1
00:00:01,680 --> 00:00:07,360
Speaker 1: A good A team good Patrick, gooda good a Tiff Hey,

2
00:00:08,760 --> 00:00:10,760
Speaker 1: Tiff and I were just talking while you're off having

3
00:00:10,840 --> 00:00:14,000
Speaker 1: a Wii, Patrick or whatever you were doing, just backing

4
00:00:14,040 --> 00:00:18,440
Speaker 1: one out and really.

5
00:00:18,560 --> 00:00:21,160
Speaker 2: Thirty second not even thirty seconds in, and it's just

6
00:00:21,160 --> 00:00:22,599
Speaker 2: too cras well.

7
00:00:22,600 --> 00:00:24,800
Speaker 1: It wasn't yours, wasn't it for I? That was back

8
00:00:24,840 --> 00:00:25,639
Speaker 1: and so don't.

9
00:00:25,440 --> 00:00:27,960
Speaker 2: Blame us leading something down with a fountain pen. The

10
00:00:28,040 --> 00:00:30,280
Speaker 2: you go, they say that, do you use a pen?

11
00:00:31,440 --> 00:00:36,680
Speaker 1: So Diff and I were talking about like high pitched noises.

12
00:00:36,800 --> 00:00:38,160
Speaker 1: I don't know how it came up.

13
00:00:38,400 --> 00:00:40,360
Speaker 3: Because I had to go turn the exhaust fan off

14
00:00:40,360 --> 00:00:42,639
Speaker 3: because I just heard it, and then I couldn't unhear it.

15
00:00:43,320 --> 00:00:46,960
Speaker 1: That's right. So in my office where I'm at now,

16
00:00:47,320 --> 00:00:52,920
Speaker 1: if Melissa's over here doing work junk and whatever, there's

17
00:00:53,000 --> 00:00:55,800
Speaker 1: apparently a sound in my office that she can hear,

18
00:00:55,960 --> 00:00:58,639
Speaker 1: and she's like, oh my god, doesn't that annoy you?

19
00:00:58,800 --> 00:01:01,520
Speaker 1: I can't even hear it, Like it's not like I

20
00:01:01,520 --> 00:01:05,399
Speaker 1: don't find it annoying, I can't actually hear it. And

21
00:01:05,440 --> 00:01:08,320
Speaker 1: then Tip was telling me, will you tell the story.

22
00:01:08,520 --> 00:01:10,959
Speaker 3: I used to work at a restaurant in Tazzy and

23
00:01:11,000 --> 00:01:14,839
Speaker 3: they had this electric kind of frequency thing plugged into

24
00:01:15,120 --> 00:01:18,520
Speaker 3: the PowerPoint that kept ants away, that ants could hear

25
00:01:18,520 --> 00:01:20,920
Speaker 3: it and wouldn't come. And I could hear it. I

26
00:01:20,920 --> 00:01:26,440
Speaker 3: could hear the noise. And I said the harves was

27
00:01:26,440 --> 00:01:30,360
Speaker 3: for annoying little critters, and yeah, I could hear it.

28
00:01:30,560 --> 00:01:33,960
Speaker 2: So if you can hear a repetitive winding sound when

29
00:01:33,959 --> 00:01:35,880
Speaker 2: you're with Craig, it's Craig.

30
00:01:37,760 --> 00:01:38,400
Speaker 1: Very hopeful.

31
00:01:38,480 --> 00:01:41,720
Speaker 3: And here I am unplugging everything all the time, wondering

32
00:01:41,720 --> 00:01:42,680
Speaker 3: what doesn't go away?

33
00:01:43,040 --> 00:01:43,920
Speaker 4: Now, what's interesting?

34
00:01:44,000 --> 00:01:46,039
Speaker 2: I can remember I've got a young guy who works

35
00:01:46,040 --> 00:01:49,360
Speaker 2: for me after school. And there's a level or a

36
00:01:49,520 --> 00:01:52,240
Speaker 2: tone at which, as we get older we can't hear it.

37
00:01:52,480 --> 00:01:53,720
Speaker 4: And there was a while.

38
00:01:53,520 --> 00:01:57,680
Speaker 2: There where teenagers were playing music in school classrooms or

39
00:01:57,720 --> 00:02:01,360
Speaker 2: playing noises that the teachers couldn't because they were too old.

40
00:02:01,840 --> 00:02:02,480
Speaker 4: So there's a.

41
00:02:02,480 --> 00:02:06,080
Speaker 2: Range of frequency range that only young people can actually hear.

42
00:02:06,160 --> 00:02:07,560
Speaker 4: I thought that was really interesting.

43
00:02:08,760 --> 00:02:10,639
Speaker 1: You know, you two are being very hurtful to me.

44
00:02:11,840 --> 00:02:13,960
Speaker 5: We're sorry, Harps, we love you.

45
00:02:16,720 --> 00:02:21,320
Speaker 1: Very insecure. Yeah, I think that's a thing. I think

46
00:02:21,360 --> 00:02:26,160
Speaker 1: that that not being able to It's the same with dogs.

47
00:02:26,280 --> 00:02:30,000
Speaker 1: Don't dogs hear a certain pitch that humans can't hear.

48
00:02:30,760 --> 00:02:32,919
Speaker 4: Absolutely, you too.

49
00:02:32,760 --> 00:02:38,520
Speaker 1: Should test that now, Patrick, I sent you a I

50
00:02:38,560 --> 00:02:40,160
Speaker 1: mean you are the tech guy. I knew the guy

51
00:02:40,200 --> 00:02:42,200
Speaker 1: that comes up with the topics, but I sent I

52
00:02:42,240 --> 00:02:45,440
Speaker 1: saw something this week in the tech realm that I thought,

53
00:02:45,480 --> 00:02:48,880
Speaker 1: oh my god, my friend would my friend would love

54
00:02:49,000 --> 00:02:50,840
Speaker 1: not only would he love one of these, but I

55
00:02:50,880 --> 00:02:54,000
Speaker 1: think he would fucking love this job. Tell Tiff what

56
00:02:54,200 --> 00:02:55,919
Speaker 1: and our listeners what I sent you?

57
00:02:56,760 --> 00:02:59,480
Speaker 4: Look In the most simplest terms, it's a jet pack.

58
00:03:00,880 --> 00:03:03,160
Speaker 2: It's a lot more sophisticated than the ones that I

59
00:03:03,200 --> 00:03:05,360
Speaker 2: saw when I was fourteen at the Royal Melbourne Show

60
00:03:05,400 --> 00:03:08,440
Speaker 2: that I've been drooling over since I was fourteen. But

61
00:03:08,800 --> 00:03:14,120
Speaker 2: a British company has called test called Gravity now allows

62
00:03:14,160 --> 00:03:15,880
Speaker 2: people to do test flights.

63
00:03:15,560 --> 00:03:17,560
Speaker 4: Of this jet pack and it is amazing.

64
00:03:17,600 --> 00:03:20,880
Speaker 2: It's kind of a cross between the backpack, but it

65
00:03:20,919 --> 00:03:24,680
Speaker 2: also looks a bit like Iron Man from the Marvel movies.

66
00:03:24,880 --> 00:03:26,840
Speaker 4: And so Craigo sent it through to me.

67
00:03:26,880 --> 00:03:28,880
Speaker 2: But I did a bit more research Crago because when

68
00:03:28,919 --> 00:03:31,919
Speaker 2: we go to the UK, we can do these test flights.

69
00:03:31,919 --> 00:03:33,360
Speaker 4: So there's a special offer.

70
00:03:33,360 --> 00:03:37,360
Speaker 2: At the moment it's one five hundred pounds, but then

71
00:03:37,440 --> 00:03:39,440
Speaker 2: if you do the full flight experience.

72
00:03:39,840 --> 00:03:41,320
Speaker 4: It kind of jumps a little bit.

73
00:03:41,200 --> 00:03:44,680
Speaker 2: More, but I figure you could shout it's two hundred

74
00:03:44,720 --> 00:03:46,960
Speaker 2: pounds and then to do a whole day of flight

75
00:03:47,040 --> 00:03:50,040
Speaker 2: training it jumps. This is just the training is six

76
00:03:50,600 --> 00:03:53,240
Speaker 2: six hundred, so probably about ten grand to do a

77
00:03:53,320 --> 00:03:54,440
Speaker 2: day's training.

78
00:03:54,680 --> 00:03:58,360
Speaker 1: The idea of learning to fly a jetpack sounds fraught

79
00:03:58,400 --> 00:03:59,000
Speaker 1: with danger.

80
00:04:00,200 --> 00:04:03,200
Speaker 2: Now they have a gantry right with ropes and supports

81
00:04:03,200 --> 00:04:05,360
Speaker 2: and all that. See, that's the thing. You go there

82
00:04:05,480 --> 00:04:08,520
Speaker 2: and they tether you to this gantry so that you're safe.

83
00:04:08,880 --> 00:04:10,600
Speaker 2: But I want to be out in the forest and

84
00:04:10,640 --> 00:04:12,920
Speaker 2: just fly over lakes and all that sort of stuff.

85
00:04:13,000 --> 00:04:16,279
Speaker 2: But you know, there are some places you can go to,

86
00:04:16,279 --> 00:04:19,000
Speaker 2: I think in Queensland, and they have these water based

87
00:04:19,120 --> 00:04:21,920
Speaker 2: jet packs. So what they It's like you've got a

88
00:04:22,000 --> 00:04:25,799
Speaker 2: jet ski underneath you and as you start to move,

89
00:04:25,960 --> 00:04:27,919
Speaker 2: it just uses water to propel you.

90
00:04:27,960 --> 00:04:28,839
Speaker 4: Have you seen that tip?

91
00:04:29,120 --> 00:04:30,120
Speaker 5: Yeah, I've seen those.

92
00:04:30,279 --> 00:04:31,640
Speaker 4: Yeah, I really want to do that. Maybe we could

93
00:04:31,680 --> 00:04:31,880
Speaker 4: do that.

94
00:04:31,920 --> 00:04:34,039
Speaker 2: Craig go on holiday in Queensland and just do the

95
00:04:34,080 --> 00:04:35,320
Speaker 2: water jet pack experience.

96
00:04:35,800 --> 00:04:39,360
Speaker 1: Yeah, well it sounds super gay, but you're gay, but

97
00:04:39,440 --> 00:04:42,839
Speaker 1: I'm not. But that's okay. It's okay, it's okay that

98
00:04:42,880 --> 00:04:43,400
Speaker 1: it's going to.

99
00:04:43,360 --> 00:04:49,920
Speaker 2: Come with us, you and I go to the water park.

100
00:04:50,640 --> 00:04:53,359
Speaker 1: Really, can we not go to the UFC as well?

101
00:04:54,200 --> 00:04:55,320
Speaker 1: Can we not do something?

102
00:04:57,400 --> 00:05:00,840
Speaker 4: What about the trucks? What's what's the trucks?

103
00:05:01,200 --> 00:05:05,560
Speaker 1: Can we just upset the water parks with fucking monster trucks?

104
00:05:05,760 --> 00:05:08,280
Speaker 2: Are you telling me that putting on a water jet

105
00:05:08,320 --> 00:05:11,320
Speaker 2: pack is gay and monster trucks isn't?

106
00:05:11,440 --> 00:05:12,159
Speaker 4: Like? What the hell?

107
00:05:12,760 --> 00:05:14,760
Speaker 1: What? I don't know, I don't know. It just no,

108
00:05:15,000 --> 00:05:17,039
Speaker 1: just you and me going to the water parks in

109
00:05:17,120 --> 00:05:21,400
Speaker 1: Queensland on a holiday, you know, But that's all right,

110
00:05:21,520 --> 00:05:27,600
Speaker 1: I said, sporty, I'm com before we go on. I

111
00:05:27,680 --> 00:05:32,960
Speaker 1: just remembered we had heaps of messages this week with

112
00:05:33,160 --> 00:05:35,480
Speaker 1: I don't know why. I don't know why we don't

113
00:05:35,480 --> 00:05:37,479
Speaker 1: have a photo of you up much, but there was

114
00:05:37,880 --> 00:05:39,720
Speaker 1: a photo of you and Tiff, But I thought we

115
00:05:39,839 --> 00:05:43,200
Speaker 1: have your scone on maybe because it was on general

116
00:05:43,240 --> 00:05:48,279
Speaker 1: distribution and not on our page. But how many people say, oh,

117
00:05:48,600 --> 00:05:52,640
Speaker 1: Patrick's nothing like what I thought? Like, I don't know.

118
00:05:52,720 --> 00:05:54,760
Speaker 1: That's either a compliment or an insult.

119
00:05:55,000 --> 00:05:56,720
Speaker 4: We thought it was dark and handsome.

120
00:05:57,480 --> 00:06:01,000
Speaker 1: Either way, it's an insult because like either they think

121
00:06:01,040 --> 00:06:04,600
Speaker 1: you've got this fucking movie star voice and then they

122
00:06:04,640 --> 00:06:07,440
Speaker 1: see your head and they're like, oh that's disappointing, or

123
00:06:07,440 --> 00:06:10,680
Speaker 1: the other way or the other way around. They think

124
00:06:10,760 --> 00:06:13,279
Speaker 1: your movie star looks but you've got a ship voice.

125
00:06:13,640 --> 00:06:16,960
Speaker 1: What do you get that? Have you had that feedback before?

126
00:06:17,839 --> 00:06:19,920
Speaker 4: No, but I'm going to go from cry for a bit.

127
00:06:21,640 --> 00:06:23,680
Speaker 1: Well you do have the dulcin No. I think you're

128
00:06:23,760 --> 00:06:25,560
Speaker 1: quite a good looking man, but you also have a

129
00:06:25,600 --> 00:06:28,640
Speaker 1: good look at Let's go to the water parks in Queensland. No,

130
00:06:28,800 --> 00:06:33,360
Speaker 1: but you do. Sorry, I'm just fucking hell. Well, clearly

131
00:06:33,400 --> 00:06:36,080
Speaker 1: I'm no good at women. So let's fucking let's try it.

