1
00:00:02,480 --> 00:00:11,120
Speaker 1: Bloomberg Audio, Studios, Podcasts, Radio News. Good morning, I'm Nathan

2
00:00:11,119 --> 00:00:14,080
Speaker 1: Hager and I'm Karen Moscow. Here are the stories we're

3
00:00:14,120 --> 00:00:14,920
Speaker 1: following today.

4
00:00:15,240 --> 00:00:17,760
Speaker 2: Karen, we begin with the latest reaction to those highly

5
00:00:17,800 --> 00:00:21,840
Speaker 2: anticipated earnings from Nvidia. The shares are down more than

6
00:00:21,880 --> 00:00:25,720
Speaker 2: four percent in early trading. The AI juggernaut met or

7
00:00:25,840 --> 00:00:30,240
Speaker 2: beat analyst's estimates on nearly every measure, but Nvidia investors

8
00:00:30,240 --> 00:00:33,960
Speaker 2: have grown accustomed to blowout quarters, and the latest numbers

9
00:00:34,000 --> 00:00:37,680
Speaker 2: did not qualify. Moreover, in Vidia's next big cash cow,

10
00:00:37,760 --> 00:00:41,519
Speaker 2: the new Blackwell processor lineup, has proven more challenging to

11
00:00:41,600 --> 00:00:45,800
Speaker 2: manufacture than anticipated. In Vidia CEO Jensen Wong spoke with

12
00:00:45,800 --> 00:00:48,599
Speaker 2: Bloomberg's Ed Ludlow after the company conference call.

13
00:00:49,080 --> 00:00:51,400
Speaker 3: We're expecting Q three to have more supply than Q two,

14
00:00:51,560 --> 00:00:53,880
Speaker 3: We're expecting Q four to have more supply than Q three,

15
00:00:54,000 --> 00:00:55,680
Speaker 3: and we're expecting Q one to have more supply than

16
00:00:55,760 --> 00:00:58,520
Speaker 3: Q four, and so I think our supply, our supply

17
00:00:58,600 --> 00:01:01,040
Speaker 3: condition going into next year will be in will be

18
00:01:01,520 --> 00:01:03,520
Speaker 3: a large improvement over this last year.

19
00:01:04,000 --> 00:01:06,920
Speaker 2: In Nvidia CEO Jensen Wong says third quarter revenue will

20
00:01:06,920 --> 00:01:09,640
Speaker 2: be about thirty two and a half billion dollars. Analysts

21
00:01:09,720 --> 00:01:12,920
Speaker 2: had predicted thirty one point nine billion on average, but

22
00:01:13,000 --> 00:01:16,520
Speaker 2: the estimates ranged as high as thirty seven point nine billion.

23
00:01:16,920 --> 00:01:20,520
Speaker 1: Well, Nathan reaction is still pouring into the Nvidia results

24
00:01:20,600 --> 00:01:24,040
Speaker 1: and Jensen Wong interview. Man Deep Singh is a senior

25
00:01:24,080 --> 00:01:26,200
Speaker 1: tech analyst with the Bloomberg Intelligence.

26
00:01:26,560 --> 00:01:29,400
Speaker 4: It's still a very solid growth story, but when it

27
00:01:29,480 --> 00:01:33,880
Speaker 4: comes to convincing investors that there are more catalysts for

28
00:01:34,240 --> 00:01:39,240
Speaker 4: upside relative to where expectations are, I think a lot

29
00:01:39,280 --> 00:01:43,720
Speaker 4: of it right now is dependent on how the industry

30
00:01:43,959 --> 00:01:48,880
Speaker 4: actually deploys Generator AI. That's what Jensen highlighted that look,

31
00:01:49,200 --> 00:01:55,480
Speaker 4: jenai is transformational. It's changing how compute is done and

32
00:01:55,560 --> 00:01:56,760
Speaker 4: everyone will use it.

33
00:01:57,080 --> 00:02:00,520
Speaker 1: Bloomberg Intelligence senior tech analyst man Deep Singh notes that

34
00:02:00,720 --> 00:02:04,280
Speaker 1: most of Nvidia's growth comes from a small group of customers.

35
00:02:04,520 --> 00:02:08,480
Speaker 1: About forty percent stems from a large data center operators,

36
00:02:08,560 --> 00:02:12,519
Speaker 1: companies like alphabet s, Google and Facebook parent meta platforms.

37
00:02:12,680 --> 00:02:14,360
Speaker 2: And we're going to have much more coverage of the

38
00:02:14,440 --> 00:02:16,760
Speaker 2: Nvidia story in a few minutes. Will bring you more

39
00:02:16,840 --> 00:02:20,440
Speaker 2: from our conversation with the CEO, Jensen Wong, and that

40
00:02:20,560 --> 00:02:23,560
Speaker 2: will be followed by analysis from web Bush Security senior

41
00:02:23,600 --> 00:02:26,600
Speaker 2: equity research analyst Dan ives Well.

42
00:02:26,560 --> 00:02:28,480
Speaker 1: Nathan and Video is not the only stock on the

43
00:02:28,520 --> 00:02:31,760
Speaker 1: move this morning following earning. Several other high tech results

44
00:02:31,760 --> 00:02:33,480
Speaker 1: came in after the bell as well, and we get

45
00:02:33,480 --> 00:02:36,240
Speaker 1: the latest with Bloomberg's John Tucker, John and.

46
00:02:36,360 --> 00:02:39,560
Speaker 5: Karen CrowdStrike shares down over two percent pre market trading.

47
00:02:39,600 --> 00:02:43,440
Speaker 5: The security software company cutting it's full your forecast. However,

48
00:02:43,520 --> 00:02:46,760
Speaker 5: some analysts of the reduction better than feared. This comes

49
00:02:46,800 --> 00:02:49,600
Speaker 5: in the wake of the CrowdStrike update. You'll remember that

50
00:02:49,720 --> 00:02:54,600
Speaker 5: crash computers worldwide last month, Salesforce gave an earnings forecast

51
00:02:54,680 --> 00:02:57,600
Speaker 5: the top analyst estimate's the top maker of customer management

52
00:02:57,639 --> 00:03:00,920
Speaker 5: software who's been trying to deal with activist investors. The

53
00:03:00,960 --> 00:03:04,840
Speaker 5: company says new higher price products with AR are just

54
00:03:04,919 --> 00:03:07,640
Speaker 5: starting to help boot sales. They're getting a popped this

55
00:03:07,680 --> 00:03:11,600
Speaker 5: morning of almost five percent, and finally, hp ticker simple

56
00:03:11,720 --> 00:03:14,720
Speaker 5: HPQ down close to two and a half percent. They're

57
00:03:14,760 --> 00:03:17,720
Speaker 5: cutting their full year profit outlook. That's because of a

58
00:03:17,800 --> 00:03:22,720
Speaker 5: continued downturn in its printing unit. John Tucker, Bloomberg Radio.

