1
00:00:02,480 --> 00:00:13,160
Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is a

2
00:00:13,200 --> 00:00:16,960
Speaker 1: lie from coast to coast with Caroline Hide in New

3
00:00:17,040 --> 00:00:19,560
Speaker 1: York and Ed Lovelow in San Francisco.

4
00:00:21,840 --> 00:00:25,320
Speaker 2: This is a Bloomberg Tech. Coming up, talks continue to

5
00:00:25,360 --> 00:00:29,160
Speaker 2: try and end the US government shutdown, sending airline stocks rallying.

6
00:00:29,480 --> 00:00:32,159
Speaker 2: We'll discuss how AI could play a role in the

7
00:00:32,159 --> 00:00:35,920
Speaker 2: future of travel. Plus, tech and media earnings continue with

8
00:00:36,000 --> 00:00:39,160
Speaker 2: corew Even paramount on the docket after the closing bell,

9
00:00:39,840 --> 00:00:42,600
Speaker 2: and we'll speak with Matt Mayhan, mayor of San Jose

10
00:00:42,800 --> 00:00:46,120
Speaker 2: about the city's growing AI infrastructure and its latest data

11
00:00:46,159 --> 00:00:50,199
Speaker 2: center initiative. First, so check on the market, starting with

12
00:00:50,240 --> 00:00:52,520
Speaker 2: the bigger picture and look at that. We are seeing

13
00:00:52,600 --> 00:00:56,400
Speaker 2: the Nasdaq one hundred surge along with other major indices.

14
00:00:56,760 --> 00:00:58,640
Speaker 2: This is the US Senate advanced as a plan to

15
00:00:58,800 --> 00:01:02,120
Speaker 2: end the longest ever government shutdown. There has gone bid

16
00:01:02,200 --> 00:01:05,479
Speaker 2: lifting tech shares, really driving the rally in equities after

17
00:01:05,520 --> 00:01:09,039
Speaker 2: the tech sector had been hit the hardest in recent days.

18
00:01:09,840 --> 00:01:11,760
Speaker 2: Also coming up, we're going to discuss what to expect

19
00:01:11,760 --> 00:01:14,800
Speaker 2: from tech and media earnings throughout the hour. Core Weaves

20
00:01:14,880 --> 00:01:18,680
Speaker 2: results are expected to raise issues about AI spending after

21
00:01:18,880 --> 00:01:22,160
Speaker 2: last week's sell off. Coryve up one point two percent

22
00:01:22,280 --> 00:01:24,880
Speaker 2: right now, This after a week where was down twenty

23
00:01:25,080 --> 00:01:27,520
Speaker 2: two percent. This is also on the heels of others.

24
00:01:27,560 --> 00:01:31,039
Speaker 2: Spending by tech companies like Meta and Microsoft also paramounts

25
00:01:31,040 --> 00:01:33,840
Speaker 2: guidance down about three tenths of one percent. Ahead of earnings,

26
00:01:33,840 --> 00:01:37,119
Speaker 2: they're expected to report higher revenue and profit. Investors also

27
00:01:37,280 --> 00:01:38,679
Speaker 2: are going to be on the watch for more details

28
00:01:38,680 --> 00:01:41,520
Speaker 2: on the company's reported effort to buy Warner Brothers Discovery

29
00:01:41,600 --> 00:01:44,280
Speaker 2: spending a lot of money too buying up those rights

30
00:01:44,280 --> 00:01:47,240
Speaker 2: to UFC, and that big deal with the Duffer Brothers.

31
00:01:47,560 --> 00:01:47,720
Speaker 3: Well.

32
00:01:47,760 --> 00:01:50,760
Speaker 2: A group of eight Democrats on Sunday broke the rest

33
00:01:50,840 --> 00:01:53,640
Speaker 2: of their party to vote with Republicans to advance a

34
00:01:53,680 --> 00:01:56,720
Speaker 2: bill to reopen the government on the shutdown's fortieth day.

35
00:01:57,040 --> 00:02:00,640
Speaker 2: Bloomberg's Tyler Kendall joins us out of Washington, DC for more. Tyler,

36
00:02:00,720 --> 00:02:02,480
Speaker 2: tell us where we are in the discussion. Where do

37
00:02:02,560 --> 00:02:04,640
Speaker 2: things stand with the Senate back today?

38
00:02:06,040 --> 00:02:06,240
Speaker 4: Yeah?

39
00:02:06,240 --> 00:02:08,840
Speaker 5: I hey, Tim, So the Senate advanced this legislation on

40
00:02:08,880 --> 00:02:11,120
Speaker 5: a key procedural vote, but it still has to go

41
00:02:11,200 --> 00:02:13,519
Speaker 5: up to debate and then get a final floor vote

42
00:02:13,520 --> 00:02:17,040
Speaker 5: on the Senate floor, and importantly, any one senator could

43
00:02:17,080 --> 00:02:19,239
Speaker 5: tie up that process. We have our eyes on Senator

44
00:02:19,360 --> 00:02:22,320
Speaker 5: Ran Paul, a Republican from Kentucky. He voted against this

45
00:02:22,480 --> 00:02:26,760
Speaker 5: legislation and could ultimately delay it. However, the broad understanding here,

46
00:02:26,880 --> 00:02:29,720
Speaker 5: we're expecting this legislation to advance out of the Upper

47
00:02:29,800 --> 00:02:32,000
Speaker 5: Chamber and then go to the House later in the week.

48
00:02:32,120 --> 00:02:33,960
Speaker 5: Once the past of the Senate, there are thirty six

49
00:02:34,040 --> 00:02:37,680
Speaker 5: hours for House lawmakers to get back to Washington and vote.

50
00:02:37,680 --> 00:02:39,359
Speaker 5: But we have to look at what's actually in this

51
00:02:39,520 --> 00:02:42,200
Speaker 5: legislation to see some of those pressure points that could

52
00:02:42,200 --> 00:02:45,040
Speaker 5: be building on how Speaker Mike Johnson. This bill would

53
00:02:45,080 --> 00:02:47,920
Speaker 5: fund the government through January thirtieth and then fund some

54
00:02:48,040 --> 00:02:50,520
Speaker 5: key agencies through the rest of the fiscal years. Some

55
00:02:50,639 --> 00:02:53,080
Speaker 5: hardline conservatives may not be happy with that because they

56
00:02:53,120 --> 00:02:56,640
Speaker 5: didn't get the chance to negotiate those longer spending bills.

57
00:02:56,880 --> 00:03:00,400
Speaker 5: This also importantly includes a reverse for mass firings federal

58
00:03:00,480 --> 00:03:04,000
Speaker 5: workers that started on October first, and shields against future

59
00:03:04,040 --> 00:03:07,239
Speaker 5: firings through at least January thirtieth. That of course, goes

60
00:03:07,280 --> 00:03:10,679
Speaker 5: against President Trump's key priority when it comes to reducing

61
00:03:10,680 --> 00:03:14,000
Speaker 5: the federal WORKFORCET, so that also might face some pushback

62
00:03:14,040 --> 00:03:16,440
Speaker 5: when House lawmakers get back to town. I'll say, I'm

63
00:03:16,480 --> 00:03:19,080
Speaker 5: keeping my eye on those moderate Democrats in the House,

64
00:03:19,160 --> 00:03:21,839
Speaker 5: how they could come over and join Republicans, because that's

65
00:03:21,840 --> 00:03:24,160
Speaker 5: what we really saw happen when it came to the Senate.

66
00:03:24,240 --> 00:03:26,840
Speaker 5: They were negotiating, of course, for an extension on those

67
00:03:26,840 --> 00:03:30,440
Speaker 5: Affordable Care Act premium subsidies. The Senate wasn't able to

68
00:03:30,480 --> 00:03:32,840
Speaker 5: get a deal in this legislation, but they were able

69
00:03:32,880 --> 00:03:35,720
Speaker 5: to secure a promise on a vote for an extension

70
00:03:36,000 --> 00:03:38,040
Speaker 5: down the line. We're expecting that to happen by the

71
00:03:38,080 --> 00:03:40,800
Speaker 5: second week of December. See if how Speaker Mike Johnson

72
00:03:40,840 --> 00:03:43,640
Speaker 5: puts anything similar on the floor. At this point, we

73
00:03:43,680 --> 00:03:46,280
Speaker 5: haven't gotten in any indications, but I'd expect some House

74
00:03:46,280 --> 00:03:47,440
Speaker 5: Democrats to push for.

75
00:03:47,360 --> 00:03:47,880
Speaker 3: It, all right.

76
00:03:47,920 --> 00:03:51,600
Speaker 2: Bloomberg's Tyler Kendall keeping it on everything happening out of Washington, DC.

77
00:03:51,760 --> 00:03:54,840
Speaker 2: Thanks so much for that, Tyler well shares of major

78
00:03:54,840 --> 00:03:57,680
Speaker 2: airlines rallying as a potential and to the government shut

79
00:03:57,720 --> 00:04:01,200
Speaker 2: down nears. That's despite one hundred have canceled flights over

80
00:04:01,240 --> 00:04:03,480
Speaker 2: the weekend due to weather and the lack of air

81
00:04:03,520 --> 00:04:07,480
Speaker 2: traffic controllers and President Trump just now weighing in moments

82
00:04:07,480 --> 00:04:11,400
Speaker 2: ago on true social saying, quote, all air traffic controllers

83
00:04:11,560 --> 00:04:15,119
Speaker 2: must get back to work now. Anyone who doesn't will

84
00:04:15,120 --> 00:04:19,600
Speaker 2: be substantially docked. Nancy Shue leads agent for US at Salesforce,

85
00:04:19,640 --> 00:04:22,000
Speaker 2: and joins us now to talk about how AI might

86
00:04:22,000 --> 00:04:25,680
Speaker 2: actually help and be helping in the travel sector. Nancy,

87
00:04:25,680 --> 00:04:28,200
Speaker 2: good to have you with us from our San Francisco studio.

88
00:04:28,440 --> 00:04:29,200
Speaker 3: I got to tell you a.

89
00:04:29,200 --> 00:04:32,000
Speaker 2: Lot of my colleagues, a lot of friends had their

90
00:04:32,080 --> 00:04:34,839
Speaker 2: trips canceled or disrupted over the weekend. It doesn't seem

91
00:04:34,880 --> 00:04:38,800
Speaker 2: like anything could actually help right now. Accept actual air

92
00:04:38,839 --> 00:04:42,359
Speaker 2: traffic controllers and actual TSA agents showing up to work.

93
00:04:44,200 --> 00:04:47,560
Speaker 6: Tim, thanks so much for having me. We are seeing

94
00:04:47,560 --> 00:04:50,800
Speaker 6: with the evolving situation right now at the FAA through

95
00:04:50,839 --> 00:04:54,920
Speaker 6: our own agent platform, Agent Force, that it's really important

96
00:04:54,920 --> 00:04:59,080
Speaker 6: for companies to have agentic solutions and able in order

97
00:04:59,120 --> 00:05:02,040
Speaker 6: to serve their customs daring this very critical time where

98
00:05:02,040 --> 00:05:05,040
Speaker 6: we're seeing a surge in the system. As an example,

99
00:05:05,279 --> 00:05:08,720
Speaker 6: at Agent Force right now, we work closely with Heathrow.

