 2: the thing is because I have a home based office

900
00:49:19,120 --> 00:49:24,000
Speaker 2: and so my main bathroom does get used by staff,

901
00:49:24,000 --> 00:49:26,200
Speaker 2: but it's also the same bathroom that has my toothbrush

902
00:49:26,239 --> 00:49:29,320
Speaker 2: in it, so my toothbrush is definitely cleep behind.

903
00:49:31,000 --> 00:49:32,960
Speaker 1: Yeah, you don't want me to come to your house

904
00:49:33,000 --> 00:49:34,480
Speaker 1: because you know where I'm going to look on what

905
00:49:34,520 --> 00:49:38,279
Speaker 1: I'm going to do with it. I'm going to I'm

906
00:49:38,320 --> 00:49:40,680
Speaker 1: just going to clean my nuts with your toothbrush and

907
00:49:40,719 --> 00:49:44,920
Speaker 1: then give it a just pop it back in. You're welcome,

908
00:49:45,920 --> 00:49:48,960
Speaker 1: thanks for that. So what I was doing one more champ,

909
00:49:49,040 --> 00:49:49,920
Speaker 1: one more champ.

910
00:49:49,920 --> 00:49:52,520
Speaker 2: Is going to say, don't clean your like. Yes, so

911
00:49:52,560 --> 00:49:55,319
Speaker 2: there are lots of micro organisms on your phone, but

912
00:49:55,480 --> 00:49:58,440
Speaker 2: don't be careful what you wipe the phone down with.

913
00:49:58,600 --> 00:50:03,400
Speaker 2: Anything above like an alcohol wipe over seventy percent is

914
00:50:03,440 --> 00:50:06,040
Speaker 2: going to damage the screen of your phone. So be

915
00:50:06,200 --> 00:50:09,359
Speaker 2: aware that what you clean your sunglasses with may not

916
00:50:09,400 --> 00:50:11,560
Speaker 2: necessarily be the right thing to clean your phone with

917
00:50:11,920 --> 00:50:14,680
Speaker 2: because the screen is touch sensitive.

918
00:50:15,480 --> 00:50:17,759
Speaker 1: So a bit of old windex, yes or no?

919
00:50:18,400 --> 00:50:20,280
Speaker 2: Well, that's a good question. A bit of old index.

920
00:50:20,280 --> 00:50:22,239
Speaker 2: I'd have to look at what the chemical content is.

921
00:50:22,480 --> 00:50:25,600
Speaker 2: Just YouTube? It can you use in index to clean your phone?

922
00:50:25,600 --> 00:50:25,759
Speaker 3: Hey?

923
00:50:25,840 --> 00:50:27,400
Speaker 2: If can you look it up for us? Is that

924
00:50:27,440 --> 00:50:28,640
Speaker 2: all right? Maybe?

925
00:50:28,840 --> 00:50:32,640
Speaker 1: Chat GP t it? I reckon that that'd be that'll

926
00:50:32,680 --> 00:50:35,960
Speaker 1: be quicker. No, really, fuck YouTube, it's not the nineties.

927
00:50:36,280 --> 00:50:40,279
Speaker 2: Hey, you know what you're here? YouTube? Google says no,

928
00:50:40,440 --> 00:50:43,480
Speaker 2: you can ah see No, why not?

929
00:50:43,719 --> 00:50:48,840
Speaker 3: Contains ammonia, which can damage your anti glare coating discolouration.

930
00:50:50,120 --> 00:50:54,040
Speaker 3: Windex is pretty pretty shit chemical that way, you.

931
00:50:54,000 --> 00:50:56,080
Speaker 1: Know, it's pretty good. Hanky in a bit of spit,

932
00:50:56,640 --> 00:51:02,160
Speaker 1: that's what Mary, that's what you're on there? That was Patrick?

933
00:51:03,120 --> 00:51:04,640
Speaker 2: Did you want one more? Did you say?

934
00:51:04,800 --> 00:51:05,320
Speaker 3: All right?

935
00:51:05,480 --> 00:51:05,719
Speaker 2: Go on?

936
00:51:05,960 --> 00:51:06,480
Speaker 1: Be quick?

937
00:51:06,719 --> 00:51:10,239
Speaker 2: Okay? Drivers in wa right, wait for this, and this

938
00:51:10,280 --> 00:51:12,080
Speaker 2: is probably happening all over Australia, but this is an

939
00:51:12,160 --> 00:51:15,719
Speaker 2: article from Western Australia. They're hitting the mute on annoying

940
00:51:15,880 --> 00:51:18,600
Speaker 2: car safety technology. And I've got friends who've done this

941
00:51:18,680 --> 00:51:21,439
Speaker 2: as well. They don't like lane assists, so they turn

942
00:51:21,480 --> 00:51:24,799
Speaker 2: off lane assists. They don't like the car warning them

943
00:51:24,800 --> 00:51:27,000
Speaker 2: that they're going too fast, so they turn it off.

