Latest / The You Project / #2201 Is AI Bias? - Patrick Bonello

Transcript

#2201 Is AI Bias? - Patrick Bonello · The You Project

• 0:00
  Speaker 1: I get a team. It's quite up. Of course, it
• 0:02
  Speaker 1: is my favorite geek in the world, and not just
• 0:05
  Speaker 1: because he's a geek. I'm in there are other for
• 0:08
  Speaker 1: other reasons I love him, but he's my favorite geek
• 0:10
  Speaker 1: amongst other things. Patrick Jones Bonello is sitting there in
• 0:13
  Speaker 1: front of the lunar landscape or not really is it
• 0:16
  Speaker 1: the earth slant. He's sitting on the moon in front
• 0:18
  Speaker 1: of the Earth. I don't know how he pulls that off,
• 0:23
  Speaker 1: but he is the tech guy. Hi, buddy, how are
• 0:25
  Speaker 1: you good?
• 0:26
  Speaker 2: I just was wondering if maybe you could expand on
• 0:28
  Speaker 2: that list.
• 0:30
  Speaker 1: Why I love you?
• 0:31
  Speaker 2: Yeah, it's just like it's nice.
• 0:33
  Speaker 1: That you show a little bit of self indulgence. Sure, well,
• 0:37
  Speaker 1: you're a man of your word. You mean what you say,
• 0:40
  Speaker 1: and you say what you mean, and you do what
• 0:42
  Speaker 1: you say you're going to do, Like right up high
• 0:45
  Speaker 1: on my list. You didn't expect that I'd actually have
• 0:47
  Speaker 1: an answer, right, Do you know what I love? I
• 0:50
  Speaker 1: love reliability. Ah. I cannot cope with people who say
• 0:55
  Speaker 1: they'll do stuff and don't do it. It fucks me off.
• 0:59
  Speaker 1: I'm like, well, if you're not going to do it,
• 1:00
  Speaker 1: don't say it. You're not that. You're the opposite. You're
• 1:04
  Speaker 1: very reliable, and you're a good human. You're just very
• 1:07
  Speaker 1: You've just got a very You've got a terrible sense
• 1:11
  Speaker 1: of human let's put out that out there. But you've
• 1:13
  Speaker 1: got a beautiful nature and you're very nice.
• 1:16
  Speaker 3: You know when you say reliability, I thought of Toyota.
• 1:19
  Speaker 3: They just go forever, don't they.
• 1:20
  Speaker 1: Toyotas, you are the Corolla of humans. You are. You
• 1:27
  Speaker 1: are the fucking Toyota crown. Remember those in the old
• 1:31
  Speaker 1: days made of mind still go on? Oh God, that
• 1:35
  Speaker 1: you should put that in the bloody Toyota museum. I
• 1:39
  Speaker 1: don't know where tipp is. I should look at the schedule.
• 1:42
  Speaker 1: Who's doing what? Melissa does something not on air anymore.
• 1:46
  Speaker 1: Let's start a thing on start a thing on Facebook,
• 1:50
  Speaker 1: our facebook page. Let's see if we can get one
• 1:53
  Speaker 1: hundred people say they want Melissa back on the podcast,
• 1:56
  Speaker 1: even just for one episode. Do you know how much
• 1:59
  Speaker 1: she would hate me saying this? And if she edits this,
• 2:01
  Speaker 1: she'll probably edit that bit out.
• 2:04
  Speaker 2: How are you, mate? You've got a big thing on Monday,
• 2:06
  Speaker 2: haven't you.
• 2:07
  Speaker 1: I do so as we record it's Friday morning, I
• 2:13
  Speaker 1: submit my thesis. In other words, I hand in all
• 2:16
  Speaker 1: the work that I've done for the last six and
• 2:20
  Speaker 1: a half years in my which is very long. I
• 2:23
  Speaker 1: don't know. Everyone's like how long. I'm like, don't worry
• 2:25
  Speaker 1: that you actually have at Monash, you have up to
• 2:30
  Speaker 1: I mean, you've got to make it work that way,
• 2:32
  Speaker 1: but ten years to do your PhD. But so anyway
• 2:36
  Speaker 1: that goes all the work I've done goes in. So
• 2:39
  Speaker 1: my thesis, which is like basically a book kind of
• 2:45
  Speaker 1: explaining and talking about and reviewing all of the work
• 2:51
  Speaker 1: that you've done, the studies that you've done, the findings
• 2:54
  Speaker 1: of the studies, how you did everything, why you did it,
• 2:57
  Speaker 1: your aims, how it all worked out, blah blah blah.
• 3:01
  Speaker 1: So your actual thesis ends up being a combination of
• 3:06
  Speaker 1: academic papers that you've written for journals. And that's the
• 3:10
  Speaker 1: guts of the book. Let's call it a book. And
• 3:12
  Speaker 1: the front of the book is an intro and aims
• 3:14
  Speaker 1: and overview and synopsis and all that stuff, And at
• 3:17
  Speaker 1: the back is the conclusions and a few different sections
• 3:21
  Speaker 1: like future research where you kind of suggest what might
• 3:24
  Speaker 1: happen in the future. Off the back because of the
• 3:26
  Speaker 1: thing with the PhD in science is you have to
• 3:30
  Speaker 1: bring something new into the world. You can't do what's
• 3:33
  Speaker 1: been done. You can either fill a hole, an academic
• 3:37
  Speaker 1: or a scientific gap, or you can build on some
• 3:41
  Speaker 1: existing research and add something to it, or find something
• 3:47
  Speaker 1: that you think is flawed and correct it. Yeah, but
• 3:51
  Speaker 1: that's it. So that gets handled in Monday, and then
• 3:54
  Speaker 1: it gets sent off to two reviewers. Mine happen to
• 3:58
  Speaker 1: be very high profile experts in the field of meta
• 4:03
  Speaker 1: perception and meta accuracy, which is fucking terrifying. So one
• 4:08
  Speaker 1: is in America and one is in Europe somewhere I
• 4:11
  Speaker 1: can't remember. They look at it, they review it, and
• 4:15
  Speaker 1: then they scribble all over it, over it with a
• 4:18
  Speaker 1: red pen metaphorically. Then it gets sent back to me
• 4:23
  Speaker 1: and then I address the concerns or whatever it is.
• 4:28
  Speaker 1: I mean, it could be very rarely, is it nothing.
• 4:31
  Speaker 1: Usually most PhD students have to redo a part of
• 4:37
  Speaker 1: what they did or you know, like answer some questions
• 4:41
  Speaker 1: or rewrite certain sections, which generally is not months of work,
• 4:46
  Speaker 1: but it could be a month of work. And then
• 4:48
  Speaker 1: that goes finally back to the university who look at
• 4:51
  Speaker 1: the feedback from the review is what you've done to
• 4:53
  Speaker 1: address the feedback and then hopefully they go all right,
• 4:59
  Speaker 1: we'll give you a doctor. Wow.
• 5:01
  Speaker 3: I was thinking of that investment of six years and
• 5:05
  Speaker 3: how it relates to technology. I can guarantee you that
• 5:08
  Speaker 3: the average person out there will.
• 5:10
  Speaker 2: Never have a phone that lasts longer than six years.
• 5:13
  Speaker 3: That'll probably have a laptop that lasts longer than six years.
• 5:16
  Speaker 3: A relationship, A relationship, that's ITD Grade three was the
• 5:20
  Speaker 3: best six years of my life.
• 5:22
  Speaker 1: But remember what I said to you at the show,
• 5:26
  Speaker 1: shit like, but keep working on it.
• 5:30
  Speaker 2: Yeah, you know what I reckon would last six years.
• 5:33
  Speaker 1: Oh, here we go the new e.
• 5:34
  Speaker 2: Bike by Vogswagen. This is so cool.
• 5:38
  Speaker 3: You know, I've seen e bikes and I'm always in
• 5:41
  Speaker 3: two minds about getting an e bike, you know, because
• 5:43
  Speaker 3: I think pedal power and keeping your fitness up. But
• 5:46
  Speaker 3: then having a bike that's got all this amazing technology
• 5:50
  Speaker 3: built into it. That's kind of exciting and cool because
• 5:53
  Speaker 3: it's got driver assisted assisted safety systems built into the bike. Right,
• 5:58
  Speaker 3: So you've got you've got a virtual display like hovering
• 6:02
  Speaker 3: in front of you. So you've got the fighter pilot
• 6:04
  Speaker 3: like hub display, and that gives you driver assistance.
• 6:09
  Speaker 2: So you've got an ability to be able to see
• 6:11
  Speaker 2: turn by turns.
• 6:13
  Speaker 3: The entire bike has an LED strip on it so
• 6:16
  Speaker 3: that when you put the brakes on, the entire bike
• 6:19
  Speaker 3: glows red to let people know. It's just amazing. So
• 6:23
  Speaker 3: the head's up display with turn directions.