132
00:06:36,160 --> 00:06:39,120
Speaker 1: Let's see what happens. Are you speaking of relationships? I

133
00:06:39,160 --> 00:06:43,880
Speaker 1: know I'm digressing, but you two are pretty much at

134
00:06:43,960 --> 00:06:47,919
Speaker 1: the verge of a life together. Can you explain to

135
00:06:48,880 --> 00:06:51,520
Speaker 1: Tiff what we would I know this is inappropriate, but

136
00:06:51,600 --> 00:06:52,600
Speaker 1: fuck our listeners.

137
00:06:52,920 --> 00:06:53,240
Speaker 4: Do you know?

138
00:06:53,360 --> 00:06:55,239
Speaker 1: Our listeners love this bit the best.

139
00:06:55,800 --> 00:06:59,080
Speaker 3: They like I'm not to post I'm not opposed to

140
00:06:59,120 --> 00:07:01,000
Speaker 3: a situation ship with Patrick.

141
00:07:01,080 --> 00:07:04,800
Speaker 2: Actually, look I love that, and you know why when

142
00:07:04,880 --> 00:07:07,240
Speaker 2: we have a private conversation do you then bring it

143
00:07:07,320 --> 00:07:08,880
Speaker 2: up in the podcast?

144
00:07:10,960 --> 00:07:15,400
Speaker 4: Can I tell my operating things. I said it.

145
00:07:14,800 --> 00:07:20,440
Speaker 2: I was saying, I really enjoyed hanging out with Tiff

146
00:07:20,560 --> 00:07:23,840
Speaker 2: last weekend, and I could be in a relationship with her.

147
00:07:24,320 --> 00:07:28,800
Speaker 2: I said, it'd be everything except sex. We could probably spoon, but.

148
00:07:30,840 --> 00:07:33,560
Speaker 4: She's awesome. Look, seriously, Tiff.

149
00:07:33,400 --> 00:07:37,560
Speaker 2: Is just the ideal, perfect person everything. I'd tick all

150
00:07:37,600 --> 00:07:38,720
Speaker 2: the boxes there, Tiff.

151
00:07:40,000 --> 00:07:42,640
Speaker 3: Now, perhaps did mentioned it last night, and I've booked

152
00:07:42,640 --> 00:07:44,560
Speaker 3: out some time to go dress shopping.

153
00:07:44,720 --> 00:07:49,000
Speaker 4: So awesome, So I'd be up for that. Not for you,

154
00:07:49,160 --> 00:07:52,520
Speaker 4: a dress for her, you idiot, heard a company.

155
00:07:54,600 --> 00:07:59,360
Speaker 1: See I reckon Now. Patrick's proposal to me was not

156
00:07:59,440 --> 00:08:04,280
Speaker 1: that kind of proposal. His hypothetical scenario with you was

157
00:08:04,360 --> 00:08:06,520
Speaker 1: he would marry you. He said he would marry you

158
00:08:07,520 --> 00:08:10,880
Speaker 1: if you would allow him a semi regular, you know,

159
00:08:11,480 --> 00:08:17,560
Speaker 1: Saturday night off dalliance with somebody with a cock. Well,

160
00:08:17,960 --> 00:08:22,560
Speaker 1: I mean, all right, okay, and boy, all right? Well whatever?

161
00:08:22,840 --> 00:08:23,119
Speaker 3: Fuck?

162
00:08:23,160 --> 00:08:23,960
Speaker 1: I don't know these.

163
00:08:23,880 --> 00:08:25,600
Speaker 4: Days goes from bad to worse.

164
00:08:26,640 --> 00:08:29,800
Speaker 1: No, Well, I mean obviously he likes boys, not girls,

165
00:08:29,840 --> 00:08:31,000
Speaker 1: but he could marry you.

166
00:08:32,200 --> 00:08:34,080
Speaker 5: And what did you say, harps when he.

167
00:08:34,120 --> 00:08:38,960
Speaker 1: Said that, I said, well, you're about forty, dude, so

168
00:08:39,559 --> 00:08:47,680
Speaker 1: that's not I mean you say that yourself, so it's

169
00:08:47,800 --> 00:08:49,360
Speaker 1: not like the worst combo.

170
00:08:53,200 --> 00:08:54,319
Speaker 5: Oh well when we when?

171
00:08:54,480 --> 00:08:54,720
Speaker 4: When?

172
00:08:55,559 --> 00:08:57,000
Speaker 5: When are we all going to put it together?

173
00:08:57,760 --> 00:09:01,440
Speaker 2: This went to the wedding projeck dating, so this could

174
00:09:01,480 --> 00:09:05,120
Speaker 2: be the first t YP marriage.

175
00:09:05,520 --> 00:09:08,680
Speaker 1: I mean, like anything goes in twenty twenty four, so

176
00:09:08,760 --> 00:09:11,559
Speaker 1: why not? I mean, you guys, apart from the sex bit,

177
00:09:12,160 --> 00:09:15,520
Speaker 1: I think you guys would be a stellar couple. And

178
00:09:15,640 --> 00:09:17,800
Speaker 1: if you could go live in the country and then

179
00:09:18,320 --> 00:09:25,439
Speaker 1: your dogs could be best friends, that'd become brothers, sisters, sisters,

180
00:09:25,880 --> 00:09:31,000
Speaker 1: well siblings, canine siblings. As long as Fritz didn't eat

181
00:09:31,160 --> 00:09:40,120
Speaker 1: fucking the cat bears.

182
00:09:36,800 --> 00:09:40,440
Speaker 2: Yeah, I think, I think yeah, cats would get it

183
00:09:40,440 --> 00:09:43,559
Speaker 2: over a dog anytime because cats have sharp claws. I

184
00:09:43,600 --> 00:09:46,160
Speaker 2: think I wouldn't let Fritz near an angry cat.

185
00:09:48,160 --> 00:09:52,240
Speaker 1: All right, can you two stop distracting me? Let's talk.

186
00:09:53,840 --> 00:09:56,160
Speaker 1: Isn't it funny when I'm the problem on my own

187
00:09:56,200 --> 00:09:58,520
Speaker 1: show with that doubt?

188
00:10:00,080 --> 00:10:03,040
Speaker 2: A couple of really nice segues right throughout this conversation.

189
00:10:03,280 --> 00:10:05,280
Speaker 2: So I'm going to jump in and not let you start.

190
00:10:07,280 --> 00:10:09,760
Speaker 2: So I got to say, now I missed out on it,

191
00:10:09,800 --> 00:10:11,960
Speaker 2: but that you were there. We caught up in castle

192
00:10:12,000 --> 00:10:14,360
Speaker 2: Maine because we went to well, you went to a

193
00:10:14,400 --> 00:10:17,040
Speaker 2: concert and it's where you featured, didn't you.

194
00:10:17,600 --> 00:10:20,800
Speaker 5: A little bit? A little bit just saying of a.

195
00:10:20,960 --> 00:10:23,840
Speaker 2: Song video clip, I feel like I'm in the presence

196
00:10:23,880 --> 00:10:24,800
Speaker 2: of someone famous.

197
00:10:24,800 --> 00:10:25,120
Speaker 4: Craig.

198
00:10:26,040 --> 00:10:27,959
Speaker 1: Oh, this is why you want to marry her, because

199
00:10:28,000 --> 00:10:28,679
Speaker 1: you're a bloody.

200
00:10:29,280 --> 00:10:32,960
Speaker 5: You're a wannabe writing on my coattails.

201
00:10:33,480 --> 00:10:37,280
Speaker 1: That's you're a groupie, like just because Tip's a big deal.

202
00:10:37,320 --> 00:10:40,760
Speaker 2: Now you don't have to marry her dragging along by

203
00:10:40,800 --> 00:10:43,480
Speaker 2: the straps on your your boxing gloves.

204
00:10:43,720 --> 00:10:44,120
Speaker 1: Hey. Now.

205
00:10:44,600 --> 00:10:47,920
Speaker 2: The reason I thought about this though, was because there's

206
00:10:47,960 --> 00:10:52,240
Speaker 2: some study that's come out into shared music experiences. So

207
00:10:53,000 --> 00:10:57,199
Speaker 2: what it revealed is that obviously when we listen to music,

208
00:10:57,240 --> 00:10:59,880
Speaker 2: I can evoke a reaction, so you know, if it's

209
00:10:59,880 --> 00:11:02,480
Speaker 2: a ode. To Joy, for example, is probably one of

210
00:11:02,480 --> 00:11:05,520
Speaker 2: the most beautiful pieces of music ever written by Beethoven.

211
00:11:06,040 --> 00:11:11,480
Speaker 2: And by coincidence, every year ABC Classic FM does a

212
00:11:11,520 --> 00:11:14,760
Speaker 2: one hundred countdown and their topic this year was the

213
00:11:14,800 --> 00:11:18,720
Speaker 2: top one hundred feel good tunes and to Joy we

214
00:11:18,760 --> 00:11:21,280
Speaker 2: all know O to Joy, Yeah, to google it, you'll

215
00:11:21,320 --> 00:11:27,720
Speaker 2: know it. So shared music experiences extenuate the sensation. So

216
00:11:28,120 --> 00:11:30,120
Speaker 2: listening to a really good piece of music, kind of

217
00:11:30,160 --> 00:11:32,920
Speaker 2: voke reaction. But what the study has found is if

218
00:11:32,960 --> 00:11:36,760
Speaker 2: you share it with somebody else, it enhances it even more,

219
00:11:36,840 --> 00:11:39,400
Speaker 2: and the connectedness between you and the person you're sharing

220
00:11:39,440 --> 00:11:41,240
Speaker 2: it with. And when I think back to some of

221
00:11:41,280 --> 00:11:43,880
Speaker 2: the best concerts I've ever been in or been to,

222
00:11:44,720 --> 00:11:47,000
Speaker 2: what's enhanced that even more is the person I was

223
00:11:47,040 --> 00:11:50,440
Speaker 2: there with at the time, enjoying it with. So I

224
00:11:50,520 --> 00:11:52,760
Speaker 2: went to Imagine Dragons a few years ago with my

225
00:11:52,800 --> 00:11:56,360
Speaker 2: nephew and his girlfriend, and you know, it was embarrassing

226
00:11:56,400 --> 00:11:58,600
Speaker 2: for them because I sing along with all the songs.

227
00:11:58,880 --> 00:11:59,720
Speaker 4: Do you do that tip?

228
00:12:00,000 --> 00:12:00,719
Speaker 3: Did you do? No?

229
00:12:00,800 --> 00:12:02,480
Speaker 5: I definitely known lip sync?

230
00:12:04,120 --> 00:12:06,240
Speaker 4: Do you sing a long? Crego?

231
00:12:06,520 --> 00:12:08,080
Speaker 5: He's got a great singing voice.

232
00:12:08,360 --> 00:12:09,680
Speaker 1: I do not. I do not.

233
00:12:10,040 --> 00:12:11,880
Speaker 5: You do have a great singing voice, though.

234
00:12:12,280 --> 00:12:15,280
Speaker 1: I can sing vaguely in tune. But if I'm at

235
00:12:15,320 --> 00:12:18,040
Speaker 1: a concert, no one needs me fucking warbling next to

236
00:12:18,080 --> 00:12:20,760
Speaker 1: them while the actual artists are on stage.

237
00:12:21,400 --> 00:12:25,440
Speaker 3: I save birthday songs from harps on my voicemail and

238
00:12:25,480 --> 00:12:26,560
Speaker 3: listen to them regularly.

239
00:12:26,840 --> 00:12:29,520
Speaker 4: Oh wow, that's really great. I didn't know that about you, Crego.

240
00:12:30,120 --> 00:12:34,559
Speaker 5: M It's true. She's denying it. But it's actually true.

241
00:12:35,520 --> 00:12:38,160
Speaker 4: True, So that's that's really impressive.

242
00:12:38,440 --> 00:12:40,440
Speaker 2: If you can, I think, if you can hold a tone,

243
00:12:40,720 --> 00:12:44,440
Speaker 2: even depending on your vocal range, just being able to

244
00:12:44,520 --> 00:12:47,079
Speaker 2: keep your voice in tone I think makes the biggest

245
00:12:47,080 --> 00:12:50,800
Speaker 2: difference as to listening experience is pleasurable or not. But

246
00:12:51,080 --> 00:12:55,680
Speaker 2: so this study showed that sharing music even virtually can

247
00:12:55,720 --> 00:13:00,559
Speaker 2: really enhance the pleasure. And we're talking about triggering in orphans.

248
00:13:00,800 --> 00:13:03,880
Speaker 2: It was a study published by e Science and they

249
00:13:03,920 --> 00:13:07,479
Speaker 2: looked across the effects with a number of different experiments

250
00:13:07,920 --> 00:13:10,720
Speaker 2: online with participants in the United States and France. So

251
00:13:11,240 --> 00:13:14,480
Speaker 2: even listening with somebody, So remember the old mixtapes and

252
00:13:15,760 --> 00:13:18,320
Speaker 2: you'd put a headphone in one ear and you'd share

253
00:13:18,360 --> 00:13:22,120
Speaker 2: the earpiece with another person, and then you wonder, that's.

254
00:13:21,920 --> 00:13:25,800
Speaker 1: God, you're you're so fucking old. But I remember that,

255
00:13:25,880 --> 00:13:28,400
Speaker 1: I remember, I remember this is how old I am.

256
00:13:28,440 --> 00:13:33,120
Speaker 1: Bro I remember making mixtapes, pressing play and record on

257
00:13:33,160 --> 00:13:35,720
Speaker 1: the cassette player off the radio.

258
00:13:35,960 --> 00:13:38,840
Speaker 4: Ye, me too, and then you just.

