1
00:00:00,320 --> 00:00:03,400
Speaker 1: He's over, says he threw his shoulder, well vacuuming.

2
00:00:03,440 --> 00:00:04,520
Speaker 2: What a pussy Rover is?

3
00:00:04,600 --> 00:00:08,200
Speaker 3: When it turns out he was from Carryuji for years.

4
00:00:08,280 --> 00:00:09,120
Speaker 4: Why am I on the show?

5
00:00:09,160 --> 00:00:09,320
Speaker 5: Then?

6
00:00:10,600 --> 00:00:10,799
Speaker 1: Yeah?

7
00:00:10,920 --> 00:00:15,920
Speaker 2: Back Rover's money glory. Chezy is coming up in just

8
00:00:15,960 --> 00:00:17,560
Speaker 2: a few minutes. What do you have on the way? Dog?

9
00:00:18,079 --> 00:00:22,560
Speaker 5: If you have a kid or a grandkid that loves

10
00:00:22,640 --> 00:00:28,840
Speaker 5: pepper Pig snits? Yeah, yeah, huge, righte a pig? My daughter,

11
00:00:29,200 --> 00:00:34,320
Speaker 5: she loves Pepper Pig. They are revealing something. And I

12
00:00:34,440 --> 00:00:35,800
Speaker 5: had no idea.

13
00:00:35,680 --> 00:00:37,960
Speaker 2: That Peppa is transgender.

14
00:00:38,120 --> 00:00:41,360
Speaker 4: No, but they they're revealing something something.

15
00:00:41,520 --> 00:00:44,280
Speaker 2: Okay, yes, all right, we'll get to that in just

16
00:00:44,320 --> 00:00:44,720
Speaker 2: a moment.

17
00:00:44,880 --> 00:00:45,800
Speaker 4: Jeffrey will like it.

18
00:00:48,400 --> 00:00:50,479
Speaker 2: Jeffery, you said that I was going to ask you

19
00:00:50,520 --> 00:00:52,680
Speaker 2: what you're doing over the weekend, which I normally do

20
00:00:52,760 --> 00:00:56,040
Speaker 2: when we wrap up the Friday leftovers. You already had

21
00:00:56,040 --> 00:00:58,160
Speaker 2: an answer prepared. What are you What are you going

22
00:00:58,240 --> 00:00:58,960
Speaker 2: to do this weekend?

23
00:01:01,160 --> 00:01:04,320
Speaker 3: Got my dental appointment tomorrow? Yeah, tomorrow morning. What are

24
00:01:04,319 --> 00:01:08,520
Speaker 3: you doing in your dentist appointment? Cleaning?

25
00:01:08,640 --> 00:01:08,840
Speaker 4: Yeah?

26
00:01:08,880 --> 00:01:11,600
Speaker 2: Okay, and we're.

27
00:01:11,400 --> 00:01:13,440
Speaker 3: Gonna check out if if I'm not in a whole

28
00:01:13,440 --> 00:01:15,520
Speaker 3: lot of pain, which I shouldn't be. We're gonna check

29
00:01:15,520 --> 00:01:17,600
Speaker 3: out the Home and Garden show, all right? And then

30
00:01:17,640 --> 00:01:19,880
Speaker 3: what are you doing for the When are you doing that?

31
00:01:19,959 --> 00:01:20,319
Speaker 1: What day?

32
00:01:20,840 --> 00:01:23,479
Speaker 2: Saturday? Yes, Saturdays? All I got on Saturday? You doing Sunday?

33
00:01:23,480 --> 00:01:27,000
Speaker 2: You got your Puper Bowl party on Sunday? No, there's

34
00:01:27,000 --> 00:01:29,039
Speaker 2: no party going to have, no party happening, my friend.

35
00:01:29,160 --> 00:01:32,920
Speaker 2: What are you planning to do on Sunday? Nothing? Really?

36
00:01:32,959 --> 00:01:35,000
Speaker 3: I mean just probably with the way the weather from

37
00:01:35,120 --> 00:01:37,360
Speaker 3: what the weather I've read the weather forecast this morning,

38
00:01:38,040 --> 00:01:39,880
Speaker 3: it's gonna be barely cold.

39
00:01:39,920 --> 00:01:42,360
Speaker 2: I might just hunker down. You're gonna watch the game.

40
00:01:42,600 --> 00:01:45,720
Speaker 2: You don't have TV, I can always keep tracking it

41
00:01:45,760 --> 00:01:46,280
Speaker 2: on the internet.

42
00:01:47,400 --> 00:01:49,360
Speaker 4: You'll be fine. Sunday's gonna be fine. No snow.

43
00:01:50,600 --> 00:01:52,640
Speaker 2: Maybe I'll ask my father in law if he wants

44
00:01:52,680 --> 00:01:55,360
Speaker 2: to have Jeffrey over, Jeffrey in the family over for

45
00:01:55,400 --> 00:01:57,800
Speaker 2: a Super Bowl party that he throws every year. You

46
00:01:57,800 --> 00:01:58,280
Speaker 2: want to do that?

47
00:01:59,560 --> 00:01:59,760
Speaker 5: Yeah?

48
00:01:59,880 --> 00:02:02,440
Speaker 2: I think my wife might be interested in mediare and lost.

49
00:02:02,520 --> 00:02:04,720
Speaker 2: Oh okay, all right, I'll ask me talk to him.

50
00:02:05,120 --> 00:02:05,560
Speaker 4: That'd be fun.

51
00:02:05,640 --> 00:02:07,800
Speaker 2: See him later today. All right, Ducie, are you ready

52
00:02:07,800 --> 00:02:12,400
Speaker 2: for the shusy? Here we go, zy rollers morning, glory.

53
00:02:12,720 --> 00:02:16,320
Speaker 2: A car crashed into a grocery store. Three people were

54
00:02:16,400 --> 00:02:19,480
Speaker 2: killed and two others critically injured after the car crashed

55
00:02:19,840 --> 00:02:23,240
Speaker 2: in Los Angeles yesterday. Please say, a woman driving a

56
00:02:23,400 --> 00:02:27,560
Speaker 2: Toyota Prius hit a bicyclist, then lost control and plowed

57
00:02:27,639 --> 00:02:29,720
Speaker 2: into a ninety nine ranch market.

58
00:02:30,160 --> 00:02:31,520
Speaker 4: This was in the Westwood area.

59
00:02:31,639 --> 00:02:34,080
Speaker 5: The three victims, a fifty five year old man, a

60
00:02:34,120 --> 00:02:36,160
Speaker 5: thirty year old man, and a forty two year old woman,

61
00:02:36,560 --> 00:02:40,200
Speaker 5: were in the store's bakery section. The driver was about

62
00:02:40,280 --> 00:02:43,040
Speaker 5: seventy years old. Was speaking with officers after the crash

63
00:02:43,080 --> 00:02:44,520
Speaker 5: and declined medical treatment.

64
00:02:45,000 --> 00:02:47,799
Speaker 2: Police kind, I feel bad for the lady, like I mean,

65
00:02:47,840 --> 00:02:50,000
Speaker 2: I feel bad for the people who were killed too.

66
00:02:50,080 --> 00:02:52,280
Speaker 2: I mean, what terrible You're just in the grocery store,

67
00:02:52,440 --> 00:02:56,960
Speaker 2: minded year own business, shopping and then a car plows

68
00:02:57,040 --> 00:02:58,960
Speaker 2: right through if it doesn't give you any time to react,

69
00:02:59,040 --> 00:03:03,040
Speaker 2: kills you. But poor little old lady, I'm sure had

70
00:03:03,120 --> 00:03:06,080
Speaker 2: no intention of doing that. And I don't know. Do

71
00:03:06,120 --> 00:03:08,359
Speaker 2: you think that they should cut your get rid of

72
00:03:08,440 --> 00:03:11,080
Speaker 2: your driver's license, taken away at a certain age. It's

73
00:03:11,200 --> 00:03:15,080
Speaker 2: lady seventy, should she still be driving? Yearly? Test? Think so?

74
00:03:15,200 --> 00:03:19,440
Speaker 2: Once you over the age of what maybe seventy. I

75
00:03:19,480 --> 00:03:23,360
Speaker 2: think this is like, wait a second, I don't want

76
00:03:23,400 --> 00:03:25,360
Speaker 2: to say fifty five. Don't want to say sixty because

77
00:03:25,360 --> 00:03:27,680
Speaker 2: that's right around the corner. How old are you United States?

78
00:03:27,919 --> 00:03:30,080
Speaker 2: Fifty seven? Fifty seven? All right, so yeah, he doesn't

79
00:03:30,080 --> 00:03:31,120
Speaker 2: want to say start at sixty.

80
00:03:31,280 --> 00:03:34,680
Speaker 4: Now. Yeah, but my mom was driving without a driver's license.

81
00:03:34,800 --> 00:03:36,600
Speaker 2: What do you mean without a driver's license?

82
00:03:37,920 --> 00:03:41,000
Speaker 5: Your driver's license is expired. I'm not going to go

83
00:03:41,040 --> 00:03:43,720
Speaker 5: in and get it, like once you get old, you're

84
00:03:43,760 --> 00:03:47,680
Speaker 5: not gonna You really think they're going to go yearly.

85
00:03:47,600 --> 00:03:50,840
Speaker 2: Get tested, because then if they get pulled over, they

86
00:03:51,000 --> 00:03:53,120
Speaker 2: wouldn't they just impound your car or something?

87
00:03:53,720 --> 00:03:55,760
Speaker 4: Yeah, I mean maybe they don't know.

88
00:03:56,280 --> 00:03:59,040
Speaker 2: So your mother she just liked you. Wonder where dog

89
00:03:59,040 --> 00:04:02,280
Speaker 2: she gets her person from? I'm very nice, that's exactly.

90
00:04:02,840 --> 00:04:05,760
Speaker 2: You got all of this behavior from your mother. I'm

91
00:04:05,760 --> 00:04:07,320
Speaker 2: not gonna I'm not going to get my wife.

92
00:04:07,320 --> 00:04:08,280
Speaker 4: I'm not listening to you.

93
00:04:08,520 --> 00:04:11,720
Speaker 2: I'm not gonna read what you can't make me stop driving. Well,

94
00:04:11,720 --> 00:04:13,760
Speaker 2: at least we know where Dougi gets the stubborness from us?

95
00:04:13,760 --> 00:04:15,480
Speaker 2: Her mom. Do you think you got you think she

96
00:04:15,560 --> 00:04:20,280
Speaker 2: got those behaviors from her mother. Interesting. All right, you see.

97
00:04:20,200 --> 00:04:23,279
Speaker 3: Here, duji, I'm just stating the facts here. Don't don't

98
00:04:23,279 --> 00:04:24,440
Speaker 3: get your panties in a bunch.

99
00:04:24,600 --> 00:04:25,840
Speaker 4: My panties are in a bunch.

100
00:04:26,800 --> 00:04:32,520
Speaker 3: But sometimes you know, you said your mother is is stubborn. Yeah, stubborn,

101
00:04:32,520 --> 00:04:34,479
Speaker 3: old Italian woman, you know. I mean that's the things

102
00:04:34,480 --> 00:04:36,640
Speaker 3: you gets it from her mom. Yeah, there you go.

103
00:04:36,760 --> 00:04:39,839
Speaker 3: He runs into stubborness, runs into family. My wife could

104
00:04:39,839 --> 00:04:41,560
Speaker 3: be stubborn too, and she's Irish.

105
00:04:41,760 --> 00:04:42,680
Speaker 4: Okay.

106
00:04:43,640 --> 00:04:43,719
Speaker 3: Uh.

107
00:04:43,839 --> 00:04:49,240
Speaker 5: The President Trump administration they launched trump RX prescription drug

108
00:04:49,279 --> 00:04:53,240
Speaker 5: website last night. They're offering discounted prices and dozens of

109
00:04:53,320 --> 00:04:57,680
Speaker 5: medications the siteless drugs from major companies like Pfizer and

110
00:04:58,320 --> 00:05:01,880
Speaker 5: Novo Nordisk, including weight as drugs, Ozembic and we Goovy.

