1
00:00:02,320 --> 00:00:06,680
Speaker 1: Bloomberg Audio Studios, podcasts, radio news.

2
00:00:07,120 --> 00:00:10,320
Speaker 2: Jensen One, CEO of Nvidia, fresh off his keynote last

3
00:00:10,360 --> 00:00:11,160
Speaker 2: night on stage.

4
00:00:11,600 --> 00:00:14,320
Speaker 3: Great to see you, Welcome to Las Vegas. Thank happy new.

5
00:00:14,240 --> 00:00:15,600
Speaker 1: Year, familiar territory.

6
00:00:15,760 --> 00:00:17,240
Speaker 3: Congratulations on your new baby.

7
00:00:17,400 --> 00:00:18,279
Speaker 1: Thank you very much.

8
00:00:18,880 --> 00:00:21,400
Speaker 2: A lot's changed since we last spoke, actually, but if

9
00:00:21,440 --> 00:00:25,040
Speaker 2: the broad spectrum of what you announced last night, new graphics, cards,

10
00:00:25,560 --> 00:00:29,360
Speaker 2: new chips, actually technically in the automotive space, products and

11
00:00:29,440 --> 00:00:32,720
Speaker 2: services on the software side, which is the single most

12
00:00:32,720 --> 00:00:35,360
Speaker 2: important for in video's future.

13
00:00:35,440 --> 00:00:39,560
Speaker 3: They're all important. You know, it's hard, it's hard. It's hard.

14
00:00:40,120 --> 00:00:41,919
Speaker 3: It's hard to pick your favorites. You know.

15
00:00:41,960 --> 00:00:45,840
Speaker 4: We announced three chips, We announced a brand new AI,

16
00:00:46,520 --> 00:00:50,159
Speaker 4: a world foundation model and first of its kind. And

17
00:00:50,320 --> 00:00:54,640
Speaker 4: we announced our work in three areas and robotics, right,

18
00:00:55,040 --> 00:00:59,279
Speaker 4: and they're all important. And the thing of course, we

19
00:00:59,400 --> 00:01:04,000
Speaker 4: announced that a brand new Blackwell RTX and has a

20
00:01:04,040 --> 00:01:12,080
Speaker 4: new AI technology called neuro Neuroshaters, and we're combining artificial

21
00:01:12,120 --> 00:01:14,920
Speaker 4: intelligence and classical computer.

22
00:01:15,440 --> 00:01:16,720
Speaker 1: ArtX the new RTX.

23
00:01:16,800 --> 00:01:20,399
Speaker 2: Yeah, we've become so accustomed to your story being dominant

24
00:01:20,440 --> 00:01:24,120
Speaker 2: in a market for high performance GPUs server X data centers.

25
00:01:24,400 --> 00:01:26,840
Speaker 2: This is going back to your roots. It's in the

26
00:01:26,840 --> 00:01:30,360
Speaker 2: desktop context. There's one right there later in the year laptop.

27
00:01:30,760 --> 00:01:34,840
Speaker 2: But for a target base that is developers, a nerdy,

28
00:01:34,920 --> 00:01:37,720
Speaker 2: hardcore gamers, what's the future of that business for you?

29
00:01:39,560 --> 00:01:41,640
Speaker 3: Computer graphics is going to be here forever, forever.

30
00:01:42,000 --> 00:01:46,560
Speaker 4: And what we've done is we've fused artificial intelligence and

31
00:01:46,600 --> 00:01:50,800
Speaker 4: computer graphics together. And the images that we're generating today

32
00:01:50,840 --> 00:01:53,000
Speaker 4: wouldn't be possible if not for the fact that we're

33
00:01:53,040 --> 00:01:57,400
Speaker 4: using computer graphics to create beautiful pixels and then use

34
00:01:57,480 --> 00:02:03,320
Speaker 4: artificial intelligence to amp that capability. For example, you know,

35
00:02:03,360 --> 00:02:05,960
Speaker 4: out of four frames I was talking about yesterday, thirty

36
00:02:06,000 --> 00:02:07,640
Speaker 4: three million pixels to sew and four K.

37
00:02:08,440 --> 00:02:09,640
Speaker 3: Out of that thirty three.

