1
00:00:02,520 --> 00:00:13,320
Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is a

2
00:00:13,360 --> 00:00:17,120
Speaker 1: lie from coast to coast with Caroline Hide in New

3
00:00:17,200 --> 00:00:19,720
Speaker 1: York and Ed Lovelow in San Francisco.

4
00:00:23,040 --> 00:00:25,040
Speaker 2: I'm Tim Stanovek in for Caroline and Ed.

5
00:00:25,120 --> 00:00:25,440
Speaker 3: Today.

6
00:00:25,480 --> 00:00:29,280
Speaker 2: This is Bloomberg Tech coming up SpaceX, coming back down

7
00:00:29,320 --> 00:00:32,280
Speaker 2: to Earth with a slightly lower valuation, and it's IPO.

8
00:00:32,560 --> 00:00:36,080
Speaker 2: We'll break down why plus Anthropic closing a funding round

9
00:00:36,120 --> 00:00:39,159
Speaker 2: at a whopping nine hundred and sixty five billion dollar valuation.

10
00:00:39,240 --> 00:00:41,919
Speaker 2: It surpasses Open Ai for the first time in the

11
00:00:41,920 --> 00:00:46,519
Speaker 2: AI race, and Dell surges after the hardware giants outlook

12
00:00:46,600 --> 00:00:48,959
Speaker 2: far surpassed Wall Street estimates. We're gonna hear from the

13
00:00:49,000 --> 00:00:52,480
Speaker 2: CFO just a little later this hour. First, though, let's

14
00:00:52,520 --> 00:00:54,840
Speaker 2: take a check on these markets on this holiday shortened

15
00:00:54,840 --> 00:00:57,280
Speaker 2: to trading week this Friday morning. The NAZAQ one hundred

16
00:00:57,280 --> 00:01:00,560
Speaker 2: continuing to push to new records, with the mark buoyed

17
00:01:00,600 --> 00:01:03,200
Speaker 2: by hopes that a ceasefire deal could bring an end

18
00:01:03,240 --> 00:01:05,880
Speaker 2: to the Iran conflict, as well as the relentless AI

19
00:01:05,920 --> 00:01:09,640
Speaker 2: optimism trade. The Deck Benchmark index up about three percent

20
00:01:09,720 --> 00:01:12,759
Speaker 2: on the week, more than ten percent just this month.

21
00:01:13,640 --> 00:01:16,760
Speaker 2: This is AI enthusiasm sens Dell shares to a new record,

22
00:01:16,800 --> 00:01:19,920
Speaker 2: climbing today more than thirty percent, highed by twenty nine

23
00:01:19,959 --> 00:01:23,240
Speaker 2: percent right now. Dell gave an outlook for annual sales

24
00:01:23,240 --> 00:01:26,520
Speaker 2: that far surpassed analyst estimates, that fueled by demand for

25
00:01:26,560 --> 00:01:30,360
Speaker 2: servers that power AI work. Let's also take a look

26
00:01:30,360 --> 00:01:33,360
Speaker 2: at today's big number. It is one point eight trillion dollars.

27
00:01:33,480 --> 00:01:35,840
Speaker 2: It's the valuation SpaceX is said to be targeting for

28
00:01:35,880 --> 00:01:36,360
Speaker 2: its IPO.

29
00:01:36,400 --> 00:01:37,480
Speaker 3: That's according to sources.

30
00:01:37,800 --> 00:01:40,360
Speaker 2: That figure, though down from the more than two trillion

31
00:01:40,400 --> 00:01:44,480
Speaker 2: dollar valuation Bloomberg reported the company was seeking back in April.

32
00:01:45,080 --> 00:01:48,480
Speaker 2: Let's get more with Bloomberg Space and Aviation Managing editor

33
00:01:48,560 --> 00:01:51,200
Speaker 2: Benedict Camel. Benedict talk to us a little bit about

34
00:01:51,240 --> 00:01:54,200
Speaker 2: why we're seeing somewhat of a revision lower for a

35
00:01:54,240 --> 00:01:56,880
Speaker 2: potential valuation for SpaceX when it is expected to go

36
00:01:56,960 --> 00:01:57,880
Speaker 2: public next month.

37
00:02:00,080 --> 00:02:02,720
Speaker 4: Yeah, so the listing is not far off. It's a

38
00:02:02,720 --> 00:02:05,760
Speaker 4: couple of days off, So the pricing will settle in

39
00:02:05,800 --> 00:02:07,480
Speaker 4: the next couple of days. And I think what we're

40
00:02:07,480 --> 00:02:10,600
Speaker 4: seeing right now is sort of the market trying to

41
00:02:10,639 --> 00:02:12,800
Speaker 4: figure out which way things will fall. It's a little

42
00:02:12,840 --> 00:02:15,800
Speaker 4: lower is the latest number we're hearing, as you said,

43
00:02:15,840 --> 00:02:18,639
Speaker 4: one point eight trillion, which you know, if you think

44
00:02:18,639 --> 00:02:21,280
Speaker 4: about trillions, that's almost a rounding errow compared to the

45
00:02:21,320 --> 00:02:24,560
Speaker 4: more than two trillion. So this is probably sort of

46
00:02:24,639 --> 00:02:27,880
Speaker 4: that both sides on the investment banking side, but also

47
00:02:27,919 --> 00:02:30,320
Speaker 4: on the bias side, trying to sort of get a

48
00:02:30,360 --> 00:02:33,400
Speaker 4: sense of the momentum. It might also be a case

49
00:02:33,400 --> 00:02:36,440
Speaker 4: of sort of, you know, come in with low expectations

50
00:02:36,440 --> 00:02:38,680
Speaker 4: and then beat them, so that might be part of that,

51
00:02:38,919 --> 00:02:41,560
Speaker 4: So it's difficult to say at this point. Also importantly,

52
00:02:42,520 --> 00:02:44,920
Speaker 4: Musk did come out a short while ago with a

53
00:02:44,960 --> 00:02:48,919
Speaker 4: single word response saying false. So we'll have to see

54
00:02:48,960 --> 00:02:52,760
Speaker 4: who's right in the end. But you know, this is probably,

55
00:02:53,480 --> 00:02:55,640
Speaker 4: as I said, sort of a positioning game going on

56
00:02:55,760 --> 00:02:58,560
Speaker 4: right now. You don't want to come in with your

57
00:02:58,560 --> 00:03:02,120
Speaker 4: guns blazing too soon. But having said that, it's been

58
00:03:02,120 --> 00:03:04,520
Speaker 4: about a week now since we got sort of a

59
00:03:04,560 --> 00:03:07,360
Speaker 4: good sense of the numbers as part of the listing,

60
00:03:07,680 --> 00:03:10,480
Speaker 4: and these are pretty you know, mind boggling figures that

61
00:03:10,480 --> 00:03:15,679
Speaker 4: we've read. You know, the the value is one of them,

62
00:03:16,040 --> 00:03:19,800
Speaker 4: but then also the total addressable market is twenty eight trillion.

63
00:03:20,680 --> 00:03:23,560
Speaker 4: These are sort of utopis numbers in some cases. So

64
00:03:23,880 --> 00:03:26,840
Speaker 4: whether it's one point eight trillion, whether it's two trillion,

65
00:03:27,360 --> 00:03:28,640
Speaker 4: the difference isn't that big.

66
00:03:28,800 --> 00:03:32,120
Speaker 2: Some might say sort of like out of this world

67
00:03:32,200 --> 00:03:36,160
Speaker 2: maybe you know, planetary expansion. Who knows before we let

68
00:03:36,200 --> 00:03:39,200
Speaker 2: you go just on that number. If it had eighteen

69
00:03:39,240 --> 00:03:41,640
Speaker 2: point seven billion dollars in revenue in twenty twenty five,

70
00:03:41,720 --> 00:03:45,280
Speaker 2: up from fourteen billion dollars, you know in twenty twenty four,

71
00:03:45,720 --> 00:03:47,440
Speaker 2: that would if it were valued at one point eight

72
00:03:47,480 --> 00:03:50,520
Speaker 2: trillion dollars, that would be a price to sales multiple

73
00:03:50,520 --> 00:03:54,720
Speaker 2: of like ninety six, which is pretty huge. I mean,

74
00:03:55,480 --> 00:03:58,320
Speaker 2: you know, software companies are typically what ten x, So

75
00:03:58,640 --> 00:04:01,360
Speaker 2: even if this is a more conservative of valuation for

76
00:04:01,400 --> 00:04:04,360
Speaker 2: a market cap, this is still you know, huge. I

77
00:04:04,360 --> 00:04:07,000
Speaker 2: guess people are you think this is a huge opportunity?

78
00:04:07,360 --> 00:04:08,200
Speaker 2: Is that realistic?

79
00:04:09,960 --> 00:04:12,160
Speaker 4: I think you're absolutely right. It's the key word is

80
00:04:12,200 --> 00:04:14,440
Speaker 4: opportunity here, and I think people are buying into this

81
00:04:14,600 --> 00:04:16,880
Speaker 4: not sort of where things stand right now, but rather

82
00:04:16,920 --> 00:04:19,440
Speaker 4: what this business might be in five years and ten

83
00:04:19,520 --> 00:04:22,240
Speaker 4: years and twenty years. And if there's one thing that

84
00:04:22,240 --> 00:04:24,560
Speaker 4: Elon Musk has shown and has proven that he can

85
00:04:24,640 --> 00:04:27,839
Speaker 4: build a market from very little or nothing. He's done

86
00:04:27,880 --> 00:04:30,560
Speaker 4: so with Tesla, he might do so again now with

87
00:04:31,040 --> 00:04:33,920
Speaker 4: space exploration. Obviously, there's a lot of things that have

88
00:04:34,000 --> 00:04:36,560
Speaker 4: to go right again. Some of the things in the

89
00:04:37,000 --> 00:04:40,279
Speaker 4: Prospectors included items like we want to have a million

90
00:04:40,320 --> 00:04:43,680
Speaker 4: people on Mars, so you know that is sort of

91
00:04:44,000 --> 00:04:45,800
Speaker 4: future fantasies, future thinking.

92
00:04:46,040 --> 00:04:47,000
Speaker 3: But if you can pull.

93
00:04:46,800 --> 00:04:50,120
Speaker 4: Off some of those things, then maybe that valuation might

94
00:04:50,160 --> 00:04:51,839
Speaker 4: not seem quite as lofty as it is now.

95
00:04:52,000 --> 00:04:55,040
Speaker 2: Okay, well, we'll have to wait and see. Bennydacamill joining

96
00:04:55,120 --> 00:04:59,359
Speaker 2: us from berwwin. Thanks Benedict Well. Speaking of valuations, Anthropic

97
00:04:59,360 --> 00:05:01,320
Speaker 2: closing a fund round at a wopping nine hundred and

98
00:05:01,320 --> 00:05:04,400
Speaker 2: sixty five billion dollar valuation. It surpasses Open AI for

99
00:05:04,440 --> 00:05:07,360
Speaker 2: the first time in the AI race. The large round

100
00:05:07,400 --> 00:05:09,320
Speaker 2: came together any matter of weeks. It's a sign of

101
00:05:09,360 --> 00:05:13,920
Speaker 2: strong demand for Claude and for of course Anthropic. Bloomberg

102
00:05:13,920 --> 00:05:16,800
Speaker 2: Sharen Gafari joining us now with more Shreen. What I

103
00:05:16,800 --> 00:05:19,280
Speaker 2: find notable in your piece is we're getting some insight

104
00:05:19,320 --> 00:05:23,440
Speaker 2: into just how much revenue for Anthropic has increased in

105
00:05:23,600 --> 00:05:25,599
Speaker 2: just the last few months. Talk to us about the

106
00:05:25,640 --> 00:05:27,640
Speaker 2: doubling that we saw in such a short period of time.

