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Speaker 1: I'll get a team. Welcome to another installment of the

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Speaker 1: year project. It's been difficult over here. I've been trying

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Speaker 1: to get a break in the conversation. These two distractions

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Speaker 1: to my left and right on my screen just wouldn't

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Speaker 1: even let me start the show because they're so chatty.

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Speaker 1: Good morning, TIV, Good morning, Good morning Patrick, Good morning Patrick,

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Speaker 1: and Fritz.

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Speaker 2: Oh sorry you ordered his sweet speak now did you?

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Speaker 2: You're complaining about me talking too much? So I thought, well,

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Speaker 2: I'll have a bit of time out.

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Speaker 1: Oh look at you being hilarious, just a bit of comedy,

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Speaker 1: straight up hanging. I just got to go get a

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Speaker 1: needle and thread to sew up my sides. God, hello, Patrick,

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Speaker 1: Hello Fritz. Why doesn't Fritz talk? He's a dog and

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Speaker 1: he doesn't understand. He's very cute. Look at that. That's

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Speaker 1: a fucking lovable face. He seems very stoic. Now I've

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Speaker 1: figured out what kind of dog. I've narrowed it down

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Speaker 1: to two dogs.

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Speaker 3: Okay, what are we getting?

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Speaker 4: Well?

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Speaker 1: See, I feel like it's a no win situation because

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Speaker 1: whatever dog you say that you're thinking that you might get,

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Speaker 1: there's going to be people that go no, definitely don't

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Speaker 1: get one of those, because they'll eat your fucking house

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Speaker 1: when you're asleep, or you know, they'll dig up your garden,

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Speaker 1: or or they eat too much, or they die too early,

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Speaker 1: or they get hip displaysure or so what's see, I

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Speaker 1: haven't even told I haven't told anyone this, So I'm

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Speaker 1: telling the whole world at once. So the first one

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Speaker 1: is going to be no surprise because I've already had

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Speaker 1: one golden retriever. The second one, seventy percent of our

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Speaker 1: audience will go, I don't even know what that is.

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Speaker 1: And I'll tell you what. I'm going to give you

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Speaker 1: each three guesses, and if either of you guess it,

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Speaker 1: I'll give you fifty bucks. But tif get off your phone.

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Speaker 4: You're not allowed to.

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Speaker 3: I'll try for that breed you talked about. Is it

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Speaker 3: that breed you talked about the other day that I

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Speaker 3: won't read?

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Speaker 1: Well?

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Speaker 4: Then then you're out, so you straight on my You know,

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Speaker 4: what about a harrier? Nah, it's a harrier? Okay?

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Speaker 2: What about an Alaskan melomotor in the ballpark?

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Speaker 1: Yeah? Yeah?

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Speaker 4: Is that going to get twenty five bucks?

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Speaker 1: No? No, the dog I'm thinking about, but it's like,

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Speaker 1: this is not a dog. You get lightly like this

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Speaker 1: dog is a commitment, and that's why I'd probably lean

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Speaker 1: more towards the Golden Retriever because they're just like me,

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Speaker 1: fat and lasyer and eat food, fat la Lasian like

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Speaker 1: cuddles a Belgium Melamoire, which they're they're they're kind of

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Speaker 1: like a slightly smaller German Shepherd and some say smarter

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Speaker 1: and better in that kind of highly trainable, fiercely loyal,

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Speaker 1: and I no, I don't want a big, alpha male dog. Everyone.

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Speaker 1: I just love them, like I've met a couple and

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Speaker 1: they're so fucking cool.

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Speaker 4: It's like black faces. Yeah, gold with a black face.

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Speaker 1: Yeah, they're they're like a human, lower maintenance anyway, I

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Speaker 1: don't know, but I've got to wait till I finish

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Speaker 1: my PhD because I just don't have time to like,

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Speaker 1: I think that's the other thing I think. And you

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Speaker 1: both dog owners, but I think if you're going to

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Speaker 1: get a dog, like for me, I want to train

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Speaker 1: the dog really well and invest the time properly in

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Speaker 1: the first six twelve months to build a relationship, create

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Speaker 1: good dynamics, and train that dog in it. Not so

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Speaker 1: that it's fucking weapon, but just I think it's irresponsible

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Speaker 1: to have a totally untrained dog, and because they just

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Speaker 1: don't like because dogs are pack animals, they like being

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Speaker 1: led as long as they're loved and all of that.

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Speaker 1: But you know so, I feel like, especially if I've

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Speaker 1: got a Belgium Melamie, I really need to invest some

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Speaker 1: time into some proper training because if you don't train

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Speaker 1: some dogs, they're fucking nightmares. But if you train them properly,

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Speaker 1: they're great. If you're looking at one right.

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Speaker 3: Now, yeah, yeah, And you definitely don't want one of

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Speaker 3: those untrained.

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Speaker 5: Do you?

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Speaker 1: No?

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Speaker 5: No terrifying no things.

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Speaker 1: So one of the guys that I listened to, his

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Speaker 1: name's Tim Kennedy, is Special Forces x USC. He's got

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Speaker 1: one and he calls it the fur Missile. So what

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Speaker 1: are you doing over there, Ti, if you're talking to

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Speaker 1: your dad?

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Speaker 3: Yeah, it's just popped his head in the studio, Make

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Speaker 3: Luna for a walk.

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Speaker 1: Tell everyone what's happening in your world before we get underway,

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Speaker 1: because it's it's there's lots going.

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Speaker 5: On, speaking of animals.

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Speaker 3: I am going to be off on a plane to

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Speaker 3: India tomorrow, and so my dad flew in yesterday. He

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Speaker 3: is manning the chaotic house that is bear.

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Speaker 5: And Lunar HQ. So he's learning the ropes.

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Speaker 3: He's learning the ropes, and he's getting rap around the

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Speaker 3: pores of those who run the household here.

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Speaker 1: Do they love him already? I mean they know him.

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Speaker 3: Yesterday I was in the kitchen and I could just

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Speaker 3: hear giggling like a schoolgirl. And I snuck my head

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Speaker 3: around the corner and Dad's on the couch with a

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Speaker 3: doner on him, with Luna under the doner, with him

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Speaker 3: smooching him, and he's giggling. And then when they're four

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Speaker 3: hours after going into hiding, when he first arrived, came out,

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Speaker 3: next minute she's he's laying under the doner and she's

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Speaker 3: on top of it.

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Speaker 1: Oh, that's hilarious. I wonder if I wonder if this

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Speaker 1: is a probably a dumb question, but maybe not. Patrick.

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Speaker 1: Do you reckon that that the animals would know that

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Speaker 1: TIFF's dad is TIFF's dad because there's some smell or

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Speaker 1: sense or some genetic familiarity.

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Speaker 4: Well, that's a really good question, isn't it.

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Speaker 1: Like they have like incredible senses.

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Speaker 2: I think what they would sense is how Tiff feels

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Speaker 2: about her father, So wow, he comes in and she

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Speaker 2: is relaxed and loving towards her dad.

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Speaker 4: That would be what they would sense, is what my friend.

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Speaker 1: Well, TIFF's dad and Tiff and I had a coffee

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Speaker 1: yesterday at one forty five, and by about two oh seven,

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Speaker 1: TIFF's dad was nearly fucking asleep at the table. The

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Speaker 1: poor old bugger. He was just he hit the wall

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Speaker 1: because he didn't sleep the night before, and he was

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Speaker 1: a little bit he was a little bit hyper aware

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Speaker 1: about ticking all the boxes and going through the airport

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Speaker 1: and getting everything. Was a little bit worried about some

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Speaker 1: of that. God bless him.

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Speaker 4: It wasn't a little nailed it.

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Speaker 2: It wasn't a little bit your conversation too, what maybe

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Speaker 2: fall asleep?

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Speaker 1: Oh yeah, no, it was definitely me. That's actually a

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Speaker 1: good point. I didn't think of that, Maybe because I'm

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Speaker 1: a boring prick. Yeah, no, thanks for bringing that to

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Speaker 1: my attention. I was thinking it was a lack of

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Speaker 1: sleep back in therapy for me. Now, now just quickly, Tiff,

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Speaker 1: you're heading off to India tomorrow. Yeah, what's the what's

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Speaker 1: the update? You organized? I know you're not organized, but

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Speaker 1: where you are?

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Speaker 3: Well, I started packing yesterday and I realized that I

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Speaker 3: don't have any India friendly clothes when the description was

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Speaker 3: loose fitting and cover your shoulders. So I had to

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Speaker 3: duck out yesterday IVO and get some loose fitting linen

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Speaker 3: pants and stuff. Yeah, but we've got a tight what

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Speaker 3: do you call it, baggage allowance, So it's a challenge.

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Speaker 3: I'm not good at packing. I normally take twenty kilos

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Speaker 3: for a week in tazzy.

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Speaker 5: Stay tuned.

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Speaker 3: There's a lot early mornings coming up.

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Speaker 1: And I love your rationale that you told me. You

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Speaker 1: say about how they wanted you to take all of

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Speaker 1: these prescription drugs for dysentery and all the potential stomach

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Speaker 1: ailments that you might you know, and you're like, oh

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Speaker 1: fuck it, other people will take them. I'll just use

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Speaker 1: theirs if I get sick taking. I'm not sure that's

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Speaker 1: a good plan.

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Speaker 3: Look, I'm not taking a bunch of prescription medication to

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Speaker 3: go and sit in the bush and then have all

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Speaker 3: of us that have no idea go, oh, we should

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Speaker 3: take this prescription medication that we're not sure what we've

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Speaker 3: got and we should take it.

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Speaker 5: No.

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Speaker 2: Now, all you do, what you do is you have

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Speaker 2: it all lined up. You google it and say right,

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Speaker 2: this is for diarrhea.

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Speaker 4: This is for this, this is for this.

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Speaker 2: You don't have to read it, just say, okay, there's

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Speaker 2: my diarrhea tablets. There's my tablets for headaches, there's my tablet.

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Speaker 1: You know what you can do. You can just take a.

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Speaker 3: Two week supply of protein bars and eat only that.

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Speaker 1: The only problem is the water. You know what you

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Speaker 1: can do is just chat, dear chatters. Okay, here's my situation.

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Speaker 1: I'm in the jungle. I'm pooing through the eye of

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Speaker 1: a needle. These are my drug options. I'm standing by

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Speaker 1: for directions.

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Speaker 2: Can I tell you, though, if you don't rely on

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Speaker 2: other people's stuff, Because when I went to China for

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Speaker 2: the first time, my tied cheek group is predominantly older women,

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Speaker 2: twenty years older than me, so I get mothered the

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Speaker 2: fair bits. But we got to the university in a

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Speaker 2: place called bed to Her and there's no coffee, and

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Speaker 2: one lady has brought those little tea bag type coffee,

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Speaker 2: you know, the Harris coffee that's like in a tea bag.

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Speaker 2: You reckon, satles, you reckon. She's going to share it

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Speaker 2: with anybody.

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Speaker 4: Man. She's selling the shit. People really see people's colors

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Speaker 4: when they're the only one with an essential drug.

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Speaker 6: Oh wow, yeah, perrel watch out hey, speaking of I

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Speaker 6: don't know this is irrelevant to our general theme of

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Speaker 6: the show, but fuck it, you'll both find this interesting.

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Speaker 1: So it was Melissa's birthday yesterday, shout out to Melissa

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Speaker 1: twenty three, and this is she'll probably kill me for

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Speaker 1: telling you this, but fuck it. So Melissa has been

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Speaker 1: Melissa has no drugs. She's never been drunk, she'd never

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Speaker 1: been high, she never had a sip of alcohol. She

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Speaker 1: doesn't drink coffee, she doesn't drink tea. But she's jealous

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Speaker 1: of us coffee drinkers, right because I go, I tell

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Speaker 1: her how fucking amazing coffee is and that she's missing out,

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Speaker 1: and just like a good what do you call a

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Speaker 1: drug dealer, I'm just like trying to get her over

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Speaker 1: the line.

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Speaker 4: Right.

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Speaker 1: So, anyway, she started drinking coffee purely just for the

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Speaker 1: cognitive benefits of having some caffeine in her system, because

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Speaker 1: she works a lot, right, and so by about two

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Speaker 1: or three pms she sometimes hits the wall. So she's

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Speaker 1: having like a lunchtime coffee and she hates it. But

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Speaker 1: she goes and buys a coffee. She thinks it's disgusting.

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Speaker 1: It's the worst shit she's ever tasted. So for and

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Speaker 1: her and I have an arrangement where we don't buy

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Speaker 1: each other birthday presence. Right, But I heard this thing

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Speaker 1: advertised on the radio called Wakey, Wakey. Have you heard

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Speaker 1: of it? I know, I know it sounds like no, Patrick,

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Speaker 1: it's not the second line that you think of either.

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Speaker 1: I know what you're thinking. I'm not going to say

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Speaker 1: that because I'm not going there on this podcast. I'm

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Speaker 1: doing one episode with no dick jokes.

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Speaker 2: Right, No, anyway, story is that I'm talking about today?

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Speaker 2: Have you read my notes?

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Speaker 3: Oh?

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Speaker 1: I have? That's funny. That is funny. But anyway, but

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Speaker 1: you're opening that door, not me. But anyway, So I

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Speaker 1: went to the supermarket and I couldn't anyway. They've got

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Speaker 1: these little they're like Baroka chew tubes full of these

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Speaker 1: pills or these large tablets and they have the equivalent

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Speaker 1: of a cup of coffee. Now, not that I'm suggesting

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Speaker 1: anyone does this, but I thought, well, she's only doing

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Speaker 1: it for the caffeine, and we're talking about a six

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Speaker 1: dollar present. So I didn't really buy her anything. But

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Speaker 1: so I just got her. I haven't given them to

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Speaker 1: it yet, I'm saying yet, but i'll So I bought

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Speaker 1: her these things where you can buy them, and it's

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Speaker 1: orange flavored, no calories, no sugar, So you get a

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Speaker 1: coffee without having a coffee. So I told her. She's

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Speaker 1: quite excited.

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Speaker 4: What about an.

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Speaker 1: Well, that's different, that's different altogether, you know, do you know,

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Speaker 1: like while we're opening this door on nootropics, So nootropics

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Speaker 1: is cognitive enhancing. So any drug that has a nootropic

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Speaker 1: effect is a potential cognitive benefit, thinking clearer and sharper

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Speaker 1: for longer, and even improving IQ for a period of time.

