1
00:00:00,560 --> 00:00:04,080
Speaker 1: I'll get a team mcraig, Anthony Harper, Patrick, James Bonillo.

2
00:00:04,120 --> 00:00:06,280
Speaker 1: The name of the show is the You Project. Every

3
00:00:07,280 --> 00:00:09,840
Speaker 1: second week, Young Patrick and I just saddle up. Usually

4
00:00:09,920 --> 00:00:13,880
Speaker 1: young Tiff is Tiffin. Who's Tiffin? Sounds like some kind

5
00:00:13,880 --> 00:00:17,160
Speaker 1: of stage show. Usually Tiff is here, she's not today,

6
00:00:17,280 --> 00:00:20,840
Speaker 1: So it's just us two alpha males just fucking holding

7
00:00:20,880 --> 00:00:23,680
Speaker 1: down the fort. But he reckons more alpha male?

8
00:00:24,000 --> 00:00:29,040
Speaker 2: You or me, ah, neither of us. Fritz, that's true.

9
00:00:29,360 --> 00:00:34,760
Speaker 3: I think it said he's nuts cut off? Can I

10
00:00:34,840 --> 00:00:37,440
Speaker 3: just ask a question? How can I never do the opener?

11
00:00:37,520 --> 00:00:38,960
Speaker 3: I know it's your show, and.

12
00:00:40,520 --> 00:00:41,960
Speaker 4: Let's start again. Let's start again?

13
00:00:42,600 --> 00:00:47,479
Speaker 1: Okay, yep, hey groovers, Welcome to the You Project. I'm

14
00:00:47,560 --> 00:00:49,920
Speaker 1: joined by one of the people I most respect in

15
00:00:49,960 --> 00:00:52,919
Speaker 1: all the world. In fact, I am humbled in his

16
00:00:53,000 --> 00:00:55,160
Speaker 1: presence and in a lot of ways I wish I

17
00:00:55,320 --> 00:00:58,600
Speaker 1: was him. Not only is he smarter, better looking, and

18
00:00:58,680 --> 00:01:02,840
Speaker 1: more talented, he shares the same birthday with the Dali Lama,

19
00:01:03,120 --> 00:01:06,160
Speaker 1: which goes a long way to explaining who he is. So,

20
00:01:06,319 --> 00:01:10,400
Speaker 1: without further ado, welcome back to the You Project. Patrick Bonello,

21
00:01:11,360 --> 00:01:11,960
Speaker 1: Hey haw good?

22
00:01:12,040 --> 00:01:13,400
Speaker 2: Was that fuck?

23
00:01:13,480 --> 00:01:13,520
Speaker 4: And?

24
00:01:13,680 --> 00:01:13,920
Speaker 1: Hell?

25
00:01:14,520 --> 00:01:19,560
Speaker 4: Now I know what you did. I'm quite terrified tell

26
00:01:19,600 --> 00:01:22,479
Speaker 4: people I did not know that was coming. Everybody that

27
00:01:22,640 --> 00:01:26,480
Speaker 4: wasn't me saying that? Wow? When did you do that?

28
00:01:26,680 --> 00:01:29,440
Speaker 4: And how explain to people what that was?

29
00:01:30,160 --> 00:01:34,520
Speaker 3: So I subscribed to a service called eleven Labs. It's

30
00:01:34,520 --> 00:01:39,720
Speaker 3: an AI voice generator. I sampled just one minute of

31
00:01:39,760 --> 00:01:43,280
Speaker 3: your voice from one of your podcasts. I uploaded it

32
00:01:43,360 --> 00:01:46,360
Speaker 3: and then I profiled you. So I put middle aged

33
00:01:46,440 --> 00:01:51,240
Speaker 3: Australian male, just a very brief descriptions, you know, deep voice,

34
00:01:51,280 --> 00:01:54,920
Speaker 3: that sort of stuff, and it generated that so effectively.

35
00:01:56,000 --> 00:01:57,480
Speaker 2: I could you could give me a.

36
00:01:57,440 --> 00:02:00,000
Speaker 3: Sentence now and I could get you to say it

37
00:02:00,120 --> 00:02:00,919
Speaker 3: back in AI.

38
00:02:02,040 --> 00:02:02,800
Speaker 2: Something simple.

39
00:02:03,440 --> 00:02:08,960
Speaker 1: That's all right. I've got a big crush on Patrick,

40
00:02:10,120 --> 00:02:15,600
Speaker 1: right my type. I don't know that this is very

41
00:02:15,600 --> 00:02:18,080
Speaker 1: good live, but anyway, here we go, Here we go. Yep,

42
00:02:18,880 --> 00:02:20,520
Speaker 1: I've got a big crush on Patrick.

43
00:02:21,080 --> 00:02:23,800
Speaker 2: Oh no, not as good? That is it?

44
00:02:23,800 --> 00:02:24,560
Speaker 4: It's not bad?

45
00:02:24,760 --> 00:02:25,920
Speaker 2: Drop it back, let me try again.

46
00:02:26,919 --> 00:02:30,040
Speaker 1: I've got a big crush on Patrick. It's kind of

47
00:02:31,040 --> 00:02:32,679
Speaker 1: it's good until it gets to your name.

48
00:02:33,080 --> 00:02:33,600
Speaker 2: Yeah.

49
00:02:34,040 --> 00:02:36,359
Speaker 3: So what you can do is you can keep uploading

50
00:02:36,440 --> 00:02:40,920
Speaker 3: additional audio and then as it profiles your voice, then

51
00:02:41,360 --> 00:02:43,800
Speaker 3: it'll be able to get it a lot better. Like,

52
00:02:43,840 --> 00:02:46,520
Speaker 3: for example, I don't think you remember saying this earlier,

53
00:02:46,520 --> 00:02:48,000
Speaker 3: but I'm sure you said this earlier.

54
00:02:48,040 --> 00:02:48,320
Speaker 2: Craig.

55
00:02:49,000 --> 00:02:50,919
Speaker 1: It just occurred to me that if all of our

56
00:02:50,960 --> 00:02:55,000
Speaker 1: listeners sent Patrick five dollars each, I will match that

57
00:02:55,120 --> 00:02:56,520
Speaker 1: with whatever we come up with.

58
00:02:59,440 --> 00:03:02,000
Speaker 4: Fuck you, fuck you and your AI skills.

59
00:03:02,560 --> 00:03:05,440
Speaker 3: So I might throw a few of these just randomly

60
00:03:05,480 --> 00:03:07,880
Speaker 3: through the show, just when it you know, if a pause,

61
00:03:07,919 --> 00:03:08,880
Speaker 3: I'll just throw something in.

62
00:03:10,200 --> 00:03:13,639
Speaker 1: That is very funny and a little bit terrifying. I've

63
00:03:13,639 --> 00:03:16,800
Speaker 1: never thought, I think it's I've seen that done to

64
00:03:16,840 --> 00:03:19,160
Speaker 1: other people. I did not expect anyone to be doing

65
00:03:19,200 --> 00:03:22,320
Speaker 1: that to me anytime soon. But thanks for introducing the

66
00:03:22,360 --> 00:03:26,640
Speaker 1: world to that. Thanks for giving people that idea. Wow,

67
00:03:27,840 --> 00:03:31,160
Speaker 1: how long did that take? I mean you're very tech savvy,

68
00:03:31,240 --> 00:03:34,040
Speaker 1: but how long did that take for you to figure that? Like,

69
00:03:34,080 --> 00:03:37,360
Speaker 1: you could literally do a whole podcast of me when

70
00:03:37,360 --> 00:03:39,040
Speaker 1: I'm not even present, Well, you.

71
00:03:39,000 --> 00:03:42,160
Speaker 3: Could do both of us and then just create it

72
00:03:42,200 --> 00:03:43,760
Speaker 3: and put it together. It would take a little bit

73
00:03:43,760 --> 00:03:47,560
Speaker 3: of work, but they are getting so much better. And

74
00:03:47,720 --> 00:03:51,520
Speaker 3: an answer your question, probably having never used the software,

75
00:03:51,600 --> 00:03:54,000
Speaker 3: never done anything with it before, I would say maybe

76
00:03:54,040 --> 00:03:54,920
Speaker 3: three or four minutes.

77
00:03:55,600 --> 00:03:57,240
Speaker 2: Once I found the clip and.

78
00:03:57,240 --> 00:04:01,000
Speaker 3: Uploaded it, it profiled it with a short amount of time.

79
00:04:01,040 --> 00:04:03,040
Speaker 3: I took the phrase, typed it up for the intro

80
00:04:03,240 --> 00:04:05,760
Speaker 3: to the show, and then I played it through about

81
00:04:05,800 --> 00:04:08,400
Speaker 3: four times and you can alter it, and then I've

82
00:04:08,480 --> 00:04:10,080
Speaker 3: chose the one I thought sounded the best.

83
00:04:10,920 --> 00:04:15,200
Speaker 1: Wow, so you could get some famous speech and get

84
00:04:15,200 --> 00:04:18,200
Speaker 1: me to say that famous speech. So could you just

85
00:04:18,440 --> 00:04:24,120
Speaker 1: upload the upload the dialogue and then is that how

86
00:04:24,160 --> 00:04:24,640
Speaker 1: it works?

87
00:04:24,800 --> 00:04:25,040
Speaker 2: Yeah?

88
00:04:25,120 --> 00:04:27,479
Speaker 3: Yeah, I can type anything, so I can either type

89
00:04:27,480 --> 00:04:31,920
Speaker 3: it in or I can just copy and paste, hit

90
00:04:31,960 --> 00:04:34,120
Speaker 3: the generate speech button, and off it goes.

91
00:04:34,520 --> 00:04:38,719
Speaker 1: Now some famous there's some famous Star Wars quote, like

92
00:04:38,800 --> 00:04:43,520
Speaker 1: in a Galaxy Far far whatever. This is probably not

93
00:04:43,680 --> 00:04:46,560
Speaker 1: something we should do in the middle of recording a podcast. Everyone,

94
00:04:46,600 --> 00:04:50,039
Speaker 1: but fuck it. Stand by, Let's see what happens. Is

95
00:04:50,080 --> 00:04:55,159
Speaker 1: there some wrong in this one? The force is strong

96
00:04:55,200 --> 00:04:55,600
Speaker 1: in this one.

97
00:04:57,680 --> 00:05:00,240
Speaker 2: There you go, Well, it kind of sounds funny you're

98
00:05:00,279 --> 00:05:01,279
Speaker 2: saying that because I know you.

99
00:05:01,520 --> 00:05:05,000
Speaker 1: It doesn't give it any inflection, does it? Like, there's

100
00:05:05,040 --> 00:05:05,679
Speaker 1: no emotion.

101
00:05:05,839 --> 00:05:10,240
Speaker 4: It's very it's very flat.

102
00:05:11,000 --> 00:05:12,480
Speaker 1: The force is strong in this one.

103
00:05:13,360 --> 00:05:14,360
Speaker 2: That's a little bit better.

104
00:05:14,680 --> 00:05:17,320
Speaker 4: Yeah, that's what did you do then like what?

105
00:05:17,880 --> 00:05:20,480
Speaker 3: Yep, there's more variable, so you can either make it

106
00:05:20,480 --> 00:05:23,800
Speaker 3: more stable or more variable. So there's there's three controls.

107
00:05:23,800 --> 00:05:31,279
Speaker 3: There's similarity, stability, and then style exaggeration Yeah yeah, wow wow,

108
00:05:32,440 --> 00:05:36,640
Speaker 3: and then you can use other languages as well.

109
00:05:36,920 --> 00:05:38,080
Speaker 1: Force is strong in this one.

110
00:05:38,360 --> 00:05:39,920
Speaker 2: It doesn't sound too bad, does it.

111
00:05:40,440 --> 00:05:44,600
Speaker 4: That's not too bad. It's not too bad. Interesting, you

112
00:05:44,640 --> 00:05:49,400
Speaker 4: are interesting, you are all right?

113
00:05:49,440 --> 00:05:51,440
Speaker 1: Well, I'm sure we'll jump in and out of fake

114
00:05:51,560 --> 00:05:54,240
Speaker 1: me through the show. I can't wait to see how

115
00:05:54,279 --> 00:05:57,320
Speaker 1: you're going to fucking, you know, destroy me as we

116
00:05:57,360 --> 00:05:57,719
Speaker 1: move on.

117
00:05:58,200 --> 00:05:59,880
Speaker 4: What are we talking about in today's episode?

118
00:06:00,040 --> 00:06:06,679
Speaker 1: If Patrick does typ one of my favorite porn films.

119
00:06:06,120 --> 00:06:09,440
Speaker 3: My next big gadget I reckon And I've been looking

120
00:06:09,480 --> 00:06:14,080
Speaker 3: at these quite closely. Ironically, they're glasses, so I guess

121
00:06:14,080 --> 00:06:16,960
Speaker 3: you would be. But smart glasses. Now, there are two

122
00:06:17,000 --> 00:06:19,680
Speaker 3: different types of smart glasses when we think about them.

123
00:06:19,960 --> 00:06:22,279
Speaker 3: One is where we talked and we've talked about the

124
00:06:22,320 --> 00:06:25,440
Speaker 3: augmented reality ones where it's super composes a picture. They're

125
00:06:25,480 --> 00:06:29,840
Speaker 3: not quite there yet, but aahweh has released a new

126
00:06:29,960 --> 00:06:32,560
Speaker 3: version of what they call their eyewear two and what

127
00:06:33,480 --> 00:06:36,640
Speaker 3: I like about it is you can wear the glasses

128
00:06:36,880 --> 00:06:39,480
Speaker 3: and you can use them just every day. They last

129
00:06:39,520 --> 00:06:43,560
Speaker 3: about eleven hours on charge, which is pretty a long time.