111
00:05:02,360 --> 00:05:04,680
Speaker 5: A four week supply of we Govy is priced at

112
00:05:04,680 --> 00:05:07,440
Speaker 5: one ninety nine for the first two months, well below

113
00:05:07,480 --> 00:05:10,240
Speaker 5: the list price of over thirteen hundred dollars.

114
00:05:10,520 --> 00:05:13,480
Speaker 4: You can print coupons to use that d Where is this?

115
00:05:13,560 --> 00:05:14,760
Speaker 2: What's this website?

116
00:05:15,320 --> 00:05:16,560
Speaker 4: Trump rx?

117
00:05:16,720 --> 00:05:20,720
Speaker 2: Trump rx dot com dot gov dot gov dot gov. Okay,

118
00:05:21,600 --> 00:05:25,200
Speaker 2: so that's good. He's obsessed with naming things after himself.

119
00:05:25,200 --> 00:05:26,159
Speaker 2: The Kennedy Center.

120
00:05:26,320 --> 00:05:30,000
Speaker 4: Oh, that's funny you bring that RX. That's really weird

121
00:05:30,000 --> 00:05:30,960
Speaker 4: that you brought that up.

122
00:05:31,320 --> 00:05:34,440
Speaker 5: There is a report that Trump has offered Senate Minority

123
00:05:34,520 --> 00:05:37,840
Speaker 5: Leader Chuck Schumer a deal to release billions of dollars

124
00:05:37,839 --> 00:05:40,839
Speaker 5: in already approved money for a New York Reil tunnel

125
00:05:40,880 --> 00:05:44,200
Speaker 5: project h on the condition his name is put on

126
00:05:44,279 --> 00:05:49,360
Speaker 5: two key travel hugs. According to multiple reports, Trump offered

127
00:05:49,400 --> 00:05:53,200
Speaker 5: to release the sixteen billion dollars in funding for the

128
00:05:53,279 --> 00:06:00,680
Speaker 5: Hudson River Gateway Tunnel if Dully duelists airport dollars dollars airport.

129
00:06:01,120 --> 00:06:03,400
Speaker 2: I got the dullard talking about Dulles.

130
00:06:03,440 --> 00:06:07,640
Speaker 5: Pallas Airport outside of Washington and Penn Station in Manhattan.

131
00:06:07,920 --> 00:06:12,360
Speaker 5: If those two hubs were named after a so so.

132
00:06:12,480 --> 00:06:15,960
Speaker 2: Penn Station would become Trump Station, yes, and Dulles would

133
00:06:16,000 --> 00:06:17,839
Speaker 2: become Trump International Airport.

134
00:06:17,960 --> 00:06:18,159
Speaker 6: Yes.

135
00:06:18,200 --> 00:06:24,320
Speaker 2: I see, Hey, he really is stuff.

136
00:06:24,440 --> 00:06:27,880
Speaker 4: Yeah, we've got Washington, what is it, the Kennedy.

137
00:06:27,520 --> 00:06:29,719
Speaker 2: Center, Yeah, the Trump Trump Kennedy Center.

138
00:06:29,960 --> 00:06:33,400
Speaker 4: Yeah. And Schumer, I believe quickly.

139
00:06:33,560 --> 00:06:38,239
Speaker 2: Somebody that says, Rover, what about Obamacare? Well, if you recall,

140
00:06:38,440 --> 00:06:41,479
Speaker 2: I hope people aren't. I guess they just the brain

141
00:06:41,600 --> 00:06:45,440
Speaker 2: stopped working after a while, but that was not Obama

142
00:06:45,480 --> 00:06:49,360
Speaker 2: didn't call it Obamacare. It was the Affordable Care Act

143
00:06:49,720 --> 00:06:54,200
Speaker 2: who called it Obamacare. Trump. Now, all the Republicans called

144
00:06:54,200 --> 00:06:56,760
Speaker 2: it Obamacare because they they thought it was gonna They

145
00:06:56,760 --> 00:06:59,920
Speaker 2: thought it would be a wait around him, like, oh,

146
00:07:00,000 --> 00:07:02,760
Speaker 2: we're gonna we're gonna tie you all this to Obama

147
00:07:03,200 --> 00:07:05,800
Speaker 2: and people are gonna hate this. Then they actually liked

148
00:07:05,839 --> 00:07:08,680
Speaker 2: Obamacare and they turned out, Yeah, and now it's known

149
00:07:08,720 --> 00:07:10,880
Speaker 2: as Obamacare. He didn't start that. He didn't I have

150
00:07:10,920 --> 00:07:11,920
Speaker 2: a healthcare.

151
00:07:11,600 --> 00:07:15,920
Speaker 3: Republicans started it because, you know, because.

152
00:07:15,680 --> 00:07:16,600
Speaker 2: He attended to it.

153
00:07:16,760 --> 00:07:20,320
Speaker 4: Yeah, go on this, what's going on with Bitcoin?

154
00:07:20,680 --> 00:07:22,320
Speaker 2: I think he might be listening to the show and

155
00:07:22,360 --> 00:07:25,160
Speaker 2: delay in there so when I say things, he's not.

156
00:07:25,360 --> 00:07:28,000
Speaker 2: He's hearing it forty seconds later in there, so he's

157
00:07:28,040 --> 00:07:31,000
Speaker 2: actually jumping in before he actually hears it. That's the

158
00:07:31,040 --> 00:07:34,200
Speaker 2: only explanation I have for this. No, I was gonna.

159
00:07:34,200 --> 00:07:37,280
Speaker 3: I was trying to reiterate that the Affordable Character was

160
00:07:37,360 --> 00:07:40,600
Speaker 3: passed with no Republican, with all Democrat.

161
00:07:40,240 --> 00:07:41,400
Speaker 2: Votes that got that passed.

162
00:07:41,640 --> 00:07:44,520
Speaker 3: So that's why the Republicans referred to it as Obamacare.

163
00:07:45,000 --> 00:07:49,040
Speaker 3: So if if it's say, if it fails, the Republicans

164
00:07:49,120 --> 00:07:52,560
Speaker 3: can squarely you put the blame on President Obama himself.

165
00:07:53,000 --> 00:07:56,440
Speaker 2: Yeah, this is anthony. Like you guys are delusional. It

166
00:07:56,520 --> 00:08:01,520
Speaker 2: was not called Obamacare by Obama, You clown. Anyway, go on.

167
00:08:01,600 --> 00:08:05,880
Speaker 5: This bitcoin price plunged sharply yesterday, dropping to sixty thousand

168
00:08:05,960 --> 00:08:08,760
Speaker 5: dollars after week of heavy losses that have wiped out

169
00:08:08,800 --> 00:08:11,040
Speaker 5: about one third of its value since the year began.

170
00:08:11,640 --> 00:08:13,960
Speaker 5: The slide extends a broader downturn that has seen the

171
00:08:14,000 --> 00:08:17,160
Speaker 5: digital asset lose nearly half of its value from late

172
00:08:17,240 --> 00:08:22,080
Speaker 5: twenty twenty five. Peaks might have to buy some bitcoin?

173
00:08:23,120 --> 00:08:26,880
Speaker 2: Are the dip? Now, snitch somebody I don't know the

174
00:08:26,880 --> 00:08:29,680
Speaker 2: guy's name, but he was texting or email as you're

175
00:08:29,680 --> 00:08:33,800
Speaker 2: going to say, is idiots? He warned you? He said, Oh,

176
00:08:33,920 --> 00:08:36,640
Speaker 2: he's not an idiot, but yeah, he warned you. He

177
00:08:36,720 --> 00:08:38,040
Speaker 2: said get out of bitcoin.

178
00:08:38,120 --> 00:08:38,360
Speaker 5: Now.

179
00:08:38,440 --> 00:08:41,960
Speaker 2: I'm telling Snitzer, I've warned Snitzer. He will not listen

180
00:08:42,000 --> 00:08:46,439
Speaker 2: to me. Are you not taking advice from our great

181
00:08:46,480 --> 00:08:49,199
Speaker 2: fans who are very knowledgeable in the crypto market, Snitz?

182
00:08:49,240 --> 00:08:52,960
Speaker 2: Are you still buying? Buying? Buying your a Bitcoin is plumbing?

183
00:08:53,000 --> 00:08:55,360
Speaker 2: What's your game plan? It's up six thousand today, but

184
00:08:57,200 --> 00:08:58,880
Speaker 2: I'd still buy cares.

185
00:08:59,120 --> 00:09:03,280
Speaker 7: Who cares saying that it's a certain person who's Satoshi,

186
00:09:03,360 --> 00:09:06,760
Speaker 7: the creator of bitcoin. They're saying that, Oh, Jeffrey Epstein, Yeah,

187
00:09:06,880 --> 00:09:10,480
Speaker 7: that's yes, Jeffrey Epstein was the creator of bitcoin.

188
00:09:10,960 --> 00:09:11,520
Speaker 4: I did know that.

189
00:09:11,600 --> 00:09:14,120
Speaker 2: Jeffrey Epstein, who if you read any of those emails,

190
00:09:14,160 --> 00:09:16,200
Speaker 2: this guy can barely spell. I don't know how this

191
00:09:16,320 --> 00:09:18,800
Speaker 2: guy made all his money because he's dumb. Oh my god,

192
00:09:19,880 --> 00:09:24,920
Speaker 2: oh dumb, dumb, dumb. Huh yeah, but yeah, yeah, he

193
00:09:25,000 --> 00:09:30,480
Speaker 2: created bitcoin. That proof. Yeah, that's really ridiculous. All right.

194
00:09:30,520 --> 00:09:34,520
Speaker 5: Today is Friday, and the Winter Olympics opening ceremony will

195
00:09:34,520 --> 00:09:35,680
Speaker 5: be live from Italy.

196
00:09:35,760 --> 00:09:37,600
Speaker 4: You can watch all of it live two.

197
00:09:37,400 --> 00:09:42,080
Speaker 5: Pm Eastern, and you can also wait to watch the

198
00:09:42,160 --> 00:09:44,560
Speaker 5: replay at a pm tonight.

199
00:09:45,000 --> 00:09:48,120
Speaker 4: NBC will hope. NBC will host live.

200
00:09:47,960 --> 00:09:51,200
Speaker 5: Coverage of the games throughout the weekend, including primetime coverage

201
00:09:51,240 --> 00:09:53,640
Speaker 5: each night. So again, if you want to wait till tonight,

202
00:09:53,679 --> 00:09:55,520
Speaker 5: it's eight pm. If you want to watch it live

203
00:09:55,559 --> 00:09:59,600
Speaker 5: as it happens, it's two pm Eastern today and then

204
00:09:59,640 --> 00:10:04,520
Speaker 5: of course Sunday six pm Eastern on NBC Super bowls sixty.

205
00:10:05,120 --> 00:10:06,960
Speaker 2: Kay I was just reading the Olympics start tonight.

206
00:10:08,559 --> 00:10:09,000
Speaker 4: They do.

207
00:10:09,160 --> 00:10:12,440
Speaker 2: Yeah, what time? I think APM? Wow?

208
00:10:12,920 --> 00:10:14,960
Speaker 4: Is that live at APM?

209
00:10:15,280 --> 00:10:15,599
Speaker 2: I don't know.

210
00:10:15,640 --> 00:10:20,080
Speaker 7: I wasn't listening only just to half the story.

211
00:10:21,720 --> 00:10:26,800
Speaker 4: Can you play crickets? He has no idea what's going

212
00:10:26,800 --> 00:10:29,040
Speaker 4: on because he's doing sound effects. He has no idea.

213
00:10:29,640 --> 00:10:32,760
Speaker 5: All right, how much would the Olympic medals be worth

214
00:10:33,360 --> 00:10:36,160
Speaker 5: if you melted them down and sold them from scrap?

215
00:10:36,200 --> 00:10:37,480
Speaker 4: Have they gone up or down?