107
00:05:29,000 --> 00:05:32,760
Speaker 5: That's right. So Anthropic is, you know, nearing fifty billion

108
00:05:32,800 --> 00:05:36,760
Speaker 5: of run rate revenue and that's a projection of their

109
00:05:36,880 --> 00:05:40,720
Speaker 5: annual revenue. The growth has been incredible. I mean just

110
00:05:40,880 --> 00:05:44,200
Speaker 5: three years ago, Anthropic was not even really a product

111
00:05:44,560 --> 00:05:48,760
Speaker 5: than what was selling any software. So that rate is

112
00:05:48,760 --> 00:05:52,680
Speaker 5: something that investors are very excited about and why you're

113
00:05:52,720 --> 00:05:58,080
Speaker 5: seeing them able to command evaluation that is now surpassing

114
00:05:58,120 --> 00:06:00,920
Speaker 5: open ai at nine hundred billion pre money. Open Ei

115
00:06:01,000 --> 00:06:04,560
Speaker 5: it was last valued earlier this spring at north of

116
00:06:04,640 --> 00:06:09,600
Speaker 5: seven hundred billion pre money. So that's how you know

117
00:06:09,640 --> 00:06:12,840
Speaker 5: you're seeing now these companies really being neck and neck.

118
00:06:13,560 --> 00:06:14,719
Speaker 3: Of course, it's.

119
00:06:14,560 --> 00:06:17,400
Speaker 5: Still early in the AI game, and these companies are

120
00:06:17,440 --> 00:06:21,559
Speaker 5: constantly surpassing each other with each model release suraring.

121
00:06:21,600 --> 00:06:24,920
Speaker 2: Could this be the final fundraising round before this company?

122
00:06:24,960 --> 00:06:28,159
Speaker 3: I pos it very well could be.

123
00:06:28,279 --> 00:06:32,880
Speaker 5: Both open Ai and Anthropic are eyeing IPOs as soon

124
00:06:32,880 --> 00:06:36,760
Speaker 5: as this fall, as we have reported, So the timing

125
00:06:36,839 --> 00:06:40,080
Speaker 5: year will be critical in terms of how are these

126
00:06:40,120 --> 00:06:43,880
Speaker 5: companies stacking up if and when they do actually move

127
00:06:43,920 --> 00:06:45,560
Speaker 5: forward with public listing.

128
00:06:45,760 --> 00:06:49,719
Speaker 2: Okay, so the question about you know, these the products

129
00:06:49,800 --> 00:06:52,640
Speaker 2: that open ai has and the products that Anthropic has.

130
00:06:52,800 --> 00:06:55,400
Speaker 2: Some people could say, wait a second, we kind of

131
00:06:55,400 --> 00:06:58,359
Speaker 2: look at these as commodities. What are these companies doing

132
00:06:58,400 --> 00:07:00,840
Speaker 2: to try to differentiate themselves from another and why is

133
00:07:00,880 --> 00:07:04,839
Speaker 2: Anthropic seemingly the hot one right now versus OpenAI or

134
00:07:04,960 --> 00:07:06,080
Speaker 2: even other model makers.

135
00:07:07,640 --> 00:07:11,320
Speaker 5: I think Anthropic has had a very strong offering with

136
00:07:11,440 --> 00:07:15,520
Speaker 5: their coding agents clod code. There were early adopters in

137
00:07:15,560 --> 00:07:17,880
Speaker 5: the software industry, and then we started to see that

138
00:07:18,040 --> 00:07:20,840
Speaker 5: roll out to Fortune five hundreds and other major business

139
00:07:20,840 --> 00:07:26,520
Speaker 5: customers who started taking up anthropics automated software AI tools.

140
00:07:26,960 --> 00:07:29,520
Speaker 5: Now that being said, again, it's always a fierce race.

141
00:07:29,600 --> 00:07:32,640
Speaker 5: We've seen Googles so improve its coding agents, Open AI's

142
00:07:32,680 --> 00:07:36,400
Speaker 5: codex tool, so picking up steam. But Anthropic really did

143
00:07:36,480 --> 00:07:41,680
Speaker 5: focus on securing those business use cases for AI earlier

144
00:07:41,720 --> 00:07:44,440
Speaker 5: on and kind of narrowly focus its attention there, and

145
00:07:44,480 --> 00:07:46,880
Speaker 5: that's been its real strength I think in the market.

146
00:07:47,240 --> 00:07:50,720
Speaker 2: Bloomberg Sharene Gafari follow Cherene for more on Bloomberg dot

147
00:07:50,720 --> 00:07:53,760
Speaker 2: com and of course on the Bloomberg terminal. Let's stay

148
00:07:53,760 --> 00:07:56,480
Speaker 2: with Anthropic because Apollo and Blackstone are working to bring

149
00:07:56,520 --> 00:07:59,960
Speaker 2: additional investors into a roughly thirty six billion dollar day

150
00:08:00,240 --> 00:08:03,520
Speaker 2: financing deal to help Anthropic build out. It's AI infrastructure

151
00:08:03,520 --> 00:08:06,640
Speaker 2: of Bloomberg Silas. Brown has the details Silas. This could

152
00:08:06,640 --> 00:08:08,840
Speaker 2: be one of the largest ever private credit deals also

153
00:08:08,840 --> 00:08:11,720
Speaker 2: one of the biggest chip financing debt transactions.

154
00:08:11,760 --> 00:08:13,080
Speaker 3: Take us into the numbers here.

155
00:08:14,480 --> 00:08:17,480
Speaker 6: Yeah, no, I mean they're kind of extraordinary numbers and symptomatic.

156
00:08:17,560 --> 00:08:19,840
Speaker 6: I think of the interest that private credit funds like

157
00:08:19,880 --> 00:08:25,400
Speaker 6: Apollo and Blackstone and notable others like bluell have in

158
00:08:25,800 --> 00:08:28,400
Speaker 6: lending to build out the kind of AI infrastructure around

159
00:08:28,400 --> 00:08:32,920
Speaker 6: these transactions, and so this is I think the largest

160
00:08:32,960 --> 00:08:35,840
Speaker 6: so far. It's going into syndication now and probably being

161
00:08:35,840 --> 00:08:39,720
Speaker 6: sold down to insurance companies, some of which Apollo owns,

162
00:08:40,679 --> 00:08:43,560
Speaker 6: and also other asset managers too. But it's become this

163
00:08:43,679 --> 00:08:48,400
Speaker 6: kind of I guess, like two track thing amongst private

164
00:08:48,400 --> 00:08:51,679
Speaker 6: credit funds, where the larger ones will take big positions

165
00:08:51,720 --> 00:08:54,800
Speaker 6: initially and then seek to sell down, sell down some

166
00:08:54,880 --> 00:08:57,720
Speaker 6: of the some of the risk through syndication. It's quite

167
00:08:57,720 --> 00:09:01,000
Speaker 6: an interesting development in like private some grade credit.

168
00:09:01,120 --> 00:09:02,960
Speaker 3: Well, as we're just covering with Sharen.

169
00:09:03,040 --> 00:09:04,360
Speaker 2: If you look at the equity side of this and

170
00:09:04,400 --> 00:09:07,360
Speaker 2: the way venture capitalists are venture capitalists are so excited

171
00:09:07,760 --> 00:09:10,720
Speaker 2: to invest in anthropic What can you tell us about

172
00:09:10,720 --> 00:09:12,719
Speaker 2: demand on the credit side.

173
00:09:13,200 --> 00:09:15,720
Speaker 6: Well, it may well be the next great savior of

174
00:09:15,760 --> 00:09:18,240
Speaker 6: private credit, because I mean, you know, the big problem

175
00:09:18,280 --> 00:09:21,800
Speaker 6: that they've had over the last year is a kind

176
00:09:21,800 --> 00:09:25,760
Speaker 6: of building of concentration around software, software as a service

177
00:09:26,320 --> 00:09:28,680
Speaker 6: and a lot of questions and concerns about you know,

178
00:09:30,120 --> 00:09:36,280
Speaker 6: portfolio concentration in software as a service and what better

179
00:09:36,320 --> 00:09:38,960
Speaker 6: place to park your money in the very thing that

180
00:09:39,000 --> 00:09:43,200
Speaker 6: seems to be disrupting the SaaS industry. So I think,

181
00:09:43,520 --> 00:09:45,480
Speaker 6: you know, you're seeing quite a lot of demand from

182
00:09:45,520 --> 00:09:48,840
Speaker 6: the larger asset managers, think Areas, think Apollo, I think

183
00:09:49,200 --> 00:09:53,600
Speaker 6: think Blackstone to try to help fund the build out.

184
00:09:53,640 --> 00:09:57,240
Speaker 6: Anything to connect the insurance capital that they manage with,

185
00:09:58,280 --> 00:10:01,080
Speaker 6: you know, with these sort of opt unities is very

186
00:10:01,160 --> 00:10:03,160
Speaker 6: much the topic du jour in private credit.

187
00:10:03,440 --> 00:10:04,880
Speaker 2: Yes, so I'm glad you brought up sort of the

188
00:10:04,920 --> 00:10:09,160
Speaker 2: irony of investing in the thing that's disrupting those existing investments,

189
00:10:09,160 --> 00:10:12,679
Speaker 2: the idea of software being disrupted by what cloud can

190
00:10:12,720 --> 00:10:15,280
Speaker 2: do and what open ai can do as well. Before

191
00:10:15,280 --> 00:10:17,840
Speaker 2: we let you go, just just give us a general overview.

192
00:10:18,120 --> 00:10:20,800
Speaker 2: You know, if we were talking and in a different world,

193
00:10:21,040 --> 00:10:23,000
Speaker 2: we'd be talking about all the challenges that the private

194
00:10:23,000 --> 00:10:25,880
Speaker 2: credit industry has faced. Could this be the great savior

195
00:10:25,960 --> 00:10:26,880
Speaker 2: for private credit?

196
00:10:28,440 --> 00:10:28,640
Speaker 3: Well?

197
00:10:28,640 --> 00:10:32,360
Speaker 6: Look, I mean I think I think my general view

198
00:10:32,440 --> 00:10:34,200
Speaker 6: is like, you know, what what do these what do

199
00:10:34,240 --> 00:10:36,400
Speaker 6: the like leading private credit firms want to speak about

200
00:10:36,400 --> 00:10:38,120
Speaker 6: at the moment. The thing that they don't want to

201
00:10:38,120 --> 00:10:41,720
Speaker 6: speak about is, I guess like leverage finance, kind of

202
00:10:41,720 --> 00:10:45,120
Speaker 6: sub investment grade kind of traditional direct lending. What private

203
00:10:45,160 --> 00:10:47,520
Speaker 6: credit is known for. What they want to speak about

204
00:10:47,600 --> 00:10:51,320
Speaker 6: is investment grade opportunities pushing into these areas like AI,

205
00:10:51,640 --> 00:10:54,920
Speaker 6: energy transition. I mean, that's where they see the opportunity set.

