1
00:00:02,520 --> 00:00:13,600
Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is alive

2
00:00:13,640 --> 00:00:17,439
Speaker 1: from coast to coast with Caroline Hyde in New York

3
00:00:17,760 --> 00:00:20,920
Speaker 1: and ed La Loow in San Francisco.

4
00:00:22,640 --> 00:00:25,840
Speaker 2: This is Bloomberg Tech coming up. Apple closes a retail

5
00:00:25,920 --> 00:00:28,400
Speaker 2: store in China for the first time ever. What this

6
00:00:28,520 --> 00:00:32,280
Speaker 2: means for the iPhone maker's plan to revive sales, Plus US.

7
00:00:32,159 --> 00:00:35,600
Speaker 3: And Chinese officials continue talks to extend the tariff truth

8
00:00:35,920 --> 00:00:40,879
Speaker 3: beyond mid August expiring with Tech Export Controls under the microscope, and.

9
00:00:40,840 --> 00:00:44,720
Speaker 2: We discuss SOFI second quarter earnings with the CEO, Anthony Nodo.

10
00:00:44,960 --> 00:00:48,280
Speaker 4: As the stock surges, Apple's.

11
00:00:47,880 --> 00:00:49,720
Speaker 2: Kind of softer down seven ten to one percent, a

12
00:00:49,760 --> 00:00:52,880
Speaker 2: big points drag at the index level, closing a store

13
00:00:52,920 --> 00:00:55,000
Speaker 2: in China which we can get to, and then headlines

14
00:00:55,000 --> 00:00:57,360
Speaker 2: in the last hour from the Wall Street Journal that

15
00:00:57,480 --> 00:01:00,440
Speaker 2: JP Morgan is now the front runner to take over

16
00:01:00,480 --> 00:01:01,800
Speaker 2: that Apple credit card business.

17
00:01:01,800 --> 00:01:03,960
Speaker 3: There's a lot to discuss, there is, and there's a

18
00:01:03,960 --> 00:01:06,759
Speaker 3: person to do it with. Bloomberg's Tom Giles joins us

19
00:01:06,760 --> 00:01:09,320
Speaker 3: now and Tom just first of all, this signal that

20
00:01:09,319 --> 00:01:12,720
Speaker 3: we're getting pulling back from one particular area bricks and

21
00:01:12,720 --> 00:01:13,840
Speaker 3: water in China.

22
00:01:13,959 --> 00:01:15,280
Speaker 5: Is it a big deal for Apple?

23
00:01:17,319 --> 00:01:19,840
Speaker 6: China is a huge deal for Apple.

24
00:01:20,000 --> 00:01:23,120
Speaker 7: Let's put it in perspective this one particular store.

25
00:01:23,959 --> 00:01:25,880
Speaker 4: There's a question mark about this mall.

26
00:01:26,319 --> 00:01:29,640
Speaker 7: You've had other retailers US based retailers like Coach, Hugo

27
00:01:29,680 --> 00:01:32,680
Speaker 7: Boss have gotten out of there. So I'm not sure

28
00:01:32,680 --> 00:01:35,440
Speaker 7: how much to read into those one particular mall. But

29
00:01:35,600 --> 00:01:38,320
Speaker 7: let's dial the lens back and talk about the big

30
00:01:38,360 --> 00:01:42,240
Speaker 7: picture in China. China is a huge market for Apple,

31
00:01:42,560 --> 00:01:45,640
Speaker 7: and they have seen sales declining there for a whole.

32
00:01:45,440 --> 00:01:47,440
Speaker 6: Host of reasons. Most recently.

33
00:01:47,520 --> 00:01:50,040
Speaker 7: You have to look at the domestic economy in China.

34
00:01:50,120 --> 00:01:53,320
Speaker 7: There are deflationary pressures. There are questions about how much

35
00:01:53,360 --> 00:01:57,120
Speaker 7: the tariffs are going to affect that economy. Remember, exports

36
00:01:57,280 --> 00:02:02,080
Speaker 7: are a huge part of China's global economy, so demand there.

37
00:02:02,200 --> 00:02:06,080
Speaker 7: How big is demand for products like Apple's iPhone. That's

38
00:02:06,080 --> 00:02:08,280
Speaker 7: what Apple needs to take into consideration. We're going to

39
00:02:08,360 --> 00:02:10,520
Speaker 7: be hearing from them in the next couple of days

40
00:02:10,520 --> 00:02:12,840
Speaker 7: to see how things are going in China. And don't

41
00:02:12,880 --> 00:02:17,560
Speaker 7: forget there's a lot of competition domestically in China from

42
00:02:17,880 --> 00:02:20,760
Speaker 7: names like Huawei and Opo and Viva We talked about

43
00:02:20,800 --> 00:02:24,440
Speaker 7: them before, but the competition there is real and people

44
00:02:24,520 --> 00:02:27,760
Speaker 7: are looking for alternatives to Apple because of this whole

45
00:02:27,840 --> 00:02:32,080
Speaker 7: all these questions about US China relations and whether and

46
00:02:32,120 --> 00:02:36,200
Speaker 7: how much pressure the government is putting on domestic markets

47
00:02:36,200 --> 00:02:40,200
Speaker 7: to focus on China names and not Apple.

48
00:02:40,360 --> 00:02:42,000
Speaker 4: That sets us up really well for earning.

49
00:02:42,080 --> 00:02:44,560
Speaker 2: So I think analyst consensus is that they will swing

50
00:02:44,680 --> 00:02:47,000
Speaker 2: back to revenue growth on a year on year basis

51
00:02:47,040 --> 00:02:50,320
Speaker 2: in Greater China. So we wait for that. The headline

52
00:02:50,320 --> 00:02:52,160
Speaker 2: this morning is from the Wall Sweet Journal and that

53
00:02:52,280 --> 00:02:55,160
Speaker 2: JP Morgan, in a pack of many, is now the

54
00:02:55,200 --> 00:02:58,480
Speaker 2: front runner to take over the credit card business. Interesting

55
00:02:58,520 --> 00:03:00,840
Speaker 2: in a sense that SERVICESVA is important.

56
00:03:00,919 --> 00:03:02,040
Speaker 4: But what do we need to know?

57
00:03:02,600 --> 00:03:05,760
Speaker 7: Well, remember that this is an important relationship for the banks.

58
00:03:05,800 --> 00:03:09,640
Speaker 7: Goldman tried it with Apple, it fizzled. There are questions

59
00:03:09,639 --> 00:03:13,040
Speaker 7: about Goldman's consumer strategy and whether that was the right

60
00:03:13,480 --> 00:03:16,760
Speaker 7: mix for them. It's a big deal for JP Morgan.

61
00:03:16,760 --> 00:03:20,840
Speaker 7: Gives them opportunity to push financial services products to a

62
00:03:20,919 --> 00:03:24,640
Speaker 7: whole new legions of Apple customers.

63
00:03:24,800 --> 00:03:25,600
Speaker 4: Big deal for them.

64
00:03:25,919 --> 00:03:29,400
Speaker 2: Bloomberg's Senior executive edit for Tech, Tom Giles here in

65
00:03:29,400 --> 00:03:31,400
Speaker 2: San Francisco. Thank you very much, let's stick with that

66
00:03:31,520 --> 00:03:34,680
Speaker 2: China story. US and Chinese officials are in their second

67
00:03:34,760 --> 00:03:37,960
Speaker 2: day of trade talks in Stockholm, this to extend their

68
00:03:38,000 --> 00:03:41,280
Speaker 2: tariff truce beyond an initial ninety day period. Let's get

69
00:03:41,280 --> 00:03:44,520
Speaker 2: over to Stockholm where Blueberg's Oliver Crook is standing by.

70
00:03:44,520 --> 00:03:47,080
Speaker 4: Oliver, what's the latest. Yeah, that's right.

71
00:03:47,200 --> 00:03:48,960
Speaker 8: We're just in the briefing room here where were expecting

72
00:03:49,040 --> 00:03:51,920
Speaker 8: Treasury Secretary Scott Bessett at any moment now in the

73
00:03:51,920 --> 00:03:54,400
Speaker 8: next couple of minutes, Jamison Greer, who have been locked

74
00:03:54,400 --> 00:03:57,520
Speaker 8: in discussions with their Chinese counterparts for the last two days,

75
00:03:57,520 --> 00:04:00,400
Speaker 8: with the Vice Premiere of China five hours yea yesterday,

76
00:04:00,440 --> 00:04:01,920
Speaker 8: about six hours so far today.

77
00:04:01,920 --> 00:04:02,960
Speaker 9: In terms of the trade.

78
00:04:02,680 --> 00:04:05,120
Speaker 8: Negotiations and the ambition, as you say it is, to

79
00:04:05,160 --> 00:04:08,200
Speaker 8: extend that trade truth that currently stands between the United

80
00:04:08,200 --> 00:04:10,760
Speaker 8: States and China. Those teriffs from the US have dropped

81
00:04:10,800 --> 00:04:13,720
Speaker 8: down to thirty percent, twenty percent of those are fentanyl related,

82
00:04:13,800 --> 00:04:16,080
Speaker 8: ten percent of those sort of baseline tariffs, and that's

83
00:04:16,080 --> 00:04:17,920
Speaker 8: down from the one hundred and twenty five percent level

84
00:04:17,960 --> 00:04:19,919
Speaker 8: we reached at the sort of fever pitch of the

85
00:04:19,960 --> 00:04:22,160
Speaker 8: trade war between the two sides. That is set to

86
00:04:23,000 --> 00:04:25,120
Speaker 8: expire on August the twelfth, and that is what they're

87
00:04:25,160 --> 00:04:27,400
Speaker 8: sort of locked in the discussions to try to extend

88
00:04:27,600 --> 00:04:30,040
Speaker 8: over another ninety days. There are plani play of other

89
00:04:30,120 --> 00:04:32,080
Speaker 8: issues at as you cover every single day that they

90
00:04:32,080 --> 00:04:34,040
Speaker 8: have to discuss. The question will be we did they

91
00:04:34,040 --> 00:04:36,159
Speaker 8: make progress on any of those things? Is there enough

92
00:04:36,160 --> 00:04:38,400
Speaker 8: progress to give a kind of timeline on when a

93
00:04:38,440 --> 00:04:42,360
Speaker 8: comprehensive framework could potentially be happening with the Chinese? Could

94
00:04:42,360 --> 00:04:44,760
Speaker 8: there be something of a timeline on the meeting between

95
00:04:44,760 --> 00:04:46,200
Speaker 8: Shiji Ping and Trump. These are going to be all

96
00:04:46,240 --> 00:04:47,960
Speaker 8: of the questions that are going to have for Treasury

97
00:04:47,960 --> 00:04:50,400
Speaker 8: Secretary Scott Besson't and probably a few other questions on

98
00:04:50,440 --> 00:04:53,760
Speaker 8: other issues of trade, the deal with the EU. There's

99
00:04:53,760 --> 00:04:57,120
Speaker 8: still some open questions about steel tariffs, about pharmaceutical tarrafts,

100
00:04:57,120 --> 00:04:59,279
Speaker 8: so great many questions to put to the Treasury Secretary

101
00:04:59,360 --> 00:05:01,040
Speaker 8: when it comes out in the next few minutes.

102
00:05:01,360 --> 00:05:03,880
Speaker 3: There certainly is Oliver just going back to our sweet

103
00:05:03,880 --> 00:05:06,159
Speaker 3: spot of tech that has been a lot been made

104
00:05:06,320 --> 00:05:08,560
Speaker 3: of rare earth metals, whether or not they've actually been

105
00:05:08,600 --> 00:05:12,280
Speaker 3: able to get more swiftly from China into the United States,

106
00:05:12,440 --> 00:05:15,120
Speaker 3: And of course there was that offering that olive branch

107
00:05:15,160 --> 00:05:17,039
Speaker 3: of h twenties going back from Nvidia.

