1 00:00:04,760 --> 00:00:08,080 Speaker 1: Welcome to the Bloomberg P and L Podcast. I'm pim Fox. 2 00:00:08,119 --> 00:00:11,159 Speaker 1: Along with my co host Lisa Abramowitz. Each day we 3 00:00:11,280 --> 00:00:14,480 Speaker 1: bring you the most important, noteworthy, and useful interviews for 4 00:00:14,520 --> 00:00:16,880 Speaker 1: you and your money, whether at the grocery store or 5 00:00:16,920 --> 00:00:20,680 Speaker 1: the trading floor. Find the Bloomberg P L Podcast on iTunes, 6 00:00:20,840 --> 00:00:29,479 Speaker 1: SoundCloud and at Bloomberg dot com. There might be a 7 00:00:29,680 --> 00:00:33,040 Speaker 1: snow jump coming to the East Coast, but there is 8 00:00:33,120 --> 00:00:36,720 Speaker 1: a dump of bad news coming for the auto industry. 9 00:00:36,800 --> 00:00:40,240 Speaker 1: You have uh the U S subprime auto lenders losing 10 00:00:40,280 --> 00:00:43,200 Speaker 1: the most money on car loans at the highest rate 11 00:00:43,560 --> 00:00:46,159 Speaker 1: since the aftermath of the two thousand and eight financial crisis. 12 00:00:46,600 --> 00:00:51,320 Speaker 1: And Kevin Tynan, Bloomberg Intelligence automobile analyst for North America, 13 00:00:51,600 --> 00:00:54,240 Speaker 1: put out a report today saying as bad as two 14 00:00:54,240 --> 00:00:57,200 Speaker 1: thousand and sixteen looked for car sales, two thousand and 15 00:00:57,240 --> 00:01:00,600 Speaker 1: seventeen starting off worse. Let's bring him in, Kevin. We 16 00:01:00,720 --> 00:01:05,200 Speaker 1: appreciate you joining us, and you have this fantastic statistic 17 00:01:05,280 --> 00:01:09,160 Speaker 1: that cars accounted for just thirty nine percent of total 18 00:01:09,240 --> 00:01:13,479 Speaker 1: US sales, the lowest percentage in history. But that might 19 00:01:13,520 --> 00:01:15,560 Speaker 1: not not be as bad as it gets, right, Oh No, 20 00:01:15,800 --> 00:01:18,800 Speaker 1: it's it's definitely going to get worse. Um And I 21 00:01:18,840 --> 00:01:22,920 Speaker 1: think what is different now. Historically what you would see 22 00:01:23,040 --> 00:01:27,600 Speaker 1: is demand cycle in and out of cars to trucks 23 00:01:27,600 --> 00:01:31,399 Speaker 1: and back and forth, and um in some inventory adjustment 24 00:01:31,400 --> 00:01:34,560 Speaker 1: with incentive spending, and then everything sort of levels out. 25 00:01:34,600 --> 00:01:38,480 Speaker 1: And what different this time is that the and and 26 00:01:38,520 --> 00:01:40,280 Speaker 1: this was the sort of crux of the piece, was 27 00:01:40,319 --> 00:01:44,520 Speaker 1: that the revenue generating segments are all trucks, the top 28 00:01:44,600 --> 00:01:47,840 Speaker 1: three or trucks and really pushing cars further and further 29 00:01:47,920 --> 00:01:50,520 Speaker 1: down the list. And why it's different this time is 30 00:01:50,600 --> 00:01:54,400 Speaker 1: because the automakers see where that revenue is being generated 31 00:01:54,520 --> 00:01:59,600 Speaker 1: and are actively unwinding their car positions, understanding that these 32 00:01:59,640 --> 00:02:02,160 Speaker 1: segments they're going to continue to shrink and shrink and shrink, 33 00:02:02,760 --> 00:02:06,640 Speaker 1: and they will align supply with demand which will be 34 00:02:06,800 --> 00:02:09,760 Speaker 1: much lower. So rather than waiting for it to come back, 35 00:02:09,800 --> 00:02:13,120 Speaker 1: they're actively getting out of those those segments, and it 36 00:02:13,160 --> 00:02:16,520 Speaker 1: will make it impossible for cars to ever recover, regardless 37 00:02:16,520 --> 00:02:21,120 Speaker 1: of gas lean prices. Kevin has the automobile industry ever 38 00:02:21,440 --> 00:02:25,640 Speaker 1: embarked on a similar strategy and found it to be 39 00:02:25,840 --> 00:02:31,800 Speaker 1: wanting um no uh in the sense that we've I 40 00:02:31,840 --> 00:02:38,680 Speaker 1: think what's happening Wednesday with cafe rules and and that 41 00:02:38,919 --> 00:02:41,359 Speaker 1: I tell people about this because this is very important 42 00:02:41,360 --> 00:02:45,799 Speaker 1: to the overall disposition of an automaker's fleet, and it's 43 00:02:45,800 --> 00:02:47,919 Speaker 1: related to how many miles per gallon the fleet has 44 00:02:47,960 --> 00:02:51,160 Speaker 1: to get right and arguably, and if you look at 45 00:02:51,160 --> 00:02:54,880 Speaker 1: some of the some of the graphs in the US 46 00:02:54,919 --> 00:02:57,560 Speaker 1: in North America, we've always wanted to buy trucks. There's 47 00:02:57,560 --> 00:03:01,160 Speaker 1: a period between the two recessions that truck sales spiked 48 00:03:01,160 --> 00:03:04,359 Speaker 1: as well, and that's the two times that that car 49 00:03:04,720 --> 00:03:08,520 Speaker 1: car sales recovered were cash for clunkers. Uh and then 50 00:03:08,560 --> 00:03:10,640 Speaker 1: when guest Lee went above four dollars a gallon in 51 00:03:10,680 --> 00:03:13,480 Speaker 1: two thousand and eight. Uh. So we've always wanted to 52 00:03:13,480 --> 00:03:16,960 Speaker 1: buy trucks, but this, this corporate average fuel economy standard 53 00:03:17,040 --> 00:03:21,000 Speaker 1: has had sort of affecting the supply side of the equation. 54 00:03:21,080 --> 00:03:23,320 Speaker 1: Telent automakers, you have to build these things to be 55 00:03:23,440 --> 00:03:26,360 Speaker 1: compliant with these rules, whether or not the consumer wants 56 00:03:26,360 --> 00:03:28,040 Speaker 1: them or not. And I think that's where we're in 57 00:03:28,120 --> 00:03:31,680 Speaker 1: new territory that says those rules didn't really take into 58 00:03:31,680 --> 00:03:35,080 Speaker 1: account the consumer. All all the onus was on the manufacturers. 