130
00:06:44,000 --> 00:06:46,760
Speaker 3: You don't need to have earphones plugged in, so you

131
00:06:46,839 --> 00:06:50,920
Speaker 3: can use them as your virtual assistance, so you could,

132
00:06:51,040 --> 00:06:53,559
Speaker 3: you know, call somebody, use them as a hands free

133
00:06:53,600 --> 00:06:57,600
Speaker 3: device you But what I really like about the Huawei

134
00:06:57,760 --> 00:07:04,000
Speaker 3: Ones is they've come up with a posture kind of assistance.

135
00:07:04,440 --> 00:07:08,760
Speaker 3: And what it does is will actually look at your

136
00:07:08,800 --> 00:07:13,920
Speaker 3: posture or work out whether you're slouching and then remind you.

137
00:07:14,520 --> 00:07:17,040
Speaker 3: So it will monitor so it actually is able to

138
00:07:17,760 --> 00:07:20,040
Speaker 3: check on your posture. And it's got a lot of

139
00:07:20,040 --> 00:07:23,120
Speaker 3: features built into it, so you know you they're lightweight,

140
00:07:23,160 --> 00:07:27,080
Speaker 3: they're comfortable, and you can tap it to play music,

141
00:07:27,320 --> 00:07:28,440
Speaker 3: you can make calls.

142
00:07:28,960 --> 00:07:31,800
Speaker 1: And you missed out a chunk of info like you

143
00:07:31,880 --> 00:07:35,480
Speaker 1: just said glasses, So it's not glasses. Yeah, there's glasses,

144
00:07:35,520 --> 00:07:36,760
Speaker 1: but is it a phone?

145
00:07:36,920 --> 00:07:37,760
Speaker 4: What is it?

146
00:07:37,760 --> 00:07:40,200
Speaker 3: It pairs to your phone, So if you imagine the

147
00:07:40,240 --> 00:07:42,720
Speaker 3: glasses you've got on now, you just touch the arm

148
00:07:42,760 --> 00:07:45,560
Speaker 3: of the glasses to activate it, and you could say,

149
00:07:45,600 --> 00:07:48,200
Speaker 3: be walking and it would be giving you directions turn

150
00:07:48,320 --> 00:07:49,320
Speaker 3: left at the next street.

151
00:07:49,400 --> 00:07:50,200
Speaker 2: That sort of stuff.

152
00:07:50,440 --> 00:07:53,360
Speaker 3: So anything that your phone can do, you can be

153
00:07:53,400 --> 00:07:56,160
Speaker 3: able to connect your glasses to as your smart assistant.

154
00:07:56,200 --> 00:07:58,600
Speaker 3: So take phone calls, make phone calls, all that sort

155
00:07:58,600 --> 00:08:01,120
Speaker 3: of stuff, and just listen to me music. One of

156
00:08:01,120 --> 00:08:04,200
Speaker 3: the things I like about this is you know, quite

157
00:08:04,200 --> 00:08:07,880
Speaker 3: often you see people with earbuds and you wonder how

158
00:08:08,000 --> 00:08:11,200
Speaker 3: dangerous that is because they can't hit traffic and it's

159
00:08:11,240 --> 00:08:13,800
Speaker 3: easy to kind of be lost in your own world.

160
00:08:14,120 --> 00:08:16,280
Speaker 3: The good thing is that this because they're not plugged

161
00:08:16,320 --> 00:08:19,720
Speaker 3: into your ear and they conduct through the top of

162
00:08:19,760 --> 00:08:22,360
Speaker 3: your ear. It means that if the doorbell goes, or

163
00:08:22,360 --> 00:08:24,480
Speaker 3: if you're walking down the street, you can still hear

164
00:08:24,480 --> 00:08:25,200
Speaker 3: things around you.

165
00:08:25,280 --> 00:08:27,239
Speaker 2: So I kind of like that feature as well.

166
00:08:28,560 --> 00:08:32,200
Speaker 1: Isn't Huawei the brand that got booted out of Australia

167
00:08:32,280 --> 00:08:33,720
Speaker 1: and the US their phones?

168
00:08:34,040 --> 00:08:36,120
Speaker 3: Yeah, it was there, Well, not the phones. You can

169
00:08:36,160 --> 00:08:39,240
Speaker 3: still buy Wa Hwei phones but you can't. It was

170
00:08:39,640 --> 00:08:42,720
Speaker 3: more the high end stuff they were using for telecommunications.

171
00:08:43,320 --> 00:08:45,480
Speaker 3: So they had a big contract in Australia to provide

172
00:08:45,520 --> 00:08:49,920
Speaker 3: telecommunication technology and both Australia and in China. The big

173
00:08:49,960 --> 00:08:52,400
Speaker 3: concern is not so much well, I mean, there was

174
00:08:52,480 --> 00:08:56,400
Speaker 3: some controversy around Huawei, but it was more that you

175
00:08:56,480 --> 00:09:01,679
Speaker 3: can't guarantee in China that a large company isn't getting

176
00:09:02,080 --> 00:09:04,880
Speaker 3: nudged and looked at by Beijing. That's the problem with

177
00:09:04,880 --> 00:09:08,719
Speaker 3: the communist government is and that's the big concern. Soanies

178
00:09:08,800 --> 00:09:12,920
Speaker 3: like Dji, the drone manufacturer, they've pulled out all drones

179
00:09:13,160 --> 00:09:16,920
Speaker 3: from the US high end drone markets, so where they're

180
00:09:17,000 --> 00:09:20,080
Speaker 3: using them in say law enforcement or fires and things

181
00:09:20,120 --> 00:09:22,680
Speaker 3: like that, and they're doing the same in Australia as well,

182
00:09:22,760 --> 00:09:25,920
Speaker 3: So they're saying they don't want the potential for China

183
00:09:26,000 --> 00:09:28,200
Speaker 3: to be monitoring what these drones are doing.

184
00:09:28,240 --> 00:09:29,560
Speaker 2: Effectively, it's surveillance.

185
00:09:30,120 --> 00:09:33,840
Speaker 3: There's no suggestion And Dji I kind of feel for

186
00:09:34,200 --> 00:09:36,439
Speaker 3: those companies because if they're doing the right thing and

187
00:09:36,480 --> 00:09:39,520
Speaker 3: they're saying, well, we're not actively monitoring you, but there's

188
00:09:39,559 --> 00:09:40,160
Speaker 3: no way to.

189
00:09:40,120 --> 00:09:40,840
Speaker 2: Really believe it.

190
00:09:40,920 --> 00:09:44,200
Speaker 3: And the suggestion is that, well, if Beijing walks up

191
00:09:44,240 --> 00:09:47,120
Speaker 3: to the front door, and I mean that in general terms,

192
00:09:47,120 --> 00:09:50,480
Speaker 3: someone representing the government knocks on the door and sees,

193
00:09:50,640 --> 00:09:53,960
Speaker 3: we want all your records, well, you know, do they

194
00:09:54,080 --> 00:09:56,160
Speaker 3: have any ability to be able to say no?

195
00:09:56,400 --> 00:09:59,599
Speaker 2: And that's the question, right, Yeah.

196
00:09:59,559 --> 00:10:03,040
Speaker 1: I just googled it because I didn't believe you, but

197
00:10:03,160 --> 00:10:08,520
Speaker 1: you are right. Australia has been Huawei Technology Co. From

198
00:10:08,760 --> 00:10:12,839
Speaker 1: supplying equipment for Australian five G mobile. Why would I

199
00:10:12,920 --> 00:10:15,920
Speaker 1: ever fucking doubt you. That's why have you Australian five

200
00:10:16,000 --> 00:10:19,320
Speaker 1: G mobile network, citing national security risks.

201
00:10:19,320 --> 00:10:21,760
Speaker 4: But they have not banned the phones.

202
00:10:21,520 --> 00:10:24,360
Speaker 2: Correct, yep, okay, okay, yeah.

203
00:10:24,120 --> 00:10:30,640
Speaker 4: Wow, Well there you go. But apparently their phones are great.

204
00:10:31,320 --> 00:10:34,199
Speaker 4: They're high end phones are meant to be great.

205
00:10:34,480 --> 00:10:35,040
Speaker 2: They're really good.

206
00:10:35,120 --> 00:10:35,280
Speaker 1: Yeah.

207
00:10:35,280 --> 00:10:37,520
Speaker 3: I've got a friend that was just we were comparing photos.

208
00:10:37,760 --> 00:10:39,160
Speaker 3: I was going to chat about this on the show

209
00:10:39,200 --> 00:10:41,679
Speaker 3: at some point. I've got some gorgeous photos and I

210
00:10:41,679 --> 00:10:44,600
Speaker 3: think I sent you a couple of the aurora, the.

211
00:10:46,160 --> 00:10:48,160
Speaker 2: Southern Aurora that we had last weekend.

212
00:10:48,400 --> 00:10:49,880
Speaker 3: I was just lucky to be at the right place

213
00:10:49,920 --> 00:10:52,600
Speaker 3: at the right time and got some gorgeous photographs and

214
00:10:53,080 --> 00:10:56,160
Speaker 3: just that beautiful red and green glow.

215
00:10:56,520 --> 00:10:58,440
Speaker 2: Fritzie and I went out there. He jumped in the

216
00:10:58,480 --> 00:10:58,960
Speaker 2: car with me.

217
00:10:59,080 --> 00:11:01,640
Speaker 3: We drove out about I don't know five minutes away,

218
00:11:01,679 --> 00:11:04,920
Speaker 3: were in total darkness, and it was gorgeous.

219
00:11:04,960 --> 00:11:06,760
Speaker 2: It was great. Got some really nice photos.

220
00:11:06,840 --> 00:11:09,160
Speaker 3: But for a lot of people who may have been

221
00:11:09,240 --> 00:11:13,839
Speaker 3: out there and wondered why they weren't seeing in real

222
00:11:13,920 --> 00:11:18,160
Speaker 3: life what our phones were actually showing when we took photos.

223
00:11:18,720 --> 00:11:21,280
Speaker 3: So the photos I sen chew and for all of

224
00:11:21,320 --> 00:11:23,360
Speaker 3: us have been on social media and had a look

225
00:11:23,400 --> 00:11:24,360
Speaker 3: on all those photos.

226
00:11:25,080 --> 00:11:26,480
Speaker 2: You may say, well.

227
00:11:26,360 --> 00:11:28,679
Speaker 3: They didn't look anything like that, But when I took

228
00:11:28,720 --> 00:11:31,720
Speaker 3: the photo, it looked amazing. And that was the case

229
00:11:31,760 --> 00:11:34,079
Speaker 3: for me as well, and it was interesting. I did

230
00:11:34,080 --> 00:11:36,120
Speaker 3: a bit of research and there are a number of

231
00:11:36,200 --> 00:11:38,959
Speaker 3: reasons why, and one of them, of course, is that

232
00:11:39,240 --> 00:11:42,160
Speaker 3: they take an extended exposure. In my case, my phone

233
00:11:42,360 --> 00:11:46,960
Speaker 3: took a six second exposure to get the image. But

234
00:11:47,000 --> 00:11:50,680
Speaker 3: the other thing is that the cones inside our eye,

235
00:11:50,720 --> 00:11:54,320
Speaker 3: the light receptors in our eye, when it gets really dark,

236
00:11:54,640 --> 00:11:58,360
Speaker 3: they effectively switch over from one sensor to another sensor,

237
00:11:58,679 --> 00:12:01,079
Speaker 3: and one of them is about to get as much

238
00:12:01,480 --> 00:12:04,640
Speaker 3: information and to pull in as much light, so it

239
00:12:04,720 --> 00:12:07,200
Speaker 3: kind of drops the use of color and goes to

240
00:12:07,280 --> 00:12:10,800
Speaker 3: almost black and white. So if you're stumbling around at

241
00:12:10,920 --> 00:12:13,600
Speaker 3: night and you've only got a faint glow in your room,

242
00:12:14,000 --> 00:12:17,360
Speaker 3: more than likely you will you will see in much

243
00:12:17,400 --> 00:12:21,440
Speaker 3: more muted tones. So if you're standing out looking out

244
00:12:21,480 --> 00:12:25,040
Speaker 3: at what we saw as the aurora. Effectively, what you're

245
00:12:25,080 --> 00:12:28,680
Speaker 3: looking at is something that's much more muted because you're

246
00:12:28,679 --> 00:12:31,040
Speaker 3: just not getting enough light to the receptors in the

247
00:12:31,040 --> 00:12:33,079
Speaker 3: back of your eye as well. So that's the reason

248
00:12:33,120 --> 00:12:37,520
Speaker 3: why most people's phones showed some really awesome pictures, but

249
00:12:38,240 --> 00:12:41,439
Speaker 3: you weren't seeing the aurora look anywhere near in the

250
00:12:41,559 --> 00:12:43,440
Speaker 3: quality that your phone was taking pictures of.

251
00:12:44,000 --> 00:12:46,320
Speaker 4: I'm looking at that picture that you sent me right now.

