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Speaker 1: I get a team. It's a You Project, of course

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Speaker 1: it is. Patrick's here, Tips here, I'm here. I hope

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Speaker 1: you're well. Hope you're enjoying the You Project. And if

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Speaker 1: you're not part of our little online group, a Rooney,

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Speaker 1: the You Project Facebook group is available for you.

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Speaker 2: Is that what it's called the You Project podcast? Or

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Speaker 2: I don't know, it's something of that group. I should

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Speaker 2: I should probably know.

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Speaker 1: But there's about four thousand of us that jump on

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Speaker 1: there and talk, and young Danny this week had something

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Speaker 1: to celebrate.

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Speaker 2: In the group. We all did that, like a.

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Speaker 1: Little online community where people just support each other in

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Speaker 1: all the good things. So if you're not part of that,

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Speaker 1: there's no hooks, catches or agendas. You just jump in

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Speaker 1: and chat or jump out whatever the case. Hi, Patrick, Hey, Hey,

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Speaker 1: doing be part of the group? Kind of Yes and no?

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Speaker 3: Yes, I joined in.

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Speaker 2: Are you a member of the group?

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Speaker 3: I think so. Yeah, But I don't monitor social media anymore. Remember,

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Speaker 3: I just don't jump that's true.

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Speaker 2: Yeah, that's true. That's probably for the best.

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Speaker 1: But after talking to David Gillespie the other day, I

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Speaker 1: was a bit depressed but also a little bit enlightened.

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Speaker 1: So I'm right now curating my relationship with social media

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Speaker 1: and all of my attention regarding all things electronic high

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Speaker 1: TIV high harms.

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Speaker 4: How are you fabulous? Friday morning?

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Speaker 1: Now, Patrick and I saw that some male was in

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Speaker 1: the background before.

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Speaker 2: We went live. I'm not sure that either he or

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Speaker 2: I have given any kind of approval for that.

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Speaker 4: Earlier in the morning to walk the dog.

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Speaker 3: Yes, it is that what he does. Oh sorry, I

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Speaker 3: thought it was a letter from Australia Poste.

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Speaker 2: Yeah, so he's like a dog walker man, is he?

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Speaker 4: Yes? Yes?

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Speaker 1: Why was he in pajamas and my pajamas, I mean jocks?

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Speaker 1: Why was the dog walker man knewed in the background?

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Speaker 2: What was that about? Did you giggling? Giggling like a

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Speaker 2: fucking guilty school girl? And Patrick's like, I wish I

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Speaker 2: had one of them in my background.

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Speaker 3: I was just going to say that I couldn't say

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Speaker 3: you must have X ray glasses because he looked pretty

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Speaker 3: close to me.

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Speaker 1: We're just fucking around for the show. Patrick, you're familiar

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Speaker 1: with entertainment, No, you're familiar with that. No, but thanks

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Speaker 1: for that. You really added to what was going on.

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Speaker 4: Truth get in the way of a good story, Patrick.

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Speaker 2: Yeah, just let that.

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Speaker 1: Just let that roll now, Patrick, You've been the victim

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Speaker 1: of a vicious crime up there in the place where

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Speaker 1: you once bragged about how safe and beautiful it was.

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Speaker 1: You don't lock your car, you don't lock your house.

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Speaker 1: But you do, now, don't you.

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Speaker 5: Well?

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Speaker 3: I do lock my car, but it was parked across

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Speaker 3: the road on one of those really hot days under

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Speaker 3: a tree because there was no shade, and I left

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Speaker 3: it overnight and someone broke into it. Yeah, smashed the windows.

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Speaker 3: Wasn't fun. But I had my backpack in it, which

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Speaker 3: is what I take to tai Chi with all my

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Speaker 3: notes and fans and a little bit of equipment and yes,

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Speaker 3: my wallet. I know everyone's been telling me how dumb

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Speaker 3: I am, and one friend in particular, Hi Sylvia, it

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Speaker 3: constantly tells me how dumb I am, So thanks for that.

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Speaker 3: But yeah, the police were really lovely. The forensic guys

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Speaker 3: were really good. But the crims or krim, I don't

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Speaker 3: know if it was more than one person were wearing

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Speaker 3: gloves so they couldn't take any prints. But but digital tracking,

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Speaker 3: thank you. They used my credit card at nine different

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Speaker 3: locations as they drove back to Melbourne. So wow, Melbourne. Yeah,

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Speaker 3: and the good thing is police have CCTV footage, so

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Speaker 3: I'm hoping that my stupidity may actually lead to a conviction.

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Speaker 3: So in some ways it's a good thing.

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Speaker 2: Will you be locking it moving forward all the time

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Speaker 2: or just a look it?

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Speaker 3: And I always lock it, but I just didn't have

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Speaker 3: it in the driveway where I normally have it nice

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Speaker 3: and safe where the camera is, and it was out

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Speaker 3: of the range of the camera.

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Speaker 1: So it's not a good feeling, is it when you

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Speaker 1: walk up to your car, or like, I've had a

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Speaker 1: few things happen over the years where you go, yeah,

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Speaker 1: you come to a door at your house and like

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Speaker 1: I didn't leave that open or whatever makes you feel

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Speaker 1: sick in the guts.

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Speaker 3: I don't know if you remember I lived. I was

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Speaker 3: renting a place in Tuak, which again is supposedly a

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Speaker 3: nice area, and I had my camera in the glovebox,

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Speaker 3: but this is before they had screens on the back

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Speaker 3: of it was a Kodak digital camera, one of the

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Speaker 3: very first ones, and it got stopped and anyway, I

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Speaker 3: thought maybe I'll just check out a few of the

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Speaker 3: pawn shops to see a few weeks later. Anyway, when

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Speaker 3: I walked out of club X. Sorry, I mean the

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Speaker 3: places that you can dock your wares, not wear your hawks.

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Speaker 3: You know, a lot a log chapel street at all

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Speaker 3: those places.

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Speaker 2: I'm not helping you out. You dug this fucking hole.

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Speaker 2: I saw it coming from two acres away.

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Speaker 3: Anyway, I went to one to watch.

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Speaker 2: Fortunately, Tiff is the best crowd in.

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Speaker 3: The world, and you are lucky when I do stand up, Tiff,

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Speaker 3: you are still going to be there right at the

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Speaker 3: front of everybody. Thank you. Anyway, so I walk in

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Speaker 3: and I see this camera that's identical to my camera

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Speaker 3: on sale, and I asked the guy, you know is

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Speaker 3: can I check out the camera? I said, if you've

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Speaker 3: got the box and cables for it and a mate

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Speaker 3: just as is. So I looked at it and the

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Speaker 3: memory card was full, and I knew that my memory

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Speaker 3: card and my camera had been full. And then I

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Speaker 3: opened up the back of it and they had Panasonic batteries.

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Speaker 3: And Panasonic batteries aren't that common in a lot of devices,

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Speaker 3: you know, you tend to get durusale and ever ready,

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Speaker 3: so I thought, I reckon, this is my camera. So

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Speaker 3: I went to the local police station and the desk

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Speaker 3: sergeant a person at the desk said, nah, we can't

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Speaker 3: do anything. You know, there's not much we can do.

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Speaker 3: But a COIB detective happened to be walking past and

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Speaker 3: he turned to me and said, oh, what happened to

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Speaker 3: your camera? And I told him the whole story. He said, right,

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Speaker 3: let's jump in the car and go and have a look.

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Speaker 3: He was a lovely guy. And we're driving there he says, yeah,

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Speaker 3: this bloody licensed thieves. So anyway, the short story is

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Speaker 3: I took the camera. We got the camera, took it

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Speaker 3: back to my place, and I had the box and

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Speaker 3: packaging for it. Serial codes matched, so I knew it

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Speaker 3: was my camera. I had to buy it back.

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Speaker 2: Oh my god.

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Speaker 3: I had to buy it back for the price that

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Speaker 3: the porn shop had purchased it for because even though

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Speaker 3: I could prove it was my camera, they had ID

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Speaker 3: stolen ID that that had been used to verify the

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Speaker 3: person's sale. But anyway, so it's just I know it's

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Speaker 3: a bit of a long winded story. Apologies for that,

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Speaker 3: but you're right, Craigo, you do feel somewhat violated when

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Speaker 3: something gets stolen that doesn't belongs to you.

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Speaker 1: It's not a competition, but I'll share one with you

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Speaker 1: that was a good one I bought when I had

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Speaker 1: Harper's on the Highway that he used to train at,

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Speaker 1: when Tiff was just you know, doing year twelve fuck

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Speaker 1: and squeezing a z it's and trying to figure out

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Speaker 1: what she wanted to do in the next you'll doing.

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Speaker 2: That decade or two.

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Speaker 1: So I bought a new motorbike patrick which I was

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Speaker 1: called a Suzuki eleven hundred hour, which was one of

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Speaker 1: the first of the super bikes in that kind of

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Speaker 1: it looked like something you would ride on the track

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Speaker 1: but on the street, right early days of those superbikes,

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Speaker 1: and back then it's probably twenty five years ago or something.

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Speaker 2: Cost me.

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Speaker 1: Like twenty three or four grand, which was a fortune,

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Speaker 1: probably like fifty grand now.

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Speaker 2: Anyway, blue and white, beautiful, amazing. Went out.

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Speaker 1: I won't say where I bought it, but anyway, went

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Speaker 1: out to this place which is not near my house.

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Speaker 1: It's the only place in Victoria I could get one.

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Speaker 1: They'd just been released. Bought it, and while I was there,

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Speaker 1: I bought this like fucking I don't know what it was,

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Speaker 1: titanium chain or something that you can't cut through, and

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Speaker 1: just so I could lock. Apart from the steering lock

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Speaker 1: on the bike, I could also lock it so nobody

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Speaker 1: could pinch it. Blah blah blah, and I was I

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Speaker 1: had to go back the next day to pick it up.

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Speaker 1: So anyway, I went back the next day, because that's

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Speaker 1: pre deliberate all that. I picked it up. Friend of

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Speaker 1: mine dropped me off road at home Bibby Bobby Boo.

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Speaker 1: Still hadn't seen one on the road, so I was

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Speaker 1: super proud of myself. Next day, I was going to

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Speaker 1: work driving and I saw opposite me at an intersection

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Speaker 1: in fact, Nepeane Highway South Road, opposite me, going the

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Speaker 1: opposite direction to me. Of course, I go, oh my god,

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Speaker 1: there's my bike. Little did I know it was actually

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Speaker 1: my fucking bike, right, And I'm like, look at that, dude,

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Speaker 1: and it's the same and it's you know, obviously I

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Speaker 1: hadn't memorized the number plate, but I didn't even think.

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Speaker 2: And then later that day I got home and clearly

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Speaker 2: mine was gone.

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Speaker 1: So I actually saw the guy flogging my riding away

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Speaker 1: on my bike, and I'm thinking what a gun is

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Speaker 1: because he's got a bike like me. And then but

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Speaker 1: the dumb thing that I did was, so you buy

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Speaker 1: it from and of course most dealers are not like this.

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Speaker 1: But you buy it from the dealer and you pick

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Speaker 1: it up tomorrow. So they can cut a key to

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Speaker 1: the bike. They can cut a key to the padlock.

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Speaker 1: All the bits and pieces I bought for security, they

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Speaker 1: can replicate in the day between when you sign on

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Speaker 1: the dotted and when you get it. So the guy

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Speaker 1: who stole it, at the very least worked for the dealership,

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Speaker 1: or worked for the dealership, or knew someone who did.

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Speaker 1: So he just came to my joint, which he also

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Speaker 1: had the address because I signed all the paper, drove

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Speaker 1: to my joint, or got dropped off, had all the

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Speaker 1: keys unlocked, everything just rode it away And you're like, ah,

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Speaker 1: and then, which is understandable. But then I got interrogated

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Speaker 1: for about four hours by the fucking insurance company like

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Speaker 1: I was a criminal and I had done this.

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Speaker 2: So yeah, I sympathize with you.

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Speaker 3: Wow. Yeah, that's that's pretty fun, isn't it.

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Speaker 2: Oh Yeah, it's ridiculous. It's ridiculous. What are we what

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Speaker 2: are we teching today? Is there anything that takes your

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Speaker 2: fancy or do you.

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Speaker 3: Just want me to throw a CPR CREPR story. And

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Speaker 3: this is one of the most bizarre things. It doesn't

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Speaker 3: surprise me in the slightest. Meta basically had patented. It's

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Speaker 3: come out that they painted a AI that would continue

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Speaker 3: to post for you when you die.

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Speaker 2: Who yeah, who wants that?