59 00:03:35,880 --> 00:03:39,720 Speaker 1: Now with production and the administration saying we want you 60 00:03:39,760 --> 00:03:42,120 Speaker 1: to produce in the US. I think the automakers are 61 00:03:42,120 --> 00:03:45,000 Speaker 1: going back to President Trump and saying, we will produce 62 00:03:45,040 --> 00:03:47,520 Speaker 1: in the US, but it has to be trucks. If 63 00:03:47,520 --> 00:03:49,320 Speaker 1: it's going to be trucks, you have to help us 64 00:03:49,320 --> 00:03:51,880 Speaker 1: on the cafe side. Well, so just to give us 65 00:03:51,880 --> 00:03:54,280 Speaker 1: a little bit of perspective here, how much more expensive 66 00:03:54,360 --> 00:03:57,640 Speaker 1: on average our trucks and cars? Well, if you look 67 00:03:57,680 --> 00:04:00,960 Speaker 1: at it segment by segment, and I'll just take for example, 68 00:04:01,240 --> 00:04:05,400 Speaker 1: the largest truck segment by volume, not by not by revenue, 69 00:04:05,440 --> 00:04:09,119 Speaker 1: but by volume, is compact crossover SUVs. The largest car 70 00:04:09,160 --> 00:04:13,480 Speaker 1: segment is compact car. So those two line up pretty nicely. Um, 71 00:04:13,520 --> 00:04:17,480 Speaker 1: the difference in retail revenue is about six thousand dollars 72 00:04:17,480 --> 00:04:19,640 Speaker 1: between the two. So you'd be in the low twenties 73 00:04:19,680 --> 00:04:23,080 Speaker 1: for your average compact car. You'd be in the mid 74 00:04:23,120 --> 00:04:25,960 Speaker 1: to upper twenties for your average compact crossover. And I 75 00:04:26,000 --> 00:04:28,560 Speaker 1: wanted to get back to the whole idea of subprime 76 00:04:28,640 --> 00:04:32,559 Speaker 1: auto loans. Is there an equal proportion of subprime auto 77 00:04:32,600 --> 00:04:36,080 Speaker 1: loans for people to buy trucks as well as cars. 78 00:04:36,320 --> 00:04:38,760 Speaker 1: Is it more directed toward cars. I'm just basically trying 79 00:04:38,800 --> 00:04:40,520 Speaker 1: to figure out, you know, because potentially that could mean 80 00:04:40,560 --> 00:04:42,920 Speaker 1: that the losses are that much greater on the trucks 81 00:04:42,920 --> 00:04:45,240 Speaker 1: if somebody is not able to pay. Correct. Yeah, it 82 00:04:45,279 --> 00:04:48,239 Speaker 1: would be because those transaction prices are higher. And really, 83 00:04:48,360 --> 00:04:50,839 Speaker 1: I think what you're seeing when you look at the 84 00:04:50,880 --> 00:04:54,680 Speaker 1: average retail transaction price in the US, it's continually going 85 00:04:54,760 --> 00:04:58,000 Speaker 1: up because of this mixed shift. But at the same time, 86 00:04:58,000 --> 00:04:59,919 Speaker 1: it's also why we're seeing a lot of lease penet 87 00:05:00,080 --> 00:05:03,640 Speaker 1: ration because it creates affordability. So what you have is 88 00:05:03,720 --> 00:05:06,800 Speaker 1: this subprime is pulling new buyers into the market, whether 89 00:05:06,880 --> 00:05:11,560 Speaker 1: that's lower credit ratings, whether that's longer terms, uh, you know, 90 00:05:11,640 --> 00:05:13,960 Speaker 1: bigger down payments, or however you have to get that 91 00:05:14,160 --> 00:05:17,240 Speaker 1: consumer to that monthly payment that they can afford, because 92 00:05:17,279 --> 00:05:20,080 Speaker 1: that's really how we buy vehicles in the US. So 93 00:05:20,160 --> 00:05:23,440 Speaker 1: if leasing makes more sense, we'll just we'll basically rent 94 00:05:23,520 --> 00:05:25,599 Speaker 1: you the car for part of the term and get 95 00:05:25,640 --> 00:05:28,200 Speaker 1: you to that number that makes sense to you. So 96 00:05:28,200 --> 00:05:30,440 Speaker 1: so there's a lot of different ways that that the 97 00:05:30,520 --> 00:05:33,479 Speaker 1: lenders and the automakers are getting people off the sidelines 98 00:05:33,480 --> 00:05:36,800 Speaker 1: and into vehicles, and it's resulting in higher prices. A 99 00:05:36,880 --> 00:05:40,479 Speaker 1: shift from into luxury entry luxury more so than we 100 00:05:40,520 --> 00:05:43,560 Speaker 1: had seen historically. But there's a lot of risk associated 101 00:05:43,560 --> 00:05:45,920 Speaker 1: with that as well. Well. As much as I will 102 00:05:46,000 --> 00:05:49,400 Speaker 1: miss my you know, the nine nine Chevrolet Camaro with 103 00:05:49,520 --> 00:05:52,680 Speaker 1: the zero one engine, I'm sorry, Kenneth, I'm not going 104 00:05:52,760 --> 00:05:55,200 Speaker 1: to Kevin, I'm not gonna be able to, uh, you know, 105 00:05:55,360 --> 00:05:58,040 Speaker 1: sort of look at it anymore with those feelings because 106 00:05:58,279 --> 00:06:01,880 Speaker 1: everything will have disappeared, at least in that segment category. 107 00:06:02,000 --> 00:06:05,560 Speaker 1: So who's so who and where are the people who 108 00:06:05,560 --> 00:06:07,000 Speaker 1: are going to make up the difference who are going 109 00:06:07,040 --> 00:06:09,880 Speaker 1: to actually continue that tradition. And then I want you 110 00:06:09,920 --> 00:06:13,599 Speaker 1: to just give your thoughts about US auto companies maybe 111 00:06:13,640 --> 00:06:17,599 Speaker 1: doing cars outside the United States, right, And let me 112 00:06:17,680 --> 00:06:21,159 Speaker 1: just say, I think in one of the areas on 113 00:06:21,200 --> 00:06:24,440 Speaker 1: the car side that I think is reasonably protect protected 114 00:06:24,520 --> 00:06:27,919 Speaker 1: is is that performance segment. And you look at uh, 115 00:06:28,360 --> 00:06:32,760 Speaker 1: you know, Tim kneskis at at Chrysler, who's a maniac 116 00:06:32,800 --> 00:06:34,880 Speaker 1: in a good way, you know, and you have hell 117 00:06:35,000 --> 00:06:38,000 Speaker 1: cats and demons. And I'm glad because I was, you know, 118 00:06:38,040 --> 00:06:41,479 Speaker 1: I was looking at a seventeen Camaro to SS you know, 119 00:06:41,520 --> 00:06:45,600 Speaker 1: the fiftieth anniversary edition. Yeah, those I think you're okay there. 120 00:06:45,640 --> 00:06:48,200 Speaker 1: I think that that the performance stuff and even if 121 00:06:48,200 --> 00:06:51,200 Speaker 1: you look at Cadillac, the V series stuff, and even 122 00:06:51,240 --> 00:06:55,040 Speaker 1: in the luxury segments, I think performances is a little 123 00:06:55,080 --> 00:06:58,200 Speaker 1: bit protected. People will always want that and the physics 124 00:06:58,279 --> 00:07:00,880 Speaker 1: just don't work as well in trucks. So there, I 125 00:07:00,920 --> 00:07:03,680 Speaker 1: think you're okay. I think it's it's the garden variety, 126 00:07:03,800 --> 00:07:09,000 Speaker 1: the sort of commodity cars. How about the Lincoln in China. Yeah, 127 00:07:09,040 --> 00:07:12,040 Speaker 1: you know, And I think that that markets outside of 128 00:07:12,080 --> 00:07:15,040 Speaker 1: the US will adjust to things and taste are a 129 00:07:15,040 --> 00:07:19,040 Speaker 1: little bit different. Whether it's weather, congestion, there's issues that 130 00:07:19,080 --> 00:07:21,560 Speaker 1: go into it to what the consumer prefers. But we're 131 00:07:21,560 --> 00:07:25,720 Speaker 1: also seeing globally, even in Europe, we're seeing a mixed 132 00:07:25,720 --> 00:07:30,720 Speaker 1: shift to trucks because we can do more with fuel economy, lightweighting. 