1 00:00:03,640 --> 00:00:06,920 Speaker 1: From the heart of where innovation, money and power COLLI 2 00:00:07,760 --> 00:00:12,280 Speaker 1: in Silicon Valley and beyond. This is Bloomberg Technology with 3 00:00:12,360 --> 00:00:28,280 Speaker 1: Emily Jay. I'm Emily changing San Francisco, and this is 4 00:00:28,280 --> 00:00:31,160 Speaker 1: Bloomberg Technology coming up in the next hour. Lift posts 5 00:00:31,160 --> 00:00:34,440 Speaker 1: the highest earnings in the company history. As right hailing 6 00:00:34,479 --> 00:00:37,920 Speaker 1: companies near a full recovery from the pandemic, White supply 7 00:00:38,360 --> 00:00:42,960 Speaker 1: seems to be finally meeting demand. Plus coin based pops 8 00:00:43,000 --> 00:00:45,879 Speaker 1: after its deal with black Rock, reinforcing crypto status as 9 00:00:45,920 --> 00:00:49,240 Speaker 1: a serious player on Wall Street. Is the crypto winter 10 00:00:49,360 --> 00:00:54,480 Speaker 1: starting to thaw? We will discuss and an estimated food 11 00:00:54,520 --> 00:00:57,480 Speaker 1: process in the U S goes uneaten. We will chat 12 00:00:57,520 --> 00:01:00,160 Speaker 1: with a startup using AI to help grocers to ave 13 00:01:00,240 --> 00:01:03,840 Speaker 1: up to thirty four million pounds of food from going 14 00:01:03,880 --> 00:01:07,480 Speaker 1: to waste. I want to get back to with results 15 00:01:07,480 --> 00:01:10,080 Speaker 1: with our own Jackie Davalos, who covers the company for 16 00:01:10,240 --> 00:01:12,960 Speaker 1: us along with Uber and door Dash. So look, good 17 00:01:13,040 --> 00:01:15,680 Speaker 1: numbers from Lift, you know, is this the start of 18 00:01:15,720 --> 00:01:19,160 Speaker 1: a broader trend? Have left and Uber fully recovered from 19 00:01:19,200 --> 00:01:23,120 Speaker 1: the pandemic. They're certainly edging a lot closer now. Those 20 00:01:23,240 --> 00:01:26,560 Speaker 1: numbers for rides are still a little bit under pre 21 00:01:26,680 --> 00:01:28,960 Speaker 1: pandemic levels. But what we could see here is that 22 00:01:29,080 --> 00:01:32,240 Speaker 1: they're not sacrificing their profits in order to really boost 23 00:01:32,280 --> 00:01:34,720 Speaker 1: those numbers. And you saw that come through just st 24 00:01:34,720 --> 00:01:39,000 Speaker 1: even in the language that the CEOs were imparting to 25 00:01:39,120 --> 00:01:42,840 Speaker 1: analysts that look, you know, we went through really rigorous 26 00:01:42,880 --> 00:01:44,959 Speaker 1: cost cutting measures in the second quarter, and it was 27 00:01:45,040 --> 00:01:48,600 Speaker 1: tough to bear with employees being laid off and hiding 28 00:01:48,600 --> 00:01:51,040 Speaker 1: off that car rental business. But what we're seeing is 29 00:01:51,080 --> 00:01:54,880 Speaker 1: that airport travel is incredibly strong, a lot of that 30 00:01:55,000 --> 00:01:58,639 Speaker 1: coming from air trouble rebounding um and you're also seeing 31 00:01:58,640 --> 00:02:03,520 Speaker 1: you know, these markets a battles between Uper and Lift intensifying. 32 00:02:03,640 --> 00:02:07,000 Speaker 1: But I think a lot of the concern around Lift 33 00:02:07,080 --> 00:02:08,800 Speaker 1: was that they were going to see some of that 34 00:02:08,919 --> 00:02:12,120 Speaker 1: market share and their attempts to stay profitable, but we 35 00:02:12,120 --> 00:02:14,960 Speaker 1: were not seeing that come through so far. Well. I 36 00:02:14,960 --> 00:02:18,320 Speaker 1: did speak to Uber CEO Dar Causershi earlier this week. Again, 37 00:02:18,520 --> 00:02:23,200 Speaker 1: Uber's results strong as well and big positive investor reaction. 