252
00:12:47,320 --> 00:12:49,679
Speaker 1: I'm wondering if I might I don't know if I'll

253
00:12:49,720 --> 00:12:51,520
Speaker 1: be able to use that in the promo for the show,

254
00:12:51,559 --> 00:12:55,680
Speaker 1: But it does look it looks it literally looks like

255
00:12:55,880 --> 00:13:00,280
Speaker 1: something made up. It looks like something sci fi because

256
00:13:00,280 --> 00:13:04,640
Speaker 1: there's there's just this blend that starts at the top

257
00:13:04,720 --> 00:13:09,520
Speaker 1: being almost black through to this burgundy indigo color, goes

258
00:13:09,559 --> 00:13:14,240
Speaker 1: into this light green dark green, and then but down

259
00:13:14,320 --> 00:13:17,600
Speaker 1: through the middle of that, it's almost like there's shards

260
00:13:17,640 --> 00:13:20,600
Speaker 1: of light and it looks it looks like a computer

261
00:13:20,720 --> 00:13:23,800
Speaker 1: generated thing. Doesn't look like a photo at all. I mean,

262
00:13:24,040 --> 00:13:26,600
Speaker 1: I'm feeling dumb at the moment. Can you explain that

263
00:13:26,679 --> 00:13:31,360
Speaker 1: to me? Like I was a three year old? I'm sorry,

264
00:13:31,520 --> 00:13:34,800
Speaker 1: could you stop playing fake me. People are not going

265
00:13:34,880 --> 00:13:37,120
Speaker 1: to go what's real? No, what's real and fake me?

266
00:13:37,960 --> 00:13:41,040
Speaker 2: Yeah, that's although what you've said it seems kind of

267
00:13:41,080 --> 00:13:42,120
Speaker 2: on par don't you reckon?

268
00:13:42,920 --> 00:13:44,560
Speaker 4: Well, I know what it is.

269
00:13:45,000 --> 00:13:49,240
Speaker 1: Yeah, I am dumb though, but thanks thanks for making me.

270
00:13:49,360 --> 00:13:51,400
Speaker 1: Of course you were right. I'm always wrong and you

271
00:13:51,440 --> 00:13:53,400
Speaker 1: are one hundred percent right all the time.

272
00:13:54,480 --> 00:13:57,480
Speaker 4: Huh oh god. How many of those do you have?

273
00:13:57,920 --> 00:13:58,040
Speaker 1: Ah?

274
00:13:58,080 --> 00:13:58,920
Speaker 2: There a couple more?

275
00:14:01,080 --> 00:14:02,319
Speaker 4: All right? Now?

276
00:14:02,720 --> 00:14:05,920
Speaker 1: Before we go on with your little kind of little

277
00:14:06,040 --> 00:14:08,400
Speaker 1: that isn't it? Don't you hate it when people say

278
00:14:08,440 --> 00:14:12,120
Speaker 1: your little thing? Last week you and I.

279
00:14:12,040 --> 00:14:15,840
Speaker 3: Had No one's ever said that, Tommy greg Yeah, you're

280
00:14:16,160 --> 00:14:19,560
Speaker 3: right right, John Holmes.

281
00:14:20,360 --> 00:14:24,360
Speaker 1: Everyone's going to be googling that now. A couple of

282
00:14:24,360 --> 00:14:26,720
Speaker 1: weeks ago, last time we were together, we had a bet.

283
00:14:26,760 --> 00:14:28,680
Speaker 1: I can't even remember what the bet was about, but

284
00:14:29,400 --> 00:14:31,800
Speaker 1: that was something to do with something that Tiff would know.

285
00:14:32,280 --> 00:14:34,640
Speaker 3: Yes, it was a picture of Richard Nixon. I sent

286
00:14:34,680 --> 00:14:37,400
Speaker 3: you a picture of Richard Nixon. You forwarded that picture

287
00:14:37,480 --> 00:14:40,480
Speaker 3: to Tiff and I said, of course Tiff will know

288
00:14:40,520 --> 00:14:42,600
Speaker 3: who that is, and you said, not a chance. It

289
00:14:42,680 --> 00:14:45,280
Speaker 3: started to ten dollar bet, and then you doubled it.

290
00:14:45,320 --> 00:14:48,960
Speaker 3: To twenty dollars and I burned and crashed and burned.

291
00:14:49,680 --> 00:14:51,760
Speaker 1: Yeah, you did crash and burn. And then this week

292
00:14:51,920 --> 00:14:57,080
Speaker 1: I went outside and just under my gate was an

293
00:14:57,120 --> 00:15:00,760
Speaker 1: Australia Post parcel and it was like weird. It was

294
00:15:01,040 --> 00:15:05,600
Speaker 1: shaped like a thick, fat, long sausage roll and I

295
00:15:05,680 --> 00:15:08,840
Speaker 1: picked it up and it felt like a very thick

296
00:15:08,960 --> 00:15:11,520
Speaker 1: fat sausage roll and it was kind.

297
00:15:11,320 --> 00:15:13,200
Speaker 2: Of felt like a John Holmes.

298
00:15:14,080 --> 00:15:14,760
Speaker 1: Yeah, it was.

299
00:15:14,840 --> 00:15:19,280
Speaker 4: Limp and heavy, speaking of John Holmes.

300
00:15:19,640 --> 00:15:25,280
Speaker 1: And I opened it and it said from Bland, from

301
00:15:25,280 --> 00:15:30,480
Speaker 1: the Tooth Fairy. And I'd forgotten all about our bet.

302
00:15:30,600 --> 00:15:35,360
Speaker 1: In fact, I didn't know until today when Melissa enlightened

303
00:15:35,440 --> 00:15:38,800
Speaker 1: me because she'd listened to the show. And I said,

304
00:15:38,880 --> 00:15:43,360
Speaker 1: Patrick sent me like a fucking million five cent pieces.

305
00:15:42,760 --> 00:15:46,040
Speaker 4: And I got, I got this this. Well, let's see,

306
00:15:46,080 --> 00:15:48,840
Speaker 4: you sent me apparently twenty dollars worth, and there's twenty

307
00:15:48,880 --> 00:15:51,200
Speaker 4: and that so twenty times twenty so four hundred and

308
00:15:51,200 --> 00:15:52,120
Speaker 4: five cent pieces.

309
00:15:52,200 --> 00:15:54,120
Speaker 2: I guess was it actually healers?

310
00:15:54,640 --> 00:15:55,920
Speaker 4: Was it actually twenty bucks?

311
00:15:56,160 --> 00:15:58,480
Speaker 2: Because it was twenty bucks and it cost me.

312
00:15:58,520 --> 00:16:01,200
Speaker 3: What you'll really enjoy is it cost me eleven bucks

313
00:16:01,200 --> 00:16:01,920
Speaker 3: to send it to you.

314
00:16:02,120 --> 00:16:04,520
Speaker 1: That's what I said to her, it must have cost

315
00:16:04,600 --> 00:16:06,520
Speaker 1: nearly that much to send it because.

316
00:16:06,240 --> 00:16:07,080
Speaker 4: It weighed a lot.

317
00:16:07,480 --> 00:16:08,480
Speaker 2: It did one point.

318
00:16:09,480 --> 00:16:13,000
Speaker 1: And also it's been brought to my attention by you

319
00:16:14,040 --> 00:16:16,320
Speaker 1: that you're actually breaking the law and doing that.

320
00:16:16,960 --> 00:16:19,400
Speaker 3: So I went to the bank, called the bank first,

321
00:16:19,400 --> 00:16:22,200
Speaker 3: our local little community branch, and said if you got

322
00:16:22,280 --> 00:16:25,520
Speaker 3: twenty bucks in five cent pieces, and they kind of

323
00:16:25,600 --> 00:16:27,400
Speaker 3: umed an out for a little bit and said, yeah, sure,

324
00:16:27,440 --> 00:16:29,280
Speaker 3: come in and grab them. So I went in there

325
00:16:29,320 --> 00:16:31,160
Speaker 3: and they gave them to me in all these cute

326
00:16:31,200 --> 00:16:33,200
Speaker 3: little neat bags, and I've got my post pack and

327
00:16:33,240 --> 00:16:34,200
Speaker 3: I'm just opening up.

328
00:16:34,160 --> 00:16:36,280
Speaker 2: The bags, tipping them in, open up the bag, tipping in.

329
00:16:36,640 --> 00:16:38,400
Speaker 3: And then I went to the post office and the

330
00:16:38,440 --> 00:16:41,360
Speaker 3: girls at the post office were pissing themselves laughing when

331
00:16:41,360 --> 00:16:44,640
Speaker 3: I told them what it was for. And then after

332
00:16:44,680 --> 00:16:46,560
Speaker 3: i'd sent it to you, of course, I started telling

333
00:16:46,600 --> 00:16:48,680
Speaker 3: lots of people what i'd done, because you know, I'm

334
00:16:48,680 --> 00:16:49,720
Speaker 3: trying to get a bit of a pat on the

335
00:16:49,760 --> 00:16:53,320
Speaker 3: back for myself. And someone said to me, you know

336
00:16:53,400 --> 00:16:57,240
Speaker 3: that's illegal. I said, what because the post office accepted it,

337
00:16:57,280 --> 00:16:58,080
Speaker 3: and so I did.

338
00:16:57,920 --> 00:16:59,840
Speaker 2: A good search and yeah, it's illegal.

339
00:16:59,480 --> 00:17:03,640
Speaker 3: To send any sort of cash via mail delivery service.

340
00:17:04,119 --> 00:17:06,439
Speaker 4: Who would have thought, I wonder why no idea?

341
00:17:06,600 --> 00:17:09,359
Speaker 1: I guess because they don't want that to be a

342
00:17:09,359 --> 00:17:12,439
Speaker 1: common practice because if if the bad guys think that

343
00:17:12,480 --> 00:17:15,240
Speaker 1: there's money floating around in the mail, then there are Yeah,

344
00:17:15,320 --> 00:17:17,360
Speaker 1: it kind of makes sense, but I don't see why

345
00:17:17,520 --> 00:17:20,680
Speaker 1: you should get penalized if you're if you're the one

346
00:17:20,720 --> 00:17:22,800
Speaker 1: pinching money, but if you're the one putting money, and

347
00:17:22,840 --> 00:17:26,240
Speaker 1: I don't think you should I get penalized.

348
00:17:26,280 --> 00:17:28,480
Speaker 4: Where we going next? Obi? Wan? Can I be?

349
00:17:29,080 --> 00:17:29,439
Speaker 2: Well?

350
00:17:29,600 --> 00:17:34,240
Speaker 3: Look, I guess I was really interested in a couple

351
00:17:34,240 --> 00:17:39,520
Speaker 3: of health related stories talking about AI because Google has

352
00:17:39,560 --> 00:17:43,879
Speaker 3: got its AI interface called Gemini, and what they're saying

353
00:17:43,920 --> 00:17:46,200
Speaker 3: is it's going to really help blind people, so people

354
00:17:46,200 --> 00:17:47,280
Speaker 3: who are vision impaired.

355
00:17:47,640 --> 00:17:49,879
Speaker 2: And there's two little things that I thought was really cool.

356
00:17:50,000 --> 00:17:54,160
Speaker 3: It's called talkback and it's using generative AI, and what

357
00:17:54,160 --> 00:18:00,639
Speaker 3: it means is that it will be able to run offline. Okay,

358
00:18:00,720 --> 00:18:02,760
Speaker 3: So one of the biggest issues with AI at the

359
00:18:02,800 --> 00:18:06,440
Speaker 3: moment is that it's a giant service somewhere, and there's

360
00:18:06,480 --> 00:18:09,520
Speaker 3: a lot of controversy over how much you know that

361
00:18:09,720 --> 00:18:14,479
Speaker 3: data generating costs in terms of power and is there

362
00:18:14,520 --> 00:18:18,200
Speaker 3: a real impact. But this language model is actually designed

363
00:18:18,240 --> 00:18:22,480
Speaker 3: for people with low vision, and it creates descriptions of

364
00:18:22,560 --> 00:18:26,199
Speaker 3: objects for blind users, but it runs totally off the

365
00:18:26,200 --> 00:18:29,600
Speaker 3: cloud and on the device itself, so they would be

366
00:18:29,640 --> 00:18:34,240
Speaker 3: able to refer back to articles of clothing. They can say, well,

367
00:18:34,280 --> 00:18:37,880
Speaker 3: this is a close up of a T shirt and

368
00:18:37,960 --> 00:18:38,440
Speaker 3: so it.

369
00:18:38,400 --> 00:18:42,680
Speaker 1: Will but people are blind, what do you mean they

370
00:18:42,680 --> 00:18:44,080
Speaker 1: can say this is a close up.

371
00:18:44,400 --> 00:18:47,000
Speaker 4: Well, because you would use so it's describing.

372
00:18:47,160 --> 00:18:52,240
Speaker 3: Yeah, so it describes, it describes it's seen, so right, yeah, yeah,

373
00:18:52,520 --> 00:18:57,239
Speaker 3: And it can get really really quite specific. It's not

374
00:18:57,359 --> 00:19:00,399
Speaker 3: just this is address, but this is a floral dress

375
00:19:00,440 --> 00:19:03,119
Speaker 3: and it's green and red and it has fringes and

376
00:19:03,160 --> 00:19:05,960
Speaker 3: that sort of stuff. And they're doing the training of

377
00:19:06,000 --> 00:19:08,440
Speaker 3: the AI with quite a fair.

378
00:19:08,200 --> 00:19:08,879
Speaker 2: Bit of my neuche.

379
00:19:08,960 --> 00:19:11,480
Speaker 3: So if you're going shopping and your vision impaired, this

380
00:19:11,560 --> 00:19:14,919
Speaker 3: could be really really useful, even just matching clothing colors

381
00:19:14,960 --> 00:19:17,280
Speaker 3: and that sort of thing. And I guess the other

382
00:19:17,280 --> 00:19:20,080
Speaker 3: thing I love about it is it makes people a

383
00:19:20,160 --> 00:19:23,399
Speaker 3: lot more independent, so there are less inhibitions because it

384
00:19:23,440 --> 00:19:26,199
Speaker 3: is harder for people to shop, and we take it

385
00:19:26,240 --> 00:19:29,280
Speaker 3: for granted. I mean, you work so hard to look

386
00:19:29,320 --> 00:19:36,080
Speaker 3: so uncoordinated, says he who's wearing a rainbow colored and

387
00:19:36,119 --> 00:19:36,640
Speaker 3: a black tea.