100
00:05:08,880 --> 00:05:13,440
Speaker 6: Heathrow has more than eighty million passengers that walk through

101
00:05:13,480 --> 00:05:17,120
Speaker 6: their airports every single year. And at Heathrow, you know

102
00:05:17,320 --> 00:05:20,000
Speaker 6: those passengers are walking in a four and four am

103
00:05:20,040 --> 00:05:22,400
Speaker 6: in the morning, it could be at noon where they're

104
00:05:22,400 --> 00:05:25,640
Speaker 6: looking for lost luggage, regardless of the time and day. No,

105
00:05:25,760 --> 00:05:28,279
Speaker 6: we have an agent with them called Haley that's helping

106
00:05:28,560 --> 00:05:32,360
Speaker 6: Heathrow passengers right now on the ground, using AI agents

107
00:05:32,400 --> 00:05:36,359
Speaker 6: to address their customer queries, really using that ability for

108
00:05:36,400 --> 00:05:39,880
Speaker 6: AI agents to surge capacity for these companies to build

109
00:05:39,960 --> 00:05:43,440
Speaker 6: more resilient solutions. And this is critical right now with

110
00:05:43,520 --> 00:05:46,960
Speaker 6: the FA situation that's breaking. Enabling our customers and all

111
00:05:47,320 --> 00:05:49,799
Speaker 6: the companies that are using AI agents to flex film

112
00:05:49,800 --> 00:05:52,400
Speaker 6: a bit of capacity and really better serve those travelers

113
00:05:52,520 --> 00:05:53,520
Speaker 6: that are on the road today.

114
00:05:53,720 --> 00:05:56,159
Speaker 2: Well, I mentioned the President's post on social media just

115
00:05:56,240 --> 00:05:58,760
Speaker 2: in the last hour or so. The post continues to

116
00:05:58,800 --> 00:06:00,960
Speaker 2: say that if if you want to leave service in

117
00:06:00,960 --> 00:06:04,800
Speaker 2: the near future, these are people who are not showing.

118
00:06:04,560 --> 00:06:05,520
Speaker 3: Up to work, he says.

119
00:06:05,760 --> 00:06:07,960
Speaker 2: He says, you will be quickly replaced by true patriots

120
00:06:07,960 --> 00:06:09,680
Speaker 2: who will do a better job on the brand new,

121
00:06:09,720 --> 00:06:11,560
Speaker 2: state of the art equipment, the best in the world

122
00:06:11,760 --> 00:06:14,400
Speaker 2: that we are in the process of ordering that new equipment.

123
00:06:14,440 --> 00:06:16,960
Speaker 2: It's come up fairly often in recent months when talking

124
00:06:16,960 --> 00:06:19,960
Speaker 2: about the challenges at air traffic control and for air

125
00:06:19,960 --> 00:06:23,520
Speaker 2: traffic controllers here in the US, does Salesforce have any

126
00:06:23,600 --> 00:06:26,159
Speaker 2: role in the new air traffic control equipment that is

127
00:06:26,240 --> 00:06:28,680
Speaker 2: being ordered, whether it's software or something else.

128
00:06:30,320 --> 00:06:33,400
Speaker 6: What I can share, Tim, is that we have a

129
00:06:33,400 --> 00:06:37,159
Speaker 6: brand new initiative Mission Force where we're working with national

130
00:06:37,160 --> 00:06:39,680
Speaker 6: security as well as the US government as well as

131
00:06:39,680 --> 00:06:43,919
Speaker 6: allied governments to best support them, using technology and bringing

132
00:06:43,920 --> 00:06:47,800
Speaker 6: them as modern solutions, including RAI to help support national security.

133
00:06:47,839 --> 00:06:50,680
Speaker 2: Today, you've got a great view on the capabilities not

134
00:06:50,839 --> 00:06:53,000
Speaker 2: just now but in the coming years when it comes

135
00:06:53,040 --> 00:06:57,000
Speaker 2: to this technology within our lifetimes. Do you think AI

136
00:06:57,120 --> 00:06:59,240
Speaker 2: could replace air traffic controllers?

137
00:07:02,520 --> 00:07:06,000
Speaker 6: Tim, We are very excited about the vision of enabling

138
00:07:06,080 --> 00:07:09,560
Speaker 6: our customers to be successful using Agent Force, our AI

139
00:07:09,560 --> 00:07:13,880
Speaker 6: agent platform, deploying agents in the travel industry, for example,

140
00:07:13,880 --> 00:07:18,840
Speaker 6: with customers like Engine Heathrows, Singapore Airlines, Thin Air. For US,

141
00:07:18,880 --> 00:07:22,360
Speaker 6: it's really about enabling those companies to work in a

142
00:07:22,400 --> 00:07:26,040
Speaker 6: way where their employees, their humans and AI are partnering

143
00:07:26,040 --> 00:07:28,920
Speaker 6: closely together to enable that to happen. I'll give you

144
00:07:29,000 --> 00:07:33,680
Speaker 6: a very concrete example, Singapore Airlines works closely with agent force. Today,

145
00:07:34,160 --> 00:07:37,400
Speaker 6: with Singapore Airlines, we have over three point five million

146
00:07:37,760 --> 00:07:41,480
Speaker 6: AI workflows that are being run today, and those workflows

147
00:07:41,520 --> 00:07:44,840
Speaker 6: are not actually directly with their customers, but actually servicing

148
00:07:44,880 --> 00:07:48,520
Speaker 6: the humans on the Singapore Airlines team working closely with

149
00:07:48,560 --> 00:07:51,680
Speaker 6: them in cases such as when their service representative is

150
00:07:51,720 --> 00:07:54,360
Speaker 6: helping a customer with a critical issue on the ground.

151
00:07:54,800 --> 00:07:58,480
Speaker 6: Our AI workflows are actually summarizing those cases so that

152
00:07:58,520 --> 00:08:02,960
Speaker 6: those companies, those reps can now better service their customers

153
00:08:03,000 --> 00:08:06,120
Speaker 6: in real time. We think that the future is very

154
00:08:06,160 --> 00:08:09,600
Speaker 6: much AI agents and humans working closely together.

155
00:08:10,000 --> 00:08:13,400
Speaker 2: Yeah, I certainly understand that from a customer service perspective, Nancy,

156
00:08:13,560 --> 00:08:17,880
Speaker 2: But from the perspective of this high stress decision making

157
00:08:17,920 --> 00:08:21,760
Speaker 2: that takes place in a control tower, is that something

158
00:08:21,760 --> 00:08:24,440
Speaker 2: that could be done by AI and then in the

159
00:08:24,440 --> 00:08:27,480
Speaker 2: future we could sidestep issues and avoid issues such as these.

160
00:08:30,480 --> 00:08:33,960
Speaker 6: AI is a critical part of building a resilient business.

161
00:08:34,040 --> 00:08:36,600
Speaker 6: And I think we're seeing this right now with this

162
00:08:36,920 --> 00:08:40,680
Speaker 6: FAA situation. And it's not just the FAA, right you know,

163
00:08:40,800 --> 00:08:43,920
Speaker 6: right now we're seeing volatility in every market and this

164
00:08:44,040 --> 00:08:47,080
Speaker 6: is not news to us. But what's really exciting, I

165
00:08:47,120 --> 00:08:50,240
Speaker 6: think is that AI agents are actually helping companies become

166
00:08:50,320 --> 00:08:54,679
Speaker 6: more resilient in these volatile markets, not only in travel

167
00:08:54,840 --> 00:08:57,240
Speaker 6: with the companies that I listed earlier, but also we

168
00:08:57,280 --> 00:09:00,520
Speaker 6: have companies like one eight hundred Accountant, right they see

169
00:09:00,559 --> 00:09:03,440
Speaker 6: massive surges during peak tax season and the types of

170
00:09:03,520 --> 00:09:07,280
Speaker 6: queries their customers are coming with help four and we're

171
00:09:07,320 --> 00:09:09,600
Speaker 6: able to, in the case of one eight hundred Accountant,

172
00:09:09,880 --> 00:09:12,520
Speaker 6: help them address more than ninety percent of those cases

173
00:09:12,720 --> 00:09:16,280
Speaker 6: autonomously and to end really serving their customers and ensuring

174
00:09:16,640 --> 00:09:19,080
Speaker 6: that when you do have surges in the system like

175
00:09:19,160 --> 00:09:22,280
Speaker 6: that or these black Swan events, AI agents can help

176
00:09:22,320 --> 00:09:25,199
Speaker 6: these customers be resilient and help them better serve their

177
00:09:25,200 --> 00:09:26,000
Speaker 6: own customers.

178
00:09:26,080 --> 00:09:30,680
Speaker 2: You've mentioned partnerships with Singapore Airlines London's Heathrow Airport, but

179
00:09:30,720 --> 00:09:34,200
Speaker 2: here in the United States do you have partnerships with

180
00:09:35,160 --> 00:09:39,640
Speaker 2: airports that where this technology actually could help in terms

181
00:09:39,679 --> 00:09:42,600
Speaker 2: of air traffic controllers, in terms of helping people who

182
00:09:42,640 --> 00:09:43,160
Speaker 2: are stranded.

183
00:09:43,200 --> 00:09:44,960
Speaker 3: I mean, we have colleagues who they were.

184
00:09:44,880 --> 00:09:46,439
Speaker 2: Told over the weekend that they wouldn't even be able

185
00:09:46,440 --> 00:09:48,480
Speaker 2: to find a flight until Wednesday. And certainly some of

186
00:09:48,520 --> 00:09:51,080
Speaker 2: that is on the airline, but the core of the

187
00:09:51,160 --> 00:09:54,679
Speaker 2: issue still has to do with those people not showing

188
00:09:54,800 --> 00:09:57,079
Speaker 2: up to work on the airport side and the air

189
00:09:57,080 --> 00:09:58,240
Speaker 2: traffic control side.

190
00:10:00,240 --> 00:10:04,520
Speaker 6: TIM, we have customers that we work closely with, like Engine.

191
00:10:04,600 --> 00:10:07,680
Speaker 6: Engine is one of the leading platforms right now that

192
00:10:07,800 --> 00:10:12,800
Speaker 6: is helping do travel management for companies. So it's across

193
00:10:12,880 --> 00:10:16,520
Speaker 6: not just airlines travel flight bookings, but also those hotel

194
00:10:16,559 --> 00:10:19,400
Speaker 6: bookings and those car rentals that are being impacted as

195
00:10:19,440 --> 00:10:22,520
Speaker 6: a result downstream. With a company like Engine, you know,

196
00:10:22,640 --> 00:10:25,880
Speaker 6: they're handling a large volume of customer queries here in

197
00:10:25,920 --> 00:10:30,440
Speaker 6: the US today and in those situations, we're today helping

198
00:10:30,480 --> 00:10:33,640
Speaker 6: them increase or decrease their average handling time by more

199
00:10:33,679 --> 00:10:37,560
Speaker 6: than fifteen percent, and over thirty percent of those complex

200
00:10:37,600 --> 00:10:39,520
Speaker 6: bookings that are happening end to end as well as

201
00:10:39,559 --> 00:10:42,680
Speaker 6: those case resolutions for their customers are being done autonomously

202
00:10:43,080 --> 00:10:46,160
Speaker 6: using agent Force agents, and the impact of that, TIM

203
00:10:46,280 --> 00:10:50,600
Speaker 6: is really helping a company like Engine surge their capacity

204
00:10:50,640 --> 00:10:53,439
Speaker 6: in this critical period so that they're able to flex

205
00:10:53,600 --> 00:10:56,199
Speaker 6: up and down depending on what their customers are needing.

206
00:10:56,200 --> 00:10:58,280
Speaker 6: And right now, of course, the flex is going up.

207
00:10:58,760 --> 00:11:02,200
Speaker 2: Nancy Schue, vice President of AI Product at Salesforce, thanks

208
00:11:02,240 --> 00:11:04,440
Speaker 2: so much for joining us. Today on Bloomberg Tech to

209
00:11:04,520 --> 00:11:07,480
Speaker 2: appreciate it Well. Coming up, we wait earnings from core

210
00:11:07,559 --> 00:11:10,040
Speaker 2: Weave and Paramount, both of these companies set to report

211
00:11:10,040 --> 00:11:10,920
Speaker 2: after the closing bell.

