1
00:00:02,400 --> 00:00:09,840
Speaker 1: Bloomberg Audio Studios, podcasts, radio news.

2
00:00:08,560 --> 00:00:12,200
Speaker 2: From Mahard where Innovation of Money and Power Collie in

3
00:00:12,320 --> 00:00:17,200
Speaker 2: Silicon Valley, NBN. This is Bloomberg Technology with Caroline Hyde

4
00:00:17,280 --> 00:00:18,680
Speaker 2: and Ed Ludlove.

5
00:00:31,920 --> 00:00:34,360
Speaker 1: Live from New York. This is Boomberg Technology coming up.

6
00:00:34,640 --> 00:00:38,200
Speaker 1: Broadcom becomes the new Nvidia, as the latter falls further

7
00:00:38,240 --> 00:00:42,080
Speaker 1: into correction territory. We'll discuss why plus TikTok CEO pays

8
00:00:42,080 --> 00:00:45,360
Speaker 1: a visit to President Elect Donald Trump, what that means

9
00:00:45,360 --> 00:00:48,839
Speaker 1: for the apps potential band, and a conversation with Senator

10
00:00:48,880 --> 00:00:52,120
Speaker 1: Amy Cloversha on how to combat the rise of AI

11
00:00:52,240 --> 00:00:56,240
Speaker 1: generated deep fake material online. But first I check in

12
00:00:56,400 --> 00:00:59,720
Speaker 1: on these markets which come down from record highs. We

13
00:01:00,040 --> 00:01:03,360
Speaker 1: digest the retail sales data that shows the US economy

14
00:01:03,400 --> 00:01:06,560
Speaker 1: remains resilient as we look ahead to the FED meeting tomorrow.

15
00:01:06,680 --> 00:01:08,440
Speaker 1: We're just on ten to hooks. But look, we date

16
00:01:08,640 --> 00:01:11,440
Speaker 1: about a five ten percent dip lower on the NAZAQ

17
00:01:11,480 --> 00:01:14,240
Speaker 1: one hundred after it has been record high after record high.

18
00:01:14,400 --> 00:01:16,360
Speaker 1: Go into some of the individual movers. It has been

19
00:01:16,440 --> 00:01:19,199
Speaker 1: chip stocks that have been dragging US lower somewhat again

20
00:01:19,280 --> 00:01:22,480
Speaker 1: coming down from a significant run for Broadcon, for example,

21
00:01:22,760 --> 00:01:25,200
Speaker 1: we're down more than five percent, but boy has it

22
00:01:25,240 --> 00:01:27,160
Speaker 1: been on a big rally, up thirty eight percent in

23
00:01:27,200 --> 00:01:30,160
Speaker 1: the previous two sessions in video, though off by two

24
00:01:30,160 --> 00:01:32,640
Speaker 1: point two percent, we are further into correction territory. That

25
00:01:32,680 --> 00:01:34,440
Speaker 1: means it's more than ten percent off of its previous

26
00:01:34,520 --> 00:01:37,640
Speaker 1: high that was met in early November. And I'm looking

27
00:01:37,680 --> 00:01:40,759
Speaker 1: at arm as somewhere in Delaware. Arm takes on its

28
00:01:40,760 --> 00:01:44,240
Speaker 1: biggest client and indeed partner Qualcom. Once again. We got

29
00:01:44,240 --> 00:01:47,520
Speaker 1: these two key influential chip designers and makes going head

30
00:01:47,520 --> 00:01:50,640
Speaker 1: to head in an IP battle that has border rammifications.

31
00:01:50,640 --> 00:01:53,639
Speaker 1: We dig into it. The Bloomberg's Ian King, the chip

32
00:01:53,800 --> 00:01:55,640
Speaker 1: Master is here, and we've got a lot to talk

33
00:01:55,680 --> 00:01:58,400
Speaker 1: about when it comes to chips. Let's just focus on

34
00:01:58,480 --> 00:02:00,760
Speaker 1: in video to start with, because is there any real

35
00:02:00,800 --> 00:02:03,200
Speaker 1: fundamental reason that we're suddenly getting in to a technical

36
00:02:03,680 --> 00:02:04,440
Speaker 1: correction here?

37
00:02:05,800 --> 00:02:09,200
Speaker 3: Nothing that you've seen any headlines on or seen any

38
00:02:09,280 --> 00:02:13,840
Speaker 3: reporting on. As you remember, Carolyn, they've said we're sold out. Basically,

39
00:02:14,240 --> 00:02:17,200
Speaker 3: their innings are essentially a product of how much they

40
00:02:17,200 --> 00:02:20,559
Speaker 3: can get from their suppliers right now. So nothing fundamentally

41
00:02:20,639 --> 00:02:23,040
Speaker 3: that would give anybody any pause. But obviously, as you

42
00:02:23,120 --> 00:02:25,560
Speaker 3: pointed out a huge amount of money that has been

43
00:02:25,560 --> 00:02:26,640
Speaker 3: poured into that stock.

44
00:02:27,040 --> 00:02:28,840
Speaker 1: It's not more than one hundred percent, still one hundred

45
00:02:28,880 --> 00:02:31,079
Speaker 1: and sixty percent over the course of the year. We

46
00:02:31,240 --> 00:02:33,799
Speaker 1: then flip to maybe a wanna be in video and

47
00:02:33,840 --> 00:02:37,760
Speaker 1: the making broad Coom really signaled the total addressable market

48
00:02:37,760 --> 00:02:42,040
Speaker 1: here for its designs within data centers, and the crowd

49
00:02:42,120 --> 00:02:44,480
Speaker 1: went wild. Can you focus in on broad Coom and

50
00:02:44,480 --> 00:02:46,160
Speaker 1: maybe a bit of profit taking on the day, But

51
00:02:46,320 --> 00:02:48,000
Speaker 1: what do they have to do to make this a reality?

52
00:02:49,000 --> 00:02:49,200
Speaker 4: Yeah?

53
00:02:49,240 --> 00:02:50,840
Speaker 3: I mean they have to work really hard. I mean

54
00:02:50,840 --> 00:02:53,520
Speaker 3: what hot Tan gave wasn't a sales target, right, we

55
00:02:53,560 --> 00:02:55,959
Speaker 3: need to be careful about that kind of As much

56
00:02:55,960 --> 00:02:58,880
Speaker 3: as ninety billion that he was talking about was an

57
00:02:58,919 --> 00:03:03,000
Speaker 3: addressable market for his type of chips, and that's by

58
00:03:03,200 --> 00:03:05,239
Speaker 3: twenty twenty seven. So what he was saying is that

59
00:03:05,280 --> 00:03:07,800
Speaker 3: we have line of sight to a huge increase in

60
00:03:07,840 --> 00:03:10,800
Speaker 3: what we do, But that pales in comparison to in video,

61
00:03:10,800 --> 00:03:12,760
Speaker 3: which is going to be one hundred and twenty billion

62
00:03:12,880 --> 00:03:16,160
Speaker 3: in data center sales alone this year according to analysts.

63
00:03:16,440 --> 00:03:20,440
Speaker 1: And when it comes to just enticing different kind of

64
00:03:20,440 --> 00:03:24,640
Speaker 1: investors on board, I mean many were basically playing catch

65
00:03:24,720 --> 00:03:26,880
Speaker 1: up to in video for the last two years. Is

66
00:03:26,919 --> 00:03:29,280
Speaker 1: there a slight fomo trade here going on? Is that

67
00:03:29,320 --> 00:03:31,560
Speaker 1: sort of what Hocktwan has to deal with, is that

68
00:03:31,600 --> 00:03:32,960
Speaker 1: everyone's looking for the next in video.

69
00:03:34,040 --> 00:03:36,800
Speaker 3: Yeah, I mean that's absolutely part of it, and part

70
00:03:37,080 --> 00:03:39,360
Speaker 3: of it might be the world if you think about it.

71
00:03:39,560 --> 00:03:43,160
Speaker 3: Broadcoms making chips, it's designing chips for the Googles and

72
00:03:43,200 --> 00:03:47,640
Speaker 3: the Microsoft's and companies like this who are basically designing

73
00:03:47,640 --> 00:03:49,360
Speaker 3: their own chips so that they don't have to buy

74
00:03:49,480 --> 00:03:51,920
Speaker 3: as much from InVideo. So there might be a kind

75
00:03:51,960 --> 00:03:54,960
Speaker 3: of a switch trade here. But bear in mind that

76
00:03:55,120 --> 00:03:58,760
Speaker 3: everybody who's been asked about this, mostly Hogtan most recently,

77
00:03:58,960 --> 00:04:01,200
Speaker 3: has said, look, there's plenty in for everybody. This is

78
00:04:01,200 --> 00:04:05,360
Speaker 3: a massive growth opportunity. Nobody's really taking anything away from anybody.

79
00:04:05,840 --> 00:04:08,640
Speaker 1: Very briefly, qualcom arm how big is this.

80
00:04:10,400 --> 00:04:13,840
Speaker 3: It's been sort of ignored. They need to settle, according

81
00:04:13,840 --> 00:04:15,960
Speaker 3: to investors, both of them need each other. This is

82
00:04:16,040 --> 00:04:18,760
Speaker 3: something that is very strange that they're on this collision course.

83
00:04:19,520 --> 00:04:22,320
Speaker 3: Our analysis says they should be settling.

84
00:04:22,360 --> 00:04:25,000
Speaker 1: They shouldn't be doing this. This is a jury trial,

85
00:04:25,200 --> 00:04:28,160
Speaker 1: a lot at risk currently up one hundred percent for

86
00:04:28,200 --> 00:04:30,480
Speaker 1: the year, at least on armshares in King breaking it

87
00:04:30,520 --> 00:04:32,360
Speaker 1: all down, We thank you so much. You've are more

88
00:04:32,440 --> 00:04:35,039
Speaker 1: chip news for you because Global Wafers, a Taiwanese maker

89
00:04:35,040 --> 00:04:37,800
Speaker 1: of silicon wafers used in chip manufacturing, thanks a lot.

90
00:04:37,800 --> 00:04:40,480
Speaker 1: It's finalized a deal to receive as much as four

91
00:04:40,600 --> 00:04:43,320
Speaker 1: hundred and six million dollars in awards from the US

92
00:04:43,400 --> 00:04:45,799
Speaker 1: Chips and Science Act is going to help build factories

93
00:04:45,800 --> 00:04:48,360
Speaker 1: in Texas and Missouri. Now, the US Commerce Department says

94
00:04:48,400 --> 00:04:50,719
Speaker 1: it will dull out the funds based on Global Wafers

95
00:04:50,800 --> 00:04:54,080
Speaker 1: reaching certain milestones. We've got to get in to the

96
00:04:54,160 --> 00:04:57,960
Speaker 1: whole breadth of semiconductors, but also ai what it's contributing

97
00:04:57,960 --> 00:05:00,320
Speaker 1: to the market come twenty twenty five. Callycox has US

98
00:05:00,480 --> 00:05:05,160
Speaker 1: Chief market strategistic Redhult's Wealth Management. Kelly, Look, we've got

99
00:05:05,200 --> 00:05:06,920
Speaker 1: a lot on the move when it comes to chips

100
00:05:06,960 --> 00:05:09,360
Speaker 1: on the downside today, but on the upside for the year.

101
00:05:09,920 --> 00:05:12,039
Speaker 1: Is this a trade you want to remain in the

102
00:05:12,080 --> 00:05:13,080
Speaker 1: semi conductor trade?

103
00:05:15,080 --> 00:05:17,680
Speaker 5: Seeing today, Caroline and I'll just you know, toss a

104
00:05:17,680 --> 00:05:19,520
Speaker 5: shout out to your prior guest, because I think he

105
00:05:19,960 --> 00:05:22,560
Speaker 5: framed the story of the sector so perfectly. But what

106
00:05:22,560 --> 00:05:25,039
Speaker 5: you're seeing is, you know, a trade that's stuck and

107
00:05:25,120 --> 00:05:27,600
Speaker 5: rarefied air right now. I mean, the AI trade has

108
00:05:27,640 --> 00:05:29,880
Speaker 5: been one of the big stories of twenty twenty four,

109
00:05:30,120 --> 00:05:32,359
Speaker 5: and unfortunately, what that means is that when the AI

110
00:05:32,440 --> 00:05:34,680
Speaker 5: story hits a bump, which to be clear, I don't

111
00:05:34,720 --> 00:05:36,599
Speaker 5: think it's hitting up bump today, but there are some

112
00:05:36,760 --> 00:05:40,120
Speaker 5: changes underfoot, clearly from what we saw on broadcomme earnings.

