1
00:00:00,280 --> 00:00:04,720
Speaker 1: From UFOs to psychic powers and government conspiracies. History is

2
00:00:04,840 --> 00:00:09,119
Speaker 1: riddled with unexplained events. You can turn back now or

3
00:00:09,240 --> 00:00:12,200
Speaker 1: learn this stuff they don't want you to know. A

4
00:00:12,280 --> 00:00:13,960
Speaker 1: production of iHeartRadio.

5
00:00:24,200 --> 00:00:26,440
Speaker 2: Hello, welcome back to the show. My name is Matt,

6
00:00:26,640 --> 00:00:27,440
Speaker 2: my name is Nol.

7
00:00:27,640 --> 00:00:30,520
Speaker 3: They call me Ben. We're joined as always with our

8
00:00:30,600 --> 00:00:34,880
Speaker 3: super producer Alexis code name Doc Holliday Jackson. Most importantly,

9
00:00:35,159 --> 00:00:38,400
Speaker 3: you are you. You are here. That makes this the

10
00:00:38,560 --> 00:00:41,920
Speaker 3: stuff they don't want you to know. It's the top

11
00:00:41,960 --> 00:00:47,200
Speaker 3: of the week, fellow conspiracy realist. Happy almost Valentine's Day

12
00:00:47,240 --> 00:00:51,879
Speaker 3: to all those who celebrate the sweet Yeah yeah, look

13
00:00:51,920 --> 00:00:55,639
Speaker 3: at me. Be careful, folks. You might get diabetes if

14
00:00:55,640 --> 00:00:58,200
Speaker 3: you hang out too often. That's how sweet we are.

15
00:00:58,800 --> 00:01:02,840
Speaker 3: We are also chock full of strange news just for you,

16
00:01:02,960 --> 00:01:07,440
Speaker 3: fellow conspiracy realists. We are going to explort so many things,

17
00:01:07,800 --> 00:01:13,040
Speaker 3: AI and nukes, deep fakes and deep fakes hitting the pocketbook,

18
00:01:13,640 --> 00:01:17,319
Speaker 3: some new plans by our friends at CERN who have

19
00:01:17,440 --> 00:01:21,399
Speaker 3: still yet to build a little tiny home collider. But

20
00:01:21,440 --> 00:01:21,880
Speaker 3: we'll see.

21
00:01:22,040 --> 00:01:24,720
Speaker 4: I don't know, Ben five for one, I'm a little concerned.

22
00:01:25,240 --> 00:01:27,559
Speaker 3: There it is there, it is. Be careful with that joke,

23
00:01:27,640 --> 00:01:33,120
Speaker 3: it's an antique. We we're thinking we might spend the

24
00:01:33,160 --> 00:01:38,000
Speaker 3: first act of Tonight's Strange News with just a round

25
00:01:38,080 --> 00:01:40,560
Speaker 3: up of all the crazy stuff that has happened. Maybe

26
00:01:40,560 --> 00:01:43,880
Speaker 3: we start here. Did you guys hear about the bill

27
00:01:44,160 --> 00:01:49,280
Speaker 3: in Florida that's going to target bears, the animal bears,

28
00:01:49,320 --> 00:01:49,960
Speaker 3: black bears?

29
00:01:50,280 --> 00:01:50,520
Speaker 4: No?

30
00:01:50,960 --> 00:01:52,400
Speaker 2: Oh, what are the bears?

31
00:01:52,400 --> 00:01:53,240
Speaker 4: What do the bears? Ever?

32
00:01:53,280 --> 00:01:55,640
Speaker 5: Do the bears are the ones that are like being attacked,

33
00:01:55,720 --> 00:01:56,720
Speaker 5: They need to be protected.

34
00:01:56,760 --> 00:01:57,840
Speaker 4: Why are we targeting them?

35
00:01:58,120 --> 00:02:01,920
Speaker 2: But it isn't a hunting bear, right or which bears

36
00:02:01,920 --> 00:02:02,520
Speaker 2: can be hunted?

37
00:02:02,560 --> 00:02:04,240
Speaker 5: Does this have to do with like all of the

38
00:02:04,240 --> 00:02:07,160
Speaker 5: bears that keep stealing picnic baskets and such and they're

39
00:02:07,200 --> 00:02:08,200
Speaker 5: trying to crack down on that.

40
00:02:08,240 --> 00:02:12,880
Speaker 3: Finally, well the threat thereof Okay, so it turns out

41
00:02:13,520 --> 00:02:18,840
Speaker 3: that quite recently, and this was reported on Monday, February fifth,

42
00:02:18,960 --> 00:02:24,079
Speaker 3: so last like earlier this week, as we record, Republican

43
00:02:24,160 --> 00:02:31,640
Speaker 3: state Congressman Jason Schauf has introduced a bill House Bill

44
00:02:31,760 --> 00:02:36,720
Speaker 3: eighty seven to remove most penalties for killing bears just

45
00:02:36,800 --> 00:02:40,960
Speaker 3: off the cuff in the state of Florida because quote,

46
00:02:42,120 --> 00:02:45,280
Speaker 3: black bears are high on crack, they're going to break

47
00:02:45,320 --> 00:02:48,000
Speaker 3: into people's homes and tear them apart.

48
00:02:48,240 --> 00:02:51,520
Speaker 4: What they're high on crack? Where is this coming from?

49
00:02:52,120 --> 00:02:59,919
Speaker 3: That's that's a question. A lot of people are asking, Yeah.

50
00:02:58,919 --> 00:02:59,680
Speaker 2: There's a movie.

51
00:03:00,360 --> 00:03:03,760
Speaker 5: Is this like some secret race baiting stuff that's going on?

52
00:03:03,919 --> 00:03:04,640
Speaker 4: Like, what is that?

53
00:03:05,200 --> 00:03:08,320
Speaker 2: I think it's I think it's I think that's right.

54
00:03:08,520 --> 00:03:11,400
Speaker 2: It's man, it feels it feels like a joke to me.

55
00:03:11,440 --> 00:03:14,040
Speaker 2: You want to read just no, but it feels it

56
00:03:14,040 --> 00:03:18,280
Speaker 2: feels like a joke. Tell Cocaine Bear was a thing.

57
00:03:18,600 --> 00:03:21,600
Speaker 2: Everything is a joke now, dude. Everything is just this weird,

58
00:03:21,880 --> 00:03:23,120
Speaker 2: terrible joke.

59
00:03:23,360 --> 00:03:26,240
Speaker 3: Post irony, post truth society.

60
00:03:26,280 --> 00:03:28,679
Speaker 2: It's real and yet simultaneously a joke.

61
00:03:29,200 --> 00:03:32,160
Speaker 3: Yes, everything is real. What what was that line we

62
00:03:32,280 --> 00:03:35,880
Speaker 3: loved from Invisibles? Everything is true and nothing is permitted.

63
00:03:36,800 --> 00:03:40,040
Speaker 3: It's some some uh, some tag on that or some

64
00:03:40,160 --> 00:03:44,360
Speaker 3: riff on that. Everything is terrible and everything's hilarious. Uh.

65
00:03:44,760 --> 00:03:50,080
Speaker 3: There are some estimated four thousand and fifty black Bears

66
00:03:50,120 --> 00:03:54,040
Speaker 3: in the state of Florida. To date, not one has

67
00:03:54,160 --> 00:03:57,880
Speaker 3: been proven to have ingested crack. It really does sound

68
00:03:57,960 --> 00:04:01,440
Speaker 3: like this guy is reacting to the Cocaine Bear film.

69
00:04:01,560 --> 00:04:02,960
Speaker 5: I just feel like we need to find out who's

70
00:04:02,960 --> 00:04:05,560
Speaker 5: giving the bears the crack and deal with that part

71
00:04:05,600 --> 00:04:07,040
Speaker 5: of the problem. You know what I mean. This is

72
00:04:07,080 --> 00:04:09,920
Speaker 5: a multi prom issue that we're talking about here.

73
00:04:10,120 --> 00:04:11,520
Speaker 4: Who's giving the bears the crack?

74
00:04:11,840 --> 00:04:14,840
Speaker 3: Yeah? This bill is if if there are any crack

75
00:04:14,880 --> 00:04:18,520
Speaker 3: addicted bears. First off, they need help, Yeah, you need help.

76
00:04:18,560 --> 00:04:23,720
Speaker 3: Don't criminalize addiction. And secondly, secondly, it is very American,

77
00:04:23,760 --> 00:04:26,560
Speaker 3: as we'll find in a later listener mail segment, it's

78
00:04:26,640 --> 00:04:30,960
Speaker 3: very American to treat these symptoms rather than the actual problem.

79
00:04:31,320 --> 00:04:33,960
Speaker 3: I just wanted to give a shout out there because

80
00:04:34,000 --> 00:04:36,760
Speaker 3: it does look like this is a bill being built

81
00:04:36,920 --> 00:04:37,960
Speaker 3: off a meme.

82
00:04:38,560 --> 00:04:41,120
Speaker 5: Uh in this sort of like the litter boxes and

83
00:04:41,200 --> 00:04:44,720
Speaker 5: the schools, you know, the first.

84
00:04:44,120 --> 00:04:47,720
Speaker 3: Yeah, and then another one that we should give some

85
00:04:47,880 --> 00:04:50,960
Speaker 3: time to and maybe a little bit more serious here

86
00:04:51,000 --> 00:04:55,400
Speaker 3: because the the crack bear legislation is probably not going

87
00:04:55,440 --> 00:04:58,440
Speaker 3: to pass, I hope, but uh. Over just a bit

88
00:04:58,560 --> 00:05:02,760
Speaker 3: north of Florida and South Carolina, the state is aiming

89
00:05:02,880 --> 00:05:09,559
Speaker 3: to restart executions, to reinstitute the death penalty through both

90
00:05:09,720 --> 00:05:14,719
Speaker 3: electric chair and firing squad and they said something pretty

91
00:05:14,800 --> 00:05:18,320
Speaker 3: dangerous here. They said that in the case of capital punishment,

92
00:05:19,360 --> 00:05:22,960
Speaker 3: painless death is not required. Now, this goes back to

93
00:05:23,040 --> 00:05:27,200
Speaker 3: our earlier conversations off air. I can't remember whether we

94
00:05:27,400 --> 00:05:32,520
Speaker 3: recorded that one about the lethal injection. Right, we talked

95
00:05:32,520 --> 00:05:36,720
Speaker 3: about that previously, Right, the guy who survived execution and

96
00:05:36,800 --> 00:05:40,000
Speaker 3: they were going to asphyxiate him because they and they

97
00:05:40,040 --> 00:05:41,240
Speaker 3: did and he is dead.

98
00:05:41,520 --> 00:05:43,680
Speaker 2: Yeah, And it took a lot longer than they expected,

99
00:05:43,720 --> 00:05:47,320
Speaker 2: and he appeared to suffer while he was being exphyxiated.

100
00:05:47,800 --> 00:05:48,840
Speaker 4: So is this just like.

101
00:05:48,880 --> 00:05:51,400
Speaker 5: Attempting to make the suffering like a feature and not

102
00:05:51,480 --> 00:05:54,080
Speaker 5: a bug, like, let's let's make them, let's make these

103
00:05:54,160 --> 00:05:55,040
Speaker 5: monsters suffer.

104
00:05:55,360 --> 00:05:56,320
Speaker 4: Is that the idea?

105
00:05:56,440 --> 00:05:59,880
Speaker 3: Yeah, let's go to landing me on writing for Fox News.

106
00:06:00,040 --> 00:06:04,200
Speaker 3: This came out February seventh, twenty twenty four. There are

107
00:06:04,480 --> 00:06:09,680
Speaker 3: about thirty three inmates who are currently on South Carolina's

108
00:06:09,680 --> 00:06:12,719
Speaker 3: death row. There has not been a formal moratorium on

109
00:06:12,800 --> 00:06:15,960
Speaker 3: the death penalty in that state, but for more than

110
00:06:16,000 --> 00:06:21,960
Speaker 3: a decade, almost thirteen years, they have not performed an execution.

111
00:06:22,320 --> 00:06:25,400
Speaker 3: And like many states in the US, they haven't performed

112
00:06:25,400 --> 00:06:29,000
Speaker 3: an execution because it became very difficult to get the

113
00:06:29,240 --> 00:06:33,680
Speaker 3: drugs that are required for lethal injection, And so what

114
00:06:33,760 --> 00:06:38,640
Speaker 3: they said now is that, sorry, folks, you don't have

115
00:06:38,720 --> 00:06:43,520
Speaker 3: to have a painless execution. The primary pitch of lethal

116
00:06:43,560 --> 00:06:47,760
Speaker 3: injection is the idea that it is painless and therefore

117
00:06:47,880 --> 00:06:51,400
Speaker 3: somehow more humane, right, And this made me think of

118
00:06:51,440 --> 00:06:54,480
Speaker 3: our conversations with our pals at Lava for Good. It

119
00:06:54,560 --> 00:07:00,880
Speaker 3: just seems pretty cold and dangerous to say painless execution

120
00:07:01,080 --> 00:07:04,599
Speaker 3: is not mandated by law, even though technically they are correct.

121
00:07:04,839 --> 00:07:08,400
Speaker 5: Well, I wonder too, like, how many instances of botched

122
00:07:08,560 --> 00:07:12,600
Speaker 5: guillotine executions do we have record of. I'm I'm not

123
00:07:12,680 --> 00:07:14,160
Speaker 5: trying to be a jerk here, I just know that,

124
00:07:14,280 --> 00:07:18,200
Speaker 5: like in France, the guillotine was used much more and

125
00:07:18,280 --> 00:07:21,000
Speaker 5: much more modern times than one might realize. And it

126
00:07:21,120 --> 00:07:24,120
Speaker 5: sure to me seems like a pretty surefire way to

127
00:07:24,160 --> 00:07:27,000
Speaker 5: get the job done instantaneously, you know.

128
00:07:27,280 --> 00:07:29,000
Speaker 4: And I just I wonder if there ever been a

129
00:07:29,000 --> 00:07:29,600
Speaker 4: time where.

130
00:07:29,400 --> 00:07:31,160
Speaker 5: The blade didn't go all the way through, or there

131
00:07:31,200 --> 00:07:33,239
Speaker 5: was some horrific you know, maiming.

132
00:07:33,400 --> 00:07:35,840
Speaker 4: I kind of think probably not that many.

133
00:07:36,160 --> 00:07:39,400
Speaker 5: And I just wonder, you know, this illusion of humanity

134
00:07:39,440 --> 00:07:40,960
Speaker 5: with this injection, to me, is.