259
00:13:38,800 --> 00:13:41,040
Speaker 1: Missed the start of the song because the fucking DJ

260
00:13:41,280 --> 00:13:44,960
Speaker 1: was introing it right, and then they kind of just

261
00:13:45,120 --> 00:13:46,280
Speaker 1: wind it up a little bit.

262
00:13:47,160 --> 00:13:49,160
Speaker 4: Yeah, that was really annoying when they talked over the

263
00:13:49,160 --> 00:13:50,520
Speaker 4: intro to the Oh.

264
00:13:50,679 --> 00:13:54,720
Speaker 1: Yeah, yeah, yeah, those were the days though. That was

265
00:13:55,040 --> 00:13:58,880
Speaker 1: I mean, there's lots of research out on the relationship

266
00:13:59,040 --> 00:14:02,880
Speaker 1: or the impact of music on people's nervous system. So if,

267
00:14:02,880 --> 00:14:06,080
Speaker 1: for example, you hear something like ode to Join it, Like,

268
00:14:06,200 --> 00:14:09,679
Speaker 1: the interesting thing too, is it's like you might hear

269
00:14:09,720 --> 00:14:14,199
Speaker 1: a piece of music like somebody loves classical music, and

270
00:14:14,320 --> 00:14:19,880
Speaker 1: that switches on their parasympathetic you know, the calm parasympathetic

271
00:14:19,920 --> 00:14:22,880
Speaker 1: nervous system at lowers their heart rate, blood pressure, slows

272
00:14:22,920 --> 00:14:27,920
Speaker 1: their breathing, right, and that's because they love it. Somebody

273
00:14:28,000 --> 00:14:31,800
Speaker 1: else fucking hates it, right, and it does the opposite.

274
00:14:31,960 --> 00:14:36,119
Speaker 1: So it's not like this music produces a universal response.

275
00:14:36,920 --> 00:14:39,880
Speaker 1: Like some people love country and western it's all they

276
00:14:39,960 --> 00:14:43,120
Speaker 1: listen to. For other people, the same song is like,

277
00:14:43,520 --> 00:14:47,000
Speaker 1: you know, fingernails on a blackboard. So, but it is

278
00:14:47,040 --> 00:14:52,960
Speaker 1: interesting the way that your physiology responds to differently to

279
00:14:53,040 --> 00:14:54,800
Speaker 1: the same stimulus to someone else.

280
00:14:55,560 --> 00:14:57,520
Speaker 4: Well, it's amazing, that's said.

281
00:14:58,200 --> 00:15:00,680
Speaker 2: It's it's interesting that if you book a survey, and

282
00:15:00,720 --> 00:15:03,240
Speaker 2: that's why I like the top one hundred countdown, but

283
00:15:03,360 --> 00:15:07,920
Speaker 2: to have so many people vote and that number one

284
00:15:08,040 --> 00:15:11,119
Speaker 2: song being owed to Joy out of all their listenership,

285
00:15:11,160 --> 00:15:13,560
Speaker 2: and we're talking tens of thousands of people, hundreds of

286
00:15:13,560 --> 00:15:15,720
Speaker 2: thousands of people who vote on this.

287
00:15:15,840 --> 00:15:16,400
Speaker 4: I just thought it was.

288
00:15:16,440 --> 00:15:19,000
Speaker 2: Quite interesting because it's one that I would have put

289
00:15:19,040 --> 00:15:22,240
Speaker 2: it really high on the list for me. And it's

290
00:15:22,240 --> 00:15:24,280
Speaker 2: funny when people say that I don't like classical music

291
00:15:24,520 --> 00:15:27,320
Speaker 2: and then you say, oh, did you like that movie?

292
00:15:27,360 --> 00:15:30,000
Speaker 2: Turn the music down or turn the audio down when

293
00:15:30,040 --> 00:15:33,640
Speaker 2: you're watching a scary movie or an uplifting rom com

294
00:15:34,120 --> 00:15:38,240
Speaker 2: and the music just helps with the sense of the emotion.

295
00:15:38,600 --> 00:15:41,800
Speaker 2: If you watch something, you know, like a Stephen King

296
00:15:42,040 --> 00:15:45,440
Speaker 2: film and you turn the music if it's not scary anymore.

297
00:15:46,200 --> 00:15:51,360
Speaker 1: Yeah, that's true. I think also with research, I had

298
00:15:51,440 --> 00:15:54,800
Speaker 1: to be a fucking kill joy. But if you ask

299
00:15:54,960 --> 00:15:59,040
Speaker 1: that same question to a thousand people under thirty, you're

300
00:15:59,040 --> 00:16:01,040
Speaker 1: not getting owed to Joy as the answer.

301
00:16:01,760 --> 00:16:04,600
Speaker 2: But if they, if they hear it with the music

302
00:16:04,640 --> 00:16:07,080
Speaker 2: and the way that it's composed, still have that same effect.

303
00:16:07,640 --> 00:16:07,800
Speaker 4: Yeah.

304
00:16:07,920 --> 00:16:11,040
Speaker 1: Maybe, I mean it depends like it's like music is

305
00:16:11,080 --> 00:16:13,680
Speaker 1: a really powerful thing, isn't it, And it's like you.

306
00:16:13,720 --> 00:16:16,480
Speaker 2: Report next time I've got my sixteen year old in

307
00:16:16,640 --> 00:16:18,320
Speaker 2: I'm going to put a set of headphones on him,

308
00:16:18,320 --> 00:16:20,480
Speaker 2: and I'm going to play three pieces of music. You

309
00:16:20,520 --> 00:16:24,360
Speaker 2: guys choose one piece each. I'll choose the Joy. If

310
00:16:24,400 --> 00:16:27,400
Speaker 2: you guys want to choose one each, then I'll play

311
00:16:27,480 --> 00:16:29,560
Speaker 2: all three and we'll get him to do a rating

312
00:16:29,640 --> 00:16:32,000
Speaker 2: of one to ten on each piece of music, and

313
00:16:32,040 --> 00:16:33,920
Speaker 2: we'll see if the Joy comes out on top.

314
00:16:34,440 --> 00:16:41,280
Speaker 5: I don't choose the Boxer, what of course you do?

315
00:16:41,520 --> 00:16:43,560
Speaker 4: Come on, Craig, you got to choose a piece of music.

316
00:16:43,760 --> 00:16:47,880
Speaker 1: Just that one sixteen year old kid constitutes a study?

317
00:16:48,320 --> 00:16:49,200
Speaker 5: Any rand?

318
00:16:49,600 --> 00:16:51,200
Speaker 4: Okay, it's a mini study.

319
00:16:51,400 --> 00:16:55,920
Speaker 2: Come on, choose a piece of music on the spot.

320
00:16:56,680 --> 00:16:57,320
Speaker 1: Ala Lujah?

321
00:16:58,400 --> 00:17:01,080
Speaker 4: Oh no, that's true?

322
00:17:01,360 --> 00:17:06,800
Speaker 1: Yeah, all right, I will play all three, and but

323
00:17:06,880 --> 00:17:08,560
Speaker 1: I'm going to say I'm going to tell you which

324
00:17:08,720 --> 00:17:09,760
Speaker 1: version of Ala Lujah?

325
00:17:09,920 --> 00:17:12,680
Speaker 4: Okay, we'll go and then well, I've.

326
00:17:12,480 --> 00:17:15,880
Speaker 1: Got to find I've just got to find the right artist.

327
00:17:16,000 --> 00:17:18,879
Speaker 1: Not Katie Lang. She does a good version, but there

328
00:17:18,880 --> 00:17:19,720
Speaker 1: are better versions.

329
00:17:19,960 --> 00:17:20,600
Speaker 4: All right? Done?

330
00:17:20,920 --> 00:17:23,080
Speaker 2: Can I give a shout out to the Dale Patterson

331
00:17:23,119 --> 00:17:24,520
Speaker 2: who sent me a link.

332
00:17:24,640 --> 00:17:26,760
Speaker 4: He's one of our listeners from Geelong and he sent

333
00:17:26,800 --> 00:17:27,480
Speaker 4: me a link.

334
00:17:27,280 --> 00:17:31,160
Speaker 2: To a really cool tech website which was really interesting

335
00:17:31,320 --> 00:17:31,760
Speaker 2: so I.

336
00:17:31,640 --> 00:17:33,760
Speaker 1: Love how you say can I and then you do it.

337
00:17:33,840 --> 00:17:43,679
Speaker 1: No you can't, can't fiance, No, no, you can't shout

338
00:17:43,720 --> 00:17:46,720
Speaker 1: out to Dale? What what was Dale emailing you about?

339
00:17:47,240 --> 00:17:51,320
Speaker 4: A tech website? Just lots of gadgets and stuff.

340
00:17:51,400 --> 00:17:54,639
Speaker 2: Of course, a fellow geek is he I don't know.

341
00:17:55,200 --> 00:17:57,240
Speaker 2: Wouldn't want to wrap him up in that bundle. I

342
00:17:57,240 --> 00:17:59,200
Speaker 2: don't think that's very nice. I don't know him. He

343
00:17:59,280 --> 00:18:01,359
Speaker 2: could be a a nice, interesting person.

344
00:18:01,560 --> 00:18:04,280
Speaker 1: And I love geeks. We love geeks. We love you. Hey.

345
00:18:04,280 --> 00:18:06,439
Speaker 1: One of the things that I've been interested in and

346
00:18:06,440 --> 00:18:09,760
Speaker 1: we've spoken about, I think once or twice maybe, or

347
00:18:09,800 --> 00:18:12,159
Speaker 1: maybe we haven't, but I feel like we have is

348
00:18:12,320 --> 00:18:17,160
Speaker 1: animals and language and how elephants have their own language,

349
00:18:17,320 --> 00:18:22,040
Speaker 1: dolphins have their own language. And I think you have

350
00:18:22,119 --> 00:18:23,280
Speaker 1: a story in the space.

351
00:18:23,840 --> 00:18:26,400
Speaker 2: Well, just there's a nice little seguay to that too.

352
00:18:26,400 --> 00:18:29,200
Speaker 2: Do you know elephants? Actually, it's now thought they have names.

353
00:18:29,520 --> 00:18:32,040
Speaker 2: They name each other, so they rock up in the

354
00:18:32,040 --> 00:18:34,239
Speaker 2: middle of the jungle and say, hey, Bob, how are

355
00:18:34,280 --> 00:18:35,080
Speaker 2: you not too bad?

356
00:18:35,119 --> 00:18:37,479
Speaker 4: Betty? Now it's interesting, isn't it.

357
00:18:37,520 --> 00:18:41,280
Speaker 2: But I do have a story about this, because look

358
00:18:42,000 --> 00:18:45,520
Speaker 2: for me, I reckon, I've got a good handle on

359
00:18:46,320 --> 00:18:49,679
Speaker 2: the kind of mood that Fritz is in. And you

360
00:18:49,720 --> 00:18:52,240
Speaker 2: know when a dog wags its tail and has all

361
00:18:52,240 --> 00:18:55,800
Speaker 2: these different cues. As a dog owner is a pet owner, tiff,

362
00:18:55,960 --> 00:18:58,040
Speaker 2: you would have a fairly good indication as to whether

363
00:18:58,080 --> 00:19:00,520
Speaker 2: your pet's happy or sad or excited, idable and all

364
00:19:00,560 --> 00:19:03,240
Speaker 2: that sort of stuff. But it's now thought that AI

365
00:19:03,800 --> 00:19:10,040
Speaker 2: potentially could actually translate what a dog is saying when

366
00:19:10,040 --> 00:19:10,640
Speaker 2: it barks.

367
00:19:10,920 --> 00:19:14,000
Speaker 4: So imagine that if with every bark.

368
00:19:13,840 --> 00:19:17,720
Speaker 2: A wine, or a growl, you could even know what

369
00:19:17,840 --> 00:19:20,760
Speaker 2: the dog is effectively trying to communicate to you, and

370
00:19:20,800 --> 00:19:23,280
Speaker 2: then in the future they could even.

371
00:19:23,040 --> 00:19:24,720
Speaker 4: Translate what craigs say.

372
00:19:25,280 --> 00:19:28,480
Speaker 2: No, But when you think about it, using AI to

373
00:19:28,600 --> 00:19:33,120
Speaker 2: analyze the tonal vocalizations of dogs, they say they can

374
00:19:33,640 --> 00:19:40,760
Speaker 2: distinguish between playful barks, aggressive growls, identify characteristics and even

375
00:19:40,800 --> 00:19:43,080
Speaker 2: the age and the breed of the dog by the

376
00:19:43,119 --> 00:19:44,400
Speaker 2: sound that it makes.

377
00:19:44,840 --> 00:19:48,160
Speaker 1: Wow, here's what dog dogs are saying. Four things right.

378
00:19:48,200 --> 00:19:52,720
Speaker 1: Dogs are saying I need a shit. Yeah, they're saying

379
00:19:52,840 --> 00:19:55,160
Speaker 1: I want to go for a walk, give me some

380
00:19:55,200 --> 00:19:58,720
Speaker 1: fucking food, and I love you. That's the four things

381
00:19:58,760 --> 00:20:04,119
Speaker 1: dogs are saying. So you're welcome. I just broke the code.

382
00:20:04,520 --> 00:20:08,119
Speaker 4: But you know, when a dog wags its tail, most

383
00:20:08,160 --> 00:20:11,639
Speaker 4: people associate that with being excited. So you meet a

384
00:20:11,640 --> 00:20:14,679
Speaker 4: new dog and the tail starts wagging. But what people

385
00:20:14,720 --> 00:20:18,359
Speaker 4: don't realize is depending on which way the tail is

386
00:20:18,440 --> 00:20:21,040
Speaker 4: leaning to so it will predominantly go left or right,

387
00:20:21,480 --> 00:20:26,240
Speaker 4: can actually mean apprehensive and potentially be not so much

388
00:20:26,240 --> 00:20:28,560
Speaker 4: a show of aggression but a show of apprehension.