133 00:07:30,760 --> 00:07:35,240 Speaker 1: We're getting better driving dynamics out of truck bodies than 134 00:07:35,280 --> 00:07:38,360 Speaker 1: we than we ever have, and it's it's helping shift 135 00:07:38,720 --> 00:07:42,080 Speaker 1: away from cars to trucks. Thanks very much for illuminating 136 00:07:42,080 --> 00:07:45,720 Speaker 1: all this force and talking cars. Kevin Tynan. He's our 137 00:07:45,800 --> 00:07:50,040 Speaker 1: senior a senior auto's analyst for Bloomberg Intelligence, and you 138 00:07:50,080 --> 00:08:06,840 Speaker 1: can follow him on Twitter at keV Tynan Ten, Lisa Abrams. 139 00:08:06,880 --> 00:08:11,000 Speaker 1: We've been learning a lot about artificial intelligence robots. You know, 140 00:08:11,040 --> 00:08:14,720 Speaker 1: I think that three D printing can also be included 141 00:08:14,920 --> 00:08:18,800 Speaker 1: in that particular list. Because there is a huge conference 142 00:08:18,880 --> 00:08:21,800 Speaker 1: that is going to take place beginning tomorrow at the 143 00:08:21,920 --> 00:08:26,360 Speaker 1: Javits Center, and it is inside three D printing. It's 144 00:08:26,400 --> 00:08:28,720 Speaker 1: the conference and the expo. It's got thirty eight events. 145 00:08:28,800 --> 00:08:33,640 Speaker 1: It's the largest event worldwide. And get this the presentation. 146 00:08:33,760 --> 00:08:36,400 Speaker 1: One of them is by Dr Orn Temper and he 147 00:08:36,520 --> 00:08:41,320 Speaker 1: uses three D printing in plastic and reconstructive surgery. Let's 148 00:08:41,400 --> 00:08:43,360 Speaker 1: learn more about all of these things. We want to 149 00:08:43,360 --> 00:08:47,959 Speaker 1: bring in Tyler Benster, general partner at Asimov Ventures in Seattle, Washington. 150 00:08:48,120 --> 00:08:52,080 Speaker 1: Also Samil Hargovn, co founder and CEO of We've spelled 151 00:08:52,320 --> 00:08:55,800 Speaker 1: w I I VV might not be exactly intuitive in 152 00:08:55,880 --> 00:08:59,760 Speaker 1: San Diego, California. So Tyler, I want to start with you, 153 00:09:00,240 --> 00:09:02,600 Speaker 1: what do you think is going to be the hottest 154 00:09:02,679 --> 00:09:05,720 Speaker 1: development at this three D printing conference this year? So 155 00:09:05,720 --> 00:09:07,920 Speaker 1: it's a really exciting year for three D printing. We've 156 00:09:07,920 --> 00:09:09,959 Speaker 1: been saying for a long time in industry, how three 157 00:09:10,040 --> 00:09:12,280 Speaker 1: D printing is going to go mainstream and key where 158 00:09:12,280 --> 00:09:15,120 Speaker 1: they're going to and I think Seen is the year 159 00:09:15,160 --> 00:09:17,960 Speaker 1: where we actually are seeing this happen. So we have 160 00:09:17,960 --> 00:09:20,440 Speaker 1: a few new developments. UM on the medical side has 161 00:09:20,480 --> 00:09:24,120 Speaker 1: highlighted earlier with dr Orn incredible new developments going on 162 00:09:24,160 --> 00:09:27,640 Speaker 1: in implants, orthopedic game plants, companies like added to orthopedics. 163 00:09:27,679 --> 00:09:31,560 Speaker 1: We have a wonderful new technologies that are allowing doctors 164 00:09:31,559 --> 00:09:34,880 Speaker 1: to literally save lives and separate can join twins bas 165 00:09:34,880 --> 00:09:37,560 Speaker 1: surgical planning and actual surgical cutting guides. And then we 166 00:09:37,559 --> 00:09:40,160 Speaker 1: have this whole new movement in medals where we're finally 167 00:09:40,160 --> 00:09:42,920 Speaker 1: starting to see this transition from three D printing is 168 00:09:42,920 --> 00:09:46,160 Speaker 1: a prototyping technology to want to finished good production. And 169 00:09:46,200 --> 00:09:48,120 Speaker 1: I know that we're really delighted to have Shamille on 170 00:09:48,160 --> 00:09:51,280 Speaker 1: here with us who has really been actually practicing finish 171 00:09:51,360 --> 00:09:54,840 Speaker 1: kid production in the flesh. I got a note that Shamil, 172 00:09:54,960 --> 00:09:58,240 Speaker 1: before you answer to the details of Weave, is that 173 00:09:58,679 --> 00:10:01,720 Speaker 1: you are the company. You're the CEO of the startup 174 00:10:01,760 --> 00:10:04,000 Speaker 1: company we've and you're trying to make it happen, and 175 00:10:04,040 --> 00:10:08,400 Speaker 1: you're wearing the suit. And Tyler, who happens to just 176 00:10:08,480 --> 00:10:11,400 Speaker 1: work at Asithma benches as a partner, he's the money guy. 177 00:10:11,800 --> 00:10:16,080 Speaker 1: He is wearing this Stanford hoodie. I mean, the contrast 178 00:10:16,280 --> 00:10:20,120 Speaker 1: cannot be better for for the setup. So I think 179 00:10:20,160 --> 00:10:22,480 Speaker 1: you you're on the bright path. Well, it's not every 180 00:10:22,559 --> 00:10:24,960 Speaker 1: day a startup CEO like me gets to get pulled 181 00:10:25,040 --> 00:10:27,360 Speaker 1: up to New York to give this conversation. Well, I 182 00:10:27,400 --> 00:10:29,800 Speaker 1: was going to say to you raised over five million 183 00:10:29,840 --> 00:10:32,880 Speaker 1: dollars in a series A financing just recently, right, Yes, sir, 184 00:10:32,960 --> 00:10:34,800 Speaker 1: all right, tell us what you're gonna do with the money. 