1
00:00:05,760 --> 00:00:10,000
Speaker 1: On this episode of Newsworld. On February twentieth, my grandson, Robert,

2
00:00:10,039 --> 00:00:12,400
Speaker 1: and I were in Los Angeles and we had the

3
00:00:12,400 --> 00:00:16,920
Speaker 1: pleasure of visiting the Divergent Technologies factory in Torrance, California.

4
00:00:17,600 --> 00:00:20,680
Speaker 1: I was so impressed by the manufacturing innovation we saw

5
00:00:20,720 --> 00:00:23,239
Speaker 1: on that tour, I wanted to share the story of

6
00:00:23,280 --> 00:00:26,920
Speaker 1: Divergent with you, So I'm really pleased to welcome my guest,

7
00:00:27,320 --> 00:00:32,120
Speaker 1: Kevin Zinger, founder and executive chairman of Divergent Technologies and

8
00:00:32,280 --> 00:00:37,120
Speaker 1: Singer Vehicles, the original equipment manufacturer of the world's fastest

9
00:00:37,200 --> 00:00:52,040
Speaker 1: street legal hypercar, the twenty one CE. Kevin, Welcome and

10
00:00:52,080 --> 00:00:53,640
Speaker 1: thank you for joining me on news World.

11
00:00:54,760 --> 00:00:58,040
Speaker 2: Well, it's my honor to be on your podcast, mister speaker,

12
00:00:58,080 --> 00:01:02,120
Speaker 2: and we as a team, I really enjoyed hosting you

13
00:01:02,360 --> 00:01:05,400
Speaker 2: and Robert, so thank you for the opportunity.

14
00:01:05,080 --> 00:01:08,840
Speaker 1: And I should say for the full exposure to our audience.

15
00:01:09,200 --> 00:01:11,960
Speaker 1: That upon leaving you, we promptly went to in and

16
00:01:11,959 --> 00:01:14,559
Speaker 1: Out Burger and my grandson was able to have animal fries.

17
00:01:14,600 --> 00:01:17,640
Speaker 1: So I felt that the entire trip was both culturally

18
00:01:17,640 --> 00:01:19,440
Speaker 1: and intellectually very exciting.

19
00:01:20,120 --> 00:01:22,400
Speaker 2: The only thing better would have been going to the

20
00:01:22,520 --> 00:01:24,480
Speaker 2: drive in part of an and out Burger with twenty

21
00:01:24,520 --> 00:01:24,800
Speaker 2: one C.

22
00:01:25,800 --> 00:01:28,600
Speaker 1: That's true. I don't think I'm quite ready yet, although

23
00:01:28,600 --> 00:01:31,000
Speaker 1: it's an amazing car, which we'll get to. But I

24
00:01:31,040 --> 00:01:33,880
Speaker 1: want to start out with you because you know, what

25
00:01:33,959 --> 00:01:37,959
Speaker 1: you've achieved is amazing. But frankly, you're kind of really remarkable.

26
00:01:37,959 --> 00:01:41,440
Speaker 1: I mean, you grew up in working class Ohio. You've

27
00:01:41,440 --> 00:01:44,319
Speaker 1: built hot rides along with your brothers, you got a

28
00:01:44,360 --> 00:01:47,560
Speaker 1: football scholarship to Yale, ended up being an All American,

29
00:01:47,960 --> 00:01:50,320
Speaker 1: and then you chose to join the United States Marine

30
00:01:50,360 --> 00:01:54,320
Speaker 1: Corps reserves. Mean, you've really had a remarkable life before

31
00:01:54,320 --> 00:01:58,120
Speaker 1: you got into manufacturing. What motivated you through all that experience?

32
00:01:59,000 --> 00:02:02,320
Speaker 2: I think that each of these things had its own

33
00:02:02,880 --> 00:02:06,640
Speaker 2: unique motivation, but in general, I was the youngest of

34
00:02:06,720 --> 00:02:09,680
Speaker 2: five in a working class family and the first to

35
00:02:09,840 --> 00:02:13,760
Speaker 2: go to college, and I ended up because Ohio is

36
00:02:13,800 --> 00:02:17,880
Speaker 2: a football crazy place and the Catholic schools are really

37
00:02:17,919 --> 00:02:22,280
Speaker 2: the football powerhouses in Ohio. I ended up going to

38
00:02:22,600 --> 00:02:27,400
Speaker 2: a very good Jesuit high school. And in that Jesuit

39
00:02:27,520 --> 00:02:32,720
Speaker 2: high school, they taught the classical virtues, one of which

40
00:02:32,800 --> 00:02:39,040
Speaker 2: is the life well lived is finding an area of

41
00:02:39,400 --> 00:02:45,640
Speaker 2: competition that allows you to express your talents and stretch

42
00:02:45,720 --> 00:02:51,440
Speaker 2: your talents in the greatest possible way. And that idea

43
00:02:51,600 --> 00:02:56,760
Speaker 2: of the classical Greek well lived taught by Jesuit priests

44
00:02:56,800 --> 00:03:01,280
Speaker 2: of all things, has always stayed in my head. As

45
00:03:01,400 --> 00:03:05,280
Speaker 2: you know, apart from your spiritual life, the driver of

46
00:03:06,080 --> 00:03:10,320
Speaker 2: how you use the gifts that you've been God given,

47
00:03:10,680 --> 00:03:12,880
Speaker 2: in my view, to their fullest extent.

48
00:03:13,400 --> 00:03:17,200
Speaker 1: When you went to you, I was reading up on

49
00:03:17,240 --> 00:03:20,760
Speaker 1: this and your coach, who himself is in the Football

50
00:03:20,800 --> 00:03:24,840
Speaker 1: Hall of Fame, said that you were the outstanding player

51
00:03:24,880 --> 00:03:28,200
Speaker 1: he ever coached, and that part of it was your intensity,

52
00:03:28,320 --> 00:03:31,240
Speaker 1: your commitment. What do you think made you so effective

53
00:03:31,240 --> 00:03:32,160
Speaker 1: on the football field.

54
00:03:33,080 --> 00:03:37,200
Speaker 2: Well, you're given this gift of life. You have a

55
00:03:37,280 --> 00:03:42,160
Speaker 2: short period to use it to the full extent. And

56
00:03:42,960 --> 00:03:47,760
Speaker 2: I always trained to the max, and part of that

57
00:03:47,880 --> 00:03:52,680
Speaker 2: training was to kind of figure out what you thought

58
00:03:52,720 --> 00:03:56,240
Speaker 2: your limit was and push behind that. And I think

59
00:03:56,280 --> 00:03:59,880
Speaker 2: when you approach life that way, you're not mentally prepared

60
00:03:59,880 --> 00:04:05,400
Speaker 2: to lose. And so that would happen again and again.

61
00:04:05,480 --> 00:04:08,680
Speaker 2: I'd give you one instance. You know, we were playing

62
00:04:08,720 --> 00:04:12,680
Speaker 2: in a game where it was actually nationally televised. It

63
00:04:12,760 --> 00:04:16,120
Speaker 2: was the ABC Game of the week Keith Jackson was

64
00:04:16,160 --> 00:04:21,120
Speaker 2: commentating and I had in this game. The score was

65
00:04:21,320 --> 00:04:25,240
Speaker 2: twelve to seven, we were losing. There were only a

66
00:04:25,240 --> 00:04:29,000
Speaker 2: few minutes left in the game. I had already blocked

67
00:04:29,000 --> 00:04:32,120
Speaker 2: two punts. The one blocked punt I had and I

68
00:04:32,120 --> 00:04:37,560
Speaker 2: played defense resulted in a touchdown, and the time was

69
00:04:37,640 --> 00:04:41,320
Speaker 2: running out in the game. It was fourth down. The

70
00:04:41,360 --> 00:04:45,440
Speaker 2: other side was about to punt, and my coach pulled

71
00:04:45,480 --> 00:04:49,880
Speaker 2: me over and said, stop pooling around. You have to

72
00:04:49,920 --> 00:04:53,360
Speaker 2: block this punt. And obviously I blocked two punts already

73
00:04:53,400 --> 00:04:57,560
Speaker 2: in this game, so people were keying in on me,

74
00:04:57,839 --> 00:05:00,560
Speaker 2: and I think, you just at that moment, you're like

75
00:05:01,720 --> 00:05:05,800
Speaker 2: this person, you know, who is a great person, Hall

76
00:05:05,880 --> 00:05:10,360
Speaker 2: of Fame coach believes in me. I will find a way.

77
00:05:10,480 --> 00:05:13,120
Speaker 2: And so basically what I did is I lined up

78
00:05:13,160 --> 00:05:15,520
Speaker 2: on one side of the ball and as they got down,

79
00:05:16,240 --> 00:05:18,120
Speaker 2: they of course, you know, wanted to make sure I

80
00:05:18,160 --> 00:05:20,640
Speaker 2: didn't block the punt, so they moved their blocking coverage

81
00:05:20,680 --> 00:05:23,000
Speaker 2: over to the one side. Then I moved over to

82
00:05:23,000 --> 00:05:27,080
Speaker 2: the other side and basically ran straight to the punter,

83
00:05:27,279 --> 00:05:29,719
Speaker 2: blacked the punt, recovered it on the one yard line,

84
00:05:29,760 --> 00:05:32,440
Speaker 2: and we ended up winning thirteen to twelve. So I

85
00:05:32,480 --> 00:05:37,640
Speaker 2: think those things are really just a matter of believing

86
00:05:37,640 --> 00:05:40,560
Speaker 2: in yourself and feeding off of the belief of others

87
00:05:40,720 --> 00:05:42,520
Speaker 2: in you, and respecting that belief.

