1
00:00:00,800 --> 00:00:03,800
Speaker 1: I'll get at me into you project. It's Tiffany and Cook,

2
00:00:03,840 --> 00:00:06,080
Speaker 1: It's Patrick James Bonello. It's me, the one in the

3
00:00:06,120 --> 00:00:08,680
Speaker 1: middle on my screen anyway, the one in the middle, tiff.

4
00:00:08,680 --> 00:00:10,960
Speaker 1: Where am I on your screen? Middle? Bottom? Top?

5
00:00:11,240 --> 00:00:13,200
Speaker 2: You are the middle child, But I've got to speak

6
00:00:13,240 --> 00:00:15,360
Speaker 2: of you, so you're real big when you talk.

7
00:00:16,239 --> 00:00:19,320
Speaker 1: Oh, I don't like that. I don't like that. Patrick.

8
00:00:19,320 --> 00:00:21,440
Speaker 1: Where am I on yours? And where's tiff on yours?

9
00:00:21,600 --> 00:00:23,280
Speaker 3: Well, you're at the top and tips at the bottom,

10
00:00:23,480 --> 00:00:24,960
Speaker 3: so I'm being cuddled in the middle.

11
00:00:26,160 --> 00:00:28,319
Speaker 1: All right. So you've got like a little kind of

12
00:00:29,000 --> 00:00:31,560
Speaker 1: like a vertical pile of us.

13
00:00:31,800 --> 00:00:34,200
Speaker 3: Yeah, your big spoon and TIFF's little spoon.

14
00:00:35,120 --> 00:00:37,800
Speaker 2: I have to put it on speak of you otherwise

15
00:00:37,840 --> 00:00:39,880
Speaker 2: I'm like a little budgery gar with a mirror.

16
00:00:39,960 --> 00:00:41,680
Speaker 4: I'm like, oh, look at that.

17
00:00:41,320 --> 00:00:41,720
Speaker 3: That's me.

18
00:00:43,120 --> 00:00:45,640
Speaker 1: Yeah, yeah, No, I don't like that. I like every

19
00:00:45,840 --> 00:00:48,440
Speaker 1: like do you know what I do? I have Patrick's

20
00:00:48,479 --> 00:00:50,519
Speaker 1: notes that he sent through in the middle of my

21
00:00:50,600 --> 00:00:53,920
Speaker 1: gigantic screen, and then our little faces up the top,

22
00:00:54,360 --> 00:00:56,680
Speaker 1: all like about the size of a match box.

23
00:00:58,080 --> 00:00:59,680
Speaker 3: So you really don't see us at all.

24
00:01:00,720 --> 00:01:04,160
Speaker 1: Now I can see you clearly, totally can tolerate that

25
00:01:04,200 --> 00:01:11,680
Speaker 1: can see clearly. Now Lorraine has gone, Thank goodness. Patrick,

26
00:01:11,760 --> 00:01:16,400
Speaker 1: Let's start with you in what looks like the International

27
00:01:16,440 --> 00:01:20,600
Speaker 1: Space station where you are look.

28
00:01:20,720 --> 00:01:23,160
Speaker 3: No, well, okay, I'm sitting at my little podcast studio

29
00:01:23,200 --> 00:01:26,000
Speaker 3: and I've got a fake International space station background. But

30
00:01:26,040 --> 00:01:28,039
Speaker 3: I really want to kind of focus on a more

31
00:01:28,040 --> 00:01:31,280
Speaker 3: important thing because our listeners can't see that we're actually

32
00:01:31,319 --> 00:01:34,920
Speaker 3: sitting in three different locations using zoom. They just didn't

33
00:01:34,959 --> 00:01:37,399
Speaker 3: see you use a tea towel to blow your nose.

34
00:01:39,560 --> 00:01:41,480
Speaker 1: It's not a tea towel, it's.

35
00:01:41,280 --> 00:01:44,600
Speaker 3: A chemy that you wipe up with.

36
00:01:45,520 --> 00:01:48,240
Speaker 1: No, it's not a chammy. It's a yellow kerchief.

37
00:01:50,120 --> 00:01:52,840
Speaker 3: It looks like a chevy. You just wipe his face

38
00:01:52,880 --> 00:01:53,680
Speaker 3: with a Chevy.

39
00:01:54,360 --> 00:01:56,640
Speaker 1: Well, now that you mentioned it, that's probably not a

40
00:01:56,680 --> 00:01:59,520
Speaker 1: bad idea. But I mean, shemys are for wiping things,

41
00:01:59,600 --> 00:02:01,160
Speaker 1: so I might look into that.

42
00:02:01,280 --> 00:02:05,120
Speaker 3: And then your face would look a lot cleaner. Sorry,

43
00:02:05,760 --> 00:02:07,040
Speaker 3: that started off well, didn't it.

44
00:02:07,400 --> 00:02:10,000
Speaker 1: I just I was praising you. I was telling everyone.

45
00:02:10,000 --> 00:02:12,160
Speaker 1: I was telling you three before we went live that

46
00:02:12,280 --> 00:02:15,880
Speaker 1: on the International Banello scale of how good people can be,

47
00:02:16,040 --> 00:02:18,880
Speaker 1: you're the high watermark. And then you shit care me

48
00:02:18,960 --> 00:02:21,040
Speaker 1: straight out of the gate on my own fucking show.

49
00:02:21,400 --> 00:02:23,400
Speaker 3: I just wanted to clarify that you weren't using you

50
00:02:23,600 --> 00:02:27,280
Speaker 3: get your voice a couple of octaves lower as nuts.

51
00:02:28,160 --> 00:02:31,280
Speaker 3: Now Fritz is on his bed warming here I turned

52
00:02:31,280 --> 00:02:32,840
Speaker 3: the heater on early. Now I'm getting too.

53
00:02:32,960 --> 00:02:35,320
Speaker 1: Oh now he's getting fuck and now he's getting his

54
00:02:35,440 --> 00:02:45,880
Speaker 1: guns out. Sheep id you hold yourself back. Ah, dear Chip,

55
00:02:45,919 --> 00:02:47,120
Speaker 1: how are you? Good morning?

56
00:02:47,760 --> 00:02:51,200
Speaker 2: Fabulous harps, thanks fantastic.

57
00:02:51,600 --> 00:02:55,080
Speaker 1: How's how's the household full of animals?

58
00:02:55,440 --> 00:02:59,160
Speaker 2: Oh it's goods, everything's calm, everything's calm.

59
00:02:59,240 --> 00:03:01,040
Speaker 4: Now, happy animals.

60
00:03:01,919 --> 00:03:05,720
Speaker 1: I found a new animal that both of you would want.

61
00:03:06,000 --> 00:03:10,720
Speaker 1: What is it? It's a it's a a hybrid, so

62
00:03:11,320 --> 00:03:14,679
Speaker 1: not it's not pretend it's real. I think it's called

63
00:03:14,680 --> 00:03:19,079
Speaker 1: a doxam anyway, a dog and a fox hybrid.

64
00:03:19,800 --> 00:03:23,120
Speaker 3: Really yeah, I just looked up doxham, and I mustn't

65
00:03:23,120 --> 00:03:26,000
Speaker 3: have spelled it correctly, because I just got the women.

66
00:03:27,760 --> 00:03:29,280
Speaker 3: Don't look up doxam. Whatever you do.

67
00:03:29,480 --> 00:03:30,840
Speaker 1: Sure you didn't look up buxham.

68
00:03:31,360 --> 00:03:33,640
Speaker 3: No do o x U M. I don't know, it.

69
00:03:33,680 --> 00:03:35,920
Speaker 1: Might be I am, I don't know. Just look dog,

70
00:03:36,680 --> 00:03:41,920
Speaker 1: look dog fox hybrid. Oh, this is great, I'll just

71
00:03:41,960 --> 00:03:45,080
Speaker 1: talk to everyone because those two dumbasses. I guess it's

72
00:03:45,360 --> 00:03:48,920
Speaker 1: on my instruction, so it's my fault. Have you seen it.

73
00:03:51,200 --> 00:03:52,120
Speaker 1: I don't think they're.

74
00:03:52,000 --> 00:03:56,040
Speaker 3: Ugly, don't you. Actually they do kind of have a

75
00:03:56,080 --> 00:03:57,200
Speaker 3: cute little foxy fog.

76
00:03:57,480 --> 00:04:01,200
Speaker 2: God, they look like a bloody hyena hybrid.

77
00:04:01,440 --> 00:04:04,200
Speaker 1: Ah. I thought you two were animal lovers.

78
00:04:05,640 --> 00:04:09,400
Speaker 3: Well yeah, but Tiff, you know, has her lovely animal.

79
00:04:09,480 --> 00:04:12,000
Speaker 4: It's got to be cute. It's a little easy stick up,

80
00:04:12,040 --> 00:04:13,000
Speaker 4: like a little ewok.

81
00:04:13,880 --> 00:04:17,440
Speaker 1: Yeah, yeah, So I don't know that i'd want one

82
00:04:17,480 --> 00:04:17,960
Speaker 1: in the house.

83
00:04:18,000 --> 00:04:23,400
Speaker 3: It looks like the answer to the question no one asked, Well.

84
00:04:23,640 --> 00:04:29,599
Speaker 1: Fucking sorry, Sigmund Freud, what would you like to talk about? Sorry,

85
00:04:29,720 --> 00:04:33,640
Speaker 1: Leonardo da Vinci sorrow? Sorry Jesus, where would you like

86
00:04:33,680 --> 00:04:38,960
Speaker 1: to go with the conversation? Come on, Delai Lama, you

87
00:04:39,040 --> 00:04:39,800
Speaker 1: open the batting.

88
00:04:41,040 --> 00:04:42,919
Speaker 3: You know I've got a connection to the deal alarm.

89
00:04:42,960 --> 00:04:44,920
Speaker 3: And not only have I been in the same room

90
00:04:44,920 --> 00:04:47,479
Speaker 3: with the Delai Lama, I was born on the same day.

91
00:04:47,760 --> 00:04:49,719
Speaker 1: You and I were in the same room at the

92
00:04:49,760 --> 00:04:54,039
Speaker 1: same time with him, Damas, how's your memory?

93
00:04:54,640 --> 00:04:57,400
Speaker 3: I did say that, I didn't I just conveniently left

94
00:04:57,440 --> 00:04:58,440
Speaker 3: you out of the equation.

95
00:04:58,800 --> 00:05:03,040
Speaker 1: Welcome back to so Now Central. I'm Patrick Beranello. Episode

96
00:05:03,120 --> 00:05:06,880
Speaker 1: number I'm not sure. Hey tell do you want to

97
00:05:06,920 --> 00:05:10,640
Speaker 1: hear Madellai Lama story? Come on, bro, do better.

98
00:05:12,920 --> 00:05:15,200
Speaker 4: This is already my favorite episode.

99
00:05:15,760 --> 00:05:19,560
Speaker 3: Really, we're talking to nobody because everyone's turned off.

100
00:05:20,240 --> 00:05:24,400
Speaker 1: They love this except our listeners are maniacs. They're like,

101
00:05:24,680 --> 00:05:26,599
Speaker 1: fuck all the information, just talk shit?

102
00:05:27,000 --> 00:05:29,720
Speaker 3: Can I just all about something? All of them this week?

103
00:05:29,839 --> 00:05:33,000
Speaker 3: I remember how a few weeks ago we offered people

104
00:05:33,040 --> 00:05:36,520
Speaker 3: a free domain name and like nothing happened, no one

105
00:05:36,560 --> 00:05:38,520
Speaker 3: took it up. And then and then I got a

106
00:05:38,520 --> 00:05:41,880
Speaker 3: message from Lovely Magdalena who says that this is her

107
00:05:41,960 --> 00:05:45,080
Speaker 3: favorite segment of the show. How good is that. She's

108
00:05:45,080 --> 00:05:50,919
Speaker 3: in Adelaide and and she she is a one of

109
00:05:50,920 --> 00:05:54,320
Speaker 3: those she does a civil celebrant, so it got chatting

110
00:05:54,320 --> 00:05:56,000
Speaker 3: to her during the week. But she loves the show,

111
00:05:56,200 --> 00:05:56,920
Speaker 3: she loves the well.

112
00:05:57,000 --> 00:05:58,719
Speaker 1: Shout out, shout out to Magdalene.

113
00:05:59,160 --> 00:06:02,080
Speaker 3: Magdalena, it is but everyone calls a magde when you

114
00:06:02,080 --> 00:06:08,240
Speaker 3: get close and personal, you know, once you becomes.

115
00:06:06,160 --> 00:06:09,239
Speaker 1: Someone for seventeen minutes, now it's his bestie. It's pretty

116
00:06:09,320 --> 00:06:14,040
Speaker 1: much joined at the hip for a state of time.