216
00:10:37,679 --> 00:10:37,920
Speaker 3: Down?

217
00:10:37,960 --> 00:10:40,720
Speaker 2: I'll bet they're almost worthless. I'll bet they're worth less

218
00:10:40,720 --> 00:10:41,920
Speaker 2: than fifty dollars apiece.

219
00:10:42,400 --> 00:10:44,960
Speaker 4: Gold and silver prices are through the roof, you know,

220
00:10:45,200 --> 00:10:46,079
Speaker 4: yeah that was true?

221
00:10:46,200 --> 00:10:48,920
Speaker 2: Yeah, yeah, but I think they use very very little

222
00:10:49,000 --> 00:10:50,800
Speaker 2: actual gold and silver and things.

223
00:10:50,840 --> 00:10:54,400
Speaker 5: I bet bronze medals five dollars and sixty cents.

224
00:10:54,400 --> 00:10:56,479
Speaker 4: They're actually made of copper, notut bronze.

225
00:10:56,960 --> 00:11:00,200
Speaker 5: It's worth way less than silver and gold silver for

226
00:11:01,400 --> 00:11:02,520
Speaker 5: fourteen dollars.

227
00:11:02,920 --> 00:11:04,280
Speaker 2: Wow o kidding yep.

228
00:11:04,280 --> 00:11:06,600
Speaker 5: Silver prices have dropped back down a little bit, but

229
00:11:06,640 --> 00:11:08,679
Speaker 5: they hit an all time high last week, and then

230
00:11:08,720 --> 00:11:12,640
Speaker 5: the gold medals twenty three hundred dollars each. They'd be

231
00:11:12,720 --> 00:11:16,199
Speaker 5: worth more if they were solid gold.

232
00:11:16,400 --> 00:11:19,200
Speaker 2: Just at the half fin ounce, right and that's a

233
00:11:19,200 --> 00:11:19,680
Speaker 2: lot of gold.

234
00:11:19,760 --> 00:11:24,720
Speaker 5: Yeah, just the outer later outer layer is gold and

235
00:11:24,760 --> 00:11:25,480
Speaker 5: the rest is silver.

236
00:11:26,520 --> 00:11:26,960
Speaker 2: All right.

237
00:11:28,040 --> 00:11:29,040
Speaker 4: Pepa Pig story.

238
00:11:29,559 --> 00:11:34,360
Speaker 5: Yeah, Peppa Pigs new season on Nickelodeon returns in March,

239
00:11:34,520 --> 00:11:37,480
Speaker 5: and they're introducing a deaf character for the first time

240
00:11:37,480 --> 00:11:40,440
Speaker 5: in the show's history. Hasbro, the company behind the show,

241
00:11:40,559 --> 00:11:44,719
Speaker 5: shared that Peppa's younger brother, George, will be revealed as

242
00:11:44,760 --> 00:11:46,360
Speaker 5: being moderately deaf.

243
00:11:47,320 --> 00:11:49,360
Speaker 4: What you can only hear in one air.

244
00:11:49,280 --> 00:11:51,640
Speaker 2: Jeffrey, Wow, it's heavy.

245
00:11:51,840 --> 00:11:53,680
Speaker 4: Maybe they're taking this character after.

246
00:11:53,520 --> 00:11:57,760
Speaker 2: You because I've never heard of that show until you've

247
00:11:57,760 --> 00:12:03,559
Speaker 2: brought it up. He's got older kids, he doesn't. Yeah,

248
00:12:03,720 --> 00:12:08,319
Speaker 2: they are both pigs though, what this character is that

249
00:12:08,400 --> 00:12:08,760
Speaker 2: a pig?

250
00:12:09,400 --> 00:12:11,280
Speaker 4: Yeah, they're filthy.

251
00:12:12,160 --> 00:12:15,120
Speaker 6: George gets in mud one day and he really gets dirty.

252
00:12:16,120 --> 00:12:20,920
Speaker 2: He loves slopping around the puddles. Go on, dush, that's it.

253
00:12:21,600 --> 00:12:23,600
Speaker 4: That's the shizy on Rovers Morning Glory.

254
00:12:24,640 --> 00:12:28,360
Speaker 2: So much good you'll want to bend over and kiss

255
00:12:28,440 --> 00:12:32,800
Speaker 2: our ass. Watch live right there on your stupid smart boat.

256
00:12:32,960 --> 00:12:35,800
Speaker 2: Just search for Rovers Morning Glory in the App Store

257
00:12:36,040 --> 00:12:49,160
Speaker 2: or Google Play. There's somebody that says, look at the

258
00:12:49,280 --> 00:12:51,840
Speaker 2: history of bitcoin. It does this every three or four years.

259
00:12:53,040 --> 00:12:54,880
Speaker 2: There's no rhyme or reason any of this stuff. Like

260
00:12:54,960 --> 00:12:58,199
Speaker 2: this guy who was complaining about stincer, I've warned him

261
00:12:58,559 --> 00:13:01,000
Speaker 2: it's going to fifty fourth. How are you going to

262
00:13:01,760 --> 00:13:05,559
Speaker 2: this all made up stuff? There's there's no actual It

263
00:13:05,679 --> 00:13:08,760
Speaker 2: is completely made up. It does do a huge dip

264
00:13:08,800 --> 00:13:13,880
Speaker 2: every four years ish, but it's not really timed. So

265
00:13:14,280 --> 00:13:16,599
Speaker 2: are you buying now your your goal is now that

266
00:13:16,720 --> 00:13:19,559
Speaker 2: the price is so much less, are you just putting

267
00:13:19,640 --> 00:13:21,360
Speaker 2: even more money into bitcoin?

268
00:13:21,840 --> 00:13:21,880
Speaker 5: No?

269
00:13:22,920 --> 00:13:30,559
Speaker 2: Just the same amount. Okay. Somebody says gold and silver plummeted.

270
00:13:30,920 --> 00:13:33,640
Speaker 2: I did it because I heard gold and silver were

271
00:13:33,679 --> 00:13:36,000
Speaker 2: at all time highs at least in the past week

272
00:13:36,120 --> 00:13:37,839
Speaker 2: or something. I mean, you say plummeted. I don't know

273
00:13:37,960 --> 00:13:41,839
Speaker 2: what that what that means. It's at four nine hundred

274
00:13:41,840 --> 00:13:45,400
Speaker 2: and sixteen dollars right now. I have a listener pretty

275
00:13:45,480 --> 00:13:49,680
Speaker 2: much near the all time high, which tried something.

276
00:13:49,960 --> 00:13:54,199
Speaker 5: Yeah, there's a listener who I believe went to a

277
00:13:54,320 --> 00:13:58,800
Speaker 5: circle k and gave Charlie and crystal silver medallions.

278
00:13:58,920 --> 00:14:00,800
Speaker 4: Uh huh, I don't know if it was silver dollars.

279
00:14:00,920 --> 00:14:02,920
Speaker 2: And then he came I wanted him back.

280
00:14:03,160 --> 00:14:06,520
Speaker 4: No, he came to me one day out in the

281
00:14:06,760 --> 00:14:09,120
Speaker 4: in the when I was doing, when I was working,

282
00:14:09,240 --> 00:14:11,080
Speaker 4: and gave me maybe.

283
00:14:10,880 --> 00:14:15,040
Speaker 5: Two or three silver medallions, not one for Rover because

284
00:14:15,040 --> 00:14:16,400
Speaker 5: he's like, Rover's got enough money?

285
00:14:16,720 --> 00:14:17,720
Speaker 4: Do you have one? Snitz?

286
00:14:17,960 --> 00:14:20,960
Speaker 5: I don't do not, Okay, So it's for Dougie Snitzer

287
00:14:21,040 --> 00:14:23,280
Speaker 5: and Jeffrey and I believe you already have one.

288
00:14:23,720 --> 00:14:26,920
Speaker 4: Yeah, so Charlie, Crystal or set. So yeah, he's awesome.

289
00:14:26,960 --> 00:14:30,240
Speaker 6: He sends emails about silver and all the time, like

290
00:14:30,440 --> 00:14:33,040
Speaker 6: buy silver. You guys are crazy. It just keeps going up.

291
00:14:33,120 --> 00:14:36,280
Speaker 6: I don't know why you guys aren't listening by the show.

292
00:14:36,800 --> 00:14:39,440
Speaker 2: But people will say that, oh, it just keeps going up.

293
00:14:39,440 --> 00:14:41,440
Speaker 2: But it's going to go down. I mean, all right,

294
00:14:41,640 --> 00:14:43,840
Speaker 2: but it's been going up. I'm like, this guy is right,

295
00:14:43,920 --> 00:14:44,880
Speaker 2: I see it going on.

296
00:14:45,320 --> 00:14:48,480
Speaker 4: Or to even buy silver Cosca.

297
00:14:50,280 --> 00:14:50,320
Speaker 5: Not?

298
00:14:50,600 --> 00:14:53,040
Speaker 2: Yeah, they have gold bars. He did that story in

299
00:14:53,120 --> 00:14:53,480
Speaker 2: the news.

300
00:14:54,720 --> 00:14:57,760
Speaker 4: That was a while. But platinum there everything, everything, And

301
00:14:57,840 --> 00:14:59,360
Speaker 4: then where do you take it to cash it in?

302
00:15:00,960 --> 00:15:02,760
Speaker 2: You don't you bury it in your backyard?

303
00:15:03,400 --> 00:15:04,400
Speaker 4: No, like where do you take it?

304
00:15:04,960 --> 00:15:11,880
Speaker 2: I don't know, out of where? And you get.

305
00:15:13,240 --> 00:15:16,600
Speaker 4: It I don't know the bank, I don't know, Like

306
00:15:17,960 --> 00:15:18,400
Speaker 4: there's a.

307
00:15:20,320 --> 00:15:23,080
Speaker 2: Story that you know, people get really worked up over

308
00:15:23,200 --> 00:15:25,000
Speaker 2: things here in the United States and they're like, oh,

309
00:15:25,080 --> 00:15:26,920
Speaker 2: it's so bad, and we got to do this, and

310
00:15:27,000 --> 00:15:28,720
Speaker 2: we've got to do that. And look at the way

311
00:15:29,000 --> 00:15:32,040
Speaker 2: that this this group is treated and women are treated,

312
00:15:32,160 --> 00:15:35,160
Speaker 2: and then the and oh the government and all this,

313
00:15:35,360 --> 00:15:37,320
Speaker 2: and you know, you know how people are, They're always

314
00:15:38,440 --> 00:15:42,400
Speaker 2: always bitching a moment about something. And I was reading

315
00:15:42,480 --> 00:15:45,440
Speaker 2: this that happened like a week or two ago in Indonesia.

316
00:15:46,960 --> 00:15:52,840
Speaker 2: Think about this. A woman and her her boyfriend were

317
00:15:53,520 --> 00:15:59,400
Speaker 2: lashed publicly flogged with a bamboo cane one hundred and

318
00:15:59,520 --> 00:16:05,320
Speaker 2: forty times each. Why they had sex outside of marriage.

319
00:16:05,840 --> 00:16:09,240
Speaker 2: Can you believe it? These people they had sex outside

320
00:16:09,280 --> 00:16:13,800
Speaker 2: of marriage Indonesia, Indonesia. They're under Sharia law in this

321
00:16:14,080 --> 00:16:18,240
Speaker 2: part of Indonesia. So they gave each this woman and

322
00:16:18,320 --> 00:16:23,480
Speaker 2: the man one hundred and forty lashes each out the

323
00:16:24,040 --> 00:16:27,400
Speaker 2: premarital sex was only one hundred lashes. They got the

324
00:16:27,480 --> 00:16:33,040
Speaker 2: other forty because they dared to drink alcohol, and alcohol

325
00:16:33,320 --> 00:16:37,720
Speaker 2: is outlawed in this region of Indonesia where Sharia law,

326
00:16:37,800 --> 00:16:41,800
Speaker 2: the Islamic law, is the way of the land there,

327
00:16:42,320 --> 00:16:45,040
Speaker 2: so they got one hundred and forty. One hundred and forty.

