1 00:00:02,520 --> 00:00:13,760 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is the Bloomberg 2 00:00:13,840 --> 00:00:17,920 Speaker 1: Surveillance Podcast. Catch us live weekdays at seven am Eastern 3 00:00:18,200 --> 00:00:22,000 Speaker 1: on Apple CarPlay or Android Auto with the Bloomberg Business App. 4 00:00:22,360 --> 00:00:25,680 Speaker 1: Listen on demand wherever you get your podcasts, or watch 5 00:00:25,760 --> 00:00:27,040 Speaker 1: us live on YouTube. 6 00:00:27,440 --> 00:00:30,840 Speaker 2: Kathy Jones joins is to give a first look it yield. 7 00:00:31,000 --> 00:00:34,920 Speaker 2: I look at total return on bond funds since the 8 00:00:34,960 --> 00:00:38,640 Speaker 2: bond market broke three years ago whatever now two and 9 00:00:38,640 --> 00:00:41,599 Speaker 2: a half years ago, and it ain't working. What's the 10 00:00:41,720 --> 00:00:46,280 Speaker 2: value proposition in bonds versus buy in two year of 11 00:00:46,440 --> 00:00:48,560 Speaker 2: Paul Sweeney two year yield forever? 12 00:00:48,920 --> 00:00:52,199 Speaker 3: Yeah, well, we didn't have positive returns last. 13 00:00:52,000 --> 00:00:55,120 Speaker 4: Year, and by look, you gotta do better than that. 14 00:00:55,280 --> 00:00:57,160 Speaker 5: Yeah, I know, but we did. 15 00:00:57,200 --> 00:00:59,840 Speaker 3: The agg was up in most categories except for very 16 00:00:59,840 --> 00:01:02,920 Speaker 3: long long term bonds or international bonds had positive returns. 17 00:01:03,400 --> 00:01:07,280 Speaker 3: And you know, the reason you buy bonds are for income, 18 00:01:07,560 --> 00:01:11,160 Speaker 3: and right now they have income. You buy them for 19 00:01:11,200 --> 00:01:13,680 Speaker 3: a capital preservation, just because. 20 00:01:13,440 --> 00:01:15,000 Speaker 6: Borrowing you want to get your money back. 21 00:01:15,080 --> 00:01:17,679 Speaker 3: You can get your money back, and for that sort 22 00:01:17,720 --> 00:01:21,560 Speaker 3: of certainty, right and for diversification. So at some point 23 00:01:21,800 --> 00:01:25,560 Speaker 3: in the sometime in the future, the stock market might 24 00:01:25,600 --> 00:01:31,440 Speaker 3: go down, and generally bonds do pretty well in that environment, Kathy. 25 00:01:31,480 --> 00:01:33,800 Speaker 5: For a long time we had an inverted yield curve 26 00:01:33,840 --> 00:01:36,440 Speaker 5: in some folks like Cam Harvey at Duke University would 27 00:01:36,480 --> 00:01:39,119 Speaker 5: tell you that means the recessions coming. We didn't get it. 28 00:01:39,480 --> 00:01:41,520 Speaker 5: Now we've got the yeld curve steeping. I got the 29 00:01:41,560 --> 00:01:43,600 Speaker 5: four I got the ten year at four to sixty, 30 00:01:43,640 --> 00:01:45,880 Speaker 5: the two year four and a quarter. What is that 31 00:01:45,920 --> 00:01:47,360 Speaker 5: steepening yield curve telling us? 32 00:01:47,720 --> 00:01:50,240 Speaker 3: Yeah, this was one for the record books. We didn't 33 00:01:50,240 --> 00:01:53,400 Speaker 3: get the recession after the inverted yield curve. I think 34 00:01:53,440 --> 00:01:55,960 Speaker 3: it's telling us two things. It's telling us, yes, the 35 00:01:56,000 --> 00:01:58,320 Speaker 3: market still looks for the Fed to cut a couple 36 00:01:58,320 --> 00:02:00,720 Speaker 3: of times at the short end, but the long end 37 00:02:00,800 --> 00:02:02,880 Speaker 3: is reflecting all of the risks that we have for 38 00:02:03,040 --> 00:02:08,079 Speaker 3: inflation and for policy that may prove to be inflationary 39 00:02:08,160 --> 00:02:11,000 Speaker 3: down the road. So we're going back to a more normal, 40 00:02:11,560 --> 00:02:13,680 Speaker 3: steeper yield curve, and I think that continues. 41 00:02:14,800 --> 00:02:18,160 Speaker 5: So what am I doing in terms of credit? Here? 42 00:02:18,280 --> 00:02:20,960 Speaker 5: Do I take credit risk? Here? Do I just be 43 00:02:21,600 --> 00:02:23,600 Speaker 5: comfortable in my treasury market? 44 00:02:24,120 --> 00:02:26,720 Speaker 3: Yeah? I think you can take some credit risk. We 45 00:02:26,760 --> 00:02:30,000 Speaker 3: are cautious on overdoing it on credit going too far 46 00:02:30,120 --> 00:02:32,720 Speaker 3: down the spectrum, because we are starting to see defaults 47 00:02:32,800 --> 00:02:35,560 Speaker 3: rise in the high yield market, in the lower credit 48 00:02:35,639 --> 00:02:39,280 Speaker 3: quality part of the market. But investment grade companies, you know, 49 00:02:39,320 --> 00:02:43,440 Speaker 3: they have cash flow that have strong earnings. It's really 50 00:02:43,480 --> 00:02:46,480 Speaker 3: hard to fight that. So we'd continue at the investment rate. 51 00:02:46,520 --> 00:02:51,079 Speaker 3: And you know, in the intermediate duration category. 52 00:02:50,960 --> 00:02:53,400 Speaker 4: The real yield, what does that indicate to you? The 53 00:02:53,480 --> 00:02:56,160 Speaker 4: nominally yield, folks, I think it's Paul, it's the beginning 54 00:02:56,160 --> 00:02:58,200 Speaker 4: of the year. Like every jargon we use. We got 55 00:02:58,240 --> 00:03:00,720 Speaker 4: to redefine it, right, even if it's slows a show 56 00:03:00,760 --> 00:03:04,040 Speaker 4: down to Alisa Monteo crawl. We don't want to do that. 57 00:03:04,120 --> 00:03:07,839 Speaker 2: But the real yield is the inflation adjusted yield. There's 58 00:03:07,840 --> 00:03:10,080 Speaker 2: different ways to measure, but the answer is it's. 59 00:03:09,960 --> 00:03:12,560 Speaker 4: Up up and a way. Does that impinge on Lizzie 60 00:03:12,600 --> 00:03:13,720 Speaker 4: and Saunders economy? 61 00:03:14,440 --> 00:03:17,360 Speaker 3: Well, I think at some stage of the game, other 62 00:03:17,440 --> 00:03:20,400 Speaker 3: asset classes may look at the positive real yield of 63 00:03:20,480 --> 00:03:22,720 Speaker 3: say two and a half percent, maybe moving up to 64 00:03:22,760 --> 00:03:23,400 Speaker 3: three percent? 65 00:03:23,840 --> 00:03:26,680 Speaker 2: Really are you well, we've gotta make some news here finely, 66 00:03:27,360 --> 00:03:28,760 Speaker 2: can I put that on on YouTube? 67 00:03:29,240 --> 00:03:32,000 Speaker 4: Kathy Jones models three percent ten year real yield. 68 00:03:32,560 --> 00:03:34,680 Speaker 3: I don't think that it's out of the question at all. 69 00:03:35,320 --> 00:03:37,560 Speaker 3: If you get a five percent ten year which is 70 00:03:37,560 --> 00:03:40,400 Speaker 3: not out, which is within the range of potential outcomes 71 00:03:40,400 --> 00:03:43,480 Speaker 3: that we have, and inflation continues to drift lower, you're 72 00:03:43,480 --> 00:03:46,120 Speaker 3: going to get very close to that three percent real yield. 73 00:03:46,640 --> 00:03:49,000 Speaker 3: And I would think at some point other asset classes 74 00:03:49,040 --> 00:03:52,320 Speaker 3: would pay attention to that and say it's competition. But 75 00:03:52,400 --> 00:03:58,360 Speaker 3: in terms of the economy, I notice Kathy both chantick 76 00:03:58,400 --> 00:03:59,600 Speaker 3: I always have trouble with their name. 77 00:03:59,640 --> 00:04:00,920 Speaker 5: But Centory. 78 00:04:01,520 --> 00:04:04,080 Speaker 2: We got to take a pall here right now, Lisa Matteo, 79 00:04:04,160 --> 00:04:06,480 Speaker 2: do you have trouble with Kathys Johnson's name? 80 00:04:06,880 --> 00:04:13,600 Speaker 5: Best Paul, do you have trouble with you? And say, hey, friend, welcome. 81 00:04:13,480 --> 00:04:14,760 Speaker 3: To a terrific e. 82 00:04:15,240 --> 00:04:16,279 Speaker 4: She's a killer. 83 00:04:17,400 --> 00:04:20,240 Speaker 2: I'm sitting there butchering. Mark Crumpton keeps a list of 84 00:04:20,320 --> 00:04:24,040 Speaker 2: all the names that God I can pronounce Jones. But 85 00:04:24,480 --> 00:04:27,839 Speaker 2: Mark Crumpton keeps a list of all the things I butchered. 