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Speaker 1: Gay Gruver's Tiffanyanne Kirkpatrick Jones, Bonelo, Craig, Anthony Harper, just

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Speaker 1: rocking up for our fortnight they get together. It really

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Speaker 1: isn't about you. I don't want to disappoint you. We

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Speaker 1: just get together for us, so fuck ya. But look,

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Speaker 1: if you want to join in, no that's not true.

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Speaker 1: It's for you too. But it is a little bit

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Speaker 1: self indulgent this fortnight they get together, but we do

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Speaker 1: it anyway. Hi, Patrick, you know, it just occurred to me.

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Speaker 2: I don't think we've done a shout out for like

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Speaker 2: two years to ask people if there is anything in

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Speaker 2: particular technology wise they would like us to talk about.

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Speaker 2: Maybe you're looking for a new phone and you're just

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Speaker 2: trying to decide whether to go Apple or Android, or

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Speaker 2: maybe I don't know, you know, you want to get

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Speaker 2: a better way of cleaning your teeth.

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Speaker 1: Well, speaking of phones, we'll go to Tiffany An Cook

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Speaker 1: at a moment. But last night on the news they

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Speaker 1: had some bloke on the news who was at the

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Speaker 1: I don't know, some convention you'd know in Las Vegas

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Speaker 1: or wherever, like the groundbreaking Tech for the next next

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Speaker 1: year and the notorious foldable Samsung phone that they've fucked

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Speaker 1: up and ran Bennett thirty five times. They've got a

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Speaker 1: new one, and they reckon, it's amazing because it's the

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Speaker 1: size of a phone. But then it folds out. I

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Speaker 1: don't know why I held up my phone like you

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Speaker 1: two don't know how big a phone is.

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Speaker 3: Sorry, Greg, see if you can fold them in half.

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Speaker 1: I'll fold you in half. Packn oragami boys.

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Speaker 2: I think it's the yeah, consumer electronic show that's seldom

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Speaker 2: less last but thank.

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Speaker 1: You, thank you, And then but they reckon it's great.

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Speaker 1: But also they had another thing, a ring that goes

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Speaker 1: on the finger like the one that Tiff has or

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Speaker 1: I don't know if both of you have. But the

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Speaker 1: new Samsung one that they reckon is amazing and puts

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Speaker 1: all your data into your phone. So I better get

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Speaker 1: one of those or not?

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Speaker 4: Is it a real good at tech?

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Speaker 1: Shut up? I figured out my earphones. Are you proud

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Speaker 1: of me? Look at me?

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Speaker 4: Yeah, I'm so proud of you.

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Speaker 5: You know, you can tuck them around the back of

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Speaker 5: your head so it ain't seen it really, You've got

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Speaker 5: massive lats so they might not reach them in my phone.

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Speaker 1: Shut up, Shut up? Tis been yelling at me. Everyone

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Speaker 1: tiss been yelling at me for two years at least

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Speaker 1: to wear headphones. So I've compromised and I've got these

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Speaker 1: little fucking I was going to say something that really

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Speaker 1: would have got me in trouble. These little weird looking

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Speaker 1: things that just hang on my ears. What do you

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Speaker 1: call these tips?

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Speaker 4: Just earbuds? Stick in your ears? Earbuds?

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Speaker 1: How long did it take you to learn how to

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Speaker 1: put them on? A bit? And then then TIV was

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Speaker 1: teaching me how to buy things online last night at

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Speaker 1: the gym. I asked her and she was laughing at

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Speaker 1: how handicapped I am in that space.

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Speaker 5: Patrick, he doesn't know how to buy something online just

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Speaker 5: on Amazon where there's a big button that says buy now.

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Speaker 1: I've never bought anything. I get a bit scared. A

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Speaker 1: quick quiz again?

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Speaker 2: Sure tell me what forward collision avoidance assist is on

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Speaker 2: a car.

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Speaker 1: I assume you're talking not in Southland, when you're in

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Speaker 1: the queue to pay for your stuff. Yep, that would

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Speaker 1: be yes, so that you don't crash into something in

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Speaker 1: front of you.

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Speaker 3: What about what about lane keep assist?

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Speaker 1: Yep, got that on my car as well. You monitor

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Speaker 1: blind spot view monitors. These are all things you're reading

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Speaker 1: off my car, are they? Yeah? Yeah, you've got these.

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Speaker 1: Does it tell you that it can park itself in?

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Speaker 1: That I can get out in the driveway and it

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Speaker 1: puts itself in the garage.

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Speaker 2: You'd have really tight fit there, so maybe it would

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Speaker 2: be helpful exactly.

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Speaker 1: Tiff, good morning, How are you?

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Speaker 6: Good morning?

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Speaker 1: Good thanks, terrific. Welcome to Friday seven thirty five and

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Speaker 1: thriving metropolis. What's the temperature in baland Patrick as we speak?

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Speaker 2: Well, I stoked up the fireplace before I jumped in.

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Speaker 2: Now it's the four point five degrees.

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Speaker 1: It's warm.

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Speaker 4: Jumped in the fireplace to be.

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Speaker 1: Stoked it up. Be stoked it up? All right, let's

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Speaker 1: jump into it. So, this, of course is tech central.

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Speaker 1: I try to stay out of the way. Really, it's

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Speaker 1: the Tiff and Patrick show. I'm just did to ask

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Speaker 1: dumb shit that some of you, not all of you,

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Speaker 1: because some of you are brilliant, but some of you

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Speaker 1: are dumb fucks like me when it comes to technology.

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Speaker 1: You know it, I know it. So I'm here to

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Speaker 1: ask the questions on behalf of the dummies. Patrick, where

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Speaker 1: do you want to start? My friend?

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Speaker 2: Four point five billion year old Lego, Well not quite

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Speaker 2: four point five billion year old Lego, but Lego that

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Speaker 2: has been made from a four point five billion.

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Speaker 1: Year old media rite has been put together.

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Speaker 2: In conjunction with Lego and the European Space Agency.

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Speaker 3: I know I shouldn't find that super exciting, but I

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Speaker 3: do to, so.

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Speaker 1: Tiff and I are shocked that you find that exciting. Okay.

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Speaker 2: So the reason is so this media rite was found

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Speaker 2: in Northwest Africa in the year two thousand and so

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Speaker 2: Lego has worked with the A Space Agency to try.

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Speaker 1: To build a Lego block because.

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Speaker 2: They believe that a lot of the materials that make

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Speaker 2: up the Lego block or this metia righte, actually are

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Speaker 2: familiar with materials on the Moon, and they reckon if

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Speaker 2: you're going to build a base on the Moon, you

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Speaker 2: want to be able to build it on the Moon

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Speaker 2: from materials that are there from the moon dust. So

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Speaker 2: this was a really interesting experiment and it makes sense

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Speaker 2: do it with Lego.

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Speaker 3: You can build everything out of Lego.

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Speaker 5: Hmm.

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Speaker 1: Cool, You're not excited at all, are you? No? I

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Speaker 1: just think building shit on the moon's a stupid idea.

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Speaker 1: The atmosphere can't support life. You can't grow shit there.

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Speaker 1: Let's do a cost benefit analysis on making the Earth

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Speaker 1: better versus trying to fucking you know, habitat is that

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Speaker 1: the word the moon? Like, let's just spend all those

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Speaker 1: trillions on the Earth that we currently live in, and

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Speaker 1: fuck all your plans for living on the moon.

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Speaker 2: But the thing is, so much research went into the

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Speaker 2: first Moon landings and it pushed technology so far forward,

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Speaker 2: and space research does so much to help us here

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Speaker 2: as well.

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Speaker 1: There are molecules that.

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Speaker 2: You can put together now in the International Space Station

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Speaker 2: that you can't put together on Earth because it's zero gravity.

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Speaker 3: So look, I know what you're saying, and it's a bit.

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Speaker 2: Of a long you know, you're drawing back a long pon,

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Speaker 2: But I think he needs to play the long game

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Speaker 2: and it does help in the long term.

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Speaker 1: Here's what I'm saying. Two billion people who live on

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Speaker 1: less than three dollars a day don't give a fuck

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Speaker 1: about this. They just want clean drinking water, they want safety,

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Speaker 1: they want clothes and warmth. So fuck your moon plans.

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Speaker 1: Let's get all the people on Earth looked after first.

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Speaker 3: I wish I had my AI lie detector.

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Speaker 2: Now I don't know if you be genuinely believing the

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Speaker 2: shit that's coming out of him.

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Speaker 1: And no, I'm kidding. No, two billion people or more

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Speaker 1: probably two million people, two billion people live in poverty.

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Speaker 1: I'm pretty sure. Not worried about what's fucking happening with

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Speaker 1: the space station.

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Speaker 2: I know inequality is just staggering, But I don't have

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Speaker 2: gold tips to taps either.

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Speaker 1: Relative to a lot of people you do. But it

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Speaker 1: is it interesting thing. Were you a lego kid or not?

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Speaker 1: You would have been more Yeah, if you were, you

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Speaker 1: ever ever a lego kid?

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Speaker 4: A little bit more a Tonka truck kid?

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Speaker 1: You know? Were you really like we fuck around a bit?

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Speaker 1: Were you really a tomboy? I'm probably going to get

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Speaker 1: in trouble when I say I can't see you ever

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Speaker 1: having played with dolls? Send the emails.

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Speaker 4: Do you have dolls? I remember a Barbie, right, I

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Speaker 4: don't know if it had a head.

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Speaker 1: I had a Steve Austin doll. Fucking If anyone had

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Speaker 1: dolls on this little trio, it was you. You probably

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Speaker 1: had all the dolls.

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Speaker 5: Wait.

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Speaker 2: I had a bionic Man doll, Steve, do you remember that?

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Speaker 2: And had a button you could push in the back

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Speaker 2: and it had a bionic arm.

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Speaker 1: Yeah, we used to. We used to flick rulers at

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Speaker 1: school off the edge of the desk, so it sounded

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Speaker 1: like him running. Do you remember that? Yeah? Yeah, And

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Speaker 1: our local milk bar had accessories. I could buy a super.

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Speaker 2: Kid at an inflatable raft and everything.

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Speaker 1: Well, I'm sure they're doing the equivalent of that now.

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Speaker 2: Yeah, that says a lot about me, So tiff Sorry,

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Speaker 2: I interrupted you. I just got excited talking about dolls.

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Speaker 1: Did you have dolls? You did?

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Speaker 4: You said I had some dolls I had did have

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Speaker 4: Tonka trucks too?

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Speaker 1: And what that?

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Speaker 4: Match box cars?

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Speaker 5: To throw them at my brothers, to piff them at

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Speaker 5: my brother and get in trouble because they're hard. That's

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Speaker 5: not getting shot if you throw all the match box

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Speaker 5: car e someone Wow.

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Speaker 1: So who would have thought young Tiffany and cooking Lon

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Speaker 1: Seston throwing hard objects at.

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Speaker 4: Her brother beach?

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Speaker 1: No lame. Sorry, sorry Turner's Beach folk, both of you

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Speaker 1: shout out to all our listener in Turner's Beach. It's

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Speaker 1: all gone. Yeah. You tell us about lie detectors.

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Speaker 2: Well, you know it's lie detecting is quite an art

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Speaker 2: and it's hard to do. It's really hard to catch

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Speaker 2: people out in a lie. We think we might be

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Speaker 2: good at it, we might be good at lying, or

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Speaker 2: we might be good at reading a lie, but the

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Speaker 2: reality is that we don't and even polygraph tests are

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Speaker 2: pretty well crap. So now there's some researchers and a

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Speaker 2: Leisha vonn Schleck and her colleagues have done a series

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Speaker 2: of research. They're from the University of Waltzburg in Germany,

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Speaker 2: and so they ran a number of experiments and they

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Speaker 2: got people to use this AI assistant to be able

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Speaker 2: to try to.

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Speaker 1: Work out whether people were lying or not.

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Speaker 2: So they got people and they incentivized people to talk

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Speaker 2: about their weekend, and then they incentivize them to lie,

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Speaker 2: and then they tried to catch them man in lies.

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Speaker 2: But what they found was the AI tool was more

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Speaker 2: effective than people at finding out whether people were lying

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Speaker 2: or not. Now do we want to know if people

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Speaker 2: are lying? But you think about how helpful it would be,

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Speaker 2: not just in legal cases and stuff like that, but

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Speaker 2: if you think about it fake news. You know, if

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Speaker 2: you were you know, I don't know, job applications, it

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Speaker 2: would be really interesting.

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Speaker 1: But people selling you stuff? What about when people are

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Speaker 1: selling your shit, the bullshit that comes out of their mouth.

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Speaker 1: That's like a bit true, kind of true, completely untrue.