108
00:05:18,480 --> 00:05:20,120
Speaker 8: Yeah, that's right, and that's really kind of the only

109
00:05:20,160 --> 00:05:23,080
Speaker 8: place you've seen a great deal of olive branches extended

110
00:05:23,120 --> 00:05:24,800
Speaker 8: from the US and from China.

111
00:05:24,560 --> 00:05:25,279
Speaker 4: To one another.

112
00:05:25,440 --> 00:05:26,960
Speaker 8: And we should say these are not just sort of

113
00:05:26,960 --> 00:05:29,560
Speaker 8: acts of goodwill. These are two sectors in which each

114
00:05:29,600 --> 00:05:31,920
Speaker 8: side is dependent on the other. Whether it's the Chinese

115
00:05:31,920 --> 00:05:34,240
Speaker 8: who have a stranglehold on those rare earth metals, on

116
00:05:34,279 --> 00:05:36,680
Speaker 8: those magnets, whether it's the United States that has a

117
00:05:36,720 --> 00:05:39,640
Speaker 8: stranglehold on those advanced AI chips. And they've made those concessions,

118
00:05:39,720 --> 00:05:41,719
Speaker 8: but not necessarily out of the goodness of their heart.

119
00:05:41,839 --> 00:05:43,400
Speaker 8: There is going to be a question about whether or

120
00:05:43,440 --> 00:05:45,679
Speaker 8: not those deliveries those rare earth metals have been flowing.

121
00:05:45,680 --> 00:05:46,600
Speaker 4: I'm sure that will be one.

122
00:05:46,480 --> 00:05:50,000
Speaker 8: Of the questions to Treasury Secretary Scott Besson. So we

123
00:05:50,040 --> 00:05:51,919
Speaker 8: will get a little bit more detail on that, Caroline

124
00:05:51,920 --> 00:05:53,640
Speaker 8: in the next couple of minutes. So stay tuned and

125
00:05:53,640 --> 00:05:56,320
Speaker 8: we'll hear from the Treasury Secretary quite soon.

126
00:05:56,520 --> 00:05:58,800
Speaker 3: We'll be coming back to you, Oliver Kruk, thank you

127
00:05:58,880 --> 00:06:01,520
Speaker 3: from dot com. Let's get you bought a context now.

128
00:06:01,600 --> 00:06:03,760
Speaker 3: Michelle Guide is with us. She is the CEO of

129
00:06:03,760 --> 00:06:06,320
Speaker 3: the CROC Institute for Techti Promacy at Purdue. Served as

130
00:06:06,320 --> 00:06:09,400
Speaker 3: Assistant Secretary of State for Global Public Affairs under the

131
00:06:09,400 --> 00:06:12,400
Speaker 3: first Trump administration that was twenty eighteen to twenty twenty,

132
00:06:12,640 --> 00:06:15,720
Speaker 3: and Michelle the context now is one of which US

133
00:06:15,760 --> 00:06:18,640
Speaker 3: and China are setting themselves up for this race, whether

134
00:06:18,680 --> 00:06:20,880
Speaker 3: it be in AI, whether it be in manufacturing, whether

135
00:06:20,880 --> 00:06:23,560
Speaker 3: it be in energy, which is the most important outcomes

136
00:06:23,600 --> 00:06:26,640
Speaker 3: you think in terms of where we take trade going forward, the.

137
00:06:26,640 --> 00:06:30,159
Speaker 10: Most important outcome is going to be American security, prosperity,

138
00:06:30,200 --> 00:06:33,000
Speaker 10: and leadership, and that's what all of these trade negotiations

139
00:06:33,040 --> 00:06:33,400
Speaker 10: are about.

140
00:06:33,440 --> 00:06:34,720
Speaker 11: There are means to that end.

141
00:06:35,120 --> 00:06:39,200
Speaker 10: China has built a massive manufacturing economy, the United States

142
00:06:39,200 --> 00:06:41,320
Speaker 10: has built a massive consumer economy.

143
00:06:41,360 --> 00:06:43,840
Speaker 11: So they make stuff and we consume it and we

144
00:06:43,920 --> 00:06:44,320
Speaker 11: buy it.

145
00:06:44,600 --> 00:06:47,280
Speaker 10: And now, being a consumer at that scale is a

146
00:06:47,320 --> 00:06:51,320
Speaker 10: big vulnerability when your largest supplier is an adversary, and

147
00:06:51,360 --> 00:06:55,080
Speaker 10: we buy and consume three hundred billion dollars more stuff

148
00:06:55,120 --> 00:06:57,000
Speaker 10: from China than they buy from US.

149
00:06:57,320 --> 00:06:58,080
Speaker 11: And that matters.

150
00:06:58,120 --> 00:07:00,440
Speaker 10: When it's not just toys at walm More, and it's

151
00:07:00,480 --> 00:07:01,680
Speaker 10: not just home appliances.

152
00:07:02,120 --> 00:07:04,920
Speaker 11: We are consuming things independent on them for.

153
00:07:04,920 --> 00:07:06,880
Speaker 10: Things that are really important to our national security, as

154
00:07:06,920 --> 00:07:10,040
Speaker 10: you had just mentioned rare earth magnets, it's batteries, it's

155
00:07:10,040 --> 00:07:14,040
Speaker 10: pharmaceutical ingredients, it's the ability to make ships across the

156
00:07:14,080 --> 00:07:16,400
Speaker 10: world that have a commercial and a defense implication. So

157
00:07:17,080 --> 00:07:20,720
Speaker 10: rebalancing our trade relationship is key to making sure that

158
00:07:20,760 --> 00:07:24,520
Speaker 10: we are reincentivizing our ability and making it more attractive

159
00:07:24,560 --> 00:07:26,680
Speaker 10: to buy and to build these things at home than

160
00:07:26,760 --> 00:07:28,200
Speaker 10: to rely on China to.

161
00:07:28,160 --> 00:07:28,800
Speaker 11: Do those things.

162
00:07:29,040 --> 00:07:31,760
Speaker 3: It's interesting we've of course had MPY Materials with an

163
00:07:31,800 --> 00:07:34,640
Speaker 3: announcement that they as one of the only rare rev

164
00:07:34,720 --> 00:07:36,880
Speaker 3: metal miners here in the United States, they're going to

165
00:07:36,880 --> 00:07:40,040
Speaker 3: be supplying apple in some way. But are there enough incentives? Well,

166
00:07:40,080 --> 00:07:42,880
Speaker 3: what is ultimately a very dirty process? Do we want

167
00:07:42,920 --> 00:07:43,600
Speaker 3: to bring that home?

168
00:07:43,640 --> 00:07:47,040
Speaker 10: Michelle more portly, Well, China is either going to do

169
00:07:47,080 --> 00:07:49,760
Speaker 10: it in a very dirty process, because we have seen

170
00:07:49,800 --> 00:07:51,560
Speaker 10: that the Chinese Communist Party does not.

171
00:07:51,600 --> 00:07:53,640
Speaker 11: Have a lot of regard for the environment.

172
00:07:53,480 --> 00:07:56,440
Speaker 10: Or we can incentivize American companies to do it here

173
00:07:56,640 --> 00:07:59,240
Speaker 10: in a much cleaner and more efficient and effective way.

174
00:07:59,280 --> 00:08:01,720
Speaker 11: And so I think have America lead in these things.

175
00:08:02,120 --> 00:08:05,520
Speaker 10: Rare earth processing and other critical minerals is going to

176
00:08:05,520 --> 00:08:08,840
Speaker 10: be really important. We'll do it much cleaner, more effectively, safely,

177
00:08:08,840 --> 00:08:11,320
Speaker 10: and trustworthy than the Chinese Communist Party.

178
00:08:12,400 --> 00:08:14,840
Speaker 4: Michelle, good morning, it's ed in San Francisco.

179
00:08:15,000 --> 00:08:17,680
Speaker 2: I don't want to go broad that meeting that's happening

180
00:08:17,760 --> 00:08:21,920
Speaker 2: right now in Stockholm between Chinese trade officials and American

181
00:08:21,920 --> 00:08:26,120
Speaker 2: trade officials. Who is currently on top in this negotiation.

182
00:08:27,960 --> 00:08:29,880
Speaker 10: Well, I think what we've seen is that everything is

183
00:08:29,920 --> 00:08:31,720
Speaker 10: on the table, and the United States has a lot

184
00:08:31,720 --> 00:08:33,800
Speaker 10: of leverage. As you said, you know, they want a

185
00:08:33,840 --> 00:08:36,200
Speaker 10: lot of things from the United States, including our chips

186
00:08:37,040 --> 00:08:41,199
Speaker 10: and including our consumer economy because they are largely export based, and.

187
00:08:41,160 --> 00:08:43,520
Speaker 11: So we matter to them as much as they matter

188
00:08:43,600 --> 00:08:43,880
Speaker 11: to us.

189
00:08:43,920 --> 00:08:46,520
Speaker 10: And so I think everything's on the table, and ultimately

190
00:08:46,600 --> 00:08:48,400
Speaker 10: here the goal is to walk out with a better

191
00:08:48,440 --> 00:08:51,479
Speaker 10: deal for the United States, so we are more prosperous,

192
00:08:51,520 --> 00:08:54,160
Speaker 10: more free, more secure, and we can incentivize building the

193
00:08:54,200 --> 00:08:57,040
Speaker 10: sectors here that are going to be important to American leadership.

194
00:08:57,120 --> 00:08:59,439
Speaker 10: The President last week just talked about our big AI

195
00:08:59,559 --> 00:09:03,120
Speaker 10: Action plan and wanting to run on American tech, and

196
00:09:03,120 --> 00:09:05,240
Speaker 10: so we need to incentivize the industries that are going

197
00:09:05,320 --> 00:09:06,720
Speaker 10: to make that possible.

198
00:09:06,840 --> 00:09:08,840
Speaker 2: And one of the pillars of that plan is for

199
00:09:08,960 --> 00:09:12,920
Speaker 2: America to export technology to the world. How important an

200
00:09:12,920 --> 00:09:17,199
Speaker 2: export market is China for the American technology stack.

201
00:09:18,200 --> 00:09:20,720
Speaker 10: Well, the jury is still out on whether or not

202
00:09:20,800 --> 00:09:23,160
Speaker 10: China is going to be an economy that wants the

203
00:09:23,200 --> 00:09:26,560
Speaker 10: American technology stack. If you listen to what Hijin Ping

204
00:09:26,640 --> 00:09:30,880
Speaker 10: has said, he wants an independent, controllable AI hardware and

205
00:09:30,920 --> 00:09:32,400
Speaker 10: software foundational system.

206
00:09:32,679 --> 00:09:34,120
Speaker 11: That means a Chinese tech stack.

207
00:09:34,480 --> 00:09:37,360
Speaker 10: And so we'll see whether or not Chi Jianping and

208
00:09:37,400 --> 00:09:40,199
Speaker 10: the Chinese economy wants American tech. It's all the more

209
00:09:40,240 --> 00:09:43,040
Speaker 10: reason that deals with our allies like the EU that

210
00:09:43,160 --> 00:09:47,520
Speaker 10: just happened, like Japan that just happened matter because if

211
00:09:47,559 --> 00:09:49,760
Speaker 10: you look at the US and our top ten democratic

212
00:09:49,800 --> 00:09:53,440
Speaker 10: allies the EU included, that's like sixty to seventy percent

213
00:09:53,559 --> 00:09:56,040
Speaker 10: of global GDP. What a great place to start for

214
00:09:56,120 --> 00:09:59,040
Speaker 10: us to deploy American technology is the backbone of the

215
00:09:59,080 --> 00:10:01,120
Speaker 10: global economy and the free world and then start to

216
00:10:01,160 --> 00:10:01,960
Speaker 10: work out from there.

217
00:10:02,400 --> 00:10:07,240
Speaker 3: Michelle, it's almost the one area of bipartisanship has been

218
00:10:07,480 --> 00:10:10,880
Speaker 3: a hawkish nature towards China. But I think about a

219
00:10:10,920 --> 00:10:12,679
Speaker 3: potential ban on TikTok.