389
00:20:28,760 --> 00:20:31,959
Speaker 2: So when two dogs meet each other, the tail can

390
00:20:32,000 --> 00:20:35,000
Speaker 2: be wagging, but it doesn't necessarily mean they're happy. It

391
00:20:35,040 --> 00:20:37,920
Speaker 2: could mean that they're apprehensive about meeting the other dog

392
00:20:38,040 --> 00:20:40,280
Speaker 2: or the situation that they're in, just by which way

393
00:20:40,320 --> 00:20:41,040
Speaker 2: the tail goes.

394
00:20:41,680 --> 00:20:42,960
Speaker 4: So yes and no.

395
00:20:43,680 --> 00:20:46,320
Speaker 1: Well, when I introduce you to new people, I always

396
00:20:46,320 --> 00:20:49,479
Speaker 1: look at the way that your tail wags, and I

397
00:20:49,480 --> 00:20:52,080
Speaker 1: can tell if you're a little bit kind of like

398
00:20:52,760 --> 00:20:57,840
Speaker 1: fearful or joyful. That's why I always walk around the back.

399
00:21:01,000 --> 00:21:03,800
Speaker 2: You know, there's a thing that people get dressed up

400
00:21:03,840 --> 00:21:06,760
Speaker 2: as what do they call that up play?

401
00:21:06,920 --> 00:21:10,840
Speaker 1: Is that it Well, there are people that let's not open.

402
00:21:10,880 --> 00:21:11,879
Speaker 1: That let's not open?

403
00:21:13,200 --> 00:21:15,320
Speaker 4: Can we can we continue on the AI theme.

404
00:21:15,840 --> 00:21:19,120
Speaker 2: I thought this was really awesome because I think probably

405
00:21:19,119 --> 00:21:22,320
Speaker 2: about a year ago, there was a photographer who entered

406
00:21:22,400 --> 00:21:27,960
Speaker 2: a photo competition with an AI image and won it,

407
00:21:28,720 --> 00:21:31,639
Speaker 2: and of course then it was revealed that the photo

408
00:21:31,760 --> 00:21:34,280
Speaker 2: wasn't a real photograph, it had been generated by AI,

409
00:21:34,359 --> 00:21:36,159
Speaker 2: and then he was disqualified and it made all the

410
00:21:36,160 --> 00:21:40,160
Speaker 2: headlines and there's all this controversy. Well, a different photographer,

411
00:21:40,400 --> 00:21:42,400
Speaker 2: a guy by the name of Miles Astra, has done

412
00:21:42,400 --> 00:21:46,440
Speaker 2: the exact opposite. He's entered a photo competition where there

413
00:21:46,520 --> 00:21:51,240
Speaker 2: was a category for AI generated artwork or AI generated photography,

414
00:21:51,480 --> 00:21:54,560
Speaker 2: but he put a real image in and he won competition,

415
00:21:54,880 --> 00:21:58,600
Speaker 2: and it was this really amazing photograph of a pink flamingo,

416
00:21:59,160 --> 00:22:03,000
Speaker 2: and the judges and everybody thought, this is fantastic.

417
00:22:03,440 --> 00:22:04,719
Speaker 4: Is an AI amazing?

418
00:22:05,000 --> 00:22:08,359
Speaker 2: And the photographer said he actually it was a real photograph,

419
00:22:08,440 --> 00:22:11,760
Speaker 2: and so he then got disqualified for submitting a real

420
00:22:11,800 --> 00:22:13,719
Speaker 2: photograph in an AI competition.

421
00:22:13,760 --> 00:22:15,600
Speaker 4: So I thought, it's kind of interesting that.

422
00:22:16,119 --> 00:22:18,960
Speaker 2: And we're not talking just run of the mill people

423
00:22:19,000 --> 00:22:23,280
Speaker 2: off the street, you and me. We're talking about some

424
00:22:23,400 --> 00:22:27,400
Speaker 2: pretty smart people from Getty Images, the New York Times,

425
00:22:28,200 --> 00:22:31,440
Speaker 2: you know, Christie's. So the judges knew what they were

426
00:22:31,480 --> 00:22:34,160
Speaker 2: talking about, and they kind of had a real sense of.

427
00:22:34,080 --> 00:22:35,679
Speaker 4: What a good photograph is.

428
00:22:36,320 --> 00:22:38,080
Speaker 2: But I just thought it was kind of great to

429
00:22:38,600 --> 00:22:40,960
Speaker 2: flip it around and that this photographer came up with

430
00:22:41,000 --> 00:22:43,440
Speaker 2: the idea. So this guy Miles Astray and.

431
00:22:43,720 --> 00:22:44,479
Speaker 4: Yeah, good on him.

432
00:22:44,560 --> 00:22:49,440
Speaker 2: It was the eighteen thirty nine Color Photography Awards, and

433
00:22:49,680 --> 00:22:51,560
Speaker 2: so he actually won two categories.

434
00:22:51,720 --> 00:22:53,240
Speaker 4: One is he came third in.

435
00:22:53,240 --> 00:22:57,000
Speaker 2: The I think it was the judges Award, and then

436
00:22:57,040 --> 00:22:59,880
Speaker 2: he came first in the People's Vote Award.

437
00:23:00,359 --> 00:23:02,040
Speaker 4: So everyone was fulled.

438
00:23:02,400 --> 00:23:04,760
Speaker 1: Everyone was tricked. I don't know that that's going to

439
00:23:04,760 --> 00:23:08,680
Speaker 1: happen too often moving forward, but I like real photography. Hey,

440
00:23:09,960 --> 00:23:12,200
Speaker 1: I don't really know what this is about, and this

441
00:23:12,280 --> 00:23:14,679
Speaker 1: isn't on our list of things to chat about, but

442
00:23:14,760 --> 00:23:18,800
Speaker 1: maybe you know. So Melissa who is like the Apple queen,

443
00:23:19,560 --> 00:23:23,479
Speaker 1: Like if you could marry Apple, Melissa would marry Apple.

444
00:23:24,000 --> 00:23:27,960
Speaker 4: I've got competition. What I've got competition?

445
00:23:28,440 --> 00:23:32,879
Speaker 1: Oh she is? She crushes so hard. You know Apple

446
00:23:33,040 --> 00:23:36,760
Speaker 1: is gay as well, right, Well, if Apple brought out

447
00:23:37,160 --> 00:23:39,760
Speaker 1: a toilet, she'd get an Apple toilet, like she would

448
00:23:39,800 --> 00:23:45,680
Speaker 1: get any Apple product. But this week, didn't Apple launch something.

449
00:23:46,800 --> 00:23:50,520
Speaker 1: Didn't they wheel out something like their version of chat

450
00:23:50,600 --> 00:23:52,320
Speaker 1: GPT or some verged it.

451
00:23:52,440 --> 00:23:53,880
Speaker 4: Yeah, This is really controversial.

452
00:23:53,920 --> 00:23:55,320
Speaker 2: In fact, it was something that I was going to

453
00:23:55,320 --> 00:24:00,400
Speaker 2: talk about because what's happened is they've basically Apple has

454
00:24:00,440 --> 00:24:02,440
Speaker 2: this big event and it talks about all their new

455
00:24:02,520 --> 00:24:05,000
Speaker 2: up and coming stuff, and one of the things they're

456
00:24:05,040 --> 00:24:09,080
Speaker 2: talking about is merging AI into the Siri operating system,

457
00:24:09,720 --> 00:24:12,960
Speaker 2: so they're taking the next so it's a big makeover

458
00:24:13,080 --> 00:24:13,560
Speaker 2: for Siri.

459
00:24:14,400 --> 00:24:16,040
Speaker 4: So effectively, what.

460
00:24:15,960 --> 00:24:18,280
Speaker 2: It's going to do is going to make Siri more natural,

461
00:24:18,560 --> 00:24:20,920
Speaker 2: more relevant, they're saying, more personal.

462
00:24:21,320 --> 00:24:22,320
Speaker 4: It's got a new look.

463
00:24:22,920 --> 00:24:26,399
Speaker 2: The icon's been made to look different and it glows better.

464
00:24:26,680 --> 00:24:28,760
Speaker 2: But what they're saying now is that you can also

465
00:24:28,840 --> 00:24:31,400
Speaker 2: handle things like stumbles in speech, so if someone has

466
00:24:31,400 --> 00:24:36,000
Speaker 2: a stutter, it'll better understand context. And you can also

467
00:24:36,200 --> 00:24:38,320
Speaker 2: type to Syria, and it can answer questions about how

468
00:24:38,320 --> 00:24:41,640
Speaker 2: you use your iPhone and you iMac and your iPad

469
00:24:41,640 --> 00:24:41,960
Speaker 2: and all.

470
00:24:41,840 --> 00:24:42,440
Speaker 4: That sort of thing.

471
00:24:42,640 --> 00:24:44,080
Speaker 2: The other thing it'll also be able to do is

472
00:24:44,119 --> 00:24:48,160
Speaker 2: interact with the other apps on your phone, so that's

473
00:24:48,160 --> 00:24:49,920
Speaker 2: one of the things that Siri hasn't been able to

474
00:24:49,960 --> 00:24:51,600
Speaker 2: do in the past. So you can get it to

475
00:24:51,680 --> 00:24:54,439
Speaker 2: go and interact with other apps, and it's going to

476
00:24:54,480 --> 00:24:56,760
Speaker 2: make the user experience a lot better.

477
00:24:57,200 --> 00:24:59,760
Speaker 4: However, there is a little bit of controversy.

478
00:24:59,800 --> 00:25:02,679
Speaker 2: Now we know that Elon Musk loves to be the

479
00:25:02,720 --> 00:25:04,000
Speaker 2: controversial person, but.

480
00:25:03,960 --> 00:25:05,040
Speaker 4: He's come out.

481
00:25:05,080 --> 00:25:08,639
Speaker 2: Elon Musk has this love hate relationship with AI, so

482
00:25:09,160 --> 00:25:12,960
Speaker 2: he effectively a second This was announced by Apple within hours,

483
00:25:13,359 --> 00:25:17,560
Speaker 2: He's tweeted about saying that he's going to cancel iPhones,

484
00:25:17,960 --> 00:25:20,040
Speaker 2: that none of his staff will be allowed to bring

485
00:25:20,119 --> 00:25:23,080
Speaker 2: iPhones into the building and if they do, they'll be

486
00:25:23,160 --> 00:25:24,440
Speaker 2: told to take out.

487
00:25:24,240 --> 00:25:26,600
Speaker 4: Their iPhones and their iPhones will be put in a

488
00:25:26,640 --> 00:25:30,840
Speaker 4: Faraday cage. Do you know what a Faraday cage is? Yeah?

489
00:25:31,680 --> 00:25:35,280
Speaker 1: Yeah, yeah, So they's yeah, like, but nobody will be

490
00:25:35,320 --> 00:25:40,160
Speaker 1: allowed to enter any of his buildings, like customers, nobody

491
00:25:40,240 --> 00:25:41,640
Speaker 1: with an Apple product.

492
00:25:42,119 --> 00:25:46,560
Speaker 2: Yeah yeah, I mean mind you he's I think he's

493
00:25:47,080 --> 00:25:51,720
Speaker 2: suing open AI or there's some sort of case going

494
00:25:51,760 --> 00:25:52,359
Speaker 2: on at the moment.

495
00:25:52,359 --> 00:25:54,080
Speaker 4: So there's there's a bit of bad blood there.

496
00:25:54,119 --> 00:25:57,160
Speaker 2: But the reason he says that he doesn't want this

497
00:25:57,400 --> 00:26:00,399
Speaker 2: integration or he thinks it's a bad thing, is that

498
00:26:00,480 --> 00:26:03,280
Speaker 2: he feels that effectively, what it's going to do is

499
00:26:03,320 --> 00:26:06,600
Speaker 2: it's just going to make them spying devices. He says

500
00:26:06,720 --> 00:26:10,640
Speaker 2: that you know effectively it's just going to to kind

501
00:26:10,680 --> 00:26:12,879
Speaker 2: of run a muck and that people will be able

502
00:26:12,960 --> 00:26:15,320
Speaker 2: to spy on him using their iPhones.

503
00:26:15,960 --> 00:26:19,600
Speaker 1: Do you know what I've noticed recently using chat GPT

504
00:26:19,880 --> 00:26:27,000
Speaker 1: four point zero. Patrick James is that old mate who

505
00:26:27,040 --> 00:26:30,000
Speaker 1: sounds like Tim Ferriss. That's the dude that talks to me,

506
00:26:30,160 --> 00:26:34,240
Speaker 1: sounds exactly like Tim Ferriss. He doesn't always get my

507
00:26:34,320 --> 00:26:39,720
Speaker 1: Australian accent. So sometimes I just need to americanize the

508
00:26:39,880 --> 00:26:44,679
Speaker 1: question because I don't type. I usually just talk like

509
00:26:44,760 --> 00:26:46,639
Speaker 1: you know how you can just ask it a question

510
00:26:46,760 --> 00:26:50,080
Speaker 1: and then it types and gives audio for the answer.

511
00:26:50,960 --> 00:26:56,239
Speaker 1: So sometimes it says, oh, I think you're asking you know?

512
00:26:56,359 --> 00:26:59,639
Speaker 1: And then then I say it again with a less

513
00:27:00,160 --> 00:27:03,560
Speaker 1: Boganny voice, and it understands what I'm saying. So I

514
00:27:03,640 --> 00:27:08,960
Speaker 1: wonder if the new Apple product can understand Bogans. Maybe

515
00:27:09,600 --> 00:27:14,800
Speaker 1: probably a Bogan friendly Bogan friendly AI. I bet they

516
00:27:14,840 --> 00:27:16,480
Speaker 1: don't even know what that is over there?