• 6:26
  Speaker 2: It's pretty futuristic.
• 6:28
  Speaker 3: And you know, in terms of being on the road
• 6:31
  Speaker 3: and being safe, bikes are pretty hard to see. I mean,
• 6:34
  Speaker 3: whether it's a motorbike or in this case an e bike.
• 6:37
  Speaker 3: You know, safety is a really massive part of that.
• 6:41
  Speaker 3: You know, you've been riding a motorbike for a long
• 6:43
  Speaker 3: time and you must be very conscious that you are
• 6:46
  Speaker 3: a small object relative to a big car and cars
• 6:50
  Speaker 3: a bigger Yeah.
• 6:52
  Speaker 1: Look, do you know what is really funny? This is
• 6:54
  Speaker 1: a little anecdote, Yes, that I would like to when
• 6:58
  Speaker 1: I finish here and after my next meeting, I'm going
• 7:01
  Speaker 1: to go and have a look at that bike as
• 7:03
  Speaker 1: I have an online kind of peruse you.
• 7:07
  Speaker 2: It's also got that I thought is amazing.
• 7:08
  Speaker 3: It's also got an integrate a crash detection system that
• 7:11
  Speaker 3: calls people if it detects that you've had a crash.
• 7:14
  Speaker 2: So it's got a.
• 7:14
  Speaker 3: Special smart helmet built into it and if something happens,
• 7:18
  Speaker 3: it will call and raise the alarm for you.
• 7:22
  Speaker 1: Yeah, I'm a little bit. I'm a bit mixed on it.
• 7:26
  Speaker 1: I'm not sure like they definitely they're cool. Yeah, I
• 7:32
  Speaker 1: just like where I live. I see a lot of kids.
• 7:35
  Speaker 1: So I think the power limit in Australia, if I'm
• 7:39
  Speaker 1: not right, it's going to be close, is eight hundred watts.
• 7:43
  Speaker 1: That's the end. I think they're governed or the limit
• 7:47
  Speaker 1: is twenty five kilometers an hour. So if you think
• 7:51
  Speaker 1: one killer what that is? That's what powering cars is
• 7:55
  Speaker 1: measured in killer wot's horsepower in the old days killerbats now,
• 7:58
  Speaker 1: so one killerbot is one thousand watts, so eight hundred
• 8:01
  Speaker 1: watts is less than one killer watt obviously, but they
• 8:06
  Speaker 1: are they are tuning these bikes up to five and
• 8:10
  Speaker 1: eight thousand watts, which is five killer watts eight killer watts.
• 8:14
  Speaker 1: Now an eight killerwat bike, which weighs even a heavy
• 8:20
  Speaker 1: heavy electric bike is probably twenty k's right, I'd have
• 8:25
  Speaker 1: to check that this bro science here. Those things accelerate
• 8:29
  Speaker 1: faster than cars, like literally faster than cars because there's
• 8:34
  Speaker 1: no lag. And so I see kids up and down
• 8:38
  Speaker 1: the streets monoing on these high power electric bikes really yeah,
• 8:43
  Speaker 1: oh yeah, yeah, it's just that that worries me. But
• 8:46
  Speaker 1: as a concept, I think they're great. I think for
• 8:51
  Speaker 1: people as they age, I think the option who maybe
• 8:56
  Speaker 1: don't have the strength and the fitness they once had,
• 8:58
  Speaker 1: but they still want to get out on a bike.
• 9:01
  Speaker 1: I think to be able to have the option of
• 9:02
  Speaker 1: pedal or have a little bit of electric assistance, I
• 9:06
  Speaker 1: think it's great. I think great.
• 9:08
  Speaker 3: And also from an eco perspective, if you can use
• 9:10
  Speaker 3: that instead of jumping into your car for little schools
• 9:13
  Speaker 3: around town. It is going to cost you about seven thousand,
• 9:17
  Speaker 3: seven hundred dollars plus another nine hundred and sixty for
• 9:20
  Speaker 3: the helmet, so a good comfortable nearly what eight and
• 9:23
  Speaker 3: a half thousand dollars.
• 9:24
  Speaker 1: Yeah, that's crazy. It's that you can go. You can
• 9:27
  Speaker 1: go and buy a scooter for the road for half
• 9:29
  Speaker 1: that price. Yeah, that's an actual registered vehicle. But you know,
• 9:35
  Speaker 1: if you've got no financial restrictions. You know, one thing
• 9:39
  Speaker 1: that you said which you probably have never thought of.
• 9:43
  Speaker 1: I know you've been on the back of my motorbike.
• 9:45
  Speaker 1: So what are my motorbikes or two my motorbikes are
• 9:48
  Speaker 1: very big. One of them's got I probably shouldn't say
• 9:53
  Speaker 1: too much on a public forum, but let's just say
• 9:57
  Speaker 1: it's quite loud. Let's just say. And when I'm riding that,
• 10:03
  Speaker 1: and it's gigantic, and I ride, you're allowed a lane split,
• 10:08
  Speaker 1: which means when the traffic stopped, you can ride between
• 10:11
  Speaker 1: the cars legally to get to the front. When I
• 10:14
  Speaker 1: ride through on my little shitty scooter, which is worth
• 10:17
  Speaker 1: about nine dollars and goes about thirteen kilometers an hour,
• 10:20
  Speaker 1: when I ride through the traffic on that, nobody notices you.
• 10:23
  Speaker 1: Nobody gives it fuck, and if they do, they might
• 10:26
  Speaker 1: even open their door on you. Right. But when you
• 10:28
  Speaker 1: ride that large loud thing, people pull their car away
• 10:34
  Speaker 1: from even if they're sitting parked, they kind of pull
• 10:37
  Speaker 1: their steering wheel away from where you're going to go through.
• 10:40
  Speaker 1: And I get treated completely differently by fellow motorists if
• 10:48
  Speaker 1: I'm on the little shitty scooter or the big loud motorbike.
• 10:51
  Speaker 3: Can I just say, though, as a driver, I think
• 10:55
  Speaker 3: that is because they're more aware of you because of
• 10:58
  Speaker 3: the sound, not because the size of the bike. If
• 11:01
  Speaker 3: I ever see a cyclist, if I see a motorbike.
• 11:04
  Speaker 3: I will always move across to give them more room
• 11:08
  Speaker 3: between me and the car next to me. So I
• 11:10
  Speaker 3: think it's more of an awareness thing rather than you
• 11:12
  Speaker 3: intimidating people by the size of the thing between your legs.
• 11:16
  Speaker 1: Yeah, well, I mean there's that who could chew. I'm
• 11:21
  Speaker 1: not even going to acknowledge it. I just did. Well,
• 11:24
  Speaker 1: I'm going to tell you that may be true, but
• 11:26
  Speaker 1: it's also true that if I'm sitting on that bike
• 11:29
  Speaker 1: at the lights and there's a car next to me,
• 11:31
  Speaker 1: generally they will not look at you. They will not
• 11:35
  Speaker 1: look at you if I'm on the scooter that open
• 11:38
  Speaker 1: the window and throw an orange at your head. Right,
• 11:41
  Speaker 1: It's like it's a totally different vibe. Anyway, I saw
• 11:46
  Speaker 1: on the news. I saw on the news the other
• 11:49
  Speaker 1: night this story that BYD delivered a bunch of cars
• 11:54
  Speaker 1: plated with the wrong years. So they were plated twenty
• 11:56
  Speaker 1: twenty six, but they actually produced in twenty twenty.
• 11:59
  Speaker 3: Five, ups one than two hundred and sixty five. Customers
• 12:04
  Speaker 3: in Australia had bought cars thinking they were the current model,
• 12:08
  Speaker 3: the twenty twenty six model, and in fact they were
• 12:10
  Speaker 3: the previous years. They were offered a compensation of eleven
• 12:13
  Speaker 3: hundred bucks. Sorry about that. Here's eleven hundred dollars compensation. Yeah,
• 12:17
  Speaker 3: they didn't wash went to the A Triple C and
• 12:20
  Speaker 3: you know, the Australian Competition and Consumer Commission.
• 12:23
  Speaker 2: And they've done a backflip obviously on this.
• 12:26
  Speaker 3: But that would be I'd be pretty peeved if I was,
• 12:28
  Speaker 3: you know one of those customers, wouldn't you?
• 12:31
  Speaker 1: I would, I would. I mean, I'd be peeved. I'd
• 12:34
  Speaker 1: be way more ap peeved if they knew. I think
• 12:37
  Speaker 1: they didn't know. I think the dealers didn't know because,
• 12:42
  Speaker 1: like to them, they were plated that year. But I
• 12:44
  Speaker 1: will say one, what they've done is the right thing
• 12:47
  Speaker 1: to do, so I'm with you. But two, those twenty
• 12:51
  Speaker 1: five and twenty six they're not a different model. They're
• 12:54
  Speaker 1: just a different year of MANUF. They're exactly the same car.
