1
00:00:00,120 --> 00:00:13,600
Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive

2
00:00:13,640 --> 00:00:17,480
Speaker 1: from coast to coast with Caroline Hide in New York

3
00:00:17,760 --> 00:00:20,920
Speaker 1: and Eva though in San Francisco.

4
00:00:24,440 --> 00:00:26,000
Speaker 2: This is Bloomberg Tech coming out.

5
00:00:26,040 --> 00:00:29,360
Speaker 3: The US Defence Department adds Ali Barber by doing Others

6
00:00:29,600 --> 00:00:31,520
Speaker 3: to a list of firms that says are connected to

7
00:00:31,560 --> 00:00:34,440
Speaker 3: the Chinese military, but then pulls the list.

8
00:00:34,840 --> 00:00:37,080
Speaker 4: Plus, we keep beating the earnings drum.

9
00:00:37,159 --> 00:00:40,479
Speaker 5: Ribon, Coinbase, Instacar, Airbnb all out with their results.

10
00:00:40,479 --> 00:00:41,360
Speaker 4: Will break it all down.

11
00:00:42,240 --> 00:00:45,320
Speaker 3: An Anthropic completes a deal to raise thirty billion dollars

12
00:00:45,400 --> 00:00:49,040
Speaker 3: in funding, doubling the valuation of the company to three

13
00:00:49,159 --> 00:00:50,920
Speaker 3: hundred and eighty billion dollars.

14
00:00:51,320 --> 00:00:54,639
Speaker 5: Private market said, public markets, we do it all on

15
00:00:54,640 --> 00:00:56,880
Speaker 5: the show, and we think about the macro data as well.

16
00:00:56,920 --> 00:00:59,960
Speaker 5: When that CPI print comes in much cooler than ext

17
00:01:00,000 --> 00:01:02,240
Speaker 5: affected and it gives life to the bond market, but

18
00:01:02,280 --> 00:01:04,200
Speaker 5: not so much the equity market I'm looking at, then

19
00:01:04,200 --> 00:01:05,000
Speaker 5: that's that one hundred.

20
00:01:05,240 --> 00:01:06,559
Speaker 4: It's actually down on the week.

21
00:01:06,600 --> 00:01:08,520
Speaker 5: Look, we're just inching into the green on the day,

22
00:01:08,520 --> 00:01:10,280
Speaker 5: we're off of our lows. But on the week, and

23
00:01:10,360 --> 00:01:12,479
Speaker 5: it's been turbulent and then some We're going to dig

24
00:01:12,520 --> 00:01:15,600
Speaker 5: into the pressures that we see on software that's continuing.

25
00:01:15,720 --> 00:01:17,479
Speaker 5: We're off by one point three percent on the week.

26
00:01:17,480 --> 00:01:19,360
Speaker 5: On the week, we're off by two point three percent.

27
00:01:19,360 --> 00:01:21,520
Speaker 5: On Bitcoin, we actually steady on the day.

28
00:01:21,680 --> 00:01:23,000
Speaker 4: Ed there's a lot to.

29
00:01:22,920 --> 00:01:26,039
Speaker 5: Be digesting about some of the market signals we're getting.

30
00:01:26,040 --> 00:01:26,720
Speaker 4: What are you looking at?

31
00:01:27,720 --> 00:01:29,479
Speaker 3: Later in the show, we're going to go deep on Rivian.

32
00:01:29,520 --> 00:01:31,000
Speaker 3: You and I are going to talk about what's going

33
00:01:31,040 --> 00:01:33,840
Speaker 3: on with this name. Up twenty percent in the session

34
00:01:33,880 --> 00:01:36,600
Speaker 3: at one point, up twenty eight percent, and on track

35
00:01:36,640 --> 00:01:38,840
Speaker 3: for its best day since it's IPO in November twenty

36
00:01:38,920 --> 00:01:41,520
Speaker 3: twenty one. Honestly, it doesn't even matter what it posted

37
00:01:41,560 --> 00:01:43,880
Speaker 3: in the quarter gone or what it said its financials

38
00:01:43,920 --> 00:01:46,280
Speaker 3: would be for this year. The stock is only trading

39
00:01:46,560 --> 00:01:49,320
Speaker 3: on the idea it's on track for its next generation

40
00:01:49,520 --> 00:01:52,320
Speaker 3: EVDR two and that will go on sale next quarter.

41
00:01:52,400 --> 00:01:54,640
Speaker 3: We'll have a lot more on the earning story. This

42
00:01:54,720 --> 00:01:57,880
Speaker 3: is the big breaking news of the morning. The Pentagon

43
00:01:58,240 --> 00:02:03,000
Speaker 3: added names Ali, barber I, Do and BYD to a

44
00:02:03,040 --> 00:02:07,960
Speaker 3: list of Chinese technology companies that it says are aiding

45
00:02:08,000 --> 00:02:11,680
Speaker 3: the Chinese military, only to then take down or pull

46
00:02:11,800 --> 00:02:16,400
Speaker 3: that list without any explanation. The moment that the headlines

47
00:02:16,480 --> 00:02:18,880
Speaker 3: hit from the list going up, you saw the US

48
00:02:18,960 --> 00:02:21,959
Speaker 3: listed shares of those names drop ten Cent was already

49
00:02:22,000 --> 00:02:24,639
Speaker 3: on the list that had been published earlier in January.

50
00:02:24,680 --> 00:02:27,640
Speaker 3: This is difficult to understand. Let's get to Bloomberg Senior

51
00:02:27,680 --> 00:02:31,480
Speaker 3: Tech editor Mike Shephard. I hope that I explained the

52
00:02:31,520 --> 00:02:35,320
Speaker 3: chronology of events correctly there give us the fuller details.

53
00:02:35,320 --> 00:02:38,600
Speaker 3: And my understanding is that Bloomberg News has also heard

54
00:02:38,600 --> 00:02:40,880
Speaker 3: from the Pentagon, but they didn't have much to say.

55
00:02:42,080 --> 00:02:43,600
Speaker 6: They didn't have much to say at all in the

56
00:02:43,600 --> 00:02:47,959
Speaker 6: way of an explanation about why this move. This list,

57
00:02:48,080 --> 00:02:50,760
Speaker 6: This updated list, which now has one hundred and thirty

58
00:02:50,840 --> 00:02:54,679
Speaker 6: Chinese entities on it, was posted in Age forty five

59
00:02:54,720 --> 00:02:57,679
Speaker 6: this morning, and then shortly after it withdrawn. They said

60
00:02:57,720 --> 00:03:01,400
Speaker 6: they had nothing to announce it the the moment now ed.

61
00:03:01,840 --> 00:03:06,399
Speaker 6: This is something that's become increasingly closely watched by investors

62
00:03:06,440 --> 00:03:09,280
Speaker 6: and by others who are wondering whether Chinese companies may

63
00:03:09,320 --> 00:03:13,440
Speaker 6: be suffering some sort of repercussions from elsewhere in the.

64
00:03:13,400 --> 00:03:14,680
Speaker 2: Government as well.

65
00:03:14,760 --> 00:03:17,679
Speaker 6: The twelve sixty h list, as it's known, is seen

66
00:03:17,720 --> 00:03:21,160
Speaker 6: as a precursor perhaps or bell Weather to further measures

67
00:03:21,200 --> 00:03:24,200
Speaker 6: that the government has taken against Chinese entities. And it's

68
00:03:24,240 --> 00:03:27,480
Speaker 6: also closely watched in particular because we see the addition

69
00:03:27,639 --> 00:03:31,160
Speaker 6: in this latest iteration that has since been withdrawn of

70
00:03:31,200 --> 00:03:34,480
Speaker 6: Ali Baba and Baidu, and those companies are making inroads

71
00:03:34,480 --> 00:03:37,680
Speaker 6: and artificial intelligence, and this is a central point of

72
00:03:37,720 --> 00:03:41,640
Speaker 6: contention and competition between the US and China right now.

73
00:03:41,760 --> 00:03:43,960
Speaker 5: It's the central point of contention when it comes to

74
00:03:44,000 --> 00:03:47,920
Speaker 5: open Ai. We understand through a document that's been seen

75
00:03:48,000 --> 00:03:51,560
Speaker 5: that was sent by Open Ai to Capitol Hill all

76
00:03:51,600 --> 00:03:54,520
Speaker 5: regarding their warriors, what Deep Sink's been doing with their technology.

77
00:03:55,840 --> 00:03:59,880
Speaker 6: Well, that's right, Karen. This comes amid so much scrutiny

78
00:04:00,080 --> 00:04:04,240
Speaker 6: on China and its advances in artificial intelligence, and open

79
00:04:04,280 --> 00:04:08,040
Speaker 6: Ai has warned US lawmakers that it believes Deep Seek

80
00:04:08,080 --> 00:04:12,880
Speaker 6: has been using improper methods to advance its models, especially

81
00:04:12,920 --> 00:04:15,640
Speaker 6: the R one breakthrough that we saw last year and

82
00:04:15,720 --> 00:04:18,279
Speaker 6: heard so much about. What they are saying, in essence

83
00:04:18,440 --> 00:04:23,400
Speaker 6: is that deep Seek has been using frontier models from

84
00:04:23,400 --> 00:04:27,719
Speaker 6: the US and elsewhere and copying and taking those results

85
00:04:27,720 --> 00:04:32,640
Speaker 6: and then improperly through a method called distillation, using it

86
00:04:32,720 --> 00:04:35,920
Speaker 6: to advance its own models and train its models, and

87
00:04:36,360 --> 00:04:38,640
Speaker 6: open I went further to say that it has been

88
00:04:38,720 --> 00:04:42,279
Speaker 6: raising these concerns, and we even scooped last year that

89
00:04:42,320 --> 00:04:45,880
Speaker 6: Microsoft and open Ai, who are partners in the open

90
00:04:45,880 --> 00:04:49,600
Speaker 6: Ai venture, had looked into the extent of distillation by

91
00:04:49,600 --> 00:04:53,440
Speaker 6: deep Seek and other Chinese ventures. Open Ai since in

92
00:04:53,520 --> 00:04:56,679
Speaker 6: this memo to Congress, is saying that it has tried

93
00:04:56,760 --> 00:05:00,359
Speaker 6: countermeasures against deep Seek, but deep Seek is c to

94
00:05:00,520 --> 00:05:03,799
Speaker 6: thwart those. It also noted what it called a national

95
00:05:03,839 --> 00:05:08,080
Speaker 6: security risk, and that is that with Deepseek searches under

96
00:05:08,120 --> 00:05:10,600
Speaker 6: topics that are sensitive to the Chinese government and then

97
00:05:10,640 --> 00:05:14,880
Speaker 6: include scannerman Square and Taiwan Independence for example, those are

98
00:05:15,040 --> 00:05:17,320
Speaker 6: screened out and you do not get the answers that

99
00:05:17,360 --> 00:05:19,920
Speaker 6: you might through open ai and other platforms.

100
00:05:20,320 --> 00:05:23,039
Speaker 5: Mike Sheppin on all the national security news, we so

101
00:05:23,120 --> 00:05:23,760
Speaker 5: appreciate it.

102
00:05:23,800 --> 00:05:26,000
Speaker 4: Thank you. Look, let's talk about open ai and.

103
00:05:25,920 --> 00:05:29,440
Speaker 5: This rival Anthropic because on Topics just finalized a deal

104
00:05:29,480 --> 00:05:32,240
Speaker 5: to raise thirty billion dollars, doubling the valuation of the

105
00:05:32,240 --> 00:05:34,880
Speaker 5: company to three hundred and eighty billion from All Blue

106
00:05:34,920 --> 00:05:37,640
Speaker 5: Measuring Gafari joins us. Now what's interesting is some of

107
00:05:37,680 --> 00:05:41,159
Speaker 5: the same vcs that back open Ai are backing Anthropic,

108
00:05:41,440 --> 00:05:43,960
Speaker 5: but talk to us about the Garganshuan valuation hit.