517
00:27:16,720 --> 00:27:18,440
Speaker 4: Not a chance if you were going to say something,

518
00:27:18,480 --> 00:27:19,040
Speaker 4: because I.

519
00:27:18,960 --> 00:27:21,080
Speaker 3: Was going to say joy, let everyone else know? Could

520
00:27:21,040 --> 00:27:23,480
Speaker 3: I had to google it? Anyone that mightn't know what

521
00:27:23,520 --> 00:27:24,760
Speaker 3: a Faraday cage is?

522
00:27:26,800 --> 00:27:27,000
Speaker 4: Yeah?

523
00:27:27,600 --> 00:27:29,919
Speaker 2: Yeah, okay, So Faraday cage if you can imagine just

524
00:27:29,960 --> 00:27:32,600
Speaker 2: a wire mesh around you.

525
00:27:32,640 --> 00:27:34,720
Speaker 4: So they usually use them during experiments.

526
00:27:34,920 --> 00:27:37,520
Speaker 2: So if you were you know how you can have

527
00:27:37,680 --> 00:27:40,720
Speaker 2: like a basically, if you if you had lightning come down,

528
00:27:41,040 --> 00:27:43,520
Speaker 2: you could protect yourself inside a Faraday cage. So it

529
00:27:43,640 --> 00:27:46,480
Speaker 2: insulates you from an electrical discharge.

530
00:27:46,560 --> 00:27:49,480
Speaker 4: Is that all the right answer, Tiff?

531
00:27:49,720 --> 00:27:50,399
Speaker 5: Yeah, yeah it is.

532
00:27:50,480 --> 00:27:54,400
Speaker 3: Yeah, it protects from an electromagnetic radiation and if you're interference.

533
00:27:54,720 --> 00:27:56,520
Speaker 3: I was thinking it might just be a lock box,

534
00:27:56,560 --> 00:27:58,800
Speaker 3: and I thought I might get one for chocolate around here, But.

535
00:27:59,640 --> 00:28:01,720
Speaker 4: Have you your chocolate from last weekend already?

536
00:28:02,000 --> 00:28:05,040
Speaker 2: I ate it on the way home, so did I

537
00:28:05,240 --> 00:28:07,359
Speaker 2: didn't get out of the car, so we bought chocolate

538
00:28:07,400 --> 00:28:10,359
Speaker 2: at the chocolate shop. Mine didn't make it back to

539
00:28:10,400 --> 00:28:13,080
Speaker 2: the land. It was only about forty five minutes away.

540
00:28:13,400 --> 00:28:14,280
Speaker 5: One didn't even.

541
00:28:14,119 --> 00:28:17,439
Speaker 3: Make it out of Castle Maye or Castle Maine if

542
00:28:17,440 --> 00:28:17,959
Speaker 3: you're fancy.

543
00:28:18,080 --> 00:28:20,080
Speaker 4: Oh yeah, is it Castle made or Castle Maine?

544
00:28:20,080 --> 00:28:22,720
Speaker 2: Maybe someone from Castle Maine or Castle Magan tell us,

545
00:28:23,200 --> 00:28:26,080
Speaker 2: I never know, Crag, I said.

546
00:28:25,920 --> 00:28:26,480
Speaker 1: Was it?

547
00:28:26,480 --> 00:28:26,840
Speaker 4: Well?

548
00:28:27,000 --> 00:28:30,160
Speaker 1: It? I think people from up there call it castle.

549
00:28:31,320 --> 00:28:34,360
Speaker 1: I'm a bogan, so I call it castle. But I

550
00:28:34,400 --> 00:28:37,200
Speaker 1: think interestingly. And this's got nothing to do with tech.

551
00:28:37,280 --> 00:28:39,880
Speaker 1: But remember if that dude we had on I think

552
00:28:39,920 --> 00:28:44,680
Speaker 1: his name is Dean Morby, the Power Left to Do. Yeah, yeah, yeah,

553
00:28:44,720 --> 00:28:47,800
Speaker 1: he's from Castle, Maine and all these homies up there,

554
00:28:47,840 --> 00:28:50,880
Speaker 1: so shout out to I mean, this is just we'll

555
00:28:51,000 --> 00:28:54,000
Speaker 1: come back in thirty seconds, Patrick. But this guy trains

556
00:28:54,040 --> 00:28:58,040
Speaker 1: a whole lot of older citizens, a lot of fifty plus,

557
00:28:58,120 --> 00:29:01,880
Speaker 1: sixty seventy plus, and he's basically well last time I

558
00:29:01,920 --> 00:29:03,960
Speaker 1: spoke to him. Anyway, I assume he's still doing it.

559
00:29:04,040 --> 00:29:09,280
Speaker 1: He had essentially a power lifting Jim Castle May Yeah,

560
00:29:09,320 --> 00:29:15,520
Speaker 1: for all these old people, and yeah, what's that? What

561
00:29:15,560 --> 00:29:16,000
Speaker 1: are you doing?

562
00:29:16,160 --> 00:29:16,560
Speaker 5: Castle?

563
00:29:17,960 --> 00:29:22,400
Speaker 2: I looked up how to pronounce Castlemaine and that's what

564
00:29:22,400 --> 00:29:23,640
Speaker 2: it came up as.

565
00:29:23,840 --> 00:29:25,960
Speaker 1: Castle Maine. It's brittish.

566
00:29:26,280 --> 00:29:28,360
Speaker 4: How can that work now? And it didn't work earlier?

567
00:29:28,520 --> 00:29:31,360
Speaker 2: So I was only playing it so I could listen

568
00:29:31,360 --> 00:29:33,240
Speaker 2: to it myself, and I didn't realize you guys could

569
00:29:33,240 --> 00:29:34,760
Speaker 2: hear it. But just for the sake of those people

570
00:29:34,760 --> 00:29:37,200
Speaker 2: who didn't hear it the first time, Castle.

571
00:29:36,840 --> 00:29:38,640
Speaker 5: Maine, I.

572
00:29:40,440 --> 00:29:44,360
Speaker 1: Think everyone, all right, that's enough now, Patrick, I think

573
00:29:44,480 --> 00:29:49,800
Speaker 1: everyone in the world other than nausies pronounces it parcel Maine.

574
00:29:51,040 --> 00:29:58,800
Speaker 1: I think all right, back on Bogan, Bogan Bergan, Like,

575
00:29:58,880 --> 00:30:02,040
Speaker 1: what's hilarious is when posh person says bogan, So it

576
00:30:02,080 --> 00:30:04,720
Speaker 1: doesn't sound like crass anymore?

577
00:30:05,600 --> 00:30:08,520
Speaker 5: And can you make it pronounce the sea word? That trick?

578
00:30:09,320 --> 00:30:13,400
Speaker 1: No, no, tiff? When did you become me?

579
00:30:14,000 --> 00:30:18,320
Speaker 5: Sounds so polite? I thought it might really soundly polite.

580
00:30:18,440 --> 00:30:22,040
Speaker 4: But genuinely speaking, you don't want to see your does Craig?

581
00:30:24,240 --> 00:30:24,400
Speaker 3: Oh?

582
00:30:24,440 --> 00:30:26,280
Speaker 4: Sorry you said the sea thing? I thought you meant craig.

583
00:30:28,840 --> 00:30:34,600
Speaker 1: God, I'm fucking copying it today. What's a collective noun

584
00:30:34,720 --> 00:30:40,920
Speaker 1: for bogan heard bogue? No, not the not the plural,

585
00:30:41,080 --> 00:30:45,360
Speaker 1: the collective noun, I don't know. Like a flock, a flotilla,

586
00:30:45,440 --> 00:30:52,000
Speaker 1: a murder, a gaggle of craigs, a gaggle of cra Yeah,

587
00:30:52,280 --> 00:30:55,920
Speaker 1: for sure it would be what about all right? Come on?

588
00:30:55,960 --> 00:30:57,920
Speaker 1: Can we get back on this terrible?

589
00:30:58,120 --> 00:31:01,000
Speaker 4: Are we scared about the Siri AI integration?

590
00:31:01,160 --> 00:31:03,520
Speaker 2: Do you want your phone knowing everything and being able

591
00:31:03,560 --> 00:31:06,440
Speaker 2: to do stuff without you even needing to ask it

592
00:31:06,480 --> 00:31:07,040
Speaker 2: to tip?

593
00:31:07,600 --> 00:31:08,040
Speaker 1: Ah?

594
00:31:08,160 --> 00:31:11,320
Speaker 5: Yeah, it's a bit weird, isn't it. I don't know what.

595
00:31:11,280 --> 00:31:14,560
Speaker 1: Does that mean though? Being able to without being without

596
00:31:14,600 --> 00:31:15,120
Speaker 1: asking it.

597
00:31:15,440 --> 00:31:18,440
Speaker 2: Well, okay, so we spoke about this a couple of

598
00:31:18,440 --> 00:31:22,320
Speaker 2: weeks ago. When I recently had an update to Android

599
00:31:22,360 --> 00:31:25,560
Speaker 2: Auto in my car using my Android phone, I had

600
00:31:25,600 --> 00:31:27,600
Speaker 2: a whole lot of text messages come through from a

601
00:31:27,640 --> 00:31:30,920
Speaker 2: single person. Because young people don't send one text, they

602
00:31:31,080 --> 00:31:34,160
Speaker 2: don't do a paragraph, they do line by line by line.

603
00:31:34,520 --> 00:31:38,480
Speaker 2: So a friend of mine sent me five text messages.

604
00:31:39,320 --> 00:31:39,520
Speaker 4: Right.

605
00:31:39,600 --> 00:31:43,640
Speaker 2: So my car then responded and said, you've just received

606
00:31:43,640 --> 00:31:45,520
Speaker 2: a whole lot of text messages from this person. Would

607
00:31:45,560 --> 00:31:48,760
Speaker 2: you like me to summarize what the conversation was about?

608
00:31:48,960 --> 00:31:52,000
Speaker 2: And I said, yeah, that's great, Google, go for it.

609
00:31:52,160 --> 00:31:55,120
Speaker 2: And it did. It summarized the whole thing, so rather

610
00:31:55,160 --> 00:31:58,640
Speaker 2: than bombarding me with five different text messages, it just

611
00:31:58,640 --> 00:32:00,680
Speaker 2: gave me the gist of what the conversation was about.

612
00:32:00,760 --> 00:32:03,880
Speaker 2: So that's where AI is being employed, and it's great

613
00:32:03,920 --> 00:32:06,520
Speaker 2: in the car, you don't want to be disturbed by

614
00:32:06,640 --> 00:32:09,600
Speaker 2: a stack of text messages. So I mean, that's just

615
00:32:09,640 --> 00:32:12,400
Speaker 2: one really simple example of potentially what.

616
00:32:12,400 --> 00:32:12,840
Speaker 4: It could do.

617
00:32:13,000 --> 00:32:18,240
Speaker 2: But I like the idea of a bogan translator or

618
00:32:18,360 --> 00:32:21,320
Speaker 2: you know what about if someone stutters and has an accent,

619
00:32:21,360 --> 00:32:24,000
Speaker 2: But those things actually do have a lot of and

620
00:32:24,040 --> 00:32:26,560
Speaker 2: a lot of merit because it's going to make life

621
00:32:26,600 --> 00:32:29,280
Speaker 2: a lot easier for people and more accessible. So it

622
00:32:29,320 --> 00:32:32,680
Speaker 2: will make that text sery or you know, or whatever

623
00:32:32,720 --> 00:32:35,840
Speaker 2: the android aut diversion is or android. So I kind

624
00:32:35,840 --> 00:32:39,360
Speaker 2: of like the idea ish. I think Elon Musk is

625
00:32:39,400 --> 00:32:42,560
Speaker 2: just doing the publicity stunt thing into.

626
00:32:42,320 --> 00:32:44,960
Speaker 1: What if there was a Seri or there was AI

627
00:32:45,120 --> 00:32:48,080
Speaker 1: that kind of had its own personality and some days

628
00:32:48,080 --> 00:32:50,880
Speaker 1: it was just like having a bad day. It's like

629
00:32:51,160 --> 00:32:53,680
Speaker 1: and you you know, you open it up and it goes,

630
00:32:53,720 --> 00:32:56,000
Speaker 1: what fucking what now?

631
00:32:56,400 --> 00:32:57,960
Speaker 2: But it'd be good if you could choose the mood

632
00:32:57,960 --> 00:33:00,600
Speaker 2: for the day to match your move, so you know,

633
00:33:00,680 --> 00:33:04,240
Speaker 2: the shitty mood, over the top nice mood.

634
00:33:05,320 --> 00:33:07,920
Speaker 4: You could do the TIFFs, the Patrick and the Greg mood.

635
00:33:08,520 --> 00:33:10,479
Speaker 1: What if you ask it a question and it's like,

636
00:33:10,560 --> 00:33:15,400
Speaker 1: that's a fucking stupid question. Try harder, Like seriously, you're

637
00:33:15,440 --> 00:33:19,000
Speaker 1: not asking me that, Like AI with attitude?

638
00:33:19,320 --> 00:33:20,400
Speaker 4: Can I make an admission?

639
00:33:20,680 --> 00:33:25,200
Speaker 2: So my identical twin brother, genetically identical to me, he

640
00:33:25,320 --> 00:33:27,000
Speaker 2: rang me up and he was telling me about a

641
00:33:27,040 --> 00:33:28,920
Speaker 2: tech problem that he had, and I got to the

642
00:33:28,960 --> 00:33:31,800
Speaker 2: point where I thought, how could you be so stupid and.

643
00:33:31,760 --> 00:33:34,320
Speaker 4: Not understand this because we're genetically identical.

644
00:33:34,760 --> 00:33:38,720
Speaker 2: It's like, you don't understand it.

645
00:33:39,920 --> 00:33:42,560
Speaker 1: Well, that's because you've exposed yourself to a lot of

646
00:33:42,680 --> 00:33:44,760
Speaker 1: training and education experience.