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Speaker 1: People trying to impress people. Yeah, by the extended warranty,

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Speaker 1: all that sort of stuff. So exact, do you know

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Speaker 1: when they sold me my car, we'll come back. Sorry

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Speaker 1: it's not a great car or anything anyone, but just

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Speaker 1: pursuant to this point, they tried to sell me three

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Speaker 1: thousand dollars body protection. I'm like, what, so the paint's

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Speaker 1: no good? Oh no, the pain's great. I go, well,

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Speaker 1: why would I need to spend just in the car

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Speaker 1: that was for you? Ah? For me, I need that.

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Speaker 1: Then I should have got that. They do the body

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Speaker 1: paint protection thing.

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Speaker 2: They tried to do that with my cake cause I'd

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Speaker 2: never bought a new car until a couple of years ago.

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Speaker 2: It's like, what, yeah, exactly the pains. They also try

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Speaker 2: to do the upsell the on the interior. They said,

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Speaker 2: if you go to the next model, you're vinyl at

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Speaker 2: the material seat, we can upgrade that to leather.

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Speaker 3: And I said, I want a dead animal in my gar.

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Speaker 1: Yeah, chart animal flesh in my car. But I think

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Speaker 1: you know what's interesting about lying is that and this

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Speaker 1: sounds obvious and funny, but it is true allegedly, or

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Speaker 1: am I lying? It's almost impossible to research. It's impossible

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Speaker 1: to get virtually impossible to get really accurate data on

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Speaker 1: lying because nobody wants to be perceived as a liar.

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Speaker 1: So and it's all self kind of reporting research. You know,

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Speaker 1: how often do you lie? Well, of course people are

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Speaker 1: going to lie about how often they lie, because nobody

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Speaker 1: wants to say they're a liar. Yeah.

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Speaker 2: I guess the other thing too, though, is there are

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Speaker 2: different types of lies. You know, there's the oh yes,

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Speaker 2: there is a Santa clause, or no, you look fantastic.

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Speaker 1: You know what do you say? Well, yeah, there isn't.

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Speaker 1: There isn't. I mean, it's either something's true or it's untrue.

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Speaker 1: But I know what you're saying what we call colloquially

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Speaker 1: white lies. You know, it's like when someone says to you,

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Speaker 1: do you like what I'm wearing? And you think it's

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Speaker 1: fucking horrible? What do you do? You go, No, it's

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Speaker 1: fucking I love you, But that's dog shit. You know

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Speaker 1: what do you say?

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Speaker 4: What about what about positive affirmations?

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Speaker 5: Remember we've talked about those before, and if they're too

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Speaker 5: far removed from your beliefs.

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Speaker 4: They're actually they have the opposite effect.

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Speaker 5: I wonder if you could throw that on and see

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Speaker 5: where you really sit and how far you can push

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Speaker 5: push your beliefs before you hit.

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Speaker 1: Yeah, I wonder if that's I mean, I think everybody

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Speaker 1: lies because and it might. You know, it's like if

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Speaker 1: somebody like, if you're if you're in danger, tif, I

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Speaker 1: would expect you to lie, like I would expect if

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Speaker 1: not that you'd be in danger, becauld you'd punch anyone

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Speaker 1: in the head. Let's say, I'm home alone, right, I'm

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Speaker 1: in danger, you know, and it's in your interest for

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Speaker 1: someone to think that someone's coming to meet you even

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Speaker 1: though they're not, or that there's someone else in the house,

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Speaker 1: or you know, like there's a time when for your

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Speaker 1: own safety, lying is a good idea, you know, and

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Speaker 1: that it's a really slippery slope and a messy landscape.

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Speaker 1: But Patrick, do you remember a show on TV called

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Speaker 1: Lie to Me?

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Speaker 5: Oh?

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Speaker 2: Yeah, that was fantastic because I reckon you look like

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Speaker 2: the guy we've spoken about that before, the guy Tim Ruff.

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Speaker 1: Is it Tim Rough? Yeah? Yeah, yeah, you look like him, Tim. Oh,

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Speaker 1: thank you.

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Speaker 2: Look up Tim Ruff and then look at crago. I reckon,

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Speaker 2: they look so similar.

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Speaker 1: I reckon, I don't. But that was based on science

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Speaker 1: from a guy called Paul Eckman, and the character's name

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Speaker 1: was cal Lightman. And that science was all around and

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Speaker 1: you know, this around micro expressions and being able to

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Speaker 1: and they mapped all this computer stuff. They mapped like

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Speaker 1: thousands of micro expressions and it was meant it was

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Speaker 1: meant to be the you know, the brain. Through that

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Speaker 1: we could tell what anyone was feeling without whether or

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Speaker 1: not they are lying, ronest or sad or happy or

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Speaker 1: resentful or frustrated. And then and then some other people

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Speaker 1: brought out some research and went, yeah, that doesn't work

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Speaker 1: across cultures though, So it's yeah, it's a slippery space yestive. No,

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Speaker 1: he doesn't look like me, does he?

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Speaker 4: He does? He really does.

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Speaker 1: Yeah, what's his name again? Patrick? I'm going to look

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Speaker 1: him up now, right now, everyone's doing that. You two

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Speaker 1: keep talking. I'm looking them up. I say.

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Speaker 2: You know, the interesting thing, though, Tive, is when does

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Speaker 2: a lie? When does an exaggeration become a lie? Because

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Speaker 2: we exaggerate. So if you're going for a job interview,

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Speaker 2: you can talk about a position that you've held and

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Speaker 2: the type of skills that you you embellish a little bit.

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Speaker 5: I wonder if there'd be a difference in that between

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Speaker 5: men and women, because men often have no trouble embellishing

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Speaker 5: or stepping into jobs that they maybe not qualified for,

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Speaker 5: whereas women have such imposter syndrome that we kind of

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Speaker 5: do the opposite.

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Speaker 2: Yeah, that's yeah, that's a good point. And you know,

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Speaker 2: whether it's the fisherman going out there saying the fish

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Speaker 2: was this big, it's always a cute one, isn't it.

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Speaker 2: My twin brother is an angler and I've never understood

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Speaker 2: the interest. And I know that it's the most popular

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Speaker 2: sport in Australia.

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Speaker 1: Did you have fish? You know what?

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Speaker 5: I went fishing once when I had a little trip

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Speaker 5: around Tazzy and didn't catch a single thing. We went

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Speaker 5: fishing and went fishing at the Great Lakes with normal fishing, right.

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Speaker 5: I think you go off for a fly fishing there,

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Speaker 5: we're standing there with normal fishing right as well.

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Speaker 3: Fish is at I used.

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Speaker 2: To go fishing with my mates, not put a hook on,

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Speaker 2: just put sinker.

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Speaker 3: I just think it's so cruel the poor fish like

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Speaker 3: they get a hook.

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Speaker 1: And my brother would say to me. That's right.

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Speaker 3: We throw them back in yes, with major trauma.

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Speaker 1: To the inside of their mouths.

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Speaker 2: Sorry, sorry to all the anglers out there, because I've

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Speaker 2: probably just alienated sixty seven percent of our listenership.

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Speaker 1: Yeah I did. Yeah, you fish quite a bit and

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Speaker 1: I didn't throw them back. We just ate them. You know.

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Speaker 1: It's the cycle. It's nature, you know. I tell you what,

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Speaker 1: though I'm the closest I've ever got to becoming a vegan.

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Speaker 1: Tiff sent me this video, a reel of this lady

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Speaker 1: who's got a pet cow. Oh my god. Like I

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Speaker 1: grew up in the country around cows and for me

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Speaker 1: to think this cow was white and fluffy, it looked

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Speaker 1: like a gigantic dog. Tiff send it to Patrick. This

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Speaker 1: is terrible on a video, but the cutest fucking thing

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Speaker 1: I've ever seen. And I felt very guilty eating my

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Speaker 1: mince meat that night, I will tell you, but not

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Speaker 1: too guilty that I couldn't need it.

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Speaker 5: If people want to follow the page, it's Lacey Mlacey

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Speaker 5: m Evans, l A. C.

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Speaker 4: I E. M Evans and there's heaps of cow pictures. Patrick,

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Speaker 4: I'll send it to you.

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Speaker 1: I've already looked it up. That's okay, I can see them.

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Speaker 4: Good lad.

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Speaker 2: I love animals, So you're not gonna You've already got

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Speaker 2: a winner on me. Oh yeah, that's pretty cute. It's

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Speaker 2: a client of mine that has a thing called the

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Speaker 2: Valet's Black Nose Sheep that you would never eat lamb

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Speaker 2: again if you ever saw a Valet's Black Nose sheep.

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Speaker 1: They're so cute. I mean they're so cute. I would

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Speaker 1: you would not. By the way, there's got nothing to

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Speaker 1: do with tech. I'm thinking about getting the dog. Oh

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Speaker 1: get a snoutzer or with it? Nah, a proper dog? What?

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Speaker 1: Oh like an actual dog that's a Palet's Black Nose sheep.

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Speaker 1: And now tip so old it can you that's terrible

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Speaker 1: for bodka. It's cute, though, I'm very cute. Put it

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Speaker 1: up in the group. If you're not in our group,

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Speaker 1: do you project? You project you're going.

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Speaker 4: To miss out on the sheep?

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Speaker 1: You're going to miss.

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Speaker 4: Out on it.

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Speaker 1: So can you put up the video one the video

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Speaker 1: of the cow so people know, like for me to

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Speaker 1: think it's cute, it's fucking cute. I want that.

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Speaker 4: You talked about it every single day since.

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Speaker 1: Very cute. It's very cute. My face. Favorite bit is

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Speaker 1: when she goes and lies on it. She just lies

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Speaker 1: on the back of this cow and the cow doesn't

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Speaker 1: give a fuck. All right, Patrick, let's talk about tech

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Speaker 1: because we can. Oh.

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Speaker 2: Yeah, that's right, that's what we're here for, right, feel free? Hey,

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Speaker 2: well okay, AI, I know is something we talk about

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Speaker 2: a lot. We talked about the light detectors. A Scottish

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Speaker 2: artist is something done, something quite controversial, and this is

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Speaker 2: a fairly I didn't know the guy. His name is

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Speaker 2: is Michael Forbes, but his works. People who own his

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Speaker 2: works include Madonna, Terry Gillham from Monty Python, Ricky Gervais.

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Speaker 1: So he's well known in a lot of circles.

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Speaker 2: Now what he's done is he's taken some of his

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Speaker 2: most impressive work and covered them in black paint, half

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Speaker 2: of them in black paint. So he's destroyed his artwork. Wow,

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Speaker 2: a protest against AI as a protest about you know,

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Speaker 2: the fact that a lot of these AI models have

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Speaker 2: been used by scraping data of artists' works. And he

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Speaker 2: said in a lot of ways, you know, it's a reaction.

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Speaker 2: He's redacted his work. Four of his paintings have been damaged.

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Speaker 2: You know, he's put this black pain on top of them,

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Speaker 2: and he sees he's actually heartbroken.

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Speaker 1: He's deliberately done this. You know.

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Speaker 2: One of the paintings was John Lennon, and you know

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Speaker 2: it featured Taylor Swift, and he's just blacked it all out.

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Speaker 2: And so it's an interesting little protest. You know, you're

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Speaker 2: not agree, you don't agree with Craig.

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Speaker 1: Well, no, it's not agree or disagree. I'm wondering. I

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Speaker 1: think it's well in some ways, I'm like, it's very brave,

404
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Speaker 1: but I go, is it going to move the needle

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Speaker 1: on anything? Will it create any positive change? And if

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Speaker 1: he's just destroyed his own artwork and there's no positive

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Speaker 1: outcome from that, yeah, and he's depressed and sad. Now

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Speaker 1: I'm like, I don't know. I mean, there's no judgment

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Speaker 1: in there for me, there's just curiosity. I wonder if

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Speaker 1: that will help in any way, if that will change

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Speaker 1: anything for the better. I guess obviously we're talking about

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Speaker 1: it on the other side of the world, so it's

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Speaker 1: brought attention to it and maybe that's a good thing.

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Speaker 1: But I don't know. I think it's an indomitable force.

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Speaker 1: AI I don't think it's going anywhere. Bit.

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Speaker 2: The hardest thing with AI that I try to reconcile

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Speaker 2: myself with is how they've scraped data without people's permission,

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Speaker 2: because this is another bit of research that's been done,

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Speaker 2: and they're saying that one of the biggest ALI models

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Speaker 2: were actually.

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Speaker 1: Trained on a lot of Australian.

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Speaker 2: Kids' photos that were scraped from you know, websites, social media.

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Speaker 2: It might have been like the school swimming carnival and

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Speaker 2: they happen to.

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Speaker 1: Publish a few photos.

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Speaker 2: So this researcher was saying, this is an organization called

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Speaker 2: Human Rights Watch, and what they said is they were

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Speaker 2: really surprised that this data set had a whole lot

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Speaker 2: of information like newborn babies with the mother still there

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Speaker 2: holding the babe and the umbilical cords still connected. I mean,

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Speaker 2: it's kind of pre schoolers playing musical instruments, schools and swimsuits.

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Speaker 3: But for some reason, there seemed to be a higher

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Speaker 3: bias for Australian kids.