185 00:10:35,080 --> 00:10:38,520 Speaker 1: And you've brought some things along, custom fit three D 186 00:10:38,720 --> 00:10:44,120 Speaker 1: printed insoles. Yes, yes, we are what I would say 187 00:10:44,280 --> 00:10:48,199 Speaker 1: actually doing it today, which is manufacturing in America three 188 00:10:48,280 --> 00:10:52,560 Speaker 1: D printed final product. And specifically we're working with custom 189 00:10:52,640 --> 00:10:57,000 Speaker 1: footwear which you order by measuring your feet using your smartphone, 190 00:10:57,600 --> 00:11:00,400 Speaker 1: and from there we are able to say into your 191 00:11:00,400 --> 00:11:03,280 Speaker 1: product in under seven days. And what I'm here to 192 00:11:03,320 --> 00:11:06,040 Speaker 1: tell you is for the footwear and apparel industry, like 193 00:11:06,440 --> 00:11:09,560 Speaker 1: like many other industries, made in America, is starting to 194 00:11:09,600 --> 00:11:12,800 Speaker 1: make business sense again in order to offer consumers that 195 00:11:12,880 --> 00:11:15,080 Speaker 1: kinds of products that they expect and want. Can I 196 00:11:15,120 --> 00:11:19,240 Speaker 1: can I just ask Shamille, what's the difference between a 197 00:11:19,280 --> 00:11:22,800 Speaker 1: machine that is automated and you know, just that's maybe 198 00:11:22,880 --> 00:11:26,280 Speaker 1: directed by one person somewhere at least overseen, which we've 199 00:11:26,280 --> 00:11:30,880 Speaker 1: seen for years. And three D printing, Yeah, and three 200 00:11:30,920 --> 00:11:34,280 Speaker 1: D printing it essentially allows you to take the complexity 201 00:11:34,320 --> 00:11:38,120 Speaker 1: away from the human uh and and and it digitally 202 00:11:38,280 --> 00:11:41,120 Speaker 1: is able to make the complex custom parts of products 203 00:11:41,160 --> 00:11:43,720 Speaker 1: that you need. And what we do is we marry 204 00:11:43,720 --> 00:11:47,000 Speaker 1: that with with sort of traditional manufacturing to make what 205 00:11:47,040 --> 00:11:50,880 Speaker 1: we called hybrid products. Okay, and then Tyler, I wanted 206 00:11:50,920 --> 00:11:53,400 Speaker 1: to ask you. You you talked about how this is 207 00:11:53,440 --> 00:11:56,600 Speaker 1: the year that three D printing is going to go mainstream. 208 00:11:56,720 --> 00:11:59,600 Speaker 1: What gives you confidence to say that? Well, I think 209 00:11:59,640 --> 00:12:02,240 Speaker 1: if we trace where the investment in R and D 210 00:12:02,360 --> 00:12:04,800 Speaker 1: has been going into we've seen an explosion on the 211 00:12:04,880 --> 00:12:07,440 Speaker 1: venture capital side. In sixteen, we had more than a 212 00:12:07,480 --> 00:12:10,800 Speaker 1: quarter billion dollars flow into startups UM, which was really 213 00:12:10,800 --> 00:12:13,560 Speaker 1: outstripping the public markets for the first time. UM. We 214 00:12:13,600 --> 00:12:16,319 Speaker 1: also have seen an incredible increase in M and a 215 00:12:16,320 --> 00:12:18,560 Speaker 1: activity of d E snatching up to the largest metal 216 00:12:18,600 --> 00:12:21,760 Speaker 1: companies UM. We've seen a large uptick in investments in 217 00:12:21,760 --> 00:12:24,200 Speaker 1: that sector. And I think that we're starting to see 218 00:12:24,200 --> 00:12:27,079 Speaker 1: this growth really being driven by the bottom up. If 219 00:12:27,080 --> 00:12:29,360 Speaker 1: we look at what's happening like with Stratesis is outlook 220 00:12:29,400 --> 00:12:32,960 Speaker 1: for seen and the public markets reaction, I think that 221 00:12:33,080 --> 00:12:34,800 Speaker 1: the markets are in agreement that a lot of this 222 00:12:34,840 --> 00:12:36,960 Speaker 1: growth is being driven by the small disruptive players that 223 00:12:36,960 --> 00:12:40,200 Speaker 1: are moving quickly. Well, you mentioned Stratusis, and I mean, boy, 224 00:12:40,280 --> 00:12:42,760 Speaker 1: if you're an investor in Stratusists, you have watched it 225 00:12:44,160 --> 00:12:47,200 Speaker 1: move high and then move low. And in fact, they 226 00:12:47,280 --> 00:12:49,280 Speaker 1: just released their results I guess it was on March 227 00:12:49,360 --> 00:12:52,520 Speaker 1: the seventh, and while the results were great for the 228 00:12:52,600 --> 00:12:56,240 Speaker 1: previous time period, their guidance and you know they were 229 00:12:56,280 --> 00:12:58,120 Speaker 1: not giving the kind of guidance any of the stock 230 00:12:58,240 --> 00:13:01,000 Speaker 1: ended up down about nine percent just that particular day. 231 00:13:01,040 --> 00:13:04,160 Speaker 1: So it's been rough going for them. Uh, Shamille, I 232 00:13:04,240 --> 00:13:06,240 Speaker 1: want you to just talk a little bit about your 233 00:13:06,280 --> 00:13:10,079 Speaker 1: background because this was a kickstarter campaign, right, I mean 234 00:13:10,120 --> 00:13:13,160 Speaker 1: that's how it all started. And now what you've managed 235 00:13:13,200 --> 00:13:16,360 Speaker 1: to purchase the Souls I love this e Souls is 236 00:13:16,400 --> 00:13:20,959 Speaker 1: a company that has a database of foot scans. Tell 237 00:13:21,040 --> 00:13:24,720 Speaker 1: us what that gives you? Yeah? Absolutely? Uh, you know, 238 00:13:24,880 --> 00:13:27,720 Speaker 1: to really build out this vision. What we're seeing in 239 00:13:27,720 --> 00:13:30,480 Speaker 1: the market is the big players like Apple Intel and 240 00:13:30,559 --> 00:13:34,480 Speaker 1: Google are spending Microsoft included are spending hundreds of millions 241 00:13:34,520 --> 00:13:36,839 Speaker 1: and dollars and three D scan and they're gonna bring 242 00:13:36,880 --> 00:13:39,440 Speaker 1: this to your phone very soon. And then you've got 243 00:13:39,520 --> 00:13:42,800 Speaker 1: Carbon and Hewlett Packard and Stratusis and three D systems 244 00:13:42,800 --> 00:13:46,160 Speaker 1: working on the printer engines. Now why this Soul's acquisition 245 00:13:46,160 --> 00:13:48,600 Speaker 1: was important for us? Is it meant that we now 246 00:13:48,679 --> 00:13:51,680 Speaker 1: have a bigger database of three D scans that we 247 00:13:51,720 --> 00:13:54,880 Speaker 1: can feed to train our technology to take that scan 248 00:13:55,000 --> 00:13:58,640 Speaker 1: and turn it into an STV STL file more efficiently. 249 00:13:58,640 --> 00:14:01,559 Speaker 1: That's the file format most pree in three D printing today. 250 00:14:01,679 --> 00:14:05,400 Speaker 1: And so that's really more new that fifty thousand scans 251 00:14:05,440 --> 00:14:07,959 Speaker 1: of three D scans of your feet would be worth 252 00:14:08,000 --> 00:14:10,600 Speaker 1: that much on it Well, well, Tyler, though, I wanted 253 00:14:10,640 --> 00:14:12,480 Speaker 1: to ask that that brings me to the next question, 254 00:14:12,520 --> 00:14:15,439 Speaker 1: which is where does the real money lie. Is it 255 00:14:15,559 --> 00:14:19,080 Speaker 1: in the programming behind the three D printers? Is it 256 00:14:19,200 --> 00:14:22,560 Speaker 1: in the actual machines that can take the technology and 257 00:14:22,600 --> 00:14:25,160 Speaker 1: make it into uh, make it into action? Where does 258 00:14:25,160 --> 00:14:28,320 Speaker 1: it go? So today it's very much on the material side. 259 00:14:28,360 --> 00:14:30,320 Speaker 1: It's the razor razor blades model, where if you look 260 00:14:30,320 --> 00:14:33,120 Speaker 1: at the margins and industry. We see margins as high 261 00:14:33,160 --> 00:14:35,760 Speaker 1: as a thousand percent on the raw feedstock, which is 262 00:14:35,800 --> 00:14:39,440 Speaker 1: pretty incredible considering most manufacturing margins. However, I think in 263 00:14:39,480 --> 00:14:41,640 Speaker 1: the long term, as the patent landscape has started to 264 00:14:41,680 --> 00:14:44,600 Speaker 1: shake out in competition has really increased, we're going to 265 00:14:44,600 --> 00:14:47,560 Speaker 1: see the long term margins on three D printing drop 266 00:14:47,640 --> 00:14:50,800 Speaker 1: to about two to three, which is the manufacturing standard. 