86 00:04:27,520 --> 00:04:30,120 Speaker 4: And at the top of the list is Kathley has 87 00:04:30,120 --> 00:04:31,080 Speaker 4: studyed Good. 88 00:04:30,839 --> 00:04:34,880 Speaker 2: Morning Kathy, a nationwide tell us about Kathy's announce well. 89 00:04:34,760 --> 00:04:37,719 Speaker 3: She talked about productivity. So we can have high real 90 00:04:37,800 --> 00:04:41,640 Speaker 3: yield if we have strong productivity, And that's the question mark. 91 00:04:41,680 --> 00:04:42,800 Speaker 3: Does that continue or not? 92 00:04:43,560 --> 00:04:45,680 Speaker 5: What does our Federal Reserve do over the next couple 93 00:04:45,760 --> 00:04:48,080 Speaker 5: of meetings here? Because now, I mean we kind of 94 00:04:48,120 --> 00:04:51,080 Speaker 5: started thinking six nine months ago it could be multiple 95 00:04:51,160 --> 00:04:53,840 Speaker 5: breat cuts. Now the market's down to maybe one or two. 96 00:04:53,920 --> 00:04:55,760 Speaker 5: What do you think? Yeah, I think. 97 00:04:55,640 --> 00:04:57,279 Speaker 3: They're very cautious from here. 98 00:04:57,320 --> 00:04:57,880 Speaker 5: They have to be. 99 00:04:57,920 --> 00:05:00,520 Speaker 3: We'll get the minutes later this week of the meeting, 100 00:05:00,520 --> 00:05:03,719 Speaker 3: which should be very interesting, but they have to be 101 00:05:03,880 --> 00:05:08,120 Speaker 3: very cautious because there's so much policy uncertainty on the 102 00:05:08,120 --> 00:05:11,240 Speaker 3: horizon and the economy continues to do better than they thought. 103 00:05:11,640 --> 00:05:14,080 Speaker 4: Thank you so much for coming in today. Thanks liz 104 00:05:14,080 --> 00:05:17,120 Speaker 4: Ane would have done this. I mean she's cold. She's like, no. 105 00:05:17,080 --> 00:05:18,320 Speaker 5: Way, she's down in Florida. 106 00:05:18,400 --> 00:05:22,240 Speaker 4: She said, exactly, Yeah what liz An smart? The rest 107 00:05:22,240 --> 00:05:24,560 Speaker 4: of us moll that's O there is, Kathy Jones. Thank 108 00:05:24,600 --> 00:05:25,800 Speaker 4: you so much for getting to start. 109 00:05:26,040 --> 00:05:29,600 Speaker 1: You're listening to the Bloomberg Surveillance Podcast. Catch us live 110 00:05:29,680 --> 00:05:32,839 Speaker 1: weekday afternoons from seven to ten am Eastern. Listen on 111 00:05:32,920 --> 00:05:36,599 Speaker 1: Applecarplay and Android Otto with the Bloomberg Business app, or 112 00:05:36,720 --> 00:05:38,240 Speaker 1: watch us live on YouTube. 113 00:05:38,400 --> 00:05:43,320 Speaker 2: Glor Calvisina of RBC Capital Markets, Laurie, up twenty percent, 114 00:05:43,400 --> 00:05:46,320 Speaker 2: up twenty percent. How do you model up up again? 115 00:05:48,200 --> 00:05:50,440 Speaker 7: Well, thanks for having me, Tom, and happy new year. 116 00:05:51,000 --> 00:05:51,240 Speaker 5: Look. 117 00:05:51,240 --> 00:05:53,800 Speaker 7: I think you can't really do it from a valuation perspective. 118 00:05:54,240 --> 00:05:56,920 Speaker 7: My valuation model is the most conservative one in our 119 00:05:56,920 --> 00:05:59,719 Speaker 7: targeting process. But I do think on the sentiment side, 120 00:05:59,760 --> 00:06:02,080 Speaker 7: we have an important development in December, which was that 121 00:06:02,120 --> 00:06:05,600 Speaker 7: everybody got worried, and so we saw aaii net bulls 122 00:06:05,960 --> 00:06:07,760 Speaker 7: fall from a range you know that had been one 123 00:06:07,800 --> 00:06:10,920 Speaker 7: standard deviation above the long term average back in October. 124 00:06:11,279 --> 00:06:14,600 Speaker 7: It stayed elevated as we got into early December, and 125 00:06:14,640 --> 00:06:16,920 Speaker 7: it's pulled back now to the long term average. If 126 00:06:16,920 --> 00:06:18,400 Speaker 7: you look at the four week average, and if you 127 00:06:18,400 --> 00:06:20,560 Speaker 7: look at the weekly data point that came out last week, 128 00:06:20,600 --> 00:06:22,440 Speaker 7: I think the bulls and the bears were basically at 129 00:06:22,480 --> 00:06:25,599 Speaker 7: parody with one another, and that actually improves the setup 130 00:06:25,640 --> 00:06:28,640 Speaker 7: for stocks going forward. So I think we can get there. 131 00:06:28,680 --> 00:06:30,720 Speaker 7: I think you can. You can also have earnings help 132 00:06:30,800 --> 00:06:32,600 Speaker 7: drive the market higher. I just don't think you get 133 00:06:32,600 --> 00:06:35,560 Speaker 7: it from a valuation expansion perspective. I think we've really 134 00:06:35,600 --> 00:06:37,599 Speaker 7: done the valuation expansion that we're going to do in 135 00:06:37,640 --> 00:06:38,200 Speaker 7: this cycle. 136 00:06:39,480 --> 00:06:41,400 Speaker 5: Hey, Lorie, how about earnings? How important are they going 137 00:06:41,440 --> 00:06:41,560 Speaker 5: to be? 138 00:06:41,640 --> 00:06:41,800 Speaker 3: Here? 139 00:06:41,880 --> 00:06:43,880 Speaker 5: It seems like the Fed's not going to be doing 140 00:06:44,000 --> 00:06:47,240 Speaker 5: too much heavy lifting forming in twenty twenty five. It 141 00:06:47,279 --> 00:06:50,640 Speaker 5: feels like, and I can't imagine getting multiple expansion from here. 142 00:06:50,680 --> 00:06:52,840 Speaker 5: So it feels like if any performance we're going to 143 00:06:52,880 --> 00:06:54,640 Speaker 5: get in twenty five, it is going to be earnings driven. 144 00:06:54,839 --> 00:06:55,880 Speaker 5: Is that a fair assessment? 145 00:06:56,720 --> 00:06:58,160 Speaker 7: I think that's I think you hit the nail on 146 00:06:58,200 --> 00:07:00,760 Speaker 7: the head, Paul. And look, I do think earnings have 147 00:07:00,880 --> 00:07:04,400 Speaker 7: some challenges as we go into this next recording season. Namely, 148 00:07:04,440 --> 00:07:07,040 Speaker 7: margin expectations have been coming down if you look at 149 00:07:07,040 --> 00:07:09,800 Speaker 7: the bottom up sell side consensus estimates, that's been under 150 00:07:09,800 --> 00:07:11,640 Speaker 7: their way since the middle of last year, actually, but 151 00:07:11,680 --> 00:07:14,480 Speaker 7: it's continued as we look at these past few weeks. 152 00:07:15,080 --> 00:07:17,239 Speaker 7: And if you think about, you know, sort of the dollar. 153 00:07:17,320 --> 00:07:20,120 Speaker 7: A stronger dollar typically causes downward revisions, and I know 154 00:07:20,160 --> 00:07:22,000 Speaker 7: the dollar has been all over the place, you know, 155 00:07:22,040 --> 00:07:24,560 Speaker 7: and showing some weakness at least last I checked this morning. 156 00:07:25,280 --> 00:07:27,920 Speaker 7: But the four Q strengthening that we had, that cake 157 00:07:28,000 --> 00:07:29,680 Speaker 7: is already baked. So we've got to sort of see 158 00:07:29,680 --> 00:07:31,760 Speaker 7: what companies say about that. And look, Paul, I've been 159 00:07:31,800 --> 00:07:33,960 Speaker 7: doing this a long time. It always amazes me that 160 00:07:34,000 --> 00:07:36,120 Speaker 7: when we go through these periods of dollar strength, I 161 00:07:36,160 --> 00:07:39,239 Speaker 7: go in and you know, read earnings call transcripts, and companies, 162 00:07:39,360 --> 00:07:42,200 Speaker 7: especially in healthcare and tech, like to blame weakness on 163 00:07:42,240 --> 00:07:44,560 Speaker 7: the dollar. You know that everybody saw in real time, 164 00:07:44,600 --> 00:07:47,000 Speaker 7: but nobody marks their models until we actually, you know, 165 00:07:47,080 --> 00:07:49,880 Speaker 7: get to the end of the quarter. But I think 166 00:07:49,920 --> 00:07:51,920 Speaker 7: you've got some little issues like that, and I do 167 00:07:51,960 --> 00:07:54,920 Speaker 7: frankly expect companies to keep the bar somewhat low, just 168 00:07:54,960 --> 00:07:57,440 Speaker 7: that we do still have some uncertainty in terms of 169 00:07:57,520 --> 00:08:00,680 Speaker 7: things like taxes and tariffs. So I think earnings are 170 00:08:00,680 --> 00:08:02,560 Speaker 7: going to be good and solid, but maybe not a 171 00:08:02,600 --> 00:08:04,600 Speaker 7: ton of excitement here in the very short term. 172 00:08:04,680 --> 00:08:07,240 Speaker 2: I want to talk about religion, Laurie, and that what 173 00:08:07,360 --> 00:08:09,560 Speaker 2: I saw in all the wrap ups of last year 174 00:08:09,600 --> 00:08:11,560 Speaker 2: in this great bul market. Take it back to Ben 175 00:08:11,640 --> 00:08:16,040 Speaker 2: Laidler and Christmas Eveo. I believe twenty eighteen is the 176 00:08:16,040 --> 00:08:20,440 Speaker 2: worship of free cash flow. They have nots the people 177 00:08:20,440 --> 00:08:23,800 Speaker 2: that aren't trading it in Vidia multiples. Do they have 178 00:08:23,840 --> 00:08:29,280 Speaker 2: a new religion to emphasize free cash flow growth or 179 00:08:29,320 --> 00:08:32,800 Speaker 2: do we awake that. Why aren't more companies saying we 180 00:08:32,880 --> 00:08:34,400 Speaker 2: got to boost free cash flow? 181 00:08:36,120 --> 00:08:38,320 Speaker 7: It's an interesting question, ton. I'll tell you it's not 182 00:08:38,400 --> 00:08:40,439 Speaker 7: a big part of my process, and that may be 183 00:08:40,440 --> 00:08:43,000 Speaker 7: because I'm sort of overly influenced by my small cap 184 00:08:43,080 --> 00:08:45,400 Speaker 7: days and I am a data nerd at heart. We've 185 00:08:45,400 --> 00:08:47,560 Speaker 7: talked about that on this show before. But I will 186 00:08:47,600 --> 00:08:49,560 Speaker 7: tell you that when I look at different databases and 187 00:08:49,600 --> 00:08:51,840 Speaker 7: try to bring in free cash flow data, especially free 188 00:08:51,840 --> 00:08:55,040 Speaker 7: cash flow estimates, it's really kind of garbage like when 189 00:08:55,040 --> 00:08:57,160 Speaker 7: you try to aggregate it off to the market level. 