• 12:57
  Speaker 1: There is no change. Yeah, you don't want to when
• 13:01
  Speaker 1: you go to sell it in two thousand and thirty,
• 13:04
  Speaker 1: you've got a four versus a five year old car.
• 13:07
  Speaker 1: Of course you want a four year old car to sell.
• 13:10
  Speaker 2: Yeah, now that's a fair call.
• 13:13
  Speaker 3: Have you ever thought about or had issues with plugging
• 13:17
  Speaker 3: in a USB cable to either transfer data or to
• 13:21
  Speaker 3: charge your phone or anything like that. I think it's
• 13:23
  Speaker 3: one of the things that a lot of us don't
• 13:25
  Speaker 3: think about, but the quality of the cable can actually
• 13:28
  Speaker 3: impact how long it takes to recharge your device or.
• 13:32
  Speaker 2: How we data gets transferred across.
• 13:35
  Speaker 3: Yeah, there are shitty USB cables out there, and there
• 13:37
  Speaker 3: are good USB cables out there, and.
• 13:40
  Speaker 2: Trying to make sure you've got the right one.
• 13:41
  Speaker 3: So generally, when you purchase a phone, if you use
• 13:44
  Speaker 3: that same cable with the phone, then you can to
• 13:47
  Speaker 3: have the right compatibility.
• 13:49
  Speaker 2: But that can actually make a big difference.
• 13:51
  Speaker 3: So sometimes I've got an old pair of headphones that
• 13:54
  Speaker 3: won't even charge if you plug, even though it's exactly
• 13:58
  Speaker 3: the same cable in terms of the USB c but
• 14:01
  Speaker 3: it will charge, and list I use only one single
• 14:04
  Speaker 3: cable in my house will charge the headphones.
• 14:08
  Speaker 1: I never thought of that. That is really interesting because
• 14:11
  Speaker 1: I don't know a few months ago, I went to
• 14:14
  Speaker 1: buy one of them table for the old iPhone and
• 14:19
  Speaker 1: there were literally ones that were six dollars and ones
• 14:22
  Speaker 1: that were forty yep, And I'm like, there's got to
• 14:26
  Speaker 1: be a reason why that's six dollars, and that's forty dollars,
• 14:30
  Speaker 1: so I bought the forty dollars one. It was like
• 14:32
  Speaker 1: it was quite long, but it was like almost made
• 14:35
  Speaker 1: of this cord, this metal cord almost. It was like yeah,
• 14:41
  Speaker 1: And you know with the plastic coated ones, they they
• 14:45
  Speaker 1: break and the fibers, the metal fibers inside just fray
• 14:50
  Speaker 1: and break. So and I'd had that happen a bunch
• 14:52
  Speaker 1: of times.
• 14:53
  Speaker 3: I've got an iPad air and it's with the original
• 14:57
  Speaker 3: iPad air.
• 14:57
  Speaker 2: So it came out with Noah on the arc. There
• 14:59
  Speaker 2: were two them. I don't know what happened to the same,
• 15:01
  Speaker 2: right we got.
• 15:02
  Speaker 1: One of the other ones was that when he was
• 15:03
  Speaker 1: keeping an inventory of the animals.
• 15:05
  Speaker 2: He was using a tablet?
• 15:06
  Speaker 1: Yeah, or was that Missus Noah? Was Missus Noah's name?
• 15:10
  Speaker 1: I should know that. No, you think I'm half a
• 15:13
  Speaker 1: biblical scholar.
• 15:14
  Speaker 3: I wonder why I was ready to throw it away
• 15:17
  Speaker 3: and I only use it to fly my drone because
• 15:19
  Speaker 3: it doesn't even connect to Wi Fi anymore. And then
• 15:21
  Speaker 3: I went to my local jcar and said, how come
• 15:24
  Speaker 3: this isn't charging? And they said, oh, because blah blah
• 15:27
  Speaker 3: blah blah blah. They gave me the right power supply
• 15:29
  Speaker 3: plus the right cable. They took a whole stack out
• 15:32
  Speaker 3: of the plastic wrap to make sure they were. Isn't
• 15:35
  Speaker 3: it great when you can go to a shop like that.
• 15:37
  Speaker 3: So he tested all these different cables, all these different
• 15:40
  Speaker 3: power supplies, matched them up, and now it works and
• 15:42
  Speaker 3: charges properly.
• 15:44
  Speaker 1: Well, that's that's good old fashioned country service, isn't it great? Yeah? Yeah,
• 15:49
  Speaker 1: it's like you know when you walk into Nelli every
• 15:51
  Speaker 1: store and they go good.
• 15:52
  Speaker 2: I Patrick, Yeah, that's exactly where I live.
• 15:56
  Speaker 3: But that means then that if you have got a
• 15:58
  Speaker 3: device that's not charging properly, it may just be as
• 16:01
  Speaker 3: simple as the cable being replaced.
• 16:03
  Speaker 1: All right, look into that folks. Yeah, Google, and you
• 16:09
  Speaker 1: see you see San Diego Pilot cloud server clusters powered
• 16:14
  Speaker 1: by retired smartphones. I don't even know what that means.
• 16:18
  Speaker 1: What does that mean?
• 16:19
  Speaker 2: Yeah? This is interesting.
• 16:20
  Speaker 3: I thought this was fascinating because we retire phones all
• 16:23
  Speaker 3: the time and throw away technology all the time, and so.
• 16:27
  Speaker 1: Why are we using the word retire.
• 16:29
  Speaker 2: Well, because don't dump them. You chuck them in the rubbish.
• 16:35
  Speaker 1: We don't say I retired that old chair. Oh you
• 16:38
  Speaker 1: mean you threw it out? Yeah, it's not a fucking human.
• 16:42
  Speaker 1: It doesn't retire. It's not now, it's sitting on the
• 16:46
  Speaker 1: couch watching Oprah eating cake. They don't retire. They get
• 16:52
  Speaker 1: disposed of retired smartphones. Oh that's that's Dave over there,
• 16:58
  Speaker 1: the smartphone with the silver hair, the frosty reading the paper.
• 17:03
  Speaker 3: Taking the innerds of two thousand retired pixel phones and
• 17:08
  Speaker 3: the they're going to create a data center out of it,
• 17:12
  Speaker 3: you know, because there's all this controversy at the moment
• 17:14
  Speaker 3: about resources that go into making data centers.
• 17:17
  Speaker 2: Data centers are the I guess, the.
• 17:19
  Speaker 3: Brain of the cloud, you know, all the cloud computing
• 17:23
  Speaker 3: that gets done somewhere somewhere at a giant data center.
• 17:26
  Speaker 3: And so if you can upscale, upcycle, recycle a whole
• 17:31
  Speaker 3: lot of old phones, and they call unicycle, Yeah, unicycle.
• 17:36
  Speaker 3: So it's called phone cluster computing. And it means they
• 17:41
  Speaker 3: take all the the core out of each of the
• 17:44
  Speaker 3: phones and then they put them all together. It means
• 17:47
  Speaker 3: low carbon, the racks aren't using as much heat and
• 17:51
  Speaker 3: it's more eco friendly using this old tech.
• 17:56
  Speaker 1: Well that's way better if we can recycle and reper
• 18:00
  Speaker 1: reuse and not I have to use more new resources.
• 18:06
  Speaker 1: So that's a good thing. Yeah, I still don't really
• 18:09
  Speaker 1: understand it, but that's okay. How isn't that the thing
• 18:14
  Speaker 1: that they're talking about at the moment in terms of AI,
• 18:19
  Speaker 1: like the overwhelm of energy that needs to go into
• 18:23
  Speaker 1: these data centers to make AI happen, especially at the
• 18:28
  Speaker 1: rate that it's evolving, and they're building like a monash.
• 18:32
  Speaker 1: I think I could be wrong. They're building a data
• 18:36
  Speaker 1: center and it's like it was on the news the
• 18:39
  Speaker 1: other night. I think that requires something like a million
• 18:43
  Speaker 1: liters of water to cool it a day or some
• 18:46
  Speaker 1: crazy I'm like, what and where does that go? And
• 18:50
  Speaker 1: can we reuse that water?
• 18:52
  Speaker 3: And there are some towns in the United States, I
• 18:55
  Speaker 3: know California is one of the leading cities and one
• 18:58
  Speaker 3: of the leading areas. Is that they basically saying we
• 19:01
  Speaker 3: don't want data centers.
• 19:02
  Speaker 2: We don't.
