1 00:00:02,640 --> 00:00:05,320 Speaker 1: Welcome to the Bloomberg Penel podcast. I'm Paul swing you 2 00:00:05,360 --> 00:00:07,680 Speaker 1: along with my co host Lisa Brahma Waits. Each day 3 00:00:07,720 --> 00:00:10,240 Speaker 1: we bring you the most noteworthy and useful interviews for 4 00:00:10,280 --> 00:00:12,520 Speaker 1: you and your money, whether at the grocery store or 5 00:00:12,560 --> 00:00:15,480 Speaker 1: the trading floor. Find a Bloomberg Penl podcast on Apple 6 00:00:15,520 --> 00:00:17,960 Speaker 1: podcast or wherever you listen to podcasts, as well as 7 00:00:17,960 --> 00:00:22,480 Speaker 1: at Bloomberg dot com. It's a big week for retail 8 00:00:22,560 --> 00:00:25,560 Speaker 1: We did get earnings from Macy's today, We're expecting j C. 9 00:00:25,760 --> 00:00:29,360 Speaker 1: Penny as well as Walmart and Target all later in 10 00:00:29,760 --> 00:00:32,199 Speaker 1: the week. And of course these earnings come with a 11 00:00:32,320 --> 00:00:36,600 Speaker 1: backdrop of potential tariffs. President Trump did delay some of 12 00:00:36,600 --> 00:00:39,640 Speaker 1: the additional tariffs they p planned to impose on goods 13 00:00:39,680 --> 00:00:44,200 Speaker 1: from China to December from September, but still the mood 14 00:00:44,479 --> 00:00:48,880 Speaker 1: is highly wary among retailers. Joining us now as Rick Helfenvine, 15 00:00:48,960 --> 00:00:52,320 Speaker 1: he's president and CEO of American Apparel and Footwear Association. 16 00:00:52,360 --> 00:00:56,440 Speaker 1: He's joining us from Las Vegas during a convention there, 17 00:00:56,560 --> 00:00:59,160 Speaker 1: and Rick, thanks for being with us. Let's start with 18 00:00:59,200 --> 00:01:02,520 Speaker 1: the convention with the with the mood that you're hearing 19 00:01:02,840 --> 00:01:07,520 Speaker 1: from the retailers in attendance today, Well, storm clouds over 20 00:01:07,520 --> 00:01:10,480 Speaker 1: the port bow. I'm telling you, I'm here in Las Vegas. 21 00:01:11,160 --> 00:01:15,520 Speaker 1: Ninety thousand people come to our semi annual industry trade 22 00:01:15,560 --> 00:01:19,920 Speaker 1: show called the Magic Show, and they're buying and they're crying. 23 00:01:20,120 --> 00:01:23,959 Speaker 1: Nobody is happy. Um. Yesterday, early in the morning, we 24 00:01:24,000 --> 00:01:28,440 Speaker 1: thought we had some terrific news from the administration. We 25 00:01:28,520 --> 00:01:33,120 Speaker 1: thought the Grin should finally spirit our Christmas season. But 26 00:01:33,319 --> 00:01:36,000 Speaker 1: later in the day, as the lists they called him 27 00:01:36,040 --> 00:01:39,120 Speaker 1: for A and four be started to pop out, we 28 00:01:39,160 --> 00:01:42,440 Speaker 1: realized we really weren't in much better shape. Seventies seven 29 00:01:42,520 --> 00:01:45,959 Speaker 1: percent approximately of the goods that we bring in for 30 00:01:46,000 --> 00:01:49,360 Speaker 1: the holiday season will be hit by tariffs I have 31 00:01:50,520 --> 00:01:55,840 Speaker 1: on September one. It's not a pretty picture. People are scrambling. 32 00:01:55,880 --> 00:01:59,640 Speaker 1: And the reason least that it affects our industry so much, 33 00:01:59,760 --> 00:02:05,080 Speaker 1: is it quite simply fortable of parallel of or We're 34 00:02:05,080 --> 00:02:08,920 Speaker 1: eighty four percentable accessors, including backpacks and hand babs come 35 00:02:09,200 --> 00:02:11,680 Speaker 1: from China and we don't really have a place to 36 00:02:11,760 --> 00:02:15,040 Speaker 1: move it. So someone's got to pay these tariffs. We've 37 00:02:15,080 --> 00:02:18,760 Speaker 1: been telling the administration over and over and over again, 38 00:02:18,800 --> 00:02:24,040 Speaker 1: please don't do this, Please don't hit the consumer so 39 00:02:24,440 --> 00:02:27,320 Speaker 1: the question is will it hit the consumer, will it 40 00:02:27,400 --> 00:02:29,919 Speaker 1: hit the retailers? How much will we pass along to 41 00:02:30,080 --> 00:02:34,240 Speaker 1: consumers versus sucked up by the retailers. Well, you know 42 00:02:34,720 --> 00:02:36,720 Speaker 1: a lot of smart people in our industry and I 43 00:02:36,960 --> 00:02:41,480 Speaker 1: speak to them regularly. No, no tariff is a good 44 00:02:41,480 --> 00:02:47,840 Speaker 1: tariff ten percent? You know, maybe it's survivable, but is not. 45 00:02:48,120 --> 00:02:51,280 Speaker 1: And every time the President has said ten percent, it 46 00:02:51,360 --> 00:02:56,080 Speaker 1: goes to So we're anticipating the worst, not the best. 47 00:02:56,680 --> 00:02:59,480 Speaker 1: We'll do the best thing that we possibly can to 48 00:03:00,320 --> 00:03:04,360 Speaker 1: you know, avoid earnings compression. But you know what, the 49 00:03:04,440 --> 00:03:07,960 Speaker 1: end results gonna be loosing. Honestly, Prices are gonna go up, 50 00:03:08,000 --> 00:03:10,080 Speaker 1: sales are going to go down. Jobs are gonna get lost. 51 00:03:10,120 --> 00:03:12,520 Speaker 1: It's not going to be a pretty time. It's gonna 52 00:03:12,560 --> 00:03:17,760 Speaker 1: be retail ugly for our industry. That's what's unfortunately gonna happen. 53 00:03:18,080 --> 00:03:21,160 Speaker 1: And we told them, we told them, we're telling them. 54 00:03:21,360 --> 00:03:23,919 Speaker 1: Nobody's listening, and you know, you don't want to hear 55 00:03:23,960 --> 00:03:30,440 Speaker 1: something really sad um. Approximately of all newborn, infant and 56 00:03:30,440 --> 00:03:33,600 Speaker 1: todblet goods sold in the United States is ten dollars 57 00:03:33,639 --> 00:03:36,000 Speaker 1: or less, and they're gonna get hit with a tariff 58 00:03:36,400 --> 00:03:40,520 Speaker 1: September one percent. What is ten percent due to ten dollars? 59 00:03:40,680 --> 00:03:45,200 Speaker 1: I mean, think about what we're doing where they exempted 60 00:03:45,320 --> 00:03:49,240 Speaker 1: car seats but not children's clothes. I mean crazy stuff. 