220
00:10:12,440 --> 00:10:13,400
Speaker 5: Currently not happening.

221
00:10:13,640 --> 00:10:17,079
Speaker 3: When we think about a potential meeting between Trump and jijingping,

222
00:10:17,400 --> 00:10:19,680
Speaker 3: some China Hawks, some of the most odd and in

223
00:10:19,760 --> 00:10:23,000
Speaker 3: the current administration for frustrated that actually President Trump is

224
00:10:23,040 --> 00:10:24,880
Speaker 3: giving way too much for a deal.

225
00:10:25,040 --> 00:10:25,920
Speaker 5: What do you make of it?

226
00:10:26,720 --> 00:10:28,959
Speaker 10: Well, I think the big picture is all of these

227
00:10:29,000 --> 00:10:32,560
Speaker 10: things are chips in the bargaining tools. They're all on

228
00:10:32,640 --> 00:10:35,000
Speaker 10: the table and up for negotiation, so we can ultimately

229
00:10:35,040 --> 00:10:37,240
Speaker 10: get to a deal that does make us more secure

230
00:10:37,240 --> 00:10:40,800
Speaker 10: and more prosperous. And so we've seen back and forth

231
00:10:40,840 --> 00:10:43,160
Speaker 10: on TikTok. We know that the Age twenty chips from

232
00:10:43,240 --> 00:10:46,719
Speaker 10: Nvidia were under export controls in April, and then in

233
00:10:46,800 --> 00:10:49,840
Speaker 10: July there were assurances that those licenses would be granted

234
00:10:49,880 --> 00:10:50,559
Speaker 10: to export them.

235
00:10:50,559 --> 00:10:52,160
Speaker 11: But all of these things are in flux.

236
00:10:51,920 --> 00:10:54,280
Speaker 10: And it's part of the high stakes negotiations that are

237
00:10:54,320 --> 00:10:57,120
Speaker 10: taking place. Ultimately that we want to get to a

238
00:10:57,200 --> 00:11:01,360
Speaker 10: place where we are incentivizing American leadership and security first.

239
00:11:01,360 --> 00:11:03,520
Speaker 3: And that takes regulation here at home as well. The

240
00:11:03,559 --> 00:11:07,240
Speaker 3: AI Action Plan meant to foster growth, particularly when it

241
00:11:07,240 --> 00:11:11,080
Speaker 3: comes to the underlying large language models and indeed the infrastructure.

242
00:11:11,320 --> 00:11:13,480
Speaker 3: What's interesting is there is this game of cat and

243
00:11:13,520 --> 00:11:17,080
Speaker 3: mouse and China yet more and more sophisticated models, open

244
00:11:17,120 --> 00:11:20,560
Speaker 3: ones coming to the full. How do you measure how

245
00:11:20,600 --> 00:11:22,920
Speaker 3: far China is in the generative AI race?

246
00:11:24,200 --> 00:11:27,160
Speaker 10: Well, I think it's how many countries and partners across

247
00:11:27,160 --> 00:11:30,000
Speaker 10: the world are adopting Chinese tech versus American tech. And

248
00:11:30,040 --> 00:11:32,720
Speaker 10: our goal is to have more countries and more companies

249
00:11:32,760 --> 00:11:35,840
Speaker 10: adopting American tech and in some cases Allied tech if

250
00:11:35,920 --> 00:11:39,000
Speaker 10: we're not the category leader, so that the tech stack

251
00:11:39,040 --> 00:11:41,880
Speaker 10: across the world is trusted. And so having a scorecard

252
00:11:42,559 --> 00:11:45,080
Speaker 10: where we track how many companies and countries are adopting

253
00:11:45,160 --> 00:11:48,800
Speaker 10: US and Allied technology versus Chinese technology is really important.

254
00:11:49,000 --> 00:11:50,800
Speaker 10: And I think, as the President laid out in his

255
00:11:50,880 --> 00:11:53,840
Speaker 10: AI Action Plan, what the administration is going to start

256
00:11:53,880 --> 00:11:57,520
Speaker 10: to do is put together exportable AI packages to start

257
00:11:57,559 --> 00:11:59,240
Speaker 10: to facilitate that more effectively.

258
00:12:00,559 --> 00:12:03,800
Speaker 2: Michelle Geider of the CROC Institute of Tech Diplomacy at Purdue,

259
00:12:03,800 --> 00:12:07,080
Speaker 2: thank you very much. Now, coming up, Spotify shares drop

260
00:12:07,120 --> 00:12:10,440
Speaker 2: as the music streaming company disappoints investors with a surprise

261
00:12:10,480 --> 00:12:11,360
Speaker 2: second quarter loss.

262
00:12:11,360 --> 00:12:13,840
Speaker 4: We'll have the details next. This is Bloomberg Tech.

263
00:12:21,640 --> 00:12:25,880
Speaker 3: Spotify shares having their worst day in two years, as

264
00:12:25,880 --> 00:12:28,840
Speaker 3: the company reported a loss in the second quarter. Let's

265
00:12:28,880 --> 00:12:31,599
Speaker 3: get more of Spotify's earnings or Bloomberg's Ashley Carmen, the

266
00:12:31,679 --> 00:12:34,480
Speaker 3: scene seems to be about employee pay in some ways

267
00:12:34,480 --> 00:12:35,400
Speaker 3: and taxes upon that.

268
00:12:36,160 --> 00:12:37,960
Speaker 12: Yeah, in some ways, Spotify is a victim of its

269
00:12:38,000 --> 00:12:41,080
Speaker 12: own success. They've basically said that because they've been doing

270
00:12:41,080 --> 00:12:43,160
Speaker 12: so well on the stock market, they've had to pay

271
00:12:43,200 --> 00:12:43,559
Speaker 12: out a.

272
00:12:43,520 --> 00:12:45,439
Speaker 5: Lot more than they anticipated.

273
00:12:44,800 --> 00:12:47,800
Speaker 12: To employees for payroll, taxes and whatnot, and so that

274
00:12:47,880 --> 00:12:49,720
Speaker 12: ended up in a loss in earnings per share.

275
00:12:50,520 --> 00:12:53,840
Speaker 2: There's a lot of like earnings mechanics and financial wizardry

276
00:12:53,840 --> 00:12:55,400
Speaker 2: around this kind of stuff. Is there a kind of

277
00:12:55,480 --> 00:12:59,640
Speaker 2: core Spotify story actually of how streaming audio is going

278
00:12:59,679 --> 00:13:01,880
Speaker 2: for them, and maybe a little bit about their video

279
00:13:01,920 --> 00:13:02,840
Speaker 2: strategy as well.

280
00:13:03,559 --> 00:13:07,920
Speaker 12: Yeah, So Spotify keeps adding subscribers users like they keep.

281
00:13:07,760 --> 00:13:10,079
Speaker 5: Growing every single quarter. It's pretty remarkable.

282
00:13:10,480 --> 00:13:12,400
Speaker 12: But what's sort of been a challenge for them is

283
00:13:12,440 --> 00:13:14,080
Speaker 12: figuring out what their next verticals are.

284
00:13:13,920 --> 00:13:15,200
Speaker 5: And seeing that through successfully.

285
00:13:15,240 --> 00:13:18,040
Speaker 12: So they've really made a push for advertising that hasn't

286
00:13:18,040 --> 00:13:20,720
Speaker 12: really panned out. They said now they are going to

287
00:13:20,760 --> 00:13:22,679
Speaker 12: be kind of rethinking.

288
00:13:22,240 --> 00:13:23,760
Speaker 5: That approach with advertising.

289
00:13:24,120 --> 00:13:28,120
Speaker 12: Their head of advertising actually stepped down yesterday. He's taking

290
00:13:28,160 --> 00:13:30,680
Speaker 12: a job at DoorDash, So they sort of suggested that

291
00:13:30,720 --> 00:13:32,160
Speaker 12: this is going to be a direction that they're going

292
00:13:32,200 --> 00:13:34,840
Speaker 12: to change course. And then they're making a very concentrated

293
00:13:34,840 --> 00:13:37,800
Speaker 12: push into video, and on today's earnings call, they said

294
00:13:37,880 --> 00:13:39,600
Speaker 12: one of their co praresidents said that.

295
00:13:39,480 --> 00:13:42,280
Speaker 5: This is a very exciting opportunity, but it's not a

296
00:13:42,400 --> 00:13:43,560
Speaker 5: necessary opportunity.

297
00:13:43,600 --> 00:13:45,120
Speaker 12: So I think they're still kind of figuring out where

298
00:13:45,120 --> 00:13:46,040
Speaker 12: they want to move next.

299
00:13:46,440 --> 00:13:48,920
Speaker 3: It's interesting that the week dollar, of course, plays into

300
00:13:48,920 --> 00:13:50,960
Speaker 3: all of this, and the third quarter to forecasts not

301
00:13:50,960 --> 00:13:55,000
Speaker 3: looking that pretty either. Ultimately, they are building more and

302
00:13:55,040 --> 00:13:57,000
Speaker 3: more users. As they say, it's sort of growing like

303
00:13:57,080 --> 00:13:59,199
Speaker 3: a weed, so that's going to be a positive momentum

304
00:13:59,280 --> 00:14:00,800
Speaker 3: story for many longer term.

305
00:14:00,880 --> 00:14:02,800
Speaker 12: Yeah, I think that that's how they're trying to position

306
00:14:02,920 --> 00:14:05,400
Speaker 12: this is that in the long term they seem very bullish,

307
00:14:05,480 --> 00:14:07,880
Speaker 12: they're excited, they feel like they've had a really great product.

308
00:14:08,040 --> 00:14:08,720
Speaker 5: It's just these.

309
00:14:08,559 --> 00:14:12,040
Speaker 12: Short term issues that they're kind of dealing with, and investors,

310
00:14:12,200 --> 00:14:13,760
Speaker 12: we'll see how they're feeling about it.

311
00:14:14,440 --> 00:14:16,839
Speaker 2: The stock's down almost eleven percent, which introday is the

312
00:14:16,880 --> 00:14:19,280
Speaker 2: biggest drop since early April, but if it closed, there

313
00:14:19,400 --> 00:14:21,440
Speaker 2: be the biggest drop since June of twenty twenty three,

314
00:14:21,600 --> 00:14:22,040
Speaker 2: So it's.

315
00:14:21,880 --> 00:14:22,720
Speaker 4: A strong reaction.

316
00:14:23,200 --> 00:14:24,840
Speaker 2: I'm not asking you something to ask you every single

317
00:14:24,880 --> 00:14:28,000
Speaker 2: quarter because this is how I listen to podcasts. How

318
00:14:28,040 --> 00:14:29,720
Speaker 2: is Spotify doing in podcasts?

319
00:14:30,480 --> 00:14:33,760
Speaker 12: They've really pivoted into video podcasts and they've been trying

320
00:14:33,760 --> 00:14:36,800
Speaker 12: to recruit more video creators to the platform, so they

321
00:14:36,800 --> 00:14:40,080
Speaker 12: really have not focused on these audio podcasts anymore. I've

322
00:14:40,120 --> 00:14:42,840
Speaker 12: reported quite a bit on how this initiative is going

323
00:14:42,880 --> 00:14:44,720
Speaker 12: for them. They're still missing quite a few of the

324
00:14:44,800 --> 00:14:46,720
Speaker 12: largest podcasters on that service.

325
00:14:46,440 --> 00:14:48,880
Speaker 5: For video, but they're still pushing and they're still trying.

326
00:14:49,840 --> 00:14:53,320
Speaker 3: Where is the audience for them? Always the growth story

327
00:14:53,360 --> 00:14:54,480
Speaker 3: at least it seems like.

328
00:14:54,440 --> 00:14:57,520
Speaker 12: It's developing markets, Yeah, but then also just trying to

329
00:14:57,560 --> 00:14:59,560
Speaker 12: get people to spend more time on the platform watch

330
00:14:59,600 --> 00:15:01,720
Speaker 12: these video which they compensate based.

331
00:15:01,560 --> 00:15:03,040
Speaker 5: That consumption rather than adds.