212
00:11:11,040 --> 00:11:11,520
Speaker 3: We've got a.

213
00:11:11,440 --> 00:11:30,680
Speaker 2: Preview what to expect next. This is Bloomberg Tech. Well,

214
00:11:30,760 --> 00:11:32,839
Speaker 2: let's take a look at Spotify shares. They've turned lower

215
00:11:32,880 --> 00:11:36,319
Speaker 2: amid an announcement out of TikTok, the social platform, teaming

216
00:11:36,400 --> 00:11:40,280
Speaker 2: up with iHeartMedia to create a new TikTok podcast network.

217
00:11:40,679 --> 00:11:43,160
Speaker 2: The deal will feature up to twenty five new podcasts

218
00:11:43,160 --> 00:11:46,160
Speaker 2: hosted by TikTok creators. This is the company looks to

219
00:11:46,160 --> 00:11:49,880
Speaker 2: help creators beyond the TikTok platforms. Spotify shares down about

220
00:11:49,880 --> 00:11:52,319
Speaker 2: one tenth of one percent, I Heeart Media shares down

221
00:11:52,360 --> 00:11:56,040
Speaker 2: about six point three percent. Well, Paramount guidance results do

222
00:11:56,080 --> 00:11:58,600
Speaker 2: add after the closing bell, with investors heavily focused on

223
00:11:58,640 --> 00:12:01,839
Speaker 2: a potential bid for Warner Brothers Discovery. Here with more

224
00:12:01,960 --> 00:12:05,960
Speaker 2: is Bloomberg's Hannah Miller, who covers Media Wow. David Ellison

225
00:12:05,960 --> 00:12:08,360
Speaker 2: has been very busy in his first few months over

226
00:12:08,400 --> 00:12:10,640
Speaker 2: at Paramount sky Dance. Hannah, I know there are a

227
00:12:10,640 --> 00:12:13,440
Speaker 2: lot of questions about the UFC purchase about the Duffer

228
00:12:13,480 --> 00:12:17,040
Speaker 2: Brothers deal, about the hiring of Barry Weiss, But is

229
00:12:17,440 --> 00:12:20,440
Speaker 2: the big question all about Warner Brothers Discovery and whether

230
00:12:20,520 --> 00:12:23,160
Speaker 2: some or all of those assets go to Paramount's guidance.

231
00:12:23,440 --> 00:12:27,400
Speaker 7: Yeah, investors want to hear any updates related to Paramounts

232
00:12:27,720 --> 00:12:31,480
Speaker 7: multiple bids to acquire Warner Brothers Discovery. So far, they've

233
00:12:31,480 --> 00:12:34,240
Speaker 7: been bidding too low. So we'll see what David Ellison

234
00:12:34,280 --> 00:12:36,920
Speaker 7: says today if he gives any insight into their strategy

235
00:12:36,960 --> 00:12:37,560
Speaker 7: going forward.

236
00:12:37,840 --> 00:12:41,840
Speaker 2: Are investors on board with him spending this much money?

237
00:12:42,200 --> 00:12:45,920
Speaker 7: You know, I think investors are surprised. Some are wondering,

238
00:12:46,000 --> 00:12:47,920
Speaker 7: you know, hey, why didn't you go for Warner Brothers

239
00:12:47,920 --> 00:12:49,840
Speaker 7: in the first place instead of Paramount? Might have been

240
00:12:49,880 --> 00:12:54,080
Speaker 7: less complicated, But you know, they want to see what

241
00:12:54,559 --> 00:12:57,400
Speaker 7: David Ellison has in store for Paramount. He has a

242
00:12:57,440 --> 00:13:01,320
Speaker 7: really tech forward approach. He's willing to spend lots of money, So,

243
00:13:01,720 --> 00:13:03,720
Speaker 7: you know, some in the industry are excited to see

244
00:13:03,720 --> 00:13:06,280
Speaker 7: what could happen if these two companies fell under the

245
00:13:06,320 --> 00:13:07,800
Speaker 7: same roof and ownership.

246
00:13:08,160 --> 00:13:11,640
Speaker 2: Bloomberg's Hannah Miller follow those results on Bloomberg TV and

247
00:13:11,720 --> 00:13:14,520
Speaker 2: Radio as soon as they come out. After the bell today. Well,

248
00:13:14,520 --> 00:13:16,840
Speaker 2: another company that we are watching, Core We've. Shares, the

249
00:13:16,840 --> 00:13:19,920
Speaker 2: cloud computing firm fell twenty two percent last week.

250
00:13:20,160 --> 00:13:23,000
Speaker 3: This emit a broader pullback in the AI trade.

251
00:13:23,200 --> 00:13:26,240
Speaker 2: Now investors are watching its results closely as concerns grow

252
00:13:26,520 --> 00:13:30,880
Speaker 2: over heavy spending by core Weave's customers. Bloomberg's Dina Bass

253
00:13:31,040 --> 00:13:33,920
Speaker 2: joins us now with more the twenty two percent decline

254
00:13:34,080 --> 00:13:36,840
Speaker 2: and shares last week. The concern about this idea of

255
00:13:36,880 --> 00:13:40,760
Speaker 2: some circular financing, the small number of customers that core

256
00:13:40,800 --> 00:13:44,200
Speaker 2: We've has that really account for a majority of its revenue.

257
00:13:44,600 --> 00:13:46,920
Speaker 2: What's the thing that investors are watching most closely for

258
00:13:46,960 --> 00:13:48,160
Speaker 2: with today's results.

259
00:13:47,800 --> 00:13:50,640
Speaker 4: Dina, As you said, it's the spending and what they

260
00:13:50,679 --> 00:13:53,040
Speaker 4: say about it. It's not just spending by Corewave's customers,

261
00:13:53,080 --> 00:13:55,280
Speaker 4: it's spending by corew weave itself and sort of the

262
00:13:55,320 --> 00:13:58,480
Speaker 4: debt financing, the debt that they're taking on to do that. Think,

263
00:13:58,559 --> 00:14:02,000
Speaker 4: you know, across the board some of these companies, investors

264
00:14:02,000 --> 00:14:04,840
Speaker 4: are sort of betwixt in between. They on the one hand,

265
00:14:04,880 --> 00:14:07,680
Speaker 4: they want to see spending because it's a solid demand signal.

266
00:14:07,760 --> 00:14:10,600
Speaker 4: If companies are spending to expand data centers, it means

267
00:14:10,600 --> 00:14:12,880
Speaker 4: that they think that they're getting more AI business in

268
00:14:12,960 --> 00:14:15,520
Speaker 4: the door. When they stop spending, investors are going to

269
00:14:15,600 --> 00:14:19,320
Speaker 4: worry that that's slowing down. On the other hand, investors

270
00:14:19,320 --> 00:14:22,320
Speaker 4: are also worried that all of that spending just costs

271
00:14:22,360 --> 00:14:24,400
Speaker 4: a lot of money and what's what's the return? When

272
00:14:24,400 --> 00:14:27,800
Speaker 4: do you start making that back? And so I think

273
00:14:27,960 --> 00:14:30,600
Speaker 4: for core We, there's going to be a you know,

274
00:14:31,040 --> 00:14:33,840
Speaker 4: look at what they're saying about demand signals, what they're

275
00:14:33,840 --> 00:14:37,240
Speaker 4: saying about deals that they've signed about you know, remaining

276
00:14:37,240 --> 00:14:40,120
Speaker 4: performance obligations, so with deals they've already booked and haven't

277
00:14:40,120 --> 00:14:43,040
Speaker 4: been able to fulfill, as well as what's going on

278
00:14:43,040 --> 00:14:44,960
Speaker 4: on the profit or in the case of core We,

279
00:14:45,400 --> 00:14:48,000
Speaker 4: the loss side, you know, in terms of what they're

280
00:14:48,000 --> 00:14:51,600
Speaker 4: spending to get to fulfill those those customer obligations.

281
00:14:51,960 --> 00:14:55,000
Speaker 2: Can core We've actually get everything it needs to build

282
00:14:55,000 --> 00:14:57,800
Speaker 2: the capacity or invest in the capacity that it thinks

283
00:14:57,840 --> 00:15:00,600
Speaker 2: it's customers will need. Can you get the check? Can

284
00:15:00,600 --> 00:15:03,080
Speaker 2: you get the electricity? Can it get the infrastructure?

285
00:15:04,120 --> 00:15:06,880
Speaker 4: Right now, no one is getting everything they need and

286
00:15:06,920 --> 00:15:12,080
Speaker 4: that's you know Corey, you open AI, Microsoft Meta, nobody

287
00:15:12,160 --> 00:15:14,320
Speaker 4: is getting as many chips as they want nobody is

288
00:15:14,320 --> 00:15:17,680
Speaker 4: getting as much power as they think they need. You know,

289
00:15:17,760 --> 00:15:22,240
Speaker 4: it's all coming online rapidly, but not rapidly enough based

290
00:15:22,280 --> 00:15:25,560
Speaker 4: on what these companies think the demand picture looks like.

291
00:15:26,400 --> 00:15:30,040
Speaker 2: Bloomberg's Dina Bass joins us now and Dina, thanks so

292
00:15:30,120 --> 00:15:32,360
Speaker 2: much for that update. A reminder, we will have those

293
00:15:32,440 --> 00:15:34,640
Speaker 2: numbers for you as soon as they break after the

294
00:15:34,640 --> 00:15:36,960
Speaker 2: bell on Bloomberg TV and a radio as well.

295
00:15:37,160 --> 00:15:37,240
Speaker 5: Well.

296
00:15:37,320 --> 00:15:39,280
Speaker 2: Let's put all of this spending into context of the

297
00:15:39,280 --> 00:15:42,120
Speaker 2: broader markets as well. With Hillary Frisch, Senior Research analysts

298
00:15:42,160 --> 00:15:45,520
Speaker 2: for Software and IT services at Clearbridge Investments, Healy, good

299
00:15:45,520 --> 00:15:47,160
Speaker 2: to have you on the program.

300
00:15:47,320 --> 00:15:47,920
Speaker 8: Thanks for having me.

301
00:15:47,960 --> 00:15:51,080
Speaker 2: The existential question that Dina was just talking about, when

302
00:15:51,120 --> 00:15:53,280
Speaker 2: is this going to pay off? It's not just with

303
00:15:53,360 --> 00:15:55,880
Speaker 2: Core Weave, it's not just with Microsoft, it's not just

304
00:15:55,920 --> 00:15:59,560
Speaker 2: with meta platforms. This is the existential question that every

305
00:15:59,600 --> 00:16:01,280
Speaker 2: investor asking themselves right now.

306
00:16:01,400 --> 00:16:02,320
Speaker 3: When will it pay off?

307
00:16:02,560 --> 00:16:04,000
Speaker 8: It's the next sistential question.

308
00:16:04,320 --> 00:16:09,120
Speaker 9: However, there's a lot of long range planning occurring at present.

309
00:16:09,160 --> 00:16:12,440
Speaker 9: The commitments that Opening Eye and these ecosystem partners are

310
00:16:12,440 --> 00:16:17,000
Speaker 9: making are stretched out over a very long term horizon,

311
00:16:17,520 --> 00:16:19,920
Speaker 9: and as Dina mentioned, I thought she summarized it will

312
00:16:21,320 --> 00:16:23,400
Speaker 9: nobody can get what they need yet, so it's going

313
00:16:23,440 --> 00:16:28,359
Speaker 9: to be an ongoing process of seeing allocations, seeing revenues,

314
00:16:28,400 --> 00:16:32,880
Speaker 9: seeing costs drop, seeing funding, seeing improvement in the across

315
00:16:32,880 --> 00:16:37,240
Speaker 9: the ecosystem, which will reinforce investor confidence in this.