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Speaker 2: Now, whatever reason it was, maybe you know, Australians are

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Speaker 2: more likely to post this sort of stuff. I wouldn't

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Speaker 2: have thought so, but there is a real concern that

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Speaker 2: these images because they've now been scraped and added to

438
00:21:15,000 --> 00:21:15,879
Speaker 2: this data set.

439
00:21:16,280 --> 00:21:19,359
Speaker 1: If you want what does that mean? Okay, like most

440
00:21:19,359 --> 00:21:21,200
Speaker 1: of us don't know what scraped means.

441
00:21:21,480 --> 00:21:25,440
Speaker 2: So what it means is that these AI algorithms need

442
00:21:25,480 --> 00:21:27,920
Speaker 2: to learn and they need examples. So they want an

443
00:21:27,920 --> 00:21:31,480
Speaker 2: example of what a middle aged man wearing glasses wearing

444
00:21:31,480 --> 00:21:35,200
Speaker 2: a black hoodie looks like, as.

445
00:21:35,000 --> 00:21:37,200
Speaker 1: If there's any of them around exactly.

446
00:21:37,640 --> 00:21:40,960
Speaker 2: So they basically go through and what they were doing

447
00:21:41,080 --> 00:21:43,159
Speaker 2: was just searching and scraping all the data from the

448
00:21:43,160 --> 00:21:46,520
Speaker 2: Internet and using that to train the ALI model. The

449
00:21:46,600 --> 00:21:50,000
Speaker 2: problem is this was all kind of done. I think

450
00:21:50,000 --> 00:21:53,520
Speaker 2: it was altruistic initially. I don't think anybody meant it maliciously.

451
00:21:53,600 --> 00:21:56,440
Speaker 2: But what they've done, and whether it's inadvertent or whether

452
00:21:56,480 --> 00:22:01,520
Speaker 2: it's been deliberate, is they have pulled in lots of photographs,

453
00:22:01,560 --> 00:22:05,480
Speaker 2: including photographs of children, real people. And the concern is,

454
00:22:05,680 --> 00:22:09,639
Speaker 2: and this is about this artist, for example, a Scottish artist.

455
00:22:09,720 --> 00:22:12,679
Speaker 2: What he's saying is his style of painting. You know,

456
00:22:12,840 --> 00:22:16,600
Speaker 2: different styles of artwork might be very unique to a

457
00:22:16,640 --> 00:22:20,080
Speaker 2: particular artist. But if you say I want to create

458
00:22:20,240 --> 00:22:24,400
Speaker 2: a painting in the same style as Craig's dads and

459
00:22:24,440 --> 00:22:27,560
Speaker 2: then it will replicate that using AI. Now, that's the

460
00:22:27,880 --> 00:22:31,960
Speaker 2: concern is that real children's faces. And it was only

461
00:22:32,000 --> 00:22:34,879
Speaker 2: a few weeks ago that a school in back of

462
00:22:34,880 --> 00:22:38,040
Speaker 2: s Marsh, a grammar school in back of Smash, hit

463
00:22:38,080 --> 00:22:42,560
Speaker 2: the headlines because one of the students was taking photographs

464
00:22:42,600 --> 00:22:46,880
Speaker 2: of girls at the school and using AI to make

465
00:22:47,560 --> 00:22:49,919
Speaker 2: fake naked pictures.

466
00:22:50,200 --> 00:22:53,320
Speaker 3: And you know, this is what AI can be used for.

467
00:22:53,600 --> 00:22:56,600
Speaker 2: So the reality is that no one has given permission

468
00:22:56,640 --> 00:22:57,840
Speaker 2: for their data to be used.

469
00:22:58,400 --> 00:23:00,280
Speaker 3: It could be one of your books, it could be

470
00:23:00,359 --> 00:23:01,400
Speaker 3: something that Tif's.

471
00:23:01,080 --> 00:23:02,880
Speaker 2: Done, it could be something that I've written, it could

472
00:23:02,920 --> 00:23:05,479
Speaker 2: be a graphic design or logo that I've created.

473
00:23:05,480 --> 00:23:05,920
Speaker 1: And that's the.

474
00:23:05,880 --> 00:23:08,240
Speaker 2: Concern is that where does it start and finish in

475
00:23:08,320 --> 00:23:11,600
Speaker 2: terms of the you know, how much of your imagery

476
00:23:11,960 --> 00:23:14,560
Speaker 2: is belongs to you as the artist, as the person

477
00:23:14,560 --> 00:23:16,960
Speaker 2: who's produced it, or the person who's written it, or

478
00:23:16,960 --> 00:23:20,119
Speaker 2: the person who said it. Your voice that's unique to you.

479
00:23:20,119 --> 00:23:23,320
Speaker 2: You have every right to control what you say. And

480
00:23:23,440 --> 00:23:25,720
Speaker 2: it was only a few episodes ago that.

481
00:23:25,880 --> 00:23:29,680
Speaker 1: I as if anyone would use my voice without my permission?

482
00:23:29,880 --> 00:23:32,359
Speaker 6: Is that three episodes ago, Well, I hang on, I

483
00:23:32,480 --> 00:23:37,240
Speaker 6: hang on somebody, Oh somebody did on this bloody call. Yeah, look,

484
00:23:37,640 --> 00:23:42,320
Speaker 6: I don't know. I think I think you know, we're

485
00:23:42,320 --> 00:23:45,160
Speaker 6: going to go around in circles with this. There's no answer.

486
00:23:45,440 --> 00:23:48,720
Speaker 6: I mean, there's no there's no answer. There's no quick

487
00:23:48,840 --> 00:23:54,439
Speaker 6: answer anyway, there's no simple answer. And it's exponentially increasing,

488
00:23:54,720 --> 00:23:54,959
Speaker 6: you know.

489
00:23:55,040 --> 00:23:59,879
Speaker 1: It's it's a fucking tsunami of change that's happening in

490
00:24:00,119 --> 00:24:01,040
Speaker 1: the virtual space.

491
00:24:01,400 --> 00:24:03,720
Speaker 2: Can I give one positive app Let's let's finish off

492
00:24:03,720 --> 00:24:05,359
Speaker 2: on the AI with the positive AI.

493
00:24:05,440 --> 00:24:08,919
Speaker 1: Still. Can we can we shelve the AI after this? Yep? Okay,

494
00:24:09,000 --> 00:24:09,480
Speaker 1: no problem.

495
00:24:10,240 --> 00:24:12,720
Speaker 2: Now, well there's a new AI model that's that that

496
00:24:12,880 --> 00:24:15,880
Speaker 2: there that's being developed at the moment.

497
00:24:16,119 --> 00:24:18,800
Speaker 1: And you know how you can use text to create

498
00:24:18,840 --> 00:24:19,320
Speaker 1: an image.

499
00:24:19,359 --> 00:24:21,720
Speaker 2: Now you can use text or you'll soon be able

500
00:24:21,720 --> 00:24:23,360
Speaker 2: to use text to create.

501
00:24:23,080 --> 00:24:24,600
Speaker 1: A three D image.

502
00:24:24,800 --> 00:24:26,800
Speaker 2: So say, for example, I wanted to print a three

503
00:24:26,880 --> 00:24:30,120
Speaker 2: D model of my dog, I could sayerate a three

504
00:24:30,200 --> 00:24:33,399
Speaker 2: D Schnautzer wearing a bow tie and it will actually

505
00:24:33,440 --> 00:24:35,960
Speaker 2: create the three D mesh model that you can print

506
00:24:36,000 --> 00:24:37,119
Speaker 2: on your own three D printer.

507
00:24:38,760 --> 00:24:41,200
Speaker 1: Is that kind of cool? Wow? And two of our

508
00:24:41,280 --> 00:24:50,480
Speaker 1: listeners are like, that's amazing. Twenty thousand, like fuck next, Okay,

509
00:24:51,359 --> 00:24:51,760
Speaker 1: the AI.

510
00:24:51,880 --> 00:24:54,000
Speaker 3: We're not going to talk about AI ever again.

511
00:24:54,400 --> 00:24:58,159
Speaker 1: Fucking hey, everyone, I can three D print my schnauzer.

512
00:24:58,600 --> 00:25:01,280
Speaker 1: Fucking there's there's the gra of the century. Make that

513
00:25:01,359 --> 00:25:08,159
Speaker 1: into a real tip. Oh three three D print your schnauzer.

514
00:25:08,480 --> 00:25:13,040
Speaker 1: Know about that. I'm not sure what I meant by that.

515
00:25:13,480 --> 00:25:15,560
Speaker 1: We all know what you meant by that. Do you

516
00:25:15,600 --> 00:25:17,639
Speaker 1: know what? Something I saw on the news, which I

517
00:25:17,680 --> 00:25:21,480
Speaker 1: see is on your list, mate? Is what? And look?

518
00:25:21,600 --> 00:25:23,320
Speaker 1: Part of me thinks this is a great part of

519
00:25:23,359 --> 00:25:29,120
Speaker 1: me hates it. I'm conflicted. Speed limiters on cars are

520
00:25:29,200 --> 00:25:34,280
Speaker 1: now mandatory or becoming mandatory in Europe, and I've long

521
00:25:34,400 --> 00:25:39,280
Speaker 1: wondered Patrick about and Tiff and everyone about. You know,

522
00:25:39,359 --> 00:25:42,359
Speaker 1: It's like I have a motorbike that will do nearly

523
00:25:42,440 --> 00:25:45,359
Speaker 1: three hundred kilometers an hour in a country where the

524
00:25:45,440 --> 00:25:49,160
Speaker 1: fastest I can legally go is one hundred and ten.

525
00:25:49,840 --> 00:25:52,120
Speaker 1: Now I love the fact that you know I've got

526
00:25:52,119 --> 00:25:56,119
Speaker 1: this lead yet, but really it's like, even if it

527
00:25:56,160 --> 00:25:58,680
Speaker 1: went one hundred and forty, you go, well, that's enough, right.

528
00:25:59,600 --> 00:26:03,040
Speaker 1: It is interesting that we produce all of these cars

529
00:26:03,040 --> 00:26:08,119
Speaker 1: and motorbikes that are essentially unusable in most places in

530
00:26:08,160 --> 00:26:10,879
Speaker 1: the world, can I make one point sure?

531
00:26:11,000 --> 00:26:14,760
Speaker 2: And I live in a rural area, and there are

532
00:26:14,920 --> 00:26:18,800
Speaker 2: occasions if I am overtaking where I am going to

533
00:26:18,880 --> 00:26:21,240
Speaker 2: admit this that I have gone over the speed limit

534
00:26:21,320 --> 00:26:24,040
Speaker 2: to overtake a vehicle as safely as I feel I

535
00:26:24,040 --> 00:26:26,760
Speaker 2: could to be able to get past effectively if it's

536
00:26:26,760 --> 00:26:29,639
Speaker 2: a be double or it's a large to get to

537
00:26:29,680 --> 00:26:33,320
Speaker 2: get past them. So look, I've only ever had one

538
00:26:33,320 --> 00:26:35,760
Speaker 2: speeding ticket in my entire driving.

539
00:26:36,000 --> 00:26:38,960
Speaker 3: Yeah, I have won a week, you know what, And

540
00:26:39,000 --> 00:26:40,159
Speaker 3: you know what the irony was.

541
00:26:40,280 --> 00:26:42,960
Speaker 2: I was driving, I was late driving to a funeral

542
00:26:42,960 --> 00:26:44,720
Speaker 2: for a person who died in a car accident, and

543
00:26:44,720 --> 00:26:45,760
Speaker 2: I got done speeding.

544
00:26:46,200 --> 00:26:49,040
Speaker 1: Wow, that's that's I don't know if that's a message,

545
00:26:49,040 --> 00:26:51,920
Speaker 1: but but but yeah, I get that everyone's done that.

546
00:26:52,000 --> 00:26:55,960
Speaker 1: But I'm talking about you know, like the new Teslas

547
00:26:55,960 --> 00:26:58,280
Speaker 1: that do not to one hundred and one point nine

548
00:26:58,359 --> 00:27:03,280
Speaker 1: seconds that where building these like these higher and higher

549
00:27:03,320 --> 00:27:08,120
Speaker 1: performance vehicles, which personally I love. But that's emotion, right,

550
00:27:08,200 --> 00:27:10,480
Speaker 1: I love them. It's fucking I love all that shit.

551
00:27:10,920 --> 00:27:15,480
Speaker 1: But from a responsibility and a strategic and a logical perspective,

552
00:27:16,240 --> 00:27:19,080
Speaker 1: it makes no sense to have vehicles that do three

553
00:27:19,119 --> 00:27:21,760
Speaker 1: times the speed limit. So do we limit the speed?

554
00:27:21,840 --> 00:27:24,280
Speaker 2: Do we limit the ability for the car to accelerate

555
00:27:24,359 --> 00:27:26,680
Speaker 2: so quickly or to be able to go at three

556
00:27:26,800 --> 00:27:28,000
Speaker 2: hundred kilometers an hour?