332
00:15:03,200 --> 00:15:05,400
Speaker 12: They're really trying to appeal spend more time through audiobooks

333
00:15:05,440 --> 00:15:08,040
Speaker 12: and maybe up level them to different tiers of subscriptions.

334
00:15:08,240 --> 00:15:10,320
Speaker 12: So I think that's where they're eyeing some possible growth.

335
00:15:11,440 --> 00:15:14,720
Speaker 2: Bluemogs actually Carmen on the streaming and Spotify beat. Thank

336
00:15:14,760 --> 00:15:17,200
Speaker 2: you very much. We have another earning story in PayPal.

337
00:15:17,520 --> 00:15:19,920
Speaker 2: Look at shares of the company down significantly, on track

338
00:15:19,920 --> 00:15:22,760
Speaker 2: for their biggest drop in almost six months. In part,

339
00:15:22,840 --> 00:15:25,320
Speaker 2: it's just the basics that they're seeing slow in growth

340
00:15:25,320 --> 00:15:28,600
Speaker 2: and payment volumes. But what happened in the morning session

341
00:15:28,760 --> 00:15:31,600
Speaker 2: was that the CEO on the call was talking about

342
00:15:31,680 --> 00:15:37,880
Speaker 2: US retail spending and sort of softening economic consumer data.

343
00:15:37,680 --> 00:15:38,120
Speaker 4: That kind thing.

344
00:15:38,160 --> 00:15:39,640
Speaker 2: But he was basically saying that they see a slight

345
00:15:39,960 --> 00:15:42,680
Speaker 2: acceleration and that's kind of worried people a little bit.

346
00:15:42,680 --> 00:15:44,240
Speaker 2: It's going to be interesting later in the hour Carrier

347
00:15:44,280 --> 00:15:47,640
Speaker 2: when we have Sofi, because it's somewhat analogous, right that

348
00:15:47,720 --> 00:15:50,120
Speaker 2: we might get a similar or maybe different read on

349
00:15:50,160 --> 00:15:52,560
Speaker 2: the strength of the consumer through the fintech lens.

350
00:15:52,880 --> 00:15:55,240
Speaker 3: From a share performance is a very different story for

351
00:15:55,280 --> 00:15:58,080
Speaker 3: so Far, which is up a whopping thirteen percent right now.

352
00:15:58,520 --> 00:16:01,080
Speaker 3: That interview to come at right here, right now. Coming up,

353
00:16:01,120 --> 00:16:04,720
Speaker 3: we've got open Ai back startup Ambient's healthcare. It was

354
00:16:04,760 --> 00:16:07,160
Speaker 3: reaching a one billion dollars valuation. We speak the co

355
00:16:07,240 --> 00:16:08,440
Speaker 3: founder Nik Kilberduma.

356
00:16:08,640 --> 00:16:10,120
Speaker 4: That's an expertive roombed tech.

357
00:16:21,280 --> 00:16:24,560
Speaker 2: Open AI back startup Ambience Healthcare has announced it's raised

358
00:16:24,560 --> 00:16:26,720
Speaker 2: two hundred and forty three million dollars in a new

359
00:16:26,760 --> 00:16:30,320
Speaker 2: funding round, valuing the administrative AI company at more than

360
00:16:30,360 --> 00:16:31,440
Speaker 2: one billion dollars.

361
00:16:31,480 --> 00:16:31,840
Speaker 4: For more.

362
00:16:32,000 --> 00:16:35,640
Speaker 2: Nik Kilberduma, Ambience Healthcare co founder and chief scientists, joins

363
00:16:35,680 --> 00:16:38,920
Speaker 2: us it's really interesting, you know, I actually go back

364
00:16:39,000 --> 00:16:41,200
Speaker 2: to maybe even three years, and this is where a

365
00:16:41,240 --> 00:16:43,160
Speaker 2: lot of people said the promise in the near term

366
00:16:43,400 --> 00:16:47,400
Speaker 2: was AI and healthcare, you know, the administrative task.

367
00:16:47,680 --> 00:16:48,840
Speaker 4: But the round is big.

368
00:16:48,960 --> 00:16:50,520
Speaker 2: I mean, what do you need two hundred and forty

369
00:16:50,520 --> 00:16:51,600
Speaker 2: three million dollars to do?

370
00:16:51,920 --> 00:16:52,160
Speaker 4: Yeah.

371
00:16:52,280 --> 00:16:55,520
Speaker 13: I think this round two hundred forty three million dollars

372
00:16:55,600 --> 00:16:57,840
Speaker 13: values as the company at one point twenty five billion dollars.

373
00:16:57,880 --> 00:17:00,440
Speaker 13: Now that round is led by oak HCFT and recent

374
00:17:00,480 --> 00:17:03,480
Speaker 13: Horoitz and with participation from open AI. I think it's

375
00:17:03,520 --> 00:17:06,080
Speaker 13: a testament to this platform that we've built for health systems,

376
00:17:06,080 --> 00:17:09,719
Speaker 13: which liberates clinicians from the administrative burden and enables them

377
00:17:09,720 --> 00:17:12,000
Speaker 13: to focus on their patient. And a big part of

378
00:17:12,000 --> 00:17:14,359
Speaker 13: it is we've built the sort of busting class platform,

379
00:17:14,400 --> 00:17:17,000
Speaker 13: which in practice what it does is before the patient

380
00:17:17,040 --> 00:17:20,000
Speaker 13: walks into the room. The system actually summarizes all the

381
00:17:20,040 --> 00:17:22,040
Speaker 13: context for the clinicians so they know what's going on

382
00:17:22,119 --> 00:17:24,760
Speaker 13: with that particular patient in the visit. It's listening in

383
00:17:24,800 --> 00:17:28,360
Speaker 13: the background, it's generating the documentation automatically for the clinician

384
00:17:28,400 --> 00:17:30,720
Speaker 13: on behalf of them, as also summary for the patient

385
00:17:30,720 --> 00:17:33,359
Speaker 13: and their families. And then afterwards it's automating all the

386
00:17:33,400 --> 00:17:38,159
Speaker 13: downstream sort of revenue cycle, coding and billing prior authorization workflows,

387
00:17:38,280 --> 00:17:41,160
Speaker 13: which is how health systems get paid. I think it's

388
00:17:41,200 --> 00:17:43,879
Speaker 13: allowing us to essentially work with many more institutions. We

389
00:17:43,920 --> 00:17:46,960
Speaker 13: work with some of the largest healthcare organizations, academic medical

390
00:17:47,000 --> 00:17:50,639
Speaker 13: centers in the country Cleveland Clinic, UCSF, Houston Methodists.

391
00:17:50,640 --> 00:17:52,200
Speaker 4: I think this surround is a testament to that way.

392
00:17:52,800 --> 00:17:55,840
Speaker 2: What's the company's core competence? You know, I understand the platform,

393
00:17:55,840 --> 00:17:57,560
Speaker 2: but what is it that you're good at that's allowed

394
00:17:57,560 --> 00:17:58,679
Speaker 2: you to build the platform.

395
00:17:58,760 --> 00:18:01,320
Speaker 13: I think a big part of it is we've built

396
00:18:01,320 --> 00:18:04,120
Speaker 13: an incredibly deep working relationship with open AI and other

397
00:18:04,160 --> 00:18:07,080
Speaker 13: foundation model makers to build the most capable foundation models

398
00:18:07,080 --> 00:18:09,600
Speaker 13: for healthcare and medicine, and then we've taken that and

399
00:18:09,680 --> 00:18:12,600
Speaker 13: packaged that into a series of workflows to help clinicians.

400
00:18:12,600 --> 00:18:15,080
Speaker 13: So I'll give you one example. We work with Cleveland Clinic,

401
00:18:15,119 --> 00:18:18,560
Speaker 13: one of the most sub specialized academic institutions in the country.

402
00:18:18,840 --> 00:18:22,119
Speaker 13: They have one hundred plus different specialty and sub specialty areas,

403
00:18:22,119 --> 00:18:24,720
Speaker 13: and you could imagine every single one of those specialists

404
00:18:24,720 --> 00:18:29,159
Speaker 13: practices different medicine, they have different workflows, there's different administrative rules,

405
00:18:29,359 --> 00:18:31,000
Speaker 13: and so what we've been able to do is create

406
00:18:31,040 --> 00:18:33,720
Speaker 13: a platform that services the needs of every single one

407
00:18:33,720 --> 00:18:37,560
Speaker 13: of those specialists. Over eighty percent of clinicians of Cleveland

408
00:18:37,560 --> 00:18:40,879
Speaker 13: Clinic use the technology in clinic every single day for

409
00:18:40,960 --> 00:18:43,400
Speaker 13: over seventy percent of those visits, and that's more than

410
00:18:43,400 --> 00:18:45,440
Speaker 13: two to three times some of the other alternatives in

411
00:18:45,480 --> 00:18:45,879
Speaker 13: the market.

412
00:18:46,119 --> 00:18:48,920
Speaker 3: Nikill go to that relationship, that working relationship that you

413
00:18:48,960 --> 00:18:51,080
Speaker 3: want to invest in further with open AI. What makes

414
00:18:51,080 --> 00:18:54,160
Speaker 3: your business defensible versus open AI just sort of building

415
00:18:54,200 --> 00:18:54,800
Speaker 3: it themselves.

416
00:18:55,920 --> 00:18:57,879
Speaker 13: I think a big part of it is as you

417
00:18:57,880 --> 00:19:00,479
Speaker 13: think about sort of the gap between general purpose reasoning

418
00:19:00,480 --> 00:19:02,480
Speaker 13: models and models that are actually a clinical grade and

419
00:19:02,560 --> 00:19:06,320
Speaker 13: compliance grade. There's a massive gap between models that truly

420
00:19:06,440 --> 00:19:08,720
Speaker 13: understand the medicine that's happening in every single visit.

421
00:19:08,760 --> 00:19:10,440
Speaker 4: We talked about Cleveland Clinic.

422
00:19:10,160 --> 00:19:13,160
Speaker 13: And other academic medical centers. Just the level of depth

423
00:19:13,200 --> 00:19:16,960
Speaker 13: and clinical reasoning that's happening across one hundred plus different specialties,

424
00:19:17,160 --> 00:19:19,720
Speaker 13: and how that's different from primary care to if you

425
00:19:19,760 --> 00:19:22,399
Speaker 13: have to go see an oncologist to even an oncological

426
00:19:22,480 --> 00:19:25,440
Speaker 13: subspecialist who might specialize in a particular type of cancer.

427
00:19:25,720 --> 00:19:28,000
Speaker 13: And it's bridging that gap in sort of the understanding

428
00:19:28,040 --> 00:19:31,239
Speaker 13: and reasoning capabilities of these models that ultimately allows us

429
00:19:31,240 --> 00:19:34,360
Speaker 13: to build software that really solves the problem for clinicians

430
00:19:34,400 --> 00:19:35,080
Speaker 13: on the front lines.

431
00:19:35,400 --> 00:19:38,080
Speaker 3: We are currently as we speak, just also seeing live

432
00:19:38,119 --> 00:19:41,400
Speaker 3: pictures of President Trump, who is currently in Scotland. He's opened,

433
00:19:41,440 --> 00:19:43,239
Speaker 3: of course, a new golf course, but he's also been

434
00:19:43,280 --> 00:19:47,560
Speaker 3: negotiating with EU, continues to be discussing relationships with the

435
00:19:47,640 --> 00:19:50,359
Speaker 3: UK going forward. We're going to be diving into that

436
00:19:50,720 --> 00:19:53,960
Speaker 3: as and where necessary for you. But let's just return

437
00:19:53,960 --> 00:19:56,119
Speaker 3: to you, Nikhil, as we hear, of course what President

438
00:19:56,119 --> 00:19:58,280
Speaker 3: Trump has been doing. I want to go to the

439
00:19:58,280 --> 00:20:02,119
Speaker 3: regulatory perspective here for your business at ambience, because I

440
00:20:02,200 --> 00:20:06,920
Speaker 3: am thinking immediately about healthcare requirements. When it comes to privacy.