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Speaker 3: Yeah? So now this happened in December, and they weren't

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Speaker 3: the first to do it. Microsoft actually had the same

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Speaker 3: idea but then shelved it's saying, yeah, probably a bit

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Speaker 3: creepy if we have a Chatbotton model. This was that

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Speaker 3: in twenty twenty one. But they're saying now, no, no, no,

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Speaker 3: we're not really going to use it. The idea had

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Speaker 3: come out of so say, for example, Crago on the

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Speaker 3: typ channel on Facebook decides to go away on an

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Speaker 3: extended holiday. You could effectively use this to post for

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Speaker 3: you while you're on a break, and I think part

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Speaker 3: of the idea. And then someone thought, ky, but what

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Speaker 3: if someone dies, it could keep posting for them, and

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Speaker 3: soily and you know that if you can, if you

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Speaker 3: could put all of your collected works into an AI,

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Speaker 3: it would really be able to mimic your voice. So

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Speaker 3: in a lot while it could effectively and who knows

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Speaker 3: down the track podcasting it could you know, it could

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Speaker 3: just be Tiff and I and an AI.

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Speaker 2: Well, very well could be.

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Speaker 1: I mean the quality of the kind of AI podcasts

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Speaker 1: that are using, you know, celebrities voices a part some

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Speaker 1: times from the cadence or the timing. But it's pretty indistinguishable.

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Speaker 1: I mean it is, but it's getting very close to

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Speaker 1: being you wouldn't know. So I also see that some

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Speaker 1: artists and writers, and I thought this would be the case,

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Speaker 1: quite hesitant to disclose when they're using AI or collaborating

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Speaker 1: with AI. What do you think the reason is for that?

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Speaker 1: Just embarrassment or fear of losing legitimacy or legitimacy.

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Speaker 3: There's a perception out there if you're an artist and

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Speaker 3: you say, oh, yeah, by the way, I used AI

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Speaker 3: to help get some themes for my new book, then

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Speaker 3: the authenticity and the sense of creativity is diluted.

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Speaker 2: I think yes.

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Speaker 3: But interestingly, there was a little bit of a research study,

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Speaker 3: and what they did was they took two and a

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Speaker 3: half thousand creative professionals and across four continents, and this

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Speaker 3: is a study done in twenty twenty four, and they

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Speaker 3: found that eighty five percent of them we're using AI

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Speaker 3: in work. Now, if you use AI to help you

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Speaker 3: get organized in the day, you help manage your emails,

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Speaker 3: and then you jump into the creative process. Even then,

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Speaker 3: the fact that AI is helping you was still a

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Speaker 3: bit of a stigma for most people. That the perception

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Speaker 3: was that you were almost like you're cheating by using AI.

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Speaker 3: I mean, I think I use it for concept work

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Speaker 3: sometimes if I'm stuck on an idea and then I think, well, yeah,

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Speaker 3: maybe I'll just jump into AI. Sometimes it's awful, it's terrible.

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Speaker 3: Other times you think, oh, yeah, that's not a bad idea.

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Speaker 3: I think that at the end of the day, it's

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Speaker 3: just like any tool. I'm sure you know people were

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Speaker 3: saying this when computers came out, and you know the

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Speaker 3: fact that we were using these devices or adding machines,

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Speaker 3: you know, calculators rather than an advocate. Yeah, and I

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Speaker 3: think it's just about global acceptance that, you know, as

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Speaker 3: it gets more and more integrated. I know that when

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Speaker 3: I take a photograph and I send peopleographs, now I

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Speaker 3: have an option to press a button and it's nano

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Speaker 3: banana on my phone and wow, lick the nano banana button.

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Speaker 3: I can change that photo. Before I send it. So

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Speaker 3: I was sitting talking to some friends. We were in

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Speaker 3: a walking group. We go walking together every Thursday morning.

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Speaker 3: We've been doing it for about fifteen or sixteen years,

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Speaker 3: and then we have a coffee afterwards. And I was

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Speaker 3: explaining this to a friend of mine. She was talking

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Speaker 3: about using AI and so I took a photo of

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Speaker 3: the group of people sitting at the table, and I

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Speaker 3: just in the prompt, I said, turn this into a

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Speaker 3: Christmas scene. Suddenly there was a Christmas tree in the background,

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Speaker 3: ballbles and decorations on the table, and you know, the

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Speaker 3: same people were there. One person was a little Christmas

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Speaker 3: hat and it did literally changed the you know what

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Speaker 3: was there. But it makes me wonder too. The reality

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Speaker 3: was so clear, it looked so real. I almost turned

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Speaker 3: it around to the other people and said, hey, remember

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Speaker 3: this is funny. We were sitting in the same positions

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Speaker 3: this time last year in December, you know, just to

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Speaker 3: see if I could fool anybody, because not everybody was

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Speaker 3: listening to the conversation. There were people in their own conversation,

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Speaker 3: you know, when you sit around with a group of people.

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Speaker 3: But the reality, well, the reality is there is no reality.

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Speaker 3: You know, are we being deceived. Well, yeah, maybe we are.

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Speaker 3: And credibility, where does that work? I mean, you use

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Speaker 3: AI all the time.

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Speaker 2: Craigo, I use it for different things.

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Speaker 1: But it's interesting you say this because, like all of

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Speaker 1: the stuff that I write on Instagram, if you don't

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Speaker 1: follow me on Instagram, folks, that's fine. But if you

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Speaker 1: want to just quig Anthony Harper. But like, I'll put

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Speaker 1: up some things like I'm just looking at one post

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Speaker 1: right now.

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Speaker 2: I wanted to read you this for a reason. It

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Speaker 2: just says it's handwritten on a whiteboard by me, one

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Speaker 2: hundred percent original. It's not brilliant.

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Speaker 1: But of course life's a shit show and then it's awesome,

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Speaker 1: and then you're sad and then happy, and then it's lunchtime.

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Speaker 1: Your challenge is not to create a perfect life, but

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Speaker 1: rather to thrive in the inevitable imperfection of it all. Now,

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Speaker 1: I've posted that post probably fifteen times over the last

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Speaker 1: few years, and the worst it ever gets is a

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Speaker 1: million views. One time it got two and a half

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Speaker 1: million views. Right, so I thought, I'm going to take that.

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Speaker 1: I took that and a few other higher rating ones,

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Speaker 1: and I wrote, so these are posts that I put

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Speaker 1: on Instagram on hundred percent original, written with my hand

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Speaker 1: on a whiteboard, taken a photo of tied it up

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Speaker 1: a bit, you know, made a bit clearer and cleaner.

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Speaker 2: I want you to come up with a post.

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Speaker 1: Similar to this or similar to these, written in my style,

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Speaker 1: a bit of swearing, whatever, but original. They were fucking terrible,

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Speaker 1: like terrible, like not like, oh my god, you couldn't

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Speaker 1: you know. But if you want to go, hey, tell

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Speaker 1: me a funny story about how the pyramids were built, well,

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Speaker 1: it can crush that, right, Or you want to give

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Speaker 1: me your thoughts on like yesterday. I'll talk for a

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Speaker 1: minute or two and then I'll shut up. But this

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Speaker 1: is very relevant to you.

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Speaker 2: Have you opened the door at all on AI agents

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Speaker 2: like agentic ai?

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Speaker 3: Yeah, a little bit. It just looks into.

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Speaker 1: Okay, So I just want to read this because this

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Speaker 1: blew me away. So agentic AI refers to artificial intelligence

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Speaker 1: systems that don't just respond to prompts. They take initiative,

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Speaker 1: set goals, make decisions, and act autonomously to achieve an objective.

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Speaker 1: In simple terms, traditional AI answers questions, agentic AI pursues outcomes.

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Speaker 1: And this is happening now. The core idea. Most current

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Speaker 1: AI tools, including chat assistance, are reactive. You asked the answer,

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Speaker 1: agentic ai is goal oriented and self directed.

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Speaker 2: You give it an outcome that you want.

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Speaker 1: It figures out the steps, it executes them, and it

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Speaker 1: adapts if and when needed. Key features of agentic ai

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Speaker 1: goal rn entered works to find towards defined objectives. Autonomous

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Speaker 1: decision making chooses actions without human input, planning ability breaks

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Speaker 1: large goals in small blah uh. I'm like, this is

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Speaker 1: just a person. This is a person. And I was

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Speaker 1: listening to a guy yesterday who's the boss of Uber.

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Speaker 1: His name is Dara Koshwahari or something. But anyway, when

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Speaker 1: he took over Uber, they were losing three billion a

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Speaker 1: year in twenty seventeen. They are now making ten billion

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Speaker 1: a year. And he's they're implementing all of these kind

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Speaker 1: of you know, these AI kind of agents to take

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Speaker 1: positions and they're employing other people. They're still one of

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Speaker 1: the biggest employers in the world, but it's the shit

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Speaker 1: that's happening. It's almost like you can't keep up. And yeah,

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Speaker 1: because Melissa started telling me about she wants to build

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Speaker 1: this team of agents, and I'm like, haka, are you

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Speaker 1: going to sack Tiff?

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Speaker 2: And I what's going on?

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Speaker 3: So there's a really lovely sense of authenticity to you

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Speaker 3: writing your posts on a whiteboard and taking a photo

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Speaker 3: and putting it up there. Last year I did a little,

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Speaker 3: a little kind of project that I started for myself,

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Speaker 3: and I had a whiteboard marker in my bathroom and

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Speaker 3: on the mirror. Every night before I went to bed,

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Speaker 3: after I brushed my teeth, i'd write a high coup.

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Speaker 3: So that's a Japanese poem. It's a five seven five

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Speaker 3: syllable so one line of five syllables, one line of seven,

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Speaker 3: one line of five. And it was really interesting pushing

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Speaker 3: yourself to be creative. You know, at the end of

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Speaker 3: the day, I'm always a bit tired, but I really

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Speaker 3: set myself a goal to write a highkup every single day,

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Speaker 3: and it was such a fun challenge. And I started

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Speaker 3: taking photos of them, which was kind of fun. You know,

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Speaker 3: I'd have to go back and look for them, and

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Speaker 3: I don't think they were earth shattering, and I don't

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Speaker 3: think I'm going to publish a book of haiku. But

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Speaker 3: there was a study recently a psychologists now saying that

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Speaker 3: people who write shopping lists. Physically writing a shopping list

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Speaker 3: rather than typing it into your phone. Instead of that,

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Speaker 3: they're actually using a cognitive processing and that actually strengthens

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Speaker 3: your memory. It's also intention and presence, and that doesn't

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Speaker 3: happen when you type it into a phone. So physically writing,

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Speaker 3: forming the words helps with the intention and the intent

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Speaker 3: and memorizing what it is on that list. So I

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Speaker 3: thought that's interesting and the fact that doing that, And

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Speaker 3: I know we've laughed at me many times about the

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Speaker 3: fact that I like to use a fountain pen. But

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Speaker 3: I love writing still and I adore writing, and I

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Speaker 3: still like using technology. But it's interesting, isn't it.

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Speaker 2: I'm with you. I think it is.

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Speaker 1: Like there's a lot of mellow drama at the moment

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Speaker 1: around around apps and around the use of AI, and

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Speaker 1: around the use of social media broadly, but I think

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Speaker 1: that every individual needs to be I have this chat

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Speaker 1: with Gillespie and tiff about, you know, just like, really,

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Speaker 1: what is happening with these brains that are getting hijacked

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Speaker 1: by this medium? And so literally you it takes your attention.

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Speaker 1: You're not choosing what to focus on, it's choosing for you.

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Speaker 1: And so now you are just a passenger. You're not

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Speaker 1: driving the bus like it has your attention, not the

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Speaker 1: other way around. So it's like I thought about it,

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Speaker 1: and definitely I've got an issue, definitely, and I have

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Speaker 1: to change it because it's my brain is my most

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Speaker 1: important tool and if anything that's going to kind of

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Speaker 1: impact my ability to think clearly, focus, create resolved problems,

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Speaker 1: you know, like use my brain well and keep my

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Speaker 1: brain healthy. To me, it's almost like I'm doing all

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Speaker 1: this training then coming home and eating doughnuts and pizza.

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Speaker 1: That's the that's the analogy for me, Like I do

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Speaker 1: all of this work with my brain and then I

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Speaker 1: just fucking unplugged my brain and let this thing hijack

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Speaker 1: my prefrontal cortex. So I'm off line and it's online

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Speaker 1: and it's I fucking hate it.

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Speaker 2: I've got to stop it.

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Speaker 3: I got a really interesting email during the week from

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Speaker 3: one of our listeners. Dale is his name Dale Patterson,

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Speaker 3: and it was a blog article that he sent through

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Speaker 3: to me about AI slop. And it's a guy by

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Speaker 3: the name of Gwinder whose handle is Gerwinder, and it's

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Speaker 3: a blog called The Prism. And what he did was

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Speaker 3: he took a whole lot of phrases, and he just

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Speaker 3: kind of paraphrased each of the key terms. So one

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Speaker 3: of them was the one percent rule. So in online communities,

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Speaker 3: one percent of users produce almost all of the content. Yeah,

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Speaker 3: the ninety nine consumers, the one person generating a content.