59
00:03:22,639 --> 00:03:24,840
Speaker 2: All right, John, thanks for also watching. Shares of super

60
00:03:24,880 --> 00:03:28,200
Speaker 2: micro Computer. They're down nearly five percent in early trading

61
00:03:28,200 --> 00:03:32,480
Speaker 2: that follows yesterday's nineteen percent plunge. Super Micro says it's

62
00:03:32,480 --> 00:03:35,720
Speaker 2: delaying filing its annual financial disclosures and will need more

63
00:03:35,720 --> 00:03:39,320
Speaker 2: time to assess its internal controls. This ten k delay

64
00:03:39,760 --> 00:03:42,760
Speaker 2: erased more than eight hundred million dollars from super Micro

65
00:03:42,880 --> 00:03:45,760
Speaker 2: chairman Charles Leang's net worth. In fact, his fortune is

66
00:03:45,800 --> 00:03:49,240
Speaker 2: slumped by nearly two thirds from its March high.

67
00:03:49,800 --> 00:03:52,360
Speaker 1: Well, we turn to the economy now, Nathan, as investors

68
00:03:52,400 --> 00:03:56,120
Speaker 1: all waited another key inflation rating tomorrow, the Personal Consumption

69
00:03:56,240 --> 00:04:00,360
Speaker 1: Expenditures price index. A top FED official is cautioning about

70
00:04:00,360 --> 00:04:04,080
Speaker 1: moving too fast on rate cuts. Atlanta FED President Raphael

71
00:04:04,120 --> 00:04:07,520
Speaker 1: Bostik says he's still looking for additional data before he'll

72
00:04:07,560 --> 00:04:09,800
Speaker 1: support lowering interest rates next month.

73
00:04:10,040 --> 00:04:12,880
Speaker 6: I don't want us to be in a situation where

74
00:04:13,160 --> 00:04:16,400
Speaker 6: we cut and then we have to raise rates again.

75
00:04:16,920 --> 00:04:19,400
Speaker 6: Like that would be a very bad outcome. It would

76
00:04:19,440 --> 00:04:22,080
Speaker 6: really undermine all the conference I was talking about.

77
00:04:22,160 --> 00:04:25,599
Speaker 1: People have it. Speaking at the Stanford Club of Georgia,

78
00:04:25,640 --> 00:04:29,520
Speaker 1: Atlanta FED President Rafael Bostik reiterated that his timeline for

79
00:04:29,600 --> 00:04:33,240
Speaker 1: cuts had moved up after inflation fell more quickly than

80
00:04:33,240 --> 00:04:36,880
Speaker 1: he expected, and the unemployment rate increased more rapidly, but

81
00:04:37,160 --> 00:04:38,240
Speaker 1: he's still cautious.

82
00:04:38,600 --> 00:04:42,279
Speaker 2: So now two geopolitics Karen a major development overseas. White

83
00:04:42,320 --> 00:04:45,359
Speaker 2: House National Security Advisor Jake Sullivan is wrapping up his

84
00:04:45,440 --> 00:04:47,800
Speaker 2: three day trip to China with a visit with the

85
00:04:47,839 --> 00:04:50,960
Speaker 2: President Chi Jinping. It is the first time Sullivan's held

86
00:04:51,000 --> 00:04:53,760
Speaker 2: one to one talks with the Chinese leader. It comes

87
00:04:53,760 --> 00:04:56,039
Speaker 2: hours after his first face to face with the top

88
00:04:56,160 --> 00:04:59,159
Speaker 2: Chinese general. Bloomberg's Gill Deesis is in Hong Kong. She

89
00:04:59,200 --> 00:05:02,479
Speaker 2: says the goal of Sullivan's trip is to set up guardrails.

90
00:05:02,800 --> 00:05:04,960
Speaker 7: There's just a lot of uncertainty too going into the

91
00:05:05,040 --> 00:05:07,719
Speaker 7: US election later this year as who exactly will be

92
00:05:07,760 --> 00:05:10,120
Speaker 7: the leader after that that you're probably looking at this

93
00:05:10,440 --> 00:05:13,440
Speaker 7: attempt by the Biden administration to kind of future proof

94
00:05:13,520 --> 00:05:16,640
Speaker 7: ties with China or at least stabilize relations heading into

95
00:05:16,640 --> 00:05:17,080
Speaker 7: that election.

96
00:05:17,160 --> 00:05:20,760
Speaker 2: Bloombergs Jill Lisis reporting from Hong Kong. Earlier, Sullivan discussed

97
00:05:20,760 --> 00:05:23,359
Speaker 2: setting up a call between presidents she and Biden with

98
00:05:23,440 --> 00:05:25,120
Speaker 2: the Chinese Foreign Minister Wangi.

99
00:05:25,800 --> 00:05:28,320
Speaker 1: Now let's get to the latest and the presidential race.

100
00:05:28,440 --> 00:05:32,000
Speaker 1: Nathan Democrat Kamala Harris is on her second day of

101
00:05:32,040 --> 00:05:34,960
Speaker 1: a two day bus tour through Georgia. She's heading through

102
00:05:35,040 --> 00:05:38,240
Speaker 1: rural areas with a focus on shoring up support among

103
00:05:38,320 --> 00:05:41,360
Speaker 1: black men. Harris is also getting ready for her first

104
00:05:41,400 --> 00:05:44,800
Speaker 1: interview since taking the nomination on CNN tonight, and we

105
00:05:44,880 --> 00:05:46,919
Speaker 1: get more from Bloomberg's Julie Fine.

106
00:05:47,200 --> 00:05:50,240
Speaker 8: It's a very high stakes moment for her, and she's

107
00:05:50,320 --> 00:05:54,080
Speaker 8: also taking some criticism because she's not doing the interview alone.

108
00:05:54,120 --> 00:05:56,960
Speaker 8: She is doing it with Tim Walls. However, at the

109
00:05:57,040 --> 00:05:59,320
Speaker 8: end of the day, she is going to be the

110
00:05:59,360 --> 00:06:02,159
Speaker 8: one that has to answer the questions, even if he's

111
00:06:02,279 --> 00:06:05,200
Speaker 8: just sitting right beside her. So it's high stakes. It's

112
00:06:05,240 --> 00:06:07,479
Speaker 8: the first time it is that situation. It is a

113
00:06:07,520 --> 00:06:08,200
Speaker 8: one on two.