441
00:20:07,080 --> 00:20:09,040
Speaker 3: How have you made sure that that's front and center

442
00:20:09,400 --> 00:20:13,240
Speaker 3: when you're relying on so many different users who well,

443
00:20:13,320 --> 00:20:14,960
Speaker 3: each hospital has a different rule case.

444
00:20:15,000 --> 00:20:17,600
Speaker 4: I'm sure it's a great question.

445
00:20:17,680 --> 00:20:20,119
Speaker 13: I think the idea of how do we build AI

446
00:20:20,200 --> 00:20:22,480
Speaker 13: that's safe, how do we do it responsibly, how do

447
00:20:22,480 --> 00:20:24,920
Speaker 13: we roll it out in a way that's effective. We're

448
00:20:25,000 --> 00:20:27,600
Speaker 13: lucky to work with some of the premier academic institutions

449
00:20:27,600 --> 00:20:29,800
Speaker 13: in the country, and that's allowed us to build infrastructure

450
00:20:29,880 --> 00:20:32,640
Speaker 13: not only to create and train AI in a safe

451
00:20:32,640 --> 00:20:35,640
Speaker 13: and private way, but also the governance processes to roll

452
00:20:35,640 --> 00:20:38,840
Speaker 13: it out responsibly. But I think the opportunity getting this

453
00:20:38,960 --> 00:20:41,280
Speaker 13: right is actually massive. You think about the ten thousand

454
00:20:41,359 --> 00:20:44,200
Speaker 13: seniors aging into Medicare every single day, the fact that

455
00:20:44,320 --> 00:20:46,919
Speaker 13: in every sort of virtual virtually every category of our

456
00:20:46,960 --> 00:20:49,320
Speaker 13: healthcare workforce, we are projecting the shortage of one hundred

457
00:20:49,359 --> 00:20:51,840
Speaker 13: plus thousand people over the next five to ten years,

458
00:20:51,960 --> 00:20:55,200
Speaker 13: and we as a country spend one trillion on administrative waste.

459
00:20:55,280 --> 00:20:58,200
Speaker 13: The opportunity to leverage AI to sort of help rehaul

460
00:20:58,240 --> 00:21:02,040
Speaker 13: how the system works, have better tools for our clinicians,

461
00:21:02,440 --> 00:21:04,760
Speaker 13: and actually take better care of our patients is pretty exciting.

462
00:21:05,400 --> 00:21:09,240
Speaker 3: Nikail Baduma of Ambience Healthcare.

463
00:21:13,640 --> 00:21:15,240
Speaker 5: Let's just shift gears into.

464
00:21:15,040 --> 00:21:17,639
Speaker 3: The other of AI and the relationship between Microsoft and

465
00:21:17,680 --> 00:21:20,960
Speaker 3: open Ai, because apparently when they're in advanced negotiations that

466
00:21:21,000 --> 00:21:25,000
Speaker 3: could change that relationship and actually help inaugurate the AI age.

467
00:21:25,359 --> 00:21:28,520
Speaker 3: The ongoing talks would give Microsoft access to open AI's

468
00:21:28,600 --> 00:21:32,160
Speaker 3: tech even after the chatchipte maker has reached its goal

469
00:21:32,359 --> 00:21:35,840
Speaker 3: of building artificial general intelligence. For more on what is

470
00:21:35,840 --> 00:21:38,440
Speaker 3: going on spring Bloomberg's Map Day. Now, this is an

471
00:21:38,480 --> 00:21:42,440
Speaker 3: age old relationship. It was the What bore really chatchipt

472
00:21:42,640 --> 00:21:44,960
Speaker 3: to the fold was the financial backing of open ai.

473
00:21:45,359 --> 00:21:47,680
Speaker 3: But the deal was always that they would have limited

474
00:21:47,720 --> 00:21:51,200
Speaker 3: access to tech if open Ai did reach AGI.

475
00:21:51,600 --> 00:21:53,040
Speaker 5: How is this going to change? Map?

476
00:21:53,800 --> 00:21:54,159
Speaker 9: That's right.

477
00:21:54,200 --> 00:21:56,119
Speaker 14: So Microsoft, as a condition of all the investment they

478
00:21:56,160 --> 00:21:58,960
Speaker 14: poured into open ai, they have access to their technology.

479
00:21:58,960 --> 00:22:00,240
Speaker 9: They can make it into their product.

480
00:22:00,480 --> 00:22:03,359
Speaker 14: They're worried for some time about a potential cliff, you know,

481
00:22:03,400 --> 00:22:05,720
Speaker 14: should open Ai say hey, we've you know, built an

482
00:22:05,760 --> 00:22:08,600
Speaker 14: artificially general intelligence system, Microsoft.

483
00:22:08,160 --> 00:22:09,400
Speaker 9: Would lose access to the tech.

484
00:22:09,800 --> 00:22:12,000
Speaker 14: So what we're hearing recently is that Microsoft is getting

485
00:22:12,000 --> 00:22:14,399
Speaker 14: more comfortable at the terms they're talking about now, I

486
00:22:14,400 --> 00:22:16,199
Speaker 14: mean that cliff might not occur, there might be a

487
00:22:16,200 --> 00:22:17,760
Speaker 14: way that they can continue to have access to some

488
00:22:17,840 --> 00:22:22,080
Speaker 14: of open AI's technology, you know, should they hit that milestone.

489
00:22:21,960 --> 00:22:24,720
Speaker 2: Matt, We've heard that talks of progressing, that they're positive

490
00:22:24,720 --> 00:22:27,320
Speaker 2: that they're still ongoing. We heard from sources that in

491
00:22:27,359 --> 00:22:30,520
Speaker 2: some valley, Sam Altman actually met with Sati Nadella to

492
00:22:30,560 --> 00:22:33,080
Speaker 2: talk about the issue. The part of it that is

493
00:22:33,080 --> 00:22:35,480
Speaker 2: on the open Ai side of this is that they

494
00:22:35,560 --> 00:22:38,359
Speaker 2: want to change that corporate structure. What do we know

495
00:22:38,400 --> 00:22:41,159
Speaker 2: about how these negotiations are moving toward that.

496
00:22:42,480 --> 00:22:44,399
Speaker 14: So we know that first of all, Microsoft is is

497
00:22:44,440 --> 00:22:47,800
Speaker 14: the biggest holdout to that re negotiation of open ai structure.

498
00:22:48,400 --> 00:22:50,840
Speaker 14: We know that open ai wants to alter it's it's

499
00:22:50,880 --> 00:22:53,200
Speaker 14: corporate charter. They want more flexibility, they want the ability

500
00:22:53,200 --> 00:22:55,000
Speaker 14: to raise a whole lot more money. And that's really

501
00:22:55,080 --> 00:22:57,640
Speaker 14: what's kind of ticking the clock here, particularly a bunch

502
00:22:57,680 --> 00:23:01,880
Speaker 14: of cash from SoftBank, the big investor, has the authority

503
00:23:01,920 --> 00:23:04,520
Speaker 14: to dial down some of that investment if opening Ey doesn't.

504
00:23:04,280 --> 00:23:05,880
Speaker 9: Complete the restructure before at the end of the year.

505
00:23:05,920 --> 00:23:07,600
Speaker 14: So it's just created this little bit of ticking clock

506
00:23:07,600 --> 00:23:09,880
Speaker 14: in the background, putting pressure on both sides to come.

507
00:23:09,880 --> 00:23:13,359
Speaker 3: Up with a deal and also revenue share. Right, Matt,

508
00:23:13,400 --> 00:23:16,479
Speaker 3: it feels as though open ai is realizing, well, how

509
00:23:16,560 --> 00:23:18,399
Speaker 3: much value they're adding and what's a little bit more

510
00:23:18,400 --> 00:23:18,680
Speaker 3: of it?

511
00:23:19,600 --> 00:23:20,000
Speaker 9: That's right.

512
00:23:20,000 --> 00:23:21,360
Speaker 14: I mean, if you want back the clock to twenty

513
00:23:21,440 --> 00:23:24,360
Speaker 14: nineteen when Microsoft first put cash in the open AI,

514
00:23:25,000 --> 00:23:27,359
Speaker 14: Microsoft got a really good deal on kind of a

515
00:23:27,359 --> 00:23:29,159
Speaker 14: flyer at this AI lab was going to be a

516
00:23:29,160 --> 00:23:31,439
Speaker 14: big deal. Roll the clock forward. Turns out there an

517
00:23:31,520 --> 00:23:34,119
Speaker 14: enormous deal and opening iye wants a bit more of

518
00:23:34,160 --> 00:23:34,880
Speaker 14: that pie for sure.

519
00:23:35,880 --> 00:23:38,280
Speaker 2: Bloomberg's Matt Day reporting with the rest of the AI

520
00:23:38,320 --> 00:23:40,720
Speaker 2: and infrastructure team really appreciate it, Thank you very much.

521
00:23:40,920 --> 00:23:44,359
Speaker 2: Just stick with Microsoft, which reports earnings tomorrow. Cashranging Global

522
00:23:44,400 --> 00:23:47,919
Speaker 2: Investment Research Managing Director the Goldman Sachs joins us. He

523
00:23:47,960 --> 00:23:50,840
Speaker 2: covers the software sector has a buy rating and a

524
00:23:50,880 --> 00:23:54,520
Speaker 2: five hundred and fifty dollars price target for Microsoft TV

525
00:23:54,680 --> 00:23:58,159
Speaker 2: time cash. But you heard the reporting there. When you

526
00:23:58,400 --> 00:24:02,320
Speaker 2: are covering Microsoft, one assumes you have to model in

527
00:24:02,359 --> 00:24:06,320
Speaker 2: this relationship with open AI, both the financial exposure but

528
00:24:06,440 --> 00:24:08,160
Speaker 2: the technology exposure as well.

529
00:24:08,680 --> 00:24:10,360
Speaker 4: What did you hear then and what do you make

530
00:24:10,359 --> 00:24:10,680
Speaker 4: of it?

531
00:24:10,760 --> 00:24:10,960
Speaker 9: Yeah?

532
00:24:11,320 --> 00:24:13,960
Speaker 15: So, first of all, congratulations on breaking that news story.

533
00:24:14,040 --> 00:24:17,720
Speaker 15: So that's incremental development. And we actually publish our note

534
00:24:18,119 --> 00:24:22,080
Speaker 15: later yesterday and we didn't cover the detailed reporting that

535
00:24:22,119 --> 00:24:24,679
Speaker 15: you guys did, so that certainly is a wrinkle, but

536
00:24:24,720 --> 00:24:26,879
Speaker 15: it does not change the overall thesis. Our view has

537
00:24:26,920 --> 00:24:30,800
Speaker 15: been that the partnership has more legs to it than

538
00:24:31,000 --> 00:24:33,760
Speaker 15: commonly believed in the media and in the Wall Street community.

539
00:24:34,080 --> 00:24:36,760
Speaker 15: There's a lot more to be gained on either side

540
00:24:36,840 --> 00:24:40,639
Speaker 15: of the fence beat access to technology from Microsoft's perspective,

541
00:24:40,840 --> 00:24:44,280
Speaker 15: or access to distribution and a work class customer base

542
00:24:44,320 --> 00:24:47,879
Speaker 15: at Microsoft brings and the ability to certainly not to

543
00:24:47,920 --> 00:24:51,240
Speaker 15: overemphasize the very common thing to train models.

544
00:24:50,920 --> 00:24:52,240
Speaker 9: And run on work cus infrastructure.

545
00:24:52,320 --> 00:24:56,360
Speaker 15: So I think if this word of progress to its

546
00:24:56,640 --> 00:24:58,960
Speaker 15: ultimate fruition that of the deal word we signed, it

547
00:24:59,000 --> 00:25:02,440
Speaker 15: would take away a at least an investor's perspective as

548
00:25:02,440 --> 00:25:04,480
Speaker 15: to what is the time duration that you can bank

549
00:25:04,520 --> 00:25:07,800
Speaker 15: and your model and what is the longevity of this partnership.