113
00:05:40,240 --> 00:05:42,559
Speaker 5: You know, when the AI trade changes or hits a bump,

114
00:05:42,600 --> 00:05:45,200
Speaker 5: then you could see some of these steeper pullbacks just

115
00:05:45,320 --> 00:05:48,120
Speaker 5: because the sector has done so well. So right now,

116
00:05:48,120 --> 00:05:50,479
Speaker 5: this is what we're warning client's about. Right Obviously, the

117
00:05:50,520 --> 00:05:54,039
Speaker 5: AI stories quite encouraging. We're excited to see where AI

118
00:05:54,160 --> 00:05:56,600
Speaker 5: goes in the coming years. But at the same time,

119
00:05:56,680 --> 00:05:59,240
Speaker 5: tech is the most overvalued.

120
00:05:58,400 --> 00:05:59,400
Speaker 6: Sector in the market.

121
00:05:59,520 --> 00:06:02,479
Speaker 5: So even there are a lot of promising science, we're

122
00:06:02,600 --> 00:06:04,960
Speaker 5: urging clients to, you know, think about balance in their

123
00:06:05,000 --> 00:06:07,920
Speaker 5: portfolios and reallocating into more unloved sectors.

124
00:06:08,279 --> 00:06:11,359
Speaker 1: Okay, so while before we get into going outside of

125
00:06:11,400 --> 00:06:14,320
Speaker 1: tech more broadly into unloved within tech, is there a

126
00:06:14,360 --> 00:06:16,800
Speaker 1: way of reorientating Many have talked about getting out of

127
00:06:16,800 --> 00:06:20,039
Speaker 1: semiconductors into software. But has that trade actually already coured?

128
00:06:20,120 --> 00:06:21,000
Speaker 1: Have you missed that boat?

129
00:06:22,240 --> 00:06:24,360
Speaker 5: Well, if you're an AI investor, if you're all about

130
00:06:24,360 --> 00:06:26,599
Speaker 5: the AI story, I think you start having you need

131
00:06:26,600 --> 00:06:28,839
Speaker 5: to start looking at the picks and shovels, and I

132
00:06:28,839 --> 00:06:30,960
Speaker 5: think many people are doing that. That's why chip makers

133
00:06:31,200 --> 00:06:33,160
Speaker 5: have had such an amazing year.

134
00:06:33,520 --> 00:06:34,760
Speaker 6: But I think it's even.

135
00:06:34,600 --> 00:06:37,120
Speaker 5: Time to look outside of chip makers there, you know,

136
00:06:37,240 --> 00:06:40,520
Speaker 5: looking at the companies that could utilize AI in their

137
00:06:40,640 --> 00:06:42,640
Speaker 5: day to day operations.

138
00:06:42,680 --> 00:06:45,840
Speaker 6: For example. You know, last year I really liked going.

139
00:06:45,600 --> 00:06:49,680
Speaker 5: Through earnings reports and seeing which companies mentioned AI and

140
00:06:49,720 --> 00:06:52,080
Speaker 5: how well they did, because there were definitely a lot

141
00:06:52,080 --> 00:06:54,000
Speaker 5: of hidden gems toward the end of last year.

142
00:06:54,200 --> 00:06:56,680
Speaker 6: That's an exercise I haven't done in a while, but

143
00:06:56,760 --> 00:06:57,480
Speaker 6: I still think that.

144
00:06:57,440 --> 00:07:00,360
Speaker 5: There's a lot of you know, hidden value there, especially

145
00:07:00,360 --> 00:07:03,400
Speaker 5: in those smaller tech companies that haven't gained as much favor.

146
00:07:03,880 --> 00:07:07,440
Speaker 1: Okay, does that remain when squarely the tech areas that

147
00:07:07,520 --> 00:07:11,600
Speaker 1: become generative AI adjacent or is it looking to the

148
00:07:11,640 --> 00:07:14,840
Speaker 1: healthcare implications to they? I mean, we've all looked at

149
00:07:14,960 --> 00:07:18,040
Speaker 1: energy from an infrastructure play, but energy is an application

150
00:07:18,120 --> 00:07:21,440
Speaker 1: to play as well, how you seeing other sectors adult

151
00:07:21,480 --> 00:07:22,920
Speaker 1: AI and help their numbers.

152
00:07:24,800 --> 00:07:25,440
Speaker 6: I'd speak clear.

153
00:07:25,480 --> 00:07:29,080
Speaker 5: I don't look too far into AI usage beyond you know,

154
00:07:29,160 --> 00:07:33,200
Speaker 5: those broader sector trends that I think every Mark Wall

155
00:07:33,200 --> 00:07:34,320
Speaker 5: Street expert watches.

156
00:07:34,760 --> 00:07:35,520
Speaker 6: But I think you're right.

157
00:07:35,560 --> 00:07:37,680
Speaker 5: I think that there are a lot of applications that

158
00:07:37,680 --> 00:07:41,040
Speaker 5: you could see, especially in healthcare, especially in energy. I

159
00:07:41,040 --> 00:07:44,440
Speaker 5: think industrials are another interesting sector for the AI trade.

160
00:07:44,520 --> 00:07:46,680
Speaker 5: But I think what investors need to remember right now

161
00:07:46,800 --> 00:07:49,440
Speaker 5: is that this is a very long term story.

162
00:07:49,480 --> 00:07:52,600
Speaker 6: You can't judge it by one day or a few days.

163
00:07:52,960 --> 00:07:55,360
Speaker 6: This is going to take years to materialize.

164
00:07:55,720 --> 00:07:58,120
Speaker 5: So if you're looking for those unlove stocks, if you're

165
00:07:58,440 --> 00:08:02,640
Speaker 5: looking for those companies that might be dabbling in AI applications,

166
00:08:02,680 --> 00:08:04,600
Speaker 5: you have to be thinking about holding them for years

167
00:08:04,640 --> 00:08:05,400
Speaker 5: and years.

168
00:08:06,120 --> 00:08:09,080
Speaker 1: How do you find them, Kelly? How do you find

169
00:08:09,120 --> 00:08:11,840
Speaker 1: the unloved smaller stock that no one's been talking about?

170
00:08:11,840 --> 00:08:13,440
Speaker 1: What is it that you're going to go into from

171
00:08:13,480 --> 00:08:17,120
Speaker 1: a data perspective, from a signal perspective, Well, I.

172
00:08:17,120 --> 00:08:17,720
Speaker 6: Think that there.

173
00:08:18,120 --> 00:08:19,360
Speaker 5: I mean, I think there are still a lot of

174
00:08:19,400 --> 00:08:22,360
Speaker 5: opportunities out there. Interest rates are quite high. That's led

175
00:08:22,400 --> 00:08:25,800
Speaker 5: to a pretty thin rally over the past year or so,

176
00:08:26,400 --> 00:08:29,800
Speaker 5: and because there have been because the rally has been

177
00:08:29,800 --> 00:08:31,840
Speaker 5: so thin. To be clear, you know, I think that

178
00:08:31,880 --> 00:08:34,280
Speaker 5: there are some some companies that are maybe on the

179
00:08:34,280 --> 00:08:37,080
Speaker 5: cusp of you know, talking about AI more, you know,

180
00:08:37,160 --> 00:08:41,000
Speaker 5: discovering applications for AI that haven't gotten that market love

181
00:08:41,080 --> 00:08:44,760
Speaker 5: that other big tech, other more attention grabbing names have

182
00:08:45,200 --> 00:08:47,120
Speaker 5: So I think you have to look at valuations first

183
00:08:47,120 --> 00:08:49,760
Speaker 5: of all, look at valuations, you know, look at the

184
00:08:49,800 --> 00:08:50,720
Speaker 5: plan for earnings.

185
00:08:50,760 --> 00:08:51,480
Speaker 6: I don't think.

186
00:08:51,320 --> 00:08:55,559
Speaker 5: Many AI companies or AI tent uh you know, AI

187
00:08:56,080 --> 00:09:00,280
Speaker 5: tangential companies are you know, seeing earnings come from you know,

188
00:09:00,360 --> 00:09:02,640
Speaker 5: AI AI applications.

189
00:09:02,960 --> 00:09:04,600
Speaker 6: This is still a very early story.

190
00:09:04,640 --> 00:09:06,319
Speaker 5: But I think right now, if you are a long

191
00:09:06,400 --> 00:09:10,080
Speaker 5: term investor, you can look at valuations. You can look

192
00:09:10,120 --> 00:09:12,920
Speaker 5: at you know, revenue signals that we've seen in Nvidio

193
00:09:12,960 --> 00:09:15,760
Speaker 5: and Broadcon for example, and see if there are those

194
00:09:15,800 --> 00:09:19,880
Speaker 5: early signs of uptake even management commentary. I think you

195
00:09:19,920 --> 00:09:22,320
Speaker 5: can find some pretty valuable things there. But that requires

196
00:09:22,360 --> 00:09:24,840
Speaker 5: having to you know, really parse through earnings reports and

197
00:09:24,920 --> 00:09:26,600
Speaker 5: listening to these earnings calls.

198
00:09:26,679 --> 00:09:27,560
Speaker 6: It takes a lot of work.

199
00:09:27,720 --> 00:09:29,320
Speaker 1: It takes a lot of work. That's why you get

200
00:09:29,360 --> 00:09:31,920
Speaker 1: paid the big bucks. But let's talk Kelly about the

201
00:09:31,960 --> 00:09:34,960
Speaker 1: macro picture here, because while we are in this moment

202
00:09:35,120 --> 00:09:38,800
Speaker 1: of valuations pretty high, run up significant, you've got a

203
00:09:38,840 --> 00:09:41,480
Speaker 1: FED that we're looking to cut tomorrow. How much risk

204
00:09:41,600 --> 00:09:42,720
Speaker 1: is there a macro policy.

205
00:09:44,160 --> 00:09:46,680
Speaker 5: I think there's a lot of risk at the moment.

206
00:09:46,840 --> 00:09:49,320
Speaker 5: And you know, right now, I still feel quite encouraged

207
00:09:49,360 --> 00:09:52,680
Speaker 5: by the economy. The economy has been incredibly resilient over

208
00:09:52,720 --> 00:09:53,840
Speaker 5: the past few years.

209
00:09:54,040 --> 00:09:55,800
Speaker 6: But the risk I see, Caroline, is.

210
00:09:55,760 --> 00:09:58,920
Speaker 5: The fact that we're leaning into this tech versus everything

211
00:09:58,960 --> 00:10:00,960
Speaker 5: else trade again in the month of December.

212
00:10:01,440 --> 00:10:04,040
Speaker 6: But you know, you still have a FED that isn't

213
00:10:04,240 --> 00:10:05,599
Speaker 6: hasn't been quite clear.

214
00:10:05,360 --> 00:10:07,920
Speaker 5: About where they will go into twenty twenty five, and

215
00:10:07,960 --> 00:10:10,280
Speaker 5: we're about to get a lot of detail around that

216
00:10:10,520 --> 00:10:14,119
Speaker 5: tomorrow when the FED releases its decision, and more importantly,

217
00:10:14,440 --> 00:10:16,679
Speaker 5: Jay Powell comes out and holds his forty five minute

218
00:10:16,679 --> 00:10:19,080
Speaker 5: press conference. I mean, this is a FED chair that

219
00:10:19,200 --> 00:10:22,840
Speaker 5: loves to talk about scenarios going into the future, and

220
00:10:23,120 --> 00:10:26,760
Speaker 5: I just I think markets and Wall Street are overestimating,

221
00:10:27,040 --> 00:10:29,880
Speaker 5: you know, where inflation could be, how high rates could go.

222
00:10:29,880 --> 00:10:32,400
Speaker 6: Because there still are signals of weakness in the job.