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Speaker 3: And then he talked about slopaganda. More online articles are

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Speaker 3: now written by AI than humans, so if you look

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Speaker 3: at an article, there's a good chance that it's going

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Speaker 3: to be an AI written article, not a human one. Moloch'spargan.

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Speaker 3: This is when large learning models so AIS compete for

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Speaker 3: votes on social media, so they push lies and rage

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Speaker 3: bait to actually win. So it's not about it's trying

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Speaker 3: to get that engagement and to get the most posts

434
00:23:19,920 --> 00:23:23,280
Speaker 3: possible or the most likes possible, So that doesn't matter.

435
00:23:23,320 --> 00:23:26,520
Speaker 3: There's no filter to say this is actually really crap.

436
00:23:26,800 --> 00:23:30,760
Speaker 3: It's just about getting that algorithm right. But this is

437
00:23:30,800 --> 00:23:32,159
Speaker 3: the one that made me think of what you were

438
00:23:32,200 --> 00:23:34,960
Speaker 3: just talking about before and switching off. I love the

439
00:23:35,000 --> 00:23:40,400
Speaker 3: paradox of boredom. We walk around with the most powerful

440
00:23:40,840 --> 00:23:45,159
Speaker 3: supercomputers that you can imagine in our pocket, and the

441
00:23:45,200 --> 00:23:48,119
Speaker 3: reality of that means the second that you get bored,

442
00:23:48,119 --> 00:23:51,000
Speaker 3: and I do this all the time. I swipe, I

443
00:23:51,119 --> 00:23:52,840
Speaker 3: jump on, I look at it, and for me it's

444
00:23:52,880 --> 00:23:55,359
Speaker 3: reading articles or whatever it happens to be looking at

445
00:23:55,440 --> 00:23:58,600
Speaker 3: YouTube reels. But the reality of it is, we don't

446
00:23:58,600 --> 00:24:01,680
Speaker 3: get bored anymore because we've always got something there to

447
00:24:01,760 --> 00:24:06,760
Speaker 3: keep us entertained. And boredom is what fuels creativity, not

448
00:24:06,880 --> 00:24:09,960
Speaker 3: having technology. So because our brains are constantly looking for

449
00:24:10,000 --> 00:24:13,119
Speaker 3: that excitement, it's there all the time. But if we

450
00:24:13,160 --> 00:24:16,320
Speaker 3: take that away, if we say to ourselves, Okay, I'm

451
00:24:16,320 --> 00:24:18,600
Speaker 3: going to go cold turkey on this, I'm going to

452
00:24:18,600 --> 00:24:21,120
Speaker 3: go Could you imagine going away for a weekend and

453
00:24:21,160 --> 00:24:26,720
Speaker 3: not taking your phone? Yeah, I've beach or going like

454
00:24:26,880 --> 00:24:27,359
Speaker 3: or a walk.

455
00:24:27,480 --> 00:24:31,840
Speaker 1: Yeah, but that, if I'm being honest, would that scare

456
00:24:31,880 --> 00:24:34,480
Speaker 1: me a little bit? It would, which is probably why

457
00:24:34,520 --> 00:24:38,280
Speaker 1: the fuck I should do it. I think we bullshit ourselves.

458
00:24:38,320 --> 00:24:41,680
Speaker 1: I think most people that I know, I don't think

459
00:24:41,720 --> 00:24:44,240
Speaker 1: you're one. I'm not Tiff would have to decide for myself,

460
00:24:44,280 --> 00:24:48,520
Speaker 1: but most people that I know, including me, actually have

461
00:24:48,600 --> 00:24:51,520
Speaker 1: a little bit of a problem. I'm not saying it's

462
00:24:51,600 --> 00:24:54,840
Speaker 1: life destroying, but I'm like, I definitely have something that

463
00:24:54,880 --> 00:24:57,640
Speaker 1: I need to put on my big boy pants and go, Yeah,

464
00:24:57,760 --> 00:25:00,520
Speaker 1: I waste time and I do the thing that I

465
00:25:00,600 --> 00:25:03,960
Speaker 1: tell people not to do, and I don't even I

466
00:25:04,080 --> 00:25:04,959
Speaker 1: kind of choose it.

467
00:25:05,520 --> 00:25:07,760
Speaker 2: But you know, the story is always I'm just going

468
00:25:07,800 --> 00:25:11,000
Speaker 2: to see what's happening with this, And then forty minutes later,

469
00:25:11,040 --> 00:25:13,520
Speaker 2: I'm like, I don't even know what started me. But

470
00:25:13,680 --> 00:25:16,720
Speaker 2: here I am forty minutes later, and I've just wasted

471
00:25:16,760 --> 00:25:20,760
Speaker 2: forty minutes of energy and fucking time productivity. You know.

472
00:25:20,880 --> 00:25:23,639
Speaker 3: So I don't know what I should bring up this

473
00:25:23,720 --> 00:25:25,960
Speaker 3: next topic because I know that you're going to ridicule me.

474
00:25:26,200 --> 00:25:30,359
Speaker 3: And I was watching a documentary recently on a new

475
00:25:30,480 --> 00:25:34,800
Speaker 3: term in the community online called gooning. Do you know

476
00:25:34,840 --> 00:25:37,159
Speaker 3: what gooning is? Do either of you know what gooning is?

477
00:25:39,960 --> 00:25:41,760
Speaker 2: I do not carry on.

478
00:25:42,160 --> 00:25:44,359
Speaker 3: I feel like the person, why why do you do.

479
00:25:44,320 --> 00:25:46,520
Speaker 1: This if you know it's going to not produce a

480
00:25:46,520 --> 00:25:50,959
Speaker 1: good response. What's your agenda? What's your reason?

481
00:25:51,080 --> 00:25:53,920
Speaker 3: I have no agenda. I'm trying to educate the masses

482
00:25:54,000 --> 00:25:55,840
Speaker 3: to masses.

483
00:25:56,520 --> 00:25:59,840
Speaker 2: Can look at you, Jesus, trying to educate the masses.

484
00:26:00,160 --> 00:26:04,080
Speaker 3: Two masses debating? No, okay, because okay, so gooning is

485
00:26:04,119 --> 00:26:10,320
Speaker 3: a term that's used to prolong the sexual build up.

486
00:26:11,280 --> 00:26:14,760
Speaker 1: Wow, right, so well there's only one of us, well

487
00:26:14,880 --> 00:26:16,800
Speaker 1: one two of us on this goal.

488
00:26:16,920 --> 00:26:20,520
Speaker 3: For whom that is relevant, well yeah, anyway, it could

489
00:26:20,520 --> 00:26:20,840
Speaker 3: be one.

490
00:26:21,200 --> 00:26:23,240
Speaker 1: But I did the same thing with food. I just

491
00:26:23,320 --> 00:26:25,720
Speaker 1: walk around it for half an hour and think about it.

492
00:26:26,040 --> 00:26:29,359
Speaker 3: But the frightening thing about this documentary that I saw

493
00:26:29,600 --> 00:26:34,000
Speaker 3: is that people can engage in this by just looking

494
00:26:34,000 --> 00:26:37,120
Speaker 3: at pornography. They have multiple screens, projectors, and all they

495
00:26:37,119 --> 00:26:39,880
Speaker 3: do is they spend a whole lot of time. We're

496
00:26:39,880 --> 00:26:43,840
Speaker 3: talking hours, eight hours, nine hours, ten hours just looking

497
00:26:43,880 --> 00:26:47,479
Speaker 3: at pornography. And there's a whole online communities that are

498
00:26:47,520 --> 00:26:49,720
Speaker 3: now dedicated to this. So once upon a time, it

499
00:26:49,800 --> 00:26:52,320
Speaker 3: was kind of embarrassing, Oh well you know, I kind

500
00:26:52,320 --> 00:26:55,159
Speaker 3: of that person did whatever. But now it's become a

501
00:26:55,200 --> 00:26:59,439
Speaker 3: whole thing. But talk about throwing your life away. I

502
00:26:59,480 --> 00:27:04,480
Speaker 3: mean I couldn't imagine spending a whole day like yeah anyway.

503
00:27:04,600 --> 00:27:08,840
Speaker 1: But I find that sad because that one hundred percent

504
00:27:08,960 --> 00:27:12,640
Speaker 1: nobody's doing that who's not an addict. Yeah, nobody's doing

505
00:27:12,640 --> 00:27:15,960
Speaker 1: that for any logical, healthy reason. Yeah, I mean all

506
00:27:16,000 --> 00:27:18,560
Speaker 1: of those people are addicted. Could be anything else. But

507
00:27:18,640 --> 00:27:21,879
Speaker 1: it's like, yeah, I don't know that's stuff.

508
00:27:21,920 --> 00:27:23,680
Speaker 2: It's like yeah, and.

509
00:27:23,640 --> 00:27:26,720
Speaker 3: Then well, artificial intimacy. And I'm kind of jumping off

510
00:27:26,720 --> 00:27:28,879
Speaker 3: that topic. But on that same list that I was

511
00:27:28,880 --> 00:27:32,960
Speaker 3: talking about the blog, you know, I had a young

512
00:27:33,000 --> 00:27:36,159
Speaker 3: guy who was sharing a long story anyway, lived me

513
00:27:36,200 --> 00:27:39,000
Speaker 3: be for three years, got kicked out of home. He

514
00:27:39,040 --> 00:27:41,399
Speaker 3: and his girlfriend were sitting on the couch once and

515
00:27:41,440 --> 00:27:44,600
Speaker 3: they were they were comparing how many friends they had

516
00:27:44,920 --> 00:27:48,480
Speaker 3: on their Facebook, on their facebooks, and I thought, they're

517
00:27:48,520 --> 00:27:53,679
Speaker 3: not your friends. You know, this artificial intimacy. You know,

518
00:27:54,600 --> 00:27:57,560
Speaker 3: no one on your Facebook list, if you've got a

519
00:27:57,600 --> 00:28:01,320
Speaker 3: thousand Facebook friends, No, they're not your friends.

520
00:28:01,520 --> 00:28:04,800
Speaker 2: But do you know what is interesting? One, you're correct.

521
00:28:05,000 --> 00:28:09,680
Speaker 1: Two from a psychological, sociological, and experiential.

522
00:28:09,000 --> 00:28:11,240
Speaker 2: Perspective, this is what I think.

523
00:28:11,320 --> 00:28:15,520
Speaker 1: Let's say somebody's got an AI friend and the net

524
00:28:15,560 --> 00:28:19,840
Speaker 1: result of their AI friend is positive. I'm not saying

525
00:28:19,880 --> 00:28:22,840
Speaker 1: that's always a case, of course it isn't. But somebody

526
00:28:22,880 --> 00:28:26,840
Speaker 1: who lives in rural wherever they live ten miles from

527
00:28:26,880 --> 00:28:29,439
Speaker 1: the next house, they're a bit disconnected. Maybe they've got

528
00:28:29,480 --> 00:28:32,520
Speaker 1: a few personal challenges, but every day they get up

529
00:28:32,560 --> 00:28:37,000
Speaker 1: and they talk to this friend and for them they

530
00:28:37,000 --> 00:28:41,200
Speaker 1: feel better, they feel you know, and obviously it's not

531
00:28:41,240 --> 00:28:45,440
Speaker 1: a real human and obviously the emotions.

532
00:28:45,600 --> 00:28:47,920
Speaker 2: The other way anyway are not real. But for the.

533
00:28:47,880 --> 00:28:51,280
Speaker 1: Person, those emotions and feelings might be real, which means

534
00:28:51,320 --> 00:28:55,560
Speaker 1: the net result the experience is good, which is not

535
00:28:55,640 --> 00:28:57,680
Speaker 1: saying I think everyone should be doing that. But I

536
00:28:57,800 --> 00:29:04,440
Speaker 1: think this area of the impact of relationships with different

537
00:29:04,560 --> 00:29:09,520
Speaker 1: forms of technology, I think that's going to become more

538
00:29:09,560 --> 00:29:11,160
Speaker 1: and more of a thing because I think.

539
00:29:11,000 --> 00:29:12,680
Speaker 2: People are going to more and more people are.

540
00:29:12,560 --> 00:29:14,600
Speaker 1: Going to have, for want of a more accurate term,

541
00:29:15,080 --> 00:29:17,880
Speaker 1: relationships with virtual entities.

542
00:29:18,640 --> 00:29:22,360
Speaker 3: I want one. I can't wait. I cannot wait, And

543
00:29:22,440 --> 00:29:24,360
Speaker 3: I think we talked about it on the last podcast.

544
00:29:24,400 --> 00:29:27,160
Speaker 3: I want an AI assistant. You know in the Iron

545
00:29:27,200 --> 00:29:29,080
Speaker 3: Man film's table that's different.

546
00:29:29,120 --> 00:29:32,520
Speaker 1: An II assistant is not an emotional relationship.

547
00:29:32,720 --> 00:29:35,360
Speaker 2: But if we're talking about intimacy, but.