• 19:03
  Speaker 3: I mean, that's easy to say, I don't want a
• 19:05
  Speaker 3: data center in my area. But I bet you they're
• 19:06
  Speaker 3: still using AI on their phones in their computers. I
• 19:10
  Speaker 3: wonder whether AI has become the catchphrase that every manufacturer
• 19:15
  Speaker 3: has to incorporate in some way or another. I bought
• 19:18
  Speaker 3: some really lovely smart globe lights to hang outside.
• 19:22
  Speaker 2: So it's a.
• 19:23
  Speaker 3: String of lights a bit like Christmas tree lights, I guess.
• 19:25
  Speaker 3: And there are fifteen of these spheres that light up
• 19:28
  Speaker 3: and you can change the colors. But it even has
• 19:30
  Speaker 3: an AI mode and I thought, oh, this is a
• 19:33
  Speaker 3: bit wanky, and so you can prompt it and I said, well,
• 19:36
  Speaker 3: I want my lights to mimic an Aurora borealis. And
• 19:40
  Speaker 3: it came back with this role with this result. So
• 19:43
  Speaker 3: we'll go from a nice blue glow to a green
• 19:46
  Speaker 3: glow and then flashes of other colors like what. So
• 19:49
  Speaker 3: it used AI to generate this color pattern, which sounded
• 19:55
  Speaker 3: fun and it was a bit of a play. And
• 19:57
  Speaker 3: I thought, now, how many leaders of water is that
• 19:59
  Speaker 3: prompt just used? You know, just the fact that AI
• 20:03
  Speaker 3: is in everything.
• 20:04
  Speaker 1: Now, Yeah, you know what's even weirder is that you
• 20:08
  Speaker 1: fucking thought of that prompt. You and your you came
• 20:13
  Speaker 1: up with that in your head to do with your
• 20:14
  Speaker 1: hanging kind of Christmas lights. Yeah, to create some kind
• 20:18
  Speaker 1: of cosmic pattern what goes on in there in my
• 20:24
  Speaker 1: oh god knows book publishers sue Google over alleged copyright
• 20:31
  Speaker 1: infringement in Gemini AI training.
• 20:34
  Speaker 3: Yeah, this has really become a sticking point with all
• 20:37
  Speaker 3: these large language learning models.
• 20:39
  Speaker 2: Lots of l's in that.
• 20:41
  Speaker 3: So, yes, these data sets that are used to train
• 20:44
  Speaker 3: a I have become controversial because of the source information.
• 20:49
  Speaker 3: And now all these publishers say are saying, well, wait
• 20:51
  Speaker 3: a minute, We've got all these best selling authors, people
• 20:54
  Speaker 3: who've published in books, and that's what they're training the
• 20:59
  Speaker 3: large learn model on and without any any sort of compensation,
• 21:04
  Speaker 3: without any permission, And this is what's going to court
• 21:07
  Speaker 3: now in the United States. So we're talking figures of
• 21:11
  Speaker 3: fines of up to ten to one hundred billion dollars
• 21:15
  Speaker 3: is what.
• 21:15
  Speaker 2: They're trying to push for.
• 21:17
  Speaker 3: I mean, at the end of the day, companies like
• 21:18
  Speaker 3: Google and Apple a trillion dollar companies, So you know,
• 21:22
  Speaker 3: a million dollar fine and a slap on the hand
• 21:24
  Speaker 3: is going to do nothing. But that said, I mean,
• 21:27
  Speaker 3: where do we go from here. It's an interesting one
• 21:29
  Speaker 3: to keep tabs on. And it comes down to, I mean,
• 21:32
  Speaker 3: if you think of all the work that's gone into
• 21:34
  Speaker 3: the research that you're going to submit on Monday, you know,
• 21:36
  Speaker 3: all the work and effort, and you know, anybody who
• 21:40
  Speaker 3: authors anything, anybody who creates something from nothing in their head,
• 21:45
  Speaker 3: as an author to then have an AI rip it
• 21:49
  Speaker 3: all off. I can get that. I absolutely would be
• 21:52
  Speaker 3: pretty peeped off if I was one of those authors.
• 21:55
  Speaker 1: Hey, I'm yeah, I agree with you. I'm I just
• 21:59
  Speaker 1: thought of something while you were talking that I've got
• 22:02
  Speaker 1: some news for you. I've got some AI news for you. Okay,
• 22:06
  Speaker 1: all right, So I'm going to break a story on
• 22:09
  Speaker 1: your show. So last night, Spotify deleted seventy five million
• 22:17
  Speaker 1: AI songs so that they call it AI slop. But
• 22:22
  Speaker 1: some of the songs are fucking amazing. I got to say, yea.
• 22:25
  Speaker 1: But yeah, so if you just go Spotify, AI music
• 22:29
  Speaker 1: deletion in your search thingy. So they decided that I
• 22:35
  Speaker 1: imagine they're only having actual artists and streaming giant Spotify
• 22:40
  Speaker 1: has deleted over seventy five million tracks as it comes
• 22:43
  Speaker 1: under fire from an industrial scale wave of artificial intelligence,
• 22:53
  Speaker 1: as it faces a revolution that's changing music as we
• 22:59
  Speaker 1: know it as hang on. As AI giants make it
• 23:03
  Speaker 1: increasingly easy to make fake music, it is piling huge
• 23:07
  Speaker 1: pressure on services like Spotify and the systems they use
• 23:10
  Speaker 1: to pay real artists. Yeah, so that's interesting because that's
• 23:16
  Speaker 1: actually some of the AI music. I mean if you
• 23:20
  Speaker 1: didn't know it was AI. But if you take that
• 23:22
  Speaker 1: kind of moral which I understand judgment into it, you're like, ah,
• 23:27
  Speaker 1: fuck this. But if you didn't know it was AI,
• 23:29
  Speaker 1: you're like, this is amazing.
• 23:31
  Speaker 3: Anyway, Off gone, It's seventy five million what they call
• 23:35
  Speaker 3: low effort tracks.
• 23:36
  Speaker 2: I think you know.
• 23:37
  Speaker 3: There's two aspects to this that kind of struck me
• 23:40
  Speaker 3: when you mentioned that. One is the fact that artists,
• 23:44
  Speaker 3: like we were talking previously about the authors, put their
• 23:48
  Speaker 3: heart and soul into writing music or writing verse or
• 23:52
  Speaker 3: pros whatever it is that they're creating. They're building something
• 23:56
  Speaker 3: that's the innate ability for human beings to create something
• 23:59
  Speaker 3: for nothing, which is magical, and.
• 24:01
  Speaker 2: So to see this slop proliferate. That's one aspect.
• 24:07
  Speaker 3: But the second thing is if you're a Spotify subscriber
• 24:11
  Speaker 3: and you're paying money to listen to songs and then
• 24:14
  Speaker 3: using the algorithm of Spotify to find other tracks that
• 24:18
  Speaker 3: you might like, I'm fir I'm feeling ripped off if
• 24:21
  Speaker 3: it's then churning out this AI slop. I want to
• 24:25
  Speaker 3: listen to music that's been created by a real person,
• 24:29
  Speaker 3: that is sung by a real person. I've been in
• 24:31
  Speaker 3: a choir for a couple of years now and it's
• 24:34
  Speaker 3: really fun. And I know how hard it is to
• 24:37
  Speaker 3: sing in tune, you know, I know how happy it
• 24:40
  Speaker 3: is and how hard now I mean that I.
• 24:41
  Speaker 1: Really do, you know, I want to see the evidence
• 24:44
  Speaker 1: of in tune.
• 24:45
  Speaker 3: Actually, I told you that we were part of a
• 24:48
  Speaker 3: reconciliation song that we sang, and we were part of
• 24:51
  Speaker 3: a number of choirs around Australia. Yeah, anyway, Beds of
• 24:54
  Speaker 3: Burning was the song that we sang for Reconciliation Week
• 24:58
  Speaker 3: and I think we're over five hundred QUI around Australia
• 25:01
  Speaker 3: and we were one of forty or fifty that got
• 25:03
  Speaker 3: to be in the video clip. I mean it was
• 25:05
  Speaker 3: only two and a half or three seconds, but we
• 25:07
  Speaker 3: were there. But coming back to it is, Yeah, the
• 25:11
  Speaker 3: authenticity of the creative process is what I want my
• 25:16
  Speaker 3: algorithm to pick up on.
• 25:17
  Speaker 2: And I want real songs by real artists with real voices.
• 25:21
  Speaker 1: What about people who aren't you, though, and they want it?
• 25:24
  Speaker 2: Well, look, I guess you just need to be you
• 25:27
  Speaker 2: need to be.
• 25:27
  Speaker 3: Really clear that what you want is non AI generated content.
• 25:33
  Speaker 3: And that's the same when you're searching on the internet.