38 00:02:23,320 --> 00:02:26,080 Speaker 1: Take a listen to what causera he had to say. 39 00:02:26,880 --> 00:02:30,120 Speaker 1: The marketplace is more balanced. The number of new drivers 40 00:02:30,120 --> 00:02:31,960 Speaker 1: that we're adding in the US is up over se 41 00:02:32,680 --> 00:02:36,040 Speaker 1: on a year. On your basis surges down e t 42 00:02:36,240 --> 00:02:39,240 Speaker 1: A s or down. Uh. So the business is really 43 00:02:39,320 --> 00:02:41,519 Speaker 1: hitting on all cylinders and it's reflected in the stock 44 00:02:41,600 --> 00:02:45,320 Speaker 1: prus which is great. So does a rising tide lift 45 00:02:45,400 --> 00:02:50,600 Speaker 1: all boats? You know, if it's it's certain seems to 46 00:02:50,720 --> 00:02:54,840 Speaker 1: be because if you think about this shared rebound, both 47 00:02:54,960 --> 00:02:57,240 Speaker 1: Uber and Lift are benefiting from that. But where we 48 00:02:57,320 --> 00:02:59,720 Speaker 1: started to see some of the divergence was in the 49 00:03:00,000 --> 00:03:02,840 Speaker 1: adagies that they were taking to really get those drivers back. 50 00:03:02,960 --> 00:03:06,720 Speaker 1: That's really what's also driving the strong ridership because the 51 00:03:06,720 --> 00:03:08,919 Speaker 1: more drivers you have to meet the demand, the lower 52 00:03:08,919 --> 00:03:10,920 Speaker 1: your fares are going to go. More people are going 53 00:03:10,960 --> 00:03:12,920 Speaker 1: to get back to the platform instead of you know, 54 00:03:12,960 --> 00:03:17,280 Speaker 1: opting to take the taxi, a yellow cab or the subway. 55 00:03:17,360 --> 00:03:20,800 Speaker 1: And so you know, Lift acknowledged that, you know, a 56 00:03:20,800 --> 00:03:24,520 Speaker 1: lot of that spend that really spooked investors last quarter 57 00:03:24,919 --> 00:03:28,440 Speaker 1: was really coming through in fairs to consumers. They were 58 00:03:28,440 --> 00:03:32,000 Speaker 1: the ones bearing a lot of that cost burden. And 59 00:03:32,040 --> 00:03:35,480 Speaker 1: now that you're seeing way times coming down, you're seeing 60 00:03:35,680 --> 00:03:40,720 Speaker 1: fares come down. Uh, those ridership levels are recovering. Uh. 61 00:03:40,880 --> 00:03:43,840 Speaker 1: In following suit. Meantime, if you did look for a 62 00:03:43,880 --> 00:03:47,320 Speaker 1: weakness in ubernvers and you pointed this out to me, Jackie, 63 00:03:47,400 --> 00:03:49,360 Speaker 1: it was in food delivery. On the other hand, we're 64 00:03:49,360 --> 00:03:53,040 Speaker 1: seeing strong numbers from DoorDash. What is DoorDash doing better 65 00:03:53,040 --> 00:03:56,880 Speaker 1: than Uber in this case? You know, I think with DoorDash, 66 00:03:56,960 --> 00:03:59,480 Speaker 1: they are just uh if. They started off as a 67 00:03:59,560 --> 00:04:04,200 Speaker 1: pure play core business that's focused on food delivery, and 68 00:04:04,200 --> 00:04:07,040 Speaker 1: they've refined that to a t and you can really 69 00:04:07,080 --> 00:04:10,320 Speaker 1: see that come through their convenience business. They projected is 70 00:04:10,360 --> 00:04:12,760 Speaker 1: going to be profitable by the end of the year, 71 00:04:13,000 --> 00:04:16,120 Speaker 1: and that's fairly impressive considering that they just launched it 72 00:04:17,120 --> 00:04:20,440 Speaker 1: less than two years ago. And so with Uber, you know, 73 00:04:20,720 --> 00:04:24,039 Speaker 1: it's taken time for them to really um tweak the 74 00:04:24,120 --> 00:04:27,840 Speaker 1: way they match, you know, certain orders with whoever is 75 00:04:27,880 --> 00:04:29,800 Speaker 1: on the road, and now that they're really trying to 76 00:04:29,920 --> 00:04:33,520 Speaker 1: cross sell the rides and the delivery to both drivers 77 00:04:33,560 --> 00:04:35,360 Speaker 1: and consumers, they've had a lot of work to do 78 00:04:35,440 --> 00:04:39,080 Speaker 1: on the algorithm side, but they're certainly catching up. All right, 79 00:04:39,240 --> 00:04:42,400 Speaker 1: Jackie Davilos, thank you so much for Evanus dig In. 80 00:04:42,520 --> 00:04:46,120 Speaker 1: We'll be watching how these UH on demand companies fair 81 00:04:46,160 --> 00:04:56,480 Speaker 1: over the next quarter. Elon Muski is boysed to take 82 00:04:56,560 --> 00:05:00,000 Speaker 1: questions at TESSAs annual shareholder meeting dubbed the Cyber Around, 83 00:05:00,279 --> 00:05:03,000 Speaker 1: taking place at his new plant in