206
00:10:54,960 --> 00:10:57,760
Speaker 6: And I think, you know, I guess like to not

207
00:10:57,880 --> 00:11:00,760
Speaker 6: to not sort of you know, not to be sick funny,

208
00:11:00,760 --> 00:11:03,400
Speaker 6: but sort of the visionaries in private credit, I think

209
00:11:03,440 --> 00:11:07,200
Speaker 6: we'd see the lasting opportunity set being more in the

210
00:11:07,280 --> 00:11:11,160
Speaker 6: investment grade space, and that is AI, that's energy transition.

211
00:11:11,440 --> 00:11:15,280
Speaker 6: It's all of those sort of opportunities that help match

212
00:11:15,320 --> 00:11:18,440
Speaker 6: insurance capital with you know, with these kind of private

213
00:11:18,440 --> 00:11:19,720
Speaker 6: investment grade opportunities.

214
00:11:19,960 --> 00:11:24,640
Speaker 2: Silas Brown joining us from London our Bloomberg News bureau. There, Silas,

215
00:11:24,640 --> 00:11:27,040
Speaker 2: good to see you. Have a great weekend well. Coming

216
00:11:27,120 --> 00:11:30,640
Speaker 2: up next, Dell is soaring the companies full year sales

217
00:11:30,679 --> 00:11:33,120
Speaker 2: outlook crush Wall Streets estimates. Look at that, the stock

218
00:11:33,200 --> 00:11:35,559
Speaker 2: up more than thirty percent. We're going to have much

219
00:11:35,600 --> 00:11:38,600
Speaker 2: more on this next. This is Bloomberg Tech.

220
00:11:50,600 --> 00:11:50,880
Speaker 3: Shares.

221
00:11:50,920 --> 00:11:53,360
Speaker 2: Adele are surging this up for the hardware giants. Outlook

222
00:11:53,440 --> 00:11:55,160
Speaker 2: far surpassed Wall Street estimates.

223
00:11:55,160 --> 00:11:55,640
Speaker 3: It boosted.

224
00:11:55,679 --> 00:11:57,880
Speaker 2: It's full your sales outlook to a massive one hundred

225
00:11:57,920 --> 00:12:00,800
Speaker 2: and sixty seven billion dollars chairs up right now by

226
00:12:00,800 --> 00:12:02,720
Speaker 2: thirty one and a half percent. It's the top performer

227
00:12:02,760 --> 00:12:04,600
Speaker 2: in the S and P five hundred. It's having its

228
00:12:04,679 --> 00:12:07,800
Speaker 2: best day ever. It's all fueled by sixty billion dollar

229
00:12:07,880 --> 00:12:11,520
Speaker 2: forecast for AI servers alone. Here's what del CFO David

230
00:12:11,559 --> 00:12:14,280
Speaker 2: Kennedy had to say post earnings.

231
00:12:14,640 --> 00:12:17,520
Speaker 7: Eighty eight percent revenue growth, you know, two hundred and

232
00:12:17,520 --> 00:12:20,760
Speaker 7: fourteen percent EPs growth and record cash flows you know,

233
00:12:20,840 --> 00:12:25,520
Speaker 7: built on real, durable and accelerating globally. The amount of

234
00:12:25,520 --> 00:12:28,360
Speaker 7: infrastructure that's needed out there. If you look at this,

235
00:12:28,679 --> 00:12:31,720
Speaker 7: you know, really production at scale. All of those things

236
00:12:31,720 --> 00:12:33,800
Speaker 7: have given us confidence, as you say, to add to

237
00:12:33,880 --> 00:12:37,280
Speaker 7: that full year guide, adding twenty seven billion dollars to

238
00:12:37,320 --> 00:12:40,320
Speaker 7: the revenue one hundred and sixty sixty seven billion dollars

239
00:12:40,360 --> 00:12:44,400
Speaker 7: now almost fifty percent increase year on year. EPs is

240
00:12:44,440 --> 00:12:48,120
Speaker 7: seventeen dollars and ninety cents. Really strong and you know,

241
00:12:48,440 --> 00:12:49,920
Speaker 7: really looking forward to the year ahead.

242
00:12:50,800 --> 00:12:54,800
Speaker 8: David, is this coming from sort of one single hyperscala customer.

243
00:12:55,400 --> 00:12:57,480
Speaker 8: Is it the neo clouds or is there more sort

244
00:12:57,480 --> 00:12:59,720
Speaker 8: of granularity you can give me about what is actually

245
00:12:59,720 --> 00:13:03,839
Speaker 8: happening in the world. Completely acknowledge that the CPU server

246
00:13:04,000 --> 00:13:06,640
Speaker 8: is back, right, that's clear in the court of gone,

247
00:13:06,760 --> 00:13:09,280
Speaker 8: but there must be something more happening under the surface here.

248
00:13:10,840 --> 00:13:13,400
Speaker 7: Yes, this is more broad based and more prevalent across

249
00:13:13,440 --> 00:13:17,400
Speaker 7: the ecosystem and our solutions. So CSG growth seventeen percent

250
00:13:17,400 --> 00:13:20,439
Speaker 7: growth in Q one, we're guiding almost similar in Q

251
00:13:20,520 --> 00:13:24,280
Speaker 7: two you mentioned the traditional server Networking business group ninety

252
00:13:24,280 --> 00:13:27,880
Speaker 7: two percent and Q one we're expecting a strong guide

253
00:13:28,000 --> 00:13:28,800
Speaker 7: to go through the year.

254
00:13:29,240 --> 00:13:30,319
Speaker 3: Obviously, we've taken up.

255
00:13:30,280 --> 00:13:34,280
Speaker 7: Our AI Storage guide, our server guide to sixty billion

256
00:13:34,320 --> 00:13:37,200
Speaker 7: dollars and storage will grow every single quarter to go

257
00:13:37,240 --> 00:13:37,720
Speaker 7: to the year.

258
00:13:37,760 --> 00:13:39,120
Speaker 3: So it's more prevalent.

259
00:13:39,080 --> 00:13:43,319
Speaker 7: Across our products, across our verticals, across our customer base,

260
00:13:43,720 --> 00:13:46,280
Speaker 7: so really more broad based and you know AI demand

261
00:13:46,320 --> 00:13:48,400
Speaker 7: if you like, beyond the GPU in terms of the

262
00:13:48,440 --> 00:13:49,840
Speaker 7: opportunities ahead.

263
00:13:50,280 --> 00:13:53,880
Speaker 8: Can you quantify that the AI demand but beyond the GPU.

264
00:13:55,400 --> 00:13:55,600
Speaker 3: Yeah.

265
00:13:55,600 --> 00:13:57,360
Speaker 7: If you look at our guide, it's up twenty seven

266
00:13:57,440 --> 00:13:58,160
Speaker 7: billion dollars.

267
00:13:58,600 --> 00:14:00,080
Speaker 3: We've taken our AI guide up.

268
00:14:00,280 --> 00:14:03,480
Speaker 7: Ten billion dollars from fifty billion to sixty billion. So

269
00:14:03,480 --> 00:14:05,880
Speaker 7: obviously the rest is in our core business and it's

270
00:14:05,880 --> 00:14:09,720
Speaker 7: more prevalent across c ISG, traditional server and the storage market.

271
00:14:09,840 --> 00:14:11,480
Speaker 7: So you know, strong across the board.

272
00:14:11,720 --> 00:14:15,880
Speaker 8: Have you set yourself a new baseline going forward of

273
00:14:15,880 --> 00:14:19,160
Speaker 8: what the world is like for particularly the AI server business.

274
00:14:19,800 --> 00:14:22,200
Speaker 7: Yeah, I think it goes beyond the AI server business.

275
00:14:22,240 --> 00:14:24,720
Speaker 7: I think it's AI demand and total across the solution

276
00:14:25,040 --> 00:14:28,320
Speaker 7: and infrastructure stack that's there. If you look at the

277
00:14:28,320 --> 00:14:31,560
Speaker 7: broad based opportunities that are appearing, I think as we

278
00:14:31,600 --> 00:14:35,400
Speaker 7: move from training models into inferencing, those inferencing workloads are

279
00:14:35,440 --> 00:14:37,760
Speaker 7: creating a net new environment, a net new tim if

280
00:14:37,800 --> 00:14:41,520
Speaker 7: you like, that's there to go attack and go go balance.

281
00:14:41,600 --> 00:14:45,360
Speaker 7: From a customer perspective, we're seeing that and those education

282
00:14:45,440 --> 00:14:48,320
Speaker 7: elements are coming in as part of the opportunity that's

283
00:14:48,320 --> 00:14:50,680
Speaker 7: in front of us. We're excited by that, and I

284
00:14:50,720 --> 00:14:53,200
Speaker 7: think that makes it a more broad based, durable growth

285
00:14:53,480 --> 00:14:55,200
Speaker 7: over the long term for us as we see that.

286
00:14:55,600 --> 00:14:58,320
Speaker 8: I appreciate the You've outlined twice that it's broad based.

287
00:14:58,680 --> 00:15:01,680
Speaker 8: Was there one big custom them or even sector in

288
00:15:01,720 --> 00:15:04,960
Speaker 8: the court of gone or one big customer sector for

289
00:15:05,040 --> 00:15:07,480
Speaker 8: the outlook in the year that has changed the trajectory

290
00:15:07,520 --> 00:15:08,280
Speaker 8: for you.

291
00:15:08,320 --> 00:15:10,880
Speaker 7: No, it's again more broad based. If you look at

292
00:15:10,880 --> 00:15:15,200
Speaker 7: our segments Neo clouds, Sovereign, those enterprise customers you will

293
00:15:15,240 --> 00:15:18,240
Speaker 7: have meant heard and spoke with Michael last week in

294
00:15:18,280 --> 00:15:22,520
Speaker 7: relation to our five thousand customers and the enterprise side

295
00:15:22,640 --> 00:15:25,480
Speaker 7: in relation to AI. As we broad base out those

296
00:15:25,520 --> 00:15:28,480
Speaker 7: AI factories, you know there's growing. If you look at

297
00:15:28,480 --> 00:15:32,520
Speaker 7: our five quarter pipeline, all individual virtuals are growing in

298
00:15:32,560 --> 00:15:35,320
Speaker 7: their own right and it shows again that the scale

299
00:15:35,360 --> 00:15:38,240
Speaker 7: and the opportunity that's both geo and virtual based.

300
00:15:38,920 --> 00:15:41,840
Speaker 2: That was del CFO David Kennedy speaking with Bloomberg's at

301
00:15:41,920 --> 00:15:45,680
Speaker 2: Ludlow just yesterday. Well Dell's message was clear, AI spending

302
00:15:45,760 --> 00:15:48,480
Speaker 2: is not slowing. Let's bring in Janet Mui, head of

303
00:15:48,560 --> 00:15:51,200
Speaker 2: market analysis over at RBC Bruant Dolphin who says that

304
00:15:51,480 --> 00:15:53,440
Speaker 2: we're moving from the build phase of AI to the

305
00:15:53,480 --> 00:15:56,040
Speaker 2: deployment phase. I want to talk about what the deployment

306
00:15:56,040 --> 00:15:57,800
Speaker 2: phase looks like, but first I just want to talk

307
00:15:57,800 --> 00:16:00,840
Speaker 2: a little bit about big picture, you know, results that

308
00:16:00,880 --> 00:16:02,680
Speaker 2: you'd see from a company like Dell. When you see

309
00:16:02,800 --> 00:16:05,840
Speaker 2: shares up this year by two hundred and thirty two percent.