267 00:14:51,200 --> 00:14:53,280 Speaker 1: I think that much of the VIA will be captured, 268 00:14:53,320 --> 00:14:56,320 Speaker 1: as we've seen in electronics, by the design. So companies 269 00:14:56,360 --> 00:14:58,320 Speaker 1: are really going to be able to command high premium 270 00:14:58,520 --> 00:15:01,960 Speaker 1: if they have a proprietary sort vertically integrated, and end 271 00:15:01,960 --> 00:15:05,640 Speaker 1: experience that is really i P driven design. If I 272 00:15:05,680 --> 00:15:08,440 Speaker 1: may just echo what Tyler said, you know, one thing 273 00:15:08,480 --> 00:15:12,120 Speaker 1: hasn't changed, making a product that people want and then 274 00:15:12,200 --> 00:15:15,760 Speaker 1: marketing that product that that hasn't changed fundamentally. So for 275 00:15:15,880 --> 00:15:18,520 Speaker 1: us as we've we've even learned that as we've gone 276 00:15:18,520 --> 00:15:20,880 Speaker 1: about what we're doing. It was one thing to figure 277 00:15:20,920 --> 00:15:22,920 Speaker 1: out the technology, but it was another thing to build 278 00:15:22,960 --> 00:15:25,080 Speaker 1: the market and have people realize you can actually get 279 00:15:25,120 --> 00:15:27,760 Speaker 1: these end products. And so having the brand in the 280 00:15:27,640 --> 00:15:30,880 Speaker 1: in the market and having a product people want is key. 281 00:15:30,880 --> 00:15:33,040 Speaker 1: Thank you so much for joining us. This is really interesting. 282 00:15:33,400 --> 00:15:36,920 Speaker 1: Tyler Benster, general partner at Asthma Ventures in Seattle, Washington. 283 00:15:37,040 --> 00:15:39,040 Speaker 1: Here with us in our Bloomberg eleven three studio. Also 284 00:15:39,040 --> 00:15:42,480 Speaker 1: with us Shamil Hargovan, co founder and CEO of We've 285 00:15:42,600 --> 00:15:58,440 Speaker 1: in San Diego, California. I am so excited about our 286 00:15:59,080 --> 00:16:02,360 Speaker 1: next guest. He is a long time UH person who 287 00:16:02,360 --> 00:16:05,440 Speaker 1: I have looked up to tremendously cast Sunseen Harvard Professor, 288 00:16:05,760 --> 00:16:11,120 Speaker 1: Bloomberg View contributor and author of hashtag Republic, Divided Democracy 289 00:16:11,240 --> 00:16:14,120 Speaker 1: in the Age of Social Media. UH. He comes to 290 00:16:14,200 --> 00:16:16,480 Speaker 1: us now casts. Thank you so much for joining us UH. 291 00:16:16,920 --> 00:16:20,080 Speaker 1: This the premise of this book is fascinating that basically 292 00:16:20,360 --> 00:16:23,960 Speaker 1: the new challenge to democracy is the way that increasing 293 00:16:24,000 --> 00:16:26,160 Speaker 1: technology is allowing people to sort of live in their 294 00:16:26,160 --> 00:16:28,440 Speaker 1: own bubbles without getting exposure to one another. Can you 295 00:16:28,440 --> 00:16:31,320 Speaker 1: explain what drew you to this and and how severe 296 00:16:31,760 --> 00:16:35,440 Speaker 1: this problem was as you found? Well, I guess I've 297 00:16:35,440 --> 00:16:37,880 Speaker 1: been drawn to it since the beginning of the Internet, 298 00:16:37,880 --> 00:16:41,560 Speaker 1: when you could see that the UH capacity for people 299 00:16:41,600 --> 00:16:44,960 Speaker 1: to sort themselves and little kind of mirrors where they're 300 00:16:45,000 --> 00:16:48,600 Speaker 1: just looking at mirrors of oneself or people who have 301 00:16:48,640 --> 00:16:53,200 Speaker 1: the same view as oneself at least, that capacity just skyrocketed. 302 00:16:53,680 --> 00:16:57,000 Speaker 1: And in the recent past we've seen it in the elections, 303 00:16:57,000 --> 00:16:59,960 Speaker 1: of course, but also in political discussion that would say 304 00:17:00,000 --> 00:17:02,800 Speaker 1: spook and Twitter. And of course, with your ability to 305 00:17:03,240 --> 00:17:07,600 Speaker 1: just scoot from one congenial view to another, you can 306 00:17:07,680 --> 00:17:10,679 Speaker 1: just hear topics and points of view that make you 307 00:17:10,720 --> 00:17:13,560 Speaker 1: feel like you're in a cozy little cocoon. And that's 308 00:17:14,000 --> 00:17:18,560 Speaker 1: uh comforting cocoons are, but it's also a form of 309 00:17:18,560 --> 00:17:21,760 Speaker 1: prison for individuals and for democracy. It's it's a danger, 310 00:17:22,960 --> 00:17:25,240 Speaker 1: uh ms Sunstein. I wonder if you could just give 311 00:17:25,280 --> 00:17:28,240 Speaker 1: us a little bit of your historical perspective, because I 312 00:17:28,280 --> 00:17:30,480 Speaker 1: note that you know, in September two thousand nine, you 313 00:17:30,520 --> 00:17:34,440 Speaker 1: were confirmed as the director of the White House omb 314 00:17:34,600 --> 00:17:39,840 Speaker 1: Office of Information and Regulatory Affairs. Uh. This is an 315 00:17:39,840 --> 00:17:44,360 Speaker 1: important agency, and I'm wondering if you could just describe 316 00:17:44,400 --> 00:17:48,120 Speaker 1: its work and what you see happening to the current 317 00:17:49,160 --> 00:17:52,520 Speaker 1: Office of Information and Regulatory Affairs. And as much as 318 00:17:52,920 --> 00:17:57,080 Speaker 1: President Donald Trump has asked for agency wide reviews to 319 00:17:57,160 --> 00:18:00,560 Speaker 1: reduce regulations, sure so the goal of the office, which 320 00:18:00,600 --> 00:18:04,960 Speaker 1: goes back to President Reagan, is to oversee environmental regulation, 321 00:18:05,160 --> 00:18:09,120 Speaker 1: safety regulation, labor health, lots of stuff, including some national 322 00:18:09,200 --> 00:18:12,520 Speaker 1: security stuff, and to make sure basically it's consistent with 323 00:18:12,560 --> 00:18:15,800 Speaker 1: the law that the costs are under control and the 324 00:18:15,800 --> 00:18:19,879 Speaker 1: benefits justify the costs. So it's not the most visible office, 325 00:18:19,960 --> 00:18:22,200 Speaker 1: but it is an office that has a pretty central 326 00:18:22,359 --> 00:18:25,960 Speaker 1: role in affecting things that affect people every day. UM. 327 00:18:26,160 --> 00:18:29,320 Speaker 1: Under President Trump, it could go in two different directions 328 00:18:29,359 --> 00:18:32,320 Speaker 1: where still at early days, UH, there's some signs of 329 00:18:33,320 --> 00:18:37,439 Speaker 1: kind of making sure that if we're going to be 330 00:18:37,480 --> 00:18:41,879 Speaker 1: issuing new regulations in an economically challenging time, they really 331 00:18:42,200 --> 00:18:46,760 Speaker 1: survive some sort of hurdle of justification. And that's accompanied 332 00:18:46,760 --> 00:18:48,919 Speaker 1: by an idea if you're going to issue one, you 333 00:18:48,960 --> 00:18:52,440 Speaker 1: have to get rid of too. Now, in principle that's 334 00:18:52,440 --> 00:18:54,959 Speaker 1: not the best idea in the world, because you may 335 00:18:55,000 --> 00:18:57,159 Speaker 1: have one good one and not too bad ones to 336 00:18:57,200 --> 00:19:00,840 Speaker 1: get rid of. But in practice, UH, the people in 337 00:19:00,880 --> 00:19:03,440 Speaker 1: the Office of Information Regulatory Affairs, I think they can 338 00:19:03,440 --> 00:19:06,119 Speaker 1: make it work, certainly for a year or two. So 339 00:19:06,200 --> 00:19:09,000 Speaker 1: one direction is just have a lot of discipline about 340 00:19:09,119 --> 00:19:12,680 Speaker 1: new regulations going out. UH. And I would favor that 341 00:19:12,680 --> 00:19:15,480 Speaker 1: that's continuous with a lot of things I've worked on 342 00:19:15,560 --> 00:19:18,760 Speaker 1: when I was there, and Another direction, which isn't so 343 00:19:18,800 --> 00:19:21,560 Speaker 1: good is what has been referred to as the deconstruction 344 00:19:21,560 --> 00:19:24,720 Speaker 1: of the administrative state. Probably some people nod their heads 345 00:19:24,760 --> 00:19:26,480 Speaker 1: when they hear that word, even though it comes from 346 00:19:26,480 --> 00:19:29,480 Speaker 1: a French literary theorist who, Uh, the critics of the 347 00:19:29,520 --> 00:19:33,560 Speaker 1: administrative state don't like so much the French literary people. Um, 348 00:19:33,600 --> 00:19:35,920 Speaker 1: but I think nodding the head isn't a very good 349 00:19:35,960 --> 00:19:40,679 Speaker 1: idea because there's UH safety regulation that prevent deaths on 350 00:19:40,720 --> 00:19:43,960 Speaker 1: the highways, their safety regulation that make sure our food 351 00:19:44,040 --> 00:19:47,320 Speaker 1: is safe, and there's UH safety regulation that makes sure 352 00:19:47,400 --> 00:19:50,040 Speaker 1: that our error is clean to breathe, and deconstruction of 353 00:19:50,040 --> 00:19:52,920 Speaker 1: the administrative state wouldn't be the best idea. So there's 354 00:19:52,960 --> 00:19:55,879 Speaker 1: a long way of saying, Uh, Trump administration could go 355 00:19:55,960 --> 00:19:58,680 Speaker 1: in one of two directions, and the first direction isn't 356 00:19:58,680 --> 00:20:01,320 Speaker 1: so bad. You know. I want to go back to 357 00:20:01,359 --> 00:20:03,720 Speaker 1: the point that you're making about people sort of seeing 358 00:20:04,680 --> 00:20:07,520 Speaker 1: themselves in mirrors or seeing their ideas just in mirrors, 359 00:20:07,640 --> 00:20:10,480 Speaker 1: and how that, I mean arguably has dictated what we 360 00:20:10,520 --> 00:20:13,200 Speaker 1: are seeing right now in the current political cycle. Uh 361 00:20:13,240 --> 00:20:17,719 Speaker 1: that's my extrapolation, not necessarily yours, but uh, but I'm 362 00:20:17,760 --> 00:20:21,000 Speaker 1: wondering how much are you seeing that in academia, because 363 00:20:21,200 --> 00:20:25,400 Speaker 1: you know what people think of uh institutions, academic institutions 364 00:20:25,400 --> 00:20:28,439 Speaker 1: being a bastion of of thought and in conversation. But 365 00:20:28,480 --> 00:20:31,160 Speaker 1: often there isn't a lot of diversity of views even 366 00:20:31,200 --> 00:20:34,440 Speaker 1: among the professors. Well, I don't see a whole lot 367 00:20:34,480 --> 00:20:37,119 Speaker 1: in academia, I confess, but that this may be my 368 00:20:37,200 --> 00:20:39,399 Speaker 1: limited travels. So I spent a long time at the 369 00:20:39,440 --> 00:20:42,200 Speaker 1: University of Chicago, and if you go through a day 370 00:20:42,240 --> 00:20:45,760 Speaker 1: without hearing twenty different views, you're probably just staying in 371 00:20:45,760 --> 00:20:50,680 Speaker 1: your office. UH. And the universities, even though they're often 372 00:20:50,720 --> 00:20:55,480 Speaker 1: reputed to be echo chamber areas, UM my own experience, 373 00:20:55,520 --> 00:20:58,359 Speaker 1: as I say, is as they just aren't. So some 374 00:20:58,440 --> 00:21:00,359 Speaker 1: of the places that are supposed to be left the 375 00:21:00,400 --> 00:21:03,720 Speaker 1: center and kind of Obama territory, there are people who 376 00:21:03,760 --> 00:21:06,960 Speaker 1: think that Obama was awful and you know, and that 377 00:21:07,040 --> 00:21:09,520 Speaker 1: the Trump direction is much better, and then we need 378 00:21:09,600 --> 00:21:11,919 Speaker 1: some conservatives in charge. And there are places that are 379 00:21:11,920 --> 00:21:15,120 Speaker 1: supposed to be conservative bastions where there are people who say, 380 00:21:15,200 --> 00:21:18,000 Speaker 1: you know what, the Democrats have some really good ideas. 381 00:21:18,320 --> 00:21:21,240 Speaker 1: So I think it's a problem in the political domain 382 00:21:21,320 --> 00:21:25,040 Speaker 1: where people self stored into little cocoons, and they regard 383 00:21:25,080 --> 00:21:29,359 Speaker 1: their fellow citizens as traders or enemies or you know, 384 00:21:29,440 --> 00:21:32,960 Speaker 1: deeply confused or in the crip of lies. That seems 385 00:21:33,000 --> 00:21:35,040 Speaker 1: to me a much more serious problem than what the 386 00:21:35,040 --> 00:21:37,720 Speaker 1: professors are doing. Do you have any hope that the 387 00:21:37,840 --> 00:21:41,960 Speaker 1: situation will improve where people will seek out views the 388 00:21:42,040 --> 00:21:44,400 Speaker 1: disagree with their own. Well, one of the great things 389 00:21:44,400 --> 00:21:48,200 Speaker 1: about our country is that we're not hopeless, and that's 390 00:21:48,320 --> 00:21:52,879 Speaker 1: meant has a pun. It's first, we're not pessimistic, and second, 391 00:21:52,920 --> 00:21:56,439 Speaker 1: we have capacity to put the future in our own hands. 