38
00:02:09,440 --> 00:02:13,160
Speaker 4: Million pixels, two million pixels were computed, the other thirty

39
00:02:13,200 --> 00:02:15,520
Speaker 4: one million pixels were generated by AI.

40
00:02:15,720 --> 00:02:18,000
Speaker 1: In other words, the AI predicts what it thinks the

41
00:02:18,000 --> 00:02:18,640
Speaker 1: pixel should.

42
00:02:18,760 --> 00:02:21,000
Speaker 3: That's right, yeah, the ultimate generative AI.

43
00:02:21,120 --> 00:02:23,640
Speaker 2: But what was interesting for me is the focus again

44
00:02:23,800 --> 00:02:26,720
Speaker 2: was away from the graphics cards, away from Blackworld undepen

45
00:02:26,840 --> 00:02:30,840
Speaker 2: It's in Cosmos. We probably don't have time to explain

46
00:02:30,880 --> 00:02:33,160
Speaker 2: in full detailed Cosmos, but you call it a world

47
00:02:33,240 --> 00:02:34,200
Speaker 2: foundation model.

48
00:02:34,360 --> 00:02:40,560
Speaker 4: Cosmos is for the physical world. What chatchiptas for words

49
00:02:40,560 --> 00:02:43,240
Speaker 4: and text. That's the easiest way to think about that.

50
00:02:43,400 --> 00:02:48,480
Speaker 2: Okay, so model text input, but can generate synthetic data

51
00:02:48,639 --> 00:02:49,679
Speaker 2: in multiple mediums.

52
00:02:50,440 --> 00:02:52,040
Speaker 3: It understands the physical world.

53
00:02:52,080 --> 00:02:55,680
Speaker 4: So for example, if I ask it a question, if

54
00:02:55,720 --> 00:02:59,919
Speaker 4: I ask you to generate multiple futures of a card

55
00:03:00,120 --> 00:03:04,119
Speaker 4: driving down the road, it would understand the the dynamics

56
00:03:04,200 --> 00:03:07,480
Speaker 4: of the world. They would understand the object permanence. It

57
00:03:07,520 --> 00:03:11,520
Speaker 4: would under understand geometry and space, and it would create

58
00:03:12,160 --> 00:03:17,280
Speaker 4: a driving uh scenario for the car that is plausible and.

59
00:03:17,200 --> 00:03:18,720
Speaker 1: So, and you open sourced it.

60
00:03:18,919 --> 00:03:20,960
Speaker 2: So I don't really think about it as a product

61
00:03:21,040 --> 00:03:25,440
Speaker 2: or a go to market. It's more about what Cosmos enables.

62
00:03:25,600 --> 00:03:26,960
Speaker 1: Is that how we should think about it.

63
00:03:27,080 --> 00:03:31,160
Speaker 4: Yeah, Well, the automics vehicle industry and the robotics industry

64
00:03:31,240 --> 00:03:32,880
Speaker 4: is a reilllying point to us, and we offer three

65
00:03:32,919 --> 00:03:33,839
Speaker 4: computers for them.

66
00:03:34,200 --> 00:03:35,720
Speaker 3: We offered, of course, the training.

67
00:03:35,480 --> 00:03:39,880
Speaker 4: Computer through DGX, through DGX, the robotics computer that's inside

68
00:03:39,920 --> 00:03:42,040
Speaker 4: the car or inside of robot and now we have

69
00:03:42,120 --> 00:03:47,000
Speaker 4: this new computer called Omniverse with Cosmos that is the

70
00:03:47,080 --> 00:03:50,760
Speaker 4: digital twin or the playground where these robots can learn

71
00:03:50,800 --> 00:03:53,920
Speaker 4: how to be robots, and so if we could accelerate

72
00:03:53,960 --> 00:03:57,440
Speaker 4: the development of an artificial intelligence for avs and for robotics,

73
00:03:57,800 --> 00:03:59,680
Speaker 4: it brings in a lot of business for us.

74
00:03:59,680 --> 00:04:02,200
Speaker 2: Of course, an academic point of tension here, if I

75
00:04:02,280 --> 00:04:05,360
Speaker 2: may Elon Musk is a customer of yours and Tesla.