310
00:16:06,160 --> 00:16:09,040
Speaker 2: You look at the chart here, Janet, this thing is parabolic.

311
00:16:09,480 --> 00:16:12,160
Speaker 2: Does this give you any pause when you look at

312
00:16:12,200 --> 00:16:15,040
Speaker 2: historically the way valuations have risen in the past in

313
00:16:15,120 --> 00:16:17,360
Speaker 2: such a short time, and then what happens afterward?

314
00:16:18,960 --> 00:16:22,200
Speaker 9: Well, thanks for having me. Well, I think the AI

315
00:16:22,280 --> 00:16:25,320
Speaker 9: theme is really strong. I think the results from Dell

316
00:16:25,440 --> 00:16:27,680
Speaker 9: is simply stunning. But it's not just Dell. I mean,

317
00:16:27,840 --> 00:16:30,640
Speaker 9: if you look across the earnings season in Q one,

318
00:16:31,360 --> 00:16:35,040
Speaker 9: I think almost all the players in the AI ecosystem,

319
00:16:35,120 --> 00:16:40,320
Speaker 9: particularly in hardware and semiconductors, they all delivered stunning results

320
00:16:40,400 --> 00:16:44,320
Speaker 9: that handlely bait expectations. So what you're talking about is

321
00:16:44,440 --> 00:16:48,880
Speaker 9: really exponential growth in the entire AI ecosystem. So that's

322
00:16:48,920 --> 00:16:52,520
Speaker 9: a very deep profit tool that we're talking about. The

323
00:16:52,560 --> 00:16:55,640
Speaker 9: companies in there, they all need each other, so that's

324
00:16:55,680 --> 00:17:00,200
Speaker 9: why we're seeing this growth is really broadening out. So

325
00:17:00,280 --> 00:17:03,480
Speaker 9: I think this is still a very much strong circular theme.

326
00:17:03,520 --> 00:17:06,440
Speaker 9: And in terms of valuation, of course, there are companies

327
00:17:06,520 --> 00:17:10,560
Speaker 9: that valuations could look a little bit elevated or even frothy.

328
00:17:11,000 --> 00:17:13,520
Speaker 9: But if you look at the Postage House in Video,

329
00:17:13,800 --> 00:17:17,400
Speaker 9: you know, TSMC, they're still having forward p in the twenties.

330
00:17:17,880 --> 00:17:20,600
Speaker 9: So I don't see it, you know, as a bubble,

331
00:17:20,720 --> 00:17:23,480
Speaker 9: and I still see it as a very much, very

332
00:17:23,520 --> 00:17:24,640
Speaker 9: strong investible theme.

333
00:17:25,240 --> 00:17:27,679
Speaker 2: Where are the investible areas right now? I mean, if

334
00:17:27,680 --> 00:17:30,119
Speaker 2: somebody looks at what Dell's doing for today, for example,

335
00:17:30,160 --> 00:17:32,480
Speaker 2: up thirty two percent, maybe they think, okay, well maybe

336
00:17:32,520 --> 00:17:35,119
Speaker 2: I missed that boat. But where else if this is

337
00:17:35,160 --> 00:17:37,480
Speaker 2: indeed broadening out, and if it's broadening out from the

338
00:17:37,480 --> 00:17:40,639
Speaker 2: build phase to the deployment phase, as you view it,

339
00:17:40,680 --> 00:17:41,760
Speaker 2: where are the opportunities?

340
00:17:43,520 --> 00:17:47,600
Speaker 9: Yeah? Sure, So I think broadly speaking, the most visibility

341
00:17:47,680 --> 00:17:51,719
Speaker 9: is still in the AI hardware and semiconductor space. So

342
00:17:52,320 --> 00:17:55,640
Speaker 9: you know, we definitely acknowledge that there has been stunnying returns,

343
00:17:55,680 --> 00:17:58,400
Speaker 9: but it could still go on. I think we shouldn't

344
00:17:58,400 --> 00:18:01,560
Speaker 9: really fight the trend there with the most visible of

345
00:18:01,600 --> 00:18:04,560
Speaker 9: the earnings and group there. I think memory is another

346
00:18:04,720 --> 00:18:09,440
Speaker 9: interesting area, given that if you hear from the tech executives,

347
00:18:09,440 --> 00:18:12,239
Speaker 9: they're all saying memory is the botshole neck and it

348
00:18:12,280 --> 00:18:15,919
Speaker 9: could last for the next, you know, at least two years.

349
00:18:16,800 --> 00:18:18,639
Speaker 9: So I think that's a very interesting part. And I

350
00:18:18,640 --> 00:18:22,480
Speaker 9: think in terms of AI deployment, we're really seeing real

351
00:18:22,560 --> 00:18:26,959
Speaker 9: tangible benefits for our companies. And I think for some

352
00:18:27,280 --> 00:18:32,520
Speaker 9: areas of software that has been quite significant sell off,

353
00:18:32,680 --> 00:18:36,840
Speaker 9: which presents opportunities for those companies that truly owns the

354
00:18:37,080 --> 00:18:43,240
Speaker 9: ecosystem to enable that enterprise AI deployment and rollout. So

355
00:18:43,320 --> 00:18:46,879
Speaker 9: we see some opportunities in those companies, but we really

356
00:18:46,920 --> 00:18:49,560
Speaker 9: have to be very selective in terms of the software space.

357
00:18:49,720 --> 00:18:52,159
Speaker 2: Yeah, we're even chart of Micron four point six percent

358
00:18:52,200 --> 00:18:55,520
Speaker 2: today that stock, that company surpassing a trillion dollar market

359
00:18:55,520 --> 00:18:59,800
Speaker 2: cap this week Skhnix over in Korea doing much of

360
00:18:59,840 --> 00:19:03,159
Speaker 2: the same. What about a broadening out two companies that

361
00:19:03,200 --> 00:19:06,320
Speaker 2: are not necessarily within technology, And I asked this because

362
00:19:06,320 --> 00:19:10,520
Speaker 2: if we talk to the executives at any company right now,

363
00:19:11,040 --> 00:19:14,560
Speaker 2: whether it's in payments, whether it's in consumer package goods,

364
00:19:14,560 --> 00:19:16,600
Speaker 2: whether it's in banking, they're going to all tell us

365
00:19:16,600 --> 00:19:19,359
Speaker 2: the same thing. We are harnessing AI right now to

366
00:19:19,440 --> 00:19:21,800
Speaker 2: make our product better and to make us more efficient.

367
00:19:22,200 --> 00:19:24,600
Speaker 2: When do we start to see those companies be the

368
00:19:24,600 --> 00:19:28,040
Speaker 2: real beneficiaries of the technology that these tech companies are

369
00:19:28,040 --> 00:19:28,920
Speaker 2: building and deploying.

370
00:19:31,040 --> 00:19:33,480
Speaker 9: Yeah, of course we are already starting to see that, right.

371
00:19:34,160 --> 00:19:38,760
Speaker 9: So I think we see that across many top players

372
00:19:38,760 --> 00:19:42,159
Speaker 9: in a broad range of industries. But I think the

373
00:19:42,280 --> 00:19:45,200
Speaker 9: key is that those players, they do have to have

374
00:19:45,560 --> 00:19:48,480
Speaker 9: the capital to spend on AI to make sure that

375
00:19:48,520 --> 00:19:51,800
Speaker 9: you have the lead over other players. And I also

376
00:19:51,920 --> 00:19:54,280
Speaker 9: think that they do have to have some sort of

377
00:19:54,280 --> 00:20:00,000
Speaker 9: competitive edged themselves that they could realize those AI putents,

378
00:20:00,280 --> 00:20:03,080
Speaker 9: because I think that the danger is that if all

379
00:20:03,119 --> 00:20:05,360
Speaker 9: of the companies, if they're not big enough, if they

380
00:20:05,359 --> 00:20:08,760
Speaker 9: don't have competitive ash, they spend on AI. And if

381
00:20:08,800 --> 00:20:12,320
Speaker 9: everyone spends on AI, then the you know, the economic

382
00:20:12,400 --> 00:20:15,800
Speaker 9: value that the surplus will be captured ultimately by consumers

383
00:20:16,119 --> 00:20:18,920
Speaker 9: rather than those companies. So I think the core thesis

384
00:20:19,000 --> 00:20:23,000
Speaker 9: is that those companies, they originally they do have to

385
00:20:23,040 --> 00:20:25,520
Speaker 9: have a competitive ash to start with. That's why we're

386
00:20:25,600 --> 00:20:29,639
Speaker 9: always preferred companies who have mold, who have a quality bias,

387
00:20:29,720 --> 00:20:33,359
Speaker 9: and who are compig players and top top tier players

388
00:20:33,400 --> 00:20:34,199
Speaker 9: in the industries.

389
00:20:34,880 --> 00:20:39,000
Speaker 2: Jenemly of RBC Bruin Dolphin joining us today from London.

390
00:20:39,160 --> 00:20:40,760
Speaker 2: Thanks so much, Janner, appreciate your time.

391
00:20:41,240 --> 00:20:41,720
Speaker 3: We're coming up.

392
00:20:41,760 --> 00:20:44,960
Speaker 2: Lenovo logging its past month in more than a quarter century.

393
00:20:45,320 --> 00:20:47,640
Speaker 2: We're going to tell you why right after this. This

394
00:20:47,880 --> 00:21:11,840
Speaker 2: is Bloomberg Tech. It's sign out for talking tech. First up,

395
00:21:11,960 --> 00:21:14,880
Speaker 2: Lenovo logging its best month and more than a quarter century.

396
00:21:15,080 --> 00:21:18,280
Speaker 2: Shares doubled in May as a massive AI infrastructure rally

397
00:21:18,280 --> 00:21:22,560
Speaker 2: catches fire across Asia following Dell's blockbuster forecast, investors are

398
00:21:22,560 --> 00:21:27,639
Speaker 2: increasingly viewing Lenovo as a potential AI infrastructure play. Plus,

399
00:21:27,680 --> 00:21:31,119
Speaker 2: Japan's finance minister announced that the country's megabanks will get

400
00:21:31,160 --> 00:21:34,280
Speaker 2: access to open AI's latest model to continue to counter

401
00:21:34,520 --> 00:21:37,840
Speaker 2: escalating cyber threats. That move coming as Japan's biggest banks

402
00:21:37,840 --> 00:21:42,120
Speaker 2: are also set to start using anthropics mythos, and Taiwan

403
00:21:42,240 --> 00:21:45,199
Speaker 2: is forecasting as fast as x work growth in fifty years.