550
00:25:07,800 --> 00:25:10,240
Speaker 15: Because the AI revenues have come out of nowhere seemingly,

551
00:25:10,480 --> 00:25:14,760
Speaker 15: and I've scaled and helped Microsoft's Azzure business propel itself

552
00:25:14,760 --> 00:25:16,800
Speaker 15: to a not to thirty percent growth through which we

553
00:25:16,840 --> 00:25:19,840
Speaker 15: thought was unthinkable two years ago. So both parties have

554
00:25:20,080 --> 00:25:22,719
Speaker 15: so much to be gained to gain from this, and

555
00:25:22,760 --> 00:25:23,600
Speaker 15: I think it's incrementally.

556
00:25:23,880 --> 00:25:26,480
Speaker 2: Let me ask it this way, what has the biggest

557
00:25:26,520 --> 00:25:30,720
Speaker 2: net benefit to Microsoft been from the relationship with open Ai.

558
00:25:30,920 --> 00:25:34,479
Speaker 15: Yeah, many things. First of all, that they are tech forward,

559
00:25:34,720 --> 00:25:38,399
Speaker 15: and you could argue that in the cloud competing cycle

560
00:25:38,600 --> 00:25:41,760
Speaker 15: that they were not exactly the first ones out of

561
00:25:41,760 --> 00:25:44,080
Speaker 15: the gate, but in this AI cycle they are the

562
00:25:44,080 --> 00:25:45,960
Speaker 15: first ones out of the gate. And there's so much

563
00:25:46,040 --> 00:25:49,200
Speaker 15: of a cachet and boasting right that you have, especially

564
00:25:49,240 --> 00:25:52,880
Speaker 15: with Ceosatin Adela, who is a ranking cider of the company,

565
00:25:52,960 --> 00:25:55,119
Speaker 15: has been there for a long time. Being able to

566
00:25:55,119 --> 00:25:57,600
Speaker 15: pivot the company at the right time. That of enormous

567
00:25:57,640 --> 00:26:01,040
Speaker 15: strategic importance. Right from a financial perspective, what it has

568
00:26:01,040 --> 00:26:04,120
Speaker 15: allowed the company to do is, although it has required

569
00:26:04,160 --> 00:26:06,639
Speaker 15: a lot of capital build out of a scale that

570
00:26:06,680 --> 00:26:08,840
Speaker 15: the world has never seen so far in the technology

571
00:26:08,880 --> 00:26:11,800
Speaker 15: world and maybe in broader industry as well, it has

572
00:26:11,840 --> 00:26:16,879
Speaker 15: allowed the Azure business to grow at scale. So depending

573
00:26:16,960 --> 00:26:18,760
Speaker 15: on whose numbers you look at, we're roughly close to

574
00:26:18,800 --> 00:26:21,400
Speaker 15: an eighty billion dollar run rate for the Azure business.

575
00:26:21,880 --> 00:26:24,439
Speaker 15: And AI has helped keep that growth rate steadily in

576
00:26:24,440 --> 00:26:26,719
Speaker 15: the thirty plus percent range, and if we get an

577
00:26:26,720 --> 00:26:31,760
Speaker 15: inflection point with respect to AI moving up from golden sacks.

578
00:26:31,760 --> 00:26:34,840
Speaker 15: We have this thing that AI is stuck at the

579
00:26:34,880 --> 00:26:37,800
Speaker 15: infrastructure layer. For every computing cycle. You need to move

580
00:26:37,840 --> 00:26:40,560
Speaker 15: to the platform and applications. When you make the progression,

581
00:26:40,880 --> 00:26:43,080
Speaker 15: you see monumental shifts that are happening in the market.

582
00:26:43,200 --> 00:26:44,679
Speaker 9: So that's all to myself's benefit.

583
00:26:45,240 --> 00:26:48,600
Speaker 3: The eighty billion run rate for Azure comes in tandem

584
00:26:48,640 --> 00:26:51,080
Speaker 3: cash with a more than eighty billion dollar need to

585
00:26:51,119 --> 00:26:55,159
Speaker 3: spend on capital expenditure. Is that currently totally vindicated in

586
00:26:55,200 --> 00:26:57,000
Speaker 3: your mind? Zyme when we see it increase.

587
00:26:58,280 --> 00:27:00,960
Speaker 15: It's a dollar for dollar right of capis gives you

588
00:27:01,000 --> 00:27:03,159
Speaker 15: a dollar of AS revenues roughly give or take, and

589
00:27:03,200 --> 00:27:06,600
Speaker 15: there's within that there is a slightly more inefficient conversion

590
00:27:06,600 --> 00:27:09,000
Speaker 15: of the dollar of capis into AI revenue and slightly

591
00:27:09,119 --> 00:27:12,920
Speaker 15: more efficient conversion. So we think that it is the

592
00:27:13,040 --> 00:27:15,439
Speaker 15: right trade off at this point in time. And the

593
00:27:15,520 --> 00:27:17,879
Speaker 15: good news of your Microsoft is that you're running a

594
00:27:17,960 --> 00:27:22,639
Speaker 15: very diversified business that all the capex is not extremely

595
00:27:22,920 --> 00:27:24,760
Speaker 15: punitive to your free cash flowers. I mean, you could

596
00:27:24,840 --> 00:27:27,160
Speaker 15: run a model where you're not generating any free cashlodob

597
00:27:27,280 --> 00:27:30,840
Speaker 15: that's not Microsoft's things, so they do generate a pretty

598
00:27:30,880 --> 00:27:34,080
Speaker 15: meaningful significant free capital margin because of the health of

599
00:27:34,080 --> 00:27:37,520
Speaker 15: the overall business. You've got to look at Microsoft not

600
00:27:37,600 --> 00:27:39,800
Speaker 15: just in the context of Azure, but there is a

601
00:27:39,920 --> 00:27:43,320
Speaker 15: broader Microsoft Cloud business which has the M three sixty five,

602
00:27:43,680 --> 00:27:46,800
Speaker 15: and then you have the server on premises business and

603
00:27:46,960 --> 00:27:50,639
Speaker 15: a couple of other businesses that are equally significant in

604
00:27:50,720 --> 00:27:54,679
Speaker 15: terms of revenue scope and significant drivers are profitable, so

605
00:27:54,680 --> 00:27:56,639
Speaker 15: they've got the ability to generate the cash to be

606
00:27:56,680 --> 00:27:57,840
Speaker 15: able to fund this capex.

607
00:27:58,200 --> 00:27:59,680
Speaker 9: That's a very important consideration.

608
00:28:00,040 --> 00:28:02,320
Speaker 15: Long as the returns keep coming and you're able to

609
00:28:02,359 --> 00:28:05,040
Speaker 15: generate a dollar of revenue for every dollar of capiss,

610
00:28:05,320 --> 00:28:08,440
Speaker 15: as long as that algorithm, broadly speaking, holes, I think

611
00:28:08,440 --> 00:28:09,800
Speaker 15: it's the right trade off for the company.

612
00:28:10,480 --> 00:28:13,359
Speaker 3: There have been concerns though, surrounding Microsoft, whether or not

613
00:28:13,359 --> 00:28:16,800
Speaker 3: it's just how great the product is to use when

614
00:28:16,840 --> 00:28:21,040
Speaker 3: you're sat within its ecosystem, but also the cyber issues

615
00:28:21,080 --> 00:28:23,919
Speaker 3: that we've seen running front and center this month cash

616
00:28:24,040 --> 00:28:26,120
Speaker 3: how much do you expect Satia to really talk.

617
00:28:25,960 --> 00:28:26,720
Speaker 9: To those issues.

618
00:28:27,440 --> 00:28:30,440
Speaker 15: I believe that there is a bit of a lag

619
00:28:30,560 --> 00:28:34,879
Speaker 15: between the actual chat GPT technology that is open a

620
00:28:34,920 --> 00:28:37,760
Speaker 15: I brought, broadly speaking technology and how much of that

621
00:28:38,120 --> 00:28:41,400
Speaker 15: gets incorporated in the Microsoft Office Copilot, and I believe

622
00:28:41,400 --> 00:28:43,240
Speaker 15: that that lag is likely to reduce over a period

623
00:28:43,240 --> 00:28:47,680
Speaker 15: of time. And we're also implementing consumer grade technology in

624
00:28:47,720 --> 00:28:50,320
Speaker 15: the enterprise. I mean, that is a completely different piece.

625
00:28:50,360 --> 00:28:53,400
Speaker 15: So I'm not surprised to hear what you've heard with

626
00:28:53,520 --> 00:28:57,160
Speaker 15: respective where the product is relative to enterprise expectations. And

627
00:28:57,160 --> 00:29:00,480
Speaker 15: I would argue that the product is I use it personally, Goldman,

628
00:29:00,560 --> 00:29:02,960
Speaker 15: and it's come a long way since about six months

629
00:29:03,040 --> 00:29:05,760
Speaker 15: nine months ago, and it's likely to go a long.

630
00:29:05,560 --> 00:29:06,400
Speaker 6: Way in the future.

631
00:29:08,840 --> 00:29:11,280
Speaker 15: That version of co pilot that we used today is

632
00:29:11,320 --> 00:29:14,720
Speaker 15: going to go through significant enhancements liberally to customize it

633
00:29:14,800 --> 00:29:17,240
Speaker 15: tailor at your workflows. Oh, that's going to get significantly better.

634
00:29:17,240 --> 00:29:18,560
Speaker 15: So the buzz is going to get better.

635
00:29:18,880 --> 00:29:21,040
Speaker 2: One thing I've always wanted to ask you cash is

636
00:29:21,640 --> 00:29:24,680
Speaker 2: present day, middle of twenty twenty five, Microsoft is the

637
00:29:24,720 --> 00:29:27,840
Speaker 2: world's second most valuable company. Right, And if I think

638
00:29:27,880 --> 00:29:30,840
Speaker 2: back to when I arrived in Silicon Valley in twenty eighteen,

639
00:29:30,840 --> 00:29:33,520
Speaker 2: but even two years ago, did you see that coming

640
00:29:33,920 --> 00:29:37,160
Speaker 2: where Microsoft would vie with Nvidia to be the most

641
00:29:37,240 --> 00:29:40,239
Speaker 2: valuable company in the world based on the direction it

642
00:29:40,280 --> 00:29:42,960
Speaker 2: was headed pre open AI and all of that.

643
00:29:43,480 --> 00:29:46,360
Speaker 15: So when I launched coverage at Goldman in twenty twenty one,

644
00:29:46,560 --> 00:29:49,280
Speaker 15: we had a big price target on Microsoft, and the

645
00:29:49,360 --> 00:29:52,200
Speaker 15: pushback that we got was, you're implying that the market

646
00:29:52,200 --> 00:29:54,720
Speaker 15: cap can grow by another half a trillion. Two it's

647
00:29:54,760 --> 00:29:57,000
Speaker 15: already a multi trillion dollar market or what was And

648
00:29:57,000 --> 00:29:58,640
Speaker 15: I think it was a couple of tillion. Yeah, And

649
00:29:58,720 --> 00:30:00,240
Speaker 15: I think what it comes down to is, if you

650
00:30:00,360 --> 00:30:02,760
Speaker 15: unlock a big tech cycle, the dollars at stake and

651
00:30:02,840 --> 00:30:04,880
Speaker 15: every tech cycle are larger and larger.

652
00:30:04,880 --> 00:30:05,600
Speaker 6: And if you are.

653
00:30:05,640 --> 00:30:08,240
Speaker 15: Leading this cycle as opposed to being a fast.

654
00:30:08,040 --> 00:30:10,840
Speaker 4: Follower, who is to say what the new market?

