1
00:00:02,560 --> 00:00:10,800
Speaker 1: Bloomberg Audio Studios, Podcasts, radio news.

2
00:00:12,720 --> 00:00:14,840
Speaker 2: This is Everybody's business from Bloomberg BusinessWeek.

3
00:00:14,920 --> 00:00:18,160
Speaker 3: I'm Max Chafkin, and I'm Stacy Vannocksmith and Max.

4
00:00:18,239 --> 00:00:21,760
Speaker 4: Here we are twenty twenty six. It is happened.

5
00:00:22,200 --> 00:00:24,480
Speaker 2: Happy New Year, Stacy, Happy New Year.

6
00:00:24,680 --> 00:00:26,560
Speaker 4: Twenty twenty five's done. We're done with it.

7
00:00:26,760 --> 00:00:27,000
Speaker 2: Yeah.

8
00:00:27,120 --> 00:00:29,120
Speaker 5: Today on the show, we're going to look ahead to

9
00:00:29,200 --> 00:00:31,760
Speaker 5: that new year. The new issue of BusinessWeek is all

10
00:00:31,840 --> 00:00:32,199
Speaker 5: about that.

11
00:00:32,440 --> 00:00:34,360
Speaker 3: Yeah, and we'll be looking at some of the biggest

12
00:00:34,400 --> 00:00:36,920
Speaker 3: stories that are going to be unfolding in twenty twenty six,

13
00:00:37,000 --> 00:00:39,960
Speaker 3: some of the economic indicators we'll be watching, and Max,

14
00:00:40,000 --> 00:00:42,520
Speaker 3: you will be previewing some potential feuds.

15
00:00:42,640 --> 00:00:43,160
Speaker 2: Oh feuds.

16
00:00:43,159 --> 00:00:46,280
Speaker 5: I love feuds, and you have promised us headline mad

17
00:00:46,360 --> 00:00:46,720
Speaker 5: life I have.

18
00:00:46,920 --> 00:00:48,680
Speaker 2: I don't know what those words mean.

19
00:00:49,240 --> 00:00:51,600
Speaker 5: But we will finish things off with a lightning round

20
00:00:51,880 --> 00:00:54,880
Speaker 5: of that and some predictions from listeners and friends.

21
00:00:55,160 --> 00:00:58,240
Speaker 3: And we are very lucky to have Bradstone, editor of BusinessWeek,

22
00:00:58,280 --> 00:01:00,560
Speaker 3: here to join us and talk through what we can

23
00:01:00,640 --> 00:01:03,720
Speaker 3: expect in the year. Head Hey Brad, Hi, guys, Happy

24
00:01:03,760 --> 00:01:11,360
Speaker 3: New Year, Happy New Year. So okay, Brad, there's a

25
00:01:11,360 --> 00:01:13,400
Speaker 3: whole issue of Business Week that just came out all

26
00:01:13,440 --> 00:01:15,880
Speaker 3: about what we can expect in twenty twenty six. You

27
00:01:15,959 --> 00:01:19,840
Speaker 3: have been looking over the lands in this way, So

28
00:01:19,920 --> 00:01:21,920
Speaker 3: what are some of the big stories that you see

29
00:01:22,000 --> 00:01:23,399
Speaker 3: unfolding this year?

30
00:01:24,040 --> 00:01:24,320
Speaker 5: Right?

31
00:01:24,440 --> 00:01:27,000
Speaker 2: Well, I'm going to highlight two big ones.

32
00:01:27,640 --> 00:01:31,240
Speaker 6: The first we really put on the cover of the

33
00:01:31,720 --> 00:01:35,400
Speaker 6: January issue. There's a big bubble on the cover, so

34
00:01:35,600 --> 00:01:38,280
Speaker 6: it doesn't take too much imagination to know what that

35
00:01:38,319 --> 00:01:38,800
Speaker 6: refers to.

36
00:01:38,920 --> 00:01:41,399
Speaker 2: But really the story, what does it refer to? Bro

37
00:01:43,560 --> 00:01:44,319
Speaker 2: It refers to.

38
00:01:44,280 --> 00:01:48,600
Speaker 6: The explosion of investment optimism and bubbly exuberance around AI

39
00:01:49,240 --> 00:01:52,320
Speaker 6: twenty twenty five it was, you know, a gangbuster's year.

40
00:01:52,720 --> 00:01:57,000
Speaker 6: A UBS estimated that spending on infrastructure so data centers

41
00:01:57,000 --> 00:02:00,080
Speaker 6: and chips and the like, went from fifteen billion in

42
00:02:00,280 --> 00:02:03,520
Speaker 6: twenty four to one hundred and twenty five billion. Venture

43
00:02:03,560 --> 00:02:06,919
Speaker 6: capitalists were one note in the year all the money

44
00:02:06,960 --> 00:02:11,600
Speaker 6: funneled into AI in videos market cap nearly doubled to

45
00:02:12,080 --> 00:02:14,480
Speaker 6: four point three trillion, So you know, that's the big

46
00:02:14,520 --> 00:02:16,920
Speaker 6: story of the year. It's probably the big story of

47
00:02:17,000 --> 00:02:20,120
Speaker 6: the decade, starting when chat GBT was unveiled at the

48
00:02:20,200 --> 00:02:22,120
Speaker 6: end of twenty twenty two, and obviously one we're going

49
00:02:22,160 --> 00:02:23,040
Speaker 6: to continue to watch.

50
00:02:24,080 --> 00:02:26,800
Speaker 3: So if you look at this bubble with all of

51
00:02:26,800 --> 00:02:29,680
Speaker 3: your knowledge, like, are we headed for a bubble popping?

52
00:02:29,760 --> 00:02:31,040
Speaker 4: Because I think that's the big concern.

53
00:02:31,200 --> 00:02:33,960
Speaker 6: I mean, I you know, like you guys have been

54
00:02:34,000 --> 00:02:36,880
Speaker 6: doing this for a long time, maybe maybe a little longer.

55
00:02:36,960 --> 00:02:39,400
Speaker 6: I moved out to Silicon Valley in the late nineties

56
00:02:39,760 --> 00:02:44,080
Speaker 6: and I saw the you know, wild optimism around the

57
00:02:44,120 --> 00:02:47,919
Speaker 6: Internet in the late nineties. And there was a reckoning

58
00:02:48,000 --> 00:02:50,240
Speaker 6: in two thousand and two thousand and one, and then

59
00:02:50,280 --> 00:02:53,280
Speaker 6: it happened again. People call it the Unicorn bubble about

60
00:02:53,320 --> 00:02:56,239
Speaker 6: ten years later. And in both cases, yeah, I mean

61
00:02:56,320 --> 00:03:00,960
Speaker 6: there was carnage, but that underlying innovation you know, emerged

62
00:03:01,040 --> 00:03:04,080
Speaker 6: and a few companies were minted as kingmakers, and like

63
00:03:04,160 --> 00:03:06,280
Speaker 6: this is the pattern with new waves of technology, and

64
00:03:06,320 --> 00:03:07,840
Speaker 6: I think that we'll see the same thing here.

65
00:03:08,240 --> 00:03:11,840
Speaker 3: I think there's extra concern now because our economy is

66
00:03:11,880 --> 00:03:16,520
Speaker 3: not as diversified as we might want it to be.

67
00:03:16,639 --> 00:03:19,359
Speaker 4: Especially in growth wise. Like I feel like we're.

68
00:03:19,200 --> 00:03:22,960
Speaker 3: So dependent right now on AI growth continuing for our

69
00:03:23,000 --> 00:03:25,440
Speaker 3: whole economy to grow that it feels like we just

70
00:03:25,480 --> 00:03:27,720
Speaker 3: have so much at stake with this bubble.

71
00:03:27,880 --> 00:03:29,200
Speaker 4: This is not your average bubble.

72
00:03:29,720 --> 00:03:33,560
Speaker 2: Hot take, it's going to burst, It's gonna bse that's

73
00:03:33,600 --> 00:03:34,000
Speaker 2: my take.

74
00:03:34,120 --> 00:03:36,200
Speaker 4: Why well, just back this up with facts.

75
00:03:36,280 --> 00:03:38,840
Speaker 5: I actually think I'm very hesitant to say this because

76
00:03:38,840 --> 00:03:42,160
Speaker 5: we're recording this in mid December for an issue that

77
00:03:42,240 --> 00:03:44,600
Speaker 5: is going to hit in two weeks, and so if

78
00:03:44,600 --> 00:03:46,800
Speaker 5: I'm wrong, we can make fun of me and whatever.

79
00:03:46,880 --> 00:03:49,440
Speaker 2: And edit it out January eighth or something.

80
00:03:50,080 --> 00:03:52,920
Speaker 5: I think the bubble maybe already has burst, and you

81
00:03:52,920 --> 00:03:56,560
Speaker 5: know in way, well, I don't know, like Oracle over

82
00:03:56,600 --> 00:04:01,080
Speaker 5: the last couple of days last week, absolutely so. So

83
00:04:01,160 --> 00:04:04,520
Speaker 5: it went down like twelve percent one day and then

84
00:04:04,600 --> 00:04:05,720
Speaker 5: five percent another day.

85
00:04:06,040 --> 00:04:07,400
Speaker 2: Now there's this stuff going on.

86
00:04:07,400 --> 00:04:11,320
Speaker 5: Bloomberg BusinessWeek did a big story about Oracle that's also

87
00:04:11,320 --> 00:04:14,200
Speaker 5: in this issue, had some information about their data center

88
00:04:14,240 --> 00:04:17,159
Speaker 5: plans that could have contributed to the drop of Oracle

89
00:04:17,200 --> 00:04:19,920
Speaker 5: stock price. But I don't know, like we've already started

90
00:04:19,920 --> 00:04:22,800
Speaker 5: to see some of these AI stocks already start to

91
00:04:22,800 --> 00:04:25,800
Speaker 5: pull back. Now, obviously they may recover and it may

92
00:04:25,839 --> 00:04:28,760
Speaker 5: look like nothing's happened. Nothing much has happened, just a blip,

93
00:04:28,880 --> 00:04:30,919
Speaker 5: But I don't know, there's a chance that we've already

94
00:04:30,960 --> 00:04:32,400
Speaker 5: seen some of these asset.