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Speaker 1: We know that people think that's a joke. Like your IQ,

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Speaker 1: your functional like actually fluctuates during the day, right, so

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Speaker 1: obviously your cognitive performance, just like your energy fluctuates through

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Speaker 1: the day. So your functional IQ fluctuates through the day,

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Speaker 1: and your IQ actually improves after you lift weights for

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Speaker 1: a couple of hours, but it also does with coffee

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Speaker 1: and nicotine. Patrick is really widely used. Oh really, people

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Speaker 1: think oh yeah, yeah yeah, so and again everyone, this

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Speaker 1: is just a conversation, no recommendation, no prescription, no endorsement,

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Speaker 1: But so Nicorette two and four milligram chewing gum sells

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Speaker 1: like fucking hot cakes back in the days when hotcakes sold. Well, yeah,

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Speaker 1: lots of my friends use that, like at least twenty

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Speaker 1: of my friends use that, and it's ay. But the

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Speaker 1: problem is, like with all drugs, if you use it

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Speaker 1: too much, it doesn't work. If you use it every day,

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Speaker 1: it doesn't work. And so but the odd, the odd

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Speaker 1: piece of nicorette seems to be I'm not saying it's

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Speaker 1: a good idea, but it seems to be effective. So

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Speaker 1: people who let's say they've got they've got a focus

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Speaker 1: for three or four hours because they've got some big

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Speaker 1: meeting or something where they've got to be cognitively switched on,

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Speaker 1: they'll do that. Another one also, another one which is

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Speaker 1: much safer and also the most research supplement on the

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Speaker 1: planet is creatine, which I use every day. Creatine and

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Speaker 1: gladly endorse. Again, it's not a recommendation, but I use.

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Speaker 1: It's very very it's a naturally occurring thing in the body.

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Speaker 1: And there's also someone i'll shut up after this, but

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Speaker 1: some really interesting research that's come out recently for people

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Speaker 1: who are sleep dep revised a sleep sleep deprived, which

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Speaker 1: I sound like I'm sleep deprivived. People who are sleep

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Speaker 1: deprived are using what they call megadoses of like four

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Speaker 1: or five times and normal things, so like thirty grams

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Speaker 1: or twenty five grams instead of five as a dose,

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Speaker 1: and that seems to offset the lack of sleep, which

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Speaker 1: is not a solution, but it's just something that some

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Speaker 1: people are doing. So there it is. Patrick.

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Speaker 4: I was just reading up on creatine.

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Speaker 2: I didn't know much about it, but it says that

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Speaker 2: it's most often found in seafood and red meat, and

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Speaker 2: I'm thinking, holy crap, I better look for vegan creatine

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Speaker 2: because I'm not getting any.

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Speaker 1: Well, yeah, and you could just I mean, it is

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Speaker 1: like if everybody's listened. Everybody who's listened to me knows

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Speaker 1: I never endorse or recommend anything but I but I

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Speaker 1: can say that I use that and it works. I

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Speaker 1: can also say that I've had a few nicorette chewing

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Speaker 1: gums over the years, but I've probably had in my

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Speaker 1: life ten and I don't smoke. And by the way,

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Speaker 1: not that nicotine is great for you, but it's it's

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Speaker 1: it's not actually the bit of the cigarettes that cause cancer.

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Speaker 1: But but yeah, I don't. I generally don't use it,

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Speaker 1: but if I have, if I need something where I've

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Speaker 1: got to be up and about, I've done that a

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Speaker 1: few times and it kind of switches on the brain

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Speaker 1: a bit. Yeah, you too, feel so this is a

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Speaker 1: conversation you too. Yeah, So when I stopped talking, that's

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Speaker 1: a queue for one of you, two fucking dummies to

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Speaker 1: start talking.

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Speaker 4: Well, okay, let me start the whole.

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Speaker 1: Fuck have you two been on a podcast before, so

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Speaker 1: let me.

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Speaker 4: Just not gas bagging.

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Speaker 2: You just don't shut up so we can't get a

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Speaker 2: worded Edgeway, I'm part.

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Speaker 5: Of the audience. I'm going to leave this whole thing.

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Speaker 1: The modelogue.

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Speaker 4: I love this.

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Speaker 1: Ah fuck, It's true. Even I get sick of me sometimes,

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Speaker 1: So I don't blame you. You know, it wasn't until

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Speaker 1: this podcast that both Tip and I learned how to

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Speaker 1: fall asleep with our eyes open. Okay, all right, point taken,

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Speaker 1: I'll be quiet.

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Speaker 4: I hate that, but it's sorry.

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Speaker 1: Whatever you want, whatever you want, whatever you want, sor right.

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Speaker 1: Don't worry about Matte.

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Speaker 4: I think I may have offended him. Tiff, She's so

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Speaker 4: no sympathy at all.

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Speaker 1: She does give a fuck. I'm just going to say

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Speaker 1: before you launch on my list of topics that you

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Speaker 1: sent through, it's always tech ai health Today. Working backwards

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Speaker 1: from the list, I can see tech ai scams cars,

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Speaker 1: and at the top of the list porn.

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Speaker 4: Please explain. I thought that'd get your attention. Look, we

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Speaker 4: don't often talk about porn, have we. We don't really

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Speaker 4: talk about porn very often.

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Speaker 2: So the first thing I can tell you, it's really

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Speaker 2: funny this story is when I compile my notes. As

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Speaker 2: you know, I often cheat, and I get one of

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Speaker 2: my assistants to actually compile the list. So I get

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Speaker 2: all the emails together and then I get them to

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Speaker 2: compile it. But the guy who was helping me this

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Speaker 2: week is seventeen, and I said, oh, don't put that

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Speaker 2: story in because it's got links. So I didn't want

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Speaker 2: him to put the porn Hub story in because I

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Speaker 2: didn't want him to click on a link and potentially

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Speaker 2: send him to porn Hub.

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Speaker 1: So that was kind of So this is the heading

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Speaker 1: that I see. Porn Hub colorizes vintage erotic scenes dating

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Speaker 1: back to eighteen ninety six using AI. What a great

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Speaker 1: use of technology.

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Speaker 4: So they knew you'd like it now.

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Speaker 2: What they did they used one hundred thousand current porn

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Speaker 2: videos to teach AI what porn was, right, wow, yep.

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Speaker 2: So they used it to analyze the colorizing. So because

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Speaker 2: this stuff back to the eight ninety six, this titillating

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Speaker 2: pawn because it wouldn't be you know what we're used

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Speaker 2: to now. But what they did was they took this

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Speaker 2: vintage footage of erotic scenes, but they trained it on

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Speaker 2: current porn and then they added and colorized it so

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Speaker 2: they to get the skin tones and all that sort

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Speaker 2: of stuff. And they're actually seriously remastered this stuff, so

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Speaker 2: it's a it's a remastered film project, and there's a

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Speaker 2: ten vintage videos of this erotica and where they weren't

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Speaker 2: able to get any soundtrack that actually dubbed their own,

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Speaker 2: I'm hoping it's seventies paorn soundtrack music.

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Speaker 1: There's going to be some very distressed people out there going, hey,

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Speaker 1: do you want to see great great great great grandma? Like, firstly,

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Speaker 1: why why why are we doing this? Well, it's just

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Speaker 1: one of those because we can things, isn't it.

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Speaker 4: I just look, maybe if they'd used AI to solved

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Speaker 4: can to cure cancer or something might have been a

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Speaker 4: nice idea, but it's porn, isn't it? Yeah?

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Speaker 1: Wow, wow, Yeah, so many things. I could say that.

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Speaker 1: As I said, I'm going to try and refrain today,

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Speaker 1: but I can't say that I'm going to line up

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Speaker 1: to Have you seen it?

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Speaker 4: No, I haven't clicked to and looked at it. Probably boring.

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Speaker 1: Oh what do you mean?

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Speaker 4: No, I don't know. I didn't want to click.

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Speaker 1: Why is your voice going so high? Why do you

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Speaker 1: sound like a twelve year old soprano all of a sudden?

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Speaker 2: No, I just was worried that my If I clicked through,

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Speaker 2: then of course it'll leave a cookie on my computer,

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Speaker 2: and suddenly all the ads will be for things late

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Speaker 2: to the pawn and we'll use my computer, my staff

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Speaker 2: use my computer. I don't want to click on something

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Speaker 2: I have. Yeah, it would just be highly inappropriate, I

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Speaker 2: think to be all.

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Speaker 1: Right, Well, if people want to go and find that,

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Speaker 1: Patrick will send you a link, then the federal police

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Speaker 1: will be out his door at dinner time.

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Speaker 4: Yeah.

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Speaker 2: Hey, you know what, you'll find this interesting because we've

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Speaker 2: had some really interesting, challenging conversations about belief systems, and

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Speaker 2: this blows my mind. But there are a lot of

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Speaker 2: people who believe the Earth is flat, for example, but

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Speaker 2: there are also conspiracy theorists that you believe, for example,

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Speaker 2: that you know, Man never went to the moon, and

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Speaker 2: there's a whole lot of theories around that. And if

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Speaker 2: you talk to somebody who is a conspiracy theorist, they

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Speaker 2: have quite a number of really good rebuttals and arguments

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Speaker 2: to support whatever the conspiracy theory is. So interestingly, what

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Speaker 2: they've done is they've trained an AI model specifically to

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Speaker 2: be able to argue against conspiracy theories. This is a

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Speaker 2: team up between researchers at the Massachusetts Institute of Technologies

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Speaker 2: at MIT, Cornell, and the American University. So what they

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Speaker 2: did was they they created a chatbot call debunk Bot,

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Speaker 2: and they were able then to sit down I think

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Speaker 2: was over two thousand people and they would fire off

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Speaker 2: their supporting arguments for a particular conspiracy theory. But because

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Speaker 2: the AI was able to challenge those questions so quickly,

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Speaker 2: nearly it was well nearly, quite a large number of

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Speaker 2: them were actually shown to have reconsidered what their conspiracy

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Speaker 2: theory was after sitting through three sessions of talking to

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Speaker 2: the debunk bot. Because you know, when you think about,

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Speaker 2: you know what people belief systems are. If I have

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Speaker 2: an argument with you about something, you're usually an expert

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Speaker 2: on that, and so it's very difficult to argue against

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Speaker 2: the point that someone is really passionate about and potentially

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Speaker 2: has researched a lot, whereas an AI can snappily get

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Speaker 2: those results so quickly that it can debunk every single

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Speaker 2: one of the arguments that's presented. And they and even

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Speaker 2: after three months, they found a high percentage of those

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Speaker 2: people were starting to challenge their belief system based on

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Speaker 2: the arguments that they had with this AI chatbot.

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Speaker 1: I love that. That's very interesting, and I think it's

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Speaker 1: all you said, a really good thing or a really

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Speaker 1: interesting thing, and you said that things that people are

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Speaker 1: passionate about, the problem with that passion is that that's emotion.

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Speaker 1: And so as soon as you're emotional about something, you're

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Speaker 1: not rational or logical necessarily right. And it's the problem

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Speaker 1: with us, all of us, and I mean humans, you

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Speaker 1: may tiff, is that our beliefs are intertwined with our

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Speaker 1: sense of identity. And so it's like when you go

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Speaker 1: I am you're making an im statement. You say, I

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Speaker 1: am a vegan. Well, that's an identity. I am a

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Speaker 1: Collingwood supporter, I am a Buddhist, I am these I

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Speaker 1: am statements. And then so regarding your belief and thinking

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00:24:05,280 --> 00:24:11,200
Speaker 1: about that particular ideology, philosophy, lifestyle, whatever, Yeah, it makes

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Speaker 1: you and I'm the same. It makes you almost unteachable

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Speaker 1: because you believe that you're right. So anything that doesn't

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Speaker 1: echo what you think is right. So the fact that they,

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Speaker 1: you know, did that and they got their responses really interesting.

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Speaker 1: But also keep in mind that conspiracy theories exist for

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Speaker 1: a reason. Like if you think that the government, for example,

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Speaker 1: tell you everything, you're an idiot, because they definitely don't,

435
00:24:41,119 --> 00:24:44,119
Speaker 1: and for good reason, I would imagine in many instances,

436
00:24:44,840 --> 00:24:48,600
Speaker 1: you know. So the fact is that some conspiracies are

437
00:24:48,680 --> 00:24:56,000
Speaker 1: actually true, a lot of them are not true, you know. Yeah,

438
00:24:56,080 --> 00:24:59,919
Speaker 1: so that's interesting. I wonder how long that would last.

439
00:25:00,240 --> 00:25:04,720
Speaker 2: Kind of turnaround, Well, this MIT professor, he's the co author,

440
00:25:04,800 --> 00:25:07,240
Speaker 2: guy with the name of David Rand and during his

441
00:25:07,520 --> 00:25:10,520
Speaker 2: media conference he was saying that one of the reasons

442
00:25:10,560 --> 00:25:16,240
Speaker 2: that AI was really overwhelmingly good is because it was respectful,

443
00:25:16,680 --> 00:25:20,560
Speaker 2: it was non conspirat when you think about it, and

444
00:25:20,600 --> 00:25:23,320
Speaker 2: you brought this up before the emotional side of it,

445
00:25:23,400 --> 00:25:27,040
Speaker 2: because it's not emotional. It was able to get the

446
00:25:27,119 --> 00:25:32,200
Speaker 2: explanations back in what was, you know, a rapid time,

447
00:25:32,680 --> 00:25:35,840
Speaker 2: and it was able to tackle every single point, but

448
00:25:35,920 --> 00:25:39,560
Speaker 2: it engaged in what they called critical thinking, providing the

449
00:25:39,640 --> 00:25:43,160
Speaker 2: counter evidence. So there was no question from the other

450
00:25:43,200 --> 00:25:46,320
Speaker 2: person's perspective. So the conspiracy theorist didn't feel like they

451
00:25:46,320 --> 00:25:49,560
Speaker 2: were getting a red blooded, passionate other person on the

452
00:25:49,560 --> 00:25:51,639
Speaker 2: other side of the argument, and what they were getting

453
00:25:51,720 --> 00:25:55,119
Speaker 2: was just factual responses rebutting what they believed in. So

454
00:25:56,320 --> 00:25:58,199
Speaker 2: it is an interesting way of kind of doing it.