404
00:21:45,359 --> 00:21:48,320
Speaker 2: The Tech Hub just revised its twenty twenty six GDP

405
00:21:48,480 --> 00:21:52,000
Speaker 2: growth outlook to nine point six four percent, fueled by

406
00:21:52,000 --> 00:21:55,919
Speaker 2: an expected forty percent explosion in exports. The economy of

407
00:21:55,920 --> 00:21:58,600
Speaker 2: the Hub for advanced tech like semiconductors has been one

408
00:21:58,600 --> 00:22:03,080
Speaker 2: of the biggest beneficiary of the AI era. We'll coming

409
00:22:03,160 --> 00:22:06,320
Speaker 2: up about next Anthropic surpassing Open AI for the first

410
00:22:06,359 --> 00:22:08,879
Speaker 2: time in the AI race with a wopping nine hundred

411
00:22:08,920 --> 00:22:12,520
Speaker 2: and sixty five billion dollar valuation. We're gonna have the

412
00:22:12,560 --> 00:22:15,240
Speaker 2: details on that in just a minute. In the meantime,

413
00:22:15,320 --> 00:22:16,960
Speaker 2: taking a look at the s and P five hundred

414
00:22:17,280 --> 00:22:19,440
Speaker 2: up right now by three tenths of one percent, the

415
00:22:19,520 --> 00:22:22,600
Speaker 2: NASDAK Composit up by two tenths, the Dell on this day,

416
00:22:23,000 --> 00:22:26,439
Speaker 2: up by more than seven tenths of one percent, the

417
00:22:26,480 --> 00:22:29,320
Speaker 2: socks flat on the day today in Dell, we'll look

418
00:22:29,359 --> 00:22:32,800
Speaker 2: at that up on earnings and that outlook a wopping

419
00:22:32,960 --> 00:22:35,840
Speaker 2: thirty percent right now in the Nasdaq one hundred up

420
00:22:35,920 --> 00:22:38,879
Speaker 2: three tenths of one percent. More on Anthropic in just

421
00:22:38,920 --> 00:22:42,200
Speaker 2: a minute. It is halftime and this is Bloomberg Tech.

422
00:23:00,680 --> 00:23:03,520
Speaker 2: I'm Tim Steneveek in for Caroline and Ed today. Welcome

423
00:23:03,560 --> 00:23:07,000
Speaker 2: back to Bloomberg Tech. Let's get check back on these

424
00:23:07,119 --> 00:23:10,520
Speaker 2: markets and highlight the record highs for tech indexes such

425
00:23:10,520 --> 00:23:13,040
Speaker 2: as the Nasdaq one hundred that Benjamink set to post

426
00:23:13,080 --> 00:23:16,040
Speaker 2: another gain on the week, taking the monthly rally to

427
00:23:16,080 --> 00:23:18,600
Speaker 2: more than ten percent. Look at that over the last month,

428
00:23:18,760 --> 00:23:21,639
Speaker 2: eleven point six percent higher on the Nasdaq one hundred.

429
00:23:21,920 --> 00:23:25,040
Speaker 2: This as the AI stock boom continues, with positive earnings

430
00:23:25,080 --> 00:23:29,919
Speaker 2: fueling optimism across Asian, European and US equities. Well, speaking

431
00:23:29,920 --> 00:23:32,600
Speaker 2: of optimism, let's get back to Anthropic. The company raised

432
00:23:32,760 --> 00:23:36,080
Speaker 2: a massive sixty five billion dollars in its latest funding round,

433
00:23:36,680 --> 00:23:39,640
Speaker 2: exploding its valuation in nearly a trillion dollars in eclipsing

434
00:23:39,720 --> 00:23:42,480
Speaker 2: rival Open AI for the first time. Rebecca Bloomberg's Rebecca

435
00:23:42,520 --> 00:23:45,119
Speaker 2: Torrents can tell us more. I have to look at

436
00:23:45,160 --> 00:23:47,640
Speaker 2: these numbers twice, Rebecca, because what we're talking about.

437
00:23:47,440 --> 00:23:48,480
Speaker 3: Is so astronomical.

438
00:23:48,560 --> 00:23:51,159
Speaker 2: I mean, a few years ago we were talking about this,

439
00:23:51,200 --> 00:23:54,120
Speaker 2: nobody would believe not just these fundraising rounds, but also

440
00:23:54,160 --> 00:23:59,600
Speaker 2: these valuations demand to get into Anthropics. Even right now,

441
00:24:00,160 --> 00:24:03,960
Speaker 2: close to a trillion dollars still massive from these metro capitalists.

442
00:24:04,640 --> 00:24:07,160
Speaker 10: It's pretty remarkable. I mean, we reported just a month

443
00:24:07,200 --> 00:24:11,080
Speaker 10: ago that Anthropic was fielding investor inbound at more than

444
00:24:11,119 --> 00:24:13,840
Speaker 10: a nine hundred billion dollar evaluation and wasn't sure yet

445
00:24:13,840 --> 00:24:15,320
Speaker 10: if it was going to take it. And then This

446
00:24:15,440 --> 00:24:18,880
Speaker 10: round came together in a matter of weeks. The original

447
00:24:18,920 --> 00:24:22,000
Speaker 10: target for the round was around thirty billion and closing

448
00:24:22,040 --> 00:24:27,080
Speaker 10: at sixty five, including commitments from strategic investors including hyperscalers

449
00:24:27,080 --> 00:24:29,600
Speaker 10: like Google and Amazon. So it's both a mix of

450
00:24:29,600 --> 00:24:32,200
Speaker 10: those previous commitments but also a lot of excess demand

451
00:24:32,200 --> 00:24:35,480
Speaker 10: from these financial firms. There are four leads in this round,

452
00:24:35,480 --> 00:24:39,240
Speaker 10: typical Silicon Valley venture capital firms, but the full list

453
00:24:39,720 --> 00:24:41,600
Speaker 10: is very long. As people are piling into this.

454
00:24:41,560 --> 00:24:42,600
Speaker 3: One, are are people?

455
00:24:42,720 --> 00:24:45,280
Speaker 2: Are are investors in these firms piling in right now?

456
00:24:45,320 --> 00:24:47,160
Speaker 2: I mean, in other cycles we've talked about in the past,

457
00:24:48,160 --> 00:24:50,480
Speaker 2: let's call them Web two point zero, for example, we

458
00:24:50,480 --> 00:24:52,399
Speaker 2: saw investors come in late because they wanted to be

459
00:24:52,440 --> 00:24:54,560
Speaker 2: part of something that was like almost at that point

460
00:24:54,560 --> 00:24:57,239
Speaker 2: guarante te to be some sort of home run. How

461
00:24:57,320 --> 00:25:00,960
Speaker 2: much is new money coming in versus existing investors?

462
00:25:00,960 --> 00:25:01,200
Speaker 3: Here?

463
00:25:02,480 --> 00:25:05,359
Speaker 10: We've got new and existing investors on this cap table.

464
00:25:05,400 --> 00:25:07,600
Speaker 10: I mean, this is a real mix of you know,

465
00:25:07,640 --> 00:25:12,320
Speaker 10: sort of long time believers in Anthropic and you know,

466
00:25:12,359 --> 00:25:15,840
Speaker 10: sort of Silicon Valley heavyweights and crossovers. In anticipation of

467
00:25:15,880 --> 00:25:19,000
Speaker 10: a potential IPO Foranthropic later this year, and as we

468
00:25:19,119 --> 00:25:23,840
Speaker 10: reported Anthropics IPO timeline remains unchanged by this fundraise, despite

469
00:25:24,000 --> 00:25:25,840
Speaker 10: you know, the sixty five billion dollars in new money

470
00:25:25,880 --> 00:25:29,400
Speaker 10: coming in. The company is not planning to delay it's

471
00:25:29,400 --> 00:25:31,520
Speaker 10: IPO at all and could go public as soon as

472
00:25:31,600 --> 00:25:34,280
Speaker 10: later this year. That's similar to what Opening I is

473
00:25:34,280 --> 00:25:37,400
Speaker 10: planning as well, So we could have a crop of

474
00:25:38,119 --> 00:25:41,000
Speaker 10: you know, really massive IPOs later this year, of course,

475
00:25:41,000 --> 00:25:43,480
Speaker 10: following SpaceX, sooner rather than later.

476
00:25:43,560 --> 00:25:45,719
Speaker 2: All right, say what you want about valuations right now.

477
00:25:45,720 --> 00:25:48,040
Speaker 2: It's an exciting time to be covering venture capital for sure.

478
00:25:48,040 --> 00:25:50,480
Speaker 2: Bloomberg's Rebecca Torents, thanks so much, Rebecca.

479
00:25:50,560 --> 00:25:51,040
Speaker 3: Good to see you.

480
00:25:51,440 --> 00:25:53,639
Speaker 2: The question how much of an impact what a I

481
00:25:53,720 --> 00:25:56,640
Speaker 2: have on the workforce, it's the million or maybe even

482
00:25:56,640 --> 00:25:59,600
Speaker 2: trillion dollar question, and according to Muddy Waters Capital CEO

483
00:25:59,640 --> 00:26:02,360
Speaker 2: Carson Luck, it could affect more than one in ten

484
00:26:02,440 --> 00:26:05,200
Speaker 2: knowledge workers. Here's what he told Bloomberg's Haws Slenda I'm

485
00:26:05,240 --> 00:26:06,040
Speaker 2: in this week.

486
00:26:06,960 --> 00:26:10,600
Speaker 11: Our house view is that we're going to see fifteen

487
00:26:10,920 --> 00:26:15,040
Speaker 11: percent displacement of knowledge workers. You know, we think it

488
00:26:15,040 --> 00:26:16,880
Speaker 11: could be as soon as three years.

489
00:26:17,840 --> 00:26:19,200
Speaker 3: Is it four? Is it five?

490
00:26:19,880 --> 00:26:23,320
Speaker 11: At some point and it's in the single digit number

491
00:26:23,320 --> 00:26:26,879
Speaker 11: of years. This will this will be a factor or

492
00:26:26,920 --> 00:26:29,760
Speaker 11: this this will occur in our view, and yes, there

493
00:26:29,800 --> 00:26:32,840
Speaker 11: will be jobs that are created by AI, but we're

494
00:26:32,840 --> 00:26:37,840
Speaker 11: talking about net losses because the technology is increasing in

495
00:26:37,880 --> 00:26:42,159
Speaker 11: capability faster than we humans are able to adapt to it.

496
00:26:42,880 --> 00:26:45,399
Speaker 2: Muddy Water CEO Carson Block there to his slend to

497
00:26:45,440 --> 00:26:47,400
Speaker 2: am In just earlier this week. While our next guest

498
00:26:47,440 --> 00:26:49,960
Speaker 2: thinks that AI could boost productivity at the national level

499
00:26:50,280 --> 00:26:52,280
Speaker 2: and that over the next ten years the trend rate

500
00:26:52,320 --> 00:26:54,800
Speaker 2: of real GDP growth for the US could rise to

501
00:26:54,800 --> 00:26:58,320
Speaker 2: two point four percent, Goldman Sachs demanding Director Matthew were

502
00:26:58,600 --> 00:27:01,520
Speaker 2: joins us now for more So, Matthew, where does this happen?

503
00:27:01,560 --> 00:27:03,560
Speaker 2: This is what everybody's trying to figure out, including the

504
00:27:03,560 --> 00:27:06,000
Speaker 2: Federal Reserve. Ja Powell was asked about this all the time,

505
00:27:06,040 --> 00:27:08,560
Speaker 2: and I can imagine that Kevin Warsh and New Fed

506
00:27:08,600 --> 00:27:11,000
Speaker 2: Shaer will be asked about this all the time. Where

507
00:27:11,040 --> 00:27:13,480
Speaker 2: does the productivity hit in the economy and when?

508
00:27:14,600 --> 00:27:17,400
Speaker 12: Sure, so, we think, in contrast to the last few

509
00:27:17,400 --> 00:27:22,200
Speaker 12: of those expressed, the productivity boost to the economy will

510
00:27:22,200 --> 00:27:25,560
Speaker 12: come gradually over the course of the next ten years.

511
00:27:25,920 --> 00:27:28,560
Speaker 12: We do think, and these are views from our economists.