647
00:33:45,000 --> 00:33:47,080
Speaker 4: I should have listened to that whole sentence, shouldn't I have?

648
00:33:48,040 --> 00:33:51,400
Speaker 1: Well, you've you've got knowledge he hasn't. That's not about genetics.

649
00:33:51,400 --> 00:33:54,160
Speaker 1: That's just about what you've learned versus what he's learned.

650
00:33:54,200 --> 00:33:57,400
Speaker 2: It was pretty basically paste or something I don't know,

651
00:33:57,440 --> 00:34:01,400
Speaker 2: with something simple if you rolled his eyes and said, yeah,

652
00:34:01,400 --> 00:34:03,440
Speaker 2: I don't know how, he doesn't do it anyway.

653
00:34:04,800 --> 00:34:08,880
Speaker 4: All right, cybersecurity, let's talk about that.

654
00:34:09,320 --> 00:34:14,319
Speaker 2: Okay, Well, you have a business, a small business, a

655
00:34:14,400 --> 00:34:15,280
Speaker 2: business of sorts.

656
00:34:15,840 --> 00:34:17,520
Speaker 4: How CyberSecure are you?

657
00:34:17,600 --> 00:34:17,800
Speaker 2: Do you?

658
00:34:17,880 --> 00:34:18,200
Speaker 4: Reckon?

659
00:34:18,960 --> 00:34:22,080
Speaker 1: I'm not the person to ask. I'm about as CyberSecure

660
00:34:22,120 --> 00:34:26,439
Speaker 1: as a fucking box of clinics. That's out tough.

661
00:34:27,120 --> 00:34:28,319
Speaker 4: Do you think it's relevant though?

662
00:34:28,360 --> 00:34:31,600
Speaker 2: I mean, I'm probably asking a really obvious question because

663
00:34:31,680 --> 00:34:34,239
Speaker 2: if I know you've been through this whole debarcle and

664
00:34:34,280 --> 00:34:37,160
Speaker 2: the stress of having to go through this yourself. But

665
00:34:37,239 --> 00:34:39,959
Speaker 2: I think that well, there's a lot of warnings coming

666
00:34:39,960 --> 00:34:42,520
Speaker 2: out now and we're talking this is like across the board.

667
00:34:42,640 --> 00:34:45,960
Speaker 2: So this is from a government level, both in Australia

668
00:34:46,160 --> 00:34:49,799
Speaker 2: and also overseas as well. The United States has when

669
00:34:49,840 --> 00:34:52,839
Speaker 2: his cyber attacks were state driven. So what I'm saying

670
00:34:52,920 --> 00:34:56,239
Speaker 2: is it's not just independent. You know, some Russian bloke

671
00:34:56,320 --> 00:34:59,320
Speaker 2: sitting in his back shed trying to hack into your computer,

672
00:34:59,600 --> 00:35:04,319
Speaker 2: but these a state sanctioned where certain states well, and

673
00:35:04,360 --> 00:35:06,480
Speaker 2: it's kind of commonly known that China has a very

674
00:35:06,480 --> 00:35:11,120
Speaker 2: active operation in hacking as well, so state sanctioned hacking.

675
00:35:11,560 --> 00:35:16,000
Speaker 2: And I think more sixty percent of small business owners

676
00:35:16,000 --> 00:35:19,800
Speaker 2: say that hackers are their biggest fear. This was according

677
00:35:19,800 --> 00:35:23,440
Speaker 2: to the US Chamber of Commerce. But sixty percent is

678
00:35:23,480 --> 00:35:27,200
Speaker 2: a massive amount. And you heard about the hack recently

679
00:35:27,440 --> 00:35:30,560
Speaker 2: at the NHS in the UK. This only happened in

680
00:35:30,600 --> 00:35:36,160
Speaker 2: the last fortnight, so happened wassh Yeah? Anyway, the National

681
00:35:36,160 --> 00:35:39,719
Speaker 2: Health Service NHS was hacked into, but it was so

682
00:35:39,920 --> 00:35:43,360
Speaker 2: bad that they ended up resorting to using paper for

683
00:35:43,400 --> 00:35:47,000
Speaker 2: communications and people who were on waiting lists for surgery

684
00:35:47,040 --> 00:35:50,200
Speaker 2: had to be put off. It impacted and potentially could

685
00:35:50,200 --> 00:35:54,520
Speaker 2: have caused major problems for people who were needed urgent surgery.

686
00:35:54,840 --> 00:35:57,480
Speaker 2: And it makes you realize how vulnerable potentially we could

687
00:35:57,560 --> 00:36:01,960
Speaker 2: be whether it's public services, could be like our electricity supply, water,

688
00:36:02,040 --> 00:36:04,359
Speaker 2: that sort of stuff. So it kind of opens it up.

689
00:36:04,640 --> 00:36:07,960
Speaker 2: And when you run a small business, because you tend

690
00:36:08,080 --> 00:36:11,000
Speaker 2: not to have the infrastructure, you don't have somebody who's

691
00:36:11,080 --> 00:36:14,320
Speaker 2: running your IT network, that kind of tends.

692
00:36:14,040 --> 00:36:16,240
Speaker 4: To leave you more vulnerable as well.

693
00:36:16,440 --> 00:36:18,960
Speaker 2: So, I mean, it's something certainly that I've thought about,

694
00:36:18,960 --> 00:36:21,160
Speaker 2: but because I guess a little bit more tech savvy,

695
00:36:21,440 --> 00:36:25,280
Speaker 2: I think about the security implications of what it means

696
00:36:25,320 --> 00:36:28,399
Speaker 2: for the data that I store. But when you think

697
00:36:28,400 --> 00:36:31,880
Speaker 2: about all the data that you've got crago, you know,

698
00:36:31,920 --> 00:36:35,760
Speaker 2: your research at the moment, how are you protecting that research?

699
00:36:37,320 --> 00:36:41,560
Speaker 1: Yeah, so it's it is stored. I don't know. I

700
00:36:42,120 --> 00:36:44,839
Speaker 1: don't do that bit, but I don't know. I don't

701
00:36:44,880 --> 00:36:48,000
Speaker 1: know it's in a cupboard. I don't know a cyber cupboard.

702
00:36:48,200 --> 00:36:51,040
Speaker 1: I don't know, Patrick, I can don't ask me. I

703
00:36:51,120 --> 00:36:53,239
Speaker 1: know how to get into it and access it. It's

704
00:36:53,239 --> 00:36:56,840
Speaker 1: not my job. I don't do security. But it's funny

705
00:36:56,880 --> 00:36:59,239
Speaker 1: you asked, right, because I'm old. But then I think

706
00:36:59,280 --> 00:37:04,759
Speaker 1: about with the rapid evolution of computing, you know, quantum computers,

707
00:37:05,120 --> 00:37:10,160
Speaker 1: arriving next Wednesday, right, and the world is that like

708
00:37:10,239 --> 00:37:13,680
Speaker 1: the way that we buy and sell and bank and

709
00:37:14,480 --> 00:37:17,759
Speaker 1: you know, medicine and all of that. Like my dear

710
00:37:17,800 --> 00:37:22,160
Speaker 1: old mum and dad. I look at them, and twenty

711
00:37:22,360 --> 00:37:25,480
Speaker 1: twenty four is bewildering for my mum and dad. Like

712
00:37:25,520 --> 00:37:29,040
Speaker 1: it just that and they're not dumb people, but it's

713
00:37:29,320 --> 00:37:32,279
Speaker 1: just it's just I don't know. I don't know what

714
00:37:32,320 --> 00:37:36,400
Speaker 1: the answer is because we can't stop technological advancement. But

715
00:37:36,520 --> 00:37:40,920
Speaker 1: I feel so sorry. Like I went out two weekends

716
00:37:40,960 --> 00:37:42,879
Speaker 1: ago with mum and dad and their friends. So there

717
00:37:42,960 --> 00:37:45,800
Speaker 1: was like eight old people, I mean fucking old, fucking

718
00:37:46,000 --> 00:37:49,560
Speaker 1: old as fuck, like Noah's friends, right, Jesus is fucking

719
00:37:49,760 --> 00:37:54,400
Speaker 1: next door Nabors, right, and me and I was looking

720
00:37:54,440 --> 00:37:56,839
Speaker 1: around the table and I was trying to explain to

721
00:37:56,880 --> 00:38:01,560
Speaker 1: them what a podcast was, just something that simple. And

722
00:38:02,400 --> 00:38:04,759
Speaker 1: I'm not at all being rude because they're fucking you know,

723
00:38:04,840 --> 00:38:07,120
Speaker 1: in some ways they're way smarter than all of us, right,

724
00:38:07,200 --> 00:38:11,920
Speaker 1: but yeah, I like, fuck and this is essentially you know,

725
00:38:11,960 --> 00:38:13,880
Speaker 1: the best way you can explain it to them is

726
00:38:13,960 --> 00:38:15,960
Speaker 1: it's kind of like a radio show that you can

727
00:38:16,040 --> 00:38:19,680
Speaker 1: just listen to whenever you want, you know, but then

728
00:38:19,760 --> 00:38:21,799
Speaker 1: more how do you how do you? Where is it

729
00:38:21,840 --> 00:38:23,799
Speaker 1: on your phone? And then trying to go, well, so

730
00:38:23,920 --> 00:38:25,279
Speaker 1: there's an app, and then that's like.

731
00:38:25,360 --> 00:38:27,600
Speaker 4: Fuck, do they understand in streaming?

732
00:38:28,680 --> 00:38:32,400
Speaker 1: Not not kind of, but you know, like none of

733
00:38:32,440 --> 00:38:35,319
Speaker 1: them have Netflix, none of them have any of those platforms,

734
00:38:35,360 --> 00:38:38,840
Speaker 1: and so I guess theoretically, but even when you explain

735
00:38:38,920 --> 00:38:41,440
Speaker 1: to them something that for us and all of our listeners,

736
00:38:41,520 --> 00:38:45,560
Speaker 1: it's like, well, how could somebody not understand that? It's

737
00:38:45,560 --> 00:38:48,160
Speaker 1: a very different when you when you're trying to understand

738
00:38:48,160 --> 00:38:54,120
Speaker 1: an eighty five year old person's worldview thinking through like TIFFs,

739
00:38:54,320 --> 00:38:58,600
Speaker 1: you know, looking through TIFFs window, and she's probably more

740
00:38:58,640 --> 00:39:01,759
Speaker 1: compassionate and understanding, but you know what I mean, it's like, well,

741
00:39:01,800 --> 00:39:04,600
Speaker 1: of course this makes sense, but to them it makes

742
00:39:04,719 --> 00:39:07,200
Speaker 1: no sense, you know, And I just I don't know.

743
00:39:07,280 --> 00:39:09,960
Speaker 1: I think for me, that's something that I worry about

744
00:39:09,960 --> 00:39:14,000
Speaker 1: for really old people like Mum is terrified of paying

745
00:39:14,040 --> 00:39:17,720
Speaker 1: things electronically because she doesn't know what they're talking about,

746
00:39:18,200 --> 00:39:20,760
Speaker 1: and the people at the bank or whatever or medicare

747
00:39:20,880 --> 00:39:23,719
Speaker 1: they just talk to her like she's an idiot, because no,

748
00:39:23,880 --> 00:39:26,760
Speaker 1: you just do this, And they talked to her quickly

749
00:39:26,920 --> 00:39:30,960
Speaker 1: and dismissively, and she doesn't actually understand what it all means.

750
00:39:31,600 --> 00:39:33,400
Speaker 1: Can I just say they worries me?

751
00:39:33,960 --> 00:39:37,040
Speaker 4: Yeah? Can I just say too though? You do sometimes

752
00:39:37,080 --> 00:39:37,880
Speaker 4: have a choice.

753
00:39:37,960 --> 00:39:40,279
Speaker 2: And I'm not going to particularly name any of the

754
00:39:40,560 --> 00:39:43,239
Speaker 2: different banks, but you've got the Big four, and then

755
00:39:43,280 --> 00:39:45,880
Speaker 2: there are other banks as well, and there are community banks,

756
00:39:45,920 --> 00:39:48,720
Speaker 2: and sometimes it's about voting with your feet.

757
00:39:49,239 --> 00:39:52,080
Speaker 4: I recently had I live in a small town.

758
00:39:52,120 --> 00:39:54,359
Speaker 2: We only had two banks in our town, and the

759
00:39:54,400 --> 00:39:55,879
Speaker 2: big bank pulled out.

760
00:39:55,880 --> 00:39:58,040
Speaker 4: One of the Big four pulled out of the township.

761
00:39:58,320 --> 00:40:00,080
Speaker 2: So I pulled all of my money out of it

762
00:40:00,280 --> 00:40:02,000
Speaker 2: and put it into the local community bank.

763
00:40:02,040 --> 00:40:04,360
Speaker 4: I thought, you know what, bug you and I can walk.

764
00:40:04,200 --> 00:40:06,279
Speaker 2: In there any time of day and I see them

765
00:40:06,320 --> 00:40:11,520
Speaker 2: explaining things delicately, understanding they will talk them through you

766
00:40:11,719 --> 00:40:14,160
Speaker 2: for older people, because generally it's older people who want

767
00:40:14,160 --> 00:40:16,200
Speaker 2: to have that face to face. And I think that

768
00:40:16,239 --> 00:40:20,120
Speaker 2: there's still ways to shop around, to ask around and

769
00:40:20,200 --> 00:40:23,840
Speaker 2: not to get lumped in and be treated like that.

770
00:40:23,920 --> 00:40:26,120
Speaker 4: So if you go to a telco provider, there's a

771
00:40:26,120 --> 00:40:27,840
Speaker 4: lot of third party telco providers.