88
00:05:43,240 --> 00:05:46,480
Speaker 1: Then you went on a Yale to the Yale Law.

89
00:05:46,360 --> 00:05:50,719
Speaker 2: School, Yes, so you know. Originally I was thinking of

90
00:05:50,800 --> 00:05:55,400
Speaker 2: getting after I graduated from school an md PhD, and

91
00:05:55,440 --> 00:05:58,359
Speaker 2: then having worked in a lab, I decided not to

92
00:05:58,440 --> 00:06:01,159
Speaker 2: do that. And I met a person who was later

93
00:06:01,200 --> 00:06:04,919
Speaker 2: the dean of Yale Law School, Guido Calibrazy, and we

94
00:06:05,000 --> 00:06:07,440
Speaker 2: actually went to the same church in New Haven, Saint

95
00:06:07,520 --> 00:06:10,160
Speaker 2: Thomas more To is a Catholic church, and he said,

96
00:06:10,440 --> 00:06:12,560
Speaker 2: what are you doing. I explained to him, and he

97
00:06:12,600 --> 00:06:16,280
Speaker 2: was a football fan, that I had been working in

98
00:06:16,320 --> 00:06:18,680
Speaker 2: the Yale Med School lab and I had decided I

99
00:06:18,800 --> 00:06:23,000
Speaker 2: didn't want to get an mdphd. And he said, why

100
00:06:23,000 --> 00:06:25,520
Speaker 2: don't you come to Yale Law School And I'm like,

101
00:06:25,600 --> 00:06:29,000
Speaker 2: I don't know anything about law, and he said, Kevin,

102
00:06:29,680 --> 00:06:32,800
Speaker 2: and this is the first time I'd heard of this school.

103
00:06:32,839 --> 00:06:36,080
Speaker 2: He said, no, Yale Law School is the Lake Cole

104
00:06:36,200 --> 00:06:40,279
Speaker 2: Normal Superior of America. And I said, well, what do

105
00:06:40,320 --> 00:06:43,359
Speaker 2: you mean. He's like in France, that's where they send

106
00:06:43,400 --> 00:06:47,719
Speaker 2: people who are thinkers who find their own way to

107
00:06:48,000 --> 00:06:51,479
Speaker 2: lead in some way. In France and here at Yale

108
00:06:51,520 --> 00:06:53,120
Speaker 2: Law School, which at the time only had about one

109
00:06:53,160 --> 00:06:56,440
Speaker 2: hundred and twenty five students in each entering class, said

110
00:06:56,440 --> 00:06:59,680
Speaker 2: there were only four required courses at the time, and

111
00:06:59,720 --> 00:07:01,800
Speaker 2: they were all past fail and they said, you want

112
00:07:01,800 --> 00:07:04,800
Speaker 2: to study science, you want to study philosophy, you can

113
00:07:04,839 --> 00:07:09,120
Speaker 2: study anything after those four courses. And so I thought, well, terrific,

114
00:07:09,800 --> 00:07:11,720
Speaker 2: and then I went to Ye Law School.

115
00:07:12,000 --> 00:07:15,080
Speaker 1: Our mutual friend, John Thornton tells the story that you

116
00:07:15,120 --> 00:07:17,560
Speaker 1: went on to become a lawyer, and that they got

117
00:07:17,560 --> 00:07:21,600
Speaker 1: this call one day that one of the great defense

118
00:07:21,640 --> 00:07:25,040
Speaker 1: attorneys in New York called and said, this young guy

119
00:07:25,160 --> 00:07:28,840
Speaker 1: just beat me in court, and I can't believe how

120
00:07:28,960 --> 00:07:31,480
Speaker 1: really really smart he is. He said, you guys at

121
00:07:31,560 --> 00:07:35,600
Speaker 1: Golden Sacks ought to grab him. And so you leave

122
00:07:36,000 --> 00:07:39,320
Speaker 1: Yale Law School and you become a deputy US Attorney.

123
00:07:40,160 --> 00:07:42,920
Speaker 2: Well what happened was I left law school. I had

124
00:07:42,960 --> 00:07:45,600
Speaker 2: been an editor of the Yale Law Journal. It's like

125
00:07:45,680 --> 00:07:50,760
Speaker 2: being on the Law Review, and at that time kind

126
00:07:50,760 --> 00:07:53,280
Speaker 2: of the usual sequence, and I didn't want to become

127
00:07:53,280 --> 00:07:57,280
Speaker 2: an academic. But my mentor, Guido calibrase you, who at

128
00:07:57,280 --> 00:08:00,160
Speaker 2: that point was the dean of Yale's law school, said

129
00:08:00,640 --> 00:08:05,080
Speaker 2: there's a judge who's been assigned the Iran Contra cases

130
00:08:05,680 --> 00:08:08,840
Speaker 2: and he's looking for a clerk. He only takes one

131
00:08:08,840 --> 00:08:11,080
Speaker 2: clerk a year. His name was Gerhard Gazelli. He's a

132
00:08:11,160 --> 00:08:15,760
Speaker 2: District of Columbia US District court judge. And so I

133
00:08:15,840 --> 00:08:18,640
Speaker 2: went to work for him for a year. I got

134
00:08:18,640 --> 00:08:23,120
Speaker 2: a top secret clearance, all the sensitive compartmented information clearances.

135
00:08:23,240 --> 00:08:28,400
Speaker 2: As somebody from a working class family, this was incredibly interesting.

136
00:08:28,560 --> 00:08:30,920
Speaker 2: And I got to work with this judge for a

137
00:08:31,000 --> 00:08:35,320
Speaker 2: year on this case. And basically what happened was that

138
00:08:36,160 --> 00:08:39,920
Speaker 2: at that point I was actually thinking of going into

139
00:08:40,400 --> 00:08:44,040
Speaker 2: business or doing something other than law. And the judge

140
00:08:44,080 --> 00:08:46,840
Speaker 2: said to me, even if you go and do business

141
00:08:46,920 --> 00:08:50,200
Speaker 2: as you said you want to do, being a trial

142
00:08:50,280 --> 00:08:53,280
Speaker 2: lawyer will teach you a lot. And I said, Judge,

143
00:08:53,320 --> 00:08:55,840
Speaker 2: I'm one year out of law school. How do you

144
00:08:55,920 --> 00:08:58,679
Speaker 2: become a trial lawyer? And I remember he picked up

145
00:08:58,679 --> 00:09:03,240
Speaker 2: the phone and called up Rudy Giuliani, who was at

146
00:09:03,240 --> 00:09:06,800
Speaker 2: the time the US Attorney for the Southern District of

147
00:09:06,840 --> 00:09:10,680
Speaker 2: New York, and said, Rudy, I've got this guy, You've

148
00:09:10,679 --> 00:09:13,080
Speaker 2: got to hire him. And I remember it was around noon.

149
00:09:13,440 --> 00:09:16,200
Speaker 2: I'm sending him up on the train from DC to

150
00:09:16,280 --> 00:09:20,679
Speaker 2: New York and Rudy hired me. And over the course

151
00:09:20,720 --> 00:09:23,680
Speaker 2: of three years, in all of the cases that I had,

152
00:09:23,760 --> 00:09:27,200
Speaker 2: I won top count convictions, including against some of the

153
00:09:27,200 --> 00:09:31,840
Speaker 2: top lawyers. And then that's when that call took place

154
00:09:32,000 --> 00:09:32,800
Speaker 2: to John Thornton.

155
00:09:33,320 --> 00:09:36,040
Speaker 1: So you then end up going over to Goldman Sachs,

156
00:09:36,400 --> 00:09:38,439
Speaker 1: which is a totally different career.

157
00:09:38,960 --> 00:09:43,600
Speaker 2: It is, And I ended up working directly for John Thornton,

158
00:09:43,920 --> 00:09:46,880
Speaker 2: and i'd say at the time and he was really

159
00:09:47,200 --> 00:09:51,880
Speaker 2: progressed to running the international operations of Goldman Sachs, and

160
00:09:52,320 --> 00:09:56,520
Speaker 2: I was really his point execution person and person that

161
00:09:58,040 --> 00:10:01,040
Speaker 2: anything that he needed really to get done from a

162
00:10:01,120 --> 00:10:05,959
Speaker 2: deal standpoint, everything from the merger between B sky B

163
00:10:06,120 --> 00:10:11,559
Speaker 2: and Sky Television into Sky in the UK, to representing

164
00:10:11,840 --> 00:10:15,679
Speaker 2: Leekha Singh in the sale of Star Television, all a

165
00:10:15,720 --> 00:10:20,400
Speaker 2: wide variety of different transactions and setting up offices and things,

166
00:10:20,480 --> 00:10:24,400
Speaker 2: and so over the course of five years working with John,

167
00:10:24,600 --> 00:10:29,160
Speaker 2: I learned a tremendous amount and was able to interact

168
00:10:29,240 --> 00:10:34,160
Speaker 2: with people directly like a Rupert Murdoch on transactions.

169
00:10:34,720 --> 00:10:37,760
Speaker 1: John says that he told you when he offered you

170
00:10:37,840 --> 00:10:41,000
Speaker 1: the job that you'd last about five years because it

171
00:10:41,120 --> 00:10:44,920
Speaker 1: just wouldn't be dynamic enough for you that you'd altimately

172
00:10:44,960 --> 00:10:47,600
Speaker 1: want to go do something more than it was under

173
00:10:47,600 --> 00:10:49,880
Speaker 1: your control. So at the end of five years, this is,

174
00:10:49,960 --> 00:10:52,000
Speaker 1: after all, one of the two or three greatest investment

175
00:10:52,000 --> 00:10:54,720
Speaker 1: firms in the world. What led you to then leave

176
00:10:54,760 --> 00:10:56,080
Speaker 1: Goldman Sachs.