455
00:25:58,240 --> 00:26:02,120
Speaker 2: And you know, they talked about over two thousand adults

456
00:26:02,560 --> 00:26:06,480
Speaker 2: they had conspiracy theories like the John F. Kennedy assassination,

457
00:26:06,640 --> 00:26:11,600
Speaker 2: alien abductions, the world being flat and around it. I

458
00:26:11,680 --> 00:26:14,800
Speaker 2: think around about twenty people were ready to walk away

459
00:26:14,800 --> 00:26:19,760
Speaker 2: from their beliefs, and another high percentage when shown this evidence,

460
00:26:20,080 --> 00:26:25,120
Speaker 2: showed a really strong sense of reconsidering what it was.

461
00:26:25,080 --> 00:26:26,480
Speaker 4: That they had believed.

462
00:26:26,480 --> 00:26:28,640
Speaker 2: So I just thought it was a really interesting use

463
00:26:28,680 --> 00:26:33,000
Speaker 2: of AI and a third of the respondents left saying

464
00:26:33,000 --> 00:26:36,800
Speaker 2: they were no longer certain of the belief and that

465
00:26:37,000 --> 00:26:40,600
Speaker 2: persisted after two months. So in answer your question, after

466
00:26:40,640 --> 00:26:43,159
Speaker 2: a two month period that was still their beliefs that

467
00:26:43,480 --> 00:26:47,000
Speaker 2: they had still challenged that belief I.

468
00:26:46,960 --> 00:26:49,359
Speaker 1: Think that a caveat needs to be I think that's

469
00:26:49,359 --> 00:26:51,600
Speaker 1: interesting and I don't disagree with any of that or

470
00:26:51,600 --> 00:26:53,919
Speaker 1: I don't think that that's not valuable. I think it is.

471
00:26:54,000 --> 00:26:56,360
Speaker 1: I think there needs to be an asterisk and a caveat,

472
00:26:57,000 --> 00:26:59,399
Speaker 1: and that is that. I don't think we should just

473
00:26:59,600 --> 00:27:05,760
Speaker 1: blindly trust artificial intelligence. I don't think that, you know,

474
00:27:05,920 --> 00:27:09,399
Speaker 1: like I saw a post the other day and somebody

475
00:27:09,480 --> 00:27:16,080
Speaker 1: had said, tell me, can you like somebody was asking chat,

476
00:27:16,119 --> 00:27:20,960
Speaker 1: GPT or one of those AI tools, tell me a

477
00:27:21,040 --> 00:27:24,359
Speaker 1: joke about Jesus and you know, and then it said

478
00:27:24,400 --> 00:27:27,199
Speaker 1: tell me, and it told them a joke or a

479
00:27:27,200 --> 00:27:30,560
Speaker 1: bunch of jokes about Jesus. And then it said, now

480
00:27:30,600 --> 00:27:33,720
Speaker 1: tell me some jokes about Muhammad and it said, I can't.

481
00:27:34,160 --> 00:27:38,400
Speaker 1: I can't tell religious like it wouldn't right. And there

482
00:27:38,440 --> 00:27:43,439
Speaker 1: was another one similar, like tell me basically tell me

483
00:27:43,480 --> 00:27:50,560
Speaker 1: a story that makes uh Kamela Harris look, you know, silly,

484
00:27:50,680 --> 00:27:53,440
Speaker 1: or and it wouldn't. But then with Donald Trump it

485
00:27:53,560 --> 00:27:58,160
Speaker 1: would so not everything where it depends on what it's

486
00:27:58,280 --> 00:28:00,320
Speaker 1: trained on. By the way, I don't think we should

487
00:28:00,400 --> 00:28:05,200
Speaker 1: necessarily be telling jokes about Christianity or Islam or Jesus

488
00:28:05,320 --> 00:28:07,520
Speaker 1: or Muhammad or I don't think so. I'm just saying

489
00:28:07,520 --> 00:28:11,880
Speaker 1: it's just I think it depends on, like not everything

490
00:28:12,000 --> 00:28:17,320
Speaker 1: that it produces is unequivocal truth. It depends on where

491
00:28:17,440 --> 00:28:20,439
Speaker 1: it's getting its source of its information from.

492
00:28:20,760 --> 00:28:23,720
Speaker 4: So the human bias of the programers is what you're saying,

493
00:28:23,840 --> 00:28:24,440
Speaker 4: is also.

494
00:28:24,280 --> 00:28:28,439
Speaker 1: One hundred percent because everything's programmed. Even it's like people

495
00:28:28,440 --> 00:28:33,960
Speaker 1: think science is flawless, it's complete shit, like not sciences,

496
00:28:34,000 --> 00:28:37,359
Speaker 1: but that idea, because science is a construct of the

497
00:28:37,440 --> 00:28:41,000
Speaker 1: human mind. We created this idea and we go, well,

498
00:28:41,000 --> 00:28:44,800
Speaker 1: we're going to test this hypothesis with these protocols. Then

499
00:28:44,880 --> 00:28:47,840
Speaker 1: we're going to and this is someone who's like running

500
00:28:47,880 --> 00:28:50,560
Speaker 1: his own research at the moment, And then you get

501
00:28:50,600 --> 00:28:53,640
Speaker 1: the research, then you interpret the data, then you tell

502
00:28:53,680 --> 00:28:56,280
Speaker 1: the world what it means. But the problem is all

503
00:28:56,320 --> 00:29:00,160
Speaker 1: the way along there's human interpretation and every human and

504
00:29:00,240 --> 00:29:06,240
Speaker 1: whether you're a minister or a scientist or an AI creator,

505
00:29:06,960 --> 00:29:10,080
Speaker 1: like every single one of those people is still a

506
00:29:10,160 --> 00:29:13,720
Speaker 1: human with bias. And the same with me, Like I

507
00:29:13,880 --> 00:29:17,000
Speaker 1: recognize that when I have these conversations with you, my

508
00:29:17,200 --> 00:29:20,360
Speaker 1: own bias, and there are times when you're right. No

509
00:29:20,400 --> 00:29:22,600
Speaker 1: I'm wrong, and I don't want you to be right

510
00:29:22,920 --> 00:29:26,120
Speaker 1: because it fucking bothers me. But you're right and I

511
00:29:26,200 --> 00:29:28,600
Speaker 1: am wrong. Right, And this is we need to be

512
00:29:28,640 --> 00:29:32,080
Speaker 1: able to acknowledge the human condition, and that is I

513
00:29:32,120 --> 00:29:35,320
Speaker 1: am flawed. I look at the window through the world,

514
00:29:35,360 --> 00:29:38,960
Speaker 1: through the Craig window I have. And until you can

515
00:29:39,080 --> 00:29:41,280
Speaker 1: recognize and realize that, you're going to get a lot

516
00:29:41,320 --> 00:29:45,280
Speaker 1: of shit wrong, and so is AI and so is science,

517
00:29:45,720 --> 00:29:48,640
Speaker 1: then we're all kidding ourselves because we think I know

518
00:29:48,760 --> 00:29:51,800
Speaker 1: the truth, but you don't. But the truth is, I

519
00:29:51,880 --> 00:29:56,520
Speaker 1: think ironically, we don't really fucking know most things. We

520
00:29:56,680 --> 00:29:57,560
Speaker 1: just think we know.

521
00:29:58,160 --> 00:30:01,400
Speaker 2: And science always has a cab yet anyway, that this

522
00:30:01,440 --> 00:30:04,880
Speaker 2: is a theory, So you know, the theory of relativity,

523
00:30:05,160 --> 00:30:08,120
Speaker 2: the theory of gravity. You know, we can display and

524
00:30:08,360 --> 00:30:11,120
Speaker 2: what you know, our best approximation of what we understand

525
00:30:11,200 --> 00:30:13,880
Speaker 2: gravity to be. But it's still just a theory, you know.

526
00:30:14,000 --> 00:30:17,000
Speaker 2: And when we talk about some of these, you can't

527
00:30:17,040 --> 00:30:20,080
Speaker 2: have hard and far fast, one hundred percent proven facts.

528
00:30:20,880 --> 00:30:23,520
Speaker 2: So science is always reticent to come out and say

529
00:30:23,600 --> 00:30:26,880
Speaker 2: this is one hundred percent this, ah.

530
00:30:26,560 --> 00:30:30,120
Speaker 1: But science doesn't communicate it like that. You're you're right,

531
00:30:30,320 --> 00:30:33,040
Speaker 1: you're absolutely right, but you know so. One of the

532
00:30:33,040 --> 00:30:37,600
Speaker 1: most famous fucking frauds of all time was by a

533
00:30:37,640 --> 00:30:41,520
Speaker 1: guy called Ansel Keyes who ran a study. His essential

534
00:30:41,680 --> 00:30:44,240
Speaker 1: theory was we've spoken about this couple of times on

535
00:30:44,360 --> 00:30:46,480
Speaker 1: I don't know if we've spoken about it on our show,

536
00:30:46,520 --> 00:30:51,360
Speaker 1: but he did a study that involved twenty different countries

537
00:30:51,400 --> 00:30:55,480
Speaker 1: and his theory. Essentially, his hypothesis was that low fat

538
00:30:55,560 --> 00:31:01,160
Speaker 1: equal low fat eating equals low fat people, and he

539
00:31:01,320 --> 00:31:05,120
Speaker 1: basically dockted the results. He cut out thirteen of the

540
00:31:05,160 --> 00:31:08,200
Speaker 1: twenty studies, so it went from a twenty country study

541
00:31:08,240 --> 00:31:12,520
Speaker 1: to a seven country study because thirteen of the country's

542
00:31:12,600 --> 00:31:16,480
Speaker 1: data contradicted his hypothesis, so he swept them under the

543
00:31:16,520 --> 00:31:20,200
Speaker 1: academic carpets so people wouldn't know. He tried to hide that,

544
00:31:20,640 --> 00:31:23,080
Speaker 1: and it went on and on and on, and the

545
00:31:24,000 --> 00:31:27,880
Speaker 1: uncomfortable truth is that since the incidents and the occurrence

546
00:31:27,920 --> 00:31:31,920
Speaker 1: of low fat eating, there's been a continual rise in

547
00:31:31,960 --> 00:31:36,719
Speaker 1: all the countries that embraced that philosophy with obesity, you know,

548
00:31:37,440 --> 00:31:42,360
Speaker 1: and so low fat, high carb high processed food, which

549
00:31:42,400 --> 00:31:45,320
Speaker 1: is what they kind of in part recommended, you know,

550
00:31:45,640 --> 00:31:49,240
Speaker 1: and that was allegedly the best science. So the food pyramid,

551
00:31:49,640 --> 00:31:52,520
Speaker 1: that was the science. And now people are many, many,

552
00:31:52,560 --> 00:31:55,120
Speaker 1: many people are kind of going, no, you know, so

553
00:31:55,240 --> 00:31:57,440
Speaker 1: you and in ten years we're going to be thinking

554
00:31:57,520 --> 00:31:59,880
Speaker 1: something else. It's a slippery landscape.

555
00:32:00,480 --> 00:32:03,800
Speaker 4: Mm hmmm. Hey, while we're on the topic of AI,

556
00:32:04,160 --> 00:32:06,000
Speaker 4: I had a story I wanted to talk about that

557
00:32:06,080 --> 00:32:08,840
Speaker 4: I really was adverse to. I kind of worry about this.

558
00:32:09,240 --> 00:32:12,480
Speaker 2: So a few shows ago, I used AI to copy

559
00:32:12,560 --> 00:32:15,440
Speaker 2: your voice and I did the of the show as

560
00:32:15,480 --> 00:32:17,760
Speaker 2: you saying how good I was. So that should have

561
00:32:17,760 --> 00:32:19,960
Speaker 2: been an indicator right off the bat that it wasn't

562
00:32:20,000 --> 00:32:20,520
Speaker 2: really you.

563
00:32:20,880 --> 00:32:22,080
Speaker 4: But what.

564
00:32:23,760 --> 00:32:25,920
Speaker 1: Hell? What are you? What are you so nasty to

565
00:32:26,000 --> 00:32:30,760
Speaker 1: me for today? Why are you picking on me today?

566
00:32:30,960 --> 00:32:33,480
Speaker 4: Well? Have you ever? Let's listen to our past episodes.

567
00:32:35,200 --> 00:32:36,960
Speaker 4: What I'm just getting really.

568
00:32:37,560 --> 00:32:40,800
Speaker 1: Well, I haven't thrown you under the bus once today.

569
00:32:40,960 --> 00:32:41,440
Speaker 4: That's right.

570
00:32:41,560 --> 00:32:46,160
Speaker 2: Today, That's why I'm getting in early.

571
00:32:46,840 --> 00:32:49,760
Speaker 1: All right, all right, I'll take it. Come on.

572
00:32:50,160 --> 00:32:54,640
Speaker 2: So Audible, which is a subscription service that I really

573
00:32:54,680 --> 00:32:58,160
Speaker 2: love because I love listening to audio books. They're now

574
00:32:58,280 --> 00:33:01,840
Speaker 2: doing a limited training service of some of their more

575
00:33:01,920 --> 00:33:06,800
Speaker 2: popular narrators and getting them to have their voices trained

576
00:33:06,800 --> 00:33:10,240
Speaker 2: by AI with their permission for them to be able

577
00:33:10,280 --> 00:33:14,920
Speaker 2: to read books using their AI voice. Now they will

578
00:33:14,920 --> 00:33:17,760
Speaker 2: be getting royalties for it, so they're giving permission. And

579
00:33:17,800 --> 00:33:20,560
Speaker 2: I kind of thought to myself, look, I kind of

580
00:33:20,600 --> 00:33:23,600
Speaker 2: feel sad. I love the idea of voice acting, and

581
00:33:24,000 --> 00:33:26,840
Speaker 2: some of the best audible books I've heard have been

582
00:33:26,880 --> 00:33:29,520
Speaker 2: from so talented people. You know, sometimes you get one

583
00:33:29,560 --> 00:33:33,320
Speaker 2: person who does the entire narration, does character voices, and

584
00:33:33,360 --> 00:33:36,680
Speaker 2: I love that, and they're usually really talented actors. So

585
00:33:36,800 --> 00:33:39,560
Speaker 2: I thought when I first saw this that it feels

586
00:33:39,560 --> 00:33:42,240
Speaker 2: a bit sad. It feels like for somebody who does

587
00:33:42,280 --> 00:33:45,280
Speaker 2: do voiceover work. I do on holds, I do voiceovers

588
00:33:45,520 --> 00:33:47,080
Speaker 2: for corporate video and stuff like that.