95
00:04:32,160 --> 00:04:34,560
Speaker 6: Prices peaked, Brad, what do you think, Yeah, I mean,

96
00:04:34,600 --> 00:04:36,520
Speaker 6: I think that's certainly true. I think this is a

97
00:04:36,560 --> 00:04:40,560
Speaker 6: FOMO induced bubble. Investors are trying to find any way

98
00:04:40,600 --> 00:04:44,520
Speaker 6: they can into this movement. A lot of these companies

99
00:04:44,520 --> 00:04:47,560
Speaker 6: are private, and so you get bets on companies like Oracle,

100
00:04:48,160 --> 00:04:51,200
Speaker 6: you know, that are optimistically trying to get in on

101
00:04:51,240 --> 00:04:54,120
Speaker 6: the action. Max is right that stock price has fallen,

102
00:04:54,240 --> 00:04:56,520
Speaker 6: but you know, you look at Nvidia and that seems

103
00:04:56,520 --> 00:04:58,840
Speaker 6: to still be a pretty safe bet. I think, like

104
00:04:58,960 --> 00:05:00,560
Speaker 6: the question is where we going to see the same

105
00:05:00,680 --> 00:05:02,599
Speaker 6: kind of pullback that we saw in two thousand and

106
00:05:02,600 --> 00:05:05,480
Speaker 6: two thousand and one, where some companies go out of business,

107
00:05:05,680 --> 00:05:07,080
Speaker 6: a lot of investors get hurt.

108
00:05:07,320 --> 00:05:09,880
Speaker 2: That's what we're going to be paying close attention to

109
00:05:10,000 --> 00:05:10,400
Speaker 2: next year.

110
00:05:10,760 --> 00:05:11,400
Speaker 4: So what are you.

111
00:05:11,839 --> 00:05:14,600
Speaker 3: Both looking for? Like what will be the signs of

112
00:05:14,640 --> 00:05:17,760
Speaker 3: a bubble bursting? Is it stock price? Is it investment?

113
00:05:17,800 --> 00:05:20,239
Speaker 3: Is it other things? Like what should we look for

114
00:05:20,839 --> 00:05:23,200
Speaker 3: if we're looking for harbingers of.

115
00:05:24,800 --> 00:05:25,400
Speaker 4: Problems?

116
00:05:26,040 --> 00:05:31,120
Speaker 6: There's still so many questions around consumer adoption of these tools,

117
00:05:31,480 --> 00:05:33,600
Speaker 6: and right now I think it's still being fueled by

118
00:05:33,760 --> 00:05:36,800
Speaker 6: novelty and maybe a little group think, like we're all

119
00:05:36,839 --> 00:05:39,560
Speaker 6: being asked in different corners of our lives to embrace

120
00:05:39,600 --> 00:05:42,200
Speaker 6: these tools. If we ever start to see indication that

121
00:05:42,480 --> 00:05:44,960
Speaker 6: consumers are pulling back, that they're not finding it quite

122
00:05:45,000 --> 00:05:47,120
Speaker 6: as useful as maybe it was promised.

123
00:05:47,279 --> 00:05:50,040
Speaker 2: That And also just like business spending, that's been.

124
00:05:50,080 --> 00:05:51,279
Speaker 4: One of the big stop investing.

125
00:05:51,400 --> 00:05:53,479
Speaker 5: Yeah, I mean one of the big themes that we've

126
00:05:53,560 --> 00:05:55,200
Speaker 5: talked about over and over again on this show is

127
00:05:55,279 --> 00:05:58,919
Speaker 5: kind of a gap between spending and returns. But you

128
00:05:58,920 --> 00:06:01,960
Speaker 5: know that's true like from the at the highest level

129
00:06:02,080 --> 00:06:05,040
Speaker 5: of these you know, open aiyes is losing lots of money,

130
00:06:05,120 --> 00:06:07,040
Speaker 5: but also is true when it comes to a lot

131
00:06:07,040 --> 00:06:09,680
Speaker 5: of companies like doing pilot programs. And with these like

132
00:06:09,880 --> 00:06:12,599
Speaker 5: AI pilot programs, the hope obviously is that is going

133
00:06:12,680 --> 00:06:15,320
Speaker 5: to pay off one day. When you look at survey data,

134
00:06:15,440 --> 00:06:17,880
Speaker 5: it hasn't paid off yet, and you sort of wonder,

135
00:06:18,440 --> 00:06:20,440
Speaker 5: you know, when is that gonna When is that day

136
00:06:20,480 --> 00:06:22,799
Speaker 5: gonna come? If that that day doesn't come in twenty

137
00:06:22,839 --> 00:06:26,120
Speaker 5: twenty six, I think that starts to maybe create problems.

138
00:06:26,560 --> 00:06:30,160
Speaker 6: I have a second story to us, yes, no, I

139
00:06:30,200 --> 00:06:33,880
Speaker 6: mean arguably, if AI is the story of the decade,

140
00:06:34,279 --> 00:06:38,800
Speaker 6: then to me, the norm busting power, expanding kind of guardrail,

141
00:06:39,600 --> 00:06:44,800
Speaker 6: flagrantly disregarding imperial presidency of Donald Trump is the big

142
00:06:44,880 --> 00:06:47,560
Speaker 6: story for next year. I mean, so much of what

143
00:06:47,760 --> 00:06:49,880
Speaker 6: we wrote about to BusinessWeek, so much of what you

144
00:06:49,920 --> 00:06:54,279
Speaker 6: guys talked about on the podcast has been, you know,

145
00:06:54,360 --> 00:06:58,919
Speaker 6: the behavior of this president, everything from you know, doge to.

146
00:06:58,320 --> 00:07:01,000
Speaker 2: Tariffs to tear down the East Wing.

147
00:07:01,440 --> 00:07:03,760
Speaker 6: I think that's the big story of the last year,

148
00:07:04,240 --> 00:07:07,240
Speaker 6: and the extent to which the Supreme Court, you know,

149
00:07:07,360 --> 00:07:11,640
Speaker 6: will we'll check him on tariffs, on the removal power

150
00:07:11,680 --> 00:07:16,560
Speaker 6: for executives like Lisa Cook, I think twenty six is

151
00:07:16,560 --> 00:07:20,320
Speaker 6: a is a defining moment in the in the aggregation

152
00:07:20,400 --> 00:07:23,680
Speaker 6: of power and the existence of checks and balances in

153
00:07:23,720 --> 00:07:25,480
Speaker 6: the American democratic process.

154
00:07:25,840 --> 00:07:29,560
Speaker 5: I think, without question, twenty twenty five was the year

155
00:07:29,640 --> 00:07:33,480
Speaker 5: of the imperial presidency. What about this year, Well, I

156
00:07:33,520 --> 00:07:36,080
Speaker 5: think this is the year what's the opposite of the

157
00:07:36,120 --> 00:07:37,160
Speaker 5: imperial presidency?

158
00:07:37,200 --> 00:07:40,800
Speaker 7: They the most presidency.

159
00:07:41,040 --> 00:07:44,360
Speaker 5: I mean, I think with the scattering of elections we

160
00:07:44,400 --> 00:07:49,280
Speaker 5: had in November, the resignations by GOP members of Congress,

161
00:07:49,760 --> 00:07:52,720
Speaker 5: polling which is looking really bad, there's reason I think

162
00:07:52,760 --> 00:07:55,920
Speaker 5: like this is the year that when sort of Donald

163
00:07:55,920 --> 00:07:58,600
Speaker 5: Trump comes back to Earth where he starts to test.

164
00:07:58,920 --> 00:08:01,520
Speaker 5: He really tested the limit of his power in twenty

165
00:08:01,560 --> 00:08:04,720
Speaker 5: twenty five. I think we're going to see more people,

166
00:08:04,960 --> 00:08:09,080
Speaker 5: both people in corporate roles, some of these businesses that

167
00:08:09,160 --> 00:08:12,160
Speaker 5: have been like basically just you know, doing whatever they

168
00:08:12,160 --> 00:08:15,320
Speaker 5: can to please a White House starting to push back gingerly,

169
00:08:15,440 --> 00:08:17,520
Speaker 5: as well as members of the Republican Party.

170
00:08:17,600 --> 00:08:19,680
Speaker 3: Well, you just wrote about how Costco is doing that,

171
00:08:19,800 --> 00:08:21,040
Speaker 3: how Costco is pushing back.

172
00:08:21,040 --> 00:08:21,920
Speaker 2: Costco's doing it.

173
00:08:22,000 --> 00:08:24,679
Speaker 5: I think the big question is, like, is Costco doing

174
00:08:24,720 --> 00:08:27,239
Speaker 5: it because they are so awesome?

175
00:08:27,400 --> 00:08:28,560
Speaker 2: Everyone loves Costco.

176
00:08:28,720 --> 00:08:33,959
Speaker 5: Costco has sued the Trump administration trying to recoup tariff money.

177
00:08:33,960 --> 00:08:36,080
Speaker 5: So the idea is that if the Supreme Court Brad

178
00:08:36,120 --> 00:08:38,800
Speaker 5: mentioned the Supreme Court is going to rule on these

179
00:08:38,840 --> 00:08:42,559
Speaker 5: Liberation Day tariffs, If the Supreme Court rules that they

180
00:08:42,559 --> 00:08:44,960
Speaker 5: are legal, that the President was not allowed to do that,

181
00:08:45,360 --> 00:08:48,040
Speaker 5: then Costco and there are a bunch of other companies

182
00:08:48,080 --> 00:08:51,920
Speaker 5: that are filing similar complaints, is trying to basically get

183
00:08:51,920 --> 00:08:54,560
Speaker 5: a refund as soon as possible. Now this is interesting

184
00:08:54,600 --> 00:08:57,160
Speaker 5: because if you think about Costco in contrast to say Amazon,

185
00:08:57,200 --> 00:09:00,760
Speaker 5: Remember earlier this year Amazon like Flow, it wasn't even

186
00:09:00,760 --> 00:09:01,080
Speaker 5: like an.

187
00:09:01,760 --> 00:09:02,959
Speaker 4: I going to show it on a bill.

188
00:09:04,440 --> 00:09:08,920
Speaker 5: Yeah, some indication that maybe Amazon would like itemize the

189
00:09:08,960 --> 00:09:12,240
Speaker 5: tariff costs. And then the White House got wind of it,

190
00:09:12,320 --> 00:09:16,120
Speaker 5: they called it, you know, like unpatriotic. Amazon immediately pulled back.

191
00:09:16,480 --> 00:09:18,920
Speaker 5: Meanwhile Costco getting involved in this legal action.

192
00:09:19,040 --> 00:09:21,760
Speaker 2: Again. The reason for this could be either that Costco

193
00:09:21,840 --> 00:09:23,600
Speaker 2: is sort of unique. They have a.

194
00:09:23,679 --> 00:09:27,720
Speaker 5: Big a really strong brand, really strong consumer loyalty. Costco

195
00:09:27,920 --> 00:09:30,680
Speaker 5: exactly like you you need your big jar of mayonnaise,

196
00:09:30,720 --> 00:09:31,680
Speaker 5: so you're not even you're.

197
00:09:31,520 --> 00:09:32,880
Speaker 4: Not too mad if it comes up in like every

198
00:09:32,880 --> 00:09:33,960
Speaker 4: single conversation, right.

199
00:09:34,000 --> 00:09:37,400
Speaker 5: And maybe Donald Trump is afraid to go after Costco specifically.