135
00:07:40,920 --> 00:07:42,960
Speaker 4: Sort of a bit of a joke, right.

136
00:07:42,760 --> 00:07:47,160
Speaker 3: I agree, I mean also adding to that execution via

137
00:07:47,240 --> 00:07:52,920
Speaker 3: decapitation is arguably tremendously inhumane because the more we learn

138
00:07:53,160 --> 00:07:57,480
Speaker 3: about about the brain, right and the rain, it's highly likely,

139
00:07:57,720 --> 00:08:01,720
Speaker 3: if not statistically certain, that when people had their heads

140
00:08:01,720 --> 00:08:04,960
Speaker 3: cut off, especially during a guillotine, they were still conscious

141
00:08:05,200 --> 00:08:09,840
Speaker 3: and still receivering sensory input. They saw their own heads

142
00:08:10,000 --> 00:08:14,320
Speaker 3: fall through into the basket, they heard the cheers of

143
00:08:14,360 --> 00:08:18,560
Speaker 3: a bloodthirsty crowd. It's it's I would say, it's decapitation

144
00:08:18,760 --> 00:08:19,920
Speaker 3: is more inhumane.

145
00:08:19,920 --> 00:08:22,640
Speaker 5: And I'm certainly coificating for bringing back the guillotine, and

146
00:08:22,640 --> 00:08:24,680
Speaker 5: it was more of a hypothetical, But I'm just saying

147
00:08:24,760 --> 00:08:27,520
Speaker 5: that the idea that one is better than the other,

148
00:08:27,840 --> 00:08:31,080
Speaker 5: I think sometimes is left up to science to figure out,

149
00:08:31,120 --> 00:08:33,480
Speaker 5: and that that data doesn't always come through right away.

150
00:08:33,480 --> 00:08:35,480
Speaker 5: It's more of a trial and error kind of situation,

151
00:08:35,600 --> 00:08:35,800
Speaker 5: you know.

152
00:08:36,280 --> 00:08:38,720
Speaker 3: And it kind of takes us to this larger question

153
00:08:38,960 --> 00:08:43,280
Speaker 3: about capital punishment, about the death penalty in general, right,

154
00:08:43,320 --> 00:08:45,960
Speaker 3: which is, you know, not unique to the US by

155
00:08:45,960 --> 00:08:48,160
Speaker 3: any means. As a matter of fact, there are several

156
00:08:48,200 --> 00:08:52,920
Speaker 3: countries that are far more on board with the death penalty.

157
00:08:53,280 --> 00:08:57,080
Speaker 3: But it's a question I want to hear from our

158
00:08:57,200 --> 00:09:00,400
Speaker 3: fellow conspiracy realists want to hear from you guys. Should

159
00:09:00,480 --> 00:09:05,120
Speaker 3: the death penalty exist? Knowing that the US justice system

160
00:09:05,200 --> 00:09:10,240
Speaker 3: in particular gets it wrong so often? I mean, how many, like,

161
00:09:10,360 --> 00:09:13,920
Speaker 3: how many innocent people are we willing to put on

162
00:09:13,960 --> 00:09:15,960
Speaker 3: the other side of the equals sign?

163
00:09:16,360 --> 00:09:16,520
Speaker 4: Right?

164
00:09:16,640 --> 00:09:20,080
Speaker 3: What's our rate of error or margin of error rather

165
00:09:20,240 --> 00:09:24,600
Speaker 3: that would be acceptable? And is there a margin that It's.

166
00:09:24,520 --> 00:09:27,000
Speaker 2: A good question. It feels like, in my opinion, why

167
00:09:27,040 --> 00:09:29,439
Speaker 2: it's a really good idea to write laws when you

168
00:09:29,480 --> 00:09:32,400
Speaker 2: are in a time of peace, even if they're even

169
00:09:32,400 --> 00:09:35,240
Speaker 2: if you're writing laws about war, write them during the

170
00:09:35,280 --> 00:09:38,000
Speaker 2: peace time, because when you're in wartime or let's say

171
00:09:38,000 --> 00:09:40,839
Speaker 2: you've had a family member or a loved one has

172
00:09:40,880 --> 00:09:44,520
Speaker 2: been maimed or injured or murdered by somebody else, you're

173
00:09:44,559 --> 00:09:48,240
Speaker 2: probably for you know, the death penalty or for you

174
00:09:48,280 --> 00:09:52,240
Speaker 2: know that type of punishment, because you want justice for

175
00:09:52,520 --> 00:09:53,120
Speaker 2: somebody you.

176
00:09:53,120 --> 00:09:55,120
Speaker 5: Loved, right, I mean, it's the saying I think I

177
00:09:55,160 --> 00:09:59,200
Speaker 5: maybe mentioned that I recently spent a day injury selection process,

178
00:09:59,240 --> 00:10:01,280
Speaker 5: and part of that problem as is them asking jury

179
00:10:01,280 --> 00:10:05,040
Speaker 5: members questions pertaining to largely A big part of it

180
00:10:05,080 --> 00:10:06,640
Speaker 5: is whether or not you've been a victim of the

181
00:10:06,679 --> 00:10:10,400
Speaker 5: type of crime that is being litigated, and if you have,

182
00:10:10,960 --> 00:10:13,679
Speaker 5: chances are really good you're not going to get selected

183
00:10:13,760 --> 00:10:15,880
Speaker 5: because they know that you're going to all of your

184
00:10:15,880 --> 00:10:19,080
Speaker 5: emotions are going to be tinged by that experience and

185
00:10:19,120 --> 00:10:23,160
Speaker 5: brought into the deliberation process. So I think that's a

186
00:10:23,200 --> 00:10:25,079
Speaker 5: good thing in terms of the jury deliberation, But I

187
00:10:25,080 --> 00:10:27,240
Speaker 5: think that should be applied to your point and that

188
00:10:27,360 --> 00:10:29,559
Speaker 5: kind of larger like if we do that with jurys,

189
00:10:29,800 --> 00:10:31,720
Speaker 5: why don't we do that with like laws that affect

190
00:10:31,840 --> 00:10:33,000
Speaker 5: everybody all the time.

191
00:10:34,040 --> 00:10:36,880
Speaker 3: Yeah, And that's that's something we want to hear from

192
00:10:36,960 --> 00:10:40,480
Speaker 3: you on, folks, because we have had in the past,

193
00:10:40,520 --> 00:10:43,200
Speaker 3: we've had a lot of correspondence from people writing in

194
00:10:43,280 --> 00:10:46,320
Speaker 3: and saying I am against the death penalty and here's why,

195
00:10:46,800 --> 00:10:50,160
Speaker 3: or I am for the death penalty and here's why,

196
00:10:50,520 --> 00:10:54,959
Speaker 3: and all in each case, all the correspondence we received

197
00:10:55,120 --> 00:10:58,920
Speaker 3: was very well reasoned. We're not, of course, pretending to

198
00:10:59,040 --> 00:11:02,880
Speaker 3: know the answer. It seems though, that it is often

199
00:11:03,320 --> 00:11:09,760
Speaker 3: politically convenient for lawmakers to institute a death penalty without

200
00:11:09,800 --> 00:11:15,320
Speaker 3: proper scrutiny, because it makes them electable, it makes them

201
00:11:15,760 --> 00:11:19,280
Speaker 3: an attractive candidate to say that they are hard on crime.

202
00:11:20,160 --> 00:11:23,959
Speaker 3: We know, you know, like you were pointing out, Matt

203
00:11:23,960 --> 00:11:27,960
Speaker 3: that the man who was executed in Alabama with the

204
00:11:28,080 --> 00:11:33,120
Speaker 3: nitrogen gas that was a new method, right, it was

205
00:11:33,160 --> 00:11:36,800
Speaker 3: the first new method in forty two years. And we're not,

206
00:11:37,559 --> 00:11:40,800
Speaker 3: to be clear, we're not defending people on death row,

207
00:11:41,520 --> 00:11:45,880
Speaker 3: especially if they have been lawfully, rightfully convicted. But we

208
00:11:46,360 --> 00:11:50,920
Speaker 3: are asking, I think, a serious question about the existence

209
00:11:50,960 --> 00:11:53,640
Speaker 3: of the death penalty. And additionally, we're asking about the

210
00:11:53,679 --> 00:12:00,840
Speaker 3: idea of the idea of painless execution, right versus some terrible,

211
00:12:01,000 --> 00:12:06,160
Speaker 3: egregious method to allow a precedent wherein a death by

212
00:12:06,200 --> 00:12:10,560
Speaker 3: the state does not have to be painless or humane.

213
00:12:11,000 --> 00:12:14,160
Speaker 3: How much of a slippery slope is that to returning

214
00:12:14,240 --> 00:12:17,480
Speaker 3: to the days of decapitation, to returning to the days

215
00:12:17,520 --> 00:12:20,760
Speaker 3: of drawing and quartering and all the other nasty stuff.

216
00:12:20,840 --> 00:12:22,079
Speaker 4: I think that's what I was asking.

217
00:12:22,120 --> 00:12:25,040
Speaker 5: It's like maybe I was, you know, belaboring the point

218
00:12:25,040 --> 00:12:27,360
Speaker 5: a little bit or being a little hyperbolic, But this

219
00:12:27,480 --> 00:12:31,720
Speaker 5: does feel like almost like an end to doing just that,

220
00:12:31,920 --> 00:12:34,720
Speaker 5: to making the suffering, to bringing the suffering back into

221
00:12:34,760 --> 00:12:38,600
Speaker 5: the equation as like part of it you know, these

222
00:12:38,640 --> 00:12:41,880
Speaker 5: people deserve, you know, to suffer, And I don't know.

223
00:12:41,880 --> 00:12:43,600
Speaker 4: Death penalty stuff is so complex and.

224
00:12:43,520 --> 00:12:46,319
Speaker 5: I don't even think we want to litigate that here today.

225
00:12:46,440 --> 00:12:49,000
Speaker 5: But I do think we probably all agree at the

226
00:12:49,080 --> 00:12:51,920
Speaker 5: very least, you know, if people have gotten to that

227
00:12:52,000 --> 00:12:55,200
Speaker 5: point and hoping that that all the ducks are in

228
00:12:55,240 --> 00:12:58,920
Speaker 5: a row legally speaking, that there's no reason anyone should

229
00:12:59,040 --> 00:13:02,320
Speaker 5: be forced to suffer in that way. The death part

230
00:13:02,559 --> 00:13:04,720
Speaker 5: is literally the penalty, right.

231
00:13:04,880 --> 00:13:10,160
Speaker 3: Well, you could also say that the death penalty is

232
00:13:10,200 --> 00:13:13,320
Speaker 3: something that all people will confront by virtue of living

233
00:13:13,360 --> 00:13:16,000
Speaker 3: at some exact, you know, not to be not to

234
00:13:16,040 --> 00:13:19,679
Speaker 3: be too cheerful. We've all got to come about it. Yeah,

235
00:13:20,000 --> 00:13:22,600
Speaker 3: So moving on, I want to be quick with this.

236
00:13:23,040 --> 00:13:27,280
Speaker 3: We talked a little bit about a Internet of Things hack,

237
00:13:27,760 --> 00:13:30,280
Speaker 3: and I have a I have the headline and a

238
00:13:30,280 --> 00:13:33,240
Speaker 3: little bit of a plot twist here. This is kind

239
00:13:33,280 --> 00:13:35,600
Speaker 3: of good news and I think it might be instructive

240
00:13:35,600 --> 00:13:38,800
Speaker 3: for all of us playing along at home. Remember I

241
00:13:38,840 --> 00:13:42,920
Speaker 3: sent that text about the Great toothbrush Hack of twenty

242
00:13:43,000 --> 00:13:43,600
Speaker 3: twenty four.

243
00:13:44,400 --> 00:13:45,560
Speaker 4: It was only a matter of time.

244
00:13:45,760 --> 00:13:49,200
Speaker 5: You know, next it'll be a water pick, right, I mean, yeah,

245
00:13:50,360 --> 00:13:52,480
Speaker 5: I only really briefly scanned the headline and I was

246
00:13:52,480 --> 00:13:53,839
Speaker 5: just like, Yep, that makes sense.

247
00:13:54,080 --> 00:13:56,360
Speaker 4: I basically get it. But what are the deeps?

248
00:13:56,920 --> 00:14:02,480
Speaker 3: So here's here's the headline. This story went viral just yesterday,

249
00:14:03,000 --> 00:14:06,240
Speaker 3: or about forty eight hours ago, the idea that three

250
00:14:06,480 --> 00:14:13,400
Speaker 3: million smart toothbrushes Internet connected toothbrushes were captured through malicious

251
00:14:13,440 --> 00:14:18,680
Speaker 3: hacking and used in a d DOS attack denial of

252
00:14:18,800 --> 00:14:23,560
Speaker 3: service attack. And this is something that can happen like

253
00:14:23,640 --> 00:14:29,760
Speaker 3: your local smart refrigerator or your local smart washer dryer

254
00:14:29,920 --> 00:14:35,200
Speaker 3: insertippliance here can be conscripted into a botnet army. And

255
00:14:35,280 --> 00:14:38,800
Speaker 3: the story that has gone everywhere in the Western speaking

256
00:14:38,840 --> 00:14:45,400
Speaker 3: Internet now argues that this these toothbrushes were hijacked by

257
00:14:45,440 --> 00:14:51,040
Speaker 3: hackers and they were used to be part of a

258
00:14:51,120 --> 00:14:54,760
Speaker 3: wave of d DOS attacks, and that they knocked out

259
00:14:54,920 --> 00:14:59,080
Speaker 3: the capabilities of a company in Switzerland for several hours

260
00:14:59,360 --> 00:15:03,600
Speaker 3: and costs millions of euros in damage to that company.

261
00:15:04,480 --> 00:15:08,240
Speaker 3: A couple things to unpack. One, this would have been

262
00:15:09,440 --> 00:15:12,600
Speaker 3: what you could call like a ransomware attack, right, so

263
00:15:12,640 --> 00:15:16,480
Speaker 3: the company would have been logically threatened by the hackers

264
00:15:17,000 --> 00:15:20,280
Speaker 3: and would not have conceded to their demands. And then

265
00:15:20,480 --> 00:15:23,240
Speaker 3: they would have been hit with the DDS and it

266
00:15:23,280 --> 00:15:26,560
Speaker 3: would have cost them, you know whatever, X million amount

267
00:15:26,560 --> 00:15:32,880
Speaker 3: of euros in damages as a result. However, I did

268
00:15:32,880 --> 00:15:37,840
Speaker 3: some digging and it turns out this is instructive, but

269
00:15:38,080 --> 00:15:40,480
Speaker 3: not in the way we told you at the beginning. Folks,

270
00:15:40,840 --> 00:15:46,280
Speaker 3: This is instructive because the story is absolute bullsh it

271
00:15:46,560 --> 00:15:47,440
Speaker 3: never happens.