76
00:04:06,560 --> 00:04:10,120
Speaker 2: Their theory or practice is based on real world data.

77
00:04:09,920 --> 00:04:10,880
Speaker 1: Gathered through vision.

78
00:04:11,120 --> 00:04:16,839
Speaker 2: Yeah, does the synthetic data underpinning of Cosmos kind of contradict.

79
00:04:16,240 --> 00:04:19,200
Speaker 4: That it doesn't replace it augments, and so you're going

80
00:04:19,240 --> 00:04:21,640
Speaker 4: to you should collect as much world data as you can.

81
00:04:21,800 --> 00:04:24,800
Speaker 4: Of course, collecting world data is very expensive, and Elon

82
00:04:24,920 --> 00:04:28,440
Speaker 4: has a great advantage because number one, he his AI

83
00:04:28,520 --> 00:04:31,480
Speaker 4: factory for his cars is fantastic, has a lot of

84
00:04:31,600 --> 00:04:36,719
Speaker 4: video gear in it. His av algorithms is incredible, it's

85
00:04:36,880 --> 00:04:40,080
Speaker 4: the best in the world. And he has a very

86
00:04:40,160 --> 00:04:42,760
Speaker 4: large fleet of cars on the road that allows him

87
00:04:42,800 --> 00:04:44,960
Speaker 4: to collect a lot of data. And so I think

88
00:04:45,000 --> 00:04:48,240
Speaker 4: he has just a phenomenal position, and he's been working

89
00:04:48,240 --> 00:04:50,159
Speaker 4: on this for a long time, and so he's he's

90
00:04:50,160 --> 00:04:52,240
Speaker 4: going to be in a great position to take advantage

91
00:04:52,240 --> 00:04:52,480
Speaker 4: of it.

92
00:04:52,680 --> 00:04:55,600
Speaker 2: Well, may I ask you that juncture, he's clearly influential

93
00:04:55,880 --> 00:04:59,560
Speaker 2: in this upcoming administration, but he also positions Tesla as

94
00:04:59,560 --> 00:05:02,520
Speaker 2: a leading AI and robotics company. Yeah, how does that

95
00:05:02,640 --> 00:05:07,040
Speaker 2: bode for Nvidia? Elon Musk's influencer President Electrump and also

96
00:05:07,080 --> 00:05:10,920
Speaker 2: thecoming administration's kind of attitude towards AI.

97
00:05:12,200 --> 00:05:15,880
Speaker 3: I don't know that the attitude towards AI.

98
00:05:16,360 --> 00:05:19,360
Speaker 4: I know Elon's attitude towards AI, and and he's very

99
00:05:19,360 --> 00:05:22,680
Speaker 4: optimistic about his future. And obviously he's working on some

100
00:05:22,720 --> 00:05:26,919
Speaker 4: of the most important AI areas. XAI is working on

101
00:05:27,160 --> 00:05:35,040
Speaker 4: foundation cognitive Intelligence AI, his test list, working on Thomas vehicles,

102
00:05:35,640 --> 00:05:40,480
Speaker 4: and optimists for humanoid robotics. These three areas of AI

103
00:05:40,760 --> 00:05:42,880
Speaker 4: are the three most important areas of AI, and so

104
00:05:42,960 --> 00:05:45,800
Speaker 4: I think he's working on exactly the right things.

105
00:05:45,960 --> 00:05:48,560
Speaker 2: You kind of positioned AI and Video's position in the

106
00:05:49,000 --> 00:05:53,320
Speaker 2: supply chain for physical AI, robotics, autonomous driving.

107
00:05:53,440 --> 00:05:55,680
Speaker 1: Explain it a bit more the role you see in

108
00:05:55,760 --> 00:05:56,280
Speaker 1: video play.

109
00:05:56,600 --> 00:05:59,200
Speaker 4: Well, we're a core technology company, and so we build

110
00:05:59,200 --> 00:06:03,080
Speaker 4: the foundational computing platforms. We're also full stack, and so

111
00:06:03,160 --> 00:06:07,159
Speaker 4: we developed the necessary algorithms, the necessary AI technologies, and

112
00:06:07,200 --> 00:06:09,159
Speaker 4: then we put it We put it out to the

113
00:06:09,200 --> 00:06:12,040
Speaker 4: industry for them to adopt it and turn it into

114
00:06:12,360 --> 00:06:13,480
Speaker 4: in market solutions.