200
00:09:37,480 --> 00:09:40,040
Speaker 5: On the other hand, maybe maybe this is something that

201
00:09:40,360 --> 00:09:42,600
Speaker 5: is the beginning of a greater pushback.

202
00:09:42,679 --> 00:09:42,880
Speaker 2: Yeah.

203
00:09:42,880 --> 00:09:44,480
Speaker 6: I would just point out that if you if you

204
00:09:44,559 --> 00:09:48,640
Speaker 6: remember when Amazon floated that, the White House called Jeff Bezos,

205
00:09:48,679 --> 00:09:52,040
Speaker 6: who has a lot of non Amazon business in front

206
00:09:52,040 --> 00:09:55,480
Speaker 6: of the Trump administration, including his space company Blue Origin.

207
00:09:56,120 --> 00:09:58,160
Speaker 6: So the White House has a lot of leverage over

208
00:09:58,160 --> 00:10:00,320
Speaker 6: companies like Amazon that they I don't I think that

209
00:10:00,360 --> 00:10:01,720
Speaker 6: they have over Costco.

210
00:10:02,040 --> 00:10:02,840
Speaker 2: And I don't.

211
00:10:02,720 --> 00:10:07,520
Speaker 6: See any any pullback from companies and business leaders in

212
00:10:08,120 --> 00:10:10,760
Speaker 6: trying to placate the White House and cork Donald Trump.

213
00:10:10,840 --> 00:10:12,840
Speaker 6: I mean, it will be interesting to see if that changes.

214
00:10:12,880 --> 00:10:16,240
Speaker 6: But right now a lot of corporate decisions are flowing

215
00:10:16,280 --> 00:10:18,319
Speaker 6: through the White House and mar A Lago.

216
00:10:18,760 --> 00:10:20,920
Speaker 5: What about you, Sacey, what do you think? What do

217
00:10:20,960 --> 00:10:23,800
Speaker 5: you make of these bubble burst.

218
00:10:24,559 --> 00:10:27,280
Speaker 3: Let's see with the AI bubble burst, I would say

219
00:10:27,320 --> 00:10:29,959
Speaker 3: I'm scared of the bubble bursting, and I'm scared of

220
00:10:30,040 --> 00:10:36,040
Speaker 3: how depending our whole economy is on AI. Also, the

221
00:10:36,080 --> 00:10:40,160
Speaker 3: thing that I notice is how I feel like we're

222
00:10:40,200 --> 00:10:41,839
Speaker 3: just not sure how AI is really going to be

223
00:10:41,920 --> 00:10:45,400
Speaker 3: used or integrated, and businesses are investing, and it reminds

224
00:10:45,480 --> 00:10:47,560
Speaker 3: me of if you guys ever saw in South Park

225
00:10:47,559 --> 00:10:48,640
Speaker 3: they had the underwear nomes.

226
00:10:48,679 --> 00:10:50,040
Speaker 4: Do you remember the underwear nomes?

227
00:10:50,120 --> 00:10:52,600
Speaker 3: It was like very odd, but there are these little

228
00:10:52,640 --> 00:10:54,600
Speaker 3: gnomes and they would steal people's underwear and they had

229
00:10:54,600 --> 00:10:57,680
Speaker 3: a business plan. And their business plan was step one,

230
00:10:58,000 --> 00:11:01,400
Speaker 3: steal everybody's underwear, Step two, session mark, question mark, question mark,

231
00:11:01,400 --> 00:11:05,240
Speaker 3: step three, millions of dollars. And I sort of feel

232
00:11:05,280 --> 00:11:07,199
Speaker 3: like that is where AI is. It's in the question

233
00:11:07,240 --> 00:11:09,240
Speaker 3: where it's like, Okay, we're gonna spend a lot of

234
00:11:09,240 --> 00:11:12,320
Speaker 3: money on AI and then somehow that's going to translate

235
00:11:12,360 --> 00:11:16,480
Speaker 3: to millions or billions of dollars, and I'm worried about

236
00:11:16,520 --> 00:11:19,440
Speaker 3: that not translating and the effect that that'll have on

237
00:11:19,480 --> 00:11:22,720
Speaker 3: the economy because it's not just you know, a couple

238
00:11:22,720 --> 00:11:25,120
Speaker 3: of big companies go down. I feel like everything so

239
00:11:25,400 --> 00:11:28,200
Speaker 3: tied into AI. That is the thing that worries me.

240
00:11:28,280 --> 00:11:30,480
Speaker 3: I'm not sure if the bubble's gonna burst or not.

241
00:11:30,559 --> 00:11:33,080
Speaker 3: I feel like I hear compelling arguments on both sides,

242
00:11:33,080 --> 00:11:35,320
Speaker 3: but it does worry me a lot.

243
00:11:36,240 --> 00:11:38,680
Speaker 6: The thing that does feel similar to the late nineties

244
00:11:38,800 --> 00:11:42,040
Speaker 6: is just the tunnel vision around AI and that total

245
00:11:42,120 --> 00:11:45,600
Speaker 6: lack of investor and corporate interest in anything else right now.

246
00:11:45,880 --> 00:11:48,640
Speaker 6: So I assure your concerns, Stacy. And it feels like

247
00:11:49,040 --> 00:11:51,640
Speaker 6: if some of these expectations aren't met, there will be

248
00:11:51,679 --> 00:11:55,319
Speaker 6: nothing to cushion this economy because there's so much investor,

249
00:11:55,400 --> 00:11:58,320
Speaker 6: interest and energy being focused into one place.

250
00:11:59,080 --> 00:12:02,680
Speaker 5: Stacey, we got bread. That's basic take on twenty twenty six. Now,

251
00:12:02,760 --> 00:12:06,600
Speaker 5: you I know you're all about the sort of economic numbers, right,

252
00:12:07,480 --> 00:12:08,599
Speaker 5: You're about the indicator.

253
00:12:09,200 --> 00:12:11,960
Speaker 2: What are you looking at for the year ahead? Well?

254
00:12:12,000 --> 00:12:14,480
Speaker 3: I did a story for BusinessWeek on whether or not

255
00:12:14,559 --> 00:12:17,480
Speaker 3: we can expect a recession in twenty twenty six, which

256
00:12:17,520 --> 00:12:19,560
Speaker 3: is slightly different than the bubble question. But I was

257
00:12:19,600 --> 00:12:22,720
Speaker 3: looking across the economy, looking at there. There's this whole

258
00:12:23,000 --> 00:12:28,959
Speaker 3: industry essentially of economic forecasters, and they are always feeding

259
00:12:29,000 --> 00:12:31,040
Speaker 3: things into their computer models trying to figure out if

260
00:12:31,040 --> 00:12:34,000
Speaker 3: we're heading into a recession. One of the economists I

261
00:12:34,040 --> 00:12:37,800
Speaker 3: talked to was Mark Zandy. He's chief economist for Moody's Analytics.

262
00:12:37,800 --> 00:12:39,880
Speaker 3: Moody's Analytics is a forecasting agency.

263
00:12:39,920 --> 00:12:40,640
Speaker 4: This is what they do.

264
00:12:40,760 --> 00:12:42,840
Speaker 3: And I said to him, will we see a recession

265
00:12:42,840 --> 00:12:43,720
Speaker 3: at twenty twenty six?

266
00:12:43,800 --> 00:12:49,240
Speaker 8: Here's what he said, Uh, I think the most likely

267
00:12:49,360 --> 00:12:52,440
Speaker 8: outlook is for us to get through without a recession.

268
00:12:53,360 --> 00:12:57,120
Speaker 3: This is excellent news, but your voice does not match

269
00:12:57,640 --> 00:12:59,040
Speaker 3: the optimism of your words.

270
00:12:59,320 --> 00:13:02,240
Speaker 8: Yeah, because I was to qualify it by saying nothing

271
00:13:02,240 --> 00:13:06,880
Speaker 8: else can go wrong. That's how tenuous things are. And

272
00:13:06,920 --> 00:13:09,440
Speaker 8: you know, there's a lot of things that could go wrong.

273
00:13:09,800 --> 00:13:13,920
Speaker 8: So we're not in recession. We should be able to

274
00:13:13,960 --> 00:13:16,439
Speaker 8: avoid one, but you know we're right on the precipice.

275
00:13:16,440 --> 00:13:19,040
Speaker 8: And again, you know, everything has to stick to script

276
00:13:19,280 --> 00:13:20,320
Speaker 8: first to avoid one.

277
00:13:20,600 --> 00:13:22,000
Speaker 4: That was like the optimistic take.

278
00:13:22,080 --> 00:13:25,679
Speaker 2: It doesn't sound awesome. No, not a last to confidence.

279
00:13:25,720 --> 00:13:26,480
Speaker 4: No no.

280
00:13:26,559 --> 00:13:28,720
Speaker 3: And he was just saying that there are things are

281
00:13:28,720 --> 00:13:30,560
Speaker 3: so frag right now. AI was one of the big

282
00:13:30,559 --> 00:13:32,720
Speaker 3: things he looked at. He was like, AI has to hold.

283
00:13:32,760 --> 00:13:35,480
Speaker 3: If it doesn't hold, or if it doesn't like sort

284
00:13:35,520 --> 00:13:37,679
Speaker 3: of succeed at the right pace, we're in a lot

285
00:13:37,720 --> 00:13:41,800
Speaker 3: of trouble. He also was talking about consumer spending. That's

286
00:13:41,800 --> 00:13:44,160
Speaker 3: a big one. That's definitely an indicator that I'm going

287
00:13:44,200 --> 00:13:46,720
Speaker 3: to watch because it is such a huge.

288
00:13:46,480 --> 00:13:47,400
Speaker 4: Part of our economy.

289
00:13:47,920 --> 00:13:52,560
Speaker 3: And right now, the wealthiest ten percent of Americans, the

290
00:13:52,559 --> 00:13:55,760
Speaker 3: top ten percent of earners, account for half of the spending,

291
00:13:56,440 --> 00:13:58,559
Speaker 3: and that puts us in a really tricky position because

292
00:13:58,640 --> 00:14:02,240
Speaker 3: if something happens to the wealthiest ten percent of the

293
00:14:02,280 --> 00:14:05,440
Speaker 3: population and they decide to save or they pull back,

294
00:14:06,280 --> 00:14:08,800
Speaker 3: that is going to be really devastating for our economy.

295
00:14:08,920 --> 00:14:14,040
Speaker 3: So consumer spending is becoming increasingly tricky to I would say,

296
00:14:14,080 --> 00:14:17,000
Speaker 3: and a lot of people are just the their spending

297
00:14:17,080 --> 00:14:19,600
Speaker 3: is going down because of inflation, because people are earning

298
00:14:19,680 --> 00:14:23,920
Speaker 3: less because the job market's so stagnant right now that people,

299
00:14:23,960 --> 00:14:26,760
Speaker 3: I think, feel like they can't ask for raises, they're

300
00:14:26,760 --> 00:14:30,880
Speaker 3: feeling nervous, they're saving. So consumer spending is another big

301
00:14:30,880 --> 00:14:31,840
Speaker 3: one that I'm gonna be watching.