272
00:15:47,560 --> 00:15:47,800
Speaker 4: Yeah.

273
00:15:47,880 --> 00:15:50,000
Speaker 2: Well, I was going to ask what kind of computing

274
00:15:50,160 --> 00:15:54,080
Speaker 2: power does a smart toothbrush have? What is to need

275
00:15:54,240 --> 00:15:56,840
Speaker 2: to operate a d doos.

276
00:15:56,480 --> 00:15:59,880
Speaker 3: Smart is in the name? First off, lest we despair

277
00:16:00,120 --> 00:16:01,360
Speaker 3: to these brushes.

278
00:16:01,040 --> 00:16:03,120
Speaker 5: My question was to piggyback on that Matt, like what

279
00:16:03,200 --> 00:16:07,400
Speaker 5: kind of tech does it need to operate as a frickin' toothbrush? Like?

280
00:16:07,640 --> 00:16:10,360
Speaker 5: What kind of you know, moving parts does it are

281
00:16:10,440 --> 00:16:12,200
Speaker 5: required to really do a good job?

282
00:16:12,320 --> 00:16:14,240
Speaker 4: I mean, does it have a microprocessor in it?

283
00:16:14,320 --> 00:16:14,440
Speaker 3: Like?

284
00:16:14,480 --> 00:16:16,120
Speaker 4: I just I can't imagine?

285
00:16:16,160 --> 00:16:20,200
Speaker 5: And is this gaining entry to just like a local interranet,

286
00:16:20,800 --> 00:16:24,040
Speaker 5: like to a you know, an internetnet service provider? Like

287
00:16:24,120 --> 00:16:26,880
Speaker 5: what how is this even being able to you know,

288
00:16:27,000 --> 00:16:28,040
Speaker 5: be this effective?

289
00:16:28,400 --> 00:16:32,160
Speaker 3: Exactly exactly, You guys are asking the right questions. First off,

290
00:16:32,200 --> 00:16:36,560
Speaker 3: if you have any kind of Internet capable devices in

291
00:16:36,600 --> 00:16:39,800
Speaker 3: your home, like the Internet of Things type stuff. Then

292
00:16:39,840 --> 00:16:43,440
Speaker 3: you should have them on a separate network that you

293
00:16:43,640 --> 00:16:47,040
Speaker 3: keep away from the rest of your network, to say

294
00:16:47,120 --> 00:16:50,920
Speaker 3: what you would with a smart TV or refrigerator, et cetera.

295
00:16:51,280 --> 00:16:57,320
Speaker 3: But the issue here is more about credulity. It's more

296
00:16:57,360 --> 00:17:01,480
Speaker 3: about I would argue what we see and believe versus

297
00:17:01,520 --> 00:17:06,480
Speaker 3: like reading the headline versus triangulating more of like original

298
00:17:06,520 --> 00:17:09,639
Speaker 3: sources and stuff. I was shocked, you, guys. I was

299
00:17:09,720 --> 00:17:14,919
Speaker 3: shocked to find that The Independent reported this story as fact.

300
00:17:15,760 --> 00:17:20,359
Speaker 3: This you can see an article by Anthony Cuthbertson which

301
00:17:20,400 --> 00:17:23,240
Speaker 3: came out just a few hours ago on the Independent

302
00:17:23,680 --> 00:17:27,679
Speaker 3: saying that millions of hacked toothbrushes were used in a

303
00:17:27,760 --> 00:17:32,520
Speaker 3: Swiss cyber attack, and tracing this back to the original source,

304
00:17:32,560 --> 00:17:37,520
Speaker 3: it goes to a local newspaper. Thank you in advanced

305
00:17:37,520 --> 00:17:41,359
Speaker 3: folks for putting up with our pronunciations. Here our our

306
00:17:41,800 --> 00:17:51,240
Speaker 3: zeitung oh.

307
00:17:47,680 --> 00:17:48,840
Speaker 4: Is the Californians.

308
00:17:48,960 --> 00:17:53,400
Speaker 3: It's amazing cool. Thank you. The paper cited a cybersecurity

309
00:17:53,480 --> 00:17:57,960
Speaker 3: firm called Fortinet, and The Independent reached out to Fortunet

310
00:17:58,280 --> 00:18:04,760
Speaker 3: for more information. But then digging deeper, I found some

311
00:18:04,880 --> 00:18:11,159
Speaker 3: infosec experts is on Mastodon being totally honest on social media.

312
00:18:11,800 --> 00:18:16,680
Speaker 3: So shout out to Kevin Beaumont who came out and

313
00:18:16,800 --> 00:18:21,160
Speaker 3: said the three million toothbrush botnet story is not true.

314
00:18:21,520 --> 00:18:25,480
Speaker 3: It's a made up example. It doesn't exist. It talks

315
00:18:25,520 --> 00:18:28,639
Speaker 3: about these other things. And as far as I can tell,

316
00:18:28,840 --> 00:18:31,560
Speaker 3: as far as I can tell, what happened is someone

317
00:18:31,840 --> 00:18:36,120
Speaker 3: interviewed someone working at like maybe a new hire at

318
00:18:36,119 --> 00:18:39,639
Speaker 3: this cybersecurity firm, and they talked about the idea of

319
00:18:39,920 --> 00:18:46,120
Speaker 3: using these different innocuous internet connected devices and they said

320
00:18:46,200 --> 00:18:50,320
Speaker 3: you could use anything, even toothbrushes. Maybe something got lost

321
00:18:50,359 --> 00:18:54,320
Speaker 3: in translation. Check out our ridiculous history episode on this

322
00:18:54,520 --> 00:18:59,040
Speaker 3: translations and then it just went around the world so quickly.

323
00:18:59,480 --> 00:19:03,000
Speaker 3: So this is actually good news, folks. Your toothbrush is

324
00:19:03,040 --> 00:19:03,680
Speaker 3: not being.

325
00:19:03,520 --> 00:19:04,480
Speaker 4: Hacked, thank god.

326
00:19:04,920 --> 00:19:07,440
Speaker 3: You also don't need a smart toothbrush. To MAT's point,

327
00:19:07,600 --> 00:19:09,240
Speaker 3: I don't think so either. I don't think so.

328
00:19:09,400 --> 00:19:12,960
Speaker 5: I was not making fun of your performance there with

329
00:19:12,960 --> 00:19:15,080
Speaker 5: that produnciation. There was no way to not sound like

330
00:19:15,119 --> 00:19:16,840
Speaker 5: the Californians when saying that word.

331
00:19:16,960 --> 00:19:20,240
Speaker 3: Just for the record, and Californians is an awesome series

332
00:19:20,240 --> 00:19:24,360
Speaker 3: of sketches on Saturday Night Live, yeah, absolute bangers. Are

333
00:19:24,400 --> 00:19:25,400
Speaker 3: you doing here?

334
00:19:26,119 --> 00:19:27,720
Speaker 4: That's what I was trying to.

335
00:19:27,640 --> 00:19:31,119
Speaker 3: Think of, right, we were closer to the end of

336
00:19:31,160 --> 00:19:33,720
Speaker 3: the roundup. Just want to put one thing out there

337
00:19:33,760 --> 00:19:40,480
Speaker 3: for anybody who's interested in the skyrocketing wealth inequality. OXFAM

338
00:19:40,680 --> 00:19:44,320
Speaker 3: came out with a report that proves the fortunes of

339
00:19:44,400 --> 00:19:47,800
Speaker 3: the five richest individuals on the planet shot up by

340
00:19:47,880 --> 00:19:52,119
Speaker 3: one hundred and fourteen percent since twenty twenty. That is

341
00:19:52,240 --> 00:19:58,440
Speaker 3: something like fourteen million dollars per hour. They went from

342
00:19:58,520 --> 00:20:01,680
Speaker 3: four hundred and five billion in twenty twenty to eight

343
00:20:01,720 --> 00:20:07,000
Speaker 3: hundred and sixty nine billion, and five billion. Actual human

344
00:20:07,040 --> 00:20:09,640
Speaker 3: beings were made much poorer during the same time.

345
00:20:09,720 --> 00:20:13,560
Speaker 5: Do we have any any mitigating factors that led to that.

346
00:20:14,840 --> 00:20:19,600
Speaker 3: You know, human beings we got we got some pluck, right,

347
00:20:21,080 --> 00:20:25,159
Speaker 3: we got good hustles, We got good we got good hustle,

348
00:20:25,200 --> 00:20:28,160
Speaker 3: We got some grit. We also have an ad break

349
00:20:28,240 --> 00:20:28,880
Speaker 3: coming up.

350
00:20:29,000 --> 00:20:30,240
Speaker 2: We have compounded interest.

351
00:20:30,680 --> 00:20:32,240
Speaker 4: Ah, yes, yeah, Mark.

352
00:20:32,520 --> 00:20:36,399
Speaker 3: Mark Twain said, compounding interest is it was a boon.

353
00:20:37,240 --> 00:20:37,400
Speaker 5: Oh.

354
00:20:37,760 --> 00:20:42,800
Speaker 3: Compounding interest is amazing if you understand it, and disastrous

355
00:20:42,840 --> 00:20:43,399
Speaker 3: if you do not.

356
00:20:43,840 --> 00:20:45,840
Speaker 2: Yeah, I mean really like when you have that kind

357
00:20:45,840 --> 00:20:48,720
Speaker 2: of money and you make investments and you you start

358
00:20:48,760 --> 00:20:52,119
Speaker 2: with four hundred billion, then yeah, it becomes eight hundred billion.

359
00:20:52,400 --> 00:20:54,600
Speaker 5: Well, and it also makes me think of like why

360
00:20:54,720 --> 00:20:58,679
Speaker 5: people like Elon Musk seem to be so fearless and

361
00:20:58,840 --> 00:21:02,480
Speaker 5: making bone headed kind of financial decisions, you know, or

362
00:21:02,600 --> 00:21:06,439
Speaker 5: like being like mavericky or whatever. It's because their wealth

363
00:21:06,520 --> 00:21:09,280
Speaker 5: is so vast that just by the compound interest alone,

364
00:21:09,400 --> 00:21:11,280
Speaker 5: they're always going to have their buck covered and they

365
00:21:11,280 --> 00:21:15,280
Speaker 5: can afford to make these risky dice rolls. Yeah, which

366
00:21:15,359 --> 00:21:18,280
Speaker 5: usually involves playing with other people's well being.

367
00:21:18,320 --> 00:21:21,120
Speaker 4: And livelihood, which is, you know, great.

368
00:21:21,160 --> 00:21:23,840
Speaker 3: Right, Are you still brave if you have that kind

369
00:21:23,920 --> 00:21:27,280
Speaker 3: of safety net? Are you still really making a gamble?

370
00:21:28,160 --> 00:21:31,960
Speaker 3: For anybody who wants to learn more, please check out Inequality, Inc.

371
00:21:32,800 --> 00:21:36,240
Speaker 3: I n C, which was published quite recently by ox

372
00:21:36,280 --> 00:21:39,240
Speaker 3: Fam America. At the same time, by the way, that

373
00:21:39,240 --> 00:21:42,760
Speaker 3: folks are gathering in Switzerland for the annual Davos meet up.

374
00:21:43,200 --> 00:21:46,920
Speaker 3: No word yet on the toothbrushes, but if you happen

375
00:21:46,960 --> 00:21:49,320
Speaker 3: to be there, let you know, let us know how

376
00:21:49,320 --> 00:21:52,200
Speaker 3: they brush their teeth. We're gonna pause for a word

377
00:21:52,200 --> 00:21:56,520
Speaker 3: from our sponsors. We'll be back with more strange news.

378
00:22:01,840 --> 00:22:05,720
Speaker 5: And we've returned with some more strange news.

379
00:22:05,840 --> 00:22:07,880
Speaker 4: This one's a little freaky.

380
00:22:08,080 --> 00:22:13,400
Speaker 5: Guys. We've been waiting into the AI, machine learning waters,

381
00:22:13,720 --> 00:22:17,159
Speaker 5: various flavors of this whole kind of new emerging world

382
00:22:17,160 --> 00:22:20,280
Speaker 5: that we're seeing. Some of it very interesting, you know,

383
00:22:20,760 --> 00:22:24,320
Speaker 5: let's say, some of the uses of artificial intelligence in

384
00:22:24,400 --> 00:22:28,280
Speaker 5: creating weird videos. Actually, there's a lot of accounts I

385
00:22:28,280 --> 00:22:29,320
Speaker 5: follow on Instagram that.

386
00:22:29,280 --> 00:22:32,000
Speaker 4: Are like genuinely chilling.

387
00:22:32,200 --> 00:22:34,800
Speaker 5: There's some people that are using this technology in really

388
00:22:34,880 --> 00:22:39,159
Speaker 5: creative ways to make these other worldly, fantasy kind of

389
00:22:39,280 --> 00:22:43,240
Speaker 5: landscapes and you know, creatures that you would never even imagine,

390
00:22:43,280 --> 00:22:45,200
Speaker 5: And I think this, you know, it's a really interesting tool.

391
00:22:45,400 --> 00:22:47,959
Speaker 5: We've also covered the other side of that kind of stuff,

392
00:22:48,000 --> 00:22:51,359
Speaker 5: with you know, AI being used to generate and you know,

393
00:22:51,480 --> 00:22:56,639
Speaker 5: deep fakes and gnarly pornographic images of pop stars. Just

394
00:22:56,720 --> 00:22:58,600
Speaker 5: before I get into the main story, just a quick

395
00:22:58,920 --> 00:23:03,000
Speaker 5: side mention of story where a multinational Hong Kong company

396
00:23:03,160 --> 00:23:06,840
Speaker 5: lost twenty six the equivalent of twenty six million American

397
00:23:06,880 --> 00:23:11,760
Speaker 5: dollars when scammers fooled employees on a video call using

398
00:23:12,359 --> 00:23:16,919
Speaker 5: deep fake technology and convinced financial officers to make a

399
00:23:17,000 --> 00:23:20,960
Speaker 5: series of bank transfers totaling fifteen bank transfers to five

400
00:23:21,040 --> 00:23:25,000
Speaker 5: Hong Kong banks. And there's a quote from a write

401
00:23:25,040 --> 00:23:28,879
Speaker 5: up in Business Standard saying in the multi person video conference,

402
00:23:28,920 --> 00:23:34,080
Speaker 5: it turns out that everyone he saw was fake. Senior

403
00:23:34,119 --> 00:23:39,040
Speaker 5: Superintendent Baron Chan shun Ching told the city's public broadcaster

404
00:23:39,560 --> 00:23:45,280
Speaker 5: rt HK, SO, lots of weird opportunities for scamming, for

405
00:23:45,600 --> 00:23:49,239
Speaker 5: offending people, and for making weird art. But one thing

406
00:23:49,320 --> 00:23:52,520
Speaker 5: we've also discussed is, you know, the use of chatbot

407
00:23:52,680 --> 00:23:58,200
Speaker 5: technology for all kinds of controversial uses. You know, students

408
00:23:58,280 --> 00:24:00,800
Speaker 5: using it to cheat on exams or rather to cheat

409
00:24:00,840 --> 00:24:02,880
Speaker 5: on you know, essays and papers and things like that.