223
00:10:32,320 --> 00:10:35,960
Speaker 1: Market helicops always taking US border. We thank you, Chief

224
00:10:36,000 --> 00:10:47,480
Speaker 1: market strategist Harid Hold's Wealth Management Happy holidays. The EU

225
00:10:47,800 --> 00:10:51,040
Speaker 1: it's investigating TikTok, suspecting it didn't do enough to stop

226
00:10:51,080 --> 00:10:54,319
Speaker 1: fake accounts and foreign powers from interfering with the Romanian

227
00:10:54,400 --> 00:10:57,160
Speaker 1: presidential election last month. Now, the probe will look at

228
00:10:57,200 --> 00:10:59,880
Speaker 1: whether the app failed to prevent bad actors from manipulating

229
00:11:00,120 --> 00:11:04,240
Speaker 1: recommendation system and if it correctly labeled political content under

230
00:11:04,240 --> 00:11:07,440
Speaker 1: the block's Digital Services Act and stigma with TikTok here

231
00:11:07,440 --> 00:11:10,160
Speaker 1: in the US, CEO show Cho met with President elect

232
00:11:10,160 --> 00:11:13,240
Speaker 1: Donald Trump just weeks before The app is expected, of course,

233
00:11:13,280 --> 00:11:15,520
Speaker 1: to be potentially banned if it's not divested in the

234
00:11:15,640 --> 00:11:19,240
Speaker 1: US over national security concerns. Rehomrs Alexander Levine is here

235
00:11:19,280 --> 00:11:21,920
Speaker 1: and everyone is a who's who of in and out

236
00:11:22,000 --> 00:11:23,800
Speaker 1: at Mari a Lago at the moment, but showed Chu

237
00:11:23,960 --> 00:11:27,319
Speaker 1: is notable considering what Trump said yesterday about the little

238
00:11:27,400 --> 00:11:29,000
Speaker 1: place in his heart he has for TikTok.

239
00:11:29,440 --> 00:11:32,680
Speaker 7: Absolutely, you know, we've seen legal blow after legal blow

240
00:11:32,679 --> 00:11:34,880
Speaker 7: after legal blow for both TikTok and its parent company

241
00:11:34,880 --> 00:11:37,440
Speaker 7: by Dance this month alone, just as they've been trying

242
00:11:37,440 --> 00:11:39,840
Speaker 7: to fight off this law that's supposed to take effect

243
00:11:39,840 --> 00:11:43,040
Speaker 7: in January. But in pulling out all the steps, we

244
00:11:43,080 --> 00:11:45,240
Speaker 7: saw a show at Mari a Lago yesterday. And to

245
00:11:45,280 --> 00:11:47,640
Speaker 7: your point, he's not the first tech leader. We've seen

246
00:11:47,679 --> 00:11:49,920
Speaker 7: Mark zuckerbergo in recent weeks to talk to Trump and

247
00:11:49,960 --> 00:11:52,040
Speaker 7: his team. We've seen Tim Cook as well. But the

248
00:11:52,080 --> 00:11:54,559
Speaker 7: stakes are so much higher right now, with the ban

249
00:11:55,040 --> 00:11:58,200
Speaker 7: just over a month away January nineteenth. The stakes are

250
00:11:58,200 --> 00:12:00,600
Speaker 7: so much higher for show than they have been for

251
00:12:00,640 --> 00:12:02,560
Speaker 7: really any of the other tech leaders that have visited

252
00:12:02,600 --> 00:12:02,920
Speaker 7: so far.

253
00:12:03,000 --> 00:12:04,959
Speaker 1: And at the moment it's being thrown at the Supreme

254
00:12:04,960 --> 00:12:08,199
Speaker 1: Court store but what technically do you think of that

255
00:12:08,320 --> 00:12:10,280
Speaker 1: argument the Supreme Court.

256
00:12:10,800 --> 00:12:13,240
Speaker 7: Basically TikTok has now asked the Supreme Court to take

257
00:12:13,240 --> 00:12:16,000
Speaker 7: the case because the DC Court had said that they

258
00:12:16,200 --> 00:12:19,040
Speaker 7: know they will not pause the law from taking effect,

259
00:12:19,160 --> 00:12:23,720
Speaker 7: and they basically upheld the law. When the Supreme Court decides,

260
00:12:23,840 --> 00:12:26,480
Speaker 7: that's going to be likely two days before the band

261
00:12:26,520 --> 00:12:28,240
Speaker 7: is supposed to take effect. And so you can be

262
00:12:28,280 --> 00:12:31,920
Speaker 7: sure that regardless of what the Supreme Court says come January,

263
00:12:32,200 --> 00:12:34,200
Speaker 7: that all these other companies that are going to be

264
00:12:34,200 --> 00:12:36,920
Speaker 7: on the hook for actually enforcing it, including Apple and Google,

265
00:12:36,960 --> 00:12:41,960
Speaker 7: most notably that preparations are definitely underway with getting ready

266
00:12:42,000 --> 00:12:43,880
Speaker 7: for actually pulling the app off of the app stores.

267
00:12:44,000 --> 00:12:47,320
Speaker 1: And before we get into how technically difficult and logistically

268
00:12:47,320 --> 00:12:50,000
Speaker 1: difficult that is, go back to what the Moon music

269
00:12:50,040 --> 00:12:53,720
Speaker 1: just seems internally externally when you do see Trump signaling

270
00:12:53,920 --> 00:12:55,880
Speaker 1: that he likes the platform at least and doesn't want

271
00:12:55,880 --> 00:12:57,640
Speaker 1: to fund young voters absolutely.

272
00:12:57,679 --> 00:12:59,720
Speaker 7: I mean, yesterday to your point, we heard him say

273
00:13:00,080 --> 00:13:02,880
Speaker 7: sweet spot for TikTok. I think we you know, you

274
00:13:02,960 --> 00:13:04,240
Speaker 7: want to be able to take what he says at

275
00:13:04,280 --> 00:13:06,320
Speaker 7: face value. But then you also have to take into

276
00:13:06,400 --> 00:13:09,960
Speaker 7: consideration that he's stacking his team, his incoming team, with

277
00:13:10,120 --> 00:13:13,920
Speaker 7: all of the most outspoken anti TikTok crusaders that have

278
00:13:14,120 --> 00:13:16,360
Speaker 7: been in Congress and across the American government. And so

279
00:13:16,640 --> 00:13:19,480
Speaker 7: there's a big question about whether once he is in office,

280
00:13:19,520 --> 00:13:21,600
Speaker 7: and once he is surrounded by all of these people

281
00:13:21,640 --> 00:13:24,800
Speaker 7: who had the knowledge of you know, the knowledge that

282
00:13:24,840 --> 00:13:26,920
Speaker 7: got the legislation and the law across the across the

283
00:13:26,920 --> 00:13:29,320
Speaker 7: finish line in the first place, whether they may be

284
00:13:29,360 --> 00:13:32,560
Speaker 7: able to convince him not to keep the platform.

285
00:13:33,400 --> 00:13:36,560
Speaker 1: Hard to know which line to discern from Alexandra Levine

286
00:13:36,559 --> 00:13:39,120
Speaker 1: always had it putting us dissected. We thank you. Meanwhile,

287
00:13:39,200 --> 00:13:44,200
Speaker 1: US Citizenship and Immigration Services finalized new H one B regulations,

288
00:13:44,280 --> 00:13:48,720
Speaker 1: actually overhauling eligibility standards for the primary visa program used

289
00:13:48,720 --> 00:13:52,960
Speaker 1: by most tech firms. Really, the regulations issued today codify

290
00:13:53,040 --> 00:13:56,800
Speaker 1: a policy of pride deference in deciding extensions of previously

291
00:13:56,800 --> 00:13:59,680
Speaker 1: approved H one B visas. The first Trump administration had

292
00:13:59,760 --> 00:14:04,839
Speaker 1: dropped that policy, significantly slowing visa extensions. Now, let's look

293
00:14:04,840 --> 00:14:06,800
Speaker 1: at Mike Gallagher for a moment now as well, former

294
00:14:06,840 --> 00:14:10,200
Speaker 1: Congressman turned Palenteer's head a defense and he said that

295
00:14:10,200 --> 00:14:13,480
Speaker 1: the US Defense Department needs to overhaul its procurement process

296
00:14:13,520 --> 00:14:15,960
Speaker 1: for a new era of modern warfare, and he's stepping

297
00:14:16,000 --> 00:14:18,160
Speaker 1: up efforts to seed startups that can help restore the

298
00:14:18,200 --> 00:14:22,640
Speaker 1: country's competitive edge. Remergs Lazette Chapman spoke with him and Lizette.

299
00:14:22,720 --> 00:14:26,280
Speaker 1: It really feels as though this American dynamism, this defense

300
00:14:26,440 --> 00:14:31,840
Speaker 1: tech euphoria post election, is just continuing here. Yeah, you're

301
00:14:31,880 --> 00:14:32,880
Speaker 1: spot on about that.

302
00:14:34,320 --> 00:14:37,680
Speaker 8: Defense tech has been on an absolute tear for the

303
00:14:37,720 --> 00:14:40,920
Speaker 8: past four or five years, and it's only set to

304
00:14:41,200 --> 00:14:46,520
Speaker 8: accelerate now that there are many of these companies have

305
00:14:46,560 --> 00:14:50,200
Speaker 8: reached a critical mass, like Palentteer, like SpaceX, and like

306
00:14:50,200 --> 00:14:51,840
Speaker 8: some of the up and comers like andrel that we

307
00:14:51,880 --> 00:14:52,800
Speaker 8: get into in the story.

308
00:14:53,600 --> 00:14:56,560
Speaker 1: Yeah, let's get into the story, because ultimately you sat

309
00:14:56,600 --> 00:14:59,120
Speaker 1: down with Gala. I mean, he's a famous China Hawk

310
00:14:59,320 --> 00:15:02,240
Speaker 1: just thinking of what we were speaking with Alexandra, but

311
00:15:02,320 --> 00:15:04,880
Speaker 1: a moment ago, and he can weigh in on TikTok.

312
00:15:04,960 --> 00:15:07,720
Speaker 1: But how do you think we'll get more of a

313
00:15:07,760 --> 00:15:11,200
Speaker 1: star top friendly Department of Defense in the US. What

314
00:15:11,280 --> 00:15:12,040
Speaker 1: changes can be made?

315
00:15:12,920 --> 00:15:17,280
Speaker 8: Oh, there's so many different changes that cadre of people

316
00:15:18,040 --> 00:15:20,240
Speaker 8: on both the dem side and also the Republican side

317
00:15:20,240 --> 00:15:22,880
Speaker 8: have been pushing for for years, going back even over

318
00:15:22,920 --> 00:15:25,800
Speaker 8: a decade when Palanteer and SpaceX actually sued the US

319
00:15:25,880 --> 00:15:30,400
Speaker 8: government for the right to compete to win contracts. Moving

320
00:15:30,440 --> 00:15:33,520
Speaker 8: it up to date now, there are a lot of

321
00:15:33,600 --> 00:15:37,800
Speaker 8: changes to the procurement process, the process of deciding what

322
00:15:38,760 --> 00:15:44,440
Speaker 8: the different branches need, how it should be designed, making

323
00:15:44,440 --> 00:15:47,120
Speaker 8: sure it's interoperable for the future, and then of course

324
00:15:47,160 --> 00:15:51,080
Speaker 8: the process of selecting bidders and then ultimately selecting the winner.

325
00:15:51,400 --> 00:15:53,440
Speaker 8: So that whole process they want to see it really

326
00:15:53,480 --> 00:15:56,520
Speaker 8: contracted from the year's long process of doing something like

327
00:15:56,560 --> 00:16:00,560
Speaker 8: an F thirty five fighter jet to something much shorter

328
00:16:00,640 --> 00:16:04,800
Speaker 8: timeframe that better reflects the types of warfare that change,

329
00:16:05,360 --> 00:16:08,080
Speaker 8: you know, every not in terms of years, but in

330
00:16:08,160 --> 00:16:10,240
Speaker 8: terms of months or even weeks. Have we seen with

331
00:16:10,280 --> 00:16:13,040
Speaker 8: the drone and a drones and AI and a lot

332
00:16:13,080 --> 00:16:16,080
Speaker 8: of autonomous systems. In your story, they're looking to shorten that.

333
00:16:16,200 --> 00:16:19,320
Speaker 1: Yeah, in your story, you highlight how Elomas cooled well,

334
00:16:19,480 --> 00:16:22,840
Speaker 1: the builders of F thirty five warplanes idiots. I mean,

335
00:16:22,840 --> 00:16:26,400
Speaker 1: he's never short on wads and descriptions, but thatte What's

336
00:16:26,400 --> 00:16:28,400
Speaker 1: interesting is about the way in which Pollenteer and Mike

337
00:16:28,440 --> 00:16:31,240
Speaker 1: Gallagher in particular, trying to foster the startup ecosystem. How

338
00:16:31,240 --> 00:16:33,240
Speaker 1: are they doing that right?