115
00:06:13,920 --> 00:06:15,560
Speaker 3: We're computing platform companies.

116
00:06:15,560 --> 00:06:17,720
Speaker 2: So you're on stage and you're surrounded by I think

117
00:06:17,760 --> 00:06:20,400
Speaker 2: a dozen humanoid robots, which.

118
00:06:20,320 --> 00:06:21,040
Speaker 1: Is nice for you.

119
00:06:21,480 --> 00:06:24,200
Speaker 2: When will I be here at CS and Las Vegas

120
00:06:24,240 --> 00:06:25,400
Speaker 2: and actually.

121
00:06:24,960 --> 00:06:26,480
Speaker 3: Have there's some robots right now?

122
00:06:26,839 --> 00:06:30,080
Speaker 2: In real terms, you must have a timeline that you

123
00:06:30,200 --> 00:06:34,240
Speaker 2: see real world commercial deployment of the technology you outlined

124
00:06:34,320 --> 00:06:34,800
Speaker 2: last night.

125
00:06:35,400 --> 00:06:36,960
Speaker 3: It depends on use case.

126
00:06:37,680 --> 00:06:39,040
Speaker 1: I would say see first use.

127
00:06:39,120 --> 00:06:41,479
Speaker 4: Yeah, the first use case will probably be in manufacturing.

128
00:06:41,520 --> 00:06:45,920
Speaker 4: You know, there's estimates tends, if not one hundred million

129
00:06:47,120 --> 00:06:50,080
Speaker 4: jobs that are workers that are the world is short

130
00:06:50,120 --> 00:06:57,760
Speaker 4: of workers and aging population declining, declining birth rates, and

131
00:06:58,560 --> 00:07:01,400
Speaker 4: so I think the world needs a lot more workers.

132
00:07:02,440 --> 00:07:04,800
Speaker 4: Robotics is one of the best ways for us to

133
00:07:05,680 --> 00:07:08,960
Speaker 4: supplement all of that and help companies recover the last

134
00:07:09,000 --> 00:07:13,000
Speaker 4: revenues on the one hand and drive productivity which reduces

135
00:07:13,040 --> 00:07:16,080
Speaker 4: inflation for the world on the other hand. And so

136
00:07:16,120 --> 00:07:18,240
Speaker 4: I think robotics is going to be very important to that.

137
00:07:18,680 --> 00:07:22,680
Speaker 4: In different areas. You could have probably deploy into manufacturing

138
00:07:22,680 --> 00:07:25,400
Speaker 4: first because they obviously need it most, which you.

139
00:07:25,360 --> 00:07:28,600
Speaker 2: See as a ginormous potential market addressable loss.

140
00:07:28,400 --> 00:07:32,040
Speaker 4: It's a fifty trillion dollar industry that wants to grow, and.

141
00:07:31,960 --> 00:07:33,960
Speaker 2: It thinks to grow. Sorry to interrupt you, Jensen. I

142
00:07:34,000 --> 00:07:35,960
Speaker 2: think the thing that Wall Streets struggling with this morning,

143
00:07:36,280 --> 00:07:41,080
Speaker 2: among many things, is DGX. They understand the investment there

144
00:07:41,200 --> 00:07:45,320
Speaker 2: that drains the foundation models. In terms of Nvidia's business model,

145
00:07:46,320 --> 00:07:50,600
Speaker 2: what you outlined last night, Cosmos and then later on

146
00:07:50,600 --> 00:07:54,200
Speaker 2: on the inference side, how physical AI helps grow your

147
00:07:54,240 --> 00:07:56,400
Speaker 2: business for them, drives DGX growth.

148
00:07:56,680 --> 00:07:57,400
Speaker 1: Just simple as that.

149
00:07:57,520 --> 00:07:58,400
Speaker 3: Yeah, as simple as that.