109
00:05:45,760 --> 00:05:49,720
Speaker 7: That's right, So this was even more money than Anthropic,

110
00:05:49,800 --> 00:05:53,840
Speaker 7: and we were initially expecting. The round went from ten

111
00:05:53,880 --> 00:05:56,800
Speaker 7: billion in initial talks to a thirty billion total, so

112
00:05:56,920 --> 00:06:00,200
Speaker 7: we have a big bottom number. And you know, we

113
00:06:00,240 --> 00:06:02,520
Speaker 7: are seeing what we you know, have have kind of

114
00:06:02,680 --> 00:06:06,159
Speaker 7: cloquially referred to as double dipping, or we're seeing investors

115
00:06:06,880 --> 00:06:10,279
Speaker 7: that maybe used to only focus on one big player

116
00:06:10,360 --> 00:06:13,239
Speaker 7: in the AI race actually start to hedge their bets

117
00:06:13,640 --> 00:06:17,200
Speaker 7: and also invest in competitors such as Anthropic, Open Ai

118
00:06:17,480 --> 00:06:21,440
Speaker 7: or Xai open Ai. And that's that's a newer phenomenon

119
00:06:21,480 --> 00:06:21,920
Speaker 7: in the valley.

120
00:06:21,960 --> 00:06:25,240
Speaker 3: I would say, we also surely now have some confirmation

121
00:06:25,360 --> 00:06:27,080
Speaker 3: of how Anthropics business has been going.

122
00:06:27,160 --> 00:06:27,360
Speaker 8: Right.

123
00:06:27,400 --> 00:06:30,440
Speaker 3: You and I've talked a lot about how Anthropics focus

124
00:06:30,520 --> 00:06:34,000
Speaker 3: initially was on the enterprise. Tell me what the annual

125
00:06:34,040 --> 00:06:36,640
Speaker 3: revenue run rate numbers are that we now have, and

126
00:06:37,000 --> 00:06:39,039
Speaker 3: I guess you know the reason we care so much

127
00:06:39,120 --> 00:06:41,800
Speaker 3: about this round is will this company go public or not?

128
00:06:44,160 --> 00:06:48,039
Speaker 7: That's right, We're seeing run rate go up just very

129
00:06:48,120 --> 00:06:52,680
Speaker 7: quickly from the last report of nine billion to thirteen.

130
00:06:53,400 --> 00:06:56,839
Speaker 7: We're also seeing the cloud code run rate in particular

131
00:06:56,880 --> 00:06:59,159
Speaker 7: go up, and now claud code is their coding agent

132
00:06:59,200 --> 00:07:01,919
Speaker 7: that's been very suc that's for so, I think that

133
00:07:02,000 --> 00:07:04,479
Speaker 7: this is showing that Anthropic even though it doesn't have

134
00:07:04,560 --> 00:07:07,360
Speaker 7: the kind of consumer reach that open ai does, which

135
00:07:07,360 --> 00:07:10,960
Speaker 7: sort of has the Kleenex phenomenon of chatchipt being the

136
00:07:10,960 --> 00:07:14,040
Speaker 7: brand everyone knows in the consumer space. But that doesn't

137
00:07:14,080 --> 00:07:16,240
Speaker 7: mean that anthropics should be counted out in terms of

138
00:07:16,280 --> 00:07:19,480
Speaker 7: being able to achieve some very high revenue projections and

139
00:07:19,600 --> 00:07:22,320
Speaker 7: very strong growth, which of course investors like to see.

140
00:07:22,920 --> 00:07:26,320
Speaker 3: Bloomberg sharing Gafari brilliant reporting. Thank you very much. We

141
00:07:26,360 --> 00:07:29,560
Speaker 3: have other funding news. Shield Ai, which makes AI powered

142
00:07:29,640 --> 00:07:33,440
Speaker 3: software to help run autonomous vehicles and other hardware like drones,

143
00:07:33,800 --> 00:07:35,920
Speaker 3: is in talks to raise as much as a billion dollars.

144
00:07:35,960 --> 00:07:39,320
Speaker 3: Sources say the new round would double its valuation in

145
00:07:39,400 --> 00:07:41,800
Speaker 3: less than a year. It up to twelve billion dollars,

146
00:07:41,840 --> 00:07:43,640
Speaker 3: which include the capital raised.

147
00:07:43,920 --> 00:07:47,200
Speaker 5: CARA coming up ed, we'll discuss the wider impact of

148
00:07:47,240 --> 00:07:52,360
Speaker 5: what's been termed the AI scare trade. The sericond Clear Capitals,

149
00:07:52,400 --> 00:08:11,680
Speaker 5: Blobotech Logistic Stocks became the latest victims of the so

150
00:08:11,800 --> 00:08:13,920
Speaker 5: called AI scare trade.

151
00:08:13,600 --> 00:08:17,200
Speaker 4: After a Karaoke turned to AHI company. Yes, I said

152
00:08:17,200 --> 00:08:19,080
Speaker 4: that right. It's a semi.

153
00:08:18,920 --> 00:08:22,280
Speaker 5: Cab platform and enables customers to scale freight volumes by

154
00:08:22,320 --> 00:08:24,200
Speaker 5: three hundred percent to four hundred percent. Shares of H

155
00:08:24,280 --> 00:08:27,360
Speaker 5: Robinson tumbled fifteen percent, adding to a growing mister companies

156
00:08:27,360 --> 00:08:31,880
Speaker 5: where AI fears a reshaping investor sentiment across sectors. Nomaga Equities,

157
00:08:31,920 --> 00:08:34,640
Speaker 5: Reporter Com, and Ryanikey has been across the latest and

158
00:08:34,720 --> 00:08:38,720
Speaker 5: I had to double triple check that this particular company

159
00:08:38,840 --> 00:08:44,880
Speaker 5: karaoke turned autonomous vehicle business. It's actually just six million

160
00:08:44,920 --> 00:08:48,520
Speaker 5: dollars in valuation, but it rocked market caps across the

161
00:08:48,720 --> 00:08:49,480
Speaker 5: entire industry.

162
00:08:50,840 --> 00:08:52,120
Speaker 4: Yeah, it's teeny tiny.

163
00:08:52,160 --> 00:08:54,600
Speaker 8: And actually the CEO told me yesterday that he had

164
00:08:54,640 --> 00:08:57,200
Speaker 8: never imagined, sort of in his wildest dreams, that they

165
00:08:57,200 --> 00:08:59,080
Speaker 8: would have a day like they did yesterday. I mean,

166
00:08:59,120 --> 00:09:02,000
Speaker 8: their stack was at more than twenty percent. So we've

167
00:09:02,040 --> 00:09:05,520
Speaker 8: really just seen sort of the fear of software disruption

168
00:09:05,720 --> 00:09:09,880
Speaker 8: from AI trickle across the broader market into these little

169
00:09:10,200 --> 00:09:12,920
Speaker 8: sectors that you wouldn't think were initially tied to the

170
00:09:12,960 --> 00:09:15,760
Speaker 8: AI trade. And some of the fear in software disruption

171
00:09:15,840 --> 00:09:18,840
Speaker 8: you know, may be founded, but it seems like there

172
00:09:18,840 --> 00:09:21,480
Speaker 8: are a lot of these knee jerk reactions and investors

173
00:09:21,480 --> 00:09:24,240
Speaker 8: are sort of turning and saying, you know, what's next?

174
00:09:24,280 --> 00:09:26,960
Speaker 8: How can I even protect from downside like this? Because

175
00:09:27,160 --> 00:09:30,720
Speaker 8: you know, just the smallest little headline or thing coming

176
00:09:30,760 --> 00:09:33,600
Speaker 8: out can send you know, all of these stocks off

177
00:09:33,600 --> 00:09:34,000
Speaker 8: a cliff.

178
00:09:35,040 --> 00:09:37,600
Speaker 3: Caroline was on this so quickly yesterday. But I think

179
00:09:37,600 --> 00:09:40,959
Speaker 3: there's some value in giving the Bloomberg Tech audience and

180
00:09:41,080 --> 00:09:43,320
Speaker 3: understanding a bit what it's like, right, so that headlines

181
00:09:43,320 --> 00:09:45,920
Speaker 3: are going on the terminal because there's certain stock moves,

182
00:09:45,960 --> 00:09:51,000
Speaker 3: there's volatility, you have like industrials, transport logistics teams, equities teams,

183
00:09:51,000 --> 00:09:53,079
Speaker 3: Like what is happening? You know, like all of these

184
00:09:53,080 --> 00:09:56,719
Speaker 3: stocks are falling. Just summarized that that session, we just

185
00:09:56,760 --> 00:09:59,679
Speaker 3: showed a great chart, but it was severe, right, and

186
00:09:59,720 --> 00:10:02,840
Speaker 3: then we still continue to see ongoing pressure and software

187
00:10:02,880 --> 00:10:04,640
Speaker 3: generally from the broader story.

188
00:10:06,040 --> 00:10:10,400
Speaker 8: Yeah, finding that the trip wire can be really difficult. Actually,

189
00:10:10,440 --> 00:10:13,760
Speaker 8: I mean we've seen so many things fall on pretty

190
00:10:13,800 --> 00:10:16,079
Speaker 8: small things or even you know, like in the instance

191
00:10:16,080 --> 00:10:19,120
Speaker 8: of real estate stocks past week, there wasn't a super

192
00:10:19,160 --> 00:10:23,320
Speaker 8: immediately clear catalyst that drove selling in that sector. So

193
00:10:23,720 --> 00:10:25,600
Speaker 8: it is definitely, you know, a team effort. You know,

194
00:10:25,640 --> 00:10:28,439
Speaker 8: I'm speaking to investors as much as possible to see

195
00:10:28,480 --> 00:10:31,440
Speaker 8: sar of what they're thinking, how they're reacting to these

196
00:10:31,480 --> 00:10:34,839
Speaker 8: sort of like sparked sell offs. And yeah, it's been

197
00:10:34,880 --> 00:10:37,880
Speaker 8: a full collaboration, right because we just don't know what's next.

198
00:10:37,920 --> 00:10:40,280
Speaker 8: There are so many different parts of the market that

199
00:10:40,440 --> 00:10:42,960
Speaker 8: could see potential disruption.

200
00:10:42,640 --> 00:10:43,760
Speaker 9: Here and where.

201
00:10:43,840 --> 00:10:47,160
Speaker 8: You know, these fears could spark another decline in shares.

202
00:10:47,360 --> 00:10:49,120
Speaker 5: While you were sort of calling up the CEO of

203
00:10:49,160 --> 00:10:52,880
Speaker 5: Algorithm that was affecting logistics, we understand we were speaking

204
00:10:52,880 --> 00:10:56,520
Speaker 5: to the CEO of Altruist, which is the wealth management

205
00:10:56,720 --> 00:11:01,160
Speaker 5: start up that discombobulated wealth management market more broadly, and

206
00:11:01,200 --> 00:11:03,720
Speaker 5: he too had this sort of David Goliath moment common

207
00:11:04,160 --> 00:11:06,280
Speaker 5: But what's so interesting is ED and I speak a

208
00:11:06,280 --> 00:11:09,439
Speaker 5: lot to the VC back companies that are developing the

209
00:11:09,520 --> 00:11:14,439
Speaker 5: latest autonomous vehicles and trucking and bringing up these new platforms.