Austin, Texas. This 84 00:05:03,080 --> 00:05:05,600 Speaker 1: year's discussion is expected to focus on a potential stock 85 00:05:05,640 --> 00:05:09,760 Speaker 1: split and corporate transparency on everything from battery sourcing to 86 00:05:09,800 --> 00:05:13,320 Speaker 1: workplace diversity. Here to discuss saw that and more. Steve Wesley, 87 00:05:13,320 --> 00:05:16,200 Speaker 1: managing partner at The Wesley Group and a former TESTA 88 00:05:16,240 --> 00:05:18,040 Speaker 1: board member, Steve always going to have you back with us. 89 00:05:18,040 --> 00:05:21,760 Speaker 1: So what are you expecting this year? Well, first, I 90 00:05:21,800 --> 00:05:24,599 Speaker 1: think you're to see some awfully happy shareholders. Look. Test 91 00:05:24,680 --> 00:05:29,400 Speaker 1: the share price up just this year alone. Second record 92 00:05:29,520 --> 00:05:34,720 Speaker 1: revenues sixty three point six or fifties six point three 93 00:05:34,800 --> 00:05:37,880 Speaker 1: billion dollars last year, growing to eighty seven billion dollars 94 00:05:37,880 --> 00:05:40,280 Speaker 1: this year. That's sixty year of a year of growth. 95 00:05:40,560 --> 00:05:42,480 Speaker 1: No one in the auto industry is coming close to that. 96 00:05:42,960 --> 00:05:50,039 Speaker 1: Second profitability, No one expected Tesla's gross or net margins. 97 00:05:50,120 --> 00:05:52,920 Speaker 1: The other majors like Volkswagen, Triota, people who are making 98 00:05:53,000 --> 00:05:55,560 Speaker 1: cars for years down at six percent. This would be 99 00:05:55,600 --> 00:05:59,960 Speaker 1: their twelfth consecutive quarter of profitability. That's awfully good news 100 00:06:00,040 --> 00:06:03,800 Speaker 1: for investors in five factories up running full bore so 101 00:06:03,839 --> 00:06:08,200 Speaker 1: it's no surprise to me the Testless flirting at trillion 102 00:06:08,200 --> 00:06:10,720 Speaker 1: dollar evaluation. We'll see if we can hold it. But 103 00:06:10,800 --> 00:06:12,920 Speaker 1: the big question today is going to be about corporate 104 00:06:12,920 --> 00:06:16,480 Speaker 1: governance e s g. How does Testla deliver on those issues? 105 00:06:16,560 --> 00:06:21,280 Speaker 1: It should be fascinating. Meantime, we are entering a really 106 00:06:21,279 --> 00:06:24,760 Speaker 1: tough phase potentially in the economy. Even Elon Musk has 107 00:06:24,760 --> 00:06:27,080 Speaker 1: said he has a super bad feeling about it. How 108 00:06:27,120 --> 00:06:31,280 Speaker 1: does Tesla fair in a recession? Are people necessarily dropping 109 00:06:31,320 --> 00:06:35,159 Speaker 1: money on new electric cars? Well, the fact of the 110 00:06:35,200 --> 00:06:39,520 Speaker 1: matter is Testless posting record sales. So if you want 111 00:06:39,560 --> 00:06:41,479 Speaker 1: to buy a Testa today, you're looking at a year 112 00:06:41,520 --> 00:06:44,760 Speaker 1: long wait. There is huge demand. The interesting thing is 113 00:06:45,040 --> 00:06:47,839 Speaker 1: how many can you actually manufacture? And that's where it 114 00:06:47,839 --> 00:06:51,680 Speaker 1: gets interesting. I think Tesla is gonna go from five 115 00:06:51,720 --> 00:06:56,520 Speaker 1: thousand vehicles sold in one to one point five million 116 00:06:56,800 --> 00:07:00,240 Speaker 1: this year. Other firms GM Ford aren't selling a action 117 00:07:00,279 --> 00:07:02,960 Speaker 1: of that. So the real question is who's figured out 118 00:07:03,000 --> 00:07:06,600 Speaker 1: supply chain? Who has factories up and running again? Teslate 119 00:07:06,680 --> 00:07:12,120 Speaker 1: five factories we know Fremont, California, Texas, Germany, China all 120 00:07:12,280 --> 00:07:15,040 Speaker 1: gearing up the full capacity, most of the others, and 121 00:07:15,240 --> 00:07:17,239 Speaker 1: yet to break ground, so there's a lot of ground 122 00:07:17,240 --> 00:07:20,000 Speaker 1: to catch up. We'll see how the others do so. 123 00:07:20,080 --> 00:07:23,600 Speaker 1: With production still the main challenge, you know, and and 124 00:07:23,640 --> 00:07:26,360 Speaker 1: how much does that have to do with continuing supply 125 00:07:26,440 --> 00:07:31,440 Speaker 1: chain issues. Well, they're all intertwined. And again I served 126 00:07:31,440 --> 00:07:33,320 Speaker 1: on the board it testsed ten years ago. I think 127 00:07:33,360 --> 00:07:35,119 Speaker 1: we made a lot of the mistakes in the book. 128 00:07:35,520 --> 00:07:38,200 Speaker 1: But they've grown up and they're hitting the ground running now. 129 00:07:38,200 --> 00:07:41,640 Speaker 1: Plus they have long term supply chain relationships in place. 