557
00:27:28,440 --> 00:27:30,840
Speaker 1: Or we could all buy a twenty five year old Mazda.

558
00:27:31,000 --> 00:27:37,320
Speaker 1: You know, we could do that with a head gasket problem. Now, look,

559
00:27:37,400 --> 00:27:40,679
Speaker 1: I mean yeah, I mean at the same time, I

560
00:27:40,760 --> 00:27:42,879
Speaker 1: love them, but I think if we didn't have cars

561
00:27:42,880 --> 00:27:45,399
Speaker 1: that went in But also I think if we didn't

562
00:27:45,400 --> 00:27:48,640
Speaker 1: have cigarettes that were we no kill people. But anyone

563
00:27:48,680 --> 00:27:51,879
Speaker 1: can buy them anywhere. You know. It's like, this is

564
00:27:52,000 --> 00:27:53,879
Speaker 1: just our society, isn't it. We've got a whole lot

565
00:27:53,920 --> 00:27:57,240
Speaker 1: of stuff that's legal that can kill you. Albeit speeding

566
00:27:57,359 --> 00:27:59,359
Speaker 1: is not legal, but we give you a car that

567
00:27:59,440 --> 00:28:03,040
Speaker 1: gives you the capability of speeding in a million ways. Yeah,

568
00:28:03,080 --> 00:28:03,480
Speaker 1: for sure.

569
00:28:04,160 --> 00:28:07,960
Speaker 2: Interestingly, this this legislation that's going through in Europe actually

570
00:28:08,000 --> 00:28:10,560
Speaker 2: has kicked off already. It's just come into law. It's

571
00:28:10,600 --> 00:28:15,800
Speaker 2: called ISA Intelligent Speed Assistance. It's now mandatory, so any

572
00:28:15,840 --> 00:28:20,080
Speaker 2: new car that's now sold in the EU will either

573
00:28:20,160 --> 00:28:23,200
Speaker 2: warn drivers when they're driving over the speed limit or

574
00:28:23,240 --> 00:28:24,719
Speaker 2: actively prevent the vehicle.

575
00:28:24,840 --> 00:28:28,440
Speaker 1: So I like the warning idea. Mind does that? Yes,

576
00:28:28,840 --> 00:28:32,440
Speaker 1: mine literally has on my window. It'll have the speed

577
00:28:32,520 --> 00:28:36,120
Speaker 1: on the left, like sorry, the speed limit whatever area

578
00:28:36,119 --> 00:28:38,360
Speaker 1: you're in, on the literally the fucking windscreen.

579
00:28:38,440 --> 00:28:40,360
Speaker 3: Wait a minute, you mean a head's up display.

580
00:28:40,560 --> 00:28:44,120
Speaker 1: Yeah, that's what I mean. Well, that's why I've got you.

581
00:28:44,680 --> 00:28:47,080
Speaker 1: And then next to that will be the speed I'm going.

582
00:28:47,120 --> 00:28:49,000
Speaker 1: And if I'm in a hundred zone and I'm doing

583
00:28:49,000 --> 00:28:52,120
Speaker 1: one hundred and two, shit starts fucking making noise. I'm like,

584
00:28:52,160 --> 00:28:55,760
Speaker 1: this is annoying. I better slow down. Two k's tiff.

585
00:28:55,800 --> 00:28:58,040
Speaker 2: Didn't he take the piss out of me last episode

586
00:28:58,080 --> 00:29:01,120
Speaker 2: about using the word hud and now he's actively using

587
00:29:01,120 --> 00:29:01,920
Speaker 2: a heart every day?

588
00:29:02,680 --> 00:29:07,719
Speaker 1: What heads up display doesn't think? We don't have to

589
00:29:07,800 --> 00:29:12,560
Speaker 1: use your bloody tech, bloody acronyms. Why it's easy to

590
00:29:12,560 --> 00:29:17,000
Speaker 1: stay hard? Tell me about an EV that charges in

591
00:29:17,240 --> 00:29:21,600
Speaker 1: under five minutes. That seems unlikely, That seems impossible.

592
00:29:22,200 --> 00:29:25,680
Speaker 2: Well that this is This is the Niyebolt. I think

593
00:29:25,680 --> 00:29:30,080
Speaker 2: it's called the Niebolt EV. And yeah, they've I reckon

594
00:29:30,120 --> 00:29:32,640
Speaker 2: that they've been able to get it up and charged.

595
00:29:32,720 --> 00:29:33,640
Speaker 1: I think it's eighty.

596
00:29:33,440 --> 00:29:35,440
Speaker 3: Percent within five within five minutes.

597
00:29:36,200 --> 00:29:39,360
Speaker 2: That's pretty amazing, So from ten percent up to eighty percent.

598
00:29:39,760 --> 00:29:43,240
Speaker 2: And look, the problem we've got is standard lithium ion

599
00:29:43,360 --> 00:29:47,200
Speaker 2: batteries don't allow a charge.

600
00:29:47,840 --> 00:29:49,360
Speaker 1: It has to be charged at a certain rate.

601
00:29:49,440 --> 00:29:52,200
Speaker 2: You can't just force a whole lot of electricity into

602
00:29:52,240 --> 00:29:55,080
Speaker 2: it and it charges fast. So the way the batteries

603
00:29:55,120 --> 00:29:58,560
Speaker 2: built is one of the reasons that they're they're really

604
00:29:58,600 --> 00:29:59,800
Speaker 2: looking at how to speed up.

605
00:29:59,680 --> 00:30:00,800
Speaker 1: The charge process.

606
00:30:01,160 --> 00:30:04,520
Speaker 2: So that because the concern with lithium batteries, and of

607
00:30:04,520 --> 00:30:06,360
Speaker 2: course we've seen a lot of this recent times is

608
00:30:06,400 --> 00:30:09,600
Speaker 2: fires because they can catch fire, and this concerns about,

609
00:30:09,640 --> 00:30:12,920
Speaker 2: you know, how combustable they are. But it's a startup company.

610
00:30:13,240 --> 00:30:17,000
Speaker 2: It's teamed up with Cambridge University in the UK, and

611
00:30:17,040 --> 00:30:19,800
Speaker 2: they're saying that they can speed up that by changing

612
00:30:19,800 --> 00:30:22,960
Speaker 2: the chemistry of a lithium ion battery, it will allow

613
00:30:23,040 --> 00:30:26,960
Speaker 2: more electricity into the battery to be retained at a much, much,

614
00:30:27,120 --> 00:30:30,520
Speaker 2: much faster rate. So that would be a massive boon

615
00:30:30,560 --> 00:30:31,080
Speaker 2: to I think.

616
00:30:30,960 --> 00:30:31,640
Speaker 1: A lot of people.

617
00:30:31,960 --> 00:30:33,960
Speaker 2: If you knew that you could charge up your vehicles

618
00:30:34,000 --> 00:30:36,920
Speaker 2: so quickly, I reckon that would be a real, you know,

619
00:30:37,240 --> 00:30:39,120
Speaker 2: really incentive for a lot of people who are maybe

620
00:30:39,120 --> 00:30:40,360
Speaker 2: a little bit resistant to get.

621
00:30:41,720 --> 00:30:44,120
Speaker 1: Definitely, that would be a game changer because right now

622
00:30:44,160 --> 00:30:46,840
Speaker 1: it's for a lot of people, it's very impractical.

623
00:30:47,040 --> 00:30:53,760
Speaker 2: So the car that they adapted to do this was

624
00:30:53,800 --> 00:30:57,240
Speaker 2: a Lotus. The lease that's looking car isn't that as

625
00:30:57,480 --> 00:30:58,520
Speaker 2: a gorgeous.

626
00:30:58,080 --> 00:31:01,959
Speaker 1: Cars Lotus make, which is a British car. Everyone. They

627
00:31:02,000 --> 00:31:06,040
Speaker 1: make beautiful cars. They've traditionally, or I should say historically,

628
00:31:06,120 --> 00:31:10,120
Speaker 1: been quite unreliable, but they are amazing looking cars. But

629
00:31:10,200 --> 00:31:13,840
Speaker 1: I'm pretty sure they're not built in England anymore. Shout

630
00:31:13,880 --> 00:31:17,280
Speaker 1: out to our English listeners. Not everything else is good though,

631
00:31:17,520 --> 00:31:20,440
Speaker 1: just maybe the old the old old school Lotuses were

632
00:31:20,480 --> 00:31:21,160
Speaker 1: a bit dodgy.

633
00:31:23,320 --> 00:31:25,160
Speaker 3: So you're going to say something before I.

634
00:31:25,040 --> 00:31:28,080
Speaker 1: Was just gonna I'm interested in the night curfew feature.

635
00:31:28,280 --> 00:31:31,440
Speaker 1: That's new software that Tesla are bringing out. What is

636
00:31:31,480 --> 00:31:31,960
Speaker 1: that about?

637
00:31:33,320 --> 00:31:37,160
Speaker 3: That's a good question, you tell me, just.

638
00:31:36,560 --> 00:31:39,280
Speaker 1: Just take this bit out. What's on your list? Motherfucker?

639
00:31:42,640 --> 00:31:45,960
Speaker 1: You can leave all this into fucking no fuck him.

640
00:31:46,120 --> 00:31:48,040
Speaker 1: He sends his little list and then he doesn't know

641
00:31:48,280 --> 00:31:50,360
Speaker 1: do you know what? Though in his defense, he did

642
00:31:50,400 --> 00:31:53,240
Speaker 1: send the list on Tuesday. It was such a why

643
00:31:53,240 --> 00:31:54,840
Speaker 1: were you so organized this week?

644
00:31:55,520 --> 00:31:59,240
Speaker 2: Because I had can I sure Okay, this is how

645
00:31:59,240 --> 00:32:02,680
Speaker 2: I prepare for the show. I read throughout the two weeks,

646
00:32:02,840 --> 00:32:05,360
Speaker 2: and when I find an article that potentially could assist,

647
00:32:05,480 --> 00:32:07,680
Speaker 2: I email it to myself and I have a folder.

648
00:32:08,720 --> 00:32:11,160
Speaker 2: I had a kit of work experience, and I got

649
00:32:11,240 --> 00:32:12,520
Speaker 2: him to collate it all for me.

650
00:32:13,520 --> 00:32:18,080
Speaker 1: Ah, so the kids, well, yeah, can you see if

651
00:32:18,120 --> 00:32:20,800
Speaker 1: the kids available for the podcast? Because you're doing shit?

652
00:32:21,640 --> 00:32:24,000
Speaker 3: Hey Christian, thanks for putting hard work.

653
00:32:24,040 --> 00:32:27,560
Speaker 1: It's hey, Christian, are you available in two weeks mate?

654
00:32:27,600 --> 00:32:33,000
Speaker 1: Because the bloke that's currently doing it not that good. No.

655
00:32:33,120 --> 00:32:35,400
Speaker 2: I do a live radio spot on a little community

656
00:32:35,480 --> 00:32:37,960
Speaker 2: radio station as well, but I didn't get to that part.

657
00:32:38,520 --> 00:32:41,440
Speaker 2: So I looked at it, thought, that's an interesting story.

658
00:32:41,520 --> 00:32:41,680
Speaker 1: You know.

659
00:32:42,880 --> 00:32:45,920
Speaker 2: New update that is calls got a night curfew mode

660
00:32:46,240 --> 00:32:49,160
Speaker 2: and it's great for parents right when they want to

661
00:32:49,200 --> 00:32:51,520
Speaker 2: make sure that their kids don't drive the car at night.

662
00:32:51,800 --> 00:32:56,200
Speaker 2: So basically you can make sure that can't being used

663
00:32:56,240 --> 00:32:57,880
Speaker 2: by someone who shouldn't be using it.

664
00:32:59,640 --> 00:33:03,280
Speaker 1: You just got busted. You just got busted time. Well,

665
00:33:03,320 --> 00:33:06,160
Speaker 1: how about instead of me asking you questions about the

666
00:33:06,200 --> 00:33:09,520
Speaker 1: notes that you've sent me and throwing you under the

667
00:33:09,560 --> 00:33:12,360
Speaker 1: bus because you're ill prepared, how about you just steer

668
00:33:12,360 --> 00:33:12,800
Speaker 1: the ship.

669
00:33:14,040 --> 00:33:15,920
Speaker 2: Why would you want me to steer the ship because

670
00:33:15,920 --> 00:33:17,800
Speaker 2: I'll be talking about shit you're not interested in.

671
00:33:18,160 --> 00:33:22,280
Speaker 1: That's not interested in all of it. I want to

672
00:33:22,320 --> 00:33:25,880
Speaker 1: know about a six legged robot guide dog because.