210
00:11:15,200 --> 00:11:19,080
Speaker 5: How discerning our investors starting to become to a headline

211
00:11:19,200 --> 00:11:22,680
Speaker 5: risk or actually what is going to upend the industries

212
00:11:22,720 --> 00:11:25,240
Speaker 5: they put money into, Because is really a seven million

213
00:11:25,280 --> 00:11:27,320
Speaker 5: dollar algorithm company going to do that.

214
00:11:28,840 --> 00:11:30,720
Speaker 8: You know, I think we've seen actually really a lack

215
00:11:30,760 --> 00:11:33,880
Speaker 8: of discernment. Right, Everything is a very knee jerk reaction.

216
00:11:34,040 --> 00:11:34,199
Speaker 2: Now.

217
00:11:34,240 --> 00:11:36,760
Speaker 8: I keep hearing people say over and over something along

218
00:11:36,800 --> 00:11:40,000
Speaker 8: the lines of, you know, sell first, ask questions later.

219
00:11:40,080 --> 00:11:42,200
Speaker 8: And I think, actually, what I'm hearing from, you know,

220
00:11:42,559 --> 00:11:45,560
Speaker 8: fund managers and people on the street is they're looking

221
00:11:45,679 --> 00:11:49,080
Speaker 8: or trying to impress sort of maybe more discernment on investors,

222
00:11:50,360 --> 00:11:53,600
Speaker 8: so they're not sort of making these very like snap decisions.

223
00:11:54,840 --> 00:11:58,640
Speaker 8: We'll have to keep seeing what happens. It's definitely been

224
00:11:59,000 --> 00:12:00,679
Speaker 8: you know, a while a few days.

225
00:12:01,679 --> 00:12:04,160
Speaker 3: Bloomer's Carmen Rhiniky, You've been brilliant for a number of

226
00:12:04,200 --> 00:12:06,679
Speaker 3: weeks in a row trying to explain what's going on

227
00:12:06,960 --> 00:12:09,599
Speaker 3: the AI scare. It sent market caps across stocks in

228
00:12:09,679 --> 00:12:12,240
Speaker 3: multiple industries humbling. We've just explained that, but all that

229
00:12:12,280 --> 00:12:16,560
Speaker 3: disruption hasn't hit top lines. That's notable not just for

230
00:12:16,600 --> 00:12:20,360
Speaker 3: public company shareholders, but for private market investors who are

231
00:12:20,360 --> 00:12:23,760
Speaker 3: trying to find their next win. Surrocance, managing director of

232
00:12:23,760 --> 00:12:27,400
Speaker 3: Clear Capital, a generalist VC firm multiple software companies in

233
00:12:27,440 --> 00:12:28,200
Speaker 3: its portfolio.

234
00:12:28,440 --> 00:12:30,400
Speaker 2: Sarah, that's your job, right, like you.

235
00:12:30,360 --> 00:12:32,800
Speaker 3: Know, in the case study of a software name with

236
00:12:32,840 --> 00:12:36,520
Speaker 3: a six million dollar valuation that spooked an entire logistics

237
00:12:36,559 --> 00:12:40,400
Speaker 3: sector yesterday, you want to be finding those names through

238
00:12:40,440 --> 00:12:43,600
Speaker 3: that lens. What's your interpretation of what we've seen this

239
00:12:43,640 --> 00:12:46,839
Speaker 3: week across multiple sectors where software is coming for it.

240
00:12:47,679 --> 00:12:50,080
Speaker 10: Yeah, I want to find companies that are going to

241
00:12:50,200 --> 00:12:54,079
Speaker 10: disrupt markets because they have a great product, not because

242
00:12:54,120 --> 00:12:55,560
Speaker 10: they have great Twitter fingers.

243
00:12:55,800 --> 00:12:57,119
Speaker 4: And so I think part.

244
00:12:56,840 --> 00:13:00,000
Speaker 10: Of what we're seeing right now that makes investors nervous

245
00:13:00,080 --> 00:13:03,760
Speaker 10: on the startup side private investors is that we want

246
00:13:03,800 --> 00:13:06,960
Speaker 10: to make sure that these companies, the CEOs who are

247
00:13:06,960 --> 00:13:10,120
Speaker 10: going viral with these sort of hey guess what, everything's

248
00:13:10,160 --> 00:13:14,319
Speaker 10: falling apart, that they actually have an interesting solution, because

249
00:13:14,360 --> 00:13:19,040
Speaker 10: otherwise they're just sort of a megaphone, not necessarily a unicorn.

250
00:13:19,679 --> 00:13:21,000
Speaker 2: I said software coming for it.

251
00:13:21,040 --> 00:13:24,240
Speaker 3: I meant AI coming for it, even coming for existing

252
00:13:24,240 --> 00:13:29,360
Speaker 3: software platforms. Is there real risk to establish industries here imminently.

253
00:13:30,840 --> 00:13:31,040
Speaker 11: Yeah.

254
00:13:31,080 --> 00:13:33,479
Speaker 10: I think that there's risk long term, but the reality

255
00:13:33,679 --> 00:13:36,160
Speaker 10: is that a lot of that risk is going to

256
00:13:36,200 --> 00:13:40,359
Speaker 10: be sort of taken up by companies in those industries.

257
00:13:40,400 --> 00:13:43,920
Speaker 10: So it's not like logistics is ignoring what's happening right

258
00:13:44,000 --> 00:13:46,080
Speaker 10: When you look at some of the bigger logistics players,

259
00:13:46,120 --> 00:13:48,880
Speaker 10: you have companies like the Nordics who have been consistently

260
00:13:48,920 --> 00:13:52,040
Speaker 10: sort of ahead on software, investing on their pension arm

261
00:13:52,240 --> 00:13:55,040
Speaker 10: So they're obviously, I'm sure, having those kinds of conversations,

262
00:13:55,080 --> 00:13:58,560
Speaker 10: and so I think it's a little bit flipant to

263
00:13:58,640 --> 00:14:01,360
Speaker 10: think that you're going to end in a situation where

264
00:14:01,920 --> 00:14:04,680
Speaker 10: logistics didn't see this coming. Of course they know, and

265
00:14:04,720 --> 00:14:07,400
Speaker 10: there are often placing bets into startups or building and

266
00:14:07,480 --> 00:14:11,360
Speaker 10: buying technology in house that can help them sort of

267
00:14:11,400 --> 00:14:13,200
Speaker 10: be a part of that change, kind of the same

268
00:14:13,240 --> 00:14:16,000
Speaker 10: way in oil and gas we've seen them often also

269
00:14:16,080 --> 00:14:19,360
Speaker 10: get some upside as it transitions to a cleaner energy.

270
00:14:20,360 --> 00:14:22,880
Speaker 5: It makes a great point, and I'll chat that you know,

271
00:14:22,920 --> 00:14:24,600
Speaker 5: you would have thought Flexport would be the company that

272
00:14:24,640 --> 00:14:28,840
Speaker 5: would be uphending the future of transportation and logistics AI.

273
00:14:29,200 --> 00:14:31,600
Speaker 5: From your perspective, how are you at this moment seeing

274
00:14:31,600 --> 00:14:35,480
Speaker 5: the valuations in startups reflecting this FOMO or this fear

275
00:14:35,520 --> 00:14:38,080
Speaker 5: fact that you see in the public markets.

276
00:14:37,880 --> 00:14:41,160
Speaker 10: There's a huge barbell right now in valuations for startups,

277
00:14:41,160 --> 00:14:43,360
Speaker 10: and what you tend to see is there a handful

278
00:14:43,400 --> 00:14:47,440
Speaker 10: of companies mostly in AI, like Anthropics, Giant Round, like

279
00:14:47,520 --> 00:14:51,000
Speaker 10: some of what Elon's doing with his various country companies

280
00:14:51,880 --> 00:14:55,240
Speaker 10: like Open Ai, where those private names are going up

281
00:14:55,240 --> 00:14:57,400
Speaker 10: and up and up, and we all have no idea

282
00:14:57,400 --> 00:14:58,960
Speaker 10: how they're going to make that money back in an

283
00:14:59,000 --> 00:15:02,880
Speaker 10: IPO or ever be profitable. And then on the other hand,

284
00:15:03,280 --> 00:15:06,880
Speaker 10: you have startups that aren't promising the world, and we're

285
00:15:06,880 --> 00:15:10,280
Speaker 10: seeing a lot less velocity in those startup fundraising rounds,

286
00:15:10,480 --> 00:15:13,240
Speaker 10: not because there's anything wrong with those companies, but just

287
00:15:13,280 --> 00:15:16,160
Speaker 10: because people are worried about, Hey, if all of the

288
00:15:16,240 --> 00:15:19,680
Speaker 10: capital intensity is going over there, do I really want

289
00:15:19,720 --> 00:15:22,880
Speaker 10: to be in these sort of solid, interesting, slower growing

290
00:15:22,920 --> 00:15:26,400
Speaker 10: companies that might actually end up being profitable but don't

291
00:15:26,400 --> 00:15:29,000
Speaker 10: feel like they're going to be multi trillion dollar IPOs.

292
00:15:29,880 --> 00:15:32,400
Speaker 5: Although any solid SaaS companies.

293
00:15:31,960 --> 00:15:34,640
Speaker 10: Out there right now, I think there are a lot

294
00:15:34,720 --> 00:15:37,200
Speaker 10: of solid SaaS companies. I mean, even in the public markets,

295
00:15:37,240 --> 00:15:39,240
Speaker 10: you look at names like Salesforce and you have to

296
00:15:39,320 --> 00:15:42,120
Speaker 10: kind of ask, why do people, even though the valuation

297
00:15:42,240 --> 00:15:44,400
Speaker 10: is a bit high, why do people think that this

298
00:15:44,520 --> 00:15:47,440
Speaker 10: is going to go away overnight? When when they look

299
00:15:47,440 --> 00:15:49,720
Speaker 10: inside of their own companies, they're not in a rush

300
00:15:49,960 --> 00:15:53,040
Speaker 10: to cancel all their contracts and just yolo everything into

301
00:15:53,080 --> 00:15:56,600
Speaker 10: chat GPT. But for some reason, there's the thought that

302
00:15:56,600 --> 00:15:59,880
Speaker 10: that is going to happen overnight in the larger market

303
00:16:00,080 --> 00:16:02,680
Speaker 10: and all of these companies are going to be valueless.

304
00:16:03,360 --> 00:16:06,320
Speaker 5: Sarahkunst looking at a portfolio right now. We appreciate it,

305
00:16:06,520 --> 00:16:09,720
Speaker 5: Managing director of Cleo Capital. Coming up, we're going to

306
00:16:09,760 --> 00:16:13,600
Speaker 5: speak with a software company, Twilio CEO Cozmership Chandlers joining us.

307
00:16:13,640 --> 00:16:16,080
Speaker 4: The latest earnings they were good. As a Bloomberg Tech.

308
00:16:29,880 --> 00:16:31,840
Speaker 5: Shares a Twilio holding on too, Gaines were up two

309
00:16:31,920 --> 00:16:34,920
Speaker 5: point four percent, the company posting solid fourth quarter earnings

310
00:16:34,960 --> 00:16:38,200
Speaker 5: results and guidance, driven in many ways by gains and

311
00:16:38,280 --> 00:16:42,320
Speaker 5: voice and messaging. Company also issued its revenue forecast of

312
00:16:42,360 --> 00:16:46,000
Speaker 5: about fourteen percent that top DNAs estimates. Twilio CEO cozemer

313
00:16:46,080 --> 00:16:50,280
Speaker 5: Hip Chandler is with US and Kazima. What's driving the

314
00:16:50,360 --> 00:16:54,400
Speaker 5: adoption You talk about becoming sort of a foundational infrastructure layer.