302
00:14:32,600 --> 00:14:35,760
Speaker 5: Yeah, I mean I feel like we've throughout the year

303
00:14:36,080 --> 00:14:38,640
Speaker 5: been sort of waiting for it to kind of fall off.

304
00:14:39,080 --> 00:14:40,240
Speaker 2: It hasn't fallen off.

305
00:14:40,320 --> 00:14:43,920
Speaker 5: Yes, So again, like it's one of these things we

306
00:14:44,000 --> 00:14:46,080
Speaker 5: just keep waiting for this recession to pop out, and

307
00:14:46,120 --> 00:14:48,040
Speaker 5: we've sort of been been in that position for like,

308
00:14:48,520 --> 00:14:49,840
Speaker 5: what the life for several years.

309
00:14:49,920 --> 00:14:52,400
Speaker 3: Yes, it's like that toy with the clown that pops

310
00:14:52,400 --> 00:14:54,640
Speaker 3: out and you're just like winding it and winding it. Yes,

311
00:14:54,880 --> 00:14:57,200
Speaker 3: I feel I keep feeling like the consumer sentiment numbers

312
00:14:57,240 --> 00:14:59,600
Speaker 3: come out, they're terrible. They're the lowest they've been in decades,

313
00:14:59,600 --> 00:15:01,800
Speaker 3: and I'm like, Okay, here we go. Next time consumer

314
00:15:01,800 --> 00:15:04,560
Speaker 3: spending comes out, it's going to be terrible. And what

315
00:15:04,560 --> 00:15:07,440
Speaker 3: do you know, it like looks pretty good. This keeps

316
00:15:07,440 --> 00:15:08,520
Speaker 3: happening over and over again.

317
00:15:08,640 --> 00:15:10,520
Speaker 2: Do you want to hit the job market quickly? Sacy?

318
00:15:10,520 --> 00:15:15,840
Speaker 5: I mean you talked about consumers being hesitant to spend

319
00:15:15,840 --> 00:15:19,840
Speaker 5: potentially or like kind of economic uncertainty hangover consumers. What

320
00:15:19,880 --> 00:15:22,720
Speaker 5: about the economic uncertainty hangover companies?

321
00:15:23,120 --> 00:15:26,840
Speaker 3: Yes, the job market, I think is probably the most

322
00:15:27,000 --> 00:15:30,320
Speaker 3: important part of the economy because it's just been so

323
00:15:30,760 --> 00:15:34,040
Speaker 3: still for a year, which is really odd. Like normally

324
00:15:34,360 --> 00:15:36,160
Speaker 3: it's moving in one direction or the other. We have

325
00:15:36,160 --> 00:15:40,040
Speaker 3: a really huge dynamic economy. It's hiring or layoffs, a

326
00:15:40,120 --> 00:15:43,440
Speaker 3: rising or something's happening, but it's been quite quiet. Like

327
00:15:43,800 --> 00:15:46,040
Speaker 3: you know, unemployment has been rising all year, but it's

328
00:15:46,080 --> 00:15:49,880
Speaker 3: still near historic lows. The number that I'm specifically watching

329
00:15:50,080 --> 00:15:53,000
Speaker 3: is the hiring rates, which is a little a little

330
00:15:53,080 --> 00:15:55,720
Speaker 3: off of like kind of the main jobs numbers, but

331
00:15:55,920 --> 00:15:58,840
Speaker 3: hiring is like the lowest it's been in decades, and

332
00:15:58,920 --> 00:16:01,520
Speaker 3: I think it's to this kind of pause. I think

333
00:16:01,520 --> 00:16:05,560
Speaker 3: a lot of companies are waiting, maybe considering AI investments

334
00:16:05,800 --> 00:16:08,720
Speaker 3: or waiting to expand with like uncertainty about tariffs and

335
00:16:08,760 --> 00:16:12,600
Speaker 3: things like that. So hiring is just abysmal. And you

336
00:16:12,640 --> 00:16:15,000
Speaker 3: cannot have a healthy economy without a healthy job market.

337
00:16:15,040 --> 00:16:16,680
Speaker 3: And our job market's just not I mean, it's not

338
00:16:17,240 --> 00:16:20,160
Speaker 3: in bad shape, but it's just kind of I don't know,

339
00:16:20,240 --> 00:16:21,480
Speaker 3: it's got like a light fever.

340
00:16:21,680 --> 00:16:22,320
Speaker 4: It's not good.

341
00:16:22,480 --> 00:16:25,200
Speaker 6: I also wonder if AI might be freezing hiring, not

342
00:16:25,600 --> 00:16:28,920
Speaker 6: the reality of it, but the expectations that companies have

343
00:16:29,000 --> 00:16:32,400
Speaker 6: created with their investors, with their boards that AI would

344
00:16:32,400 --> 00:16:35,440
Speaker 6: bring efficiencies. What a terrible time to start hiring in

345
00:16:35,680 --> 00:16:44,040
Speaker 6: mass if that is the expectation that you have set.

346
00:16:44,720 --> 00:16:48,960
Speaker 5: All right, let's go to feuds, Stacy. Yes, you know, Brad,

347
00:16:49,000 --> 00:16:51,440
Speaker 5: I think knows this too. I love a fud, I

348
00:16:51,480 --> 00:16:54,440
Speaker 5: know you do. I feel like feuds are a great way.

349
00:16:54,680 --> 00:16:56,440
Speaker 4: Twenty twenty five was a very good year for you,

350
00:16:56,480 --> 00:16:57,040
Speaker 4: By the way.

351
00:16:57,160 --> 00:16:59,280
Speaker 5: I wanted to talk about that because a year ago

352
00:16:59,360 --> 00:17:02,040
Speaker 5: in Bloomber in the Business Week your head issue, I

353
00:17:02,800 --> 00:17:05,280
Speaker 5: made a feud list, my predicted feuds for the year.

354
00:17:05,440 --> 00:17:07,480
Speaker 4: So you've been tracking feuds for years, so.

355
00:17:07,440 --> 00:17:09,960
Speaker 5: I've got yet I've been tracking feuds. I've got a

356
00:17:09,960 --> 00:17:13,160
Speaker 5: little report card here from last year, and I thought

357
00:17:13,200 --> 00:17:15,280
Speaker 5: we could go over some of those and then talk about.

358
00:17:15,080 --> 00:17:16,159
Speaker 4: The new fields for it.

359
00:17:16,200 --> 00:17:19,000
Speaker 5: All right, So so last year, this is really important.

360
00:17:19,040 --> 00:17:22,960
Speaker 5: I had dog Man versus Paddington. I think clearcut win

361
00:17:23,119 --> 00:17:25,520
Speaker 5: for dog Man on this one. Both movies came out

362
00:17:25,520 --> 00:17:28,880
Speaker 5: around the same time Paddington in Peru. It was the

363
00:17:28,920 --> 00:17:33,360
Speaker 5: lowest grossing Paddington yet dog We went to Peru and

364
00:17:33,400 --> 00:17:35,440
Speaker 5: no one cared or not that many people cared or

365
00:17:35,480 --> 00:17:38,080
Speaker 5: not as many people as cared about the earlier Paddington movies.

366
00:17:38,320 --> 00:17:40,040
Speaker 5: Dog Man, on the other hand, it grossed a little

367
00:17:40,040 --> 00:17:43,200
Speaker 5: bit less but way smaller budget. Plus hey new ip,

368
00:17:43,920 --> 00:17:45,560
Speaker 5: I think I think this is a clear win for

369
00:17:45,600 --> 00:17:47,280
Speaker 5: the half Man, half dog.

370
00:17:47,720 --> 00:17:50,800
Speaker 2: Okay, speaking of Sam Altman prevailing.

371
00:17:50,960 --> 00:17:55,280
Speaker 5: My opinion in the Altman versus Elon feud is that

372
00:17:55,320 --> 00:17:58,640
Speaker 5: what you predicted? Max Well, I didn't actually make any predictions.

373
00:17:58,680 --> 00:18:00,760
Speaker 5: I just said that these would be the feud. Wait one,

374
00:18:00,920 --> 00:18:04,160
Speaker 5: how Well, I would say, I'm curious what Brad thinks

375
00:18:04,160 --> 00:18:09,159
Speaker 5: says here. But Altman went into the year, you know

376
00:18:09,200 --> 00:18:11,119
Speaker 5: where Elon is kind of top of the world.

377
00:18:11,160 --> 00:18:12,280
Speaker 2: He's suing open.

378
00:18:12,040 --> 00:18:15,160
Speaker 4: Ai chainsaws, He's yeah, he's.

379
00:18:15,000 --> 00:18:18,280
Speaker 5: Close to Trump, and the year ends with Alman being

380
00:18:18,359 --> 00:18:20,320
Speaker 5: I think at the center of the of the sort

381
00:18:20,359 --> 00:18:22,960
Speaker 5: of business story of the year, which is Ai, but

382
00:18:23,080 --> 00:18:25,800
Speaker 5: also getting lots of great access to the White House,

383
00:18:25,800 --> 00:18:28,200
Speaker 5: which you would have thought would be you know, Elon's

384
00:18:28,240 --> 00:18:30,680
Speaker 5: main kind of Trump card. I feel like this is

385
00:18:30,720 --> 00:18:32,520
Speaker 5: a close call, though I don't want to I don't

386
00:18:32,520 --> 00:18:33,600
Speaker 5: want to actually draw.

387
00:18:33,840 --> 00:18:37,560
Speaker 6: Yeah, I'm going to give it to Elon, and I'll

388
00:18:37,600 --> 00:18:41,920
Speaker 6: explain why I don't disagree with Max's reasoning, but I think, look,

389
00:18:42,080 --> 00:18:44,720
Speaker 6: Elon has so many ways to win. And you look

390
00:18:44,720 --> 00:18:47,439
Speaker 6: at SpaceX right now, on track for one hundred and

391
00:18:47,440 --> 00:18:48,680
Speaker 6: eighty launches this year.

392
00:18:49,000 --> 00:18:50,560
Speaker 2: You know, Starlink is killing it.

393
00:18:51,000 --> 00:18:55,440
Speaker 6: And Bluemberg has reported that SpaceX is on the verge

394
00:18:55,440 --> 00:18:57,960
Speaker 6: of an IPO. It could raise thirty billion dollars a

395
00:18:58,000 --> 00:19:01,399
Speaker 6: one point five trillion dollar valuation. Elon himself will be

396
00:19:01,440 --> 00:19:06,479
Speaker 6: sitting on north of five hundred billion worth of SpaceX shares,

397
00:19:07,000 --> 00:19:10,520
Speaker 6: and and his companies are so tightly linked, as Max

398
00:19:10,600 --> 00:19:13,439
Speaker 6: knows so well that it puts Tesla in a position

399
00:19:13,480 --> 00:19:16,359
Speaker 6: to succeed, I mean, all all of the x AI.