548
00:29:35,400 --> 00:29:37,720
Speaker 3: No, I'm thinking, like in your case, you've got Melissa,

549
00:29:37,880 --> 00:29:40,760
Speaker 3: I'm thinking that where you've got someone you can talk to,

550
00:29:41,120 --> 00:29:43,400
Speaker 3: you can kind of say, well, what's happening today, what's up?

551
00:29:43,440 --> 00:29:46,520
Speaker 3: You know, have a full on confirmation. I know what

552
00:29:46,520 --> 00:29:49,239
Speaker 3: you're saying. But I think that eventually the more you

553
00:29:49,320 --> 00:29:52,760
Speaker 3: rely on that. I mean in the I'm talking about

554
00:29:52,800 --> 00:29:55,240
Speaker 3: a movie here, but we all felt kind of, you know,

555
00:29:55,560 --> 00:29:59,920
Speaker 3: warm about Javis, the AI that Tony Stark uses. I thought,

556
00:30:00,080 --> 00:30:03,320
Speaker 3: I want him to be my friend too. So I think,

557
00:30:03,560 --> 00:30:05,400
Speaker 3: even though we know it's an AI, even though we

558
00:30:05,440 --> 00:30:07,680
Speaker 3: know it's a chat bot or whatever, that it would

559
00:30:07,720 --> 00:30:10,600
Speaker 3: be impossible not to form some sort of connection, some

560
00:30:10,640 --> 00:30:14,400
Speaker 3: sort of fondness for that entity that is with you

561
00:30:14,560 --> 00:30:17,560
Speaker 3: every day if you wake up chatting and what am

562
00:30:17,560 --> 00:30:19,920
Speaker 3: I doing today? How can I better do this? Because

563
00:30:19,960 --> 00:30:23,239
Speaker 3: we start to rely on it, and that crutch that

564
00:30:23,280 --> 00:30:26,800
Speaker 3: we start to use, it can be beneficial. It'll be fantastic.

565
00:30:26,840 --> 00:30:28,760
Speaker 3: Don't forget to do this. Don't forget to do that.

566
00:30:28,920 --> 00:30:31,920
Speaker 3: You know, you know we've got this coming up. I

567
00:30:32,000 --> 00:30:35,600
Speaker 3: think that we would eventually form a relationship of sorts

568
00:30:35,640 --> 00:30:37,560
Speaker 3: with whatever AI chat what we're using.

569
00:30:38,440 --> 00:30:40,200
Speaker 1: And put up your hand. If you've ever been in

570
00:30:40,240 --> 00:30:44,760
Speaker 1: an unhealthy human relationship, everyone in the fucking world, you know, yes,

571
00:30:45,640 --> 00:30:46,280
Speaker 1: Tip's ready.

572
00:30:46,520 --> 00:30:46,720
Speaker 3: Yeah.

573
00:30:46,800 --> 00:30:50,080
Speaker 5: Come thinking about the impact, the long term impact of

574
00:30:50,560 --> 00:30:53,560
Speaker 5: just another area in our life where we are essentially

575
00:30:53,600 --> 00:30:57,400
Speaker 5: avoiding discomfort because I think about the conversations I've had

576
00:30:57,480 --> 00:31:02,320
Speaker 5: on friendships and relationships where rupture and repair is what

577
00:31:02,440 --> 00:31:08,600
Speaker 5: creates depth and intimacy. And yet then somebody chooses this

578
00:31:09,160 --> 00:31:11,960
Speaker 5: AI version of friendship which gives them all the feel goods.

579
00:31:11,960 --> 00:31:13,680
Speaker 4: But it's another area that.

580
00:31:13,640 --> 00:31:16,440
Speaker 5: We always having every other area of life where we

581
00:31:16,920 --> 00:31:19,239
Speaker 5: don't have to get uncomfortable, and in future then we

582
00:31:19,280 --> 00:31:22,600
Speaker 5: avoid it more and more, and what little connection we

583
00:31:22,840 --> 00:31:25,400
Speaker 5: already had with real people will have less of because

584
00:31:25,440 --> 00:31:28,160
Speaker 5: it's too hard. I'm not willing to get uncomfortable. I'm

585
00:31:28,160 --> 00:31:30,920
Speaker 5: not willing to express needs or show up for the

586
00:31:30,960 --> 00:31:34,680
Speaker 5: other person because in this relationship with AI, it's all

587
00:31:34,720 --> 00:31:35,120
Speaker 5: about me.

588
00:31:35,560 --> 00:31:38,320
Speaker 3: It's one sided. Yeah, that's so interesting, Tip, I actually

589
00:31:38,320 --> 00:31:40,920
Speaker 3: really like that point. I've often talked. You know, I've

590
00:31:40,960 --> 00:31:45,640
Speaker 3: got really close friends that have very differing political views,

591
00:31:45,720 --> 00:31:49,560
Speaker 3: I mean extremist political views. You know, they think veganism

592
00:31:49,680 --> 00:31:53,440
Speaker 3: is a wank. They like Donald Rump, you know they Yeah,

593
00:31:54,080 --> 00:31:58,920
Speaker 3: it's quite funny, and and but I like them a lot.

594
00:31:59,520 --> 00:32:04,480
Speaker 3: They're the lovely people. They're great friends. And if I

595
00:32:04,560 --> 00:32:06,760
Speaker 3: had an AI chatbot, it would just agree with everything

596
00:32:06,760 --> 00:32:08,600
Speaker 3: that I said. I love what you just said, Tip,

597
00:32:08,920 --> 00:32:11,280
Speaker 3: It's so true, and I love the challenges. I love

598
00:32:11,320 --> 00:32:13,440
Speaker 3: the diversity of people in my life. I like people

599
00:32:13,480 --> 00:32:16,520
Speaker 3: to argue with me, tell me I'm wrong, you know,

600
00:32:17,240 --> 00:32:21,400
Speaker 3: nag me for leaving my wallet in the car. But

601
00:32:21,480 --> 00:32:23,320
Speaker 3: the reality of it is here, who wants a whole

602
00:32:23,280 --> 00:32:25,320
Speaker 3: lot of yes men around you just kind of they're

603
00:32:25,360 --> 00:32:27,440
Speaker 3: telling you that you're great all the time.

604
00:32:27,920 --> 00:32:29,640
Speaker 5: How good is it when you've got a friend and

605
00:32:29,680 --> 00:32:31,640
Speaker 5: they're having a hard time and you get to show

606
00:32:31,760 --> 00:32:32,200
Speaker 5: up for them?

607
00:32:32,360 --> 00:32:33,760
Speaker 4: Well I was not going to do that.

608
00:32:34,200 --> 00:32:39,640
Speaker 2: Yeah, yeah, absolutely, you make valid points. I think.

609
00:32:41,320 --> 00:32:42,960
Speaker 1: I hear what you're both saying. I think it's a

610
00:32:42,960 --> 00:32:46,720
Speaker 1: little bit situation and context dependent, you know. I think

611
00:32:46,760 --> 00:32:48,720
Speaker 1: a lot of people don't have anyone that gives a

612
00:32:48,760 --> 00:32:51,440
Speaker 1: fuck about them, like really really really loves them and

613
00:32:51,480 --> 00:32:53,840
Speaker 1: really cares. And there are a lot of people who

614
00:32:53,840 --> 00:32:58,080
Speaker 1: are deeply, deeply sad and disconnected and alone. And I

615
00:32:58,200 --> 00:33:01,440
Speaker 1: don't for any minute think that AI is the answer

616
00:33:01,560 --> 00:33:04,800
Speaker 1: to that, just like I don't think one person is

617
00:33:04,840 --> 00:33:06,440
Speaker 1: the answer.

618
00:33:06,200 --> 00:33:07,600
Speaker 2: For any do you know what I mean? I think

619
00:33:07,640 --> 00:33:09,760
Speaker 2: the answer is us trying to figure out ourselves and

620
00:33:10,200 --> 00:33:11,280
Speaker 2: to understand our.

621
00:33:11,200 --> 00:33:13,680
Speaker 1: Own mind and our own emotions and our own behaviors

622
00:33:13,720 --> 00:33:16,920
Speaker 1: and our own subjective experience of life and to work

623
00:33:16,960 --> 00:33:20,360
Speaker 1: through that. But I think it's like it's for some

624
00:33:20,480 --> 00:33:24,520
Speaker 1: people it's going to be a positive addition to their life,

625
00:33:24,560 --> 00:33:28,600
Speaker 1: and for some people it's going to lead to some unhealthy, toxic, devastating,

626
00:33:29,000 --> 00:33:33,600
Speaker 1: bloody relationship or shudo relationship. But just like you know,

627
00:33:33,640 --> 00:33:35,480
Speaker 1: you've got someone in your life now, and from the

628
00:33:35,480 --> 00:33:41,160
Speaker 1: outside looking into it, if it seems to me overwhelmingly positive,

629
00:33:42,160 --> 00:33:45,200
Speaker 1: you know, but then you've also had other humans in

630
00:33:45,240 --> 00:33:48,040
Speaker 1: your life where that was the opposite, and the same

631
00:33:48,080 --> 00:33:53,880
Speaker 1: with me, It's like, I don't think because you know,

632
00:33:54,200 --> 00:33:56,720
Speaker 1: we build this connection, rapport and trust and love, which

633
00:33:56,760 --> 00:34:00,320
Speaker 1: is great, but as we know, that doesn't all ways

634
00:34:00,360 --> 00:34:03,600
Speaker 1: work out over the long term. So but you're right

635
00:34:03,640 --> 00:34:07,480
Speaker 1: in that, you know, being able to have hard relationships

636
00:34:07,720 --> 00:34:09,799
Speaker 1: and to be reflective and to be able to kind

637
00:34:09,840 --> 00:34:12,279
Speaker 1: of figure out what's going on with me really and

638
00:34:12,280 --> 00:34:14,960
Speaker 1: what's going on with me in relation to other people.

639
00:34:15,760 --> 00:34:19,359
Speaker 1: But I think nonetheless that moving forward, there will be

640
00:34:20,239 --> 00:34:24,040
Speaker 1: you know, in a decade, the prevalence of these kinds

641
00:34:24,080 --> 00:34:29,160
Speaker 1: of relationships I think is going to be high high.

642
00:34:29,280 --> 00:34:29,720
Speaker 2: Patrick.

643
00:34:29,840 --> 00:34:33,000
Speaker 1: Let's digress a little bit, because I saw this on

644
00:34:33,360 --> 00:34:37,239
Speaker 1: Telly or somewhere I saw this about this dude who

645
00:34:37,320 --> 00:34:43,759
Speaker 1: was trying to hack his robot. He's a programmer, and

646
00:34:43,800 --> 00:34:47,080
Speaker 1: he hacked his bloody vacuum he's robot vacuum because he

647
00:34:47,120 --> 00:34:50,400
Speaker 1: wanted to use it with his game console. And he

648
00:34:50,480 --> 00:34:56,319
Speaker 1: ended up hacking six seven hundred vacuums around America and

649
00:34:56,400 --> 00:34:59,320
Speaker 1: he could see into all these like he could literally

650
00:34:59,400 --> 00:35:02,600
Speaker 1: had video into all of these homes in real time of.

651
00:35:02,600 --> 00:35:07,360
Speaker 2: What people were doing. That's wasn't it. Yeah, that's fucking terrifying.

652
00:35:07,760 --> 00:35:12,320
Speaker 3: So Dji is the company that makes the amazing drones

653
00:35:12,480 --> 00:35:15,200
Speaker 3: that are very popular around the world. I think I've

654
00:35:15,320 --> 00:35:19,680
Speaker 3: exclusively had Dji drones. I still fly them. But they

655
00:35:19,719 --> 00:35:25,600
Speaker 3: released the Dji Romo robot vacuum cleaner recently. And so

656
00:35:25,719 --> 00:35:27,800
Speaker 3: this guy who was a bit of a security expert

657
00:35:27,880 --> 00:35:30,839
Speaker 3: and decided he wanted to use his joystick controlleries and

658
00:35:30,960 --> 00:35:32,720
Speaker 3: you know, his game control I think was the Xbox

659
00:35:32,760 --> 00:35:35,840
Speaker 3: controller or to control the vacuum. Thought would be a

660
00:35:35,840 --> 00:35:39,160
Speaker 3: bit fun, and then realized getting into the base code

661
00:35:39,239 --> 00:35:42,359
Speaker 3: that because they talked back to the bay station and

662
00:35:42,600 --> 00:35:45,440
Speaker 3: they learn because the idea of these robot vacuums is

663
00:35:45,480 --> 00:35:47,520
Speaker 3: they look at the world around them. They map the

664
00:35:47,600 --> 00:35:49,920
Speaker 3: area and then they use that to be able to

665
00:35:50,080 --> 00:35:54,120
Speaker 3: effectively clean better. But yeah, this is amazing. So he

666
00:35:54,120 --> 00:35:56,560
Speaker 3: didn't need a security pin or anything because he already

667
00:35:56,560 --> 00:35:59,680
Speaker 3: had an account. He was able to log in and

668
00:35:59,680 --> 00:36:02,680
Speaker 3: get access to other vacuum cleaners. And the scary thing

669
00:36:02,800 --> 00:36:05,160
Speaker 3: is that they have light sensors that can sense the

670
00:36:05,200 --> 00:36:08,520
Speaker 3: objects around them. They make maps of the house, and

671
00:36:08,560 --> 00:36:11,880
Speaker 3: they also have cameras. It's a frightening thought that someone

672
00:36:11,920 --> 00:36:15,040
Speaker 3: could then literally use your own device against you, to

673
00:36:15,400 --> 00:36:17,879
Speaker 3: spy on you, to map out your house, to look

674
00:36:17,880 --> 00:36:18,640
Speaker 3: at what you've got.