392 00:21:56,560 --> 00:21:59,400 Speaker 1: That's what we the people did a long time ago, 393 00:21:59,560 --> 00:22:03,879 Speaker 1: and we've that repeatedly since. So the fact is that 394 00:22:04,119 --> 00:22:07,280 Speaker 1: what our communications world is is if it's a world 395 00:22:07,400 --> 00:22:10,680 Speaker 1: of self sorting where we uh, you know, just learned 396 00:22:10,760 --> 00:22:14,359 Speaker 1: a single thing about civil rights, let's say that maybe 397 00:22:14,400 --> 00:22:16,399 Speaker 1: not be true or at least is in the full picture, 398 00:22:16,600 --> 00:22:19,040 Speaker 1: or we learned a bunch of different things, depends on 399 00:22:19,080 --> 00:22:23,840 Speaker 1: our own choices, both as individuals and people are providing 400 00:22:23,840 --> 00:22:26,880 Speaker 1: the stuff. So I think that there are some good 401 00:22:26,920 --> 00:22:31,040 Speaker 1: signs that Facebook is reassessing it's a news feed. It's 402 00:22:31,040 --> 00:22:34,440 Speaker 1: news feed is really an echo chamber generator in my view, 403 00:22:34,560 --> 00:22:37,359 Speaker 1: and it's reassessing that, so we're going to see some 404 00:22:37,480 --> 00:22:40,399 Speaker 1: changes on the individual side and on the provider side 405 00:22:40,400 --> 00:22:42,480 Speaker 1: in the next few years. Thank you very much for 406 00:22:42,520 --> 00:22:45,639 Speaker 1: spending time with us. Professor Cass Sunstein is a Bloomberg 407 00:22:45,680 --> 00:22:50,040 Speaker 1: View contributor. He's also a professor at Harvard University. His 408 00:22:50,119 --> 00:22:54,879 Speaker 1: new book is entitled Hashtag Republic, Divided Democracy in the 409 00:22:55,040 --> 00:23:11,840 Speaker 1: Age of Social Media shares a mobile I are hired 410 00:23:11,840 --> 00:23:15,000 Speaker 1: by nearly thirty percent. This comes after the announcement that 411 00:23:15,160 --> 00:23:20,000 Speaker 1: Intel will pay fifteen billion dollars for this technology company. 412 00:23:20,440 --> 00:23:26,159 Speaker 1: It provides vision based advanced driver assistance systems. This is 413 00:23:26,200 --> 00:23:30,160 Speaker 1: everything from lane and vehicle detection, adaptive cruise control, traffic 414 00:23:30,240 --> 00:23:33,480 Speaker 1: sign recognition. Here to tell us more on en trine 415 00:23:33,480 --> 00:23:37,440 Speaker 1: of us in our senior Semiconductor and Hardware analyst for 416 00:23:37,520 --> 00:23:41,439 Speaker 1: Bloomberg Intelligence, he never takes his hands off the wheel 417 00:23:41,880 --> 00:23:45,040 Speaker 1: on on. Thank you so much for giving us your time. 418 00:23:45,080 --> 00:23:47,680 Speaker 1: I know on your well learned holiday, but I want 419 00:23:47,720 --> 00:23:50,359 Speaker 1: to get your thoughts on what is it about a 420 00:23:50,359 --> 00:23:53,320 Speaker 1: company that has three hundred and sixty million in sales 421 00:23:53,400 --> 00:23:56,639 Speaker 1: getting bought for fifteen billion dollars. Can't you do a 422 00:23:56,640 --> 00:24:00,000 Speaker 1: lot with fifteen billion they certainly can. You can build 423 00:24:00,040 --> 00:24:02,560 Speaker 1: the new fab and then some UM. But look, this 424 00:24:02,680 --> 00:24:05,920 Speaker 1: is the future of semi conductors, right. I mean, if 425 00:24:05,920 --> 00:24:07,840 Speaker 1: you look at the handset market, it's slowing. If you 426 00:24:07,880 --> 00:24:10,240 Speaker 1: look at the PC market, it's slowing. The server market 427 00:24:10,840 --> 00:24:14,600 Speaker 1: is more competitive and that's slowing as well. So everybody's 428 00:24:14,680 --> 00:24:20,000 Speaker 1: all um UM driving fans UM towards the auto semic 429 00:24:20,000 --> 00:24:23,080 Speaker 1: conductor market. But the promise that it is large, it 430 00:24:23,240 --> 00:24:28,159 Speaker 1: is profitable, and it is fast growing. Now with autos, 431 00:24:28,320 --> 00:24:32,360 Speaker 1: there's a special tweak in in that you whatever design 432 00:24:32,400 --> 00:24:34,480 Speaker 1: winds that you have, if you get into a car 433 00:24:35,119 --> 00:24:37,280 Speaker 1: with a new system, you don't see revenues for a 434 00:24:37,320 --> 00:24:40,280 Speaker 1: couple more years because it has to be tested extensively 435 00:24:40,359 --> 00:24:44,760 Speaker 1: before products are shipped out. It's very different from consumer electronics. 436 00:24:44,800 --> 00:24:50,200 Speaker 1: So the thirteen UM revenue that they're playing forty three 437 00:24:50,240 --> 00:24:55,119 Speaker 1: times Stralian common sales UH, it's obviously growing very fast, 438 00:24:55,280 --> 00:24:57,919 Speaker 1: but the true growth potential of that is not going 439 00:24:57,960 --> 00:25:01,680 Speaker 1: to be visible for several years UM. And that's part 440 00:25:01,800 --> 00:25:03,520 Speaker 1: of the issue because we're not going to be able 441 00:25:03,560 --> 00:25:06,119 Speaker 1: to see it. The gross margins are better than that 442 00:25:06,200 --> 00:25:09,960 Speaker 1: the Intel of Intel, and it's UM it's in a 443 00:25:10,000 --> 00:25:13,359 Speaker 1: segment that you can't easily design your way into. So 444 00:25:13,600 --> 00:25:17,200 Speaker 1: many is uh is the smart route and mobilize a 445 00:25:17,240 --> 00:25:19,560 Speaker 1: great company. But the question is you know you're right? 