673
00:33:25,880 --> 00:33:30,680
Speaker 2: Was this yeah, yeah, yeah, okay, Well, so when we

674
00:33:30,720 --> 00:33:33,320
Speaker 2: think of all those robot dogs, and Boston Dynamics has

675
00:33:33,400 --> 00:33:36,200
Speaker 2: been very popular in the past with the development that

676
00:33:36,200 --> 00:33:38,480
Speaker 2: they've done. We've all seen the Boston Dynamics dogs, you know,

677
00:33:38,600 --> 00:33:40,640
Speaker 2: or the robots that get pushed over, they get back

678
00:33:40,720 --> 00:33:43,600
Speaker 2: up again. But I thought this was interesting because when

679
00:33:43,680 --> 00:33:47,200
Speaker 2: we think about, you know, the fact that what could

680
00:33:47,200 --> 00:33:50,960
Speaker 2: you use those dogs for? You know, and now they're saying, well,

681
00:33:51,280 --> 00:33:53,440
Speaker 2: why not use them to help people who are visually

682
00:33:53,440 --> 00:33:56,400
Speaker 2: impaired or vision impaired, I should say, to be able

683
00:33:56,440 --> 00:33:59,000
Speaker 2: to help them and that way, don't have to worry

684
00:33:59,040 --> 00:34:01,000
Speaker 2: about cleaning up after dog. I mean, it's got a

685
00:34:01,000 --> 00:34:02,840
Speaker 2: lot of benefits there. You just charge it up then

686
00:34:02,840 --> 00:34:06,080
Speaker 2: have defeated. No, but I height of Fritz, by the way,

687
00:34:06,160 --> 00:34:08,279
Speaker 2: my dog. I would never replace him with an electronic dog.

688
00:34:08,320 --> 00:34:12,400
Speaker 2: By the way, No, I wouldn't. We were about to

689
00:34:12,400 --> 00:34:15,799
Speaker 2: get a dog, aren't you. Didn't you say, yeah, so yeah,

690
00:34:15,840 --> 00:34:16,560
Speaker 2: you couldn't.

691
00:34:16,239 --> 00:34:16,840
Speaker 1: Possibly do that.

692
00:34:16,960 --> 00:34:20,360
Speaker 2: You'll you'll realize once you've got one. Anyway, So this

693
00:34:21,040 --> 00:34:25,080
Speaker 2: guide dog robot. It also the benefit of this is

694
00:34:25,160 --> 00:34:27,200
Speaker 2: would have a whole lot of tech built into it

695
00:34:27,239 --> 00:34:30,120
Speaker 2: to be able to It's been developed in Shang High University,

696
00:34:30,440 --> 00:34:33,120
Speaker 2: and it would have things like light ar and radar

697
00:34:33,480 --> 00:34:37,640
Speaker 2: and sensors built into it to be able to accurately,

698
00:34:38,120 --> 00:34:41,640
Speaker 2: you know, see and navigate around the world and assist people.

699
00:34:42,640 --> 00:34:45,880
Speaker 2: And I guess you know, I think seeing eye dogs

700
00:34:45,880 --> 00:34:49,320
Speaker 2: are amazing, but you know, they only have a certain

701
00:34:49,400 --> 00:34:50,760
Speaker 2: lifespan and you've got.

702
00:34:50,600 --> 00:34:51,120
Speaker 1: To train them.

703
00:34:51,200 --> 00:34:53,120
Speaker 2: A whole lot of effort and energy goes into it.

704
00:34:53,320 --> 00:34:56,880
Speaker 2: So yeah, this could be really beneficial. You're not interested

705
00:34:56,920 --> 00:34:57,359
Speaker 2: at all with.

706
00:34:57,360 --> 00:35:01,360
Speaker 1: Rose and cons pros. I'm with you, like they're probably

707
00:35:01,400 --> 00:35:06,239
Speaker 1: going to be in some ways more effective and more

708
00:35:06,360 --> 00:35:11,600
Speaker 1: features and functions, But you need the love, You need

709
00:35:11,600 --> 00:35:14,080
Speaker 1: the emotion you need to get. You need to line

710
00:35:14,160 --> 00:35:17,120
Speaker 1: the floor with your guide dog and snuggle. You need

711
00:35:17,200 --> 00:35:20,480
Speaker 1: your guide dogs sleeping on your bed and licking your

712
00:35:20,560 --> 00:35:22,320
Speaker 1: face and farting.

713
00:35:22,680 --> 00:35:25,160
Speaker 2: The problem is in countries, say, for exact, China is

714
00:35:25,200 --> 00:35:27,840
Speaker 2: a really good example. They're just a not enough guide dogs.

715
00:35:27,920 --> 00:35:29,920
Speaker 3: That's true. That's the other problem.

716
00:35:29,960 --> 00:35:32,200
Speaker 2: So there's this long learning curve where you've got to

717
00:35:32,239 --> 00:35:35,640
Speaker 2: teach them, you've got to breathe them. And so there

718
00:35:35,640 --> 00:35:38,200
Speaker 2: are people who are missing out because they're just as

719
00:35:38,280 --> 00:35:41,239
Speaker 2: a more need than there are supply and so much

720
00:35:41,280 --> 00:35:43,040
Speaker 2: work that goes into it. But if you can build them,

721
00:35:43,360 --> 00:35:45,799
Speaker 2: train them, it means you just download it straight into

722
00:35:45,840 --> 00:35:48,439
Speaker 2: the dog or the electronic dog, the six legged dog,

723
00:35:48,480 --> 00:35:49,520
Speaker 2: and off your go and running.

724
00:35:50,080 --> 00:35:56,560
Speaker 1: I see that Japan has finally discovered Viagrapatrick, So the

725
00:35:56,680 --> 00:36:03,279
Speaker 1: story above, the one you just read, discovered viagra. Yeah, No,

726
00:36:03,480 --> 00:36:06,880
Speaker 1: Japanese government finally says farewell to floppy discs.

727
00:36:06,920 --> 00:36:11,560
Speaker 2: Really, I thought this was interesting because I know the

728
00:36:11,640 --> 00:36:13,920
Speaker 2: Japanese government was still using floppies.

729
00:36:15,120 --> 00:36:19,279
Speaker 1: Yes, they've got an electronic viagra, so they're getting rid

730
00:36:19,320 --> 00:36:20,799
Speaker 1: of the flopping discs.

731
00:36:21,200 --> 00:36:22,960
Speaker 3: It's like descended to primary s.

732
00:36:23,120 --> 00:36:26,600
Speaker 1: Its fucking year eight all over again. Isn't it Friday morning?

733
00:36:26,640 --> 00:36:32,600
Speaker 1: It's early yes, so at it's why were the China,

734
00:36:32,880 --> 00:36:36,040
Speaker 1: sorry Japanese government using floppy discs anyway?

735
00:36:36,719 --> 00:36:39,920
Speaker 2: Well, they just had computer systems that hadn't been updated.

736
00:36:40,000 --> 00:36:43,160
Speaker 2: They were still using a lot of this old tech

737
00:36:43,320 --> 00:36:46,960
Speaker 2: because it was working. You know, why fix what's not broken?

738
00:36:47,000 --> 00:36:50,200
Speaker 2: I mean, it sounds absolutely absurd. I think the last

739
00:36:50,239 --> 00:36:52,839
Speaker 2: floppy disks would have been used what twenty five years

740
00:36:52,840 --> 00:36:55,880
Speaker 2: ago or something. I didn't know in terms of traditionally,

741
00:36:56,239 --> 00:37:02,160
Speaker 2: but so it was. Japan has a pretty rigid culture.

742
00:37:02,200 --> 00:37:05,160
Speaker 2: I mean, I really want to go to Japan. It's

743
00:37:05,200 --> 00:37:08,080
Speaker 2: one of those bucket list countries that I'd love to

744
00:37:08,120 --> 00:37:12,760
Speaker 2: go to. And so, yeah, there was some single environment

745
00:37:12,880 --> 00:37:17,600
Speaker 2: systems where floppy disks were working and people were still

746
00:37:17,680 --> 00:37:19,920
Speaker 2: using them in the government departments.

747
00:37:20,400 --> 00:37:22,840
Speaker 1: I mean, if I feel like I interrupted you, Sorry, Patrick,

748
00:37:23,160 --> 00:37:26,680
Speaker 1: were you going to say something? And in opening the

749
00:37:26,719 --> 00:37:30,520
Speaker 1: door for Tiff, I then interrupted Patrick. Sorry Patrick, go on, Tiff.

750
00:37:30,960 --> 00:37:33,520
Speaker 5: No, that was way back in the guide dog conversation,

751
00:37:33,800 --> 00:37:36,040
Speaker 5: and all I was going to say is I missed

752
00:37:36,280 --> 00:37:38,799
Speaker 5: hearing the whole reason they have six legs, because soon

753
00:37:38,800 --> 00:37:41,279
Speaker 5: as the conversation started, I went and googled how to

754
00:37:41,280 --> 00:37:43,040
Speaker 5: blind people pick up after their dog?

755
00:37:43,760 --> 00:37:45,440
Speaker 4: So I missed the whole conversation.

756
00:37:46,400 --> 00:37:50,920
Speaker 1: How do they Yeah, I'm interested, that's interesting. Well, I'm

757
00:37:50,920 --> 00:37:55,400
Speaker 1: pretty sure that they are trained not to kind of

758
00:37:55,560 --> 00:37:59,520
Speaker 1: pooh in a certain spot and on command. I'm sure

759
00:37:59,520 --> 00:38:01,759
Speaker 1: that there's a about one hundred people listening now who

760
00:38:01,880 --> 00:38:05,080
Speaker 1: absolutely know the answer to this. What's the I'll tell

761
00:38:05,080 --> 00:38:08,960
Speaker 1: you what this is not technology is it's it's pretty good,

762
00:38:09,080 --> 00:38:12,600
Speaker 1: all right? Why while tists finding that out? You just

763
00:38:12,719 --> 00:38:15,719
Speaker 1: keep plowing on, Patrick, I'll try. I don't know, I

764
00:38:15,719 --> 00:38:16,839
Speaker 1: don't know where to go from here.

765
00:38:16,960 --> 00:38:17,040
Speaker 6: Now.

766
00:38:18,000 --> 00:38:21,960
Speaker 2: The we kind of mock the Japanese government for using

767
00:38:21,960 --> 00:38:24,120
Speaker 2: floppy disks, but you know a lot of the medical

768
00:38:24,160 --> 00:38:25,720
Speaker 2: profession still uses fax machines.

769
00:38:25,719 --> 00:38:27,800
Speaker 1: When was the last time I used a fax machine, Craigo,

770
00:38:29,160 --> 00:38:32,279
Speaker 1: Not for well personally, not for a long time. But yeah,

771
00:38:32,320 --> 00:38:34,719
Speaker 1: I know some even in some medical centers now, they

772
00:38:34,800 --> 00:38:38,000
Speaker 1: still they still use faxes and stuff. Because the other

773
00:38:38,080 --> 00:38:39,759
Speaker 1: day I was at the dock and I saw a

774
00:38:39,800 --> 00:38:42,440
Speaker 1: fax machine and a facts coming through. I'm like, am

775
00:38:42,480 --> 00:38:44,320
Speaker 1: I in back to the future? Yeah?

776
00:38:44,760 --> 00:38:48,080
Speaker 2: You know, the interesting thing is fax machines and facts

777
00:38:48,160 --> 00:38:53,560
Speaker 2: transmissions can't be intercepted. If I wanted to safely send

778
00:38:53,640 --> 00:38:58,160
Speaker 2: you a message, email is a bit precarious, So I

779
00:38:58,160 --> 00:38:59,799
Speaker 2: guess if I said the facts, it might be a

780
00:38:59,800 --> 00:39:01,239
Speaker 2: say way to send a message to you.

781
00:39:01,280 --> 00:39:04,160
Speaker 3: Hadn't thought about that, because have I admitted this story

782
00:39:04,239 --> 00:39:04,400
Speaker 3: to you.

783
00:39:04,480 --> 00:39:06,520
Speaker 2: When I was working at a newsroom in Geelong as

784
00:39:06,520 --> 00:39:09,360
Speaker 2: a young journalist, I used to get it was a

785
00:39:09,400 --> 00:39:11,200
Speaker 2: guy by the name of Stuart MacArthur who was a

786
00:39:11,239 --> 00:39:15,080
Speaker 2: local politician, and he used to on a Friday send

787
00:39:15,120 --> 00:39:18,200
Speaker 2: a media release that was like twelve to twenty pages

788
00:39:18,640 --> 00:39:22,680
Speaker 2: and wow, his faxes had rolls of fax paper and

789
00:39:22,719 --> 00:39:26,440
Speaker 2: when the role ran out, that was it. So at

790
00:39:26,480 --> 00:39:28,880
Speaker 2: the start of the weekend, we'd get it on Monday

791
00:39:28,920 --> 00:39:31,239
Speaker 2: morning because we hadn't done news at the weekend, and

792
00:39:31,280 --> 00:39:33,279
Speaker 2: suddenly all the facts had run out because it'd sent

793
00:39:33,320 --> 00:39:35,360
Speaker 2: this twenty page fax the night before.