130 00:07:42,160 --> 00:07:45,280 Speaker 1: That's why they're able to grow literally sixty seventy percent 131 00:07:45,320 --> 00:07:48,080 Speaker 1: a year. It's heartbreaking to watch firms like Lucid, and 132 00:07:48,120 --> 00:07:51,240 Speaker 1: I'm really pulling for They make a beautiful car, but 133 00:07:51,280 --> 00:07:54,080 Speaker 1: they said they would produce twenty tho units this year. 134 00:07:54,320 --> 00:07:57,000 Speaker 1: That's a pittance. Then they dropped it to twelve. Now 135 00:07:57,040 --> 00:07:59,840 Speaker 1: they've dropped it to six, So tough news for Lucid. 136 00:08:00,040 --> 00:08:02,840 Speaker 1: Reminder fall of us, it's a little harder to make 137 00:08:02,880 --> 00:08:05,560 Speaker 1: electric vehicles than you might think. It took Tesla ten 138 00:08:05,680 --> 00:08:08,000 Speaker 1: years to get where they are today. It's gonna be 139 00:08:08,040 --> 00:08:10,640 Speaker 1: hard for others to catch up. We'll see how General Motors, 140 00:08:10,680 --> 00:08:13,720 Speaker 1: Ford and the others do. Well. Let's talk about the competition. 141 00:08:14,520 --> 00:08:18,720 Speaker 1: Which competitor are you most optimistic about? And you know 142 00:08:18,760 --> 00:08:21,000 Speaker 1: which of these companies are really going to give Tesla 143 00:08:21,320 --> 00:08:25,200 Speaker 1: potentially run for its money. Well, let's start at the beginning. 144 00:08:26,040 --> 00:08:28,760 Speaker 1: Mary Bar at General Motors said, we're going to catch 145 00:08:28,800 --> 00:08:34,520 Speaker 1: up with Tesla. By they're not. They've produced first half 146 00:08:34,559 --> 00:08:39,000 Speaker 1: of the year eight thousand electric cars. Uh, they're way behind. 147 00:08:39,760 --> 00:08:45,760 Speaker 1: They're struggling with supply chain, struggling with manufacturing. Ford appears 148 00:08:45,800 --> 00:08:48,520 Speaker 1: to be rising for the ashes. They're going to sell 149 00:08:48,600 --> 00:08:53,400 Speaker 1: and sold twenty five cars already this year with the 150 00:08:53,520 --> 00:08:57,319 Speaker 1: E four one, fifties a great car, and the Mustang, 151 00:08:57,679 --> 00:09:00,480 Speaker 1: So they're rising for the from the ash is well, 152 00:09:00,520 --> 00:09:06,640 Speaker 1: General Motors is literally and figuratively trying to put out fires. 153 00:09:06,640 --> 00:09:09,240 Speaker 1: So as much as I'm pulling for GM and four, 154 00:09:09,240 --> 00:09:11,079 Speaker 1: it doesn't look like they're going to be the real 155 00:09:11,160 --> 00:09:15,080 Speaker 1: challenger anytime soon. Volkswagen it's a whole head of steam up. 156 00:09:15,080 --> 00:09:17,920 Speaker 1: They're gonna go over two evs first half of the 157 00:09:18,000 --> 00:09:21,480 Speaker 1: year more by year end. They're producing about half what 158 00:09:21,640 --> 00:09:25,880 Speaker 1: Tesla is, but eight times more than Ford and GM combined. 159 00:09:26,400 --> 00:09:29,640 Speaker 1: So VW is in a strong place global supply chain, 160 00:09:30,120 --> 00:09:34,240 Speaker 1: manufacturing facilities on every continent deep pockets. If anybody has 161 00:09:34,280 --> 00:09:37,720 Speaker 1: a shot to catch Tesla in the short term, it's Volkswagen. 