675
00:36:18,680 --> 00:36:21,680
Speaker 2: And it's crazy, as I understand it, correct me if

676
00:36:21,680 --> 00:36:23,840
Speaker 2: I'm wrong, but yet one that is fucking terrifying.

677
00:36:23,880 --> 00:36:26,440
Speaker 1: But the dude who did that obviously did it accidentally.

678
00:36:26,520 --> 00:36:28,600
Speaker 1: Then he went to whoever he needed to go to

679
00:36:28,640 --> 00:36:34,200
Speaker 1: and went, hey, guess what, I did this accidentally and

680
00:36:34,320 --> 00:36:36,360
Speaker 1: kind of put up his hands so that he wouldn't

681
00:36:36,360 --> 00:36:40,080
Speaker 1: be charged with any kind of I'm sure that's that's

682
00:36:40,120 --> 00:36:44,360
Speaker 1: a crime if he was doing it intentionally. But so yeah,

683
00:36:43,320 --> 00:36:48,080
Speaker 1: I think he just demonstrated to them that their system

684
00:36:48,200 --> 00:36:48,680
Speaker 1: or their.

685
00:36:48,520 --> 00:36:50,840
Speaker 2: Tech was relatively hackable and flawed.

686
00:36:51,360 --> 00:36:53,799
Speaker 3: Yeah, there are a lot of white they call them

687
00:36:53,800 --> 00:36:56,800
Speaker 3: white hat hackers out there that actually support the industry.

688
00:36:57,000 --> 00:37:00,239
Speaker 3: They look for vulnerabilities. Google has a competition that it

689
00:37:00,320 --> 00:37:03,520
Speaker 3: runs to try to get people to find vulnerabilities in

690
00:37:03,600 --> 00:37:05,919
Speaker 3: its systems, and then it gives them, it rewards them.

691
00:37:06,000 --> 00:37:08,160
Speaker 3: So yeah, there are a lot of really good programmers

692
00:37:08,200 --> 00:37:11,200
Speaker 3: out there who were altruistic and in some cases get

693
00:37:11,280 --> 00:37:14,160
Speaker 3: rewarded for that. But I thought this was interesting. And

694
00:37:14,200 --> 00:37:16,200
Speaker 3: the other thing as well. I didn't realize that robot

695
00:37:16,280 --> 00:37:19,520
Speaker 3: vacuum cleaners have microphones in them as well, the ultimate

696
00:37:19,600 --> 00:37:21,439
Speaker 3: spy device in the way.

697
00:37:21,840 --> 00:37:22,880
Speaker 2: Why would they need that.

698
00:37:23,440 --> 00:37:26,200
Speaker 3: I don't know. I'm not sure. Yeah, I don't know.

699
00:37:26,360 --> 00:37:28,480
Speaker 3: Maybe you can talk to them, Crago. It's like, hey,

700
00:37:28,520 --> 00:37:32,960
Speaker 3: little fella came over here. It's pretty lowly at my joint.

701
00:37:35,520 --> 00:37:41,200
Speaker 2: So they're launching a timber, yeah, wooden satellite that surely

702
00:37:41,680 --> 00:37:45,560
Speaker 2: that seems inconsistent with going into space like shit burning up.

703
00:37:46,000 --> 00:37:48,560
Speaker 3: No, No, quite the opposite. In fact, it's and shit

704
00:37:48,560 --> 00:37:51,000
Speaker 3: burning up is exactly right, So you're kind of right

705
00:37:51,040 --> 00:37:54,279
Speaker 3: and wrong. There was a bit of work done on

706
00:37:54,320 --> 00:37:56,919
Speaker 3: the International Space Station, and I think we chatted about

707
00:37:56,920 --> 00:38:00,360
Speaker 3: this maybe two years ago, where they were testing different

708
00:38:00,440 --> 00:38:03,759
Speaker 3: sorts of wood to see what their resilience was like

709
00:38:03,960 --> 00:38:08,160
Speaker 3: in space. Space debris and the chemicals that are released

710
00:38:08,160 --> 00:38:10,920
Speaker 3: into the atmosphere when a lot of satellites burn up

711
00:38:10,960 --> 00:38:13,520
Speaker 3: in the atmosphere, Aluminium, that sort of stuff are actually

712
00:38:13,600 --> 00:38:17,799
Speaker 3: quite toxic chemicals. And so a Japanese company has been

713
00:38:17,840 --> 00:38:21,040
Speaker 3: doing a lot of research into the concept of encasing

714
00:38:21,280 --> 00:38:25,680
Speaker 3: the satellite in wood, and it looks like that the

715
00:38:26,239 --> 00:38:29,719
Speaker 3: Ligno SAT is the first wooden satellite that's going to

716
00:38:29,719 --> 00:38:33,319
Speaker 3: be sent into space. And the reason that it's going

717
00:38:33,400 --> 00:38:36,279
Speaker 3: to be great is because when it eventually expires, it's

718
00:38:36,400 --> 00:38:39,200
Speaker 3: used by date. When it burns up in the atmosphere,

719
00:38:39,280 --> 00:38:41,839
Speaker 3: it's just wood, and it's not going to release I mean,

720
00:38:41,840 --> 00:38:44,759
Speaker 3: it's still going to have obviously electronics inside it, you know,

721
00:38:44,760 --> 00:38:48,480
Speaker 3: they're not carving up transistors like hand camping transistors. But

722
00:38:48,719 --> 00:38:51,520
Speaker 3: the bulk of the satellite, the exterior part, and it's

723
00:38:51,560 --> 00:38:53,839
Speaker 3: quite durable. The interesting thing that came out of this

724
00:38:53,920 --> 00:38:57,719
Speaker 3: research on the International Space Station is when you take

725
00:38:57,840 --> 00:39:00,799
Speaker 3: wood into space, there's no back to and there's no

726
00:39:00,920 --> 00:39:04,880
Speaker 3: moisture the things that normally will cause wood to rot,

727
00:39:05,120 --> 00:39:07,399
Speaker 3: so all the you know, and so when you think

728
00:39:07,440 --> 00:39:11,239
Speaker 3: about it. It's the perfect material to go out into

729
00:39:11,239 --> 00:39:14,279
Speaker 3: space because it's it's going to be fairly resilient. And

730
00:39:14,360 --> 00:39:17,279
Speaker 3: that's what came up during this research study. And now

731
00:39:17,560 --> 00:39:19,560
Speaker 3: the practical example is it looks like they're going to

732
00:39:19,600 --> 00:39:22,359
Speaker 3: fire off this, not fire off, they're going to put

733
00:39:22,360 --> 00:39:25,040
Speaker 3: it on board a launch saddle, a launch rocket, and

734
00:39:26,000 --> 00:39:27,799
Speaker 3: wooden satellites would be great.

735
00:39:28,080 --> 00:39:31,040
Speaker 2: Based on your no bacteria and no, what was the

736
00:39:31,040 --> 00:39:33,080
Speaker 2: other thing you said, like.

737
00:39:33,120 --> 00:39:35,719
Speaker 3: Because it's fro it's cold, So there's so the water

738
00:39:35,760 --> 00:39:37,600
Speaker 3: won't be rotting because bacteria is in water.

739
00:39:37,640 --> 00:39:39,760
Speaker 1: I guess No, No, you said in no space, in space,

740
00:39:39,800 --> 00:39:43,439
Speaker 1: there's like what causes the wood to write normally he's

741
00:39:43,440 --> 00:39:44,080
Speaker 1: not up there.

742
00:39:44,520 --> 00:39:46,920
Speaker 3: Yeah, that's right, so bacteria and water.

743
00:39:48,040 --> 00:39:50,480
Speaker 1: So I'm wondering if old mate was in space at

744
00:39:50,480 --> 00:39:53,040
Speaker 1: the space station and someone died and you just pushed

745
00:39:53,080 --> 00:39:55,880
Speaker 1: him out the door, would he just be held in

746
00:39:56,000 --> 00:39:57,760
Speaker 1: state perpetually kind of.

747
00:39:57,640 --> 00:40:01,800
Speaker 2: In space embarment and then you could.

748
00:40:01,640 --> 00:40:04,400
Speaker 1: Go grab him a couple of decades later, when we

749
00:40:04,520 --> 00:40:06,920
Speaker 1: figured out how to kind of restart the bit.

750
00:40:06,840 --> 00:40:09,640
Speaker 2: That broke and just pull him back on board, and

751
00:40:09,640 --> 00:40:12,160
Speaker 2: he's like, fuck, that was a good sleep. Yeah, you've

752
00:40:12,160 --> 00:40:15,000
Speaker 2: been sleeping for twenty five years, bro.

753
00:40:15,160 --> 00:40:17,200
Speaker 3: The Ultimate Crygenics. Yeah, that's right.

754
00:40:18,239 --> 00:40:21,959
Speaker 1: Hey, one battery swap, we're talking about cars. I don't

755
00:40:21,960 --> 00:40:23,560
Speaker 1: even know how would you do that? I must be

756
00:40:23,600 --> 00:40:28,200
Speaker 1: done by a machine. A battery slap. I'll swap. Obviously,

757
00:40:28,200 --> 00:40:32,000
Speaker 1: we're talking about EV's in less than zero point five seconds.

758
00:40:32,239 --> 00:40:37,920
Speaker 1: Neo sets new record for four consecutive days. So that

759
00:40:38,080 --> 00:40:42,799
Speaker 1: is battery life in evs and the technology around that

760
00:40:43,040 --> 00:40:44,560
Speaker 1: is changing pretty quickly.

761
00:40:45,640 --> 00:40:48,440
Speaker 3: So yeah, there's two aspects to that. So obviously, the

762
00:40:48,800 --> 00:40:52,120
Speaker 3: duration it takes to charge a battery has been a

763
00:40:52,160 --> 00:40:54,320
Speaker 3: bit of a pushback in the market because people do

764
00:40:54,400 --> 00:40:57,600
Speaker 3: want to wait all that time. So in China, Neo

765
00:40:58,440 --> 00:41:01,040
Speaker 3: has they do it. I think they've up over one

766
00:41:01,120 --> 00:41:03,799
Speaker 3: hundred and seventy five thousand battery swaps since they were

767
00:41:03,840 --> 00:41:07,799
Speaker 3: set up, and that's an amazing amount. So they basically

768
00:41:07,880 --> 00:41:10,480
Speaker 3: have a concept whereby if you buy this car, there

769
00:41:10,480 --> 00:41:12,719
Speaker 3: are all these service stations that are around China that you

770
00:41:12,719 --> 00:41:14,719
Speaker 3: can go to where you do a swap and go

771
00:41:15,040 --> 00:41:17,240
Speaker 3: so you don't charge the battery. They have a stock

772
00:41:17,320 --> 00:41:20,319
Speaker 3: supply of ready charged batteries and they swap and go

773
00:41:20,960 --> 00:41:26,520
Speaker 3: and the swap stations are now getting more batteries, they're

774
00:41:26,520 --> 00:41:28,880
Speaker 3: getting faster the technology because it used to take a while.

775
00:41:28,960 --> 00:41:31,880
Speaker 3: It used to take five minutes, four to five minutes

776
00:41:31,920 --> 00:41:34,160
Speaker 3: for the battery to be taken out and then swapped,

777
00:41:34,360 --> 00:41:36,040
Speaker 3: but now it's a lot more efficient. They've got a

778
00:41:36,080 --> 00:41:37,839
Speaker 3: lot better with it. And I know we spoke about

779
00:41:37,880 --> 00:41:41,399
Speaker 3: this with the motorcycle manufacturers, the top I think top

780
00:41:41,440 --> 00:41:44,919
Speaker 3: three motorcycle manufacturers, but they just electric cycles haven't taken

781
00:41:44,960 --> 00:41:49,440
Speaker 3: on very much. The e bikes have and they're ridiculously fast,

782
00:41:49,480 --> 00:41:52,800
Speaker 3: and legislations trying to catch up with that. The latest

783
00:41:52,800 --> 00:41:54,680
Speaker 3: on that is that I know I'm digressing, but the

784
00:41:54,760 --> 00:41:57,239
Speaker 3: latest on the e bikes thing is that they want

785
00:41:57,280 --> 00:42:00,239
Speaker 3: to actually classify them as motorbikes and make people will

786
00:42:00,280 --> 00:42:02,960
Speaker 3: have bikes bike licenses to be.