512
00:27:28,560 --> 00:27:32,320
Speaker 12: Segulement Sachs said about twenty five percent of tasks in

513
00:27:32,359 --> 00:27:35,840
Speaker 12: the US economy could potentially be automated. Now, at the

514
00:27:35,880 --> 00:27:39,520
Speaker 12: headline level, that is a scary number because that would suggest, oh, gosh,

515
00:27:39,560 --> 00:27:41,680
Speaker 12: twenty five percent of jobs are going to be lost.

516
00:27:41,720 --> 00:27:45,800
Speaker 12: But in reality, the vast majority of those tasks will

517
00:27:45,800 --> 00:27:49,200
Speaker 12: be automated, which will free up workers to pivot to

518
00:27:49,320 --> 00:27:52,399
Speaker 12: higher productive tasks. Not all of them will lead to

519
00:27:52,480 --> 00:27:55,760
Speaker 12: job losses. When we think about where that's going to exist,

520
00:27:55,840 --> 00:27:57,560
Speaker 12: we've done a lot of detailed work in terms of

521
00:27:57,600 --> 00:28:01,119
Speaker 12: sector bi sector, Which sectors have the most tasks that

522
00:28:01,160 --> 00:28:04,600
Speaker 12: can be automated. Some sectors are very immune, some sectors

523
00:28:04,680 --> 00:28:08,080
Speaker 12: are quite more vulnerable. But we do think over ten

524
00:28:08,160 --> 00:28:10,600
Speaker 12: years it'll be a gradual process. There will be new

525
00:28:10,680 --> 00:28:12,760
Speaker 12: jobs created as well that will also be higher productive.

526
00:28:12,800 --> 00:28:14,320
Speaker 2: Well, I'm glad you brought up the nuance and sort

527
00:28:14,320 --> 00:28:16,960
Speaker 2: of the distinction map between actually losing jobs and then

528
00:28:17,000 --> 00:28:19,560
Speaker 2: people being freed up to do stuff that's more productive.

529
00:28:19,720 --> 00:28:22,400
Speaker 2: In terms of the vulnerabilities that you and your team

530
00:28:22,640 --> 00:28:25,720
Speaker 2: have identified, what are they? Are they certain jobs, are

531
00:28:25,720 --> 00:28:29,119
Speaker 2: they certain industries? What should people be prepared for In

532
00:28:29,200 --> 00:28:30,040
Speaker 2: terms of disruption.

533
00:28:31,080 --> 00:28:34,600
Speaker 12: Sure, well, I think the jobs that are most client

534
00:28:34,760 --> 00:28:37,840
Speaker 12: or human facing that are probably the safest. It's the jobs, though,

535
00:28:37,840 --> 00:28:42,320
Speaker 12: that have more repetitive tasks that are probably.

536
00:28:41,960 --> 00:28:43,120
Speaker 3: The most vulnerable.

537
00:28:43,200 --> 00:28:47,400
Speaker 12: At this point, we have some colleaguese Glemnsak's research who

538
00:28:47,400 --> 00:28:51,400
Speaker 12: have identified specific areas where there are more vulnerabilities, and

539
00:28:51,480 --> 00:28:54,200
Speaker 12: there are specific segments. But we do think in some

540
00:28:54,360 --> 00:28:57,160
Speaker 12: cases some of the concern with regards to job losses

541
00:28:57,480 --> 00:29:01,840
Speaker 12: are well overdone. You've seen references in certain media publications

542
00:29:01,880 --> 00:29:05,160
Speaker 12: referring to the jobs apocalypse are share and CEO of

543
00:29:05,200 --> 00:29:07,920
Speaker 12: gold and Sacks, David Solomon published an op ed this piece,

544
00:29:08,480 --> 00:29:11,120
Speaker 12: which is the view and we very much believe it

545
00:29:11,160 --> 00:29:13,400
Speaker 12: here at Golden Sachs at in aggregate, there will be

546
00:29:13,440 --> 00:29:17,040
Speaker 12: more jobs created than jobs lost, but we shouldn't take

547
00:29:17,040 --> 00:29:18,600
Speaker 12: away from the fact that this will be a painful

548
00:29:18,960 --> 00:29:21,640
Speaker 12: transition at the individual level in certain sectors.

549
00:29:21,840 --> 00:29:25,960
Speaker 2: Is there a certain historical corollary we can look at.

550
00:29:26,000 --> 00:29:28,440
Speaker 2: I mean, in the past we've heard this era as

551
00:29:28,560 --> 00:29:32,480
Speaker 2: referred to as like a new industrial revolution, but in

552
00:29:32,560 --> 00:29:35,320
Speaker 2: terms of the tech that, in your view you believe

553
00:29:35,400 --> 00:29:37,920
Speaker 2: is being deployed as a result of this investment, and

554
00:29:38,040 --> 00:29:41,800
Speaker 2: as a result of what's happening to infrastructure right now,

555
00:29:42,160 --> 00:29:44,520
Speaker 2: what's a good historical corollary for us to think about.

556
00:29:45,520 --> 00:29:48,200
Speaker 12: Well, one historical corollary that we really like to point to,

557
00:29:48,240 --> 00:29:50,640
Speaker 12: and this is worked by MIT. If you look at

558
00:29:51,320 --> 00:29:54,080
Speaker 12: occupations that exist today, so one hundred and seventy million

559
00:29:54,200 --> 00:29:57,840
Speaker 12: jobs in the US economy, the majority of those jobs

560
00:29:57,920 --> 00:30:02,480
Speaker 12: or occupations I should say, didn't act exist in nineteen forty.

561
00:30:02,560 --> 00:30:07,200
Speaker 12: The innovation technological progress of the US economy is one

562
00:30:07,200 --> 00:30:09,880
Speaker 12: of the reasons the US economy is so dynamic. New

563
00:30:09,960 --> 00:30:13,520
Speaker 12: jobs are always created each and every year, and more

564
00:30:13,600 --> 00:30:16,560
Speaker 12: jobs are created than jobs are lost. I think one

565
00:30:16,600 --> 00:30:18,360
Speaker 12: other thing we should be pointing to is that there

566
00:30:18,360 --> 00:30:21,240
Speaker 12: has been a de industrialization of the US economy over

567
00:30:21,320 --> 00:30:24,520
Speaker 12: several decades. There are many new jobs that exist today

568
00:30:24,520 --> 00:30:27,600
Speaker 12: that didn't exist before. I think we should think about

569
00:30:27,640 --> 00:30:30,280
Speaker 12: over the last twenty five years, the digital economy, the

570
00:30:30,360 --> 00:30:33,560
Speaker 12: Internet that's created a lot of new occupations that didn't

571
00:30:34,080 --> 00:30:37,600
Speaker 12: exist before. Think of influencers, think of gig workers, think

572
00:30:37,640 --> 00:30:39,320
Speaker 12: of the video game sector.

573
00:30:39,400 --> 00:30:41,080
Speaker 3: There are millions and millions of new.

574
00:30:40,960 --> 00:30:44,280
Speaker 12: Jobs that didn't actually exist before. These were also occupations

575
00:30:44,680 --> 00:30:47,240
Speaker 12: that didn't exist. We don't think this time is any different.

576
00:30:47,280 --> 00:30:49,880
Speaker 12: The US economy will adapt and be creating new jobs.

577
00:30:50,680 --> 00:30:53,640
Speaker 2: I hesitate to even ask this question because it's opening

578
00:30:53,680 --> 00:30:55,840
Speaker 2: a real can of worms with just a minute left, Matt.

579
00:30:55,880 --> 00:30:58,800
Speaker 2: But what if it doesn't. What if the promise is

580
00:30:58,840 --> 00:31:01,719
Speaker 2: that that have been made and that investors are betting

581
00:31:01,720 --> 00:31:03,360
Speaker 2: on don't actually come to fruition.

582
00:31:04,480 --> 00:31:07,520
Speaker 12: Yeah, that's a very very important question right now, because

583
00:31:07,560 --> 00:31:09,840
Speaker 12: one of the things we're seeing is that we need

584
00:31:09,920 --> 00:31:14,640
Speaker 12: to see the enterprise users of AI generating profits on

585
00:31:14,680 --> 00:31:17,800
Speaker 12: the back of the investment that they've been making. If

586
00:31:17,840 --> 00:31:22,040
Speaker 12: that occurs, then you have a self perpetuating economic ecosystem

587
00:31:22,120 --> 00:31:25,280
Speaker 12: for the AI complex. Right now, all of the funding

588
00:31:25,360 --> 00:31:28,280
Speaker 12: is primarily coming from external investors as well as cash

589
00:31:28,320 --> 00:31:32,080
Speaker 12: flow from other businesses. Think of the hyperscalers. But right now,

590
00:31:32,120 --> 00:31:35,719
Speaker 12: the only part of the stack that's generating a lot

591
00:31:35,760 --> 00:31:38,920
Speaker 12: of profits on the back of AI are the semiconductor companies.

592
00:31:39,480 --> 00:31:41,600
Speaker 12: So as we think about the stock prices of the

593
00:31:41,640 --> 00:31:45,000
Speaker 12: semiconductor companies as well as the valuations, for example, of

594
00:31:45,080 --> 00:31:47,760
Speaker 12: some of the private companies you mentioned earlier, there is

595
00:31:47,800 --> 00:31:50,800
Speaker 12: some vulnerability here if we don't start to see enterprise

596
00:31:50,920 --> 00:31:54,280
Speaker 12: users generate the profits that are necessary for them to

597
00:31:54,320 --> 00:31:58,800
Speaker 12: continue investing, which will generate revenues for the application companies,

598
00:31:58,800 --> 00:32:02,120
Speaker 12: the model companies, infrastructure, and then the semi conductor companies.

599
00:32:02,280 --> 00:32:05,800
Speaker 2: Matt, we are very thoughtful conversation. I appreciate you taking

600
00:32:05,840 --> 00:32:07,960
Speaker 2: the time in joining us this morning. That's Goldman Sachs

601
00:32:08,040 --> 00:32:11,440
Speaker 2: Manning Director, Matt, and we're joining us in San Francisco. Well,

602
00:32:11,800 --> 00:32:14,320
Speaker 2: what began is a rocket startup, now a big bet

603
00:32:14,360 --> 00:32:18,040
Speaker 2: on satellites, AI and yeah, Mars with a projected valuation

604
00:32:18,080 --> 00:32:22,040
Speaker 2: close to two trillion dollars. SpaceX's IPO could reshade markets.

605
00:32:22,440 --> 00:32:25,640
Speaker 2: But is Wall Street rushing in too fast? Bloomberg Originals

606
00:32:25,720 --> 00:32:26,480
Speaker 2: took a deep dive.

607
00:32:30,080 --> 00:32:34,360
Speaker 13: SpaceX is taking off and we're not just talking about rockets.

608
00:32:34,800 --> 00:32:36,120
Speaker 3: We've never seen anything like this.

609
00:32:39,240 --> 00:32:42,640
Speaker 13: SpaceX's initial public offering is expected to raise as much

610
00:32:42,640 --> 00:32:46,440
Speaker 13: as seventy five billion dollars, more than double the record

611
00:32:46,480 --> 00:32:49,760
Speaker 13: setting twenty nine point four billion dollars raised by Saudi

612
00:32:49,800 --> 00:32:51,320
Speaker 13: Aramco in twenty nineteen.