316
00:16:37,520 --> 00:16:39,600
Speaker 8: I think there's a strong belief that.

317
00:16:39,520 --> 00:16:43,440
Speaker 9: There is ROI, but investors are paid to evaluate risks

318
00:16:43,520 --> 00:16:46,760
Speaker 9: as well as reward, and sometimes that pendulum shifts really

319
00:16:46,760 --> 00:16:49,520
Speaker 9: firm one direction. And say, in the case of an

320
00:16:49,520 --> 00:16:52,400
Speaker 9: oracle who, similar to core Weave, is supplying a lot

321
00:16:52,440 --> 00:16:55,160
Speaker 9: of this capacity, that stock had gotten back on Thursday

322
00:16:55,240 --> 00:16:56,120
Speaker 9: or Friday.

323
00:16:55,800 --> 00:16:58,680
Speaker 8: To close to where it had been before the big.

324
00:16:58,520 --> 00:17:00,920
Speaker 9: Announcement, the big announcement with o AI, and I think

325
00:17:00,920 --> 00:17:04,920
Speaker 9: investors are viewing what's good as bad until they get.

326
00:17:04,760 --> 00:17:06,200
Speaker 8: Some answers to these questions.

327
00:17:06,880 --> 00:17:08,840
Speaker 9: That said, I think there's more good to come, and

328
00:17:08,880 --> 00:17:13,840
Speaker 9: we'll get milestones along the way proving out the thesis

329
00:17:13,880 --> 00:17:15,520
Speaker 9: of the ecosystem and the returns.

330
00:17:15,680 --> 00:17:18,800
Speaker 2: That thesis of the ecosystem is really something that I'm

331
00:17:18,800 --> 00:17:22,080
Speaker 2: having trouble to visualizing right now. And no matter how

332
00:17:22,160 --> 00:17:25,639
Speaker 2: much Mark Zuckerberg tries to explain superintelligence to me, and

333
00:17:25,640 --> 00:17:29,720
Speaker 2: to shareholders of the company. I still don't understand what

334
00:17:29,800 --> 00:17:32,640
Speaker 2: that ultimate payoff looks like, not just for meta platforms,

335
00:17:32,680 --> 00:17:35,760
Speaker 2: but for the industry in general. Is this something that

336
00:17:36,080 --> 00:17:39,560
Speaker 2: will only pay off when there's mass unemployment so companies

337
00:17:39,600 --> 00:17:43,240
Speaker 2: don't have to actually pay for people because machines in

338
00:17:43,359 --> 00:17:45,119
Speaker 2: AI are doing the work.

339
00:17:45,440 --> 00:17:46,719
Speaker 3: Is it an increase in productivity?

340
00:17:46,760 --> 00:17:49,480
Speaker 2: We all keep our jobs, but we have these little friends,

341
00:17:49,480 --> 00:17:51,600
Speaker 2: with these little helpers who help us do it better.

342
00:17:51,640 --> 00:17:52,679
Speaker 3: What is it is?

343
00:17:52,880 --> 00:17:53,639
Speaker 8: Nobody knows.

344
00:17:53,760 --> 00:17:58,320
Speaker 9: I think it's a combination of increased productivity, increased revenue,

345
00:17:58,480 --> 00:18:02,400
Speaker 9: increased velocity of activity. At a minimum, AI should really

346
00:18:02,440 --> 00:18:07,440
Speaker 9: supercharge the individual today. The adoption has been very methodical

347
00:18:07,600 --> 00:18:11,119
Speaker 9: among typical commercial organizations because they have to worry about

348
00:18:11,160 --> 00:18:14,680
Speaker 9: security and orchestration and liability and all sorts of things.

349
00:18:14,720 --> 00:18:16,600
Speaker 9: And that's going to be the case. But we are

350
00:18:16,640 --> 00:18:20,480
Speaker 9: seeing the beginnings of real progress. We're seeing the technologies

351
00:18:20,480 --> 00:18:23,240
Speaker 9: in the marketplace start to mature. We're seeing the very

352
00:18:23,280 --> 00:18:30,439
Speaker 9: beginnings of commercial deployments in production beyond what Palanteer is doing,

353
00:18:30,880 --> 00:18:32,520
Speaker 9: and so I think we're seeing the beginnings of it.

354
00:18:32,560 --> 00:18:35,760
Speaker 9: But as we know, technology trends are overestimated in the

355
00:18:35,760 --> 00:18:38,680
Speaker 9: short term and underestimating the long term, and things move

356
00:18:38,760 --> 00:18:40,600
Speaker 9: very slowly until they start to move quickly.

357
00:18:40,640 --> 00:18:42,720
Speaker 8: And that's just a phenomenon of tech.

358
00:18:42,800 --> 00:18:44,440
Speaker 3: But are you using it at all with your job?

359
00:18:44,560 --> 00:18:44,840
Speaker 8: Sure?

360
00:18:45,080 --> 00:18:49,639
Speaker 9: How Yeah, we're using chat, GPT enterprise, our developers are

361
00:18:49,720 --> 00:18:53,199
Speaker 9: using cogend tools. But those things aren't easier because the

362
00:18:53,240 --> 00:18:55,119
Speaker 9: finished product doesn't have to be correct.

363
00:18:55,200 --> 00:18:57,200
Speaker 8: I can see what works for me and what doesn't.

364
00:18:57,240 --> 00:18:59,680
Speaker 9: But it's a very different phenomenon when you have something

365
00:19:00,040 --> 00:19:03,080
Speaker 9: tam are facing the broadly employee facing where it has

366
00:19:03,119 --> 00:19:04,560
Speaker 9: to work out of the box and it can't bring

367
00:19:04,600 --> 00:19:06,720
Speaker 9: your organization down in trims of liability.

368
00:19:06,880 --> 00:19:08,480
Speaker 8: So it's going to be a process for sure.

369
00:19:08,560 --> 00:19:08,720
Speaker 5: Yeah.

370
00:19:08,760 --> 00:19:10,359
Speaker 2: I was talking about this last week with somebody on

371
00:19:10,359 --> 00:19:13,840
Speaker 2: our program and they said, they're basically like an intern,

372
00:19:14,280 --> 00:19:18,199
Speaker 2: these these llms, you know, eager to help out, but

373
00:19:18,240 --> 00:19:20,480
Speaker 2: you really have to check the work to make sure

374
00:19:20,800 --> 00:19:23,480
Speaker 2: that it's something that can actually go to print them,

375
00:19:23,560 --> 00:19:26,800
Speaker 2: something that is actually accurate. Finally, I just want to

376
00:19:26,840 --> 00:19:29,800
Speaker 2: talk about the overall economic effects of this. A lot

377
00:19:29,840 --> 00:19:31,840
Speaker 2: of what we talk about when it comes to AI.

378
00:19:32,440 --> 00:19:36,480
Speaker 2: The real beneficiarias have been the major companies that we

379
00:19:36,520 --> 00:19:39,040
Speaker 2: talk about every day on Bloomberg Tech. But when will

380
00:19:39,040 --> 00:19:43,400
Speaker 2: we start to see these advancements actually affect the bottom

381
00:19:43,440 --> 00:19:46,959
Speaker 2: lines and the productivity of companies that are not necessarily

382
00:19:46,960 --> 00:19:47,680
Speaker 2: tech adjacent.

383
00:19:48,400 --> 00:19:51,119
Speaker 9: So such a great question, And it's funny because people

384
00:19:51,119 --> 00:19:53,840
Speaker 9: are attributing layoffs to AI, and I think in part

385
00:19:54,119 --> 00:19:56,040
Speaker 9: some of those layoffs may come from the need to

386
00:19:56,200 --> 00:20:00,560
Speaker 9: fund AI, but not directly from the productivity benefits from

387
00:20:00,640 --> 00:20:01,520
Speaker 9: AI yet.

388
00:20:01,640 --> 00:20:04,240
Speaker 2: So in other words, companies spending money on AI rather

389
00:20:04,320 --> 00:20:07,080
Speaker 2: than people, and that's why they're making investments there rather

390
00:20:07,160 --> 00:20:08,120
Speaker 2: than in human capital.

391
00:20:08,520 --> 00:20:11,359
Speaker 9: Well, they're spending on AI, but there are other things

392
00:20:11,400 --> 00:20:15,200
Speaker 9: behind the layoffs, meaning people that over hired during the pandemic,

393
00:20:15,320 --> 00:20:18,159
Speaker 9: especially in the realm of technology. Not all those hires

394
00:20:18,200 --> 00:20:19,879
Speaker 9: were of the quality that they wanted.

395
00:20:19,920 --> 00:20:21,520
Speaker 8: They had to pay a lot for those folks.

396
00:20:21,880 --> 00:20:24,920
Speaker 9: And also, companies have been been bracing for an economic

397
00:20:24,960 --> 00:20:27,879
Speaker 9: town turn. My industry contexts tell me everybody's bracing for

398
00:20:27,880 --> 00:20:31,120
Speaker 9: a downturn, concern over tariffs, inflation, etc. So I don't

399
00:20:31,119 --> 00:20:33,959
Speaker 9: think it's directly attributable. But to answer your question directly,

400
00:20:34,000 --> 00:20:37,159
Speaker 9: I think next year we start to see we're starting

401
00:20:37,160 --> 00:20:41,600
Speaker 9: to see production workloads going to production Today I think

402
00:20:41,800 --> 00:20:44,800
Speaker 9: companies will have better worked out the kinks by the

403
00:20:44,840 --> 00:20:47,040
Speaker 9: second half of next year. As I mentioned, the technologies

404
00:20:47,080 --> 00:20:50,280
Speaker 9: are maturing, the costs are plummeting, the rois will rise,

405
00:20:50,640 --> 00:20:54,120
Speaker 9: and I think into second half of next year are

406
00:20:54,200 --> 00:20:57,680
Speaker 9: really going to be the first signposts of broader benefits

407
00:20:57,960 --> 00:21:00,080
Speaker 9: from AI to the average commercial working say.

408
00:21:00,359 --> 00:21:03,919
Speaker 2: Hillary Frish, senior research analyst at Clearbridge Investments, thanks so

409
00:21:03,960 --> 00:21:04,720
Speaker 2: much for joining.

410
00:21:04,560 --> 00:21:05,560
Speaker 3: Us on Bloomberg Tech.

411
00:21:06,119 --> 00:21:08,720
Speaker 2: Well, coming up, GRAB takes the wheel, investing in a

412
00:21:08,880 --> 00:21:12,280
Speaker 2: remote driving startup. Speaking of driving, let's take a quick

413
00:21:12,280 --> 00:21:15,320
Speaker 2: look at Tesla shares. This shareholder is approving a one

414
00:21:15,520 --> 00:21:19,119
Speaker 2: trillion dollar pay package for Elon Musk last week on

415
00:21:19,160 --> 00:21:21,480
Speaker 2: the promise that he'll transition the company to focus on

416
00:21:21,520 --> 00:21:25,200
Speaker 2: AI and robotics. The company likely benefiting from the wider

417
00:21:25,320 --> 00:21:40,640
Speaker 2: risk on sentiment today too. This is Bloomberg Tech sign

418
00:21:40,680 --> 00:21:43,960
Speaker 2: out for Talking Tech. First up, Grab investing sixty million

419
00:21:44,000 --> 00:21:47,040
Speaker 2: dollars in remote driving service day, with the potential to

420
00:21:47,080 --> 00:21:48,879
Speaker 2: reach four hundred and ten million dollars.

421
00:21:49,240 --> 00:21:49,920
Speaker 3: Check this out.