177
00:10:57,240 --> 00:11:01,960
Speaker 2: I remember I was in how it was late at night.

178
00:11:02,480 --> 00:11:05,559
Speaker 2: Rupert Murdock had summoned me to talk about a transaction

179
00:11:06,160 --> 00:11:09,040
Speaker 2: that he was on the other side of, and he

180
00:11:09,200 --> 00:11:11,200
Speaker 2: was there with the lawyer that he had, and I

181
00:11:11,240 --> 00:11:14,400
Speaker 2: remember we had this long conversation. It was late at

182
00:11:14,480 --> 00:11:17,600
Speaker 2: night and we were just talking in general, and I

183
00:11:17,679 --> 00:11:21,760
Speaker 2: remember him saying, these businesses aren't life and death to me.

184
00:11:21,840 --> 00:11:24,320
Speaker 2: It's much more important than that. And then I started

185
00:11:24,400 --> 00:11:26,480
Speaker 2: talking to him about being an entrepreneur and he's like,

186
00:11:27,280 --> 00:11:29,599
Speaker 2: why are you doing this? And I think, what do

187
00:11:29,679 --> 00:11:34,160
Speaker 2: you mean. I'm at Goldman Sachs. It's no like someone

188
00:11:34,480 --> 00:11:40,920
Speaker 2: like you really should be creating something. And I thought, okay.

189
00:11:41,400 --> 00:11:43,600
Speaker 2: I thought more and more and more, and that led me.

190
00:11:44,160 --> 00:11:48,720
Speaker 1: So you then decide to co found Coda Automotive, which

191
00:11:48,760 --> 00:11:51,360
Speaker 1: is an electric vehicle manufacturer. This is about two thousand

192
00:11:51,360 --> 00:11:55,120
Speaker 1: and eight. But that becomes for you a real evolutionary

193
00:11:55,120 --> 00:11:58,040
Speaker 1: process from when you first thought about it. As you

194
00:11:58,080 --> 00:12:00,840
Speaker 1: got into it, you really be in looking at the

195
00:12:00,880 --> 00:12:05,000
Speaker 1: whole notion of what is a sustainable production system, not

196
00:12:05,240 --> 00:12:08,400
Speaker 1: just what is a sustainable fuel? Talk about that problem.

197
00:12:08,440 --> 00:12:11,560
Speaker 1: I think it's a very interesting evolution and very important.

198
00:12:12,480 --> 00:12:17,320
Speaker 2: I learned a couple of very big lessons which resulted

199
00:12:17,360 --> 00:12:21,880
Speaker 2: in me founding Divergent Technologies. One of the lessons was

200
00:12:22,760 --> 00:12:24,839
Speaker 2: I would say that around kind of two thousand and

201
00:12:24,920 --> 00:12:29,280
Speaker 2: seven two thousand and eight, we were focused on building

202
00:12:29,360 --> 00:12:32,440
Speaker 2: an affordable ev but the first thing we looked at

203
00:12:32,679 --> 00:12:36,160
Speaker 2: was battery cells. And I'd say we were the first

204
00:12:36,240 --> 00:12:41,760
Speaker 2: to work with and generate with a battery company a

205
00:12:42,320 --> 00:12:47,600
Speaker 2: large format prismatic lithium iron phosphate cell. That is the

206
00:12:47,640 --> 00:12:52,199
Speaker 2: cell that China has scaled up with that company. Originally

207
00:12:52,320 --> 00:12:56,880
Speaker 2: I tried to build the battery factory in Ohio and

208
00:12:57,800 --> 00:13:00,839
Speaker 2: because the US at that time, I would say, during

209
00:13:00,880 --> 00:13:06,680
Speaker 2: the Obama administration Secretary of Commerce Gary Lock, they were all, hey,

210
00:13:06,679 --> 00:13:09,440
Speaker 2: if you can't build in the US, you know, China

211
00:13:09,640 --> 00:13:13,280
Speaker 2: is our partner, you should build this factory in China.

212
00:13:13,960 --> 00:13:16,680
Speaker 2: That factory was set up, and if you look on

213
00:13:16,760 --> 00:13:19,560
Speaker 2: YouTube and you put in Coda and Gary Lock and

214
00:13:19,640 --> 00:13:22,560
Speaker 2: Kevin Zinger, you'll see it's about a two minute video

215
00:13:22,640 --> 00:13:27,160
Speaker 2: of me giving a tour of that factory. That gave

216
00:13:27,880 --> 00:13:31,600
Speaker 2: China what I think was the decisive edge in scaling

217
00:13:31,679 --> 00:13:36,720
Speaker 2: up battery production. That is what CAATL licensed and scaled

218
00:13:36,800 --> 00:13:41,040
Speaker 2: up that battery cell technology. When I was doing that,

219
00:13:41,480 --> 00:13:46,080
Speaker 2: as it relates to China, I looked at the CO

220
00:13:46,400 --> 00:13:51,160
Speaker 2: two emissions that related to manufacturing in China, and as

221
00:13:51,200 --> 00:13:56,000
Speaker 2: you know, China uses dedicated coal power for manufacturing. When

222
00:13:56,040 --> 00:14:02,400
Speaker 2: you manufacture a battery cell using coal fired power, which

223
00:14:02,440 --> 00:14:05,840
Speaker 2: is what is used in China, the emissions from that

224
00:14:06,760 --> 00:14:10,880
Speaker 2: are greater. I'd say, for the average, say a ninety

225
00:14:11,000 --> 00:14:15,520
Speaker 2: kilowatt hour battery pack in a car, you're generating over

226
00:14:15,559 --> 00:14:19,080
Speaker 2: two hundred kilograms of CO two omitted per kilowatt hour.

227
00:14:20,400 --> 00:14:26,040
Speaker 2: That manufacturing is greater than say, driving a Toyota Camry

228
00:14:26,520 --> 00:14:30,280
Speaker 2: with all of its manufacturing emissions plus eighty thousand miles

229
00:14:30,320 --> 00:14:34,800
Speaker 2: of driving. And when I realized that, I realized that

230
00:14:36,600 --> 00:14:43,360
Speaker 2: how you manufacture something and how you look at extraction, processing, manufacturing,

231
00:14:44,040 --> 00:14:47,960
Speaker 2: then the actual use of fuel or electricity, and then disposal.

232
00:14:48,360 --> 00:14:52,120
Speaker 2: That life cycle assessment which this analysis has also been

233
00:14:52,160 --> 00:14:55,320
Speaker 2: done by Goldman Sachs in a very good report called

234
00:14:56,040 --> 00:15:00,840
Speaker 2: electric Vehicles Enter the life Cycle Assessment Era. That kind

235
00:15:00,880 --> 00:15:07,080
Speaker 2: of uncovers whether these vehicles are environmentally friendly or not.

236
00:15:07,160 --> 00:15:09,680
Speaker 2: And a lot of it has to do with where

237
00:15:09,720 --> 00:15:14,200
Speaker 2: you manufacture that battery cell and what the power source is.

238
00:15:14,960 --> 00:15:17,840
Speaker 2: I'll stop there. I can then tell how that informed

239
00:15:17,880 --> 00:15:19,640
Speaker 2: the next company that I started.

240
00:15:20,080 --> 00:15:21,920
Speaker 1: This is the evolution. Although I want to take a

241
00:15:21,960 --> 00:15:24,120
Speaker 1: brief detour because in the middle of all this you're

242
00:15:24,160 --> 00:15:26,720
Speaker 1: also in the Marine Corps. I mean, how did that

243
00:15:26,720 --> 00:15:27,080
Speaker 1: fit in?

244
00:15:28,000 --> 00:15:31,760
Speaker 2: Well, I don't want to test the patience of your listeners.

245
00:15:31,760 --> 00:15:35,040
Speaker 2: But what happened is in between my deciding to go

246
00:15:35,080 --> 00:15:38,120
Speaker 2: to Yale Law School and entering Yale Law School, I

247
00:15:38,160 --> 00:15:41,440
Speaker 2: had some time and my older brother, during the Vietnam War,

248
00:15:41,720 --> 00:15:45,240
Speaker 2: served in the Army. Both my parents served in World

249
00:15:45,280 --> 00:15:49,520
Speaker 2: War Two as enlisted service people in the Army Air Corps,

250
00:15:49,560 --> 00:15:54,440
Speaker 2: which was the predecessor to the Air Force, and educated

251
00:15:54,480 --> 00:15:57,280
Speaker 2: as I was by Jesuit High School and men for

252
00:15:57,360 --> 00:16:00,600
Speaker 2: others and one of the books that I read in

253
00:16:00,880 --> 00:16:05,280
Speaker 2: high school was a book by William Manchester called Goodbye

254
00:16:05,360 --> 00:16:09,360
Speaker 2: Darkness about his service in the Marine Corps as an

255
00:16:09,440 --> 00:16:13,960
Speaker 2: enlisted Marine during World War Two. And my parents never

256
00:16:14,000 --> 00:16:17,040
Speaker 2: really talked about the war. My brother didn't either, But

257
00:16:17,120 --> 00:16:21,320
Speaker 2: I thought, as a citizen, this is something where I've

258
00:16:21,360 --> 00:16:25,520
Speaker 2: gotten these benefits, where I should do some service. And

259
00:16:25,600 --> 00:16:30,440
Speaker 2: so I enlisted in the Marine Corps Reserves and went

260
00:16:30,480 --> 00:16:34,800
Speaker 2: through Paris Island boot Camp Camp La June for advanced

261
00:16:34,840 --> 00:16:38,000
Speaker 2: infantry training, and then because I was being assigned to

262
00:16:38,520 --> 00:16:41,880
Speaker 2: a special operations unit out of Quancet Point Naval Air

263
00:16:41,880 --> 00:16:44,960
Speaker 2: Station in Rhode Island, I had to go through jump

264
00:16:45,040 --> 00:16:48,440
Speaker 2: school at what at the time was called Fort Benning, Georgia.