446 00:25:20,240 --> 00:25:22,720 Speaker 1: Did they do they overpay? We? We won't know to 447 00:25:22,720 --> 00:25:25,040 Speaker 1: be quite on it for five years. Well, so, can 448 00:25:25,040 --> 00:25:27,359 Speaker 1: you give us a sense of just how competitive the 449 00:25:27,480 --> 00:25:31,960 Speaker 1: landscape is for becoming sort of the data provider of 450 00:25:32,000 --> 00:25:34,960 Speaker 1: the system provider for autonomous cars? I mean, it seems 451 00:25:34,960 --> 00:25:37,600 Speaker 1: like Intel is trying to position itself to be the 452 00:25:37,760 --> 00:25:41,159 Speaker 1: number one provider of that type of of data system 453 00:25:41,320 --> 00:25:45,320 Speaker 1: and technology technological system. But who are its competitors and uh, 454 00:25:45,520 --> 00:25:48,320 Speaker 1: what's the sort of market share potentially look like down 455 00:25:48,320 --> 00:25:51,840 Speaker 1: the line. Yeah, it's that's that's a great question, and 456 00:25:52,480 --> 00:25:55,760 Speaker 1: it's got a cloudy two part answer, which is one 457 00:25:56,040 --> 00:26:00,200 Speaker 1: is that the architecture of technology in cars, it's help 458 00:26:00,320 --> 00:26:03,360 Speaker 1: is changing. Companies like in Vidia and now inte are 459 00:26:03,480 --> 00:26:06,840 Speaker 1: pitching for quote unquote um the guard box or the 460 00:26:06,920 --> 00:26:09,439 Speaker 1: one system to rule at all in the auto right, 461 00:26:09,480 --> 00:26:13,480 Speaker 1: So they want all auto technologies to coalesce around one 462 00:26:13,720 --> 00:26:17,840 Speaker 1: intelligent system it's artificially intelligent or talks to the data 463 00:26:17,840 --> 00:26:20,879 Speaker 1: center and will take you from point A to point 464 00:26:20,880 --> 00:26:25,199 Speaker 1: B with as little human intervention as possible. That's the 465 00:26:25,280 --> 00:26:29,879 Speaker 1: utopian scenario five ten years after. What exists now is 466 00:26:29,920 --> 00:26:34,920 Speaker 1: a bunch of disparate systems with as many as thirty 467 00:26:34,960 --> 00:26:40,000 Speaker 1: two and ten UM micro controller subsystems, anything from checking 468 00:26:40,040 --> 00:26:43,359 Speaker 1: your oil levels to your tryer pressure to UM to 469 00:26:43,440 --> 00:26:46,400 Speaker 1: seeing what the temperature is outside. And these systems don't 470 00:26:46,440 --> 00:26:49,920 Speaker 1: necessarily all talk to one another, and there's no central 471 00:26:50,640 --> 00:26:54,359 Speaker 1: um intelligent control points. So that's what it is today. 472 00:26:54,560 --> 00:26:59,040 Speaker 1: Companies like in Video, potentially Tesla, potentially Intel now are 473 00:26:59,080 --> 00:27:03,400 Speaker 1: all coalescing towards the future. It's a much slower market 474 00:27:03,520 --> 00:27:09,360 Speaker 1: to turn UM, particularly in advanced driver system systems that 475 00:27:09,359 --> 00:27:13,840 Speaker 1: that that everybody is pitching. The The number of things 476 00:27:13,960 --> 00:27:16,919 Speaker 1: that we need to do between here and the truly 477 00:27:17,040 --> 00:27:22,480 Speaker 1: driverless car is many, many, many, many folds. But here's 478 00:27:22,480 --> 00:27:25,360 Speaker 1: the flip site. You know, we sell roughly about eighty 479 00:27:25,400 --> 00:27:29,360 Speaker 1: million cars a year, and and each of those cars 480 00:27:29,400 --> 00:27:32,480 Speaker 1: contained somewhere in the the intern eighty dollars of silicon 481 00:27:33,000 --> 00:27:36,400 Speaker 1: that could go substantially higher, two, three, four or five 482 00:27:36,520 --> 00:27:40,639 Speaker 1: times higher based on whether it's a driverless car or 483 00:27:41,520 --> 00:27:45,320 Speaker 1: it's a semi driverless car. UM and so that's the 484 00:27:45,400 --> 00:27:49,480 Speaker 1: utopian scenario, and it becomes very very sticky. It's high 485 00:27:49,560 --> 00:27:53,719 Speaker 1: margin business is sticky business. Um, it's not as volatile 486 00:27:53,760 --> 00:27:57,080 Speaker 1: as the conserveral times. And that's me intell pitch. Here's 487 00:27:57,119 --> 00:28:00,280 Speaker 1: another utopian scenario. How about if you go public three 488 00:28:00,359 --> 00:28:02,800 Speaker 1: years ago, you raise a billion dollars and you have 489 00:28:02,840 --> 00:28:05,480 Speaker 1: a market cap of a little bit more than five billion. 490 00:28:06,000 --> 00:28:11,879 Speaker 1: Fast forward three years you sell out for fifteen billion UM. 491 00:28:12,040 --> 00:28:15,280 Speaker 1: Pretty nice chunk of change for the thunders. It's so great, 492 00:28:15,280 --> 00:28:19,200 Speaker 1: why are they selling? Look, I mean there's a point 493 00:28:19,200 --> 00:28:21,480 Speaker 1: to be made with respect to scale. If you look 494 00:28:21,640 --> 00:28:26,160 Speaker 1: at the semikinnecter industry in general, it is become one 495 00:28:26,200 --> 00:28:28,399 Speaker 1: of scale in terms of design, one of scale in 496 00:28:28,480 --> 00:28:32,640 Speaker 1: terms of factories, and one in terms of touch. Small 497 00:28:32,800 --> 00:28:39,360 Speaker 1: semiconductors companies in most spaces will become UM an oxymoron. 498 00:28:39,440 --> 00:28:42,240 Speaker 1: It's going to be very very tough to exist if 499 00:28:42,240 --> 00:28:44,720 Speaker 1: you don't have scale. Um, you're going to find it 500 00:28:44,880 --> 00:28:46,800 Speaker 1: very hard to compete with the likes of n XP, 501 00:28:47,000 --> 00:28:49,960 Speaker 1: which is now being acquired by Quantcom, which in fact 502 00:28:50,040 --> 00:28:52,280 Speaker 1: box free scale, which is the number one auto supplier. 503 00:28:52,400 --> 00:28:55,480 Speaker 1: So um, you're going to find it very very difficult 504 00:28:55,480 --> 00:28:58,880 Speaker 1: to compete with these beheamoth from an R and D perspective, 505 00:28:59,000 --> 00:29:03,080 Speaker 1: and for more, boy they're thinking, is that I get 506 00:29:03,120 --> 00:29:06,920 Speaker 1: a big R and D partner with Intel right an 507 00:29:06,920 --> 00:29:08,920 Speaker 1: on Street of Austin. Thank you so much for joining us. 508 00:29:08,920 --> 00:29:19,320 Speaker 1: He's senior Semiconductor and Hardware analyst for Bloomberg Intelligence. Thanks 509 00:29:19,360 --> 00:29:21,960 Speaker 1: for listening to the Bloomberg P and L podcast. You 510 00:29:22,000 --> 00:29:26,120 Speaker 1: can subscribe and listen to interviews at iTunes, SoundCloud, or 511 00:29:26,160 --> 00:29:30,240 Speaker 1: whatever podcast platform you prefer. I'm pim Fox. I'm out 512 00:29:30,240 --> 00:29:33,120 Speaker 1: there on Twitter at pim Fox. I'm out there on 513 00:29:33,160 --> 00:29:36,440 Speaker 1: Twitter at Lisa Abramo. It's one before the podcast. You 514 00:29:36,440 --> 00:29:39,080 Speaker 1: can always at catch us worldwide on Bloomberg Radio