61 00:03:49,360 --> 00:03:51,960 Speaker 1: I will say that one important thing for me when 62 00:03:52,000 --> 00:03:55,040 Speaker 1: my child children were babies was to buy those ten 63 00:03:55,120 --> 00:03:57,240 Speaker 1: packs of ones Ease and then be able to if 64 00:03:57,280 --> 00:04:00,400 Speaker 1: they if they had an issue, just simply throw it 65 00:04:00,480 --> 00:04:02,240 Speaker 1: out that having to worry about it because it was 66 00:04:02,320 --> 00:04:04,720 Speaker 1: five dollars for ten onesies or whatever else. But Rick, 67 00:04:04,800 --> 00:04:06,280 Speaker 1: you know, I want to I want to talk into 68 00:04:06,320 --> 00:04:09,920 Speaker 1: all seriousness looking forward at some of the retailers and 69 00:04:10,000 --> 00:04:12,360 Speaker 1: how they're adapting to this scenario. Some people would push 70 00:04:12,400 --> 00:04:15,119 Speaker 1: back and say, why is so much of the apparel 71 00:04:15,720 --> 00:04:20,120 Speaker 1: manufactured over in China? Why can't the supply chain be moved? Well, 72 00:04:20,200 --> 00:04:24,200 Speaker 1: you know what, our retail consumer for the last several years, 73 00:04:24,520 --> 00:04:28,920 Speaker 1: particularly the millennial customer, is very conscious about product quality, 74 00:04:29,200 --> 00:04:33,960 Speaker 1: product safety, um sustainability, environment, workers, right to human rights. 75 00:04:34,640 --> 00:04:36,880 Speaker 1: And we've been able to do that in China and 76 00:04:37,080 --> 00:04:40,479 Speaker 1: do it effectively, whereas when we go outside of China 77 00:04:40,520 --> 00:04:45,160 Speaker 1: it becomes a much more difficult gold to attain. The 78 00:04:45,360 --> 00:04:49,720 Speaker 1: Chinese have been extremely efficient to work with so they 79 00:04:50,480 --> 00:04:54,360 Speaker 1: really generally meet the high expectations of the American market. 80 00:04:54,480 --> 00:04:58,119 Speaker 1: So what's the administration telling us? They're telling us point 81 00:04:58,160 --> 00:05:02,480 Speaker 1: blank get out of China. So where are we gonna go? 82 00:05:02,839 --> 00:05:05,720 Speaker 1: You know? Number two places Vietnam. The presidents threatened them 83 00:05:05,760 --> 00:05:09,080 Speaker 1: with tariffs. Number three is India. He's threatened them. We 84 00:05:09,200 --> 00:05:13,320 Speaker 1: don't even have a second choice. So, um, we're in 85 00:05:13,360 --> 00:05:15,960 Speaker 1: a tough spot. We're gonna we're gonna work through it 86 00:05:16,040 --> 00:05:18,840 Speaker 1: at ten percent. If it goes to at least, I 87 00:05:18,920 --> 00:05:21,040 Speaker 1: don't know what's going to happen. So Rick, it's been 88 00:05:21,040 --> 00:05:23,479 Speaker 1: a pretty gloomy Wednesday. A lot of people talking about 89 00:05:23,560 --> 00:05:26,560 Speaker 1: the worst case scenarios. You're definitely piled on there. But 90 00:05:26,680 --> 00:05:29,720 Speaker 1: you are in Vegas and you're at this huge trade show. 91 00:05:30,000 --> 00:05:35,680 Speaker 1: Anything getting excited today? Um? Yeah, I mean it's funny. 92 00:05:36,960 --> 00:05:40,320 Speaker 1: It's funny. I'm winning hand. Um, it's positive. There's a 93 00:05:40,360 --> 00:05:42,120 Speaker 1: lot of people, here's a lot of activities, a lot 94 00:05:42,160 --> 00:05:45,400 Speaker 1: of buying going on. On the other hand, people are worried. So, 95 00:05:45,640 --> 00:05:49,679 Speaker 1: you know, the economy finally got good, We're finally getting 96 00:05:49,760 --> 00:05:51,719 Speaker 1: to where we're supposed to be, but you know, retail 97 00:05:51,720 --> 00:05:54,960 Speaker 1: has been challenged. Leasa for the last couple of years 98 00:05:55,000 --> 00:05:57,160 Speaker 1: ago back to two oh one seven, we had more 99 00:05:57,279 --> 00:06:00,880 Speaker 1: bankruptcies than than two o eight. Uh. And then too, 100 00:06:00,920 --> 00:06:02,480 Speaker 1: oh wait, you go to two o one eight, we 101 00:06:02,600 --> 00:06:05,600 Speaker 1: lost over a million square foot of retail in this 102 00:06:05,760 --> 00:06:08,600 Speaker 1: year to oh one nine. The first four months of 103 00:06:08,960 --> 00:06:12,320 Speaker 1: the year, we had more announced store closings than all 104 00:06:12,400 --> 00:06:15,840 Speaker 1: of the last year. So retail businesses a struggle. And 105 00:06:15,960 --> 00:06:18,240 Speaker 1: then you you, you know, look as a as a 106 00:06:18,440 --> 00:06:22,600 Speaker 1: bell weather for the economy, and you know, two thirds 107 00:06:22,640 --> 00:06:25,200 Speaker 1: of our economy is based on the consumer. Ten percent 108 00:06:25,279 --> 00:06:29,480 Speaker 1: of the jobs are in retail. We keep telling the administration, hey, great, 109 00:06:29,560 --> 00:06:32,520 Speaker 1: you're talking to China. That's a good thing, but stay 110 00:06:32,600 --> 00:06:35,120 Speaker 1: away from the consumer because we're the ones driving the 111 00:06:35,200 --> 00:06:39,800 Speaker 1: economy and they we just worry the administration's getting bad advice. 112 00:06:40,400 --> 00:06:42,320 Speaker 1: Rick helfan Bin, thank you so much for being with us. 113 00:06:42,400 --> 00:06:45,440 Speaker 1: Have fun in Las Vegas. It sounds like perhaps another 114 00:06:45,560 --> 00:06:48,120 Speaker 1: another go at the slot machines. Rick Helvin bine At, 115 00:06:48,160 --> 00:06:51,240 Speaker 1: President CEO of American Apparel and Footwall Association, phoning in 116 00:06:51,360 --> 00:07:06,560 Speaker 1: from Vegas. Thirty year yields in the US currently two 117 00:07:06,720 --> 00:07:11,520 Speaker 1: point oh four percent, the lowest on record. Tumbling in 118 00:07:11,640 --> 00:07:14,520 Speaker 1: the wake of fears of a recession of a global 119 00:07:14,680 --> 00:07:18,920 Speaker 1: turndown as we do get weaker than expected manufacturing data 120 00:07:19,240 --> 00:07:22,960 Speaker 1: out of China as well as the German economy shrinking 121 00:07:23,040 --> 00:07:25,760 Speaker 1: in the second quarter. Joining us now Axel Mark, President 122 00:07:25,800 --> 00:07:29,320 Speaker 1: and chief investment officer at MERK Investments, coming to us 123 00:07:29,400 --> 00:07:31,840 Speaker 1: from San Francisco. Axel thank you so much for being 124 00:07:31,920 --> 00:07:33,600 Speaker 1: with us. What do you make of these thirty year 125 00:07:33,640 --> 00:07:37,760 Speaker 1: yields today? Great to be with you. Well, as you 126 00:07:37,880 --> 00:07:41,760 Speaker 1: point out, they do