613
00:32:52,200 --> 00:32:53,960
Speaker 3: This is the biggest s I peer overall time.

614
00:32:54,200 --> 00:32:57,760
Speaker 14: We're looking at two trillion dollars in valuation.

615
00:32:58,960 --> 00:33:01,280
Speaker 15: You on long and said that he didn't really plan

616
00:33:01,360 --> 00:33:04,640
Speaker 15: on taking SpaceX public, but that was before the merger

617
00:33:04,640 --> 00:33:07,560
Speaker 15: with Xai, before he needed tens of billions of dollars

618
00:33:07,560 --> 00:33:09,760
Speaker 15: to build out these ambitions.

619
00:33:10,400 --> 00:33:13,920
Speaker 13: But this massive valuation is also a test. Could all

620
00:33:13,920 --> 00:33:16,120
Speaker 13: this hype make it seem worth more than it is.

621
00:33:16,560 --> 00:33:19,800
Speaker 1: If it's free ordained, then it becomes hard to predict

622
00:33:19,800 --> 00:33:23,560
Speaker 1: how much of the buyers are buying because the fundamentalers

623
00:33:23,600 --> 00:33:26,520
Speaker 1: are the valuation, So then that kind of distorts the market.

624
00:33:27,120 --> 00:33:29,040
Speaker 15: Investors are buying the dream.

625
00:33:29,080 --> 00:33:36,400
Speaker 13: Sure, we all know the dream, but what about the reality.

626
00:33:37,480 --> 00:33:39,880
Speaker 2: SpaceX and the age of the giant IPO. Check out

627
00:33:39,920 --> 00:33:42,960
Speaker 2: the full episode over at Bloomberg dot com or on YouTube,

628
00:33:43,480 --> 00:33:46,000
Speaker 2: and let's just talk about that reality. SpaceX does seem

629
00:33:46,040 --> 00:33:48,280
Speaker 2: to be coming back down to Earth, ever so slightly,

630
00:33:48,320 --> 00:33:51,520
Speaker 2: after cutting its IPO evaluation goal too, at least one

631
00:33:51,520 --> 00:33:54,200
Speaker 2: point eight trillion dollars instead of above two trillion dollars.

632
00:33:54,200 --> 00:33:55,800
Speaker 3: That's according to sources. Let's break it.

633
00:33:55,720 --> 00:33:58,720
Speaker 2: Down with Bloomberg Intelligence analyst George Fergus and Georgia can't

634
00:33:58,720 --> 00:34:02,000
Speaker 2: help but smile when I see those numbers, because I mean,

635
00:34:02,040 --> 00:34:04,000
Speaker 2: coming back down to Earth, it's all relative. When we're

636
00:34:04,000 --> 00:34:06,280
Speaker 2: talking about you know this blockbuster. What could be the

637
00:34:06,280 --> 00:34:10,080
Speaker 2: biggest IPO ever one point eight trillion dollars. You have

638
00:34:10,160 --> 00:34:14,680
Speaker 2: spent many years of valuing companies in aerospace. What is

639
00:34:14,719 --> 00:34:18,160
Speaker 2: the valuation promise of a one point eight trillion dollar

640
00:34:18,280 --> 00:34:23,759
Speaker 2: market cap? When SpaceX what has you know, revenue in

641
00:34:23,840 --> 00:34:26,560
Speaker 2: twenty twenty four of fourteen billion dollars.

642
00:34:29,000 --> 00:34:32,840
Speaker 16: Yeah, so obviously those numbers are quite lofty. You know,

643
00:34:32,840 --> 00:34:35,719
Speaker 16: we're spending some time right now doing our sort of

644
00:34:36,160 --> 00:34:41,719
Speaker 16: some of the parts analysis on SpaceX's value, and my

645
00:34:42,160 --> 00:34:45,879
Speaker 16: friends Man Deep and his team in the AI side

646
00:34:45,880 --> 00:34:48,720
Speaker 16: of Bloomberg Intelligence, there's sort of at a four hundred

647
00:34:48,760 --> 00:34:54,880
Speaker 16: billion dollars for XAI, and John Butler, who runs our

648
00:34:54,920 --> 00:34:59,880
Speaker 16: telecommunications analysis, he's at sort of six hundred billion four

649
00:35:00,920 --> 00:35:05,600
Speaker 16: for the communications for the satellite constellation. And you know,

650
00:35:05,640 --> 00:35:09,120
Speaker 16: on the on the launch side, we kind of we're

651
00:35:09,120 --> 00:35:14,680
Speaker 16: looking at companies like rocket Lab that are ninety times revenue,

652
00:35:15,520 --> 00:35:17,080
Speaker 16: and when we look at what we you know, what

653
00:35:17,120 --> 00:35:21,839
Speaker 16: we think revenue is for SpaceX launch business, including their

654
00:35:21,880 --> 00:35:24,360
Speaker 16: internal launch they don't which they don't put in the

655
00:35:24,440 --> 00:35:29,040
Speaker 16: revenue numbers you cited. We think that that's the market

656
00:35:29,080 --> 00:35:34,800
Speaker 16: says it's worth one point two sort of trillion dollars. Again,

657
00:35:34,840 --> 00:35:39,080
Speaker 16: that's a multiple of revenue, which is always aggressive. It's

658
00:35:39,120 --> 00:35:40,960
Speaker 16: a very high multiple of revenue that gets them to

659
00:35:41,040 --> 00:35:44,000
Speaker 16: around two trillion dollars and a lot of it built

660
00:35:44,160 --> 00:35:49,759
Speaker 16: on the rocket launch business. So definitely some very lofty valuations.

661
00:35:49,880 --> 00:35:52,520
Speaker 2: Well, it brings us to the Musk factor here, George,

662
00:35:52,520 --> 00:35:53,759
Speaker 2: and I think there are a lot of people over

663
00:35:53,760 --> 00:35:56,720
Speaker 2: the last decade who have said, you know, the Tesla

664
00:35:56,840 --> 00:35:58,879
Speaker 2: is not valued as an auto company, and you really

665
00:35:58,880 --> 00:36:02,960
Speaker 2: have to divorce additional valuation metrics in order to get

666
00:36:02,960 --> 00:36:05,680
Speaker 2: to a number that we believe is the opportunity for Tesla.

667
00:36:06,160 --> 00:36:08,759
Speaker 2: I know you cover aerospace and your background is in

668
00:36:08,840 --> 00:36:13,080
Speaker 2: aerospace and defense, but is that the extra six hundred

669
00:36:13,480 --> 00:36:14,520
Speaker 2: billion dollars here?

670
00:36:14,600 --> 00:36:15,480
Speaker 3: Is that Elon Musk?

671
00:36:16,800 --> 00:36:20,239
Speaker 16: So I think you have to have to in order

672
00:36:20,280 --> 00:36:23,600
Speaker 16: to buy into this IPO valuation. I think you have

673
00:36:23,680 --> 00:36:27,080
Speaker 16: to believe in Elon Musk and the dream as you

674
00:36:27,120 --> 00:36:30,600
Speaker 16: mentioned earlier, and look, I think there's good reasons to

675
00:36:30,600 --> 00:36:32,839
Speaker 16: believe in them. You have to decide what value you're

676
00:36:32,840 --> 00:36:36,360
Speaker 16: willing to pay for it. But you know, like we

677
00:36:36,400 --> 00:36:40,400
Speaker 16: saw yesterday, we saw Blue Origin, you know, had a

678
00:36:40,520 --> 00:36:43,879
Speaker 16: one of their engines blow up on the bad down

679
00:36:43,920 --> 00:36:48,840
Speaker 16: in Cape Canaveral yesterday. You know, they're about three launches

680
00:36:48,920 --> 00:36:53,280
Speaker 16: deep on New Glen. It's not as easy as Elon

681
00:36:53,400 --> 00:36:55,960
Speaker 16: Musk has made it look. He shot you know, his

682
00:36:56,080 --> 00:36:59,759
Speaker 16: company shot off almost one hundred and seventy rockets last

683
00:36:59,880 --> 00:37:02,960
Speaker 16: year year with minimal problems compared to what's going on

684
00:37:03,040 --> 00:37:06,960
Speaker 16: right now Blue Origin. So there is a track record

685
00:37:07,040 --> 00:37:11,480
Speaker 16: of success from Elon Musk and his companies. I'm not

686
00:37:11,520 --> 00:37:13,960
Speaker 16: saying that makes the valuation correct, but you have to

687
00:37:14,000 --> 00:37:17,200
Speaker 16: buy into that. And Elon has shown a lot of

688
00:37:17,200 --> 00:37:18,320
Speaker 16: success in what he's done.

689
00:37:18,360 --> 00:37:20,080
Speaker 2: And maybe if it goes into the index, we'll all

690
00:37:20,080 --> 00:37:22,239
Speaker 2: have to buy into it, whether we want to or not.

691
00:37:22,840 --> 00:37:26,640
Speaker 2: George Ferguson of Bloomberg Intelligence, George, thanks so much. George

692
00:37:26,640 --> 00:37:29,839
Speaker 2: did mention Blue Origin. We're going to be talking about

693
00:37:29,840 --> 00:37:31,759
Speaker 2: that with Lauren Brush in a few minutes. Coming up though,

694
00:37:31,760 --> 00:37:34,120
Speaker 2: Before that, we're going to hear from Google deep minds

695
00:37:34,160 --> 00:37:37,440
Speaker 2: head of robotics, Caroline Parata, on her take on the

696
00:37:37,440 --> 00:37:51,520
Speaker 2: future of embodied AI. This is Bloomberg Tech. Google deep

697
00:37:51,520 --> 00:37:54,960
Speaker 2: mind says humanoid robotics is one of the key focus areas.

698
00:37:55,320 --> 00:37:58,920
Speaker 2: Carolina Parata, who leads the company's robot Mobility and robot

699
00:37:59,000 --> 00:38:02,480
Speaker 2: Vision group spoke with Bloomberg Tech Asia's Sharry On at

700
00:38:02,480 --> 00:38:05,840
Speaker 2: the Humanoid Summit in Tokyo about why she sees embodied

701
00:38:05,840 --> 00:38:07,360
Speaker 2: AI as the next frontier.

702
00:38:08,280 --> 00:38:11,359
Speaker 17: We've been working on bringing Gemini into the physical world,

703
00:38:11,800 --> 00:38:13,319
Speaker 17: and what that does is that it brings all of

704
00:38:13,360 --> 00:38:17,320
Speaker 17: Gemini's world understanding multimodality in order to enable robots to

705
00:38:17,400 --> 00:38:20,480
Speaker 17: understand their environment, to reason, and to be able to

706
00:38:20,520 --> 00:38:23,440
Speaker 17: take action to the level of precision of a human expert.

707
00:38:23,719 --> 00:38:26,800
Speaker 18: I just mentioned that partnership with Boston Dynamics. So Gemini

708
00:38:27,000 --> 00:38:29,640
Speaker 18: will go into Atlas, we'll go into Spot the Little

709
00:38:29,680 --> 00:38:32,280
Speaker 18: Dog as well. Yeah, tell us a little bit about

710
00:38:32,360 --> 00:38:35,520
Speaker 18: what the future looks like for Deep Mind and Gemini Robotics.