265
00:16:49,000 --> 00:16:52,280
Speaker 1: You're cling a guy who fills up every day with something.

266
00:17:08,760 --> 00:17:11,960
Speaker 1: So now we're back to the real breakthrough, which is

267
00:17:12,000 --> 00:17:16,000
Speaker 1: the focus on processes. And I have to say, having

268
00:17:16,119 --> 00:17:19,159
Speaker 1: visited Divergent, someday you're going to have to set up

269
00:17:19,160 --> 00:17:21,600
Speaker 1: an entire tour service to be able. You're going to

270
00:17:21,640 --> 00:17:23,080
Speaker 1: have so many people want to come see this because

271
00:17:23,720 --> 00:17:27,080
Speaker 1: when you see it and you realize how you have

272
00:17:27,200 --> 00:17:32,720
Speaker 1: integrated artificial intelligence with three D printing with robotics, with

273
00:17:32,960 --> 00:17:37,280
Speaker 1: very sophisticated use of materials. This is the factory of

274
00:17:37,320 --> 00:17:41,040
Speaker 1: the future today. I mean, you have leapfrogged over virtually

275
00:17:41,200 --> 00:17:44,560
Speaker 1: every potential competitive system. Did that just come to you

276
00:17:44,680 --> 00:17:46,840
Speaker 1: or how did you put all of that together?

277
00:17:48,200 --> 00:17:53,160
Speaker 2: I mean what happened was with the Automotive and Battery company.

278
00:17:53,400 --> 00:17:56,879
Speaker 2: I had been living in the Bay Area, so in

279
00:17:57,000 --> 00:18:01,840
Speaker 2: the Silicon Valley area, and I had interaction, had a

280
00:18:01,880 --> 00:18:05,400
Speaker 2: couple of discussions with Andy Grove after he had retired

281
00:18:05,440 --> 00:18:09,240
Speaker 2: from being chairman CEO of Intel, and I'd say we

282
00:18:09,400 --> 00:18:14,240
Speaker 2: both shared I told him about my frustration with the

283
00:18:14,240 --> 00:18:19,399
Speaker 2: inability of finding capital to build a factory in the

284
00:18:19,520 --> 00:18:24,919
Speaker 2: United States. And we also looked and said, hey, and

285
00:18:25,040 --> 00:18:29,400
Speaker 2: this feeds into obviously a focus and passion of President

286
00:18:29,440 --> 00:18:34,280
Speaker 2: Trump and both his administrations. From a trade policy standpoint

287
00:18:34,320 --> 00:18:38,600
Speaker 2: and from a funding standpoint, we were looking at Silicon

288
00:18:38,680 --> 00:18:41,239
Speaker 2: Valley and if you had some hardware aspect to your

289
00:18:41,280 --> 00:18:44,480
Speaker 2: tech startup, unless it said and by the way, we're

290
00:18:44,520 --> 00:18:48,480
Speaker 2: going to outsource manufacturing to China, you didn't get funded.

291
00:18:49,080 --> 00:18:53,640
Speaker 2: And we saw things because of these trade policies, because

292
00:18:53,840 --> 00:18:58,440
Speaker 2: of the nature of that type of capital. We were,

293
00:18:59,040 --> 00:19:05,719
Speaker 2: for example, having an Apple transfer Process manufacturing IP like

294
00:19:05,840 --> 00:19:11,600
Speaker 2: Critical Advanced Manufacturing IP over to China and companies like

295
00:19:11,720 --> 00:19:17,240
Speaker 2: fox Con start to build a next generation of manufacturing

296
00:19:17,440 --> 00:19:22,040
Speaker 2: ahead of the United States, as well as move manufacturing

297
00:19:22,160 --> 00:19:27,560
Speaker 2: capacity over to China in the eighties. I think must

298
00:19:27,560 --> 00:19:29,800
Speaker 2: have come out in the late eighties that book by

299
00:19:29,880 --> 00:19:34,920
Speaker 2: Paul Kennedy, The Rise and Decline of Great Powers. It

300
00:19:34,960 --> 00:19:39,720
Speaker 2: was clear to me that no leading power maintains that

301
00:19:39,760 --> 00:19:48,720
Speaker 2: position if its industrial capacity is less than its pure competitors. Today,

302
00:19:48,880 --> 00:19:52,000
Speaker 2: we're in a a lot of must talk about fork

303
00:19:52,040 --> 00:19:55,280
Speaker 2: in the road. I mean we're in a manufacturing fork

304
00:19:55,320 --> 00:19:57,520
Speaker 2: in the road. More than anything else, We're in an

305
00:19:57,680 --> 00:20:03,160
Speaker 2: existential fork in the road. China in two thousand had

306
00:20:03,280 --> 00:20:09,040
Speaker 2: seven percent of global manufacturing market share. It's now trending

307
00:20:09,080 --> 00:20:15,040
Speaker 2: toward forty five percent. The US had twenty five percent.

308
00:20:15,280 --> 00:20:19,360
Speaker 2: It's now trending toward eleven percent. The US plus all

309
00:20:19,400 --> 00:20:25,800
Speaker 2: of its allies have not only less overall industrial manufacturing

310
00:20:25,840 --> 00:20:33,240
Speaker 2: capacity than China, they have less advanced manufacturing. That is unsustainable.

311
00:20:33,359 --> 00:20:37,800
Speaker 2: I looked at that at a slightly earlier point and said,

312
00:20:39,480 --> 00:20:45,920
Speaker 2: all of the things that I know about machine learning automation, manufacturing,

313
00:20:47,040 --> 00:20:48,879
Speaker 2: if you were going to start with a clean sheet

314
00:20:48,920 --> 00:20:52,400
Speaker 2: of paper and reindustrialize the US. Because at that time,

315
00:20:52,440 --> 00:20:57,000
Speaker 2: I said, we will lose our position as a leading

316
00:20:57,119 --> 00:21:01,280
Speaker 2: nation state if we do not reindustry realize. But we

317
00:21:01,359 --> 00:21:04,159
Speaker 2: can't go back to what we were doing before. We

318
00:21:04,200 --> 00:21:08,000
Speaker 2: can't go back to the way things are or were

319
00:21:08,640 --> 00:21:13,439
Speaker 2: before we offshored our manufacturer. We need to make a leapfrog,

320
00:21:13,920 --> 00:21:18,760
Speaker 2: the kind of leapfrog say JFK made when he brought

321
00:21:18,760 --> 00:21:22,520
Speaker 2: in Werner vun Braun, the rocket scientist, and said, how

322
00:21:22,560 --> 00:21:24,800
Speaker 2: do we catch up to the Soviets? And Verner front

323
00:21:24,840 --> 00:21:27,600
Speaker 2: Bron said, you will never catch up to the Soviets

324
00:21:27,600 --> 00:21:29,879
Speaker 2: by going to Earth orbit. You need to go to

325
00:21:29,960 --> 00:21:32,880
Speaker 2: lunar orbit and develop the technology to do that right.

326
00:21:33,320 --> 00:21:37,240
Speaker 2: And that in turn obviously created semiconductor industry many different things.

327
00:21:37,720 --> 00:21:41,120
Speaker 2: I simply said, you can't do industry four point zero.

328
00:21:41,160 --> 00:21:43,080
Speaker 2: You can't do what Fox, kN and Apple have done

329
00:21:43,119 --> 00:21:47,240
Speaker 2: with CNC machining and automation. You need to completely leapfrog

330
00:21:47,320 --> 00:21:50,880
Speaker 2: that with a total digital system. And if you're starting

331
00:21:50,880 --> 00:21:53,800
Speaker 2: a company, the first thing you ask is what's the

332
00:21:53,840 --> 00:21:56,720
Speaker 2: biggest problem you can solve? And I looked at things

333
00:21:56,800 --> 00:22:00,560
Speaker 2: like car companies, which obviously go through these peaks and

334
00:22:00,640 --> 00:22:02,840
Speaker 2: valleys which we saw in two thousand and eight nine,

335
00:22:03,359 --> 00:22:07,560
Speaker 2: because their factories are designed specific huge amount of capital

336
00:22:07,680 --> 00:22:12,240
Speaker 2: goes into designing a single model type both for the

337
00:22:12,320 --> 00:22:16,040
Speaker 2: vehicle and then the factory. Right, so design specificity, And

338
00:22:16,080 --> 00:22:20,919
Speaker 2: so I said, okay, what happens if you solve that

339
00:22:21,119 --> 00:22:25,439
Speaker 2: problem at a given price point by creating a fully

340
00:22:25,480 --> 00:22:31,640
Speaker 2: digital system. Machine learning generates a structure. That structure then

341
00:22:31,760 --> 00:22:36,480
Speaker 2: gets printed with fidelity the way that it's printed. It

342
00:22:36,480 --> 00:22:40,000
Speaker 2: gets printed in assemblable blocks, and then an automated system

343
00:22:40,480 --> 00:22:45,760
Speaker 2: assembles those. And that's a super simplified version of what

344
00:22:46,040 --> 00:22:49,280
Speaker 2: we're doing. But that in turn allows you, in a

345
00:22:49,359 --> 00:22:55,240
Speaker 2: non design specific way, to design any kind of structure

346
00:22:55,359 --> 00:22:59,359
Speaker 2: for AirLand s, in space vehicles. Generate that structure, have

347
00:22:59,440 --> 00:23:03,679
Speaker 2: it be a far better, lighter, better performing structure, be

348
00:23:03,760 --> 00:23:05,960
Speaker 2: able to print it off the same equipment, and then

349
00:23:06,000 --> 00:23:08,879
Speaker 2: be able to assemble it off the same equipment. Whether

350
00:23:08,920 --> 00:23:13,280
Speaker 2: it's an Aston Martin Vantage frame or a Lackheed Martin

351
00:23:13,760 --> 00:23:18,320
Speaker 2: Cruise missile system. You can design, print, assemble both of

352
00:23:18,359 --> 00:23:19,480
Speaker 2: those back to back.