reflect fears of a global slowdown. Um, 127 00:07:42,240 --> 00:07:45,000 Speaker 1: the the biggest sue I have with all this coverage 128 00:07:45,040 --> 00:07:48,040 Speaker 1: of the markets is that all the issues you're mentioning 129 00:07:48,200 --> 00:07:50,440 Speaker 1: is are not issues the fit can fix. The fit 130 00:07:50,520 --> 00:07:53,560 Speaker 1: cannot fix China, the fit cannot fix Germany, the fit 131 00:07:53,880 --> 00:07:58,040 Speaker 1: cannot fix the trade war. And financial conditions are super easy, 132 00:07:58,280 --> 00:08:01,000 Speaker 1: and so rate cuts I'm not the solution. The reason 133 00:08:01,200 --> 00:08:04,240 Speaker 1: these long term rates are low is because obviously when 134 00:08:04,320 --> 00:08:08,200 Speaker 1: you have a global trade war, the business sentiment is declining, 135 00:08:08,400 --> 00:08:11,000 Speaker 1: and and yes, you're going to invest less when those 136 00:08:11,040 --> 00:08:14,760 Speaker 1: sort of tensions are about, but you you're giving it 137 00:08:14,840 --> 00:08:16,680 Speaker 1: the wrong medicine if you call for a right cut 138 00:08:16,720 --> 00:08:19,080 Speaker 1: in the sort of environment. So if the FED can't 139 00:08:19,120 --> 00:08:24,560 Speaker 1: do anything. Then are people not pessimistic enough? Um? Well 140 00:08:25,080 --> 00:08:28,320 Speaker 1: are they? The question is what sort of pessimistm is there? Right? 141 00:08:28,360 --> 00:08:30,920 Speaker 1: The U S economy is a fairly closed economy, um. 142 00:08:30,960 --> 00:08:34,000 Speaker 1: The and if in many ways it's astounding how well 143 00:08:34,040 --> 00:08:36,880 Speaker 1: the US economy has held up in light of all 144 00:08:36,920 --> 00:08:39,079 Speaker 1: of this, Right, it's not. It's not a surprise that 145 00:08:39,200 --> 00:08:43,200 Speaker 1: global businesses um face some headwinds. But consumers have been 146 00:08:43,240 --> 00:08:47,200 Speaker 1: doing very well. Um. Indeed, as I may remind people, 147 00:08:47,360 --> 00:08:50,839 Speaker 1: the unemployment rate is near a record low. Right. And 148 00:08:51,480 --> 00:08:53,760 Speaker 1: also the the sort of challenges that we're facing. A 149 00:08:53,920 --> 00:08:57,040 Speaker 1: tweet dependent tomorrow, the President could come out with a 150 00:08:57,040 --> 00:08:59,640 Speaker 1: tweet and saying everything is great on the trade front, um. 151 00:08:59,800 --> 00:09:03,480 Speaker 1: And then what then we're faced with potentially overheating economy. 152 00:09:03,720 --> 00:09:06,560 Speaker 1: And here we are talking about the recession because maybe 153 00:09:06,640 --> 00:09:08,600 Speaker 1: maybe somewhat terrors are going to be imposed. Now. What's 154 00:09:08,640 --> 00:09:12,360 Speaker 1: happening is, of course, um, the inventories are being jolted 155 00:09:12,400 --> 00:09:15,040 Speaker 1: around as people are holding things, and then maybe investments 156 00:09:15,080 --> 00:09:17,559 Speaker 1: don't take place because of the uncertainty. So clearly that's 157 00:09:17,600 --> 00:09:20,520 Speaker 1: the headwind. But again the FIT can't fix that. And 158 00:09:20,840 --> 00:09:22,880 Speaker 1: that's also why the yield curve is not inverting the 159 00:09:22,960 --> 00:09:26,120 Speaker 1: way historically inverts. Normally you would have the three year 160 00:09:26,160 --> 00:09:28,280 Speaker 1: ten year in word and then gradually going from the 161 00:09:28,400 --> 00:09:30,520 Speaker 1: kind of the three month tenure. This way, it's going 162 00:09:30,520 --> 00:09:33,439 Speaker 1: the other way around. So we're imposing their recession the 163 00:09:33,480 --> 00:09:35,800 Speaker 1: other way around around the FED tightening because of an 164 00:09:35,840 --> 00:09:40,480 Speaker 1: overheating economy. It's the President inducing a slowdown with the 165 00:09:40,520 --> 00:09:43,319 Speaker 1: tweets and and the trade tensions. And this is not 166 00:09:43,559 --> 00:09:46,599 Speaker 1: this You don't need the same sort of cure to 167 00:09:46,720 --> 00:09:50,000 Speaker 1: the disease because the disease is different. So I'm trying 168 00:09:50,040 --> 00:09:51,839 Speaker 1: to put together a lot of what you're saying, and 169 00:09:52,400 --> 00:09:55,160 Speaker 1: it's interesting, it's sort of a controversial issue. You're actually 170 00:09:55,520 --> 00:09:58,400 Speaker 1: making an argument that the the U. S. Economy is 171 00:09:58,520 --> 00:10:01,559 Speaker 1: closer to overheating then many people think, and that the 172 00:10:01,640 --> 00:10:03,959 Speaker 1: FED should really respond to the economic data. That just 173 00:10:04,080 --> 00:10:07,439 Speaker 1: isn't that that bad at this point? What are you 174 00:10:07,520 --> 00:10:11,000 Speaker 1: looking at to indicate that we're closer to an overheating 175 00:10:11,040 --> 00:10:13,400 Speaker 1: than anyone else who I speak to seem to think. 176 00:10:14,240 --> 00:10:16,959 Speaker 1: I'm not saying this is the baseline scenario, but it 177 00:10:17,120 --> 00:10:20,199 Speaker 1: is a risk not to be ignored. Right um, And 178 00:10:20,480 --> 00:10:23,439 Speaker 1: and absolutely, the the the inversion of the yelk cuve 179 00:10:23,600 --> 00:10:26,800 Speaker 1: is but one indicator that there's a slowdown. There's clearly 180 00:10:26,840 --> 00:10:31,719 Speaker 1: global headwinds. But um, the difference I make is that 181 00:10:32,120 --> 00:10:34,920 Speaker 1: we do have an election coming next year. The president 182 00:10:35,120 --> 00:10:37,520 Speaker 1: will want to be re elected just like any president 183 00:10:37,600 --> 00:10:39,240 Speaker 1: perfo him as well, so he wants to have a 184 00:10:39,320 --> 00:10:42,120 Speaker 1: strong economy, and so he has every incentive in the 185 00:10:42,200 --> 00:10:45,520 Speaker 1: world to reduce those straight tensions which I saw yesterday. Right, 186 00:10:45,559 --> 00:10:47,800 Speaker 1: you can take some of these things off again very quickly. 