794
00:39:36,200 --> 00:39:37,680
Speaker 1: Really annoying, and this happened.

795
00:39:37,400 --> 00:39:40,400
Speaker 2: Quite regularly so and we didn't need all that information

796
00:39:40,480 --> 00:39:41,640
Speaker 2: because it wasn't print.

797
00:39:41,760 --> 00:39:43,720
Speaker 1: It was just a thirty second news story.

798
00:39:44,040 --> 00:39:47,320
Speaker 2: So then one Friday I sent him back a fax,

799
00:39:47,360 --> 00:39:49,400
Speaker 2: but what I wrote on it was I had a

800
00:39:49,400 --> 00:39:52,000
Speaker 2: long sheet and I wrote, do not send long facts,

801
00:39:52,160 --> 00:39:54,080
Speaker 2: and then I taped it to the other end. So

802
00:39:54,120 --> 00:39:57,959
Speaker 2: it was a continuous loop. So when he got into

803
00:39:58,000 --> 00:40:00,080
Speaker 2: his office on the Monday morning, it just had the same.

804
00:40:00,000 --> 00:40:03,200
Speaker 1: A message on loop for his entire effects role. Sorry

805
00:40:03,200 --> 00:40:05,680
Speaker 1: my god, did you ever get busted for that? No?

806
00:40:05,800 --> 00:40:07,840
Speaker 3: That he didn't send long factors anymore.

807
00:40:07,920 --> 00:40:12,160
Speaker 1: It worked. That's hilarious. Hey, I don't know why this

808
00:40:12,320 --> 00:40:15,800
Speaker 1: is a weird departure, but in the middle of the

809
00:40:15,880 --> 00:40:19,800
Speaker 1: night last night, I woke up and my mind was

810
00:40:19,840 --> 00:40:22,600
Speaker 1: busy and I couldn't sleep, so I turned on the TV. Now,

811
00:40:22,920 --> 00:40:25,480
Speaker 1: neither of you will know, probably, and neither do you

812
00:40:25,520 --> 00:40:28,200
Speaker 1: need to know. A guy called Joe Walsh who's a

813
00:40:28,280 --> 00:40:32,880
Speaker 1: musician and he was part of the Eagles. Anyway, I

814
00:40:32,920 --> 00:40:34,960
Speaker 1: love Joe Walsh, and I love the Eagles because I'm

815
00:40:35,040 --> 00:40:37,600
Speaker 1: super old. But I was listening to him talking about

816
00:40:37,640 --> 00:40:41,360
Speaker 1: his music and he wrote a song patrick In I

817
00:40:41,400 --> 00:40:45,800
Speaker 1: think it got published in twenty twelve called analog Man,

818
00:40:47,080 --> 00:40:49,839
Speaker 1: and here are some of the lyrics. Welcome to cyberspace.

819
00:40:49,880 --> 00:40:53,640
Speaker 1: I'm lost in the fog. Everything's digital. I'm still analog.

820
00:40:54,160 --> 00:40:56,319
Speaker 1: When something goes wrong, I don't have a clue. Some

821
00:40:56,360 --> 00:40:58,360
Speaker 1: ten year old smart ass tests has show me what

822
00:40:58,440 --> 00:41:00,880
Speaker 1: to do. Sign on with high speed. You don't have

823
00:41:00,920 --> 00:41:03,680
Speaker 1: to wait to sit there for days and vegetate. I

824
00:41:03,719 --> 00:41:07,680
Speaker 1: access my email, read all my spam. I'm an analog man.

825
00:41:07,880 --> 00:41:10,560
Speaker 1: The world's living in a digital dream. It's not really there.

826
00:41:10,600 --> 00:41:13,319
Speaker 1: It's all on the screen makes me forget who I am.

827
00:41:13,360 --> 00:41:16,120
Speaker 1: I'm an analog man. Yeah, I'm an analog man in

828
00:41:16,160 --> 00:41:18,320
Speaker 1: a digital world. I'm going to get me an analog

829
00:41:18,440 --> 00:41:20,640
Speaker 1: girl who loves me for what I am. I'm an

830
00:41:20,640 --> 00:41:24,520
Speaker 1: analog man. That could have been written for me. That's

831
00:41:24,600 --> 00:41:29,600
Speaker 1: fucking Joe Walsh, just fucking groundbreaking twelve years ago. That

832
00:41:29,760 --> 00:41:33,000
Speaker 1: was That's good. I actually like it. They're great lyrics.

833
00:41:33,280 --> 00:41:36,880
Speaker 3: Hey, you mentioned that your new car has a bone

834
00:41:37,000 --> 00:41:40,359
Speaker 3: sterilizer in it.

835
00:41:39,760 --> 00:41:44,720
Speaker 1: So it's got a what looks like a glove box,

836
00:41:44,760 --> 00:41:47,640
Speaker 1: but it's skinny, so same in the same spot, but

837
00:41:47,719 --> 00:41:53,400
Speaker 1: above the actual glove box. And I guess it's about

838
00:41:53,800 --> 00:41:57,879
Speaker 1: as like a couple of inches deep, so not much

839
00:41:58,000 --> 00:42:00,840
Speaker 1: like five centimeters, And you open the door or the

840
00:42:01,680 --> 00:42:04,120
Speaker 1: whatever to that, and you put your phone in, you

841
00:42:04,160 --> 00:42:09,000
Speaker 1: press a button and then it it sterilizes, I guess

842
00:42:09,160 --> 00:42:11,719
Speaker 1: is the word. It sterilizes your phone. It kills all

843
00:42:11,760 --> 00:42:15,319
Speaker 1: the germs that are on your phone, which I don't

844
00:42:15,360 --> 00:42:18,240
Speaker 1: think anyone in the world was asking for that feature.

845
00:42:18,480 --> 00:42:23,480
Speaker 2: But nonetheless, I beg to differ really different because the

846
00:42:23,520 --> 00:42:25,360
Speaker 2: next little story that I did want to chat about

847
00:42:25,560 --> 00:42:30,600
Speaker 2: is how your phone, your watch, and particularly the you know,

848
00:42:30,920 --> 00:42:33,920
Speaker 2: the clip or the not the clip. The band on

849
00:42:33,960 --> 00:42:37,160
Speaker 2: your watch is a breeding ground for E. Coli and

850
00:42:37,320 --> 00:42:41,480
Speaker 2: staff bacteria. And how none of us really I mean,

851
00:42:41,520 --> 00:42:43,360
Speaker 2: I've got to say I never cleaned the band of

852
00:42:43,480 --> 00:42:45,200
Speaker 2: my watch and it's cloth, which is one.

853
00:42:45,120 --> 00:42:45,880
Speaker 1: Of the worst things.

854
00:42:46,680 --> 00:42:50,520
Speaker 2: So they say that were we should be cleaning our

855
00:42:50,640 --> 00:42:52,439
Speaker 2: device is a lot more than we do.

856
00:42:52,719 --> 00:42:54,560
Speaker 3: You know, you're pressing it up against your face.

857
00:42:54,719 --> 00:42:58,239
Speaker 2: You know you've got on your body, and it makes

858
00:42:58,280 --> 00:42:59,560
Speaker 2: more sense when you start to think of it.

859
00:42:59,560 --> 00:43:02,200
Speaker 3: In those two you can sterilizing kits.

860
00:43:02,760 --> 00:43:02,920
Speaker 1: You know.

861
00:43:02,960 --> 00:43:04,719
Speaker 2: The funny thing is every time I look at your

862
00:43:04,800 --> 00:43:08,560
Speaker 2: window and I say zoom window, it looks like you're

863
00:43:08,640 --> 00:43:10,239
Speaker 2: sitting in a sterilizing kit.

864
00:43:11,440 --> 00:43:14,160
Speaker 1: That's deliberate because it's glowing. Oh yeah, yeah, yeah, because

865
00:43:14,200 --> 00:43:17,759
Speaker 1: it's got your car. Yeah, that's true. Well, speaking of

866
00:43:17,800 --> 00:43:22,120
Speaker 1: things that are on your person, you've seen this bracelet

867
00:43:22,160 --> 00:43:24,279
Speaker 1: that's been on my wrist for twenty nine years and

868
00:43:24,320 --> 00:43:30,799
Speaker 1: never come off. It's very politically incorrectly called back in

869
00:43:30,800 --> 00:43:34,560
Speaker 1: the day a slave bracelet. Oh right, and then and

870
00:43:34,640 --> 00:43:36,680
Speaker 1: they put it on, they screw it on, and it's

871
00:43:36,719 --> 00:43:41,120
Speaker 1: got the initials, my initials and my mate who passed away, Maddie.

872
00:43:41,880 --> 00:43:44,160
Speaker 1: But that's been on my wrist for twenty nine years

873
00:43:44,200 --> 00:43:47,160
Speaker 1: and never come off once ever. And I wonder when

874
00:43:47,200 --> 00:43:52,120
Speaker 1: on in nine ninety five, I wonder, I wonder what's

875
00:43:52,160 --> 00:43:54,520
Speaker 1: living under that? Wow?

876
00:43:55,000 --> 00:43:58,440
Speaker 2: No, the interesting thing is copper is actually bacteria resistant.

877
00:43:58,640 --> 00:44:04,799
Speaker 6: Some metals gold to thank You's the original bracelets, cop up,

878
00:44:05,040 --> 00:44:06,360
Speaker 6: There were copper bracelets.

879
00:44:06,360 --> 00:44:09,120
Speaker 2: They were used as a medium of exchange in West

880
00:44:09,200 --> 00:44:11,320
Speaker 2: Africa as part of the slave trade.

881
00:44:11,400 --> 00:44:13,680
Speaker 1: What has that got to do with my gold bracelet?

882
00:44:13,760 --> 00:44:13,920
Speaker 6: Oh?

883
00:44:13,960 --> 00:44:19,279
Speaker 1: Okay, okay, okay, okay. Well, I think the reason that

884
00:44:19,320 --> 00:44:22,520
Speaker 1: they called it anyway is because it gets when you

885
00:44:22,560 --> 00:44:24,840
Speaker 1: buy it, they put it on with a screwdriver. It

886
00:44:24,880 --> 00:44:28,160
Speaker 1: gets screwed on. There's no clip or clasp. You can't

887
00:44:28,200 --> 00:44:31,960
Speaker 1: take it off unless you you know, you have those tools.

888
00:44:32,040 --> 00:44:34,839
Speaker 1: But anyway, nobody needed to know that. Oh. I think

889
00:44:34,840 --> 00:44:38,480
Speaker 1: it's a lovely thing that you're still wearing that. I think, Well,

890
00:44:38,800 --> 00:44:40,439
Speaker 1: it makes me think about him every day.

891
00:44:40,840 --> 00:44:43,200
Speaker 3: Yeah, when you go to an airport, what happens when you.

892
00:44:43,160 --> 00:44:45,560
Speaker 1: Get Yeah, that's interesting. A few times they've asked me

893
00:44:45,600 --> 00:44:47,439
Speaker 1: to take it off and I say I can't take

894
00:44:47,440 --> 00:44:51,359
Speaker 1: it off, and they're like, then I sometimes have to

895
00:44:51,400 --> 00:44:54,640
Speaker 1: like put my arm through the thing before the rest

896
00:44:54,640 --> 00:44:59,319
Speaker 1: of my body, or one place they taped it like

897
00:44:59,360 --> 00:45:03,760
Speaker 1: they put like gaffer tape around my wrist and said,

898
00:45:03,840 --> 00:45:06,320
Speaker 1: I'm like, okay, sure.

899
00:45:06,200 --> 00:45:10,080
Speaker 5: That's not gonna Well, I don't know what a knife

900
00:45:10,080 --> 00:45:11,760
Speaker 5: to your body and stroll on through?

901
00:45:12,120 --> 00:45:15,360
Speaker 1: Yeah? No, no, no, because I don't know. I actually

902
00:45:15,400 --> 00:45:19,560
Speaker 1: don't understand what they think A round bracelet, I might

903
00:45:20,600 --> 00:45:23,319
Speaker 1: what I might do with that on a plane, or

904
00:45:23,360 --> 00:45:25,600
Speaker 1: maybe it's I don't know, maybe yeah, I don't know.

905
00:45:25,960 --> 00:45:30,440
Speaker 1: Who knows? Patrick, save us this.

906
00:45:30,560 --> 00:45:32,640
Speaker 2: I thought this is kind of not a tech related

907
00:45:32,719 --> 00:45:34,799
Speaker 2: story so much, but I thought it would be one

908
00:45:34,800 --> 00:45:39,920
Speaker 2: that would interest you because you're a big advocate of exercise,

909
00:45:39,960 --> 00:45:42,840
Speaker 2: and I know tiff is as well. Not only is

910
00:45:42,880 --> 00:45:46,800
Speaker 2: it thought that exercise mitigates cognitive decline, but it also

911
00:45:47,200 --> 00:45:52,840
Speaker 2: is linked to your gut microbia as well, so it

912
00:45:52,880 --> 00:45:56,520
Speaker 2: can actually assist in lots of different ways. So, I mean,

913
00:45:56,880 --> 00:45:59,800
Speaker 2: we know that cognitive decline is something that.