589
00:33:47,120 --> 00:33:49,520
Speaker 4: And I thought, to myself, this feels a bit sad.

590
00:33:49,760 --> 00:33:52,480
Speaker 2: Would I AI my voice and just you know, put

591
00:33:52,480 --> 00:33:54,000
Speaker 2: the script in and just do it that way? What

592
00:33:54,040 --> 00:33:58,280
Speaker 2: it feels like it's losing humanity. However, one thing that

593
00:33:58,360 --> 00:34:01,160
Speaker 2: just occurred to me, and it happened this week. James

594
00:34:01,240 --> 00:34:04,440
Speaker 2: Earl Jones passed away. Now, if you could, if I

595
00:34:04,920 --> 00:34:07,480
Speaker 2: would beg you to think of another voice that is

596
00:34:07,520 --> 00:34:11,479
Speaker 2: more iconic than James Earl Jones. You know Darth Vadamvasa

597
00:34:11,600 --> 00:34:15,240
Speaker 2: from The Lion King. He has one of the most iconic,

598
00:34:15,400 --> 00:34:20,239
Speaker 2: beautiful voices you've ever heard. Now, if his family consented

599
00:34:20,920 --> 00:34:24,160
Speaker 2: and they trained an AI model on James Earl Jones,

600
00:34:24,440 --> 00:34:27,480
Speaker 2: I'm really warring with this. It's not James Earl Jones,

601
00:34:27,560 --> 00:34:30,359
Speaker 2: but it is James Earl Jones because it's sampled from him.

602
00:34:30,360 --> 00:34:34,000
Speaker 2: It's using the nuances of his inflections and tonalities and all.

603
00:34:33,920 --> 00:34:36,680
Speaker 4: That sort of stuff. But is it really him? If

604
00:34:36,680 --> 00:34:37,360
Speaker 4: he narrates?

605
00:34:39,080 --> 00:34:44,160
Speaker 1: That's interesting. It's interesting because what if you well, obviously

606
00:34:44,200 --> 00:34:48,200
Speaker 1: it's not. It's just it's a program using his voice.

607
00:34:48,520 --> 00:34:52,479
Speaker 1: But then but then maybe it is, like you think

608
00:34:52,520 --> 00:34:58,080
Speaker 1: about if if you didn't know that it was AI created,

609
00:34:58,200 --> 00:35:01,400
Speaker 1: but it was using his voice, you would have the

610
00:35:01,480 --> 00:35:05,000
Speaker 1: same experience as if it was really him. It's the

611
00:35:05,080 --> 00:35:06,879
Speaker 1: knowing that fucks it up, isn't it.

612
00:35:07,800 --> 00:35:10,680
Speaker 4: Yeah, that's that's actually a really accurate points. That's interesting.

613
00:35:11,280 --> 00:35:13,440
Speaker 1: It's the knowing that makes it not. But if you

614
00:35:13,560 --> 00:35:16,600
Speaker 1: didn't know, it's like, remember you were telling was it

615
00:35:16,640 --> 00:35:18,320
Speaker 1: you telling us about the Banksies?

616
00:35:19,520 --> 00:35:22,320
Speaker 4: No? You know the art right? Last episode?

617
00:35:22,400 --> 00:35:25,960
Speaker 1: Right? Well, I know We had that conversation, but I

618
00:35:26,440 --> 00:35:28,440
Speaker 1: couldn't remember if you or I started. But you think

619
00:35:28,520 --> 00:35:31,920
Speaker 1: about like you know it's a Banksye, it's worth two

620
00:35:32,000 --> 00:35:35,200
Speaker 1: hundred thousand dollars. It really is a Banksy, but you

621
00:35:35,320 --> 00:35:38,760
Speaker 1: think it's not. It's worth sixty dollars. It's not about

622
00:35:38,760 --> 00:35:42,200
Speaker 1: the painting, it's about what you think you know. And

623
00:35:42,360 --> 00:35:47,640
Speaker 1: I'm thinking another very awesome voice, maybe maybe half a

624
00:35:47,760 --> 00:35:51,560
Speaker 1: rung down Morgan Freeman. He's also right up there, isn't

625
00:35:51,600 --> 00:35:52,800
Speaker 1: he like super voice?

626
00:35:53,200 --> 00:35:56,000
Speaker 4: So you know what where my mind went is if

627
00:35:56,080 --> 00:35:59,319
Speaker 4: you were blindfolded and put on a message table, I

628
00:35:59,360 --> 00:36:02,600
Speaker 4: have very solh Yes, yes.

629
00:36:03,640 --> 00:36:04,920
Speaker 1: You've obviously thought about this.

630
00:36:05,040 --> 00:36:09,120
Speaker 2: A bit walked in and gave you a message and

631
00:36:09,160 --> 00:36:09,920
Speaker 2: then I walked out.

632
00:36:10,800 --> 00:36:14,520
Speaker 1: You've seen Tip's hands. She looks like a fucking construction worker.

633
00:36:16,120 --> 00:36:19,839
Speaker 1: That's not even a joke. If somebody had to rub

634
00:36:19,880 --> 00:36:22,959
Speaker 1: my back and ass, I would much rather you, because

635
00:36:22,960 --> 00:36:25,839
Speaker 1: if you like getting fucking sand blasted.

636
00:36:26,280 --> 00:36:29,000
Speaker 5: It would be good exfoliation. It's good for your skin.

637
00:36:29,880 --> 00:36:32,239
Speaker 1: I don't want to massage from you, Eva, but thank you.

638
00:36:32,760 --> 00:36:35,719
Speaker 1: We're still friends. But I don't want you rubbing my ship.

639
00:36:35,840 --> 00:36:38,279
Speaker 1: But Patrick, maybe with a little bit of en you're

640
00:36:38,280 --> 00:36:42,000
Speaker 1: in the background, and some fucking some baby oil. Just

641
00:36:42,120 --> 00:36:45,399
Speaker 1: maybe Fritz licking my toes while Patrick does it. I mean,

642
00:36:46,120 --> 00:36:47,400
Speaker 1: I could think of worse things.

643
00:36:50,600 --> 00:36:53,400
Speaker 4: I asked, I did notice.

644
00:36:53,080 --> 00:36:55,840
Speaker 1: You you opened the door, and then I come in

645
00:36:55,880 --> 00:36:57,360
Speaker 1: and you're like, oh, how did that happen?

646
00:36:58,960 --> 00:37:01,759
Speaker 4: You didn't just open the door, dude, You crow bart

647
00:37:01,800 --> 00:37:07,640
Speaker 4: it and then widened it to make it French doores?

648
00:37:09,400 --> 00:37:11,760
Speaker 1: All right, I'm staying quiet, you to keep going.

649
00:37:13,080 --> 00:37:17,200
Speaker 2: I like, look, we're all mindful of AI fakes and

650
00:37:17,280 --> 00:37:19,280
Speaker 2: fake them and all that sort of stuff. But Google,

651
00:37:19,360 --> 00:37:22,440
Speaker 2: now of all companies, is planning to roll out a

652
00:37:22,520 --> 00:37:26,360
Speaker 2: new tech that will identify whether a photo was taken

653
00:37:26,440 --> 00:37:29,920
Speaker 2: with a camera, edited by software like Photoshop, or produced

654
00:37:30,600 --> 00:37:34,200
Speaker 2: entirely by a I I think that's actually pretty good

655
00:37:34,520 --> 00:37:38,040
Speaker 2: when it comes to, you know, being able to debunk

656
00:37:38,760 --> 00:37:41,400
Speaker 2: fake news, but also knowing that if you were a

657
00:37:41,480 --> 00:37:46,280
Speaker 2: client and you're asking for someone to produce some work

658
00:37:46,440 --> 00:37:49,120
Speaker 2: for you and they're trying to pass it off as

659
00:37:49,280 --> 00:37:52,600
Speaker 2: fake and looks so accurate, you could then check that

660
00:37:53,280 --> 00:37:55,200
Speaker 2: so you know, or if you know, TIFF's got an

661
00:37:55,200 --> 00:37:59,200
Speaker 2: autographed photo of Craig and she's trying to a thousand

662
00:37:59,280 --> 00:38:02,319
Speaker 2: bucks on ay and I do it scan and I say,

663
00:38:02,360 --> 00:38:05,799
Speaker 2: wait a minute, that's not Craig. That's been AI generated

664
00:38:05,840 --> 00:38:08,200
Speaker 2: and the signature is too pixelated. And I'm not going

665
00:38:08,200 --> 00:38:09,000
Speaker 2: to pay any them for that.

666
00:38:10,520 --> 00:38:13,760
Speaker 1: Yeah, yeah, because that would that'd be a big seller.

667
00:38:15,920 --> 00:38:19,759
Speaker 1: That'd be huge, don't you think though that? Moving forward? Mate,

668
00:38:19,760 --> 00:38:21,920
Speaker 1: this is going to be an ongoing thing, like just

669
00:38:21,960 --> 00:38:24,600
Speaker 1: trying to figure out what's real. I just thought of something.

670
00:38:24,600 --> 00:38:25,319
Speaker 1: You know what we could do?

671
00:38:25,719 --> 00:38:28,759
Speaker 2: We could do autograph photos of the three of us

672
00:38:29,200 --> 00:38:31,919
Speaker 2: posted onto eBay and then put it out to see

673
00:38:31,960 --> 00:38:32,760
Speaker 2: who gets the best.

674
00:38:32,800 --> 00:38:32,920
Speaker 4: Bit.

675
00:38:35,440 --> 00:38:37,640
Speaker 1: I feel like none of them are going to sell that,

676
00:38:37,719 --> 00:38:38,600
Speaker 1: would you too much?

677
00:38:39,160 --> 00:38:41,640
Speaker 4: No, I'll just put Fritz in there. Fritz will sell.

678
00:38:42,760 --> 00:38:45,040
Speaker 1: Tiff was telling me that she met someone the other day.

679
00:38:45,080 --> 00:38:46,920
Speaker 1: I'm not throwing her under the bus because this is

680
00:38:46,960 --> 00:38:50,160
Speaker 1: lovely who was nervous to meet her because she because

681
00:38:50,200 --> 00:38:51,200
Speaker 1: Tif's famous.

682
00:38:51,520 --> 00:38:52,680
Speaker 4: Yeah, I can understand.

683
00:38:52,760 --> 00:38:55,520
Speaker 1: How did you? How did you feel being famous? Tif?

684
00:38:56,719 --> 00:38:58,239
Speaker 5: It's so funny, isn't it.

685
00:38:59,600 --> 00:39:01,279
Speaker 1: It's yep?

686
00:39:03,640 --> 00:39:05,759
Speaker 3: I was like that put me on a pedestal because

687
00:39:05,760 --> 00:39:07,840
Speaker 3: I'll fall off and break my leg. I'm not I

688
00:39:07,880 --> 00:39:08,879
Speaker 3: don't belong up there.

689
00:39:10,080 --> 00:39:13,200
Speaker 1: Yeah, we know what happens when I stand on pedestals.

690
00:39:12,600 --> 00:39:13,000
Speaker 4: Don't we do?

691
00:39:16,719 --> 00:39:17,319
Speaker 5: Emergency?

692
00:39:18,360 --> 00:39:21,920
Speaker 1: That replied, Big Gone, buddy.

693
00:39:22,800 --> 00:39:25,880
Speaker 4: So I'm going to do one more AI story because

694
00:39:25,880 --> 00:39:28,760
Speaker 4: this is a particularly good one, and it's also about

695
00:39:28,800 --> 00:39:31,480
Speaker 4: a painter that I one of their pieces of art

696
00:39:31,480 --> 00:39:34,280
Speaker 4: that I love because it's also associated with a movie

697
00:39:34,280 --> 00:39:38,160
Speaker 4: that I love called The Woman in Gold and good

698
00:39:38,200 --> 00:39:42,719
Speaker 4: Stuff Climped. So Good Stuff Climped Austrian painter. A lot

699
00:39:42,760 --> 00:39:46,799
Speaker 4: of his paintings were lost. They were either stolen or

700
00:39:46,840 --> 00:39:48,960
Speaker 4: they were and there's a whole group that were actually

701
00:39:48,960 --> 00:39:53,080
Speaker 4: burnt in a fire. So there was a massive fire

702
00:39:53,320 --> 00:39:57,880
Speaker 4: when the Germans left Vienna. They burnt a lot of buildings.

703
00:39:57,960 --> 00:40:02,240
Speaker 2: And what they've done is they've taken black and white

704
00:40:02,239 --> 00:40:09,120
Speaker 2: photographs of those paintings, then trained an AI model on

705
00:40:09,239 --> 00:40:13,640
Speaker 2: Gustav Climt's style of painting, and then they've been able

706
00:40:13,680 --> 00:40:17,880
Speaker 2: to recolorize the imagery to give us some better understanding

707
00:40:17,920 --> 00:40:22,200
Speaker 2: of what the original painting would have looked like. So

708
00:40:22,239 --> 00:40:24,360
Speaker 2: are you familiar with the movie The Woman in Gold?

709
00:40:24,760 --> 00:40:28,240
Speaker 2: Helen Mirren was in it. It's a phenomenal story. Basically,

710
00:40:28,239 --> 00:40:31,360
Speaker 2: it's a true story about the reparation of this painting

711
00:40:31,400 --> 00:40:33,719
Speaker 2: by Clympt called The Woman in Gold that hung in

712
00:40:33,760 --> 00:40:36,520
Speaker 2: a gallery in Vienna for years. It was kind of

713
00:40:36,520 --> 00:40:40,920
Speaker 2: the Mona Lisa of Vienna, of Austria and the original family.

714
00:40:41,000 --> 00:40:43,560
Speaker 2: So that this woman, this woman who lived in New York.