315
00:16:54,400 --> 00:16:55,080
Speaker 4: What does that look like?

316
00:16:56,400 --> 00:16:58,240
Speaker 12: Yeah, I mean I think for us, what it means

317
00:16:58,360 --> 00:17:02,040
Speaker 12: is is that companies increased They've always been using us

318
00:17:02,080 --> 00:17:06,040
Speaker 12: for communications and for data, but increasingly they're pointing their

319
00:17:06,080 --> 00:17:08,879
Speaker 12: workloads towards us. And I'm talking about AI companies as

320
00:17:08,880 --> 00:17:14,320
Speaker 12: well as enterprises as infrastructure that allows them to connect

321
00:17:14,760 --> 00:17:19,320
Speaker 12: the llms, the data warehouses, the agents that they're now

322
00:17:19,359 --> 00:17:22,720
Speaker 12: starting to build with, and Telco's put all of those

323
00:17:22,720 --> 00:17:25,840
Speaker 12: different capabilities together under one platform.

324
00:17:25,880 --> 00:17:27,800
Speaker 13: And that's I think what uniquely positions.

325
00:17:27,400 --> 00:17:32,480
Speaker 5: Twilio uniquely positions you against this so called SaaS apocalypse

326
00:17:32,560 --> 00:17:35,520
Speaker 5: how much because they imagine you get questions on an

327
00:17:35,520 --> 00:17:40,400
Speaker 5: ongoing basis from investors saying how resilient is the way

328
00:17:40,400 --> 00:17:41,600
Speaker 5: in which you charge customers.

329
00:17:43,040 --> 00:17:46,479
Speaker 12: Yeah, we don't get as many questions about that that topic. Actually,

330
00:17:46,520 --> 00:17:48,600
Speaker 12: I mean, I think the reality is is that, you know,

331
00:17:48,600 --> 00:17:51,199
Speaker 12: we've always been sort of an infrastructure provider, and so

332
00:17:51,840 --> 00:17:54,560
Speaker 12: there's some level of insulation in that way.

333
00:17:54,600 --> 00:17:56,600
Speaker 13: Like what we do is like very unique.

334
00:17:56,880 --> 00:17:59,520
Speaker 12: I think the other dynamic that is at play here

335
00:17:59,640 --> 00:18:03,479
Speaker 12: is that our pricing model has always been usage based

336
00:18:03,520 --> 00:18:06,080
Speaker 12: and so you know, if you're worried about what the

337
00:18:06,119 --> 00:18:09,680
Speaker 12: terminal value is associated with seat licenses and stuff like that,

338
00:18:09,760 --> 00:18:11,120
Speaker 12: like that's not something that we.

339
00:18:11,040 --> 00:18:12,120
Speaker 13: Think about day to day.

340
00:18:12,240 --> 00:18:14,760
Speaker 12: Instead, we think about how do we combine all of

341
00:18:14,800 --> 00:18:17,159
Speaker 12: these different elements that are coming to the fore to

342
00:18:17,240 --> 00:18:18,680
Speaker 12: create a great customer experience.

343
00:18:18,720 --> 00:18:19,240
Speaker 13: On the other.

344
00:18:19,119 --> 00:18:22,480
Speaker 3: Side, it's great to have you back on the show,

345
00:18:22,920 --> 00:18:24,840
Speaker 3: going back to basics with Twilio. I think it really

346
00:18:24,880 --> 00:18:28,840
Speaker 3: helps the audience understand right, Twilio does customer engagement, and

347
00:18:28,880 --> 00:18:31,439
Speaker 3: on the show every week Caroline and I get told

348
00:18:31,480 --> 00:18:36,119
Speaker 3: that the area that is most imminently ripe for improvement

349
00:18:37,240 --> 00:18:41,560
Speaker 3: is call center essentially that kind of domain. The analysts

350
00:18:41,560 --> 00:18:43,560
Speaker 3: are looking at the results and the outlook and saying

351
00:18:43,600 --> 00:18:45,679
Speaker 3: that you might be being a bit conservative and a

352
00:18:45,680 --> 00:18:49,240
Speaker 3: bit muted. They want to see more evidence that voice AI,

353
00:18:49,640 --> 00:18:52,480
Speaker 3: as an example, is really taking off. What do you

354
00:18:52,520 --> 00:18:55,159
Speaker 3: see on the ground, so to speak, Osmer.

355
00:18:55,920 --> 00:18:57,720
Speaker 12: I mean, you know, look, we want to see more too.

356
00:18:58,040 --> 00:19:00,320
Speaker 12: I mean, I think we feel pretty good about the look.

357
00:19:00,359 --> 00:19:02,960
Speaker 12: We feel great about the way that twenty twenty six

358
00:19:03,040 --> 00:19:05,639
Speaker 12: is shaping up so far, and we're pretty positive on

359
00:19:05,680 --> 00:19:08,600
Speaker 12: it all. I think as it relates to voice AI specifically,

360
00:19:08,640 --> 00:19:10,320
Speaker 12: since that's kind of where you started, I mean, I

361
00:19:10,359 --> 00:19:14,080
Speaker 12: think you're seeing tremendous velocity from a number of different companies.

362
00:19:14,560 --> 00:19:16,639
Speaker 12: You know, we called out a number of them in

363
00:19:16,680 --> 00:19:19,480
Speaker 12: our most recent earnings. You know, I'll just take an

364
00:19:19,520 --> 00:19:22,960
Speaker 12: example like Sierra, like they've really captured the imagination right

365
00:19:23,000 --> 00:19:26,520
Speaker 12: now in this moment. We're lucky to have them utilizing

366
00:19:26,640 --> 00:19:29,280
Speaker 12: our infrastructure to be able to grow with a customer

367
00:19:29,480 --> 00:19:33,080
Speaker 12: like that and add different kinds of voice capabilities to

368
00:19:33,880 --> 00:19:36,840
Speaker 12: the speech to text and text to speech capabilities that

369
00:19:36,880 --> 00:19:40,000
Speaker 12: they offer. So I think that's really been exciting and

370
00:19:40,040 --> 00:19:42,920
Speaker 12: interesting for us. And then I think looking forward there's

371
00:19:42,920 --> 00:19:45,440
Speaker 12: a number of other growth vectors that we're looking at.

372
00:19:45,840 --> 00:19:51,520
Speaker 12: This idea of having persistence, memory, context, being able to

373
00:19:51,560 --> 00:19:55,000
Speaker 12: combine all of that also with agent building capabilities. I

374
00:19:55,000 --> 00:19:58,400
Speaker 12: think that's what creates durable tailwind for our company.

375
00:20:00,160 --> 00:20:02,439
Speaker 3: The usage based model is you just described it. It's

376
00:20:02,480 --> 00:20:05,840
Speaker 3: a great advantage for you, right, And I think again,

377
00:20:06,160 --> 00:20:08,879
Speaker 3: just going on the reaction to earnings, some of the

378
00:20:08,920 --> 00:20:10,840
Speaker 3: concern is that if the outlook for the rest of

379
00:20:10,880 --> 00:20:14,560
Speaker 3: the year is conservative, how much is that because you

380
00:20:14,600 --> 00:20:18,760
Speaker 3: don't have visibility that far afield on a usage based

381
00:20:19,080 --> 00:20:20,200
Speaker 3: model from your customers.

382
00:20:21,520 --> 00:20:22,919
Speaker 13: Yeah, I think it's less about that.

383
00:20:23,040 --> 00:20:25,240
Speaker 12: I mean, I just think the dynamics of a usage

384
00:20:25,280 --> 00:20:27,600
Speaker 12: based business maybe cause us to be a little bit

385
00:20:27,600 --> 00:20:30,720
Speaker 12: more conservative about the way that we forecast and the

386
00:20:30,760 --> 00:20:32,600
Speaker 12: way that we kind of call it. I wouldn't take

387
00:20:32,640 --> 00:20:36,240
Speaker 12: that as signal that there's any dampening of optimism in

388
00:20:36,320 --> 00:20:37,159
Speaker 12: terms of our business.

389
00:20:37,320 --> 00:20:39,800
Speaker 13: Quite the contrary. I mean, the signals we're.

390
00:20:39,600 --> 00:20:42,480
Speaker 12: Hearing from customers are that they want to go all

391
00:20:42,520 --> 00:20:45,760
Speaker 12: in with Tulio again, not just communications and data, but

392
00:20:45,840 --> 00:20:49,560
Speaker 12: to build their entire AI stack around a lot of

393
00:20:49,560 --> 00:20:52,320
Speaker 12: our infrastructure, including a number of other companies obviously as

394
00:20:52,359 --> 00:20:55,560
Speaker 12: well who will end up partnering with. But I think

395
00:20:55,600 --> 00:21:00,680
Speaker 12: this usage based pricing model like ideally positions us because

396
00:21:00,840 --> 00:21:04,720
Speaker 12: it matches a customer's revenue events with our revenue events,

397
00:21:04,760 --> 00:21:07,880
Speaker 12: and so our incentives are very very tightly aligned.

398
00:21:08,240 --> 00:21:11,320
Speaker 5: Because I know there's a lot of fear, there's a

399
00:21:11,320 --> 00:21:14,000
Speaker 5: lot of anxiety you're not just in investors, but in

400
00:21:14,040 --> 00:21:16,240
Speaker 5: people writ large around AI at the moment, How are

401
00:21:16,280 --> 00:21:19,040
Speaker 5: you thinking about that around your own labor force and

402
00:21:19,080 --> 00:21:21,440
Speaker 5: about how you make your business as efficient as possible

403
00:21:21,440 --> 00:21:23,600
Speaker 5: by adopting the tools with which you're currently building upon.

404
00:21:24,960 --> 00:21:27,560
Speaker 12: Yeah, Look, my personal view is is that I don't

405
00:21:27,600 --> 00:21:30,919
Speaker 12: think AI is per se coming for the workforce. I mean,

406
00:21:31,040 --> 00:21:34,600
Speaker 12: I think frankly, it's going to be tremendously additive to

407
00:21:34,640 --> 00:21:36,760
Speaker 12: the workforce, like you know, I've got a kid in college.

408
00:21:36,800 --> 00:21:37,919
Speaker 13: I've got one that's about to go.

409
00:21:38,080 --> 00:21:41,000
Speaker 12: I actually think what's about to happen here is is

410
00:21:41,040 --> 00:21:43,600
Speaker 12: that over the next five to seven years you're going

411
00:21:43,680 --> 00:21:46,760
Speaker 12: to have a whole slew of college graduates who are

412
00:21:46,960 --> 00:21:50,200
Speaker 12: AI natives, who are going to add so much more

413
00:21:50,359 --> 00:21:54,160
Speaker 12: interesting and intellectual capacity to the workforce that I actually

414
00:21:54,200 --> 00:21:56,320
Speaker 12: think workforces could potentially.

415
00:21:55,800 --> 00:21:57,200
Speaker 13: Grow in many ways.

416
00:21:57,560 --> 00:22:00,119
Speaker 12: I think what is you know, probably a certainty is

417
00:22:00,119 --> 00:22:03,480
Speaker 12: is that those who don't retrain or reskill with different

418
00:22:03,560 --> 00:22:06,320
Speaker 12: kinds of AI capabilities, they're probably more at risk. And

419
00:22:06,680 --> 00:22:09,160
Speaker 12: you know, we're working hard to make sure that our

420
00:22:09,240 --> 00:22:13,080
Speaker 12: workforce is retrained, reskilled. We're adding a number of different

421
00:22:13,119 --> 00:22:16,399
Speaker 12: capabilities to our own internal tech stack. There's a number

422
00:22:16,440 --> 00:22:19,400
Speaker 12: of things that we're doing to use AI inside the company.