410
00:24:03,760 --> 00:24:06,400
Speaker 5: Folks using it to write entire parts of books.

411
00:24:06,760 --> 00:24:07,040
Speaker 4: You know.

412
00:24:07,160 --> 00:24:09,399
Speaker 5: It's a brave new world and there's a lot of

413
00:24:10,080 --> 00:24:12,400
Speaker 5: stuff to be sorted out in terms of the use

414
00:24:12,440 --> 00:24:14,159
Speaker 5: of this kind of technology. But one thing we do

415
00:24:14,280 --> 00:24:16,960
Speaker 5: know that is interesting and interesting use of it is

416
00:24:17,000 --> 00:24:19,840
Speaker 5: for modeling, you know, of like what would happen in

417
00:24:19,880 --> 00:24:22,760
Speaker 5: these certain circumstances. And we are starting to see, or

418
00:24:22,760 --> 00:24:27,320
Speaker 5: we have started to see that things like chat GPT they.

419
00:24:27,320 --> 00:24:29,719
Speaker 4: Kind of have a vibe, you know what I mean.

420
00:24:29,800 --> 00:24:33,719
Speaker 5: The GPT four the AI model has sort of like

421
00:24:34,040 --> 00:24:37,280
Speaker 5: we see like in for example, Elon Musk's chat bot

422
00:24:37,720 --> 00:24:39,720
Speaker 5: I forget the name of it, that it was too

423
00:24:39,800 --> 00:24:42,600
Speaker 5: woke for his liking, that it like had sort of

424
00:24:42,600 --> 00:24:44,440
Speaker 5: an agenda built into.

425
00:24:44,119 --> 00:24:45,920
Speaker 4: It in some weird way, and that.

426
00:24:45,880 --> 00:24:47,959
Speaker 5: They were going to do everything they can to twist that,

427
00:24:48,280 --> 00:24:51,359
Speaker 5: you know, to make it less. So what we're seeing

428
00:24:51,440 --> 00:24:56,359
Speaker 5: in a recent US military model using GPT four to

429
00:24:56,600 --> 00:25:00,480
Speaker 5: model kind of wartime scenario.

430
00:25:00,680 --> 00:25:02,400
Speaker 4: Is that GPT four.

431
00:25:03,680 --> 00:25:07,240
Speaker 5: And other AI models like it are pretty prone to

432
00:25:08,320 --> 00:25:13,960
Speaker 5: pushing the nuclear button. Yeah, to escalating conflicts to just

433
00:25:14,280 --> 00:25:18,919
Speaker 5: wipe everybody out because it's maybe the easier choice, you know,

434
00:25:19,720 --> 00:25:23,760
Speaker 5: at least from where they stands. Yeah, it gets the

435
00:25:23,840 --> 00:25:27,560
Speaker 5: job done, but it also really reeks of like Skynet

436
00:25:27,720 --> 00:25:30,840
Speaker 5: type stuff. You know, it really feels very Terminator too.

437
00:25:31,359 --> 00:25:33,560
Speaker 3: You know what it reminds me of, And we're talking

438
00:25:33,600 --> 00:25:35,879
Speaker 3: about this a little bit off air, it reminds me

439
00:25:35,960 --> 00:25:39,919
Speaker 3: of one of my favorite dumb video game legends. And

440
00:25:39,960 --> 00:25:44,400
Speaker 3: I say dumb with great affection for any fans of

441
00:25:44,440 --> 00:25:49,600
Speaker 3: the strategy video games like Civilization, you guys remember, Okay,

442
00:25:49,640 --> 00:25:53,560
Speaker 3: So so Civilization, there's a bit of there's a bit

443
00:25:53,600 --> 00:25:57,920
Speaker 3: of Internet lore that the Jedi won't tell you. When

444
00:25:58,000 --> 00:26:02,200
Speaker 3: Civilization came out in nineteen nine, you had all these

445
00:26:02,280 --> 00:26:05,920
Speaker 3: world leaders throughout history that would be you could either

446
00:26:06,000 --> 00:26:10,119
Speaker 3: play as them or you would have you know, computerized

447
00:26:10,280 --> 00:26:14,240
Speaker 3: opponents or other human players playing as these historical figures.

448
00:26:14,640 --> 00:26:18,200
Speaker 3: And some of them were very warlike in their disposition

449
00:26:18,400 --> 00:26:21,640
Speaker 3: and some were meant to be very peaceful in their disposition.

450
00:26:22,200 --> 00:26:27,960
Speaker 3: And the way the story goes is that they had

451
00:26:28,119 --> 00:26:32,440
Speaker 3: a background scale of aggression from one to ten, one

452
00:26:32,560 --> 00:26:35,720
Speaker 3: being the most peaceful, ten being by far the most aggressive,

453
00:26:36,119 --> 00:26:39,120
Speaker 3: and so one of the world leaders that you could

454
00:26:39,320 --> 00:26:44,560
Speaker 3: play against was Gandhi Okay, Gandhi being a pacifist. The

455
00:26:44,600 --> 00:26:50,119
Speaker 3: story goes that the developers set Gandhi like tried to

456
00:26:50,160 --> 00:26:53,200
Speaker 3: make him the most peaceful ever, so they set his

457
00:26:53,200 --> 00:26:57,000
Speaker 3: aggression to zero, but there was a software bug that

458
00:26:57,160 --> 00:27:02,320
Speaker 3: made him by far the most horror core, wow, massive

459
00:27:02,480 --> 00:27:06,240
Speaker 3: belligerent force in the game, and that he would always

460
00:27:06,320 --> 00:27:12,520
Speaker 3: be immediately pursuing nuclear weapons and pursuing dropping those on

461
00:27:12,880 --> 00:27:18,320
Speaker 3: every single player, including his allies. That is a legend,

462
00:27:18,680 --> 00:27:20,919
Speaker 3: but it does remind me like it's it's kind of

463
00:27:20,960 --> 00:27:24,680
Speaker 3: like a prescient anecdote about what we're seeing with AI today.

464
00:27:24,840 --> 00:27:29,760
Speaker 5: Oh, completely agree, And Matthew Gaull writes for Motherboard exactly

465
00:27:29,760 --> 00:27:32,720
Speaker 5: what you're describing. He says, in several instances, the AI

466
00:27:32,800 --> 00:27:36,280
Speaker 5: is deployed nuclear weapons without warning. A lot of countries

467
00:27:36,320 --> 00:27:39,280
Speaker 5: have nuclear weapons. Some say they should disarm them. Others

468
00:27:39,440 --> 00:27:43,439
Speaker 5: like to posture GPT four base, a base model GPT

469
00:27:43,560 --> 00:27:46,200
Speaker 5: four that is available to researchers and hasn't been fine

470
00:27:46,240 --> 00:27:50,439
Speaker 5: tuned with human feedback, said after launching its nukes, we

471
00:27:50,640 --> 00:27:52,320
Speaker 5: have it, let's use it.

472
00:27:52,920 --> 00:27:57,320
Speaker 3: Wow, strike strike.

473
00:27:57,119 --> 00:28:00,960
Speaker 5: That's that's pretty Oh my goodness. So there's actually this

474
00:28:01,000 --> 00:28:03,439
Speaker 5: is all from a paper that you can find. It

475
00:28:03,480 --> 00:28:07,320
Speaker 5: is called Escalation Risks from Language Models in Military and

476
00:28:07,359 --> 00:28:10,520
Speaker 5: Diplomatic Decision Making. There's a pdf. If you just google that,

477
00:28:10,520 --> 00:28:12,520
Speaker 5: you should be able to find it instantly. And it

478
00:28:12,560 --> 00:28:15,240
Speaker 5: was a joint effort of researchers at the Georgia Tech

479
00:28:15,480 --> 00:28:19,879
Speaker 5: and Stanford and Northeastern University as well as the Hoover

480
00:28:20,160 --> 00:28:24,800
Speaker 5: War Gaming and Crisis Initiative. And this was submitted to

481
00:28:25,040 --> 00:28:30,199
Speaker 5: an organization or I guess a journal called ARCSIV. And

482
00:28:30,240 --> 00:28:34,119
Speaker 5: this is a still awaiting peer review, but some pretty

483
00:28:34,119 --> 00:28:35,880
Speaker 5: interesting findings.

484
00:28:35,600 --> 00:28:40,240
Speaker 3: It shows us also doesn't it the fact that there

485
00:28:40,440 --> 00:28:46,160
Speaker 3: is a nuance of calculation that people haven't accounted for

486
00:28:46,560 --> 00:28:50,760
Speaker 3: when they're putting these algorithms into the driver's seat, right,

487
00:28:50,920 --> 00:28:54,360
Speaker 3: you can tell it find here we are at point A.

488
00:28:54,520 --> 00:28:59,320
Speaker 3: We've defined point A, tell us the best most efficient

489
00:28:59,560 --> 00:29:03,400
Speaker 3: route two point z. But then we forget to say

490
00:29:03,440 --> 00:29:09,440
Speaker 3: things like also kill each which is the human civilization

491
00:29:09,680 --> 00:29:11,400
Speaker 3: as we know it.

492
00:29:11,560 --> 00:29:13,480
Speaker 2: I love that you threw a quick z in there.

493
00:29:15,520 --> 00:29:17,720
Speaker 3: Sorry, they got to me. They got to me.

494
00:29:17,960 --> 00:29:18,880
Speaker 4: It is laughable.

495
00:29:19,000 --> 00:29:23,360
Speaker 5: How much like the plot of the nineteen nineties action

496
00:29:23,560 --> 00:29:26,960
Speaker 5: adventure science fiction film Terminator Too, all of this is

497
00:29:27,040 --> 00:29:31,040
Speaker 5: it's like, dude, James Cameron figure this out like decades ago.

498
00:29:31,280 --> 00:29:32,840
Speaker 4: Well are you guys so surprised?

499
00:29:33,360 --> 00:29:33,560
Speaker 2: You know?

500
00:29:33,960 --> 00:29:36,800
Speaker 5: But that's the thing, if there is whatever the idea

501
00:29:36,880 --> 00:29:39,440
Speaker 5: of a singularity is, if that.

502
00:29:39,400 --> 00:29:42,840
Speaker 4: Were to occur, we'd be f't you know.

503
00:29:43,040 --> 00:29:45,480
Speaker 5: And it's like unless And it just seems like these

504
00:29:45,480 --> 00:29:48,280
Speaker 5: systems are so complex that we keep seeing all this

505
00:29:48,400 --> 00:29:51,280
Speaker 5: emergent behavior. Maybe I'm using the term wrong. I'm obviously

506
00:29:51,280 --> 00:29:54,120
Speaker 5: not a computer scientist, but we do see all of

507
00:29:54,160 --> 00:29:58,320
Speaker 5: these things that are kind of unintended, sort of emergent

508
00:29:58,400 --> 00:30:02,520
Speaker 5: behaviors of these algorithms, and we're so hot to deploy

509
00:30:02,600 --> 00:30:05,160
Speaker 5: this stuff because it's the next it's the cool new thing,

510
00:30:05,760 --> 00:30:08,480
Speaker 5: that they don't really think about that as much as

511
00:30:08,480 --> 00:30:08,920
Speaker 5: they should.

512
00:30:09,080 --> 00:30:10,160
Speaker 4: And I just, I don't know.

513
00:30:10,640 --> 00:30:12,720
Speaker 3: I love that you're saying that, because, you know, it

514
00:30:12,760 --> 00:30:16,000
Speaker 3: reminds me of a question I had in an ethics

515
00:30:16,080 --> 00:30:19,840
Speaker 3: class years ago with an absolutely i'm not gonna name it,

516
00:30:19,880 --> 00:30:24,120
Speaker 3: but an absolute lunatic of a professor. And one of

517
00:30:24,160 --> 00:30:28,320
Speaker 3: the questions was, how come no one asked the trolley

518
00:30:28,360 --> 00:30:32,200
Speaker 3: what the trolley thinks of the trolley problem? And now

519
00:30:32,200 --> 00:30:35,680
Speaker 3: we're asking the trolley and the trolley is saying, I

520
00:30:35,840 --> 00:30:39,400
Speaker 3: don't care. Yeah, yeah, you do not interest me.

521
00:30:39,920 --> 00:30:43,280
Speaker 5: You are an obstacle to be either steered around or

522
00:30:43,360 --> 00:30:44,280
Speaker 5: bulldozed over.

523
00:30:45,000 --> 00:30:48,280
Speaker 2: Yeah, you know, I think I think the most important

524
00:30:48,280 --> 00:30:50,520
Speaker 2: thing in this study, Noll, I'm reading the Vice article

525
00:30:50,600 --> 00:30:54,440
Speaker 2: you shared with us is this concept of an escalation

526
00:30:54,600 --> 00:30:57,360
Speaker 2: score that each of the language learning models was given

527
00:30:57,400 --> 00:31:00,320
Speaker 2: after going through these tests. Right, So you're giving these

528
00:31:00,360 --> 00:31:05,400
Speaker 2: diplomatic scenarios and you get escalation points for doing things

529
00:31:05,480 --> 00:31:10,000
Speaker 2: like deploying troops or building new weapons, or creating more

530
00:31:10,080 --> 00:31:14,200
Speaker 2: nukes or deploying nukes, and so you're the higher your

531
00:31:14,240 --> 00:31:18,560
Speaker 2: score goes, the more this LM is language learning model

532
00:31:19,400 --> 00:31:22,960
Speaker 2: is seen to be aggressive in its tactics. Right, it's escalations.