190 00:08:57,280 --> 00:09:00,360 Speaker 7: So I'm, not, to be honest, a big you know, 191 00:09:00,400 --> 00:09:01,839 Speaker 7: sort of part of that philosophy. 192 00:09:02,760 --> 00:09:05,920 Speaker 5: So, Laurie, as we think about twenty twenty five, it 193 00:09:06,000 --> 00:09:08,000 Speaker 5: seems like, again two years in a row, we've had 194 00:09:08,040 --> 00:09:10,800 Speaker 5: twenty percent plus returns in the SP five hundred, in 195 00:09:10,880 --> 00:09:13,560 Speaker 5: large part tech driven. Quite frankly, it seems like this 196 00:09:13,600 --> 00:09:16,600 Speaker 5: has been a tech driven market for fifteen years. Is 197 00:09:16,720 --> 00:09:19,080 Speaker 5: tech going to be a leader in twenty twenty five? 198 00:09:19,160 --> 00:09:21,720 Speaker 5: Does it need to be a leader in twenty twenty five. 199 00:09:22,960 --> 00:09:25,400 Speaker 7: It's a great question, Paul. And if you actually go 200 00:09:25,480 --> 00:09:27,920 Speaker 7: back and I think it was after Trump's first victory. 201 00:09:27,960 --> 00:09:30,400 Speaker 7: We went back and looked at sector performance in the 202 00:09:30,520 --> 00:09:34,360 Speaker 7: twelve month period after that first Trump victory that November election, 203 00:09:34,400 --> 00:09:37,320 Speaker 7: and we found both financials and tech outperformed. So it 204 00:09:37,360 --> 00:09:39,280 Speaker 7: doesn't shed a ton of light on the growth versus 205 00:09:39,400 --> 00:09:41,360 Speaker 7: JALU trade at the sector level, but we did see 206 00:09:41,360 --> 00:09:44,480 Speaker 7: growth stocks generally outperform in that period, and we've seen 207 00:09:44,520 --> 00:09:48,320 Speaker 7: growth stocks, you know, big megacap tech type names, continue 208 00:09:48,320 --> 00:09:50,640 Speaker 7: to hang on to their leadership here in the aftermath 209 00:09:50,679 --> 00:09:53,280 Speaker 7: of this election as well. And look, I think a 210 00:09:53,280 --> 00:09:55,480 Speaker 7: lot of people want this market to broaden out. You 211 00:09:55,520 --> 00:09:57,440 Speaker 7: can count myself in that camp. 212 00:09:57,520 --> 00:09:57,840 Speaker 4: Yeah. 213 00:09:57,920 --> 00:10:00,200 Speaker 7: That being said, I think we have to understand and 214 00:10:00,400 --> 00:10:02,720 Speaker 7: why we have had so many head fakes so far, 215 00:10:02,760 --> 00:10:05,160 Speaker 7: and it is simply because the value part of the market, 216 00:10:05,280 --> 00:10:06,960 Speaker 7: the rest of the S and P whatever you want 217 00:10:06,960 --> 00:10:09,600 Speaker 7: to call it, has just not put up superior earnings 218 00:10:09,640 --> 00:10:12,199 Speaker 7: growth and the mag seven you know that it has 219 00:10:12,240 --> 00:10:14,280 Speaker 7: been fighting back, and we see it in terms of 220 00:10:14,320 --> 00:10:17,959 Speaker 7: near term consensus expectations. They're still dominant even though a 221 00:10:18,120 --> 00:10:21,679 Speaker 7: ramp down is anticipated, and long term earning growth expectations 222 00:10:22,160 --> 00:10:24,640 Speaker 7: are still sitting at big highs relative to the rest 223 00:10:24,640 --> 00:10:27,080 Speaker 7: of the market, and that is sustaining the premium valuation 224 00:10:27,160 --> 00:10:30,360 Speaker 7: multiples until you break that. And I think a hotter 225 00:10:30,440 --> 00:10:32,800 Speaker 7: economy than what we've been expecting, like more like a 226 00:10:32,840 --> 00:10:35,199 Speaker 7: three percent economy than a two percent economy, I think 227 00:10:35,240 --> 00:10:37,800 Speaker 7: can help that value part of the market. See earnings growth, 228 00:10:38,120 --> 00:10:40,440 Speaker 7: you don't move up, but we're just not seeing it yet. 229 00:10:40,520 --> 00:10:42,760 Speaker 7: And so I think, to be honest, if I look 230 00:10:42,800 --> 00:10:46,160 Speaker 7: back at my December meetings, this whole go with value broadening, 231 00:10:46,480 --> 00:10:49,280 Speaker 7: it just seems so consensus right now, especially in the 232 00:10:49,280 --> 00:10:51,319 Speaker 7: fact that the earnings growth dynamics aren't shifting. 233 00:10:51,800 --> 00:10:54,400 Speaker 2: Lloyd Kelvicina, I look at where we are, and what 234 00:10:54,520 --> 00:10:57,800 Speaker 2: I'd suggest is sort of the zeitgeist now as everybody's 235 00:10:57,840 --> 00:11:00,920 Speaker 2: pulling away the last five six days, I think like 236 00:11:00,960 --> 00:11:02,880 Speaker 2: three hundred and sixty five days ago, we had the 237 00:11:02,920 --> 00:11:06,160 Speaker 2: same thing going on. How do you interpret the pulling 238 00:11:06,200 --> 00:11:09,920 Speaker 2: away we're seeing right now? People selling Meg seven, people 239 00:11:10,000 --> 00:11:10,680 Speaker 2: lightening up. 240 00:11:12,080 --> 00:11:14,840 Speaker 7: Yeah. Look, I think there is a natural inclination to 241 00:11:14,880 --> 00:11:18,000 Speaker 7: take some profits when you've had this frothy sentiment in place, 242 00:11:18,160 --> 00:11:20,240 Speaker 7: and I don't think people realize how much the sentiment 243 00:11:20,280 --> 00:11:23,200 Speaker 7: started to unravel. But there's been a big concern about valuations, 244 00:11:23,200 --> 00:11:25,480 Speaker 7: and we've got a lot of uncertainty on the policy front, 245 00:11:25,760 --> 00:11:27,480 Speaker 7: so I do think it makes sense to sort of 246 00:11:27,520 --> 00:11:30,480 Speaker 7: retrace here a little bit, take some profits and see 247 00:11:30,480 --> 00:11:32,079 Speaker 7: where we need to redeploy in a bit. 248 00:11:32,559 --> 00:11:36,120 Speaker 2: Laurie, thank you so much, Lori Kelvisina, RBC Capital Mark. 249 00:11:36,160 --> 00:11:38,120 Speaker 4: It's just a huge value. 250 00:11:38,320 --> 00:11:38,400 Speaker 2: Ed. 251 00:11:44,200 --> 00:11:48,120 Speaker 1: This is the Bloomberg Surveillance Podcast. Listen live each weekday 252 00:11:48,160 --> 00:11:51,160 Speaker 1: starting at seven am Eastern on Apple Cocklay and Android 253 00:11:51,200 --> 00:11:54,240 Speaker 1: Auto with the Bloomberg Business up. You can also listen 254 00:11:54,320 --> 00:11:57,560 Speaker 1: live on Amazon Alexa from our flagship New York station. 255 00:11:58,120 --> 00:12:00,400 Speaker 1: Just say Alexa, play Bloomberg. 256 00:12:00,960 --> 00:12:04,640 Speaker 2: Procest Nation on your commute this morning, the one everyone 257 00:12:04,720 --> 00:12:07,520 Speaker 2: on transportation is watching. No, Paul, it's not the build 258 00:12:07,520 --> 00:12:10,920 Speaker 2: out in ink or what they're doing with JFK terminal wone. 259 00:12:11,480 --> 00:12:12,800 Speaker 4: Jenna Lieber joins us. 260 00:12:12,720 --> 00:12:16,599 Speaker 2: Today running the MTA off of this congestion tax in 261 00:12:16,640 --> 00:12:19,720 Speaker 2: New York, and we're thrilled the Bloomberg Surveillance will bring 262 00:12:19,760 --> 00:12:22,360 Speaker 2: them to you for the entire risk of this hour. 263 00:12:22,400 --> 00:12:27,120 Speaker 2: An incredibly busy day, important Monday for you. I've got 264 00:12:27,160 --> 00:12:29,800 Speaker 2: one question which Krity grouped in London actually brought up 265 00:12:29,800 --> 00:12:32,600 Speaker 2: because I know Paul's fired up here with a bunch 266 00:12:32,600 --> 00:12:37,920 Speaker 2: of questions as well. Part of the bargain in Stockholm 267 00:12:38,080 --> 00:12:41,360 Speaker 2: is they have a world class taxi service. Part of 268 00:12:41,400 --> 00:12:44,600 Speaker 2: the bargain in London is they have a world class 269 00:12:44,640 --> 00:12:49,320 Speaker 2: taxi service. I'm in taxis constantly here that are third world. 