114
00:06:08,560 --> 00:06:12,120
Speaker 1: Bloomberg's July Fine reports the Harris campaign is brushing off

115
00:06:12,120 --> 00:06:16,040
Speaker 1: the criticism, saying former President Trump has also done joint

116
00:06:16,120 --> 00:06:19,840
Speaker 1: interviews with his running mate jd Vance. Tonight's interview airs

117
00:06:19,880 --> 00:06:26,320
Speaker 1: at nine pm Wall Street Time on CNN. But it's

118
00:06:26,360 --> 00:06:27,520
Speaker 1: time now for a look at some of the other

119
00:06:27,640 --> 00:06:29,799
Speaker 1: stories making news in New York and around the world,

120
00:06:29,839 --> 00:06:32,440
Speaker 1: and for that we're joined by Bloomberg's Michael Barr Michael,

121
00:06:32,440 --> 00:06:33,200
Speaker 1: Good morning.

122
00:06:33,000 --> 00:06:36,839
Speaker 9: Good morning, Karen. The listeria outbreak from Bor's Head Deli

123
00:06:36,920 --> 00:06:40,120
Speaker 9: meat has been linked to fifty seven illnesses in eighteen

124
00:06:40,160 --> 00:06:43,480
Speaker 9: states and the deaths of nine people, including two in

125
00:06:43,520 --> 00:06:47,960
Speaker 9: New York and New Jersey. Carshawn Morgenstein says his father,

126
00:06:48,200 --> 00:06:51,760
Speaker 9: a Holocaust survivor, was in good health until he says

127
00:06:51,800 --> 00:06:56,719
Speaker 9: his dad got listeria after eating tainted liverwurst. Morgenstein says

128
00:06:56,839 --> 00:07:00,440
Speaker 9: the infection led to meningitis and brain damage, and.

129
00:07:00,440 --> 00:07:03,480
Speaker 10: He always a lunch meet, always boores Head.

130
00:07:03,720 --> 00:07:06,640
Speaker 11: We're all still in shock for all of the things

131
00:07:06,680 --> 00:07:08,559
Speaker 11: you know that he's seen and been through in his life.

132
00:07:08,920 --> 00:07:12,200
Speaker 9: The CDC Warren's customers may still have tainted meat in

133
00:07:12,280 --> 00:07:16,400
Speaker 9: their fridge with best by dates through October. A Nevada

134
00:07:16,480 --> 00:07:19,960
Speaker 9: jury has found a democratic former Las Vegas area politician

135
00:07:20,040 --> 00:07:24,360
Speaker 9: guilty of murdering an investigative journalists who wrote articles critical

136
00:07:24,360 --> 00:07:28,320
Speaker 9: of his conduct in office. After deliberating for almost twelve hours,

137
00:07:28,360 --> 00:07:31,920
Speaker 9: the jury found Robert Tellis guilty of murdering Jeff German

138
00:07:32,360 --> 00:07:36,280
Speaker 9: of the Las Vegas Review Journal. Clark County District Attorney

139
00:07:36,280 --> 00:07:39,200
Speaker 9: Steve Wolfson says the jury sent a clear message.

140
00:07:39,320 --> 00:07:45,400
Speaker 12: Did any attempts to silence the media or to silence

141
00:07:45,600 --> 00:07:51,280
Speaker 12: or intimidate a journalist will not be tolerated. That's what

142
00:07:51,320 --> 00:07:52,280
Speaker 12: occurred in this case.

143
00:07:52,480 --> 00:07:56,720
Speaker 9: Clark County District Attorney Steve Wolfson jurors set tell Us

144
00:07:56,760 --> 00:07:59,320
Speaker 9: his sentence at twenty years to life in prison, tell

145
00:07:59,400 --> 00:08:03,240
Speaker 9: Us tonight killing German, and instead blamed a broad conspiracy

146
00:08:03,240 --> 00:08:07,120
Speaker 9: of people for framing him. It won't end tomorrow. That's

147
00:08:07,120 --> 00:08:10,240
Speaker 9: according to the Israel Defense Force. Of the raids in

148
00:08:10,280 --> 00:08:13,280
Speaker 9: the West Bank, the IDF is calling it a counter

149
00:08:13,520 --> 00:08:17,760
Speaker 9: terrorism operation. The Palestinian Health Ministry says the raids that

150
00:08:17,840 --> 00:08:21,880
Speaker 9: began Wednesday have left at least eleven people dead. New

151
00:08:21,960 --> 00:08:25,240
Speaker 9: York City Mayor Eric Adams announced significant progress in his

152
00:08:25,400 --> 00:08:28,720
Speaker 9: war on illegal smoke shops. The mayor used a crane

153
00:08:28,760 --> 00:08:31,640
Speaker 9: to move the more than four tons of seased cannabis

154
00:08:31,720 --> 00:08:35,479
Speaker 9: products that were destroyed in an incinerator at a facility

155
00:08:35,559 --> 00:08:39,320
Speaker 9: in Westbury, Nassau County. Back in May, New York City

156
00:08:39,400 --> 00:08:42,960
Speaker 9: launched a crackdown on the sale of illegal cannabis products.

157
00:08:43,320 --> 00:08:47,120
Speaker 13: What we have accomplished is exactly what we knew we

158
00:08:47,280 --> 00:08:51,439
Speaker 13: could accomplish with the right insight. And the right focus

159
00:08:51,480 --> 00:08:55,400
Speaker 13: and determination. A thousand shops were closed.

160
00:08:55,679 --> 00:08:59,800
Speaker 9: The crackdown involves a joint law enforcement effort including the NYPD,

161
00:09:00,360 --> 00:09:04,040
Speaker 9: the New York City Sheriff, and other agencies. Global news

162
00:09:04,040 --> 00:09:06,200
Speaker 9: twenty four hours a day and whenever you want it

163
00:09:06,200 --> 00:09:07,120
Speaker 9: with the Bloomberg News.

164
00:09:07,160 --> 00:09:07,360
Speaker 10: Now.

165
00:09:07,679 --> 00:09:09,880
Speaker 9: I'm Michael Barr, and this is Bloomberg.

166
00:09:09,960 --> 00:09:10,200
Speaker 12: Karen.

167
00:09:10,360 --> 00:09:17,240
Speaker 1: All right, Michael Barr, thank you time now for the

168
00:09:17,240 --> 00:09:19,800
Speaker 1: Bloomberg Sports UF date with John Stashauer.