187 00:10:48,000 --> 00:10:50,480 Speaker 1: Questions how much damage will have been caused in the 188 00:10:50,559 --> 00:10:52,920 Speaker 1: interim and and and what we can do about it. 189 00:10:53,320 --> 00:10:55,880 Speaker 1: But the feder Reserve, in my view, would be very 190 00:10:55,920 --> 00:10:59,439 Speaker 1: well served to to be data dependent and patient rather 191 00:10:59,520 --> 00:11:02,520 Speaker 1: than be allowing political development. And nobody knows what the 192 00:11:02,559 --> 00:11:05,680 Speaker 1: heck that even means. Instead, it's egging on the president 193 00:11:05,920 --> 00:11:07,880 Speaker 1: to to escalate the trade war, and he did it 194 00:11:07,960 --> 00:11:10,360 Speaker 1: the day after that was said. And so my view 195 00:11:10,520 --> 00:11:12,439 Speaker 1: is that if the FED just took the long view 196 00:11:12,480 --> 00:11:15,400 Speaker 1: on this and took a deep breath, Um, yeah, maybe 197 00:11:15,480 --> 00:11:17,760 Speaker 1: the s MP would plunge more, But maybe that would 198 00:11:17,760 --> 00:11:20,120 Speaker 1: send a signal to the White House and instead of 199 00:11:20,200 --> 00:11:22,760 Speaker 1: the FED becoming a tool of the president. They suddenly 200 00:11:22,760 --> 00:11:25,359 Speaker 1: don't want to become a tool. But Powell is exactly 201 00:11:25,480 --> 00:11:28,440 Speaker 1: doing what what the President wants and and is egging 202 00:11:28,520 --> 00:11:31,480 Speaker 1: him on in many ways. Axcel, just real quick here, 203 00:11:31,800 --> 00:11:34,319 Speaker 1: what would you have to see to change your view 204 00:11:34,400 --> 00:11:36,880 Speaker 1: and say, you know what, markets are right? The President 205 00:11:37,000 --> 00:11:40,400 Speaker 1: is right, the Fed should cut rates well. Financial conditions 206 00:11:40,440 --> 00:11:43,200 Speaker 1: need to deteriorate. Financial conditions is not the VIX index. 207 00:11:43,280 --> 00:11:46,559 Speaker 1: The financial conditions is. And look at the financial the 208 00:11:46,880 --> 00:11:49,920 Speaker 1: Chicago Fed Financial Conditions Index rather than most of the 209 00:11:49,960 --> 00:11:51,920 Speaker 1: other ones that have too much weight on the VIX. 210 00:11:52,400 --> 00:11:55,120 Speaker 1: You need to have a deterioration in the transmission channel. 211 00:11:55,240 --> 00:11:57,400 Speaker 1: That is what the FEED should look at. Access to 212 00:11:57,480 --> 00:11:59,640 Speaker 1: credit needs to become more difficult. You don't need to 213 00:11:59,679 --> 00:12:01,800 Speaker 1: have the hiccup in d s MP. And so if 214 00:12:01,880 --> 00:12:06,240 Speaker 1: that were to happen, lowing rates helped. Lowing rates doesn't 215 00:12:06,280 --> 00:12:08,959 Speaker 1: do any good. And and that's why I'm not suggesting 216 00:12:09,000 --> 00:12:11,240 Speaker 1: that is in the slowdown. But the FIT can't help 217 00:12:11,320 --> 00:12:15,079 Speaker 1: the slowdown if we already have accommodative monetary policy. And 218 00:12:15,160 --> 00:12:17,360 Speaker 1: so there's really nothing the FIT can do at this stage. 219 00:12:17,480 --> 00:12:18,959 Speaker 1: And it would be very helpful for the FETE to 220 00:12:19,040 --> 00:12:22,680 Speaker 1: just communicate what it can and cannot do. Yeah, axel Mark, 221 00:12:22,920 --> 00:12:24,920 Speaker 1: thank you so much for being with us. Axel Mark, 222 00:12:24,960 --> 00:12:28,960 Speaker 1: President and Chief Investment Officer at Merk Investments in San Francisco. 223 00:12:43,800 --> 00:12:46,679 Speaker 1: We Work filed it's s one form ahead of its 224 00:12:46,720 --> 00:12:50,640 Speaker 1: initial public offering today and our reporters an analysts have 225 00:12:50,720 --> 00:12:54,960 Speaker 1: been parsing through the document. Quite a description of losses 226 00:12:55,200 --> 00:12:58,800 Speaker 1: and also hope for community and what that could potentially 227 00:12:58,840 --> 00:13:01,320 Speaker 1: reap in terms of joining us. Now, we're very lucky 228 00:13:01,360 --> 00:13:04,360 Speaker 1: to say is Jeff lang Baum, his senior reat Sirie 229 00:13:04,440 --> 00:13:08,000 Speaker 1: equity analyst for Bloomberg Intelligence, and Ellen Hewitt Startups reporter 230 00:13:08,200 --> 00:13:10,679 Speaker 1: for Bloomberg News joining us from our Bloomberg nine sixties 231 00:13:10,679 --> 00:13:13,839 Speaker 1: studio in San Francisco. Ellen, let's start with you. What 232 00:13:13,960 --> 00:13:17,400 Speaker 1: do we learn today from the WE Work Companies I 233 00:13:17,600 --> 00:13:20,520 Speaker 1: p O filing. There's so much to pass through. I'm 234 00:13:20,559 --> 00:13:22,440 Speaker 1: still going through it, and I still have a lot 235 00:13:22,480 --> 00:13:24,439 Speaker 1: to go through. I think the main story is, yes, 236 00:13:24,559 --> 00:13:26,959 Speaker 1: this is a company with a lot of growth and 237 00:13:27,320 --> 00:13:30,240 Speaker 1: a lot of losses. They have been losing, um, you know, 238 00:13:30,400 --> 00:13:33,640 Speaker 1: close to two billion dollars in Those were numbers that 239 00:13:33,679 --> 00:13:36,000 Speaker 1: we knew already, but we're starting to get a closer 240 00:13:36,080 --> 00:13:38,360 Speaker 1: look at just how quickly it's growing and just how 241 00:13:38,440 --> 00:13:41,000 Speaker 1: quickly it's losses are growing. And there's lots of other 242 00:13:41,120 --> 00:13:44,120 Speaker 1: interesting information in there as well, in particular about the 243 00:13:44,160 --> 00:13:47,599 Speaker 1: relationship between its CEO and co founder Adam Newman and 244 00:13:47,760 --> 00:13:50,559 Speaker 1: the company. There's a lot of complicated financial structures that 245 00:13:50,679 --> 00:13:54,120 Speaker 1: over the years we work has done to help support UM. 246 00:13:54,280 --> 00:13:57,640 Speaker 1: Mr Newman and vice versa. There's this very close relationship 247 00:13:57,679 --> 00:14:00,680 Speaker 1: with a lot of financial structures in there. So Jeff 248 00:14:00,840 --> 00:14:03,760 Speaker 1: building on Ellen just said, we saw just how quickly 249 00:14:03,800 --> 00:14:06,120 Speaker 1: their their revenues are growing and how quickly their losses 250 00:14:06,120 --> 00:14:08,760 Speaker 1: are growing. At first blush. What's your big takeaway? Was 251 00:14:08,840 --> 00:14:11,160 Speaker 1: this better than expected from your from your point of 252 00:14:11,240 --> 00:14:15,240 Speaker 1: view or