150
00:07:58,480 --> 00:08:00,600
Speaker 4: I think if you just look at simply like that,

151
00:08:00,640 --> 00:08:04,000
Speaker 4: we have three computers, and two of the computers d

152
00:08:04,160 --> 00:08:07,160
Speaker 4: GX and Omniverse drives an enormous amount of data that

153
00:08:07,560 --> 00:08:10,840
Speaker 4: is necessary to train the AI models, and so Omniverse

154
00:08:10,880 --> 00:08:14,720
Speaker 4: creates the data that we then use to train AI models.

155
00:08:15,000 --> 00:08:18,680
Speaker 4: The training is what drives d GX sales. And the

156
00:08:18,720 --> 00:08:21,560
Speaker 4: more robots that are that are available, the more data

157
00:08:21,600 --> 00:08:23,600
Speaker 4: we can create, the more AI models we have to

158
00:08:23,760 --> 00:08:27,960
Speaker 4: we have to go train. That's that cycle is ultimately

159
00:08:28,000 --> 00:08:31,600
Speaker 4: what we're striving for. All of that drives consumption for

160
00:08:31,760 --> 00:08:32,600
Speaker 4: data center growth.

161
00:08:32,679 --> 00:08:36,200
Speaker 2: There is a surge in AI spending data center growth.

162
00:08:37,440 --> 00:08:39,480
Speaker 2: Some of our audience are a bit concerned about how

163
00:08:39,520 --> 00:08:42,960
Speaker 2: sustainable that is short, medium, and long term.

164
00:08:43,360 --> 00:08:45,880
Speaker 3: Well at at the limit.

165
00:08:45,960 --> 00:08:49,120
Speaker 4: Artificial intelligence is a single most important technology force of

166
00:08:49,160 --> 00:08:52,680
Speaker 4: our time, and it's really about we're at the beginning

167
00:08:52,720 --> 00:08:55,880
Speaker 4: of that and in the future every single data center

168
00:08:55,920 --> 00:08:59,280
Speaker 4: will be driven by AI and and the type of

169
00:08:59,320 --> 00:09:02,040
Speaker 4: computing that we today. And so if you look at

170
00:09:02,080 --> 00:09:05,400
Speaker 4: the world today, we're about a year and a half

171
00:09:05,480 --> 00:09:10,680
Speaker 4: into the remodeling, if you will, the modernization, the reinvention

172
00:09:10,760 --> 00:09:13,360
Speaker 4: of computing. And so I think that over the next

173
00:09:13,400 --> 00:09:16,120
Speaker 4: several years you're going to see the transition from the

174
00:09:16,120 --> 00:09:16,760
Speaker 4: old way of.

175
00:09:16,720 --> 00:09:18,880
Speaker 3: Doing computing general purpose computing.

176
00:09:19,000 --> 00:09:21,640
Speaker 4: There's a new way of doing computing, artificial intelligence and

177
00:09:21,679 --> 00:09:24,160
Speaker 4: accelerated computing, and so we have a lot of growth

178
00:09:24,160 --> 00:09:24,480
Speaker 4: to go do.

179
00:09:25,000 --> 00:09:27,599
Speaker 2: Let's go back to your and in videous roots and

180
00:09:27,640 --> 00:09:31,960
Speaker 2: therein lies the complication, right the story accelerated computing. You

181
00:09:32,000 --> 00:09:35,720
Speaker 2: spent four years to redefining the computer for me, but

182
00:09:35,800 --> 00:09:40,160
Speaker 2: then we get rtx Blackwell single black Well in that

183
00:09:40,240 --> 00:09:45,520
Speaker 2: form factor. The target audience is hardcore gamers but also developers.

184
00:09:45,559 --> 00:09:47,120
Speaker 2: And I wondered if you could give me any early

185
00:09:47,200 --> 00:09:50,640
Speaker 2: examples or evidence of how you see the gaming industry

186
00:09:50,960 --> 00:09:54,280
Speaker 2: adopting your technology, Well, AI.

187
00:09:54,160 --> 00:09:59,400
Speaker 4: Is going to reinvigorate.

188
00:09:58,080 --> 00:09:59,400
Speaker 3: The video game industry.