711
00:38:35,760 --> 00:38:39,000
Speaker 17: Yeah, so we're really excited about gemin Robotics bringing all

712
00:38:39,040 --> 00:38:41,080
Speaker 17: of that intelligence from Gemini into the physical world, but

713
00:38:41,080 --> 00:38:43,840
Speaker 17: there's still a lot of work to do. Gemini Robotics

714
00:38:43,880 --> 00:38:46,279
Speaker 17: is able to give you that reasoning, it's able to

715
00:38:46,280 --> 00:38:48,920
Speaker 17: give you that interactivity, it's able to give you multimodality,

716
00:38:49,320 --> 00:38:52,080
Speaker 17: but it's not yet able to what we're pushing the

717
00:38:52,080 --> 00:38:55,640
Speaker 17: boundary on is on doing highly dexterous tasks like, for example,

718
00:38:55,960 --> 00:38:59,680
Speaker 17: folding origami or packing a launch box that requires a

719
00:38:59,719 --> 00:39:02,200
Speaker 17: lot of dexterity that humans have and we don't really

720
00:39:02,239 --> 00:39:05,319
Speaker 17: realize it, but it's incredibly important to make robots.

721
00:39:05,080 --> 00:39:07,720
Speaker 18: Useful when it comes to the scalability of the industry

722
00:39:07,719 --> 00:39:13,320
Speaker 18: itself and competing also with dozens of these new companies

723
00:39:13,440 --> 00:39:16,720
Speaker 18: not only in the US, but dozens in China as well,

724
00:39:16,880 --> 00:39:18,520
Speaker 18: and where is the edge?

725
00:39:18,760 --> 00:39:22,160
Speaker 17: So there's a really exciting time right now for robotics

726
00:39:22,239 --> 00:39:25,080
Speaker 17: all over the world. I think that the really hard

727
00:39:25,160 --> 00:39:27,960
Speaker 17: problem that people don't realize is that the edge is

728
00:39:28,040 --> 00:39:33,080
Speaker 17: add understanding the nuance and complexity of the human world. Actually,

729
00:39:33,160 --> 00:39:36,080
Speaker 17: a lot of what you see out there is predefined sequences,

730
00:39:36,200 --> 00:39:40,359
Speaker 17: memorize sequences that the robots are doing. The actual intelligence

731
00:39:40,880 --> 00:39:43,040
Speaker 17: needs to be there in order for robots to operate

732
00:39:43,080 --> 00:39:45,720
Speaker 17: in all of our environments. Our environments are constantly changing,

733
00:39:45,760 --> 00:39:49,520
Speaker 17: there's humans in them, they're unstructured. That is what's needed

734
00:39:49,520 --> 00:39:51,320
Speaker 17: in order to get robots to be really helpful in

735
00:39:51,320 --> 00:39:52,000
Speaker 17: the physical world.

736
00:39:52,480 --> 00:39:54,600
Speaker 2: That was Google Deep Mind Vice president and head of

737
00:39:54,640 --> 00:39:58,000
Speaker 2: Humanoid Robotics, Carolina Parata, along with our own Sherry On

738
00:39:58,280 --> 00:40:03,279
Speaker 2: in Tokyo, a major setback for Jeff Bezos's space ambitions

739
00:40:03,360 --> 00:40:06,760
Speaker 2: after Blue Origins New Glen rocket explodes during a test

740
00:40:06,800 --> 00:40:10,239
Speaker 2: in Florida. Lauren Grush joins us on that next, this

741
00:40:10,360 --> 00:40:22,200
Speaker 2: is Bloomberg. Let's get to Blue Origin, the company's new

742
00:40:22,239 --> 00:40:25,000
Speaker 2: Glen rocket. You see it right there, exploding in a

743
00:40:25,120 --> 00:40:28,719
Speaker 2: massive fireball while undergoing a test on a Florida launchpad.

744
00:40:29,040 --> 00:40:31,279
Speaker 2: Blue Origin, writing in a post on X quote, we

745
00:40:31,400 --> 00:40:34,960
Speaker 2: experienced an anomaly during today's hot fire test. All personnel

746
00:40:35,000 --> 00:40:38,000
Speaker 2: have been accounted for. We will provide updates as we

747
00:40:38,160 --> 00:40:41,759
Speaker 2: learn more. Bloomberg's Lauren Grush joins us now with more.

748
00:40:41,960 --> 00:40:44,560
Speaker 2: The word anomaly can mean a lot of different things. Lauren,

749
00:40:45,239 --> 00:40:47,319
Speaker 2: What do we know about what happened last night?

750
00:40:48,640 --> 00:40:51,279
Speaker 14: Well, I think the details are still trickling, and we

751
00:40:51,320 --> 00:40:53,239
Speaker 14: don't know a whole lot. But we do have some

752
00:40:53,400 --> 00:40:56,799
Speaker 14: very vivid imagery of this event. This is probably one

753
00:40:56,840 --> 00:41:00,680
Speaker 14: of the largest explosions I've ever covered on rocket in

754
00:41:00,760 --> 00:41:04,160
Speaker 14: my time being a reporter. But yes, we still don't

755
00:41:04,160 --> 00:41:05,640
Speaker 14: know a lot. All we know is that they were

756
00:41:05,640 --> 00:41:08,880
Speaker 14: conducting a test. They were preparing for their fourth launch

757
00:41:08,880 --> 00:41:11,360
Speaker 14: of New Glenn, which was supposed to launch a batch

758
00:41:11,480 --> 00:41:16,520
Speaker 14: of Amazon satellites for the Amazon LEO. Fortunately for Amazon,

759
00:41:16,560 --> 00:41:18,920
Speaker 14: those satellites were not on board, and as you mentioned,

760
00:41:18,960 --> 00:41:22,839
Speaker 14: you know, there no personnel were hurt or there were

761
00:41:22,880 --> 00:41:25,400
Speaker 14: no injuries, so that's all good. But this is a

762
00:41:25,440 --> 00:41:28,600
Speaker 14: pretty catastrophic moment for New Glenn for sure.

763
00:41:28,719 --> 00:41:30,040
Speaker 3: Yeah, what about setback?

764
00:41:30,080 --> 00:41:35,440
Speaker 2: I mean in terms of months, years to a mission

765
00:41:35,800 --> 00:41:39,560
Speaker 2: or to at least a goal for New Glen. What

766
00:41:39,600 --> 00:41:40,760
Speaker 2: does it do to the program?

767
00:41:41,320 --> 00:41:45,280
Speaker 14: Sure, you know, in terms of the timeline. Obviously that's subjective.

768
00:41:45,320 --> 00:41:48,440
Speaker 14: It will depend on if they are able to figure

769
00:41:48,480 --> 00:41:52,000
Speaker 14: out the origin of the problem pretty quickly, how fast

770
00:41:52,040 --> 00:41:55,480
Speaker 14: they can you know, fix it. But this is very

771
00:41:55,600 --> 00:41:59,960
Speaker 14: certain to have a very big impact on the schedule

772
00:42:00,120 --> 00:42:02,919
Speaker 14: for Blue Origin moving forward. It's also kind of hard

773
00:42:02,920 --> 00:42:06,480
Speaker 14: to understate just how important nuclein is for everything that

774
00:42:06,480 --> 00:42:09,680
Speaker 14: Blue Origin wants to do. Right It's their main orbital rocket.

775
00:42:09,920 --> 00:42:13,520
Speaker 14: It's supposed to launch future satellites for the company. It's

776
00:42:13,600 --> 00:42:15,600
Speaker 14: you know, as Blue Origin has how did they have

777
00:42:15,680 --> 00:42:19,680
Speaker 14: a ten billion dollars backlog on this vehicle with customer contracts.

778
00:42:20,000 --> 00:42:25,360
Speaker 14: It's a key rocket for launching Blue Origins Lunar Lander,

779
00:42:25,440 --> 00:42:28,279
Speaker 14: which is a key component of NASA's Artemis program to

780
00:42:28,280 --> 00:42:30,799
Speaker 14: send humans back to the Moon, and all of that

781
00:42:30,920 --> 00:42:34,280
Speaker 14: is likely to suffer delays. Also, damage to the launch

782
00:42:34,320 --> 00:42:37,319
Speaker 14: pad will probably take that out of operation for some

783
00:42:37,480 --> 00:42:39,440
Speaker 14: time too, So it's not just the rocket they have

784
00:42:39,520 --> 00:42:43,400
Speaker 14: to fix, it's all the infrastructure that just got exploded

785
00:42:43,440 --> 00:42:44,399
Speaker 14: in the meantime as well.

786
00:42:44,640 --> 00:42:46,520
Speaker 2: Yeah, at the risk of mixing metaphors, I don't want

787
00:42:46,520 --> 00:42:48,680
Speaker 2: to put the car before the horse here, Lauren. But

788
00:42:48,719 --> 00:42:52,680
Speaker 2: if we consider NASA's reliance on Blue Origin for the

789
00:42:52,760 --> 00:42:56,759
Speaker 2: Artemis program, as you just referenced, does NASA plan for

790
00:42:56,800 --> 00:43:00,280
Speaker 2: setbacks like this or would they have to go and say,

791
00:43:00,480 --> 00:43:03,120
Speaker 2: you know, maybe we have to rely on a different partner.

792
00:43:04,080 --> 00:43:07,640
Speaker 14: Certainly, Actually, NASA did kind of work this into their

793
00:43:07,680 --> 00:43:10,480
Speaker 14: decision making because you know, Blue Origin isn't the only

794
00:43:10,520 --> 00:43:15,240
Speaker 14: partner that NASA has obviously when it comes to building

795
00:43:15,239 --> 00:43:18,440
Speaker 14: a lunar lander. It's both Blue Origin and SpaceX that

796
00:43:18,480 --> 00:43:21,239
Speaker 14: are developing landers for the Artemis program. And they do

797
00:43:21,320 --> 00:43:25,200
Speaker 14: that on purpose because of it, because of unforeseen problems

798
00:43:25,200 --> 00:43:27,080
Speaker 14: that might arise like this one. They won't like to

799
00:43:27,120 --> 00:43:30,319
Speaker 14: have different options that they can turn to, and so

800
00:43:30,360 --> 00:43:32,719
Speaker 14: SpaceX is that other option that they can turn to.

801
00:43:33,120 --> 00:43:35,080
Speaker 14: But again, you know, it's still too early to say.

802
00:43:35,320 --> 00:43:39,239
Speaker 14: You know, if they will actually use SpaceX's lander over

803
00:43:39,280 --> 00:43:43,040
Speaker 14: Blue Origin, perhaps they can turn this around more quickly

804
00:43:43,080 --> 00:43:44,600
Speaker 14: than we think, but you know it's going to be

805
00:43:44,680 --> 00:43:45,080
Speaker 14: some time.

806
00:43:45,440 --> 00:43:49,360
Speaker 2: Bloomberg's Lauren Brush joining us with that. Checkout Lauren's reporting

807
00:43:49,440 --> 00:43:51,760
Speaker 2: and the entire Space teams reporting on the Bloomberg Terminal

808
00:43:51,840 --> 00:43:53,640
Speaker 2: and at Bloomberg dot com. That is going to do

809
00:43:53,680 --> 00:43:55,840
Speaker 2: it for this edition of Bloomberg Tech. Don't forget to

810
00:43:55,920 --> 00:43:59,200
Speaker 2: check out our podcast Minded on the Terminal, Apple, Spotify,

811
00:43:59,280 --> 00:44:00,880
Speaker 2: and iHeart this is Bloomberg.

812
00:44:04,719 --> 00:44:04,759
Speaker 6: I