914
00:45:59,719 --> 00:46:02,040
Speaker 1: A lot of people worry about as they get older.

915
00:46:02,360 --> 00:46:04,799
Speaker 2: And you know, remember we had those brain games that

916
00:46:04,840 --> 00:46:08,399
Speaker 2: you'd play on in Well, they realized that none of that.

917
00:46:08,600 --> 00:46:12,320
Speaker 2: It does help a little bit, but physical exercise getting

918
00:46:12,360 --> 00:46:16,719
Speaker 2: out their circulation include you know, is the best possible

919
00:46:16,760 --> 00:46:19,880
Speaker 2: thing you can do for your brain health, is your

920
00:46:19,920 --> 00:46:23,239
Speaker 2: overall body health and exercise. But it also can be

921
00:46:23,320 --> 00:46:26,080
Speaker 2: linked to gut microbia. And I thought, wow, that's kind

922
00:46:26,080 --> 00:46:30,279
Speaker 2: of interesting. So and people go through difficult times and

923
00:46:30,280 --> 00:46:35,000
Speaker 2: I've got friends who have real problems with with digestion

924
00:46:35,120 --> 00:46:37,120
Speaker 2: and all that sort of stuff, So it may be

925
00:46:37,200 --> 00:46:41,520
Speaker 2: that simple exercise rather than a sedentary lifestyle.

926
00:46:41,680 --> 00:46:45,440
Speaker 1: Yeah, IM prove that Union of South Australia last year,

927
00:46:45,480 --> 00:46:48,080
Speaker 1: I think it was in December twenty twenty three published

928
00:46:48,640 --> 00:46:53,319
Speaker 1: a whole raft of research and findings around this, and

929
00:46:53,920 --> 00:47:02,320
Speaker 1: you're exactly right. And they compared an exercise intervention against

930
00:47:03,000 --> 00:47:08,880
Speaker 1: medical interventions, so anti axiotics and antidepressants. And this is

931
00:47:08,920 --> 00:47:13,600
Speaker 1: not a direction or a recommendation anyone. Consult your consult

932
00:47:13,640 --> 00:47:18,680
Speaker 1: your person or persons. But yeah, the exercise exercise alone

933
00:47:18,719 --> 00:47:21,640
Speaker 1: created much better results. So I think it was like

934
00:47:21,680 --> 00:47:24,680
Speaker 1: one hundred and fifty percent, which seems a very convenient number,

935
00:47:24,719 --> 00:47:28,920
Speaker 1: but yeah, much better results versus just medication. So just

936
00:47:29,040 --> 00:47:33,640
Speaker 1: exercise versus just medication from that perspective. But even like

937
00:47:33,680 --> 00:47:35,560
Speaker 1: we've had a lady on who was I don't know

938
00:47:35,600 --> 00:47:39,600
Speaker 1: if she's any more Professor Ingrid, the head of psychiatry

939
00:47:40,040 --> 00:47:43,960
Speaker 1: at Royal Adelaide Hospital, who's obviously a doctor and a

940
00:47:43,960 --> 00:47:48,560
Speaker 1: psychiatrist and someone who exercises a lot, and for her

941
00:47:49,560 --> 00:47:53,480
Speaker 1: medication even for people with mental health issues, is the

942
00:47:53,560 --> 00:48:00,000
Speaker 1: last option like drugs that she tries, lifestyle, food, exercise, life,

943
00:48:00,080 --> 00:48:03,799
Speaker 1: like trying to get people to change their own biochemistry

944
00:48:05,040 --> 00:48:08,120
Speaker 1: and what's happening in their brain on a biochemical level

945
00:48:08,800 --> 00:48:13,520
Speaker 1: with healthy interventions, because you know, any drug that you take,

946
00:48:14,600 --> 00:48:17,120
Speaker 1: even if it works on one level, there are going

947
00:48:17,200 --> 00:48:20,480
Speaker 1: to be there are going to be side effects somewhere between,

948
00:48:20,640 --> 00:48:24,000
Speaker 1: you know, very minor and very major, so you know

949
00:48:24,040 --> 00:48:26,399
Speaker 1: that's going to be factored in as well. But yeah,

950
00:48:26,440 --> 00:48:29,200
Speaker 1: that's no revelation to me. But you're exactly right, mate,

951
00:48:29,239 --> 00:48:32,799
Speaker 1: and it's great, and I wish everybody. The problem is

952
00:48:32,840 --> 00:48:36,440
Speaker 1: in inverted commas is that exercise is hard and popping

953
00:48:36,480 --> 00:48:37,480
Speaker 1: a pill is easy.

954
00:48:38,120 --> 00:48:40,680
Speaker 2: And another bit of research I read recently was that

955
00:48:41,080 --> 00:48:44,480
Speaker 2: just walking forty minutes three times a week if you

956
00:48:44,520 --> 00:48:47,120
Speaker 2: can't manage anything else, just doing a vigorous walk.

957
00:48:47,400 --> 00:48:49,439
Speaker 3: But now you know more about this than I would.

958
00:48:49,480 --> 00:48:53,600
Speaker 2: The hippocampus is directly the part of the brain that

959
00:48:54,080 --> 00:48:57,719
Speaker 2: is engaged when we do more exercise. And now they're

960
00:48:57,719 --> 00:49:01,120
Speaker 2: linking the hipper campus with what's happening in gut health.

961
00:49:01,480 --> 00:49:05,279
Speaker 2: So that's the correlation, and what they're trying connection to

962
00:49:05,560 --> 00:49:07,920
Speaker 2: is what's going on with you hippocampus.

963
00:49:07,960 --> 00:49:09,839
Speaker 3: Can you explain more about that? I mean, what does

964
00:49:09,880 --> 00:49:10,560
Speaker 3: actually happen?

965
00:49:11,360 --> 00:49:16,200
Speaker 1: I mean, so like the gut is interestingly called the

966
00:49:16,239 --> 00:49:19,320
Speaker 1: second brain now and the heart is called the third

967
00:49:19,360 --> 00:49:22,200
Speaker 1: brain now a lot of people you know, but everything's

968
00:49:22,400 --> 00:49:25,880
Speaker 1: interacting all the time. Like the gut microbiome that you

969
00:49:25,920 --> 00:49:30,520
Speaker 1: were talking about is affected by everything from the food

970
00:49:30,600 --> 00:49:33,400
Speaker 1: you eat to the sleep that you have to Like if,

971
00:49:33,480 --> 00:49:36,200
Speaker 1: for example, you think a negative thought now which I've

972
00:49:36,200 --> 00:49:40,200
Speaker 1: said this many times, but that produces cortisol and cortisole

973
00:49:40,239 --> 00:49:44,560
Speaker 1: affects your gut microbiome. Like everything be the thought's mind

974
00:49:44,600 --> 00:49:46,600
Speaker 1: as we call the mind, which is really a construct

975
00:49:46,719 --> 00:49:49,880
Speaker 1: or the physical brain itself, or the nervous system, or

976
00:49:49,920 --> 00:49:53,600
Speaker 1: the gut or the heart. You know, everything's intertwined all

977
00:49:53,640 --> 00:49:56,200
Speaker 1: the time, mate, and that's the that's the beauty of

978
00:49:56,200 --> 00:50:00,799
Speaker 1: this stuff. Is trying to like, research is important. I

979
00:50:00,840 --> 00:50:04,320
Speaker 1: wrote a post about this the other day. And there's

980
00:50:05,560 --> 00:50:08,160
Speaker 1: there's this term that gets thrown around a lot, and

981
00:50:08,200 --> 00:50:11,440
Speaker 1: the term is evidence based. Right, so people come out

982
00:50:11,480 --> 00:50:13,920
Speaker 1: all the time and go, oh, this is an evidence

983
00:50:13,960 --> 00:50:20,480
Speaker 1: based protocol, or this is evidence based formula, or but often,

984
00:50:20,920 --> 00:50:24,440
Speaker 1: like I would say, more often than not, it's either

985
00:50:24,800 --> 00:50:29,279
Speaker 1: completely untrue or misleading. And so and I know I've

986
00:50:29,320 --> 00:50:34,359
Speaker 1: diverged a little bit, but you know, learning to you know,

987
00:50:34,520 --> 00:50:37,120
Speaker 1: pay it. Even with what we talk about, which is

988
00:50:37,320 --> 00:50:40,719
Speaker 1: very informal and very casual, but even if we say

989
00:50:40,800 --> 00:50:44,200
Speaker 1: something on here that might resonate with people, I always

990
00:50:44,239 --> 00:50:47,040
Speaker 1: say to people, don't do something because we spoke about it.

991
00:50:47,120 --> 00:50:50,879
Speaker 1: Do something. Maybe go and open the door and do

992
00:50:50,960 --> 00:50:53,880
Speaker 1: some research for yourself and talk to somebody smarter than

993
00:50:53,960 --> 00:50:58,400
Speaker 1: us three dickheads, and then maybe after that then try

994
00:50:58,480 --> 00:51:01,360
Speaker 1: something or or oh, you know, if you want to

995
00:51:01,360 --> 00:51:04,480
Speaker 1: do something really basic like an equals one, you're the

996
00:51:04,600 --> 00:51:09,400
Speaker 1: researcher and the researched, just try something like Patrick said,

997
00:51:10,160 --> 00:51:12,719
Speaker 1: you know, walking every day for thirty minutes, or and

998
00:51:12,840 --> 00:51:15,000
Speaker 1: just see how you feel. You know, it's you don't

999
00:51:15,040 --> 00:51:17,640
Speaker 1: need to go to a doctor for that, or you know,

1000
00:51:17,800 --> 00:51:19,719
Speaker 1: instead of having three meals a day have the same

1001
00:51:19,719 --> 00:51:22,239
Speaker 1: amount of calories, but in five meals and maybe your

1002
00:51:22,360 --> 00:51:27,319
Speaker 1: digestive issues will be, you know, diminished somewhat. Like I think,

1003
00:51:27,360 --> 00:51:29,319
Speaker 1: it's a little bit of trial and error with all

1004
00:51:29,320 --> 00:51:29,920
Speaker 1: of this stuff.

1005
00:51:31,080 --> 00:51:33,560
Speaker 2: I have a little kind of mental policy that I do.

1006
00:51:33,680 --> 00:51:36,480
Speaker 2: I always take stairs when I can. Well, probably not

1007
00:51:36,520 --> 00:51:39,520
Speaker 2: in a thirty story building, but for the most part,

1008
00:51:39,560 --> 00:51:41,799
Speaker 2: if I can take the stairs, I always will. But

1009
00:51:41,840 --> 00:51:44,680
Speaker 2: then someone said to me, actually a tai Chi master

1010
00:51:44,800 --> 00:51:47,880
Speaker 2: who I met in China, who couldn't speak English, and

1011
00:51:47,920 --> 00:51:53,080
Speaker 2: we translated our entire day of conversations through phones. But

1012
00:51:53,160 --> 00:51:56,680
Speaker 2: he said to me, don't go downstairs because of the impact.

1013
00:51:56,840 --> 00:52:00,319
Speaker 2: So upstairs good downstairs, use an escalator or lift.

1014
00:52:00,680 --> 00:52:03,640
Speaker 1: So there you go. That's pretty true. I mean, we've

1015
00:52:03,640 --> 00:52:06,000
Speaker 1: got to go downstairs. But it's like you're way better

1016
00:52:06,040 --> 00:52:08,520
Speaker 1: off running up a hill for a range of reasons

1017
00:52:08,560 --> 00:52:11,359
Speaker 1: than running down a hill. Yep, yep, exactly. So that's

1018
00:52:11,360 --> 00:52:12,040
Speaker 1: what he said to me.

1019
00:52:12,160 --> 00:52:14,320
Speaker 2: And the other thing that I tell my Tishi students

1020
00:52:14,600 --> 00:52:16,240
Speaker 2: is when you're brushing your teeth.

1021
00:52:16,400 --> 00:52:17,959
Speaker 1: I don't know I've said this before, but when you're.

1022
00:52:17,840 --> 00:52:20,920
Speaker 2: Brushing your teeth, your two minute roughly routine, stand on

1023
00:52:20,920 --> 00:52:24,280
Speaker 2: one foot as you're brushing your tooth teeth, then change

1024
00:52:24,280 --> 00:52:27,160
Speaker 2: to the other foot halfway through. And it's just such

1025
00:52:27,160 --> 00:52:30,160
Speaker 2: a simple thing that's not going to impact in any way,

1026
00:52:30,239 --> 00:52:33,439
Speaker 2: doesn't take any extra efforts, but the.

1027
00:52:33,360 --> 00:52:34,399
Speaker 1: Ability for you.