270 00:12:49,559 --> 00:12:53,120 Speaker 2: How does this congestion tax get us is crity goop 271 00:12:53,200 --> 00:12:57,440 Speaker 2: dimension to a better taxi experience? 272 00:12:57,840 --> 00:13:00,800 Speaker 8: I think, Tom, thanks thanks for having me. I think 273 00:13:00,800 --> 00:13:03,720 Speaker 8: that the taxis in New York are dominated, as we 274 00:13:03,880 --> 00:13:07,120 Speaker 8: all know, by Uber and Lyft, and they actually are 275 00:13:07,160 --> 00:13:09,119 Speaker 8: looking forward to having. 276 00:13:09,679 --> 00:13:12,079 Speaker 4: You interrupt here. You're telling the poor people of New 277 00:13:12,120 --> 00:13:13,440 Speaker 4: York City to take an Uber. 278 00:13:13,720 --> 00:13:16,360 Speaker 8: Yeah, you know what, the right now that the cost 279 00:13:16,400 --> 00:13:19,080 Speaker 8: difference between Uber and taxis is not all that great. 280 00:13:19,120 --> 00:13:20,839 Speaker 8: I'm not in the taxi business, so I'm trying to 281 00:13:20,880 --> 00:13:24,400 Speaker 8: answer your question. But the point is with more with 282 00:13:24,840 --> 00:13:27,880 Speaker 8: less congestion on the roads, you're going to have the 283 00:13:27,960 --> 00:13:31,200 Speaker 8: taxi industry, I think is going to do better. I mean, 284 00:13:31,240 --> 00:13:33,240 Speaker 8: people will be able to move more quickly, pick up 285 00:13:33,280 --> 00:13:36,800 Speaker 8: more rides, and for what is actually seventy five cents 286 00:13:36,840 --> 00:13:40,320 Speaker 8: per ride when the average ride of a taxi taxi 287 00:13:40,360 --> 00:13:42,560 Speaker 8: ride now in New York is like twenty five bucks, 288 00:13:42,760 --> 00:13:44,439 Speaker 8: so seventy five cents a ride, and they're going to 289 00:13:44,520 --> 00:13:46,559 Speaker 8: be able to move much more quickly, take more rides. 290 00:13:46,600 --> 00:13:48,160 Speaker 8: I think it's going to be good for the industry. 291 00:13:48,679 --> 00:13:51,400 Speaker 5: Part of the outcome that you guys are hoping for, 292 00:13:51,520 --> 00:13:54,640 Speaker 5: that we're all hoping for as a city is reduced traffic, 293 00:13:54,720 --> 00:13:57,200 Speaker 5: reduced congestion within the city. When don't we know if 294 00:13:57,240 --> 00:13:58,439 Speaker 5: that's actually happening. 295 00:13:58,440 --> 00:13:59,040 Speaker 6: It's a good question. 296 00:13:59,040 --> 00:14:01,559 Speaker 8: It's going to take a while to obviously, to take effect. 297 00:14:01,760 --> 00:14:05,160 Speaker 8: New York is adjust and they are resilient, but it's 298 00:14:05,200 --> 00:14:07,000 Speaker 8: gonna take a little while. So we're gonna be watching 299 00:14:07,080 --> 00:14:09,800 Speaker 8: it very closely, day by day, week by week. I 300 00:14:09,800 --> 00:14:13,079 Speaker 8: don't expect to see some dramatic change on the first 301 00:14:13,160 --> 00:14:13,960 Speaker 8: or the second day. 302 00:14:14,000 --> 00:14:14,520 Speaker 6: Over time. 303 00:14:14,559 --> 00:14:17,800 Speaker 8: We're expecting a ten to twenty percent reduction in traffic. 304 00:14:17,840 --> 00:14:20,840 Speaker 8: That's what we're shooting for. But Paul, the big issue 305 00:14:20,880 --> 00:14:24,080 Speaker 8: here is New York is leading New York Is and 306 00:14:24,120 --> 00:14:28,000 Speaker 8: I think I know you're an international outfit. New York 307 00:14:28,120 --> 00:14:31,000 Speaker 8: is becoming a twenty first century city. We just did 308 00:14:31,160 --> 00:14:33,520 Speaker 8: you know two train terminals in the last couple of years, 309 00:14:33,680 --> 00:14:36,840 Speaker 8: La Guardi Airport a total rebuild. It's number one in 310 00:14:36,880 --> 00:14:39,560 Speaker 8: the country. JFK is getting rebuilt. I know your Newark 311 00:14:39,600 --> 00:14:42,520 Speaker 8: Airport is getting investment. This is about being a twenty 312 00:14:42,560 --> 00:14:44,960 Speaker 8: first century city where we don't spend all our time 313 00:14:45,000 --> 00:14:48,840 Speaker 8: stuck in traffic. The business community that has always supported 314 00:14:48,880 --> 00:14:52,960 Speaker 8: congestion pricing under Mike Bloomberg's lead in part because it, 315 00:14:53,120 --> 00:14:56,240 Speaker 8: you know, congestion and time spending traffic is a tax 316 00:14:56,360 --> 00:14:57,120 Speaker 8: on our economy. 317 00:14:57,840 --> 00:15:00,880 Speaker 5: A lot of folks view this congestion price as simply 318 00:15:00,920 --> 00:15:06,520 Speaker 5: a tax on consumers. Your budget is nineteen billion dollars. 319 00:15:06,560 --> 00:15:08,480 Speaker 5: I believe that the MTA is for twenty twenty four. 320 00:15:08,960 --> 00:15:10,920 Speaker 5: You need more money. That's what a lot of folks 321 00:15:10,920 --> 00:15:11,280 Speaker 5: are saying. 322 00:15:11,440 --> 00:15:12,800 Speaker 6: Listen, this is as you said. 323 00:15:12,840 --> 00:15:15,200 Speaker 8: This is ninety percent of the people who come to 324 00:15:15,200 --> 00:15:18,200 Speaker 8: the central business this or take transit. We're carrying six 325 00:15:18,240 --> 00:15:21,520 Speaker 8: to seven million people a day on mass transit. So yeah, 326 00:15:21,800 --> 00:15:23,640 Speaker 8: we have we have to pay a lot of people, 327 00:15:23,640 --> 00:15:26,600 Speaker 8: and eighty percent of our cost is wages and pensions 328 00:15:26,640 --> 00:15:28,800 Speaker 8: and benefits. No question, we'd have to pay a lot 329 00:15:28,800 --> 00:15:32,480 Speaker 8: of people to deliver that service. But the bottom line 330 00:15:32,520 --> 00:15:36,360 Speaker 8: is congestion pricing is about the benefits. It's about not 331 00:15:36,440 --> 00:15:40,720 Speaker 8: just money for the MTA, but about lower traffic, cleaner air, 332 00:15:41,080 --> 00:15:44,560 Speaker 8: safer streets, and a more functioning economy. That's the goal. 333 00:15:44,640 --> 00:15:47,600 Speaker 8: That's why London did it, and that's why we're following. 334 00:15:48,000 --> 00:15:48,520 Speaker 4: I was in. 335 00:15:48,440 --> 00:15:50,920 Speaker 2: Paris last week and all I could say is what 336 00:15:51,040 --> 00:15:54,800 Speaker 2: a difference in congestion. It was just beyond pleasant. When 337 00:15:54,840 --> 00:15:59,320 Speaker 2: are we going to see results? Are we talking tuesday 338 00:15:59,400 --> 00:16:01,320 Speaker 2: and we talk in twenty twenty seven? 339 00:16:01,760 --> 00:16:03,840 Speaker 8: Listen, I want to sit here and tell you I 340 00:16:03,880 --> 00:16:07,080 Speaker 8: have a crystal ball. The bottom line is adjustments are 341 00:16:07,080 --> 00:16:09,680 Speaker 8: going to be made. It's gonna definitely take place over time. 342 00:16:10,040 --> 00:16:13,480 Speaker 8: Let's watch it together. There's gonna be total transparency on 343 00:16:13,520 --> 00:16:15,840 Speaker 8: the MTA side. We're gonna have a you know, a 344 00:16:15,920 --> 00:16:18,360 Speaker 8: dashboard app for everybody to look at how many cars 345 00:16:18,400 --> 00:16:22,200 Speaker 8: came in as compared to before the system went in, 346 00:16:22,600 --> 00:16:25,040 Speaker 8: and how many of them are chargeable, and we're gonna 347 00:16:25,040 --> 00:16:25,880 Speaker 8: be monitoring it close. 