388
00:19:36,640 --> 00:19:42,000
Speaker 1: Sir, hey, fuck you, Brad Pitt, just fuck now, talk

389
00:19:42,040 --> 00:19:46,320
Speaker 1: about the clock calling the kettle black. Mister Cardigan wearing

390
00:19:46,560 --> 00:19:47,879
Speaker 1: fucking beret wearer.

391
00:19:48,080 --> 00:19:50,960
Speaker 2: I'm not wearing a beret or a cardigan today.

392
00:19:51,040 --> 00:19:53,840
Speaker 1: Yeah, that's just today. You're wearing an ABC logo on

393
00:19:53,920 --> 00:19:54,760
Speaker 1: a T shirt.

394
00:19:54,960 --> 00:19:57,639
Speaker 3: That's because I started doing Actually no, it's a Pride

395
00:19:57,720 --> 00:20:00,679
Speaker 3: logo because today's idahol a day. But also today I

396
00:20:00,720 --> 00:20:04,760
Speaker 3: started doing a regular segment on ABC Regional Radio.

397
00:20:05,800 --> 00:20:09,560
Speaker 1: Can I tell you that I have a fan I

398
00:20:09,600 --> 00:20:12,600
Speaker 1: won't say his name, but I have a fan on

399
00:20:12,640 --> 00:20:15,640
Speaker 1: my IG who's very very keen to.

400
00:20:15,600 --> 00:20:18,520
Speaker 4: Catch up with me, sending me nice messages.

401
00:20:19,320 --> 00:20:20,000
Speaker 2: That's nice.

402
00:20:20,400 --> 00:20:24,719
Speaker 1: He's a bit of a sweetheart too, he's nice.

403
00:20:25,359 --> 00:20:26,400
Speaker 4: I'm pretty sure I know.

404
00:20:27,080 --> 00:20:30,639
Speaker 3: No friendship. I'm thinking friendship that you doesn't have to go.

405
00:20:30,680 --> 00:20:32,280
Speaker 3: I mean, he knows it doesn't.

406
00:20:33,000 --> 00:20:35,480
Speaker 4: Is requesting a bit more than friendship, But that's all right.

407
00:20:36,280 --> 00:20:37,400
Speaker 2: Personally, training.

408
00:20:39,000 --> 00:20:43,320
Speaker 4: There's something like that. That's yeah, yeah, that's I might

409
00:20:43,680 --> 00:20:47,680
Speaker 4: pour it into you. Thanks for that, friends though, and

410
00:20:47,800 --> 00:20:48,000
Speaker 4: go on.

411
00:20:48,560 --> 00:20:51,199
Speaker 3: No, So I was just saying how exciting this is

412
00:20:51,400 --> 00:20:54,439
Speaker 3: and using things like AI offline to be able to

413
00:20:54,440 --> 00:20:57,120
Speaker 3: assist people who are vision impaired. And the other thing

414
00:20:57,160 --> 00:21:00,080
Speaker 3: that relates to this, there's a Seattle startup at the

415
00:21:00,119 --> 00:21:05,280
Speaker 3: moment and they've got this really really really cool gadget

416
00:21:05,320 --> 00:21:08,920
Speaker 3: called one court. So if you imagine you're sitting down

417
00:21:09,160 --> 00:21:12,720
Speaker 3: at a sporting game, or you're watching a sporting game tennis,

418
00:21:13,320 --> 00:21:15,440
Speaker 3: you know, grid iron or whatever it happens to be,

419
00:21:15,880 --> 00:21:19,960
Speaker 3: and you lay your hands on the screen if your

420
00:21:20,040 --> 00:21:23,879
Speaker 3: vision impaired, and it gives you haptic feedback of what's

421
00:21:23,880 --> 00:21:26,560
Speaker 3: actually happening on the court. So if you're playing tennis,

422
00:21:26,640 --> 00:21:29,600
Speaker 3: I could you could feel it and the vibrations match

423
00:21:30,080 --> 00:21:31,960
Speaker 3: what's being played out on the court.

424
00:21:32,240 --> 00:21:36,320
Speaker 4: Oh wow wow, yeah, yeah, you're watching good. What if

425
00:21:36,320 --> 00:21:38,359
Speaker 4: you're watching a porno? Does it do the same?

426
00:21:38,560 --> 00:21:40,280
Speaker 2: You had to go there, didn't you? No?

427
00:21:40,400 --> 00:21:43,400
Speaker 4: I didn't. I choose to. You know, by the way,

428
00:21:43,440 --> 00:21:46,439
Speaker 4: everyone Patrick, that was he? That was fake me? That

429
00:21:46,520 --> 00:21:46,960
Speaker 4: wasn't real?

430
00:21:47,000 --> 00:21:52,360
Speaker 2: MAE say that, Yeah that was Patrick.

431
00:21:52,960 --> 00:21:55,560
Speaker 4: So now I can get you in trouble just quickly

432
00:21:55,600 --> 00:21:56,359
Speaker 4: before we move on.

433
00:21:56,840 --> 00:21:59,480
Speaker 1: You know what I like about those the glasses that

434
00:21:59,600 --> 00:22:04,440
Speaker 1: essentially describe what's happening in front of people. Think about

435
00:22:04,480 --> 00:22:08,080
Speaker 1: the potential applications for safety, you know, crossing the road,

436
00:22:08,359 --> 00:22:12,280
Speaker 1: holes in the footpath, you know, obstacles like that's a

437
00:22:12,320 --> 00:22:13,920
Speaker 1: pretty cool application as well.

438
00:22:14,400 --> 00:22:17,320
Speaker 3: Yeah, that's a nice little seguay because there's a really

439
00:22:17,400 --> 00:22:21,160
Speaker 3: great story about a guy in the United States who.

440
00:22:21,080 --> 00:22:23,159
Speaker 1: Would just point out to put everyone how much you

441
00:22:23,320 --> 00:22:24,280
Speaker 1: just fobbed me off?

442
00:22:24,320 --> 00:22:27,320
Speaker 4: Then did I You went?

443
00:22:27,600 --> 00:22:32,600
Speaker 3: You wentblished that, she went, Yeah, it was my topic.

444
00:22:32,680 --> 00:22:34,280
Speaker 2: I was telling you how exciting it is.

445
00:22:34,600 --> 00:22:40,520
Speaker 1: You were talking about choosing fucking clothes. No, like, oh,

446
00:22:40,640 --> 00:22:43,159
Speaker 1: here's a close up of a T shirt? What about

447
00:22:43,160 --> 00:22:46,680
Speaker 1: saving someone's life? Your dickhead.

448
00:22:46,320 --> 00:22:49,760
Speaker 2: But you gave me the perfect segue to the next segment.

449
00:22:49,840 --> 00:22:51,320
Speaker 2: It's a really keep.

450
00:22:51,119 --> 00:22:53,440
Speaker 4: Going, say keep going segway. Boy.

451
00:22:53,800 --> 00:22:56,679
Speaker 3: So this, this guy in the United States got a

452
00:22:56,680 --> 00:22:59,679
Speaker 3: black T shirt with just a stop sign on the

453
00:22:59,720 --> 00:23:01,960
Speaker 3: front of it and then just stood by the side

454
00:23:02,000 --> 00:23:05,240
Speaker 3: of the road and autonomous cars was stopping because they

455
00:23:05,240 --> 00:23:06,440
Speaker 3: thought he was a stop sign.

456
00:23:07,160 --> 00:23:08,600
Speaker 4: That's great, isn't it.

457
00:23:08,760 --> 00:23:10,200
Speaker 2: I near'd like it.

458
00:23:10,440 --> 00:23:13,440
Speaker 4: That's but also, I mean, I wonder if he could

459
00:23:13,480 --> 00:23:15,520
Speaker 4: get charged with anything.

460
00:23:16,000 --> 00:23:19,280
Speaker 3: Right years, I don't know, so this guy's his name's

461
00:23:19,359 --> 00:23:21,040
Speaker 3: Jason Carr is from Arizona.

462
00:23:21,600 --> 00:23:24,080
Speaker 2: And look, I think he was doing it to prove

463
00:23:24,119 --> 00:23:24,600
Speaker 2: a point.

464
00:23:24,680 --> 00:23:29,120
Speaker 3: So Waimo is the company that has robotaxis and they're

465
00:23:29,200 --> 00:23:32,639
Speaker 3: running tests at the moment. So initially he just stood

466
00:23:32,680 --> 00:23:35,360
Speaker 3: at the edge of the road, and yeah, the car

467
00:23:35,400 --> 00:23:38,800
Speaker 3: came to a complete stop, and then it eventually resumed

468
00:23:38,880 --> 00:23:40,600
Speaker 3: driving once he walked away.

469
00:23:40,440 --> 00:23:44,280
Speaker 2: Or hid the T shirt. But look, he said that

470
00:23:44,840 --> 00:23:46,160
Speaker 2: it was something that he was doing.

471
00:23:46,200 --> 00:23:48,040
Speaker 3: It was a bit of a publicity stunt, I guess,

472
00:23:48,119 --> 00:23:50,440
Speaker 3: or you know, to kind of to be able to

473
00:23:50,480 --> 00:23:54,440
Speaker 3: emphasize a point that these self driving vehicles still have

474
00:23:54,520 --> 00:23:57,399
Speaker 3: a long way to go to differentiate between a sign

475
00:23:57,440 --> 00:23:59,919
Speaker 3: on a stick by the side road and an intersect

476
00:24:00,520 --> 00:24:02,920
Speaker 3: and just someone standing in a T shirt. But yeah,

477
00:24:03,080 --> 00:24:05,199
Speaker 3: I mean my first reaction was to have a bit

478
00:24:05,200 --> 00:24:08,679
Speaker 3: of a chuckle as well. But it does show, you know,

479
00:24:08,720 --> 00:24:12,639
Speaker 3: the risks of how an autonomous system like that and

480
00:24:12,680 --> 00:24:16,320
Speaker 3: a vehicle is a major heavy vehicle, you know, particularly

481
00:24:16,800 --> 00:24:20,240
Speaker 3: if it's an electric powered vehicle. They're even heavier, aren't they.

482
00:24:20,560 --> 00:24:22,520
Speaker 3: You can you can fool them, and there was all

483
00:24:22,520 --> 00:24:25,720
Speaker 3: the controversy a few years ago, well not that long ago, actually,

484
00:24:25,840 --> 00:24:29,240
Speaker 3: over whether or not the totally autonomous driving of the

485
00:24:29,240 --> 00:24:32,520
Speaker 3: Tesla's was able to pick up a child and differentiate

486
00:24:32,600 --> 00:24:35,360
Speaker 3: between a child walking across the road, and so there

487
00:24:35,400 --> 00:24:37,679
Speaker 3: was again a little bit of controversy around that. At

488
00:24:37,680 --> 00:24:39,320
Speaker 3: the end of the day, we want to make sure

489
00:24:39,320 --> 00:24:42,880
Speaker 3: we've got driver safety. But the current driver safety that's

490
00:24:42,880 --> 00:24:45,520
Speaker 3: built into a lot of vehicles is phenomenal. I know

491
00:24:45,560 --> 00:24:47,240
Speaker 3: I'm always crying about this, but it is good.

492
00:24:47,320 --> 00:24:48,040
Speaker 2: It's getting better.

493
00:24:48,280 --> 00:24:50,399
Speaker 3: It means that people are less likely to fall asleep

494
00:24:50,440 --> 00:24:52,399
Speaker 3: at the will because their car will notify them if

495
00:24:52,400 --> 00:24:54,960
Speaker 3: they not off or if they drift out of their lane,

496
00:24:55,000 --> 00:24:56,000
Speaker 3: and that's got to be good.

497
00:24:56,840 --> 00:24:57,639
Speaker 4: Yeah.

498
00:24:57,680 --> 00:25:02,680
Speaker 1: One of the challenges I think though, is that some

499
00:25:02,720 --> 00:25:04,400
Speaker 1: of the cars are so high tech.

500
00:25:04,480 --> 00:25:06,120
Speaker 4: Now. I love cars, I love motorbikes.

501
00:25:06,240 --> 00:25:08,920
Speaker 1: I watch reviews all the time, as you know, which

502
00:25:08,920 --> 00:25:12,240
Speaker 1: is ironic because I drive a fucking old Suzuki Swift.

503
00:25:12,320 --> 00:25:14,960
Speaker 1: But you know, like I haven't had a nice car

504
00:25:15,080 --> 00:25:18,200
Speaker 1: for years because I kind of went through a phase.

505
00:25:18,240 --> 00:25:20,840
Speaker 1: But I still love watching reviews, and I've been watching

506
00:25:21,160 --> 00:25:26,120
Speaker 1: lots of reviews lately on new fancy cars, electric cars,

507
00:25:26,600 --> 00:25:30,639
Speaker 1: and I watched this guy testing a car called the

508
00:25:30,680 --> 00:25:33,320
Speaker 1: Tank five hundred, which is essentially the size of a

509
00:25:33,400 --> 00:25:34,120
Speaker 1: land Cruiser.

510
00:25:34,880 --> 00:25:35,800
Speaker 4: It's Chinese.

511
00:25:36,480 --> 00:25:38,520
Speaker 1: It looks like a two hundred thousand dollars car at

512
00:25:38,560 --> 00:25:41,600
Speaker 1: seventy grand, give or take, except one of the problems.

513
00:25:41,640 --> 00:25:43,520
Speaker 1: And he jumps in and he's talking, and he takes

514
00:25:43,560 --> 00:25:46,479
Speaker 1: off and he's been driving for one hundred meters and

515
00:25:46,520 --> 00:25:50,399
Speaker 1: the car tells him, you're tired, pull over and have

516
00:25:50,520 --> 00:25:50,920
Speaker 1: a rest.