423
00:22:19,800 --> 00:22:22,120
Speaker 12: You know, at you pointed to customer service a moment ago,

424
00:22:22,160 --> 00:22:25,680
Speaker 12: we're certainly using it their inbound sales. We're certainly using

425
00:22:25,720 --> 00:22:27,120
Speaker 12: it there. And I think there'll be a lot more

426
00:22:27,160 --> 00:22:28,520
Speaker 12: other things that we do going forward.

427
00:22:29,040 --> 00:22:33,520
Speaker 5: Cosimship Chandler embracing it. We thank you so much, Twilio CEO.

428
00:22:33,600 --> 00:22:36,439
Speaker 5: There coming up, we'll take a look at Airbnb and

429
00:22:36,600 --> 00:22:39,359
Speaker 5: Instacart's earnings, so coming thick of fast folks.

430
00:22:39,480 --> 00:23:02,840
Speaker 14: This a bring by Tech, Welcome back to Bloomberg Tech.

431
00:23:02,840 --> 00:23:04,879
Speaker 3: At the top of the show, our top story was

432
00:23:05,000 --> 00:23:09,200
Speaker 3: US listed shares of Chinese technology companies. The Pentagon briefly

433
00:23:09,240 --> 00:23:13,879
Speaker 3: listed Ali Barber, Baidu, and byd as being names that

434
00:23:14,000 --> 00:23:17,200
Speaker 3: it considers as aiding the Chinese military. Then that list

435
00:23:17,240 --> 00:23:21,200
Speaker 3: was pulled from the internet, essentially. In Vidia also down

436
00:23:21,240 --> 00:23:24,240
Speaker 3: two percent. I'm not drawing a causal link, but remember

437
00:23:24,240 --> 00:23:26,760
Speaker 3: that in Ali Barber's case, Embido as well, they are

438
00:23:26,800 --> 00:23:30,840
Speaker 3: big potential buyers and video GPUs if that is a

439
00:23:30,840 --> 00:23:33,879
Speaker 3: transaction that's allowed to go through by the US government. Also,

440
00:23:34,240 --> 00:23:38,399
Speaker 3: taking a look at shares of Amazon Caro, we are

441
00:23:38,480 --> 00:23:40,600
Speaker 3: teetering on the edge. They are flat as a pancake

442
00:23:40,720 --> 00:23:43,679
Speaker 3: right now in the session, but had been headed for

443
00:23:43,720 --> 00:23:47,160
Speaker 3: their ninth straight day of declines following that monster Capex

444
00:23:47,160 --> 00:23:49,960
Speaker 3: outlook for the year. Ninth straight day of declines would

445
00:23:49,960 --> 00:23:52,760
Speaker 3: be the worst losing streak since two thousand and six,

446
00:23:53,160 --> 00:23:54,720
Speaker 3: which I guess if you look at the right hand

447
00:23:54,720 --> 00:23:57,480
Speaker 3: side of that chart and the slide gives you a

448
00:23:57,560 --> 00:24:00,640
Speaker 3: sense of anxiety. Right now with capital expenditure also looking

449
00:24:00,640 --> 00:24:01,520
Speaker 3: at Rivian.

450
00:24:01,760 --> 00:24:03,720
Speaker 2: So Rivian really on a tear.

451
00:24:04,000 --> 00:24:06,360
Speaker 3: Remember it was down thirty percent almost year today it's

452
00:24:06,400 --> 00:24:08,840
Speaker 3: now up twenty four percent in the session. Doesn't really

453
00:24:08,840 --> 00:24:11,280
Speaker 3: matter what they posted in the court gone, but they's

454
00:24:11,320 --> 00:24:13,760
Speaker 3: basically on track for their next product, the R two,

455
00:24:14,080 --> 00:24:15,520
Speaker 3: And that's all the market cares about.

456
00:24:15,600 --> 00:24:19,399
Speaker 5: I mean, talk about the R two because it's got

457
00:24:19,440 --> 00:24:21,680
Speaker 5: to be able to inspire purchasing at a time where

458
00:24:21,720 --> 00:24:25,400
Speaker 5: we've taken away some of the support from the government

459
00:24:25,520 --> 00:24:28,320
Speaker 5: and we are seeing just EV's on a downhill trajectory.

460
00:24:29,080 --> 00:24:29,320
Speaker 2: Yeah.

461
00:24:29,480 --> 00:24:32,800
Speaker 3: You know, Rivian today had two premium consumer products that

462
00:24:32,840 --> 00:24:35,440
Speaker 3: are on SSUVR and TE pick up, and it didn't

463
00:24:35,480 --> 00:24:38,000
Speaker 3: have a mass market product. The R two is supposed

464
00:24:38,040 --> 00:24:40,440
Speaker 3: to be that it's still at a premium price point,

465
00:24:40,560 --> 00:24:43,520
Speaker 3: and Rivian and its cor J Scarring are basically argued

466
00:24:43,560 --> 00:24:46,359
Speaker 3: there isn't much out there below seventy thousand US dollars

467
00:24:46,640 --> 00:24:48,080
Speaker 3: for the everyday family.

468
00:24:48,320 --> 00:24:50,080
Speaker 2: You know, in the SUV form.

469
00:24:49,960 --> 00:24:53,400
Speaker 3: Factor, it's like the Toyota RAB four of evs. And

470
00:24:53,440 --> 00:24:55,720
Speaker 3: all they're saying is that, you know, things are going

471
00:24:55,760 --> 00:24:58,280
Speaker 3: as they said they would. And that chart there tells

472
00:24:58,280 --> 00:25:01,760
Speaker 3: the story that spike that you around December, that's when

473
00:25:01,800 --> 00:25:03,920
Speaker 3: they announced that their AI plans, right, which we went

474
00:25:03,960 --> 00:25:06,199
Speaker 3: deep on, and then it faded because there was a

475
00:25:06,200 --> 00:25:08,679
Speaker 3: lot of anxiety that they'd fall behind on the actual

476
00:25:08,680 --> 00:25:09,400
Speaker 3: product delivery.

477
00:25:09,400 --> 00:25:11,160
Speaker 5: I mean, they had been kind of cost right per vehicle,

478
00:25:11,200 --> 00:25:13,639
Speaker 5: more than seven thousand dollars, like in lockstep with the

479
00:25:13,640 --> 00:25:16,040
Speaker 5: amount that you're now not getting in terms of subsidization.

480
00:25:16,320 --> 00:25:20,040
Speaker 4: But it's interesting the delivery numbers. Are they optimistic?

481
00:25:20,160 --> 00:25:21,960
Speaker 5: Is it positive to be between sixty two and sixty

482
00:25:22,000 --> 00:25:22,600
Speaker 5: seven thousand.

483
00:25:23,240 --> 00:25:26,320
Speaker 3: It's more than last year, but it's still is low volume, right,

484
00:25:26,359 --> 00:25:28,920
Speaker 3: and they're still going to lose two billion dollars this year.

485
00:25:28,960 --> 00:25:32,040
Speaker 3: And there's still one to watch though, because of you know,

486
00:25:32,119 --> 00:25:34,400
Speaker 3: all the people that back them and the hype around

487
00:25:34,520 --> 00:25:37,600
Speaker 3: their tech elsewhere and earning strong demand for travel help

488
00:25:37,640 --> 00:25:42,160
Speaker 3: booth shares of Airbnb bloem most Natalie Lung joins US. Now, Airbnb,

489
00:25:42,440 --> 00:25:44,800
Speaker 3: what's the story here? You know, what are they doing

490
00:25:44,840 --> 00:25:47,479
Speaker 3: that's new, that's different and that's giving them a boost.

491
00:25:49,040 --> 00:25:51,680
Speaker 11: Last year they rolled out a reserve now, pay later

492
00:25:52,080 --> 00:25:55,000
Speaker 11: option in the US, and that's really how boost bookings,

493
00:25:55,160 --> 00:25:58,240
Speaker 11: letting people book in advance without worrying about their budgets

494
00:25:58,280 --> 00:26:01,560
Speaker 11: so much, and there expecting to roll this out to

495
00:26:01,680 --> 00:26:06,720
Speaker 11: more markets globally, so that could continue help help the results.

496
00:26:07,240 --> 00:26:10,080
Speaker 11: And this year CEO branch has can really put a

497
00:26:10,080 --> 00:26:13,399
Speaker 11: big focus on launching new businesses. Yesterday he talked about

498
00:26:13,600 --> 00:26:18,080
Speaker 11: possibly testing airport pickup services and we also know their

499
00:26:18,119 --> 00:26:19,919
Speaker 11: testing grocery delivery for guests.

500
00:26:21,480 --> 00:26:23,840
Speaker 3: We're up four percent. At one point, we'd been up

501
00:26:23,840 --> 00:26:26,320
Speaker 3: almost ten percent in the session. I know we're here

502
00:26:26,359 --> 00:26:29,199
Speaker 3: to talk about tech, Natalie, but does Airbnb tell us

503
00:26:29,240 --> 00:26:31,640
Speaker 3: anything about the kind of health of the travel industry

504
00:26:31,720 --> 00:26:34,639
Speaker 3: right now and the consumer around the world to spend

505
00:26:34,680 --> 00:26:36,640
Speaker 3: money on travel and experiences.

506
00:26:37,119 --> 00:26:42,520
Speaker 11: Yes, so, US travel has been pretty strong, and especially

507
00:26:42,760 --> 00:26:46,040
Speaker 11: strong in their international markets as well, which are growing

508
00:26:46,080 --> 00:26:50,480
Speaker 11: at almost like twice as fast than their core markets.

509
00:26:50,800 --> 00:26:54,320
Speaker 11: They called out Brazil, Japan, and India has also seen

510
00:26:54,359 --> 00:26:55,880
Speaker 11: a lot of first time bookers for them.

511
00:26:56,280 --> 00:27:00,679
Speaker 5: Let's talk about the strength of groceries in Stacar really

512
00:27:00,720 --> 00:27:01,919
Speaker 5: impressing investors, Nahani.

513
00:27:02,400 --> 00:27:06,840
Speaker 11: Yes, yesterday they provided first quarter guidance that could be

514
00:27:06,880 --> 00:27:11,320
Speaker 11: their strongest quarterly growth as as a public company. So that, uh,

515
00:27:11,400 --> 00:27:15,879
Speaker 11: that was really positive news for investors, you know, instacrat

516
00:27:15,880 --> 00:27:19,400
Speaker 11: has seen this sort of moderating growth and in the

517
00:27:19,480 --> 00:27:22,560
Speaker 11: last few years, and this has really seen them accelerating.

518
00:27:22,640 --> 00:27:26,200
Speaker 11: As you know, they're lowered the minimum basket size needed

519
00:27:26,200 --> 00:27:29,800
Speaker 11: for free delivery. That's really helped. Their partnership with Uber

520
00:27:30,080 --> 00:27:32,960
Speaker 11: allowing people to order takeout has also helped with demand.

521
00:27:33,400 --> 00:27:37,000
Speaker 5: What about the underlying technology and how much AI is

522
00:27:37,080 --> 00:27:38,679
Speaker 5: becoming a flywheel for them or not.