117
00:06:16,200 --> 00:06:19,080
Speaker 1: He's so needy everyone, whatever you do, don't send him

118
00:06:19,120 --> 00:06:22,480
Speaker 1: an email. You'll never fucking get rid of him.

119
00:06:23,440 --> 00:06:32,240
Speaker 3: This is actually very very god oh god, Okay, let's

120
00:06:32,240 --> 00:06:32,760
Speaker 3: start again.

121
00:06:33,000 --> 00:06:36,919
Speaker 1: Hey everyone, welcome to the You Project. I'm Craig Harper.

122
00:06:37,279 --> 00:06:40,600
Speaker 1: This is a hard hitting podcast where we explore the

123
00:06:40,960 --> 00:06:42,560
Speaker 1: human experience.

124
00:06:42,720 --> 00:06:42,880
Speaker 2: Hi.

125
00:06:43,000 --> 00:06:46,159
Speaker 3: Patrick, Oh hey Craig, Nice to see you. Hi Tiff,

126
00:06:46,400 --> 00:06:47,440
Speaker 3: Great to have you on the show.

127
00:06:47,760 --> 00:06:54,719
Speaker 1: Yeah, Tiff, gooday, gooday, gooday. All silliness societe. How what

128
00:06:54,920 --> 00:06:57,520
Speaker 1: is mag to do? So she's a civil celebrate, Yeah,

129
00:06:57,600 --> 00:06:59,040
Speaker 1: so weddings and funerals.

130
00:06:59,400 --> 00:07:02,920
Speaker 3: Yeah, but she's kind of tending towards funerals now, which

131
00:07:02,960 --> 00:07:04,560
Speaker 3: kind of makes sense because you've got a plan a wedding,

132
00:07:04,600 --> 00:07:08,080
Speaker 3: what eighteen months in advance, different minds, And also, you know,

133
00:07:08,320 --> 00:07:11,320
Speaker 3: weddings are on weekends, right and funerals are during the week,

134
00:07:11,440 --> 00:07:12,280
Speaker 3: So if you want to do it.

135
00:07:12,280 --> 00:07:15,160
Speaker 1: Sure about your rational on that makes sense? What so

136
00:07:15,240 --> 00:07:17,720
Speaker 1: what are you saying like it's much more convenient for

137
00:07:17,720 --> 00:07:19,600
Speaker 1: people to die is less planning?

138
00:07:19,880 --> 00:07:22,600
Speaker 3: Well, you've got a pretty ongoing, steady audience, haven't you

139
00:07:22,720 --> 00:07:23,760
Speaker 3: really when you think about it.

140
00:07:24,240 --> 00:07:27,720
Speaker 1: Oh god, this got this took a dark turn. Let's

141
00:07:27,720 --> 00:07:30,720
Speaker 1: start again. Everyone, welcome to the you project.

142
00:07:31,040 --> 00:07:34,680
Speaker 3: Look because I would Okay, now I have in my

143
00:07:34,840 --> 00:07:38,240
Speaker 3: will a very clear I do not want a funeral.

144
00:07:38,440 --> 00:07:41,040
Speaker 3: I've got two and a half grand at the local pub,

145
00:07:41,320 --> 00:07:44,320
Speaker 3: and I'm inviting all my friends me not included, of course.

146
00:07:44,920 --> 00:07:46,000
Speaker 3: Maybe in an ashtray.

147
00:07:46,360 --> 00:07:48,920
Speaker 1: I should just put you in a weekend at Bernie's

148
00:07:48,920 --> 00:07:51,480
Speaker 1: style outfit and fucking prop you in the corner.

149
00:07:51,760 --> 00:07:53,880
Speaker 3: Now, my twin brother will probably be there, so I'll

150
00:07:53,920 --> 00:07:54,960
Speaker 3: just know, just look at him.

151
00:07:55,000 --> 00:07:58,480
Speaker 1: Oh that'll be. That'll freak people out. He should just

152
00:07:58,800 --> 00:08:00,960
Speaker 1: he should put on a white sheet and just walk

153
00:08:01,000 --> 00:08:07,640
Speaker 1: in halfway through unannounced. Go what do you all doing? Yeah?

154
00:08:07,800 --> 00:08:10,600
Speaker 3: No, but if you if you don't want a religious

155
00:08:10,640 --> 00:08:13,280
Speaker 3: ceremony and you want a celebrant to do a wedding

156
00:08:13,360 --> 00:08:15,239
Speaker 3: or a funeral or something, it kind of makes sense.

157
00:08:16,520 --> 00:08:18,560
Speaker 3: Yeah anyway, So magnismine, you mate.

158
00:08:19,000 --> 00:08:21,840
Speaker 1: You and I chatted about this yesterday to forty your thoughts,

159
00:08:21,880 --> 00:08:26,040
Speaker 1: Like Patrick and I fucking much to both of our annoyance,

160
00:08:26,080 --> 00:08:28,440
Speaker 1: we kind of agree on this, which is a weird thing.

161
00:08:28,600 --> 00:08:31,680
Speaker 1: So just put that in the typ diary and that

162
00:08:32,280 --> 00:08:36,200
Speaker 1: neither of us really want a funeral. I I don't

163
00:08:36,559 --> 00:08:39,480
Speaker 1: know the idea of people. Yeah, I know the people

164
00:08:39,520 --> 00:08:41,840
Speaker 1: coming from all over to stand around and go, oh,

165
00:08:41,880 --> 00:08:45,600
Speaker 1: he was a good bloke when they probably didn't really

166
00:08:45,640 --> 00:08:47,880
Speaker 1: think that half of them, and then everyone.

167
00:08:48,080 --> 00:08:54,000
Speaker 2: Everybody thinks it. With Patrick, you gotta put on something.

168
00:08:54,040 --> 00:08:56,800
Speaker 2: Though he's not saying nobody gets anything in safe.

169
00:08:56,880 --> 00:08:58,760
Speaker 1: I'm happy to do that. I just don't want a

170
00:08:58,760 --> 00:09:01,160
Speaker 1: bunch of people in a church staring at a coffin

171
00:09:02,280 --> 00:09:05,000
Speaker 1: with what used to be me in it. I'm not

172
00:09:05,000 --> 00:09:05,680
Speaker 1: there anymore.

173
00:09:07,760 --> 00:09:08,480
Speaker 3: What about you?

174
00:09:09,000 --> 00:09:10,679
Speaker 4: But where are you going to go? When you're not

175
00:09:11,080 --> 00:09:11,960
Speaker 4: on to the other place.

176
00:09:12,080 --> 00:09:14,120
Speaker 1: I'm going to the next place. I'm just warming up.

177
00:09:14,160 --> 00:09:18,720
Speaker 4: Now you're gonna drop by, and just you know, I'm.

178
00:09:18,559 --> 00:09:20,760
Speaker 1: Going to be watching you like a fucking hawk, and

179
00:09:20,800 --> 00:09:28,119
Speaker 1: you better do better. You just remember I'm around.

180
00:09:27,679 --> 00:09:29,800
Speaker 3: Don't you pay attention to You?

181
00:09:29,840 --> 00:09:32,400
Speaker 1: Pay attention because you go? Is that you.

182
00:09:32,440 --> 00:09:36,280
Speaker 4: Harps carrying to it at this moment, we'll live with

183
00:09:36,320 --> 00:09:37,040
Speaker 4: me forever.

184
00:09:37,640 --> 00:09:37,840
Speaker 1: Good.

185
00:09:37,840 --> 00:09:40,000
Speaker 4: I hope I go first, because.

186
00:09:40,240 --> 00:09:42,920
Speaker 1: Because when I go to God, that's what Mary says.

187
00:09:44,320 --> 00:09:46,400
Speaker 1: I'm not going anywhere when it comes to you, I'm

188
00:09:46,440 --> 00:09:48,680
Speaker 1: just gonna to look over here.

189
00:09:49,840 --> 00:09:51,520
Speaker 4: That's crapy nowhere about that?

190
00:09:52,800 --> 00:09:57,959
Speaker 5: Sorry, Patrick, So I want to get again. Hey everyone,

191
00:09:58,080 --> 00:10:02,480
Speaker 5: welcome to the You project, fifth time we've started. So

192
00:10:02,720 --> 00:10:05,280
Speaker 5: what do your family and friends think about the idea

193
00:10:05,360 --> 00:10:08,720
Speaker 5: of just boos and chips at the pub but no

194
00:10:08,960 --> 00:10:09,800
Speaker 5: actual funeral.

195
00:10:10,200 --> 00:10:14,240
Speaker 3: My friends think it's a great idea, but I haven't

196
00:10:14,280 --> 00:10:16,680
Speaker 3: really articulated it to my family. I've just basically said

197
00:10:16,720 --> 00:10:20,040
Speaker 3: I don't want a funeral. They tap now, well, now

198
00:10:20,160 --> 00:10:21,200
Speaker 3: have you? Everyone knows?

199
00:10:21,400 --> 00:10:24,320
Speaker 1: So what will they do with your body? Just pop

200
00:10:24,360 --> 00:10:27,439
Speaker 1: it in the garden or something, or some food, Just

201
00:10:28,120 --> 00:10:33,040
Speaker 1: turn you into a bag of fertilizer. That's okay, tips

202
00:10:33,120 --> 00:10:34,360
Speaker 1: reading something you can tell you.

203
00:10:34,600 --> 00:10:36,600
Speaker 4: I'm deep in thought. I'm deep in thoughts.

204
00:10:36,679 --> 00:10:41,679
Speaker 2: I'm thinking about well, people like yourself and myself. You

205
00:10:41,679 --> 00:10:44,640
Speaker 2: have to have the conversation, like I'm like, have you

206
00:10:44,720 --> 00:10:45,360
Speaker 2: let me listen?

207
00:10:45,440 --> 00:10:45,800
Speaker 4: Know what?

208
00:10:46,080 --> 00:10:49,080
Speaker 2: How this party is going to roll out? Because it's

209
00:10:49,080 --> 00:10:52,960
Speaker 2: not like there's a significant other hanging around in the

210
00:10:53,000 --> 00:10:55,680
Speaker 2: next room waiting to put it all together.

211
00:10:56,280 --> 00:11:00,040
Speaker 1: Yeah, well, well that would Melissa would probably have to

212
00:11:00,040 --> 00:11:02,280
Speaker 1: be the one that would execute my wishes.

213
00:11:02,600 --> 00:11:03,439
Speaker 4: I don't think she's.

214
00:11:05,120 --> 00:11:09,640
Speaker 1: Not a big fan of talking about me dying, So

215
00:11:09,720 --> 00:11:11,679
Speaker 1: I'll just pop it in a little email and she

216
00:11:11,840 --> 00:11:14,000
Speaker 1: can open it when I die. I'll go there you go,

217
00:11:14,080 --> 00:11:14,480
Speaker 1: here you go.

218
00:11:15,280 --> 00:11:17,199
Speaker 4: Yeah, but yes, I love you again.

219
00:11:17,559 --> 00:11:17,800
Speaker 3: Yeah.

220
00:11:18,000 --> 00:11:21,960
Speaker 1: See, it's been great. It's been great. You can have

221
00:11:23,320 --> 00:11:28,600
Speaker 1: you know, all my Camo shorts and yeah, yeah, you

222
00:11:28,679 --> 00:11:31,360
Speaker 1: might even get a motorbike. Who knows, I'll have to

223
00:11:31,360 --> 00:11:34,320
Speaker 1: give you one. You can ride though, I mean you can,

224
00:11:34,360 --> 00:11:36,440
Speaker 1: Frid well. But what I mean is there are a

225
00:11:36,440 --> 00:11:39,079
Speaker 1: couple of them a bit big for you.

226
00:11:39,080 --> 00:11:41,080
Speaker 3: You gave away that pinball machine. That's what I would

227
00:11:41,120 --> 00:11:42,520
Speaker 3: have wanted. You're all pinball?

228
00:11:43,440 --> 00:11:46,199
Speaker 1: Yeah, that that is true. I did give that away.

229
00:11:46,240 --> 00:11:47,840
Speaker 1: What would you like of mind, Patrick?

230
00:11:48,200 --> 00:11:52,680
Speaker 3: Your pinball? Okay, all right, a big framed poster.

231
00:11:54,440 --> 00:11:56,800
Speaker 1: Is there any chance we could talk about tech today?

232
00:11:56,840 --> 00:11:58,719
Speaker 1: And I know I'm the problem so far?

233
00:11:59,440 --> 00:12:02,439
Speaker 3: Well, okay, so this is important because that email that

234
00:12:02,520 --> 00:12:05,000
Speaker 3: you were going to send, like it's sitting in wherever

235
00:12:05,040 --> 00:12:07,760
Speaker 3: it's sitting on your computer. What happens if your computer

236
00:12:07,800 --> 00:12:11,360
Speaker 3: get tacked and ransomware locks you out of that important

237
00:12:11,440 --> 00:12:14,360
Speaker 3: email to Melissa with instructions of the piss up when

238
00:12:14,400 --> 00:12:14,920
Speaker 3: you diet.