772
00:40:27,840 --> 00:40:29,839
Speaker 2: Now, if you walk in and you're not satisfied, because

773
00:40:29,840 --> 00:40:32,279
Speaker 2: you think you're being treated like a dummy, go somewhere else,

774
00:40:32,360 --> 00:40:33,120
Speaker 2: vote with your feet.

775
00:40:34,400 --> 00:40:36,560
Speaker 1: Everything you said makes sense to me. But if you

776
00:40:36,640 --> 00:40:38,560
Speaker 1: said to my mum and dad go to a third

777
00:40:38,600 --> 00:40:41,239
Speaker 1: party telco provider and vote with they'd be like, I

778
00:40:41,239 --> 00:40:43,120
Speaker 1: don't know what the fuck do you mean? I mean,

779
00:40:43,120 --> 00:40:45,640
Speaker 1: this is the point we all get that my mum

780
00:40:45,680 --> 00:40:48,960
Speaker 1: and dad do not understand anything you just said. So

781
00:40:49,000 --> 00:40:50,360
Speaker 1: that's the problem.

782
00:40:50,560 --> 00:40:53,759
Speaker 2: Yeah, can I You know, I was so excited by this.

783
00:40:54,239 --> 00:40:59,120
Speaker 2: The FBI recently hacked some hackers. And there are different

784
00:40:59,160 --> 00:41:02,440
Speaker 2: ways that hackers can get into your system. So, you know,

785
00:41:02,520 --> 00:41:04,560
Speaker 2: you click on a link and then they skim the

786
00:41:04,600 --> 00:41:06,799
Speaker 2: information they want to get your ID so they can

787
00:41:06,840 --> 00:41:09,279
Speaker 2: pretend that they're you. But the other thing they can

788
00:41:09,280 --> 00:41:11,799
Speaker 2: do is they use ransomware where they take all of

789
00:41:11,840 --> 00:41:14,360
Speaker 2: your data, they lock it up, they encrypt it, and

790
00:41:14,400 --> 00:41:17,919
Speaker 2: then they exploit that and say, well, if you want

791
00:41:17,920 --> 00:41:19,480
Speaker 2: your data back, you've got to pay.

792
00:41:19,320 --> 00:41:22,240
Speaker 4: Us X amount of dollars. Okay, so that's ransomware.

793
00:41:22,680 --> 00:41:26,000
Speaker 2: But now the FBI, I've managed to get seven thousand

794
00:41:26,160 --> 00:41:29,719
Speaker 2: key keys to ransomware and they're just giving them away

795
00:41:29,719 --> 00:41:33,320
Speaker 2: for free. So if someone a business, an individual, whatever

796
00:41:34,239 --> 00:41:38,719
Speaker 2: gets hacked and they have all their data locked up. Now,

797
00:41:38,760 --> 00:41:43,000
Speaker 2: the FBI has acts seven thousand ransomware keys, which I

798
00:41:43,000 --> 00:41:46,600
Speaker 2: thought was really good, so you can basically get access

799
00:41:46,640 --> 00:41:50,799
Speaker 2: to your data without having this whole ransom situation over

800
00:41:50,840 --> 00:41:52,600
Speaker 2: the top of you. So it's good to see that

801
00:41:52,680 --> 00:41:56,120
Speaker 2: the good guys, that the white hat hackers.

802
00:41:55,920 --> 00:42:00,840
Speaker 4: Are getting their way around some of the naughty people

803
00:42:00,840 --> 00:42:01,600
Speaker 4: out there. Crago.

804
00:42:02,120 --> 00:42:04,560
Speaker 1: I love that, and I like it that there are

805
00:42:04,600 --> 00:42:05,640
Speaker 1: white hat hackers.

806
00:42:06,120 --> 00:42:06,440
Speaker 4: Love it.

807
00:42:06,480 --> 00:42:09,280
Speaker 1: I love that idea. I did see on the news

808
00:42:09,400 --> 00:42:11,400
Speaker 1: on I don't know what channel it was, but and

809
00:42:11,440 --> 00:42:14,680
Speaker 1: it looked a bit weird to me this week a

810
00:42:14,800 --> 00:42:19,080
Speaker 1: robotic thumb that people were yes, so instead of having

811
00:42:19,880 --> 00:42:23,120
Speaker 1: four digits and one thumb, they had four fingers and

812
00:42:23,200 --> 00:42:26,880
Speaker 1: two thumbs on one. So they've now essentially got six

813
00:42:26,960 --> 00:42:30,640
Speaker 1: fingers on one hand. I'm not sure that's necessary, but

814
00:42:30,719 --> 00:42:32,040
Speaker 1: tell us about it. Yeah.

815
00:42:32,080 --> 00:42:34,520
Speaker 2: Well, so this study showed that ninety eight percent of

816
00:42:34,560 --> 00:42:36,799
Speaker 2: the people who took part in it were able to

817
00:42:37,239 --> 00:42:43,479
Speaker 2: more successfully manipulate objects with a third thumb, and only

818
00:42:43,520 --> 00:42:46,719
Speaker 2: thirteen people were unable to perform the task within the

819
00:42:46,719 --> 00:42:49,680
Speaker 2: first minutes. So people put on this glove, it gives

820
00:42:49,719 --> 00:42:53,319
Speaker 2: them an extra thumb, and within a minute, ninety eight

821
00:42:53,360 --> 00:42:57,200
Speaker 2: percent were able to use it more effectively than their

822
00:42:57,239 --> 00:43:01,800
Speaker 2: normal hand. So the dexterity was improved by having this augmentation,

823
00:43:02,480 --> 00:43:05,080
Speaker 2: so it could be used in lots of areas. And

824
00:43:05,120 --> 00:43:07,520
Speaker 2: they're saying that it's kind of like, you know, you're

825
00:43:07,600 --> 00:43:11,879
Speaker 2: grasping ability, so the dexterity was increased as well. It's

826
00:43:12,000 --> 00:43:14,960
Speaker 2: kind of really good. It's a robotic thumb. Would that

827
00:43:15,080 --> 00:43:15,840
Speaker 2: be great, wouldn't it?

828
00:43:16,400 --> 00:43:19,040
Speaker 1: Ah? I tell you who would love that? Mary for

829
00:43:19,160 --> 00:43:20,040
Speaker 1: opening jars?

830
00:43:20,560 --> 00:43:23,200
Speaker 4: Yes, exactly, so you get the double thumbs up. How

831
00:43:23,239 --> 00:43:23,640
Speaker 4: good's that?

832
00:43:25,440 --> 00:43:28,240
Speaker 1: I'm not even lying when I was up there last Saturday,

833
00:43:28,320 --> 00:43:31,400
Speaker 1: because I go every Saturday to take fucking hercules to

834
00:43:31,440 --> 00:43:37,440
Speaker 1: the gym Ronnie mcgronstar, And yeah, Mary asked me to

835
00:43:37,480 --> 00:43:40,040
Speaker 1: open multiple things because she was cooking, and you know

836
00:43:40,120 --> 00:43:42,360
Speaker 1: she takes out the jars of whatever out of the

837
00:43:42,400 --> 00:43:45,040
Speaker 1: fridge or the cupboard. I may as well just go

838
00:43:45,160 --> 00:43:47,919
Speaker 1: up there to open jars every Saturday and then drive home.

839
00:43:48,000 --> 00:43:51,800
Speaker 1: But if she had the robotic fucking thumb, she wouldn't

840
00:43:51,800 --> 00:43:54,400
Speaker 1: need me. I'd become redundant.

841
00:43:55,239 --> 00:43:58,359
Speaker 4: That's it, just a robotic thumb and that's all your work.

842
00:44:00,880 --> 00:44:04,000
Speaker 1: What role does Craig play is essentially a robotic thumb.

843
00:44:04,960 --> 00:44:06,160
Speaker 1: It comes at no cost.

844
00:44:06,920 --> 00:44:09,560
Speaker 2: It must be pretty easy to use if people only

845
00:44:09,600 --> 00:44:13,239
Speaker 2: took sixty seconds to be able to feel comfortable using it,

846
00:44:13,280 --> 00:44:15,400
Speaker 2: because I would think that if you had a glove

847
00:44:15,480 --> 00:44:17,920
Speaker 2: with an extra thumb pointing out, that would be weird.

848
00:44:18,400 --> 00:44:19,759
Speaker 4: But evidently not.

849
00:44:20,360 --> 00:44:24,000
Speaker 2: That says a lot about the user experience. If it's

850
00:44:24,000 --> 00:44:26,000
Speaker 2: that easy to pick up and start working with, don't

851
00:44:26,000 --> 00:44:26,360
Speaker 2: you reckon?

852
00:44:26,400 --> 00:44:30,440
Speaker 1: Well, yeah, I guess I mean more, I don't know,

853
00:44:30,520 --> 00:44:35,719
Speaker 1: maybe more importantly, like for people who like amputees who

854
00:44:35,760 --> 00:44:38,000
Speaker 1: have had accidents or whatever, you think, what are the

855
00:44:38,040 --> 00:44:43,920
Speaker 1: potential applications. There's a well known fuck. I think his

856
00:44:44,080 --> 00:44:48,719
Speaker 1: name is Paul Gelder. It might be he is a

857
00:44:48,800 --> 00:44:54,319
Speaker 1: guy who had one of his arms bitten off and

858
00:44:54,920 --> 00:44:57,440
Speaker 1: or like his forearm and hand and one of his

859
00:44:57,560 --> 00:45:01,760
Speaker 1: legs bitten off. Paul dig Gelder, Paul de Gelder, Thanks

860
00:45:01,800 --> 00:45:07,919
Speaker 1: tiff In believe it or not. Patrick Sidney Harbor shark

861
00:45:07,960 --> 00:45:13,080
Speaker 1: attack like like, imagine being fucking attacked by a shark

862
00:45:13,120 --> 00:45:16,920
Speaker 1: and he was a navy diver, but he's got these

863
00:45:17,239 --> 00:45:22,520
Speaker 1: motherfucker of a bionic end and he's jacked, like he's

864
00:45:22,560 --> 00:45:26,400
Speaker 1: this bit strong, jacked athletic dude. And he's got a

865
00:45:26,440 --> 00:45:30,800
Speaker 1: prosthetic bionic arm and hand and also a leg I think,

866
00:45:31,160 --> 00:45:34,319
Speaker 1: or just a prosthetic leg. But yeah, I think that's

867
00:45:34,360 --> 00:45:38,080
Speaker 1: one of the I think pretty soon we're going Look,

868
00:45:39,120 --> 00:45:41,359
Speaker 1: this is just what I think. I could be wildly wrong,

869
00:45:41,960 --> 00:45:45,760
Speaker 1: but I think we're going to see in the next

870
00:45:45,800 --> 00:45:50,440
Speaker 1: decade we're going to see quadriplegics walking through, you know,

871
00:45:50,520 --> 00:45:53,520
Speaker 1: with the stuff that they can now do with not

872
00:45:53,640 --> 00:45:56,920
Speaker 1: only the spine and the nervous system, but also robotics

873
00:45:56,960 --> 00:46:01,520
Speaker 1: and and you know, imagine, imagine people like our friend

874
00:46:01,560 --> 00:46:05,759
Speaker 1: tif Joel SARTI imagine, fuck, how good would that be

875
00:46:05,880 --> 00:46:08,160
Speaker 1: for him to be able to get to that point

876
00:46:08,200 --> 00:46:11,120
Speaker 1: in time? And Yeah, I think it's exciting. I think

877
00:46:11,160 --> 00:46:13,799
Speaker 1: for me, this is the well, one of the there's many,

878
00:46:13,840 --> 00:46:17,360
Speaker 1: but one of the upsides Patrick of like this kind

879
00:46:17,400 --> 00:46:21,279
Speaker 1: of genius that is coming online is that when we

880
00:46:21,360 --> 00:46:24,239
Speaker 1: can do stuff like help people walk that would never

881
00:46:24,320 --> 00:46:27,760
Speaker 1: have been able to walk, you know, for me, that's

882
00:46:27,360 --> 00:46:30,000
Speaker 1: it's it's all all the negative is worth it if

883
00:46:30,000 --> 00:46:31,200
Speaker 1: we can do things like that.

884
00:46:31,600 --> 00:46:33,600
Speaker 4: Yeah, and there's lots of different trains of thought too.

885
00:46:33,640 --> 00:46:38,040
Speaker 2: There's the exoskeleton where they basically have an exoskeleton around

886
00:46:38,120 --> 00:46:42,959
Speaker 2: the non functioning limbs, the legs. Of course, you could

887
00:46:42,960 --> 00:46:46,759
Speaker 2: then you know, match that up with say the brain implant,

888
00:46:47,080 --> 00:46:48,719
Speaker 2: so you do it that way. But but I think

889
00:46:48,760 --> 00:46:51,880
Speaker 2: we've spoken about this before as well, bypassing the injury

890
00:46:51,920 --> 00:46:55,240
Speaker 2: to the spine where you yeah, an ability to actually

891
00:46:55,280 --> 00:46:59,360
Speaker 2: have the nerve tissue connected and bypass the broken connection

892
00:46:59,480 --> 00:47:00,879
Speaker 2: there and so potentially that.

893
00:47:00,800 --> 00:47:03,560
Speaker 4: Could be as well. So I'm super exciting.

894
00:47:03,719 --> 00:47:06,800
Speaker 1: Yeah, and you think about the muscles, like, for example,

895
00:47:06,840 --> 00:47:10,800
Speaker 1: if somebody gets say a let's say between the shoulder blades,

896
00:47:10,840 --> 00:47:13,719
Speaker 1: so the thoracic so at T five or six, right,

897
00:47:14,480 --> 00:47:18,400
Speaker 1: and so they their arms work, but their legs don't work.