353
00:23:20,080 --> 00:23:24,640
Speaker 1: As you developed this, the divergent factory I saw, if

354
00:23:24,640 --> 00:23:27,920
Speaker 1: I understand the story correctly, is the result of eleven

355
00:23:28,000 --> 00:23:33,200
Speaker 1: years of evolution in which now Divergent has five hundred

356
00:23:33,200 --> 00:23:36,000
Speaker 1: and twenty patents, and your son Lucas, who's a great

357
00:23:36,000 --> 00:23:38,679
Speaker 1: story in his own right, has fifty of them. So

358
00:23:38,760 --> 00:23:43,199
Speaker 1: you guys have been methodically solving problems one step at

359
00:23:43,200 --> 00:23:47,359
Speaker 1: a time and just gradually building the system, if you will,

360
00:23:47,840 --> 00:23:51,080
Speaker 1: until now it is I think unmatched by anything else

361
00:23:51,119 --> 00:23:51,600
Speaker 1: in the world.

362
00:23:52,240 --> 00:23:54,439
Speaker 2: What I'd say is not meaning to correct you, but

363
00:23:54,520 --> 00:23:58,240
Speaker 2: we have about seven hundred and fifty patents today. I'm

364
00:23:58,240 --> 00:24:00,560
Speaker 2: the lead and venner with about two hundre and I

365
00:24:00,560 --> 00:24:03,760
Speaker 2: think two hundred and twenty two at last count. Lucas

366
00:24:03,760 --> 00:24:07,320
Speaker 2: has around eighty. Now he's my son and partner in

367
00:24:07,359 --> 00:24:11,960
Speaker 2: the business. What I'd say is about three years ago

368
00:24:12,240 --> 00:24:16,000
Speaker 2: or four years ago, we had the first version of

369
00:24:16,040 --> 00:24:20,760
Speaker 2: the factory that could be commercialized, and since that time

370
00:24:21,800 --> 00:24:26,080
Speaker 2: this has gone into production. So automotive, which obviously you're

371
00:24:26,119 --> 00:24:29,439
Speaker 2: doing the safety performance structures for passenger cars, right, This

372
00:24:29,600 --> 00:24:35,120
Speaker 2: is enormous risk if you're not manufacturing properly those structures

373
00:24:35,280 --> 00:24:40,000
Speaker 2: for those vehicles we brought in as customers. For example,

374
00:24:40,040 --> 00:24:42,560
Speaker 2: we're shipping frames to Aston Martin for a variant of

375
00:24:42,600 --> 00:24:47,959
Speaker 2: the Aston Martin Vantage today. But Aston Martin, Bugatti, an

376
00:24:48,000 --> 00:24:52,919
Speaker 2: Italian company I can't name, McLaren, Mercedes AMG, and a

377
00:24:52,960 --> 00:24:56,280
Speaker 2: German company I can't name. Those are all production customers.

378
00:24:56,520 --> 00:25:00,600
Speaker 2: So we actually proved three years ago this system was

379
00:25:00,600 --> 00:25:05,840
Speaker 2: fully commercial and are now shipping structures and on production

380
00:25:06,000 --> 00:25:11,920
Speaker 2: programs with six major automotive brands. Obviously, the system is

381
00:25:11,960 --> 00:25:15,000
Speaker 2: an adaptive system, so we take all of that data

382
00:25:15,560 --> 00:25:19,480
Speaker 2: generated by the system, and the system is version the

383
00:25:19,520 --> 00:25:23,680
Speaker 2: software and hardware. But what you saw is now a

384
00:25:23,760 --> 00:25:29,240
Speaker 2: factory that is ready to scale and which we want

385
00:25:29,280 --> 00:25:33,680
Speaker 2: to take from that initial factory to tens and then

386
00:25:33,880 --> 00:25:38,960
Speaker 2: hundreds of factories. So literally every single state in the

387
00:25:39,080 --> 00:25:45,840
Speaker 2: United States could have multiple digital factories across the country.

388
00:25:46,240 --> 00:25:48,480
Speaker 1: Now, if I could just take a minute to stay

389
00:25:48,480 --> 00:25:51,720
Speaker 1: with the Zinger cars, because as I understand it, when

390
00:25:51,720 --> 00:25:54,439
Speaker 1: you approach the big auto companies, they were too slow

391
00:25:55,040 --> 00:25:57,680
Speaker 1: and too timid, and see you just decided you'd build

392
00:25:57,680 --> 00:26:00,119
Speaker 1: a car to show them that could be done. I

393
00:26:00,200 --> 00:26:02,360
Speaker 1: have to say I was out in your car factory

394
00:26:02,880 --> 00:26:06,760
Speaker 1: and it's pretty breathtaking. I mean, these are amazing cars

395
00:26:06,800 --> 00:26:09,200
Speaker 1: can you talk just from here about the whole notion

396
00:26:09,280 --> 00:26:12,760
Speaker 1: of the Zinger vehicle models and the way you've approached this,

397
00:26:12,760 --> 00:26:14,520
Speaker 1: because it's quite an amazing story.

398
00:26:15,560 --> 00:26:18,720
Speaker 2: Yeah. So, going back, probably if somebody looked at a

399
00:26:18,800 --> 00:26:21,640
Speaker 2: Google search, they would see when I was a company

400
00:26:21,640 --> 00:26:25,560
Speaker 2: of one, I bought one of these archaic commercial three

401
00:26:25,640 --> 00:26:30,000
Speaker 2: D printers and worked and built a first prototype car

402
00:26:30,760 --> 00:26:34,399
Speaker 2: that was called the Blade. From there, we then used

403
00:26:34,400 --> 00:26:37,880
Speaker 2: that as I hired people and started to scale as

404
00:26:37,960 --> 00:26:41,879
Speaker 2: a laboratory as a development platform. And about three and

405
00:26:41,880 --> 00:26:47,159
Speaker 2: a half years ago Lucas, my son and my partner said, Dad,

406
00:26:47,800 --> 00:26:49,560
Speaker 2: this is how we really became. The two of us

407
00:26:49,560 --> 00:26:52,320
Speaker 2: are kind of founders of the car company, which is

408
00:26:52,359 --> 00:26:55,000
Speaker 2: owned by the tech company. He said, why don't we

409
00:26:55,040 --> 00:27:00,239
Speaker 2: turn that platform into a car company. We can do

410
00:27:00,320 --> 00:27:05,119
Speaker 2: it with almost no capital, because you're almost like an Apple,

411
00:27:05,160 --> 00:27:08,880
Speaker 2: you know how Apple is a fabulous product design company.

412
00:27:08,920 --> 00:27:12,800
Speaker 2: It uses others for that fabrication. We could use the

413
00:27:12,840 --> 00:27:17,920
Speaker 2: tools of Divergent and the factory of Divergent to rapidly

414
00:27:18,119 --> 00:27:22,159
Speaker 2: design the most advanced vehicle in the world. Take it

415
00:27:22,200 --> 00:27:25,160
Speaker 2: through crash safety, take it through emissions, which we did

416
00:27:25,200 --> 00:27:30,080
Speaker 2: in all fifty states, including California, and then take it

417
00:27:30,119 --> 00:27:33,679
Speaker 2: to the track and show that it is faster than

418
00:27:33,720 --> 00:27:37,280
Speaker 2: any production Ferrari, faster than any production Maclair, and faster

419
00:27:37,400 --> 00:27:41,359
Speaker 2: than any production Mercedes or Portia meaning street legal car,

420
00:27:42,040 --> 00:27:45,520
Speaker 2: which we did. We chattered the circuit of the America's

421
00:27:45,520 --> 00:27:49,280
Speaker 2: record in Austin, the Goodwood Hill Climb record, the Laguna

422
00:27:49,359 --> 00:27:53,199
Speaker 2: Seca record. Now that car in a factory which was

423
00:27:53,200 --> 00:27:57,080
Speaker 2: set up by Andy Lambert. Alan had hired him over

424
00:27:57,119 --> 00:28:00,760
Speaker 2: a decade ago to set up manufacturing and production at SpaceX,

425
00:28:01,040 --> 00:28:03,280
Speaker 2: and he ran that for about a decade and he

426
00:28:03,359 --> 00:28:06,040
Speaker 2: came over to us and he's now set up our

427
00:28:06,080 --> 00:28:09,880
Speaker 2: production factory for the Zinger twenty one C. And as

428
00:28:09,920 --> 00:28:13,080
Speaker 2: you saw, cars are now rolling off and being shipped

429
00:28:13,080 --> 00:28:16,320
Speaker 2: to customers. And that is within a period of time

430
00:28:16,920 --> 00:28:21,200
Speaker 2: that no auto company in the world could match. We designed, built,

431
00:28:21,240 --> 00:28:26,960
Speaker 2: and are shipping the most advanced, highest performing production car ever.