517
00:25:51,840 --> 00:25:52,040
Speaker 4: Right.

518
00:25:52,160 --> 00:25:54,640
Speaker 1: It keeps telling him because it's got all of these

519
00:25:54,680 --> 00:26:00,239
Speaker 1: senses that it can allegedly sense fatigue or tiredness or

520
00:26:00,280 --> 00:26:03,720
Speaker 1: however it does. And so every two hundred meters that

521
00:26:03,800 --> 00:26:05,919
Speaker 1: was telling him to pull over because he was tired,

522
00:26:06,320 --> 00:26:09,119
Speaker 1: and he just literally jumped in and started driving. So

523
00:26:10,080 --> 00:26:13,560
Speaker 1: they're sorting out the kinks. But you know, I wonder,

524
00:26:13,840 --> 00:26:15,720
Speaker 1: like I kind of love the fact that I have

525
00:26:15,800 --> 00:26:18,560
Speaker 1: a five year old car that's kind of basic.

526
00:26:19,560 --> 00:26:19,760
Speaker 4: You know.

527
00:26:19,840 --> 00:26:22,880
Speaker 1: It's like there's I don't need to be a buddy

528
00:26:23,119 --> 00:26:25,040
Speaker 1: tech journeius to be able to get in it and

529
00:26:25,080 --> 00:26:25,680
Speaker 1: operate it.

530
00:26:27,359 --> 00:26:27,600
Speaker 3: Yeah.

531
00:26:27,760 --> 00:26:28,359
Speaker 2: Look, I.

532
00:26:30,160 --> 00:26:32,840
Speaker 3: Love the more safety you have in a car, but

533
00:26:32,880 --> 00:26:35,520
Speaker 3: I still love to drive a manual every now and again.

534
00:26:35,600 --> 00:26:39,040
Speaker 3: I love, you know, stick shift it's nice to go

535
00:26:39,119 --> 00:26:40,560
Speaker 3: through the gears and feel the.

536
00:26:40,560 --> 00:26:42,080
Speaker 2: Car and know when to change.

537
00:26:42,160 --> 00:26:46,760
Speaker 3: And as you know, you've driven sticks many times on

538
00:26:46,800 --> 00:26:51,160
Speaker 3: the power of the vehicle. You remember the term powerband. Yeah,

539
00:26:51,200 --> 00:26:54,280
Speaker 3: and I love that. I love the people of our

540
00:26:54,359 --> 00:26:57,240
Speaker 3: generation understand what that means. And the other thing is

541
00:26:57,240 --> 00:26:59,159
Speaker 3: I've taught a lot of people to drive in my

542
00:26:59,320 --> 00:27:02,920
Speaker 3: Nissan on this NXR coop. And the good thing about

543
00:27:02,960 --> 00:27:05,040
Speaker 3: teaching a young person how to drive and a manual

544
00:27:05,160 --> 00:27:06,919
Speaker 3: is they have a lot more respect for how an

545
00:27:07,000 --> 00:27:10,960
Speaker 3: engine works, because you know that when you go from

546
00:27:11,000 --> 00:27:13,200
Speaker 3: first gear to second gear to third gear, you can

547
00:27:13,280 --> 00:27:17,920
Speaker 3: feel and hear how your engine is being taxed and

548
00:27:17,960 --> 00:27:21,760
Speaker 3: how much effort the engine is going through and the car.

549
00:27:22,240 --> 00:27:24,800
Speaker 3: I like that, And I'm not a petrol head by

550
00:27:24,960 --> 00:27:27,200
Speaker 3: a long shot, but I still love the feeling. And

551
00:27:27,520 --> 00:27:29,919
Speaker 3: a friend of mine she had to look for so

552
00:27:29,960 --> 00:27:32,679
Speaker 3: many different models before she was even able to purchase

553
00:27:32,720 --> 00:27:35,159
Speaker 3: a manual car. I think the WRX is one of

554
00:27:35,200 --> 00:27:37,600
Speaker 3: the few cars on the road that still is a manual.

555
00:27:38,160 --> 00:27:39,639
Speaker 2: It's very, very hard to buy a manual.

556
00:27:39,720 --> 00:27:42,880
Speaker 1: View. Yeah, mine's manual. Mine's five speed. It's a little

557
00:27:42,920 --> 00:27:45,480
Speaker 1: one point four turbo, little Suzuki sport.

558
00:27:45,520 --> 00:27:46,600
Speaker 4: It's great, It's great.

559
00:27:47,400 --> 00:27:51,040
Speaker 1: Here's something that caught my eye. I don't know why

560
00:27:51,840 --> 00:27:55,879
Speaker 1: researchers build AI driven sarcasm detector.

561
00:27:56,119 --> 00:27:56,520
Speaker 2: Oh I.

562
00:27:59,240 --> 00:28:00,840
Speaker 4: Was that built for me?

563
00:28:02,160 --> 00:28:06,400
Speaker 3: It feels like it doesn't it It really really really

564
00:28:06,480 --> 00:28:10,879
Speaker 3: does that. There is a seriousness behind this because being

565
00:28:11,000 --> 00:28:13,640
Speaker 3: able to detect sarcasm.

566
00:28:13,960 --> 00:28:14,720
Speaker 2: I know we call it.

567
00:28:14,640 --> 00:28:17,280
Speaker 3: The lowest form of whip, but I believe also it

568
00:28:17,400 --> 00:28:25,160
Speaker 3: shows intelligence. Potentially maybe, but evidently knowing sarcasm means your

569
00:28:25,200 --> 00:28:30,359
Speaker 3: interaction with people is a lot more natural. So what

570
00:28:30,440 --> 00:28:35,080
Speaker 3: it means, So this is some researchers who have basically

571
00:28:35,600 --> 00:28:40,160
Speaker 3: looked at sarcasm as a way to make the AI

572
00:28:40,320 --> 00:28:47,160
Speaker 3: model understand more about how language works. And sarcasm can

573
00:28:47,200 --> 00:28:50,320
Speaker 3: be hard to detect even if you're just an average person.

574
00:28:50,640 --> 00:28:53,640
Speaker 3: But if you're trying to train an AI model to

575
00:28:53,760 --> 00:28:58,680
Speaker 3: be more clever to understand how people work, the sarcasm

576
00:28:58,720 --> 00:29:03,120
Speaker 3: director detect certainly has a lot of benefits.

577
00:29:03,160 --> 00:29:06,400
Speaker 2: So I kind of like it that it's an interesting.

578
00:29:06,160 --> 00:29:08,440
Speaker 3: Idea, and then when you start to dig down a

579
00:29:08,480 --> 00:29:11,320
Speaker 3: little bit deeper, it makes a lot of sense. Because

580
00:29:11,640 --> 00:29:14,719
Speaker 3: we have a lot of nuances in communication and in

581
00:29:14,760 --> 00:29:17,840
Speaker 3: our conversation. I mean, look at my shows when we

582
00:29:17,880 --> 00:29:20,200
Speaker 3: get let's face it.

583
00:29:20,680 --> 00:29:22,640
Speaker 4: I mean, that's why we have people who love it

584
00:29:22,680 --> 00:29:24,920
Speaker 4: and people who hate it. Speaking of sarcasm.

585
00:29:25,160 --> 00:29:29,800
Speaker 1: This afternoon, I had a meeting with my senior academic supervisor, Chris,

586
00:29:29,960 --> 00:29:35,680
Speaker 1: and my other supervisor, Lucy, and another guy called Campbell

587
00:29:35,680 --> 00:29:39,000
Speaker 1: who helps with analytics and data and shout out to Campbell,

588
00:29:39,040 --> 00:29:42,800
Speaker 1: and and anyway, we're all on this call and we're

589
00:29:42,800 --> 00:29:45,480
Speaker 1: trying to figure out we're talking about this, you know,

590
00:29:45,560 --> 00:29:48,440
Speaker 1: looking at I won't bore everyone, but we're looking at

591
00:29:48,480 --> 00:29:54,400
Speaker 1: different variables that we could correlate with what too, Sorry, anyway,

592
00:29:54,760 --> 00:29:57,240
Speaker 1: we're thinking we're talking about different things that we could

593
00:29:57,320 --> 00:30:01,920
Speaker 1: correlate with or explore, being a relationship between meta accuracy

594
00:30:02,160 --> 00:30:05,640
Speaker 1: and so meta accuracy and age meta accuracy and income

595
00:30:05,680 --> 00:30:09,560
Speaker 1: metaaccuracy and all these different things. And I said, like,

596
00:30:09,760 --> 00:30:12,280
Speaker 1: as you know, Sarka as a maner joke, I go,

597
00:30:12,360 --> 00:30:16,760
Speaker 1: what about meta accuracy and star scigns and like every

598
00:30:16,840 --> 00:30:19,440
Speaker 1: like maybe virgos are really fucking good at it, right,

599
00:30:20,600 --> 00:30:23,480
Speaker 1: or capricorns maybe they can just you know, they're great

600
00:30:23,520 --> 00:30:26,000
Speaker 1: at this. And all three of them just looked at

601
00:30:26,000 --> 00:30:29,480
Speaker 1: me like I was a complete fuck with and Chris,

602
00:30:29,560 --> 00:30:32,720
Speaker 1: my senior supervisor, didn't even respond and he just kept

603
00:30:33,720 --> 00:30:37,800
Speaker 1: he just kept talking, Oh and ah, there it is,

604
00:30:37,840 --> 00:30:41,280
Speaker 1: and that's probably why I shouldn't be in this environment anyway,

605
00:30:41,560 --> 00:30:43,480
Speaker 1: keep going, I'm really getting bored.

606
00:30:43,520 --> 00:30:46,280
Speaker 3: No, oh, I didn't pick up and that I said

607
00:30:46,360 --> 00:30:50,000
Speaker 3: no instead of now, oh, there you go, keep going.

608
00:30:50,680 --> 00:30:52,440
Speaker 2: Yeah, that was it. That was just the sarcasm thing.

609
00:30:52,480 --> 00:30:53,160
Speaker 2: I thought it was great.

610
00:30:53,880 --> 00:30:57,440
Speaker 3: Do you Another little AI story that I had to

611
00:30:57,520 --> 00:30:59,480
Speaker 3: kind of throw in here is how people are using

612
00:30:59,480 --> 00:31:01,360
Speaker 3: AI now for insurance fraud.

613
00:31:01,400 --> 00:31:03,560
Speaker 2: Did you see that? It came up a little while ago.

614
00:31:03,960 --> 00:31:04,840
Speaker 2: So what they're.

615
00:31:04,640 --> 00:31:08,680
Speaker 3: Doing, yeah, because when you put in an accident claim,

616
00:31:09,040 --> 00:31:11,480
Speaker 3: you show your vehicle and the damage.

617
00:31:11,520 --> 00:31:12,840
Speaker 2: And thankfully I.

618
00:31:12,840 --> 00:31:14,680
Speaker 3: Haven't had too many accidents, but I did head a

619
00:31:14,760 --> 00:31:17,200
Speaker 3: kangaroo in my new car after they had it three

620
00:31:17,240 --> 00:31:20,680
Speaker 3: months and wow, yeah it was a really messy hit.

621
00:31:20,760 --> 00:31:23,240
Speaker 3: And I look it was already dead on the road,

622
00:31:23,320 --> 00:31:25,400
Speaker 3: because that would have made me even more distressed if

623
00:31:25,400 --> 00:31:27,960
Speaker 3: it had been alive and I was responsible for killing it.

624
00:31:28,040 --> 00:31:29,120
Speaker 2: But that's it.

625
00:31:29,440 --> 00:31:31,040
Speaker 3: Yet took out a big chunk of the front of

626
00:31:31,080 --> 00:31:35,480
Speaker 3: my car. But what people are doing is they're actually

627
00:31:35,920 --> 00:31:40,560
Speaker 3: faking claims by putting a picture of their car into

628
00:31:40,600 --> 00:31:43,400
Speaker 3: AI and say, put a DNT in the front right

629
00:31:43,440 --> 00:31:44,800
Speaker 3: fender and.

630
00:31:44,720 --> 00:31:45,719
Speaker 2: Then submitting it.

631
00:31:46,600 --> 00:31:49,720
Speaker 3: Really, so insurance companies are now and this was a

632
00:31:49,760 --> 00:31:53,280
Speaker 3: study in the UK done by Alliance, and they're saying

633
00:31:54,160 --> 00:31:56,440
Speaker 3: that what they're having to do is now really look

634
00:31:56,560 --> 00:32:00,240
Speaker 3: closely at accidents because they may be what they call

635
00:32:00,320 --> 00:32:03,400
Speaker 3: shallow fakes. So we've heard of deep fakes. This is

636
00:32:03,400 --> 00:32:08,040
Speaker 3: a shallow fake. So it's yeah, it's not always convincing.

637
00:32:08,280 --> 00:32:12,479
Speaker 3: And and look, some of them can be close. But

638
00:32:12,920 --> 00:32:14,960
Speaker 3: it wouldn't even have occurred to me to do something

639
00:32:15,040 --> 00:32:17,920
Speaker 3: like this, you know. It's funny some people just think

640
00:32:17,960 --> 00:32:21,120
Speaker 3: that way. So yeah, that was an interesting one.

641
00:32:21,440 --> 00:32:23,320
Speaker 1: Well, I think that's going to happen. Stuff like that's

642
00:32:23,360 --> 00:32:24,960
Speaker 1: going to happen more and more, isn't it. How do

643
00:32:25,000 --> 00:32:28,600
Speaker 1: we use this technology to shaft people, to embezzle, to

644
00:32:29,840 --> 00:32:34,760
Speaker 1: you know, create some kind of unfair advantage you know, Yeah,

645
00:32:34,840 --> 00:32:36,320
Speaker 1: that's gonna it's not going away.