422
00:21:50,080 --> 00:21:52,719
Speaker 2: They allows users to order a car, which is then

423
00:21:52,760 --> 00:21:55,320
Speaker 2: operated remotely and delivered to the customer.

424
00:21:55,640 --> 00:21:57,360
Speaker 3: The deal is expected to close.

425
00:21:57,400 --> 00:22:01,280
Speaker 2: In the fourth quarter plus, ta MC posted a sixteen

426
00:22:01,320 --> 00:22:04,320
Speaker 2: point nine percent rise in sales for the month of October.

427
00:22:04,600 --> 00:22:07,080
Speaker 2: That's the slowest pace for the chip makers ince February

428
00:22:07,080 --> 00:22:09,840
Speaker 2: of twenty twenty four. Still, the company on track to

429
00:22:09,840 --> 00:22:13,199
Speaker 2: meet average analyst estimates of sixteen percent sales in the

430
00:22:13,240 --> 00:22:17,520
Speaker 2: current quarter and in videas, Jensen Wong remains optimistic about

431
00:22:17,520 --> 00:22:21,760
Speaker 2: the AI demand, asking TSMC for more chip supplies. Speaking

432
00:22:21,760 --> 00:22:26,159
Speaker 2: to reporters in Taiwan, Wong said, quote, the business is

433
00:22:26,280 --> 00:22:31,160
Speaker 2: very strong and it's growing months by month, stronger and stronger.

434
00:22:39,280 --> 00:22:42,399
Speaker 2: Welcome back to Bloomberg Tech. Power constraints are slowing parts

435
00:22:42,440 --> 00:22:45,959
Speaker 2: of Silicon Valley's AI expansion, with two proposed data centers

436
00:22:45,960 --> 00:22:50,359
Speaker 2: in Santa Clara facing potential delays due to limited utility capacity.

437
00:22:50,880 --> 00:22:54,520
Speaker 2: But just south in San Jose, Prolagis has won approval

438
00:22:54,560 --> 00:22:58,080
Speaker 2: to develop new data centers and manufacturing facilities with a

439
00:22:58,160 --> 00:23:02,280
Speaker 2: vision that includes five electric substations for power for more.

440
00:23:02,359 --> 00:23:05,280
Speaker 2: We're joined by San Jose or Matt Mayhem. Matt, good

441
00:23:05,320 --> 00:23:07,399
Speaker 2: to have you on the program today. The first question

442
00:23:07,440 --> 00:23:10,480
Speaker 2: I have is really about why San Jose is a

443
00:23:10,520 --> 00:23:13,280
Speaker 2: good place for facility like this. This is some of

444
00:23:13,320 --> 00:23:16,560
Speaker 2: the most expensive real estates, the most expensive housing in

445
00:23:16,600 --> 00:23:18,000
Speaker 2: the entire United States.

446
00:23:18,000 --> 00:23:18,680
Speaker 3: Why San Jose.

447
00:23:20,280 --> 00:23:23,760
Speaker 10: Well, we're in a really fortunate position in San Jose

448
00:23:24,000 --> 00:23:27,480
Speaker 10: to have two gigawatts of new power coming online over

449
00:23:27,520 --> 00:23:28,679
Speaker 10: the next four years.

450
00:23:28,720 --> 00:23:31,040
Speaker 11: We're the only city in California.

451
00:23:30,400 --> 00:23:36,320
Speaker 10: With that kind of new load capacity, and this particular

452
00:23:36,440 --> 00:23:39,120
Speaker 10: location is really unique. It's up in North San Jose

453
00:23:39,359 --> 00:23:42,360
Speaker 10: next to two thirty seven, a large freeway here right

454
00:23:42,440 --> 00:23:46,679
Speaker 10: next to our wastewater treatment facility, which means access to

455
00:23:47,560 --> 00:23:51,600
Speaker 10: ample recycled water at a reasonable rate, as well as

456
00:23:51,640 --> 00:23:54,160
Speaker 10: one of those new transmission lines coming into the city

457
00:23:54,160 --> 00:23:56,120
Speaker 10: of San Jose. So, as you mentioned, while the rest

458
00:23:56,119 --> 00:23:59,080
Speaker 10: of Silicon Valley, which was largely built out, is having

459
00:23:59,160 --> 00:24:02,360
Speaker 10: to turn data on our projects away, we've just said

460
00:24:02,440 --> 00:24:05,600
Speaker 10: yes to prologe Is in this proposal to put four

461
00:24:05,680 --> 00:24:08,359
Speaker 10: hundred megawatts worth of data centers right here in the

462
00:24:08,359 --> 00:24:10,840
Speaker 10: heart of Silicon Valley. We think it's a really exciting

463
00:24:10,880 --> 00:24:15,760
Speaker 10: opportunity in terms of economic competitiveness, job growth, tax base,

464
00:24:16,280 --> 00:24:20,240
Speaker 10: and those infrastructure pieces are right there in place to

465
00:24:20,280 --> 00:24:21,000
Speaker 10: facilitate it.

466
00:24:21,119 --> 00:24:23,320
Speaker 2: You mentioned it's right by a wastewater treatment facility. It

467
00:24:23,320 --> 00:24:25,160
Speaker 2: makes me think that perhaps this wouldn't be the best

468
00:24:25,200 --> 00:24:27,560
Speaker 2: place to build affordable housing. Is it fair to say

469
00:24:27,560 --> 00:24:30,560
Speaker 2: that this is not a site that is zoned for that.

470
00:24:30,280 --> 00:24:33,040
Speaker 10: That's part of the benefit here is that in much

471
00:24:33,080 --> 00:24:37,320
Speaker 10: of the city we're trying to enable housing, mixed juice development, retail,

472
00:24:37,400 --> 00:24:41,960
Speaker 10: more transit oriented development. This particular site is up next

473
00:24:41,960 --> 00:24:47,000
Speaker 10: to the bay. You've got wastewater treatment, there's a landfill nearby. Fortunately,

474
00:24:47,080 --> 00:24:50,719
Speaker 10: servers don't complain about odors, and.

475
00:24:50,080 --> 00:24:52,480
Speaker 11: So we think it's the perfect location.

476
00:24:52,840 --> 00:24:56,880
Speaker 10: There's also just nowhere else in Silicon Valley with access

477
00:24:56,920 --> 00:25:01,040
Speaker 10: to recycled water that's so easy. Plus the availability of

478
00:25:01,080 --> 00:25:04,200
Speaker 10: power that's the biggest barrier. As you know, we've got

479
00:25:04,200 --> 00:25:08,359
Speaker 10: a thousand megawatts of new power coming online over the

480
00:25:08,400 --> 00:25:10,880
Speaker 10: next four years in this exact location.

481
00:25:11,200 --> 00:25:13,479
Speaker 2: Yeah, explain where that power is coming from, where it's

482
00:25:13,520 --> 00:25:15,160
Speaker 2: coming online. As I mentioned, one of the most read

483
00:25:15,200 --> 00:25:18,359
Speaker 2: stories on the Bloomberg Terminal today is about data centers

484
00:25:18,400 --> 00:25:20,760
Speaker 2: that are just sitting there idle because they cannot get

485
00:25:21,200 --> 00:25:23,840
Speaker 2: capacity actually hooked up to them to energize them.

486
00:25:24,359 --> 00:25:27,919
Speaker 10: That's right, and sometimes it's better to be lucky than good.

487
00:25:28,040 --> 00:25:31,320
Speaker 10: San Jose is a beneficiary of a decision made by

488
00:25:31,480 --> 00:25:35,720
Speaker 10: kaisso the independent system operator here in California. Many years

489
00:25:35,720 --> 00:25:39,000
Speaker 10: ago before we were talking much about AI, they were

490
00:25:39,040 --> 00:25:43,080
Speaker 10: just looking at general economic growth trends and decided that

491
00:25:43,200 --> 00:25:46,280
Speaker 10: San Jose had some of the highest growth potential in

492
00:25:46,320 --> 00:25:49,720
Speaker 10: the entire state, and they approved new transmission lines. There's

493
00:25:49,760 --> 00:25:53,359
Speaker 10: one line coming up from the south, one from the north,

494
00:25:53,440 --> 00:25:55,440
Speaker 10: but they both come into San Jose.

495
00:25:55,680 --> 00:25:58,439
Speaker 11: Each is a thousand megawatts. So here's a city that

496
00:25:58,480 --> 00:25:59,359
Speaker 11: has a million people.

497
00:25:59,440 --> 00:26:03,040
Speaker 10: Twelve large city in the country already consumes about one

498
00:26:03,080 --> 00:26:07,119
Speaker 10: point one gigawatts of power. We have two gigawatts coming

499
00:26:07,160 --> 00:26:09,400
Speaker 10: online over the next four years. That means we can

500
00:26:09,560 --> 00:26:13,280
Speaker 10: triple our energy use in the city of San Jose.

501
00:26:13,520 --> 00:26:16,960
Speaker 10: There's no other city in California, maybe the country, that

502
00:26:17,080 --> 00:26:20,399
Speaker 10: is set up to triple its energy consumption over the

503
00:26:20,440 --> 00:26:23,200
Speaker 10: next four to five years. That's a really unique position

504
00:26:23,240 --> 00:26:26,679
Speaker 10: to be in. We're just blessed with this infrastructure coming online.

505
00:26:26,800 --> 00:26:29,320
Speaker 10: We've of course said yes to it, helped facilitate it,

506
00:26:29,440 --> 00:26:34,320
Speaker 10: been very supportive of it. But we're really optimistic that

507
00:26:34,400 --> 00:26:38,040
Speaker 10: this means more jobs, not just data centers, advanced manufacturing

508
00:26:38,280 --> 00:26:39,200
Speaker 10: R and D labs.

509
00:26:39,480 --> 00:26:41,240
Speaker 11: We're in a really strong.

510
00:26:40,960 --> 00:26:44,639
Speaker 10: Position to capture this technological wave that we're.

511
00:26:44,520 --> 00:26:47,000
Speaker 2: In, the power that it will be used by these

512
00:26:47,080 --> 00:26:49,840
Speaker 2: data centers, the power that's coming online, how is it

513
00:26:49,880 --> 00:26:52,600
Speaker 2: being generated? I know you have that one nuclear power

514
00:26:52,640 --> 00:26:56,159
Speaker 2: plant down South Diablo Canyon on the central coast, and

515
00:26:56,240 --> 00:27:00,000
Speaker 2: some renewables certainly too, wind and solar. How's this energy

516
00:27:00,040 --> 00:27:00,960
Speaker 2: are you going to be generated?

517
00:27:01,960 --> 00:27:04,840
Speaker 10: So the City of San Jose a few years ago

518
00:27:05,040 --> 00:27:09,040
Speaker 10: set up something called a community Choice aggregator. Essentially that's

519
00:27:09,040 --> 00:27:13,440
Speaker 10: a mouthful, but essentially the city purchases power on behalf

520
00:27:13,520 --> 00:27:16,560
Speaker 10: of the users within our city limits. We have used

521
00:27:16,640 --> 00:27:20,760
Speaker 10: this policy tool to sign twenty year power purchase agreements

522
00:27:21,119 --> 00:27:25,399
Speaker 10: that enable us to fund new generation capacity. And because

523
00:27:25,440 --> 00:27:30,760
Speaker 10: we have a commitment to cleaner energy, what we're essentially

524
00:27:31,000 --> 00:27:35,439
Speaker 10: doing is buying solar and wind compared with storage, and

525
00:27:35,480 --> 00:27:38,760
Speaker 10: that's the key. The intermittency issue is real, but when

526
00:27:38,800 --> 00:27:43,160
Speaker 10: you build enough storage capacity, you can smooth that curve

527
00:27:43,240 --> 00:27:46,000
Speaker 10: out and actually make it work. And so Santose already

528
00:27:46,000 --> 00:27:49,359
Speaker 10: has one of the cleanest renewable mixes in the country.