400
00:19:16,520 --> 00:19:18,840
Speaker 2: Of course, he could pull out a win in AI

401
00:19:19,080 --> 00:19:19,480
Speaker 2: just by.

402
00:19:19,359 --> 00:19:21,080
Speaker 4: Virtually a trillion dollar pay package.

403
00:19:21,240 --> 00:19:25,560
Speaker 6: Yeah, and this idea, I don't know. I mean, yeah,

404
00:19:25,880 --> 00:19:30,800
Speaker 6: Elon is you know, SpaceX right now is the juggernaut

405
00:19:30,800 --> 00:19:33,680
Speaker 6: of her his portfolio, and it's a really good position.

406
00:19:33,880 --> 00:19:36,520
Speaker 2: Real quick. Kendrick v. Drake, I think that.

407
00:19:36,520 --> 00:19:38,800
Speaker 4: Was a great feud. I think my favorite feud.

408
00:19:38,720 --> 00:19:43,000
Speaker 5: Huge l for Drake, though, I mean, oh lost, I

409
00:19:43,080 --> 00:19:46,919
Speaker 5: know that Kendrick the super Bowl performance? All right, New feuds,

410
00:19:49,320 --> 00:19:52,760
Speaker 5: zero predictions first feud in Video Versuawei.

411
00:19:52,880 --> 00:19:53,200
Speaker 4: Okay.

412
00:19:53,240 --> 00:19:58,480
Speaker 5: Now, Huawei is a gigantic Chinese tech conglomerate, And the

413
00:19:58,520 --> 00:20:01,359
Speaker 5: reason I put these two the other is because Huawei

414
00:20:01,400 --> 00:20:04,879
Speaker 5: is one of the Chinese companies that is making chips,

415
00:20:04,920 --> 00:20:07,240
Speaker 5: like state of the art chips in China. Now, we

416
00:20:07,280 --> 00:20:09,439
Speaker 5: had this, we had this thing that came up earlier

417
00:20:09,440 --> 00:20:13,000
Speaker 5: in December where Trump basically said, okay, in video, you're

418
00:20:13,040 --> 00:20:17,160
Speaker 5: allowed to sell more advanced chips to China. A bunch

419
00:20:17,200 --> 00:20:20,640
Speaker 5: of China hawks like totally freaked out because like they're

420
00:20:20,640 --> 00:20:24,000
Speaker 5: gonna give these like really important strategic assets to it as.

421
00:20:24,160 --> 00:20:25,800
Speaker 4: A national security issue.

422
00:20:25,840 --> 00:20:28,119
Speaker 5: For a long time, it's unclear how China is going

423
00:20:28,160 --> 00:20:30,200
Speaker 5: to play this, but there are at least some signs

424
00:20:30,200 --> 00:20:32,240
Speaker 5: that they're not going to maybe buy that many of

425
00:20:32,320 --> 00:20:36,240
Speaker 5: these in Vidia chips basically because they think that Huawei

426
00:20:36,280 --> 00:20:38,320
Speaker 5: can do just as well. That like that that the

427
00:20:38,400 --> 00:20:41,960
Speaker 5: chips aren't as big an advantage as we thought. We've

428
00:20:41,960 --> 00:20:45,560
Speaker 5: seen this play out similarly like with Apple, where Huawei

429
00:20:45,600 --> 00:20:48,080
Speaker 5: has and a couple other Chinese companies have really caught up.

430
00:20:48,080 --> 00:20:53,119
Speaker 5: But like Chinese tech companies are catching up even in

431
00:20:53,160 --> 00:20:56,439
Speaker 5: these areas that I think we saw as being you know,

432
00:20:56,600 --> 00:20:59,520
Speaker 5: sort of the domain of the United States, and so

433
00:20:59,560 --> 00:21:01,560
Speaker 5: I think that is that is an interesting story.

434
00:21:01,600 --> 00:21:04,400
Speaker 6: Watch, well, what a flex from China, you know, publicly

435
00:21:04,440 --> 00:21:08,160
Speaker 6: reject the Nvidia chips, say that you want to build

436
00:21:08,200 --> 00:21:11,040
Speaker 6: a self reliant industry, and then probably go source those

437
00:21:11,040 --> 00:21:15,840
Speaker 6: in Vidia chips anyway, maybe indirectly. So either way, I

438
00:21:15,880 --> 00:21:17,800
Speaker 6: do think it's a big rivalry and I think either

439
00:21:17,840 --> 00:21:20,320
Speaker 6: way China ends up with a stronger hand.

440
00:21:20,760 --> 00:21:24,320
Speaker 2: All right, Now, last year I predicted that Trump would

441
00:21:24,320 --> 00:21:26,600
Speaker 2: feud Jerome Powell, and I feel very good about that

442
00:21:26,640 --> 00:21:28,600
Speaker 2: prediction because it was like a thing we talked to

443
00:21:28,600 --> 00:21:29,439
Speaker 2: you about, nails it.

444
00:21:29,560 --> 00:21:32,320
Speaker 5: Yeah, and in fact I got in. I got in fight.

445
00:21:32,359 --> 00:21:33,959
Speaker 5: There are people who are like, no, they're not going

446
00:21:34,040 --> 00:21:36,160
Speaker 5: to fight. I had a few arguments at the beginning

447
00:21:36,160 --> 00:21:38,359
Speaker 5: of the year because at the time, like Trump was

448
00:21:38,400 --> 00:21:40,720
Speaker 5: saying kind of nice things about Jerome Powell and.

449
00:21:40,760 --> 00:21:42,679
Speaker 4: Joam Powell's not like a feisty person.

450
00:21:42,800 --> 00:21:43,080
Speaker 5: He is.

451
00:21:43,640 --> 00:21:46,920
Speaker 3: No, he's not. Yeah, he's not gonna. I don't know,

452
00:21:47,000 --> 00:21:48,600
Speaker 3: so throw shade at anybody.

453
00:21:48,640 --> 00:21:49,719
Speaker 2: But here's what I'm wondering.

454
00:21:49,880 --> 00:21:53,359
Speaker 5: I mean, obviously, I think Trump and the FED is

455
00:21:53,440 --> 00:21:56,880
Speaker 5: a big feud in twenty twenty six. But I'm kind

456
00:21:56,920 --> 00:21:59,480
Speaker 5: of curious, Stacy, like this is really your Bell Balley

457
00:21:59,520 --> 00:22:04,320
Speaker 5: week for better What is the feud? Like, like, in

458
00:22:04,400 --> 00:22:07,400
Speaker 5: terms of Trump and the Fed? Is it still Trump

459
00:22:07,560 --> 00:22:10,960
Speaker 5: and Powell? Because Trump is gonna name very soon. I

460
00:22:10,960 --> 00:22:14,440
Speaker 5: think we believe, you know, a replacement to Powell that's

461
00:22:14,440 --> 00:22:16,480
Speaker 5: gonna create a weird lame duck situation for a.

462
00:22:18,080 --> 00:22:19,920
Speaker 2: Yeah, so do we get.

463
00:22:19,760 --> 00:22:24,240
Speaker 5: Like sort of Trump and one of the Kevins against Powell?

464
00:22:24,480 --> 00:22:27,640
Speaker 5: Or does one of the Kevins I believe w Wash

465
00:22:27,800 --> 00:22:29,480
Speaker 5: or Hassart right?

466
00:22:29,880 --> 00:22:30,760
Speaker 4: Is Kevin Hassett?

467
00:22:30,800 --> 00:22:31,439
Speaker 2: Right? Sorry?

468
00:22:31,760 --> 00:22:33,840
Speaker 5: Well, anyway, I have to say I just have to

469
00:22:33,880 --> 00:22:36,520
Speaker 5: pause and say my all time favorite thing that Trump

470
00:22:36,560 --> 00:22:39,880
Speaker 5: ever did as a politician was when he endorsed Eric

471
00:22:40,280 --> 00:22:43,680
Speaker 5: for Senate in uh in Missouri, like two years three

472
00:22:43,720 --> 00:22:46,920
Speaker 5: years ago. There were two candidates running for Senate uh

473
00:22:47,000 --> 00:22:49,840
Speaker 5: in Missouri, and he just endorsed Eric. He essentially endorsed

474
00:22:49,840 --> 00:22:53,199
Speaker 5: them both and and so so, so anytime there's an

475
00:22:53,240 --> 00:22:57,600
Speaker 5: opportunity for that with the Trump Okay, So my question

476
00:22:57,640 --> 00:23:00,800
Speaker 5: Stacey is, yeah, like who is the fe with is it?

477
00:23:01,040 --> 00:23:04,280
Speaker 5: Is it Trump and whoever he picks against? Kind of

478
00:23:04,359 --> 00:23:08,920
Speaker 5: like the dubvish forces or does whoever he pick turn

479
00:23:08,960 --> 00:23:11,960
Speaker 5: around and some fed commentators are saying this and sort

480
00:23:11,960 --> 00:23:14,880
Speaker 5: of suddenly become captive to the institution, like turn around

481
00:23:14,920 --> 00:23:18,280
Speaker 5: and start resisting Trump as soon as they get the nomination.

482
00:23:19,880 --> 00:23:20,720
Speaker 4: That's interesting.

483
00:23:20,880 --> 00:23:25,600
Speaker 3: I mean, I think the feud this year, the feud

484
00:23:25,640 --> 00:23:28,480
Speaker 3: between Trump and Jerome Powell, which I do think was

485
00:23:28,520 --> 00:23:32,480
Speaker 3: a feud as insofar as Jerome Powell has.

486
00:23:32,320 --> 00:23:34,520
Speaker 4: Feuds, which I don't think he has a lot of them.

487
00:23:34,920 --> 00:23:38,000
Speaker 3: But I really think it was over power because the

488
00:23:38,000 --> 00:23:40,399
Speaker 3: Federal Reserve just has a lot of power over the

489
00:23:40,440 --> 00:23:44,800
Speaker 3: economy and the president doesn't really have access to that.

490
00:23:44,840 --> 00:23:49,960
Speaker 3: It's pretty protected, right, and pal just wouldn't budge. He

491
00:23:50,400 --> 00:23:53,600
Speaker 3: would not budge, and that I think infuriated President Trump

492
00:23:53,600 --> 00:23:54,879
Speaker 3: because it's real power.

493
00:23:55,000 --> 00:23:56,720
Speaker 4: The Federal Reserve chair, the.