646
00:32:37,000 --> 00:32:38,360
Speaker 2: Yeah, so that's that's a thing now.

647
00:32:38,520 --> 00:32:42,720
Speaker 3: Crago yep, And I look, there were there's been a

648
00:32:42,800 --> 00:32:47,760
Speaker 3: twenty nine percent increase in fraud reported, you know, according

649
00:32:47,800 --> 00:32:51,560
Speaker 3: to this particular report by Alliance and and so it's

650
00:32:51,600 --> 00:32:54,080
Speaker 3: happening a lot more. And they talked about a van

651
00:32:54,160 --> 00:32:57,520
Speaker 3: and they showed a picture of this van free Ai

652
00:32:57,760 --> 00:33:01,360
Speaker 3: and post Ai and the person have created a dint

653
00:33:01,800 --> 00:33:03,200
Speaker 3: in the in the side of the car.

654
00:33:03,360 --> 00:33:06,080
Speaker 2: So yeah, it's it's a thing. Are we giving people

655
00:33:06,160 --> 00:33:07,640
Speaker 2: bad bad ideas? Though?

656
00:33:08,200 --> 00:33:09,920
Speaker 4: I think the ideas were already out there?

657
00:33:10,000 --> 00:33:10,560
Speaker 2: Okay, good?

658
00:33:11,680 --> 00:33:15,840
Speaker 1: Yeah, I want to know why Pizza Hut got fined

659
00:33:15,880 --> 00:33:17,400
Speaker 1: two and a half million bucks.

660
00:33:17,880 --> 00:33:22,760
Speaker 3: I know the I kind of feel that this is

661
00:33:22,800 --> 00:33:26,560
Speaker 3: a very important message that the you know that the

662
00:33:26,600 --> 00:33:29,680
Speaker 3: authorities are dishing out to companies like this, Oh, dishing

663
00:33:29,680 --> 00:33:30,600
Speaker 3: out like a pizza.

664
00:33:31,120 --> 00:33:33,760
Speaker 4: No pun intended when you said that, I thought of that.

665
00:33:34,120 --> 00:33:37,880
Speaker 2: Well, the thing is, can you get spam on a pizza?

666
00:33:39,040 --> 00:33:40,120
Speaker 4: Oh? Tish book?

667
00:33:40,840 --> 00:33:42,040
Speaker 2: It's getting, isn't it.

668
00:33:42,160 --> 00:33:46,080
Speaker 1: I don't think you want like our our older folk,

669
00:33:46,520 --> 00:33:49,320
Speaker 1: our older listeners know what spam is, but probably our

670
00:33:49,920 --> 00:33:52,520
Speaker 1: forty and under brigade they wouldn't know what spam is.

671
00:33:52,600 --> 00:33:55,200
Speaker 3: Patrick, Yeah, so spam in a can that was just

672
00:33:55,320 --> 00:33:56,600
Speaker 3: I don't know what the meat. Well, I don't think

673
00:33:56,600 --> 00:33:58,720
Speaker 3: anybody knows what's inside spam. They put it in a

674
00:33:58,760 --> 00:34:00,440
Speaker 3: can and you can make a boot out of it.

675
00:34:00,520 --> 00:34:03,520
Speaker 4: Sp I think let's just say it was ham.

676
00:34:03,680 --> 00:34:05,920
Speaker 2: Ishh Yeah, any part.

677
00:34:05,880 --> 00:34:08,520
Speaker 4: In that it was in the neighborhood of ham.

678
00:34:08,680 --> 00:34:11,080
Speaker 2: I think snouts and assholes is probably.

679
00:34:10,800 --> 00:34:14,000
Speaker 1: You know, but I think I think I'll tell you

680
00:34:14,040 --> 00:34:17,440
Speaker 1: what it was. It was like a canful of salt.

681
00:34:17,960 --> 00:34:21,080
Speaker 1: It was a saltier shit you've ever tasted. They probably

682
00:34:21,120 --> 00:34:23,200
Speaker 1: put all that salt in there to kill.

683
00:34:22,960 --> 00:34:26,319
Speaker 3: The taste, yeah, and also keep it going. Didn't they

684
00:34:26,440 --> 00:34:28,560
Speaker 3: use it during Wasn't it developed for World War II

685
00:34:28,719 --> 00:34:29,120
Speaker 3: or something?

686
00:34:29,200 --> 00:34:31,080
Speaker 2: I thought I think it was troops.

687
00:34:31,239 --> 00:34:33,680
Speaker 4: I think like fair bit of fat, fair bit of salt.

688
00:34:33,880 --> 00:34:37,720
Speaker 1: Probably if you're in the middle of nowhere and trying

689
00:34:37,760 --> 00:34:38,839
Speaker 1: to stay alive.

690
00:34:38,600 --> 00:34:40,879
Speaker 4: Who knows, I mean, anything would taste pretty good.

691
00:34:41,200 --> 00:34:41,680
Speaker 2: Yeah.

692
00:34:41,760 --> 00:34:45,719
Speaker 3: So in Australia, the Communications and Media Authority, the ACMA,

693
00:34:46,560 --> 00:34:52,719
Speaker 3: they investigate complaints when people receive unsolicited emails or texts

694
00:34:53,120 --> 00:34:55,480
Speaker 3: and you don't have an ability to be able to

695
00:34:55,520 --> 00:34:58,080
Speaker 3: opt out. So it's laura in Australia. If you get

696
00:34:58,120 --> 00:34:59,920
Speaker 3: a bulk email sent to you or a bulk ten

697
00:35:00,560 --> 00:35:03,359
Speaker 3: and you try to opt out and you can't, then

698
00:35:03,400 --> 00:35:04,680
Speaker 3: the company's doing.

699
00:35:04,400 --> 00:35:05,520
Speaker 2: That is at fault.

700
00:35:05,960 --> 00:35:09,600
Speaker 3: And evidently in this particular instance, it was reported that

701
00:35:09,800 --> 00:35:14,120
Speaker 3: ten million spam marketing text and emails were sent out

702
00:35:14,160 --> 00:35:19,160
Speaker 3: in four months time, and people were trying to unsubscribe

703
00:35:19,440 --> 00:35:22,160
Speaker 3: to stop receiving them and they couldn't so and then

704
00:35:22,200 --> 00:35:25,560
Speaker 3: another four point three million marketing messages was sent out

705
00:35:25,960 --> 00:35:29,960
Speaker 3: without the option to unsubscribe. So it sends a really

706
00:35:30,080 --> 00:35:36,160
Speaker 3: clear message that you know, country, countries, companies know these laws.

707
00:35:36,200 --> 00:35:38,040
Speaker 2: These laws have been around for a long time now.

708
00:35:38,080 --> 00:35:39,680
Speaker 3: So I just thought it would be an interesting one

709
00:35:39,719 --> 00:35:43,280
Speaker 3: to mention that, you know, if you're receiving unsolicited emails

710
00:35:43,280 --> 00:35:45,480
Speaker 3: and you want to dub somebody in for doing it, gee,

711
00:35:45,480 --> 00:35:46,040
Speaker 3: I'll tell you what.

712
00:35:46,080 --> 00:35:48,040
Speaker 2: The find's pretty big, can.

713
00:35:47,920 --> 00:35:52,440
Speaker 1: I'd tell you something in the same ballpark. So I'm

714
00:35:52,480 --> 00:35:54,319
Speaker 1: not going to say what company. But I had this

715
00:35:55,800 --> 00:35:58,600
Speaker 1: kind of what do you call the computer protectiony stuff?

716
00:35:58,840 --> 00:35:59,480
Speaker 4: What do you call that?

717
00:36:00,120 --> 00:36:00,720
Speaker 2: Any virus?

718
00:36:01,280 --> 00:36:02,640
Speaker 4: Antivirus? Thank you Patrick.

719
00:36:03,320 --> 00:36:06,400
Speaker 1: So I had that installed I won't say what company,

720
00:36:06,520 --> 00:36:11,799
Speaker 1: and it like every eight minutes it would pop up

721
00:36:11,840 --> 00:36:16,080
Speaker 1: with whatever, right, and then it ran out and I

722
00:36:16,200 --> 00:36:19,000
Speaker 1: decided to go with something else and this one that

723
00:36:19,080 --> 00:36:22,200
Speaker 1: ran out to try to get that out of my

724
00:36:22,360 --> 00:36:26,920
Speaker 1: fucking computer. It was like it was a virus, like

725
00:36:27,040 --> 00:36:30,600
Speaker 1: it would not go away. I tried to uninstall it,

726
00:36:30,719 --> 00:36:33,400
Speaker 1: or I did what I thought uninstall it. I followed

727
00:36:33,440 --> 00:36:36,640
Speaker 1: the YouTube video, I uninstalled it, and then it was

728
00:36:36,719 --> 00:36:40,319
Speaker 1: back and it kept going, you're expired. You need to

729
00:36:40,360 --> 00:36:41,520
Speaker 1: do this, you need to do that.

730
00:36:41,600 --> 00:36:43,480
Speaker 4: If you don't do this, like the world's going to

731
00:36:43,520 --> 00:36:44,719
Speaker 4: blow up and we're going to you know.

732
00:36:44,800 --> 00:36:48,000
Speaker 1: It's like, in the end, it was more of a

733
00:36:48,080 --> 00:36:50,840
Speaker 1: problem than the fucking viruses I was trying to protect

734
00:36:50,880 --> 00:36:51,560
Speaker 1: myself from.

735
00:36:52,239 --> 00:36:55,640
Speaker 3: Yeah, so a lot of laptop and computer companies do

736
00:36:55,800 --> 00:36:59,239
Speaker 3: deals with these antivirus companies, starting with Mac.

737
00:36:59,480 --> 00:37:01,920
Speaker 2: I think probably is the one you're thinking of a

738
00:37:02,000 --> 00:37:05,480
Speaker 2: fee McAfee. Sorry, I just had something caught in my throat.

739
00:37:06,080 --> 00:37:06,520
Speaker 1: Yeah, so.

740
00:37:08,120 --> 00:37:11,359
Speaker 3: It's not unusual to have the anti virus installed, but

741
00:37:11,440 --> 00:37:14,280
Speaker 3: it's only a limited trial for say, thirty thirty days,

742
00:37:14,560 --> 00:37:16,799
Speaker 3: and it is really painful trying to get rid of it,

743
00:37:16,840 --> 00:37:18,840
Speaker 3: and it is I'm really impressed that you did a

744
00:37:18,920 --> 00:37:21,360
Speaker 3: YouTube and jumped on there and tried.

745
00:37:21,160 --> 00:37:23,000
Speaker 2: To get rid of it yourself, Craigi. I thought that

746
00:37:23,040 --> 00:37:23,720
Speaker 2: was very impressive.

747
00:37:23,800 --> 00:37:25,800
Speaker 4: Yeah, I thought I'd done it, and then about twenty

748
00:37:25,800 --> 00:37:27,480
Speaker 4: minutes later, it was back, and then I had to

749
00:37:27,480 --> 00:37:30,359
Speaker 4: get the actual smart person in the organization to come

750
00:37:30,400 --> 00:37:31,800
Speaker 4: over and do it. Liza.

751
00:37:31,960 --> 00:37:34,720
Speaker 1: Yeah, she came over and did it in thirteen seconds

752
00:37:34,719 --> 00:37:36,400
Speaker 1: and looked at me quizzically.

753
00:37:36,480 --> 00:37:38,400
Speaker 2: And she uses a Mac. Oh are you on a

754
00:37:38,440 --> 00:37:39,000
Speaker 2: Mac as well?

755
00:37:39,480 --> 00:37:42,120
Speaker 4: I'm not on a Mac, so it wasn't that brand,

756
00:37:42,160 --> 00:37:43,920
Speaker 4: you said, But I don't want to say it on

757
00:37:43,960 --> 00:37:46,120
Speaker 4: air because I feel like they might hijack me.

758
00:37:46,480 --> 00:37:47,320
Speaker 2: Yeah, fair enough.

759
00:37:47,880 --> 00:37:51,760
Speaker 3: It's interesting while you're talking about that at the moment,

760
00:37:51,880 --> 00:37:54,080
Speaker 3: Dell has put out a warning just recently in the

761
00:37:54,120 --> 00:37:57,279
Speaker 3: last few days because they had a data breach and

762
00:37:57,520 --> 00:38:01,560
Speaker 3: they believe forty nine million customers may have had information

763
00:38:02,000 --> 00:38:05,879
Speaker 3: and that that's now gone onto the dark web, and

764
00:38:06,320 --> 00:38:09,840
Speaker 3: that's potentially Yeah, this could be serious for a lot

765
00:38:09,880 --> 00:38:10,160
Speaker 3: of people.

766
00:38:10,440 --> 00:38:15,919
Speaker 4: Nine million. I mean, how does.

767
00:38:14,360 --> 00:38:17,400
Speaker 1: How did they ever compensate for that? Because it's like

768
00:38:17,480 --> 00:38:21,400
Speaker 1: it's almost unknowable, like the potential and I'm sure the

769
00:38:21,480 --> 00:38:24,920
Speaker 1: vast majority of people would be fine, but I mean,

770
00:38:24,960 --> 00:38:28,280
Speaker 1: even if it was one percent of forty nine million,

771
00:38:28,320 --> 00:38:31,840
Speaker 1: that's four hundred and ninety thousand people. That's half a

772
00:38:31,880 --> 00:38:36,000
Speaker 1: million people, give or take. I mean, yeah, that's that's

773
00:38:36,080 --> 00:38:40,160
Speaker 1: the scary thing. Now when other when people that don't

774
00:38:40,160 --> 00:38:43,200
Speaker 1: have your best interests at heart have got access to

775
00:38:43,239 --> 00:38:45,080
Speaker 1: all your shit, that makes me nervous.