944
00:51:27,200 --> 00:51:30,960
Speaker 2: And it seems like this is a survey that was

945
00:51:30,960 --> 00:51:33,840
Speaker 2: done in Western Australia by Double Ami, the insurance company,

946
00:51:34,080 --> 00:51:37,280
Speaker 2: and they said twenty three percent admitted to having turning

947
00:51:37,400 --> 00:51:41,160
Speaker 2: off or dialing down car safety features, and seventy two

948
00:51:41,239 --> 00:51:46,480
Speaker 2: percent say noises and lights are distracting. So they find

949
00:51:46,600 --> 00:51:48,920
Speaker 2: all those noises and lights and you know when someone

950
00:51:48,960 --> 00:51:51,799
Speaker 2: overtakes you and the light blinks and a noise might

951
00:51:51,840 --> 00:51:54,280
Speaker 2: come up to say that there's someone in your blind spot.

952
00:51:54,440 --> 00:51:56,839
Speaker 2: But most drivers, so seventy two percent of drivers says

953
00:51:56,880 --> 00:51:59,600
Speaker 2: they didn't like all those noises in their cars, and

954
00:51:59,640 --> 00:52:01,279
Speaker 2: twenty three percent of turning them off.

955
00:52:02,120 --> 00:52:04,200
Speaker 1: I agree with them, but I don't know how to

956
00:52:04,239 --> 00:52:07,640
Speaker 1: turn anything off. My new car is my new car

957
00:52:07,719 --> 00:52:10,759
Speaker 1: is it's essentially a computer. It's like I don't know

958
00:52:11,440 --> 00:52:13,319
Speaker 1: if it can do one hundred things I know how

959
00:52:13,360 --> 00:52:16,120
Speaker 1: to do. For I do not know how to use

960
00:52:16,160 --> 00:52:18,719
Speaker 1: that car other than drive it and park it and

961
00:52:19,760 --> 00:52:22,520
Speaker 1: lock it and unlock it. It just does so much

962
00:52:22,520 --> 00:52:23,960
Speaker 1: shit that's beyond mine.

963
00:52:24,200 --> 00:52:25,920
Speaker 2: Next time I'm over, let's go for a drive and

964
00:52:25,960 --> 00:52:26,400
Speaker 2: maybe I can.

965
00:52:26,520 --> 00:52:29,440
Speaker 1: Ah, you'll love it, Yeah, you'll love it.

966
00:52:29,640 --> 00:52:31,919
Speaker 2: But you know what, there are companies are going back

967
00:52:31,920 --> 00:52:35,960
Speaker 2: to knobs and dials. I had my car being repaired

968
00:52:35,960 --> 00:52:39,480
Speaker 2: recently because unfortunately, I had an interaction or an altercation

969
00:52:39,560 --> 00:52:44,040
Speaker 2: with a kangaroo. The kangaroo survived, my car didn't. It's

970
00:52:44,239 --> 00:52:46,360
Speaker 2: kind of bumped the side of the car. But I

971
00:52:46,400 --> 00:52:48,560
Speaker 2: was driving a courtesy car for a while and I

972
00:52:48,600 --> 00:52:51,239
Speaker 2: didn't realize how much I like all the features in

973
00:52:51,239 --> 00:52:53,719
Speaker 2: my car. You know, the head's up display, But what

974
00:52:53,760 --> 00:52:56,200
Speaker 2: I love about it is that I can reach down

975
00:52:56,239 --> 00:52:59,480
Speaker 2: and still physically hit a button to turn the temperature

976
00:52:59,520 --> 00:53:01,919
Speaker 2: up or down. There's a screen version, but it also

977
00:53:02,040 --> 00:53:06,320
Speaker 2: has analog versions as well, Knobs to control the volume,

978
00:53:06,600 --> 00:53:09,400
Speaker 2: you know, change the tuning, to move things around. So

979
00:53:09,520 --> 00:53:12,680
Speaker 2: I kind of like that. It's got some tech features,

980
00:53:12,680 --> 00:53:14,879
Speaker 2: but it's also got a lot of analog features as well.

981
00:53:15,760 --> 00:53:18,200
Speaker 1: I had to do a gig in Ballarat yesterday and

982
00:53:18,239 --> 00:53:18,440
Speaker 1: I was.

983
00:53:19,280 --> 00:53:23,120
Speaker 2: Oh my god, he went right past my house. I'm

984
00:53:23,280 --> 00:53:25,440
Speaker 2: just shattered. I'm so shattered.