898
00:47:19,520 --> 00:47:23,279
Speaker 1: But their legs actually work. It's just that there's no

899
00:47:24,160 --> 00:47:27,719
Speaker 1: basically juice getting to the legs, you know. So as

900
00:47:27,760 --> 00:47:31,759
Speaker 1: you said, like the actual muscles, there's nothing wrong with

901
00:47:31,840 --> 00:47:34,960
Speaker 1: the muscles, they're just not getting any neural connection for

902
00:47:35,040 --> 00:47:38,359
Speaker 1: the brain to make the legs work. So yeah, if

903
00:47:38,360 --> 00:47:40,920
Speaker 1: you could build a little kind of a neural bridge

904
00:47:41,360 --> 00:47:46,439
Speaker 1: over that break so that that signal gets through, I mean,

905
00:47:46,600 --> 00:47:48,520
Speaker 1: I reckon you and I could probably figure that out

906
00:47:48,520 --> 00:47:50,640
Speaker 1: on a weekend. If we really put our minds.

907
00:47:50,400 --> 00:47:54,160
Speaker 5: To it, can get the crab to build it.

908
00:47:55,560 --> 00:48:00,879
Speaker 1: Exactly. I could conceptualize it. You know, I do work

909
00:48:00,880 --> 00:48:03,200
Speaker 1: at Brain Park or I do research at Brain Park,

910
00:48:03,280 --> 00:48:05,600
Speaker 1: So fuck, how hard can it be? I'm kidding everyone,

911
00:48:05,640 --> 00:48:07,280
Speaker 1: Please don't send me hate emails.

912
00:48:07,600 --> 00:48:11,200
Speaker 4: But I love through the door. They did, they not filter?

913
00:48:11,880 --> 00:48:13,400
Speaker 4: People look like.

914
00:48:14,120 --> 00:48:18,160
Speaker 1: I'm like the stupid mascot. You know, have AFL clubs

915
00:48:18,200 --> 00:48:21,000
Speaker 1: have a mascot. I'm the Brain Park mascot. I just

916
00:48:21,000 --> 00:48:24,000
Speaker 1: fucking walk around bumping into shit and people pat.

917
00:48:23,760 --> 00:48:25,520
Speaker 5: Me Brain Park Labrador.

918
00:48:26,000 --> 00:48:28,200
Speaker 4: Yeah yeah, the one who's pushing at the door that

919
00:48:28,280 --> 00:48:28,840
Speaker 4: says Paul.

920
00:48:29,480 --> 00:48:29,640
Speaker 5: Yeah.

921
00:48:29,719 --> 00:48:31,919
Speaker 1: Yeah. Like I just pushed my head against the door

922
00:48:32,000 --> 00:48:34,359
Speaker 1: until someone hears me banging and then they let me in.

923
00:48:35,560 --> 00:48:39,280
Speaker 1: It's sad, but like I love the pats and the food.

924
00:48:39,680 --> 00:48:39,919
Speaker 4: Yeah.

925
00:48:39,960 --> 00:48:43,759
Speaker 2: So talking about uplifting technology, this was I thought, this

926
00:48:43,800 --> 00:48:47,399
Speaker 2: is a nice little segue. So the Chinese drone manufacturer

927
00:48:47,440 --> 00:48:53,000
Speaker 2: Dji has for the first time ever flown a drone

928
00:48:53,080 --> 00:48:55,520
Speaker 2: to the top of Everest up up to one of

929
00:48:55,560 --> 00:48:58,560
Speaker 2: the base stations at Everest. Because the air is quite

930
00:48:58,640 --> 00:49:02,839
Speaker 2: thin and it's hard to get the lift capacity. And

931
00:49:02,960 --> 00:49:06,000
Speaker 2: what they're talking about is using the fly cart thirty

932
00:49:06,600 --> 00:49:09,600
Speaker 2: to be able to fly up there. So we're talking

933
00:49:09,680 --> 00:49:14,920
Speaker 2: six thousand meters six kilometers up and it was able to.

934
00:49:16,719 --> 00:49:18,399
Speaker 4: Be able to deliver.

935
00:49:20,040 --> 00:49:22,320
Speaker 2: Resources up to people at the top of Everest or

936
00:49:22,440 --> 00:49:25,360
Speaker 2: up up that high. And because the big the problem

937
00:49:25,400 --> 00:49:28,560
Speaker 2: there is the high winds, the sub zero temperatures, is

938
00:49:28,560 --> 00:49:31,320
Speaker 2: a whole lot of factors that have meant that drones

939
00:49:31,320 --> 00:49:32,919
Speaker 2: in the past haven't been able to get up there.

940
00:49:33,040 --> 00:49:36,239
Speaker 2: But it also means that they can clean up all

941
00:49:36,280 --> 00:49:38,839
Speaker 2: the crap that's on top of Everest as well. There's

942
00:49:38,880 --> 00:49:40,400
Speaker 2: a whole lot of junk up there, a lot of

943
00:49:40,480 --> 00:49:43,680
Speaker 2: well lots of stuff up there, so they can a

944
00:49:43,680 --> 00:49:46,560
Speaker 2: whole lot of dead people and dead people yeah, yep.

945
00:49:46,719 --> 00:49:49,000
Speaker 2: So the good thing is that they were able to

946
00:49:49,040 --> 00:49:51,239
Speaker 2: do this. They did a round trip and they still

947
00:49:51,239 --> 00:49:53,840
Speaker 2: had forty three percent battery power by the end of it,

948
00:49:53,840 --> 00:49:57,120
Speaker 2: which is kind of cool. And what it will do though,

949
00:49:57,239 --> 00:49:58,839
Speaker 2: is it's going to make it a lot safer two

950
00:49:58,920 --> 00:50:02,239
Speaker 2: because they do clean up parts of Everest, And what

951
00:50:02,280 --> 00:50:04,200
Speaker 2: it's going to mean is that for the sherpas and

952
00:50:04,239 --> 00:50:08,319
Speaker 2: people who are trying to preserve the natural area they

953
00:50:08,360 --> 00:50:10,319
Speaker 2: can stand in pulling these drones. I thought that was

954
00:50:10,360 --> 00:50:12,800
Speaker 2: really kind of cool that they're doing that with the drones.

955
00:50:12,920 --> 00:50:15,120
Speaker 2: I had a personal example last weekend. I think I

956
00:50:15,120 --> 00:50:18,240
Speaker 2: told Tip about this. I do a bit of drone

957
00:50:18,239 --> 00:50:20,400
Speaker 2: photography and one of my clients wanted me to go

958
00:50:20,480 --> 00:50:24,359
Speaker 2: out and do some drone work just around some earth

959
00:50:24,440 --> 00:50:27,120
Speaker 2: moving that they were doing. And I left the land

960
00:50:27,400 --> 00:50:29,600
Speaker 2: and I was only driving forty five minutes and it

961
00:50:29,719 --> 00:50:32,880
Speaker 2: was nice and still kind of nice day. And I

962
00:50:32,960 --> 00:50:36,280
Speaker 2: get to the location and they're gusting winds of forty

963
00:50:36,280 --> 00:50:39,880
Speaker 2: five kilometers an hour and at one point the drone

964
00:50:39,920 --> 00:50:42,280
Speaker 2: that I've got can at top speed can go about

965
00:50:42,280 --> 00:50:44,759
Speaker 2: seventy clicks, so it's fast. If you put it into

966
00:50:44,800 --> 00:50:47,200
Speaker 2: sport mode, it's pretty fast. So I had it in

967
00:50:47,280 --> 00:50:52,080
Speaker 2: sport mode and it was still going backwards. Yeah, it

968
00:50:52,120 --> 00:50:53,560
Speaker 2: was pretty full on. So I had to kind of

969
00:50:53,560 --> 00:50:55,480
Speaker 2: fly closer to the ground and then move it to

970
00:50:55,560 --> 00:50:57,759
Speaker 2: one location and then let the wind kind of push

971
00:50:57,800 --> 00:50:59,040
Speaker 2: it at maximum speed.

972
00:50:59,160 --> 00:51:01,320
Speaker 4: But that was kind of interesting.

973
00:51:01,360 --> 00:51:03,640
Speaker 2: So when to fly all the way up, you know,

974
00:51:03,719 --> 00:51:07,200
Speaker 2: to to that part of Everest and to you know,

975
00:51:07,440 --> 00:51:11,399
Speaker 2: nineteen thousand six hundred and eighty five feet sounds more

976
00:51:11,400 --> 00:51:13,880
Speaker 2: impressive than six thousand meters, doesn't it.

977
00:51:13,920 --> 00:51:17,799
Speaker 1: Well, six kilometers. The top of Everest is nearly nine kilometers,

978
00:51:17,840 --> 00:51:19,800
Speaker 1: so that must be up to one of the base

979
00:51:19,880 --> 00:51:25,200
Speaker 1: camps or one of the camp tours, but still six

980
00:51:25,280 --> 00:51:28,560
Speaker 1: kilometers up in the air. Dude. Yeah, Like you think

981
00:51:28,600 --> 00:51:32,720
Speaker 1: of a hundred story building that's one thousand feet usually

982
00:51:32,760 --> 00:51:37,319
Speaker 1: because there's like ten foot a floor, so that that

983
00:51:37,320 --> 00:51:40,120
Speaker 1: would be the equivalent of what did you say, how

984
00:51:40,120 --> 00:51:41,680
Speaker 1: many thousand feet?

985
00:51:42,239 --> 00:51:43,360
Speaker 4: Nineteen thousand feet?

986
00:51:44,640 --> 00:51:49,480
Speaker 1: That'd be the equivalent of a nineteen hundred story building.

987
00:51:51,080 --> 00:51:54,400
Speaker 1: That's fucking Hey, we needs jam. How can people find

988
00:51:54,400 --> 00:51:57,319
Speaker 1: you my friend and come and you know, play with

989
00:51:57,400 --> 00:52:00,960
Speaker 1: you and your drone? And also perhaps you need to

990
00:52:01,040 --> 00:52:05,040
Speaker 1: organize the the wedding arrangements just so all of us

991
00:52:05,120 --> 00:52:06,640
Speaker 1: can plan.

992
00:52:07,320 --> 00:52:09,480
Speaker 2: Well. If someone wants to just chat about nerd stuff

993
00:52:09,520 --> 00:52:11,160
Speaker 2: with me, I'm always happy to do that.

994
00:52:11,200 --> 00:52:12,960
Speaker 4: And thank you Dale from Geelong.

995
00:52:13,680 --> 00:52:15,839
Speaker 1: You get married if I'll pay for it.

996
00:52:16,400 --> 00:52:20,000
Speaker 2: Ah, we want to go to Vegas, Tiff, Let's go

997
00:52:20,040 --> 00:52:20,800
Speaker 2: to Vegas again.

998
00:52:21,000 --> 00:52:25,759
Speaker 1: I'm not paying for your honey. If you want to

999
00:52:25,760 --> 00:52:27,239
Speaker 1: get married, I.

1000
00:52:27,400 --> 00:52:30,040
Speaker 4: Pay for it. And we want to get married in Vegas.

1001
00:52:30,320 --> 00:52:32,680
Speaker 1: I will pay for your wedding up to a value

1002
00:52:32,680 --> 00:52:36,840
Speaker 1: of five thousand dollars. Has to be a legal wedding.

1003
00:52:37,160 --> 00:52:39,160
Speaker 4: You know this is being recorded, right you can't.

1004
00:52:39,360 --> 00:52:42,880
Speaker 1: I don't care. I'm happy if you actually really get married.

1005
00:52:42,920 --> 00:52:43,640
Speaker 1: I'll pay for it.

1006
00:52:44,160 --> 00:52:46,200
Speaker 4: Yeah, we will go to Vegas and get married.

1007
00:52:46,239 --> 00:52:48,200
Speaker 1: And then you're not getting married in Vegas. You've got

1008
00:52:48,200 --> 00:52:50,840
Speaker 1: to get married here. We need a real wedding and

1009
00:52:50,920 --> 00:52:53,680
Speaker 1: it needs to be legal, and me and the typ

1010
00:52:53,920 --> 00:52:55,160
Speaker 1: folks are going to come along.

1011
00:52:55,680 --> 00:52:57,240
Speaker 5: My mom's going to be so happy.

1012
00:52:58,520 --> 00:52:59,919
Speaker 4: Only if you're the bride's maid.

1013
00:53:01,440 --> 00:53:04,719
Speaker 1: I'll be the flower girl. I'll do security. I'll fucking sing,

1014
00:53:04,880 --> 00:53:05,520
Speaker 1: don't worry.

1015
00:53:06,040 --> 00:53:09,520
Speaker 2: Yeah, people can contact me going to websites now, dot com,

1016
00:53:09,520 --> 00:53:11,560
Speaker 2: todau because Genesis effects is too.

1017
00:53:11,480 --> 00:53:16,160
Speaker 4: Hard to spell. So you know, I created my.

1018
00:53:16,160 --> 00:53:19,680
Speaker 2: Business name before the internet was a thing, and so

1019
00:53:20,239 --> 00:53:22,440
Speaker 2: no one knows how to spell genesis effects, so I

1020
00:53:22,520 --> 00:53:25,120
Speaker 2: just kind of created websites now dot com today you

1021
00:53:25,360 --> 00:53:28,239
Speaker 2: is the alternative. I mean, we do a lot of websites,

1022
00:53:28,280 --> 00:53:30,960
Speaker 2: so I guess that's a good reason to have that,

1023
00:53:31,000 --> 00:53:33,920
Speaker 2: But it's just the easiest way to spell what we do.

1024
00:53:35,080 --> 00:53:38,040
Speaker 1: I think sometimes we try and get too tricky with names.

1025
00:53:38,239 --> 00:53:40,800
Speaker 1: I think that I think your new name works best. Patrick,

1026
00:53:40,920 --> 00:53:44,640
Speaker 1: Thank you, Pa, thank you, thank you. I think this

1027
00:53:44,680 --> 00:53:46,640
Speaker 1: episode is going to be called Patrick and Tiff for

1028
00:53:46,680 --> 00:53:47,759
Speaker 1: getting married for sure,