189
00:09:59,640 --> 00:10:02,200
Speaker 4: On the w one hand, for developers, is going to

190
00:10:02,200 --> 00:10:05,760
Speaker 4: reduce the cost of creating the content. On the other hand,

191
00:10:06,040 --> 00:10:08,200
Speaker 4: all of the characters that are in the games are

192
00:10:08,240 --> 00:10:10,800
Speaker 4: going to be smart characters in the future, so every

193
00:10:10,800 --> 00:10:12,640
Speaker 4: time you interact with them, they're going to be interacting

194
00:10:12,640 --> 00:10:14,920
Speaker 4: with you in a much more intelligent way. And so

195
00:10:14,960 --> 00:10:17,320
Speaker 4: the games are going to be more interesting, the characters

196
00:10:17,320 --> 00:10:21,080
Speaker 4: are going to be more interesting, the content development cost

197
00:10:21,200 --> 00:10:23,160
Speaker 4: is going to decline, and that's going to be really

198
00:10:23,160 --> 00:10:24,040
Speaker 4: great for the industry.

199
00:10:24,120 --> 00:10:26,560
Speaker 3: And so I think that the future is really.

200
00:10:26,360 --> 00:10:31,000
Speaker 4: Bright for video games, and these virtual worlds and artificial

201
00:10:31,040 --> 00:10:33,160
Speaker 4: intelligence is going to really reinvigorate it.

202
00:10:33,600 --> 00:10:35,199
Speaker 1: Project digits, may I.

203
00:10:35,160 --> 00:10:35,960
Speaker 3: Pick it up? Yeah?

204
00:10:36,040 --> 00:10:42,240
Speaker 1: Yeah, yeah, three thousand dollars digits? Yeah, a supercomputer desk?

205
00:10:42,360 --> 00:10:42,720
Speaker 3: Exactly?

206
00:10:43,240 --> 00:10:45,480
Speaker 4: How could you imagine you're just sitting there just like that,

207
00:10:45,559 --> 00:10:46,760
Speaker 4: You're working on your PC?

208
00:10:47,320 --> 00:10:48,640
Speaker 3: Well?

209
00:10:47,960 --> 00:10:51,080
Speaker 1: Here, why would I need one of these? Probably not me?

210
00:10:51,760 --> 00:10:54,760
Speaker 2: But how big is the addressable market for this? What

211
00:10:54,920 --> 00:10:56,120
Speaker 2: is the addressable market?

212
00:10:56,240 --> 00:11:00,720
Speaker 4: There are thirty million software developers. They're probably something along

213
00:11:00,720 --> 00:11:05,240
Speaker 4: the lines of ten million designers around the world. Probably

214
00:11:05,280 --> 00:11:09,559
Speaker 4: another twenty million creative artists. Hard to say exactly how

215
00:11:09,559 --> 00:11:12,760
Speaker 4: many students. I'm going to guess probably a couple one

216
00:11:12,840 --> 00:11:15,240
Speaker 4: hundred million students around the world.

217
00:11:15,880 --> 00:11:17,400
Speaker 3: Everybody is going to have to board it.

218
00:11:17,520 --> 00:11:20,960
Speaker 4: Everybody's going to have to well, they can afford computers,

219
00:11:21,480 --> 00:11:23,600
Speaker 4: and so here's if they can afford computers and they

220
00:11:23,640 --> 00:11:27,720
Speaker 4: would like to have a companion that helps them do AI,

221
00:11:28,720 --> 00:11:29,640
Speaker 4: this is the way to do it.

222
00:11:29,640 --> 00:11:30,760
Speaker 1: Can I just clarify something?

223
00:11:30,840 --> 00:11:31,400
Speaker 3: Yeah, on it?

224
00:11:31,440 --> 00:11:35,520
Speaker 2: I think you said on stage mac os, Linux and Windows,

225
00:11:35,679 --> 00:11:38,360
Speaker 2: but no, no, the location said just Linux.

226
00:11:38,040 --> 00:11:43,520
Speaker 4: No, No, whatever computer you use, you're literally enjoying how it's

227
00:11:43,520 --> 00:11:46,120
Speaker 4: going to be used. It's sitting right there and you

228
00:11:46,280 --> 00:11:48,720
Speaker 4: just connect to it wirelessly like it's your personal.

229
00:11:48,400 --> 00:11:50,360
Speaker 1: Cloud, I promised the audience.

230
00:11:50,360 --> 00:11:51,040
Speaker 3: So I'd clarify that.