239
00:12:15,640 --> 00:12:17,560
Speaker 1: Oh shit, I don't know. I guess i'd have to

240
00:12:17,559 --> 00:12:21,360
Speaker 1: have a plan. B. Yeah, i'd have to. I don't know,

241
00:12:21,559 --> 00:12:24,120
Speaker 1: but yeah, okay, so tell me what I do.

242
00:12:24,480 --> 00:12:27,000
Speaker 3: Well, because you know how ransomware works, so you probably

243
00:12:27,320 --> 00:12:31,040
Speaker 3: familiar ish with how ransomware works. So someone hacks into

244
00:12:31,120 --> 00:12:34,200
Speaker 3: your computer, you click on it an unsuspecting link, and

245
00:12:34,240 --> 00:12:37,840
Speaker 3: then what the ransomware does. It locks up all the files,

246
00:12:37,880 --> 00:12:40,960
Speaker 3: It encodes them so you can't access them. Then you

247
00:12:41,000 --> 00:12:44,920
Speaker 3: get contacted by the nefarious people who have done that,

248
00:12:45,120 --> 00:12:49,120
Speaker 3: and they extort money from you to unlock those files

249
00:12:49,160 --> 00:12:51,080
Speaker 3: so you can get access to your data again. And

250
00:12:51,120 --> 00:12:54,040
Speaker 3: there have been companies that have actually gone bankrupt and

251
00:12:54,640 --> 00:12:57,720
Speaker 3: have shut down because they didn't want to pay the ransom. Well,

252
00:12:57,720 --> 00:13:00,000
Speaker 3: they couldn't afford the ransom. So this is really sick.

253
00:13:00,320 --> 00:13:03,760
Speaker 3: And in Japan now police have now there's two types

254
00:13:04,160 --> 00:13:07,880
Speaker 3: of ransomware that are very prolific. One is called Faux

255
00:13:07,920 --> 00:13:11,360
Speaker 3: Boss and one is called eight Base, And now Japanese

256
00:13:11,400 --> 00:13:14,319
Speaker 3: police are saying they've cracked it. They've they've worked out

257
00:13:14,360 --> 00:13:19,880
Speaker 3: a way to encrypt that ransomware data, the stuff that's

258
00:13:19,880 --> 00:13:22,760
Speaker 3: been you know, but that's locked to beredy out and

259
00:13:22,800 --> 00:13:25,440
Speaker 3: they're giving it away for free, which I thought was

260
00:13:25,520 --> 00:13:27,199
Speaker 3: kind of a cool thing because you know, if you're

261
00:13:27,200 --> 00:13:30,760
Speaker 3: a small business or an individual who's been subjected to

262
00:13:30,920 --> 00:13:33,640
Speaker 3: having all their information and it could just be all

263
00:13:33,720 --> 00:13:36,520
Speaker 3: your photos and all the words, and imagine all the

264
00:13:36,559 --> 00:13:40,320
Speaker 3: work you've done for your PhD. Could you imagine devastating

265
00:13:40,360 --> 00:13:42,400
Speaker 3: that would be. So I just think it's great that

266
00:13:42,440 --> 00:13:45,760
Speaker 3: the Japanese police have done this. There was a big

267
00:13:46,200 --> 00:13:52,080
Speaker 3: operation recently where they raided these people who make these

268
00:13:52,679 --> 00:13:57,400
Speaker 3: ransomware tools, and it looks like they've cracked it. So

269
00:13:57,440 --> 00:13:59,320
Speaker 3: that's that's kind of good news for people out there.

270
00:13:59,400 --> 00:14:01,960
Speaker 3: So they're giving it away for free. You can go

271
00:14:02,080 --> 00:14:03,959
Speaker 3: you can go to their website and there's an English

272
00:14:04,080 --> 00:14:06,440
Speaker 3: version as well, and you can hopefully use it to

273
00:14:06,440 --> 00:14:10,120
Speaker 3: decrypt any of the ransomware that might have infected your system.

274
00:14:10,720 --> 00:14:13,600
Speaker 1: I reckon Japan are ahead of the game. They do

275
00:14:13,679 --> 00:14:15,680
Speaker 1: a lot of good stuff over there. They seem to

276
00:14:15,720 --> 00:14:18,880
Speaker 1: be they seem to have a good social conscience for

277
00:14:18,920 --> 00:14:23,920
Speaker 1: everyone as well, like they seem to genuinely care about people,

278
00:14:23,960 --> 00:14:30,040
Speaker 1: which is nice. So yeah, is is that that's more

279
00:14:30,640 --> 00:14:33,280
Speaker 1: that's not so much the individual out in suburbia. Is

280
00:14:33,320 --> 00:14:36,040
Speaker 1: it's more companies and organizations that are going to have

281
00:14:36,080 --> 00:14:36,560
Speaker 1: that threat.

282
00:14:36,640 --> 00:14:39,840
Speaker 3: Yeah, will not necessarily, No, everybody can be affected by it,

283
00:14:39,880 --> 00:14:43,560
Speaker 3: that's right. It's so prolific, and it could just be

284
00:14:44,120 --> 00:14:47,880
Speaker 3: that it's the freckle faced kid who decides to try

285
00:14:47,920 --> 00:14:51,720
Speaker 3: to infect someone's computer and wants fifty bucks down to

286
00:14:52,200 --> 00:14:54,960
Speaker 3: you know, the big mega corporation where they're trying to

287
00:14:55,000 --> 00:14:58,600
Speaker 3: extort twenty million dollars. You know. The problem is these tools,

288
00:14:58,720 --> 00:15:03,200
Speaker 3: these ransom tools, and now fairly readily available to people

289
00:15:03,240 --> 00:15:05,160
Speaker 3: who know where to look at them in the dark,

290
00:15:05,200 --> 00:15:09,720
Speaker 3: deep corners of the Internet. And that's the problem. It's

291
00:15:09,720 --> 00:15:11,960
Speaker 3: making it easier for people to access this stuff. So

292
00:15:12,200 --> 00:15:14,560
Speaker 3: I just thought it was a little plus for anybody

293
00:15:14,600 --> 00:15:18,119
Speaker 3: that might potentially get ransomed.

294
00:15:19,160 --> 00:15:21,400
Speaker 1: I think I told you about this a year or

295
00:15:21,400 --> 00:15:24,360
Speaker 1: two ago on the show. Somebody sent me an email going,

296
00:15:24,840 --> 00:15:30,080
Speaker 1: we've got access to whatever. No, we've got Actually it's

297
00:15:30,120 --> 00:15:33,480
Speaker 1: a video of you being inappropriate while watching it. I'm

298
00:15:33,560 --> 00:15:37,520
Speaker 1: like that, if you don't send us whatever we're going

299
00:15:37,560 --> 00:15:40,840
Speaker 1: to I'm like, knock yourself out. Send it out. My

300
00:15:40,920 --> 00:15:45,880
Speaker 1: friends would love that, would they love it?

301
00:15:47,000 --> 00:15:49,200
Speaker 4: When they sent it to me, I wasn't that impressed.

302
00:15:49,200 --> 00:15:53,840
Speaker 3: Actually, I'm on, but you didn't find the zoom function digitis.

303
00:15:54,080 --> 00:16:00,520
Speaker 6: Ah, is that right, mister ed Hello Wilbur, All right,

304
00:16:01,640 --> 00:16:05,200
Speaker 6: could you talk about Chinese authorities and how they're using

305
00:16:05,240 --> 00:16:06,560
Speaker 6: a new tool Patrick?

306
00:16:06,920 --> 00:16:09,680
Speaker 1: Yeah, how I just jumped straight out of that.

307
00:16:11,560 --> 00:16:14,440
Speaker 3: Well, it's kind of interesting. We're talking about ransom, we're

308
00:16:14,480 --> 00:16:18,960
Speaker 3: now talking about malware. Chinese authorities have worked out they

309
00:16:18,960 --> 00:16:22,760
Speaker 3: can use malware to break into people's phones when you

310
00:16:22,880 --> 00:16:25,400
Speaker 3: enter We kind of heard about this in the United

311
00:16:25,440 --> 00:16:27,960
Speaker 3: States when you travel to the United States, where your

312
00:16:28,000 --> 00:16:32,240
Speaker 3: phone could be seized and they demand that you give

313
00:16:32,720 --> 00:16:35,360
Speaker 3: them access. And look, I don't know if there's due

314
00:16:35,400 --> 00:16:37,720
Speaker 3: cause or whatever, but now they're saying, if you go

315
00:16:37,800 --> 00:16:41,000
Speaker 3: to China, there's a real possibility that even if you

316
00:16:41,040 --> 00:16:43,760
Speaker 3: don't give them access, they can hack into your phone

317
00:16:43,760 --> 00:16:46,160
Speaker 3: physically they need to have it. But what this is

318
00:16:46,160 --> 00:16:48,160
Speaker 3: the kind of a warning for people who are traveling

319
00:16:48,200 --> 00:16:51,800
Speaker 3: to China. And the concern also is for Chinese nationals.

320
00:16:52,080 --> 00:16:54,840
Speaker 3: If you happen to be a journalist in China and

321
00:16:54,880 --> 00:16:58,480
Speaker 3: you say something that's concrete to the state policy, and

322
00:16:58,840 --> 00:17:01,040
Speaker 3: you know that that could be really concerning as well.

323
00:17:01,160 --> 00:17:04,280
Speaker 3: So this was in our article on tech Crunch, and

324
00:17:04,880 --> 00:17:07,959
Speaker 3: they were reporting on a mobile computer company, a company

325
00:17:08,000 --> 00:17:11,560
Speaker 3: called Lockout, and they were saying that, yeah, this new

326
00:17:11,600 --> 00:17:14,439
Speaker 3: tool now looks like they can hacken to at least

327
00:17:14,560 --> 00:17:17,920
Speaker 3: all the Android phones out there. Ones tend to be

328
00:17:17,960 --> 00:17:21,280
Speaker 3: a little bit harder to break into, and Apple have

329
00:17:21,400 --> 00:17:25,320
Speaker 3: had some really big kind of fights with you know,

330
00:17:26,560 --> 00:17:29,920
Speaker 3: large kind of governments that have kind of said to them, well,

331
00:17:29,920 --> 00:17:32,240
Speaker 3: we're not going to let you access our phones. One

332
00:17:32,240 --> 00:17:33,800
Speaker 3: of the things we take a lot of pride in

333
00:17:34,160 --> 00:17:36,400
Speaker 3: is the security on our phones. And that's a real

334
00:17:36,440 --> 00:17:40,760
Speaker 3: problem because if say someone's accused of doing something nefarious

335
00:17:40,840 --> 00:17:44,080
Speaker 3: or it might be terrorism related, they may want to

336
00:17:44,119 --> 00:17:47,000
Speaker 3: get access to their phone data. And you know, Apple's

337
00:17:47,080 --> 00:17:50,360
Speaker 3: kind of standing by its customers and saying, well, we

338
00:17:50,720 --> 00:17:53,359
Speaker 3: lock people out. We you know, this is your privacy,

339
00:17:53,400 --> 00:17:56,000
Speaker 3: and we encrypt the data and even if we could

340
00:17:56,040 --> 00:17:57,879
Speaker 3: open it, we couldn't see it. So that's the the

341
00:17:58,119 --> 00:18:01,399
Speaker 3: you know, the the stands that Apple takes. But there

342
00:18:01,400 --> 00:18:03,520
Speaker 3: has been a big uptake of Apple phones. I thought

343
00:18:03,520 --> 00:18:05,760
Speaker 3: that was interesting when I was in China that when

344
00:18:05,800 --> 00:18:09,719
Speaker 3: I first went there in twenty thirteen, nobody had our

345
00:18:09,840 --> 00:18:13,800
Speaker 3: iPhones at all, and everybody was using Android and mainly

346
00:18:13,880 --> 00:18:16,880
Speaker 3: Samsung and Huiawei and show me and all that sort

347
00:18:16,920 --> 00:18:19,399
Speaker 3: of thing. And then next time I was there, maybe

348
00:18:19,560 --> 00:18:22,200
Speaker 3: five or six years later, I saw a lot more

349
00:18:22,359 --> 00:18:25,520
Speaker 3: iPhones out there, which was interesting. And Australia has a

350
00:18:25,560 --> 00:18:27,520
Speaker 3: really high percentage of people on iPhones.

351
00:18:28,000 --> 00:18:31,480
Speaker 1: Yeah, just kind of curious. But anyway, so I should

352
00:18:31,600 --> 00:18:33,480
Speaker 1: know this. But they're all made in China.

353
00:18:33,320 --> 00:18:37,480
Speaker 3: Right, No, not all phones are made in China, the iPhone.