776
00:38:45,360 --> 00:38:48,759
Speaker 3: Yeah, and look, one of the things they're saying is

777
00:38:48,800 --> 00:38:51,400
Speaker 3: that it could be as much as the name of

778
00:38:51,440 --> 00:38:54,600
Speaker 3: the buyer, the company named the address. So there's quite

779
00:38:54,600 --> 00:38:58,920
Speaker 3: a few markers that are very specific to the individual customer,

780
00:38:58,920 --> 00:39:01,440
Speaker 3: and that's one of the problems. And you know, things

781
00:39:01,520 --> 00:39:03,600
Speaker 3: like your name and your physical address. That sort of

782
00:39:03,600 --> 00:39:06,520
Speaker 3: stuff is really, you know, something that's quite problematic. But

783
00:39:06,600 --> 00:39:09,520
Speaker 3: one of the things that you should do is go

784
00:39:09,640 --> 00:39:12,360
Speaker 3: to the website of the vendor, if it happens to

785
00:39:12,360 --> 00:39:16,359
Speaker 3: be in this case, Dell, and follow their instructions and suggestions.

786
00:39:16,719 --> 00:39:18,799
Speaker 3: But the first thing you need to do is go

787
00:39:18,880 --> 00:39:22,319
Speaker 3: and change your password. Absolute first thing you do. Now,

788
00:39:22,360 --> 00:39:24,760
Speaker 3: I haven't had a Dell computer for quite a few years,

789
00:39:25,200 --> 00:39:27,040
Speaker 3: but that was the first thing I did was jump

790
00:39:27,080 --> 00:39:29,160
Speaker 3: in and see if I still had a Dell account

791
00:39:29,440 --> 00:39:31,840
Speaker 3: and if there was a password, and I generated a

792
00:39:31,880 --> 00:39:35,239
Speaker 3: new password just in case. That was one of the

793
00:39:35,280 --> 00:39:38,239
Speaker 3: first things. And also two factor authentication. You might have

794
00:39:38,280 --> 00:39:40,839
Speaker 3: seen it written down as two FA that's another thing

795
00:39:40,880 --> 00:39:42,640
Speaker 3: that you can do. Make sure then that two factor

796
00:39:42,719 --> 00:39:46,839
Speaker 3: authentication means that before you can sign in, you have

797
00:39:46,960 --> 00:39:51,560
Speaker 3: to either have a second factor authentication, either a text

798
00:39:51,600 --> 00:39:53,640
Speaker 3: message or an email get sent to you with a

799
00:39:53,719 --> 00:39:56,319
Speaker 3: code and then you put the code in. So it's

800
00:39:56,320 --> 00:39:58,400
Speaker 3: not enough just to have the password. You need that

801
00:39:58,440 --> 00:40:00,719
Speaker 3: factor code to then pull it there as well. It's

802
00:40:00,719 --> 00:40:03,840
Speaker 3: a pain, but it's a level of security as well.

803
00:40:04,560 --> 00:40:07,560
Speaker 1: I saw this real today, mate, and a guy was

804
00:40:08,280 --> 00:40:09,920
Speaker 1: I don't know if it was. It was like a

805
00:40:09,960 --> 00:40:13,200
Speaker 1: little almost like a road test of a product. This

806
00:40:13,239 --> 00:40:16,680
Speaker 1: guy was sitting in what looked to be a cafe.

807
00:40:16,760 --> 00:40:19,920
Speaker 1: There was lots of people around. He was talking and

808
00:40:20,520 --> 00:40:22,920
Speaker 1: we could hear what he was hearing. He had like

809
00:40:23,000 --> 00:40:26,319
Speaker 1: this thing in his ear, and then he said.

810
00:40:26,760 --> 00:40:27,120
Speaker 4: I don't know.

811
00:40:27,160 --> 00:40:30,160
Speaker 1: He gave some instruction to cut out the background noise

812
00:40:30,280 --> 00:40:33,640
Speaker 1: and just to focus on one person across the table.

813
00:40:34,560 --> 00:40:37,920
Speaker 1: Took out all the noise except this bloke's voice, and

814
00:40:37,960 --> 00:40:41,760
Speaker 1: then you could clearly hear what he was saying, except

815
00:40:41,840 --> 00:40:44,920
Speaker 1: he was speaking in Spanish, and then he said, now

816
00:40:45,000 --> 00:40:48,200
Speaker 1: converted into English. So all of a sudden, all the

817
00:40:48,239 --> 00:40:51,000
Speaker 1: noise in the room has gone, or you know, it's

818
00:40:51,000 --> 00:40:53,840
Speaker 1: gone from a ten to or one, and now we

819
00:40:53,880 --> 00:40:57,160
Speaker 1: can hear clearly hear this guy, and then we then

820
00:40:57,200 --> 00:41:02,279
Speaker 1: it gets translated in pretty much real time into English, like.

821
00:41:02,600 --> 00:41:04,279
Speaker 3: Yeah, it makes you feel sad that we don't have

822
00:41:04,320 --> 00:41:06,600
Speaker 3: a Cold war and spies anymore, because that.

823
00:41:06,600 --> 00:41:08,040
Speaker 2: Would have been really handy, wouldn't it.

824
00:41:08,360 --> 00:41:13,359
Speaker 4: Ah, Yeah, I'm pretty sure we do have spies. I'm

825
00:41:13,360 --> 00:41:14,200
Speaker 4: pretty sure there.

826
00:41:14,040 --> 00:41:16,320
Speaker 3: Are still shout out to everybody at AISIO.

827
00:41:17,239 --> 00:41:20,680
Speaker 1: I'm going to show my age here because I read

828
00:41:20,719 --> 00:41:24,399
Speaker 1: the one of the titles of one of your kind

829
00:41:24,400 --> 00:41:27,719
Speaker 1: of articles or one of your discussion points under social media,

830
00:41:27,760 --> 00:41:31,760
Speaker 1: and it says young people share their experience of being doxed.

831
00:41:32,520 --> 00:41:34,000
Speaker 1: I don't know what dost means.

832
00:41:34,560 --> 00:41:37,319
Speaker 3: This is actually a bit of bit insidious. This it's

833
00:41:37,360 --> 00:41:40,960
Speaker 3: a terrible thing to do to somebody. It's where online. Okay,

834
00:41:40,960 --> 00:41:43,600
Speaker 3: we'll give an example. You're online gaming and you have

835
00:41:43,640 --> 00:41:45,839
Speaker 3: a bit of an altercation with someone because quite often

836
00:41:45,880 --> 00:41:49,200
Speaker 3: online gamers can talk to each other and someone takes

837
00:41:49,200 --> 00:41:52,520
Speaker 3: a dislike to you. But then they get your personal details,

838
00:41:52,560 --> 00:41:55,840
Speaker 3: your address, and then they start sending pizza delivery people

839
00:41:55,840 --> 00:41:58,319
Speaker 3: to your house. And we're not talking one person, we're

840
00:41:58,320 --> 00:42:01,759
Speaker 3: talking fifty people. So suddenly you're getting packages delivered to

841
00:42:01,800 --> 00:42:04,440
Speaker 3: your house. You're getting pizzas delivered to your house, and

842
00:42:05,160 --> 00:42:08,359
Speaker 3: it could be amazingly distressing. This happened to a guy

843
00:42:08,400 --> 00:42:12,320
Speaker 3: who was only seventeen and his whole family was thrown

844
00:42:12,400 --> 00:42:15,480
Speaker 3: in a curveball here and it meant that, you know,

845
00:42:15,480 --> 00:42:17,920
Speaker 3: he got into an argument online playing a game called

846
00:42:18,320 --> 00:42:20,879
Speaker 3: Call of Duty, and then for about three or four

847
00:42:20,960 --> 00:42:24,359
Speaker 3: weeks he kept getting you know, uber eats and pizzas

848
00:42:24,640 --> 00:42:28,279
Speaker 3: and it says sometimes fifty times a day, and that's

849
00:42:28,280 --> 00:42:31,239
Speaker 3: what it is. It's a really malicious thing people can do.

850
00:42:31,440 --> 00:42:34,719
Speaker 3: I mean, I always get distressed when people the keyboard warriors,

851
00:42:34,760 --> 00:42:38,360
Speaker 3: you know, people who are so tough behind the keyboard,

852
00:42:38,719 --> 00:42:40,759
Speaker 3: and they wouldn't say if you wouldn't do it in

853
00:42:40,800 --> 00:42:43,359
Speaker 3: real life if you don't think about it. And look,

854
00:42:43,400 --> 00:42:45,120
Speaker 3: there's always going to be people out there who'll do

855
00:42:45,160 --> 00:42:47,239
Speaker 3: this sort of stuff. But yeah, so that's what dosing is.

856
00:42:48,080 --> 00:42:50,120
Speaker 3: But as you can imagine, the whole family would have

857
00:42:50,120 --> 00:42:52,120
Speaker 3: been pretty distressed about this sort of thing happen.

858
00:42:52,320 --> 00:42:55,640
Speaker 1: I wonder what the solution to this is for the

859
00:42:56,280 --> 00:42:59,720
Speaker 1: food companies or the restaurants or because you think about

860
00:42:59,840 --> 00:43:02,400
Speaker 1: you you could ring up. I mean, I live on

861
00:43:02,440 --> 00:43:05,759
Speaker 1: a street with fifty restaurants. You've taken cafes. I could

862
00:43:05,800 --> 00:43:08,799
Speaker 1: ring up the pizza joint that's one hundred and eighty

863
00:43:08,840 --> 00:43:11,680
Speaker 1: meters away and order ten pizzas. As long as I

864
00:43:11,719 --> 00:43:14,520
Speaker 1: give them an address and a phone number, they're going

865
00:43:14,560 --> 00:43:15,799
Speaker 1: to make the ten pizzas.

866
00:43:16,239 --> 00:43:18,319
Speaker 2: Look, I think the only way to get around that

867
00:43:18,480 --> 00:43:21,440
Speaker 2: is for people to prepay and to say I mean,

868
00:43:21,440 --> 00:43:22,799
Speaker 2: at the end of the day, if someone sends me

869
00:43:22,800 --> 00:43:25,320
Speaker 2: a pizza and it's been paid for, I'm not too concerned.

870
00:43:25,480 --> 00:43:30,120
Speaker 3: Right, Yeah, I mean, look, it's you know, the society

871
00:43:30,200 --> 00:43:32,480
Speaker 3: is breaking down when people start sending a kilo and

872
00:43:32,520 --> 00:43:34,000
Speaker 3: a half of coins in the mail.

873
00:43:34,080 --> 00:43:35,000
Speaker 2: I mean, that's just kidding.

874
00:43:37,960 --> 00:43:41,280
Speaker 4: Yeah. By the way, Patrick's home address for the Federal

875
00:43:41,320 --> 00:43:44,040
Speaker 4: Police if you're listening, he's in Milan. I don't know

876
00:43:44,080 --> 00:43:44,840
Speaker 4: the exact address.

877
00:43:44,880 --> 00:43:46,799
Speaker 1: It just occurred to me that if all of our

878
00:43:46,840 --> 00:43:50,920
Speaker 1: listeners sent Patrick five dollars each, I will match that

879
00:43:51,040 --> 00:43:52,319
Speaker 1: with whatever we come up with.

880
00:43:53,920 --> 00:43:55,360
Speaker 2: It's greg that's a great idea.

881
00:43:55,840 --> 00:43:59,200
Speaker 1: You're an idiot. Stop that was fake me. That wasn't

882
00:43:59,239 --> 00:44:03,800
Speaker 1: really everyone that. By the way, fake me is way too.

883
00:44:03,640 --> 00:44:04,960
Speaker 2: Polite, you reckon.

884
00:44:05,640 --> 00:44:07,880
Speaker 4: Yeah, yeah, fake.

885
00:44:07,719 --> 00:44:13,040
Speaker 1: Me is too articulate and nice. I really need to apologize.

886
00:44:13,080 --> 00:44:15,400
Speaker 1: I was going to do a tai chi class with Patrick,

887
00:44:15,480 --> 00:44:20,279
Speaker 1: but I weaseled my way out of it. There's no apology,

888
00:44:20,520 --> 00:44:21,520
Speaker 1: there's just relief.

889
00:44:22,000 --> 00:44:24,240
Speaker 2: You're right. Actually yeah, it's just relief.

890
00:44:25,080 --> 00:44:28,000
Speaker 4: Like fake me, fake me doesn't know real me because

891
00:44:28,040 --> 00:44:31,160
Speaker 4: fake me he would know. Fake me should know that.

892
00:44:31,200 --> 00:44:32,920
Speaker 4: Real me would never apologize for that.

893
00:44:33,960 --> 00:44:36,200
Speaker 1: Of course you were. I'm always wrong and you are

894
00:44:36,239 --> 00:44:41,560
Speaker 1: one hundred percent right all the time. You wish, all right,

895
00:44:41,719 --> 00:44:45,359
Speaker 1: take us home with something. Just round this bad boy

896
00:44:45,480 --> 00:44:46,200
Speaker 1: up if you could.

897
00:44:46,480 --> 00:44:47,880
Speaker 2: It sounds like you want to get rid of me.

898
00:44:48,680 --> 00:44:49,520
Speaker 4: No, you can do it.

899
00:44:49,480 --> 00:44:51,960
Speaker 1: For as long as I just realized. You know why

900
00:44:52,000 --> 00:44:54,680
Speaker 1: we've gotten through a lot in a short time. I

901
00:44:54,719 --> 00:44:58,200
Speaker 1: don't want to say it's tiff, but it's tiff. It's

902
00:44:59,000 --> 00:45:02,200
Speaker 1: there's a a big conversational whole.