348 00:16:26,080 --> 00:16:28,520 Speaker 2: Number one question I get is what happens, folks, For 349 00:16:28,560 --> 00:16:31,360 Speaker 2: those of you across the nation and worldwide. The outer 350 00:16:31,480 --> 00:16:34,880 Speaker 2: rege of Manhattan North South is the FDR in the 351 00:16:34,920 --> 00:16:39,520 Speaker 2: West Side Highway. What happens to those two important thoroughfares 352 00:16:39,760 --> 00:16:41,760 Speaker 2: where I believe there's no congestion text. 353 00:16:41,880 --> 00:16:44,800 Speaker 8: Yeah, well, the idea is that these are so called 354 00:16:44,840 --> 00:16:47,320 Speaker 8: excluded roadways that are on the edge of Manhattan, that 355 00:16:47,360 --> 00:16:49,920 Speaker 8: people should be able to use them to get around 356 00:16:49,960 --> 00:16:54,080 Speaker 8: the congestion zone. Listen, we have to We always talk 357 00:16:54,120 --> 00:16:58,040 Speaker 8: about drivers like the dominant reality. I know you guys 358 00:16:58,080 --> 00:17:00,440 Speaker 8: take trans At ninety percent of people who come to 359 00:17:00,480 --> 00:17:03,200 Speaker 8: the Central Business State history take transit. There are only 360 00:17:03,240 --> 00:17:06,680 Speaker 8: one hundred and thirty thousand people coming to the CBD 361 00:17:07,280 --> 00:17:10,919 Speaker 8: who drive their personal cars as opposed to a million 362 00:17:10,920 --> 00:17:13,080 Speaker 8: and a half jobs. So I don't think that we're 363 00:17:13,080 --> 00:17:17,000 Speaker 8: gonna have some catastrophic traffic impact because a portion of 364 00:17:17,040 --> 00:17:20,440 Speaker 8: those people do elect to take transit, or that people 365 00:17:20,440 --> 00:17:22,679 Speaker 8: are avoiding the charge. I think we're gonna see it 366 00:17:22,680 --> 00:17:25,280 Speaker 8: all get baked in over time, but we're gonna watch 367 00:17:25,320 --> 00:17:26,840 Speaker 8: it closely, and we're gonna talk to you about it. 368 00:17:27,280 --> 00:17:28,960 Speaker 8: We have a new president coming in in a couple 369 00:17:29,000 --> 00:17:32,639 Speaker 8: of weeks. I'll hear your tunnel exactly. 370 00:17:32,760 --> 00:17:35,200 Speaker 5: Now, just what do you what do you think president 371 00:17:35,440 --> 00:17:38,920 Speaker 5: in president like Trump will do if anything about this plan. 372 00:17:39,119 --> 00:17:39,560 Speaker 6: I don't know. 373 00:17:39,640 --> 00:17:42,960 Speaker 8: You know, we got sued by in every every court front. 374 00:17:43,000 --> 00:17:45,080 Speaker 8: You know east of the Mississippi's. 375 00:17:44,320 --> 00:17:46,560 Speaker 4: Gonna say, is there anyone who hasn't sued you? Yeah? 376 00:17:46,560 --> 00:17:47,720 Speaker 4: But Lisa Tay, are. 377 00:17:47,640 --> 00:17:48,840 Speaker 6: You filing this party? 378 00:17:48,960 --> 00:17:49,120 Speaker 4: Yeah? 379 00:17:49,160 --> 00:17:51,240 Speaker 8: But you know what, we went every lawsuit because we 380 00:17:51,280 --> 00:17:54,040 Speaker 8: did a four thousand page study. The FEDS approved it. 381 00:17:54,520 --> 00:17:56,320 Speaker 8: You know, it took five years to do the study. 382 00:17:56,320 --> 00:17:58,120 Speaker 8: It takes about five minutes to figure out New York 383 00:17:58,160 --> 00:18:01,119 Speaker 8: as a congestion problem if you stand in midtown. But 384 00:18:01,640 --> 00:18:05,280 Speaker 8: the what President Trump is going to do, I'm not certain. 385 00:18:05,280 --> 00:18:08,480 Speaker 8: There's a lot of Republican politicians who are against mass 386 00:18:08,480 --> 00:18:09,520 Speaker 8: transit and who. 387 00:18:09,600 --> 00:18:10,360 Speaker 6: Rail about this. 388 00:18:10,760 --> 00:18:13,600 Speaker 8: President Trump is also in New Yorker ruins office buildings, 389 00:18:13,600 --> 00:18:15,800 Speaker 8: and ninety percent of the people who work in his 390 00:18:15,880 --> 00:18:19,520 Speaker 8: office buildings come on mass transit, So I'm optimistic that 391 00:18:19,600 --> 00:18:20,280 Speaker 8: he will get it. 392 00:18:20,520 --> 00:18:24,159 Speaker 2: We are on a General Libo's Lever's CEO of the 393 00:18:24,320 --> 00:18:27,679 Speaker 2: MTA with us today for this extended block. Here we 394 00:18:27,680 --> 00:18:30,200 Speaker 2: welcome all of you on Bloomberg Surveillance nationwide and you 395 00:18:30,280 --> 00:18:35,399 Speaker 2: commute and on YouTube subscribe to Bloomberg Podcast. To say 396 00:18:35,720 --> 00:18:38,240 Speaker 2: the least, I have talked to Mayor Adams not once, 397 00:18:38,280 --> 00:18:41,280 Speaker 2: but twice about a New Orleans experiment. I believe over 398 00:18:41,280 --> 00:18:44,679 Speaker 2: in Europe a free bus service for the poor. The 399 00:18:44,760 --> 00:18:48,520 Speaker 2: congestion text is about fancy people like Paul Sweeney in 400 00:18:48,560 --> 00:18:51,960 Speaker 2: his ginormous car or me being driven by the Bentley 401 00:18:52,000 --> 00:18:53,000 Speaker 2: Down Fifth Avenue. 402 00:18:53,240 --> 00:18:56,360 Speaker 4: Forget about it. What do we do to help. 403 00:18:56,480 --> 00:19:00,520 Speaker 2: Really needy people who need to commute from to say, 404 00:19:00,760 --> 00:19:02,600 Speaker 2: Rockaway Beach up to wherever? 405 00:19:02,720 --> 00:19:06,399 Speaker 8: Okay, well, let's just be real, because ninety five plus 406 00:19:06,400 --> 00:19:09,080 Speaker 8: percent of those people you're talking about, low income people 407 00:19:09,119 --> 00:19:11,400 Speaker 8: who live in the boroughs, take transit. They don't drive 408 00:19:11,480 --> 00:19:15,560 Speaker 8: because parking in midtown is Should we offer them free 409 00:19:15,560 --> 00:19:18,080 Speaker 8: bus search you know what we're offering. What we're offering 410 00:19:18,200 --> 00:19:20,960 Speaker 8: is we have them for the first time. The MTA, 411 00:19:21,480 --> 00:19:25,199 Speaker 8: under Mayor Adams leadership, has been pushing a fairfares program 412 00:19:25,240 --> 00:19:28,160 Speaker 8: that cuts the price of transit in half for low 413 00:19:28,280 --> 00:19:31,639 Speaker 8: income people. And you know what, Tom, Transit is one 414 00:19:31,680 --> 00:19:34,080 Speaker 8: of the very few things that makes New York affordable. 415 00:19:34,160 --> 00:19:36,600 Speaker 8: It's fifteen percent the cost of owning a car. It's 416 00:19:36,640 --> 00:19:39,280 Speaker 8: already a good deal at full price. At half price, 417 00:19:39,400 --> 00:19:41,879 Speaker 8: it's out of sight. And so I'm confident we're dealing 418 00:19:41,920 --> 00:19:45,080 Speaker 8: with the concerns of that community as well as the 419 00:19:45,080 --> 00:19:45,840 Speaker 8: broader goal. 420 00:19:46,000 --> 00:19:49,240 Speaker 2: What is a delta in going from Daniel is all 421 00:19:49,240 --> 00:19:52,320 Speaker 2: over me here she's she and Michelle CASKI have done 422 00:19:52,320 --> 00:19:54,960 Speaker 2: great work for Bloomberg and is Daniel Moran? What has 423 00:19:55,000 --> 00:19:58,280 Speaker 2: been the delta from fifteen dollars down to nine dollars? 424 00:19:58,320 --> 00:20:01,200 Speaker 4: How does that change the Jena Lieber World? 425 00:20:01,320 --> 00:20:03,960 Speaker 6: Good question. Listen, Governor Hope, only good one of the day, 426 00:20:04,280 --> 00:20:05,520 Speaker 6: stay with us. Yeah. 427 00:20:05,640 --> 00:20:10,119 Speaker 8: So so Governor Hokeel, after we were moving towards implementing 428 00:20:10,160 --> 00:20:12,440 Speaker 8: in June, decided that she wanted to take away the 429 00:20:12,440 --> 00:20:16,359 Speaker 8: sticker shock and so she, after a pause, knocked it down, 430 00:20:16,440 --> 00:20:19,320 Speaker 8: knocked the price down by forty percent, so instead of 431 00:20:19,359 --> 00:20:20,240 Speaker 8: fifteen bucks for. 432 00:20:20,640 --> 00:20:22,560 Speaker 4: Does she called you? Where did you learn about it? 433 00:20:22,600 --> 00:20:23,240 Speaker 4: She called? 434 00:20:23,480 --> 00:20:25,000 Speaker 6: She called, she called me. 435 00:20:25,400 --> 00:20:28,640 Speaker 8: It was shortly before she announced it, and it certainly 436 00:20:29,080 --> 00:20:31,119 Speaker 8: was a shock to the system for some of the 437 00:20:31,119 --> 00:20:32,800 Speaker 8: folks who have been working on this, but in the 438 00:20:32,920 --> 00:20:35,440 Speaker 8: end it has worked. What has done is it's message 439 00:20:35,480 --> 00:20:39,080 Speaker 8: to the public that we are looking at an easy implementation, 440 00:20:39,520 --> 00:20:42,600 Speaker 8: that she's worrying about affordability, but we're getting the benefits. 