328
00:16:45,120 --> 00:16:47,360
Speaker 2: This is not like a tap with these things. By

329
00:16:47,440 --> 00:16:52,400
Speaker 2: the way, one hundred and forty lashes with a bamboo

330
00:16:52,800 --> 00:16:55,600
Speaker 2: cane stick. Whatever this thing is, I mean it is

331
00:16:56,600 --> 00:16:59,480
Speaker 2: They say it's ratan. I guess I don't know is

332
00:16:59,520 --> 00:17:01,440
Speaker 2: that what is that? Is that bamboo or I don't

333
00:17:01,440 --> 00:17:04,840
Speaker 2: know what britann is. It's like wicker. Wow, maybe has more?

334
00:17:04,920 --> 00:17:07,760
Speaker 2: Give Jackson hurt, I feel like more. You really are

335
00:17:07,800 --> 00:17:08,840
Speaker 2: getting whipped with that.

336
00:17:09,160 --> 00:17:09,360
Speaker 1: Yeah.

337
00:17:11,119 --> 00:17:14,479
Speaker 2: The woman sobbed and collapsed as she was getting struck.

338
00:17:15,680 --> 00:17:18,600
Speaker 2: They were only two out of the many people that

339
00:17:18,680 --> 00:17:22,760
Speaker 2: were there getting flogged publicly as part of this ceremony.

340
00:17:23,359 --> 00:17:25,040
Speaker 2: I mean, this is really They have to take them

341
00:17:25,080 --> 00:17:27,080
Speaker 2: away in an ambulance afterwards.

342
00:17:28,480 --> 00:17:28,760
Speaker 1: I mean.

343
00:17:29,280 --> 00:17:33,359
Speaker 2: And so my point was this, you want to complain

344
00:17:33,440 --> 00:17:35,760
Speaker 2: about things, to talk about how bad things are. Just

345
00:17:35,840 --> 00:17:41,080
Speaker 2: imagine for one second that if you had pre marital sex,

346
00:17:41,240 --> 00:17:45,159
Speaker 2: we rounded you up, took you to public square and

347
00:17:45,920 --> 00:17:48,000
Speaker 2: beat you one hundred and forty times with a cane,

348
00:17:50,320 --> 00:17:53,000
Speaker 2: so you don't have it so bad. Here's the woman

349
00:17:53,040 --> 00:17:57,200
Speaker 2: getting whacked. They got it. They have somebody almost like

350
00:17:57,240 --> 00:18:02,000
Speaker 2: in an executioner's mask. They have this person caning this woman.

351
00:18:02,880 --> 00:18:05,720
Speaker 2: There was another there. Here she is, she's crying, of course.

352
00:18:07,200 --> 00:18:09,160
Speaker 2: I mean you should see their back after they Here's

353
00:18:09,200 --> 00:18:12,000
Speaker 2: the guy. He just got whacked by the executioner right

354
00:18:12,040 --> 00:18:14,760
Speaker 2: in the back. You know how bad this hurts you?

355
00:18:14,920 --> 00:18:16,920
Speaker 2: Always wearing his shirt. It's not even his bare back.

356
00:18:17,280 --> 00:18:20,760
Speaker 2: Oh my god, their back, I'll bet is torn up.

357
00:18:21,000 --> 00:18:23,040
Speaker 2: They're gonna be scarred for the rest of their lives

358
00:18:23,160 --> 00:18:27,360
Speaker 2: after this. They weren't the only people that were flogged

359
00:18:27,480 --> 00:18:33,000
Speaker 2: that day. There was a Sharia police officer, which I

360
00:18:33,040 --> 00:18:34,760
Speaker 2: guess is a guy who goes around and forcing the

361
00:18:34,840 --> 00:18:40,159
Speaker 2: Sharia law. The Sharia police officer and his female partner,

362
00:18:42,320 --> 00:18:45,359
Speaker 2: they had to be flogged because they were accused of

363
00:18:45,520 --> 00:18:50,800
Speaker 2: being in close proximity to each other in a private place,

364
00:18:51,040 --> 00:18:54,000
Speaker 2: which also is illegal under Sharia law. So they got

365
00:18:54,560 --> 00:18:59,360
Speaker 2: just twenty three strikes from the Ratan king and they say,

366
00:18:59,400 --> 00:19:02,359
Speaker 2: we make no exceptions even for our own members. You know,

367
00:19:02,560 --> 00:19:05,960
Speaker 2: you're too close to a woman, you get in close proximity.

368
00:19:06,200 --> 00:19:07,880
Speaker 2: I don't know how close that is, where you can't

369
00:19:07,880 --> 00:19:10,879
Speaker 2: be within arm's length or something, or a football field.

370
00:19:10,920 --> 00:19:15,080
Speaker 2: I don't know what their rule is, but so I

371
00:19:15,280 --> 00:19:18,880
Speaker 2: just you know, people think and complain about how bad

372
00:19:18,960 --> 00:19:21,480
Speaker 2: things are here. Now, things are not perfect, look at

373
00:19:21,560 --> 00:19:24,280
Speaker 2: improve things. There's nothing wrong with that. But you have

374
00:19:24,359 --> 00:19:28,000
Speaker 2: to put this into perspective about how bad other places

375
00:19:28,080 --> 00:19:31,840
Speaker 2: in the world are and all your perceived slights and

376
00:19:32,520 --> 00:19:34,159
Speaker 2: this and that and the other, like this is like

377
00:19:34,240 --> 00:19:37,119
Speaker 2: this wacko yesterday we talked about at the on the

378
00:19:37,200 --> 00:19:40,320
Speaker 2: school board who was upset that somebody had the gall

379
00:19:40,560 --> 00:19:44,040
Speaker 2: to use the word homeless instead of unhoused. And she

380
00:19:44,160 --> 00:19:46,159
Speaker 2: went on and on and on and on about this.

381
00:19:47,000 --> 00:19:50,119
Speaker 2: That's that is your level of concern. That's what you

382
00:19:50,200 --> 00:19:53,200
Speaker 2: have time to be worried about. Look what happened, Look

383
00:19:53,280 --> 00:19:54,440
Speaker 2: what's going on around the world.

384
00:19:55,000 --> 00:19:57,200
Speaker 3: Yeah, look at North Korea, for example, you say something

385
00:19:57,240 --> 00:20:01,720
Speaker 3: bad about your leader, you're executed instant or for a

386
00:20:01,800 --> 00:20:04,520
Speaker 3: lesser offences. They put you in what's called a well

387
00:20:04,560 --> 00:20:06,920
Speaker 3: it's a labor camp, but they like to call it

388
00:20:07,160 --> 00:20:10,680
Speaker 3: a re education camp. Same thing like in other parts

389
00:20:10,680 --> 00:20:16,200
Speaker 3: of the world or in other authoritarian countries. Take yeah,

390
00:20:16,320 --> 00:20:20,000
Speaker 3: so like take Russia, China, and Iran, they're all autocracies.

391
00:20:20,440 --> 00:20:24,800
Speaker 3: Well in this autocracies, uh huh. Or take Iran or

392
00:20:24,840 --> 00:20:26,720
Speaker 3: that part of Indonesia, you were just talking about. It

393
00:20:26,760 --> 00:20:35,119
Speaker 3: would be called a theocracy. We're religion ecocracy, Okay, yes, theocracy.

394
00:20:35,600 --> 00:20:38,720
Speaker 3: It means that religion is just as much as influenced

395
00:20:38,760 --> 00:20:42,120
Speaker 3: in the government as the government has in the religion,

396
00:20:42,200 --> 00:20:46,000
Speaker 3: so they're correlated together. Make Jenkeson's where tan is bamboo.

397
00:20:46,119 --> 00:20:49,120
Speaker 3: It splits while you're beating someone with it. It basically

398
00:20:49,280 --> 00:20:53,760
Speaker 3: turns into razor blades and turns your flesh into ground beef.

399
00:20:54,720 --> 00:20:57,239
Speaker 3: I've seen pictures of people after they were flogged. There

400
00:20:57,320 --> 00:20:58,800
Speaker 3: was somebody when I was a little kid, there was

401
00:20:59,240 --> 00:21:04,320
Speaker 3: a famous I don't remember exactly, there was a public

402
00:21:04,480 --> 00:21:07,879
Speaker 3: flogging that took place somewhere, don't even remember where, but

403
00:21:07,960 --> 00:21:09,360
Speaker 3: it was a big deal. It was in the news

404
00:21:09,400 --> 00:21:11,359
Speaker 3: because they're like, I can't believe they're going to flog

405
00:21:11,520 --> 00:21:14,160
Speaker 3: this person. Maybe it was like an American or something

406
00:21:14,240 --> 00:21:16,439
Speaker 3: that went over to a foreign country and did something

407
00:21:16,520 --> 00:21:19,520
Speaker 3: and people were outraged that there was going to be

408
00:21:19,560 --> 00:21:20,600
Speaker 3: this public flogging.

409
00:21:20,680 --> 00:21:24,320
Speaker 2: Do you remember the snitz I mean for the posters

410
00:21:24,359 --> 00:21:27,400
Speaker 2: stealing that one? No, no way before that I'm talking about.

411
00:21:27,440 --> 00:21:29,280
Speaker 2: You would have been like you probably would have been

412
00:21:29,320 --> 00:21:31,560
Speaker 2: about fifteen years old or something at the time when

413
00:21:31,600 --> 00:21:35,000
Speaker 2: this happened, but somebody and it was a big thing,

414
00:21:35,080 --> 00:21:38,520
Speaker 2: and it was nobody had ever really heard of flogging.

415
00:21:38,600 --> 00:21:41,119
Speaker 2: What do you mean? What is that? And some country

416
00:21:41,160 --> 00:21:43,560
Speaker 2: and they were flogging, must have been an American or something.

417
00:21:44,720 --> 00:21:46,840
Speaker 2: And there were pictures that had come out of people

418
00:21:46,920 --> 00:21:52,240
Speaker 2: after they were flogged, and oh my god, man, you

419
00:21:52,400 --> 00:21:54,560
Speaker 2: just go, oh, you're getting almost like spanked or something.

420
00:21:54,600 --> 00:21:57,760
Speaker 2: It's what you think now, Absolutely not. It is unreal

421
00:21:58,320 --> 00:22:01,080
Speaker 2: how bad it tears you up? If they have double jeopardy.

422
00:22:01,200 --> 00:22:04,040
Speaker 6: So if you have this premarital sex, let's say you're

423
00:22:04,119 --> 00:22:06,320
Speaker 6: you're in love, in love with this person, you guys

424
00:22:06,480 --> 00:22:09,360
Speaker 6: sneak off, you have the sex, Now, will.

425
00:22:09,200 --> 00:22:10,560
Speaker 2: You get in trouble again?

426
00:22:10,640 --> 00:22:13,119
Speaker 4: If somebody said I saw them again together.

427
00:22:13,119 --> 00:22:16,280
Speaker 2: Or have you served something, something tells me that they're

428
00:22:16,359 --> 00:22:20,440
Speaker 2: probably not too probably de lenient. Yeah, if you get

429
00:22:20,520 --> 00:22:22,280
Speaker 2: caught again, yeah, I don't think they go, oh, we

430
00:22:22,400 --> 00:22:24,240
Speaker 2: flogged you one hundred and forty times, not go back

431
00:22:24,280 --> 00:22:26,560
Speaker 2: to banging each other. I don't know. I don't think

432
00:22:26,640 --> 00:22:30,400
Speaker 2: that's what they're Can I say I've got it more

433
00:22:31,040 --> 00:22:31,879
Speaker 2: more flogs?

434
00:22:31,960 --> 00:22:32,160
Speaker 1: Yeah?

435
00:22:32,400 --> 00:22:35,720
Speaker 2: Two hundred and eighty. You're gonna double your flogging next time?

436
00:22:36,680 --> 00:22:38,280
Speaker 2: That probably be enough to kill somebody.