162 00:09:38,080 --> 00:09:42,040 Speaker 1: Longer term, don't count out the Chinese. The world's largest 163 00:09:42,040 --> 00:09:48,280 Speaker 1: producer of batteries, Chinese government subsidizing their batteries, currently producing 164 00:09:48,280 --> 00:09:50,400 Speaker 1: more than half the evs the world, and it's the 165 00:09:50,400 --> 00:09:53,520 Speaker 1: biggest auto market. So Chinese are gonna come on quicker 166 00:09:53,520 --> 00:09:56,040 Speaker 1: than people think in the near term. I'm just hoping 167 00:09:56,080 --> 00:09:59,080 Speaker 1: as many American companies make the cut as possible. Don't 168 00:09:59,120 --> 00:10:02,760 Speaker 1: forget thirty new EV companies have coming to the market 169 00:10:02,800 --> 00:10:06,559 Speaker 1: in the last year, precisely the time the economy is 170 00:10:06,600 --> 00:10:10,800 Speaker 1: slowing down. Expect to shakeout in the marketplace. Be careful, 171 00:10:10,840 --> 00:10:14,200 Speaker 1: you're betting on winners, not the losers. Meantime, you've got 172 00:10:14,240 --> 00:10:17,040 Speaker 1: the Twitter side show going on for Elon Musk and 173 00:10:17,160 --> 00:10:19,480 Speaker 1: even you. When we when we last spoke about this, 174 00:10:19,559 --> 00:10:24,040 Speaker 1: we're not happy about his behavior. It's been a huge distraction. 175 00:10:24,360 --> 00:10:27,880 Speaker 1: Many Testa shareholders and Tesla owners aren't happy about it. 176 00:10:28,440 --> 00:10:30,960 Speaker 1: How much do you think that has hurt the brand? 177 00:10:30,960 --> 00:10:33,320 Speaker 1: Has that hurt the Tesla brand hasn't hurt the Elon 178 00:10:33,400 --> 00:10:37,079 Speaker 1: Musk brand. Well, look, it's a deal of two cities. 179 00:10:37,320 --> 00:10:41,400 Speaker 1: On the way hand, you've got a nearly trillion dollar company, 180 00:10:41,920 --> 00:10:45,319 Speaker 1: the most powerful brand in the auto world, with zero 181 00:10:45,360 --> 00:10:48,160 Speaker 1: marketing budget. If anybody had told you that would happen 182 00:10:48,640 --> 00:10:50,800 Speaker 1: five years ago, they would have said that's a dream 183 00:10:50,880 --> 00:10:53,840 Speaker 1: come true. But I think it could be too much 184 00:10:54,160 --> 00:10:56,400 Speaker 1: of a good thing, and I think for many people, 185 00:10:56,440 --> 00:10:59,119 Speaker 1: including the SEC, it appears to be something of a distraction. 186 00:10:59,679 --> 00:11:02,480 Speaker 1: Uh and it's something that I think it needs to 187 00:11:02,480 --> 00:11:06,400 Speaker 1: be changed over time. People need to realize this is 188 00:11:06,440 --> 00:11:10,920 Speaker 1: a multi trillion dollar SmackDown. Who's going to control the 189 00:11:10,960 --> 00:11:14,080 Speaker 1: global EV market, not just for cars but trucks as well, 190 00:11:14,720 --> 00:11:18,320 Speaker 1: and who's going to control the next big thing, which 191 00:11:18,360 --> 00:11:20,640 Speaker 1: is the move to autonomous vehicles. This is going to 192 00:11:20,720 --> 00:11:24,000 Speaker 1: be cut throat competition. I think Tesla needs to throw 193 00:11:24,080 --> 00:11:26,240 Speaker 1: every ounce of focus they can and staying in the 194 00:11:26,320 --> 00:11:29,840 Speaker 1: driver's seat. Let me give you one example. Tesla's had 195 00:11:30,040 --> 00:11:36,240 Speaker 1: the best, longest range, least expensive, most reliable batteries in 196 00:11:36,280 --> 00:11:42,480 Speaker 1: the sector. They're now developing their new revolutionary eight battery composition. 197 00:11:42,880 --> 00:11:45,719 Speaker 1: It should be better at range, cheaper and greener than 198 00:11:45,720 --> 00:11:48,160 Speaker 1: anything ever made. But c A t L, the world's 199 00:11:48,160 --> 00:11:51,040 Speaker 1: biggest battery manufacturer in China claims to have some leap 200 00:11:51,080 --> 00:11:54,439 Speaker 1: frog advantages. This is going to be a fascinating SmackDown. 201 00:11:54,760 --> 00:11:57,120 Speaker 1: Tesla is going to need all the focus they can get. 202 00:11:57,360 --> 00:11:59,959 Speaker 1: I'd keep the side shows to a minimum. Whoever win 203 00:12:00,160 --> 00:12:02,400 Speaker 1: this next round is going to have done something special. 