• 25:35
  Speaker 1: But I'm saying. I'm saying, like, Okay, here's the thing.
• 25:39
  Speaker 1: If you didn't know, like, you would never pick this
• 25:42
  Speaker 1: is AI. I mean, these are voices instruments. It's incredible
• 25:46
  Speaker 1: some of it. And I understand the emotion and the indignation.
• 25:51
  Speaker 1: I get all of that. But then we'll use AI
• 25:54
  Speaker 1: in a million other ways. You know, where where copywriters
• 25:59
  Speaker 1: are being put out a bit business. You know, there
• 26:00
  Speaker 1: are lots of people who are not going to have
• 26:03
  Speaker 1: a job. They'll have to have a different job or
• 26:05
  Speaker 1: a different version of the same job. And there's all
• 26:07
  Speaker 1: this ethical moral, kind of psychological sociological soup of is
• 26:13
  Speaker 1: this good, is this bad? Is this is this you know,
• 26:17
  Speaker 1: morally correct or not? And I get all of that.
• 26:20
  Speaker 1: But if there's a beautiful painting, is a beautiful painting
• 26:25
  Speaker 1: and you love it and you think it's fucking amazing, breathtaking,
• 26:29
  Speaker 1: and then you find out it wasn't done by a human,
• 26:32
  Speaker 1: it's still the same painting. Now you're just looking through
• 26:35
  Speaker 1: a different lens. And this is like and again I
• 26:39
  Speaker 1: totally understand from the musician's perspective, and them taking it
• 26:44
  Speaker 1: down doesn't bother me one bit. It is what it is.
• 26:48
  Speaker 1: But I think moving forward. You know, there's you're never
• 26:53
  Speaker 1: going to be able to a machine. AI can never
• 26:56
  Speaker 1: replace the creativity of a human. All those AIS that
• 27:01
  Speaker 1: are being the songs like they're created in a way
• 27:04
  Speaker 1: by humans anyway. But yeah, I just don't know that
• 27:11
  Speaker 1: you can kind of pick and choose, or that it
• 27:14
  Speaker 1: makes sense to alleviate it from one field but not
• 27:19
  Speaker 1: another where people are being impacted all round anyway, you know. So,
• 27:25
  Speaker 1: But you know, my favorite music will always be human created,
• 27:29
  Speaker 1: not AI generated. But I don't know. I just think
• 27:33
  Speaker 1: just because I don't like it or you don't like it,
• 27:35
  Speaker 1: that doesn't mean that's how it should be. Not everyone
• 27:38
  Speaker 1: needs to agree with you or think like you or
• 27:41
  Speaker 1: sing in a choir. That's cool. I'm on board. Like
• 27:45
  Speaker 1: there are lots of things that I do not like
• 27:47
  Speaker 1: that I think should be in existence, Like who the
• 27:51
  Speaker 1: fuck am I to determine what should be available to
• 27:54
  Speaker 1: the world just because I hate certain things. I still
• 27:58
  Speaker 1: think people should be able to choose those if they want. Like,
• 28:02
  Speaker 1: nobody's being duped all of those AI songs, it's evident.
• 28:09
  Speaker 3: Yeah, well then they haven't existed before, but they're based
• 28:13
  Speaker 3: on other songs, and that's where the creative process, I guess,
• 28:17
  Speaker 3: or the artificial creative processes come from. I'm thinking that
• 28:20
  Speaker 3: what I was trying to think about is a comparison.
• 28:22
  Speaker 3: If you took ten hand drawn pictures of elephants and
• 28:27
  Speaker 3: you plugged it into a large learning model and said,
• 28:30
  Speaker 3: now draw me an elephant, then all it can go
• 28:32
  Speaker 3: by is the ten elephants that it's learned from, and
• 28:36
  Speaker 3: it will use those. So the creative process really is
• 28:39
  Speaker 3: just a sampling of those ten elephants. Now, I took
• 28:43
  Speaker 3: a group of primary school kids and we went to
• 28:45
  Speaker 3: the zoo and we looked at an elephant, and then
• 28:47
  Speaker 3: we went back to the classroom and said, now draw
• 28:50
  Speaker 3: an elephant.
• 28:51
  Speaker 2: Then they're going to draw something that's in their memory
• 28:54
  Speaker 2: from what they've actually seen, and every result is going
• 28:57
  Speaker 2: to be different with every single one of those children.
• 29:00
  Speaker 1: One hundred percent. But both of those things can coexist.
• 29:04
  Speaker 2: They can. Yeah, But I think that we need to
• 29:06
  Speaker 2: label them as such.
• 29:08
  Speaker 1: I think they are like you can tell on in
• 29:13
  Speaker 1: like I've got a couple of AI songs that I
• 29:15
  Speaker 1: use as background music for ig posts. They're fucking amazing.
• 29:20
  Speaker 1: But it's not a person, it's not a band. It's
• 29:22
  Speaker 1: not a singer, it's not an artist.
• 29:25
  Speaker 2: Yeah.
• 29:26
  Speaker 1: But in your defense, though, Patrick James, I will say
• 29:31
  Speaker 1: there have been I might be I might be arguing
• 29:35
  Speaker 1: against myself here, but I just do recall that there
• 29:38
  Speaker 1: have been make up artists or pretend, not pretend, fabricated
• 29:44
  Speaker 1: artists who they give a name and then yeah, you
• 29:48
  Speaker 1: don't know that that's actually AI. That I do not
• 29:51
  Speaker 1: agree with. I think if it's going to be AI,
• 29:55
  Speaker 1: you know, it's like the cigarettes. If it can give
• 29:57
  Speaker 1: you cancer, write that shit all over the front of
• 29:59
  Speaker 1: the cigarettes. And then if people still want to buy that,
• 30:02
  Speaker 1: knowing that it can kill you off you go. You know, yeah,
• 30:07
  Speaker 1: So I go.
• 30:08
  Speaker 2: Two words. Millie Vanilli.
• 30:13
  Speaker 1: Now there's a bunch of people listening.
• 30:15
  Speaker 2: Who don't know about Can you explain? You got to explain.
• 30:18
  Speaker 1: So Milli Vanilli were a band, I'm going to say
• 30:21
  Speaker 1: in the nineties. They were, in fact a duo who
• 30:24
  Speaker 1: both looked very cool. They are both you know, super
• 30:28
  Speaker 1: good look and crazy hair, like you know, pop culture
• 30:32
  Speaker 1: one oh one, and they they sold millions of records.
• 30:37
  Speaker 1: They were world famous, and then one day the world
• 30:42
  Speaker 1: discovered that they weren't the actual singers. They were just
• 30:45
  Speaker 1: two performers lip syncing someone else's songs and lip syncing
• 30:51
  Speaker 1: to someone else's voice. The motherfuckers couldn't even sing, which like,
• 30:57
  Speaker 1: what a great scam, what a great story. I mean,
• 30:59
  Speaker 1: bit shit at the time, But yeah, that is actually
• 31:03
  Speaker 1: a good recall by you. I love that story. But
• 31:07
  Speaker 1: you know that's interesting. That's not totally dissimilar to what
• 31:11
  Speaker 1: we're talking about, where people thought they were listening to
• 31:15
  Speaker 1: these two dudes that were handsome and charismatic and whatever,
• 31:19
  Speaker 1: and their experience was real. Oh, I love Millie Vanelli.
• 31:24
  Speaker 1: They sound great, great songs, great voices, you know, great
• 31:28
  Speaker 1: fucking celebrities whatever. It's like, nah, dude, it's all smoke
• 31:32
  Speaker 1: and mirrors.
• 31:33
  Speaker 3: But I want to know what about the actual blokes
• 31:35
  Speaker 3: who were singing it? Were they just but ugly and
• 31:37
  Speaker 3: didn't want to put them on stage.
• 31:39
  Speaker 1: Well, we can tell the world now. We can probably
• 31:42
  Speaker 1: let them know the world that it was actually Patrick
• 31:44
  Speaker 1: and Craig. We were just too fucking too bloody old
• 31:52
  Speaker 1: desert boots belding out a song, and you know, they
• 31:54
  Speaker 1: wouldn't give us the gig, so we got these fell
• 31:56
  Speaker 1: ins story.
• 32:01
  Speaker 3: While we're talking about you know what's happening with AI.
• 32:05
  Speaker 3: There's a really interesting article that's been put out that
• 32:08
  Speaker 3: kind of suggests that a lot of AI has Western
• 32:14
  Speaker 3: moral perspectives. So it basically, these large language models prioritize
• 32:19
  Speaker 3: Western morals and perspectives.
• 32:21
  Speaker 2: So because they're.