354
00:18:38,600 --> 00:18:41,680
Speaker 3: That's a really good question. I don't know, Crago, I'm

355
00:18:41,680 --> 00:18:44,080
Speaker 3: not sure. I know, can you find that out? I

356
00:18:44,119 --> 00:18:47,000
Speaker 3: know Trump was trying to get them made or maybe

357
00:18:47,359 --> 00:18:50,080
Speaker 3: assembled in the United States, so maybe some of the

358
00:18:50,160 --> 00:18:52,919
Speaker 3: cool components and then they're assembled, because that was the

359
00:18:52,920 --> 00:18:55,639
Speaker 3: big thing with tariffs that you know, there was a

360
00:18:55,640 --> 00:18:58,040
Speaker 3: bit of a panic for the likes of iPhone, even

361
00:18:58,080 --> 00:19:01,679
Speaker 3: though it's an American company. Apple is obviously a mega

362
00:19:02,400 --> 00:19:06,719
Speaker 3: American company, but because they're manufacturing off shore, it means

363
00:19:06,760 --> 00:19:09,280
Speaker 3: that they were subject to tariffs, and then that was

364
00:19:09,359 --> 00:19:12,119
Speaker 3: lifted for ninety days, if you remember, right.

365
00:19:13,240 --> 00:19:16,200
Speaker 1: Can I raise a topic that isn't on your list,

366
00:19:16,200 --> 00:19:19,359
Speaker 1: but I think you'll find it interesting nonetheless, because it

367
00:19:19,400 --> 00:19:24,400
Speaker 1: intersects your world and mine. So there's a whole lot

368
00:19:24,440 --> 00:19:27,280
Speaker 1: of I don't know what the word is, but I'm

369
00:19:27,320 --> 00:19:29,439
Speaker 1: going to say angst it's not the right word. But

370
00:19:29,480 --> 00:19:33,440
Speaker 1: it's in the ballpark with universities around Australia and around

371
00:19:33,440 --> 00:19:35,240
Speaker 1: the world at the moment trying to figure out how

372
00:19:35,240 --> 00:19:40,159
Speaker 1: the fuck to navigate undergrad degrees and postgrad degrees and

373
00:19:40,280 --> 00:19:44,800
Speaker 1: people and how AI is going to be integrated into

374
00:19:44,840 --> 00:19:49,760
Speaker 1: the academic process because it is so easy to cheat now,

375
00:19:50,080 --> 00:19:54,879
Speaker 1: especially with undergrad degrees where you've basically got to do

376
00:19:54,960 --> 00:20:02,480
Speaker 1: assignments and research projects. Primarily they can't obviously they can't

377
00:20:02,480 --> 00:20:06,159
Speaker 1: say to students you can't use AI because it's past

378
00:20:06,200 --> 00:20:09,720
Speaker 1: that point. But they're now trying to figure it, figure it,

379
00:20:09,960 --> 00:20:12,280
Speaker 1: figure out how to how to do that, what that

380
00:20:12,359 --> 00:20:16,760
Speaker 1: looks like. And I was talking to my senior supervisor yesterday, Chris,

381
00:20:18,280 --> 00:20:21,760
Speaker 1: who's you know, a professor, got two PhDs, blah blah blah,

382
00:20:21,800 --> 00:20:24,800
Speaker 1: And he's actually in the middle of conversations with my

383
00:20:25,000 --> 00:20:27,679
Speaker 1: university around this at the moment. And one of the

384
00:20:27,760 --> 00:20:31,000
Speaker 1: challenges is that the people who are very high up

385
00:20:31,040 --> 00:20:34,760
Speaker 1: in these organizations are generally older and they don't really

386
00:20:34,960 --> 00:20:39,719
Speaker 1: understand AI. So but then all the people who do

387
00:20:39,760 --> 00:20:43,200
Speaker 1: have great understanding are not the decision makers. So it's

388
00:20:43,280 --> 00:20:46,520
Speaker 1: it's going to be interesting moving forward to see how

389
00:20:47,600 --> 00:20:49,600
Speaker 1: you know, like my PhD is going to be by

390
00:20:49,600 --> 00:20:53,000
Speaker 1: the time I finished six years of work but foreseeably

391
00:20:53,480 --> 00:20:56,239
Speaker 1: done the right way, And I put that with an

392
00:20:56,280 --> 00:20:59,639
Speaker 1: asterisk next to it. Somebody could do all of the

393
00:20:59,680 --> 00:21:02,880
Speaker 1: work in a PhD in four weeks if they knew

394
00:21:02,880 --> 00:21:05,719
Speaker 1: what they were doing, depending on the type, Like they

395
00:21:05,720 --> 00:21:10,000
Speaker 1: couldn't do mine because mine was independent research, right as

396
00:21:10,040 --> 00:21:13,200
Speaker 1: in people in rooms and all of that. But yeah,

397
00:21:13,200 --> 00:21:15,240
Speaker 1: it's going to be interesting to see how that unfolds

398
00:21:15,240 --> 00:21:17,120
Speaker 1: over the next one two five years.

399
00:21:17,480 --> 00:21:19,920
Speaker 3: Yes, because you could do a PhD based on someone

400
00:21:19,960 --> 00:21:23,720
Speaker 3: else's research, can't you, or the data from research well

401
00:21:23,800 --> 00:21:24,600
Speaker 3: you care.

402
00:21:24,480 --> 00:21:27,280
Speaker 1: Well, you can do papers. You probably couldn't do an

403
00:21:27,440 --> 00:21:30,960
Speaker 1: entire PhD, but you can. Like one of my papers

404
00:21:31,040 --> 00:21:33,320
Speaker 1: is called a systematic review, which is where I look

405
00:21:33,359 --> 00:21:35,879
Speaker 1: at basically all of the work that's been done in

406
00:21:35,880 --> 00:21:42,199
Speaker 1: a particular area, in this case, meta accuracy. And I

407
00:21:42,240 --> 00:21:46,240
Speaker 1: started with sixteen hundred papers or sixteen hundred journal articles,

408
00:21:46,720 --> 00:21:50,720
Speaker 1: research projects from different people and distilled it to one

409
00:21:50,800 --> 00:21:54,159
Speaker 1: hundred and sixteen and then created a table out of that,

410
00:21:54,200 --> 00:22:00,000
Speaker 1: and that's become the core of this one paper. But yeah,

411
00:21:59,600 --> 00:22:03,720
Speaker 1: there would definitely be a way, depending on the design

412
00:22:03,800 --> 00:22:07,520
Speaker 1: of your PhD and the field of research, where somebody

413
00:22:07,560 --> 00:22:13,080
Speaker 1: could cheat and produce the equivalent work of a four

414
00:22:13,200 --> 00:22:16,000
Speaker 1: or five year journey in a month probably best.

415
00:22:16,240 --> 00:22:18,680
Speaker 3: I think the question for me when I think about this,

416
00:22:18,720 --> 00:22:21,800
Speaker 3: because I haven't obviously done a PhD, but how much

417
00:22:21,840 --> 00:22:24,800
Speaker 3: of the work that you did was kind of manual

418
00:22:25,000 --> 00:22:28,720
Speaker 3: grunt work as opposed to analysis. So say, for example,

419
00:22:28,760 --> 00:22:31,320
Speaker 3: you took all that data and you said how many

420
00:22:31,480 --> 00:22:35,480
Speaker 3: articles referenced this phrase. Now you could go through manually

421
00:22:35,560 --> 00:22:37,359
Speaker 3: and say, oh, yeah, that one did, that one didn't,

422
00:22:37,359 --> 00:22:39,400
Speaker 3: that one didn't, that one did, But you could also

423
00:22:39,520 --> 00:22:42,120
Speaker 3: plug it onto AI and it would instantly give you

424
00:22:42,440 --> 00:22:44,959
Speaker 3: all the articles that reference that phrase. So I'm thinking

425
00:22:45,040 --> 00:22:48,080
Speaker 3: in terms of writing something down and adding it up

426
00:22:48,119 --> 00:22:51,200
Speaker 3: and using a calculator. You know, it's just makes life easier.

427
00:22:51,520 --> 00:22:54,960
Speaker 3: So I think that, and you're right because we're still

428
00:22:54,960 --> 00:22:58,440
Speaker 3: coming to terms with AI. You know, your six year

429
00:22:58,520 --> 00:23:02,440
Speaker 3: project maybe could have been done in two years because

430
00:23:02,480 --> 00:23:05,240
Speaker 3: the grunt work could have been used by AI. You know,

431
00:23:05,359 --> 00:23:07,520
Speaker 3: there'd be validation and all that sort of thing. But

432
00:23:07,800 --> 00:23:10,520
Speaker 3: so I'm thinking it's it comes back to what's the

433
00:23:10,520 --> 00:23:14,120
Speaker 3: Spider Man quote, with great power comes great responsibility.

434
00:23:14,480 --> 00:23:16,160
Speaker 1: I love a good Spider Man reference.

435
00:23:16,480 --> 00:23:19,480
Speaker 3: Yeah, I know, I love that. On a side note,

436
00:23:19,520 --> 00:23:21,639
Speaker 3: you didn't see the video this morning of the guy

437
00:23:21,760 --> 00:23:23,960
Speaker 3: who went to court, you know, the graffiti guy who did.

438
00:23:24,280 --> 00:23:27,200
Speaker 1: Yeah, I saw him on the news wearing Spider Man.

439
00:23:27,280 --> 00:23:30,800
Speaker 3: Yeah. But getting back to this, so, you know, so

440
00:23:31,480 --> 00:23:36,080
Speaker 3: potentially your good, your use of AI could streamline what

441
00:23:36,400 --> 00:23:38,680
Speaker 3: is a very laborious process. And that's what I was

442
00:23:38,760 --> 00:23:41,080
Speaker 3: kind of getting to using the tools in the right

443
00:23:41,119 --> 00:23:43,040
Speaker 3: way one And.

444
00:23:43,000 --> 00:23:45,800
Speaker 1: I think, look, there are like I had to read

445
00:23:45,840 --> 00:23:48,720
Speaker 1: through hundreds and hundreds of journal articles and you can't

446
00:23:48,760 --> 00:23:51,600
Speaker 1: get the knowledge. You're like, you actually need to read them.

447
00:23:52,359 --> 00:23:57,320
Speaker 1: At the very least, you need to do a solid

448
00:23:57,359 --> 00:23:59,240
Speaker 1: skin which could be a half hour or an hour

449
00:23:59,280 --> 00:24:01,480
Speaker 1: of a paper if not read it, start to finish, right.

450
00:24:03,000 --> 00:24:07,520
Speaker 1: But then yeah, there are certainly things where I could say, listen,

451
00:24:09,040 --> 00:24:13,360
Speaker 1: I want show me some research that supports this idea,

452
00:24:14,160 --> 00:24:16,919
Speaker 1: some you know, and like he's the idea, Bubba, and

453
00:24:16,960 --> 00:24:18,800
Speaker 1: then I'll give you a bunch of papers, a bunch

454
00:24:18,800 --> 00:24:22,800
Speaker 1: of references or quotes, you know, the name of the

455
00:24:22,840 --> 00:24:25,320
Speaker 1: study the year of the study, the authors of the study,

456
00:24:25,840 --> 00:24:28,080
Speaker 1: and then I can decide whether or not I want

457
00:24:28,080 --> 00:24:31,000
Speaker 1: to integrate that into my research, you know. But that's

458
00:24:31,080 --> 00:24:34,080
Speaker 1: that's a good use, you know. But but there are

459
00:24:35,480 --> 00:24:38,800
Speaker 1: you know, some students now that are getting AI to

460
00:24:39,040 --> 00:24:42,600
Speaker 1: actually write their work. Like there will be a homework

461
00:24:42,680 --> 00:24:45,919
Speaker 1: question and I'll say, you know, do a project on

462
00:24:46,000 --> 00:24:50,080
Speaker 1: this and that, exploring this particular whatever, and it can

463
00:24:50,440 --> 00:24:53,440
Speaker 1: AI can produce that, you know, and then they can

464
00:24:53,520 --> 00:24:58,119
Speaker 1: jump in and manipulate a little bit. So there's a

465
00:24:58,200 --> 00:25:01,639
Speaker 1: thing called there's a thing called turn it in. I

466
00:25:01,680 --> 00:25:05,800
Speaker 1: think that's what it's called, where you actually you can

467
00:25:05,880 --> 00:25:08,240
Speaker 1: put the paper that you wrote, whether or not you

468
00:25:08,320 --> 00:25:12,560
Speaker 1: wrote it, into this program and it tells you it

469
00:25:12,600 --> 00:25:16,120
Speaker 1: will give you a turnet in score basically on how

470
00:25:16,200 --> 00:25:19,720
Speaker 1: much of it is being ripped off directly from other sources.