437
00:22:40,680 --> 00:22:43,320
Speaker 3: Lashes perfect, you know, per person.

438
00:22:43,440 --> 00:22:46,840
Speaker 2: Yeah, that could be almost enough to kill somebody. People

439
00:22:46,880 --> 00:22:48,720
Speaker 2: I guess are remembering this. It was.

440
00:22:51,880 --> 00:22:52,440
Speaker 1: Where was it?

441
00:22:52,640 --> 00:22:55,440
Speaker 2: This guy says it was in Singapore. A US citizen

442
00:22:55,920 --> 00:22:59,840
Speaker 2: Michael Fay or Faye, vandalized a bunch of cars, and

443
00:23:00,320 --> 00:23:03,760
Speaker 2: Rob says, I remember that the US government negotiated down

444
00:23:03,880 --> 00:23:06,360
Speaker 2: the number of lashings that he was going to get.

445
00:23:07,280 --> 00:23:09,560
Speaker 2: Chrissy says he spit gum on the ground. He was

446
00:23:09,560 --> 00:23:12,159
Speaker 2: an American, That's why he got flogged. I don't know,

447
00:23:12,280 --> 00:23:14,080
Speaker 2: but I just remember there was something like that, and

448
00:23:14,200 --> 00:23:16,960
Speaker 2: it was never heard of it before. I've got to

449
00:23:17,000 --> 00:23:19,000
Speaker 2: take a break. We'll be right back on Rover's Morning Glory.

450
00:23:19,119 --> 00:23:20,440
Speaker 2: Hang on, chit few.

451
00:23:21,040 --> 00:23:23,200
Speaker 4: Craigage is a year round problem.

452
00:23:23,320 --> 00:23:27,359
Speaker 2: My penis is quite small. Welcome back to rovers Morning Glory.

453
00:23:39,359 --> 00:23:41,400
Speaker 2: Somebody said that that guy who was caned, I guess

454
00:23:41,600 --> 00:23:43,879
Speaker 2: it was in nineteen ninety four. The guy's name was

455
00:23:43,920 --> 00:23:48,200
Speaker 2: Michael Fay. They said he's from Erie, Pennsylvania. Really he

456
00:23:48,920 --> 00:23:51,040
Speaker 2: vantilized some cars over there and then he came back.

457
00:23:51,080 --> 00:23:53,399
Speaker 2: And this person says he was arrested for doing the

458
00:23:53,440 --> 00:23:55,600
Speaker 2: same thing once he got back to America.

459
00:23:56,400 --> 00:23:56,879
Speaker 1: And I.

460
00:23:58,400 --> 00:24:01,879
Speaker 2: Was looking this up. I don't know if he got

461
00:24:01,920 --> 00:24:04,440
Speaker 2: a resident for that. But after he returned to the

462
00:24:04,560 --> 00:24:06,720
Speaker 2: United States, he was caned. They were going to cane

463
00:24:06,800 --> 00:24:10,359
Speaker 2: him six times in nineteen ninety four. No, no, not Garie, idiot.

464
00:24:11,320 --> 00:24:13,600
Speaker 2: And when it is the last time you saw somebody

465
00:24:13,640 --> 00:24:17,400
Speaker 2: get caned here, that's how I was like. Here in Singapore,

466
00:24:17,760 --> 00:24:21,879
Speaker 2: he vandalized some cars and he was a teenager, and

467
00:24:21,960 --> 00:24:26,119
Speaker 2: they said six lashes. But then the American Government's like,

468
00:24:26,200 --> 00:24:29,920
Speaker 2: that's ridiculous, just give them four. They negotiated it down

469
00:24:29,960 --> 00:24:31,639
Speaker 2: to four lashes.

470
00:24:31,440 --> 00:24:32,360
Speaker 4: Or how about one?

471
00:24:32,800 --> 00:24:35,480
Speaker 2: How about zero? But I mean, come on, I don't know.

472
00:24:35,520 --> 00:24:37,719
Speaker 2: I'd be mad if he was vandalizing my car too,

473
00:24:37,800 --> 00:24:41,120
Speaker 2: I suppose, right, Yeah, I look at them a little

474
00:24:41,119 --> 00:24:45,159
Speaker 2: bit differently because there was it says he was stealing

475
00:24:45,280 --> 00:24:49,320
Speaker 2: street signs and vandalizing cars, like spray painting cars and

476
00:24:49,440 --> 00:24:54,720
Speaker 2: smashing cars windshields. The lady who got caned one hundred

477
00:24:54,760 --> 00:24:59,000
Speaker 2: and forty times in Indonesia, all she did was have

478
00:24:59,119 --> 00:25:03,440
Speaker 2: sex with her boyfriend and drink alcohol. Forty lashes for

479
00:25:03,520 --> 00:25:06,280
Speaker 2: drinking alcohol, one hundred for having sex outside of marriage.

480
00:25:06,600 --> 00:25:11,360
Speaker 2: That's a victimless crime. So that's that's crazy. The six

481
00:25:11,560 --> 00:25:15,240
Speaker 2: lashes for vandalizing. There was something like eighty cars or

482
00:25:15,320 --> 00:25:20,520
Speaker 2: something like that were vandalized. To me, I'm like, maybe

483
00:25:20,560 --> 00:25:21,920
Speaker 2: they Maybe that's not so bad.

484
00:25:23,359 --> 00:25:26,000
Speaker 3: Robert if Ducie said something about it, asked if I

485
00:25:26,240 --> 00:25:27,080
Speaker 3: think I was cane here?

486
00:25:27,320 --> 00:25:30,080
Speaker 2: Ad No, he was cane there in Singapore. If that

487
00:25:30,200 --> 00:25:31,480
Speaker 2: was to have been done here, that would have been

488
00:25:31,480 --> 00:25:32,439
Speaker 2: a violation at the eighth.

489
00:25:32,280 --> 00:25:34,480
Speaker 3: Minute of the United States constitusen stating against cruel and

490
00:25:34,560 --> 00:25:35,400
Speaker 3: unusual punishment.

491
00:25:36,160 --> 00:25:36,360
Speaker 1: Wow.

492
00:25:37,240 --> 00:25:43,000
Speaker 2: He came back and he was He suffered burns to

493
00:25:43,119 --> 00:25:47,320
Speaker 2: his hands and his face after a buttane incident, and

494
00:25:47,440 --> 00:25:49,600
Speaker 2: then he was admitted to the Betty Ford Center for

495
00:25:50,040 --> 00:25:51,400
Speaker 2: butane Abuse.

496
00:25:51,800 --> 00:25:51,960
Speaker 4: Oh.

497
00:25:52,440 --> 00:25:55,800
Speaker 2: He said that sniffing butane made him forget what happened

498
00:25:55,840 --> 00:25:59,600
Speaker 2: in Singapore. Oh, those four lashes, I mean, this is insane.

499
00:26:00,680 --> 00:26:03,320
Speaker 2: That doesn't lead you to buttane sniffing. Oh, I gotta

500
00:26:03,400 --> 00:26:06,159
Speaker 2: forget those four lashes I got in Singapore after I

501
00:26:06,960 --> 00:26:09,840
Speaker 2: after I stole those signs and vandalized those cars. Oh,

502
00:26:09,880 --> 00:26:14,400
Speaker 2: boo hoo. I've never heard of somebody sniffing but tane.

503
00:26:15,640 --> 00:26:17,040
Speaker 2: How do you get addicted to that? How do you

504
00:26:17,080 --> 00:26:20,720
Speaker 2: even start doing that. Who's like, who suggests to you

505
00:26:20,800 --> 00:26:22,440
Speaker 2: when you're a kid, Hey, you know what we should do?

506
00:26:22,480 --> 00:26:26,720
Speaker 2: We should get some buttane and Friday night. Yeah what Yeah,

507
00:26:26,840 --> 00:26:33,359
Speaker 2: Usually it's glue rubber cement. He was arrested later in

508
00:26:33,480 --> 00:26:35,879
Speaker 2: Florida a couple of years after that for possession of

509
00:26:35,920 --> 00:26:43,439
Speaker 2: marijuana and drug paraphernalia and something else for reckless driving.

510
00:26:43,480 --> 00:26:45,639
Speaker 2: Blah blah blah blah blah. I don't know whatever happened

511
00:26:45,640 --> 00:26:49,080
Speaker 2: to the guy, but that was a big story when

512
00:26:49,119 --> 00:26:55,880
Speaker 2: I was a kid. There's a well, the stock market

513
00:26:55,880 --> 00:26:57,680
Speaker 2: has been going a little bit crazy recently.

514
00:26:58,640 --> 00:26:59,800
Speaker 4: Have you checked it for one case?

515
00:26:59,880 --> 00:27:05,040
Speaker 2: I have not. Now what's happened is technology stocks took

516
00:27:05,080 --> 00:27:07,840
Speaker 2: a dump. A lot of technology stocks took a dump

517
00:27:08,160 --> 00:27:10,800
Speaker 2: in the past day or two, and it was because

518
00:27:11,000 --> 00:27:15,160
Speaker 2: of AI. All these software companies have lost a bunch

519
00:27:15,200 --> 00:27:18,560
Speaker 2: of value because they're worried. People are worried. Investors are

520
00:27:18,600 --> 00:27:22,360
Speaker 2: worried that they'll have no value. People won't need these

521
00:27:22,480 --> 00:27:26,480
Speaker 2: companies anymore because AI will be doing everything that the

522
00:27:26,560 --> 00:27:29,320
Speaker 2: software does. So if you have a company that makes

523
00:27:29,400 --> 00:27:33,359
Speaker 2: software or a platform software as a service and people

524
00:27:33,400 --> 00:27:36,639
Speaker 2: are using that for salesforce is a big one. But

525
00:27:37,680 --> 00:27:41,160
Speaker 2: there's all sorts of different things that, you know, different products.

526
00:27:41,960 --> 00:27:44,840
Speaker 2: I see them. I don't know what we work day?

527
00:27:45,000 --> 00:27:46,720
Speaker 2: Isn't that like an employee?

528
00:27:47,080 --> 00:27:47,639
Speaker 1: Yeah? What is that?

529
00:27:47,760 --> 00:27:48,080
Speaker 2: I don't know.

530
00:27:48,200 --> 00:27:49,840
Speaker 4: You never go into work day here.

531
00:27:50,800 --> 00:27:53,359
Speaker 2: It's too much. I can't get into it. It's they

532
00:27:53,400 --> 00:27:55,720
Speaker 2: make you jump through hoops to log into work Day.

533
00:27:55,760 --> 00:27:58,159
Speaker 2: You got to put in fifty two different codes, and

534
00:27:58,880 --> 00:28:00,760
Speaker 2: and then every time I I tried to log in,

535
00:28:00,880 --> 00:28:02,760
Speaker 2: it goes, oh it's been thirty days. You need to

536
00:28:02,840 --> 00:28:05,320
Speaker 2: change your password. Oh my god, can't I just keep

537
00:28:05,359 --> 00:28:08,359
Speaker 2: the same password. It's a hassle. So I try not

538
00:28:08,440 --> 00:28:12,040
Speaker 2: to log into work Day. But I guess people are

539
00:28:12,080 --> 00:28:14,360
Speaker 2: worried that these software companies are going to be replaced

540
00:28:14,359 --> 00:28:17,879
Speaker 2: by AI. And I know that Anthropic, which is an

541
00:28:17,880 --> 00:28:21,160
Speaker 2: AI company, they came out with something called Clawed Cowork,

542
00:28:21,520 --> 00:28:26,280
Speaker 2: which is AI agents that have access to all of

543
00:28:26,400 --> 00:28:30,080
Speaker 2: your They have connectors and plugins that accesses all of

544
00:28:30,160 --> 00:28:33,680
Speaker 2: your stuff on your network and on your computer. It

545
00:28:33,760 --> 00:28:36,840
Speaker 2: will read your documents for you and you can just

546
00:28:36,920 --> 00:28:39,480
Speaker 2: deploy these AI agents. Let's say you work in a

547
00:28:39,560 --> 00:28:44,240
Speaker 2: law firm, for instance, and there's companies that have products

548
00:28:45,400 --> 00:28:48,280
Speaker 2: software that is designed to be used by law firms,

549
00:28:49,000 --> 00:28:51,280
Speaker 2: and they charge big bucks for this software. Well, now

550
00:28:51,360 --> 00:28:56,440
Speaker 2: these AI agents are just doing everything that the software does.