231
00:11:51,440 --> 00:11:53,720
Speaker 1: Excited. Yeah, yeah, we're running short time.

232
00:11:53,840 --> 00:11:57,160
Speaker 2: President Electrump has been speaking during the course of conversation.

233
00:11:58,720 --> 00:12:00,719
Speaker 2: How imperative is it that you go to mar A

234
00:12:00,800 --> 00:12:03,880
Speaker 2: Lago and meet with him? If Nvidia is America's leading

235
00:12:03,880 --> 00:12:05,000
Speaker 2: AI company, and.

236
00:12:05,040 --> 00:12:07,240
Speaker 3: Will you I'd be delighted to go see him. Have

237
00:12:07,320 --> 00:12:08,079
Speaker 3: you been invited?

238
00:12:08,720 --> 00:12:10,640
Speaker 4: Not yet, but I would be delighted to go see

239
00:12:10,679 --> 00:12:16,360
Speaker 4: him and congratulate him and do everything we can to

240
00:12:16,360 --> 00:12:17,680
Speaker 4: help this administration succeed.

241
00:12:18,440 --> 00:12:20,360
Speaker 2: A lot of what you outlined on stage last night

242
00:12:20,400 --> 00:12:22,840
Speaker 2: in the realm of physical AI. You know, I saw

243
00:12:23,440 --> 00:12:26,760
Speaker 2: x Pong, for example, in the autonomous driving context that's

244
00:12:26,760 --> 00:12:29,360
Speaker 2: happening in China, like they are doing a lot on robotics.

245
00:12:29,559 --> 00:12:31,360
Speaker 1: So I'm going to ask you about tariffs.

246
00:12:31,920 --> 00:12:34,840
Speaker 2: You know, it's likely this coming administration will be as

247
00:12:34,880 --> 00:12:38,360
Speaker 2: restrictive on technology export and tariffs will be a function.

248
00:12:38,480 --> 00:12:39,480
Speaker 3: How have you prepared for that?

249
00:12:39,600 --> 00:12:40,000
Speaker 1: Jensen?

250
00:12:42,400 --> 00:12:47,760
Speaker 4: Whatever the administration ultimately decides, will give them as much

251
00:12:48,240 --> 00:12:51,880
Speaker 4: insight as we can from our perspective, and I'm sure

252
00:12:51,880 --> 00:12:54,520
Speaker 4: that the administration will make the right moves that's the

253
00:12:54,559 --> 00:12:55,760
Speaker 4: best interest of our country.

254
00:12:56,360 --> 00:12:57,240
Speaker 1: Twenty twenty five.

255
00:12:57,640 --> 00:12:59,360
Speaker 2: I kind of started the conversation by saying a lot

256
00:12:59,360 --> 00:13:02,720
Speaker 2: has changed since we last spoke in the summer. You

257
00:13:02,840 --> 00:13:05,640
Speaker 2: said that the age of general robotics is just around

258
00:13:05,640 --> 00:13:09,800
Speaker 2: the corner. Is twenty twenty five the year of general robotics?

259
00:13:09,880 --> 00:13:12,560
Speaker 2: Or is that a little premature to your mind?

260
00:13:12,800 --> 00:13:16,520
Speaker 4: The development is going gangbusters, as you can see all

261
00:13:16,520 --> 00:13:18,400
Speaker 4: the different robots that are going to be around here,

262
00:13:18,920 --> 00:13:23,360
Speaker 4: and the enabling technology necessary for general robotics is coming together.

263
00:13:23,440 --> 00:13:26,560
Speaker 4: All the pieces are coming together. The industry still has

264
00:13:26,600 --> 00:13:30,040
Speaker 4: a lot of engineering to do. If you look long term,

265
00:13:30,320 --> 00:13:33,960
Speaker 4: you pick your horizon in ten or twenty years, the

266
00:13:34,080 --> 00:13:37,040
Speaker 4: number of robots that's going to be on Earth that's

267
00:13:37,080 --> 00:13:39,760
Speaker 4: going to be measured in probably tens of nine hundreds

268
00:13:39,760 --> 00:13:43,920
Speaker 4: and not potentially billions of robots, and so those days

269
00:13:43,960 --> 00:13:47,520
Speaker 4: are clearly coming. Is it going to happen in the