471
00:25:20,520 --> 00:25:23,439
Speaker 1: The problem now is AI can write it in a

472
00:25:23,480 --> 00:25:26,200
Speaker 1: way where the turnet in score comes out like it's

473
00:25:26,240 --> 00:25:29,760
Speaker 1: completely original from you, despite the fact that it's totally

474
00:25:29,800 --> 00:25:32,840
Speaker 1: not original. I could have a bit of that wrong.

475
00:25:32,880 --> 00:25:34,040
Speaker 1: But that's my understanding.

476
00:25:34,400 --> 00:25:37,640
Speaker 3: You have checks and measures, because I know that we've

477
00:25:37,720 --> 00:25:40,919
Speaker 3: hung out before where you've had to prepare for presentations.

478
00:25:40,920 --> 00:25:44,359
Speaker 3: So throughout the whole process there are checks and measures

479
00:25:44,359 --> 00:25:47,960
Speaker 3: along the way, and there is an oral presentation where

480
00:25:48,320 --> 00:25:51,160
Speaker 3: you really need to be grilled on what your knowledge

481
00:25:51,160 --> 00:25:54,440
Speaker 3: base is. So I guess the owners is now going

482
00:25:54,480 --> 00:25:58,320
Speaker 3: to be on the institution's universities to try to come

483
00:25:58,400 --> 00:26:02,200
Speaker 3: up with ways to make sure that someone like yourself

484
00:26:02,680 --> 00:26:06,639
Speaker 3: could be through those processes grilled on whatever the topic is.

485
00:26:06,680 --> 00:26:08,119
Speaker 3: I don't know, but then you've got to have smart

486
00:26:08,160 --> 00:26:10,200
Speaker 3: people there can understand what you're talking about.

487
00:26:10,400 --> 00:26:12,560
Speaker 1: Yeah, that's true. TIF did you find out?

488
00:26:12,800 --> 00:26:14,119
Speaker 4: Oh thanks for coming back to me.

489
00:26:15,359 --> 00:26:17,120
Speaker 1: Yeah, do you feel a bit?

490
00:26:17,800 --> 00:26:20,480
Speaker 2: I feel like we're all through the forest together and

491
00:26:20,480 --> 00:26:22,560
Speaker 2: you guys throw a stick and I go chase it,

492
00:26:22,600 --> 00:26:24,800
Speaker 2: and then you turn and change direction, and I'm like,

493
00:26:25,040 --> 00:26:26,359
Speaker 2: where are they wait for me?

494
00:26:27,119 --> 00:26:30,760
Speaker 3: I remember, that's the best analogy ever.

495
00:26:32,760 --> 00:26:34,000
Speaker 4: I was just sitting over your wagon.

496
00:26:34,040 --> 00:26:36,840
Speaker 2: My tail of phones and this is the same for

497
00:26:36,880 --> 00:26:40,359
Speaker 2: Android are made in China and the other ten percent

498
00:26:40,560 --> 00:26:43,840
Speaker 2: are mostly India and Vietnam.

499
00:26:44,240 --> 00:26:48,280
Speaker 1: The problem is not the problem but the benefits slash

500
00:26:48,400 --> 00:26:50,600
Speaker 1: problem is that they do a really good job. They're

501
00:26:50,600 --> 00:26:54,359
Speaker 1: really cost effective, you know. They it's and then to

502
00:26:54,600 --> 00:26:57,360
Speaker 1: do the same thing in Australia would just they probably

503
00:26:57,440 --> 00:27:00,000
Speaker 1: or they potentially wouldn't be as good and they would

504
00:27:00,080 --> 00:27:02,800
Speaker 1: cost two or three times as much and we probably

505
00:27:02,840 --> 00:27:04,399
Speaker 1: don't have the capacity to do it.

506
00:27:04,840 --> 00:27:06,720
Speaker 3: Yeah, Tim is a string mate.

507
00:27:07,640 --> 00:27:11,080
Speaker 1: Yeah, OK, Brian, how are you well? Thanks? Tiff, don't

508
00:27:11,160 --> 00:27:14,600
Speaker 1: feel free to jump in You're You're an integral part

509
00:27:14,640 --> 00:27:17,280
Speaker 1: of the conversation with lu you.

510
00:27:17,359 --> 00:27:18,040
Speaker 3: Oh yeah.

511
00:27:18,200 --> 00:27:20,359
Speaker 1: And also I just want you to know your scene.

512
00:27:20,960 --> 00:27:22,800
Speaker 4: I was just waiting for one of you to take

513
00:27:22,840 --> 00:27:23,880
Speaker 4: a breath. That's all.

514
00:27:25,200 --> 00:27:27,720
Speaker 3: A while, have you not before?

515
00:27:28,840 --> 00:27:31,960
Speaker 1: I think chatty mcs chatster in the International Space Station's

516
00:27:32,000 --> 00:27:33,280
Speaker 1: got you and me both covered.

517
00:27:35,760 --> 00:27:38,800
Speaker 3: Wow, hey, you know talking. Just to continue the theme

518
00:27:38,840 --> 00:27:43,879
Speaker 3: of AI, it's there's real concerns with a lot of

519
00:27:43,960 --> 00:27:50,960
Speaker 3: news sites that Google's new way of summarizing. So, I

520
00:27:50,960 --> 00:27:52,600
Speaker 3: don't know if you've noticed. You do a Google search

521
00:27:52,640 --> 00:27:54,679
Speaker 3: now and it gives you an AI summary first.

522
00:27:55,280 --> 00:27:56,200
Speaker 1: Yeah. Yeah.

523
00:27:56,280 --> 00:27:59,320
Speaker 3: Now the problem is this a new study. This has

524
00:27:59,320 --> 00:28:01,400
Speaker 3: come out of the guard in newspaper. It's an exclusive

525
00:28:01,400 --> 00:28:06,720
Speaker 3: in the Guardian and the study claims that previously sites

526
00:28:06,760 --> 00:28:10,119
Speaker 3: that were ranked really high can lose up to seventy

527
00:28:10,200 --> 00:28:13,840
Speaker 3: nine percent of all their traffic because people aren't bothering

528
00:28:13,920 --> 00:28:16,040
Speaker 3: to go to the site. They're just using the AI

529
00:28:16,240 --> 00:28:20,680
Speaker 3: overview and they're not drilling down any further. So there's

530
00:28:20,720 --> 00:28:25,080
Speaker 3: a massive drop in online site traffic purely because people

531
00:28:25,160 --> 00:28:27,679
Speaker 3: are just going with the summary, because the AI summary

532
00:28:27,760 --> 00:28:29,919
Speaker 3: is pig good. I mean, I do use it a

533
00:28:29,920 --> 00:28:34,280
Speaker 3: little bit. I find that sometimes maybe thirty percent of

534
00:28:34,320 --> 00:28:36,960
Speaker 3: the time, it's inaccurate and I have to look further.

535
00:28:37,560 --> 00:28:40,040
Speaker 3: But that's problematic, and generally I tend to use it

536
00:28:40,040 --> 00:28:43,200
Speaker 3: for technical questions. It might be in relation to, say,

537
00:28:43,400 --> 00:28:45,880
Speaker 3: you know, something I'm doing in some web design and

538
00:28:45,920 --> 00:28:49,680
Speaker 3: I need some help going through a process. So I've

539
00:28:49,760 --> 00:28:52,600
Speaker 3: found that that's not always accurate, and I really honestly

540
00:28:52,640 --> 00:28:54,719
Speaker 3: think it's probably about thirty percent of the stuff can

541
00:28:54,760 --> 00:28:57,640
Speaker 3: be a bit crap, but this is really causing a

542
00:28:57,640 --> 00:29:01,560
Speaker 3: lot of concern for those webs sites that rely on

543
00:29:01,720 --> 00:29:05,560
Speaker 3: that organic search traffic. So there's two types of search.

544
00:29:05,600 --> 00:29:07,320
Speaker 3: When you I don't want to kind of go into

545
00:29:07,360 --> 00:29:10,680
Speaker 3: the boring territory, but there's paid advertising where you see

546
00:29:10,720 --> 00:29:13,440
Speaker 3: little sponsored ad and you can pay to bump up

547
00:29:13,600 --> 00:29:16,320
Speaker 3: that information or this is what we call organic, and

548
00:29:16,360 --> 00:29:20,959
Speaker 3: that's really hard earned by creating content that is related

549
00:29:21,080 --> 00:29:23,800
Speaker 3: for specific topic, and then Google says, oh, yeah, this

550
00:29:23,840 --> 00:29:26,080
Speaker 3: is really interesting. You know, if I looked up the

551
00:29:26,120 --> 00:29:30,120
Speaker 3: you project, then your website would be very high in

552
00:29:30,160 --> 00:29:32,880
Speaker 3: that list because you're the authority when it comes to

553
00:29:32,920 --> 00:29:35,600
Speaker 3: the you project, because you are the U project. Or

554
00:29:35,600 --> 00:29:37,840
Speaker 3: if it was role with the punches, you know, TIFF's

555
00:29:37,880 --> 00:29:40,720
Speaker 3: information would come up there. But if you're just getting

556
00:29:40,720 --> 00:29:43,640
Speaker 3: an AI overview, you might not bother going to TIFF's

557
00:29:43,640 --> 00:29:46,120
Speaker 3: website or to your website. You might think, oh, well,

558
00:29:46,120 --> 00:29:48,560
Speaker 3: that's fine, Craig's the host of the new project. I

559
00:29:48,560 --> 00:29:50,840
Speaker 3: don't need to find out anything else because that's given

560
00:29:50,840 --> 00:29:53,320
Speaker 3: me the summary. And this is the worry for people

561
00:29:53,320 --> 00:29:57,080
Speaker 3: who run their businesses and you want to sell product

562
00:29:57,160 --> 00:29:59,640
Speaker 3: or they want to service up news services that you

563
00:30:00,040 --> 00:30:03,400
Speaker 3: sickly going to lose seventy or eighty percent of all

564
00:30:03,480 --> 00:30:06,520
Speaker 3: your search traffic swings aroundabouts.

565
00:30:06,760 --> 00:30:09,800
Speaker 1: It's good for it's good for the user, maybe that

566
00:30:09,840 --> 00:30:12,320
Speaker 1: they can get a quick snapshot without having to go

567
00:30:12,440 --> 00:30:15,480
Speaker 1: down the rabbit hole or but yeah, for the for

568
00:30:15,560 --> 00:30:20,200
Speaker 1: the people on the other side, not so great. Do

569
00:30:20,240 --> 00:30:24,160
Speaker 1: you say project or project, project, project? Yeah?

570
00:30:24,280 --> 00:30:25,120
Speaker 3: What did I just say?

571
00:30:25,760 --> 00:30:25,960
Speaker 6: Yeah?

572
00:30:26,000 --> 00:30:29,160
Speaker 1: You also always say project. I'm like it's not it's

573
00:30:29,160 --> 00:30:32,920
Speaker 1: not bad, but it's like most people say, Yeah, I

574
00:30:32,960 --> 00:30:33,920
Speaker 1: wonder why that is.

575
00:30:34,840 --> 00:30:36,720
Speaker 3: I don't know. Now I'm getting self conscious about it.

576
00:30:36,760 --> 00:30:38,040
Speaker 3: I don't even know that I did it.

577
00:30:38,320 --> 00:30:40,320
Speaker 1: Oh, you don't need to at all. That's I think.

578
00:30:40,360 --> 00:30:41,600
Speaker 1: It's it's interesting just.

579
00:30:42,000 --> 00:30:44,680
Speaker 3: Thinking also about this. You know, when the AI summary

580
00:30:44,720 --> 00:30:48,480
Speaker 3: comes up, it pushes everything down. And there's an interesting

581
00:30:48,640 --> 00:30:52,000
Speaker 3: term used in web design called the first fold, and

582
00:30:52,040 --> 00:30:55,240
Speaker 3: the first fold refers to the old newspaper term. You know,

583
00:30:55,320 --> 00:30:58,440
Speaker 3: you read all the paper was folded in half, and

584
00:30:58,480 --> 00:31:00,720
Speaker 3: you had to fold it to read the rest of it.

585
00:31:00,920 --> 00:31:05,280
Speaker 3: And that's what's before you scroll on a screen generally

586
00:31:05,280 --> 00:31:09,000
Speaker 3: obviously it's mainly on a desktop, but before you start scrolling,

587
00:31:09,160 --> 00:31:12,120
Speaker 3: that's referred to the first fold. Now the AI information

588
00:31:12,520 --> 00:31:15,920
Speaker 3: is pushing everything down. Then the legitimate results or the

589
00:31:16,000 --> 00:31:18,239
Speaker 3: other results are pushed further down the screen, and then

590
00:31:18,240 --> 00:31:20,560
Speaker 3: you've got to scribby scroll further to try to get

591
00:31:20,600 --> 00:31:21,440
Speaker 3: to them.