339
00:16:33,760 --> 00:16:38,120
Speaker 8: They're reaching out to a lot of companies through something

340
00:16:38,160 --> 00:16:41,360
Speaker 8: that they expanded they just recently expanded under under Mike Gallagher,

341
00:16:41,720 --> 00:16:46,320
Speaker 8: who leads Global Defense now for Palenteer, and it's.

342
00:16:45,960 --> 00:16:49,480
Speaker 1: To encourage software.

343
00:16:49,040 --> 00:16:51,680
Speaker 8: Startups that want to do business with the US government

344
00:16:52,120 --> 00:16:57,120
Speaker 8: to apply through Palenteer's fed Start program so that Palenteer

345
00:16:57,200 --> 00:17:01,320
Speaker 8: can host their software for fee and deal with all

346
00:17:01,360 --> 00:17:06,000
Speaker 8: of the accreditation issues, the different requirements all the software

347
00:17:06,400 --> 00:17:09,679
Speaker 8: updates and monitoring and keeping them up to up to

348
00:17:09,760 --> 00:17:12,040
Speaker 8: date and current. And that's a really big deal for

349
00:17:12,440 --> 00:17:17,280
Speaker 8: a lot of startups who have different needs from different

350
00:17:17,520 --> 00:17:20,959
Speaker 8: Every agency might have a different requirement to comply with.

351
00:17:21,000 --> 00:17:22,119
Speaker 1: Now, first startup with only.

352
00:17:21,960 --> 00:17:24,879
Speaker 8: Twenty people or maybe fifty people, that's very hard to

353
00:17:24,880 --> 00:17:29,280
Speaker 8: set up that infrastructure that takes a long period of

354
00:17:29,320 --> 00:17:32,359
Speaker 8: time they said years and you know, down to something

355
00:17:32,440 --> 00:17:35,119
Speaker 8: shorter that they can handle. That's what fed Start and

356
00:17:35,240 --> 00:17:38,199
Speaker 8: Palenteer are working to do. And it's in competition with

357
00:17:38,280 --> 00:17:41,760
Speaker 8: other companies like second Front for example, that's also looking.

358
00:17:41,520 --> 00:17:45,159
Speaker 1: To do that. Yeah, trying to reduce the compliance headache.

359
00:17:45,280 --> 00:17:47,920
Speaker 1: Is that Chatmander is a great read. Go check it out.

360
00:17:48,040 --> 00:17:50,880
Speaker 1: We appreciate you on today. Let's just talk about elsewhere

361
00:17:50,880 --> 00:17:54,760
Speaker 1: in the VC ecosystem. Data Bricks raising ten billion dollars

362
00:17:54,800 --> 00:17:58,000
Speaker 1: in new funding, a series J which brings US Software

363
00:17:58,000 --> 00:18:00,720
Speaker 1: makes valuation to a whopping sixty two billion Data Brick

364
00:18:00,800 --> 00:18:04,880
Speaker 1: stating it intends to invest this capital towards new AI products, acquisitions,

365
00:18:05,160 --> 00:18:08,439
Speaker 1: and significant expansion of its international go to market operations.

366
00:18:09,359 --> 00:18:12,560
Speaker 1: Now coming up some tech m and a news. Also

367
00:18:12,880 --> 00:18:17,199
Speaker 1: in the startup space, Grammarly acquiring coder Grammarly's incoming CEO

368
00:18:17,320 --> 00:18:18,920
Speaker 1: is going to be joining us next. This's is Bloomberg

369
00:18:18,920 --> 00:18:26,200
Speaker 1: Technology Grammily. It's the maker of AI powered writing assistance software,

370
00:18:26,280 --> 00:18:29,359
Speaker 1: and it's acquiring productivity startup Coda in a deal that

371
00:18:29,400 --> 00:18:32,920
Speaker 1: will also bring in a new CEO, Shashi Marotra. It's

372
00:18:32,960 --> 00:18:35,680
Speaker 1: currently the co founder and CEO of Coda and is

373
00:18:35,760 --> 00:18:37,920
Speaker 1: lated to take over the top job at the combined

374
00:18:37,920 --> 00:18:40,520
Speaker 1: Grammarly joins us now for more on the deal. So

375
00:18:40,640 --> 00:18:44,480
Speaker 1: coming together productivity tools, what do you offer as one?

376
00:18:45,200 --> 00:18:48,120
Speaker 2: Yeah, I'm really excited about this opportunity Coda joining with Germily.

377
00:18:48,160 --> 00:18:50,439
Speaker 2: I've been personal user of the product for many years,

378
00:18:50,840 --> 00:18:54,960
Speaker 2: really drawn to the innovative approach, passionate people. But the

379
00:18:55,040 --> 00:18:58,159
Speaker 2: reason that's happened was the leaders of both companies that

380
00:18:58,240 --> 00:19:00,560
Speaker 2: got together and just painted our vision for the future,

381
00:19:00,600 --> 00:19:03,240
Speaker 2: what we saw with the future of AI productivity, and

382
00:19:03,240 --> 00:19:05,879
Speaker 2: it just turned out that our view was near identical.

383
00:19:06,000 --> 00:19:09,160
Speaker 2: We both saw the technology evolving to what we call

384
00:19:09,280 --> 00:19:13,240
Speaker 2: user centered AI and a future world where the applications

385
00:19:13,280 --> 00:19:16,640
Speaker 2: we use won't feel as isolated, siloed, rigid that we're

386
00:19:16,720 --> 00:19:20,320
Speaker 2: used today, instead really focused on the user adapted to

387
00:19:20,320 --> 00:19:22,879
Speaker 2: each person, their teams, their roles. So we're going to

388
00:19:22,880 --> 00:19:25,720
Speaker 2: be building a user centered AI platform or the future

389
00:19:25,760 --> 00:19:28,480
Speaker 2: for focused on applications and agents for everybody.

390
00:19:28,640 --> 00:19:33,120
Speaker 1: It's a competitive space. I hear agents being named by startup,

391
00:19:33,200 --> 00:19:36,959
Speaker 1: by large publicly traded business alike, and I hear of

392
00:19:37,280 --> 00:19:39,159
Speaker 1: you know, Apple trying to integrate trying to make my

393
00:19:39,200 --> 00:19:41,560
Speaker 1: email flow easier. How are you going to compete against

394
00:19:41,560 --> 00:19:42,920
Speaker 1: big tech as well as startups?

395
00:19:43,400 --> 00:19:45,280
Speaker 2: Yeah, I mean, maybe just start with the term agent.

396
00:19:45,320 --> 00:19:48,000
Speaker 2: I know, it's a hot term everybody is using these days.

397
00:19:48,359 --> 00:19:51,399
Speaker 2: I think of Grammarly as actually the original AI agent.

398
00:19:51,480 --> 00:19:54,199
Speaker 2: I mean, it's about forty million users use We use

399
00:19:54,240 --> 00:19:57,400
Speaker 2: Grammarly every day, goes through about two hundred billion words

400
00:19:57,440 --> 00:19:59,880
Speaker 2: a day, and one of the key things about that

401
00:20:00,080 --> 00:20:03,440
Speaker 2: agent is that it works right alongside you. One of

402
00:20:03,440 --> 00:20:05,800
Speaker 2: the big innovations that Garmley has worked on is that

403
00:20:05,880 --> 00:20:08,639
Speaker 2: instead of forcing to go to some other place, it

404
00:20:08,720 --> 00:20:11,760
Speaker 2: follows you into every different surface. About five hundred thousand

405
00:20:11,760 --> 00:20:15,679
Speaker 2: different applications that have been integrated with with Grammarly. One

406
00:20:15,720 --> 00:20:17,600
Speaker 2: of the terms the Granmarley team likes to use I've

407
00:20:17,600 --> 00:20:20,000
Speaker 2: really loved is the idea that they've built this AI

408
00:20:20,119 --> 00:20:24,520
Speaker 2: super highway and it's the gateway to have agents actually

409
00:20:24,560 --> 00:20:27,359
Speaker 2: work with you in every other tool. But one observation

410
00:20:27,480 --> 00:20:29,560
Speaker 2: is right now there's sort of only one car running

411
00:20:29,600 --> 00:20:32,640
Speaker 2: on that highway that the Grammarly tool set today. It's amazing,

412
00:20:32,680 --> 00:20:34,760
Speaker 2: but what it does is just help you with your

413
00:20:34,960 --> 00:20:37,760
Speaker 2: with your proof reading. And one of the things we're

414
00:20:37,760 --> 00:20:39,000
Speaker 2: going to do is we're going to take one of

415
00:20:39,040 --> 00:20:40,639
Speaker 2: the most popular parts of the Code of Product, we

416
00:20:40,680 --> 00:20:42,679
Speaker 2: call it Code of Brain, which is a network of

417
00:20:42,800 --> 00:20:45,520
Speaker 2: hundreds of integrations into all your all of your back

418
00:20:45,560 --> 00:20:47,679
Speaker 2: end systems, and we're going to turn them into agents

419
00:20:47,720 --> 00:20:50,000
Speaker 2: on this platform. And so what you can imagine is

420
00:20:50,080 --> 00:20:55,520
Speaker 2: instead of interacting with Grammarly as just a proof reading agent,

421
00:20:55,840 --> 00:20:58,320
Speaker 2: you can imagine that now the suggestion that come to

422
00:20:58,359 --> 00:21:01,320
Speaker 2: you will help you draft consents, can help you structure

423
00:21:01,359 --> 00:21:04,679
Speaker 2: customer conversations, can help you update your CRM systems, and

424
00:21:04,720 --> 00:21:07,720
Speaker 2: we can really bring agents right to the user's that's

425
00:21:07,720 --> 00:21:09,040
Speaker 2: one of the main things we'll be working on.

426
00:21:09,200 --> 00:21:12,240
Speaker 1: Shisha. You said how your goals of the two companies

427
00:21:12,359 --> 00:21:16,159
Speaker 1: were basically completely in line. Is the goal and IPO

428
00:21:16,240 --> 00:21:18,119
Speaker 1: in line as well. When you're looking at the changes

429
00:21:18,119 --> 00:21:22,000
Speaker 1: made of Grammarly, new CTO from Instacart, new CFO coming

430
00:21:22,000 --> 00:21:24,560
Speaker 1: from Hashi Corp. You with your background at YouTube and

431
00:21:24,720 --> 00:21:27,239
Speaker 1: big companies as well as startups, it looks as though

432
00:21:27,240 --> 00:21:28,200
Speaker 1: you're destined for an IPO.

433
00:21:29,440 --> 00:21:29,560
Speaker 9: You know.

434
00:21:29,640 --> 00:21:33,200
Speaker 2: I think I think the goal is to build an

435
00:21:33,280 --> 00:21:36,919
Speaker 2: enduring company, and I think that in this sort of

436
00:21:36,920 --> 00:21:40,000
Speaker 2: crazy world of AI changing everything we work on, I

437
00:21:40,040 --> 00:21:42,879
Speaker 2: think it's a very smallest of companies that can have

438
00:21:43,119 --> 00:21:47,639
Speaker 2: that meaningful platform to really be that that future of AI.

439
00:21:48,160 --> 00:21:50,960
Speaker 2: I think the approach of Grammarly and now with CODA,

440
00:21:51,000 --> 00:21:53,159
Speaker 2: I think we can really be at the forefront of that.

441
00:21:53,520 --> 00:21:55,640
Speaker 2: And yeah, we'd like to be one of those top

442
00:21:55,720 --> 00:21:57,800
Speaker 2: three or four companies that people think of when they

443
00:21:57,840 --> 00:22:01,560
Speaker 2: think about the AI tools for for their world to share.

444
00:22:01,960 --> 00:22:05,040
Speaker 1: Rotra, thank you for coming on incoming, CEO of Grammarly,

445
00:22:12,960 --> 00:22:14,960
Speaker 1: Welcome back to the new meg Technology. Karen Hide in

446
00:22:14,960 --> 00:22:16,800
Speaker 1: New York. Quick check on your markets. Look, we're all

447
00:22:16,800 --> 00:22:19,560
Speaker 1: eyes on the FED tomorrow and digesting some retail data

448
00:22:19,600 --> 00:22:22,760
Speaker 1: today that still shows the US economy is going strong.

449
00:22:23,119 --> 00:22:23,439
Speaker 10: Go new.