715
00:40:43,880 --> 00:40:47,120
Speaker 2: It was her auntie. The painting was of her auntie

716
00:40:47,200 --> 00:40:49,840
Speaker 2: and it belonged to her family, and it was stolen

717
00:40:50,280 --> 00:40:54,120
Speaker 2: by the Nazis and then eventually it was you know,

718
00:40:54,239 --> 00:40:59,160
Speaker 2: it was then put on display in Austria, and she

719
00:40:59,400 --> 00:41:04,120
Speaker 2: fought to get the painting back and it happened. It

720
00:41:04,160 --> 00:41:06,120
Speaker 2: was amazing. It's a phenomenal. If you haven't seen the film,

721
00:41:06,160 --> 00:41:09,400
Speaker 2: it's great. I'll certainly encourage you to see it. But

722
00:41:09,960 --> 00:41:12,880
Speaker 2: I just think this is an amazing way to restore

723
00:41:13,000 --> 00:41:17,759
Speaker 2: something that was tragically lost to fire and using this

724
00:41:17,840 --> 00:41:21,120
Speaker 2: late you know, this really great AI tech to not

725
00:41:21,440 --> 00:41:24,560
Speaker 2: just recolorize, but to recolorize. So we're not talking porn

726
00:41:24,600 --> 00:41:29,359
Speaker 2: hub here. We're talking good climped right the whole use

727
00:41:29,360 --> 00:41:32,359
Speaker 2: your powers for good or evil in this game.

728
00:41:32,680 --> 00:41:35,760
Speaker 4: I'm thinking this is a good version of our first story.

729
00:41:38,040 --> 00:41:40,239
Speaker 1: Well, I definitely think that's a better app but I

730
00:41:40,280 --> 00:41:42,839
Speaker 1: wonder then even with that, Like when you get let's

731
00:41:42,880 --> 00:41:49,000
Speaker 1: say you get the kind of the restored artificially AI enhanced,

732
00:41:49,480 --> 00:41:52,120
Speaker 1: you know you still know that that's not the original.

733
00:41:52,280 --> 00:41:55,200
Speaker 1: I wonder, you know, so much of this stuff is

734
00:41:55,239 --> 00:41:58,640
Speaker 1: about like what you think about it.

735
00:41:58,920 --> 00:41:59,920
Speaker 4: Like, But I've got a.

736
00:42:00,120 --> 00:42:05,640
Speaker 2: Production of the Gustaff Climped painting in my home. It's

737
00:42:05,680 --> 00:42:09,160
Speaker 2: a really large format, it's almost a meter high, and

738
00:42:09,200 --> 00:42:11,680
Speaker 2: it looks stunning. It's nowhere near what the original looks like,

739
00:42:11,880 --> 00:42:14,600
Speaker 2: but it's nice because I love the painting and it's

740
00:42:14,640 --> 00:42:17,279
Speaker 2: great to have a prince of it. When I see

741
00:42:17,320 --> 00:42:19,440
Speaker 2: it, it makes me think about it. I couldn't you know,

742
00:42:19,600 --> 00:42:24,360
Speaker 2: I think of, you know, some of the master painters.

743
00:42:24,360 --> 00:42:25,880
Speaker 2: None of us are ever going to be able to

744
00:42:26,160 --> 00:42:28,799
Speaker 2: afford h Monte or you know, anything like that. But

745
00:42:30,040 --> 00:42:33,000
Speaker 2: you know, at least you can appreciate it by having

746
00:42:33,040 --> 00:42:35,439
Speaker 2: a reproduction of it in some way, shape or form.

747
00:42:36,440 --> 00:42:38,480
Speaker 1: We've got a friend of a friend of the You

748
00:42:38,560 --> 00:42:40,680
Speaker 1: project who's been on a couple of times, my friend

749
00:42:40,719 --> 00:42:44,879
Speaker 1: Dylan Dylan Key's art. You follow him, don't you tip?

750
00:42:45,080 --> 00:42:49,160
Speaker 3: Yeah, amazing, and I think.

751
00:42:50,840 --> 00:42:53,920
Speaker 1: I think he's going to be famous one days. He's

752
00:42:53,920 --> 00:42:56,720
Speaker 1: a big deal on Planet Craig. I love him. Dylan

753
00:42:56,760 --> 00:43:00,120
Speaker 1: Key's art, go and follow him and he does the

754
00:43:00,120 --> 00:43:07,880
Speaker 1: most incredible charcoal stuff. But what's interesting is, like he

755
00:43:07,960 --> 00:43:10,160
Speaker 1: does you know, a lot of a lot of animals

756
00:43:10,160 --> 00:43:11,760
Speaker 1: and stuff, and it's so good.

757
00:43:12,239 --> 00:43:13,440
Speaker 4: Wow, I'm looking at it now.

758
00:43:13,760 --> 00:43:17,880
Speaker 1: Yeah, you can't believe that this motherfucker drew that. I'm like,

759
00:43:17,960 --> 00:43:23,200
Speaker 1: how did you with charcoal? And but what's interesting is

760
00:43:23,239 --> 00:43:26,120
Speaker 1: you can buy, by the way, if you buy an original,

761
00:43:26,160 --> 00:43:28,080
Speaker 1: I think you can still buy original for a grand

762
00:43:28,160 --> 00:43:30,360
Speaker 1: or fifteen hundred or I don't know whatever. Like, but

763
00:43:30,440 --> 00:43:33,920
Speaker 1: when I first met him, like he was doing all

764
00:43:33,920 --> 00:43:37,040
Speaker 1: this incredible stuff and he only had a two or

765
00:43:37,080 --> 00:43:39,719
Speaker 1: three hundred followers, and I saw his stuff and I

766
00:43:39,760 --> 00:43:42,720
Speaker 1: reached out and went, hey, your shit's awesome. You should

767
00:43:42,719 --> 00:43:45,280
Speaker 1: be famous or something like that. And then we connected

768
00:43:45,320 --> 00:43:47,880
Speaker 1: and we spoke, and then he got a little bit

769
00:43:47,880 --> 00:43:50,200
Speaker 1: more of a following. So I think he's up to

770
00:43:50,280 --> 00:43:52,920
Speaker 1: like three or four thousand followers or something on install

771
00:43:52,960 --> 00:43:55,600
Speaker 1: or something. But my long winded point is you can

772
00:43:55,640 --> 00:43:58,120
Speaker 1: buy one of his originals for still what I think

773
00:43:58,239 --> 00:44:02,399
Speaker 1: is really cheap. By he does these incredible prints which

774
00:44:02,400 --> 00:44:08,120
Speaker 1: are pretty much indistinguishable from the original, and that's like

775
00:44:08,160 --> 00:44:11,759
Speaker 1: one hundred bucks. And I think it's so funny, like

776
00:44:12,200 --> 00:44:14,799
Speaker 1: you would somebody would have to tell you that this

777
00:44:15,000 --> 00:44:18,520
Speaker 1: is a print, that's how good they are. He sent

778
00:44:18,560 --> 00:44:20,560
Speaker 1: me one, and I didn't know that if it was

779
00:44:20,680 --> 00:44:23,959
Speaker 1: print or like, I didn't know, and I'm like, wow,

780
00:44:23,960 --> 00:44:27,600
Speaker 1: this is fucking amazing. But yeah, then you go, well

781
00:44:28,520 --> 00:44:31,239
Speaker 1: you could get the like some things which are worth

782
00:44:31,239 --> 00:44:34,000
Speaker 1: a million bucks, and then you could get a phenomenal

783
00:44:34,080 --> 00:44:36,800
Speaker 1: print that to look at from a few meters away,

784
00:44:37,960 --> 00:44:39,640
Speaker 1: you know. I mean, I'm sure a lot of people

785
00:44:39,640 --> 00:44:41,839
Speaker 1: would know, but for the average punter, like I look

786
00:44:41,840 --> 00:44:44,399
Speaker 1: at stuff, you go wow, I wonder if you get

787
00:44:44,400 --> 00:44:47,480
Speaker 1: the same joy. I wonder if it does the same

788
00:44:47,560 --> 00:44:50,840
Speaker 1: thing to your emotions and your body if it's a

789
00:44:50,880 --> 00:44:54,600
Speaker 1: print versus something real, if perceptually it's identical.

790
00:44:55,160 --> 00:44:59,319
Speaker 2: My cousin is a artist who does the cartoons for

791
00:44:59,360 --> 00:45:00,440
Speaker 2: the Times of Malta.

792
00:45:00,560 --> 00:45:04,440
Speaker 4: So he lives in Europe and he does their weekly cartoon.

793
00:45:04,880 --> 00:45:05,440
Speaker 4: And he's got a.

794
00:45:05,440 --> 00:45:08,560
Speaker 2: Great portfolio, and I've got about five of his pieces

795
00:45:08,600 --> 00:45:12,040
Speaker 2: of work now. I actually I've only ever bought one original,

796
00:45:12,080 --> 00:45:13,880
Speaker 2: and that was to give away as a gift. But

797
00:45:13,920 --> 00:45:16,879
Speaker 2: the other stuff My favorite print of his is called

798
00:45:16,960 --> 00:45:20,560
Speaker 2: Imbeciles of Frontier, so it's Imbeciles without Borders, and it's

799
00:45:20,560 --> 00:45:22,640
Speaker 2: got all the world leaders and a big banner over

800
00:45:22,640 --> 00:45:24,920
Speaker 2: the top and one of the guys standing behind the

801
00:45:24,920 --> 00:45:27,880
Speaker 2: other guys doing a you know, the rabbit years behind

802
00:45:27,920 --> 00:45:28,320
Speaker 2: him and all that.

803
00:45:28,400 --> 00:45:32,000
Speaker 4: It's a cute. It's a really beautiful framed print, but

804
00:45:32,080 --> 00:45:34,520
Speaker 4: it is just a print. And I think the original

805
00:45:34,560 --> 00:45:37,000
Speaker 4: had already sold anyway, so I couldn't have bought the original.

806
00:45:37,239 --> 00:45:39,760
Speaker 4: But it still gives me that same reaction, and everybody

807
00:45:39,800 --> 00:45:43,080
Speaker 4: who comes to my house who sees it really loves it.

808
00:45:43,080 --> 00:45:46,840
Speaker 2: It's just so wonderfully drawn and it's really detailed, you know,

809
00:45:46,880 --> 00:45:48,239
Speaker 2: when I was looking at the stuff that you're just

810
00:45:48,320 --> 00:45:51,200
Speaker 2: talking about. Now, people obviously can't see it, but it's

811
00:45:51,800 --> 00:45:55,520
Speaker 2: they are indistinguishable from a black and white photo. There's

812
00:45:55,560 --> 00:45:59,240
Speaker 2: soap and so people who can, you know, meticulously create

813
00:45:59,360 --> 00:46:03,360
Speaker 2: beautiful art. I can say it's amazing, but sometimes you

814
00:46:03,360 --> 00:46:05,800
Speaker 2: can't afford the original, but it's nice to have a reproduction.

815
00:46:05,840 --> 00:46:08,279
Speaker 2: I think it still gives you that warm fuzzies, don't

816
00:46:08,320 --> 00:46:09,040
Speaker 2: you what do you reckon?

817
00:46:09,080 --> 00:46:09,319
Speaker 4: Tiff?

818
00:46:09,520 --> 00:46:09,960
Speaker 1: Yeah?

819
00:46:10,000 --> 00:46:10,239
Speaker 4: Well?

820
00:46:10,719 --> 00:46:11,960
Speaker 1: Oh sorry god, Tiff.

821
00:46:12,320 --> 00:46:14,319
Speaker 3: Yeah No, I think it's interesting. It's all about the

822
00:46:14,360 --> 00:46:17,680
Speaker 3: context of what someone appreciates, because I was just thinking

823
00:46:17,760 --> 00:46:22,239
Speaker 3: in my head, someone doesn't appreciate someone's the story of

824
00:46:22,280 --> 00:46:27,320
Speaker 3: someone drawing it. What's the difference between getting a copy

825
00:46:27,360 --> 00:46:31,719
Speaker 3: of the print that was his reference photo because they

826
00:46:31,719 --> 00:46:36,080
Speaker 3: look exactly the same. But the idea is you appreciate

827
00:46:36,200 --> 00:46:39,960
Speaker 3: someone's gift, and you appreciate telling the people that come

828
00:46:40,000 --> 00:46:42,040
Speaker 3: to your house and go, oh, that's a nice print.

829
00:46:42,200 --> 00:46:44,840
Speaker 3: You go, oh, that's drawn by Dylan Keyes. Have a

830
00:46:44,840 --> 00:46:45,839
Speaker 3: look what this guy does.

831
00:46:46,600 --> 00:46:47,040
Speaker 4: Hmmm.

832
00:46:48,760 --> 00:46:53,680
Speaker 1: I saw this guy drawing. He was a street artist

833
00:46:54,160 --> 00:46:58,640
Speaker 1: as a video and he was drawing with his feet

834
00:46:58,920 --> 00:47:03,040
Speaker 1: because you've got no arm. And I mean I'm not saying, oh,

835
00:47:03,120 --> 00:47:05,479
Speaker 1: gee's art was good for a bloke drawing with his foot.

836
00:47:06,120 --> 00:47:10,799
Speaker 1: His art was just phenomenal, I mean amazing. And then

837
00:47:10,840 --> 00:47:13,880
Speaker 1: on top of that, I'm like, this bloke's doing this

838
00:47:13,920 --> 00:47:17,960
Speaker 1: with his foot. I could have all the bloody training

839
00:47:18,080 --> 00:47:23,640
Speaker 1: and like education and resources and I couldn't do anything

840
00:47:24,120 --> 00:47:27,719
Speaker 1: but one tenth of that. And then so the art

841
00:47:28,080 --> 00:47:30,000
Speaker 1: all on the side of the art is amazing. And

842
00:47:30,040 --> 00:47:33,719
Speaker 1: then you think how the art was created to me

843
00:47:33,880 --> 00:47:35,920
Speaker 1: that time's at by one hundred and I go, I

844
00:47:35,960 --> 00:47:38,600
Speaker 1: would love some of that guy's art, you know, just

845
00:47:38,680 --> 00:47:41,480
Speaker 1: because of the story that accompanies it as well.