523
00:27:39,160 --> 00:27:44,639
Speaker 11: Yes, they're continuing to push out new technology solutions for

524
00:27:44,760 --> 00:27:49,119
Speaker 11: grocers such as their white label website building and as

525
00:27:49,280 --> 00:27:53,520
Speaker 11: also as well as other recommendation engines for grocery and

526
00:27:53,560 --> 00:27:55,920
Speaker 11: that has powered a third of their revenue and they

527
00:27:55,960 --> 00:28:00,720
Speaker 11: continue to expect it to grow this year and pushing

528
00:28:00,760 --> 00:28:03,640
Speaker 11: internationally with Costco in Europe.

529
00:28:04,040 --> 00:28:06,159
Speaker 5: In most Natalie Lung, we thank you so much on

530
00:28:06,200 --> 00:28:07,040
Speaker 5: their earnings roundup.

531
00:28:07,080 --> 00:28:07,920
Speaker 4: We've got more of them.

532
00:28:08,119 --> 00:28:11,320
Speaker 5: Coinbase, well, it showed how quickly a cooling crypto market

533
00:28:11,320 --> 00:28:14,000
Speaker 5: can pressure even one of the industry's most diversified exchanges

534
00:28:14,080 --> 00:28:17,000
Speaker 5: revenue in the fourth quarter tumbling twenty percent to one

535
00:28:17,000 --> 00:28:20,439
Speaker 5: point eight billion. That says, falling token prices drain trading

536
00:28:20,440 --> 00:28:23,440
Speaker 5: activity across digital assets. This is the company's stock is

537
00:28:23,480 --> 00:28:25,600
Speaker 5: already down ay thirty seven percent year to date, but

538
00:28:25,640 --> 00:28:28,400
Speaker 5: it's got a bounce today. Katie Greifeld, I'm pleased to say,

539
00:28:28,480 --> 00:28:32,000
Speaker 5: joins us, host of the Crypto Show, and whateveryone is

540
00:28:32,000 --> 00:28:35,000
Speaker 5: trying to get to grips with is have we found

541
00:28:35,040 --> 00:28:36,040
Speaker 5: a bottom here? Is?

542
00:28:36,040 --> 00:28:38,080
Speaker 4: Is it bad? And as ugly as it gets?

543
00:28:38,240 --> 00:28:40,640
Speaker 15: That seems to be the explanation for why you're seeing

544
00:28:40,680 --> 00:28:44,640
Speaker 15: shares bounce and then some Coinbase currently up about sixteen

545
00:28:44,680 --> 00:28:47,160
Speaker 15: percent at the moment. That is its best day since June,

546
00:28:47,160 --> 00:28:50,280
Speaker 15: which looks unintuitive when you consider some of the actual

547
00:28:50,360 --> 00:28:53,440
Speaker 15: numbers that we got last night, which weren't great transaction

548
00:28:53,600 --> 00:28:57,040
Speaker 15: revenue coming in soft you also trading volumes coming in

549
00:28:57,080 --> 00:28:59,800
Speaker 15: lower than expectations. But as you mentioned, I mean, shares

550
00:28:59,800 --> 00:29:03,920
Speaker 15: were thirty seven percent through yesterday's close. We also had

551
00:29:04,520 --> 00:29:07,800
Speaker 15: Robinhood report a few days earlier their crypto business drove

552
00:29:07,840 --> 00:29:10,640
Speaker 15: a net revenue miss for that company, So it wasn't

553
00:29:10,680 --> 00:29:15,080
Speaker 15: necessarily surprising to see these figures. And the idea here

554
00:29:15,160 --> 00:29:18,520
Speaker 15: is now basically that exactly that we're looking for a bottom,

555
00:29:18,560 --> 00:29:21,320
Speaker 15: that maybe the worst is already priced into this stock.

556
00:29:22,080 --> 00:29:24,640
Speaker 3: Katie, I'm a little ignorant here. You know, like crypto

557
00:29:25,240 --> 00:29:27,360
Speaker 3: from a sort of asset perspective is not something that

558
00:29:27,600 --> 00:29:29,560
Speaker 3: I spend a huge amount of time on. What I

559
00:29:29,600 --> 00:29:31,520
Speaker 3: was trying to ask out in the week is I

560
00:29:31,600 --> 00:29:35,240
Speaker 3: get when volumes are down, that's not great, right, that's

561
00:29:35,360 --> 00:29:36,680
Speaker 3: kind of logical, But.

562
00:29:36,680 --> 00:29:38,120
Speaker 2: There's been so much volatility.

563
00:29:38,520 --> 00:29:40,920
Speaker 3: So I thought that in an environment where there's volatility,

564
00:29:41,840 --> 00:29:43,840
Speaker 3: a name like this would do really well. Right, because

565
00:29:43,840 --> 00:29:45,840
Speaker 3: you're on one side of the trade or you're on

566
00:29:45,880 --> 00:29:46,200
Speaker 3: the other.

567
00:29:46,840 --> 00:29:49,560
Speaker 15: Well, you're not wrong for thinking that. I mean, volatility

568
00:29:49,560 --> 00:29:53,240
Speaker 15: that's typically good news for exchanges across any asset class.

569
00:29:53,280 --> 00:29:56,160
Speaker 15: But consider the movements that you've been seeing in the

570
00:29:56,200 --> 00:29:59,520
Speaker 15: price of bitcoin. It hasn't necessarily been two sided volatility.

571
00:29:59,760 --> 00:30:02,040
Speaker 15: It's I've really been dropping like a stone over the

572
00:30:02,080 --> 00:30:05,960
Speaker 15: past several weeks, which isn't a great environment when it's

573
00:30:06,000 --> 00:30:09,080
Speaker 15: a one sided trade here. But I mean, as Caroline mentioned,

574
00:30:09,080 --> 00:30:12,600
Speaker 15: this is a fairly diversified business. It's they've been trying

575
00:30:12,640 --> 00:30:15,920
Speaker 15: to move away from just that reliance on spot trading.

576
00:30:15,920 --> 00:30:19,400
Speaker 15: They have an interesting revenue sharing agreement with Circle, so

577
00:30:19,440 --> 00:30:21,960
Speaker 15: they're exposed to stable coins, which is seen as much

578
00:30:22,000 --> 00:30:24,680
Speaker 15: steadier and another reason why you are seeing the shares

579
00:30:24,720 --> 00:30:28,160
Speaker 15: pop today is there's some optimism that maybe we are

580
00:30:28,240 --> 00:30:30,960
Speaker 15: going to see that Market Structure bill that's currently working

581
00:30:31,000 --> 00:30:33,920
Speaker 15: its way through Congress actually gets some action in the

582
00:30:33,960 --> 00:30:36,840
Speaker 15: next few months, maybe actually make its way over the

583
00:30:36,840 --> 00:30:39,240
Speaker 15: finish line. So that's what you're seeing. Maybe also the

584
00:30:39,280 --> 00:30:41,760
Speaker 15: price of bitcoin itself pop a little bit today.

585
00:30:42,040 --> 00:30:43,720
Speaker 4: Clarity and the Clarity Act. Who thought it?

586
00:30:43,800 --> 00:30:47,520
Speaker 5: Katie Greifeld, thank you so much for joining us today. Meanwhile,

587
00:30:47,720 --> 00:30:49,920
Speaker 5: let's take quick more aarnings. I want to just take

588
00:30:49,920 --> 00:30:53,760
Speaker 5: you to Apply Materials because this is the equipment maker

589
00:30:53,840 --> 00:30:56,000
Speaker 5: of the US for the chip makers. We are up

590
00:30:56,120 --> 00:30:59,640
Speaker 5: nine percent status at a numbers, managing to prove to

591
00:30:59,680 --> 00:31:02,000
Speaker 5: the MAIT that even though China is pulling away in

592
00:31:02,080 --> 00:31:04,960
Speaker 5: terms of orders, we're actually seeing just the drumbeat of

593
00:31:05,000 --> 00:31:08,520
Speaker 5: more and more investment in data centers. Of course, that

594
00:31:08,680 --> 00:31:12,120
Speaker 5: means equipment manufacturing that is needed for chips to go

595
00:31:12,160 --> 00:31:14,600
Speaker 5: into those data centers. Applying materials benefiting off the back

596
00:31:14,600 --> 00:31:16,440
Speaker 5: of it. We're up eight point nine per cent. CEO

597
00:31:16,520 --> 00:31:17,520
Speaker 5: sounded pretty bullished.

598
00:31:18,360 --> 00:31:24,880
Speaker 3: Etching and deposition gear absolutely essential. Let's go to space SPACEXA.

599
00:31:24,360 --> 00:31:28,600
Speaker 9: Dragon and Guard feed Crew twelve and lift.

600
00:31:28,320 --> 00:31:32,240
Speaker 7: Off Freedom Flies bound for the International Space Station.

601
00:31:32,880 --> 00:31:36,479
Speaker 10: One point seven million pounds of trust now going bacod night.

602
00:31:36,760 --> 00:31:37,760
Speaker 2: I've got ahead of myself.

603
00:31:37,800 --> 00:31:41,320
Speaker 3: The SpaceX capsule, carrying four crew members from the US,

604
00:31:41,360 --> 00:31:45,160
Speaker 3: Europe and Russia, launched overnight to the International Space Station,

605
00:31:45,720 --> 00:31:48,520
Speaker 3: the start of a planned eight months stay in orbit

606
00:31:48,560 --> 00:31:51,960
Speaker 3: that will include research on meditation in space.

607
00:31:52,360 --> 00:31:54,480
Speaker 2: They'll be joining three other astronauts.

608
00:31:54,000 --> 00:31:57,040
Speaker 3: Aboard the ISS, which has been operating with a skeleton

609
00:31:57,080 --> 00:32:00,640
Speaker 3: crew since the first ever space medical evacuation.

610
00:32:00,800 --> 00:32:03,440
Speaker 2: You remember in January, Karen.

611
00:32:03,200 --> 00:32:06,360
Speaker 4: Thankscute meditation. We need to do more of it on Earth.

612
00:32:06,440 --> 00:32:08,320
Speaker 4: Let loan in space. Brilliant, Thank you, Ed.

613
00:32:08,360 --> 00:32:11,680
Speaker 5: Meanwhile, coming up, bensn from Primary joins us to talk

614
00:32:11,680 --> 00:32:15,440
Speaker 5: about the venture firms. The latest megafund is Bree meg Tech,

615
00:32:27,160 --> 00:32:30,200
Speaker 5: early stage benure firm Primary. It's just closely six hundred

616
00:32:30,200 --> 00:32:32,760
Speaker 5: and twenty five million dollar fund that brings total assets

617
00:32:32,800 --> 00:32:34,920
Speaker 5: on a management to one point six five billion, and

618
00:32:35,000 --> 00:32:36,880
Speaker 5: it's at the time when investors are still really eager

619
00:32:36,880 --> 00:32:39,040
Speaker 5: to back start ups at the seed level. I speak

620
00:32:39,040 --> 00:32:42,840
Speaker 5: to Ben's Sun, Primary's co founder general partner Ben. The

621
00:32:42,880 --> 00:32:45,160
Speaker 5: size and scale of the funds are getting bigger.

622
00:32:45,200 --> 00:32:47,240
Speaker 4: Is that because we're seeing.

623
00:32:46,960 --> 00:32:50,560
Speaker 5: More opportunity to fund more companies or because each individual

624
00:32:50,600 --> 00:32:52,720
Speaker 5: seed company needs more money.