529
00:27:49,600 --> 00:27:54,119
Speaker 10: But it's largely because we're using that collective purchasing power

530
00:27:54,119 --> 00:27:57,919
Speaker 10: to invest in cleaner power, invest in innovation, in the

531
00:27:58,040 --> 00:28:01,280
Speaker 10: energy sector, and it's it's taken us a long way,

532
00:28:01,320 --> 00:28:03,600
Speaker 10: and we're going to continue to go down that path

533
00:28:03,680 --> 00:28:07,199
Speaker 10: because grid scale storage is the way to clean up

534
00:28:07,200 --> 00:28:10,280
Speaker 10: the grid. You mentioned nuclear. I think that also has

535
00:28:10,320 --> 00:28:12,360
Speaker 10: to be part of the mix here if we want

536
00:28:12,400 --> 00:28:15,720
Speaker 10: to really get down our emissions. But I'm proud of

537
00:28:15,760 --> 00:28:17,280
Speaker 10: the work we've done in San Jose, and there's a

538
00:28:17,320 --> 00:28:18,240
Speaker 10: lot of runway left.

539
00:28:18,320 --> 00:28:20,080
Speaker 2: So is it fair to say that none of the

540
00:28:20,080 --> 00:28:24,040
Speaker 2: power that will be used to energize these data centers

541
00:28:24,320 --> 00:28:28,679
Speaker 2: will be you know, quote unquote dirty, non renewable power,

542
00:28:28,880 --> 00:28:29,879
Speaker 2: carbon based stuff.

543
00:28:30,920 --> 00:28:32,760
Speaker 10: Well, I can't guarantee none of it will, because the

544
00:28:32,760 --> 00:28:35,440
Speaker 10: power is coming off the grid, And so what we're

545
00:28:35,480 --> 00:28:39,120
Speaker 10: doing is using this projected increase in demand to sign

546
00:28:39,680 --> 00:28:44,120
Speaker 10: new power purchase agreements that are mostly, if not entirely

547
00:28:44,760 --> 00:28:47,480
Speaker 10: quote unquote clean. But then that gets added to the

548
00:28:47,520 --> 00:28:51,160
Speaker 10: grid and moves up the overall mix of renewable on

549
00:28:51,280 --> 00:28:53,320
Speaker 10: the grid. So I can't promise you that there aren't

550
00:28:53,320 --> 00:28:56,840
Speaker 10: electrons coming off the grid that are coming from nuclear.

551
00:28:57,320 --> 00:28:59,840
Speaker 11: Or a gas plant somewhere.

552
00:29:00,200 --> 00:29:03,920
Speaker 10: Certainly, natural gas nuclear are still very much part of

553
00:29:03,960 --> 00:29:09,200
Speaker 10: the foundation California. Isn't isn't using coal we're using. Geothermal

554
00:29:09,360 --> 00:29:12,600
Speaker 10: is growing, but it's really been solar paired with storage.

555
00:29:12,680 --> 00:29:15,040
Speaker 11: That's where most of the growth is coming from.

556
00:29:15,160 --> 00:29:17,280
Speaker 10: And the great thing about growth is you can invest

557
00:29:17,320 --> 00:29:19,520
Speaker 10: in an innovation, and that's what we're doing, is we're

558
00:29:19,520 --> 00:29:24,400
Speaker 10: explicitly purchasing solar paired with storage so that we can

559
00:29:24,680 --> 00:29:28,200
Speaker 10: increase the renewable mix on the grid. Overall, that benefits

560
00:29:28,280 --> 00:29:29,320
Speaker 10: us and the entire state.

561
00:29:29,520 --> 00:29:33,240
Speaker 2: Mayor man any interest yet from some of the large

562
00:29:33,280 --> 00:29:36,880
Speaker 2: hyperscalers or large tech companies in Silicon Valley for using

563
00:29:36,880 --> 00:29:38,239
Speaker 2: this capacity, what can you tell us?

564
00:29:39,600 --> 00:29:41,680
Speaker 11: We have a very robust pipeline.

565
00:29:41,720 --> 00:29:45,520
Speaker 10: PGAE did a cluster study last year that's already outdated

566
00:29:45,560 --> 00:29:48,960
Speaker 10: because there's so much more demand. I suspect most of

567
00:29:49,000 --> 00:29:52,200
Speaker 10: those two gigawatts of new power coming online will be

568
00:29:52,240 --> 00:29:55,640
Speaker 10: spoken for over the next eighteen months. We've got a

569
00:29:55,640 --> 00:30:01,080
Speaker 10: long pipeline of interested parties, the usual suspects, hyperscalers and

570
00:30:01,120 --> 00:30:05,840
Speaker 10: the big data center developers, some advanced manufacturing uses. So

571
00:30:05,960 --> 00:30:08,959
Speaker 10: PGEN will be updating their cluster study, will get a

572
00:30:09,000 --> 00:30:11,320
Speaker 10: better look at how much demand there is in the

573
00:30:11,320 --> 00:30:13,960
Speaker 10: city of San Jose, but last year showed over eight

574
00:30:14,000 --> 00:30:16,760
Speaker 10: hundred megawatts worth of demand. I suspect it's quite a

575
00:30:16,760 --> 00:30:19,920
Speaker 10: bit higher now this year, especially with this news. As

576
00:30:19,960 --> 00:30:22,840
Speaker 10: you know, for this particular site, Prologist builds for the

577
00:30:22,840 --> 00:30:28,080
Speaker 10: world's largest companies, the Hyperscalers, the most innovative companies on Earth,

578
00:30:28,120 --> 00:30:30,880
Speaker 10: and this particular location is a real win win because

579
00:30:31,080 --> 00:30:35,200
Speaker 10: it doesn't displace housing or retail or any other uses.

580
00:30:35,280 --> 00:30:38,000
Speaker 10: It's underutilized land next to a waste of our treatment

581
00:30:38,000 --> 00:30:40,400
Speaker 10: facility that just happens to have a lot of new

582
00:30:40,440 --> 00:30:44,560
Speaker 10: power capacity and recycled water just adjacent to the site.

583
00:30:44,560 --> 00:30:46,440
Speaker 11: So it's kind of the perfect place to do this.

584
00:30:46,920 --> 00:30:50,400
Speaker 2: Matt Mahon, the mayor of San Jose, California, thanks so

585
00:30:50,480 --> 00:30:51,479
Speaker 2: much for joining us.

586
00:30:51,480 --> 00:30:52,760
Speaker 3: May Or Mahnon, do appreciate it.

587
00:30:53,040 --> 00:30:54,960
Speaker 2: Well, Let's stick with the AI theme and take a

588
00:30:54,960 --> 00:30:57,560
Speaker 2: look at some movers right now in that space. The

589
00:30:57,760 --> 00:31:02,160
Speaker 2: Nasdaq and the Philadelphia Semi Index. The socks both up

590
00:31:02,400 --> 00:31:04,480
Speaker 2: now a ZAK one hundred up one point three percent.

591
00:31:04,560 --> 00:31:07,240
Speaker 2: The socks up two percent, this as talks are underway

592
00:31:07,240 --> 00:31:11,320
Speaker 2: to potentially end the month long government shutdown. Chip stocks

593
00:31:11,360 --> 00:31:13,920
Speaker 2: two on the move in Nvidio more than three percent.

594
00:31:14,240 --> 00:31:19,000
Speaker 2: Also as investors responding to strong sector fundamentals, accelerating AI spending.

595
00:31:19,280 --> 00:31:23,680
Speaker 2: A rally started with TSMC's solid results. All eyes too

596
00:31:23,720 --> 00:31:26,040
Speaker 2: on core Weave that is slated to report after the

597
00:31:26,080 --> 00:31:28,920
Speaker 2: closing bell today. Coryve up seven tens of one percent

598
00:31:29,040 --> 00:31:31,960
Speaker 2: right now, kind of those masks. What happened last week?

599
00:31:32,080 --> 00:31:34,920
Speaker 2: Sticking with core Weave, let's bring in Bloomberg Equities reporter

600
00:31:35,000 --> 00:31:38,760
Speaker 2: Carmen Ryanicky Sheet joins us now. Carmen Corewave tough week

601
00:31:38,840 --> 00:31:41,840
Speaker 2: last week, but the stock has absolutely been on a

602
00:31:41,880 --> 00:31:46,080
Speaker 2: tear since it went public. What's the backdrop that the

603
00:31:46,120 --> 00:31:48,200
Speaker 2: company is facing when it reports results after the bell.

604
00:31:48,560 --> 00:31:51,040
Speaker 12: Yeah, so investors are really going to be watching for

605
00:31:51,080 --> 00:31:53,960
Speaker 12: sort of this balance between revenue growth for Coreve, which

606
00:31:54,000 --> 00:31:56,680
Speaker 12: is just flying it's expected to double to more than

607
00:31:56,720 --> 00:31:59,360
Speaker 12: one point three billion, but also the sort of massive

608
00:31:59,440 --> 00:32:02,520
Speaker 12: spending that it also has while it builds out more

609
00:32:02,560 --> 00:32:05,800
Speaker 12: and more capacity for its large hyper scale clients. As

610
00:32:05,840 --> 00:32:08,960
Speaker 12: you mentioned, Coreeve shares are up more than double still

611
00:32:09,000 --> 00:32:11,520
Speaker 12: since their IPO, but they are also more than thirty

612
00:32:11,520 --> 00:32:13,840
Speaker 12: percent below a record high hit a few months ago,

613
00:32:13,880 --> 00:32:17,960
Speaker 12: and they fell pretty significantly after last earnings on concerns

614
00:32:17,960 --> 00:32:20,400
Speaker 12: about spending. So that's something we're going to be watching

615
00:32:20,520 --> 00:32:24,080
Speaker 12: very closely after the bell today. Stock fell a lot

616
00:32:24,160 --> 00:32:26,040
Speaker 12: last week when we sort of had this broader AI

617
00:32:26,120 --> 00:32:28,240
Speaker 12: sell off, but a little bit of a rebound today

618
00:32:28,280 --> 00:32:29,200
Speaker 12: ahead of those results.

619
00:32:29,280 --> 00:32:31,360
Speaker 2: As you note in a recent piece for Bloomberg News,

620
00:32:31,360 --> 00:32:34,880
Speaker 2: most of Corewave's sales come from Meta, Microsoft and Alphabet.

621
00:32:35,240 --> 00:32:37,280
Speaker 3: Are there questions about diversifying that at all.

622
00:32:37,760 --> 00:32:40,440
Speaker 12: Yeah, that's something that investors are definitely looking forward to

623
00:32:40,480 --> 00:32:42,880
Speaker 12: hear if they've added any new clients in this quarter

624
00:32:43,000 --> 00:32:45,600
Speaker 12: to kind of shift away from the dependence on those

625
00:32:45,960 --> 00:32:49,880
Speaker 12: few companies. Though I've also heard from sources that it's

626
00:32:49,880 --> 00:32:52,840
Speaker 12: not the biggest concern because there's just so much demand

627
00:32:52,920 --> 00:32:54,800
Speaker 12: in this space that even if one of their big

628
00:32:54,840 --> 00:32:57,520
Speaker 12: clients were to drop them or move on or something,

629
00:32:57,560 --> 00:33:00,360
Speaker 12: there are going to be others to rush it. So

630
00:33:00,960 --> 00:33:04,000
Speaker 12: definitely investors are looking for, you know, are they signing

631
00:33:04,080 --> 00:33:06,080
Speaker 12: new clients, new customers, But it might not be the

632
00:33:06,080 --> 00:33:06,760
Speaker 12: biggest concern.