169
00:09:19,880 --> 00:09:22,440
Speaker 14: John, good morning, Good morning, Karen. Mets and Phoenix. They

170
00:09:22,480 --> 00:09:25,760
Speaker 14: fell behind four nothingk Corbyn, Carrol homerd Off, Luis seven Reno.

171
00:09:25,800 --> 00:09:27,839
Speaker 14: The Mets rally tied the game fifth in ety two

172
00:09:27,880 --> 00:09:30,160
Speaker 14: onunch shot for Harrison Vader. They went up five to

173
00:09:30,240 --> 00:09:32,800
Speaker 14: four of the six, but in the eighth Carol with

174
00:09:32,960 --> 00:09:36,160
Speaker 14: a grand slam of Edwin Diaz. Arizona one eight to

175
00:09:36,240 --> 00:09:38,559
Speaker 14: five and Atlanta keeps winning five one at Minnesota in

176
00:09:38,559 --> 00:09:41,160
Speaker 14: the bras are four games ahead of the Mets. Second

177
00:09:41,160 --> 00:09:44,000
Speaker 14: straight night, Yankees couldn't muster much offense. A night after

178
00:09:44,040 --> 00:09:46,560
Speaker 14: losing four to two, they fell five to two. Carlos

179
00:09:46,640 --> 00:09:49,640
Speaker 14: Raddon gave up a first stunning homer to National's rookie

180
00:09:49,760 --> 00:09:52,160
Speaker 14: Dylan Cruz, second pick the last year's draft, his first

181
00:09:52,160 --> 00:09:54,560
Speaker 14: big leaguemer Rendon gave up two in the first and

182
00:09:54,640 --> 00:09:57,320
Speaker 14: two more in the second. The Yanks stranded eight in

183
00:09:57,360 --> 00:09:59,520
Speaker 14: their attempt to come back. Here's Aaron Boone.

184
00:10:00,120 --> 00:10:03,320
Speaker 11: Didn't do enough last two nights, just pushing runs across

185
00:10:04,679 --> 00:10:10,520
Speaker 11: and so lost the series. So you know, tough one,

186
00:10:11,200 --> 00:10:14,440
Speaker 11: you know, regrouping off day and curators started a little

187
00:10:14,480 --> 00:10:16,840
Speaker 11: quick three to day or but just one of those

188
00:10:16,880 --> 00:10:19,679
Speaker 11: days where weren't able to just finish off some rallies.

189
00:10:19,720 --> 00:10:21,840
Speaker 14: Juan Soto back where he used to play. He had

190
00:10:21,880 --> 00:10:24,200
Speaker 14: his worst series, zero for twelve, only drew one walk.

191
00:10:24,240 --> 00:10:26,160
Speaker 14: Aaron Judges did drive in a run last night, but

192
00:10:26,200 --> 00:10:28,360
Speaker 14: he did not homer in the series. Baltimore lost to

193
00:10:28,400 --> 00:10:30,839
Speaker 14: the Dodgers six to four. Yanks remained game ahead. Red

194
00:10:30,880 --> 00:10:33,720
Speaker 14: Sox shoutout Toronto three nothing. Battle of Division leaders, Houston

195
00:10:33,760 --> 00:10:36,680
Speaker 14: blank the Phillies ten to nothing. Jordan Alvarez hit three

196
00:10:36,679 --> 00:10:38,960
Speaker 14: home runs and a wild one. In Pittsburgh, the Pirates

197
00:10:39,000 --> 00:10:41,200
Speaker 14: led the Cubs ten to three, and the seventh inning.

198
00:10:41,440 --> 00:10:43,840
Speaker 14: Cups scored eleven times in their last three at bats.

199
00:10:43,880 --> 00:10:46,640
Speaker 14: They won fourteen to ten. US Open last night eas

200
00:10:46,640 --> 00:10:49,360
Speaker 14: he wins for Coco Goff and no back Jokobitch. Earlier sixteen,

201
00:10:49,440 --> 00:10:52,360
Speaker 14: Andre and Rubleev came back from a two set deficit

202
00:10:52,400 --> 00:10:55,000
Speaker 14: to win. Third round begins today, so does the season

203
00:10:55,080 --> 00:10:59,120
Speaker 14: ending Tour Championship Golf in Atlanta, thirty player field. By Sunday,

204
00:10:59,440 --> 00:11:01,839
Speaker 14: there'll be a f X champ who gets twenty five million.

205
00:11:01,840 --> 00:11:05,079
Speaker 14: Pittsburgh Steelers named Russell Wilson their Week one starting quarterback.

206
00:11:05,160 --> 00:11:08,320
Speaker 14: You beat out Justin Fields. Patriots coach Drive Mayo says

207
00:11:08,320 --> 00:11:11,760
Speaker 14: he'll name his daughter today. John stash I went Bloomberg Sports.

208
00:11:11,840 --> 00:11:12,920
Speaker 10: Karen Nathan all.

209
00:11:12,880 --> 00:11:13,920
Speaker 15: Right, John, thank you well.

210
00:11:13,960 --> 00:11:17,360
Speaker 1: If you're listening to us in Boston, our new home

211
00:11:17,440 --> 00:11:20,160
Speaker 1: beginning September third is going to be on ninety two

212
00:11:20,240 --> 00:11:23,800
Speaker 1: nine FM, That is the day after Labor Day. This

213
00:11:23,920 --> 00:11:27,520
Speaker 1: coming Tuesday, Bloomberg Radio moving to ninety two nine FM

214
00:11:27,679 --> 00:11:28,800
Speaker 1: in Boston.

215
00:11:30,840 --> 00:11:34,960
Speaker 10: Coast to coast on Bloomberg Radio, nationwide on Sirius XM,

216
00:11:35,040 --> 00:11:37,920
Speaker 10: and around the world on Bloomberg dot Com and the

217
00:11:38,000 --> 00:11:42,280
Speaker 10: Bloomberg Business app. This is Bloomberg Daybreak. Good morning, I'm

218
00:11:42,320 --> 00:11:43,040
Speaker 10: Nathan Hager.

219
00:11:43,120 --> 00:11:47,440
Speaker 2: We continue our coverage of chip giant Nvidia the earnings

220
00:11:47,440 --> 00:11:50,120
Speaker 2: report that Wall Street had been waiting for pretty much

221
00:11:50,200 --> 00:11:54,040
Speaker 2: all quarter long. The AI chip giant delivered an underwhelming

222
00:11:54,240 --> 00:11:58,319
Speaker 2: forecast and disappointed with news that it's still ironing out

223
00:11:58,360 --> 00:12:02,240
Speaker 2: production issues with its new US chips. Bloomberg's at Ludlow

224
00:12:02,320 --> 00:12:05,600
Speaker 2: spoke with the CEO of Nvidia, Jensen Wong, and they

225
00:12:05,640 --> 00:12:09,520
Speaker 2: began by discussing those issues with Blackwell. We now bring

226
00:12:09,559 --> 00:12:10,760
Speaker 2: you part of that discussion.