787
00:42:02,920 --> 00:42:05,640
Speaker 1: Able to well, they are essentially a lot of them.

788
00:42:05,840 --> 00:42:11,040
Speaker 1: But I think the thing that non motorbike people don't

789
00:42:11,080 --> 00:42:15,080
Speaker 1: really get about motorbikes, and Tip can speak to this

790
00:42:15,280 --> 00:42:18,600
Speaker 1: is who the fuck wants to ride something that's silent,

791
00:42:19,440 --> 00:42:23,680
Speaker 1: Like for me, it's about it's about the visceral, the vibration,

792
00:42:23,880 --> 00:42:27,839
Speaker 1: it's about the noise, it's about the throttle response, it's

793
00:42:27,840 --> 00:42:31,399
Speaker 1: about like and also one of the reasons people love

794
00:42:31,440 --> 00:42:35,839
Speaker 1: evs is because they're much faster than fuel cars or

795
00:42:36,480 --> 00:42:40,319
Speaker 1: internal combustion engines, right, but that's not the case with motorbikes.

796
00:42:40,560 --> 00:42:46,040
Speaker 1: Like my motorbikes are faster than you need. So yeah,

797
00:42:46,080 --> 00:42:48,560
Speaker 1: but nonetheless, I think they will take off, and they

798
00:42:48,600 --> 00:42:50,279
Speaker 1: are building, but I think it's going to be a

799
00:42:50,320 --> 00:42:56,920
Speaker 1: slower uptake because most motorcyclists ride them because they love motorbikes,

800
00:42:56,920 --> 00:42:59,000
Speaker 1: whereas a lot of people drive because they've got to

801
00:42:59,040 --> 00:42:59,719
Speaker 1: get from A to B.

802
00:43:01,680 --> 00:43:04,960
Speaker 3: Yeah, that's a good point. I was fascinated to see

803
00:43:05,080 --> 00:43:09,160
Speaker 3: that earlier this month, that company Neo with the swapover batteries.

804
00:43:09,360 --> 00:43:13,640
Speaker 3: They did the one hundred millionth battery swap, one hundred

805
00:43:13,880 --> 00:43:17,960
Speaker 3: million battery swap. That's crazy, so is it?

806
00:43:18,200 --> 00:43:20,360
Speaker 2: I don't know if you know. But so, like you

807
00:43:20,400 --> 00:43:22,080
Speaker 2: go to a servo, you put in your patrol, you

808
00:43:22,080 --> 00:43:24,560
Speaker 2: pay your eighty bucks or whatever you pay. So with

809
00:43:24,640 --> 00:43:27,080
Speaker 2: this you go and you get your battery slap swapped over,

810
00:43:27,160 --> 00:43:31,080
Speaker 2: and there's a set like obviously that's not for zero,

811
00:43:31,360 --> 00:43:33,520
Speaker 2: so they must have to go and pay a set

812
00:43:33,520 --> 00:43:35,560
Speaker 2: and fee every time that happens.

813
00:43:35,719 --> 00:43:38,480
Speaker 3: Yeah, I don't know. I'm I'm not entirely sure how

814
00:43:38,520 --> 00:43:40,719
Speaker 3: that how it works, what the charge would be. Yeah,

815
00:43:40,719 --> 00:43:43,239
Speaker 3: but for the convenience, that'd be awesome, wouldn't it.

816
00:43:43,760 --> 00:43:44,000
Speaker 2: Yeah?

817
00:43:44,200 --> 00:43:46,520
Speaker 1: Tip, Would you drive an EV as in a car?

818
00:43:46,680 --> 00:43:49,160
Speaker 1: Have you thought about I mean your cars?

819
00:43:49,719 --> 00:43:51,520
Speaker 2: It's not that at all, but it's what is your

820
00:43:51,520 --> 00:43:54,320
Speaker 2: car four or five years.

821
00:43:53,840 --> 00:43:59,600
Speaker 5: One's at twenty eighteen, so.

822
00:43:58,040 --> 00:44:00,840
Speaker 2: That's eighty ish years old. Would you X car? What

823
00:44:00,920 --> 00:44:04,120
Speaker 2: are the what are the percentage chances of your next

824
00:44:04,120 --> 00:44:04,959
Speaker 2: car being an EV?

825
00:44:05,640 --> 00:44:07,279
Speaker 4: I mean I'm not that far.

826
00:44:07,360 --> 00:44:09,319
Speaker 5: I'm not a real car person, so I don't like

827
00:44:09,360 --> 00:44:12,200
Speaker 5: the driving experience. I just find them. They when they

828
00:44:12,760 --> 00:44:14,400
Speaker 5: take off in front of me or I hear them,

829
00:44:14,440 --> 00:44:17,080
Speaker 5: they still freak me out. I find them weird, especially

830
00:44:17,719 --> 00:44:21,360
Speaker 5: EV buses, Like, yeah.

831
00:44:22,080 --> 00:44:25,880
Speaker 3: Buses are there, there's not that churning polluted diesel smell.

832
00:44:26,280 --> 00:44:28,280
Speaker 3: You know, if you're sitting behind on a bike, that'd

833
00:44:28,280 --> 00:44:31,200
Speaker 3: be awesome sitting behind an electric.

834
00:44:31,640 --> 00:44:33,840
Speaker 2: Very valid, very valid point, Patrick.

835
00:44:33,920 --> 00:44:38,000
Speaker 1: I have nearly died of carbon fucking monoxide poisoning a

836
00:44:38,080 --> 00:44:42,319
Speaker 1: thousand times, sitting behind fucking buses and trucks that are

837
00:44:42,360 --> 00:44:47,560
Speaker 1: just spewing out toxic shit into my face, that's not

838
00:44:47,600 --> 00:44:51,000
Speaker 1: the attractive part of it, be on the open road,

839
00:44:51,360 --> 00:44:52,000
Speaker 1: the fresh air.

840
00:44:53,120 --> 00:44:55,880
Speaker 3: The interesting point to that is that I think with

841
00:44:56,040 --> 00:44:59,760
Speaker 3: the EV market, my wish for that would be totally

842
00:45:00,000 --> 00:45:03,440
Speaker 3: aonymous EV. So I'm not talking about going for the

843
00:45:03,480 --> 00:45:07,640
Speaker 3: weekend drive. I'm thinking the commute because you put if

844
00:45:07,680 --> 00:45:11,799
Speaker 3: you put AI in charge of EV on the road

845
00:45:11,920 --> 00:45:15,600
Speaker 3: during the commute during the peak hour, I guarantee you

846
00:45:15,640 --> 00:45:17,880
Speaker 3: peak hour won't be as bad as what it is now,

847
00:45:18,320 --> 00:45:21,880
Speaker 3: take the huge kind of human error out of it,

848
00:45:22,360 --> 00:45:24,080
Speaker 3: and that's where I see it would be really good

849
00:45:24,120 --> 00:45:27,000
Speaker 3: for the daily commute. So people could be working in

850
00:45:27,040 --> 00:45:29,400
Speaker 3: their cars listening to an audiobook not having to worry

851
00:45:29,400 --> 00:45:32,520
Speaker 3: about that, no accidents on the roads, or less accidents

852
00:45:32,560 --> 00:45:34,840
Speaker 3: on the road. So I think that's where the combination

853
00:45:34,960 --> 00:45:38,160
Speaker 3: of EV and a AI together would be great. But

854
00:45:38,480 --> 00:45:41,880
Speaker 3: when I had my car windows smashed last week, I

855
00:45:41,960 --> 00:45:45,160
Speaker 3: got a courtesy car through my insurance company, and it

856
00:45:45,239 --> 00:45:49,080
Speaker 3: was the Toyota Corolla Hybrid. And I've got to tell

857
00:45:49,120 --> 00:45:52,799
Speaker 3: you four point eight liters per one hundred kilometers, so

858
00:45:53,080 --> 00:45:55,640
Speaker 3: it ran off the smell of an oily rag. But

859
00:45:56,000 --> 00:45:59,200
Speaker 3: because it's a pretty the Toyota have been doing hybrids

860
00:45:59,239 --> 00:46:03,640
Speaker 3: for a long time. There is a battery button where

861
00:46:03,680 --> 00:46:06,359
Speaker 3: if you stay below forty kilometers an hour, I could

862
00:46:06,440 --> 00:46:10,479
Speaker 3: drive to the supermarket Nana style and not use any

863
00:46:10,520 --> 00:46:13,319
Speaker 3: petrol at all. And that was playing with battery a

864
00:46:13,320 --> 00:46:17,280
Speaker 3: lot when I was driving the car sticking under forty.

865
00:46:18,480 --> 00:46:22,759
Speaker 1: Well, they were pioneers with the press, which was I

866
00:46:22,800 --> 00:46:25,080
Speaker 1: don't know, thirty five years ago, and that was one

867
00:46:25,160 --> 00:46:27,719
Speaker 1: hundred percent ev back then, and we're all like, that's

868
00:46:27,840 --> 00:46:30,040
Speaker 1: fucking that's never going to take off.

869
00:46:31,960 --> 00:46:34,799
Speaker 2: Yeah, yeah, yeah, I was going to say to you,

870
00:46:35,000 --> 00:46:37,680
Speaker 2: it's something on the tip of my tongue. Oh, that's right.

871
00:46:37,719 --> 00:46:42,120
Speaker 1: That guy Dara from Uber they were talking about.

872
00:46:42,600 --> 00:46:45,800
Speaker 2: This was on Diary of a CEO, Stephen Bartlett.

873
00:46:46,640 --> 00:46:52,880
Speaker 1: They were talking about the reality that autonomous vehicles avs

874
00:46:52,920 --> 00:46:56,160
Speaker 1: are going to overtake or going to play a very

875
00:46:56,160 --> 00:46:58,680
Speaker 1: big role in the Uber space and the.

876
00:46:58,760 --> 00:46:59,960
Speaker 2: Like moving forward.

877
00:47:01,320 --> 00:47:04,080
Speaker 1: And he said, like, they're talking about what are the

878
00:47:04,120 --> 00:47:07,480
Speaker 1: potential hurdles with people getting in a car with no driver,

879
00:47:07,680 --> 00:47:12,200
Speaker 1: and it's all really psychological and emotional, and I would

880
00:47:12,280 --> 00:47:14,480
Speaker 1: have to look at the research, but what he said

881
00:47:15,320 --> 00:47:20,160
Speaker 1: is that it's about ten times safer. So autonomous vehicles

882
00:47:20,200 --> 00:47:23,640
Speaker 1: are about ten times safer than humans driven by vehicles,

883
00:47:23,640 --> 00:47:25,680
Speaker 1: and they've got lots and lots and lots of data.

884
00:47:25,880 --> 00:47:29,200
Speaker 1: It's just that the idea still freaks people out. So

885
00:47:29,800 --> 00:47:33,239
Speaker 1: I would gladly get in an autonomous vehicle. I would gladly.

886
00:47:34,480 --> 00:47:37,120
Speaker 2: I could think of nothing better than just sitting back,

887
00:47:37,320 --> 00:47:41,560
Speaker 2: just doing whatever, or having a snooze. You love driving, though,

888
00:47:41,560 --> 00:47:41,880
Speaker 2: don't you.

889
00:47:42,800 --> 00:47:44,719
Speaker 3: I enjoy driving, and I've got to tell you, I

890
00:47:44,800 --> 00:47:47,080
Speaker 3: was devastated when the car got broken into because I

891
00:47:47,080 --> 00:47:50,880
Speaker 3: love my cart cause I'd never had a new car before.

892
00:47:50,880 --> 00:47:53,960
Speaker 3: It always bought secondhand cars, and the previous car I

893
00:47:54,000 --> 00:47:56,960
Speaker 3: had was probably one of the ugliest cars on the

894
00:47:57,000 --> 00:48:00,799
Speaker 3: market during my reno. Sce Nick McGahan, I know.

895
00:48:00,800 --> 00:48:02,960
Speaker 2: You've had a couple of ugly cars. That fucking this

896
00:48:03,200 --> 00:48:06,960
Speaker 2: and that Burgundy and that was an ugly motherfucker.

897
00:48:07,520 --> 00:48:11,080
Speaker 3: Oh my god, you're in my mother Jesus, Like I said,

898
00:48:11,440 --> 00:48:12,600
Speaker 3: I said, motherfucker.

899
00:48:12,680 --> 00:48:13,440
Speaker 2: Let's be clear.

900
00:48:14,080 --> 00:48:17,120
Speaker 3: That's a good looking car. Then, Nissan NXR Coop is

901
00:48:17,160 --> 00:48:19,840
Speaker 3: a bloody good looking car. I got to tell you anyway,

902
00:48:20,160 --> 00:48:22,439
Speaker 3: aside from the insights, because it even had a target roof.