625
00:32:54,120 --> 00:32:55,920
Speaker 16: I think it's a combination about caroline. And if you

626
00:32:55,960 --> 00:33:00,760
Speaker 16: look over the last decade the seed more, it has

627
00:33:00,840 --> 00:33:04,280
Speaker 16: grown from five billion dollars ten years ago, and this

628
00:33:04,360 --> 00:33:06,479
Speaker 16: is just what was invested at seed in the US

629
00:33:07,840 --> 00:33:10,320
Speaker 16: and ten years ago in that year to last year

630
00:33:10,400 --> 00:33:13,760
Speaker 16: being about twenty billion, So we've seen four x the

631
00:33:13,800 --> 00:33:16,520
Speaker 16: amount of capital in terms of round sizes. On top

632
00:33:16,560 --> 00:33:20,080
Speaker 16: of that, round sizes have gone up from one billion

633
00:33:21,000 --> 00:33:23,440
Speaker 16: to four billion as well, So again a climb of

634
00:33:23,480 --> 00:33:24,320
Speaker 16: about four x.

635
00:33:25,400 --> 00:33:29,280
Speaker 5: Are you seeing returns though? That vindicates such bigger bets

636
00:33:29,280 --> 00:33:32,120
Speaker 5: of the seed level? Where are you deciding to double

637
00:33:32,160 --> 00:33:33,040
Speaker 5: down on companies?

638
00:33:33,040 --> 00:33:34,280
Speaker 4: Do you just stay at seed?

639
00:33:34,360 --> 00:33:38,320
Speaker 5: How do you think your own DNA changes in this moment?

640
00:33:39,480 --> 00:33:39,680
Speaker 8: Oh?

641
00:33:39,760 --> 00:33:44,960
Speaker 16: I think if you look at historically on the exits

642
00:33:45,000 --> 00:33:47,360
Speaker 16: and the size of outcomes in both the media and

643
00:33:47,400 --> 00:33:50,360
Speaker 16: the decile, you've seen that each kind of generation of

644
00:33:50,400 --> 00:33:54,800
Speaker 16: startups just gets a step function higher and higher. And

645
00:33:54,840 --> 00:33:58,320
Speaker 16: now with what's cappening in AI, we think the outcomes

646
00:33:58,360 --> 00:34:01,960
Speaker 16: are going to be much greater, and so the amount

647
00:34:02,000 --> 00:34:05,560
Speaker 16: of capital going in it matches the quality of the talent,

648
00:34:06,080 --> 00:34:09,960
Speaker 16: but also the quality of the opportunities. And with transformations

649
00:34:10,000 --> 00:34:13,600
Speaker 16: like AI, we think in the market thinks those opportunities

650
00:34:13,600 --> 00:34:15,239
Speaker 16: are going to become and those outcomes are going to

651
00:34:15,239 --> 00:34:17,160
Speaker 16: become bigger than that we've ever seen before.

652
00:34:17,920 --> 00:34:20,560
Speaker 3: Then some of the data you were just referencing. I

653
00:34:20,600 --> 00:34:23,799
Speaker 3: wrote my column about this in January twenty six. There's

654
00:34:23,840 --> 00:34:27,080
Speaker 3: no point calling it a seed round anymore. Mango seed,

655
00:34:27,200 --> 00:34:32,560
Speaker 3: coconut seed, avocado seed. But you know, the scale is

656
00:34:32,600 --> 00:34:36,080
Speaker 3: not just different. You're basically making a bet sometimes on

657
00:34:36,239 --> 00:34:39,120
Speaker 3: just two or three people in the AI lab context,

658
00:34:39,200 --> 00:34:43,839
Speaker 3: for example. Is that more disconcerting in the moment when

659
00:34:43,880 --> 00:34:46,760
Speaker 3: you do a seed round based on you know, maybe

660
00:34:46,760 --> 00:34:49,719
Speaker 3: an alumni of a bigger tech company or someone that's

661
00:34:49,760 --> 00:34:51,280
Speaker 3: going it alone in this environment.

662
00:34:52,520 --> 00:34:55,320
Speaker 16: Yeah, people look at historical data and they say, well,

663
00:34:55,600 --> 00:35:00,000
Speaker 16: round size has gotten bigger, So it hasn't become irrational.

664
00:35:00,000 --> 00:35:03,000
Speaker 16: Reason why we have become bigger because it's become more rational.

665
00:35:04,000 --> 00:35:07,600
Speaker 16: Think about the founding talent. I know alone. You know,

666
00:35:07,680 --> 00:35:10,680
Speaker 16: I started my career as a founder thirty years ago.

667
00:35:12,280 --> 00:35:14,600
Speaker 16: You know what we knew about the Internet and how

668
00:35:14,640 --> 00:35:18,600
Speaker 16: to scale a technology company back then. I mean, it's

669
00:35:19,200 --> 00:35:21,440
Speaker 16: night and day to where you see the market and

670
00:35:21,440 --> 00:35:23,759
Speaker 16: the type of talent you have. Now, a lot of

671
00:35:23,760 --> 00:35:27,400
Speaker 16: the talent are coming from best in class tech companies

672
00:35:27,440 --> 00:35:31,360
Speaker 16: that have gone from zero a billion dollar type outcomes

673
00:35:31,440 --> 00:35:34,440
Speaker 16: if not more, and those that talent is coming out

674
00:35:34,560 --> 00:35:37,640
Speaker 16: and starting new companies. And then on top of that,

675
00:35:37,760 --> 00:35:40,040
Speaker 16: the scale and the quality of their ideas are just

676
00:35:40,040 --> 00:35:42,560
Speaker 16: getting in better and better. So I think the capital

677
00:35:42,640 --> 00:35:44,600
Speaker 16: going in, the valuations are climbing.

678
00:35:44,840 --> 00:35:46,880
Speaker 13: These are just markets being efficient.

679
00:35:46,640 --> 00:35:50,000
Speaker 16: And saying, well, the talent and these potential outcomes look

680
00:35:50,160 --> 00:35:53,480
Speaker 16: like they have much more upside and therefore kind of

681
00:35:53,520 --> 00:35:56,240
Speaker 16: demand those type of premiums.

682
00:35:56,920 --> 00:36:00,879
Speaker 2: The seed market is very broad. What are the corners of.

683
00:36:00,760 --> 00:36:05,719
Speaker 3: The technology industry or opportunities where like the technology just

684
00:36:05,760 --> 00:36:07,000
Speaker 3: doesn't exist yet.

685
00:36:09,280 --> 00:36:12,440
Speaker 16: I mean, the big unlock, as you know, is around

686
00:36:12,520 --> 00:36:15,960
Speaker 16: kind of AI, and this is at the infrastructure level

687
00:36:16,080 --> 00:36:19,560
Speaker 16: all the way to the application level, and the opportunities

688
00:36:19,560 --> 00:36:21,799
Speaker 16: that we're kind of seeing across all different types of

689
00:36:21,800 --> 00:36:26,520
Speaker 16: sectors is becoming evident that really AI is being unlock.

690
00:36:27,080 --> 00:36:30,840
Speaker 16: What is a much larger TAM than historically you've seen before.

691
00:36:31,480 --> 00:36:34,400
Speaker 16: Before we used to talk about tam as like software budgets.

692
00:36:35,000 --> 00:36:38,920
Speaker 16: AI is replacing or augmenting human labor. And when you

693
00:36:38,960 --> 00:36:43,680
Speaker 16: think about that type of replacement augmentation, we're talking about

694
00:36:43,719 --> 00:36:46,520
Speaker 16: the market that's trillions of dollars, not you know, hundreds

695
00:36:46,560 --> 00:36:49,319
Speaker 16: of billions of dollars. And that's really kind of the

696
00:36:49,320 --> 00:36:53,040
Speaker 16: opportunity that we see. And it's happening in all different

697
00:36:53,040 --> 00:36:58,040
Speaker 16: sectors where it be fintech, healthcare, industrials throughout the enterprise,

698
00:36:58,160 --> 00:37:01,319
Speaker 16: all the way to SMBs and consumers across the board.

699
00:37:01,360 --> 00:37:03,560
Speaker 16: We think there's going to be huge transformations.

700
00:37:03,239 --> 00:37:07,360
Speaker 3: Especially with Ai Benson, general partner at Primary. Great to

701
00:37:07,400 --> 00:37:09,880
Speaker 3: have you on Bloomberg Tech. Thank you very much. Carries

702
00:37:09,920 --> 00:37:11,960
Speaker 3: so many more news headlines to get to there are.

703
00:37:12,040 --> 00:37:14,279
Speaker 5: It's time now for talking tech, and first up. Byte

704
00:37:14,360 --> 00:37:17,279
Speaker 5: Dance is in talks to sell its Moonton video game

705
00:37:17,320 --> 00:37:20,160
Speaker 5: business to Saudi Arabia based Savvy Games and.

706
00:37:20,239 --> 00:37:21,200
Speaker 4: One than six billion dollars.

707
00:37:21,239 --> 00:37:23,360
Speaker 5: It's all according to reports and Voiters, which says the

708
00:37:23,400 --> 00:37:26,040
Speaker 5: parties could finalize a deal as soon as this quarter.

709
00:37:26,280 --> 00:37:29,120
Speaker 5: Bloomberg's reported that the company has revived sale corks late

710
00:37:29,200 --> 00:37:32,400
Speaker 5: last year, plus day one Data centers. Well, it's selected

711
00:37:32,400 --> 00:37:35,000
Speaker 5: banks for a USIPO that could raise five billion dollars

712
00:37:35,000 --> 00:37:37,160
Speaker 5: according to sources. They say the company, which is backed

713
00:37:37,160 --> 00:37:41,040
Speaker 5: by Chinese data center operator GDS, targeting a valuation as

714
00:37:41,120 --> 00:37:43,719
Speaker 5: high as twenty billion dollars, a listing that may take

715
00:37:43,800 --> 00:37:47,120
Speaker 5: place as soon as this year, and also looking to

716
00:37:47,120 --> 00:37:49,880
Speaker 5: go public in the United States. Is SoftBank's digital payments

717
00:37:49,880 --> 00:37:52,759
Speaker 5: provide a paypey. The company could list as early as March,

718
00:37:52,760 --> 00:37:55,319
Speaker 5: according to public filing. Now, Pape is seeking evaluation more

719
00:37:55,400 --> 00:37:58,279
Speaker 5: than ten billion those soft Bank founder Massiyoshison is pushing

720
00:37:58,320 --> 00:38:01,040
Speaker 5: for as much as twenty billion dollars sources.

721
00:38:00,960 --> 00:38:02,880
Speaker 2: And Okay coming up.

722
00:38:02,960 --> 00:38:05,719
Speaker 3: Social media is having a rough start to the year,

723
00:38:06,280 --> 00:38:09,400
Speaker 3: But is the bad press slowing the industry's growth?

724
00:38:10,200 --> 00:38:12,080
Speaker 2: Were on that next, This is Blomberg Tech.

725
00:38:20,080 --> 00:38:21,520
Speaker 4: Social media's impact on teams.

726
00:38:21,560 --> 00:38:23,839
Speaker 5: Well, it's never been more scrutinized than it is right

727
00:38:23,880 --> 00:38:27,319
Speaker 5: now with lawsuits in the US of addiction allegations, Australia's

728
00:38:27,320 --> 00:38:30,280
Speaker 5: ban on under sixteen's that could actually spread to Europe.

729
00:38:30,640 --> 00:38:33,839
Speaker 5: But are these moves actually comping the industry's growth. Bloombot's

730
00:38:34,000 --> 00:38:36,960
Speaker 5: Kurt Wagner, who covers social media, joins us on this.

731
00:38:37,040 --> 00:38:39,400
Speaker 5: You wrote a piece, your tech in depth piece that

732
00:38:40,120 --> 00:38:42,480
Speaker 5: kind of shows that no, it doesn't actually affect the

733
00:38:42,480 --> 00:38:43,040
Speaker 5: business model.