• 32:22
  Speaker 3: Built on our Western values and Western literature and all
• 32:26
  Speaker 3: the rest of it, it means that there's a bit
• 32:27
  Speaker 3: of a divide because there's now a bias towards the
• 32:31
  Speaker 3: Western viewpoints in the Western way of life.
• 32:35
  Speaker 1: So here's what I think about that. If it's built
• 32:38
  Speaker 1: by people living in the West and all, it's all
• 32:41
  Speaker 1: the majority of its kind of data comes from that
• 32:45
  Speaker 1: kind of information portals, et cetera, that's understandable. I'm not
• 32:53
  Speaker 1: saying it's good. I wonder if the same is true.
• 32:57
  Speaker 1: You know, like what's India India, what's China? One point
• 33:00
  Speaker 1: four billion, Indias over a billion, so there's probably two
• 33:05
  Speaker 1: and a half billion people. I bet there llms aren't
• 33:10
  Speaker 1: sharing a uniquely Western moral perspective. I think maybe over
• 33:16
  Speaker 1: here in the West that's true. But it's kind of
• 33:18
  Speaker 1: understandable because it's built by us for us primarily, I guess,
• 33:24
  Speaker 1: But then I could be wrong, but I would think
• 33:26
  Speaker 1: that would I would think in you know, the East,
• 33:29
  Speaker 1: there would be a moral kind of slant that way. Well,
• 33:33
  Speaker 1: I would, I guess.
• 33:35
  Speaker 3: But we've got to think of these large corporates that
• 33:37
  Speaker 3: proliferate the entire world. And if you've got smaller countries, Okay,
• 33:42
  Speaker 3: you can talk about China having its own AI and
• 33:44
  Speaker 3: building its own models, but there are a lot of
• 33:46
  Speaker 3: smaller countries that couldn't afford to do that, and they're
• 33:49
  Speaker 3: not Western and they are still adopting Western technology, so
• 33:54
  Speaker 3: they're now being underrepresented. So all the Pacific nations think
• 33:58
  Speaker 3: about those.
• 34:00
  Speaker 1: It's understandable though, Like I'm not saying it's good, but
• 34:04
  Speaker 1: I'm just going, yeah, of course, what are the Solomon
• 34:06
  Speaker 1: Islands going to do? You know? And they But it's
• 34:09
  Speaker 1: like I think we think that that people who build
• 34:15
  Speaker 1: all this chat stuff have some kind of innate moral compass. No,
• 34:22
  Speaker 1: their job is to make money.
• 34:23
  Speaker 2: Just go.
• 34:24
  Speaker 1: Of course that's what they do. Do you think companies
• 34:27
  Speaker 1: give a fuck about anything? Most companies other than shareholders
• 34:31
  Speaker 1: in the bottom line, No, I think you need to
• 34:34
  Speaker 1: expect companies that are built for profit to do what
• 34:38
  Speaker 1: companies that are built for profit to do.
• 34:41
  Speaker 3: Now, I think what The underlying part of this research though,
• 34:44
  Speaker 3: was looking at the applications of AI and say things
• 34:47
  Speaker 3: like health technology. So if you're using AI and health
• 34:50
  Speaker 3: technology and then you're deploying that health technology in a
• 34:54
  Speaker 3: country where there is a bias, So okay, what about
• 34:57
  Speaker 3: b and I body mass index? If you TUK someone
• 34:59
  Speaker 3: from the so Hormon Islands and someone from Australia and
• 35:03
  Speaker 3: then BMI potentially because and people's bodies adapt to the culture.
• 35:09
  Speaker 3: I think there's some people who can survive purely on
• 35:11
  Speaker 3: meat almost if they live in the farm more than
• 35:13
  Speaker 3: territories of Canada or something, whereas someone else who lives
• 35:17
  Speaker 3: in the Mediterranean is quite comfortable eating.
• 35:20
  Speaker 2: More vegetables, you know. I mean there's this interesting.
• 35:22
  Speaker 3: Disparity with how our bodies have evolved and how our
• 35:25
  Speaker 3: culturally bodies have evolved. So when you look at BMI,
• 35:28
  Speaker 3: it may actually be very different when you apply it
• 35:31
  Speaker 3: to a whole culture of people who have a different
• 35:34
  Speaker 3: eCos they've lived in.
• 35:35
  Speaker 1: BMI is fucking outdated, dumb nine fifty science. But I
• 35:40
  Speaker 1: know what you're saying. But the thing is that you
• 35:43
  Speaker 1: could have a fit, healthy samoan who's one hundred and
• 35:49
  Speaker 1: ten kilos and five foot ten, but he's just a
• 35:55
  Speaker 1: fucking giant, and one hundred and ten kilos for him
• 35:58
  Speaker 1: is in shape, whereas he might be your height five
• 36:03
  Speaker 1: foot two and like what do you weigh sixty nine
• 36:07
  Speaker 1: or seventy or something?
• 36:10
  Speaker 2: Sixty seven?
• 36:11
  Speaker 1: Yeah, so you know, it's it's completely different kind of measurement,
• 36:18
  Speaker 1: and it's somewhat redundant. It's largely redundant. But I get
• 36:21
  Speaker 1: what you're saying, but also think about this as just
• 36:25
  Speaker 1: a sidebar. So the Inuit population, we don't use the
• 36:31
  Speaker 1: other word anymore, by the.
• 36:32
  Speaker 2: Way, Eskimo, no, I think I got on that one show.
• 36:36
  Speaker 1: Yeah, you're not allowed to say that. So anyway, the
• 36:38
  Speaker 1: Inuit population over you know millennia existed on essentially protein fat,
• 36:48
  Speaker 1: so fish whatever, and no vegetables and no fruit ever
• 36:55
  Speaker 1: because where the fuck do you get a tree there?
• 36:59
  Speaker 1: Like where do you plant your potatoes? So, and they
• 37:03
  Speaker 1: adapted to that. And what is also interesting is they
• 37:06
  Speaker 1: had a diet high in protein and high in fat,
• 37:11
  Speaker 1: so high fat, high protein and until the last few decades,
• 37:16
  Speaker 1: extremely low incidents of heart disease.
• 37:19
  Speaker 3: Based on the detO diet. Would they be in kytosis?
• 37:22
  Speaker 3: All the time.
• 37:23
  Speaker 1: Yes, yeah, yes, yeah, yeah yeah, and so yeah, they're
• 37:28
  Speaker 1: using ketones for energy, not carbohydrates. So yeah, but it is.
• 37:33
  Speaker 1: It is amazing how bodies the human body, it really is.
• 37:39
  Speaker 1: It's the same thing, but it's not the same thing.
• 37:43
  Speaker 2: It's phenomenal, isn't it.
• 37:44
  Speaker 1: You know?
• 37:44
  Speaker 3: Interestingly, I just did an AI search on esquimo, the term,
• 37:48
  Speaker 3: and for generations they say it was believed to meet
• 37:50
  Speaker 3: eaters of raw meat, and it's a colonial term that
• 37:54
  Speaker 3: was used to describe the Inuit people, which is kind
• 37:57
  Speaker 3: of crazy, isn't it.
• 37:58
  Speaker 1: Can I just say everyone that I do not endorse
• 38:02
  Speaker 1: the use of that word that Patrick, not me, Patrick
• 38:05
  Speaker 1: has been using Patrick Bonello. Patrick, I told him not
• 38:11
  Speaker 1: to use that word. He proceeded using it against my
• 38:15
  Speaker 1: legal advice. So send your emails to him.
• 38:18
  Speaker 2: To explain why you shouldn't use it. I thought I'd
• 38:20
  Speaker 2: go through and.
• 38:21
  Speaker 1: That way we'd now, well, we probably didn't need to
• 38:23
  Speaker 1: use the word. It's like there's a couple of other words.
• 38:26
  Speaker 1: We go fucking with your story, all right, keep going,
• 38:30
  Speaker 1: We're on a time budget. Keep going.
• 38:33
  Speaker 3: Dementia is so prolific in our society, and you push,
• 38:38
  Speaker 3: you just pushed.
• 38:39
  Speaker 1: A button in me right then when you said that, yeah.
• 38:42
  Speaker 3: It is, I mean it's affected my family. I know
• 38:44
  Speaker 3: it's affected your family. But this is interesting that a
• 38:47
  Speaker 3: twenty year study into the use of brain training, so
• 38:51
  Speaker 3: we know that what we eat and exercise can really
• 38:54
  Speaker 3: assist in staving off some sorts of dementia. But now
• 38:59
  Speaker 3: this news. It's basically a computerized speed of processing training.
• 39:05
  Speaker 3: So they effectively computer games that constantly forced the mind
• 39:11
  Speaker 3: to think in different ways and adapt to the way
• 39:14
  Speaker 3: that you're using the game. They say that it can
• 39:18
  Speaker 3: reduce the risk of dementia by up to twenty five percent.