227
00:12:11,440 --> 00:12:14,640
Speaker 3: We made a mass change to improve the yield. Functionality

228
00:12:14,679 --> 00:12:17,880
Speaker 3: of Blackwell is wonderful. We're sampling Blackwell all over the

229
00:12:17,880 --> 00:12:24,160
Speaker 3: world today. We show people giving tours to people of

230
00:12:24,240 --> 00:12:26,200
Speaker 3: the Blackwall systems that we have up and running.

231
00:12:27,200 --> 00:12:29,240
Speaker 15: You could find pictures of Blackwell.

232
00:12:28,880 --> 00:12:33,360
Speaker 3: Systems all over the web. We have started volume production.

233
00:12:34,240 --> 00:12:38,520
Speaker 3: Volume production will ship in Q four. Q four, we

234
00:12:38,600 --> 00:12:43,320
Speaker 3: will have billions of dollars of Blackwell revenues and.

235
00:12:44,720 --> 00:12:47,560
Speaker 15: We will ramp from there. We will ramp from there.

236
00:12:48,040 --> 00:12:48,880
Speaker 15: The demand for.

237
00:12:48,960 --> 00:12:54,040
Speaker 3: Blackwell far exceeds its supply, of course in the beginning,

238
00:12:54,840 --> 00:12:57,839
Speaker 3: because the demand is so great, but we're going to

239
00:12:57,920 --> 00:13:00,960
Speaker 3: have lots and lots of supply and we will be

240
00:13:01,040 --> 00:13:05,120
Speaker 3: able to ramp starting in Q four. We have billions

241
00:13:05,120 --> 00:13:08,080
Speaker 3: of dollars of revenues, and we'll remp from there into

242
00:13:08,120 --> 00:13:10,440
Speaker 3: Q one into Q two and two next year. We're

243
00:13:10,440 --> 00:13:11,720
Speaker 3: going to have a great next year as well.

244
00:13:12,960 --> 00:13:16,199
Speaker 16: Jensen, what is the demand for accelerated computing beyond the

245
00:13:16,280 --> 00:13:17,320
Speaker 16: hyperscalers and.

246
00:13:17,400 --> 00:13:22,560
Speaker 3: Meta hyperscalers represent about forty five percent of our total

247
00:13:22,920 --> 00:13:24,040
Speaker 3: data center business.

248
00:13:24,080 --> 00:13:25,920
Speaker 15: We're relatively diversified today.

249
00:13:26,520 --> 00:13:31,760
Speaker 3: We have hyperscalers, we have Internet service providers, we have

250
00:13:32,360 --> 00:13:40,480
Speaker 3: sovereign ais, we have industries enterprises, so it's fairly fairly

251
00:13:40,520 --> 00:13:48,080
Speaker 3: diversified a site outside of hyperscalers. The other fifty five percent, Now,

252
00:13:48,880 --> 00:13:52,480
Speaker 3: the application use across all of that, all of that

253
00:13:52,600 --> 00:13:58,240
Speaker 3: data center starts with accelerated computing. Accelerated computing does everything,

254
00:13:58,280 --> 00:14:03,080
Speaker 3: of course, from well the models the things that we

255
00:14:03,120 --> 00:14:06,920
Speaker 3: know about, which is generative AI and that gets most

256
00:14:06,920 --> 00:14:09,880
Speaker 3: of the attention. But at the core we also do

257
00:14:10,840 --> 00:14:17,319
Speaker 3: database processing, pre and post processing of data before you

258
00:14:17,920 --> 00:14:23,760
Speaker 3: use it for generative AI, trans coding, scientific simulations, computer

259
00:14:23,840 --> 00:14:27,280
Speaker 3: graphics of course, image processing of course, and so there's

260
00:14:27,600 --> 00:14:33,080
Speaker 3: tons of applications that people use are accelerated computing for, and.

261
00:14:33,120 --> 00:14:36,720
Speaker 15: One of them is generative AI. And so let's see

262
00:14:36,760 --> 00:14:39,680
Speaker 15: what else can I say, I think that's that.

263
00:14:39,800 --> 00:14:42,840
Speaker 16: Let jump in Jensen please on sovereign AI. You and

264
00:14:42,840 --> 00:14:45,600
Speaker 16: I've talked about that before, and it was so interesting

265
00:14:45,640 --> 00:14:49,000
Speaker 16: to hear something behind it that in this fiscal year

266
00:14:49,400 --> 00:14:51,200
Speaker 16: there will be low double digit I think you said

267
00:14:51,240 --> 00:14:54,320
Speaker 16: billions of dollars in sovereign AI sales. But to the

268
00:14:54,400 --> 00:14:57,160
Speaker 16: lay person, what does that mean? It means deals with

269
00:14:57,240 --> 00:14:58,680
Speaker 16: specific governments, if so.

270
00:14:58,680 --> 00:15:01,680
Speaker 15: Were, it's not necessarily.

271
00:15:02,240 --> 00:15:08,840
Speaker 3: Sometimes it deals with a particular regional service provider that's

272
00:15:08,920 --> 00:15:11,960
Speaker 3: been funded by the government, and oftentimes that's the case

273
00:15:12,480 --> 00:15:14,920
Speaker 3: in a case of In the case of Japan, for example,

274
00:15:15,040 --> 00:15:22,960
Speaker 3: the Japanese government came out and offered UH subsidies of

275
00:15:23,440 --> 00:15:26,840
Speaker 3: a couple of billion dollars I think for several different

276
00:15:27,360 --> 00:15:31,800
Speaker 3: internet companies and telcos to be able to fund their

277
00:15:31,880 --> 00:15:37,200
Speaker 3: AI infrastructure. India has a sovereign AI initiative going and

278
00:15:37,240 --> 00:15:44,800
Speaker 3: they're building their AI infrastructure. Canada, the UK, France, Italy,

279
00:15:46,600 --> 00:15:50,560
Speaker 3: I'm missing somebody, Singapore, Malaysia, Uh.

280
00:15:50,840 --> 00:15:52,000
Speaker 15: You know a large.