432
00:28:27,080 --> 00:28:31,400
Speaker 2: And it's American made, it's off American patented technology. And

433
00:28:32,359 --> 00:28:34,440
Speaker 2: this is we call it the twenty one CE after

434
00:28:34,480 --> 00:28:37,320
Speaker 2: twenty one century because this is like twenty first century

435
00:28:37,359 --> 00:28:38,480
Speaker 2: American muscle car.

436
00:28:38,840 --> 00:28:42,080
Speaker 1: And as I understand it, it produces something like sixteen

437
00:28:42,200 --> 00:28:45,320
Speaker 1: hundred and fifty horse power and can go about two

438
00:28:45,440 --> 00:28:48,160
Speaker 1: hundred and ten miles an hour. And it's street legal.

439
00:28:48,760 --> 00:28:51,840
Speaker 2: It's completely street legal. You know, it's been through full crash,

440
00:28:52,080 --> 00:28:56,920
Speaker 2: full emissions. The car is about a three thousand pound car.

441
00:28:57,120 --> 00:28:59,960
Speaker 2: It's got thirteen hundred and fifty horse power, all wheel drive.

442
00:29:00,080 --> 00:29:04,200
Speaker 2: I've two EV motors upfront, our own design V eight.

443
00:29:04,280 --> 00:29:06,480
Speaker 2: We designed and built our own V eight, much of

444
00:29:06,520 --> 00:29:09,720
Speaker 2: which is printed. The top speed of the arrow body

445
00:29:09,800 --> 00:29:11,800
Speaker 2: car is two hundred and fifty three miles an hour.

446
00:29:12,280 --> 00:29:14,400
Speaker 2: The car does zero to sixty and one point eight

447
00:29:14,480 --> 00:29:18,480
Speaker 2: eight seconds. What I'd say the most impressive thing though,

448
00:29:18,560 --> 00:29:20,880
Speaker 2: is when you take the car to the track and

449
00:29:21,000 --> 00:29:24,560
Speaker 2: like reference tracks tracks that are the famous tracks, it

450
00:29:24,720 --> 00:29:29,320
Speaker 2: way out performs any production car ever built by any

451
00:29:29,360 --> 00:29:32,360
Speaker 2: of the great European companies, whether it's a McLaren or

452
00:29:32,360 --> 00:29:36,520
Speaker 2: a Ferrari or a Bugatti. It is in one very

453
00:29:36,560 --> 00:29:39,600
Speaker 2: short period of time. You see that Ford versus Ferrari,

454
00:29:39,960 --> 00:29:42,760
Speaker 2: this was Zinger versus the world, and the world was defeated.

455
00:29:58,720 --> 00:30:01,720
Speaker 1: I really want our listeners to understand what you have

456
00:30:01,880 --> 00:30:07,920
Speaker 1: built is a process system using the most advanced technology

457
00:30:07,920 --> 00:30:12,040
Speaker 1: in the world and integrating it synergistically so that each

458
00:30:12,080 --> 00:30:15,240
Speaker 1: of the breakthroughs reinforces the next breakthrough. But can you

459
00:30:15,320 --> 00:30:17,240
Speaker 1: just walk us through a little bit of what happens

460
00:30:17,240 --> 00:30:19,160
Speaker 1: and how is it done at the what you would

461
00:30:19,200 --> 00:30:22,040
Speaker 1: call the divergent adaptive production system.

462
00:30:22,440 --> 00:30:26,959
Speaker 2: Sure. So the system has three subsystems. One is a

463
00:30:27,200 --> 00:30:34,000
Speaker 2: machine learning based generative engineering engine. One is a printer

464
00:30:34,240 --> 00:30:38,920
Speaker 2: that takes what that engineering engine generates and with fidelity

465
00:30:39,120 --> 00:30:43,840
Speaker 2: in three dimensions, prints that structure. And then an assembly

466
00:30:43,920 --> 00:30:48,360
Speaker 2: cell that takes those component structures and puts them together,

467
00:30:48,880 --> 00:30:53,000
Speaker 2: say into a full vehicle structure, whether it's a large drone,

468
00:30:53,120 --> 00:30:57,520
Speaker 2: a collaborative combat aircraft, or the chassis of the twenty

469
00:30:57,560 --> 00:31:01,760
Speaker 2: one s. So how that works is, say you have

470
00:31:01,840 --> 00:31:06,040
Speaker 2: an Aston Martin or a Lockheed Martin. Let's take Lockheed

471
00:31:06,280 --> 00:31:09,560
Speaker 2: because a big focus of ours right now is aerospace

472
00:31:09,600 --> 00:31:12,840
Speaker 2: and defense. They may come to us and say we've

473
00:31:12,840 --> 00:31:16,920
Speaker 2: got a modular cruise missile system. Here are the requirements.

474
00:31:16,960 --> 00:31:20,680
Speaker 2: Here are the engineering load cases, the stresses that'll have

475
00:31:20,840 --> 00:31:24,760
Speaker 2: when say it's something that is launched from under the

476
00:31:24,800 --> 00:31:28,240
Speaker 2: wing of an airplane. Here are the loads when the

477
00:31:28,280 --> 00:31:32,040
Speaker 2: plane is carrying that off a bomb release unit. Here

478
00:31:32,080 --> 00:31:34,320
Speaker 2: are the stresses when it gets released. Here are the

479
00:31:34,320 --> 00:31:39,880
Speaker 2: thermal requirements vibration. They give us those requirements. At that point,

480
00:31:39,920 --> 00:31:44,560
Speaker 2: Divergent takes over design authority, and really the machine takes

481
00:31:44,600 --> 00:31:47,920
Speaker 2: over design authority in that we then take those requirements,

482
00:31:48,440 --> 00:31:51,920
Speaker 2: we put those into the machine. The machine runs a

483
00:31:52,040 --> 00:31:57,280
Speaker 2: simulation of the performance of a structure. It also runs

484
00:31:58,080 --> 00:32:06,200
Speaker 2: concurrently the generation of manufacturing instructions and assembly instructions. It's

485
00:32:06,240 --> 00:32:10,880
Speaker 2: called bidirectional evolutionary structures optimization. The machine is adding and

486
00:32:10,920 --> 00:32:16,480
Speaker 2: subtracting material in a simulation until it creates a perfectly

487
00:32:16,520 --> 00:32:21,880
Speaker 2: optimized structure perfectly pareto optimized structure. At that point, the

488
00:32:21,960 --> 00:32:26,960
Speaker 2: machine has fully optimized the structure, both for its performance

489
00:32:27,360 --> 00:32:31,600
Speaker 2: but also for its manufacturing and assembly. So say you're

490
00:32:32,000 --> 00:32:35,520
Speaker 2: I'll take an example. McLaren would ordinarily take six to

491
00:32:35,640 --> 00:32:39,520
Speaker 2: nine months to do the design for a suspension component

492
00:32:39,680 --> 00:32:42,560
Speaker 2: for their new hypercarp. This is all out in public

493
00:32:43,000 --> 00:32:47,520
Speaker 2: domain that we're working with them. We replace that six

494
00:32:47,600 --> 00:32:51,080
Speaker 2: to nine months and an engineering team with about fifteen

495
00:32:51,120 --> 00:32:53,600
Speaker 2: hours of compute time, and at the end of that

496
00:32:53,800 --> 00:32:56,520
Speaker 2: fifteen hours of compute time, they have a structure that's

497
00:32:56,560 --> 00:33:01,160
Speaker 2: twenty to forty percent lighter, stiffer outperforms. The structure is

498
00:33:01,280 --> 00:33:07,520
Speaker 2: lower cost, and that structure has its manufacturing and assembly instructions,

499
00:33:07,720 --> 00:33:11,600
Speaker 2: and we can immediately manufacture and assemble it. This is

500
00:33:11,640 --> 00:33:16,920
Speaker 2: a machine for taking a design, minimizing material and energy

501
00:33:16,960 --> 00:33:22,200
Speaker 2: in its building, maximizing its performance, lowering its cost, printing

502
00:33:22,200 --> 00:33:24,920
Speaker 2: it off a machine that doesn't care whether it's printing

503
00:33:25,000 --> 00:33:28,360
Speaker 2: for Aston Martin or Lockheed Martin. And then an assembly

504
00:33:28,440 --> 00:33:31,640
Speaker 2: system that assembles the assemblable blocks that doesn't care whether

505
00:33:31,680 --> 00:33:35,440
Speaker 2: it's manufacturing or assembling for Aston Martin or Lockheed Martin.

506
00:33:36,080 --> 00:33:38,760
Speaker 2: We in turn charge for that engineering, and then we

507
00:33:38,880 --> 00:33:41,840
Speaker 2: charge per piece for what we delivered to the customer.

508
00:33:42,480 --> 00:33:45,760
Speaker 1: You had actually done work for General Atomic, which produces

509
00:33:45,760 --> 00:33:48,440
Speaker 1: the Predator among other things, and which is a very

510
00:33:48,520 --> 00:33:52,360
Speaker 1: very sophisticated company, And they came back with results of

511
00:33:52,520 --> 00:33:57,520
Speaker 1: your intervention that was so amazing and there's such a

512
00:33:57,560 --> 00:34:01,480
Speaker 1: serious firm that it really sort of stopped me in

513
00:34:01,520 --> 00:34:04,360
Speaker 1: my tracks, made me think about, you know, how big

514
00:34:04,400 --> 00:34:07,000
Speaker 1: a breakthrough that this potentially is.