846
00:47:41,560 --> 00:47:44,920
Speaker 2: You know, every year, my mum used to subscribe to

847
00:47:45,520 --> 00:47:50,840
Speaker 2: a Christmas card bundle from artists without hands, and I

848
00:47:51,080 --> 00:47:53,880
Speaker 2: vividly remember that she would there would get these gorgeous

849
00:47:53,960 --> 00:47:57,080
Speaker 2: Christmas cards she would send all our family and it

850
00:47:57,120 --> 00:48:00,399
Speaker 2: was specifically from artists who weren't paid in traditionally their hands,

851
00:48:00,440 --> 00:48:01,360
Speaker 2: some with their mouths.

852
00:48:01,640 --> 00:48:04,480
Speaker 4: That that'll my mind. That's yeah, isn't that great?

853
00:48:04,760 --> 00:48:10,239
Speaker 2: The talent knows no bounds, and disability isn't always a

854
00:48:10,320 --> 00:48:11,640
Speaker 2: hindrance to creativity?

855
00:48:12,480 --> 00:48:16,320
Speaker 1: One hundred percent, one hundred percent coup going Champ.

856
00:48:16,520 --> 00:48:18,200
Speaker 2: Hey, this is I thought you might find this an

857
00:48:18,239 --> 00:48:21,840
Speaker 2: interesting story because I know you like tech, but you

858
00:48:21,960 --> 00:48:25,360
Speaker 2: also like old tech. You like an analogue display on

859
00:48:25,400 --> 00:48:27,839
Speaker 2: your motorbike, not a digital display, would I be right?

860
00:48:28,760 --> 00:48:29,800
Speaker 4: Correct? Yeah?

861
00:48:29,840 --> 00:48:32,560
Speaker 2: So in the United States there's a massive push at

862
00:48:32,600 --> 00:48:35,040
Speaker 2: the moment, and it's actually gone to the House Committee.

863
00:48:35,320 --> 00:48:40,680
Speaker 2: They're talking about forcing manufacturers to put AM radios.

864
00:48:40,239 --> 00:48:41,120
Speaker 4: Back in cars.

865
00:48:41,800 --> 00:48:46,040
Speaker 2: Wow, because new cars don't have AM radios, they are

866
00:48:46,040 --> 00:48:50,799
Speaker 2: only digital services and streaming services. And the thing they're

867
00:48:50,840 --> 00:48:54,400
Speaker 2: saying is you've got to put AM radios back in cars,

868
00:48:54,440 --> 00:48:56,720
Speaker 2: and you're not allowed to make it a subscription service

869
00:48:57,040 --> 00:48:59,960
Speaker 2: because of course some manufacturers and I know Elin Musks

870
00:49:00,120 --> 00:49:02,680
Speaker 2: been a little bit criticized for this. If you buy

871
00:49:02,719 --> 00:49:05,279
Speaker 2: one of his cars, you can then upgrade just by

872
00:49:05,320 --> 00:49:09,919
Speaker 2: buying a subscription, so the physical vehicle doesn't change, you're

873
00:49:09,920 --> 00:49:12,759
Speaker 2: just subscribing to extra features, and so that's how they're

874
00:49:12,840 --> 00:49:14,160
Speaker 2: upselling people these days.

875
00:49:14,200 --> 00:49:15,919
Speaker 4: They're actually not just selling the car.

876
00:49:16,239 --> 00:49:18,440
Speaker 2: They're saying, yes, you can buy the AXE, but if

877
00:49:18,480 --> 00:49:20,320
Speaker 2: you want to have the sharpened version, you've got to

878
00:49:20,360 --> 00:49:24,920
Speaker 2: buy a subscription. So the reasoning or the rationale behind

879
00:49:24,960 --> 00:49:29,240
Speaker 2: the AM radio though, is that AM travels a lot

880
00:49:29,280 --> 00:49:33,319
Speaker 2: further than FM or DATA. I mean we're talking much, much,

881
00:49:33,440 --> 00:49:37,920
Speaker 2: much greater range because it's about the way that the

882
00:49:39,040 --> 00:49:43,719
Speaker 2: wave is generated. So that's called vertical polarization and horizontal

883
00:49:43,760 --> 00:49:47,080
Speaker 2: polarizing waves, and that's how the sound waves generated, but

884
00:49:47,120 --> 00:49:49,640
Speaker 2: the radio waves are generated. So this is interesting though

885
00:49:49,719 --> 00:49:53,120
Speaker 2: that they're trying to put a lot of pressure on

886
00:49:53,200 --> 00:49:55,680
Speaker 2: car makers to have the AM rang so that if

887
00:49:55,680 --> 00:50:00,879
Speaker 2: there's a national disaster or an emergency, they broadcast using AM.

888
00:50:01,239 --> 00:50:04,359
Speaker 2: So for example, here in Australia, if there's bushfires, if

889
00:50:04,360 --> 00:50:07,360
Speaker 2: you're tuning into an FM signal, you don't have the

890
00:50:07,520 --> 00:50:09,759
Speaker 2: range that you will on an AM signal. And it

891
00:50:09,800 --> 00:50:11,319
Speaker 2: makes a lot of sense when you start to think

892
00:50:11,320 --> 00:50:14,840
Speaker 2: about it in those terms, because we recently this week,

893
00:50:15,160 --> 00:50:19,280
Speaker 2: we had no cell phone coverage, We had no mobile phones,

894
00:50:19,600 --> 00:50:21,960
Speaker 2: so the second I stepped out of my house, my

895
00:50:22,080 --> 00:50:25,200
Speaker 2: phone was useless. I couldn't get Internet and I couldn't

896
00:50:25,239 --> 00:50:27,600
Speaker 2: make or receive phone calls. So the only way you

897
00:50:27,600 --> 00:50:29,400
Speaker 2: could make and receive calls was if you were in

898
00:50:29,440 --> 00:50:31,640
Speaker 2: a Wi Fi hotspot, So that.

899
00:50:31,719 --> 00:50:33,520
Speaker 4: Was a real challenge for a lot of people in town.

900
00:50:33,560 --> 00:50:35,960
Speaker 2: They were doing upgrades that were getting rid of three

901
00:50:36,040 --> 00:50:38,719
Speaker 2: G going to the five G towers, but it meant

902
00:50:38,719 --> 00:50:42,080
Speaker 2: that anybody who was using the Telstra towers was effectively

903
00:50:42,120 --> 00:50:44,680
Speaker 2: without a device. So if there's a bushfire and you're

904
00:50:44,719 --> 00:50:47,360
Speaker 2: trying to tune in to find out the latest information,

905
00:50:47,440 --> 00:50:50,680
Speaker 2: you may not have phone coverage, you may not have data,

906
00:50:51,040 --> 00:50:53,680
Speaker 2: and which case AM may be the only way to

907
00:50:53,719 --> 00:50:56,160
Speaker 2: get a really distant signal and be able to get

908
00:50:56,160 --> 00:50:58,280
Speaker 2: an update on an emergency situation.

909
00:50:59,600 --> 00:51:02,399
Speaker 1: I love it, good AM station mate. I think they're

910
00:51:02,440 --> 00:51:04,879
Speaker 1: going the way of the Dodo. But I tune into

911
00:51:05,080 --> 00:51:09,880
Speaker 1: SCN in the mornings, Melbourne's home of Sport and Garry

912
00:51:09,920 --> 00:51:13,320
Speaker 1: and timbang on. Yeah that's interesting. Hey, can I share

913
00:51:13,360 --> 00:51:15,319
Speaker 1: some tech with you that you might not know?

914
00:51:15,880 --> 00:51:16,680
Speaker 4: You might know it?

915
00:51:17,280 --> 00:51:21,480
Speaker 1: Yeah, right, So this is hot off the presses. Elon

916
00:51:21,640 --> 00:51:28,440
Speaker 1: Musk's neural link device blind Site gets FDA approval FDA

917
00:51:28,560 --> 00:51:33,319
Speaker 1: Breakthrough Device designation. Blind Site is an experiment mental implant

918
00:51:33,400 --> 00:51:36,879
Speaker 1: aimed at restoring vision in people who have lost sight

919
00:51:37,080 --> 00:51:42,240
Speaker 1: in both eyes, even for people who are born blind.

920
00:51:42,800 --> 00:51:46,319
Speaker 1: Elon Musk's Brain computer interface implant startup neural Link as

921
00:51:46,400 --> 00:51:50,480
Speaker 1: received FDA Breakthrough Approval designation for blind Site and implant

922
00:51:51,000 --> 00:51:57,319
Speaker 1: that restores vision. So it implants a micro electrode array

923
00:51:57,400 --> 00:52:02,000
Speaker 1: into the visual cortex of a person's brain, then activates neurons,

924
00:52:02,040 --> 00:52:05,160
Speaker 1: which provides the individuals with an image. I read about

925
00:52:05,160 --> 00:52:09,160
Speaker 1: it yesterday and said, at like, right now, it's giving

926
00:52:09,200 --> 00:52:13,200
Speaker 1: people like a grainy view of the world, but eventually

927
00:52:13,440 --> 00:52:16,640
Speaker 1: it's going to be way better than twenty twenty human

928
00:52:16,719 --> 00:52:20,480
Speaker 1: vision and give you a capacity to see infrared as well.

929
00:52:22,800 --> 00:52:24,080
Speaker 4: Wows seeing in the dark.

930
00:52:24,760 --> 00:52:28,759
Speaker 2: A good friend of mine, he went progressively blind in

931
00:52:28,800 --> 00:52:32,080
Speaker 2: his late teenage years. He's a mad car fanatic and

932
00:52:32,120 --> 00:52:36,359
Speaker 2: he actually has a couple of collectible cars. He still

933
00:52:36,400 --> 00:52:38,760
Speaker 2: is a car enthusiast, so even though he's now blind

934
00:52:38,840 --> 00:52:43,399
Speaker 2: fully blind, he's very passionate about cars. And for him

935
00:52:43,440 --> 00:52:46,160
Speaker 2: to have suddenly lost the ability to drive in his

936
00:52:46,360 --> 00:52:48,719
Speaker 2: late teens, well early twenties, so he still drove a

937
00:52:48,719 --> 00:52:52,279
Speaker 2: little bit and then actually got progressively blind, this would

938
00:52:52,280 --> 00:52:55,560
Speaker 2: be amazing for him to be able to get out

939
00:52:55,600 --> 00:52:57,759
Speaker 2: on the road again or be able to appreciate his

940
00:52:57,840 --> 00:53:00,879
Speaker 2: collection of cars. I think for peace, people who are

941
00:53:01,320 --> 00:53:06,279
Speaker 2: vision impaired from birth, they see the world in such

942
00:53:06,320 --> 00:53:10,120
Speaker 2: a different way in terms of augmented senses that have

943
00:53:10,320 --> 00:53:13,520
Speaker 2: made up for their lack of vision. Whereas somebody has

944
00:53:13,680 --> 00:53:17,400
Speaker 2: lost vision because of older age or potentially because of

945
00:53:17,440 --> 00:53:20,280
Speaker 2: an accident. You can see there'd be massive, a massive

946
00:53:20,440 --> 00:53:23,000
Speaker 2: jump to try to do this. I wonder whether somebody

947
00:53:23,040 --> 00:53:25,200
Speaker 2: who's been vision impaired, and I've got some friends who

948
00:53:25,440 --> 00:53:29,160
Speaker 2: have been vision impaired from birth as well, and I'd

949
00:53:29,200 --> 00:53:31,040
Speaker 2: love to ask them whether or not they would want

950
00:53:31,080 --> 00:53:31,879
Speaker 2: to get sight.

951
00:53:32,200 --> 00:53:34,279
Speaker 4: It's a really interesting one, isn't it.

952
00:53:35,000 --> 00:53:37,480
Speaker 1: I never thought of that That is a great question.

953
00:53:38,000 --> 00:53:41,600
Speaker 1: That is because I just thought, oh, of course, but

954
00:53:41,719 --> 00:53:43,160
Speaker 1: then maybe.

955
00:53:42,920 --> 00:53:46,319
Speaker 4: Not that is bias because we can see one.

956
00:53:46,280 --> 00:53:50,560
Speaker 1: Hundred I saw this documentary on this guy. You know,

957
00:53:51,200 --> 00:53:56,280
Speaker 1: obviously black bat's a blind Patrick tell people, I'm sure

958
00:53:56,320 --> 00:54:00,280
Speaker 1: you know how they navigate the world. So nar, yeah,

959
00:54:00,320 --> 00:54:05,319
Speaker 1: echo location, sonar? Yeah yeah, yeah. So so this guy

960
00:54:05,560 --> 00:54:08,719
Speaker 1: taught this blind dude taught himself echo location.

961
00:54:09,360 --> 00:54:11,080
Speaker 4: Oh yeah, yeah.

962
00:54:11,120 --> 00:54:17,240
Speaker 1: So he may slight dish like these noises and depending

963
00:54:17,280 --> 00:54:20,600
Speaker 1: on how quickly it comes back to him, and he

964
00:54:21,600 --> 00:54:26,120
Speaker 1: could navigate the world with his own version of sonar

965
00:54:26,400 --> 00:54:30,160
Speaker 1: I guess or echo location that he developed, and he

966
00:54:30,160 --> 00:54:33,239
Speaker 1: would know when things were in front of him that

967
00:54:33,840 --> 00:54:36,640
Speaker 1: like nobody had told him. But yeah, because he developed

968
00:54:36,640 --> 00:54:40,560
Speaker 1: this unbelievable almost like extra sense.

969
00:54:40,920 --> 00:54:41,520
Speaker 4: That's amazing.

970
00:54:41,600 --> 00:54:43,960
Speaker 2: Can I just debunk one little statement you just made

971
00:54:44,680 --> 00:54:48,520
Speaker 2: sure that's not actually blind. They do have small eyes,

972
00:54:48,560 --> 00:54:51,760
Speaker 2: they have a little bit of vision. They're very sensitive vision,

973
00:54:51,960 --> 00:54:54,600
Speaker 2: but it's actually sensitive to being able to see at

974
00:54:54,719 --> 00:54:57,040
Speaker 2: night as well. But they're not I mean, the term

975
00:54:57,080 --> 00:54:59,240
Speaker 2: blind is a bat. I know we use a lot,

976
00:54:59,400 --> 00:55:02,080
Speaker 2: so they don't have very good site, but they're not

977
00:55:02,120 --> 00:55:02,840
Speaker 2: actually blind.