450
00:22:23,480 --> 00:22:25,280
Speaker 1: Sometimes bad news. Then as that one hundred fourth, sir,

451
00:22:25,320 --> 00:22:26,879
Speaker 1: it's record high. We're off by just three tens and

452
00:22:26,880 --> 00:22:29,280
Speaker 1: percent chip makers on the downside, in particular some profit

453
00:22:29,280 --> 00:22:31,440
Speaker 1: taking over at Broadcom. Move on and have a look

454
00:22:31,440 --> 00:22:33,600
Speaker 1: at what's happening in individual movers when it comes to

455
00:22:33,600 --> 00:22:36,320
Speaker 1: the crypto space as well. Bitcoin still up at one

456
00:22:36,320 --> 00:22:37,960
Speaker 1: point one hundred and eight thousand, We're one hundred and

457
00:22:37,960 --> 00:22:40,360
Speaker 1: six thousand as we trade, are still holding onto those

458
00:22:40,400 --> 00:22:43,199
Speaker 1: record highs. Micro strategy though, just seeing a bit of

459
00:22:43,200 --> 00:22:45,760
Speaker 1: profit taking show, we say, after a five hundred percent

460
00:22:45,840 --> 00:22:48,480
Speaker 1: run up this year, of course, basically a Bitcoin proxy

461
00:22:48,640 --> 00:22:51,679
Speaker 1: entering the Nasdaq one hundred on Friday, many feeling this

462
00:22:51,720 --> 00:22:54,520
Speaker 1: will be the beginning of a momentum trade. But how

463
00:22:54,600 --> 00:22:57,199
Speaker 1: much of this is a priced in already? Much of that,

464
00:22:57,280 --> 00:22:59,760
Speaker 1: of course, is because sectors like crypto are continuing to

465
00:22:59,800 --> 00:23:02,879
Speaker 1: out following the election of Trump. How is broader hiring?

466
00:23:02,920 --> 00:23:06,639
Speaker 1: How is startup optimism? Payrolls processing company Gusto has a

467
00:23:06,680 --> 00:23:09,520
Speaker 1: bird's eye perspective. Hr startup has announced, in fact, a

468
00:23:09,520 --> 00:23:13,200
Speaker 1: new partnership with zero. It's a leading accounting software platform

469
00:23:13,240 --> 00:23:16,600
Speaker 1: for small businesses motally lad Let's ask Gusto CEO and

470
00:23:16,640 --> 00:23:18,720
Speaker 1: co founder Josh Reeves, It's great to have you here.

471
00:23:18,800 --> 00:23:20,720
Speaker 1: Pleasure to be here. Thanks, Carolyn. So let's talk about

472
00:23:20,720 --> 00:23:23,120
Speaker 1: the partnership and why you're focusing on small and you're

473
00:23:23,200 --> 00:23:26,080
Speaker 1: already a provider to an awful lot of small and

474
00:23:26,119 --> 00:23:29,439
Speaker 1: medium sized enterprises, why furrow that even more so?

475
00:23:29,480 --> 00:23:32,000
Speaker 11: We're thrilled to support and serve over four hundred thousand

476
00:23:32,000 --> 00:23:35,159
Speaker 11: small businesses today. And one of the things we realized

477
00:23:35,160 --> 00:23:37,360
Speaker 11: a couple of years ago is you have small businesses

478
00:23:37,359 --> 00:23:39,639
Speaker 11: that are going to use Gusto directly, but there's a

479
00:23:39,640 --> 00:23:42,800
Speaker 11: lot of small businesses out there served by existing platforms

480
00:23:42,880 --> 00:23:45,760
Speaker 11: LEG zero and zero focuses like you mentioned on accounting.

481
00:23:46,040 --> 00:23:48,080
Speaker 11: A lot of these other platforms do not want to

482
00:23:48,119 --> 00:23:51,200
Speaker 11: go build things like payroll themselves, and so we created

483
00:23:51,200 --> 00:23:54,560
Speaker 11: this industry called embedded payroll, which is basically the ability

484
00:23:54,560 --> 00:23:56,880
Speaker 11: for folks legs zero and that's what we're announcing today

485
00:23:57,160 --> 00:24:00,320
Speaker 11: to launch their own payroll products powered by Gusta, so

486
00:24:00,400 --> 00:24:03,320
Speaker 11: more analogous to that stripe type business model, and we're

487
00:24:03,359 --> 00:24:04,800
Speaker 11: really excited about it because it's a way for us

488
00:24:04,840 --> 00:24:06,920
Speaker 11: to reach more small businesses where they're.

489
00:24:06,720 --> 00:24:10,760
Speaker 1: At and are they ultimately underserved at the moment Because

490
00:24:11,720 --> 00:24:14,520
Speaker 1: your startup space is a busy one, there are plenty

491
00:24:14,520 --> 00:24:17,560
Speaker 1: of hr payroll startups trying to be the be all

492
00:24:17,600 --> 00:24:19,840
Speaker 1: and end all to everyone. How are you finding that

493
00:24:20,000 --> 00:24:21,760
Speaker 1: small medium sized enterprise space.

494
00:24:22,080 --> 00:24:24,199
Speaker 11: Yeah, so I always loved reminding folks there's more dentist

495
00:24:24,240 --> 00:24:26,840
Speaker 11: offices in the US than tech startups. So we really

496
00:24:26,880 --> 00:24:29,200
Speaker 11: do obsess over and zero does as well, and a

497
00:24:29,240 --> 00:24:31,119
Speaker 11: lot of our partners. Actually, we're thrilled to partner with

498
00:24:31,119 --> 00:24:35,200
Speaker 11: a number of companies, including Chase Payment Solutions, to basically

499
00:24:35,240 --> 00:24:38,720
Speaker 11: bring modern, delightful payroll to where they're at in a

500
00:24:38,760 --> 00:24:41,840
Speaker 11: more accessible, intuitive way. Saves them time, saves the money,

501
00:24:41,880 --> 00:24:45,040
Speaker 11: prevents mistakes, filing issues, and we've built now ten plus

502
00:24:45,119 --> 00:24:48,119
Speaker 11: years of infrastructure processing over half a trillion dollars of

503
00:24:48,119 --> 00:24:50,639
Speaker 11: payroll to really earn that credibility and be who these

504
00:24:50,680 --> 00:24:52,960
Speaker 11: partners want to choose when they're building out their own

505
00:24:53,000 --> 00:24:53,680
Speaker 11: payroll products.

506
00:24:53,720 --> 00:24:55,480
Speaker 1: Interestingly, I don't think a dentist office is going to

507
00:24:55,480 --> 00:24:57,359
Speaker 1: be hiring many people abroad, but you've been trying to

508
00:24:57,359 --> 00:25:00,080
Speaker 1: focus on this making it easier to hire internationally. So

509
00:25:00,119 --> 00:25:02,280
Speaker 1: we're getting the news today that H one b's, for example,

510
00:25:02,320 --> 00:25:04,520
Speaker 1: are going to be overhauled and streamlined made easier by

511
00:25:04,560 --> 00:25:08,320
Speaker 1: the current administration. How are people's propensity to hiring abroad

512
00:25:08,359 --> 00:25:09,199
Speaker 1: at this moment, so.

513
00:25:09,200 --> 00:25:11,600
Speaker 11: It really depends on industry. With Gusto, you do have

514
00:25:11,600 --> 00:25:15,320
Speaker 11: the ability to hire both contractors and employees internationally. I'd

515
00:25:15,320 --> 00:25:19,399
Speaker 11: say there's been more resonance on the contractors side, but again,

516
00:25:20,000 --> 00:25:22,800
Speaker 11: many many products that we're expanding into International is just one.

517
00:25:22,880 --> 00:25:25,440
Speaker 11: We offer a lot of functionality around time tracking for

518
00:25:25,640 --> 00:25:29,000
Speaker 11: one K, business insurance, all the different pain points. It's

519
00:25:29,000 --> 00:25:31,280
Speaker 11: really hard still to run and start a small business,

520
00:25:31,480 --> 00:25:32,880
Speaker 11: and our job is to make that easier.

521
00:25:33,280 --> 00:25:37,680
Speaker 1: It's hard to run a startup, even as successful as yours.

522
00:25:37,720 --> 00:25:40,399
Speaker 1: You haven't raised money since twenty twenty one, ultimately because

523
00:25:40,600 --> 00:25:44,159
Speaker 1: looking at your profitability you don't need to. But what

524
00:25:44,320 --> 00:25:46,840
Speaker 1: is the pressure on you to IPO to have an exit?

525
00:25:47,000 --> 00:25:49,840
Speaker 1: Is it? Are you finding that the competitive mode when

526
00:25:49,880 --> 00:25:52,320
Speaker 1: your versus a deal or a rippling is getting harder

527
00:25:52,480 --> 00:25:53,520
Speaker 1: or is it fine?

528
00:25:53,600 --> 00:25:55,640
Speaker 11: We welcome the competition. We want to be the best

529
00:25:55,640 --> 00:25:58,400
Speaker 11: product in the market. We believe we are. We're also

530
00:25:58,520 --> 00:26:01,440
Speaker 11: just only one deck into this journey. We talk about

531
00:26:01,480 --> 00:26:04,160
Speaker 11: it being a multi decade journey, so at some point

532
00:26:04,160 --> 00:26:06,200
Speaker 11: in the future we will be public. Nothing to share

533
00:26:06,240 --> 00:26:08,879
Speaker 11: there but really our obsession is on how do we

534
00:26:08,920 --> 00:26:12,639
Speaker 11: give the best possible experience to those customers and do

535
00:26:12,720 --> 00:26:14,439
Speaker 11: that through our actions, through the work we put in,

536
00:26:14,480 --> 00:26:16,800
Speaker 11: and also through the partnerships we signed with folks like Zero.

537
00:26:17,280 --> 00:26:20,320
Speaker 1: And the talent you have when you're lying in bed

538
00:26:20,320 --> 00:26:22,240
Speaker 1: and you've got something on your mind, does it tend

539
00:26:22,280 --> 00:26:24,920
Speaker 1: to be talent acquisition? Is it about general to AI?

540
00:26:24,960 --> 00:26:26,040
Speaker 1: What are you thinking most about?

541
00:26:26,720 --> 00:26:29,880
Speaker 11: Mostly thinking about team building and as we, like you said,

542
00:26:30,000 --> 00:26:33,000
Speaker 11: have free cash flow, positive, a solid business model, real

543
00:26:33,040 --> 00:26:36,200
Speaker 11: customer need that we're really delivering true value for We're

544
00:26:36,240 --> 00:26:39,400
Speaker 11: being very aggressive reinvesting that capital, that free cash flow

545
00:26:39,480 --> 00:26:44,560
Speaker 11: into building new products, building additional services for our customers

546
00:26:44,600 --> 00:26:47,200
Speaker 11: to use, and so that usually means hiring. Team building

547
00:26:47,359 --> 00:26:50,320
Speaker 11: and I'm doing a lot of time these days interviewing candidates.

548
00:26:50,600 --> 00:26:52,920
Speaker 1: As is the life of a CEO. Josh, it's great

549
00:26:52,920 --> 00:26:54,679
Speaker 1: to have you. Thanks for something by as you're in

550
00:26:54,680 --> 00:26:58,359
Speaker 1: New York is of course the CEO of Gusto joshes them. Meanwhile,

551
00:26:58,400 --> 00:27:01,360
Speaker 1: coming up these spotlight upon us, we'll talk consumer investing.

552
00:27:01,600 --> 00:27:04,960
Speaker 1: In twenty twenty five, Shamin Walch is with US managing

553
00:27:05,000 --> 00:27:09,520
Speaker 1: director at BAM Ventures Plus a conversation with Minnesota Senator

554
00:27:09,600 --> 00:27:12,600
Speaker 1: Amy clovershah all about antitrust. You don't want to miss it.

555
00:27:12,600 --> 00:27:33,600
Speaker 1: This is Blue Beg technology. We want to just take

556
00:27:33,600 --> 00:27:36,440
Speaker 1: a look at consumer investing trends right now after retail

557
00:27:36,480 --> 00:27:39,000
Speaker 1: sales looks so good today? Were they looking like into

558
00:27:39,040 --> 00:27:41,719
Speaker 1: twenty twenty five. BAM Ventures is going to join us

559
00:27:41,720 --> 00:27:43,960
Speaker 1: in VC Spotlight. The firm's portfolio boasts some of the

560
00:27:44,000 --> 00:27:47,399
Speaker 1: biggest names in consumer investing like Zolar nerd Walt, Wanderley,

561
00:27:47,840 --> 00:27:51,480
Speaker 1: Band Ventures managing director Shaman Walt joins us for now

562
00:27:51,600 --> 00:27:55,679
Speaker 1: for more. And it's interesting that maybe consumer bets we

563
00:27:55,720 --> 00:27:58,439
Speaker 1: all know them because we use them, but perhaps they

564
00:27:58,440 --> 00:28:01,520
Speaker 1: haven't got the valuations of semi conducted a software space

565
00:28:01,560 --> 00:28:04,199
Speaker 1: of late. But what does consumer resiliency look like?