worse? UM? I would say probably about the same. UM. 253 00:14:15,679 --> 00:14:18,160 Speaker 1: The one thing that really stood out to me was 254 00:14:18,240 --> 00:14:21,240 Speaker 1: that it's it's not clear how they can continue to 255 00:14:21,360 --> 00:14:24,760 Speaker 1: grow revenue the same magnitude that they've been growing it 256 00:14:25,160 --> 00:14:28,160 Speaker 1: without also continuing to increase their costs. Right, because their 257 00:14:28,200 --> 00:14:32,720 Speaker 1: revenue um grows when they add new incremental locations, and 258 00:14:32,960 --> 00:14:37,040 Speaker 1: that's a costly endeavor, and so in order for them 259 00:14:37,120 --> 00:14:40,600 Speaker 1: to approach profitability, they really have to I think scale 260 00:14:40,640 --> 00:14:44,720 Speaker 1: back the the expansion um and and then that, you know, 261 00:14:44,840 --> 00:14:46,720 Speaker 1: kind of gets you back to what's the valuation and 262 00:14:46,760 --> 00:14:48,120 Speaker 1: how are we looking at this thing? Is it a 263 00:14:48,200 --> 00:14:52,640 Speaker 1: high growth vehicle or is it an eventual profit generator? Ellen? 264 00:14:52,720 --> 00:14:56,280 Speaker 1: This morning Tom Keene was parsing through the filing and 265 00:14:56,480 --> 00:15:01,000 Speaker 1: he found numerous references the word community. I imagine it 266 00:15:01,200 --> 00:15:04,640 Speaker 1: was over ten and I'm wondering what actually at its 267 00:15:04,760 --> 00:15:08,840 Speaker 1: heart is this business, what is its competitive advantage and 268 00:15:09,160 --> 00:15:11,880 Speaker 1: what will distinguish it from from from other companies that 269 00:15:11,920 --> 00:15:14,200 Speaker 1: try to do the similar kind of thing. If you 270 00:15:14,480 --> 00:15:16,960 Speaker 1: ask we Work, they'll they'll give you an answer that's 271 00:15:17,000 --> 00:15:19,840 Speaker 1: that's pretty abstract. They talk about the idea of the 272 00:15:20,000 --> 00:15:22,920 Speaker 1: power of we, and that's connected to this idea of community. 273 00:15:23,000 --> 00:15:27,200 Speaker 1: It's this this sense of togetherness and and working together 274 00:15:27,360 --> 00:15:29,680 Speaker 1: better and and it's part of this brand that we 275 00:15:29,800 --> 00:15:31,960 Speaker 1: Work has really developed that they try to use to 276 00:15:32,000 --> 00:15:34,840 Speaker 1: set themselves apart from your Regius or your other sort 277 00:15:34,880 --> 00:15:38,960 Speaker 1: of stayed office providers. They really believe that building a 278 00:15:39,080 --> 00:15:42,600 Speaker 1: global network of these flexible office spaces is going to 279 00:15:42,640 --> 00:15:46,560 Speaker 1: provide something that is beyond just easy access to space. 280 00:15:46,680 --> 00:15:49,040 Speaker 1: You know, they have a lot of enterprise customers that 281 00:15:49,200 --> 00:15:51,640 Speaker 1: I imagine look at we Work as a very simple 282 00:15:52,120 --> 00:15:54,880 Speaker 1: and easy way to, for example, set up a satellite 283 00:15:54,920 --> 00:15:57,240 Speaker 1: office in a city where they maybe don't currently have 284 00:15:57,320 --> 00:15:59,880 Speaker 1: a presence. It's much easier to do that by paying 285 00:16:00,040 --> 00:16:03,200 Speaker 1: we Work, then by you know, hiring your own real 286 00:16:03,320 --> 00:16:05,400 Speaker 1: estate team to go and look for places and signed 287 00:16:05,440 --> 00:16:07,400 Speaker 1: a ten year lease and and that's maybe the more 288 00:16:08,080 --> 00:16:12,040 Speaker 1: practical business application. But yeah, they talk about this idea 289 00:16:12,120 --> 00:16:14,720 Speaker 1: of community being really central to what makes me work different. 290 00:16:14,800 --> 00:16:18,480 Speaker 1: In fact, when they sold UM bonds last year for 291 00:16:18,560 --> 00:16:21,400 Speaker 1: the first time, this was when we first encountered the 292 00:16:21,600 --> 00:16:26,600 Speaker 1: infamous metric community adjusted EBIT, which many people mocked UM. 293 00:16:27,200 --> 00:16:29,560 Speaker 1: But it's interesting that we Work chose that because it 294 00:16:29,880 --> 00:16:31,840 Speaker 1: is indicative of how much they believe in this idea 295 00:16:31,880 --> 00:16:36,560 Speaker 1: of community being central to uh their business. If you'll notice, 296 00:16:36,600 --> 00:16:38,880 Speaker 1: community adjusted EBA does not in the s one, although 297 00:16:38,920 --> 00:16:41,200 Speaker 1: I looked back at some of the draft versions and 298 00:16:41,280 --> 00:16:44,160 Speaker 1: it isn't the first three draft versions of five, so 299 00:16:44,360 --> 00:16:47,520 Speaker 1: some made it some of the way. Banker said, no way, 300 00:16:47,600 --> 00:16:52,040 Speaker 1: are you subjecting yourself to that again, guys, no, just stop, Jeff, 301 00:16:52,120 --> 00:16:54,480 Speaker 1: I do want to ask about the business model from 302 00:16:54,600 --> 00:16:57,920 Speaker 1: a real estate perspective. I always am unclear of how 303 00:16:58,080 --> 00:17:01,760 Speaker 1: much of we Work property is own versus least. What 304 00:17:01,920 --> 00:17:05,199 Speaker 1: sort of the breakdown here the majority is least. They 305 00:17:05,280 --> 00:17:07,960 Speaker 1: disclosed in the s one that they have forty seven 306 00:17:08,040 --> 00:17:12,840 Speaker 1: billion dollars of lease obligation UM and that compares to 307 00:17:13,119 --> 00:17:17,480 Speaker 1: four billion dollars of committed revenue backlog. So UM. You know, 308 00:17:18,240 --> 00:17:22,359 Speaker 1: if and when we have a economic downturn that pulls 309 00:17:22,480 --> 00:17:26,480 Speaker 1: tenants away from office space there on the hook for 310 00:17:26,560 --> 00:17:29,600 Speaker 1: a lot more than what they are obligated to receive 311 00:17:30,200 --> 00:17:32,640 Speaker 1: UM and and you know that this will that will 312 00:17:32,720 --> 00:17:35,560 Speaker 1: really test the power of their community. How many of 313 00:17:35,640 --> 00:17:38,600 Speaker 1: these tenants that are on short term leases with them 314 00:17:39,320 --> 00:17:42,840 Speaker 1: stay UM as opposed to you know, pulling back and 315 00:17:43,280 --> 00:17:46,639 Speaker 1: finding