281
00:15:51,760 --> 00:15:57,560
Speaker 3: Number of countries are subsidizing their regional data centers so

282
00:15:57,600 --> 00:16:01,680
Speaker 3: that they could become able to build out their AI infrastructure.

283
00:16:02,160 --> 00:16:08,560
Speaker 3: They recognize that their country's knowledge, their country's data. Digital

284
00:16:08,640 --> 00:16:12,760
Speaker 3: data is also their natural resource, not just the land

285
00:16:12,800 --> 00:16:15,360
Speaker 3: they're sitting on, not just the air above them. But

286
00:16:15,400 --> 00:16:19,400
Speaker 3: they realize now that their digital knowledge is part of

287
00:16:19,440 --> 00:16:23,920
Speaker 3: their natural and national resource, and they had to harvest

288
00:16:23,960 --> 00:16:28,840
Speaker 3: that and process that and transform it into their national

289
00:16:29,080 --> 00:16:30,320
Speaker 3: digital intelligence.

290
00:16:30,760 --> 00:16:33,520
Speaker 15: And so this is what we call sovereign AI.

291
00:16:33,560 --> 00:16:36,080
Speaker 3: You could imagine almost every single country in the world

292
00:16:36,480 --> 00:16:41,040
Speaker 3: will eventually recognize this and build out their AI infrastructure.

293
00:16:41,840 --> 00:16:44,560
Speaker 16: Jensen, you use the word resource, and that makes me

294
00:16:44,600 --> 00:16:47,520
Speaker 16: think about the energy requirements here. I think on the

295
00:16:47,560 --> 00:16:50,440
Speaker 16: cool you talk about how the next generation models will

296
00:16:50,440 --> 00:16:53,840
Speaker 16: have many orders of magnitude greater compute needs. But how

297
00:16:53,840 --> 00:16:56,600
Speaker 16: will the energy needs increase and what is the advantage

298
00:16:56,600 --> 00:17:00,120
Speaker 16: you feel in Vidia has in that sense.

299
00:17:01,080 --> 00:17:03,920
Speaker 3: Well, the most important thing that we do is increase

300
00:17:04,040 --> 00:17:08,080
Speaker 3: the performance of and increase the performance and efficiency of

301
00:17:08,119 --> 00:17:12,760
Speaker 3: our next generation. So Blackwell is many times more performance

302
00:17:13,359 --> 00:17:17,040
Speaker 3: than Hopper at the same level of power used, and

303
00:17:17,119 --> 00:17:21,359
Speaker 3: so that's energy efficiency, more performance with the same amount

304
00:17:21,359 --> 00:17:24,480
Speaker 3: of power or same performance at a lower power And

305
00:17:24,640 --> 00:17:25,520
Speaker 3: that's number one.

306
00:17:26,000 --> 00:17:28,800
Speaker 15: And the second is using LUCA cooling.

307
00:17:29,000 --> 00:17:32,040
Speaker 3: We support air, we support air cooling, we support liqual cooling,

308
00:17:32,119 --> 00:17:34,399
Speaker 3: but liqual cooling is a lot more energy efficient, and

309
00:17:34,480 --> 00:17:37,679
Speaker 3: so the combination of all of that, you're going to

310
00:17:37,680 --> 00:17:41,280
Speaker 3: get a pretty large, pretty large step up. But the

311
00:17:41,320 --> 00:17:44,240
Speaker 3: important thing to also realize is that AI doesn't really

312
00:17:44,280 --> 00:17:47,320
Speaker 3: care where it goes to school, and so increasingly we're

313
00:17:47,320 --> 00:17:51,199
Speaker 3: going to see AI be trained somewhere else, have that

314
00:17:51,280 --> 00:17:54,600
Speaker 3: model come back and be used near the population, or

315
00:17:54,880 --> 00:17:57,639
Speaker 3: even running on your PC or your phone.

316
00:17:57,680 --> 00:17:58,240
Speaker 15: And so we're going.

317
00:17:58,240 --> 00:18:01,000
Speaker 3: To train large models, but the goal is not to

318
00:18:01,119 --> 00:18:03,240
Speaker 3: run the large models necessarily all the time.

319
00:18:03,359 --> 00:18:05,160
Speaker 15: You can, you can surely do that for some.

320
00:18:05,119 --> 00:18:09,520
Speaker 3: Of the premium services and the very high value AIS,

321
00:18:10,240 --> 00:18:12,840
Speaker 3: but it's very likely that these large models would then

322
00:18:12,920 --> 00:18:16,360
Speaker 3: help to train and teach smaller models, and what we'll

323
00:18:16,400 --> 00:18:19,760
Speaker 3: end up doing is have one large a few large

324
00:18:19,760 --> 00:18:22,800
Speaker 3: models that are able to train a whole bunch of

325
00:18:22,800 --> 00:18:23,639
Speaker 3: small models.

326
00:18:23,400 --> 00:18:24,400
Speaker 15: And they run everywhere.

327
00:18:24,760 --> 00:18:27,840
Speaker 2: That was the CEO of Nvidia, Jensen Wong, speaking with

328
00:18:27,840 --> 00:18:31,320
Speaker 2: Bloomberg's Ed Ludlow following the company's earnings. You can catch

329
00:18:31,359 --> 00:18:35,040
Speaker 2: the entire interview on the Bloomberg Talks podcast. Subscribe to

330
00:18:35,080 --> 00:18:38,600
Speaker 2: download this and all our high profile conversations on Apple,

331
00:18:38,960 --> 00:18:42,480
Speaker 2: Spotify or anywhere else you get your podcasts and for

332
00:18:42,560 --> 00:18:45,280
Speaker 2: more and what we've heard from Nvidia and the stock reaction.

333
00:18:45,359 --> 00:18:48,800
Speaker 2: We are joined now by Dan Ives, senior equity research

334
00:18:48,880 --> 00:18:52,159
Speaker 2: analysts at web Bush Securities. Dan, good morning. I know

335
00:18:52,200 --> 00:18:54,920
Speaker 2: you've been out front for quite some time as one

336
00:18:54,960 --> 00:18:57,840
Speaker 2: of the leading bulls on the what you've been calling

337
00:18:57,880 --> 00:19:02,480
Speaker 2: the AI tech revolutionist industrial revolution, I think is how

338
00:19:02,640 --> 00:19:06,120
Speaker 2: you've termed it. After what we heard from the CEO,

339
00:19:06,480 --> 00:19:09,680
Speaker 2: Jensen Wong, do you have any reservations now?