204 00:12:02,679 --> 00:12:05,559 Speaker 1: If Tesla wins the autonomous race, it could be a 205 00:12:05,600 --> 00:12:07,840 Speaker 1: two trillion dollar company. That would be quite a trick. 206 00:12:08,280 --> 00:12:11,520 Speaker 1: All right, Uh, Steve Wesley, always good to have you here. 207 00:12:11,640 --> 00:12:15,239 Speaker 1: What's the group managing partner? Thank you for stopping by. Okay, 208 00:12:15,240 --> 00:12:18,720 Speaker 1: coming up Meta's brand new reward on global threats and 209 00:12:18,760 --> 00:12:22,520 Speaker 1: in particular, how the company is tackling a Russian troll farm. 210 00:12:22,960 --> 00:12:26,040 Speaker 1: Have more on that from a top Meta executive. Next, 211 00:12:26,520 --> 00:12:46,280 Speaker 1: Mrs Bloomberg. Meta says it just shut down a Russian 212 00:12:46,440 --> 00:12:49,559 Speaker 1: troll farm. The Facebook parent company releasing the quarterly report 213 00:12:49,640 --> 00:12:52,120 Speaker 1: that outlines the actions it's taken against fake accounts and 214 00:12:52,120 --> 00:12:55,520 Speaker 1: hackers who tried to create the appearance of support for 215 00:12:55,600 --> 00:13:00,240 Speaker 1: Russia's war on Ukraine. Vanemo, global threaten Intelligence strategy lead 216 00:13:00,240 --> 00:13:02,360 Speaker 1: out Meta joined us now from more on this, So 217 00:13:02,400 --> 00:13:05,599 Speaker 1: talk to us about this particular operation. Just how widespread 218 00:13:06,160 --> 00:13:11,559 Speaker 1: and effective was it? Well in terms of being widespread, 219 00:13:11,559 --> 00:13:13,840 Speaker 1: it was really trying to hit everywhere across the Internet 220 00:13:13,840 --> 00:13:15,960 Speaker 1: pretty much all at the same time. What we had 221 00:13:16,000 --> 00:13:18,280 Speaker 1: was a troll farm, so an organization run from St. 222 00:13:18,320 --> 00:13:21,040 Speaker 1: Petersburg and Russia that was hiring people off the street 223 00:13:21,080 --> 00:13:23,800 Speaker 1: to run fake accounts kind of everywhere on the Internet. 224 00:13:23,840 --> 00:13:28,200 Speaker 1: They could think of those reports of fake accounts on YouTube, Telegram, TikTok, Twitter, 225 00:13:28,559 --> 00:13:31,160 Speaker 1: We found them on Instagram, UM, and what they were 226 00:13:31,160 --> 00:13:33,240 Speaker 1: trying to do was make it look like there was 227 00:13:33,320 --> 00:13:36,360 Speaker 1: large scales support for the Russian innovasion of Ukraine. So 228 00:13:36,400 --> 00:13:40,000 Speaker 1: that's the widespread effect. But in terms of effect, all 229 00:13:40,040 --> 00:13:41,800 Speaker 1: we saw was that they weren't very good at what 230 00:13:41,840 --> 00:13:44,360 Speaker 1: they did. UM. A lot of their fake accounts kept 231 00:13:44,400 --> 00:13:47,160 Speaker 1: on getting caught by the automated systems before we even 232 00:13:47,320 --> 00:13:50,080 Speaker 1: investigated them and took them down. Real people kept on 233 00:13:50,120 --> 00:13:52,560 Speaker 1: calling them out as trolls UM. And there were even 234 00:13:52,600 --> 00:13:55,640 Speaker 1: cases when they would try to steer people towards celebrities 235 00:13:55,720 --> 00:13:58,040 Speaker 1: or influences on social media and then they put their 236 00:13:58,040 --> 00:14:00,440 Speaker 1: own account. So, for example, at one point they tried 237 00:14:00,480 --> 00:14:03,240 Speaker 1: to steer people towards the UK Foreign Secretary Liz Trust 238 00:14:03,600 --> 00:14:06,800 Speaker 1: and instead of finding the Foreign secretaries favorite page on Facebook. 239 00:14:06,960 --> 00:14:09,160 Speaker 1: They found something that hadn't been used since twenty eighteen, 240 00:14:09,600 --> 00:14:12,520 Speaker 1: so they were trying to spread themselves wide. But nothing 241 00:14:12,559 --> 00:14:14,200 Speaker 1: we saw show that they were actually having much of 242 00:14:14,200 --> 00:14:17,599 Speaker 1: an impact this time. So it sounds like this particular 243 00:14:17,640 --> 00:14:21,920 Speaker 1: operation wasn't very sophisticated. How unique was this operation? Is 244 00:14:21,920 --> 00:14:28,360 Speaker 1: this something that you've seen before. We've seen attempts like 245 00:14:28,480 --> 00:14:30,960 Speaker 1: this before in lots of different parts of the world. 