494
00:23:56,840 --> 00:24:00,720
Speaker 3: You know, setting interest rates, that is incredibly powerful way

495
00:24:00,760 --> 00:24:03,679
Speaker 3: of raising money for the government, way of stimulating or

496
00:24:03,720 --> 00:24:06,560
Speaker 3: slowing down the economy. I mean, it's a lot of power,

497
00:24:06,640 --> 00:24:09,399
Speaker 3: and I think Trump wants it, he sees it, he

498
00:24:09,480 --> 00:24:13,879
Speaker 3: wants it. I think the person who steps into that

499
00:24:14,040 --> 00:24:17,919
Speaker 3: role could make some trouble for Trump. I feel like

500
00:24:19,040 --> 00:24:21,240
Speaker 3: Jerome Palace put up quite a bit of resistance. Lisa

501
00:24:21,280 --> 00:24:24,840
Speaker 3: Cooks put up resistance. They've both been successful in staying

502
00:24:24,840 --> 00:24:28,240
Speaker 3: in their positions. Also, you know, there's been more descent

503
00:24:29,040 --> 00:24:32,560
Speaker 3: within the Federal So the Federal Open Market Committee, they

504
00:24:32,640 --> 00:24:34,399
Speaker 3: vote on whether or not to raise interest rates of

505
00:24:34,440 --> 00:24:36,320
Speaker 3: what to do, and normally it's a unanimous vote.

506
00:24:36,320 --> 00:24:38,359
Speaker 4: It's almost always unanimous, unanimous.

507
00:24:38,400 --> 00:24:40,840
Speaker 3: Recently, the last couple of times there have been very

508
00:24:40,840 --> 00:24:44,520
Speaker 3: public descent, which they've said, oh, you know, Trump's wormed

509
00:24:44,560 --> 00:24:46,439
Speaker 3: his way into the FED, which I think is true.

510
00:24:46,600 --> 00:24:50,639
Speaker 3: And I also think it lays the groundwork for FED

511
00:24:50,680 --> 00:24:55,520
Speaker 3: governors to disagree with Trump publicly and to maybe have

512
00:24:55,680 --> 00:24:57,840
Speaker 3: more of an individual voice than before.

513
00:24:57,920 --> 00:24:59,639
Speaker 4: So I don't think it's.

514
00:24:59,520 --> 00:25:01,840
Speaker 3: A slam dunk for Trump, because once you get into

515
00:25:01,840 --> 00:25:04,920
Speaker 3: that position, I mean, you know J. Powell was appointed

516
00:25:05,000 --> 00:25:07,399
Speaker 3: by President Trump, was what he said.

517
00:25:07,520 --> 00:25:10,919
Speaker 5: I think the prediction is Trump first, whoever he nominates that, like, oh,

518
00:25:11,080 --> 00:25:14,479
Speaker 5: we're going to have like three weeks of honeymoon, and

519
00:25:14,520 --> 00:25:17,280
Speaker 5: then like it's going to be one true social insult

520
00:25:17,320 --> 00:25:19,640
Speaker 5: after another against one of the kevin I think so too.

521
00:25:19,720 --> 00:25:22,199
Speaker 5: All right, Stacy, we got a couple more things to

522
00:25:22,280 --> 00:25:25,320
Speaker 5: do before we get to listener predictions. The first is

523
00:25:25,400 --> 00:25:27,959
Speaker 5: is I understand it. You've devised a game for us

524
00:25:27,760 --> 00:25:28,960
Speaker 5: for me and Brad.

525
00:25:29,160 --> 00:25:32,480
Speaker 4: Yes, it is headlines mad Libs. Have you both played

526
00:25:32,480 --> 00:25:34,600
Speaker 4: mad Libs by Max?

527
00:25:34,760 --> 00:25:37,440
Speaker 5: I do because I have children, and I have to

528
00:25:37,480 --> 00:25:40,040
Speaker 5: say I think it may be the most inane thing.

529
00:25:40,520 --> 00:25:41,640
Speaker 2: My fantastic game.

530
00:25:41,720 --> 00:25:43,000
Speaker 4: I will not hear it's smeared.

531
00:25:43,440 --> 00:25:47,160
Speaker 3: So basically what I was thinking is, you know that

532
00:25:47,520 --> 00:25:49,440
Speaker 3: we don't know what the headlines of twenty twenty six

533
00:25:49,480 --> 00:25:49,760
Speaker 3: are going.

534
00:25:49,760 --> 00:25:52,680
Speaker 4: To be, but we have all been reporting for a

535
00:25:52,720 --> 00:25:53,200
Speaker 4: long time.

536
00:25:53,280 --> 00:25:56,119
Speaker 3: We all have kind of a reporter's intuition, and I

537
00:25:56,240 --> 00:25:59,320
Speaker 3: was hoping to tap into that intuition with mad Libs.

538
00:25:59,760 --> 00:26:02,840
Speaker 3: So I have headlines written out and I have left

539
00:26:02,840 --> 00:26:05,760
Speaker 3: some of the words blank, some adjectives, some nouns, some

540
00:26:05,840 --> 00:26:08,080
Speaker 3: proper names. So I'm going to ask you and Brad

541
00:26:08,080 --> 00:26:09,720
Speaker 3: to fill them in, and then I'm going to read

542
00:26:09,800 --> 00:26:13,760
Speaker 3: you a couple of predictive headlines that I think could

543
00:26:13,920 --> 00:26:17,200
Speaker 3: end up gracing the Bloomberg Business Week covers of twenty

544
00:26:17,280 --> 00:26:17,760
Speaker 3: twenty six.

545
00:26:17,840 --> 00:26:20,240
Speaker 5: Brad, this is not how Business Week normally choose, but

546
00:26:20,359 --> 00:26:23,800
Speaker 5: perhaps perhaps this is how we should do it.

547
00:26:23,840 --> 00:26:26,879
Speaker 2: So I will be telling yeah, careful notes, Brad.

548
00:26:26,880 --> 00:26:31,119
Speaker 3: This sounds like a commitment for a twenty twenty six headline.

549
00:26:31,600 --> 00:26:36,200
Speaker 4: Anyway, here we go. So, first thing, I need an.

550
00:26:36,040 --> 00:26:41,440
Speaker 3: Adjective Max Harry okay, number Brad twelve.

551
00:26:42,200 --> 00:26:45,840
Speaker 4: Okay, company Max any company?

552
00:26:46,080 --> 00:26:48,360
Speaker 2: Snickers an.

553
00:26:50,400 --> 00:27:00,560
Speaker 4: Hershey Okay company Brad Crumble now a.

554
00:27:02,080 --> 00:27:10,240
Speaker 7: Max vice president of marketing, a proper name, Brad samuel

555
00:27:12,600 --> 00:27:20,240
Speaker 7: a chore, Max laundry. Something an adult has to do, Brad.

556
00:27:21,119 --> 00:27:22,399
Speaker 2: Save for retirement.

557
00:27:24,119 --> 00:27:28,960
Speaker 4: And something enjoyable, something relaxing, Max surfing. Okay, Okay.

558
00:27:29,040 --> 00:27:31,639
Speaker 3: Here are the two predictive headlines of twenty twenty six.

559
00:27:32,320 --> 00:27:36,840
Speaker 3: Here's the first one, magnificent seven. More like Harry twelve.

560
00:27:37,840 --> 00:27:40,879
Speaker 3: A new crop of companies are the stock markets Darlings,

561
00:27:40,920 --> 00:27:45,080
Speaker 3: including Hershey's, Crumble, including Hershey's and Crumble.

562
00:27:45,880 --> 00:27:48,879
Speaker 5: All right, okay, So like Crack, we would have to

563
00:27:49,040 --> 00:27:55,280
Speaker 5: imagine like a huge shift economic shift. Yeah, the AI

564
00:27:56,640 --> 00:28:03,200
Speaker 5: completely collapses economy. He plunges into a historic depression, the

565
00:28:03,240 --> 00:28:04,200
Speaker 5: only thing left.

566
00:28:04,320 --> 00:28:06,480
Speaker 2: So we're eating our feeling exactly.

567
00:28:06,119 --> 00:28:07,399
Speaker 4: Right, we're eating our feelings.

568
00:28:07,520 --> 00:28:10,480
Speaker 6: Just also, I think that you know the financial press's

569
00:28:10,520 --> 00:28:13,920
Speaker 6: ability to coin you know the word for a group

570
00:28:13,960 --> 00:28:17,000
Speaker 6: of companies from the magnificent seven to fang in this

571
00:28:17,040 --> 00:28:18,639
Speaker 6: scenario has really fallen apart.

572
00:28:18,680 --> 00:28:22,919
Speaker 2: What are we calling it? The Harry twelve? Yeah? Al

573
00:28:25,920 --> 00:28:26,280
Speaker 2: all right.

574
00:28:26,320 --> 00:28:30,760
Speaker 3: The second headline is my AI VP of Marketing, My

575
00:28:30,840 --> 00:28:35,119
Speaker 3: AI systant Samuel can do laundry, save for retirement and surf.

576
00:28:36,320 --> 00:28:39,800
Speaker 4: It's my new prediction that works. Yeah.

577
00:28:39,800 --> 00:28:42,440
Speaker 2: I think that's like open AI actually literally said.

578
00:28:42,480 --> 00:28:44,960
Speaker 3: Would be a solid VP of marketing.

579
00:28:46,760 --> 00:28:51,000
Speaker 5: Tracks the surfing optimist can serve. But I don't know

580
00:28:51,000 --> 00:28:52,760
Speaker 5: about a chatgyptwo.

581
00:28:52,200 --> 00:28:53,320
Speaker 4: Well, surf the web.

582
00:28:54,920 --> 00:28:58,080
Speaker 6: Or this new AI enabled vice president of marketing is

583
00:28:58,120 --> 00:29:02,400
Speaker 6: doing the job so well that the actual employee is surfing.

584
00:29:02,640 --> 00:29:07,320
Speaker 2: Brad Harry twelve cover a business week? What say you? Well,

585
00:29:07,360 --> 00:29:10,000
Speaker 2: it seems like from the Mad Live that the Hairy

586
00:29:10,080 --> 00:29:15,840
Speaker 2: twelve are our sweet like companies selling sugary treats right,

587
00:29:15,920 --> 00:29:20,120
Speaker 2: Hershey and crumbleson. Never bet against the sweet tooth of

588
00:29:20,160 --> 00:29:20,520
Speaker 2: the buckle.

589
00:29:20,560 --> 00:29:21,200
Speaker 4: That's true.

590
00:29:21,360 --> 00:29:24,840
Speaker 2: So say, I say, up, poly market, if you're listening,

591
00:29:24,920 --> 00:29:25,680
Speaker 2: you heard it here first?

592
00:29:25,720 --> 00:29:26,560
Speaker 4: You heard it here first?

593
00:29:26,560 --> 00:29:28,360
Speaker 3: I mean I would buy them, meg, I would buy

594
00:29:28,360 --> 00:29:32,880
Speaker 3: a magazine that had candy and the Hairy twelve twelve?

595
00:29:32,960 --> 00:29:34,000
Speaker 2: Why is it Harry though?