551
00:28:57,280 --> 00:28:59,640
Speaker 2: You don't have to pay for the software anymore. So

552
00:28:59,680 --> 00:29:02,680
Speaker 2: the agents, which are a lot cheaper to operate. Not

553
00:29:02,800 --> 00:29:04,880
Speaker 2: only does it replace the software, but guess what it

554
00:29:04,960 --> 00:29:12,000
Speaker 2: replaces the people who use the software. So all these

555
00:29:12,040 --> 00:29:14,760
Speaker 2: software companies are in the toilet over the past couple

556
00:29:14,800 --> 00:29:15,160
Speaker 2: of days.

557
00:29:15,200 --> 00:29:17,680
Speaker 4: I mean, we're It's scary, isn't it.

558
00:29:18,440 --> 00:29:20,440
Speaker 2: I don't know, man, I don't know what's going to happen,

559
00:29:20,520 --> 00:29:25,560
Speaker 2: because I just saw this thing where this guy was talking.

560
00:29:25,640 --> 00:29:28,240
Speaker 2: He has a company and they had I think, like

561
00:29:28,360 --> 00:29:31,480
Speaker 2: ten salespeople. Now you look out here, I don't know

562
00:29:31,520 --> 00:29:34,080
Speaker 2: how many salespeople we have at iHeart, and you go out.

563
00:29:34,120 --> 00:29:36,440
Speaker 2: They're not going to replace our sales people with AI.

564
00:29:37,160 --> 00:29:41,239
Speaker 2: This company replaced all their salespeople with AI. How they

565
00:29:41,400 --> 00:29:46,120
Speaker 2: train these AI agents and they're closing deals they're doing

566
00:29:46,320 --> 00:29:48,840
Speaker 2: The guy was saying that that the AI agents, like

567
00:29:48,920 --> 00:29:52,720
Speaker 2: within a week of deploying them, close the seventy thousand

568
00:29:52,720 --> 00:29:53,200
Speaker 2: dollars deal.

569
00:29:53,680 --> 00:29:56,880
Speaker 4: There's no way AI could do what our salespeople do.

570
00:29:57,760 --> 00:29:58,440
Speaker 4: There's no way.

571
00:29:58,680 --> 00:30:02,880
Speaker 2: It's about you say that now, but you're completely wrong. Absolutely.

572
00:30:03,360 --> 00:30:06,200
Speaker 2: Here's what IT does do. Let's say you have a

573
00:30:07,320 --> 00:30:11,320
Speaker 2: you have salespeople out here, and they go, hey, kind

574
00:30:11,360 --> 00:30:13,280
Speaker 2: of the lower on the total poll you are as

575
00:30:13,320 --> 00:30:17,600
Speaker 2: a salesperson, they give you the worst leads. The higher

576
00:30:17,680 --> 00:30:20,160
Speaker 2: up you are, the more successful you are, you have

577
00:30:20,280 --> 00:30:24,360
Speaker 2: the better clients, the better leads. So anyways, the AI,

578
00:30:24,800 --> 00:30:28,760
Speaker 2: it will just say, oh, I can contact a thousand

579
00:30:28,800 --> 00:30:31,520
Speaker 2: people all at once. I can communicate with a thousand

580
00:30:31,520 --> 00:30:34,440
Speaker 2: people all at once, unlike a salesperson who gets their

581
00:30:34,520 --> 00:30:37,520
Speaker 2: list and they go, let's see that one. I don't know,

582
00:30:39,160 --> 00:30:42,040
Speaker 2: and they never stop. They work twenty four hours a day,

583
00:30:42,760 --> 00:30:46,600
Speaker 2: seven days a week. And this guy replaced all of

584
00:30:46,720 --> 00:30:48,680
Speaker 2: these salespeople in his company with AI.

585
00:30:49,960 --> 00:30:50,600
Speaker 4: What's the product?

586
00:30:50,600 --> 00:30:55,920
Speaker 2: They're selling events, so sponsorship at events, they do live events,

587
00:30:57,320 --> 00:31:01,160
Speaker 2: conferences and things, and so they're selling. They're selling all

588
00:31:01,280 --> 00:31:04,400
Speaker 2: sorts of stuff. And he said that he will never

589
00:31:04,560 --> 00:31:08,480
Speaker 2: hire another human being to do that ever again. He said,

590
00:31:08,560 --> 00:31:12,560
Speaker 2: if I could, if I could find a good human being,

591
00:31:12,880 --> 00:31:15,800
Speaker 2: I'll hire them. But good luck to you. He said

592
00:31:15,800 --> 00:31:18,120
Speaker 2: that all my salespeople, they'll work there for a year

593
00:31:18,120 --> 00:31:18,640
Speaker 2: and then they quit.

594
00:31:18,800 --> 00:31:22,120
Speaker 5: What company would buy from AI and not a physical person.

595
00:31:22,480 --> 00:31:25,800
Speaker 5: The relationships that you have with a client I know

596
00:31:25,920 --> 00:31:30,880
Speaker 5: from myself, like I know my client loves me. And

597
00:31:31,120 --> 00:31:35,000
Speaker 5: if if it's an AI buughy just calling saying hey,

598
00:31:35,560 --> 00:31:38,920
Speaker 5: you want to buy some advertising? Okay, I think that

599
00:31:39,160 --> 00:31:41,600
Speaker 5: I'm more personable than an AI, don't you.

600
00:31:43,320 --> 00:31:48,000
Speaker 4: For this product? We're selling personalities, we're selling music.

601
00:31:48,200 --> 00:31:50,640
Speaker 2: How do you well it might be AI on the

602
00:31:50,680 --> 00:31:54,640
Speaker 2: other end. Also, Yeah, that person who's buying it, they're

603
00:31:54,640 --> 00:31:56,880
Speaker 2: going to be replaced and they're gonna they're going to

604
00:31:56,920 --> 00:31:59,880
Speaker 2: train an AI agent to say, hey, look at all

605
00:32:00,120 --> 00:32:04,080
Speaker 2: of the opportunities. Here's our budget for advertising, and you

606
00:32:04,240 --> 00:32:08,880
Speaker 2: need to don't go with gut because you like Dougey.

607
00:32:09,200 --> 00:32:11,920
Speaker 2: You have to go with the most effective use of

608
00:32:12,040 --> 00:32:14,800
Speaker 2: our capital and what's going to get us the best

609
00:32:14,880 --> 00:32:17,960
Speaker 2: return on investment, who has the best ratings for the

610
00:32:18,040 --> 00:32:20,880
Speaker 2: lowest price point, so on and so forth. So you're

611
00:32:20,880 --> 00:32:22,600
Speaker 2: not even going to be dealing with a person, because

612
00:32:22,600 --> 00:32:25,320
Speaker 2: that's going to be AI robot on the other end.

613
00:32:26,960 --> 00:32:30,360
Speaker 2: It's going to get crazy here real fast, like real crazy.

614
00:32:30,360 --> 00:32:32,320
Speaker 2: I don't think people understand what's about ready to hit

615
00:32:33,560 --> 00:32:37,240
Speaker 2: your job is unless you're a plumber or an electrician.

616
00:32:37,320 --> 00:32:42,760
Speaker 2: Your job is on the chopping block. And I'm telling

617
00:32:42,840 --> 00:32:46,480
Speaker 2: you right now, these companies they don't. They would love

618
00:32:46,560 --> 00:32:48,560
Speaker 2: to get rid of you. They want to get rid

619
00:32:48,600 --> 00:32:51,520
Speaker 2: of You're a hassle to the company you works. Yes,

620
00:32:51,600 --> 00:32:54,440
Speaker 2: you are. All employees are hassles to the companies that

621
00:32:54,520 --> 00:32:56,880
Speaker 2: they work for, and they are going to be it

622
00:32:57,040 --> 00:32:59,880
Speaker 2: used to be when they're like these companies, the software

623
00:33:00,000 --> 00:33:02,000
Speaker 2: companies and stuff, they go, hey, we have this product

624
00:33:02,320 --> 00:33:04,720
Speaker 2: and it's gonna make your workers so much more effective.

625
00:33:04,760 --> 00:33:06,400
Speaker 2: You're they're gonna be able to get so much done.

626
00:33:06,600 --> 00:33:09,000
Speaker 2: That's not how they sell stuff now. The way they

627
00:33:09,040 --> 00:33:13,400
Speaker 2: sell stuff now is, hey we have this AI. You

628
00:33:13,480 --> 00:33:17,640
Speaker 2: can get rid of twenty employees. You can get rid

629
00:33:17,680 --> 00:33:20,640
Speaker 2: of people. That's how they sell stuff now. And that's

630
00:33:20,640 --> 00:33:23,000
Speaker 2: what these companies are responding to. And it's gonna get

631
00:33:23,120 --> 00:33:28,600
Speaker 2: It's gonna get absolutely wild. Snencer, are you concerned about

632
00:33:29,920 --> 00:33:32,680
Speaker 2: AI and the future of AI? You have kids, These

633
00:33:32,760 --> 00:33:37,000
Speaker 2: kids gotta you've got to have jobs. What do you

634
00:33:37,080 --> 00:33:41,240
Speaker 2: think of future holds? I mean, no, I'm not I'm

635
00:33:41,280 --> 00:33:44,360
Speaker 2: not worried. I'm not worried. I think you can't be.

636
00:33:44,680 --> 00:33:48,600
Speaker 7: You have tom one I mean, my son who's in

637
00:33:48,640 --> 00:33:52,320
Speaker 7: the Air Force, he works, uh with cyber crimes and

638
00:33:52,320 --> 00:33:54,440
Speaker 7: those kind of things. Anyways, he's in that field anyway,

639
00:33:54,480 --> 00:33:57,480
Speaker 7: so's he's dealing with, you know, computers and whatnot.

640
00:33:57,600 --> 00:33:59,800
Speaker 2: Yeah, but they'll just AI. They'll go, oh, we have

641
00:33:59,840 --> 00:34:02,960
Speaker 2: a twenty people that do this, and one AI can

642
00:34:03,280 --> 00:34:06,959
Speaker 2: sift through all this data. So they're going to redoced.

643
00:34:06,960 --> 00:34:11,600
Speaker 2: I mean, it's going to be absolutely insane. What's coming.

644
00:34:11,920 --> 00:34:16,160
Speaker 2: I mean, I just I'm expecting kind of the I'm

645
00:34:16,400 --> 00:34:17,480
Speaker 2: planning for the worst.

646
00:34:18,920 --> 00:34:20,600
Speaker 6: You don't have to run out of space or pay

647
00:34:20,680 --> 00:34:22,440
Speaker 6: for a space for your business because you don't need

648
00:34:22,520 --> 00:34:25,520
Speaker 6: to hire people to be in there selling your stuff, right,

649
00:34:25,600 --> 00:34:27,520
Speaker 6: you don't have to pay for health insurance for any

650
00:34:27,520 --> 00:34:29,239
Speaker 6: of your employees or anything like that.

651
00:34:30,000 --> 00:34:34,000
Speaker 2: So you almost save money. But the problem, the weird

652
00:34:34,160 --> 00:34:37,120
Speaker 2: aspect of this is so you save all this money,

653
00:34:37,160 --> 00:34:38,960
Speaker 2: you get rid of all the people. All those people

654
00:34:39,000 --> 00:34:40,480
Speaker 2: get laid off. And by the way, they just had

655
00:34:40,640 --> 00:34:44,719
Speaker 2: numbers released, it's the most layoffs in a single month

656
00:34:44,840 --> 00:34:48,840
Speaker 2: since what was it two thousand and nine or something,

657
00:34:49,400 --> 00:34:52,839
Speaker 2: one hundred and eight, one hundred some thousand people laid off,

658
00:34:53,680 --> 00:34:58,000
Speaker 2: Just five thousand people hired, so a minus of over

659
00:34:58,080 --> 00:35:02,120
Speaker 2: one hundred thousand jobs lost in the past month and

660
00:35:02,560 --> 00:35:06,640
Speaker 2: the number of job openings the windling. Nobody has job openings.