566
00:28:05,320 --> 00:28:08,560
Speaker 4: Well, first off, Caroline, good morning, and I wanted to

567
00:28:08,640 --> 00:28:12,199
Speaker 4: thank you for having me here and for those who

568
00:28:12,280 --> 00:28:14,520
Speaker 4: may not be familiar with me. As Caroline said, I'm

569
00:28:14,520 --> 00:28:17,480
Speaker 4: a managing director at dand Ventures. We're a pre seed

570
00:28:17,520 --> 00:28:20,480
Speaker 4: and seed consumer focus fund based in Los Angeles and

571
00:28:20,520 --> 00:28:23,359
Speaker 4: built by the founders of billion dollar public companies like

572
00:28:23,480 --> 00:28:27,000
Speaker 4: Legal Zoom, an Honest Company. And then as you mentioned, yeah,

573
00:28:27,040 --> 00:28:30,640
Speaker 4: you know the privilege of investing early in household names

574
00:28:30,720 --> 00:28:35,000
Speaker 4: like sweet Grains, snaps, cope ly nerd Wallet, et cetera.

575
00:28:35,600 --> 00:28:39,680
Speaker 4: And to your question, you know, it's interesting because I

576
00:28:39,720 --> 00:28:45,320
Speaker 4: think valuations are what catch headlines, but we often underestimate

577
00:28:45,360 --> 00:28:49,840
Speaker 4: the inputs that it takes to get to those numbers

578
00:28:50,000 --> 00:28:53,640
Speaker 4: and also the equity breakdown. So, for example, you know,

579
00:28:53,680 --> 00:28:56,360
Speaker 4: a company that exits for five billion dollars is an

580
00:28:56,760 --> 00:28:59,160
Speaker 4: eye popping amount, but when you look at the cap

581
00:28:59,200 --> 00:29:02,000
Speaker 4: table and you see that a founder, you know, on

582
00:29:02,120 --> 00:29:04,640
Speaker 4: two percent of that business, they actually made less than

583
00:29:05,640 --> 00:29:07,840
Speaker 4: a company where the founder owned twenty five percent of

584
00:29:07,840 --> 00:29:11,440
Speaker 4: a five hundred million dollar exit. So the valuations are

585
00:29:11,480 --> 00:29:14,960
Speaker 4: often you know, a particular on the brand side may

586
00:29:15,000 --> 00:29:17,640
Speaker 4: not be there on the text, of course they do

587
00:29:17,720 --> 00:29:22,280
Speaker 4: have that potential, but you know, the equity outcomes for

588
00:29:22,400 --> 00:29:25,280
Speaker 4: the investors and the founder, as you'd be surprised to see,

589
00:29:25,320 --> 00:29:26,960
Speaker 4: are often much better.

590
00:29:27,360 --> 00:29:30,360
Speaker 1: Yeah, and so you're very much trying to align oneself

591
00:29:30,480 --> 00:29:32,920
Speaker 1: with the founder and with their own legal background. I'm

592
00:29:32,920 --> 00:29:35,600
Speaker 1: sure you're ensuring that they maintain a lot of holding

593
00:29:35,960 --> 00:29:38,520
Speaker 1: and serve themselves well by having ownership of the business

594
00:29:38,520 --> 00:29:41,840
Speaker 1: as it matures and takes funding. What then about finding

595
00:29:41,880 --> 00:29:44,160
Speaker 1: these diamonds in the rough. How are you deciding, Okay,

596
00:29:44,200 --> 00:29:47,000
Speaker 1: this is a startup, a consumer facing startup that is

597
00:29:47,000 --> 00:29:48,640
Speaker 1: it a pivot point is about to go up into

598
00:29:48,680 --> 00:29:49,200
Speaker 1: the right.

599
00:29:50,640 --> 00:29:53,280
Speaker 4: We have this internal mantra that we like to we

600
00:29:53,800 --> 00:29:55,640
Speaker 4: say that we have to love the founder and not

601
00:29:55,720 --> 00:29:58,440
Speaker 4: hate the idea at the stage that we invest it

602
00:29:58,480 --> 00:30:01,840
Speaker 4: truly is about the founders, and you know we we

603
00:30:01,840 --> 00:30:04,920
Speaker 4: we love what we call the silent assassins, the folks

604
00:30:04,960 --> 00:30:09,520
Speaker 4: that are focused on building their business, who know their customer,

605
00:30:09,680 --> 00:30:12,720
Speaker 4: who know how people actually operate. You know, there are

606
00:30:12,760 --> 00:30:15,920
Speaker 4: a lot of things that we theoretically would like to

607
00:30:15,960 --> 00:30:18,160
Speaker 4: exist or like to do. You know, I'd love to

608
00:30:18,160 --> 00:30:20,440
Speaker 4: be the fittest woman in the world, but you know,

609
00:30:20,480 --> 00:30:23,360
Speaker 4: maybe I won't put the effort and time into an

610
00:30:23,400 --> 00:30:27,000
Speaker 4: exercise regime or counting my macro nutrients. And the founders

611
00:30:27,000 --> 00:30:30,720
Speaker 4: that actually understand how people, you know, live and behave

612
00:30:31,040 --> 00:30:34,040
Speaker 4: and what gets them to a purchase decision is really

613
00:30:34,040 --> 00:30:35,040
Speaker 4: what we're looking for.

614
00:30:35,320 --> 00:30:37,440
Speaker 1: And do they do that via EQ? Are they doing

615
00:30:37,520 --> 00:30:39,560
Speaker 1: that through data? What do you want to see when

616
00:30:39,720 --> 00:30:43,640
Speaker 1: one founder that you don't hate the idea of comes

617
00:30:43,680 --> 00:30:44,240
Speaker 1: and pitches you.

618
00:30:45,120 --> 00:30:48,640
Speaker 6: Yeah, I think, I think it's both, and I think.

619
00:30:48,720 --> 00:30:53,440
Speaker 4: More importantly it's around understanding not only their consumer but

620
00:30:53,560 --> 00:30:56,800
Speaker 4: themselves as well what their strengths and weaknesses are.

621
00:30:56,840 --> 00:30:57,760
Speaker 6: So, if there are.

622
00:30:58,080 --> 00:31:01,040
Speaker 4: Incredibly data driven, maybe they have hire a team that

623
00:31:01,160 --> 00:31:04,320
Speaker 4: is very EQ and brand driven, or vice versa. If

624
00:31:04,320 --> 00:31:07,080
Speaker 4: they're incredibly brand driven, then they hire a team who

625
00:31:07,160 --> 00:31:11,040
Speaker 4: understands operational efficiencies and knows that, you know, they need

626
00:31:11,080 --> 00:31:13,760
Speaker 4: to hit their margins. And so I think the most

627
00:31:13,760 --> 00:31:16,080
Speaker 4: important thing we look for is a founder who understands

628
00:31:16,120 --> 00:31:18,920
Speaker 4: their customers, as I mentioned, but also who knows how

629
00:31:18,960 --> 00:31:20,120
Speaker 4: to hire around them.

630
00:31:20,600 --> 00:31:24,000
Speaker 1: Look, you've been at Angel Investing for more than seventeen years,

631
00:31:24,120 --> 00:31:26,840
Speaker 1: You've been in your seat at bound benures for a

632
00:31:26,920 --> 00:31:29,920
Speaker 1: number of years, and what are valuations like at this

633
00:31:30,000 --> 00:31:32,560
Speaker 1: particular moment. How are you looking into twenty twenty five

634
00:31:32,600 --> 00:31:35,600
Speaker 1: and thinking about whether these are the right sort of

635
00:31:35,680 --> 00:31:37,400
Speaker 1: checks to be writing at the right valuation.

636
00:31:38,320 --> 00:31:40,800
Speaker 6: Yeah, I think that we.

637
00:31:42,400 --> 00:31:42,680
Speaker 9: Are.

638
00:31:42,720 --> 00:31:48,200
Speaker 4: In Valuations are very specific to the sectors right now.

639
00:31:48,360 --> 00:31:52,160
Speaker 4: You know, you hear about the buzzwords of AI or crypto,

640
00:31:52,320 --> 00:31:56,480
Speaker 4: and they can command a hefty evaluation. They also are

641
00:31:56,600 --> 00:32:01,160
Speaker 4: very capital intensive, I think, to the point I was

642
00:32:01,200 --> 00:32:03,640
Speaker 4: making it at the beginning around the inputs and the output.

643
00:32:04,440 --> 00:32:07,560
Speaker 4: A lot of times funds will back into valuations based

644
00:32:07,600 --> 00:32:09,760
Speaker 4: on how much they need to deploy, and it may

645
00:32:09,800 --> 00:32:12,800
Speaker 4: be detached from how much a company itself.

646
00:32:12,520 --> 00:32:13,280
Speaker 6: Is actually worth.

647
00:32:13,600 --> 00:32:16,120
Speaker 4: If you're a large fund and you need to write

648
00:32:16,160 --> 00:32:18,520
Speaker 4: ten million dollar checks and you love a particular category

649
00:32:18,520 --> 00:32:20,800
Speaker 4: and you give them ten ten million dollars, then you

650
00:32:20,840 --> 00:32:24,080
Speaker 4: need to back into evaluation from there, as opposed to

651
00:32:24,440 --> 00:32:26,960
Speaker 4: investing in a company they may not need as much.

652
00:32:27,280 --> 00:32:30,440
Speaker 1: It's interesting that you said crypto is sort of the buzzword,

653
00:32:30,560 --> 00:32:33,800
Speaker 1: and sure, bitcoins have been the buzzword, micro strategy been

654
00:32:33,800 --> 00:32:35,760
Speaker 1: in the buzzword. But all are we seeing more and

655
00:32:35,800 --> 00:32:39,560
Speaker 1: more founders coming to you with a Web three adjacent

656
00:32:39,640 --> 00:32:42,080
Speaker 1: company now or consume a focus that is building in

657
00:32:42,120 --> 00:32:44,040
Speaker 1: Web three once again? Are we at that stage of

658
00:32:44,040 --> 00:32:46,120
Speaker 1: the cycle we are?

659
00:32:46,520 --> 00:32:48,760
Speaker 4: We see a lot of founders who have a Web

660
00:32:48,840 --> 00:32:52,480
Speaker 4: three component. I do see it having come back into vogue,

661
00:32:53,400 --> 00:32:58,400
Speaker 4: and like I mentioned, AI is the mode.

662
00:32:58,320 --> 00:33:02,000
Speaker 1: Jour And to that point, when you're consumer founder, is

663
00:33:02,040 --> 00:33:05,160
Speaker 1: it just that you want to see AI boosting productivity

664
00:33:05,200 --> 00:33:08,200
Speaker 1: internally rather than trying to back themselves into a generative

665
00:33:08,240 --> 00:33:08,920
Speaker 1: AI business.

666
00:33:10,160 --> 00:33:12,760
Speaker 4: Do you mean what we look for as investors or

667
00:33:12,760 --> 00:33:14,280
Speaker 4: what founders are pursuing these days.

668
00:33:14,360 --> 00:33:16,239
Speaker 1: Yeah, what a founder's pursue. What are you seeing and

669
00:33:16,280 --> 00:33:20,280
Speaker 1: what are you wanting? Briefly, Yeah, well what we're wanting.

670
00:33:20,880 --> 00:33:24,280
Speaker 4: The way that we think about AI is the way

671
00:33:24,280 --> 00:33:26,360
Speaker 4: we think about the Internet. You know, It's like if

672
00:33:26,360 --> 00:33:28,280
Speaker 4: a founder came to us and told us they're building

673
00:33:28,280 --> 00:33:31,480
Speaker 4: an Internet company. I think it's ubiquitous, it's necessary, it

674
00:33:31,560 --> 00:33:35,239
Speaker 4: is the future for us. We're really looking at, you know,

675
00:33:35,280 --> 00:33:37,760
Speaker 4: the other elements that will make you a successful business,

676
00:33:37,760 --> 00:33:41,400
Speaker 4: what your distribution, your team, sales and marketing, the AI itself.

677
00:33:41,480 --> 00:33:45,000
Speaker 4: For us particularly and at our fund size is not

678
00:33:45,360 --> 00:33:48,840
Speaker 4: the sole determinant of whether a company is attractive or not,

679
00:33:49,200 --> 00:33:51,840
Speaker 4: and I think founders are catching on to that as well.