903
00:48:22,480 --> 00:48:24,720
Speaker 3: You could take the roof section trick. Can we stop

904
00:48:24,760 --> 00:48:26,799
Speaker 3: talking about your car? I think we spoke about it

905
00:48:26,800 --> 00:48:30,600
Speaker 3: five times this podcast. Could you get onto some tech news? Okay,

906
00:48:31,040 --> 00:48:34,680
Speaker 3: my latest app session? Can I tell you about my

907
00:48:34,760 --> 00:48:35,440
Speaker 3: latest app?

908
00:48:35,560 --> 00:48:38,080
Speaker 1: Yeah, for God's sake, just don't talk about you fucking

909
00:48:38,160 --> 00:48:39,160
Speaker 1: broken window again.

910
00:48:39,360 --> 00:48:42,239
Speaker 3: I never used it in my car. Okay, you're not

911
00:48:42,280 --> 00:48:47,200
Speaker 3: a law to use your apps on your phone. So

912
00:48:47,400 --> 00:48:50,360
Speaker 3: I found I discovered this app recently called yucker y

913
00:48:50,520 --> 00:48:55,440
Speaker 3: U k A. And what it is. It's a free app,

914
00:48:55,600 --> 00:48:58,480
Speaker 3: doesn't have ads, but you do have a subscription tire.

915
00:48:58,800 --> 00:49:01,120
Speaker 3: But you can go to the souper market and scan

916
00:49:01,360 --> 00:49:04,880
Speaker 3: the barcode of all the products in the supermarket and

917
00:49:04,960 --> 00:49:06,880
Speaker 3: it tells you whether it's good, and it gives you

918
00:49:06,920 --> 00:49:09,200
Speaker 3: a breakdown and it says, okay, this is good for

919
00:49:09,280 --> 00:49:12,279
Speaker 3: this reason, this reason, this reason, but it's bad for

920
00:49:12,320 --> 00:49:14,920
Speaker 3: that reason. It might have too many two caloric so

921
00:49:14,960 --> 00:49:17,000
Speaker 3: it might have too many calories, or it might have

922
00:49:17,800 --> 00:49:20,880
Speaker 3: preservatives in it that are known to be harmful. It

923
00:49:20,920 --> 00:49:23,920
Speaker 3: has changed the way I shop for stuff. You know,

924
00:49:24,200 --> 00:49:26,880
Speaker 3: I use coconut cream in a lot of my pasta

925
00:49:26,960 --> 00:49:30,640
Speaker 3: sources because I don't use real crane. But there were

926
00:49:30,760 --> 00:49:36,000
Speaker 3: nine different creams and coconut milks, and only one of

927
00:49:36,040 --> 00:49:38,640
Speaker 3: them rated good. The rest of them were rated bad.

928
00:49:39,120 --> 00:49:41,799
Speaker 3: So the app's fantastic. And the other thing that I

929
00:49:41,800 --> 00:49:43,920
Speaker 3: can do is I can you can set filters, So

930
00:49:43,960 --> 00:49:47,279
Speaker 3: if you say, for example, were gluten intolerant, you could

931
00:49:47,280 --> 00:49:50,680
Speaker 3: set a gluten intolerant feature, and then when you scan stuff,

932
00:49:50,680 --> 00:49:53,880
Speaker 3: without having to read the barcode or read the contents,

933
00:49:54,080 --> 00:49:57,080
Speaker 3: it'll instantly tell you whether it's safe for you to have,

934
00:49:57,239 --> 00:49:59,200
Speaker 3: or if you've got a nut allergy, or in my case,

935
00:49:59,239 --> 00:50:01,200
Speaker 3: I set it for VA because I can't read bloody

936
00:50:01,280 --> 00:50:04,640
Speaker 3: labels anymore. I need a magnifying glass, or I take

937
00:50:04,640 --> 00:50:07,480
Speaker 3: a photo of the label and zoom in because it

938
00:50:07,560 --> 00:50:10,839
Speaker 3: takes forever to work out what all those numbers mean

939
00:50:10,920 --> 00:50:13,400
Speaker 3: and whether they contain an animal product or if it's

940
00:50:13,480 --> 00:50:16,680
Speaker 3: nuts or whatever. So it's yeah, it's my absolute obsession.

941
00:50:16,680 --> 00:50:18,640
Speaker 3: And the more I tell people about it, the more

942
00:50:18,640 --> 00:50:20,520
Speaker 3: people say, oh, yeah, I got it as well. It

943
00:50:20,640 --> 00:50:22,920
Speaker 3: sounds it's got minivative.

944
00:50:23,440 --> 00:50:25,759
Speaker 2: What's the problem with that? Do you think? What's the

945
00:50:25,760 --> 00:50:28,560
Speaker 2: potential problem with that app? Because I think you and

946
00:50:28,600 --> 00:50:30,120
Speaker 2: I might be thinking the same thing.

947
00:50:30,239 --> 00:50:33,279
Speaker 5: I just opened Chatters, and when is the yaka app

948
00:50:33,280 --> 00:50:34,759
Speaker 5: good and what's its philosophy?

949
00:50:34,800 --> 00:50:35,680
Speaker 4: With what is good?

950
00:50:36,080 --> 00:50:36,200
Speaker 5: In?

951
00:50:37,080 --> 00:50:39,360
Speaker 4: So I think you have to understand what.

952
00:50:39,280 --> 00:50:43,759
Speaker 5: You know about food and additives and like a lot

953
00:50:43,760 --> 00:50:46,360
Speaker 5: of the stuff David Gillespie talks about about seed oils

954
00:50:46,440 --> 00:50:50,080
Speaker 5: and everything, and yeah, what's its philosophy and what's it calling?

955
00:50:50,120 --> 00:50:51,960
Speaker 4: It was like the star rating on foods?

956
00:50:52,400 --> 00:50:56,000
Speaker 2: Yeah, and did you think Also, sorry, Patrick, I think

957
00:50:56,040 --> 00:50:57,600
Speaker 2: you just and I'm not saying it's bad.

958
00:50:57,640 --> 00:51:00,879
Speaker 1: It could be fucking amazing. So there's no judgment curiosity.

959
00:51:01,560 --> 00:51:05,960
Speaker 1: But like, for example, we have had too many talks

960
00:51:06,000 --> 00:51:08,600
Speaker 1: with David Gillespie about seed oils, but there is some

961
00:51:08,760 --> 00:51:12,800
Speaker 1: astounding science to support what he says. He never makes

962
00:51:12,800 --> 00:51:15,640
Speaker 1: a claim and doesn't back it up with proper research.

963
00:51:16,320 --> 00:51:18,359
Speaker 1: And then last night on the news on Channel seven,

964
00:51:18,400 --> 00:51:21,040
Speaker 1: they're like, ah, all the noise about seed oils, it's

965
00:51:21,080 --> 00:51:21,920
Speaker 1: not true.

966
00:51:22,120 --> 00:51:23,680
Speaker 2: They're all good. You know.

967
00:51:23,800 --> 00:51:26,239
Speaker 1: It's like they were just saying the exact opposite, but

968
00:51:26,400 --> 00:51:30,640
Speaker 1: nobody was referencing anything. Like the thing was, Nah, it's

969
00:51:30,680 --> 00:51:35,000
Speaker 1: not true. I'm a dietitian. It's good. Therefore you should

970
00:51:35,000 --> 00:51:37,400
Speaker 1: believe me because I'm no fuck that that's cool. You

971
00:51:37,520 --> 00:51:39,480
Speaker 1: might be true, you might be right, but give me

972
00:51:39,520 --> 00:51:42,600
Speaker 1: some science, give me some research, show me evidence that

973
00:51:42,640 --> 00:51:45,359
Speaker 1: what you're saying is true, because these things have been

974
00:51:45,400 --> 00:51:48,520
Speaker 1: happening for millennia, where we think something and then we

975
00:51:48,600 --> 00:51:51,920
Speaker 1: find out later like so many drugs like solidamide that

976
00:51:52,000 --> 00:51:53,920
Speaker 1: was given to pregnant women for this and that that

977
00:51:54,080 --> 00:51:57,160
Speaker 1: caused all these deformities. Well, at one stage this was

978
00:51:57,200 --> 00:51:58,920
Speaker 1: the right thing. You should have it, and it was

979
00:51:59,120 --> 00:52:03,600
Speaker 1: devastatedly terrible on women, right, but at one stage that

980
00:52:03,680 --> 00:52:06,799
Speaker 1: was good science. So I think we're so gullible that

981
00:52:06,840 --> 00:52:11,880
Speaker 1: we just go. My question would be with you, yaka

982
00:52:12,000 --> 00:52:15,680
Speaker 1: as you call it, like who science are you using?

983
00:52:15,840 --> 00:52:18,359
Speaker 1: Like what are the criteria that you are saying this

984
00:52:18,440 --> 00:52:20,480
Speaker 1: is good or bad? And how do we know that

985
00:52:20,760 --> 00:52:23,359
Speaker 1: you are right and the other people who say other

986
00:52:23,440 --> 00:52:27,080
Speaker 1: things are wrong. That's and by the way, everyone, I

987
00:52:27,120 --> 00:52:29,360
Speaker 1: have no opinion on it. It could be bloody brilliant

988
00:52:29,400 --> 00:52:30,640
Speaker 1: because I haven't even seen it.

989
00:52:30,640 --> 00:52:31,400
Speaker 2: But that's just what.

990
00:52:32,239 --> 00:52:34,480
Speaker 1: Even when I talk about science, or even when I

991
00:52:34,520 --> 00:52:38,520
Speaker 1: talk about potential behavior or choices around health and wellness,

992
00:52:39,040 --> 00:52:41,680
Speaker 1: I go, this is what I think. I don't go,

993
00:52:41,960 --> 00:52:44,560
Speaker 1: you should all do this because I've read a paper

994
00:52:45,040 --> 00:52:48,000
Speaker 1: or I've trained lots of people or yeah, I just

995
00:52:48,080 --> 00:52:52,320
Speaker 1: think that I think the concept is a good idea,

996
00:52:52,400 --> 00:52:53,919
Speaker 1: but I would just like to dig in.

997
00:52:53,840 --> 00:52:56,239
Speaker 2: And go, what's the science behind it?

998
00:52:56,280 --> 00:52:58,760
Speaker 1: And I know that sounds fucking worrying and I'm raining

999
00:52:58,760 --> 00:53:01,920
Speaker 1: on your parade, but I just think, Eh, you know,

1000
00:53:02,000 --> 00:53:04,920
Speaker 1: it's like the Health Star rating system. Gillespie just wrote

1001
00:53:05,280 --> 00:53:09,080
Speaker 1: an article on that. It's fucking incredible. So you get

1002
00:53:09,120 --> 00:53:12,360
Speaker 1: something like a with the current Health Star rating system,

1003
00:53:13,160 --> 00:53:17,439
Speaker 1: you can have a cereal that's full of process shit

1004
00:53:17,600 --> 00:53:18,680
Speaker 1: and sugar.

1005
00:53:19,960 --> 00:53:22,040
Speaker 2: Gets four and a half stars. In fact, he had

1006
00:53:22,040 --> 00:53:24,040
Speaker 2: a photo of one. And then he had a free

1007
00:53:24,160 --> 00:53:26,960
Speaker 2: range organic and I know you're not going to want this, Patrick,

1008
00:53:27,239 --> 00:53:30,320
Speaker 2: but steak, so it had the only ingredient was beef.

1009
00:53:30,520 --> 00:53:35,120
Speaker 2: It got zero point five stars compared to process sugary.

1010
00:53:35,239 --> 00:53:41,359
Speaker 2: Fucking Now, it's like, this is fucking ridiculous and it's

1011
00:53:41,480 --> 00:53:47,680
Speaker 2: based on all of these absolutely flawed criteria. But the

1012
00:53:47,719 --> 00:53:52,200
Speaker 2: one before that, which was the there's another star rating system.

1013
00:53:52,360 --> 00:53:54,800
Speaker 1: The way that people got the stars for their product

1014
00:53:54,840 --> 00:53:58,920
Speaker 1: was they bought them. There was no actual analysis, like,

1015
00:53:58,960 --> 00:54:03,560
Speaker 1: there was no nutrition, there was no science behind this rating.

1016
00:54:04,040 --> 00:54:06,799
Speaker 2: It was like, ah, we have this, we want to

1017
00:54:06,960 --> 00:54:09,520
Speaker 2: get your endorsement and they're like, wow, it's thirty grand

1018
00:54:09,560 --> 00:54:13,000
Speaker 2: for that. Cool, here's the thirty or whatever. You know, Like,

1019
00:54:13,040 --> 00:54:16,560
Speaker 2: it's just this stuff is don't believe everything that you

1020
00:54:16,680 --> 00:54:19,120
Speaker 2: hear or see. It's like you've got to learn a bit. Yes, tip,

1021
00:54:19,160 --> 00:54:21,560
Speaker 2: you've got your fingers twitching. I can tell, well, just

1022
00:54:21,719 --> 00:54:22,160
Speaker 2: was reading.