270
00:13:47,559 --> 00:13:49,360
Speaker 4: next couple of years or the next five years, hard

271
00:13:49,360 --> 00:13:52,120
Speaker 4: to say, but the development of robotics is going to

272
00:13:52,120 --> 00:13:55,080
Speaker 4: be all over the world now and we're seeing startup companies,

273
00:13:55,200 --> 00:13:59,840
Speaker 4: large companies, industrial companies, consumer electronics companies all getting involved

274
00:13:59,880 --> 00:14:02,360
Speaker 4: in the future of robotics. And our offering to the

275
00:14:02,400 --> 00:14:05,840
Speaker 4: industry is a three computer system. And so whether they're

276
00:14:06,480 --> 00:14:09,400
Speaker 4: developing the robot, training the robot, we have DJX systems

277
00:14:09,400 --> 00:14:12,240
Speaker 4: for them and DJX clouds for them. If they're simulating

278
00:14:12,240 --> 00:14:14,800
Speaker 4: the robots, we have Omniverse for them, and if they

279
00:14:14,920 --> 00:14:16,160
Speaker 4: want to deploy that when they're.

280
00:14:15,960 --> 00:14:17,600
Speaker 3: Ready to deploy the robots, we have.

281
00:14:19,400 --> 00:14:22,920
Speaker 4: Little little computers that basically is the computer brain of

282
00:14:22,920 --> 00:14:25,920
Speaker 4: the robot that they can put inside the robot. And

283
00:14:25,960 --> 00:14:28,600
Speaker 4: so we'll work with the industry across the board from

284
00:14:28,920 --> 00:14:31,600
Speaker 4: the development of the robot to the deployment of the robot.

285
00:14:32,120 --> 00:14:35,280
Speaker 4: And we have computer systems for them, algorithms for them,

286
00:14:35,360 --> 00:14:38,040
Speaker 4: AIS for them, and we'll partner with the industry and

287
00:14:38,040 --> 00:14:39,960
Speaker 4: make this future happen very very quick.

288
00:14:40,400 --> 00:14:43,400
Speaker 2: Which line of business grows fast? Is this year data center,

289
00:14:43,600 --> 00:14:44,640
Speaker 2: gaming or other?

290
00:14:45,560 --> 00:14:48,080
Speaker 4: They're all going to grow fast. I think gaming is

291
00:14:48,080 --> 00:14:53,360
Speaker 4: continuing to grow our times. Vehicle business is already on

292
00:14:53,400 --> 00:14:55,520
Speaker 4: its way to be a five billion dollar business this

293
00:14:55,600 --> 00:14:59,440
Speaker 4: year and so and sometimes right run rate and so

294
00:15:00,160 --> 00:15:03,200
Speaker 4: the autonomous vehicle businesses is just starting to get off

295
00:15:03,240 --> 00:15:05,520
Speaker 4: the ground, and that tells you something about how we

296
00:15:05,600 --> 00:15:07,840
Speaker 4: address it. And the reason for that is we get

297
00:15:07,840 --> 00:15:10,480
Speaker 4: the benefit from the beginning of the development of the

298
00:15:10,480 --> 00:15:13,280
Speaker 4: AIS all the way to the deployment of the cars.

299
00:15:13,840 --> 00:15:15,160
Speaker 3: Because a car.

300
00:15:14,920 --> 00:15:18,920
Speaker 4: Company needs two factories, a car factory that builds the

301
00:15:18,960 --> 00:15:21,160
Speaker 4: cars and an AI factory that builds the AI sport

302
00:15:21,160 --> 00:15:24,440
Speaker 4: the cars, and both of these, both of these areas

303
00:15:24,480 --> 00:15:27,000
Speaker 4: we get to participate. And so I think it's going

304
00:15:27,040 --> 00:15:28,000
Speaker 4: to be a very large business.

305
00:15:28,400 --> 00:15:30,240
Speaker 2: I've made you late for your next appointment. Yeah, it's

306
00:15:30,280 --> 00:15:32,440
Speaker 2: crazy literally grateful for your time. It's good to see

307
00:15:32,440 --> 00:15:34,680
Speaker 2: you as well. Jensen One, the Nvidia CEO,