340
00:19:10,640 --> 00:19:13,520
Speaker 17: I mean, Nata, I'm more bullish today than I probably

341
00:19:13,640 --> 00:19:17,000
Speaker 17: was twenty four hours ago, becure, and I actually in

342
00:19:17,040 --> 00:19:20,800
Speaker 17: the Fox should be up, not down, but because of

343
00:19:20,840 --> 00:19:24,239
Speaker 17: the underlying demand. I mean, you know Jensen talked out

344
00:19:24,280 --> 00:19:27,520
Speaker 17: with the little of the Ludwell interview. That's the key here,

345
00:19:27,960 --> 00:19:32,240
Speaker 17: demand surgeon on the enterprise, the outlook for next quarter,

346
00:19:32,920 --> 00:19:35,400
Speaker 17: maybe on the hair and miss whispers. I think it's

347
00:19:35,440 --> 00:19:38,760
Speaker 17: conservative and they're going to continue to beat that number.

348
00:19:38,920 --> 00:19:42,960
Speaker 17: Blackwell issues I think are a lot so in my opinion,

349
00:19:43,760 --> 00:19:49,160
Speaker 17: this is actually an affirmation of the bullish AI pieces.

350
00:19:49,840 --> 00:19:54,040
Speaker 2: Does Nvidia need to be more specific though on where

351
00:19:54,080 --> 00:19:57,920
Speaker 2: that demand is coming from and how much demand it's

352
00:19:58,000 --> 00:19:59,160
Speaker 2: expecting going forward.

353
00:20:00,080 --> 00:20:02,720
Speaker 17: Look, I think the numbers speak to themselves. I mean,

354
00:20:02,720 --> 00:20:06,080
Speaker 17: this is his store in terms of what we're seeing

355
00:20:06,119 --> 00:20:10,359
Speaker 17: from a demand perspective. And I think the conference call

356
00:20:10,480 --> 00:20:15,760
Speaker 17: last night solidified this is not stub ordering, this is

357
00:20:15,800 --> 00:20:20,160
Speaker 17: not hype. This is a fourth and ducal revolution that's

358
00:20:20,240 --> 00:20:23,960
Speaker 17: playing out right now, being led by godfather of AI,

359
00:20:24,680 --> 00:20:25,760
Speaker 17: Jensen and Nvidios.

360
00:20:27,400 --> 00:20:31,400
Speaker 2: He said that he's expecting billions of dollars in revenue

361
00:20:31,600 --> 00:20:36,000
Speaker 2: from the Blackwell chips. A lot of analysts on the

362
00:20:36,040 --> 00:20:39,720
Speaker 2: call were looking for more specificity on that as well.

363
00:20:40,160 --> 00:20:43,840
Speaker 2: How much are you expecting that the Blackwell chips could

364
00:20:43,840 --> 00:20:46,720
Speaker 2: generate in terms of monetizing AI.

365
00:20:47,680 --> 00:20:52,040
Speaker 17: From everything we're seeing, its tens of billions, not billions.

366
00:20:52,119 --> 00:20:56,840
Speaker 17: And who Look, Jensen is a He's a Grand Master

367
00:20:57,080 --> 00:21:02,000
Speaker 17: World Series poker player. He's not going to reveal his playbook,

368
00:21:02,040 --> 00:21:05,119
Speaker 17: nor should he. But when you and I think this

369
00:21:05,240 --> 00:21:08,880
Speaker 17: is important for the rest of tech, there's a multiplier.

370
00:21:09,119 --> 00:21:12,280
Speaker 17: For every dollar spend in videoship, we've eaten ten dollars

371
00:21:12,320 --> 00:21:15,320
Speaker 17: for the rest of tech. I believe tech should be

372
00:21:15,440 --> 00:21:20,680
Speaker 17: up today relative to everything we heard. That I think

373
00:21:20,760 --> 00:21:22,879
Speaker 17: keeps his tech well market going higher.

374
00:21:24,040 --> 00:21:29,000
Speaker 2: Are you going to be reducing your outlook for where

375
00:21:29,280 --> 00:21:32,439
Speaker 2: the revenue goes as far as not just in Vidio,

376
00:21:32,680 --> 00:21:35,720
Speaker 2: but other AI players moving forward. Now that we have

377
00:21:36,119 --> 00:21:43,639
Speaker 2: gotten something of a less than powerhouse outlook from Nvidia

378
00:21:43,720 --> 00:21:45,879
Speaker 2: this time around, Yeah, and that.

379
00:21:45,960 --> 00:21:50,000
Speaker 17: Would be the initial nature. But I think, I mean,

380
00:21:50,040 --> 00:21:53,720
Speaker 17: you know, we talked on your show after Apple's Worldwide

381
00:21:53,760 --> 00:21:57,880
Speaker 17: Developer Conference. At that point, the stock was one ninety,

382
00:21:58,520 --> 00:22:01,560
Speaker 17: sentiment was negative. Here it is two and a half

383
00:22:01,600 --> 00:22:05,280
Speaker 17: months later, stocks two twenty six, and the sentiments chem drastically.

384
00:22:05,880 --> 00:22:08,520
Speaker 17: I think it's going to be a similar dynamic within

385
00:22:08,720 --> 00:22:13,120
Speaker 17: Vidio over the coming days and weeks. But again, the bears,

386
00:22:13,440 --> 00:22:16,760
Speaker 17: they've been negative on this for the last year and

387
00:22:16,800 --> 00:22:19,520
Speaker 17: it's a historic run, and I think they'll continue to

388
00:22:19,520 --> 00:22:22,240
Speaker 17: be negative. Trying to grasp the straws.

389
00:22:22,640 --> 00:22:25,080
Speaker 2: How important is it going to be for Nvidia to

390
00:22:25,160 --> 00:22:29,679
Speaker 2: grow its customer base beyond the hyperscalers, beyond companies like

391
00:22:29,880 --> 00:22:33,119
Speaker 2: meta platforms, to get into, you know, something that Ed

392
00:22:33,200 --> 00:22:37,320
Speaker 2: Ludlow has been focusing on pretty closely, sovereign AI government,

393
00:22:37,480 --> 00:22:40,520
Speaker 2: something that Jensen Wang himself has said that he's going

394
00:22:40,600 --> 00:22:44,040
Speaker 2: to be focusing on, you know, as early as February.

395
00:22:44,800 --> 00:22:50,639
Speaker 17: Yeah, look, and I think twenty maybe thirty percent of

396
00:22:50,720 --> 00:22:54,359
Speaker 17: what's called a trillion dollars of AI cap ax will

397
00:22:54,400 --> 00:22:56,600
Speaker 17: be the tech players. And you've already seen that all

398
00:22:56,680 --> 00:23:00,320
Speaker 17: the story for Meta, Theamazon, all the Hyperscaros do books,

399
00:23:01,200 --> 00:23:05,879
Speaker 17: but government, the rest of enterprise, that's what's still on

400
00:23:05,960 --> 00:23:11,239
Speaker 17: the comp We only have three percent of enterprises that

401
00:23:11,320 --> 00:23:13,920
Speaker 17: have actually even started to go down the AI journey.