246 00:14:31,160 --> 00:14:33,520 Speaker 1: So so we've taken down troll farms in the past, 247 00:14:33,560 --> 00:14:37,960 Speaker 1: for example in Nicaragua, in Albania, we've taken down other 248 00:14:38,360 --> 00:14:40,920 Speaker 1: activity by Russian trolls as well. But there was an 249 00:14:40,920 --> 00:14:44,120 Speaker 1: interesting twist to this case, and it's that the operation 250 00:14:44,160 --> 00:14:46,800 Speaker 1: was really working in two halves. It was running a 251 00:14:46,800 --> 00:14:49,680 Speaker 1: public channel on Telegram which was trying to, if you like, 252 00:14:49,880 --> 00:14:53,280 Speaker 1: crowdsource comments which were supporting Russia, and when it didn't 253 00:14:53,320 --> 00:14:56,320 Speaker 1: get real crowdsource comments, it would use the fake accounts 254 00:14:56,320 --> 00:14:58,680 Speaker 1: to go in instead, And it's the same operation running 255 00:14:58,720 --> 00:15:01,080 Speaker 1: all these things. And then what the people behind the 256 00:15:01,120 --> 00:15:03,880 Speaker 1: operation would do would be they do in the interviews 257 00:15:03,920 --> 00:15:06,760 Speaker 1: on Russian state TV and supportive media and say, look, 258 00:15:06,800 --> 00:15:08,880 Speaker 1: what a great job we're doing. So It's like there 259 00:15:08,920 --> 00:15:12,440 Speaker 1: were multiple layers of deception nestled inside one another, almost 260 00:15:12,480 --> 00:15:15,040 Speaker 1: like a Russian doll. But ultimately they were trying to 261 00:15:15,080 --> 00:15:17,480 Speaker 1: make it look like they were effective, but they were 262 00:15:17,560 --> 00:15:19,520 Speaker 1: using fakes to do it, and then the fake has 263 00:15:19,560 --> 00:15:24,600 Speaker 1: gone caught. In general, how effective has Russian have Russian 264 00:15:24,600 --> 00:15:28,120 Speaker 1: disinformation campaigns actually been. Over the course of the last 265 00:15:28,120 --> 00:15:33,840 Speaker 1: several months of this war on Ukraine, we've taken down 266 00:15:34,680 --> 00:15:37,200 Speaker 1: I think about half a dozen different Russian operations that 267 00:15:37,200 --> 00:15:40,320 Speaker 1: have been targeting Ukraine recently, so since the war began. 268 00:15:41,040 --> 00:15:43,520 Speaker 1: In general, what we've seen is that they've been struggling 269 00:15:43,560 --> 00:15:46,720 Speaker 1: to get any kind of real engagement, but we've also 270 00:15:46,760 --> 00:15:49,120 Speaker 1: seen that they keep on trying, and this is the 271 00:15:49,160 --> 00:15:51,200 Speaker 1: time to keep our foot on the gas. What we 272 00:15:51,240 --> 00:15:54,520 Speaker 1: really need to do is take these operations as a lesson. 273 00:15:54,560 --> 00:15:56,440 Speaker 1: We need to learn from them, and we need to 274 00:15:56,520 --> 00:15:58,680 Speaker 1: keep looking because we know threat actors like this are 275 00:15:58,720 --> 00:16:01,360 Speaker 1: not going to go away. We need to take them seriously, 276 00:16:01,760 --> 00:16:03,840 Speaker 1: and each time we find something like this, we need 277 00:16:03,880 --> 00:16:06,520 Speaker 1: to explain to people. Here's what it was, Here's how 278 00:16:06,520 --> 00:16:08,920 Speaker 1: it worked, Here's the kind of content that they were pushing, 279 00:16:08,960 --> 00:16:11,600 Speaker 1: Here's the way they were operating because this time around 280 00:16:11,840 --> 00:16:14,320 Speaker 1: they weren't very good at what they did. But we 281 00:16:14,360 --> 00:16:16,000 Speaker 1: need to prepare for the next time. And that's what 282 00:16:16,120 --> 00:16:18,080 Speaker 1: as threatning investigators we always have to be ready for. 283 00:16:18,880 --> 00:16:23,280 Speaker 1: Are you speaking directly with other big tech companies Apple, Google, TikTok, 284 00:16:23,280 --> 00:16:28,040 Speaker 1: Twitter about