596
00:29:34,040 --> 00:29:34,600
Speaker 4: Because of you?

597
00:29:42,800 --> 00:29:45,880
Speaker 5: Final little segment before we leave, Brad, before we leave

598
00:29:45,920 --> 00:29:48,760
Speaker 5: you all and let you continue eating black eyed peas

599
00:29:48,800 --> 00:29:51,400
Speaker 5: or whatever. We've got a lightning round, so none of

600
00:29:51,480 --> 00:29:52,800
Speaker 5: us should think too hard about this.

601
00:29:53,000 --> 00:29:53,320
Speaker 4: Okay.

602
00:29:53,320 --> 00:29:55,400
Speaker 5: It's like a like a one or two word answer,

603
00:29:55,960 --> 00:29:59,160
Speaker 5: and we're going to go through the the blank of

604
00:29:59,200 --> 00:29:59,560
Speaker 5: the year.

605
00:29:59,640 --> 00:30:02,920
Speaker 2: So here you go, Brad. Political Movement of.

606
00:30:02,920 --> 00:30:10,680
Speaker 5: The year, climate absolutists. Oh Stacy, Maha Maha Okay. Mine

607
00:30:10,720 --> 00:30:13,240
Speaker 5: is the one where you're like, uh, all these people

608
00:30:13,240 --> 00:30:17,400
Speaker 5: want to I forget what it's called, like digital abstinence basically,

609
00:30:18,200 --> 00:30:20,000
Speaker 5: but it's like it's like fancified.

610
00:30:20,760 --> 00:30:23,560
Speaker 2: It's like Ezra Cline is on this now. Okay. Musical

611
00:30:23,600 --> 00:30:24,360
Speaker 2: genre Brad.

612
00:30:24,480 --> 00:30:29,000
Speaker 7: Musical Genre of the year, r and b Ai generated music.

613
00:30:29,120 --> 00:30:30,120
Speaker 2: Oh God, Stacy.

614
00:30:30,160 --> 00:30:34,520
Speaker 5: Country Okay, highest gross higher gross Dune three or the

615
00:30:34,560 --> 00:30:37,600
Speaker 5: forthcoming Avengers movie Brad spider Man four.

616
00:30:39,440 --> 00:30:41,840
Speaker 4: He went rogue. Okay, I say Avengers.

617
00:30:42,040 --> 00:30:43,920
Speaker 2: I'm going Dune three, but only because I like it.

618
00:30:43,960 --> 00:30:44,600
Speaker 2: I actually have.

619
00:30:44,560 --> 00:30:46,360
Speaker 4: No No one is going to go see Done three.

620
00:30:46,440 --> 00:30:46,840
Speaker 2: Okay.

621
00:30:47,160 --> 00:30:53,520
Speaker 5: Country that wins the World Cup Brazil Stacy, Germany us

622
00:30:53,560 --> 00:30:55,040
Speaker 5: A come on, okay.

623
00:30:55,240 --> 00:30:57,560
Speaker 2: Nobel Peace Prize winner, Brad.

624
00:30:57,480 --> 00:31:00,840
Speaker 6: I have no idea, but I will, let's say, not

625
00:31:01,320 --> 00:31:04,240
Speaker 6: the current president of the United States.

626
00:31:04,400 --> 00:31:07,600
Speaker 4: Stacey, I don't know past.

627
00:31:07,440 --> 00:31:15,600
Speaker 5: Okay, FIFA Peace Prize winner Brad Donald Trump again, they

628
00:31:15,600 --> 00:31:18,040
Speaker 5: gotta give it to I'm saying, NBS, they gotta give it.

629
00:31:18,080 --> 00:31:21,880
Speaker 2: There's the there's I actually.

630
00:31:21,560 --> 00:31:23,680
Speaker 5: Don't know if they give out the FIFA Peace Prize

631
00:31:23,760 --> 00:31:25,360
Speaker 5: every every year.

632
00:31:25,560 --> 00:31:27,320
Speaker 4: Maybe they could give out a few a year, why.

633
00:31:27,240 --> 00:31:28,760
Speaker 2: Not, Okay, Brad?

634
00:31:28,880 --> 00:31:32,720
Speaker 6: Midterm results, Yeah, I think the Democrats retake the House,

635
00:31:32,800 --> 00:31:37,240
Speaker 6: but by a very small margin and nothing really changes same.

636
00:31:38,800 --> 00:31:42,000
Speaker 5: I say the Democrats retake both No, you guys are right.

637
00:31:42,480 --> 00:31:47,080
Speaker 5: Timoth Ay Chalomey unmasked as East d Kid, East Kid.

638
00:31:47,200 --> 00:31:48,520
Speaker 5: I actually don't know how to say this. Do you

639
00:31:48,560 --> 00:31:49,440
Speaker 5: know what I'm talking about?

640
00:31:49,640 --> 00:31:51,160
Speaker 4: That he's secretly a rapper?

641
00:31:51,320 --> 00:31:53,800
Speaker 2: Yes, Timothy Chalomey secretly a rapper.

642
00:31:54,600 --> 00:31:58,000
Speaker 5: Yes, I'm not deep in the lore here, but I'm

643
00:31:58,040 --> 00:32:00,360
Speaker 5: gonna say yes to Okay, kind of looks like him

644
00:32:00,400 --> 00:32:02,200
Speaker 5: when you look at the picture of the guy.

645
00:32:02,040 --> 00:32:03,600
Speaker 2: Wearing the mask.

646
00:32:05,960 --> 00:32:12,360
Speaker 6: Job all right, hot new office trend raw napping under

647
00:32:12,360 --> 00:32:15,040
Speaker 6: your desk, oh office naps.

648
00:32:15,200 --> 00:32:15,800
Speaker 4: I like that.

649
00:32:16,640 --> 00:32:20,280
Speaker 3: I'm gonna say that, like face time is back, like

650
00:32:20,280 --> 00:32:22,000
Speaker 3: people putting in crazy hours.

651
00:32:22,040 --> 00:32:25,760
Speaker 5: Okay, related prediction in the office offices.

652
00:32:25,320 --> 00:32:27,920
Speaker 2: Are the hot new office trend, like yeah, like.

653
00:32:28,000 --> 00:32:30,480
Speaker 5: No, Like it's we're going to see some big company

654
00:32:31,160 --> 00:32:34,120
Speaker 5: pull back from the the open office craze.

655
00:32:34,320 --> 00:32:36,960
Speaker 3: I mean, look at Jamie Diamond and like that huge

656
00:32:37,040 --> 00:32:38,680
Speaker 3: new building he built with the inn.

657
00:32:38,840 --> 00:32:41,280
Speaker 5: No, but do they have do they have divided offices?

658
00:32:41,440 --> 00:32:45,640
Speaker 5: I'm saying like this trend. I'm saying, yeah, doors are

659
00:32:45,680 --> 00:32:49,520
Speaker 5: the hot new office trend. That's my prediction, because you're

660
00:32:49,520 --> 00:32:52,800
Speaker 5: having fewer people come to the office because there's because

661
00:32:52,800 --> 00:32:55,080
Speaker 5: of work from home and so on, and all these

662
00:32:55,160 --> 00:32:56,560
Speaker 5: like zooms and face times.

663
00:32:56,560 --> 00:32:57,600
Speaker 2: It's just so much louder.

664
00:32:57,640 --> 00:33:00,920
Speaker 5: It's just so hard to have a zoom conversation from

665
00:33:00,960 --> 00:33:03,880
Speaker 5: a tightly I mean when you're packed inside cubicles.

666
00:33:04,000 --> 00:33:06,680
Speaker 3: I hope that's true, but I think that ship is sailed.

667
00:33:06,720 --> 00:33:10,440
Speaker 3: It's just so much cheaper to pack people in, and

668
00:33:10,480 --> 00:33:11,160
Speaker 3: I think money went.

669
00:33:11,280 --> 00:33:14,520
Speaker 2: I applaud maxis prediction. I want to go back to the.

670
00:33:14,440 --> 00:33:16,920
Speaker 6: Time when we all yes, when we all ended the

671
00:33:17,000 --> 00:33:19,640
Speaker 6: location of the size of each other's offices is a

672
00:33:19,720 --> 00:33:22,920
Speaker 6: proxy for how well we were doing inside the workplace.

673
00:33:23,360 --> 00:33:26,040
Speaker 4: Corner switch floor.

674
00:33:26,480 --> 00:33:28,720
Speaker 5: I actually like kind of open offices. I feel like

675
00:33:28,760 --> 00:33:30,880
Speaker 5: most people don't actually like them.

676
00:33:31,000 --> 00:33:32,959
Speaker 2: Which is you're like, why did we do this? But

677
00:33:33,160 --> 00:33:33,520
Speaker 2: I don't know.

678
00:33:33,600 --> 00:33:34,760
Speaker 4: I just can't because of money.

679
00:33:34,840 --> 00:33:37,640
Speaker 2: I just can't. Yeah, well it's always that, isn't it? Okay?

680
00:33:37,720 --> 00:33:41,560
Speaker 5: Last one new AI trend Stacy.

681
00:33:42,200 --> 00:33:47,000
Speaker 3: I think that we're going to start seeing AI engineered

682
00:33:47,000 --> 00:33:50,680
Speaker 3: to be people's friends or like compant, you know what

683
00:33:50,720 --> 00:33:53,280
Speaker 3: I mean, like personality engineer. I think we're going to

684
00:33:53,320 --> 00:33:58,760
Speaker 3: start seeing AI entities that are like tailored to our needs,

685
00:33:58,840 --> 00:34:03,040
Speaker 3: like sort of like an assistant or an assistant slash friend.

686
00:34:03,240 --> 00:34:04,600
Speaker 4: I just I think we're going.

687
00:34:04,560 --> 00:34:07,720
Speaker 3: To start to see AI being tailored to our kind

688
00:34:07,760 --> 00:34:10,320
Speaker 3: of emotional slash life needs.

689
00:34:10,440 --> 00:34:11,160
Speaker 4: That's what I think.

690
00:34:12,000 --> 00:34:15,520
Speaker 6: I'm going to say restrictions on usage like the screen

691
00:34:15,600 --> 00:34:19,600
Speaker 6: time equivalent for AI, not just with parents for kids,

692
00:34:20,000 --> 00:34:23,800
Speaker 6: but people in their personalized dating apps. We're going to

693
00:34:23,880 --> 00:34:26,879
Speaker 6: look for kind of genuine connection and ways to keep

694
00:34:26,920 --> 00:34:28,160
Speaker 6: AI out of the equation.