402
00:23:14,440 --> 00:23:17,399
Speaker 17: That's why to get out the popcorn moment. This is

403
00:23:17,560 --> 00:23:20,680
Speaker 17: lebron in high school before we went to the NBA.

404
00:23:21,840 --> 00:23:23,880
Speaker 2: But is our tech company is going to be able

405
00:23:23,920 --> 00:23:26,480
Speaker 2: to sustain the kind of spending that they've been doing

406
00:23:27,280 --> 00:23:30,040
Speaker 2: to scale up their AI play?

407
00:23:30,600 --> 00:23:32,680
Speaker 17: Well, it's really the ROI. And I think what we're

408
00:23:32,680 --> 00:23:37,119
Speaker 17: seeing what use cases and talunteer service now you know,

409
00:23:37,119 --> 00:23:39,919
Speaker 17: I think Salesforce and others, is that it's really just

410
00:23:40,000 --> 00:23:42,280
Speaker 17: started to the rois there. And I there's the big

411
00:23:42,320 --> 00:23:45,359
Speaker 17: thing that Jensen talked about. They are seeing the ROI.

412
00:23:46,480 --> 00:23:49,879
Speaker 17: And as you come to see the ROI, that's going

413
00:23:49,960 --> 00:23:52,359
Speaker 17: to be the next step. And this season not even

414
00:23:53,040 --> 00:23:58,040
Speaker 17: just started Apple with iPhone sixteen, which would be the

415
00:23:58,080 --> 00:23:59,440
Speaker 17: consumer AI revolution.

416
00:24:01,359 --> 00:24:04,480
Speaker 2: Are you concerned at all about the delays that we've

417
00:24:04,520 --> 00:24:08,720
Speaker 2: seen in the next generation Blackwell chips and the trouble

418
00:24:08,760 --> 00:24:13,120
Speaker 2: that Jensen Wang has acknowledged that he's had getting them

419
00:24:13,200 --> 00:24:14,639
Speaker 2: to perform the way they need to.

420
00:24:16,119 --> 00:24:19,800
Speaker 17: I think that they actually put those concerns to rest

421
00:24:19,920 --> 00:24:22,680
Speaker 17: last night. I mean they were concerned that that could

422
00:24:22,680 --> 00:24:25,879
Speaker 17: be called one two, three billion and moved back, and

423
00:24:25,920 --> 00:24:28,320
Speaker 17: they actually put those concerns to rest. So I actually

424
00:24:28,359 --> 00:24:32,919
Speaker 17: think black Well issues put the rest outlook robust, and

425
00:24:32,960 --> 00:24:35,679
Speaker 17: then when you look over all at these numbers, I

426
00:24:35,720 --> 00:24:40,920
Speaker 17: mean this should be criticizing Djokovic for losing one game

427
00:24:41,080 --> 00:24:42,640
Speaker 17: of one set in the US.

428
00:24:42,520 --> 00:24:46,080
Speaker 2: Open, got about a minute left. Dan, I think one

429
00:24:46,119 --> 00:24:48,679
Speaker 2: of the last times we spoke, you said that it

430
00:24:48,720 --> 00:24:52,040
Speaker 2: was about nine pm in an Ai party. That's going

431
00:24:52,119 --> 00:24:55,000
Speaker 2: into the early morning hours. What time is it for

432
00:24:55,040 --> 00:24:58,040
Speaker 2: you in the Ai story now?

433
00:24:58,640 --> 00:25:01,720
Speaker 17: I mean, especially in text run out from then, I'd

434
00:25:01,760 --> 00:25:06,000
Speaker 17: say nine to thirty ten pm to where this is filk.

435
00:25:06,119 --> 00:25:08,040
Speaker 17: Is there going to be glass in the dance floor?

436
00:25:08,160 --> 00:25:10,240
Speaker 17: Does the music stop? Every once in a while we

437
00:25:10,280 --> 00:25:13,640
Speaker 17: saw Tokyo Black Monday. Yeah, this is going to four

438
00:25:13,680 --> 00:25:16,360
Speaker 17: am in terms of the party, and it's ten pm

439
00:25:16,640 --> 00:25:17,160
Speaker 17: not either.

440
00:25:17,400 --> 00:25:20,280
Speaker 2: This is Bloomberg day Break Today, your morning brief on

441
00:25:20,359 --> 00:25:23,880
Speaker 2: the stories making news from Wall Street to Washington and beyond.

442
00:25:24,160 --> 00:25:26,960
Speaker 1: Look for us on your podcast feed at six am

443
00:25:27,000 --> 00:25:30,679
Speaker 1: Eastern each morning, on Apple, Spotify, and anywhere else you

444
00:25:30,760 --> 00:25:31,960
Speaker 1: get your podcasts.

445
00:25:32,040 --> 00:25:34,720
Speaker 2: You can also listen live each morning starting at five

446
00:25:34,760 --> 00:25:37,359
Speaker 2: am Wall Street Time on Bloomberg eleven three to zero

447
00:25:37,440 --> 00:25:40,840
Speaker 2: in New York, Bloomberg ninety nine one in Washington, Bloomberg

448
00:25:40,920 --> 00:25:43,600
Speaker 2: one oh six to one in Boston, and Bloomberg ninety

449
00:25:43,600 --> 00:25:45,000
Speaker 2: sixty in San Francisco.

450
00:25:45,400 --> 00:25:48,520
Speaker 1: Our flagship New York station is also available on your

451
00:25:48,600 --> 00:25:54,040
Speaker 1: Amazon Alexa devices. Just say Alexa Play Bloomberg eleven thirty plus.

452
00:25:54,040 --> 00:25:57,440
Speaker 2: Listen coast to coast on the Bloomberg Business app, SERRIUSXM,

453
00:25:57,600 --> 00:26:01,840
Speaker 2: the iHeartRadio app, and on Bloomberg. I'm Nathan Hager.

454
00:26:01,640 --> 00:26:02,800
Speaker 15: And I'm Karen Moscow.

455
00:26:03,000 --> 00:26:05,760
Speaker 1: Join us again tomorrow morning for all the news you

456
00:26:05,880 --> 00:26:09,080
Speaker 1: need to start your day right here on Bloomberg Daybreak