661
00:35:06,800 --> 00:35:10,040
Speaker 2: Nobody's hiring because they go well, eventually AI is going

662
00:35:10,080 --> 00:35:12,200
Speaker 2: to replace this person in six months or something. But

663
00:35:14,280 --> 00:35:17,840
Speaker 2: the interesting thing about what Chrystal just said is, so

664
00:35:17,960 --> 00:35:19,640
Speaker 2: you save all this money, you get rid of all

665
00:35:19,680 --> 00:35:23,440
Speaker 2: the people, But all those people that you fired are

666
00:35:23,520 --> 00:35:28,600
Speaker 2: consumers of various products and you're selling something. So whatever

667
00:35:28,680 --> 00:35:30,480
Speaker 2: it is you're selling that, you're making for a lot

668
00:35:30,560 --> 00:35:32,880
Speaker 2: less now, and it's easier because you have AI doing it.

669
00:35:33,080 --> 00:35:35,879
Speaker 2: Who's going to buy it? Because they've been fired from

670
00:35:35,920 --> 00:35:36,440
Speaker 2: their jobs?

671
00:35:36,520 --> 00:35:37,479
Speaker 4: Yeah, they have no money.

672
00:35:38,239 --> 00:35:41,240
Speaker 6: Ah, what's going to happen? Rich people and poor people,

673
00:35:42,160 --> 00:35:44,239
Speaker 6: that's all. There will be people who have a lot

674
00:35:44,320 --> 00:35:45,640
Speaker 6: of money and people who have nothing.

675
00:35:46,000 --> 00:35:51,000
Speaker 2: It's going to be Elon Musk's, Jeff Bezels people like that,

676
00:35:51,280 --> 00:35:55,439
Speaker 2: and then everybody else. But you said if nobody's buying

677
00:35:55,440 --> 00:35:59,680
Speaker 2: their stuff, they're not going to be rich. But they're

678
00:35:59,719 --> 00:36:04,160
Speaker 2: so deeply entrenched in you know, government and all sorts

679
00:36:04,200 --> 00:36:07,360
Speaker 2: of things, and I think those people are going to

680
00:36:07,400 --> 00:36:10,280
Speaker 2: be Okay, it's the rest of us that have something

681
00:36:10,320 --> 00:36:11,719
Speaker 2: to really worry about. Yeah.

682
00:36:12,280 --> 00:36:14,200
Speaker 6: Ever since I was growing up, the people always be like,

683
00:36:14,239 --> 00:36:17,040
Speaker 6: the middle class is going away, the middle class is going.

684
00:36:16,880 --> 00:36:18,759
Speaker 2: Away and actually going away.

685
00:36:18,880 --> 00:36:19,040
Speaker 1: Yeah.

686
00:36:19,040 --> 00:36:21,160
Speaker 6: I see it now as an adult and go, wow,

687
00:36:21,320 --> 00:36:23,520
Speaker 6: maybe what everybody was saying is true.

688
00:36:25,200 --> 00:36:31,359
Speaker 2: Yeah, here's someone I feel vending machines. Do you think

689
00:36:31,440 --> 00:36:35,680
Speaker 2: AI can do that too? No, not at the moment,

690
00:36:36,000 --> 00:36:39,560
Speaker 2: but eventually, I think things are going to really pick

691
00:36:39,680 --> 00:36:44,520
Speaker 2: up and pace and figure out. I think it's really

692
00:36:44,560 --> 00:36:47,960
Speaker 2: going to start accelerating what robots are doing. I just

693
00:36:48,000 --> 00:36:52,600
Speaker 2: got an email from Weamo and they go, they go, oh, hey,

694
00:36:52,719 --> 00:36:56,600
Speaker 2: by the way, you're in Miami. Not there right now,

695
00:36:56,680 --> 00:36:59,239
Speaker 2: but you're in Miami. You can start using Weamo. We've

696
00:37:00,000 --> 00:37:03,879
Speaker 2: expanded into Miami, so book your right in the app

697
00:37:03,960 --> 00:37:05,879
Speaker 2: right now. So if you're an Uber driver, your day's

698
00:37:05,880 --> 00:37:11,000
Speaker 2: are numbered. There are very few professions, that's very few

699
00:37:11,080 --> 00:37:14,800
Speaker 2: professions that are going to be unaffected by AI. And

700
00:37:14,880 --> 00:37:16,880
Speaker 2: I don't want to sound like a doomsday guy, but

701
00:37:18,320 --> 00:37:20,359
Speaker 2: I mean a lot of the AI stuff is cool.

702
00:37:20,400 --> 00:37:23,480
Speaker 2: It's real cool, but it's also kind of scary.

703
00:37:23,600 --> 00:37:23,719
Speaker 1: Now.

704
00:37:23,800 --> 00:37:29,279
Speaker 2: Maybe maybe you know I'm overthinking this. People, You know,

705
00:37:29,440 --> 00:37:32,040
Speaker 2: we kind of adapt humanity adapts or figure things out,

706
00:37:32,080 --> 00:37:35,399
Speaker 2: but this might be a little bit different. Somebody says

707
00:37:35,440 --> 00:37:39,279
Speaker 2: doing computer programming is already obsolete. Yeah. I used to

708
00:37:39,360 --> 00:37:42,160
Speaker 2: tell people, oh yeah, you got to get into programming.

709
00:37:42,280 --> 00:37:43,640
Speaker 2: You have to do this, you have to do that,

710
00:37:44,080 --> 00:37:47,319
Speaker 2: your job will be secure. Not anymore. Those jobs wiped out.

711
00:37:47,760 --> 00:37:51,680
Speaker 2: Vibe coding, yep. If you are a if you're a kid,

712
00:37:51,840 --> 00:37:54,400
Speaker 2: and you're going to college for that, you're wasting your

713
00:37:54,440 --> 00:37:58,680
Speaker 2: money because no company is going to hire a computer

714
00:37:58,760 --> 00:38:03,400
Speaker 2: programmer any or they might hire one instead of one hundred.

715
00:38:04,200 --> 00:38:08,000
Speaker 2: It's probably the profession with the worst prospects at this

716
00:38:08,120 --> 00:38:14,839
Speaker 2: point now. And the AI that's writing software is incredible.

717
00:38:15,800 --> 00:38:19,239
Speaker 2: I'm telling you I've used it, and it's what would

718
00:38:19,320 --> 00:38:24,799
Speaker 2: take somebody normally a week to do can be done

719
00:38:24,920 --> 00:38:29,800
Speaker 2: in ten minutes. It's that transformational. You can make almost

720
00:38:29,840 --> 00:38:36,320
Speaker 2: anything now. It's absolutely crazy. Our whole texting system was

721
00:38:36,320 --> 00:38:42,680
Speaker 2: built with AI. I just wrote some stuff I say

722
00:38:42,760 --> 00:38:46,680
Speaker 2: I wrote, I didn't even write it. Something for Chocolate

723
00:38:46,800 --> 00:38:49,279
Speaker 2: Charlie to use. Here a tool for him to use

724
00:38:49,400 --> 00:38:54,799
Speaker 2: on the show. It took me Saturday nights. Saturday nights tools.

725
00:38:54,800 --> 00:38:56,960
Speaker 2: Oh no, no, no, you don't plug this thing in

726
00:38:57,640 --> 00:39:07,320
Speaker 2: it's not a jackhammer. I'm sorry, I apologize. Defend yourself. No, no,

727
00:39:07,480 --> 00:39:15,839
Speaker 2: it's not the sperminator. No no, uh no, I made something.

728
00:39:15,840 --> 00:39:17,520
Speaker 2: It's something that he spends a lot of time on

729
00:39:17,920 --> 00:39:21,160
Speaker 2: and it's a very tedious task for him. And it

730
00:39:21,239 --> 00:39:25,120
Speaker 2: took me two days to develop something and it's it

731
00:39:25,239 --> 00:39:29,040
Speaker 2: works like a chant. It is I mean, I'm telling

732
00:39:29,080 --> 00:39:33,000
Speaker 2: you it is absolutely incredible. And AI for that for

733
00:39:33,160 --> 00:39:37,759
Speaker 2: writing software is perfect, is perfect for that because that's

734
00:39:37,800 --> 00:39:43,560
Speaker 2: a set of rules programming that it's just it is

735
00:39:43,719 --> 00:39:48,799
Speaker 2: or it isn't. It's you know, it's not as it's

736
00:39:48,880 --> 00:39:51,560
Speaker 2: not like other tasks that you can tell AI to do.

737
00:39:51,640 --> 00:39:53,320
Speaker 2: And you go, well, there's sort of a gray area.

738
00:39:53,520 --> 00:39:55,560
Speaker 2: You know, you got to make a judgment call on this.

739
00:39:55,719 --> 00:39:57,440
Speaker 2: Either that works or it doesn't work, or you know,

740
00:39:57,560 --> 00:40:04,520
Speaker 2: it's And there's a large a repository of information, open

741
00:40:04,560 --> 00:40:06,920
Speaker 2: source code that all this stuff has been trained on.

742
00:40:07,200 --> 00:40:10,040
Speaker 2: And so it's very very very smart when it comes

743
00:40:10,080 --> 00:40:12,000
Speaker 2: to coding, like incredibly smart.

744
00:40:12,560 --> 00:40:14,520
Speaker 6: But not pictures. I just try to jump on a

745
00:40:14,600 --> 00:40:17,680
Speaker 6: trend the other day. Make me, you know, look like

746
00:40:17,800 --> 00:40:20,279
Speaker 6: I'm at work and I work in radio, and you

747
00:40:20,360 --> 00:40:22,759
Speaker 6: give a couple of little descriptors, and it's gonna make

748
00:40:22,840 --> 00:40:26,359
Speaker 6: you a little a caricature of yourself. And I had

749
00:40:26,440 --> 00:40:29,239
Speaker 6: three hands, and I was everybody else that I've seen.

750
00:40:29,719 --> 00:40:32,960
Speaker 6: Theirs look great, but mine. I would even ask it

751
00:40:33,120 --> 00:40:36,239
Speaker 6: to remove one of the mugs of coffee in my

752
00:40:36,400 --> 00:40:39,719
Speaker 6: hand and it would still populate the same photo over

753
00:40:39,760 --> 00:40:40,200
Speaker 6: and over again.

754
00:40:40,239 --> 00:40:42,319
Speaker 2: I was like, it knows you better than you'd think.

755
00:40:42,680 --> 00:40:44,440
Speaker 2: It's like she needs three hands for all little hand

756
00:40:44,560 --> 00:40:54,640
Speaker 2: jobs that she's given. It knows my job. Yeah, it's

757
00:40:54,680 --> 00:40:58,120
Speaker 2: looked deep in your past. It goes ah, Okay, no,

758
00:40:58,320 --> 00:41:02,480
Speaker 2: I I don't know, but that's the stuff. Here's the

759
00:41:02,520 --> 00:41:05,080
Speaker 2: thing I heard somebody else. I heard Keith Kennedy talking

760
00:41:05,120 --> 00:41:07,640
Speaker 2: about exactly whatever you're talking about. I haven't seen this.

761
00:41:07,880 --> 00:41:11,200
Speaker 2: I don't get on with people that he was talking

762
00:41:11,239 --> 00:41:13,880
Speaker 2: about this. Oh yeah, I put I told AI to

763
00:41:14,000 --> 00:41:16,359
Speaker 2: make me this caricature, and it blah blah blah blah.