978
00:55:03,080 --> 00:55:07,400
Speaker 1: Sorry, Okay, all right, So the site the vision impaired.

979
00:55:07,520 --> 00:55:11,359
Speaker 2: Well not necessarily they're not. It's not sharp, colorful vision

980
00:55:11,440 --> 00:55:15,279
Speaker 2: or anything like that. So they don't see like you do.

981
00:55:15,640 --> 00:55:19,440
Speaker 1: I'm vision impaired if you look at my face.

982
00:55:20,040 --> 00:55:22,200
Speaker 4: But the echo location, they're much better at that.

983
00:55:22,239 --> 00:55:24,640
Speaker 2: So I guess when they're flying, particularly at night, if

984
00:55:24,640 --> 00:55:26,560
Speaker 2: they can use their echo location to see a rat

985
00:55:26,680 --> 00:55:27,440
Speaker 2: or a mouse.

986
00:55:27,280 --> 00:55:29,520
Speaker 4: Or something and be able to swoop down.

987
00:55:32,280 --> 00:55:36,640
Speaker 1: Hell do they do? They? I don't know, all right,

988
00:55:36,719 --> 00:55:39,280
Speaker 1: black bats are not blind, just vision impaired.

989
00:55:41,200 --> 00:55:42,520
Speaker 4: Well that's subjective.

990
00:55:43,000 --> 00:55:45,880
Speaker 2: Not at night at night that's going to outperform you

991
00:55:46,040 --> 00:55:47,200
Speaker 2: hands wings down?

992
00:55:47,960 --> 00:55:51,680
Speaker 1: But is that is that with eyes or echo location both?

993
00:55:54,200 --> 00:55:57,080
Speaker 1: All right, I'm gonna I'm going to do a deep

994
00:55:57,120 --> 00:56:00,879
Speaker 1: dive intoday. No not so, I don't have time next.

995
00:56:00,760 --> 00:56:03,399
Speaker 4: You know, give us some advice. I like the advice thing.

996
00:56:03,440 --> 00:56:04,960
Speaker 2: You know, we should ask people if they want me

997
00:56:05,000 --> 00:56:06,959
Speaker 2: to kind of look up stuff for them at any point.

998
00:56:07,040 --> 00:56:11,319
Speaker 4: Uh, happily have a chat. Hey, batteries in your laptops,

999
00:56:12,000 --> 00:56:15,960
Speaker 4: so the life of the battery in your laptop can

1000
00:56:16,080 --> 00:56:20,080
Speaker 4: be compromised if you plug it in continuously all the time,

1001
00:56:20,080 --> 00:56:22,359
Speaker 4: which is what I do. And I forget to unplug it.

1002
00:56:22,680 --> 00:56:25,279
Speaker 4: So one of the things that we've now found with

1003
00:56:25,520 --> 00:56:31,319
Speaker 4: improving the longevity of standard batteries is not to discharge

1004
00:56:31,320 --> 00:56:33,640
Speaker 4: them by one hundred percent and not to charge them

1005
00:56:33,640 --> 00:56:36,480
Speaker 4: to one hundred percent. And in fact, I believe Tesla's

1006
00:56:37,040 --> 00:56:39,560
Speaker 4: and a lot of electric car manufacturers, when you plug

1007
00:56:39,600 --> 00:56:42,440
Speaker 4: them into charge, they try.

1008
00:56:42,200 --> 00:56:44,640
Speaker 2: To charge to say about eighty five ninety percent. They

1009
00:56:44,640 --> 00:56:47,600
Speaker 2: don't ever go full to one hundred. So it's only

1010
00:56:47,600 --> 00:56:49,880
Speaker 2: occasionally that you would do the part of me that

1011
00:56:49,880 --> 00:56:51,760
Speaker 2: you would do that. And so just a bit of advice.

1012
00:56:51,840 --> 00:56:54,960
Speaker 2: So when you're looking at you know the way that

1013
00:56:55,080 --> 00:56:58,239
Speaker 2: you use battery power. I mean, for a lot of us,

1014
00:56:58,280 --> 00:56:59,799
Speaker 2: I guess we keep out. I mean I work off

1015
00:56:59,800 --> 00:57:03,400
Speaker 2: allaptop a lot. Sitting here right now, I'm off the laptop,

1016
00:57:03,400 --> 00:57:06,160
Speaker 2: but I have a desktop machine. But the longevity of

1017
00:57:06,200 --> 00:57:09,200
Speaker 2: the battery will be really be dictated by how we

1018
00:57:09,320 --> 00:57:11,600
Speaker 2: use it. So for good battery health. And this is

1019
00:57:11,600 --> 00:57:15,320
Speaker 2: not just laptops, it's smartphones, anything that uses a battery, scooters,

1020
00:57:15,360 --> 00:57:18,120
Speaker 2: you name it. But don't plug it in and leave

1021
00:57:18,160 --> 00:57:19,960
Speaker 2: it plugged in overnight. I know we do it with

1022
00:57:20,000 --> 00:57:23,600
Speaker 2: our phones all the time. Phone manufacturers are getting better

1023
00:57:23,800 --> 00:57:28,080
Speaker 2: at regulating battery charging so that they don't damage the battery,

1024
00:57:28,120 --> 00:57:29,960
Speaker 2: and they have some really good tech built into some

1025
00:57:30,000 --> 00:57:33,040
Speaker 2: of the newer phones. But yeah, so they're saying, you know,

1026
00:57:33,160 --> 00:57:35,680
Speaker 2: don't keep your laptop plugged in or tablet or whatever

1027
00:57:35,680 --> 00:57:37,320
Speaker 2: it happens to be. So I just thought i'd throw

1028
00:57:37,360 --> 00:57:40,000
Speaker 2: that one out there. If you want to try to impress.

1029
00:57:40,160 --> 00:57:42,560
Speaker 1: Are you saying I shouldn't plug my phone in overnight

1030
00:57:42,600 --> 00:57:44,120
Speaker 1: and leave it all night.

1031
00:57:44,160 --> 00:57:46,520
Speaker 2: Well that's what they say. Yeah, you shouldn't leave it

1032
00:57:46,560 --> 00:57:48,720
Speaker 2: on all night. You should charge it and then take

1033
00:57:48,720 --> 00:57:51,040
Speaker 2: it off charge. Don't leave it plugged in overnight, so

1034
00:57:51,240 --> 00:57:52,160
Speaker 2: before you go to bed.

1035
00:57:52,600 --> 00:57:55,360
Speaker 3: So Mom's got setting and it only and it only

1036
00:57:55,480 --> 00:57:58,520
Speaker 3: charges to eighty percent. So I leave it in overnight,

1037
00:57:58,560 --> 00:57:59,400
Speaker 3: but it only evers.

1038
00:57:59,680 --> 00:58:03,760
Speaker 4: Yes, yes, some of the smartest.

1039
00:58:02,520 --> 00:58:05,680
Speaker 5: Settings on your laptop. When I had my laptop.

1040
00:58:05,320 --> 00:58:08,280
Speaker 3: Setup, I had a guy set up and he was

1041
00:58:08,400 --> 00:58:09,920
Speaker 3: he did all that clever stuff.

1042
00:58:10,120 --> 00:58:13,560
Speaker 4: Yeah, so fully charging and fully discharging puts the battery

1043
00:58:13,640 --> 00:58:16,840
Speaker 4: under a lot more stress, and that's thought to shorten

1044
00:58:16,920 --> 00:58:20,040
Speaker 4: its live but we're not. We're talking about.

1045
00:58:20,000 --> 00:58:23,400
Speaker 2: A massive increase in the duration of the life of

1046
00:58:23,400 --> 00:58:26,160
Speaker 2: the battery. If you try to avoid doing that, so

1047
00:58:26,200 --> 00:58:28,680
Speaker 2: you will get a lot longer out of the battery

1048
00:58:28,680 --> 00:58:29,240
Speaker 2: if you do that.

1049
00:58:29,360 --> 00:58:29,760
Speaker 4: And listen.

1050
00:58:29,800 --> 00:58:31,360
Speaker 2: Once upon a time, remember we used to be able

1051
00:58:31,360 --> 00:58:33,280
Speaker 2: to change the batteries in our phones. We just swap

1052
00:58:33,360 --> 00:58:35,720
Speaker 2: them over, and then of course we don't do that now,

1053
00:58:35,760 --> 00:58:38,040
Speaker 2: so we need to be more mindful about how we

1054
00:58:38,080 --> 00:58:40,880
Speaker 2: do that and how we charge and discharge so that

1055
00:58:40,920 --> 00:58:43,000
Speaker 2: we're not, you know, not damaging the battery.

1056
00:58:43,120 --> 00:58:45,800
Speaker 4: So not one hundred percent, not zero percent. There you

1057
00:58:45,800 --> 00:58:47,000
Speaker 4: go somewhere in.

1058
00:58:46,920 --> 00:58:49,800
Speaker 1: Betaatrick, did you, Oh, you don't have an iPhone? You

1059
00:58:49,840 --> 00:58:51,120
Speaker 1: have a Samsung? Do you?

1060
00:58:51,280 --> 00:58:54,920
Speaker 4: I've got a pixel, Google Pixel. So I just.

1061
00:58:55,680 --> 00:58:59,760
Speaker 1: Updated because I'm I'm a dummy with tech obviously, but

1062
00:58:59,840 --> 00:59:03,400
Speaker 1: I updated. Is it iOS eighteen or seventeen, tifth the

1063
00:59:03,440 --> 00:59:07,440
Speaker 1: latest or you know eighteen? So I just updated to

1064
00:59:07,600 --> 00:59:13,280
Speaker 1: iOS eighteen on my iPhone fourteen. But what's interesting is

1065
00:59:13,400 --> 00:59:17,120
Speaker 1: I was having a look at I was having a

1066
00:59:17,160 --> 00:59:19,200
Speaker 1: listen to the start of a podcast the other day.

1067
00:59:19,200 --> 00:59:22,320
Speaker 1: I can't remember one of ours? Or are you project one?

1068
00:59:22,960 --> 00:59:26,439
Speaker 1: And now with a new update, you open it up

1069
00:59:26,960 --> 00:59:30,080
Speaker 1: and the text as you're talking, like right now, if

1070
00:59:30,080 --> 00:59:32,480
Speaker 1: somebody's listening to this on an iPhone and you've got

1071
00:59:32,480 --> 00:59:35,480
Speaker 1: the update. You can go in and it gives the

1072
00:59:35,520 --> 00:59:39,080
Speaker 1: whole text of the whole show in real time as

1073
00:59:39,120 --> 00:59:42,640
Speaker 1: you're talking. It scrolls up the screen with so no.

1074
00:59:42,760 --> 00:59:45,680
Speaker 4: Typeost I've had that. I've had that built into my

1075
00:59:45,800 --> 00:59:48,480
Speaker 4: phone for about five years. It's great that I haven't.

1076
00:59:48,960 --> 00:59:49,440
Speaker 1: You haven't.

1077
00:59:49,840 --> 00:59:51,120
Speaker 4: They probably had an event.

1078
00:59:52,040 --> 00:59:54,600
Speaker 1: It's not your job to bring me down every time

1079
00:59:54,800 --> 00:59:56,200
Speaker 1: I just mentioned something.

1080
00:59:56,240 --> 00:59:58,880
Speaker 2: Okay, let me give you some pro Apple stories then,

1081
00:59:58,920 --> 01:00:00,960
Speaker 2: because they did have a big look Lunch event recently.

1082
01:00:01,040 --> 01:00:02,880
Speaker 2: And I've got to say, there are two little things

1083
01:00:02,920 --> 01:00:05,240
Speaker 2: that did pique my interest in knowing that you're an

1084
01:00:05,280 --> 01:00:05,960
Speaker 2: Apple person.

1085
01:00:06,680 --> 01:00:09,400
Speaker 4: The new AirPods that are coming up are coming out.

1086
01:00:09,520 --> 01:00:11,480
Speaker 4: I actually have a hearing.

1087
01:00:11,200 --> 01:00:13,880
Speaker 2: Test built into them, so you can test your own

1088
01:00:13,920 --> 01:00:16,040
Speaker 2: hearing using the new Apple AirPods.

1089
01:00:16,040 --> 01:00:18,280
Speaker 4: I thought that was pretty good. And the other thing

1090
01:00:18,600 --> 01:00:21,240
Speaker 4: that is really good that you're probably going to need Crago.

1091
01:00:21,400 --> 01:00:27,640
Speaker 1: Is if that's about five, you could put.

1092
01:00:27,760 --> 01:00:31,320
Speaker 2: Your Apple Watch on and it will detect sleep apnear.

1093
01:00:32,160 --> 01:00:38,800
Speaker 1: So why would I have sleep AP Now? I'm fucking

1094
01:00:39,040 --> 01:00:42,520
Speaker 1: lean and healthy. What do you think because I'm old,

1095
01:00:42,960 --> 01:00:45,520
Speaker 1: I'm going to sound like a walrus when I sleep.

1096
01:00:46,080 --> 01:00:49,680
Speaker 3: People with diagnosed sleep APNE right now are like, yeah,

1097
01:00:50,040 --> 01:00:50,600
Speaker 3: not lean.

1098
01:00:52,840 --> 01:01:00,000
Speaker 4: Email what he puts the podcast on himself to sleep well?

1099
01:01:00,000 --> 01:01:03,120
Speaker 1: Well, a lot of people who are overweight have sleep

1100
01:01:03,120 --> 01:01:03,520
Speaker 1: ap there.

1101
01:01:03,800 --> 01:01:06,680
Speaker 4: That's Trotye who's overweight. Thank you. That is in there

1102
01:01:06,720 --> 01:01:07,400
Speaker 4: for all our listeners.

1103
01:01:07,400 --> 01:01:09,920
Speaker 1: Well, and also not everyone who's got sleep APNA is

1104
01:01:09,960 --> 01:01:13,640
Speaker 1: out of shape. Of course guys should have clarified that

1105
01:01:13,720 --> 01:01:16,640
Speaker 1: at the start. But why would you assume I wouldn't

1106
01:01:16,640 --> 01:01:20,440
Speaker 1: need it, but you are tears? Wouldn't like what's behind that?