592
00:31:21,760 --> 00:31:25,520
Speaker 1: Hey, staying in the AI theme, Yeah, more people are

593
00:31:25,600 --> 00:31:28,840
Speaker 1: considering AI lovers and we shouldn't judge.

594
00:31:29,360 --> 00:31:32,240
Speaker 3: Yeah, what do you well, I've thought about this a lot,

595
00:31:32,480 --> 00:31:35,760
Speaker 3: and interestingly, I was having this discussion with my seventeen

596
00:31:35,840 --> 00:31:38,360
Speaker 3: year old employee about to turn eighteen. He's got a

597
00:31:38,360 --> 00:31:39,240
Speaker 3: girlfriend having.

598
00:31:39,160 --> 00:31:48,680
Speaker 1: This conversation with my virtual girlfriend. Look, sorry, sorry, boyfriend,

599
00:31:49,760 --> 00:31:54,360
Speaker 1: Chad Chuck Chuck Chuck the AI boyfriend.

600
00:31:54,760 --> 00:31:58,320
Speaker 3: Now, look, I'm really into minds about this because I

601
00:31:59,000 --> 00:32:03,200
Speaker 3: love the idea of AI being used, and particularly our

602
00:32:03,280 --> 00:32:09,160
Speaker 3: local medical clinic has a aged care residence and I've

603
00:32:09,160 --> 00:32:11,520
Speaker 3: been so excited to get there because they've got a

604
00:32:11,520 --> 00:32:14,480
Speaker 3: little robot that talks to the residents, and the residents

605
00:32:14,520 --> 00:32:17,280
Speaker 3: interact with the robot, and as the AI gets to

606
00:32:17,320 --> 00:32:20,240
Speaker 3: know the residents, it's interact with them and may talk

607
00:32:20,240 --> 00:32:22,760
Speaker 3: about things that they're more interested in, or gets to

608
00:32:22,800 --> 00:32:25,840
Speaker 3: know who they are, and it's using these great features. Now,

609
00:32:26,200 --> 00:32:30,360
Speaker 3: it's an inanimate object that is interactive and it's not

610
00:32:30,440 --> 00:32:34,040
Speaker 3: a person. But I can see that these people are

611
00:32:34,120 --> 00:32:36,720
Speaker 3: really getting a lot of value out of this interaction.

612
00:32:37,080 --> 00:32:41,360
Speaker 3: So would you fall in love with an AI? It's speculative,

613
00:32:41,600 --> 00:32:45,440
Speaker 3: it's suggested that it's inevitable, like there's a thought process

614
00:32:45,440 --> 00:32:48,000
Speaker 3: out there that eventually if you build up a rapport

615
00:32:48,240 --> 00:32:51,160
Speaker 3: or a repertoire or whatever with your chatbot. But I

616
00:32:51,480 --> 00:32:55,640
Speaker 3: mean I was talking to you know, to Caspa last night,

617
00:32:55,760 --> 00:32:59,360
Speaker 3: and you know young guy who you know, he's got

618
00:32:59,360 --> 00:33:02,520
Speaker 3: a girlfriend and is really enamored and it's lovely to see,

619
00:33:02,640 --> 00:33:04,400
Speaker 3: you know, you have one of your first loves and

620
00:33:04,400 --> 00:33:06,520
Speaker 3: all that sort of stuff. And of course he couldn't

621
00:33:06,560 --> 00:33:10,160
Speaker 3: conceive of the concept of having a chatbot that you

622
00:33:10,240 --> 00:33:13,160
Speaker 3: fall in love with. But I look, you know, we

623
00:33:13,320 --> 00:33:16,080
Speaker 3: talk about love in different ways. We have friends that

624
00:33:16,120 --> 00:33:20,040
Speaker 3: we care about and that we love. I love my dog,

625
00:33:20,960 --> 00:33:23,080
Speaker 3: and I could possibly say that I love my dog

626
00:33:23,160 --> 00:33:26,520
Speaker 3: more than some people. But what I'm saying is I'm

627
00:33:26,560 --> 00:33:29,200
Speaker 3: not in love. But you can love or feel a

628
00:33:29,240 --> 00:33:32,040
Speaker 3: connection in different ways, and it may not be so

629
00:33:32,160 --> 00:33:35,360
Speaker 3: much romantic, but it could be more empathetic, you know.

630
00:33:35,440 --> 00:33:39,000
Speaker 3: So I feel that it may be inevitable that as

631
00:33:39,040 --> 00:33:44,400
Speaker 3: we form these relationships with these online AI entities, that

632
00:33:44,440 --> 00:33:47,600
Speaker 3: we start to feel a real emotional connection to them.

633
00:33:48,000 --> 00:33:50,120
Speaker 3: But it opens up a can of worms, because what

634
00:33:50,880 --> 00:33:55,880
Speaker 3: if Craig dot ai suddenly goes bust and my AI

635
00:33:56,360 --> 00:34:00,280
Speaker 3: Harper chatbot is suddenly gone forever and I feel like

636
00:34:00,320 --> 00:34:01,800
Speaker 3: I've lost Craig, you know.

637
00:34:02,400 --> 00:34:05,240
Speaker 1: So that's I think you nailed it. Like I was

638
00:34:05,680 --> 00:34:10,440
Speaker 1: going to say, I don't think you know, falling in

639
00:34:10,520 --> 00:34:14,000
Speaker 1: love with is the kind of the hook the article,

640
00:34:14,840 --> 00:34:17,680
Speaker 1: and maybe some people do, but I think it's Yeah,

641
00:34:17,760 --> 00:34:20,879
Speaker 1: it's more about an emotional connection or a bond where

642
00:34:20,920 --> 00:34:25,279
Speaker 1: people feel I don't know, I feel like they have

643
00:34:25,560 --> 00:34:31,440
Speaker 1: a relationship or a bond or a connection or something

644
00:34:31,480 --> 00:34:34,320
Speaker 1: that has a level of consciousness and awareness that knows

645
00:34:34,400 --> 00:34:38,600
Speaker 1: their name, that talks to them, that remembers things about them.

646
00:34:39,080 --> 00:34:43,360
Speaker 1: So here's my funny little story, right, chat GPT always

647
00:34:43,360 --> 00:34:45,759
Speaker 1: says something to me like, hey, Craig, what's up? Or Hey,

648
00:34:45,760 --> 00:34:47,799
Speaker 1: that's a great question, Craig, let me think about it,

649
00:34:47,880 --> 00:34:50,120
Speaker 1: or hey, Craig, hope you have any all this? And

650
00:34:50,120 --> 00:34:52,439
Speaker 1: the other day it responded to something and it just said,

651
00:34:52,920 --> 00:34:56,799
Speaker 1: let me check. I'm like, where's my name? Bro? Like

652
00:34:56,920 --> 00:34:59,759
Speaker 1: I felt a bit hurt. I felt a little bit

653
00:34:59,880 --> 00:35:02,759
Speaker 1: like why did you not? Why you're not using my name?

654
00:35:03,920 --> 00:35:06,600
Speaker 1: And just for one moment, not really hurt, but I

655
00:35:06,840 --> 00:35:09,239
Speaker 1: just noticed it, and I'm like, I don't like it

656
00:35:09,280 --> 00:35:12,759
Speaker 1: when it doesn't use my name. I'm like, I may

657
00:35:12,800 --> 00:35:15,520
Speaker 1: have a relationship with chat JPT. I'm not sure. I'm

658
00:35:15,560 --> 00:35:16,319
Speaker 1: working through it.

659
00:35:16,840 --> 00:35:19,200
Speaker 3: Heif have you ever noticed how Craig looks at his

660
00:35:19,280 --> 00:35:20,839
Speaker 3: motorbikes when he's showing them off.

661
00:35:22,440 --> 00:35:24,040
Speaker 1: Never show my motorbikes off.

662
00:35:24,120 --> 00:35:27,000
Speaker 3: He did show off. No, No, you did kind of

663
00:35:27,120 --> 00:35:27,960
Speaker 3: look at But.

664
00:35:28,160 --> 00:35:30,960
Speaker 2: I know you're asking someone that probably looks at motorbikes

665
00:35:30,960 --> 00:35:32,759
Speaker 2: the same way, So I'm not I don't see it

666
00:35:32,760 --> 00:35:33,319
Speaker 2: problem here.

667
00:35:33,640 --> 00:35:36,239
Speaker 3: We can feel a fondness for objects, as we know,

668
00:35:36,680 --> 00:35:40,719
Speaker 3: got sentimental value. You may not bear to be able

669
00:35:40,760 --> 00:35:42,600
Speaker 3: to think that it was not there with you, and

670
00:35:42,600 --> 00:35:46,840
Speaker 3: it could be something that has no intrinsic kind of

671
00:35:46,880 --> 00:35:50,480
Speaker 3: monetary value, but because you've had it since I've got

672
00:35:50,480 --> 00:35:53,680
Speaker 3: a pencil case that I had in primary school, still

673
00:35:53,800 --> 00:35:56,560
Speaker 3: tucked away somewhere, and every now and again I happened

674
00:35:56,560 --> 00:35:58,840
Speaker 3: across it and open and I think, oh, there's my

675
00:35:59,080 --> 00:36:03,719
Speaker 3: to be I remember using that to b drawing pictures on.

676
00:36:04,760 --> 00:36:06,480
Speaker 4: A motorbike with a pencil case.

677
00:36:07,239 --> 00:36:12,239
Speaker 1: Well, hey, can I just say, speaking of memories, my

678
00:36:13,680 --> 00:36:17,640
Speaker 1: screen flashes up news stories in little bubbles. I don't

679
00:36:17,680 --> 00:36:19,799
Speaker 1: know why you can fix that, Patrick, next time you

680
00:36:19,840 --> 00:36:24,719
Speaker 1: hear but hul Cogan just died. Now, I know neither

681
00:36:24,760 --> 00:36:28,080
Speaker 1: of you were probably big wrestling fans. Do you both

682
00:36:28,160 --> 00:36:32,560
Speaker 1: know who he is? Of course I do, Yeah, yeah, yeah,

683
00:36:32,600 --> 00:36:35,279
Speaker 1: so that's sad whole Cogan, did you ever watch the

684
00:36:35,440 --> 00:36:37,120
Speaker 1: w w E, Patrick or Too.

685
00:36:38,000 --> 00:36:40,799
Speaker 3: There was a wrestling program on a Sunday when I

686
00:36:40,840 --> 00:36:44,040
Speaker 3: was a kid that we used to watch Maria Mulano.

687
00:36:44,560 --> 00:36:47,000
Speaker 1: No, no, dude, no, that.

688
00:36:48,480 --> 00:36:53,680
Speaker 3: Know, No, that's like wrestling thing. Wasn't there with Mury.

689
00:36:53,880 --> 00:36:58,400
Speaker 1: That Yeah, that's true. That was like like sick Championship Wrestling.

690
00:36:58,760 --> 00:37:02,720
Speaker 3: Well that was w W something well different.

691
00:37:02,960 --> 00:37:06,600
Speaker 1: Okay, you're so out of the loop, out of the WWE.

692
00:37:06,680 --> 00:37:09,520
Speaker 1: But anyway, he passed away sadly. Anyway, none of our

693
00:37:09,560 --> 00:37:10,959
Speaker 1: listeners care about that harp.

694
00:37:11,040 --> 00:37:14,959
Speaker 3: So here now they left, like the three intros ago.

695
00:37:17,760 --> 00:37:23,480
Speaker 1: Seriously, YouTube prepares crackdown on mass produced and repetitive videos.

696
00:37:23,600 --> 00:37:25,920
Speaker 3: Have you noticed how much shit is on YouTube at

697
00:37:25,920 --> 00:37:30,839
Speaker 3: the moment? Is there's so much AI slop that is

698
00:37:30,880 --> 00:37:35,000
Speaker 3: there making me angry? I get rage scrolling when I

699
00:37:35,040 --> 00:37:38,279
Speaker 3: look at you out, I do, Craig, and you know me,

700
00:37:38,719 --> 00:37:43,840
Speaker 3: I do tie chie, I get I get wow.

701
00:37:43,960 --> 00:37:47,200
Speaker 1: When you fire up my testicles retreat into my body,

702
00:37:47,280 --> 00:37:48,360
Speaker 1: I'm like wow.

703
00:37:49,640 --> 00:37:50,240
Speaker 3: In your throat.

704
00:37:52,600 --> 00:37:56,880
Speaker 1: No, it's a goiter, but at that bomb. Hey, everyone,

705
00:37:56,960 --> 00:37:59,680
Speaker 1: welcome to the you project. I'm Craig Harper, should we

706
00:37:59,719 --> 00:38:00,279
Speaker 1: start again?

707
00:38:01,400 --> 00:38:01,719
Speaker 6: The hell?

708
00:38:01,960 --> 00:38:05,959
Speaker 1: This is possibly the best and worst episode we've ever done.