764
00:41:17,560 --> 00:41:21,080
Speaker 2: This is what this is why we're doomed. And no

765
00:41:21,200 --> 00:41:23,800
Speaker 2: offense to Crystal or Keith Kennedy, but these are the

766
00:41:23,920 --> 00:41:27,960
Speaker 2: moronic things that they're using AI for total waste of time.

767
00:41:28,680 --> 00:41:31,200
Speaker 2: These things are going to take your job. Period. We

768
00:41:31,320 --> 00:41:35,720
Speaker 2: got to start preparing for this. Use it secure cancer, yeah, something,

769
00:41:35,880 --> 00:41:43,360
Speaker 2: use it for something. It's something. Jeremy says. AI coding

770
00:41:43,920 --> 00:41:48,400
Speaker 2: is awful. It's made Windows unusable with every update. I

771
00:41:48,440 --> 00:41:50,000
Speaker 2: don't know about that, but I can just tell you

772
00:41:50,120 --> 00:41:53,400
Speaker 2: that the stuff that has been made that I personally

773
00:41:53,480 --> 00:41:58,600
Speaker 2: have had experiences with, I'm absolutely blown away by it.

774
00:41:59,080 --> 00:42:01,439
Speaker 2: I mean just I can on a scale of one

775
00:42:01,520 --> 00:42:02,680
Speaker 2: to one hundred, this is a.

776
00:42:04,239 --> 00:42:04,880
Speaker 4: It's one hundred.

777
00:42:05,120 --> 00:42:11,320
Speaker 2: That's how transformational it is. It's it's absolutely wild what

778
00:42:11,520 --> 00:42:14,040
Speaker 2: this stuff can do and what would take me. And

779
00:42:14,120 --> 00:42:16,320
Speaker 2: I'm not like a great code or number was like,

780
00:42:16,360 --> 00:42:19,520
Speaker 2: you know, that's not my profession or whatever, but what

781
00:42:19,680 --> 00:42:22,080
Speaker 2: would take I was working on something, and what would

782
00:42:22,080 --> 00:42:25,359
Speaker 2: take me like a couple of years ago, what would

783
00:42:25,440 --> 00:42:29,759
Speaker 2: take me might take me two months to do, you

784
00:42:29,880 --> 00:42:33,399
Speaker 2: can do in half a day with AI, no joke.

785
00:42:33,800 --> 00:42:40,520
Speaker 2: It's absolutely insane. Now, AI, as far as other things,

786
00:42:40,840 --> 00:42:43,920
Speaker 2: is still kind of stupid, but it's getting better and

787
00:42:44,000 --> 00:42:47,479
Speaker 2: better every time. And Jeffery yartt, what do you think about?

788
00:42:47,600 --> 00:42:49,960
Speaker 2: What does your brain think about any of this stuff?

789
00:42:50,040 --> 00:42:53,960
Speaker 2: Like big picture things like this, AI and machines heavy

790
00:42:54,360 --> 00:42:58,920
Speaker 2: all the talk of AI. It's like I'm just gonna

791
00:42:59,000 --> 00:43:02,120
Speaker 2: basically agree with you of what AI is going to do.

792
00:43:02,280 --> 00:43:05,000
Speaker 3: Sometimes it's good for something, but if it's gonna take over,

793
00:43:05,120 --> 00:43:08,439
Speaker 3: it's gonna put people out of work. People can't earn money,

794
00:43:08,760 --> 00:43:12,360
Speaker 3: they can't buy the product. It's gonna be a slippery slope.

795
00:43:12,400 --> 00:43:14,560
Speaker 3: And also at the same time, it's a chain reaction.

796
00:43:15,320 --> 00:43:15,719
Speaker 2: As to.

797
00:43:17,520 --> 00:43:20,960
Speaker 3: Mart's you said this before the march of technology, you're

798
00:43:21,040 --> 00:43:22,640
Speaker 3: not gonna be able to stop it or rain in

799
00:43:22,760 --> 00:43:22,960
Speaker 3: on it.

800
00:43:24,400 --> 00:43:27,120
Speaker 2: And if you got the next thing, you know, I

801
00:43:27,200 --> 00:43:28,760
Speaker 2: mean like as far back as.

802
00:43:28,800 --> 00:43:31,560
Speaker 3: Say the I wanna say, like maybe the late Sevans

803
00:43:31,600 --> 00:43:33,640
Speaker 3: going in the early eighties when auto plays started to

804
00:43:33,640 --> 00:43:37,480
Speaker 3: become automated with robots. You still need people to maintain

805
00:43:37,560 --> 00:43:40,000
Speaker 3: those robots to make sure that they're doing the job

806
00:43:40,080 --> 00:43:42,840
Speaker 3: correctly and that something doesn't go wrong. The ability to

807
00:43:42,960 --> 00:43:45,600
Speaker 3: have a human in there to make a repair or

808
00:43:45,680 --> 00:43:50,120
Speaker 3: something like that. Yeah, but it's insane the way I'm

809
00:43:50,160 --> 00:43:52,760
Speaker 3: just I'm just sitting here, you know, thinking about exactly

810
00:43:52,920 --> 00:43:55,680
Speaker 3: as you're talking. It's like we could be out of

811
00:43:55,719 --> 00:44:00,359
Speaker 3: work personality. I mean, you've talked about maybe AI taking

812
00:44:00,400 --> 00:44:02,640
Speaker 3: over the sales aren't because they get do the work

813
00:44:02,680 --> 00:44:04,920
Speaker 3: it could. AI could do the work faster.

814
00:44:04,760 --> 00:44:05,680
Speaker 2: Than what a human could do.

815
00:44:05,960 --> 00:44:09,200
Speaker 3: But what do you're saying is that you're missing the

816
00:44:09,400 --> 00:44:12,520
Speaker 3: human interaction with the salesperson and the client.

817
00:44:13,040 --> 00:44:15,719
Speaker 2: Well, we're once the technology gets there, and it's it's

818
00:44:15,800 --> 00:44:19,200
Speaker 2: not there yet. Like we've heard people have heard AI podcasts.

819
00:44:19,760 --> 00:44:23,120
Speaker 2: They're not great, but five years from now they might

820
00:44:23,200 --> 00:44:26,879
Speaker 2: be fantastic. Ten years from now, absolutely, And what they'll

821
00:44:26,920 --> 00:44:32,239
Speaker 2: do is they'll train AI. iHeart anybody. They'll train these

822
00:44:32,360 --> 00:44:36,600
Speaker 2: AI models on all of they think of the recorded

823
00:44:36,680 --> 00:44:39,040
Speaker 2: material they have of this show. For instance, they have

824
00:44:39,160 --> 00:44:41,800
Speaker 2: twenty three years of this show. They don't own it,

825
00:44:41,880 --> 00:44:46,120
Speaker 2: do they well that this was the last contract they did.

826
00:44:46,200 --> 00:44:49,400
Speaker 2: This was not a this was not a thing. Nobody

827
00:44:49,600 --> 00:44:51,880
Speaker 2: was doing this with AI. That's how recent all of

828
00:44:51,960 --> 00:44:54,120
Speaker 2: these developments are. I promise you if you tried to

829
00:44:54,200 --> 00:44:55,960
Speaker 2: do a contract with them today, they're going to go, oh,

830
00:44:56,000 --> 00:44:58,880
Speaker 2: we can, we can use your voice and your content

831
00:44:58,960 --> 00:45:01,920
Speaker 2: to train our AI models. It's it's it's gonna be

832
00:45:01,920 --> 00:45:04,560
Speaker 2: a thing. And so they have twenty three years of

833
00:45:04,680 --> 00:45:06,800
Speaker 2: material and they could just train and they could just

834
00:45:07,000 --> 00:45:09,600
Speaker 2: keep the show going in perpetuity without any of us,

835
00:45:10,840 --> 00:45:13,160
Speaker 2: and they would know exactly. They're like, we know what

836
00:45:13,239 --> 00:45:15,120
Speaker 2: do she would say when it comes to this, We

837
00:45:15,239 --> 00:45:19,879
Speaker 2: know what Jeffrey would would do in this particular instance. Chad,

838
00:45:19,920 --> 00:45:23,680
Speaker 2: you're on Rovery's moorn to Glory. You're morning Chad? Hey

839
00:45:24,040 --> 00:45:25,080
Speaker 2: you hey man, what's happening about?

840
00:45:26,719 --> 00:45:31,279
Speaker 1: Nothing? So I can't remember the exact timing that I

841
00:45:31,520 --> 00:45:34,839
Speaker 1: called at an issue with Verizon on a billing thing.

842
00:45:35,800 --> 00:45:38,160
Speaker 1: And when you call Verizon, they just give you AI,

843
00:45:39,239 --> 00:45:41,880
Speaker 1: and of course it wouldn't fix what I needed. I

844
00:45:42,000 --> 00:45:45,920
Speaker 1: was trying to get to and I finally got to

845
00:45:46,040 --> 00:45:50,120
Speaker 1: a person, and Verizon wanted to charge in twenty dollars

846
00:45:50,239 --> 00:45:54,480
Speaker 1: to talk to someone. Twenty dollars, Yeah, to talk to

847
00:45:54,960 --> 00:45:57,160
Speaker 1: a customer service agent. I give you that for a

848
00:45:57,239 --> 00:45:59,880
Speaker 1: problem that they created. Yeah, that's what a what an

849
00:46:00,360 --> 00:46:01,359
Speaker 1: that would be? Yeah?

850
00:46:01,400 --> 00:46:03,320
Speaker 2: Well banks, you know they charge you not to go

851
00:46:03,400 --> 00:46:05,160
Speaker 2: to the many banks. If you want to go up

852
00:46:05,200 --> 00:46:07,040
Speaker 2: to a teller, they charge you to go to a teller.

853
00:46:07,160 --> 00:46:09,200
Speaker 2: So that stuff has been going on for years, but

854
00:46:09,400 --> 00:46:12,799
Speaker 2: now it's going to be supercharged because customer service people,

855
00:46:13,080 --> 00:46:16,640
Speaker 2: you're going to be watch out because they're gonna they're

856
00:46:16,640 --> 00:46:20,080
Speaker 2: gonna take over your job. I mean, it's crazy Somebody says,

857
00:46:20,120 --> 00:46:24,160
Speaker 2: I white people's asses for a living. Is AI going

858
00:46:24,200 --> 00:46:26,240
Speaker 2: to be able to take my job? And not today,

859
00:46:27,040 --> 00:46:29,359
Speaker 2: not yet, but then you who's going to be paying

860
00:46:29,400 --> 00:46:31,800
Speaker 2: for you to white people's asses in the future, because

861
00:46:31,840 --> 00:46:37,360
Speaker 2: nobody will have a job because the AI took it. Doushi,

862
00:46:37,480 --> 00:46:39,880
Speaker 2: what do you have coming up? And the award winning

863
00:46:40,000 --> 00:46:42,240
Speaker 2: can never be replicated by AI?

864
00:46:42,560 --> 00:46:46,839
Speaker 4: Shuzy uh Lego said, that's going to be released. It's

865
00:46:47,040 --> 00:46:49,800
Speaker 4: really really cool and I might have to buy it.

866
00:46:49,960 --> 00:46:51,520
Speaker 4: I'll tell you what it is next.

867
00:46:51,719 --> 00:46:53,319
Speaker 2: All right, we'll get to that in just a minute.

868
00:46:53,360 --> 00:46:56,160
Speaker 2: Someone says, a I could never replace j l R.

869
00:46:56,280 --> 00:46:58,520
Speaker 2: Yeah he would. He would confuse the model you try

870
00:46:58,520 --> 00:47:03,279
Speaker 2: and train AI are jeffreyisms. And it would be when

871
00:47:03,280 --> 00:47:05,040
Speaker 2: we get the quantum computing and I think maybe they

872
00:47:05,080 --> 00:47:08,560
Speaker 2: could do it. Maybe perhaps. All right, let me take

873
00:47:08,560 --> 00:47:09,879
Speaker 2: a break. We'll be right back with the news.

874
00:47:09,960 --> 00:47:10,239
Speaker 5: Hang on,