somewhere else to run their business. UM, if they 316 00:17:46,680 --> 00:17:48,560 Speaker 1: don't need that cost, And then what does that mean 317 00:17:48,640 --> 00:17:52,280 Speaker 1: for we Work going forward? Ellen, what's the what's their 318 00:17:52,359 --> 00:17:55,320 Speaker 1: goal as far as how they plan to expand revenues here? 319 00:17:56,520 --> 00:17:58,760 Speaker 1: You know, I think it's just continuing to look at 320 00:17:58,880 --> 00:18:01,159 Speaker 1: growing in parts of the world where they don't have 321 00:18:01,240 --> 00:18:04,240 Speaker 1: as big a presence. Commercial real estate is a huge 322 00:18:04,320 --> 00:18:06,560 Speaker 1: addressable market. This is something that they always talk about 323 00:18:06,640 --> 00:18:08,720 Speaker 1: when they're trying to make the pitch for why you 324 00:18:08,760 --> 00:18:12,200 Speaker 1: should believe that this company is worth forty seven billion dollars, 325 00:18:12,240 --> 00:18:15,280 Speaker 1: which was their most recent private valuation. They look to 326 00:18:15,680 --> 00:18:18,399 Speaker 1: areas such as in South America and in Asia and 327 00:18:18,600 --> 00:18:22,119 Speaker 1: point to, you know, the low penetration that their business 328 00:18:22,200 --> 00:18:26,040 Speaker 1: has among you know, the office real estate market, and 329 00:18:26,240 --> 00:18:28,840 Speaker 1: and they say, look, we've really figured out how to 330 00:18:29,440 --> 00:18:32,680 Speaker 1: retrofit and fit out with furniture and office very quickly, 331 00:18:32,800 --> 00:18:35,360 Speaker 1: very cheaply. You know, it might also look the same 332 00:18:35,400 --> 00:18:37,480 Speaker 1: as we work somewhere else in the world, but look, 333 00:18:37,560 --> 00:18:39,040 Speaker 1: we can do it for not a lot of money 334 00:18:39,040 --> 00:18:40,440 Speaker 1: and not a lot of time, and that's going to 335 00:18:40,520 --> 00:18:43,200 Speaker 1: help us grow more quickly than everyone else. Um. And 336 00:18:43,400 --> 00:18:45,960 Speaker 1: as as we mentioned earlier, they talk a lot about 337 00:18:46,080 --> 00:18:49,360 Speaker 1: how if they needed to get to profitability, they could 338 00:18:49,440 --> 00:18:51,719 Speaker 1: just stop growing. And in fact, in they s one 339 00:18:51,720 --> 00:18:54,720 Speaker 1: they cite a couple examples, including one in London where 340 00:18:55,200 --> 00:18:57,800 Speaker 1: in the wake of Brexit they felt like maybe they 341 00:18:57,800 --> 00:19:01,040 Speaker 1: should slow down growth, and in doing so they were 342 00:19:01,080 --> 00:19:03,080 Speaker 1: able to show that their occupancy rates went up. So 343 00:19:03,480 --> 00:19:05,879 Speaker 1: they're obviously looking for examples where they can point to 344 00:19:06,520 --> 00:19:10,119 Speaker 1: and say, look, if things go poorly, we have a 345 00:19:10,200 --> 00:19:12,399 Speaker 1: little bit of a place to fall back on, which is, 346 00:19:12,440 --> 00:19:14,760 Speaker 1: if we stop growing so quickly, we won't lose money 347 00:19:14,800 --> 00:19:17,200 Speaker 1: as quickly. Um. But yeah, while they think the going 348 00:19:17,280 --> 00:19:18,879 Speaker 1: is good, they'd like to grow as quickly as possible. 349 00:19:18,920 --> 00:19:21,520 Speaker 1: Reverseas Jeff, I do have to wonder, especially if most 350 00:19:21,560 --> 00:19:26,840 Speaker 1: of their contracts releases and not ownership over these commercial properties, 351 00:19:27,440 --> 00:19:30,600 Speaker 1: what the asset liability balance is, Like, I mean it's 352 00:19:30,640 --> 00:19:33,600 Speaker 1: not secured. What are their assets that they could liquidate 353 00:19:33,680 --> 00:19:37,679 Speaker 1: if they do have a problem. That's unclear. Um, they 354 00:19:38,320 --> 00:19:42,040 Speaker 1: do own some, but they're all kind of complicated structures. Um. 355 00:19:42,240 --> 00:19:46,440 Speaker 1: But but realistically, this is a it's a it's a 356 00:19:46,640 --> 00:19:51,200 Speaker 1: very complicated large sublease business. Right. They lease off the space, 357 00:19:51,440 --> 00:19:53,960 Speaker 1: they turn it around, they make it cool, um, and 358 00:19:54,040 --> 00:19:57,160 Speaker 1: then they sublease it. And they've got average lease length 359 00:19:57,320 --> 00:20:00,760 Speaker 1: of their leases are average fifteen years and there's member 360 00:20:01,160 --> 00:20:05,520 Speaker 1: leases are average fifteen months, and so they are definitely mismatched. 361 00:20:05,720 --> 00:20:09,199 Speaker 1: And you know, the over the past ten years, as 362 00:20:09,240 --> 00:20:11,840 Speaker 1: they've been growing, it has worked because the office market 363 00:20:11,880 --> 00:20:15,000 Speaker 1: has been expanding. Um. But that is has yet to 364 00:20:15,080 --> 00:20:19,120 Speaker 1: really be tested. Jeff Langbaum, Senior read and Sirie Equity 365 00:20:19,119 --> 00:20:22,480 Speaker 1: analyst for Bloomberg Intelligence. Ellen qwittt Uh, startup supporter for 366 00:20:22,560 --> 00:20:25,400 Speaker 1: Bloomberg News, joining us from our San Francisco studios. Thank 367 00:20:25,480 --> 00:20:39,040 Speaker 1: you so much for your time. We talk a lot 368 00:20:39,080 --> 00:20:43,560 Speaker 1: about the war in technology, the war for the latest advancements, 369 00:20:43,880 --> 00:20:46,840 Speaker 1: and a lot of times people talk about quantum computing, 370 00:20:47,000 --> 00:20:50,160 Speaker 1: the idea of what's next, sort of what's the next 371 00:20:50,240 --> 00:20:53,520 Speaker 1: see change within the computing industry. Luckily we have Dr 372 00:20:53,600 --> 00:20:57,040 Speaker 1: Bob Sutor, he's vice president and IBM QUE Strategy and 373 00:20:57,160 --> 00:21:00,560 Speaker 1: Ecosystem at IBM joining us here in bloom We're gonna 374 00:21:00,560 --> 00:21:04,440 Speaker 1: active broker studios. So, Drs Sutor, I'm wondering, can you 375 00:21:04,520 --> 00:21:08,200 Speaker 1: just start by explaining what is it that you do? Well, 376 00:21:08,280 --> 00:21:11,280 Speaker 1: I'm in IBM Research. Okay, there we go. I mean, 377 00:21:11,520 --> 00:21:15,040 Speaker 1: basically we talk about quanting quantum computing. What are we 378 00:21:15,119 --> 