515
00:34:07,880 --> 00:34:12,200
Speaker 2: Yeah, So two plus years ago General Atomics reached out

516
00:34:12,200 --> 00:34:15,880
Speaker 2: to us. They asked us to re engineer one of

517
00:34:15,920 --> 00:34:20,960
Speaker 2: their smaller unmanned aerial systems, and we were able to

518
00:34:21,280 --> 00:34:24,600
Speaker 2: in a very short period of time, reduce the part

519
00:34:24,680 --> 00:34:28,520
Speaker 2: count by ninety eight percent, so things like fuel tanks

520
00:34:28,560 --> 00:34:31,800
Speaker 2: instead of being separate with brackets and attachments, they actually

521
00:34:31,840 --> 00:34:35,319
Speaker 2: get printed into the structure. As an example, that's how

522
00:34:35,360 --> 00:34:38,080
Speaker 2: we reduce one hundred and eighty four parts in that

523
00:34:38,200 --> 00:34:41,439
Speaker 2: drone to four parts, so one hundred and eighty four

524
00:34:41,840 --> 00:34:46,319
Speaker 2: to four ninety eight percent part reduction. We reduce the

525
00:34:46,360 --> 00:34:49,919
Speaker 2: production cycle time from twelve days to less than a day,

526
00:34:50,360 --> 00:34:54,399
Speaker 2: like over ninety percent reduction in production cycle time. We

527
00:34:54,480 --> 00:34:57,839
Speaker 2: reduce the per unit cost by over forty percent, and

528
00:34:57,920 --> 00:35:01,000
Speaker 2: we reduce the development cost by over or fifty percent

529
00:35:01,320 --> 00:35:06,000
Speaker 2: and the development time by about ninety five percent. I'd say.

530
00:35:06,160 --> 00:35:10,680
Speaker 2: More recently, we have contracts with almost every single major

531
00:35:10,840 --> 00:35:14,960
Speaker 2: US defense prime and aerospace company. We were able to

532
00:35:15,080 --> 00:35:17,920
Speaker 2: on a modular cruise missile system. From the start of

533
00:35:18,000 --> 00:35:23,799
Speaker 2: engineering to successful flight testing. It took ten weeks. That

534
00:35:23,880 --> 00:35:28,239
Speaker 2: ten weeks would be compared to years in a normal process.

535
00:35:28,280 --> 00:35:33,120
Speaker 2: As an example, General Atomics after we did that, actually

536
00:35:33,239 --> 00:35:37,440
Speaker 2: published the results in a press release. Immediately, we had

537
00:35:37,480 --> 00:35:41,319
Speaker 2: almost every single major US defense prime reach out to us,

538
00:35:41,840 --> 00:35:45,640
Speaker 2: and that really kicked off our involvement in aerospace and defense.

539
00:35:46,600 --> 00:35:50,040
Speaker 1: Basically, if you think about the fact that you're universally applicable,

540
00:35:50,440 --> 00:35:54,400
Speaker 1: I mean, what you do doesn't actually matter which particular product,

541
00:35:55,000 --> 00:35:58,000
Speaker 1: because you're taking the basic the same approach. I saw

542
00:35:58,040 --> 00:36:01,640
Speaker 1: a note that said that potentially on a worldwide basis,

543
00:36:01,760 --> 00:36:04,040
Speaker 1: this is like a five trillion dollar market.

544
00:36:05,200 --> 00:36:08,879
Speaker 2: Yes, this company, I'd say, we don't want to get

545
00:36:08,880 --> 00:36:11,680
Speaker 2: ahead of our skis. We've got one factory. We do

546
00:36:11,760 --> 00:36:15,040
Speaker 2: have six major auto brands doing this. I don't think

547
00:36:15,080 --> 00:36:18,440
Speaker 2: any of them thought this would happen for another decade

548
00:36:19,000 --> 00:36:22,920
Speaker 2: or more. We have almost every single major US prime

549
00:36:23,280 --> 00:36:26,839
Speaker 2: I'd say for the US on the defense side, our

550
00:36:26,880 --> 00:36:33,000
Speaker 2: achilles heel right now is inability to rapidly develop and

551
00:36:33,040 --> 00:36:39,040
Speaker 2: then manufacture at volume. This system solves both of those

552
00:36:39,120 --> 00:36:45,279
Speaker 2: problems today. Is scalable today, and the same factory that

553
00:36:45,480 --> 00:36:51,600
Speaker 2: is printing missiles and torpedoes and collaborative combat aircraft can

554
00:36:51,680 --> 00:36:56,200
Speaker 2: also print for Aston Martin and Bugatti and McLaren and

555
00:36:56,400 --> 00:37:00,759
Speaker 2: Mercedes off of the same equipment at the same time.

556
00:37:01,080 --> 00:37:06,000
Speaker 2: Or we can do replacements spare parts for defense aircraft,

557
00:37:06,080 --> 00:37:09,080
Speaker 2: for jets, jet fighters, other things that need it. We

558
00:37:09,120 --> 00:37:12,400
Speaker 2: can develop new weapons, we can re engineer old weapons.

559
00:37:12,760 --> 00:37:18,080
Speaker 2: But this gives us, in my view, the only plausible,

560
00:37:18,200 --> 00:37:23,880
Speaker 2: real deterrent to China, and that is very rapid development

561
00:37:23,960 --> 00:37:26,400
Speaker 2: of the new kind of weapons that people like Elon

562
00:37:26,560 --> 00:37:30,200
Speaker 2: Musk and the Defense Department talk about, unmanned AirLand, sea,

563
00:37:30,200 --> 00:37:35,239
Speaker 2: in space vehicles, the ability to rapidly develop those and

564
00:37:35,280 --> 00:37:39,600
Speaker 2: then immediately scale manufacturing in a distributed way, and also

565
00:37:39,680 --> 00:37:42,000
Speaker 2: the ability if you look at our defense budget, which

566
00:37:42,040 --> 00:37:44,920
Speaker 2: is over eight hundred billion, three hundred billion of that

567
00:37:45,080 --> 00:37:49,719
Speaker 2: is for sustainment replacement parts. These new machines can digitize

568
00:37:49,719 --> 00:37:55,000
Speaker 2: those parts and as needed, manufacture those parts. We're already

569
00:37:55,000 --> 00:37:58,440
Speaker 2: doing things for the C one thirty right now, spare parts.

570
00:37:59,160 --> 00:38:04,160
Speaker 2: That means that you could massively reduce those sustainment costs

571
00:38:04,400 --> 00:38:09,000
Speaker 2: while massively increasing the readiness of aircraft. So I think

572
00:38:09,080 --> 00:38:13,960
Speaker 2: there's a very very very good fit there. And as

573
00:38:14,000 --> 00:38:18,120
Speaker 2: you said, that kind of designed agnostic equipment allows you

574
00:38:18,280 --> 00:38:24,279
Speaker 2: to save money, create higher performance products, and have the

575
00:38:24,440 --> 00:38:28,719
Speaker 2: kind of volumes of missiles and other armaments and munitions

576
00:38:28,960 --> 00:38:30,560
Speaker 2: that actually will deter ch China.

577
00:38:31,280 --> 00:38:34,080
Speaker 1: I think back to the book by the Chief Logistician

578
00:38:34,760 --> 00:38:38,719
Speaker 1: in the first Iraq War who talked about moving mountains,

579
00:38:39,120 --> 00:38:42,319
Speaker 1: because the sheer volume of stuff we send forward and

580
00:38:42,400 --> 00:38:44,560
Speaker 1: as you saw in Afghanistan, the amount of stuff we

581
00:38:44,640 --> 00:38:49,120
Speaker 1: leave behind. In this model, you could imagine a specific

582
00:38:49,200 --> 00:38:53,400
Speaker 1: divergent factory that moved into the field with the expeditionary

583
00:38:53,440 --> 00:38:58,600
Speaker 1: force and provided real time manufacturing on site, that could

584
00:38:58,600 --> 00:39:01,040
Speaker 1: actually take virtually every spare part of what they needed

585
00:39:01,680 --> 00:39:05,200
Speaker 1: and simply do it digitally right there, cutting out all

586
00:39:05,239 --> 00:39:09,680
Speaker 1: sorts of the logistics tale, and also only producing what you.

587
00:39:09,800 --> 00:39:15,520
Speaker 2: Need exactly, not keeping excess inventory. I think distributing out

588
00:39:15,640 --> 00:39:22,520
Speaker 2: factories to different theaters certainly would functionally allow this system

589
00:39:22,520 --> 00:39:25,280
Speaker 2: to do exactly what you're describing, mister speaker.

590
00:39:26,640 --> 00:39:29,320
Speaker 1: One last question, which is, you're really one of the

591
00:39:29,360 --> 00:39:32,520
Speaker 1: most interesting and smartest people I've met in a long

592
00:39:32,560 --> 00:39:36,000
Speaker 1: career of meeting a lot of interesting people. What keeps

593
00:39:36,040 --> 00:39:37,800
Speaker 1: you up at night? What do you worry about the most?

594
00:39:39,800 --> 00:39:43,239
Speaker 2: Well? I have a concern and I also have optimism.