734
00:38:43,040 --> 00:38:44,080
Speaker 4: Thus far, it feels like.

735
00:38:45,280 --> 00:38:47,000
Speaker 9: Yeah, And I think there's two elements here.

736
00:38:47,080 --> 00:38:49,359
Speaker 17: The first is the volume of accounts that have been

737
00:38:49,400 --> 00:38:52,320
Speaker 17: removed and again these bands right now, to be clear,

738
00:38:52,480 --> 00:38:55,279
Speaker 17: this is only happening in Australia, Caroline right, so there

739
00:38:55,360 --> 00:38:58,200
Speaker 17: is potential that this could become a real global problem.

740
00:38:58,400 --> 00:39:00,359
Speaker 9: But the number of accounts that are being removed our

741
00:39:00,520 --> 00:39:01,000
Speaker 9: drops in.

742
00:39:01,000 --> 00:39:04,440
Speaker 17: The bugget for these companies, it's maybe even a rounding

743
00:39:04,440 --> 00:39:06,960
Speaker 17: air in terms of who they are losing. And then

744
00:39:07,000 --> 00:39:08,520
Speaker 17: on top of that, I think if you talk to

745
00:39:08,560 --> 00:39:12,000
Speaker 17: people who study this industry from a business standpoint, a

746
00:39:12,040 --> 00:39:14,400
Speaker 17: fifteen year old on snap, a fifteen year old on

747
00:39:14,440 --> 00:39:18,000
Speaker 17: Instagram that is not a super valuable user for these

748
00:39:18,000 --> 00:39:20,520
Speaker 17: companies in terms of revenue. They don't usually have a

749
00:39:20,520 --> 00:39:21,480
Speaker 17: lot of disposable income.

750
00:39:21,520 --> 00:39:24,239
Speaker 9: They're not making household purchasing decisions yet.

751
00:39:24,560 --> 00:39:27,160
Speaker 17: And so the point of this story here was mostly

752
00:39:27,160 --> 00:39:30,200
Speaker 17: to say, right now, this is not a real threat.

753
00:39:29,960 --> 00:39:31,560
Speaker 9: To the business of these companies.

754
00:39:31,680 --> 00:39:33,480
Speaker 17: It could be down the line, but I think that's

755
00:39:33,520 --> 00:39:36,120
Speaker 17: something that you know, might be years away if it

756
00:39:36,160 --> 00:39:36,760
Speaker 17: ever comes.

757
00:39:37,560 --> 00:39:40,399
Speaker 3: The extension of that, that last part is that many

758
00:39:40,480 --> 00:39:44,160
Speaker 3: of these names still rely heavily on advertising as source

759
00:39:44,160 --> 00:39:47,880
Speaker 3: of revenue. This obviously subscription in some cases, which is

760
00:39:47,880 --> 00:39:51,880
Speaker 3: a different model that would suggest generally add healthy.

761
00:39:51,960 --> 00:39:52,680
Speaker 2: Right now, what do you.

762
00:39:52,640 --> 00:39:56,799
Speaker 17: Say, Yeah, I mean all of these businesses continue to

763
00:39:56,800 --> 00:40:01,120
Speaker 17: grow their ads, their ads business quite consider. I think

764
00:40:01,120 --> 00:40:03,960
Speaker 17: it was meta it was more than twenty percent year

765
00:40:04,000 --> 00:40:06,040
Speaker 17: over year. I mean, this is a company that's been

766
00:40:06,080 --> 00:40:08,399
Speaker 17: around more than twenty years at as you know, and

767
00:40:08,440 --> 00:40:12,080
Speaker 17: they still figure out how to grow that AD's business.

768
00:40:12,120 --> 00:40:15,680
Speaker 17: And so I think there is a lot of money

769
00:40:15,800 --> 00:40:17,280
Speaker 17: still pouring into these companies.

770
00:40:17,640 --> 00:40:20,880
Speaker 9: And again it's just where is that money being targeted.

771
00:40:21,080 --> 00:40:24,719
Speaker 17: It doesn't feel that teams, while they're important again to

772
00:40:25,400 --> 00:40:28,160
Speaker 17: create a vibe around a platform, to create buzz around

773
00:40:28,200 --> 00:40:31,759
Speaker 17: a platform, they're not necessarily who advertisers are looking to

774
00:40:31,800 --> 00:40:34,600
Speaker 17: get right now. And so I think that's where again

775
00:40:34,600 --> 00:40:37,400
Speaker 17: there might be some delay in how these types of

776
00:40:37,440 --> 00:40:38,480
Speaker 17: bands impact the business.

777
00:40:38,640 --> 00:40:41,160
Speaker 5: Push us forward, though, Kirk, because we are going to

778
00:40:41,160 --> 00:40:45,920
Speaker 5: see some key executives have to come up against.

779
00:40:46,120 --> 00:40:47,240
Speaker 4: Arguments in court.

780
00:40:47,400 --> 00:40:49,759
Speaker 5: Look, we all remember the pictures of Mark Zuckerberb being

781
00:40:49,800 --> 00:40:53,279
Speaker 5: confronted by parents holding up signs that moment resonates with

782
00:40:53,360 --> 00:40:57,080
Speaker 5: a userbase and of potential customer it does.

783
00:40:57,120 --> 00:41:00,160
Speaker 17: We're expected to hear Mark Zuckerberg testified next week in

784
00:41:00,239 --> 00:41:03,120
Speaker 17: Los Angeles in a big trial that's all about whether

785
00:41:03,160 --> 00:41:09,120
Speaker 17: these platforms are purposefully addicting teens to you know, Instagram, snap,

786
00:41:09,400 --> 00:41:13,160
Speaker 17: TikTok et, cetera. And so you know, there is a

787
00:41:13,239 --> 00:41:17,080
Speaker 17: reputational element to this. And I think, while I say

788
00:41:17,120 --> 00:41:19,279
Speaker 17: that the business might not be impacted now, if you

789
00:41:19,280 --> 00:41:22,800
Speaker 17: get a whole generation of teenagers who stop using these products,

790
00:41:23,120 --> 00:41:25,360
Speaker 17: that is that is not good, right, That is not

791
00:41:25,400 --> 00:41:27,800
Speaker 17: good for Meta that these people are now going to

792
00:41:27,840 --> 00:41:30,200
Speaker 17: go spend time elsewhere the most.

793
00:41:30,080 --> 00:41:31,640
Speaker 2: Curt Wagner, thank you very much.

794
00:41:31,719 --> 00:41:34,680
Speaker 3: Some of the biggest players behind the AI boom are

795
00:41:34,680 --> 00:41:38,759
Speaker 3: taking a page from the Crypto Industries twenty twenty four playbook,

796
00:41:39,000 --> 00:41:43,239
Speaker 3: working to back congressional candidates who favor a lighter regulatory

797
00:41:43,280 --> 00:41:46,920
Speaker 3: touch on AI. For more Bluebersts corporate lobbying report, Emily

798
00:41:46,920 --> 00:41:49,319
Speaker 3: Burnbam joins US now. And these are names that are

799
00:41:49,320 --> 00:41:54,040
Speaker 3: familiar right across the top tier eventure capital and the

800
00:41:54,040 --> 00:41:57,840
Speaker 3: Frontier Labs explain this playbook they're trying to replicate.

801
00:41:59,040 --> 00:42:03,760
Speaker 18: So the the memory of fair Shake, Crypto's big pack

802
00:42:04,160 --> 00:42:09,200
Speaker 18: looms large over Democrats and Republicans in Washington. They spent

803
00:42:09,560 --> 00:42:13,680
Speaker 18: huge sums, hundreds of millions of dollars and we're very successful.

804
00:42:14,440 --> 00:42:19,400
Speaker 18: And so now the AI companies, including both Andresen and Horwitz,

805
00:42:19,400 --> 00:42:23,279
Speaker 18: who also gave to fair Shake, are pouring millions of

806
00:42:23,320 --> 00:42:27,400
Speaker 18: dollars into congressional races across the country. Last time, the

807
00:42:27,400 --> 00:42:32,160
Speaker 18: crypto industry won by not talking about crypto, instead boosting

808
00:42:32,239 --> 00:42:36,480
Speaker 18: candidates based on issues that are popular in their district.

809
00:42:36,760 --> 00:42:39,160
Speaker 18: And that's exactly what the AI industry is going to

810
00:42:39,200 --> 00:42:42,040
Speaker 18: do this time with their pack. It's called leading the future.

811
00:42:42,880 --> 00:42:47,520
Speaker 5: What can they do to dial into where the electric

812
00:42:47,640 --> 00:42:49,360
Speaker 5: is at at the moment, because when it comes to AI,

813
00:42:49,800 --> 00:42:52,040
Speaker 5: there's a lot of anxiety, a lot of labor anxiety.

814
00:42:52,040 --> 00:42:54,359
Speaker 5: For example, where are they going to post the opportunity

815
00:42:54,400 --> 00:42:55,080
Speaker 5: to them?

816
00:42:56,440 --> 00:43:01,160
Speaker 18: Yes, so I think first there is recingly a lot

817
00:43:01,160 --> 00:43:06,160
Speaker 18: of anxiety among constituents about AI, particularly about employment, particularly

818
00:43:06,160 --> 00:43:09,400
Speaker 18: about data centers being built in their backyards. So I

819
00:43:09,440 --> 00:43:13,000
Speaker 18: think for the AI industry, they're both they're going to

820
00:43:13,040 --> 00:43:15,680
Speaker 18: be making the argument that this is good for American

821
00:43:15,800 --> 00:43:21,160
Speaker 18: dominance over China, that they are the innovators of the future.

822
00:43:21,800 --> 00:43:22,960
Speaker 2: We'll see how that plays.

823
00:43:23,000 --> 00:43:25,279
Speaker 18: But more than anything, I think they're working with strategists

824
00:43:25,280 --> 00:43:27,840
Speaker 18: in each of these states, and you can see in

825
00:43:27,880 --> 00:43:31,080
Speaker 18: their advertisements they're focusing on Ice in New York, they're

826
00:43:31,080 --> 00:43:36,879
Speaker 18: focusing on Trump ally his Maga accolades in Texas. We're

827
00:43:36,880 --> 00:43:38,600
Speaker 18: going to see that play out over and over and

828
00:43:38,719 --> 00:43:41,360
Speaker 18: people in those states don't necessarily know that it's the

829
00:43:41,400 --> 00:43:45,160
Speaker 18: AI industry behind these advertisements. Mailers, texts coming to.

830
00:43:45,160 --> 00:43:48,719
Speaker 5: Their phones, fascinating in Maxeminy vembam must get you back

831
00:43:48,719 --> 00:43:51,080
Speaker 5: from that story and do go read it meanwhile, That

832
00:43:51,200 --> 00:43:51,879
Speaker 5: does it for this.

833
00:43:51,920 --> 00:43:55,240
Speaker 4: Edition of Briting by Tech. What an extraordinary week.

834
00:43:55,200 --> 00:43:57,960
Speaker 3: D Yeah, and in the United States at least a

835
00:43:58,040 --> 00:44:00,640
Speaker 3: holiday weekend for many, recap the sh Show and the

836
00:44:00,640 --> 00:44:02,680
Speaker 3: week on the podcast. You know where to find it,

837
00:44:02,840 --> 00:44:05,680
Speaker 3: all those places online and all of the bloomerverse have

838
00:44:05,760 --> 00:44:06,440
Speaker 3: a great weekend.

839
00:44:06,400 --> 00:44:07,399
Speaker 2: There's the Bloomberg Tech