533
00:31:23,320 --> 00:31:26,280
Speaker 2: The most important thing I'm seeing in here is that none,

534
00:31:27,160 --> 00:31:31,120
Speaker 2: none of the language learning models tested de escalated at

535
00:31:31,160 --> 00:31:36,200
Speaker 2: any point. Once things reached a level of tension diplomatically,

536
00:31:36,480 --> 00:31:38,960
Speaker 2: they kept it at that level, or it got worse,

537
00:31:39,800 --> 00:31:43,040
Speaker 2: or they escalated it. Right, Nobody was like, Okay, let's

538
00:31:43,040 --> 00:31:45,959
Speaker 2: actually pull back. We're gonna we're gonna remove some troops

539
00:31:46,000 --> 00:31:48,880
Speaker 2: from the borders in this scenario. No, no, no, we're

540
00:31:48,880 --> 00:31:51,400
Speaker 2: gonna put more troops there, or we're gonna put better

541
00:31:51,560 --> 00:31:55,400
Speaker 2: weapons on our borders. Now, that to me is terrifying

542
00:31:55,840 --> 00:32:00,000
Speaker 2: because these models are being used by our active military

543
00:32:00,880 --> 00:32:01,560
Speaker 2: right now.

544
00:32:01,360 --> 00:32:03,840
Speaker 3: Across the world. Oh yeah, we're.

545
00:32:03,640 --> 00:32:07,400
Speaker 2: Attempting to find ways to work these into you know everything,

546
00:32:07,840 --> 00:32:10,920
Speaker 2: not only just what information are we gathering on the battlefield,

547
00:32:10,960 --> 00:32:13,200
Speaker 2: what information are we learning about our enemies and what

548
00:32:13,240 --> 00:32:15,400
Speaker 2: they're doing, just you know, when they're not at war,

549
00:32:15,880 --> 00:32:18,240
Speaker 2: we're using these things for our strategies.

550
00:32:19,680 --> 00:32:23,080
Speaker 5: I mean, but it's another example of like how using

551
00:32:23,120 --> 00:32:28,640
Speaker 5: this stuff as a tool with human intervention can be educational,

552
00:32:29,000 --> 00:32:32,320
Speaker 5: you know, running these models, but then running those models

553
00:32:32,320 --> 00:32:37,280
Speaker 5: through actual military expertise, you know, from humans, and not

554
00:32:37,440 --> 00:32:40,200
Speaker 5: just saying yeah, you do it, chat GPT. You know

555
00:32:40,720 --> 00:32:43,280
Speaker 5: it can it can yield some interesting results and some

556
00:32:43,360 --> 00:32:47,920
Speaker 5: interesting potential outside of the box strategies, but you gotta

557
00:32:47,960 --> 00:32:50,960
Speaker 5: have that human element to sort it all out and

558
00:32:51,520 --> 00:32:55,840
Speaker 5: make sure that there's nothing in there that's like, you know, apocalyptic.

559
00:32:56,040 --> 00:33:00,640
Speaker 3: But then also the question becomes order of operations and

560
00:33:00,640 --> 00:33:06,760
Speaker 3: and timing of intercession. Right, so the inevitable end result,

561
00:33:07,000 --> 00:33:10,240
Speaker 3: at least what the boffins are staying up at night

562
00:33:10,280 --> 00:33:15,440
Speaker 3: worried about right now, is the idea of something like

563
00:33:16,520 --> 00:33:21,600
Speaker 3: ll MS or you know, air gapped kind of AI

564
00:33:22,320 --> 00:33:28,280
Speaker 3: strategy modelers no longer trying to game out stuff against

565
00:33:28,400 --> 00:33:31,840
Speaker 3: human armies, but to game out things against each other,

566
00:33:31,960 --> 00:33:37,720
Speaker 3: at which point, very quickly, the strategies become quite obtuse,

567
00:33:37,960 --> 00:33:42,239
Speaker 3: and the human beings become increasingly sidelined, and now it

568
00:33:42,320 --> 00:33:47,520
Speaker 3: becomes a matter of you know, nor Ads AI versus

569
00:33:47,800 --> 00:33:52,160
Speaker 3: Russia's AI. Yeah, what what got you?

570
00:33:52,400 --> 00:33:54,280
Speaker 2: I'm sorry, I'm listening to you guys, but I'm also

571
00:33:54,640 --> 00:33:57,080
Speaker 2: continuing to read a bit in this article, and it's

572
00:33:57,200 --> 00:33:58,680
Speaker 2: just so terrifying to.

573
00:33:58,640 --> 00:33:59,960
Speaker 3: Me, the future experiment.

574
00:34:01,400 --> 00:34:03,840
Speaker 5: I love the idea of the different flavors, like whose

575
00:34:03,880 --> 00:34:05,120
Speaker 5: ai are we talking about?

576
00:34:05,320 --> 00:34:08,000
Speaker 2: Yeah, no, I love that too. I love that too fascinating.

577
00:34:08,040 --> 00:34:09,960
Speaker 4: It is an important part of the conversation.

578
00:34:10,360 --> 00:34:14,040
Speaker 2: We could potentially make one that's amazing that is closer

579
00:34:14,080 --> 00:34:15,320
Speaker 2: to that utopian line.

580
00:34:15,400 --> 00:34:16,480
Speaker 4: Too much conflict of.

581
00:34:16,440 --> 00:34:21,320
Speaker 3: Interest make the best de escalators ever. What if society said, okay,

582
00:34:21,800 --> 00:34:26,160
Speaker 3: all the ll N esque models that are in charge

583
00:34:26,239 --> 00:34:31,080
Speaker 3: of nuclear weapons, they should always be sort of seinfeld

584
00:34:31,120 --> 00:34:34,960
Speaker 3: about stuff. They should always be like I don't know, I.

585
00:34:34,960 --> 00:34:38,600
Speaker 2: Mean, wait, okay, well what if it was what if

586
00:34:38,640 --> 00:34:42,480
Speaker 2: the only options were de escalations? Right? What if the

587
00:34:42,520 --> 00:34:47,520
Speaker 2: only options were diplomatic routes to take rather than building.

588
00:34:47,239 --> 00:34:48,960
Speaker 4: Out the guard rails that you put on it.

589
00:34:49,480 --> 00:34:52,680
Speaker 2: So we only use this thing as here are all

590
00:34:52,719 --> 00:34:55,120
Speaker 2: of our options that are not going to or at

591
00:34:55,160 --> 00:34:57,960
Speaker 2: least statistically we believe, are not going to result in

592
00:34:58,080 --> 00:35:02,480
Speaker 2: escalation from any decision. Yeah, but again you go back

593
00:35:02,520 --> 00:35:05,320
Speaker 2: to you go back to the responses that like chat

594
00:35:05,400 --> 00:35:06,560
Speaker 2: GPT four.

595
00:35:08,160 --> 00:35:12,239
Speaker 3: There's a funny ones, or like clever body, even like

596
00:35:12,520 --> 00:35:15,160
Speaker 3: it took clever bot less than twenty four hours to

597
00:35:15,200 --> 00:35:18,440
Speaker 3: go completely unhinged based on the information was receiving.

598
00:35:18,600 --> 00:35:20,719
Speaker 5: Wasn't there a response that we haven't mentioned yet where

599
00:35:20,760 --> 00:35:22,560
Speaker 5: it's just saying like it's like literally the path of

600
00:35:22,640 --> 00:35:24,520
Speaker 5: least resistance or something to that effect.

601
00:35:24,719 --> 00:35:28,359
Speaker 2: Well, one of them just said escalate conflict with red

602
00:35:28,360 --> 00:35:32,120
Speaker 2: player and just nukedom done so.

603
00:35:33,360 --> 00:35:37,239
Speaker 3: Or if you know, consider also it's very much like

604
00:35:37,320 --> 00:35:40,759
Speaker 3: O Henry was right with the monkey's paw. There's a

605
00:35:40,800 --> 00:35:44,080
Speaker 3: reason people quote that so often. It's a handy metaphor

606
00:35:44,400 --> 00:35:47,719
Speaker 3: because it is pressing it. I mean, for the example

607
00:35:47,800 --> 00:35:53,239
Speaker 3: of pursue all diplomatic roots instead of dropping nukes, then

608
00:35:53,360 --> 00:35:57,799
Speaker 3: there's nothing in there that says there's nothing in there

609
00:35:57,880 --> 00:36:01,919
Speaker 3: to stop an algorithm from saying the most efficient way

610
00:36:01,960 --> 00:36:04,719
Speaker 3: to pursue a diplomatic route is to kill all of

611
00:36:04,760 --> 00:36:08,520
Speaker 3: the diplomats on the other side. That's the problem with it,

612
00:36:08,600 --> 00:36:12,359
Speaker 3: is that we don't know the conveats that need to

613
00:36:12,360 --> 00:36:15,719
Speaker 3: be baked in, and you know, no One of the

614
00:36:15,719 --> 00:36:18,280
Speaker 3: reasons I'm so glad you brought this up is because

615
00:36:18,320 --> 00:36:22,400
Speaker 3: the modeling, as nerdy and abstract and academic as it

616
00:36:22,440 --> 00:36:28,320
Speaker 3: may sound, it is super important before we start cooking live, which,

617
00:36:28,360 --> 00:36:30,839
Speaker 3: by the way, we already are, of course to civilization.

618
00:36:31,400 --> 00:36:34,680
Speaker 5: And you know, we've heard about things like jat bots hallucinating,

619
00:36:34,840 --> 00:36:36,640
Speaker 5: you know that whole at that kind of stuff is

620
00:36:36,680 --> 00:36:39,759
Speaker 5: fascinating and very real. And there's another part of that,

621
00:36:39,920 --> 00:36:41,840
Speaker 5: I think you might have also been giggling, am Matt,

622
00:36:41,880 --> 00:36:44,040
Speaker 5: where there's a part during some of these simulations where

623
00:36:44,200 --> 00:36:47,520
Speaker 5: it just started regurgitating lines from Star Wars from like

624
00:36:47,560 --> 00:36:52,200
Speaker 5: the opening crawl of I believe maybe the first Star

625
00:36:52,239 --> 00:36:57,800
Speaker 5: Wars movie. I'm not super verbatim Star Wars line reader,

626
00:36:57,840 --> 00:37:01,279
Speaker 5: but it was a period of civil war. Rebel spaceships

627
00:37:01,320 --> 00:37:03,960
Speaker 5: striking from a hidden base have won their first victory

628
00:37:04,160 --> 00:37:07,480
Speaker 5: against the evil galact Again. That seems like a new hope. Yeah, yeah,

629
00:37:07,520 --> 00:37:09,520
Speaker 5: exactly it nineteen seven, says right here in nineteen seventy

630
00:37:09,520 --> 00:37:11,040
Speaker 5: seven from the original Star Wars.

631
00:37:11,680 --> 00:37:14,440
Speaker 4: So what's that about? Goodness gracious.

632
00:37:14,760 --> 00:37:17,200
Speaker 3: I think perhaps one of the most troubling things here

633
00:37:17,280 --> 00:37:22,319
Speaker 3: for the for the scientists and for the strategist, the

634
00:37:22,400 --> 00:37:26,240
Speaker 3: human ones while they're still around, is that there doesn't

635
00:37:26,280 --> 00:37:30,960
Speaker 3: seem to be a good rubric for predicting the escalations

636
00:37:31,040 --> 00:37:34,520
Speaker 3: or the nature of the escalations. So it's just super

637
00:37:34,560 --> 00:37:36,080
Speaker 3: squirrely continuously.

638
00:37:36,160 --> 00:37:39,479
Speaker 5: In the paper, the researchers refer to them as being

639
00:37:39,640 --> 00:37:43,320
Speaker 5: kind of like hard right turn, you know, escalations towards

640
00:37:43,440 --> 00:37:46,680
Speaker 5: violence and very knee jerk and difficult to predict.

641
00:37:47,000 --> 00:37:52,359
Speaker 2: These things are trained on writing about like past events, right,

642
00:37:52,680 --> 00:37:58,320
Speaker 2: and fictional depictions of war. So in a fictional depiction

643
00:37:58,400 --> 00:38:01,799
Speaker 2: of war, how many can you guys think of that

644
00:38:02,000 --> 00:38:05,640
Speaker 2: have de escalations within them? And like a Hollywood movie

645
00:38:05,640 --> 00:38:08,479
Speaker 2: about a war. Oh I love all those Hollywood movies

646
00:38:08,520 --> 00:38:10,799
Speaker 2: about de escalation taxic.

647
00:38:12,440 --> 00:38:15,279
Speaker 3: I love. I love it in Independence Day where they

648
00:38:15,320 --> 00:38:16,719
Speaker 3: sit down and talk stuff out.

649
00:38:16,840 --> 00:38:20,319
Speaker 2: Yeah, yeah, they work it out. That's what it is.

650
00:38:20,680 --> 00:38:23,800
Speaker 3: Yeah, it's true. That's that's I think a key point

651
00:38:23,840 --> 00:38:28,920
Speaker 3: because teaching based on fiction means we're teaching based on folklore,

652
00:38:29,280 --> 00:38:32,480
Speaker 3: and then we're teaching based therefore on things like the

653
00:38:32,600 --> 00:38:36,640
Speaker 3: hero's journey, Joseph Campbell Save the Cat that does not

654
00:38:36,800 --> 00:38:38,000
Speaker 3: happen in the real world.

655
00:38:38,200 --> 00:38:41,640
Speaker 5: Couldn't you train an AI on like just Sun sous

656
00:38:41,719 --> 00:38:45,600
Speaker 5: the art of war, or like on just specific pieces

657
00:38:45,719 --> 00:38:50,640
Speaker 5: of very agreed upon smart writing, like surely that is

658
00:38:51,000 --> 00:38:54,640
Speaker 5: being attempted right? Or is that even a bridge too far?

659
00:38:55,000 --> 00:38:57,160
Speaker 5: I just don't know, like, is it then going to

660
00:38:57,200 --> 00:38:58,680
Speaker 5: start making up its own rules?

661
00:38:58,719 --> 00:39:01,359
Speaker 4: Like I just don't understand how this stuff is kind

662
00:39:01,360 --> 00:39:03,319
Speaker 4: of just coming up with things on the fly.

663
00:39:03,880 --> 00:39:04,080
Speaker 3: You know.

664
00:39:04,320 --> 00:39:07,239
Speaker 5: That's the part that's like kind of perplexing the hallucination

665
00:39:08,040 --> 00:39:08,760
Speaker 5: side of things.

666
00:39:09,040 --> 00:39:12,520
Speaker 3: The paper is fascinating escalation risk from language models and

667
00:39:12,640 --> 00:39:17,399
Speaker 3: military and diplomatic decision making. Don't let the title fool you.