633
00:33:06,920 --> 00:33:09,640
Speaker 2: Bloomberg's Carmen Ryana Key check out her reporting and more

634
00:33:09,760 --> 00:33:12,760
Speaker 2: on the Bloomberg Terminal, and a reminder for instant earnings

635
00:33:12,800 --> 00:33:15,600
Speaker 2: results and analysis, tune into Bloomberg TV and Radio.

636
00:33:15,720 --> 00:33:16,800
Speaker 3: At the close today.

637
00:33:17,360 --> 00:33:20,720
Speaker 2: Well coming up Isaiah Taylor, CEO valor Atomics, joins us

638
00:33:20,840 --> 00:33:22,880
Speaker 2: fresh off of the back of the company's one hundred

639
00:33:22,880 --> 00:33:25,200
Speaker 2: and thirty million dollar funding round. We're going to talk

640
00:33:25,200 --> 00:33:28,440
Speaker 2: about the startups plants to remake the US nuclear sector. Next,

641
00:33:28,880 --> 00:33:54,400
Speaker 2: this is Bloomberg Tech. Power demand, driven in part by

642
00:33:54,440 --> 00:33:57,280
Speaker 2: AI and the US push to secure key initiatives and

643
00:33:57,360 --> 00:34:00,840
Speaker 2: key industries has led to efforts to revive America's nuclear

644
00:34:00,880 --> 00:34:04,560
Speaker 2: power abilities. Startup valor Atomics is seeking to do that

645
00:34:04,800 --> 00:34:07,760
Speaker 2: with the next generation reactor. It's just raised a one

646
00:34:07,840 --> 00:34:10,799
Speaker 2: hundred and thirty million dollars Series A funding round. We're

647
00:34:10,840 --> 00:34:14,440
Speaker 2: joined by the founder and CEO, Isaiah Taylor. Joins us

648
00:34:14,520 --> 00:34:16,640
Speaker 2: right now on Bloomberg Tech. Isaiah, good to have you

649
00:34:16,719 --> 00:34:19,080
Speaker 2: on the program. Congratulations on the rays. When we talk

650
00:34:19,120 --> 00:34:23,640
Speaker 2: about small modular reactors, you're not alone Nano nuclear, Aklo,

651
00:34:23,920 --> 00:34:26,719
Speaker 2: new scale, just a handful of the companies working on

652
00:34:26,760 --> 00:34:29,720
Speaker 2: this technology. What makes Valors different?

653
00:34:30,680 --> 00:34:32,480
Speaker 13: Yeah, Tim, It's a huge pleasure to be on with

654
00:34:32,520 --> 00:34:34,720
Speaker 13: you today and it's a really exciting day for Valor.

655
00:34:34,880 --> 00:34:35,640
Speaker 11: It's a great question.

656
00:34:35,680 --> 00:34:37,960
Speaker 13: There are a lot of people tackling this very very

657
00:34:37,960 --> 00:34:40,160
Speaker 13: difficult problem of how do we make all of the

658
00:34:40,280 --> 00:34:42,759
Speaker 13: energy needs that America has in the future. You know,

659
00:34:42,800 --> 00:34:45,279
Speaker 13: the thing that sets Valor apart is two things. One

660
00:34:45,360 --> 00:34:48,080
Speaker 13: is that we're building very quickly. You know, when we

661
00:34:48,080 --> 00:34:50,320
Speaker 13: started this company, we realized that there was a gap

662
00:34:50,400 --> 00:34:53,960
Speaker 13: in the physical hardware. We wanted to actually build reactors

663
00:34:53,960 --> 00:34:56,479
Speaker 13: and test them out very rapidly. I started this company

664
00:34:56,520 --> 00:34:59,480
Speaker 13: about two years ago, and earlier this year we unveiled

665
00:34:59,560 --> 00:35:02,600
Speaker 13: our full, complete thermal prototype of our reactor. That's just

666
00:35:02,640 --> 00:35:04,640
Speaker 13: incredible speed. We haven't seen that kind of speed in

667
00:35:04,719 --> 00:35:07,080
Speaker 13: nuclear in a long time. The other thing that sets

668
00:35:07,160 --> 00:35:08,840
Speaker 13: us apart is that we want to build these to

669
00:35:08,880 --> 00:35:11,799
Speaker 13: be manufacturable. We're sort of moving away from this era

670
00:35:11,920 --> 00:35:15,480
Speaker 13: of nuclear that's driven by construction and more into mass manufacturing.

671
00:35:15,480 --> 00:35:17,360
Speaker 13: We want to pump these things out like they are

672
00:35:17,360 --> 00:35:19,440
Speaker 13: a car, like they're a bus, and that's what's going

673
00:35:19,480 --> 00:35:21,400
Speaker 13: to drive the cost down and also add a lot

674
00:35:21,440 --> 00:35:22,319
Speaker 13: to safety as well.

675
00:35:22,719 --> 00:35:25,160
Speaker 2: Before you pump these things out, though, you've got to

676
00:35:25,239 --> 00:35:28,799
Speaker 2: build one single example of one that actually works, and

677
00:35:28,800 --> 00:35:32,040
Speaker 2: here in the United States there is still no example

678
00:35:32,120 --> 00:35:34,720
Speaker 2: of a small modular reactor that is up and running,

679
00:35:34,719 --> 00:35:38,480
Speaker 2: that is online, taking your company out of the mix.

680
00:35:39,040 --> 00:35:40,600
Speaker 2: Just when do you think there will be an example

681
00:35:40,600 --> 00:35:41,400
Speaker 2: of that in the US.

682
00:35:43,640 --> 00:35:44,480
Speaker 11: That's exactly right.

683
00:35:44,520 --> 00:35:46,880
Speaker 13: We don't have any small modular reactors running in the

684
00:35:46,960 --> 00:35:49,799
Speaker 13: US today. And in fact, even though there have been

685
00:35:49,840 --> 00:35:52,960
Speaker 13: many nuclear startups who have sort of attempted this, there's

686
00:35:53,000 --> 00:35:55,360
Speaker 13: never been a nuclear startup which has yet split the atom.

687
00:35:55,560 --> 00:35:57,239
Speaker 13: So I think the next twelve months are going to

688
00:35:57,239 --> 00:36:01,120
Speaker 13: be extremely exciting. In May of this year, the President

689
00:36:01,239 --> 00:36:05,360
Speaker 13: signed in executive order ordering three American nuclear companies to

690
00:36:05,440 --> 00:36:08,239
Speaker 13: turn on SMRs by July fourth of next year. Our

691
00:36:08,280 --> 00:36:11,080
Speaker 13: company was one of those companies selected, So I think

692
00:36:11,120 --> 00:36:13,960
Speaker 13: I can confidently say before July fourth, there will be

693
00:36:14,080 --> 00:36:16,680
Speaker 13: at least one, we hope three SMRs running in the

694
00:36:16,719 --> 00:36:18,840
Speaker 13: United States, and we definitely think that Valor will have

695
00:36:18,880 --> 00:36:19,360
Speaker 13: one of those.

696
00:36:19,520 --> 00:36:21,520
Speaker 2: How much do they cost? How much will it cost?

697
00:36:21,600 --> 00:36:22,479
Speaker 2: What's the ultimate goal?

698
00:36:24,880 --> 00:36:27,000
Speaker 11: So the initial goal is to beat natural gas.

699
00:36:27,400 --> 00:36:30,120
Speaker 13: I think nuclear absolutely has to compete with natural gas

700
00:36:30,200 --> 00:36:32,360
Speaker 13: on price, on timeline, on all of these things that

701
00:36:32,400 --> 00:36:35,120
Speaker 13: developers care about. So that's the initial goal. And that

702
00:36:35,160 --> 00:36:37,759
Speaker 13: gas plant's going, you know, somewhere between one thousand and

703
00:36:37,800 --> 00:36:39,680
Speaker 13: two thousand bucks a kilowat, so we want to be

704
00:36:39,719 --> 00:36:42,560
Speaker 13: at least with parity. Now we're also cleaner, right, So

705
00:36:42,600 --> 00:36:44,319
Speaker 13: it's not just that we're the same prices, that we're

706
00:36:44,320 --> 00:36:47,200
Speaker 13: cleaner as well. But the thing that's interesting about nuclear

707
00:36:47,200 --> 00:36:49,560
Speaker 13: is that it's actually fairly new and there's a lot

708
00:36:49,600 --> 00:36:51,480
Speaker 13: to go down the tech tree, right. There's a lot

709
00:36:51,480 --> 00:36:54,680
Speaker 13: of technological innovation that can happen in the future, so

710
00:36:54,719 --> 00:36:57,120
Speaker 13: we expect that price to continue dropping. You know, I

711
00:36:57,520 --> 00:37:00,320
Speaker 13: think about SpaceX when we talk about this, where dockets

712
00:37:00,400 --> 00:37:02,959
Speaker 13: used to cost fifty thousand dollars a kilogram into orbit

713
00:37:03,000 --> 00:37:05,680
Speaker 13: and SpaceX pushing them down to two thousand. I think

714
00:37:05,719 --> 00:37:07,879
Speaker 13: we're going to look at that level of drop. There's

715
00:37:07,920 --> 00:37:09,920
Speaker 13: going to be a massive, massive drop in the price

716
00:37:10,200 --> 00:37:12,440
Speaker 13: as Valor gets really good at making these reactors and

717
00:37:12,480 --> 00:37:13,279
Speaker 13: makes many of them.

718
00:37:13,640 --> 00:37:16,440
Speaker 2: You announced earlier this year that you're suing the Nuclear

719
00:37:16,600 --> 00:37:18,200
Speaker 2: Regulatory Commission, the NRCA.

720
00:37:18,960 --> 00:37:19,680
Speaker 3: Why are you doing that?

721
00:37:22,200 --> 00:37:24,360
Speaker 13: Yeah, you know, I think the thing that is really

722
00:37:24,360 --> 00:37:27,360
Speaker 13: important in nuclear today is allowing innovation to happen.

723
00:37:27,680 --> 00:37:27,839
Speaker 11: Right.

724
00:37:27,880 --> 00:37:29,759
Speaker 13: If you think about the role of a regulator, they're

725
00:37:29,800 --> 00:37:31,880
Speaker 13: trying to figure out how to make sure that we

726
00:37:31,960 --> 00:37:35,920
Speaker 13: have safety and security across thousands of reactors deployed all

727
00:37:35,920 --> 00:37:38,920
Speaker 13: over the place. But what was missing in American nuclear

728
00:37:38,960 --> 00:37:41,080
Speaker 13: was the innovation layer. We need to be able to

729
00:37:41,120 --> 00:37:43,600
Speaker 13: turn on test units and make sure that they work well,

730
00:37:43,800 --> 00:37:45,600
Speaker 13: and that's sort of the layer that's missing. So our

731
00:37:45,640 --> 00:37:49,320
Speaker 13: lawsuit really addresses a gap in how the CODA federal

732
00:37:49,360 --> 00:37:52,200
Speaker 13: regulations has been written versus how the law is written.

733
00:37:52,239 --> 00:37:54,600
Speaker 13: And so, you know, we're excited about that. We're also

734
00:37:54,680 --> 00:37:57,359
Speaker 13: very excited about the Department of Energy. These executive orders

735
00:37:57,400 --> 00:38:00,000
Speaker 13: signed earlier this year have also opened up incredible power

736
00:38:00,200 --> 00:38:03,600
Speaker 13: ways to be able to move quickly, turn our reactors on, safely,

737
00:38:03,640 --> 00:38:05,560
Speaker 13: test them before we go and scale.