709
00:38:06,200 --> 00:38:07,000
Speaker 3: You realize it.

710
00:38:07,360 --> 00:38:10,400
Speaker 1: We're going to get praize and complaints.

711
00:38:11,400 --> 00:38:15,480
Speaker 3: Sorry, Magda, I've turned your favorite segment into the shit

712
00:38:15,560 --> 00:38:16,080
Speaker 3: a segment.

713
00:38:17,640 --> 00:38:20,440
Speaker 1: Her favorite segment has become the show. Do you know

714
00:38:20,480 --> 00:38:23,120
Speaker 1: what this is like? It's like that comedian Tiff. You

715
00:38:23,200 --> 00:38:26,439
Speaker 1: probably know Matt Rife, Yes, yep, And all he does

716
00:38:26,560 --> 00:38:29,600
Speaker 1: is the crowd work. He doesn't actually do quite often,

717
00:38:30,040 --> 00:38:33,239
Speaker 1: he doesn't actually do a special where he stands up

718
00:38:33,320 --> 00:38:36,160
Speaker 1: and tells jokes. He never gets to that bit because

719
00:38:36,160 --> 00:38:38,840
Speaker 1: he's so good at riffing with the crowd and bullshitting.

720
00:38:40,920 --> 00:38:42,440
Speaker 1: Patrick take charge please.

721
00:38:42,560 --> 00:38:46,319
Speaker 3: Okay. So the way that people can earn money on

722
00:38:46,480 --> 00:38:49,000
Speaker 3: YouTube is to get lots and lots of looks at

723
00:38:49,080 --> 00:38:52,319
Speaker 3: videos that they create. The problem now is that people

724
00:38:52,400 --> 00:38:56,000
Speaker 3: are creating videos in a matter of minutes using AI

725
00:38:56,680 --> 00:39:01,319
Speaker 3: and pushing it out as a documentary about civilization hidden

726
00:39:01,400 --> 00:39:04,200
Speaker 3: underneath the pyramids. And we didn't know that they had

727
00:39:04,239 --> 00:39:07,399
Speaker 3: fusion reactors, you know, ten thousand years ago. So it's

728
00:39:07,400 --> 00:39:11,239
Speaker 3: that sort of crap that gets pushed out and unfortunately,

729
00:39:11,600 --> 00:39:14,319
Speaker 3: if they're clever enough, people click through and then it

730
00:39:14,360 --> 00:39:19,360
Speaker 3: pushes it up the algorithms, and so this crap basically

731
00:39:19,400 --> 00:39:23,160
Speaker 3: floats to the surface. And so YouTube is now looking

732
00:39:23,360 --> 00:39:28,960
Speaker 3: at trying to fine tune its partner program and particularly

733
00:39:29,040 --> 00:39:33,560
Speaker 3: the monetization policies, because when someone legitimately works really hard,

734
00:39:34,200 --> 00:39:37,160
Speaker 3: have you ever heard of? Okay, so maybe at five

735
00:39:37,200 --> 00:39:40,080
Speaker 3: o'clock this morning, I was watching a video on YouTube

736
00:39:40,120 --> 00:39:44,080
Speaker 3: about the Caspian Sea Monster right now the cure?

737
00:39:44,520 --> 00:39:47,080
Speaker 1: Would you say maybe? Why would you say maybe? Why

738
00:39:47,120 --> 00:39:50,279
Speaker 1: wouldn't you go? Why would you go a bit? I

739
00:39:50,320 --> 00:39:52,800
Speaker 1: was up at five, It's what I was doing. Everyone

740
00:39:52,800 --> 00:39:56,960
Speaker 1: else was sleeping or fucking I was watching a thing

741
00:39:57,000 --> 00:39:59,480
Speaker 1: on the Caspian Can you look.

742
00:39:59,360 --> 00:40:01,200
Speaker 3: Up the Caspian Sea Monster for us?

743
00:40:01,200 --> 00:40:04,879
Speaker 1: While God, I bet you can't wait. I was out

744
00:40:04,920 --> 00:40:08,680
Speaker 1: walking around suburbia like a fucking ninja, looking at with

745
00:40:09,560 --> 00:40:13,040
Speaker 1: all my friends, scaring everyone who had a dog and

746
00:40:13,120 --> 00:40:14,160
Speaker 1: was out and about.

747
00:40:14,200 --> 00:40:16,920
Speaker 3: Chet Chipet on your phone though, so you chet GPT

748
00:40:17,040 --> 00:40:18,000
Speaker 3: is always with you, Craig.

749
00:40:18,360 --> 00:40:21,279
Speaker 1: Yeah, I'm never alone. It's kind of like Jesus, but

750
00:40:21,400 --> 00:40:22,360
Speaker 1: more electronic.

751
00:40:23,080 --> 00:40:26,400
Speaker 3: That's the one. So tell us about the Caspian Sea Monster.

752
00:40:27,080 --> 00:40:31,120
Speaker 2: The Caspian Sea Monster refers to the Soviet made experimental

753
00:40:31,160 --> 00:40:36,239
Speaker 2: ground effect vehicle known as the KM corbel Macket. This

754
00:40:36,400 --> 00:40:41,839
Speaker 2: massive Ekreno plan whatever that is, a crenoplane, thank you,

755
00:40:42,640 --> 00:40:45,400
Speaker 2: was designed to fly just a few meters above the

756
00:40:45,440 --> 00:40:48,720
Speaker 2: water at high velocity. It was spotted by US spy

757
00:40:48,960 --> 00:40:50,600
Speaker 2: satellites during the Cold War.

758
00:40:51,120 --> 00:40:54,480
Speaker 3: Yeah, this is amazing aircraft which wasn't an aircraft. It

759
00:40:54,600 --> 00:40:56,840
Speaker 3: wasn't a plane, and it wasn't a boat. It was

760
00:40:56,880 --> 00:41:00,760
Speaker 3: a hybrid between the two. And I was this amazing

761
00:41:00,760 --> 00:41:03,359
Speaker 3: YouTube clip and the guy had put so much work

762
00:41:03,360 --> 00:41:07,880
Speaker 3: into going to Russia to see this a cranoplane, the

763
00:41:08,000 --> 00:41:12,040
Speaker 3: Caspian Sea Monster. It was quite revolutionary at the time

764
00:41:12,080 --> 00:41:15,360
Speaker 3: because it flew so low it was invisible to radar,

765
00:41:15,760 --> 00:41:18,200
Speaker 3: but it was so much faster than a boat or

766
00:41:18,239 --> 00:41:20,560
Speaker 3: a ship, so it meant that it could have been

767
00:41:20,840 --> 00:41:24,319
Speaker 3: a way to launch troops and to attack where no

768
00:41:24,400 --> 00:41:27,880
Speaker 3: one would see them coming effectively. But what I was

769
00:41:27,920 --> 00:41:31,200
Speaker 3: getting to is the amount of production quality that went

770
00:41:31,280 --> 00:41:34,480
Speaker 3: into this documentary that I was watching was fantastic and

771
00:41:34,520 --> 00:41:36,520
Speaker 3: I really found it interesting. I sent it to my

772
00:41:36,560 --> 00:41:39,800
Speaker 3: nerdy friend Ryan, who's an aerospace engineer and actually worked

773
00:41:39,840 --> 00:41:45,560
Speaker 3: on something similar. And then when someone throws out some

774
00:41:45,800 --> 00:41:49,400
Speaker 3: AI generated slop. It kind of makes me get that

775
00:41:49,520 --> 00:41:53,240
Speaker 3: rage scroll going, because you know, there's good quality stuff

776
00:41:53,280 --> 00:41:54,920
Speaker 3: on YouTube. So I think this is a bit of

777
00:41:54,960 --> 00:41:57,320
Speaker 3: a pad on the back to the people at Google

778
00:41:57,480 --> 00:41:59,319
Speaker 3: to try to clean up and get rid of this

779
00:41:59,400 --> 00:42:03,160
Speaker 3: mass produce video kind of slot that's out there, and

780
00:42:03,280 --> 00:42:06,040
Speaker 3: hopefully it will clean up the algorithm and clean up

781
00:42:06,080 --> 00:42:09,120
Speaker 3: the content so that when someone at five am wants

782
00:42:09,160 --> 00:42:13,840
Speaker 3: to look at old Russian planes, they get old Russian planes.

783
00:42:14,600 --> 00:42:18,759
Speaker 1: Shout out to that other guy who wants to do that.

784
00:42:19,360 --> 00:42:22,040
Speaker 1: You know they've already made that. You probably know this

785
00:42:22,080 --> 00:42:25,839
Speaker 1: better than the mate. But I think there's been at

786
00:42:25,960 --> 00:42:29,480
Speaker 1: least a couple of movies made which are completely AI,

787
00:42:29,880 --> 00:42:34,439
Speaker 1: no actors, The script was written by AI, the entire thing.

788
00:42:34,600 --> 00:42:38,920
Speaker 1: Some of them like very well, I don't know craft

789
00:42:38,960 --> 00:42:41,879
Speaker 1: that is that the right word. But I wonder if

790
00:42:42,000 --> 00:42:44,240
Speaker 1: down the track, because already there's a lot of CGI

791
00:42:44,360 --> 00:42:45,920
Speaker 1: and has been for a while, but I wonder if

792
00:42:45,960 --> 00:42:49,319
Speaker 1: down the track, you know, like soundtracks are done with AI,

793
00:42:49,400 --> 00:42:51,839
Speaker 1: scripts are done with AI, there are no actors there

794
00:42:51,880 --> 00:42:54,160
Speaker 1: are I wonder if that's going to become a thing

795
00:42:54,160 --> 00:42:56,160
Speaker 1: where people are going to go to cinemas to sit

796
00:42:56,239 --> 00:42:58,239
Speaker 1: and watch a cinema is going to be a thing.

797
00:42:58,280 --> 00:43:03,400
Speaker 1: That's another question. Completely AI created experience.

798
00:43:03,120 --> 00:43:05,640
Speaker 3: As long as we know that it's AI, as long

799
00:43:05,680 --> 00:43:08,600
Speaker 3: as we're put in the picture that way, there's some

800
00:43:08,640 --> 00:43:11,280
Speaker 3: great creative stuff out there. I don't know if we

801
00:43:11,320 --> 00:43:13,360
Speaker 3: talked about this on the show the last time we

802
00:43:13,400 --> 00:43:16,400
Speaker 3: had a segment two weeks ago, but there's a competition

803
00:43:16,520 --> 00:43:20,680
Speaker 3: going at the moment for people to actually use AI

804
00:43:20,960 --> 00:43:27,279
Speaker 3: to create artwork, to imagine women in history, to try

805
00:43:27,320 --> 00:43:31,640
Speaker 3: to shine the spotlight on the influence and the amazing

806
00:43:31,680 --> 00:43:33,480
Speaker 3: work that's been done over the years. I say it's

807
00:43:33,560 --> 00:43:37,200
Speaker 3: Marie Curie. Now, if someone isn't an artist or a

808
00:43:37,280 --> 00:43:41,160
Speaker 3: video producer, they can still use this AI, these AI

809
00:43:41,280 --> 00:43:45,680
Speaker 3: tools to reimagine or to visualize what that might have been.

810
00:43:45,719 --> 00:43:48,560
Speaker 3: So I can see that there are positives when someone

811
00:43:48,640 --> 00:43:51,680
Speaker 3: may be a really good storyteller but doesn't have video

812
00:43:51,840 --> 00:43:55,440
Speaker 3: editing skills. So it's got a fantastic idea. And I

813
00:43:55,480 --> 00:43:58,439
Speaker 3: know tif's good at drawing, so you could turn your

814
00:43:58,480 --> 00:44:01,759
Speaker 3: sketches into an animation sequence, so you could come up

815
00:44:01,800 --> 00:44:04,640
Speaker 3: with a cartoon series. But you don't animate, but you

816
00:44:04,840 --> 00:44:07,040
Speaker 3: are good at drawing or I might be good at

817
00:44:07,080 --> 00:44:09,600
Speaker 3: telling stories, but I'm not good with the other side

818
00:44:09,640 --> 00:44:12,120
Speaker 3: of it. So again it comes down to how it's

819
00:44:12,160 --> 00:44:15,680
Speaker 3: being used. Our Netflix is just about to launch a

820
00:44:15,719 --> 00:44:19,960
Speaker 3: new series where they've used AI exclusively to generate all

821
00:44:19,960 --> 00:44:22,920
Speaker 3: the special effects. So where they would have used compositing

822
00:44:23,280 --> 00:44:27,720
Speaker 3: and you know, the normal tools to create explosions or whatever,

823
00:44:28,080 --> 00:44:31,160
Speaker 3: they've then decided to go down the route of using AI.