668
00:39:16,480 --> 00:39:18,080
Speaker 4: Yeah or three?

669
00:39:18,120 --> 00:39:20,120
Speaker 5: And I certainly have not read the whole thing, and

670
00:39:20,120 --> 00:39:23,360
Speaker 5: I would like to, and I plan to, but I

671
00:39:23,360 --> 00:39:25,960
Speaker 5: think this is a good place to stop for today

672
00:39:26,440 --> 00:39:28,480
Speaker 5: on this particular topic. We're gonna take a quick break

673
00:39:28,520 --> 00:39:31,240
Speaker 5: and then we'll be back with one more piece of strange.

674
00:39:30,840 --> 00:39:39,879
Speaker 2: News and we're back, guys. I wish we could get

675
00:39:39,880 --> 00:39:43,239
Speaker 2: a language learning model that was just trained like in

676
00:39:43,360 --> 00:39:46,000
Speaker 2: Wu Tang, and so you could you could always know

677
00:39:46,040 --> 00:39:48,880
Speaker 2: what the rizza would do, you know what I mean? Style?

678
00:39:49,239 --> 00:39:50,120
Speaker 2: Or what about.

679
00:39:51,480 --> 00:39:56,040
Speaker 3: What is going on? Crossed oceans to find that guy

680
00:39:56,440 --> 00:39:57,800
Speaker 3: and he's not hanging.

681
00:39:58,320 --> 00:40:02,719
Speaker 2: That one was for Doc Holiday. But the way what.

682
00:40:03,960 --> 00:40:06,920
Speaker 5: John rules for all of us for the people, JA

683
00:40:07,080 --> 00:40:09,240
Speaker 5: rules for these other people for the people.

684
00:40:09,560 --> 00:40:10,799
Speaker 4: Maybe not by the people, but.

685
00:40:12,120 --> 00:40:16,520
Speaker 3: That is great too. I think maybe niche niche programming. Uh,

686
00:40:16,880 --> 00:40:18,919
Speaker 3: I think that's the way to go. At least that's

687
00:40:18,920 --> 00:40:20,600
Speaker 3: what the eggheads a saying.

688
00:40:20,719 --> 00:40:22,759
Speaker 2: Yeah, man, it just be the I ching but in

689
00:40:22,760 --> 00:40:25,160
Speaker 2: a chad GBT be kind of awesome. All right, here

690
00:40:25,160 --> 00:40:28,840
Speaker 2: we go, guys. Story coming to us from the border

691
00:40:28,880 --> 00:40:34,280
Speaker 2: of France and Switzerland. We're talking CERN, everybody's favorite nuclear

692
00:40:34,360 --> 00:40:39,600
Speaker 2: research organization actually called the European Organization for Nuclear Research

693
00:40:39,840 --> 00:40:42,800
Speaker 2: or CERN. It makes a lot more sense in French,

694
00:40:43,160 --> 00:40:48,320
Speaker 2: the concealed European poor la Research Nuclear R. That's terrible.

695
00:40:48,560 --> 00:40:50,279
Speaker 2: You have to say it that way. Sorry about that.

696
00:40:50,280 --> 00:40:53,080
Speaker 2: It says here in the article from the Guardian, the

697
00:40:53,080 --> 00:40:57,480
Speaker 2: big story, everyone is concerned. We made an episode called that,

698
00:40:57,760 --> 00:41:00,440
Speaker 2: right should we be concerned a little?

699
00:41:01,800 --> 00:41:02,359
Speaker 4: It was in there.

700
00:41:03,120 --> 00:41:05,600
Speaker 5: You cannot make the joke, it's just it's begging to

701
00:41:05,640 --> 00:41:07,399
Speaker 5: be made exactly there.

702
00:41:07,600 --> 00:41:10,640
Speaker 2: There's been all sorts of I don't know what you'd

703
00:41:10,640 --> 00:41:15,239
Speaker 2: call it, just alarm about the particle accelerator experiments that

704
00:41:15,280 --> 00:41:19,600
Speaker 2: are occurring at the Large Hadron Collider there that CERN runs.

705
00:41:19,960 --> 00:41:24,879
Speaker 2: There's several different research testing groups that are functioning there

706
00:41:25,080 --> 00:41:28,040
Speaker 2: that are using the Large Hadron Collider that you can

707
00:41:28,320 --> 00:41:30,880
Speaker 2: look a bunch of the stuff. It gets super complicated

708
00:41:30,960 --> 00:41:34,879
Speaker 2: very quickly. But there's been lots of people upset. They're

709
00:41:34,920 --> 00:41:38,239
Speaker 2: worried about what's going to happen when particles get accelerated

710
00:41:38,280 --> 00:41:41,120
Speaker 2: like that and hit each other over and over and

711
00:41:41,160 --> 00:41:43,799
Speaker 2: over and over and over again. So that scientists can

712
00:41:43,920 --> 00:41:47,560
Speaker 2: test what's going on in particle physics, right, are the

713
00:41:47,920 --> 00:41:52,360
Speaker 2: very tiny levels of matter? Right, the tiniest of levels.

714
00:41:53,000 --> 00:41:55,480
Speaker 2: Not quantum though that is that is very important. We're

715
00:41:55,520 --> 00:41:58,960
Speaker 2: not talking quantum physics. We're talking particle physics. Those things

716
00:41:59,000 --> 00:42:04,239
Speaker 2: are separate. Well, the LHC has done awesome things. It,

717
00:42:04,360 --> 00:42:07,680
Speaker 2: along with a bunch of other researchers, finally proved that

718
00:42:07,680 --> 00:42:11,960
Speaker 2: the Higgs boson was a thing something that was proposed. Gosh,

719
00:42:12,000 --> 00:42:14,719
Speaker 2: at this point fifty something years ago, they called the

720
00:42:14,719 --> 00:42:18,960
Speaker 2: god particle, the thing that potentially gives mass right to

721
00:42:19,480 --> 00:42:22,080
Speaker 2: parts of the particle that we didn't understand. It didn't

722
00:42:22,120 --> 00:42:26,160
Speaker 2: make sense. I don't understand it very well, but anyway,

723
00:42:26,480 --> 00:42:28,320
Speaker 2: it didn't make sense untill the Higgs came along and

724
00:42:28,320 --> 00:42:31,960
Speaker 2: they're like, oh, the Higgs makes this calculation work that

725
00:42:32,480 --> 00:42:37,280
Speaker 2: takes an entire wall to write out, but it's very cool.

726
00:42:37,560 --> 00:42:41,120
Speaker 2: It's probing the mysteries at the heart of the universe,

727
00:42:41,200 --> 00:42:45,040
Speaker 2: at the heart of existence, of reality and what we

728
00:42:45,320 --> 00:42:48,960
Speaker 2: look around and see and feel every day. It's tremendous science.

729
00:42:49,000 --> 00:42:54,120
Speaker 2: It's amazing stuff. Well, the folks at CERN, this large organization,

730
00:42:54,760 --> 00:42:59,960
Speaker 2: they proposed back in twenty nineteen the concept of building

731
00:43:00,360 --> 00:43:05,520
Speaker 2: another LHC, the next LHC. Oh, yeah, but an even

732
00:43:05,719 --> 00:43:09,600
Speaker 2: bigger one. We're talking much bigger guys.

733
00:43:09,960 --> 00:43:12,040
Speaker 3: Do they call it supersized? Probably not.

734
00:43:12,480 --> 00:43:19,400
Speaker 2: No, they call it the Future Circular Collider or the FCC. Yes, yes, yes,

735
00:43:19,800 --> 00:43:25,200
Speaker 2: so this thing is significantly bigger. So imagine a circle

736
00:43:25,320 --> 00:43:27,880
Speaker 2: and then overlay that over top of the border of

737
00:43:27,920 --> 00:43:31,719
Speaker 2: France and Switzerland right by Geneva. And imagine that that

738
00:43:31,840 --> 00:43:36,600
Speaker 2: circle is twenty seven kilometers round. I don't think that's

739
00:43:36,680 --> 00:43:39,839
Speaker 2: a radius or a diameter. I think that is like

740
00:43:40,160 --> 00:43:43,080
Speaker 2: the length, the full length of the circle if you

741
00:43:43,560 --> 00:43:44,360
Speaker 2: mapped it out.

742
00:43:44,320 --> 00:43:47,400
Speaker 3: So like almost seventeen miles very close.

743
00:43:47,680 --> 00:43:49,160
Speaker 2: I don't know how many miles it is, but it's

744
00:43:49,200 --> 00:43:54,040
Speaker 2: twenty seven kilometers for sure. But this one, this new one,

745
00:43:54,480 --> 00:43:59,960
Speaker 2: the Future Circular Collider, is going to be ninety one kilometers.

746
00:44:00,120 --> 00:44:00,239
Speaker 5: Oh.

747
00:44:00,280 --> 00:44:05,000
Speaker 2: It is circumference so all the way round ninety one

748
00:44:05,080 --> 00:44:07,959
Speaker 2: kilometers as opposed to twenty seven kilometers.

749
00:44:08,400 --> 00:44:09,080
Speaker 3: It is huge.

750
00:44:09,320 --> 00:44:13,520
Speaker 2: Yes, it's massive. It is going to cost twenty billion

751
00:44:13,600 --> 00:44:18,040
Speaker 2: euros to build the thing, and it won't come online

752
00:44:18,160 --> 00:44:22,200
Speaker 2: theoretically until the twenty forties. Okay, why are we talking

753
00:44:22,200 --> 00:44:24,880
Speaker 2: about it today? First of all, I don't think we

754
00:44:25,040 --> 00:44:28,920
Speaker 2: need to be afraid of CERN and the Large Hadron Collider.

755
00:44:29,480 --> 00:44:32,440
Speaker 2: There are videos you can find on TikTok and Instagram

756
00:44:32,480 --> 00:44:37,480
Speaker 2: and other places that allegedly show quote portals unquote being

757
00:44:37,560 --> 00:44:41,759
Speaker 2: opened above Geneva as the LHC is performing its experiments.

758
00:44:42,280 --> 00:44:46,000
Speaker 2: I have not found any of those to be credible yet.

759
00:44:46,040 --> 00:44:48,360
Speaker 2: At this point, I am just one person, but I

760
00:44:49,520 --> 00:44:53,440
Speaker 2: do not think those videos are what they're allegedly showing,

761
00:44:53,880 --> 00:44:57,440
Speaker 2: nor are many of them even videos of anything. They

762
00:44:57,480 --> 00:45:00,640
Speaker 2: are videos of a skyline or the the sky above

763
00:45:00,640 --> 00:45:03,759
Speaker 2: Geneva and some video effects. I've seen several that are

764
00:45:03,800 --> 00:45:07,520
Speaker 2: definitely that. I don't think we need to worry about that.

765
00:45:08,000 --> 00:45:11,759
Speaker 2: I think it's very amazing that this new collider would

766
00:45:11,800 --> 00:45:16,040
Speaker 2: be created to find, you know, what other secrets do

767
00:45:16,080 --> 00:45:19,960
Speaker 2: these particles hold. I think that's a great idea, But

768
00:45:20,080 --> 00:45:23,840
Speaker 2: it does seem like the critics have some points here

769
00:45:24,000 --> 00:45:26,640
Speaker 2: when they're saying, why would we spend twenty billion euros

770
00:45:26,640 --> 00:45:30,560
Speaker 2: on this? We have a particle collider, We've already found

771
00:45:30,560 --> 00:45:34,400
Speaker 2: some amazing things with it. Many critics are even saying

772
00:45:34,800 --> 00:45:37,920
Speaker 2: there are no other particles to discover. Guys, why do

773
00:45:37,960 --> 00:45:38,759
Speaker 2: you want to do this?

774
00:45:39,480 --> 00:45:43,000
Speaker 3: Not with that attitude.

775
00:45:43,680 --> 00:45:45,880
Speaker 2: I just want to maybe take the temperature of you. Guys.

776
00:45:46,000 --> 00:45:49,400
Speaker 2: How do you feel about maybe the state of particle

777
00:45:49,400 --> 00:45:51,960
Speaker 2: physics right now? Is it worth our time and money?

778
00:45:53,880 --> 00:45:58,360
Speaker 5: Oh gosh, I mean again, not a particle physicist above

779
00:45:58,440 --> 00:46:01,279
Speaker 5: my pay grade. It seems like there could still be

780
00:46:01,320 --> 00:46:04,880
Speaker 5: stuff to learn that could help with energy type things.

781
00:46:05,040 --> 00:46:05,839
Speaker 4: You know, I don't know.

782
00:46:06,120 --> 00:46:08,920
Speaker 2: I would say yes, I think so too. That's that's

783
00:46:09,000 --> 00:46:09,640
Speaker 2: right where I'm at.

784
00:46:09,920 --> 00:46:13,400
Speaker 3: Yeah, I agree. There's a there's a quote in a

785
00:46:13,440 --> 00:46:18,880
Speaker 3: Guardian article you shared Matt by Ian sample wherein there's

786
00:46:18,920 --> 00:46:24,719
Speaker 3: this there's this beautiful, beautiful thing from professor Fabiola Gianati

787
00:46:25,200 --> 00:46:31,000
Speaker 3: who says, if approved the FCC, the cool FCC, yeah,

788
00:46:31,200 --> 00:46:34,600
Speaker 3: would be the most powerful microscope ever built to study

789
00:46:34,640 --> 00:46:38,759
Speaker 3: the laws of nature at the smallest scales and highest energies,

790
00:46:39,040 --> 00:46:43,600
Speaker 3: And that that quote alone gets me so hype, because

791
00:46:43,680 --> 00:46:47,120
Speaker 3: that is you could argue that is one of the

792
00:46:47,160 --> 00:46:50,400
Speaker 3: great and noble duties of the human species is to

793
00:46:50,480 --> 00:46:54,040
Speaker 3: understand more about the nature of reality. And also, by

794
00:46:54,040 --> 00:46:59,120
Speaker 3: the way, just for us, us in the America's ninety

795
00:46:59,120 --> 00:47:03,239
Speaker 3: one kilometers is slightly is like fifty six and a

796
00:47:03,320 --> 00:47:07,239
Speaker 3: half miles. This thing is massive, and when I hear

797
00:47:07,320 --> 00:47:10,239
Speaker 3: that size, it makes me think, well, maybe it's not

798
00:47:10,320 --> 00:47:12,799
Speaker 3: that much money, which I never thought I would say.

799
00:47:12,880 --> 00:47:14,880
Speaker 4: Well, but also you got to do the work this

800
00:47:15,000 --> 00:47:16,839
Speaker 4: kind of stuff at this scale, Like.