1023
00:54:22,280 --> 00:54:24,920
Speaker 5: Like one of the points that Chatters makes is that

1024
00:54:25,000 --> 00:54:28,760
Speaker 5: it judges foods in isolation. For example, olive oil loses

1025
00:54:28,800 --> 00:54:32,799
Speaker 5: points for calories, cheese looks worse than diet yogurt and

1026
00:54:32,840 --> 00:54:34,400
Speaker 5: honey may not even get a score.

1027
00:54:35,040 --> 00:54:36,840
Speaker 4: And then, yeah, we're relying on.

1028
00:54:37,040 --> 00:54:39,280
Speaker 5: Being told what to eat, not how to think about

1029
00:54:39,280 --> 00:54:40,200
Speaker 5: the food we eat.

1030
00:54:40,440 --> 00:54:43,680
Speaker 2: I think the problem is that calories have been demonized.

1031
00:54:43,880 --> 00:54:46,719
Speaker 2: It's like, well, dude, you fucking need calories every day.

1032
00:54:46,760 --> 00:54:49,440
Speaker 2: It's calories aren't good or bad. It's how many you

1033
00:54:49,600 --> 00:54:53,600
Speaker 2: have based on how many you expend. But there are

1034
00:54:53,640 --> 00:54:59,720
Speaker 2: some things, certain chemicals and certain flavoroids and fucking preservatives

1035
00:54:59,719 --> 00:55:05,359
Speaker 2: that unequivocally bad. So no amount is good. Sorry, Patrick, And.

1036
00:55:05,400 --> 00:55:08,800
Speaker 3: It's been really good at educating myself to ultra processed stuff,

1037
00:55:09,680 --> 00:55:12,080
Speaker 3: high sodium, that sort of thing. But I think the

1038
00:55:12,120 --> 00:55:15,879
Speaker 3: other thing is the filtering for vegan because I can't

1039
00:55:15,960 --> 00:55:18,000
Speaker 3: read the labels as well as I used to be

1040
00:55:18,040 --> 00:55:20,759
Speaker 3: able to, so being able to quickly do that and

1041
00:55:20,800 --> 00:55:23,399
Speaker 3: walk past. But you know, what I found was interesting too,

1042
00:55:23,560 --> 00:55:26,600
Speaker 3: is that sometimes the cheapest stuff on the market in

1043
00:55:26,680 --> 00:55:32,080
Speaker 3: terms of the amount of additives, because really, shelf life

1044
00:55:32,200 --> 00:55:35,480
Speaker 3: is one of these things that producers want to be

1045
00:55:35,520 --> 00:55:37,160
Speaker 3: able to have a product that stays on the shelf

1046
00:55:37,160 --> 00:55:40,320
Speaker 3: as long as possible. You know, if you open up wraps,

1047
00:55:40,640 --> 00:55:42,440
Speaker 3: or you know, if you buy raps at the supermarket,

1048
00:55:42,480 --> 00:55:44,840
Speaker 3: the majority of them have a life shelf life of

1049
00:55:44,920 --> 00:55:47,719
Speaker 3: like six months. I don't know any bread product that

1050
00:55:47,760 --> 00:55:50,320
Speaker 3: should last six months. And even when you open it,

1051
00:55:50,320 --> 00:55:51,920
Speaker 3: it can sit in the fridge for two weeks and

1052
00:55:51,920 --> 00:55:54,319
Speaker 3: you think hasn't ever got any mold on it. You

1053
00:55:54,360 --> 00:55:57,640
Speaker 3: know that you've got to ask the questions. You know,

1054
00:55:57,880 --> 00:56:00,799
Speaker 3: those things actually safe. I'm making my own made wraps now,

1055
00:56:00,800 --> 00:56:03,560
Speaker 3: I'm pretty happy with myself. So I'm just making it

1056
00:56:03,560 --> 00:56:06,680
Speaker 3: from oat flour and lind seed that I mill myself,

1057
00:56:07,120 --> 00:56:07,600
Speaker 3: and I've just.

1058
00:56:07,680 --> 00:56:09,000
Speaker 2: Think that's a wise decision.

1059
00:56:09,040 --> 00:56:10,759
Speaker 1: Also, I just wanted to jump back to what you

1060
00:56:10,760 --> 00:56:16,040
Speaker 1: were talking about the nutritional labels, right you can't read them.

1061
00:56:16,480 --> 00:56:19,279
Speaker 2: And the reason you can't read them is because it's

1062
00:56:19,320 --> 00:56:22,600
Speaker 2: fucking size four fonts on the back of the box

1063
00:56:22,960 --> 00:56:25,960
Speaker 2: down the bottom left or right hand corner, because they

1064
00:56:26,040 --> 00:56:29,560
Speaker 2: don't want it to get any attention. What was in

1065
00:56:29,600 --> 00:56:33,040
Speaker 2: that box was good news for them, it'd be all

1066
00:56:33,040 --> 00:56:36,799
Speaker 2: over the front in big letters. So the front is

1067
00:56:36,840 --> 00:56:38,320
Speaker 2: an ad. It's not information.

1068
00:56:38,640 --> 00:56:40,840
Speaker 1: The shit in that box that they don't want you

1069
00:56:40,920 --> 00:56:44,040
Speaker 1: to read, and the ingredients list that they don't want

1070
00:56:44,080 --> 00:56:47,919
Speaker 1: you to read, with all those preservatives, additives numbers, that's

1071
00:56:47,960 --> 00:56:50,319
Speaker 1: what you fuck. The front of the box. It's an ad.

1072
00:56:50,400 --> 00:56:54,160
Speaker 1: It's a trick, it's a fucking it's a delusion. Like

1073
00:56:54,280 --> 00:56:56,719
Speaker 1: go to the back and actually try to understand what

1074
00:56:56,719 --> 00:56:58,520
Speaker 1: you're putting in your gob We've got to go give

1075
00:56:58,600 --> 00:57:01,000
Speaker 1: us one more before we go cham your choice.

1076
00:57:01,360 --> 00:57:05,520
Speaker 3: I'm so excited. Next week we've got a lunar eclipse

1077
00:57:05,800 --> 00:57:08,760
Speaker 3: and it made me think about the new Artemis mission.

1078
00:57:08,800 --> 00:57:11,880
Speaker 3: So the Artemis two mission is the astronauts. They're going

1079
00:57:11,920 --> 00:57:14,680
Speaker 3: to be heading off soon this year. In fact, it's

1080
00:57:14,680 --> 00:57:17,720
Speaker 3: only a short time away, and the people in the

1081
00:57:17,800 --> 00:57:20,280
Speaker 3: Artomis spacecraft. We're going to go back to the Moon

1082
00:57:20,320 --> 00:57:22,320
Speaker 3: they're not landing on the Moon, but they're going to

1083
00:57:22,360 --> 00:57:25,080
Speaker 3: go around the Moon and run all these studies. But

1084
00:57:25,600 --> 00:57:28,280
Speaker 3: because of the placement of the Moon, they're going to

1085
00:57:28,320 --> 00:57:32,320
Speaker 3: be the furthest away from Earth than any other human

1086
00:57:32,360 --> 00:57:35,560
Speaker 3: being in his wyow So cool.

1087
00:57:35,680 --> 00:57:39,200
Speaker 1: Huh, you would love to go to space when that's

1088
00:57:39,360 --> 00:57:42,120
Speaker 1: like that'd be you'd probably chop off a knacker for

1089
00:57:42,160 --> 00:57:42,680
Speaker 1: that onenn't you?

1090
00:57:42,960 --> 00:57:43,080
Speaker 5: Well?

1091
00:57:43,080 --> 00:57:46,080
Speaker 3: I think last month last episode, I talked about a

1092
00:57:46,120 --> 00:57:50,000
Speaker 3: company that's sending ashes into space. I want to get

1093
00:57:50,000 --> 00:57:53,120
Speaker 3: my ashes sent into space. That's where I'm at. But

1094
00:57:53,160 --> 00:57:55,120
Speaker 3: the other thing that I found interesting about the Artemis

1095
00:57:55,240 --> 00:57:59,840
Speaker 3: mission is they're equipping the astronauts with ten year old

1096
00:58:00,120 --> 00:58:04,560
Speaker 3: DSLR cameras Nicon cameras because there was a nick On

1097
00:58:04,640 --> 00:58:07,320
Speaker 3: camera that came out, which is kind of fascinating. The

1098
00:58:07,360 --> 00:58:13,680
Speaker 3: camera is twenty sixteen camera, the D five Nikon camera,

1099
00:58:14,160 --> 00:58:18,600
Speaker 3: and it's got a it's more resilient to radiation and

1100
00:58:18,640 --> 00:58:22,840
Speaker 3: it has a much higher ISO rating, So ISO is

1101
00:58:22,880 --> 00:58:27,760
Speaker 3: the sensitivity to light, and it had this ridiculously good

1102
00:58:27,960 --> 00:58:31,520
Speaker 3: sensitivity built into it that's more than the comp than

1103
00:58:31,560 --> 00:58:35,160
Speaker 3: the current Nikons, which is fascinating, and it means that

1104
00:58:35,280 --> 00:58:38,760
Speaker 3: contrast between the darkness of space and any object they're

1105
00:58:38,760 --> 00:58:41,720
Speaker 3: taking photographs of. So that's what they're taking with them.

1106
00:58:41,760 --> 00:58:44,680
Speaker 3: Ten year old cameras are going to be flying around

1107
00:58:44,800 --> 00:58:47,640
Speaker 3: with human beings and going to be the furthest way

1108
00:58:47,760 --> 00:58:50,080
Speaker 3: that any human's ever been in history.

1109
00:58:51,360 --> 00:58:54,000
Speaker 1: Look at you, just bringing the bloody facts and the

1110
00:58:54,080 --> 00:58:57,120
Speaker 1: amusement and the entertainment. Now I heard that you had

1111
00:58:57,120 --> 00:59:03,760
Speaker 1: your car broken into. Ah, Patrick, of course can be.

1112
00:59:04,040 --> 00:59:06,120
Speaker 1: Somebody wrote in the group, I hate it when you

1113
00:59:06,160 --> 00:59:09,720
Speaker 1: ask Patrick where people can find you, Oh, because they

1114
00:59:09,720 --> 00:59:12,280
Speaker 1: don't like So now I'm now I'm scared.

1115
00:59:12,360 --> 00:59:15,000
Speaker 2: But oh well that's okay. I go.

1116
00:59:15,520 --> 00:59:17,640
Speaker 3: If anybody wants to contact me, they can just go

1117
00:59:17,680 --> 00:59:20,520
Speaker 3: to websites now dot com, dot a U and fill

1118
00:59:20,560 --> 00:59:23,040
Speaker 3: out the form and just say hi, let us know

1119
00:59:23,080 --> 00:59:23,680
Speaker 3: what you want us to do.

1120
00:59:23,800 --> 00:59:26,360
Speaker 2: Oh okay, I was unaware. Thank you for bringing that up.

1121
00:59:27,120 --> 00:59:32,680
Speaker 3: Tif did you know that I know? And also Tichi

1122
00:59:32,760 --> 00:59:35,200
Speaker 3: at home, dot com, DoD au. I have all these

1123
00:59:35,240 --> 00:59:38,640
Speaker 3: free exercises and you can meet Fritz my the Wonder dog,

1124
00:59:38,800 --> 00:59:40,160
Speaker 3: and we can do tichee together.

1125
00:59:41,320 --> 00:59:44,000
Speaker 1: Well yes, and also everyone, he doesn't get paid, so

1126
00:59:44,120 --> 00:59:44,880
Speaker 1: give him a break.

1127
00:59:44,920 --> 00:59:48,320
Speaker 2: He's allowed to promote we give him fuck all. You know,

1128
00:59:48,640 --> 00:59:51,640
Speaker 2: he's only got he's got a devalued car.

1129
00:59:51,760 --> 00:59:54,600
Speaker 1: Now he lives in fucking Upper oh. I can't say

1130
00:59:54,600 --> 00:59:55,600
Speaker 1: what I was going to say, but it.

1131
00:59:55,600 --> 00:59:59,680
Speaker 3: Would have been hilarious going to say yes exactly.

1132
00:59:59,240 --> 01:00:01,360
Speaker 2: But you know who would have sent us an email?

1133
01:00:01,480 --> 01:00:05,720
Speaker 2: Someone Tiff, thank you. Have a good Friday, both of you.

1134
01:00:05,840 --> 01:00:08,480
Speaker 1: We'll say goodbye fair but thanks both of you, and

1135
01:00:08,480 --> 01:00:09,200
Speaker 1: thanks listeners,