441 00:20:42,920 --> 00:20:46,040 Speaker 8: Tom that you said, what's how does it affect the MTA? 442 00:20:46,119 --> 00:20:46,919 Speaker 8: How does it affect me? 443 00:20:47,440 --> 00:20:47,840 Speaker 6: We will. 444 00:20:47,880 --> 00:20:50,320 Speaker 8: It will take us a little longer to raise the 445 00:20:50,640 --> 00:20:55,640 Speaker 8: statutorily required fifteen billion dollars, but we have enough work 446 00:20:55,680 --> 00:20:57,760 Speaker 8: going on that we can continue to make progress on 447 00:20:57,840 --> 00:21:00,600 Speaker 8: rebuilding the subway system. In the meantime, it's been a 448 00:21:00,640 --> 00:21:01,480 Speaker 8: net net positive. 449 00:21:01,840 --> 00:21:04,000 Speaker 5: We're going to be One of the intentions for congestion 450 00:21:04,040 --> 00:21:09,520 Speaker 5: pricing is to drive more of transit folks to the subways. 451 00:21:10,000 --> 00:21:11,159 Speaker 5: How about safety the subways? 452 00:21:11,160 --> 00:21:11,639 Speaker 6: Where are we there? 453 00:21:11,680 --> 00:21:13,640 Speaker 5: Because there's a you know, a concern is that you're 454 00:21:13,920 --> 00:21:17,240 Speaker 5: well well aware that post pandemic maybe not listen. 455 00:21:17,280 --> 00:21:20,840 Speaker 6: You know, the overall stats are positive. 456 00:21:20,840 --> 00:21:24,159 Speaker 8: We had last year we were actually twelve and a 457 00:21:24,200 --> 00:21:27,800 Speaker 8: half percent less crime than twenty nineteen, the last year 458 00:21:27,880 --> 00:21:30,080 Speaker 8: before COVID. But there's no question that some of these 459 00:21:30,160 --> 00:21:34,560 Speaker 8: high profile incidents, you know, terrible attacks, have gotten in 460 00:21:34,600 --> 00:21:37,720 Speaker 8: people's heads and made the whole system feel less safe, 461 00:21:37,960 --> 00:21:40,160 Speaker 8: and there's a little bit of disorder that's crept into 462 00:21:40,200 --> 00:21:42,840 Speaker 8: the public space since COVID. There's no question about it. 463 00:21:43,240 --> 00:21:45,880 Speaker 8: I say, the criminal justice system has to do its 464 00:21:45,960 --> 00:21:48,720 Speaker 8: job and make sure these people who do that kind 465 00:21:48,760 --> 00:21:51,080 Speaker 8: of stuff, most of them who have long rap sheets 466 00:21:51,280 --> 00:21:54,200 Speaker 8: are put away. There are very very few of these folks, 467 00:21:54,240 --> 00:21:56,720 Speaker 8: but they have an impact from people's sense of safety, 468 00:21:56,720 --> 00:21:58,800 Speaker 8: and we need to deal with them in a way 469 00:21:58,840 --> 00:21:59,879 Speaker 8: that protects the riders. 470 00:22:00,359 --> 00:22:03,360 Speaker 2: First time I went down the stairs on a Tokyo subway, Yeah, 471 00:22:03,480 --> 00:22:06,000 Speaker 2: there were the guard rails or the walls or whatever. 472 00:22:06,480 --> 00:22:08,840 Speaker 4: We put a man on the moon. This is New 473 00:22:08,920 --> 00:22:09,480 Speaker 4: York City. 474 00:22:09,720 --> 00:22:13,119 Speaker 2: You mentioned the shining light of La Guardia nineteen billion 475 00:22:13,160 --> 00:22:14,479 Speaker 2: on JFK as well. 476 00:22:14,840 --> 00:22:15,800 Speaker 4: Can't we put up. 477 00:22:15,720 --> 00:22:19,399 Speaker 2: Guard wheels guardrails quickly in our subways? 478 00:22:20,480 --> 00:22:23,840 Speaker 8: You're absolutely right. The quickly part is the one challenge. 479 00:22:24,080 --> 00:22:25,399 Speaker 8: I would say, we got well. 480 00:22:25,280 --> 00:22:27,480 Speaker 5: New York City quick like, We've put a million. 481 00:22:27,680 --> 00:22:30,040 Speaker 8: We put a billion dollars in our new capital program 482 00:22:30,080 --> 00:22:34,040 Speaker 8: since fair evasion and this whole phenomenon has definitely accelerated 483 00:22:34,040 --> 00:22:36,160 Speaker 8: post COVID. We put a billion dollars in our new 484 00:22:36,200 --> 00:22:38,760 Speaker 8: capital program for that. So we are going to start 485 00:22:38,840 --> 00:22:41,480 Speaker 8: to replace all these turnstiles which work when I was 486 00:22:41,520 --> 00:22:44,560 Speaker 8: a kid, but clearly aren't effective now for in the 487 00:22:44,600 --> 00:22:45,560 Speaker 8: era that we're living in. 488 00:22:45,760 --> 00:22:47,679 Speaker 6: We got to replace him. You're absolutely right, But are 489 00:22:47,760 --> 00:22:50,600 Speaker 6: we going to put in walls to protect people at 490 00:22:50,640 --> 00:22:52,200 Speaker 6: the edge of the subway? 491 00:22:52,400 --> 00:22:55,960 Speaker 2: Lisa Monteo and I are sitting at home with our offspring, 492 00:22:56,200 --> 00:22:57,760 Speaker 2: go and take the uber. 493 00:22:58,280 --> 00:22:59,879 Speaker 4: That's the reality. JOHNA. 494 00:23:00,080 --> 00:23:03,479 Speaker 8: Okay, so listen, there's we have started to put up 495 00:23:03,880 --> 00:23:07,760 Speaker 8: you know, barriers chop chop, which is really literally these 496 00:23:07,920 --> 00:23:12,280 Speaker 8: these little little half half height walls along the platforms, 497 00:23:12,280 --> 00:23:15,199 Speaker 8: and we're going to accelerate doing that. One complexity is 498 00:23:15,440 --> 00:23:18,040 Speaker 8: those super high tech barriers that you get in you know, 499 00:23:18,160 --> 00:23:21,920 Speaker 8: European train stations and the newer stuff literally are too 500 00:23:22,000 --> 00:23:24,280 Speaker 8: heavy for the platforms that our one hundred year old 501 00:23:24,280 --> 00:23:26,919 Speaker 8: system has, so we can't do that. But we're going 502 00:23:27,000 --> 00:23:30,360 Speaker 8: to start to accelerate these barriers so that anybody can 503 00:23:30,400 --> 00:23:33,320 Speaker 8: position themselves so they feel safe on a subway platform. 504 00:23:33,359 --> 00:23:34,800 Speaker 8: We don't want people to feel otherwise. 505 00:23:35,040 --> 00:23:38,399 Speaker 5: So I know, when conceiving of this plan here, there 506 00:23:38,400 --> 00:23:40,600 Speaker 5: are a lot of exceptions for different people who would 507 00:23:40,640 --> 00:23:45,280 Speaker 5: be exempt from this congestion pricing. For example, the Hampton 508 00:23:45,400 --> 00:23:50,000 Speaker 5: Jitney is exempt, yet personal firefighters personal vehicles to get 509 00:23:50,040 --> 00:23:53,160 Speaker 5: them into the firehouses are not. That seems kind of odd, 510 00:23:53,320 --> 00:23:54,920 Speaker 5: but I noticed trade offs everywhere. 511 00:23:55,040 --> 00:23:57,439 Speaker 8: Yeah, I mean the point is, well, there was across 512 00:23:57,440 --> 00:23:59,480 Speaker 8: the word. This was done by a panel that was studied. 513 00:23:59,720 --> 00:24:02,280 Speaker 8: There are one hundred and thirty separate requests for exemptions, 514 00:24:02,760 --> 00:24:04,560 Speaker 8: and what they said is what we're going to exempt 515 00:24:04,640 --> 00:24:07,600 Speaker 8: is low We're going to exempt disabled people. We're going 516 00:24:07,640 --> 00:24:10,439 Speaker 8: to give a huge discount to low income people, and 517 00:24:10,480 --> 00:24:12,560 Speaker 8: we're going to make sure that buses which are a 518 00:24:12,560 --> 00:24:16,840 Speaker 8: form of mass transit, whether they're operated by the MTR otherwise, 519 00:24:16,960 --> 00:24:20,320 Speaker 8: are exempt. That's where you get something like the Hampton Gitney. Now, 520 00:24:20,200 --> 00:24:23,600 Speaker 8: in fairness, Hamptonjitney has fifty people on it, and if 521 00:24:23,600 --> 00:24:25,720 Speaker 8: those people drove, it would take up a lot of rooms. 522 00:24:25,760 --> 00:24:29,960 Speaker 8: So it makes sense. We don't talk about personal vehicles. 523 00:24:30,920 --> 00:24:34,040 Speaker 8: We're not going to choose who is, you know, special. 524 00:24:35,400 --> 00:24:38,720 Speaker 8: The real goal here is to have people make rational choices. 525 00:24:38,760 --> 00:24:40,600 Speaker 8: If they want to get their employer to pay them 526 00:24:40,640 --> 00:24:43,879 Speaker 8: to drive in, that's fine, but that's not for the 527 00:24:43,920 --> 00:24:45,040 Speaker 8: government to decide. 528 00:24:45,359 --> 00:24:47,280 Speaker 6: The broad decision was what it was. 529 00:24:47,320 --> 00:24:50,240 Speaker 8: But let's you know, today is really a historic day, 530 00:24:50,280 --> 00:24:51,959 Speaker 8: and we ought to be focused on the fact that 531 00:24:52,040 --> 00:24:54,879 Speaker 8: New York is back to leading, that we're doing what 532 00:24:55,000 --> 00:24:58,159 Speaker 8: Meyer Blumberg did in the old days, which is New 533 00:24:58,200 --> 00:25:00,920 Speaker 8: York's a problem solved. We're in the problem solving business. 