• 39:21
  Speaker 3: That this is not a just you know, flash in
• 39:23
  Speaker 3: the pan. This is something that's been you know, this
• 39:25
  Speaker 3: advanced cognitive training. It's actually called advanced cognitive training for
• 39:30
  Speaker 3: independent and vital elderly.
• 39:32
  Speaker 2: It's called active. They just make those words up, don't they.
• 39:35
  Speaker 1: Yeah, they just do, they do. But well, I'm very
• 39:37
  Speaker 1: excited about this piece of news that you're bringing because
• 39:41
  Speaker 1: I've spoken about it quite a bit. I've posted about
• 39:44
  Speaker 1: it this week on Instagram. I have not seen or
• 39:47
  Speaker 1: heard of this, so I'm definitely going to go and
• 39:49
  Speaker 1: have a look at that. I'm with you mate, like
• 39:51
  Speaker 1: people you know, even people who work out a lot,
• 39:55
  Speaker 1: and training your body is also good for your brain,
• 39:58
  Speaker 1: of course, but your brain your cognitive capacity or ability
• 40:04
  Speaker 1: to focus and think critically and recall stuff, remember stuff,
• 40:09
  Speaker 1: make good decisions, that just naturally declines. But it doesn't
• 40:15
  Speaker 1: have to be a linear deterioration. In fact, we've seen
• 40:20
  Speaker 1: lots of people in older age doing things like you're
• 40:23
  Speaker 1: talking about, but also just starting to live weight, starting
• 40:26
  Speaker 1: to walk, doing a little bit of study, like you know,
• 40:30
  Speaker 1: answering some questions, and like, if we train our brain,
• 40:34
  Speaker 1: it's very similar to our body in that the way
• 40:37
  Speaker 1: that it ages and functions changes. But most of us
• 40:41
  Speaker 1: stop actively learning. Actually I can't say that for sure.
• 40:46
  Speaker 1: I'm sure that is true, but i've anyway, it's my
• 40:49
  Speaker 1: experience that the bulk of a stuff actively learning, as
• 40:53
  Speaker 1: in consciously going to learn new things probably around forty
• 40:58
  Speaker 1: or even younger, and so there is just a decline.
• 41:01
  Speaker 1: But that's why, you know, people say to me all
• 41:04
  Speaker 1: the time things like I wish I did a degree,
• 41:07
  Speaker 1: and I'm like, go do one, Go and do like,
• 41:10
  Speaker 1: if you've got the time, do it online. Do some
• 41:13
  Speaker 1: face to faces even better, because now you're in a
• 41:15
  Speaker 1: room with humans, You're answering questions, you're solving problems, you're
• 41:20
  Speaker 1: learning new stuff, you've got a teacher that you can
• 41:22
  Speaker 1: ask things. Yeah, I just think education, even if it's
• 41:26
  Speaker 1: just for your brain's health, it's more than that. But
• 41:30
  Speaker 1: even if it was only to make your brain work
• 41:32
  Speaker 1: better is right up there, and anything like this that
• 41:37
  Speaker 1: you're talking about can only help.
• 41:40
  Speaker 2: Yeah, it's pretty exciting stuff.
• 41:41
  Speaker 3: So I think it's as you say, it's a combination
• 41:43
  Speaker 3: of a whole lot of things, but every little bit
• 41:46
  Speaker 3: is a building block I guess to hopefully staving.
• 41:49
  Speaker 2: That off in the long term.
• 41:51
  Speaker 1: And I think for people like you and maybe me
• 41:54
  Speaker 1: to a lesser extent, but that kind of protocol or
• 41:57
  Speaker 1: that kind of tool is awesome because you're kind of
• 42:00
  Speaker 1: suited to that, right.
• 42:02
  Speaker 2: M Oh, look, it's called field of view training. You know.
• 42:06
  Speaker 3: I was thinking while we were chatting about this. We've
• 42:08
  Speaker 3: spoken on the show about this a few years ago.
• 42:11
  Speaker 3: There's a game that I play in virtual reality called
• 42:14
  Speaker 3: beat Saber and basically, holding two lightsabers, you're listening to
• 42:19
  Speaker 3: a song and these cubes are flying at you in
• 42:22
  Speaker 3: three D and you have to swipe your lightsaber in
• 42:25
  Speaker 3: time to the music in the right direction and the
• 42:28
  Speaker 3: right color, so you matching color direction and sound at
• 42:32
  Speaker 3: the same time. And I got to a point where
• 42:35
  Speaker 3: it was really hard when I started, and then I realized,
• 42:38
  Speaker 3: and I don't know how this works with your brain,
• 42:41
  Speaker 3: but if I swipe with my right hand but don't
• 42:44
  Speaker 3: think about my left hand, so I imagine you've got
• 42:47
  Speaker 3: to coordinate the movements, only focus on one side, my
• 42:52
  Speaker 3: brain just takes care of the other side without me
• 42:54
  Speaker 3: thinking about it so consciously. So it's my subconscious is
• 42:58
  Speaker 3: still taking it in. The data is coming in. I'm
• 43:00
  Speaker 3: optically seeing it. I'm seeing this thing rushing towards me.
• 43:04
  Speaker 3: But if I only concentrate on my right hand side
• 43:07
  Speaker 3: and don't think about the left, the left just does
• 43:10
  Speaker 3: what it's doing without any conscious thought.
• 43:13
  Speaker 2: How does that now?
• 43:14
  Speaker 1: Yeah, that's amazing. So just kind of similarly we're talking
• 43:18
  Speaker 1: about motorbikes before. So if I'm coming up to a
• 43:22
  Speaker 1: set of traffic lights and I'm going to turn left
• 43:24
  Speaker 1: and whatever right, so as will every other motorcyclist. Right up,
• 43:30
  Speaker 1: I pull in the clutch, which is on the left,
• 43:33
  Speaker 1: I put on a pull in the right front brake
• 43:37
  Speaker 1: with my right hand. I tap my foot on this
• 43:41
  Speaker 1: thing on the right side, which is the rear brake.
• 43:44
  Speaker 1: I change gears with my left foot, so I'm using
• 43:47
  Speaker 1: all of both hands, both feet all at the same time.
• 43:51
  Speaker 1: I'm changing gears, I'm listening to the revs. I'm moving
• 43:54
  Speaker 1: into the corner at the right speed. I'm breaking at
• 43:57
  Speaker 1: the right rate. Then I'm coming out of the corner
• 43:59
  Speaker 1: and accelerating a and pulling in the church the clutch
• 44:02
  Speaker 1: multiple times, changing years, da da da. I don't even
• 44:05
  Speaker 1: think about that at all, because I'm thinking about lunch. Yeah,
• 44:09
  Speaker 1: I have had I have paid zero attention to what
• 44:12
  Speaker 1: my hands and feet are doing. And also I've clicked
• 44:16
  Speaker 1: on the indicator with my thumb, my left thumb. You know,
• 44:19
  Speaker 1: you just move this little toggle to the left and
• 44:23
  Speaker 1: you're turning left, toggle to the right, you're turning right,
• 44:25
  Speaker 1: and to cancel it, you press it in with your thumb.
• 44:28
  Speaker 1: So it's like so many things are happening at once.
• 44:32
  Speaker 1: That because I started riding motorbikes when I was about ten,
• 44:35
  Speaker 1: so that's half a century of riding bikes, I don't
• 44:38
  Speaker 1: have to think about what I'm doing. Yes, I need
• 44:42
  Speaker 1: to pay attention to the road and the conditions and
• 44:44
  Speaker 1: the traffic. But I don't have to pay attention to
• 44:48
  Speaker 1: what my hands and feet are doing. It's crazy, is it?
• 44:51
  Speaker 3: That bit of gray matter sitting inside that amazing? It's
• 44:55
  Speaker 3: totally amazing, totally amazing.
• 44:57
  Speaker 1: Thinking's happening all the time. You're just not a we
• 45:00
  Speaker 1: of a lot of it.
• 45:01
  Speaker 3: Yeah, that's right, and for some of us more than others. Hey,
• 45:05
  Speaker 3: the interesting thing about our brain I think I've always
• 45:09
  Speaker 3: found and for me it's been tai Chi.
• 45:11
  Speaker 2: It takes me away from the moment.
• 45:13
  Speaker 3: It kind of stops all the noise and chatter in
• 45:16
  Speaker 3: my brain, I you know, regularly every day, and it
• 45:20
  Speaker 3: quietens the noise in my brain. Have you heard of
• 45:23
  Speaker 3: a thing called blue space therapy.
• 45:28
  Speaker 1: I feel like I've heard of that. I have no
• 45:31
  Speaker 1: idea what it is.