680
00:33:51,920 --> 00:33:54,320
Speaker 4: I think there was a period of time we're just

681
00:33:54,360 --> 00:34:03,480
Speaker 4: adding a dot aih was they thought was changing things

682
00:34:03,520 --> 00:34:06,600
Speaker 4: in terms of activeness. But I think at this point

683
00:34:06,760 --> 00:34:11,319
Speaker 4: founders are starting to realize we need to show some

684
00:34:11,600 --> 00:34:12,960
Speaker 4: differentiation beyond that.

685
00:34:13,560 --> 00:34:16,320
Speaker 1: Well, said Schaman Welch, an Asian director at ban Benches.

686
00:34:16,560 --> 00:34:19,160
Speaker 1: Thank you so much for your time today. Now let's

687
00:34:19,200 --> 00:34:21,759
Speaker 1: just talk about Senate Judiciary Subcommittee set to here on

688
00:34:21,800 --> 00:34:24,200
Speaker 1: anti trust and legal experts. Let's get to Kaylee Lines

689
00:34:24,239 --> 00:34:24,760
Speaker 1: in Washington.

690
00:34:26,040 --> 00:34:29,719
Speaker 12: I'd like to welcome our global Bloomberg television and radio audiences.

691
00:34:29,760 --> 00:34:34,080
Speaker 12: I'm joined in conversation by Democratic Senator Amy Klobuchar of Minnesota,

692
00:34:34,120 --> 00:34:37,319
Speaker 12: live from Capitol Hill. Senator, thank you very much for

693
00:34:37,360 --> 00:34:40,280
Speaker 12: being here. You are leading a subcommittee hearing today titled

694
00:34:40,280 --> 00:34:45,680
Speaker 12: Continuing a Bipartisan Path Forward for Antitrust Enforcement and Reform.

695
00:34:45,719 --> 00:34:48,279
Speaker 12: And I do wonder, in what will become January a

696
00:34:48,360 --> 00:34:52,120
Speaker 12: Republican controlled Congress and bill members and White House, what

697
00:34:52,320 --> 00:34:54,480
Speaker 12: that bipartisan path actually looks like.

698
00:34:55,480 --> 00:34:57,840
Speaker 10: Okay, well, first of all, thanks for having me on, Kaylee.

699
00:34:57,880 --> 00:34:58,759
Speaker 1: It's great to be on.

700
00:34:59,000 --> 00:35:02,440
Speaker 10: And I think what you've seen in this area of antitrust,

701
00:35:03,360 --> 00:35:07,279
Speaker 10: you've seen some broad bipartisan agreement on a number of

702
00:35:07,320 --> 00:35:08,120
Speaker 10: these cases.

703
00:35:08,200 --> 00:35:08,399
Speaker 1: Right.

704
00:35:08,560 --> 00:35:13,399
Speaker 10: For instance, the Google case started under the Trump administration,

705
00:35:13,640 --> 00:35:16,880
Speaker 10: the first Trump administration, as did the Facebook case that

706
00:35:17,000 --> 00:35:19,800
Speaker 10: was at the FTC. Google was at the Justice Department.

707
00:35:20,400 --> 00:35:25,200
Speaker 10: Then it proceeded through the Biden administration. Biden administration also

708
00:35:25,840 --> 00:35:31,080
Speaker 10: brought some major cases, for instance against Ticketmaster and other companies,

709
00:35:31,160 --> 00:35:34,800
Speaker 10: and so you've seen a more aggressive anti trust enforcement

710
00:35:34,880 --> 00:35:38,000
Speaker 10: over the last few years. Now you have a new

711
00:35:38,120 --> 00:35:41,960
Speaker 10: appointees going in place, and at least one of them

712
00:35:42,520 --> 00:35:46,440
Speaker 10: I have heard the belief is over at the Justice

713
00:35:46,480 --> 00:35:50,680
Speaker 10: Department with some former Democratic anti trust enforcers that she

714
00:35:50,800 --> 00:35:53,480
Speaker 10: knows what she's doing. I'm looking forward to meeting with her,

715
00:35:53,640 --> 00:35:58,400
Speaker 10: Gail Slater, and I'm hoping that we will continue those cases.

716
00:35:58,960 --> 00:36:02,160
Speaker 10: I love competition, Okay, I like capitalism. That's why I'm

717
00:36:02,160 --> 00:36:03,600
Speaker 10: for anti trust enforcement.

718
00:36:04,760 --> 00:36:07,960
Speaker 12: Well, you've mentioned Gail Slater. What about Andrew Ferguson. Do

719
00:36:08,000 --> 00:36:10,799
Speaker 12: you think he loves the issue of competition in the

720
00:36:10,840 --> 00:36:12,799
Speaker 12: same way that you do. Do you trust that the

721
00:36:12,880 --> 00:36:15,120
Speaker 12: FTC will be in good hands under his leadership?

722
00:36:15,600 --> 00:36:17,719
Speaker 10: You know, I am looking forward to meeting with him.

723
00:36:17,719 --> 00:36:20,759
Speaker 10: Interestingly enough, we do not confirm that position because he

724
00:36:20,840 --> 00:36:25,040
Speaker 10: was already on the commission. There is a new member

725
00:36:25,120 --> 00:36:28,040
Speaker 10: that is being appointed on the Republican side. I'll note

726
00:36:28,080 --> 00:36:31,120
Speaker 10: that he also he wrote a piece on the breakup

727
00:36:31,160 --> 00:36:34,160
Speaker 10: of Ticketmaster in which he favored that. So I just

728
00:36:34,200 --> 00:36:37,719
Speaker 10: think with anti trust because at its core, it is

729
00:36:37,760 --> 00:36:42,600
Speaker 10: about competition, and it's been laggered for many decades, and

730
00:36:42,640 --> 00:36:45,440
Speaker 10: as a result, we're seeing more and more consolidation. It

731
00:36:45,480 --> 00:36:47,920
Speaker 10: isn't that big companies are bad. It's that sometimes when

732
00:36:47,920 --> 00:36:51,280
Speaker 10: you have no competition, then you start getting less innovation,

733
00:36:51,600 --> 00:36:55,360
Speaker 10: more high prices, et cetera, et cetera. So I'm actually

734
00:36:55,360 --> 00:36:57,560
Speaker 10: really excited about this center. Lee and I are doing

735
00:36:57,560 --> 00:37:00,760
Speaker 10: this together, this hearing center. Grassing and I have passed

736
00:37:00,760 --> 00:37:03,120
Speaker 10: our bill together, and I think you're going to continue

737
00:37:03,120 --> 00:37:06,120
Speaker 10: to see interest in tech. Fact Center, Cruise and I

738
00:37:06,160 --> 00:37:10,680
Speaker 10: did a joint interview this morning and bill that we

739
00:37:10,840 --> 00:37:13,719
Speaker 10: have gotten through the Senate on taking online porn off

740
00:37:13,800 --> 00:37:17,120
Speaker 10: the Internet different than anti trust. However, You're just going

741
00:37:17,200 --> 00:37:19,720
Speaker 10: to continue to see bipartisan work on tech.

742
00:37:21,000 --> 00:37:22,960
Speaker 12: Well, I'm glad that you have brought up the Take

743
00:37:23,000 --> 00:37:25,480
Speaker 12: It Down Act, which you co sponsored with Senator Cruz.

744
00:37:26,000 --> 00:37:29,600
Speaker 12: Is that trying to tackle symptoms of an underlying disease

745
00:37:29,719 --> 00:37:32,480
Speaker 12: rather than the disease itself. And the disease I'm referring

746
00:37:32,480 --> 00:37:34,839
Speaker 12: to here is unregulated artificial intelligence.

747
00:37:36,080 --> 00:37:39,120
Speaker 10: Thanks, I really would like to put in some rules

748
00:37:39,120 --> 00:37:42,600
Speaker 10: of the road on AI. And this bill is actually

749
00:37:42,600 --> 00:37:47,200
Speaker 10: broader than just AI pornographic is pictures. It's actually also

750
00:37:47,320 --> 00:37:51,359
Speaker 10: real pictures as well as AI created ones. We're now

751
00:37:51,400 --> 00:37:54,399
Speaker 10: seeing one in twelve Americans saying that they have been

752
00:37:54,440 --> 00:37:56,600
Speaker 10: a victim or no, someone that's a victim of this.

753
00:37:56,920 --> 00:37:59,960
Speaker 10: We've had twenty suicides in one year of young kids.

754
00:38:00,239 --> 00:38:04,640
Speaker 10: Twenty suicides because someone a girlfriend, boyfriend, someone they knew

755
00:38:04,800 --> 00:38:07,200
Speaker 10: put up their photo. They were embarrassed that their friends

756
00:38:07,200 --> 00:38:09,799
Speaker 10: and their family would know, and they killed themselves. These

757
00:38:09,880 --> 00:38:13,600
Speaker 10: are FBI statistics. So Senator Cruse and I came together

758
00:38:13,680 --> 00:38:15,839
Speaker 10: to build us two things. One make it clearly a

759
00:38:15,840 --> 00:38:20,399
Speaker 10: crime to use pornographic imagery of someone else, whether it's

760
00:38:20,440 --> 00:38:23,680
Speaker 10: AI created or real. And then number two, that the

761
00:38:23,719 --> 00:38:26,040
Speaker 10: platforms have to take it down. That's why it's called

762
00:38:26,040 --> 00:38:29,200
Speaker 10: the Take It Down Act. They take down other violations

763
00:38:29,239 --> 00:38:32,120
Speaker 10: of intellectual property and the fact that people can be

764
00:38:32,160 --> 00:38:35,440
Speaker 10: abused in this way to the point of committing suicide.

765
00:38:35,600 --> 00:38:40,479
Speaker 10: And in one case that I know of, Senator Cruz's case,

766
00:38:40,480 --> 00:38:43,040
Speaker 10: he actually had a call Snapchat to get the image

767
00:38:43,080 --> 00:38:46,560
Speaker 10: down after months of this victim from his state dealing

768
00:38:46,560 --> 00:38:46,920
Speaker 10: with it.

769
00:38:47,080 --> 00:38:47,880
Speaker 1: That's just wrong.

770
00:38:49,719 --> 00:38:51,600
Speaker 12: Senator, I'd like to ask you about another one of

771
00:38:51,640 --> 00:38:55,040
Speaker 12: your colleagues, your fellow Democrats, Senator Elizabeth Warren of Massachusetts,

772
00:38:55,080 --> 00:38:58,000
Speaker 12: wrote a letter we understand, to President elect Donald Trump

773
00:38:58,080 --> 00:39:01,200
Speaker 12: asking for firm conflict of interest rules to be put

774
00:39:01,280 --> 00:39:04,319
Speaker 12: into place. Related to Elon Musk, who, of course has

775
00:39:04,320 --> 00:39:07,120
Speaker 12: been tapped to co lead this new Department of Government Efficiency,

776
00:39:07,160 --> 00:39:09,560
Speaker 12: have you had any conversations with Senator Warren about that,

777
00:39:09,640 --> 00:39:12,160
Speaker 12: or at the very least you share in that sentiment.

778
00:39:13,239 --> 00:39:15,880
Speaker 10: Now, I haven't seen this letter, but I will say

779
00:39:15,960 --> 00:39:19,879
Speaker 10: that I believe that we need conflict of interest rules

780
00:39:19,880 --> 00:39:23,560
Speaker 10: in place for people who are making major decisions in

781
00:39:23,600 --> 00:39:28,040
Speaker 10: the government. That is what our people have done voluntarily

782
00:39:28,920 --> 00:39:31,439
Speaker 10: for years now. And you have a number of very

783
00:39:31,520 --> 00:39:34,880
Speaker 10: wealthy people going into the Trump administration. There's been wealthy

784
00:39:35,560 --> 00:39:38,480
Speaker 10: people as well under Democratic administration, but you have a

785
00:39:38,600 --> 00:39:42,520
Speaker 10: number of them coming in and we need the conflict

786
00:39:42,600 --> 00:39:45,040
Speaker 10: rules in force, and we need to know that the

787
00:39:45,080 --> 00:39:47,600
Speaker 10: decisions they are making are not for their own interest

788
00:39:47,680 --> 00:39:49,840
Speaker 10: but for the interests of the American people. And I

789
00:39:49,840 --> 00:39:52,440
Speaker 10: would hope that President elect Trump agrees.