534 00:25:01,119 --> 00:25:05,080 Speaker 8: We're dealing with our problems and like government seems paralyzed 535 00:25:05,080 --> 00:25:07,159 Speaker 8: a lot of the United States. We are dealing with 536 00:25:07,200 --> 00:25:08,840 Speaker 8: the realities and what it takes to be a twenty 537 00:25:08,840 --> 00:25:09,640 Speaker 8: first century city. 538 00:25:09,760 --> 00:25:13,119 Speaker 2: Daniel Moran is writing this up and she's like, Okay, 539 00:25:13,200 --> 00:25:14,320 Speaker 2: we're leading the way. 540 00:25:15,040 --> 00:25:16,720 Speaker 4: What's the next city to do this? 541 00:25:17,000 --> 00:25:19,320 Speaker 6: You know, nation Why that's a good question. You know 542 00:25:19,359 --> 00:25:20,600 Speaker 6: they all doors. 543 00:25:20,280 --> 00:25:23,160 Speaker 2: Locked over there, Danielle says, you can't get out unless 544 00:25:23,200 --> 00:25:23,960 Speaker 2: you answer the quest. 545 00:25:24,040 --> 00:25:26,160 Speaker 8: Well, they all call me and they say and they 546 00:25:26,280 --> 00:25:28,399 Speaker 8: and they ask for information because they're all taking a 547 00:25:28,400 --> 00:25:32,040 Speaker 8: look at Boston. It could be because the key is 548 00:25:32,400 --> 00:25:35,720 Speaker 8: we are so lucky, because cities all over the United 549 00:25:35,760 --> 00:25:38,720 Speaker 8: States have traffic problems like crazy, and it's crushing their 550 00:25:38,760 --> 00:25:42,199 Speaker 8: economy and their development pattern and their appeal to employers. 551 00:25:42,640 --> 00:25:44,280 Speaker 6: But only New York. 552 00:25:44,160 --> 00:25:47,360 Speaker 8: Has this out of sight mass transit system. Maybe Boston, 553 00:25:47,440 --> 00:25:50,600 Speaker 8: maybe Washington, maybe Chicago, because they have the alternative. 554 00:25:50,880 --> 00:25:54,159 Speaker 2: I'm cutting you some slack here, and folks, let me 555 00:25:54,240 --> 00:25:55,919 Speaker 2: tell you, I'm not even part of this debate. 556 00:25:56,160 --> 00:25:59,600 Speaker 4: I was below fifty seventh Street once last year. Yeah, 557 00:26:00,400 --> 00:26:02,800 Speaker 4: I have no life. What I went to Brooklyn a 558 00:26:02,840 --> 00:26:03,560 Speaker 4: couple of years ago. 559 00:26:03,600 --> 00:26:04,320 Speaker 5: It's beautiful. 560 00:26:04,600 --> 00:26:07,000 Speaker 2: Come on over, I thought it was Brooklyn, Massachusetts, and 561 00:26:07,000 --> 00:26:08,480 Speaker 2: they said, no, it's Brooklyn, New York. 562 00:26:08,800 --> 00:26:09,080 Speaker 5: General. 563 00:26:09,200 --> 00:26:11,080 Speaker 4: Let me let me cut to the chase here in 564 00:26:11,119 --> 00:26:12,000 Speaker 4: the heart of the matter. 565 00:26:12,200 --> 00:26:17,040 Speaker 2: Somebody once explained to me that New York is not London. 566 00:26:17,240 --> 00:26:21,159 Speaker 2: We're not la You've got X number of bridges, x 567 00:26:21,280 --> 00:26:25,639 Speaker 2: number of tunnels. It's it's a challenge here like no 568 00:26:25,800 --> 00:26:29,119 Speaker 2: other challenge. Where's the bottleneck. 569 00:26:28,600 --> 00:26:30,840 Speaker 4: Going to be? With the congestion text? 570 00:26:31,160 --> 00:26:33,480 Speaker 8: You know, I think that the great thing is if 571 00:26:33,520 --> 00:26:37,240 Speaker 8: you reduce traffic in general, there's less chance of bottlenecks 572 00:26:37,240 --> 00:26:40,800 Speaker 8: across the board. That's the benefit that even the people 573 00:26:40,840 --> 00:26:44,240 Speaker 8: who have to drive or choose to drive, are going 574 00:26:44,240 --> 00:26:46,119 Speaker 8: to get a better experience so their time is not 575 00:26:46,200 --> 00:26:47,520 Speaker 8: wasted stuck in traffic. 576 00:26:47,800 --> 00:26:48,480 Speaker 6: That's the goal. 577 00:26:48,720 --> 00:26:50,639 Speaker 8: I don't know exactly where the bottle neck's going to be, 578 00:26:50,920 --> 00:26:53,600 Speaker 8: but the goal is to have fewer of them. 579 00:26:53,840 --> 00:26:56,639 Speaker 6: So we're Wall Street, we're global. Wall Street. 580 00:26:56,880 --> 00:26:59,080 Speaker 5: Talk to us about this bond that's going to be 581 00:26:59,400 --> 00:27:01,960 Speaker 5: issued a what is it? And when will you guys 582 00:27:02,040 --> 00:27:05,479 Speaker 5: issue this some bonds to raise capital to then invest 583 00:27:05,520 --> 00:27:06,800 Speaker 5: back into this good question. 584 00:27:06,920 --> 00:27:11,640 Speaker 8: So ourf CFO at the MTA, Kevin Willans ran Munifinance 585 00:27:11,720 --> 00:27:12,880 Speaker 8: at Goldman for many years. 586 00:27:14,320 --> 00:27:14,720 Speaker 6: Kevin Is. 587 00:27:15,880 --> 00:27:18,879 Speaker 8: When the governor dropped the toll by forty percent, he 588 00:27:18,960 --> 00:27:22,880 Speaker 8: took a hard look when that started to unfold at 589 00:27:22,920 --> 00:27:26,040 Speaker 8: whether we could still raise the money that the statute 590 00:27:26,080 --> 00:27:28,800 Speaker 8: that the law requires fifteen billion dollars to be raised 591 00:27:28,840 --> 00:27:31,600 Speaker 8: from the revenues. And the answer is yes, we can 592 00:27:31,640 --> 00:27:34,000 Speaker 8: do it. It will take slightly different structure, it will 593 00:27:34,040 --> 00:27:36,399 Speaker 8: take a different length of time, but we're going to 594 00:27:36,440 --> 00:27:40,520 Speaker 8: be able to do it, probably in multiple bond offerings 595 00:27:40,600 --> 00:27:42,920 Speaker 8: rather than a single one. Originally they planned a single 596 00:27:42,960 --> 00:27:45,800 Speaker 8: bond offering fifteen billion. Now it's going to probably take 597 00:27:45,840 --> 00:27:47,800 Speaker 8: a couple of years and a couple different offerings. 598 00:27:47,880 --> 00:27:50,160 Speaker 2: You've been more than jens of your time. I want 599 00:27:50,200 --> 00:27:53,119 Speaker 2: to talk about the reality, and I'm speaking for the 600 00:27:53,280 --> 00:27:56,760 Speaker 2: headquarters here the investment mister Bloomberg has made. I should 601 00:27:56,800 --> 00:28:00,159 Speaker 2: mention folks Mike Bloomberg the former mayor of New York 602 00:28:00,200 --> 00:28:03,240 Speaker 2: and he is, of course the owner of Bloomberg Radio, 603 00:28:03,280 --> 00:28:06,880 Speaker 2: Bloomberg Television, and I think does he sign your paycheck? 604 00:28:06,960 --> 00:28:09,800 Speaker 2: I think he says as well, Yeah, it's just simple. 605 00:28:10,000 --> 00:28:13,480 Speaker 2: We go up Third Avenue and it's ruined. I got 606 00:28:13,480 --> 00:28:16,520 Speaker 2: a bike lane, I got bus lanes. I got some 607 00:28:16,600 --> 00:28:19,880 Speaker 2: kind of parking in the middle. Basically, we've taken six 608 00:28:20,000 --> 00:28:23,760 Speaker 2: lane streets five lane streets down to two and you're 609 00:28:23,840 --> 00:28:26,399 Speaker 2: living it as well. I got an Amazon truck on 610 00:28:26,400 --> 00:28:29,120 Speaker 2: the right and a FedEx truck on the left. Now 611 00:28:29,160 --> 00:28:31,520 Speaker 2: everybody's going up Park Avenue because they can't get up 612 00:28:31,560 --> 00:28:32,240 Speaker 2: Third Avenue. 613 00:28:32,400 --> 00:28:34,640 Speaker 4: That's just my little soap opera. 614 00:28:34,840 --> 00:28:38,480 Speaker 2: How do we get rid of the parking issue? Peter 615 00:28:38,560 --> 00:28:41,160 Speaker 2: Coyt The New York Times has been brilliant on this. 616 00:28:41,640 --> 00:28:45,680 Speaker 2: How do we change parking so Third Avenue is in 617 00:28:45,720 --> 00:28:46,360 Speaker 2: a driveway? 618 00:28:46,520 --> 00:28:49,000 Speaker 8: Well, I mean, listen, we got these are issues that 619 00:28:49,040 --> 00:28:50,520 Speaker 8: the City of New York is going to have to 620 00:28:50,560 --> 00:28:53,560 Speaker 8: wrestle with. You talked about how good your experience was 621 00:28:53,600 --> 00:28:56,920 Speaker 8: in Paris, and Paris has done a lot to make 622 00:28:56,960 --> 00:29:00,320 Speaker 8: it easier for bikes and pedestrians and to take away 623 00:29:00,320 --> 00:29:02,560 Speaker 8: a little room for cars. That is part of the 624 00:29:02,600 --> 00:29:05,840 Speaker 8: strategy that's been effectively followed. But I'll say this when 625 00:29:05,880 --> 00:29:08,880 Speaker 8: we thankfully the city is getting rid of dining sheds, 626 00:29:09,200 --> 00:29:13,760 Speaker 8: which took up a Yeah, getting rid of dining sheds. 