695
00:34:28,760 --> 00:34:31,200
Speaker 5: I'm gonna I'm going to big like piggyback on that one,

696
00:34:31,280 --> 00:34:36,719
Speaker 5: with tools to like consumer tools to allow you to

697
00:34:36,760 --> 00:34:40,480
Speaker 5: sniff out AI usage, so like in your chat, in

698
00:34:40,520 --> 00:34:44,160
Speaker 5: your in your text messaging application, or in your dating

699
00:34:44,200 --> 00:34:46,920
Speaker 5: app or whatever, like I could imagine, and I think

700
00:34:46,920 --> 00:34:49,600
Speaker 5: it would be useful to have like a filter a

701
00:34:49,640 --> 00:34:53,040
Speaker 5: percent chance that your friend used AI to act.

702
00:34:53,120 --> 00:34:54,839
Speaker 3: It's like when you get the phone fall and it's

703
00:34:54,880 --> 00:34:58,360
Speaker 3: like probably spam, except it'll be like, this is probably

704
00:34:58,400 --> 00:34:58,920
Speaker 3: a robot.

705
00:34:59,239 --> 00:35:03,359
Speaker 5: This chat, this podcast is one hundred percent human for now,

706
00:35:03,520 --> 00:35:04,560
Speaker 5: Stacey and I think.

707
00:35:04,400 --> 00:35:08,719
Speaker 2: We've run out of time. Yes, we have, Bradstone. Thanks.

708
00:35:08,880 --> 00:35:09,399
Speaker 2: If I were a.

709
00:35:09,360 --> 00:35:11,360
Speaker 3: Robot, I would know what to say. I would smooth

710
00:35:11,400 --> 00:35:12,319
Speaker 3: the ending out better.

711
00:35:12,960 --> 00:35:15,360
Speaker 2: Brad, Thank you for coming. Thanks guys, that was fun.

712
00:35:15,520 --> 00:35:20,720
Speaker 4: Thanks Brad, Stacy.

713
00:35:21,280 --> 00:35:24,840
Speaker 5: Before we close out this episode, before we say goodbye

714
00:35:24,920 --> 00:35:27,320
Speaker 5: to the New Year, we've already said goodbye, Brad. You remember,

715
00:35:27,360 --> 00:35:30,359
Speaker 5: we asked listeners to send in predictions for New Year,

716
00:35:30,400 --> 00:35:33,000
Speaker 5: what they were thinking. We got some great voice memos.

717
00:35:33,320 --> 00:35:36,240
Speaker 5: Charlie also went on the street and asked some people

718
00:35:36,600 --> 00:35:38,520
Speaker 5: as well to get their take. Let's give a listen

719
00:35:38,560 --> 00:35:41,080
Speaker 5: to what our listeners think is going to happen in

720
00:35:41,120 --> 00:35:41,560
Speaker 5: the new Year.

721
00:35:41,880 --> 00:35:44,040
Speaker 1: My prediction is that twenty twenty six is the year

722
00:35:44,080 --> 00:35:47,960
Speaker 1: that college finally loses its appeal to Americans.

723
00:35:48,320 --> 00:35:50,160
Speaker 4: I think Theron's definitely going to do some sort of

724
00:35:50,200 --> 00:35:50,880
Speaker 4: dance routine.

725
00:35:51,000 --> 00:35:53,279
Speaker 3: Sometime next year there will be more than one video

726
00:35:53,320 --> 00:35:54,720
Speaker 3: of him doing a good dance.

727
00:35:54,960 --> 00:35:58,600
Speaker 9: The first prediction I have is the continued rise in

728
00:35:58,640 --> 00:36:02,480
Speaker 9: the sale in the celebration of physical media, paper books

729
00:36:02,520 --> 00:36:05,720
Speaker 9: to cassette tapes to final records. I also am hopeful

730
00:36:05,800 --> 00:36:08,440
Speaker 9: that substock is going to become an economic engine for

731
00:36:08,520 --> 00:36:09,920
Speaker 9: really high quality journalism.

732
00:36:10,000 --> 00:36:12,480
Speaker 2: Everything's protein protein these days. I think fiber is gonna

733
00:36:12,480 --> 00:36:15,319
Speaker 2: make a humback. Travis Kelsey is going to be the

734
00:36:15,360 --> 00:36:17,719
Speaker 2: one who will be calling off the engagement to Taylor

735
00:36:17,800 --> 00:36:21,560
Speaker 2: Swift as he struggles with post retirement identity. Watching reels

736
00:36:21,680 --> 00:36:22,640
Speaker 2: is the new smoking.

737
00:36:23,280 --> 00:36:29,080
Speaker 5: No piece of banana art, either with or Sanz duct

738
00:36:29,080 --> 00:36:32,680
Speaker 5: tape will fetch a penny over five hundred thousand dollars.

739
00:36:32,680 --> 00:36:36,760
Speaker 1: Twenty twenty sixty gonna be the year of a major public, cultural,

740
00:36:36,800 --> 00:36:40,359
Speaker 1: and maybe even political backlash against AI. We're gonna end

741
00:36:40,400 --> 00:36:43,400
Speaker 1: up with all the bars and tattooing and having no

742
00:36:43,520 --> 00:36:45,919
Speaker 1: droid's policy by the end of twenty twenty six.

743
00:36:46,640 --> 00:36:50,120
Speaker 5: Well, first of all, thank you to Brent Ray, Pete David,

744
00:36:50,440 --> 00:36:53,719
Speaker 5: and everyone who who gave us predictions. Also thanks to

745
00:36:53,800 --> 00:36:56,800
Speaker 5: Charlie for going out and asking people. I gotta say,

746
00:36:57,280 --> 00:36:59,560
Speaker 5: I love the I love the no droids thing. You know,

747
00:36:59,719 --> 00:37:02,640
Speaker 5: I'm totally on board, you know, I'm my bar is

748
00:37:02,680 --> 00:37:04,840
Speaker 5: no droids, have a no droids policy?

749
00:37:04,920 --> 00:37:07,480
Speaker 4: What does that mean? It is no droids?

750
00:37:07,480 --> 00:37:08,200
Speaker 2: Well what what?

751
00:37:08,200 --> 00:37:11,239
Speaker 5: What Brandroids who sent this in is saying is that

752
00:37:11,280 --> 00:37:15,240
Speaker 5: there's gonna be a cultural backlash to AI. And he's

753
00:37:15,320 --> 00:37:18,000
Speaker 5: suggesting that, you know, in the Star Wars bar where

754
00:37:18,040 --> 00:37:20,840
Speaker 5: you have androids and aliens and so on going together. Okay,

755
00:37:20,880 --> 00:37:23,160
Speaker 5: he's gonna he's imagining a situation.

756
00:37:22,760 --> 00:37:25,120
Speaker 4: Where the bar where like Jaba the hut was.

757
00:37:25,320 --> 00:37:29,040
Speaker 2: Yeah, Jaba will be allowed. But C three po gotta

758
00:37:29,080 --> 00:37:29,800
Speaker 2: go oh.

759
00:37:32,239 --> 00:37:37,640
Speaker 3: Letting it comes to my bar, C three pos, welcome

760
00:37:37,680 --> 00:37:41,800
Speaker 3: in my bar. I liked the comeback of Fiber very interesting.

761
00:37:42,000 --> 00:37:43,880
Speaker 5: I mean that I feel like that is a slam

762
00:37:43,960 --> 00:37:46,120
Speaker 5: dunk right what yeah about this Chris this?

763
00:37:46,280 --> 00:37:48,080
Speaker 2: Uh, this Travis Kelce prediction.

764
00:37:48,360 --> 00:37:52,719
Speaker 3: Oh that Travis is no way, no way that he

765
00:37:52,800 --> 00:37:54,759
Speaker 3: will call out. I mean if he calls off his

766
00:37:54,800 --> 00:37:56,880
Speaker 3: engagement to Jaylor Swift.

767
00:37:56,600 --> 00:37:59,160
Speaker 4: He's like clearly with the Chiefs.

768
00:37:59,200 --> 00:38:01,520
Speaker 3: I think the that his career might be in its

769
00:38:01,600 --> 00:38:04,880
Speaker 3: last year or two and being with her presents so

770
00:38:05,160 --> 00:38:10,400
Speaker 3: many very interesting business opportunities for him, his profile so

771
00:38:10,640 --> 00:38:11,680
Speaker 3: much higher than it was.

772
00:38:11,719 --> 00:38:13,480
Speaker 4: But when they started dating, I think.

773
00:38:13,960 --> 00:38:16,799
Speaker 5: Yeah, I think this is true love. I am on

774
00:38:16,840 --> 00:38:20,200
Speaker 5: the record this marriage is going to last. That is

775
00:38:20,200 --> 00:38:20,760
Speaker 5: my prediction.

776
00:38:21,040 --> 00:38:21,960
Speaker 4: I mean, I think it's.

777
00:38:22,080 --> 00:38:24,600
Speaker 3: It would be really hard if it didn't, because it's

778
00:38:24,719 --> 00:38:25,600
Speaker 3: also public.

779
00:38:25,640 --> 00:38:26,399
Speaker 2: I ain't going to.

780
00:38:26,360 --> 00:38:28,359
Speaker 5: Get that house in the suburbs with the basketball court,

781
00:38:28,480 --> 00:38:29,120
Speaker 5: is all I'm saying.

782
00:38:29,160 --> 00:38:32,080
Speaker 4: I think so. And the music studio. I believe in

783
00:38:32,120 --> 00:38:34,319
Speaker 4: those crazy kids. We'll see all right.

784
00:38:34,560 --> 00:38:36,640
Speaker 2: Happy New Year, Stacey, Happy New Year, Max.

785
00:38:40,920 --> 00:38:43,960
Speaker 3: This show is produced by Stacy Wong. Magnus Hendrickson is

786
00:38:44,000 --> 00:38:47,200
Speaker 3: our supervising producer, and Amy Kean is our executive producer.

787
00:38:47,360 --> 00:38:51,400
Speaker 3: Sam Roga Chandel's engineering, and Dave Purcell factchecks. Sage Bauman

788
00:38:51,440 --> 00:38:55,320
Speaker 3: heads Bloomberg Podcasts. Special thanks to Jeff Muscus, Julia Rubin,

789
00:38:55,440 --> 00:38:57,920
Speaker 3: Charlie Gorvin, Angel Recchio, and Marie Ling.

790
00:38:58,200 --> 00:39:00,520
Speaker 4: If you have a minute, please rate and rear the show.

791
00:39:00,560 --> 00:39:02,759
Speaker 3: It means a lot to us, And if you have

792
00:39:02,800 --> 00:39:05,279
Speaker 3: a story that should be our business, please email us.

793
00:39:05,520 --> 00:39:08,600
Speaker 3: Everybody's at Bloomberg dot net. That is, everybody's with an

794
00:39:08,680 --> 00:39:10,279
Speaker 3: us at bloomberg dot net.

795
00:39:10,560 --> 00:39:12,399
Speaker 4: Thank you for listening. We'll see you next week.

796
00:39:12,520 --> 00:39:14,160
Speaker 2: Happy New Year, Happy New Year,