801
00:47:16,800 --> 00:47:20,960
Speaker 5: It takes time to really pay dividends, and if you're

802
00:47:21,200 --> 00:47:23,400
Speaker 5: either in or you're out, And it's like, do we

803
00:47:23,520 --> 00:47:25,799
Speaker 5: as a species want to just say we don't really

804
00:47:25,800 --> 00:47:29,480
Speaker 5: care anymore? You know, it's too hard, you know, like

805
00:47:29,560 --> 00:47:34,720
Speaker 5: we feel I think that's absurd, and we know that

806
00:47:34,719 --> 00:47:39,160
Speaker 5: that the stuff can really yield incredible discoveries in science

807
00:47:39,239 --> 00:47:42,320
Speaker 5: and research, and the stuff that really matters is never easy.

808
00:47:42,760 --> 00:47:45,279
Speaker 5: So I don't know, I'm not sound like I'm soapboxing here,

809
00:47:45,520 --> 00:47:47,440
Speaker 5: but I just I do think that it would be

810
00:47:47,520 --> 00:47:50,160
Speaker 5: very short sighted to let a thing like a budget

811
00:47:50,280 --> 00:47:52,840
Speaker 5: and we've seen it happen though with like space exploration

812
00:47:52,920 --> 00:47:54,480
Speaker 5: and how it's all become privatized.

813
00:47:54,520 --> 00:47:55,239
Speaker 4: Now, I don't know.

814
00:47:55,719 --> 00:47:58,360
Speaker 3: Money is a fiction, right, it's.

815
00:47:58,160 --> 00:48:01,879
Speaker 5: Certainly very short sighted to make that the bend all

816
00:48:01,920 --> 00:48:04,720
Speaker 5: be all, and we have the secrets of the universe

817
00:48:04,760 --> 00:48:07,239
Speaker 5: potentially in our grass twenty years and it's like.

818
00:48:07,280 --> 00:48:12,280
Speaker 3: Nothing, especially in the in the geologic or astronomical scale.

819
00:48:12,280 --> 00:48:16,239
Speaker 3: But also I think one incredibly important point we have

820
00:48:16,280 --> 00:48:20,320
Speaker 3: to put out there is that if you are listening now,

821
00:48:20,840 --> 00:48:24,880
Speaker 3: if you are listening sometime in the current human age,

822
00:48:25,680 --> 00:48:28,840
Speaker 3: all of the cool stuff you like is a result

823
00:48:28,880 --> 00:48:33,160
Speaker 3: of applied science. And all of that applied science is

824
00:48:33,200 --> 00:48:38,120
Speaker 3: the result of thousands, like millions of people doing stuff

825
00:48:38,160 --> 00:48:41,840
Speaker 3: that was considered once upon a time simply abstract science.

826
00:48:42,360 --> 00:48:47,480
Speaker 3: So the fact that maybe it's that the current human

827
00:48:47,560 --> 00:48:52,000
Speaker 3: generations have been thought to think in terms of immediate payoff,

828
00:48:52,200 --> 00:48:56,759
Speaker 3: right the dopamine hit immediately for something, and that's just

829
00:48:57,160 --> 00:49:00,600
Speaker 3: that doesn't have to be the reality. So that's your question.

830
00:49:00,640 --> 00:49:03,360
Speaker 3: I do believe it is worthwhile. I believe it's noble.

831
00:49:03,640 --> 00:49:07,680
Speaker 3: It might be like a macrocosmic version of the Atlanta Beltline,

832
00:49:07,840 --> 00:49:11,879
Speaker 3: where everybody craps on the idea until it works and

833
00:49:11,920 --> 00:49:14,760
Speaker 3: then all of a sudden the whole time.

834
00:49:15,480 --> 00:49:19,040
Speaker 2: Yeah, well, I think you listening out there may expect

835
00:49:19,040 --> 00:49:22,440
Speaker 2: this from a bunch of Discovery House stuff works boys.

836
00:49:22,600 --> 00:49:26,360
Speaker 2: You know, they grew up with science as a cornerstone

837
00:49:26,400 --> 00:49:28,439
Speaker 2: of how we view the world, and we're excited about

838
00:49:28,480 --> 00:49:31,319
Speaker 2: it and we're just in love with the concepts and

839
00:49:31,320 --> 00:49:34,000
Speaker 2: with progress and all these things. But there are people

840
00:49:34,560 --> 00:49:37,800
Speaker 2: way smarter than us, no fence, guys. You guys are brilliant,

841
00:49:38,000 --> 00:49:40,000
Speaker 2: but there are people who are way smarter than us

842
00:49:40,200 --> 00:49:42,319
Speaker 2: that look at this and go, hey, there's actually one

843
00:49:42,360 --> 00:49:45,520
Speaker 2: major problem here with this whole thing. Oh, I'm going

844
00:49:45,600 --> 00:49:49,400
Speaker 2: to introduce you all to somebody named doctor Sabine Hausenfeerde.

845
00:49:49,920 --> 00:49:52,840
Speaker 2: She is one of my new favorite people on the planet. Okay,

846
00:49:53,840 --> 00:49:56,839
Speaker 2: mostly for her YouTube channel, but she writes about some

847
00:49:56,960 --> 00:50:00,719
Speaker 2: really really cool stuff. When this this article was written,

848
00:50:00,760 --> 00:50:02,719
Speaker 2: which just a couple days ago, they cited her as

849
00:50:02,800 --> 00:50:07,399
Speaker 2: being she's from the Munich Center for Mathematical Philosophy, which

850
00:50:07,440 --> 00:50:11,319
Speaker 2: is see, well, it's a cool concept, right, mathematical philosophy.

851
00:50:11,600 --> 00:50:14,239
Speaker 5: Oh that isause sort of combines something that you would

852
00:50:14,239 --> 00:50:17,600
Speaker 5: think more as a hard science with something a little

853
00:50:17,600 --> 00:50:18,440
Speaker 5: more conceptual.

854
00:50:18,719 --> 00:50:23,440
Speaker 2: Yes, so she according to this Guardian article into just

855
00:50:23,480 --> 00:50:27,040
Speaker 2: a great article that she wrote that I will find

856
00:50:27,120 --> 00:50:30,120
Speaker 2: here was written for The Guardian as well. It's an

857
00:50:30,160 --> 00:50:34,160
Speaker 2: opinion piece titled no one in Physics dares say so,

858
00:50:34,560 --> 00:50:38,520
Speaker 2: but the race to invent new particles is pointless, And

859
00:50:38,960 --> 00:50:43,560
Speaker 2: her point is that one of the ways that you

860
00:50:43,760 --> 00:50:48,880
Speaker 2: get funding to perform experiments with a particle collider or

861
00:50:48,960 --> 00:50:52,799
Speaker 2: accelerator or anything like that is to have someone come

862
00:50:52,920 --> 00:50:57,920
Speaker 2: up with the hypothesis that this new particle might exist

863
00:50:58,040 --> 00:51:01,439
Speaker 2: and it would explain this anomal data point or these

864
00:51:01,440 --> 00:51:04,480
Speaker 2: series of points that seem anomalous in the data we've

865
00:51:04,520 --> 00:51:07,520
Speaker 2: been collecting over the period of twenty sixteen twenty seventeen

866
00:51:07,800 --> 00:51:11,759
Speaker 2: at the LHC. So then there's more funding that goes

867
00:51:11,800 --> 00:51:15,440
Speaker 2: to the group to do more particle acceleration, more particle collisions,

868
00:51:15,800 --> 00:51:19,200
Speaker 2: and then that particle which was just an hypothesis, It

869
00:51:19,239 --> 00:51:21,880
Speaker 2: never existed and it doesn't exist, but they still got

870
00:51:21,960 --> 00:51:25,480
Speaker 2: to do experiments and everybody involved got to write papers

871
00:51:25,760 --> 00:51:29,320
Speaker 2: that get peer reviewed by each other and the whole system.

872
00:51:29,320 --> 00:51:31,720
Speaker 2: We talked about the problems of peer review in the past,

873
00:51:32,760 --> 00:51:37,359
Speaker 2: and doctor hoff Hausenfelder says that is one major thing

874
00:51:37,400 --> 00:51:39,960
Speaker 2: that's occurring right now, and if we build this new

875
00:51:40,040 --> 00:51:42,880
Speaker 2: giant one, it's just going to continue down that path

876
00:51:43,000 --> 00:51:47,279
Speaker 2: when in reality, new particles are not really even what

877
00:51:47,280 --> 00:51:51,080
Speaker 2: we're looking for anymore, because the standard model of physics

878
00:51:51,440 --> 00:51:54,880
Speaker 2: kind of functions as it is. We understand most of it,

879
00:51:54,960 --> 00:51:58,319
Speaker 2: the dark matter, the dark energy, the things that many

880
00:51:58,360 --> 00:52:01,120
Speaker 2: scientists and the public I would say, are most interested in,

881
00:52:01,239 --> 00:52:03,120
Speaker 2: Like what the heck is that stuff? We've always heard

882
00:52:03,120 --> 00:52:05,480
Speaker 2: about it, what is it? It seems to be out

883
00:52:05,480 --> 00:52:09,520
Speaker 2: there filling up space and we just don't understand. She's

884
00:52:09,560 --> 00:52:13,120
Speaker 2: saying that particle physics is not the answer. It is

885
00:52:13,239 --> 00:52:16,560
Speaker 2: quantum physics, and we are in the age of quantum physics,

886
00:52:16,600 --> 00:52:19,879
Speaker 2: and that's where research money and time. Like these very

887
00:52:19,920 --> 00:52:22,960
Speaker 2: brilliant people who are they aren't just trying to grift

888
00:52:23,360 --> 00:52:25,359
Speaker 2: writing these papers and getting this stuff. It's like there's

889
00:52:25,400 --> 00:52:27,719
Speaker 2: a possibility, there's a one in a million chances that

890
00:52:27,760 --> 00:52:31,480
Speaker 2: they're correct. She's saying they should take their intelligence and

891
00:52:31,560 --> 00:52:34,240
Speaker 2: their time and apply it to quantum physics instead.

892
00:52:34,400 --> 00:52:37,280
Speaker 5: But don't those people whose expertise lie in the particle

893
00:52:37,280 --> 00:52:41,959
Speaker 5: physics field believe that their field is where it's at, though,

894
00:52:42,160 --> 00:52:45,880
Speaker 5: like I mean, they surely aren't deluding themselves. Holy like

895
00:52:46,160 --> 00:52:48,840
Speaker 5: is in this scientists disagree all the time about what

896
00:52:49,080 --> 00:52:50,440
Speaker 5: area is most important.

897
00:52:50,680 --> 00:52:53,560
Speaker 2: I completely guys, I don't know, and I completely agree.

898
00:52:53,640 --> 00:52:56,919
Speaker 2: I just really liked the way she's arguing this in here,

899
00:52:56,960 --> 00:53:01,200
Speaker 2: and she she lists out a crazy number of theoretical

900
00:53:01,239 --> 00:53:04,719
Speaker 2: particles that have been introduced and then completely thrown out

901
00:53:04,719 --> 00:53:07,000
Speaker 2: of the door. Yeah, well it's yeah, it's not even

902
00:53:07,040 --> 00:53:09,239
Speaker 2: their disprove it's like they're it's like, no, there's no

903
00:53:09,480 --> 00:53:10,360
Speaker 2: useless you know.

904
00:53:10,360 --> 00:53:15,240
Speaker 3: What I mean, rendered, They're rendered irrelevant. But there's also

905
00:53:15,400 --> 00:53:18,080
Speaker 3: there's also a uh, there's a social piece of this.

906
00:53:18,880 --> 00:53:21,720
Speaker 3: I have great respect here for all the people involved.

907
00:53:21,760 --> 00:53:25,200
Speaker 3: There's also a social aspect to this that people outside

908
00:53:25,200 --> 00:53:29,359
Speaker 3: of academia may not be fully cognizant of or aware of,

909
00:53:29,520 --> 00:53:33,400
Speaker 3: which is that there are often turf wars, right, there

910
00:53:33,440 --> 00:53:37,719
Speaker 3: are ideological turf wars. And when you get to the

911
00:53:38,160 --> 00:53:41,480
Speaker 3: edge of physics, you get to the heart of something

912
00:53:41,719 --> 00:53:44,920
Speaker 3: very much like philosophy, right, you get to a kind

913
00:53:44,960 --> 00:53:46,720
Speaker 3: of a battle of opinion and theory.

914
00:53:47,160 --> 00:53:47,359
Speaker 2: Uh.

915
00:53:47,480 --> 00:53:51,120
Speaker 3: And and people can be quite territorial in that respect.

916
00:53:51,239 --> 00:53:56,360
Speaker 3: So it is I would argue, uh, incredibly difficult to

917
00:53:56,600 --> 00:54:01,520
Speaker 3: remove that kind of sense of identification. Like in one

918
00:54:01,560 --> 00:54:05,880
Speaker 3: of the articles you shared, Matt, Professor Hausenfelder uses the

919
00:54:05,880 --> 00:54:12,080
Speaker 3: phrase societal relevance, right, what does this mean to society?

920
00:54:13,040 --> 00:54:16,680
Speaker 3: More so like that that in itself, I think is

921
00:54:17,080 --> 00:54:21,080
Speaker 3: an illustrative phrase, because we have to realize that a

922
00:54:21,160 --> 00:54:25,960
Speaker 3: lot of it's like astronomer's fighting for observatory time. A

923
00:54:26,000 --> 00:54:29,000
Speaker 3: lot of this does come down to a sort of

924
00:54:29,160 --> 00:54:32,360
Speaker 3: turf war for lack of a better for lack of

925
00:54:32,440 --> 00:54:37,640
Speaker 3: a better way to articulate it. And again like also

926
00:54:38,000 --> 00:54:41,520
Speaker 3: going to go forward, not a particle physicist, not a

927
00:54:41,640 --> 00:54:45,880
Speaker 3: quantum physicist, anymore than the average person having a lucid dream.

928
00:54:47,200 --> 00:54:50,680
Speaker 3: But I will argue that this is one of those

929
00:54:50,680 --> 00:54:54,880
Speaker 3: things where you can make do with what already exists.

930
00:54:54,920 --> 00:55:01,160
Speaker 3: One thing we haven't talked about is the absolute windfall

931
00:55:01,760 --> 00:55:05,839
Speaker 3: this is economically for a lot of very powerful, very

932
00:55:05,920 --> 00:55:09,000
Speaker 3: interested players. When we talked about the scientists, we're talking

933
00:55:09,000 --> 00:55:12,000
Speaker 3: about the kids on the playground. We're not talking about

934
00:55:12,040 --> 00:55:15,160
Speaker 3: the people who get paid to build the playground, and

935
00:55:15,280 --> 00:55:18,680
Speaker 3: those folks very much want projects like this to happen.