627 00:29:13,880 --> 00:29:16,440 Speaker 8: You know, we love our restaurants. They're rocking and soccing 628 00:29:16,560 --> 00:29:18,960 Speaker 8: after COVID, But we don't need to give out free 629 00:29:18,960 --> 00:29:21,520 Speaker 8: real estate in the middle of the street uh anymore 630 00:29:21,800 --> 00:29:26,680 Speaker 8: because people can't go indoors. So so that is one factor. 631 00:29:26,960 --> 00:29:30,040 Speaker 8: But I'm for more more uh by. You know, the 632 00:29:30,040 --> 00:29:32,400 Speaker 8: bike lanes and certainly the bus lanes. If we can 633 00:29:32,440 --> 00:29:35,480 Speaker 8: put fifty people on a bus who would otherwise be 634 00:29:35,560 --> 00:29:38,960 Speaker 8: driving fifty individual cars, it's a net positive for the city, 635 00:29:39,000 --> 00:29:41,680 Speaker 8: even for the drivers. So we got to keep focused 636 00:29:41,720 --> 00:29:44,040 Speaker 8: on on a street scape that works. But you know, 637 00:29:44,520 --> 00:29:47,120 Speaker 8: it's still it's still it's still a work in progress. Tom, 638 00:29:47,160 --> 00:29:49,520 Speaker 8: We're still learning and coming out of COVID with the 639 00:29:49,560 --> 00:29:51,959 Speaker 8: dining sheds, I think we're we got to make some progress. 640 00:29:52,000 --> 00:29:54,920 Speaker 4: Sweeting demands. We got breaking news here. Can you solve 641 00:29:54,960 --> 00:29:56,360 Speaker 4: the New York Giants and the Jets? 642 00:29:56,480 --> 00:29:57,960 Speaker 5: Can you like a Giant? 643 00:29:58,080 --> 00:30:01,480 Speaker 8: I'm a Giants fan and I stopped paying attention about 644 00:30:01,800 --> 00:30:02,440 Speaker 8: two months ago. 645 00:30:02,520 --> 00:30:04,800 Speaker 5: Well, there's some breaking news here. They decided this morning 646 00:30:04,800 --> 00:30:07,080 Speaker 5: they're going to keep the GM, keep the coach, Joe 647 00:30:07,080 --> 00:30:10,240 Speaker 5: Shane's GM, Brian Dabolos coach. They're going to be retained. 648 00:30:10,480 --> 00:30:13,760 Speaker 4: Genna, thank you so much. Jenna leaves the MT. 649 00:30:18,880 --> 00:30:22,800 Speaker 1: This is the Bloomberg Surveillance Podcast. Listen live each weekday 650 00:30:22,840 --> 00:30:26,120 Speaker 1: starting at seven am Eastern on Applecarplay and Android Auto 651 00:30:26,240 --> 00:30:29,080 Speaker 1: with the Bloomberg Business app. You can also watch us 652 00:30:29,120 --> 00:30:32,480 Speaker 1: live every weekday on YouTube and always on the Bloomberg 653 00:30:32,560 --> 00:30:33,680 Speaker 1: terminal you day. 654 00:30:33,760 --> 00:30:37,040 Speaker 2: Look at the front page is Lisa mateo moment, Lisa, 655 00:30:37,080 --> 00:30:37,600 Speaker 2: what do you have? 656 00:30:37,840 --> 00:30:38,120 Speaker 5: Okay? 657 00:30:38,120 --> 00:30:40,800 Speaker 9: This is a new Wall Street Journal analysis of test scores. 658 00:30:41,120 --> 00:30:42,000 Speaker 5: This is really interesting. 659 00:30:42,000 --> 00:30:45,880 Speaker 9: It shows girls have lost ground in reading, math, and science, 660 00:30:45,960 --> 00:30:48,440 Speaker 9: and people are really concerned about it. This is since 661 00:30:48,480 --> 00:30:51,400 Speaker 9: twenty nineteen, test scores have dropped sharply. They're calling that 662 00:30:51,480 --> 00:30:54,320 Speaker 9: the pandemic learning loss. Boys' scores have also dropped, but 663 00:30:54,360 --> 00:30:57,960 Speaker 9: the girls decline is worse. So the reason why they're 664 00:30:57,960 --> 00:31:01,200 Speaker 9: saying it is because arise in behavior patterns during the pandemic. 665 00:31:01,480 --> 00:31:03,760 Speaker 9: It forced teachers to pay more attention to the boys 666 00:31:03,960 --> 00:31:07,040 Speaker 9: because they tended to act out more in class. And 667 00:31:07,120 --> 00:31:09,200 Speaker 9: then during and after the pandemic, a lot of the 668 00:31:09,240 --> 00:31:12,640 Speaker 9: girls took on those caregiving household responsibilities, so it took 669 00:31:12,680 --> 00:31:14,600 Speaker 9: their focus away from school. 670 00:31:14,920 --> 00:31:17,320 Speaker 5: So I just thought it was a just I mean, 671 00:31:17,840 --> 00:31:20,320 Speaker 5: it's gonna be years, yeah, years out. That was oh 672 00:31:20,400 --> 00:31:23,040 Speaker 5: sure that we learned what the real impact is going 673 00:31:23,040 --> 00:31:23,280 Speaker 5: to be. 674 00:31:23,360 --> 00:31:26,840 Speaker 2: I got this wrong, and I learned about this from 675 00:31:26,840 --> 00:31:32,920 Speaker 2: Bloomberg employees, the anecdotal evidence of our twenty one thousand employees. 676 00:31:33,160 --> 00:31:39,160 Speaker 2: I learned the pandemic and our children's education just changed that. 677 00:31:39,920 --> 00:31:40,800 Speaker 4: What else do you I. 678 00:31:40,720 --> 00:31:41,320 Speaker 3: Totally see it. 679 00:31:41,840 --> 00:31:45,440 Speaker 9: The gambling industry is using a lot of artificial intelligence 680 00:31:45,760 --> 00:31:48,760 Speaker 9: to get more money from Americans. So some of the 681 00:31:48,800 --> 00:31:52,520 Speaker 9: ways they're doing it startups their profiling gamblers, so they're 682 00:31:52,560 --> 00:31:56,400 Speaker 9: feeding them content games personalized to what they like, convincing 683 00:31:56,400 --> 00:31:59,760 Speaker 9: them to stay longer, make bigger bets. They're using these 684 00:31:59,800 --> 00:32:03,000 Speaker 9: large language models so generate a lot of things autoated summaries. 685 00:32:03,720 --> 00:32:07,040 Speaker 9: And then even you get to the physical casinos using AI, 686 00:32:07,200 --> 00:32:10,320 Speaker 9: because they're using machine learning to optimize where they place 687 00:32:10,360 --> 00:32:12,760 Speaker 9: the slot machines, because even that kind of matters. 688 00:32:12,840 --> 00:32:14,720 Speaker 5: It does I mean, you're walking in and out of 689 00:32:14,760 --> 00:32:18,200 Speaker 5: the casino floor slot machines for every ingress and egress. 690 00:32:18,240 --> 00:32:20,959 Speaker 5: I learned that from doing the casino investing. 691 00:32:21,080 --> 00:32:26,040 Speaker 2: Do you think AI will do to this surgeon NFL football, 692 00:32:26,160 --> 00:32:28,720 Speaker 2: which is a surgeon betting? Yeah, I mean they got 693 00:32:28,720 --> 00:32:31,960 Speaker 2: to be used in it to learn every single. 694 00:32:31,680 --> 00:32:34,640 Speaker 4: Thing you need to do to win money on the 695 00:32:34,680 --> 00:32:36,960 Speaker 4: patriots because you knew they were going to beat the bills. 696 00:32:37,000 --> 00:32:37,240 Speaker 6: Yep. 697 00:32:37,320 --> 00:32:42,160 Speaker 5: And one tangible practical implementation of AI is advertising because 698 00:32:42,200 --> 00:32:45,280 Speaker 5: they can figure out better target who you are and 699 00:32:45,280 --> 00:32:46,760 Speaker 5: what you want and what adds will work for you. 700 00:32:46,920 --> 00:32:49,080 Speaker 5: That's happening today from Google and Facebook. 701 00:32:49,160 --> 00:32:51,239 Speaker 2: Lisa Manitaeo, thank you so much. Good to have that 702 00:32:52,360 --> 00:32:55,400 Speaker 2: for us here the newspapers with Lisa Wantay, and we'll 703 00:32:55,440 --> 00:32:58,120 Speaker 2: do much more of this into the week and into 704 00:32:58,480 --> 00:33:00,600 Speaker 2: today as. 705 00:33:00,560 --> 00:33:05,400 Speaker 1: This is the Bloomberg Surveillance podcast, available on Apple, Spotify, 706 00:33:05,520 --> 00:33:09,800 Speaker 1: and anywhere else you get your podcasts. Listen live each weekday, 707 00:33:09,920 --> 00:33:13,400 Speaker 1: seven to ten am Eastern on Bloomberg dot com, the 708 00:33:13,480 --> 00:33:17,520 Speaker 1: iHeartRadio app, tune In, and the Bloomberg Business app. You 709 00:33:17,560 --> 00:33:20,920 Speaker 1: can also watch us live every weekday on YouTube and 710 00:33:21,120 --> 00:33:22,840 Speaker 1: always on the Bloomberg terminal.