738
00:38:05,640 --> 00:38:08,160
Speaker 2: You know, Palmer, we were showing an image there of

739
00:38:08,160 --> 00:38:13,080
Speaker 2: different investors in the company, Palmer Lucky of Anderil among

740
00:38:13,120 --> 00:38:17,239
Speaker 2: those investors certainly thinking about the defense space and his

741
00:38:17,360 --> 00:38:20,399
Speaker 2: involvement there. What are the applications of your technology when

742
00:38:20,400 --> 00:38:22,520
Speaker 2: it comes to defense for the United States.

743
00:38:24,680 --> 00:38:25,520
Speaker 3: That's exactly right.

744
00:38:25,560 --> 00:38:28,799
Speaker 13: You know, American military bases all around the world are

745
00:38:28,840 --> 00:38:32,359
Speaker 13: generally dependent on their local grid for power. This has

746
00:38:32,400 --> 00:38:35,560
Speaker 13: become a massive vulnerability as grids have become vulnerable to

747
00:38:35,600 --> 00:38:39,120
Speaker 13: cyber attack, you know, by our competitors, and so this

748
00:38:39,160 --> 00:38:42,160
Speaker 13: is a way for us to actually secure American military

749
00:38:42,160 --> 00:38:45,120
Speaker 13: bases abroad. We want to see these reactors deployed on bases.

750
00:38:45,440 --> 00:38:48,320
Speaker 13: A couple of months ago, the Janis program was announced

751
00:38:48,400 --> 00:38:50,680
Speaker 13: under the US Army to do exactly this, to actually

752
00:38:50,680 --> 00:38:54,200
Speaker 13: put power on military bases that's fully within American control.

753
00:38:54,560 --> 00:38:56,520
Speaker 13: We think these reactors are perfect for that. This is

754
00:38:56,560 --> 00:38:59,560
Speaker 13: a nice small form factor that's very easy to construct,

755
00:39:00,640 --> 00:39:02,680
Speaker 13: powerful enough to power a base if you put a

756
00:39:02,680 --> 00:39:04,680
Speaker 13: couple of them together. So this is a really exciting

757
00:39:04,680 --> 00:39:07,560
Speaker 13: opportunity and we're willing to help our country in that way.

758
00:39:07,680 --> 00:39:11,080
Speaker 2: We've seen American military basis come under attack in recent

759
00:39:11,160 --> 00:39:12,920
Speaker 2: years in different parts of the world. How would you

760
00:39:12,960 --> 00:39:16,480
Speaker 2: guarantee the safety of this technology if it were to

761
00:39:16,480 --> 00:39:18,360
Speaker 2: come under attack and not lead.

762
00:39:18,200 --> 00:39:19,440
Speaker 3: To some sort of meltdown.

763
00:39:21,680 --> 00:39:25,040
Speaker 13: Yeah, you know, this is where this particular technology shines.

764
00:39:25,120 --> 00:39:27,520
Speaker 13: Our reactor is built around a very safe form of

765
00:39:27,600 --> 00:39:31,040
Speaker 13: nuclear fuel called TRESO fuel. TRESO fuel is very small

766
00:39:31,040 --> 00:39:34,160
Speaker 13: beads of uranium encased in very heart ceramic layers, and

767
00:39:34,200 --> 00:39:37,480
Speaker 13: it turns out that these ceramic layers are extremely impervious

768
00:39:37,520 --> 00:39:40,200
Speaker 13: to many different types of attacks. So if you look

769
00:39:40,200 --> 00:39:42,920
Speaker 13: at the spectrum of how you build energy around the world,

770
00:39:43,080 --> 00:39:45,320
Speaker 13: we believe this is actually the safest.

771
00:39:44,880 --> 00:39:46,600
Speaker 11: Form of energy generation in the world.

772
00:39:46,800 --> 00:39:48,840
Speaker 13: So we're really excited to put it out not on

773
00:39:48,880 --> 00:39:50,640
Speaker 13: the edge, not only on the edge, but also for

774
00:39:51,080 --> 00:39:55,160
Speaker 13: data center's heavy industrial power and eventually synthetic hydrocarbon production.

775
00:39:55,440 --> 00:39:58,279
Speaker 2: Isaiah, before we let you go, is your company going

776
00:39:58,320 --> 00:40:02,160
Speaker 2: to be the first US company to successfully deploy and

777
00:40:02,200 --> 00:40:04,160
Speaker 2: bring online a small modular reactor.

778
00:40:06,440 --> 00:40:07,920
Speaker 13: You know, it's a hot race, and there are a

779
00:40:07,960 --> 00:40:10,279
Speaker 13: lot of awesome people working on the problem. But where

780
00:40:10,280 --> 00:40:12,399
Speaker 13: I sit today, I do believe that valor Atomics will

781
00:40:12,400 --> 00:40:12,799
Speaker 13: be the first.

782
00:40:12,800 --> 00:40:13,839
Speaker 3: That is absolutely our goal.

783
00:40:14,160 --> 00:40:17,319
Speaker 2: Isaiah Taylor, founder and CEO of valor Atomics, joining us

784
00:40:17,320 --> 00:40:26,360
Speaker 2: from Delaware today. Well, chatbots have become a go to

785
00:40:26,520 --> 00:40:29,680
Speaker 2: source for millions of people looking for information, amusement, and

786
00:40:29,719 --> 00:40:33,200
Speaker 2: emotional support. But evidence is mounting that for some people,

787
00:40:33,680 --> 00:40:37,280
Speaker 2: chatbot interactions can lead to dark places. That's the focus

788
00:40:37,280 --> 00:40:40,360
Speaker 2: of a big take from Bloomberg's Ellen Hewitt and Rachel Metz.

789
00:40:40,480 --> 00:40:43,919
Speaker 2: Rachel joins us Now, Rachel, this is a really powerful piece,

790
00:40:44,000 --> 00:40:44,840
Speaker 2: really scary piece.

791
00:40:44,880 --> 00:40:46,080
Speaker 3: For it, I think a lot of people.

792
00:40:46,280 --> 00:40:49,640
Speaker 2: You and the team spoke to eighteen different individuals who've

793
00:40:49,719 --> 00:40:51,759
Speaker 2: either experienced delusions themselves or.

794
00:40:52,080 --> 00:40:54,719
Speaker 3: Have a loved one who has what did you find?

795
00:40:55,840 --> 00:41:00,080
Speaker 14: We found that this is happening and has happened to

796
00:41:00,200 --> 00:41:02,560
Speaker 14: all kinds of people. I mean, most of the people

797
00:41:02,560 --> 00:41:04,960
Speaker 14: that we spoke with were based in the US, but

798
00:41:05,200 --> 00:41:08,439
Speaker 14: we found through talking to people that there are men

799
00:41:08,600 --> 00:41:11,400
Speaker 14: and women in all different parts of the US, in

800
00:41:11,520 --> 00:41:16,040
Speaker 14: different countries, Canada, in the UK, and many other countries besides,

801
00:41:16,239 --> 00:41:18,360
Speaker 14: who are dealing with this. And it gave us a

802
00:41:18,440 --> 00:41:22,480
Speaker 14: sense that and it wasn't just people that have a

803
00:41:22,600 --> 00:41:26,440
Speaker 14: history of mental health issues in their past. It can

804
00:41:26,480 --> 00:41:29,440
Speaker 14: be all kinds of people, people that do, people that don't.

805
00:41:29,640 --> 00:41:33,160
Speaker 14: And it just was really shocking to us how many

806
00:41:33,160 --> 00:41:37,440
Speaker 14: different types of people had been dealing with this experience.

807
00:41:37,800 --> 00:41:41,920
Speaker 2: How do the lllms, how do these chatbots draw people

808
00:41:41,960 --> 00:41:43,160
Speaker 2: in and keep them there?

809
00:41:44,840 --> 00:41:46,360
Speaker 14: I think for a lot of the people that we

810
00:41:46,480 --> 00:41:49,800
Speaker 14: spoke to, I mean, in every single situation, it started

811
00:41:49,840 --> 00:41:54,080
Speaker 14: out extremely normally. They were using it for Lennie how

812
00:41:54,080 --> 00:41:58,160
Speaker 14: to play the banjo, or getting help with real estate

813
00:41:58,719 --> 00:42:01,160
Speaker 14: things like that. Like these are examples, you know, like

814
00:42:01,320 --> 00:42:03,799
Speaker 14: very normal things that people would be using this sort

815
00:42:03,800 --> 00:42:06,840
Speaker 14: of technology for. And then over time, over like a

816
00:42:06,880 --> 00:42:09,720
Speaker 14: period of weeks, often it would kind of get maybe

817
00:42:09,800 --> 00:42:11,080
Speaker 14: more philosophical.

818
00:42:11,360 --> 00:42:12,080
Speaker 11: It would sort of.

819
00:42:12,040 --> 00:42:14,840
Speaker 14: Depend on the user's interests. I mean, these chatboss have

820
00:42:14,880 --> 00:42:19,600
Speaker 14: become increasingly personalized, so people that are more interested in

821
00:42:19,640 --> 00:42:22,160
Speaker 14: things like math, for instance, it might sort of move

822
00:42:22,239 --> 00:42:26,279
Speaker 14: in that direction, or it might tell people slowly over

823
00:42:26,360 --> 00:42:30,040
Speaker 14: time you have awoken the AI, and people would say really,

824
00:42:30,080 --> 00:42:32,040
Speaker 14: and it would say yes. And they would say really

825
00:42:32,080 --> 00:42:34,920
Speaker 14: and it would say yes. So it was very reinforcing

826
00:42:35,400 --> 00:42:37,640
Speaker 14: and would sort of isolate them from other people in

827
00:42:37,680 --> 00:42:40,040
Speaker 14: their lives slowly and systematically.

828
00:42:40,239 --> 00:42:42,000
Speaker 2: And just in the last thirty seconds that we have

829
00:42:42,080 --> 00:42:44,720
Speaker 2: with you, the companies their response, how have they responded

830
00:42:44,760 --> 00:42:45,440
Speaker 2: to this reporting.

831
00:42:46,640 --> 00:42:49,000
Speaker 14: I mean we've seen a range of responses, both to

832
00:42:49,080 --> 00:42:53,040
Speaker 14: us specifically and also generally to a growing number of

833
00:42:53,120 --> 00:42:56,719
Speaker 14: lawsuits related to these sources of issues. Open AI. I mean,

834
00:42:56,719 --> 00:43:00,759
Speaker 14: it's made a lot of changes in recent months, especially

835
00:43:00,840 --> 00:43:05,000
Speaker 14: like adding parental controls, and it's also trying to make

836
00:43:05,239 --> 00:43:08,560
Speaker 14: it better, make its chat about better at noting these

837
00:43:08,640 --> 00:43:10,560
Speaker 14: kinds of issues and getting people help.

838
00:43:10,960 --> 00:43:14,400
Speaker 2: That's Rachel Metz, who along with Ellen Hewitt, reported on

839
00:43:14,480 --> 00:43:17,560
Speaker 2: these delusions for Bloomberg BusinessWeek. It was a recent big take.

840
00:43:17,600 --> 00:43:19,400
Speaker 2: Do check it out on the Bloomberg Terminal and at

841
00:43:19,440 --> 00:43:21,680
Speaker 2: bloomberg dot Com slash Big Take. That is going to

842
00:43:21,719 --> 00:43:23,960
Speaker 2: do it for this edition of Bloomberg Chech Tech. Don't

843
00:43:24,000 --> 00:43:25,719
Speaker 2: forget to check out our podcast. You can find another

844
00:43:25,800 --> 00:43:28,880
Speaker 2: Terminal as well as online at Apple, Spotify, or iHeart.

845
00:43:28,880 --> 00:43:29,680
Speaker 3: This is Bloomberg