655
00:30:10,880 --> 00:30:13,360
Speaker 15: Nobody envisioned this kind of playing out the way it

656
00:30:13,400 --> 00:30:16,040
Speaker 15: did so, and we're still early in AI. So if

657
00:30:16,080 --> 00:30:17,960
Speaker 15: you listen to the economist, they're talking about how the

658
00:30:18,000 --> 00:30:21,400
Speaker 15: labor market could be incorporated by way of AI. If

659
00:30:21,400 --> 00:30:23,680
Speaker 15: that were to happen, you got a lot more value

660
00:30:23,680 --> 00:30:26,800
Speaker 15: creation along the way. So I'm not I'm pleasantly surprised

661
00:30:26,840 --> 00:30:29,360
Speaker 15: about how quickly it has happened, but I was just

662
00:30:29,640 --> 00:30:33,000
Speaker 15: remarking earlier that Microsoft stock has actually performed in line

663
00:30:33,000 --> 00:30:35,840
Speaker 15: with the nastac finally, since the launch of Chat GPT.

664
00:30:36,240 --> 00:30:38,440
Speaker 15: For a while, it was lagging, and I kept telling myself,

665
00:30:38,480 --> 00:30:40,320
Speaker 15: this is the company that facilitated the birth of this

666
00:30:40,400 --> 00:30:42,600
Speaker 15: AI revolution a long with Nvidia and Open Ai, and

667
00:30:42,640 --> 00:30:43,640
Speaker 15: their stock is lagging.

668
00:30:43,640 --> 00:30:44,800
Speaker 6: It doesn't make any sense right now.

669
00:30:44,880 --> 00:30:48,320
Speaker 15: Finally we're just about even, Sophie vindication.

670
00:30:48,200 --> 00:30:51,360
Speaker 2: Yashraan and Managing Director of Global Investment Research at Goldman's

671
00:30:51,400 --> 00:30:53,160
Speaker 2: has great to have you here on Bloomberg Tech.

672
00:30:53,400 --> 00:30:54,960
Speaker 4: Thank you very much. Carry some news.

673
00:30:55,160 --> 00:30:57,480
Speaker 3: Yeah, it's time to talking tech now and first up,

674
00:30:57,680 --> 00:31:02,000
Speaker 3: door Dash spotifflies Global of Advertising Lee Brown will join

675
00:31:02,040 --> 00:31:04,640
Speaker 3: the food delivery company as chief revenue Officer starting in

676
00:31:04,720 --> 00:31:05,240
Speaker 3: late August.

677
00:31:05,520 --> 00:31:05,680
Speaker 13: Now.

678
00:31:05,720 --> 00:31:09,360
Speaker 3: Brown previously led Spotify's two billion dollar ad business across

679
00:31:09,480 --> 00:31:12,320
Speaker 3: ninety international markets and is set to oversee door Dash's

680
00:31:12,360 --> 00:31:14,760
Speaker 3: revenue in the US, Canada, Australia and New Zealand.

681
00:31:15,200 --> 00:31:16,680
Speaker 5: Whilst Weimo is set to.

682
00:31:16,720 --> 00:31:19,560
Speaker 3: Launch its robo taxi service in Dallas next year in

683
00:31:19,600 --> 00:31:22,720
Speaker 3: a partnership with rental cil company Avis. Now Weiver says

684
00:31:22,720 --> 00:31:26,440
Speaker 3: Avis will serve as a pleat fleet partner providing infrastructure, maintenance,

685
00:31:26,480 --> 00:31:27,680
Speaker 3: car management operations.

686
00:31:27,920 --> 00:31:28,920
Speaker 4: The Dallas Deel.

687
00:31:28,840 --> 00:31:31,800
Speaker 3: Marks a multi year partnership that Waimo and Avis plan

688
00:31:31,920 --> 00:31:35,800
Speaker 3: to expand into more cities over time and venture debt

689
00:31:35,880 --> 00:31:38,680
Speaker 3: firm to Cora, Hare's raised six hundred eighty five million

690
00:31:38,720 --> 00:31:40,640
Speaker 3: dollars with the backings from the likes of Peter Teel

691
00:31:40,680 --> 00:31:43,760
Speaker 3: and Marc Andreesen. Now, according to CEO Kerry Finley, the

692
00:31:43,840 --> 00:31:46,280
Speaker 3: money will be used to make loans to about twenty

693
00:31:46,440 --> 00:31:50,040
Speaker 3: to thirty million dollars to startups. Now, the latest investment

694
00:31:50,040 --> 00:31:52,440
Speaker 3: brings the firm's assets and management to about one point

695
00:31:52,440 --> 00:31:53,640
Speaker 3: four billion dollar zed.

696
00:31:55,000 --> 00:31:55,760
Speaker 4: Okay, coming up.

697
00:31:55,800 --> 00:31:59,320
Speaker 2: So FI CEO Anthony Noto joins us to discuss the company's.

698
00:31:58,920 --> 00:31:59,920
Speaker 4: Second quarter result.

699
00:32:00,240 --> 00:32:03,360
Speaker 2: An upbeat forecast and my goodness to shares already taking

700
00:32:03,400 --> 00:32:04,360
Speaker 2: off this Tuesday.

701
00:32:04,400 --> 00:32:04,960
Speaker 4: Stay with us.

702
00:32:05,160 --> 00:32:19,000
Speaker 16: This is Bloomberg Tech shares are so far climbing off.

703
00:32:19,080 --> 00:32:22,560
Speaker 2: The company reported second quarter revenue seventy two percent EU

704
00:32:22,680 --> 00:32:26,160
Speaker 2: of year jump in fee based revenues. Let's discuss with

705
00:32:26,240 --> 00:32:29,080
Speaker 2: the man in charge, SOFI CEO Anthony Noto. You know

706
00:32:29,120 --> 00:32:31,360
Speaker 2: the SOFI story, Anthony, has become kind of simple. You've

707
00:32:31,440 --> 00:32:34,880
Speaker 2: kind of invested in fee based business lines, many of

708
00:32:34,920 --> 00:32:37,960
Speaker 2: them they've been consistent. But now what the market seems

709
00:32:38,000 --> 00:32:40,800
Speaker 2: to be seeing is that flowing through to the bottom

710
00:32:40,840 --> 00:32:43,440
Speaker 2: line as well. Would you just explain how that went

711
00:32:43,480 --> 00:32:44,040
Speaker 2: in the quarter.

712
00:32:45,040 --> 00:32:48,720
Speaker 17: Sure, we've made the conscious effort of diverse fire or

713
00:32:48,800 --> 00:32:52,560
Speaker 17: business into these capital light, less credit risk a few

714
00:32:52,600 --> 00:32:55,280
Speaker 17: revenue streams, one of which is our long platform business

715
00:32:55,320 --> 00:32:58,560
Speaker 17: where people pay us to use our originations platform, which

716
00:32:58,600 --> 00:33:02,720
Speaker 17: includes our underwriting capability, our marketing capabilities, and our servicing

717
00:33:02,720 --> 00:33:04,800
Speaker 17: capabilities to produce loans for them.

718
00:33:04,880 --> 00:33:06,160
Speaker 6: For a fee that they pay us.

719
00:33:06,480 --> 00:33:09,640
Speaker 17: We also generate fees in our SOFI money account business

720
00:33:10,000 --> 00:33:12,880
Speaker 17: through interchange, as well as our brokerage business, and then

721
00:33:12,920 --> 00:33:15,600
Speaker 17: of course our credit card businesses. And so as we've

722
00:33:15,600 --> 00:33:18,720
Speaker 17: diversified the products that we offer, the revenue streams have

723
00:33:18,720 --> 00:33:21,880
Speaker 17: also diversified. We're about forty four percent of our revenue

724
00:33:21,880 --> 00:33:24,960
Speaker 17: outcomes from these fees that are generated without use of

725
00:33:25,000 --> 00:33:27,080
Speaker 17: capital and without credit risk, and so.

726
00:33:27,080 --> 00:33:28,880
Speaker 6: That deversks the balance sheet quite a bit.

727
00:33:29,280 --> 00:33:31,720
Speaker 17: So our ability to grow their overall business forty four

728
00:33:31,720 --> 00:33:35,680
Speaker 17: percent with a twenty nine percent operating margin is reflective

729
00:33:35,760 --> 00:33:39,800
Speaker 17: of that diversification and less risky revenue that's more visible

730
00:33:39,840 --> 00:33:40,320
Speaker 17: as well.

731
00:33:41,280 --> 00:33:45,280
Speaker 2: Anthony, you just talked about de risking. Elsewhere in the

732
00:33:45,280 --> 00:33:49,080
Speaker 2: earnings domain, PayPal was asked about the strength of the

733
00:33:49,200 --> 00:33:54,360
Speaker 2: US consumer and comments from that company with somewhat negative

734
00:33:54,400 --> 00:33:57,240
Speaker 2: that they see some sort of cracks in the strength

735
00:33:57,280 --> 00:34:00,720
Speaker 2: of the consumer from those that use your platfor your

736
00:34:00,800 --> 00:34:02,120
Speaker 2: various financial offerings.

737
00:34:02,120 --> 00:34:03,720
Speaker 4: What are you seeing present day?

738
00:34:04,560 --> 00:34:07,320
Speaker 17: Yeah, they have a very different strategy and business than us,

739
00:34:07,320 --> 00:34:10,560
Speaker 17: and a very different target audience. We're appealing to the

740
00:34:10,640 --> 00:34:13,600
Speaker 17: overachievers in the United States that are looking for ways

741
00:34:14,200 --> 00:34:16,920
Speaker 17: to be able to save, to achieve, and invest to

742
00:34:16,960 --> 00:34:20,319
Speaker 17: achieve their long term ambitions, whatever their American dream may be.

743
00:34:20,400 --> 00:34:23,160
Speaker 17: So we're helping them spend less than they make and

744
00:34:23,200 --> 00:34:26,319
Speaker 17: invest the rest, and we're seeing really strong trends for them.

745
00:34:26,520 --> 00:34:29,200
Speaker 17: We see them loaning their cost of debt by refinancing

746
00:34:29,440 --> 00:34:33,439
Speaker 17: out of expensive credit card debt that charges twenty four

747
00:34:33,520 --> 00:34:36,640
Speaker 17: to thirty percent interest into our loans that only charge

748
00:34:36,680 --> 00:34:37,960
Speaker 17: twelve to thirty percent interest.

749
00:34:38,320 --> 00:34:41,120
Speaker 6: We see them moving their money into SOFI money. We

750
00:34:41,160 --> 00:34:42,080
Speaker 6: give three point.

751
00:34:41,840 --> 00:34:44,920
Speaker 17: Eight percent interest on our savings account in SOFI money

752
00:34:45,080 --> 00:34:47,400
Speaker 17: with it if you're a direct deposit customer or a

753
00:34:47,400 --> 00:34:51,080
Speaker 17: SOFI plus customer, we offer them investment opportunities that are

754
00:34:51,120 --> 00:34:56,160
Speaker 17: really attractive. We offer stocks without commissions, fractional shares, we

755
00:34:56,239 --> 00:34:59,040
Speaker 17: have sofi ets that are award winning as well as

756
00:34:59,120 --> 00:35:02,560
Speaker 17: robo accounts. But we also offer IPOs in addition to that,

757
00:35:02,760 --> 00:35:06,160
Speaker 17: private equity, so you can invest in private credit, private

758
00:35:06,200 --> 00:35:10,000
Speaker 17: real estate, venture capital funds as well as long short

759
00:35:10,560 --> 00:35:14,400
Speaker 17: public hedge funds and then finally private growth, growth equity

760
00:35:14,480 --> 00:35:19,640
Speaker 17: capabilities and so much more diverse business are consumers very strong, credits,

761
00:35:19,680 --> 00:35:23,600
Speaker 17: performing very well, continues improved spending through SOFI money is

762
00:35:23,640 --> 00:35:26,799
Speaker 17: also very strong. So we're seeing a consumer that's really

763
00:35:26,800 --> 00:35:30,040
Speaker 17: trying to lower their costs and spend less than they

764
00:35:30,120 --> 00:35:32,400
Speaker 17: make and invest the rest and the flywheel is really working.

765
00:35:32,920 --> 00:35:33,160
Speaker 5: Avan.