790
00:39:54,320 --> 00:39:57,680
Speaker 12: Finally. President Elect Trump yesterday met with the CEO of

791
00:39:57,719 --> 00:40:00,200
Speaker 12: TikTok Show Too at mar A Lago, after saying in

792
00:40:00,239 --> 00:40:03,040
Speaker 12: a news conference Senator that he is a warm spot

793
00:40:03,040 --> 00:40:04,839
Speaker 12: in his heart for TikTok. When asked if you would

794
00:40:04,880 --> 00:40:07,000
Speaker 12: like to see the band go through or will try

795
00:40:07,040 --> 00:40:08,759
Speaker 12: to stop it. Given some of the issues we have

796
00:40:08,760 --> 00:40:12,160
Speaker 12: already discussed around technology in particular and what is propagated

797
00:40:12,520 --> 00:40:14,799
Speaker 12: on these platforms, what is your view about whether that

798
00:40:14,880 --> 00:40:17,239
Speaker 12: band should be enforced come January.

799
00:40:18,000 --> 00:40:21,719
Speaker 10: Of course, this came out of Congress with strong bipartisan support,

800
00:40:21,960 --> 00:40:25,399
Speaker 10: and there are two avenues here. One is that they

801
00:40:25,400 --> 00:40:28,800
Speaker 10: can follow the law and divest and find a buyer

802
00:40:28,920 --> 00:40:31,719
Speaker 10: for the company, and the second is that they still

803
00:40:31,719 --> 00:40:35,120
Speaker 10: are appealing to the Supreme Court. So my view has

804
00:40:35,160 --> 00:40:38,280
Speaker 10: been that we should have rules of the road in place,

805
00:40:38,400 --> 00:40:41,160
Speaker 10: by the way, for all platforms. I have been way

806
00:40:41,200 --> 00:40:43,640
Speaker 10: out there, as I think you know, in terms of

807
00:40:43,719 --> 00:40:50,000
Speaker 10: getting not just pornography off the Internet, but other very

808
00:40:50,160 --> 00:40:52,799
Speaker 10: very difficult things that are on there right now, and

809
00:40:52,840 --> 00:40:54,680
Speaker 10: that we should have a better policing of that, and

810
00:40:54,719 --> 00:40:57,920
Speaker 10: people should have the right to protect their own intellectual properties,

811
00:40:58,239 --> 00:41:01,920
Speaker 10: and also that we should have antitrust enforcement. You just

812
00:41:02,000 --> 00:41:04,959
Speaker 10: can't have, say, Google, with a ninety percent market share

813
00:41:05,000 --> 00:41:07,920
Speaker 10: on the search engine and not have any competition and

814
00:41:07,960 --> 00:41:11,279
Speaker 10: then allow them to self preference, as we see with

815
00:41:11,320 --> 00:41:13,800
Speaker 10: Amazon and other companies their own.

816
00:41:13,640 --> 00:41:14,680
Speaker 1: Products at the top.

817
00:41:15,080 --> 00:41:18,120
Speaker 10: That's why the NFIB, which is not a liberal organization,

818
00:41:18,400 --> 00:41:22,759
Speaker 10: the National Federation of Independent Businesses, is strongly supporting the

819
00:41:22,760 --> 00:41:25,719
Speaker 10: bill that I have with Senator Grassley, which simply puts

820
00:41:25,719 --> 00:41:27,839
Speaker 10: some rules in the road in place for a competition

821
00:41:27,920 --> 00:41:28,640
Speaker 10: on the internet.

822
00:41:30,080 --> 00:41:33,319
Speaker 12: All right, Democratic Senator Amy Klobaschar of Minnesota joining us

823
00:41:33,320 --> 00:41:36,080
Speaker 12: live from Capitol Hill on Bloomberg Television and Radio. Thank

824
00:41:36,120 --> 00:41:37,799
Speaker 12: you so much, and I'll send it back to you

825
00:41:37,920 --> 00:41:38,479
Speaker 12: in New York.

826
00:41:39,000 --> 00:41:43,200
Speaker 1: Kaylie Lyns, we thank you, Senator Amy Clobshaw on Minnesota

827
00:41:43,280 --> 00:41:46,719
Speaker 1: as well. Let's just break all of this down politics

828
00:41:46,719 --> 00:41:48,920
Speaker 1: intersecting with technology. We do that with Blue Meggs, Mike

829
00:41:48,920 --> 00:41:52,240
Speaker 1: Shephard and just going to the bipath is in nature

830
00:41:52,239 --> 00:41:55,440
Speaker 1: of anti trust focus, it does feel as though many

831
00:41:55,480 --> 00:41:59,040
Speaker 1: interpret Trump administration well business friendly, but he's put some

832
00:41:59,040 --> 00:42:02,840
Speaker 1: people in seats that have really critical eyes on companies

833
00:42:02,840 --> 00:42:03,480
Speaker 1: such as Google.

834
00:42:04,400 --> 00:42:07,480
Speaker 9: That's certainly been our sense as we've reported out Trump's

835
00:42:07,480 --> 00:42:10,520
Speaker 9: selections for these key positions, including the head of the

836
00:42:10,520 --> 00:42:14,200
Speaker 9: Anti trust division at the Justice Department and the person

837
00:42:14,200 --> 00:42:17,440
Speaker 9: who would succeed Lena Kahn at the Federal Trade Commission.

838
00:42:17,680 --> 00:42:20,279
Speaker 9: And now we've heard it from Amy Klobuchra herself, the

839
00:42:20,320 --> 00:42:24,840
Speaker 9: Senator from Minnesota, who has really spearheaded efforts in Congress

840
00:42:24,920 --> 00:42:28,600
Speaker 9: in the Senate on this area of competition enforcement, and

841
00:42:28,640 --> 00:42:32,319
Speaker 9: she is signaling some optimism that the incoming Trump team

842
00:42:32,719 --> 00:42:35,360
Speaker 9: will not divert too much from the playbook when it

843
00:42:35,360 --> 00:42:38,839
Speaker 9: comes to cracking down on areas, especially big tech, where

844
00:42:38,840 --> 00:42:42,040
Speaker 9: we've seen a lot of concentration of market power. We

845
00:42:42,120 --> 00:42:44,399
Speaker 9: saw her reference Google at the very end of her

846
00:42:44,719 --> 00:42:47,839
Speaker 9: remarks to our colleague Kayley Liones, Yeah, and.

847
00:42:47,760 --> 00:42:50,720
Speaker 1: Saying that she's looking forward to meeting with Andrew Ferguson

848
00:42:50,760 --> 00:42:53,799
Speaker 1: as well. Mike, I want to shift more broadly into

849
00:42:53,840 --> 00:42:57,319
Speaker 1: the context of technology and the next administration, because there

850
00:42:57,400 --> 00:42:59,719
Speaker 1: is a merry go round at Mara Lago at the

851
00:42:59,719 --> 00:43:02,200
Speaker 1: moment of all the key names in tech, whether it

852
00:43:02,239 --> 00:43:05,480
Speaker 1: be Netflix, we know, Bezos's jew we have just had

853
00:43:05,520 --> 00:43:08,759
Speaker 1: show cho Is it really a key focus on technology

854
00:43:08,760 --> 00:43:09,280
Speaker 1: in the future.

855
00:43:10,120 --> 00:43:13,439
Speaker 9: Well, it really has been a parade of these high

856
00:43:13,480 --> 00:43:17,360
Speaker 9: profile CEOs going in to meet with President elect Donald

857
00:43:17,400 --> 00:43:20,200
Speaker 9: Trump to have their cases heard and to hear a

858
00:43:20,239 --> 00:43:23,520
Speaker 9: little bit from him themselves so that they understand a

859
00:43:23,560 --> 00:43:25,719
Speaker 9: little bit how to relate with him. Think of it

860
00:43:25,719 --> 00:43:29,200
Speaker 9: as corporate diplomacy, but a two way Street. Trump really

861
00:43:29,280 --> 00:43:32,840
Speaker 9: likes to exercise that sort of function of his office

862
00:43:32,840 --> 00:43:35,440
Speaker 9: to reach out to CEOs in the way that a

863
00:43:35,520 --> 00:43:38,120
Speaker 9: president would also reach out to heads of state. He

864
00:43:38,760 --> 00:43:41,399
Speaker 9: likes that kind of engagement. We saw it in action

865
00:43:41,600 --> 00:43:44,200
Speaker 9: so much during his first term in office, and now

866
00:43:44,239 --> 00:43:46,720
Speaker 9: we're already seeing signs of it now as he prepares

867
00:43:46,760 --> 00:43:49,920
Speaker 9: to return to the White House. And for these companies,

868
00:43:49,960 --> 00:43:52,600
Speaker 9: it's a chance for them to be heard, especially for

869
00:43:52,640 --> 00:43:56,120
Speaker 9: shout Chew. His company is facing this existential question of

870
00:43:56,160 --> 00:43:59,360
Speaker 9: a band that could take effect as soon as January nineteenth.

871
00:44:00,040 --> 00:44:04,080
Speaker 1: That is an existential question for TikTok other companies maybe

872
00:44:04,080 --> 00:44:06,200
Speaker 1: going in and saying, look, my key worry here is

873
00:44:06,280 --> 00:44:09,439
Speaker 1: talent and access to talent. One of the most read

874
00:44:09,480 --> 00:44:11,960
Speaker 1: stories on the Bloomberg today and across the web is

875
00:44:11,960 --> 00:44:14,480
Speaker 1: about h one B visas, how the current administration, how

876
00:44:14,480 --> 00:44:17,920
Speaker 1: the current US decision and am Immigration Services are basically

877
00:44:18,400 --> 00:44:23,120
Speaker 1: making final changes to making it easier, more streamlined. Is

878
00:44:23,120 --> 00:44:25,560
Speaker 1: that something that might be upended by the next administration.

879
00:44:25,640 --> 00:44:26,719
Speaker 1: What's hiring going to look like?

880
00:44:27,480 --> 00:44:29,880
Speaker 9: Well, there is a risk of that happening, of course,

881
00:44:29,920 --> 00:44:33,320
Speaker 9: And one of the concerns that companies, not just tech companies,

882
00:44:33,320 --> 00:44:36,560
Speaker 9: but tech companies in particular in reference to the H

883
00:44:36,640 --> 00:44:40,960
Speaker 9: one B program, they're only eighty five thousand visas available

884
00:44:41,080 --> 00:44:45,360
Speaker 9: every year. They're really coveted. The competition is really really

885
00:44:45,400 --> 00:44:48,880
Speaker 9: stiff for them. And tech companies need that workforce of

886
00:44:49,160 --> 00:44:51,880
Speaker 9: skilled workers with a dance degrees to be able to

887
00:44:52,960 --> 00:44:57,840
Speaker 9: propel their development of the latest technologies, and any change

888
00:44:57,880 --> 00:45:00,600
Speaker 9: to their program is a disturbance and force and at

889
00:45:00,719 --> 00:45:04,640
Speaker 9: risks impeding their progress. During the last Trump administration, they

890
00:45:04,640 --> 00:45:07,800
Speaker 9: had dropped a policy known as prior deference, which helped

891
00:45:07,800 --> 00:45:10,960
Speaker 9: grease the skids for some of these applications. And this

892
00:45:11,040 --> 00:45:15,440
Speaker 9: policy was just codified reinstated with rules that were finalized

893
00:45:15,480 --> 00:45:21,080
Speaker 9: today by the Customs and Immigration Service and the Department

894
00:45:21,080 --> 00:45:24,839
Speaker 9: of Homeland Security. What we want to see, what we're

895
00:45:24,840 --> 00:45:28,200
Speaker 9: looking for going ahead as a Trump team takes office,

896
00:45:28,320 --> 00:45:30,560
Speaker 9: is what will they do there as they try to

897
00:45:30,600 --> 00:45:32,680
Speaker 9: address the broader question of the border.

898
00:45:33,320 --> 00:45:36,520
Speaker 1: Mike Shepherd bringing it all together for us from Washington.

899
00:45:36,640 --> 00:45:39,759
Speaker 1: Thank you very much. Indeed, now that does it. From

900
00:45:39,760 --> 00:45:42,200
Speaker 1: this edition in Bloomberg Technology, You do not want to

901
00:45:42,239 --> 00:45:44,320
Speaker 1: forget to check out our podcast. Find it on the

902
00:45:44,400 --> 00:45:47,640
Speaker 1: terminal as well as online on Apple Spotify and iHeart

903
00:45:48,120 --> 00:45:49,280
Speaker 1: this is blue bag technology.