00:21:18,320 Speaker 1: actually talking about here? Well, I mentioned IBM Research because 379 00:21:18,359 --> 00:21:21,600 Speaker 1: we deal with the really, really, really new things that 380 00:21:21,880 --> 00:21:23,960 Speaker 1: are going to be coming to market in five, ten, 381 00:21:24,080 --> 00:21:28,159 Speaker 1: or sometimes twenty years. So quantum computing, which is what 382 00:21:28,280 --> 00:21:32,840 Speaker 1: we do. UM is developing an entirely new type of 383 00:21:32,960 --> 00:21:37,200 Speaker 1: hardware and software stack to solve problems that really today 384 00:21:37,240 --> 00:21:40,239 Speaker 1: are just not tractable using existing systems. So give us 385 00:21:40,240 --> 00:21:47,719 Speaker 1: an example. So let's take um um option um risk analysis. Right, 386 00:21:47,760 --> 00:21:49,920 Speaker 1: So you're trying to figure out you have a portfolio 387 00:21:50,080 --> 00:21:51,520 Speaker 1: and you could be a hedge fund, or this could 388 00:21:51,560 --> 00:21:54,720 Speaker 1: be your retirement account. When you start thinking of the 389 00:21:54,800 --> 00:21:58,040 Speaker 1: stocks and bonds and derivatives and all these different types 390 00:21:58,480 --> 00:22:02,359 Speaker 1: of instruments, they're so many different connections between them and 391 00:22:02,480 --> 00:22:04,680 Speaker 1: also things that are happening in the world. When you 392 00:22:04,760 --> 00:22:09,440 Speaker 1: start to analyze these things, the combinations just grow exponentially, 393 00:22:09,560 --> 00:22:12,440 Speaker 1: and here I literally mean exponentially and not just a 394 00:22:12,600 --> 00:22:16,960 Speaker 1: lot all right. Current computers can't handle that. They can't 395 00:22:17,040 --> 00:22:21,280 Speaker 1: handle that growth, and so they require either a tremendous, 396 00:22:21,600 --> 00:22:25,320 Speaker 1: in fact ridiculous amount of memory to process or maybe 397 00:22:25,520 --> 00:22:28,280 Speaker 1: only a million years to do the computation. This is 398 00:22:28,320 --> 00:22:30,359 Speaker 1: a really important point and it's something that a lot 399 00:22:30,400 --> 00:22:33,560 Speaker 1: of businesses are looking into, and even from a governmental standpoint, 400 00:22:33,600 --> 00:22:37,240 Speaker 1: there have been proposals that perhaps regulation of banks, for example, 401 00:22:37,280 --> 00:22:40,600 Speaker 1: should be done with quantum computing to basically abstract out 402 00:22:40,720 --> 00:22:43,280 Speaker 1: what the potential risks could be given what you're seeing 403 00:22:43,440 --> 00:22:47,160 Speaker 1: on the ground when it comes to current day application 404 00:22:47,280 --> 00:22:49,680 Speaker 1: of some of these technologies, what are you seeing in 405 00:22:49,840 --> 00:22:54,040 Speaker 1: terms of that So first quantum computing is several years away. 406 00:22:54,200 --> 00:22:57,440 Speaker 1: I really need to emphasize that. So we are looking 407 00:22:57,600 --> 00:23:00,280 Speaker 1: for the applications that can do better than cloud csicle 408 00:23:00,320 --> 00:23:03,879 Speaker 1: computers in three to five to ten years. So this 409 00:23:04,200 --> 00:23:07,400 Speaker 1: isn't a situation where you use a quantum computer today 410 00:23:07,800 --> 00:23:11,840 Speaker 1: to help you. It's longer term. But people who have 411 00:23:12,160 --> 00:23:15,560 Speaker 1: longer term research programs, who can invest in this and 412 00:23:15,640 --> 00:23:18,320 Speaker 1: want to be first to market will get behind this. 413 00:23:18,720 --> 00:23:22,359 Speaker 1: So I mentioned the financial services applications. Uh, there are 414 00:23:22,560 --> 00:23:27,320 Speaker 1: some situations where quantum computing may help find new patterns 415 00:23:27,400 --> 00:23:30,240 Speaker 1: and data, so to help AI, to help machine learning, 416 00:23:30,640 --> 00:23:34,240 Speaker 1: and then also chemistry. There's always this idea that we 417 00:23:34,359 --> 00:23:37,520 Speaker 1: want to find new drugs, discover new drugs. Now, when 418 00:23:37,560 --> 00:23:39,920 Speaker 1: I hear drug discovery, it's almost like you're wandering around 419 00:23:39,960 --> 00:23:43,240 Speaker 1: in a forest looking for the great drug. Let's compute 420 00:23:43,320 --> 00:23:48,240 Speaker 1: that instead, right, Let's actually model the molecules exactly in 421 00:23:48,280 --> 00:23:51,080 Speaker 1: a computer, so we can compute with them, we can 422 00:23:51,160 --> 00:23:53,600 Speaker 1: manipulate them and figure out how they're going to work 423 00:23:53,680 --> 00:23:56,800 Speaker 1: with you. It's quantum getting basically just really fast computer. 424 00:23:57,560 --> 00:24:00,760 Speaker 1: It's a completely different type of computer. So it's not 425 00:24:01,000 --> 00:24:05,280 Speaker 1: like your laptop or your phone from the very lowest level. 426 00:24:05,840 --> 00:24:09,200 Speaker 1: It's completely different, which means all the software above it's 427 00:24:09,240 --> 00:24:12,480 Speaker 1: completely different as well. Who's ahead in the race for 428 00:24:12,960 --> 00:24:16,439 Speaker 1: the secret sauce when it comes to quantum computing? I mean, uh, 429 00:24:16,640 --> 00:24:20,240 Speaker 1: we talk about the US versus China. Are we seeing 430 00:24:20,440 --> 00:24:22,359 Speaker 1: a greater degree of development in China than the U 431 00:24:22,480 --> 00:24:24,880 Speaker 1: S on this? On this front, well, we really can't tell, 432 00:24:25,080 --> 00:24:27,879 Speaker 1: so I can't comment. I can only talk about what 433 00:24:27,960 --> 00:24:30,800 Speaker 1: I know about um in for example, the United States 434 00:24:30,920 --> 00:24:34,240 Speaker 1: and Europe. Um all of us are doing a tremendous 435 00:24:34,280 --> 00:24:38,280 Speaker 1: amount of work. They're different quantum computing technologies. UM, I 436 00:24:38,320 --> 00:24:42,040 Speaker 1: would say right now, and yes it's my organization, but 437 00:24:42,320 --> 00:24:46,240 Speaker 1: I think IBM is ahead in terms of producing the 438 00:24:46,359 --> 00:24:51,080 Speaker 1: quantum computers and making them available. We've had quantum computers online. 