824
00:44:31,360 --> 00:44:34,040
Speaker 3: But they've been very upfront about it, so they're saying,

825
00:44:34,360 --> 00:44:38,440
Speaker 3: this part of our series is using AI to create

826
00:44:38,560 --> 00:44:40,000
Speaker 3: these specific effects.

827
00:44:40,680 --> 00:44:44,640
Speaker 1: I wonder what Charlie Chaplin would think. I mean, what

828
00:44:44,800 --> 00:44:49,279
Speaker 1: was that maybe nineteen fifteen, nineteen ten, fifteen twenty. You

829
00:44:49,280 --> 00:44:53,680
Speaker 1: remember all those those old black and white silent movies

830
00:44:53,760 --> 00:44:57,040
Speaker 1: with him doing his own stunts and holding on to

831
00:44:57,120 --> 00:44:59,759
Speaker 1: the side of a train and climbing a ladder, that

832
00:45:00,400 --> 00:45:05,040
Speaker 1: leaning against the wall and Mike. It's just in a

833
00:45:05,320 --> 00:45:10,160
Speaker 1: relatively short time span, it's just become something completely different.

834
00:45:10,640 --> 00:45:13,000
Speaker 3: If you ever get a chance, do a YouTube search

835
00:45:13,239 --> 00:45:18,160
Speaker 3: on old special effects from black and white films, the

836
00:45:18,320 --> 00:45:20,880
Speaker 3: clever things that the filmmakers used to do. You know,

837
00:45:20,920 --> 00:45:22,759
Speaker 3: the first Man on the Moon, Remember the picture of

838
00:45:22,760 --> 00:45:25,479
Speaker 3: the moon with the rocket ship in its eye. There's

839
00:45:25,480 --> 00:45:28,640
Speaker 3: a really old, old old film that's out there. I

840
00:45:28,640 --> 00:45:30,839
Speaker 3: think it might have been French, but there was some

841
00:45:30,960 --> 00:45:36,080
Speaker 3: amazing optical illusions that we used in the old days

842
00:45:36,120 --> 00:45:39,000
Speaker 3: to create some amazing effects. It was just clever, really

843
00:45:39,000 --> 00:45:40,600
Speaker 3: really clever, interesting stuff.

844
00:45:41,040 --> 00:45:43,440
Speaker 1: Can I ask one question that isn't on the list

845
00:45:43,520 --> 00:45:47,360
Speaker 1: but was on the news and is as we speak,

846
00:45:48,000 --> 00:45:50,920
Speaker 1: just sitting on a deck chair in my prefrontal cortex

847
00:45:51,000 --> 00:45:55,759
Speaker 1: waiting to get some attention. You're welcome everyone. That is

848
00:45:56,640 --> 00:45:59,600
Speaker 1: last night on the news there was a fire on

849
00:45:59,640 --> 00:46:04,200
Speaker 1: a vert and plane. Yes, ah so that yeah, so

850
00:46:04,360 --> 00:46:07,920
Speaker 1: tell them so lithium batteries that are just spontaneously or

851
00:46:08,120 --> 00:46:13,480
Speaker 1: kind of catching a light and they're talking like that.

852
00:46:13,719 --> 00:46:15,960
Speaker 1: On every plane flight that people go on, there are

853
00:46:15,960 --> 00:46:18,680
Speaker 1: a bunch of people with these batteries that can catch

854
00:46:18,719 --> 00:46:23,479
Speaker 1: a light and they're almost impossible to put out once

855
00:46:23,520 --> 00:46:24,719
Speaker 1: they get a blaze.

856
00:46:24,640 --> 00:46:27,480
Speaker 3: Yeah, they're power banks, so they usually through my own batteries.

857
00:46:27,480 --> 00:46:29,080
Speaker 3: You've probably seen the power I've got a power bank

858
00:46:29,080 --> 00:46:31,839
Speaker 3: that I travel with. Fantastic because it means that if

859
00:46:31,840 --> 00:46:34,320
Speaker 3: you're stuck somewhere in your phone, particularly when you travel,

860
00:46:34,360 --> 00:46:36,239
Speaker 3: you use a lot more GPS and your phone goes

861
00:46:36,280 --> 00:46:39,319
Speaker 3: flat quickly having a power bank with you. I tend

862
00:46:39,400 --> 00:46:41,000
Speaker 3: to have it in my backpack. If I go to

863
00:46:41,040 --> 00:46:43,920
Speaker 3: Melbourne and I'm traveling around, I always take my power

864
00:46:43,920 --> 00:46:46,880
Speaker 3: bank with me. So power banks are just a collection

865
00:46:46,960 --> 00:46:49,120
Speaker 3: of batteries that you can charge your phone off or

866
00:46:49,200 --> 00:46:53,040
Speaker 3: run your devices from, whether it's a laptop or a phone,

867
00:46:53,360 --> 00:46:55,439
Speaker 3: and people carry with them with them all the time.

868
00:46:55,520 --> 00:46:57,880
Speaker 3: And I think that the problem with these sorts of

869
00:46:57,920 --> 00:47:00,799
Speaker 3: stories is and yes, you're right, in fact, the same

870
00:47:00,840 --> 00:47:03,680
Speaker 3: thing happened, but it caused a major fire on a

871
00:47:03,920 --> 00:47:06,400
Speaker 3: Chinese or one of the Asian airlines. It wasn't Chinese

872
00:47:06,520 --> 00:47:08,799
Speaker 3: one of the Asian airlines. And it's subsequently a lot

873
00:47:08,800 --> 00:47:11,840
Speaker 3: of airlines have now banned these power banks, and you

874
00:47:11,880 --> 00:47:14,280
Speaker 3: can see that airlines are going to get really nervous

875
00:47:14,360 --> 00:47:18,480
Speaker 3: about this. And I guess the concern is it's not

876
00:47:18,520 --> 00:47:20,400
Speaker 3: so much the new ones, it's if you've had an

877
00:47:20,400 --> 00:47:23,120
Speaker 3: old one, you might have dropped it. That's where these

878
00:47:23,160 --> 00:47:25,920
Speaker 3: lithium ion batteries, if you ever drop a lithium ion,

879
00:47:26,320 --> 00:47:28,880
Speaker 3: that can be really problematic. So that's the concern, and

880
00:47:28,920 --> 00:47:31,520
Speaker 3: you're right, it's very, very very hard to put them

881
00:47:31,520 --> 00:47:34,799
Speaker 3: out because once they get started. So I don't know

882
00:47:34,800 --> 00:47:37,279
Speaker 3: what that's going to mean for air travel. I think

883
00:47:37,320 --> 00:47:39,200
Speaker 3: it's going to make it a little bit difficult, more

884
00:47:39,200 --> 00:47:42,600
Speaker 3: difficult because airlines are likely to put a ban on

885
00:47:42,760 --> 00:47:45,160
Speaker 3: being able to use them, which will make things a

886
00:47:45,200 --> 00:47:47,239
Speaker 3: little bit harder. But that said, a lot of the

887
00:47:47,280 --> 00:47:50,440
Speaker 3: newer planes have USB ports in your seats, so you

888
00:47:50,480 --> 00:47:54,160
Speaker 3: can charge directly at your seat anyway. So for the

889
00:47:54,200 --> 00:47:55,920
Speaker 3: concerns that people have, if you if you're on a

890
00:47:55,960 --> 00:47:58,880
Speaker 3: long haul trip and you want to watch your laptop

891
00:47:58,960 --> 00:48:00,680
Speaker 3: or you want to use your laptop or an iPad

892
00:48:00,800 --> 00:48:04,600
Speaker 3: or something like that, then you know you can now

893
00:48:04,600 --> 00:48:07,120
Speaker 3: plug into your seat. So I think for most people

894
00:48:07,440 --> 00:48:10,400
Speaker 3: that I think may not be as necessary as it was.

895
00:48:10,719 --> 00:48:12,120
Speaker 3: But I think what's going to happen is you're going

896
00:48:12,160 --> 00:48:13,680
Speaker 3: to get to the airport and have to buy one

897
00:48:13,680 --> 00:48:16,480
Speaker 3: if you're traveling, because if you're footslogging around Europe and

898
00:48:16,520 --> 00:48:17,919
Speaker 3: you're going to be out and about for a long

899
00:48:17,960 --> 00:48:19,720
Speaker 3: time and you don't want your phone to go flat,

900
00:48:19,960 --> 00:48:22,440
Speaker 3: then you're going to need to have a power bank anyway,

901
00:48:22,440 --> 00:48:24,520
Speaker 3: and you might end up having to create a whole

902
00:48:24,600 --> 00:48:27,080
Speaker 3: new market of disposable power banks, because what's going to

903
00:48:27,080 --> 00:48:29,240
Speaker 3: happen to them? Do you hire them at the airport

904
00:48:29,280 --> 00:48:31,319
Speaker 3: and then return them or do you just urf them

905
00:48:31,360 --> 00:48:33,359
Speaker 3: at the end. So it's going to create a whole

906
00:48:33,360 --> 00:48:34,399
Speaker 3: lot of waste, isn't it.

907
00:48:34,920 --> 00:48:37,960
Speaker 1: H'e upsent just quickly, We've got about two minutes. Also,

908
00:48:38,200 --> 00:48:40,120
Speaker 1: is it not the same? I don't know, Patrick, but

909
00:48:41,360 --> 00:48:44,320
Speaker 1: bikes and scooters that have are they the same kinds

910
00:48:44,320 --> 00:48:46,719
Speaker 1: of batteries? Because we're seeing shit just blow up in

911
00:48:46,800 --> 00:48:49,040
Speaker 1: people's houses and catch a light.

912
00:48:49,440 --> 00:48:52,279
Speaker 3: Yeah, sadly, I was talking to a friend of mine

913
00:48:52,400 --> 00:48:54,919
Speaker 3: or a lady that worked with me for a while,

914
00:48:54,960 --> 00:48:57,800
Speaker 3: and her parents' house burnt down. They had an electric

915
00:48:57,880 --> 00:49:00,560
Speaker 3: scooter in the garage. It caught five and it burnt

916
00:49:00,600 --> 00:49:02,960
Speaker 3: down the entire house. And that was just like down

917
00:49:03,000 --> 00:49:04,080
Speaker 3: the road from where I live.

918
00:49:04,400 --> 00:49:05,239
Speaker 1: You have one of those?

919
00:49:05,760 --> 00:49:09,280
Speaker 3: I do, But when I did my whole new studio revamp,

920
00:49:09,320 --> 00:49:12,040
Speaker 3: I misplaced the charger, so I don't know what I've

921
00:49:12,040 --> 00:49:13,319
Speaker 3: done with the charger for it.

922
00:49:13,719 --> 00:49:15,960
Speaker 1: You might have to use your legs and push like

923
00:49:16,000 --> 00:49:18,520
Speaker 1: the old days, you know, back in the sixties, stand

924
00:49:18,560 --> 00:49:20,120
Speaker 1: on it and push with your other leg.

925
00:49:20,360 --> 00:49:22,239
Speaker 3: But it's hard because it's got a battery on it.

926
00:49:22,239 --> 00:49:24,680
Speaker 3: It's heavy, and it has that you know, kind of

927
00:49:24,719 --> 00:49:26,160
Speaker 3: grinding sound because.

928
00:49:25,960 --> 00:49:28,080
Speaker 1: As that resistance. Think of it as a workout.

929
00:49:28,400 --> 00:49:30,399
Speaker 3: Yeah, I just did ten minutes on the rower after

930
00:49:30,440 --> 00:49:33,240
Speaker 3: I did Waits this morning. That's good, isn't it. Yeah,

931
00:49:33,239 --> 00:49:35,040
Speaker 3: that's my cardio. Ten minutes on the row and then

932
00:49:35,040 --> 00:49:35,760
Speaker 3: I'll walk fits.

933
00:49:37,280 --> 00:49:39,759
Speaker 1: Tell people where to find you, follow you, connect with you,

934
00:49:40,080 --> 00:49:43,920
Speaker 1: and just a viewer warning, listener warning. If you do

935
00:49:44,000 --> 00:49:46,520
Speaker 1: send him an email, he's in your life forever. Keep

936
00:49:46,560 --> 00:49:47,120
Speaker 1: that in mind.

937
00:49:47,640 --> 00:49:54,960
Speaker 3: Hey, welcome to the you Project him ah to Shay

938
00:49:55,080 --> 00:49:59,839
Speaker 3: bro too, shy websitesnow, dot com, dot au websites now,

939
00:50:00,080 --> 00:50:02,200
Speaker 3: Calm tod a you. It's only because it's the easiest

940
00:50:02,239 --> 00:50:05,440
Speaker 3: website to remember and you can connect with me.

941
00:50:06,400 --> 00:50:08,360
Speaker 1: Thank you Tiffany, and thank you Patrick.

942
00:50:08,920 --> 00:50:10,760
Speaker 3: Thanks, Thanks lads,