595
00:39:44,040 --> 00:39:48,680
Speaker 2: My concern is, I'll say, two years ago, when I

596
00:39:48,760 --> 00:39:53,080
Speaker 2: first did this with General Atomics, my view of the

597
00:39:53,120 --> 00:39:56,799
Speaker 2: military industrial complex or whatever you want to call it,

598
00:39:56,800 --> 00:40:01,360
Speaker 2: the defense industrial base, How's that was one that comes

599
00:40:01,400 --> 00:40:05,400
Speaker 2: from probably the first Golf War, which is we just

600
00:40:05,520 --> 00:40:11,600
Speaker 2: have overwhelming technology and capacity. I've now seen that that

601
00:40:11,680 --> 00:40:15,040
Speaker 2: defense industrial base has suffered the way the rest of

602
00:40:15,080 --> 00:40:20,200
Speaker 2: our commercial base has, and even worse from moving our

603
00:40:20,200 --> 00:40:24,840
Speaker 2: supply chain offshore. We don't have and it's not a

604
00:40:24,920 --> 00:40:28,520
Speaker 2: secret because almost every single congressional hearing, and we just

605
00:40:28,560 --> 00:40:32,719
Speaker 2: testified recently in front of Senator Wicker and the rest

606
00:40:32,800 --> 00:40:36,880
Speaker 2: of the Senate Armed Services Committee about this problem. We

607
00:40:36,960 --> 00:40:40,440
Speaker 2: don't have the industrial base that is here to not

608
00:40:40,520 --> 00:40:43,759
Speaker 2: only develop new weapons rapidly and then volume produce them,

609
00:40:44,120 --> 00:40:47,120
Speaker 2: but even for our existing weapons, we don't have the

610
00:40:47,200 --> 00:40:51,080
Speaker 2: casting suppliers on shore. We don't have this supply chain.

611
00:40:51,560 --> 00:40:55,160
Speaker 2: And the reason I've focused so much now on defense

612
00:40:55,320 --> 00:40:58,480
Speaker 2: is I think we're at an existential moment. This is

613
00:40:58,600 --> 00:41:03,280
Speaker 2: the last best chance we have to leap frog Chinese

614
00:41:03,360 --> 00:41:08,160
Speaker 2: manufacturing technology and catch up with that manufacturing and I

615
00:41:08,200 --> 00:41:13,239
Speaker 2: think what you saw, respectfully is that solution. So my

616
00:41:13,480 --> 00:41:19,000
Speaker 2: fear is that will not be identified rapidly enough. People

617
00:41:19,040 --> 00:41:22,720
Speaker 2: won't fully understand what you've seen. They can only really

618
00:41:22,760 --> 00:41:25,560
Speaker 2: do it by spending enough time to do it. People

619
00:41:25,640 --> 00:41:27,920
Speaker 2: will look and somebody says, oh, that's three D printing.

620
00:41:28,400 --> 00:41:32,080
Speaker 2: We are far more advanced than any three D printing

621
00:41:32,120 --> 00:41:37,960
Speaker 2: system commercially available. This is really a fully digital engineering

622
00:41:38,040 --> 00:41:42,319
Speaker 2: and manufacturing system where all the software and hardware has

623
00:41:42,360 --> 00:41:46,120
Speaker 2: been developed as a full system. It's moving from the

624
00:41:46,200 --> 00:41:50,560
Speaker 2: typewriter to mac desktop publishing in one step, and people

625
00:41:50,680 --> 00:41:55,840
Speaker 2: have to really understand that to see that. So my

626
00:41:56,000 --> 00:42:00,120
Speaker 2: concern is about the adoption of that and the bureaucracy

627
00:42:00,160 --> 00:42:05,200
Speaker 2: within the military that would look and say, oh, we

628
00:42:05,280 --> 00:42:09,280
Speaker 2: don't understand this. Therefore we have to put it through

629
00:42:09,680 --> 00:42:13,640
Speaker 2: whatever long process we need to make sure that we

630
00:42:14,040 --> 00:42:17,279
Speaker 2: smash it from a square peg into something round that

631
00:42:17,280 --> 00:42:19,640
Speaker 2: we can stick into our round hoole, and it takes

632
00:42:19,760 --> 00:42:23,480
Speaker 2: up time and loses the jump on the Chinese that

633
00:42:23,520 --> 00:42:27,320
Speaker 2: we have right now. I'd say my optimism comes from

634
00:42:27,680 --> 00:42:32,120
Speaker 2: the reason why President Trump's administration has tariffs is they

635
00:42:32,200 --> 00:42:35,520
Speaker 2: want to bring manufacturing back to the United States. Right,

636
00:42:36,120 --> 00:42:39,000
Speaker 2: we were a great country. I grew up obviously parents

637
00:42:39,000 --> 00:42:42,520
Speaker 2: of the greatest generation. I grew up in Cleveland, I'm

638
00:42:42,560 --> 00:42:48,000
Speaker 2: sixty five now, where manufacturing you took pride in America,

639
00:42:48,040 --> 00:42:51,640
Speaker 2: made things right. That's a lot of our dignity in

640
00:42:51,719 --> 00:42:56,320
Speaker 2: middle class came from that. We've lost that the tariffs,

641
00:42:56,320 --> 00:43:00,160
Speaker 2: for example, and trade policy that was to really we

642
00:43:00,160 --> 00:43:04,440
Speaker 2: build that manufacturing. This is the solution to do it.

643
00:43:05,120 --> 00:43:09,759
Speaker 2: So my optimism is that we have an administration that

644
00:43:10,200 --> 00:43:14,959
Speaker 2: I think in a productively disruptive way. I hope through

645
00:43:15,600 --> 00:43:18,520
Speaker 2: people like yourself, mister Speaker, who do come and see it,

646
00:43:18,560 --> 00:43:21,399
Speaker 2: who do take the time to understand this is one

647
00:43:21,480 --> 00:43:24,640
Speaker 2: of one in the world and is something that the

648
00:43:24,719 --> 00:43:28,920
Speaker 2: United States needs to take from one to one hundred

649
00:43:28,960 --> 00:43:32,640
Speaker 2: to one thousand. My optimism is that that can happen.

650
00:43:33,440 --> 00:43:36,400
Speaker 1: Well, my hope is that and I think President Trump

651
00:43:36,520 --> 00:43:39,560
Speaker 1: and Secretary Headsets maybe up to this. You know, in

652
00:43:39,560 --> 00:43:43,000
Speaker 1: World War Two we went from a jumpstart and it

653
00:43:43,120 --> 00:43:46,680
Speaker 1: was astonishing how fast we ramped up. And I think

654
00:43:46,719 --> 00:43:51,520
Speaker 1: that you are the first system I've seen which gives

655
00:43:51,560 --> 00:43:53,880
Speaker 1: us the opportunity to ramp up in that kind a

656
00:43:53,880 --> 00:43:58,040
Speaker 1: similar kind of way, and who once again the leapfrog

657
00:43:58,120 --> 00:44:00,680
Speaker 1: passed all of our competitors in a way that just

658
00:44:00,800 --> 00:44:03,200
Speaker 1: leaves them behind. So, Kevin, I want to thank you

659
00:44:03,239 --> 00:44:05,399
Speaker 1: for joining me. I think of you not only as

660
00:44:05,480 --> 00:44:09,440
Speaker 1: extraordinarily bright and hard working, but a genuine patriot, somebody

661
00:44:09,440 --> 00:44:13,240
Speaker 1: who has spent most of your life developing a system

662
00:44:13,520 --> 00:44:18,000
Speaker 1: which could in fact be the difference between survival and

663
00:44:18,080 --> 00:44:21,080
Speaker 1: failure for the United States. And I want to let

664
00:44:21,080 --> 00:44:23,759
Speaker 1: our listeners know that they can learn more about the

665
00:44:23,800 --> 00:44:28,399
Speaker 1: groundbreaking work you're doing at Divergent Technologies by visiting your

666
00:44:28,400 --> 00:44:33,160
Speaker 1: website at Divergent three d dot com. And if they

667
00:44:33,320 --> 00:44:36,400
Speaker 1: like cars, they are to check out the Zinger vehicles

668
00:44:36,840 --> 00:44:39,359
Speaker 1: at Zinger dot com. And I just want to thank

669
00:44:39,440 --> 00:44:42,600
Speaker 1: you for taking this time out of your extraordinarily busy

670
00:44:42,600 --> 00:44:45,280
Speaker 1: schedule to help educate us well.

671
00:44:45,320 --> 00:44:47,799
Speaker 2: Thank you and God bless you, mister speaker, for all

672
00:44:47,840 --> 00:44:49,600
Speaker 2: you do and for supporting us.

673
00:44:52,840 --> 00:44:55,359
Speaker 1: Thank you to my guest, Kevin Zinger. You can learn

674
00:44:55,360 --> 00:44:59,720
Speaker 1: more about his company, Divergent Technologies on our show page

675
00:45:00,000 --> 00:45:03,319
Speaker 1: at newsworld dot com. Newsworld is produced by Gingrich three

676
00:45:03,400 --> 00:45:08,000
Speaker 1: sixty and iHeartMedia. Our executive producer is Guernsey Sloan. Our

677
00:45:08,080 --> 00:45:12,239
Speaker 1: researcher is Rachel Peterson. The artwork for the show Who's

678
00:45:12,280 --> 00:45:15,600
Speaker 1: created by Steve Penley. Special thanks to the team at

679
00:45:15,600 --> 00:45:19,200
Speaker 1: Gingrich three sixty. If you've been enjoying Newtsworld, I hope

680
00:45:19,200 --> 00:45:21,799
Speaker 1: you'll go to Apple Podcast and both rate us with

681
00:45:21,920 --> 00:45:25,440
Speaker 1: five stars and give us a review so others can

682
00:45:25,520 --> 00:45:28,960
Speaker 1: learn what it's all about. Right now, listeners of newts

683
00:45:29,000 --> 00:45:32,640
Speaker 1: World can sign up for my three freeweekly columns at

684
00:45:32,640 --> 00:45:37,239
Speaker 1: gingrichstree sixty dot com slash newsletter. I'm Newt Gingrich. This

685
00:45:37,440 --> 00:45:38,640
Speaker 1: is Newtsworld