1107
01:01:21,160 --> 01:01:25,240
Speaker 4: Look, he's very old. You are older than us though,

1108
01:01:25,320 --> 01:01:27,640
Speaker 4: and it does tend to come age, doesn't it.

1109
01:01:28,280 --> 01:01:32,000
Speaker 1: Now you're being agist. I can't talk about Parker now.

1110
01:01:32,400 --> 01:01:34,760
Speaker 1: It's like I feel like I'm getting gaged up on

1111
01:01:34,800 --> 01:01:35,440
Speaker 1: my own show.

1112
01:01:37,320 --> 01:01:42,800
Speaker 4: You gotta kind of are no, But I think, well,

1113
01:01:42,800 --> 01:01:44,760
Speaker 4: I was just doing a pro Apple story. This is

1114
01:01:44,880 --> 01:01:47,680
Speaker 4: me doing a pro Apple story. I thought you'd be interested.

1115
01:01:48,240 --> 01:01:50,480
Speaker 1: I'm not pro Apple though, I'm not anything. I just

1116
01:01:50,520 --> 01:01:54,400
Speaker 1: happen to have an iPhone. In fact, Melissa hates my laptop.

1117
01:01:54,480 --> 01:01:57,280
Speaker 1: I've got a what do you call non Apple? Like

1118
01:01:57,360 --> 01:02:01,000
Speaker 1: I've just got an old school piece. I've just got

1119
01:02:01,080 --> 01:02:05,800
Speaker 1: a laptop. Fucking that she thinks is a piece of shit.

1120
01:02:05,880 --> 01:02:09,400
Speaker 1: But I'm used to it, so I won't change it.

1121
01:02:09,440 --> 01:02:11,240
Speaker 1: Probably is a piece of shit. Give us one more

1122
01:02:11,280 --> 01:02:14,200
Speaker 1: to wind up, Just something, no pressure, just something.

1123
01:02:13,920 --> 01:02:17,320
Speaker 4: Amazing photovoltaic cells. How's that?

1124
01:02:18,400 --> 01:02:18,919
Speaker 1: Yeah? Good?

1125
01:02:19,160 --> 01:02:19,320
Speaker 3: Yeah?

1126
01:02:19,320 --> 01:02:22,240
Speaker 4: I thought you'd like carry on. No, this is really

1127
01:02:22,280 --> 01:02:24,160
Speaker 4: interesting because for those of us.

1128
01:02:24,480 --> 01:02:27,400
Speaker 2: I mean, I have an old When I subscribe to

1129
01:02:27,480 --> 01:02:30,560
Speaker 2: Time magazine about thirty years ago, I got a free

1130
01:02:30,640 --> 01:02:34,040
Speaker 2: calculator with a solar panel in it, and I've never

1131
01:02:34,080 --> 01:02:35,480
Speaker 2: had to charge that bugger.

1132
01:02:35,280 --> 01:02:36,600
Speaker 4: Up for thirty years.

1133
01:02:36,840 --> 01:02:39,280
Speaker 2: You sit it out anywhere inside, you don't have to

1134
01:02:39,280 --> 01:02:42,280
Speaker 2: be outside, just any ambient light, and that bugger works.

1135
01:02:42,480 --> 01:02:44,959
Speaker 2: And I've always thought to myself, why the hell don't

1136
01:02:44,960 --> 01:02:48,400
Speaker 2: we have other stuff that we can use indoors. Well, finally,

1137
01:02:48,760 --> 01:02:51,720
Speaker 2: a new tech startup in Wogga Wogger is going to

1138
01:02:51,760 --> 01:02:54,240
Speaker 2: be the first Australian company to produce a new type

1139
01:02:54,280 --> 01:02:56,960
Speaker 2: of solar cell and they're saying it'll be able to

1140
01:02:57,040 --> 01:03:00,960
Speaker 2: generate enough electricity just indoors and eventually get rid of

1141
01:03:01,000 --> 01:03:04,560
Speaker 2: disposable batteries so you remote control anything that you use

1142
01:03:04,640 --> 01:03:08,080
Speaker 2: indoors Potentially could be run off. This new photo voltaic

1143
01:03:08,160 --> 01:03:09,960
Speaker 2: cell that is.

1144
01:03:10,080 --> 01:03:13,600
Speaker 1: That is actually a really good story because that I'd

1145
01:03:13,640 --> 01:03:17,000
Speaker 1: never thought of that. But those little kind of solar

1146
01:03:17,120 --> 01:03:21,560
Speaker 1: powered calculators. I used to have one and they were

1147
01:03:21,920 --> 01:03:24,680
Speaker 1: they are great, So yeah, why can't they do that

1148
01:03:24,760 --> 01:03:27,040
Speaker 1: with all the you know the stuff that we use

1149
01:03:27,080 --> 01:03:27,600
Speaker 1: in the house.

1150
01:03:27,800 --> 01:03:31,240
Speaker 2: Well, things like keyboards need to be connected constantly, and

1151
01:03:31,720 --> 01:03:35,120
Speaker 2: bearing in mind, a calculator uses similar tif to your

1152
01:03:35,480 --> 01:03:38,200
Speaker 2: tablet uses it kind of an e ink. Liquid crystal

1153
01:03:38,200 --> 01:03:41,600
Speaker 2: displays don't take much power to power to have them

1154
01:03:41,600 --> 01:03:43,680
Speaker 2: come up. But you know, these days, a lot of

1155
01:03:43,680 --> 01:03:46,240
Speaker 2: the technology we use just takes more power. It's not

1156
01:03:47,080 --> 01:03:50,280
Speaker 2: it needs something a bit more robust than a standard

1157
01:03:50,280 --> 01:03:53,280
Speaker 2: Betric battery. But I think it's kind of really cool.

1158
01:03:53,320 --> 01:03:56,440
Speaker 2: It's called Hallo cell, and they reckon they're going to

1159
01:03:56,440 --> 01:04:01,720
Speaker 2: start producing seven centimeter long photovoltaic to generate enough power

1160
01:04:01,720 --> 01:04:05,280
Speaker 2: to replace a pair of disposable batteries in a TV remote,

1161
01:04:05,400 --> 01:04:08,240
Speaker 2: or so the charging cable for a set of headphones.

1162
01:04:09,360 --> 01:04:11,919
Speaker 1: You could build a wind farm in your backyard, mate,

1163
01:04:12,000 --> 01:04:12,840
Speaker 1: you've got enough.

1164
01:04:12,680 --> 01:04:15,240
Speaker 4: Space, well not even the backyard, I just have it indoors.

1165
01:04:15,280 --> 01:04:16,280
Speaker 4: I've got a pretty big house.

1166
01:04:17,400 --> 01:04:19,400
Speaker 1: And you produce a lot of wind, so you should

1167
01:04:19,400 --> 01:04:24,479
Speaker 1: be able to run the whole fucking house. Patrick. Where

1168
01:04:24,480 --> 01:04:26,240
Speaker 1: can people connect with you? My friend?

1169
01:04:26,440 --> 01:04:28,240
Speaker 4: No one's going to want to connect with me after

1170
01:04:28,280 --> 01:04:28,720
Speaker 4: this show.

1171
01:04:28,960 --> 01:04:31,520
Speaker 1: Here they are, Yeah, they are. We love you even

1172
01:04:31,560 --> 01:04:34,760
Speaker 1: though you threw me under the bus and I apparently

1173
01:04:34,800 --> 01:04:39,360
Speaker 1: throw you under the bus a lot so.

1174
01:04:37,880 --> 01:04:40,800
Speaker 2: It didn't just run over you reversed about four time.

1175
01:04:42,600 --> 01:04:45,840
Speaker 2: You know, it's just go to websites noow dot com

1176
01:04:45,840 --> 01:04:48,040
Speaker 2: TODAYU is probably the easiest way.

1177
01:04:47,840 --> 01:04:50,000
Speaker 4: To find me. So websites now to com today you.

1178
01:04:50,120 --> 01:04:52,320
Speaker 2: But if you want to send a message and get

1179
01:04:52,400 --> 01:04:55,560
Speaker 2: us to talk about something on the next show, I'd

1180
01:04:55,640 --> 01:04:58,520
Speaker 2: love to hear from people if there's something in particular,

1181
01:04:58,640 --> 01:05:01,720
Speaker 2: if you've condoling, if you need to send some messages

1182
01:05:01,720 --> 01:05:02,240
Speaker 2: of support.

1183
01:05:02,400 --> 01:05:07,160
Speaker 1: Because it's no probably are going to go fuck Craig.

1184
01:05:07,240 --> 01:05:09,720
Speaker 1: He doesn't need it, and you're right, I don't. Well,

1185
01:05:09,760 --> 01:05:11,600
Speaker 1: I think that's a good idea. Why don't we do

1186
01:05:11,640 --> 01:05:17,640
Speaker 1: the entire next show off listener requests so they can

1187
01:05:17,680 --> 01:05:21,240
Speaker 1: do two places. One is email, you say your email again.

1188
01:05:21,120 --> 01:05:23,400
Speaker 2: I'll just go to websites now, dot com, tod au.

1189
01:05:23,480 --> 01:05:25,240
Speaker 2: You can fill out the form there and send something

1190
01:05:25,240 --> 01:05:27,080
Speaker 2: through to me, it'll come straight directly through to me,

1191
01:05:27,920 --> 01:05:28,680
Speaker 2: or you.

1192
01:05:28,600 --> 01:05:32,920
Speaker 1: Can go tother you project Facebook page, you project podcast

1193
01:05:33,000 --> 01:05:37,480
Speaker 1: Facebook page. Say this is for Patrick, and leave you

1194
01:05:37,520 --> 01:05:40,960
Speaker 1: a question or your idea for a bit of research

1195
01:05:41,160 --> 01:05:45,400
Speaker 1: or an exploration of a topic, and next time will

1196
01:05:45,400 --> 01:05:50,800
Speaker 1: be a completely listener generated and directed discussion.

1197
01:05:51,440 --> 01:05:52,800
Speaker 4: It seems like a lot of work for me.

1198
01:05:54,800 --> 01:05:56,440
Speaker 1: It sounds like a lot of work for one of

1199
01:05:56,480 --> 01:06:00,000
Speaker 1: your underlings. You said, by the way, it was your

1200
01:06:00,160 --> 01:06:02,320
Speaker 1: suggestion fucking thirty seconds ago.

1201
01:06:04,440 --> 01:06:07,000
Speaker 4: I think, all I'm just now nervous.

1202
01:06:08,000 --> 01:06:10,479
Speaker 1: You make a suggestion and then you go, oh my god,

1203
01:06:10,560 --> 01:06:12,640
Speaker 1: that's a lot of work for me. We don't fucking

1204
01:06:12,760 --> 01:06:13,160
Speaker 1: raise it.

1205
01:06:13,560 --> 01:06:15,720
Speaker 2: What happens if we do a whole one hour show

1206
01:06:15,880 --> 01:06:18,360
Speaker 2: on one topic, Well we won't.

1207
01:06:18,440 --> 01:06:20,000
Speaker 4: That little asked it out.

1208
01:06:20,760 --> 01:06:23,480
Speaker 1: Well, we need to put in some rules. I was

1209
01:06:23,520 --> 01:06:26,240
Speaker 1: talking to Tiff last night, right, I fucked up earlier

1210
01:06:26,280 --> 01:06:28,960
Speaker 1: this week. I know we're finished, but I'm running a

1211
01:06:29,000 --> 01:06:31,440
Speaker 1: mentoring group and I kind of I've got about seventeen

1212
01:06:31,480 --> 01:06:33,520
Speaker 1: people in the group, and I kind of forgot we're

1213
01:06:33,600 --> 01:06:36,040
Speaker 1: running through and I've forgot to say at the start,

1214
01:06:36,400 --> 01:06:38,200
Speaker 1: just keep it to two or three minutes. Each of

1215
01:06:38,200 --> 01:06:41,080
Speaker 1: you and I thought we'd get through the whole group.

1216
01:06:41,120 --> 01:06:43,240
Speaker 1: Bit of a debrief on the week. It was my fault.

1217
01:06:43,280 --> 01:06:45,480
Speaker 1: I didn't make it clear, so nobody's at fault. But

1218
01:06:46,080 --> 01:06:48,320
Speaker 1: let's just say that we got through about seven people

1219
01:06:48,360 --> 01:06:50,000
Speaker 1: in an hour, and I thought we'd get through the

1220
01:06:50,040 --> 01:06:53,240
Speaker 1: whole group in about forty minutes. So I think with

1221
01:06:53,360 --> 01:06:56,560
Speaker 1: the topics for yours, will dedicate you know, kind of

1222
01:06:56,560 --> 01:06:58,960
Speaker 1: three or four minutes to each topic or question, then

1223
01:06:59,000 --> 01:07:00,680
Speaker 1: we'll be able to get through twenty or so.

1224
01:07:01,080 --> 01:07:02,680
Speaker 4: Okay, that sounds really good. I'm in for that.

1225
01:07:03,160 --> 01:07:06,120
Speaker 2: Go for it websites now dot com, dot au or

1226
01:07:06,400 --> 01:07:08,640
Speaker 2: the new project Facebook page.

1227
01:07:09,600 --> 01:07:12,680
Speaker 1: Tiff. Good luck, you don't need luck, but have fun

1228
01:07:12,720 --> 01:07:16,400
Speaker 1: on the have fun on the sojourn, enjoy your time

1229
01:07:17,040 --> 01:07:21,000
Speaker 1: in India. Thanks huh, and good luck trying to find

1230
01:07:21,000 --> 01:07:23,640
Speaker 1: a coffee and drugs for when you're puoing through the

1231
01:07:23,680 --> 01:07:28,000
Speaker 1: I of a needle. And stay hydrated, but care for

1232
01:07:28,120 --> 01:07:28,720
Speaker 1: what you drink.

1233
01:07:28,920 --> 01:07:31,880
Speaker 5: Oh yeah, stay hydrated, but don't drink the water.

1234
01:07:36,240 --> 01:07:39,760
Speaker 1: Yeah, good luck with that, We'll say goodbye, fair but Patrick,

1235
01:07:39,800 --> 01:07:44,000
Speaker 1: thank you, TIF, thank you listeners, thank you