1028
00:52:34,480 --> 00:52:37,319
Speaker 2: And I'm trying to think of the term that our

1029
00:52:37,400 --> 00:52:41,920
Speaker 2: brain uses to predict a fall. I can't think of

1030
00:52:42,480 --> 00:52:47,600
Speaker 2: the terminology, but it's the same. It's the same instinct

1031
00:52:47,680 --> 00:52:49,320
Speaker 2: that cats us to land.

1032
00:52:49,120 --> 00:52:51,800
Speaker 1: On all four feet. And you can improve.

1033
00:52:51,440 --> 00:52:54,600
Speaker 2: That, so our ability to be able to improve and

1034
00:52:54,680 --> 00:52:57,960
Speaker 2: work on our brain to get better at balance core stability.

1035
00:52:58,280 --> 00:52:59,800
Speaker 1: That also includes predicting.

1036
00:53:00,239 --> 00:53:02,440
Speaker 2: You know, when you have that sensation almost that you

1037
00:53:02,480 --> 00:53:04,839
Speaker 2: can get stumble and then you do what you need

1038
00:53:04,920 --> 00:53:06,399
Speaker 2: to stop yourself falling over.

1039
00:53:06,719 --> 00:53:07,640
Speaker 1: You can improve that.

1040
00:53:08,680 --> 00:53:10,680
Speaker 3: Part of the way to improve that is literally just

1041
00:53:10,680 --> 00:53:11,800
Speaker 3: to stand on one foot.

1042
00:53:12,080 --> 00:53:14,479
Speaker 2: So if you just stand on your foot every day

1043
00:53:14,520 --> 00:53:16,920
Speaker 2: while you're brushing your teeth or twice a day, and

1044
00:53:16,960 --> 00:53:20,680
Speaker 2: then alternate that, then it's something so so simple to do.

1045
00:53:20,680 --> 00:53:22,520
Speaker 1: You know what, I love that. I love that you

1046
00:53:22,560 --> 00:53:26,320
Speaker 1: say that because I'm weird. Right since I was a kid,

1047
00:53:26,400 --> 00:53:29,520
Speaker 1: I've always done weird shit. I've always gone like I

1048
00:53:29,520 --> 00:53:31,719
Speaker 1: remember being seven and going wonder how long I can

1049
00:53:31,760 --> 00:53:34,160
Speaker 1: hold my breath. I've spoken about this before. I wonder

1050
00:53:34,200 --> 00:53:36,359
Speaker 1: how long I can do it underwater? I wonder how

1051
00:53:36,440 --> 00:53:37,959
Speaker 1: you know, I used to just do all this shit,

1052
00:53:38,040 --> 00:53:41,319
Speaker 1: But even now, like I have this rule and here

1053
00:53:41,400 --> 00:53:44,600
Speaker 1: at home where I only walk up the stairs two

1054
00:53:44,600 --> 00:53:47,160
Speaker 1: at a time, yeah, me too, I do that as well.

1055
00:53:47,200 --> 00:53:49,319
Speaker 1: I only walk two at a time. And even if

1056
00:53:49,360 --> 00:53:51,480
Speaker 1: I'm carrying my dinner and shit up only two at

1057
00:53:51,520 --> 00:53:54,120
Speaker 1: a time. Another thing that I do not all the time,

1058
00:53:54,160 --> 00:53:57,439
Speaker 1: if I'm being honest, but probably half the time. When

1059
00:53:57,440 --> 00:54:00,080
Speaker 1: I put my shoes and socks on, I stand on

1060
00:54:00,040 --> 00:54:03,160
Speaker 1: one foot I put on. So my rule is, I've

1061
00:54:03,200 --> 00:54:05,719
Speaker 1: got to stand up. I don't sit down to put

1062
00:54:05,760 --> 00:54:07,360
Speaker 1: my shoes and socks on. I've got to stand up.

1063
00:54:07,360 --> 00:54:09,440
Speaker 1: I've got to lift one foot obviously off the ground,

1064
00:54:09,440 --> 00:54:11,560
Speaker 1: put the sock on, put the shoe on, and then

1065
00:54:11,600 --> 00:54:14,120
Speaker 1: do it on the other one. And it's like I

1066
00:54:14,239 --> 00:54:16,279
Speaker 1: used to. I started doing that a couple of years ago,

1067
00:54:16,320 --> 00:54:19,359
Speaker 1: and I'd fucking overbalance and fall, not fall, But you know,

1068
00:54:19,920 --> 00:54:23,160
Speaker 1: and now pretty much I never like it. And my

1069
00:54:23,360 --> 00:54:26,600
Speaker 1: stability and balance is way better than it was three

1070
00:54:26,680 --> 00:54:30,320
Speaker 1: years ago and I'm sixty so but that's just doing

1071
00:54:30,360 --> 00:54:33,360
Speaker 1: those And there's things like you know, It's like sometimes

1072
00:54:33,440 --> 00:54:35,839
Speaker 1: if I'm writing notes on the whiteboard, i'd write with

1073
00:54:35,880 --> 00:54:39,680
Speaker 1: my right hand and I'm left handed. And then if

1074
00:54:39,719 --> 00:54:41,840
Speaker 1: I do that, like sometimes I'll go, I'm only going

1075
00:54:41,880 --> 00:54:43,920
Speaker 1: to write on not when I'm doing my messages for

1076
00:54:44,000 --> 00:54:46,680
Speaker 1: social media, but just when I'm thinking out loud, which

1077
00:54:46,680 --> 00:54:48,719
Speaker 1: I do on the whiteboard a lot. I just use

1078
00:54:48,800 --> 00:54:52,240
Speaker 1: my right hand. And it's amazing how quickly you improve

1079
00:54:52,320 --> 00:54:55,480
Speaker 1: in a matter of days at doing something that's completely

1080
00:54:55,560 --> 00:54:59,080
Speaker 1: atypical for you. Brain plasticity, it's amazing.

1081
00:54:59,320 --> 00:55:03,200
Speaker 2: I think appropriate exception is the ability to predict a

1082
00:55:03,280 --> 00:55:06,240
Speaker 2: fall or to right yourself. But I kind of probably

1083
00:55:06,239 --> 00:55:07,640
Speaker 2: should have looked it up before I said it, but

1084
00:55:07,680 --> 00:55:09,720
Speaker 2: it occurred to me while we're talking, while you were talking.

1085
00:55:09,760 --> 00:55:13,279
Speaker 2: But you can rewrite your brain to be able to

1086
00:55:13,320 --> 00:55:15,440
Speaker 2: work in different ways, whether as you said, you know,

1087
00:55:15,800 --> 00:55:17,200
Speaker 2: I think it's great that you do the left hand

1088
00:55:17,320 --> 00:55:19,880
Speaker 2: right hand thing, but I was also quietly thinking, oh

1089
00:55:19,960 --> 00:55:22,319
Speaker 2: my god, we could be the same person because I

1090
00:55:22,360 --> 00:55:25,400
Speaker 2: stand on one foot to put my shoe on as well,

1091
00:55:25,680 --> 00:55:30,319
Speaker 2: and always tie my shoelacers one foot.

1092
00:55:30,200 --> 00:55:34,399
Speaker 1: We definitely should be married, so you get right out

1093
00:55:34,400 --> 00:55:39,000
Speaker 1: of the way, Tiff. Yeah, but it's that, you know.

1094
00:55:39,080 --> 00:55:41,480
Speaker 1: So there's a guy called Norman Deutsge without trying to

1095
00:55:41,480 --> 00:55:44,080
Speaker 1: sound like a geek, he wrote a book years ago

1096
00:55:44,160 --> 00:55:46,759
Speaker 1: called The Brain That Changes Itself, and he was he

1097
00:55:46,880 --> 00:55:49,280
Speaker 1: was one of the pioneers in this space. He opened

1098
00:55:49,280 --> 00:55:54,439
Speaker 1: the door because forever, until about forty years ago, we

1099
00:55:54,600 --> 00:55:58,440
Speaker 1: thought that the brain you talked about the hippocampus before,

1100
00:55:58,480 --> 00:56:02,719
Speaker 1: which is pretty much like the epicenter of learning and memory, right,

1101
00:56:03,600 --> 00:56:05,840
Speaker 1: and we'd go, ah, well, if you hip a campus

1102
00:56:05,880 --> 00:56:09,000
Speaker 1: as fuck, you won't remember anything anymore. But that's not

1103
00:56:09,080 --> 00:56:12,360
Speaker 1: true because the brain can adopt other roles and you

1104
00:56:12,400 --> 00:56:15,879
Speaker 1: can retrain the brain as you said, which is neural plasticity.

1105
00:56:15,960 --> 00:56:19,440
Speaker 1: But yeah, we used to go, well, this bit of

1106
00:56:19,440 --> 00:56:21,080
Speaker 1: the brain does that, and if that bit of the

1107
00:56:21,080 --> 00:56:25,480
Speaker 1: brain's broken, then you don't have that ability anymore. But yeah,

1108
00:56:25,480 --> 00:56:29,120
Speaker 1: we now know that that's not necessary. It will probably

1109
00:56:29,160 --> 00:56:32,680
Speaker 1: be impaired, but other brains can take over some of

1110
00:56:32,719 --> 00:56:34,960
Speaker 1: the function for one of a better term.

1111
00:56:35,160 --> 00:56:39,400
Speaker 2: It's interesting because there's now there's a lot of focus

1112
00:56:39,680 --> 00:56:43,879
Speaker 2: on teenagers using the internet and being addicted to their

1113
00:56:43,920 --> 00:56:49,120
Speaker 2: phones because of what is happening to their brains during adolescence.

1114
00:56:49,160 --> 00:56:51,239
Speaker 2: We know there's a great lot of formation going on

1115
00:56:51,280 --> 00:56:55,600
Speaker 2: in a teenage brain. So there's a real concern that

1116
00:56:55,680 --> 00:56:59,360
Speaker 2: the use of technology and internet could be impacting the

1117
00:56:59,400 --> 00:57:02,279
Speaker 2: way you know, juvenile development.

1118
00:57:01,840 --> 00:57:06,480
Speaker 1: And particularly adolescent development is progressing. And I think the.

1119
00:57:06,480 --> 00:57:10,920
Speaker 2: Jury's still out, but you know, playing games, using the internet,

1120
00:57:11,160 --> 00:57:15,279
Speaker 2: scrolling away all those things that we see teenagers doing.

1121
00:57:15,440 --> 00:57:19,560
Speaker 2: Everybody does, but saying it could actually be more damaging

1122
00:57:19,640 --> 00:57:22,280
Speaker 2: in an adolescent brain for the pure fact that that's

1123
00:57:22,320 --> 00:57:25,960
Speaker 2: where their brain is doing the most real developmental changes.

1124
00:57:26,360 --> 00:57:29,240
Speaker 1: Well, you know, sixty years ago, what was going to

1125
00:57:29,280 --> 00:57:32,720
Speaker 1: derail the world, what was going to destroy adolescence and

1126
00:57:32,760 --> 00:57:38,280
Speaker 1: the future, was Elvis Presley's hips. So you know, hey, mate,

1127
00:57:38,360 --> 00:57:40,440
Speaker 1: how can people find you and connect with you?

1128
00:57:41,000 --> 00:57:44,400
Speaker 2: Well, websites noow dot com, dot au or ti Chi

1129
00:57:44,640 --> 00:57:47,320
Speaker 2: at home. You know, we still haven't done our virtual

1130
00:57:47,360 --> 00:57:49,320
Speaker 2: tai Chi class Crago. I'm going to take you up

1131
00:57:49,360 --> 00:57:52,360
Speaker 2: on that one again. Can we please do a zoom call?

1132
00:57:52,480 --> 00:57:54,280
Speaker 1: You know what we should do. We should wait till

1133
00:57:54,640 --> 00:57:57,920
Speaker 1: you've got your bloody special studio built. Yeah, okay, you

1134
00:57:57,960 --> 00:57:59,880
Speaker 1: can come up I'll come up for the weekend. We'll

1135
00:58:00,040 --> 00:58:03,880
Speaker 1: boon on the couch and Tiff can make us dinner.

1136
00:58:07,320 --> 00:58:10,240
Speaker 1: That was a joke everyone. If I don't even be there,

1137
00:58:10,280 --> 00:58:12,240
Speaker 1: we wouldn't let her come. It's a man's weekend.

1138
00:58:12,560 --> 00:58:15,240
Speaker 5: I've already got the first DIBs on. We've already talked

1139
00:58:15,280 --> 00:58:18,000
Speaker 5: about yesterday. So you're you're second in line.

1140
00:58:17,760 --> 00:58:20,560
Speaker 3: Bro, We've already organized a date.

1141
00:58:21,800 --> 00:58:23,000
Speaker 4: Wife has come first.

1142
00:58:24,080 --> 00:58:29,800
Speaker 1: Really yeah, okay, thanks everyone, Thanks Thanks Steve.

1143
00:58:30,400 --> 00:58:30,800
Speaker 5: Thanks