• 45:33
  Speaker 3: Well, this is a way that they're helping people who
• 45:36
  Speaker 3: deal with trauma, anxiety, addiction, depression. And what they do
• 45:41
  Speaker 3: is they've found that going by an ocean, a river,
• 45:45
  Speaker 3: a lake, and just sitting by that space, having an
• 45:49
  Speaker 3: open sky in front of you, having the sound of
• 45:51
  Speaker 3: the water lapping up on the shore, hearing the trickle
• 45:54
  Speaker 3: of water or whatever it happens to be can actually
• 45:58
  Speaker 3: totally transform the person who's you know, who's experiencing that
• 46:04
  Speaker 3: to the point where it can reduce the anxiety, It
• 46:06
  Speaker 3: can help with OCD and all sorts of things that
• 46:09
  Speaker 3: affect our brain, and it just takes you neurologically into
• 46:13
  Speaker 3: a totally different space just by being exposed to this
• 46:17
  Speaker 3: blue therapy, this blue space therapy.
• 46:20
  Speaker 1: It's so interesting you say that because you know where
• 46:23
  Speaker 1: my john is. So I live eight hundred meters from
• 46:26
  Speaker 1: the beach. If I walk down the back streets, and
• 46:29
  Speaker 1: quite often, at least once a month, I walk out
• 46:33
  Speaker 1: on you know, in Hampton Beach. You've been there many times,
• 46:36
  Speaker 1: and you know they have the stone the breakwater things
• 46:39
  Speaker 1: that go out into the water, and they're probably about
• 46:44
  Speaker 1: some of them about one hundred meters long. I walk
• 46:47
  Speaker 1: out and I get to the basically to the water,
• 46:50
  Speaker 1: and I sit on the last rock that you can
• 46:52
  Speaker 1: sit on before you're going to get wet. And I've
• 46:56
  Speaker 1: never said this before to anyone, but if I'm having
• 46:59
  Speaker 1: a rough day or there's just underlying stuff, it's not
• 47:03
  Speaker 1: even it's not even front of mind. But when I
• 47:07
  Speaker 1: go out there and by the time you're out there,
• 47:10
  Speaker 1: you can't hear anything, really, you can just hear the
• 47:12
  Speaker 1: water lapping against the rocks, and because you're looking straight out,
• 47:17
  Speaker 1: all you can see is like you said, blue sky.
• 47:19
  Speaker 1: Blue water makes me quite emotional, like it brings something up.
• 47:26
  Speaker 1: And I may or may not have shed a tear
• 47:30
  Speaker 1: on that breakwater quite a few times, where yeah, there's
• 47:34
  Speaker 1: just something going on and being out there kind of
• 47:37
  Speaker 1: brings it to the surface. But I think, oh, this
• 47:41
  Speaker 1: is happening for a reason, so I don't get up
• 47:44
  Speaker 1: and run back to the beach. I just sit out there. Yeah.
• 47:48
  Speaker 1: I find that completely believable.
• 47:52
  Speaker 3: The science behind it suggests that it reduces the active cortisol.
• 48:00
  Speaker 2: Stress hormone is what it's doing. It's getting rid of
• 48:03
  Speaker 2: that stress hormone.
• 48:06
  Speaker 1: It's like a giant blue zanax, really, isn't it.
• 48:10
  Speaker 2: But isn't it great that we can do that.
• 48:12
  Speaker 3: We can do brain training, or we can go for
• 48:14
  Speaker 3: a walk on a beach or go for you know,
• 48:16
  Speaker 3: spend time in nature amongst the trees, among a lake
• 48:19
  Speaker 3: or a river or a creek and not have to
• 48:22
  Speaker 3: take drugs to induce something that's going to be calming
• 48:26
  Speaker 3: and beneficial to us.
• 48:27
  Speaker 1: Oh well, here's the thing about like sitting out where
• 48:31
  Speaker 1: that in that spot where I do, or you being
• 48:33
  Speaker 1: in nature with your favorite canine slash person. That changes
• 48:40
  Speaker 1: you buiochemistry. It changes what's happening in your brain, you know,
• 48:44
  Speaker 1: Just like a drug will change what's happening in your brain,
• 48:47
  Speaker 1: so does tai chi. Right, it changes the bike. That's
• 48:50
  Speaker 1: why people's heart rates go down and their parasympathetic nervous
• 48:54
  Speaker 1: system kicks in, and their blood pressure lowers and their
• 48:58
  Speaker 1: respiration lowers, like all of these physiological and biochemical and
• 49:02
  Speaker 1: neurological changes that are brought on by tai chi. But
• 49:06
  Speaker 1: we just think, oh, we need a pill to change
• 49:09
  Speaker 1: our physiology. You sure don't. Your pill could be tai chi.
• 49:14
  Speaker 1: And speaking of that, Patrick's got a new space and
• 49:16
  Speaker 1: this week he had eighteen people in his class, and
• 49:20
  Speaker 1: there are openings now. I don't know how many people
• 49:25
  Speaker 1: from Bland you know, listen to the show, but for
• 49:28
  Speaker 1: the few who do, tell them where it's at now
• 49:33
  Speaker 1: and how they can get involved.
• 49:34
  Speaker 2: Well, there's I do two lots of classes.
• 49:38
  Speaker 3: I do one in back to Marsh on a Wednesday night,
• 49:40
  Speaker 3: and we've been restricted to a very small area in
• 49:43
  Speaker 3: a neighborhood center and then been trying to took them
• 49:46
  Speaker 3: into going to a new hall. So spending a little
• 49:49
  Speaker 3: bit more money so we could hire a hall and
• 49:51
  Speaker 3: we double the number of people this term who are
• 49:54
  Speaker 3: now doing my tai chi class. I was just so
• 49:55
  Speaker 3: excited about that. We were talking about that before the show.
• 49:58
  Speaker 3: But to go, I'm going to eight or ten at eighteen.
• 50:02
  Speaker 1: Yeah, that's great. Yeah, I've got an idea for you.
• 50:06
  Speaker 1: I think you got to like this idea. I think
• 50:09
  Speaker 1: you should do some research on what's the biggest tai
• 50:11
  Speaker 1: chi class in the world in this book of record stuff, right,
• 50:15
  Speaker 1: and I think you should run it on an oval
• 50:17
  Speaker 1: in summer in Bland and we'll promote the shit out
• 50:21
  Speaker 1: of it. Yeah, if you do it, I'll come up
• 50:23
  Speaker 1: and do the class, and let's get a thousand people
• 50:28
  Speaker 1: doing a tai chi class and put Balan on the map.
• 50:31
  Speaker 2: Oh no, wait for this one.
• 50:33
  Speaker 3: Okay, this is a bit difficult because the largest synchronized
• 50:36
  Speaker 3: tai chie display occurred in October twenty fifteen with fifty
• 50:40
  Speaker 3: thousand participants. All right, we're not doing that, but they
• 50:43
  Speaker 3: gathered across fifteen locations.
• 50:45
  Speaker 2: That's that's not that's not the same, is it. I'll
• 50:49
  Speaker 2: have more research into this one.
• 50:51
  Speaker 1: I reckon if it was like a you know, fifteen
• 50:54
  Speaker 1: hundred and two thousand, I reckon we could give that
• 50:56
  Speaker 1: a crack.
• 50:57
  Speaker 2: Yeah, that's it.
• 50:58
  Speaker 3: I'd be I'd try, Oh, twenty thousand participants, the biggest idea.
• 51:07
  Speaker 2: Yeah, nice one, but anyway, it's a good idea.
• 51:09
  Speaker 1: Maybe get your crop top out and we'll do Jazus
• 51:11
  Speaker 1: size again.
• 51:13
  Speaker 2: Zomber, Patrick Zomber.
• 51:14
  Speaker 1: Tell people how to connect with you, please.
• 51:17
  Speaker 3: Sure, they could go to websites now, dot com, dot
• 51:20
  Speaker 3: au if they want to talk tech. If they want
• 51:23
  Speaker 3: us to talk about something, just message me and we
• 51:25
  Speaker 3: can chat about it in the next show.
• 51:26
  Speaker 2: If it's tech related, but it could be anything. I'll
• 51:28
  Speaker 2: talk about anything. Craig will talk about anything. We'll be happy.
• 51:32
  Speaker 1: Yeah, the more suggestions the better. Let's be honest.
• 51:35
  Speaker 3: Well, go to tychie at home, dot com, todau and
• 51:38
  Speaker 3: join in with Fritz and I my dog and do
• 51:40
  Speaker 3: some Tai Chee exercises.
• 51:41
  Speaker 1: With us, Fritz the Wonder Dog. Yeah all right, mate,
• 51:45
  Speaker 1: appreciate you your ace. We'll say goodbye up there, but thanks buddy, cheers,
• 51:50
  Speaker 1: See you mate.