985
00:53:26,239 --> 00:53:28,520
Speaker 1: I thought about coming to see you, but I had

986
00:53:28,560 --> 00:53:33,160
Speaker 1: to be back in time for a thing. Anyway, For

987
00:53:34,560 --> 00:53:37,040
Speaker 1: I did think of you as I saw the Bland

988
00:53:38,800 --> 00:53:42,120
Speaker 1: and I thought, I thought, no, self, don't tell him

989
00:53:42,120 --> 00:53:44,760
Speaker 1: you went the Ballarat. And then I fucked up, didn't I? Anyway,

990
00:53:46,760 --> 00:53:51,600
Speaker 1: I was leaving the rac V gold Fields gold Mine,

991
00:53:51,680 --> 00:53:55,520
Speaker 1: gold Field's bloody resort in It's actually in Creswick, which

992
00:53:55,560 --> 00:54:00,840
Speaker 1: is right near Ballarat. Anyway, I'm like, Creswickwick, we thank you.

993
00:54:01,120 --> 00:54:03,680
Speaker 1: I was. I was five minutes out of the car

994
00:54:03,760 --> 00:54:07,040
Speaker 1: park and driving back. And if you don't keep your

995
00:54:07,040 --> 00:54:10,239
Speaker 1: eyes in a certain like where the car thinks your

996
00:54:10,280 --> 00:54:13,080
Speaker 1: eyes should be, it tells you to pull over and

997
00:54:13,120 --> 00:54:16,800
Speaker 1: have arrest. It's like, might be time for a coffee

998
00:54:16,800 --> 00:54:19,319
Speaker 1: and a rest. I'm like, how about you shut the

999
00:54:19,360 --> 00:54:24,080
Speaker 1: fuck up like he was telling me at you know,

1000
00:54:24,360 --> 00:54:27,440
Speaker 1: five o'clock in the afternoon, pull over, chill out, have arrest,

1001
00:54:27,480 --> 00:54:29,000
Speaker 1: have a coffee and then reboot.

1002
00:54:29,040 --> 00:54:31,800
Speaker 2: I'm like, no, bro, shush, I thought we're going to

1003
00:54:31,880 --> 00:54:33,839
Speaker 2: say that you're It said to you that your left

1004
00:54:33,840 --> 00:54:35,839
Speaker 2: eyes so beautiful. You're right. I keeps trying to look

1005
00:54:35,880 --> 00:54:36,160
Speaker 2: at it.

1006
00:54:39,440 --> 00:54:42,879
Speaker 1: Fucking hell. Patrick, tell people about you where they can

1007
00:54:42,920 --> 00:54:43,719
Speaker 1: find you, and.

1008
00:54:44,040 --> 00:54:47,000
Speaker 4: Really anybody wants to know anything about way if you

1009
00:54:47,000 --> 00:54:50,880
Speaker 4: want to interact on any level, websites noow dot com

1010
00:54:50,920 --> 00:54:53,880
Speaker 4: dot Au, websites now dot com dot au, or you

1011
00:54:53,920 --> 00:54:55,560
Speaker 4: can go to ty chi at home and do tai

1012
00:54:55,680 --> 00:54:58,080
Speaker 4: chie with me, because I feel like I've a split personality.

1013
00:54:58,280 --> 00:55:01,239
Speaker 2: There's my tychi me and then there's my tech bor

1014
00:55:01,440 --> 00:55:03,160
Speaker 2: not boring. It's kind of fun because we get to

1015
00:55:03,160 --> 00:55:05,520
Speaker 2: do lots of fun stuff with clients. But yeah, so

1016
00:55:05,560 --> 00:55:08,000
Speaker 2: there's the websites now me and the tai Chi me.

1017
00:55:09,960 --> 00:55:14,920
Speaker 1: Tech you and so yeah, prefrontal cortex, all logical thinking,

1018
00:55:15,080 --> 00:55:18,640
Speaker 1: and then the the spiritual tie chie. Get out of

1019
00:55:18,680 --> 00:55:20,680
Speaker 1: your brain, out of your thoughts, out of your bloody

1020
00:55:20,800 --> 00:55:27,000
Speaker 1: cognitive whatever. Yeah, that is quiet, it's pretty We'll say

1021
00:55:27,000 --> 00:55:29,680
Speaker 1: goodbye a fair but tif thank you. Thanks.

1022
00:55:29,800 --> 00:55:30,120
Speaker 3: Kids.

1023
00:55:30,800 --> 00:55:32,640
Speaker 1: Try to get you, try to get your computer work

1024
00:55:32,680 --> 00:55:33,040
Speaker 1: the will you.

1025
00:55:34,200 --> 00:55:37,040
Speaker 3: I wish Patrick could fix it.

1026
00:55:37,040 --> 00:55:39,160
Speaker 2: It's an excuse to come visit. I'll come visit help

1027
00:55:39,160 --> 00:55:42,560
Speaker 1: You with your computer okay, all right, see everyone Bye.