766
00:35:33,280 --> 00:35:36,120
Speaker 3: It's interesting that that flywheel comes at the same time

767
00:35:36,520 --> 00:35:38,560
Speaker 3: as basically the market's got a flywheel of its own

768
00:35:38,600 --> 00:35:42,480
Speaker 3: and seeing froth in certain sectors, Retail investors really wanted

769
00:35:42,520 --> 00:35:45,480
Speaker 3: to get in on the latest meme stock as well

770
00:35:45,520 --> 00:35:48,239
Speaker 3: as ipo. How are you thinking about general to AI,

771
00:35:48,400 --> 00:35:50,160
Speaker 3: like helping with the education side of things. I know

772
00:35:50,160 --> 00:35:52,799
Speaker 3: you're targeting over achievers, but are they diversified enough in

773
00:35:52,800 --> 00:35:53,680
Speaker 3: their own investments?

774
00:35:54,400 --> 00:35:54,640
Speaker 9: Sure?

775
00:35:54,640 --> 00:35:56,480
Speaker 17: And let me take your question and talk about what

776
00:35:56,600 --> 00:36:01,480
Speaker 17: I think are two technology supercycles that are unprecedented. We're

777
00:36:01,560 --> 00:36:03,480
Speaker 17: driving the growth that we are over the last eight

778
00:36:03,560 --> 00:36:05,720
Speaker 17: years without the benefit of crypto.

779
00:36:05,440 --> 00:36:09,080
Speaker 4: Or blockchain or AI, but I think the combination.

780
00:36:08,680 --> 00:36:12,839
Speaker 17: Of blockchain and crypto as well as AI are two

781
00:36:12,880 --> 00:36:15,160
Speaker 17: super cycles that will put a tail wind behind our

782
00:36:15,200 --> 00:36:19,040
Speaker 17: company and really help us really revolutionize the financial services

783
00:36:19,080 --> 00:36:22,640
Speaker 17: industry in ways that continue to give people faster ways

784
00:36:22,680 --> 00:36:25,920
Speaker 17: to send money at lower costs and to do it safer.

785
00:36:26,200 --> 00:36:26,920
Speaker 6: In addition to.

786
00:36:26,880 --> 00:36:29,520
Speaker 17: Being able to invest in this asset class, which does

787
00:36:29,640 --> 00:36:32,239
Speaker 17: help as it relates to the areas outside of the

788
00:36:32,239 --> 00:36:35,400
Speaker 17: country that may not have exposure to the US dollar

789
00:36:35,480 --> 00:36:38,040
Speaker 17: and its stability. In addition to be able to invest

790
00:36:38,080 --> 00:36:40,640
Speaker 17: in that asset, will allow people to borrow against that asset,

791
00:36:40,640 --> 00:36:43,280
Speaker 17: which will lower their cost of funding and in addition

792
00:36:43,320 --> 00:36:45,399
Speaker 17: to that will allow them to be able to pay

793
00:36:45,480 --> 00:36:51,000
Speaker 17: across borders more easily and quicker. Artificial intelligence is helping

794
00:36:51,040 --> 00:36:54,080
Speaker 17: us today across our entire business. We're using in the

795
00:36:54,160 --> 00:37:00,800
Speaker 17: back office to resolve disputes faster, to file suspecify reports,

796
00:37:01,120 --> 00:37:05,120
Speaker 17: to solve account takeover issues faster. On the consumer side,

797
00:37:05,120 --> 00:37:08,160
Speaker 17: we're offering something called cash Coach, which is the ability

798
00:37:08,200 --> 00:37:10,520
Speaker 17: to look at your cash crossed all your accounts. So

799
00:37:10,520 --> 00:37:13,239
Speaker 17: it's really that's not impacting our results yet. It's on

800
00:37:13,280 --> 00:37:16,680
Speaker 17: the com but they're both really exciting super cycles to

801
00:37:16,719 --> 00:37:17,520
Speaker 17: see the benefits.

802
00:37:17,520 --> 00:37:21,719
Speaker 2: From Anthony Nodo, CEO of sci Fi A Sofi, thank

803
00:37:21,760 --> 00:37:23,360
Speaker 2: you very much joining us. We actually has some breaking

804
00:37:23,400 --> 00:37:26,280
Speaker 2: news crossing the Bloomberg terminal and it comes from China's

805
00:37:26,280 --> 00:37:29,680
Speaker 2: trade envoy Lee Chengyang. He's talking about the progress of

806
00:37:29,719 --> 00:37:32,080
Speaker 2: talks in Stockholm. He says that the US and China

807
00:37:32,320 --> 00:37:35,520
Speaker 2: have agreed to extend the trade truce. They have exchanged

808
00:37:35,600 --> 00:37:38,880
Speaker 2: views on various macro economic issues, They agree on the

809
00:37:38,880 --> 00:37:42,640
Speaker 2: importance of safeguarding soald trade, and that the talks have

810
00:37:42,719 --> 00:37:45,839
Speaker 2: been constructive on major topics. The main headline I think

811
00:37:46,080 --> 00:37:48,120
Speaker 2: right Carra, is that they have agreed to extend the

812
00:37:48,160 --> 00:37:51,520
Speaker 2: trade truce and that the talks between the China, between

813
00:37:51,640 --> 00:37:55,120
Speaker 2: China and US negotiators currently in Stockholm will continue. In

814
00:37:55,200 --> 00:37:57,920
Speaker 2: what Lee calls close communication.

815
00:38:03,280 --> 00:38:07,880
Speaker 3: Meta set to report earnings after the closing bell on Wednesday.

816
00:38:07,880 --> 00:38:10,200
Speaker 3: I believe it is with investors closely watching its AI

817
00:38:10,280 --> 00:38:13,000
Speaker 3: investments for more Blue megs, Kurt Wagner joins us, Look,

818
00:38:13,000 --> 00:38:15,799
Speaker 3: we've got some big ends to think about more broadly, Kurt,

819
00:38:15,880 --> 00:38:18,160
Speaker 3: and I'm interested as to where we go in terms

820
00:38:18,200 --> 00:38:20,879
Speaker 3: of the spending that everyone's looking at is about talent,

821
00:38:20,920 --> 00:38:21,680
Speaker 3: it's about capex.

822
00:38:21,680 --> 00:38:22,400
Speaker 5: Will it be raised?

823
00:38:23,120 --> 00:38:25,840
Speaker 18: I think that's the speculation, is that, especially once you

824
00:38:25,880 --> 00:38:28,800
Speaker 18: saw what Google did last week raising their capital expenditure

825
00:38:28,840 --> 00:38:31,840
Speaker 18: target for the year, I think there's some assumption that

826
00:38:32,120 --> 00:38:34,480
Speaker 18: Meta might do the same, given the scale a ideal

827
00:38:34,480 --> 00:38:36,759
Speaker 18: and all this very expensive hiring they're doing on the

828
00:38:36,760 --> 00:38:37,440
Speaker 18: AI front.

829
00:38:37,840 --> 00:38:40,280
Speaker 6: Now, remember they already raised.

830
00:38:40,000 --> 00:38:43,920
Speaker 18: The range for their capex last quarter as well, So

831
00:38:43,960 --> 00:38:46,160
Speaker 18: there was a different number in January, a different number

832
00:38:46,200 --> 00:38:48,279
Speaker 18: in April, and now we'll be watching tomorrow to see

833
00:38:48,320 --> 00:38:50,759
Speaker 18: if there's another new number. But given the spending AI,

834
00:38:50,880 --> 00:38:52,840
Speaker 18: I would not be surprised if they go that route.

835
00:38:53,520 --> 00:38:56,960
Speaker 2: And yet we're always reminded every quarter that Meta makes

836
00:38:57,000 --> 00:39:00,800
Speaker 2: all its money from advertising, and so there's AI story

837
00:39:00,800 --> 00:39:04,520
Speaker 2: where adds a better price more powerfully, and then there's like,

838
00:39:04,680 --> 00:39:06,160
Speaker 2: is all this investment going to pay off?

839
00:39:06,200 --> 00:39:07,400
Speaker 4: What is the street expecting?

840
00:39:08,040 --> 00:39:08,200
Speaker 9: Well?

841
00:39:08,239 --> 00:39:10,120
Speaker 18: I think the good news for them now is that

842
00:39:10,200 --> 00:39:14,759
Speaker 18: the AI story they're telling today feels more urgent and

843
00:39:14,920 --> 00:39:17,520
Speaker 18: more timely, I think than the one they've been telling

844
00:39:17,560 --> 00:39:19,480
Speaker 18: for the last year or two, which was related to

845
00:39:19,520 --> 00:39:23,040
Speaker 18: like the metaverse, and so here now they're talking about chatbots,

846
00:39:23,040 --> 00:39:26,680
Speaker 18: they're talking about LMS, data centers, like things that people

847
00:39:26,680 --> 00:39:29,240
Speaker 18: I think have a better understanding of what the potential

848
00:39:29,280 --> 00:39:29,880
Speaker 18: outcome is.

849
00:39:30,280 --> 00:39:31,840
Speaker 6: The metaverse was always ed.

850
00:39:31,920 --> 00:39:34,279
Speaker 18: You will remember that the main thing that they were

851
00:39:34,280 --> 00:39:37,960
Speaker 18: sinking all of this money into, and there was no real, you.

852
00:39:37,920 --> 00:39:39,840
Speaker 6: Know, end insight to that.

853
00:39:39,960 --> 00:39:42,279
Speaker 18: Now I don't think there's an end insight to AI either,

854
00:39:43,000 --> 00:39:44,920
Speaker 18: but at least I think they're doing something that a

855
00:39:44,920 --> 00:39:46,000
Speaker 18: bunch of other companies are doing.

856
00:39:46,040 --> 00:39:48,359
Speaker 6: It's a little easier perhaps to wrap your head around.

857
00:39:48,640 --> 00:39:51,239
Speaker 2: Blue Vers Kurt Wagner looking forward to meta after the

858
00:39:51,239 --> 00:39:54,239
Speaker 2: bell tomorrow. Thank you very much, Caro. That does it

859
00:39:54,239 --> 00:39:56,040
Speaker 2: for this additional Bloomberg Tech. But we had some big

860
00:39:56,080 --> 00:39:57,920
Speaker 2: breaking news in the last few moments.

861
00:39:57,960 --> 00:39:59,920
Speaker 3: We did, and it's so important to the tech eCos

862
00:40:00,400 --> 00:40:03,840
Speaker 3: and more broadly the world economy. We're looking at China

863
00:40:03,880 --> 00:40:06,000
Speaker 3: saying it does indeed agree with the United States to

864
00:40:06,040 --> 00:40:08,600
Speaker 3: extend that tariff truce. Remember it was likely to expire

865
00:40:08,960 --> 00:40:12,080
Speaker 3: in mid August as to where currently tariff's had been

866
00:40:12,120 --> 00:40:13,960
Speaker 3: set at about the thirty percent level.

867
00:40:14,239 --> 00:40:17,279
Speaker 2: We are going to read the language very carefully. All

868
00:40:17,320 --> 00:40:21,640
Speaker 2: those experts on wording China and US talks with candid

869
00:40:21,840 --> 00:40:25,279
Speaker 2: says Lee chain Gang candid good thing or bad thing?

870
00:40:25,400 --> 00:40:27,600
Speaker 4: The markets will tell us in due course caract.

871
00:40:27,400 --> 00:40:29,600
Speaker 3: And what does it mean for semiconductors? What does it

872
00:40:29,640 --> 00:40:31,560
Speaker 3: mean for the flow of rare earth metals? Do not

873
00:40:31,640 --> 00:40:33,520
Speaker 3: forget to check out our podcast. You can find it

874
00:40:33,560 --> 00:40:36,319
Speaker 3: on the Terminal soll As, online on Apple, Spotify, and

875
00:40:36,400 --> 00:40:38,440
Speaker 3: iHeart from New York from San Francisco.

876
00:40:39,160 --> 00:40:40,120
Speaker 5: This is Bloomberg Tech