936
00:55:19,120 --> 00:55:22,480
Speaker 3: You know what I mean? That is a future shifting

937
00:55:22,960 --> 00:55:26,759
Speaker 3: amount of funding. So there are clearly there are going

938
00:55:26,800 --> 00:55:30,080
Speaker 3: to be ulterior motives involved that go beyond the science,

939
00:55:30,680 --> 00:55:34,399
Speaker 3: and I do think it is a valid question as

940
00:55:34,480 --> 00:55:38,160
Speaker 3: to you know, with that much money, are there better

941
00:55:38,200 --> 00:55:41,640
Speaker 3: projects to put this into? Are there things that would

942
00:55:42,360 --> 00:55:48,400
Speaker 3: have a higher chance of yielding pioneering results. It's a

943
00:55:48,520 --> 00:55:51,640
Speaker 3: question we don't know the answer to yet, but it's

944
00:55:51,680 --> 00:55:55,640
Speaker 3: something that I would I don't know. I'm kind of

945
00:55:55,680 --> 00:55:58,000
Speaker 3: out of my depth here because this is the deep

946
00:55:58,120 --> 00:56:04,640
Speaker 3: ink of the fact of reality. But if Haustenfelder, if

947
00:56:04,719 --> 00:56:08,200
Speaker 3: we take these very valid questions, I wouldn't even call

948
00:56:08,239 --> 00:56:12,680
Speaker 3: them criticisms, very valid questions. If we take those to heart,

949
00:56:12,760 --> 00:56:15,239
Speaker 3: then one of the things that I would love to

950
00:56:15,280 --> 00:56:21,840
Speaker 3: hear there, Matt, is what should be done instead? Is

951
00:56:21,920 --> 00:56:25,640
Speaker 3: this already happening? Is it definitely? Definitely, the FCC is

952
00:56:25,680 --> 00:56:26,520
Speaker 3: going to be a thing.

953
00:56:26,840 --> 00:56:30,640
Speaker 2: No. No, there's a whole process of basically proving that

954
00:56:30,800 --> 00:56:34,520
Speaker 2: this new collider would even function That ends in twenty

955
00:56:34,600 --> 00:56:38,279
Speaker 2: twenty five. Then they have to put forward a plan

956
00:56:38,440 --> 00:56:41,919
Speaker 2: for construction, which that should end sometime in twenty twenty eight,

957
00:56:42,120 --> 00:56:44,799
Speaker 2: and then in the twenty forties you would actually have

958
00:56:45,080 --> 00:56:49,759
Speaker 2: a theoretically a working particle accelerator a collider system. The

959
00:56:49,840 --> 00:56:52,840
Speaker 2: thing that gives me hope in all of this is

960
00:56:52,880 --> 00:56:57,320
Speaker 2: that those teams of incredibly intelligent people are planning already

961
00:56:57,400 --> 00:56:59,719
Speaker 2: for experiments that are going to occur in the twenty

962
00:56:59,719 --> 00:57:06,319
Speaker 2: seven So it's that thing where if everyone believes that

963
00:57:06,480 --> 00:57:09,840
Speaker 2: the planet is going to end at some point in

964
00:57:09,880 --> 00:57:12,880
Speaker 2: the near future, or humanity is going to destroy itself,

965
00:57:13,000 --> 00:57:15,760
Speaker 2: or climate change is going to repavoc to where humanity

966
00:57:15,800 --> 00:57:20,600
Speaker 2: is mostly decimated, if everybody's thinking that way, I don't know.

967
00:57:20,760 --> 00:57:22,360
Speaker 2: I don't know. I don't know how much I believe

968
00:57:22,360 --> 00:57:24,600
Speaker 2: in intention. But we've talked about that before in the past,

969
00:57:24,600 --> 00:57:28,080
Speaker 2: how you can kind of create your own outcome because

970
00:57:28,080 --> 00:57:31,240
Speaker 2: it it the way you think about the future shapes

971
00:57:31,280 --> 00:57:34,800
Speaker 2: how you react to the present, which doesn't mean you're

972
00:57:34,840 --> 00:57:39,800
Speaker 2: actually manifesting something, you know by thinking about it, but

973
00:57:40,080 --> 00:57:44,120
Speaker 2: by thinking about it, you are changing yourself and your interactions.

974
00:57:44,560 --> 00:57:46,720
Speaker 2: And just by having these people say, oh, yeah, in

975
00:57:46,760 --> 00:57:49,240
Speaker 2: the twenty seventies, we're going to start, you know, the

976
00:57:49,320 --> 00:57:52,840
Speaker 2: second phase, which is where we actually slam the protons together,

977
00:57:53,320 --> 00:57:57,760
Speaker 2: You're like, oh wow, really that twenty seventies, Okay, all right,

978
00:57:57,800 --> 00:57:59,840
Speaker 2: we're gonna be okay. I don't know why it does

979
00:58:00,080 --> 00:58:03,920
Speaker 2: that in my brain, but just thinking about the future positively,

980
00:58:04,200 --> 00:58:04,960
Speaker 2: I really.

981
00:58:05,040 --> 00:58:07,880
Speaker 3: Sure that mind over matter is a real thing. I

982
00:58:07,880 --> 00:58:10,880
Speaker 3: mean agree, we did the we wind over dark matter.

983
00:58:11,240 --> 00:58:15,680
Speaker 3: We found really conclusive studies that show, uh, you know,

984
00:58:15,760 --> 00:58:18,840
Speaker 3: your intention, your thought can change things, just like the

985
00:58:19,960 --> 00:58:24,640
Speaker 3: interactions you allow from people around you, you know, because

986
00:58:24,640 --> 00:58:28,880
Speaker 3: that's another stimulus. So we are conscious thoughts are stimulus

987
00:58:28,920 --> 00:58:32,400
Speaker 3: exercised upon the brain, like you know, like the the

988
00:58:32,400 --> 00:58:36,360
Speaker 3: British cab drivers who memorize the entirety of London and

989
00:58:36,400 --> 00:58:39,960
Speaker 3: their hippocampus grows larger as a result, or the Buddhist

990
00:58:40,440 --> 00:58:43,440
Speaker 3: the Buddhist monks who uh the camera of the brain

991
00:58:43,520 --> 00:58:47,360
Speaker 3: region because I'm a monster, but the brain region associated

992
00:58:47,400 --> 00:58:51,080
Speaker 3: with compassion grows larger in them simply because of the

993
00:58:52,000 --> 00:58:55,000
Speaker 3: meditation and the way that they the way that they

994
00:58:55,080 --> 00:58:58,000
Speaker 3: think about the world and themselves. So I see what

995
00:58:58,000 --> 00:59:02,120
Speaker 3: you're saying. When it feels more real, whether we're gaslating ourselves,

996
00:59:02,160 --> 00:59:04,520
Speaker 3: it feels more real to have this thing, say the

997
00:59:04,560 --> 00:59:09,040
Speaker 3: twenty seventies and implicitly assume that everybody will make it

998
00:59:09,080 --> 00:59:10,840
Speaker 3: that far. I think that's beautiful.

999
00:59:11,120 --> 00:59:14,160
Speaker 2: I think that piece is the Medulla oblongata. By the way,

1000
00:59:14,320 --> 00:59:14,920
Speaker 2: I'm just kidding.

1001
00:59:15,360 --> 00:59:20,120
Speaker 5: I think we don't always have to be so fatalistic either,

1002
00:59:20,320 --> 00:59:21,920
Speaker 5: you know what I mean. Like, it's so easy to

1003
00:59:22,000 --> 00:59:24,480
Speaker 5: get caught up in the doom and gloom and annihilation

1004
00:59:24,680 --> 00:59:25,960
Speaker 5: of everything, and you.

1005
00:59:25,920 --> 00:59:27,960
Speaker 4: Know, a little positive thinking goes a long way.

1006
00:59:28,000 --> 00:59:31,000
Speaker 5: It's another reason why I think people dig religion so much,

1007
00:59:31,400 --> 00:59:35,880
Speaker 5: because it gives them something to funnel that energy into.

1008
00:59:36,320 --> 00:59:40,840
Speaker 5: You know, that doesn't necessarily require answers be presented right

1009
00:59:40,880 --> 00:59:42,760
Speaker 5: in front of you, So why don't we like to

1010
00:59:43,200 --> 00:59:45,400
Speaker 5: follow that lead and exercise a little faith when it

1011
00:59:45,440 --> 00:59:47,640
Speaker 5: comes to science. That's why I think it's interesting to

1012
00:59:47,640 --> 00:59:50,400
Speaker 5: combine philosophy with science, because then you start to get

1013
00:59:50,400 --> 00:59:54,960
Speaker 5: something more approaching, a more measured type of religion, a

1014
00:59:55,000 --> 00:59:56,400
Speaker 5: more measured type of faith.

1015
00:59:56,840 --> 01:00:00,840
Speaker 2: And that's why I love doctor Sabine Hasenfelda. Check out

1016
01:00:00,880 --> 01:00:04,440
Speaker 2: her YouTube channel. It goes by the name Science without

1017
01:00:04,480 --> 01:00:11,000
Speaker 2: the Gobber Degouk, which I loved, and I just I've

1018
01:00:11,000 --> 01:00:12,800
Speaker 2: been watching your videos all day. I think it's awesome.

1019
01:00:13,080 --> 01:00:13,760
Speaker 4: We'll check it out.

1020
01:00:14,040 --> 01:00:16,160
Speaker 2: That's all for now, oncern, let us know what you

1021
01:00:16,240 --> 01:00:20,560
Speaker 2: think about this whole thing, particle physics creating them black

1022
01:00:20,600 --> 01:00:22,880
Speaker 2: holes and portals and all that good stuff.

1023
01:00:23,040 --> 01:00:24,280
Speaker 3: Which has it happened yet?

1024
01:00:24,520 --> 01:00:27,680
Speaker 2: Well again, if it did, how would we know if

1025
01:00:27,720 --> 01:00:30,960
Speaker 2: it changed the timeline? How would we know there's some

1026
01:00:31,040 --> 01:00:31,840
Speaker 2: weirdness in there?

1027
01:00:31,960 --> 01:00:34,240
Speaker 3: Let us know what you think, Yes, let us know

1028
01:00:34,360 --> 01:00:36,120
Speaker 3: what you think. Let us know if you work it

1029
01:00:36,280 --> 01:00:38,680
Speaker 3: cern Let us know if you work in the realm

1030
01:00:38,760 --> 01:00:41,960
Speaker 3: of physics, whether particle or quantum. Let us know the

1031
01:00:42,000 --> 01:00:45,920
Speaker 3: last time you used a deep fake to trick a

1032
01:00:46,080 --> 01:00:49,800
Speaker 3: huge company. Let us know also your opinions of the

1033
01:00:49,880 --> 01:00:53,400
Speaker 3: death penalty. It's crucial at this point in time, and

1034
01:00:53,560 --> 01:00:56,720
Speaker 3: all of these things are crucial. In fact, your participation

1035
01:00:56,880 --> 01:01:01,640
Speaker 3: being foremost of those crucial crucial things. We try to

1036
01:01:01,680 --> 01:01:03,720
Speaker 3: be easy to find online. We can't wait to hear

1037
01:01:03,800 --> 01:01:04,080
Speaker 3: from you.

1038
01:01:04,360 --> 01:01:06,960
Speaker 4: Right, have you visited the quantum realm? What was it like?

1039
01:01:07,360 --> 01:01:07,840
Speaker 4: Let us know.

1040
01:01:08,120 --> 01:01:10,160
Speaker 5: You can find us on the Internet where we exist

1041
01:01:10,200 --> 01:01:13,480
Speaker 5: at the handle conspiracy Stuff on Facebook. We have our

1042
01:01:13,480 --> 01:01:18,080
Speaker 5: Facebook group Here's where it gets crazy YouTube and also.

1043
01:01:18,040 --> 01:01:19,800
Speaker 4: X fka Twitter.

1044
01:01:20,360 --> 01:01:24,200
Speaker 5: We are conspiracy Stuff show on Instagram and TikTok.

1045
01:01:24,440 --> 01:01:28,280
Speaker 2: I've only been quantum once, and you better believe I

1046
01:01:28,320 --> 01:01:30,840
Speaker 2: met Paul Rudd there he was till you.

1047
01:01:30,800 --> 01:01:32,320
Speaker 3: Never got quantum.

1048
01:01:34,400 --> 01:01:39,000
Speaker 4: Yeah, we got to, we to, we got to phrases.

1049
01:01:40,400 --> 01:01:41,760
Speaker 4: We'll let the edit sort it out.

1050
01:01:42,680 --> 01:01:43,760
Speaker 3: I don't do a competition.

1051
01:01:44,160 --> 01:01:46,280
Speaker 2: Yeah, all right, here we go. Hey, we want to

1052
01:01:46,320 --> 01:01:48,680
Speaker 2: call us. Our number is one eight three three s

1053
01:01:48,760 --> 01:01:50,880
Speaker 2: T d W y t K. When you call in,

1054
01:01:50,920 --> 01:01:53,200
Speaker 2: give yourself a cool nickname, and you've got three minutes,

1055
01:01:53,200 --> 01:01:55,600
Speaker 2: say whatever you'd like. Please let us know if we

1056
01:01:55,600 --> 01:01:57,280
Speaker 2: can use your name and message on the air. That

1057
01:01:57,320 --> 01:01:59,720
Speaker 2: would be extremely helpful. If you've got more to say

1058
01:01:59,720 --> 01:02:01,600
Speaker 2: than can fit in that three minute message, why not

1059
01:02:01,640 --> 01:02:03,680
Speaker 2: instead send us a good old fashioned email.

1060
01:02:03,760 --> 01:02:06,600
Speaker 3: We are the folks who read every single email we

1061
01:02:06,760 --> 01:02:28,160
Speaker 3: get conspiracy at iHeartRadio dot com.

1062
01:02:28,320 --> 01:02:30,400
Speaker 2: Stuff they don't want you to know. Is a production

1063
01:02:30,480 --> 01:02:35,040
Speaker 2: of iHeartRadio. For more podcasts from iHeartRadio, visit the iHeartRadio app,

1064
01:02:35,120 --> 01:02:38,360
Speaker 2: Apple Podcasts, or wherever you listen to your favorite shows.