903
00:45:04,960 --> 00:45:05,200
Speaker 2: You know.

904
00:45:05,920 --> 00:45:10,880
Speaker 3: There's some researchers here in Australia have been looking at

905
00:45:11,120 --> 00:45:15,800
Speaker 3: how children are being educated and they're saying that children

906
00:45:15,880 --> 00:45:21,440
Speaker 3: produce better pieces of writing by hand, so their ability

907
00:45:21,480 --> 00:45:25,320
Speaker 3: to learn and at a certain age. So we're talking

908
00:45:25,360 --> 00:45:28,440
Speaker 3: say grade one and grade two if they are still writing.

909
00:45:28,480 --> 00:45:31,439
Speaker 3: And this is where education sytem in Australia is being

910
00:45:31,520 --> 00:45:36,600
Speaker 3: praised because when you're writing, you're singularly focused on what

911
00:45:36,640 --> 00:45:39,520
Speaker 3: you're doing is spelling every single letter. You're writing out

912
00:45:39,520 --> 00:45:43,319
Speaker 3: every single letter, and it's a much a better way

913
00:45:43,360 --> 00:45:46,080
Speaker 3: to focus and to be able to get kids.

914
00:45:45,960 --> 00:45:46,279
Speaker 2: To do that.

915
00:45:46,280 --> 00:45:49,399
Speaker 3: And I thought, isn't that great that handwriting is such

916
00:45:49,400 --> 00:45:52,239
Speaker 3: a good thing for young people and that we still doing.

917
00:45:52,800 --> 00:45:57,080
Speaker 3: Obviously keyboard skills are imperative for kids as they're getting older,

918
00:45:57,480 --> 00:46:01,279
Speaker 3: but certainly at a younger age they're saying, your handwriting

919
00:46:01,360 --> 00:46:04,440
Speaker 3: is really, really good. I've got friends of mine who

920
00:46:04,520 --> 00:46:06,600
Speaker 3: live around the corner from you. I just gave their

921
00:46:06,680 --> 00:46:09,480
Speaker 3: fourteen year old a fountain pin because he was telling

922
00:46:09,960 --> 00:46:13,680
Speaker 3: likes to write, and so it's great. It was funny

923
00:46:13,680 --> 00:46:15,960
Speaker 3: because I went over to their place a few weeks

924
00:46:15,960 --> 00:46:19,520
Speaker 3: ago and his fingers were blue. The bed leaked.

925
00:46:19,719 --> 00:46:22,919
Speaker 2: I'm so dodgy. Was that an expensive one to start

926
00:46:22,960 --> 00:46:23,239
Speaker 2: off with?

927
00:46:24,640 --> 00:46:27,319
Speaker 4: You know? It? Never? I mean, I don't know about you.

928
00:46:27,440 --> 00:46:28,520
Speaker 4: A couple of things.

929
00:46:28,280 --> 00:46:32,239
Speaker 1: Here, but we we had to use fountain pens like

930
00:46:32,360 --> 00:46:34,880
Speaker 1: we had in the old days. We had like we

931
00:46:34,920 --> 00:46:37,239
Speaker 1: didn't dip it in a bloody thing of ink, but

932
00:46:37,520 --> 00:46:40,480
Speaker 1: they had these ink cartridges and we.

933
00:46:40,600 --> 00:46:43,920
Speaker 4: Had to write. Is it called cursive right where all

934
00:46:43,920 --> 00:46:45,080
Speaker 4: the letters are connected?

935
00:46:45,480 --> 00:46:50,480
Speaker 2: Seriously? Yeah, of course I still write cursive, do you? Yeah?

936
00:46:50,520 --> 00:46:51,120
Speaker 2: With the fountain?

937
00:46:52,000 --> 00:46:53,759
Speaker 4: Are you? And are you my mum? Are you an

938
00:46:53,800 --> 00:46:54,600
Speaker 4: eighty five year.

939
00:46:54,520 --> 00:46:56,160
Speaker 2: Old writing with a fountain pen?

940
00:46:56,320 --> 00:47:00,120
Speaker 3: I actually have a beautiful mont Blanc fountain pen that

941
00:47:00,160 --> 00:47:01,439
Speaker 3: I write with every day.

942
00:47:02,440 --> 00:47:04,160
Speaker 4: Yeah, that's clearly.

943
00:47:04,520 --> 00:47:06,080
Speaker 2: I feel like I need to write you a letter.

944
00:47:06,760 --> 00:47:09,880
Speaker 4: I feel for fuck your letter. Don't send me a letter.

945
00:47:10,719 --> 00:47:14,799
Speaker 4: Fuck you know you're so weird. It's so weird. Hey,

946
00:47:14,960 --> 00:47:17,239
Speaker 4: but I never thought about the fact that.

947
00:47:19,640 --> 00:47:24,040
Speaker 1: Kids might soon stop writing. Like when you see like

948
00:47:24,160 --> 00:47:29,080
Speaker 1: literally two year olds, three year olds using computers, tablets, phones,

949
00:47:29,160 --> 00:47:35,680
Speaker 1: whatever and typing and navigating a keyboard, then I wonder

950
00:47:35,760 --> 00:47:37,840
Speaker 1: if I wonder if there's going to be a time

951
00:47:38,360 --> 00:47:41,839
Speaker 1: in the near future. You know what, he just took

952
00:47:41,880 --> 00:47:44,200
Speaker 1: off and took his headphone off. So are you going

953
00:47:44,280 --> 00:47:46,439
Speaker 1: to pretend that you know what I'm talking about? Now?

954
00:47:47,360 --> 00:47:50,400
Speaker 3: I had Fritz was trying to get out of the office,

955
00:47:50,440 --> 00:47:52,279
Speaker 3: and I thought, I hobe he might need to go

956
00:47:52,320 --> 00:47:53,440
Speaker 3: to the toilet or something.

957
00:47:53,520 --> 00:47:55,680
Speaker 1: So I hope he did a big dump on your

958
00:47:55,760 --> 00:48:00,800
Speaker 1: fucking sofa. Hey, I was just saying, before you took rudely,

959
00:48:01,920 --> 00:48:08,840
Speaker 1: I wish I had some fake Patrick, don't look at you.

960
00:48:08,920 --> 00:48:11,880
Speaker 1: What Yeah, you're trying to find some more fake me.

961
00:48:12,360 --> 00:48:14,440
Speaker 1: I was just saying, I wonder if we're going to

962
00:48:14,440 --> 00:48:16,359
Speaker 1: get to a time in the near future where kids

963
00:48:16,400 --> 00:48:19,520
Speaker 1: don't actually learn to write with pen and pencil anymore,

964
00:48:20,000 --> 00:48:21,879
Speaker 1: because we don't need it.

965
00:48:22,480 --> 00:48:23,800
Speaker 4: The world doesn't need.

966
00:48:23,640 --> 00:48:24,719
Speaker 2: That, not in Australia.

967
00:48:24,800 --> 00:48:27,319
Speaker 3: Evidently that's still a core part of our teaching, which

968
00:48:27,320 --> 00:48:27,680
Speaker 3: is great.

969
00:48:27,760 --> 00:48:29,520
Speaker 1: I know it is now, but I wonder if it'll

970
00:48:29,560 --> 00:48:33,480
Speaker 1: be in ten years. Like we're trying to eradicate paper.

971
00:48:34,320 --> 00:48:37,560
Speaker 1: We're already almost a cashless society.

972
00:48:38,320 --> 00:48:40,800
Speaker 3: But hasn't Tiff been using one of those tablets in

973
00:48:40,840 --> 00:48:43,000
Speaker 3: a pen, because that's the other thing you can do.

974
00:48:43,160 --> 00:48:45,120
Speaker 3: You can just have a tablet that you can write on.

975
00:48:45,200 --> 00:48:48,040
Speaker 3: My laptop flips over and I have a little stylust

976
00:48:48,400 --> 00:48:50,759
Speaker 3: so I can take notes and write them that way.

977
00:48:51,239 --> 00:48:53,040
Speaker 3: You know, I'd played around with it for a little while.

978
00:48:53,080 --> 00:48:56,400
Speaker 3: In fact, your last conference that you did, do you

979
00:48:56,400 --> 00:48:57,920
Speaker 3: remember I went along to that and you had some

980
00:48:57,960 --> 00:49:00,680
Speaker 3: great guests speakers. Well, I took that and making notes

981
00:49:00,920 --> 00:49:03,600
Speaker 3: and I flipped the laptop over and I was writing

982
00:49:03,600 --> 00:49:04,719
Speaker 3: my notes on the back of it.

983
00:49:05,000 --> 00:49:07,319
Speaker 2: But it's not the same as having ink on a

984
00:49:07,320 --> 00:49:08,040
Speaker 2: piece of paper.

985
00:49:08,560 --> 00:49:13,560
Speaker 1: Hmmm, well, think about the trees, bro, think about the trees. Ah,

986
00:49:15,160 --> 00:49:18,160
Speaker 1: tell people how they can come and break into your

987
00:49:19,440 --> 00:49:23,520
Speaker 1: very unsecure house in Bland and do yoga with you

988
00:49:23,560 --> 00:49:29,239
Speaker 1: and get you to build them all taichi, yoga pillarties,

989
00:49:29,280 --> 00:49:32,000
Speaker 1: it's all the same. I really need to apologize. I

990
00:49:32,040 --> 00:49:34,200
Speaker 1: was going to do a tai chie class with Patrick,

991
00:49:34,320 --> 00:49:37,799
Speaker 1: but I weaseled my way out of it. Stop it,

992
00:49:37,880 --> 00:49:41,920
Speaker 1: stop playing fake me. All right, I'm taking the piece everyone.

993
00:49:42,080 --> 00:49:45,520
Speaker 1: They're definitely not the same thing. They're all boring.

994
00:49:48,719 --> 00:49:50,440
Speaker 4: Oh, he's telling need to apologize.

995
00:49:50,440 --> 00:49:52,760
Speaker 1: I was going to do a tai chie class with Patrick,

996
00:49:52,880 --> 00:49:54,359
Speaker 1: but I weaseled my way out of it.

997
00:49:56,520 --> 00:49:59,000
Speaker 4: There we go, yep, there we go.

998
00:50:00,000 --> 00:50:04,279
Speaker 1: We say, dot dot com be what smelkod doubt that

999
00:50:04,400 --> 00:50:05,879
Speaker 1: was supposed to be websites?

1000
00:50:06,040 --> 00:50:08,719
Speaker 3: Now dot com tod au. Maybe I have to put

1001
00:50:08,760 --> 00:50:09,399
Speaker 3: gaps in it.

1002
00:50:10,640 --> 00:50:13,040
Speaker 4: Go and type it in now, properly, Go and type

1003
00:50:13,080 --> 00:50:15,000
Speaker 4: it in. I'll talk while you're doing that and see

1004
00:50:15,040 --> 00:50:16,480
Speaker 4: if you can get it right this time.

1005
00:50:17,600 --> 00:50:22,080
Speaker 1: You really you've lowered your colors today.

1006
00:50:21,040 --> 00:50:22,400
Speaker 2: Isn't it. Well? You know the other thing is we

1007
00:50:22,480 --> 00:50:23,839
Speaker 2: normally do them earlier in the day.

1008
00:50:25,640 --> 00:50:27,759
Speaker 4: I don't mind. I don't mind five o'clock. It's five

1009
00:50:27,920 --> 00:50:30,800
Speaker 4: fifty and it's dark as fucking hand.

1010
00:50:32,040 --> 00:50:34,440
Speaker 2: It's it's well, it's pretty dark everywhere. I guess at

1011
00:50:34,480 --> 00:50:34,920
Speaker 2: the moment.

1012
00:50:37,200 --> 00:50:38,880
Speaker 1: Websites now, dot com dot a.

1013
00:50:40,719 --> 00:50:43,800
Speaker 2: Not really not really spell it phonetically.

1014
00:50:46,680 --> 00:50:52,080
Speaker 1: What if you just write ay dash you.

1015
00:50:54,160 --> 00:50:57,000
Speaker 3: That's so weird, that is so strange. I'm gonna have

1016
00:50:57,000 --> 00:50:58,839
Speaker 3: to play around with it. Look, we'll try one more time.

1017
00:50:58,880 --> 00:51:00,840
Speaker 3: I'm going to move a little of the sliders and

1018
00:51:00,920 --> 00:51:02,120
Speaker 3: see what happens.

1019
00:51:02,239 --> 00:51:06,760
Speaker 1: Sorry, now, dot com dot a you that's.

1020
00:51:06,600 --> 00:51:08,280
Speaker 2: In terrible yea website?

1021
00:51:09,000 --> 00:51:09,200
Speaker 3: Are you?

1022
00:51:09,800 --> 00:51:10,000
Speaker 4: Yeah?

1023
00:51:10,040 --> 00:51:13,719
Speaker 1: Can you perfect that before the next one? Patrick, this

1024
00:51:13,800 --> 00:51:16,800
Speaker 1: has been your worst effort. You're on your first warning

1025
00:51:17,719 --> 00:51:19,760
Speaker 1: and you're on thin ice.

1026
00:51:20,120 --> 00:51:23,960
Speaker 3: I'm not even going to you're gonna have you.

1027
00:51:25,480 --> 00:51:28,080
Speaker 1: No, you know, here's the beauty of your pay I

1028
00:51:28,080 --> 00:51:29,920
Speaker 1: can harbor or double it and you're still getting the

1029
00:51:29,960 --> 00:51:32,040
Speaker 1: same welcome.

1030
00:51:32,520 --> 00:51:34,960
Speaker 2: Yeah, thanks for that, mate, Thanks mate,