439 00:24:51,600 --> 00:24:53,520 Speaker 1: I mean, people can go to the IBM q experience 440 00:24:53,680 --> 00:24:56,399 Speaker 1: right now and use use a quantum computer. We've had 441 00:24:56,440 --> 00:25:00,520 Speaker 1: them for three years on the cloud. Hundred forty people registered, 442 00:25:01,080 --> 00:25:04,199 Speaker 1: So that's really interesting. That brings me to my next question. 443 00:25:04,720 --> 00:25:08,000 Speaker 1: Are you finding the talent that you need to hire 444 00:25:08,200 --> 00:25:10,720 Speaker 1: to bring into the fold who can do this work 445 00:25:11,040 --> 00:25:15,080 Speaker 1: and pushes forward. We're finding some of it, but education 446 00:25:15,320 --> 00:25:17,679 Speaker 1: is a big part of what we're trying to support 447 00:25:17,760 --> 00:25:20,639 Speaker 1: right now, because if this is so different, if you 448 00:25:20,720 --> 00:25:23,600 Speaker 1: think about all the software engineers out there, none of 449 00:25:23,680 --> 00:25:28,040 Speaker 1: them a priori know how to code a quantum computer. Now, 450 00:25:28,080 --> 00:25:31,159 Speaker 1: it turns out in many organizations there's the occasional quantum 451 00:25:31,200 --> 00:25:35,680 Speaker 1: physicists who you can recruit, uh, But we're trying to 452 00:25:35,760 --> 00:25:40,520 Speaker 1: train more in undergraduate classes. We're supporting graduate students um. This, 453 00:25:40,680 --> 00:25:42,879 Speaker 1: in fact, though, I will say, is the most common 454 00:25:42,960 --> 00:25:45,520 Speaker 1: question when we talk to clients, who should I hire? 455 00:25:45,720 --> 00:25:48,119 Speaker 1: What sorts of people should I have and get on 456 00:25:48,320 --> 00:25:51,639 Speaker 1: board now to help me with this quantum computing future? 457 00:25:52,240 --> 00:25:55,880 Speaker 1: Which industry do you think will be most radically changed 458 00:25:56,720 --> 00:25:59,879 Speaker 1: by the advent of some of this technology? First up, 459 00:26:00,119 --> 00:26:04,560 Speaker 1: financial services, Second up all those things that relate to chemistry, 460 00:26:05,040 --> 00:26:09,240 Speaker 1: so ultimately healthcare, but also material science, creating new alloys, 461 00:26:09,440 --> 00:26:13,119 Speaker 1: all sorts of materials that people will see. Bring this 462 00:26:13,240 --> 00:26:15,040 Speaker 1: down to the level of you know, when you go 463 00:26:15,119 --> 00:26:17,720 Speaker 1: to buy clothes, is it something where you could potentially 464 00:26:17,800 --> 00:26:20,760 Speaker 1: have a jacket that keeps all of your warmth in 465 00:26:21,040 --> 00:26:23,760 Speaker 1: and yet is paper thin? Or I mean, what, what's 466 00:26:23,880 --> 00:26:26,440 Speaker 1: what's the actual kind of application here to give people 467 00:26:26,480 --> 00:26:29,920 Speaker 1: a tangible sense of how different things could look in 468 00:26:30,000 --> 00:26:33,119 Speaker 1: their physical world. As a response to this, or in 469 00:26:33,600 --> 00:26:37,879 Speaker 1: on the heels of this technological advance, well dime Lar Mercedes, 470 00:26:37,960 --> 00:26:40,000 Speaker 1: for example, who is one of our partners in the 471 00:26:40,080 --> 00:26:44,159 Speaker 1: ibm Q network. They're working on new battery technology. So 472 00:26:44,800 --> 00:26:48,000 Speaker 1: future electric cars, if everything goes well with quantum computing, 473 00:26:48,280 --> 00:26:52,119 Speaker 1: will be much more efficient and last much longer. And 474 00:26:52,280 --> 00:26:54,320 Speaker 1: that's how you will see it. Most people in their 475 00:26:54,400 --> 00:26:56,200 Speaker 1: day to day lives will not say, hey, I'm using 476 00:26:56,200 --> 00:26:59,439 Speaker 1: a quantum computer to do this. They may see new shampoos. Yes, 477 00:26:59,480 --> 00:27:03,600 Speaker 1: they may see new materials, new new textiles, um, new 478 00:27:03,760 --> 00:27:07,560 Speaker 1: materials in their cars. Uh, you know, we may actually 479 00:27:07,680 --> 00:27:10,720 Speaker 1: use quantum computers to create new materials to create even 480 00:27:10,760 --> 00:27:14,240 Speaker 1: better quantum computers. What about cost wise? I mean, is 481 00:27:14,280 --> 00:27:16,200 Speaker 1: it going to be cost prohibitive for anyone with the 482 00:27:16,240 --> 00:27:19,080 Speaker 1: biggest companies to sort of engage with this technology at 483 00:27:19,119 --> 00:27:22,120 Speaker 1: the outset? Uh? No, it won't be because it will 484 00:27:22,160 --> 00:27:24,359 Speaker 1: be available on the cloud, So people will not be 485 00:27:24,560 --> 00:27:27,800 Speaker 1: buying their own quantum computers. They will be accessing them 486 00:27:27,880 --> 00:27:30,800 Speaker 1: over the cloud in different models. In fact, the IBMQ 487 00:27:30,920 --> 00:27:33,119 Speaker 1: experience which I mentioned before, If you want to get 488 00:27:33,200 --> 00:27:36,080 Speaker 1: up and started. It's no charge. The software we use 489 00:27:36,280 --> 00:27:39,240 Speaker 1: is open source, there's no charge. I'm sure it's sort 490 00:27:39,280 --> 00:27:41,400 Speaker 1: of a good tactic. In other words, get enough people 491 00:27:41,560 --> 00:27:44,240 Speaker 1: in the fold and understanding what this is to have 492 00:27:44,400 --> 00:27:47,000 Speaker 1: the ecosystem to keep it going and push it ahead. 493 00:27:47,320 --> 00:27:49,600 Speaker 1: Dr Bob Sutor, thank you so much for being here, 494 00:27:49,680 --> 00:27:54,200 Speaker 1: fascinating vice president of ibm Q Strategy and Ecosystem, joining 495 00:27:54,280 --> 00:27:58,399 Speaker 1: us here in our eleven three oh studios. Thanks for 496 00:27:58,480 --> 00:28:00,520 Speaker 1: listening to the Bloomberg P and L pod Cast. You 497 00:28:00,560 --> 00:28:03,200 Speaker 1: can subscribe and listen to interviews at Apple Podcasts or 498 00:28:03,240 --> 00:28:06,200 Speaker 1: whatever podcast platform you prefer. I'm Paul Sweeney. I'm on 499 00:28:06,280 --> 00:28:08,920 Speaker 1: Twitter at pt Sweeney. I'm Lisa abram Woyds. I'm on 500 00:28:08,960 --> 00:28:11,720 Speaker 1: Twitter at Lisa A. Bram wits one. Before the podcast, 501 00:28:11,760 --> 00:28:14,359 Speaker 1: you can always catch us worldwide. I'm Bloomberg Radio