coordinating efforts on this front. Whenever we do 285 00:16:28,080 --> 00:16:31,000 Speaker 1: a threat report like this, we share with industry partners, 286 00:16:31,000 --> 00:16:34,280 Speaker 1: we share with researchers, we share with we share with 287 00:16:34,320 --> 00:16:36,840 Speaker 1: the public. Right we report these things and that's because 288 00:16:36,880 --> 00:16:39,720 Speaker 1: we found that that influence operations. They're a bit like 289 00:16:39,880 --> 00:16:42,520 Speaker 1: mold growing in your house. They grow best in dark places, 290 00:16:42,880 --> 00:16:44,480 Speaker 1: and so when you find them, there's two things you 291 00:16:44,480 --> 00:16:46,320 Speaker 1: really need to do. You need to clean them up, 292 00:16:46,640 --> 00:16:47,920 Speaker 1: but the on you need to shine a light on 293 00:16:47,960 --> 00:16:49,320 Speaker 1: them as well. You need to move them into a 294 00:16:49,320 --> 00:16:51,760 Speaker 1: bright place. And we've always found that the more we 295 00:16:51,800 --> 00:16:54,080 Speaker 1: can share information about these operations, the more we can 296 00:16:54,320 --> 00:16:57,440 Speaker 1: make people aware of how they behave it's harder for 297 00:16:57,480 --> 00:17:01,520 Speaker 1: them to come back. What keeps you up at night? 298 00:17:01,600 --> 00:17:04,320 Speaker 1: I mean we're heading into the U S mid terms 299 00:17:04,359 --> 00:17:07,879 Speaker 1: here in the United States? Have you seen activity rising 300 00:17:07,920 --> 00:17:13,960 Speaker 1: on that front. I'm a threat investigator, so investigations keep 301 00:17:13,960 --> 00:17:15,760 Speaker 1: me up at night. It's it's what we all do 302 00:17:15,800 --> 00:17:19,040 Speaker 1: on the team. UM. In terms of the mid terms, sorry, 303 00:17:19,880 --> 00:17:24,960 Speaker 1: we haven't seen any upticking activity so far. For example, 304 00:17:25,000 --> 00:17:28,360 Speaker 1: this Russian operation that we've taken down was really focused 305 00:17:28,400 --> 00:17:30,320 Speaker 1: on the war in Ukraine and it was all about 306 00:17:30,359 --> 00:17:33,720 Speaker 1: pushing the Russian point of view. But again, operations like 307 00:17:33,800 --> 00:17:35,200 Speaker 1: this are a lesson and one of the big things 308 00:17:35,320 --> 00:17:37,800 Speaker 1: from the Russian operation was that what they were trying 309 00:17:37,840 --> 00:17:40,760 Speaker 1: to do was use a fake operation to make a 310 00:17:40,880 --> 00:17:43,639 Speaker 1: more public operation look like it was working. And this 311 00:17:43,680 --> 00:17:46,280 Speaker 1: is something we call perception hacking. It's trying to fool 312 00:17:46,320 --> 00:17:48,199 Speaker 1: people that there's something big going on, if you like. 313 00:17:48,280 --> 00:17:50,400 Speaker 1: It's like dropping an ice cube into the water and saying, 314 00:17:50,440 --> 00:17:53,159 Speaker 1: look as an iceberg underneath. And that's the kind of 315 00:17:53,200 --> 00:17:57,120 Speaker 1: tactic which could be very easily transferred to other areas. 316 00:17:57,520 --> 00:17:59,879 Speaker 1: So we have to take threat actors like this serious. 317 00:18:00,200 --> 00:18:02,680 Speaker 1: Just because they were ham fisted this time around doesn't 318 00:18:02,720 --> 00:18:04,239 Speaker 1: mean that they will be the next time. And so 319 00:18:04,359 --> 00:18:06,679 Speaker 1: what we're looking out for as investigators, and the thing 320 00:18:06,760 --> 00:18:08,960 Speaker 1: that's keeping us up at night is making sure we 321 00:18:09,040 --> 00:18:12,440 Speaker 1: keep ahead of whatever trends are out there. Meantime, we've 322 00:18:12,440 --> 00:18:17,360 Speaker 1: been following this story about TikTok and the Chinese government 323 00:18:17,480 --> 00:18:20,719 Speaker 1: or an entity supported by the Chinese government trying to 324 00:18:20,840 --> 00:18:24,080 Speaker 1: set up a stealth account on TikTok to target Western 325 00:18:24,119 --> 00:18:29,959 Speaker 1: audiences with propaganda. You know, is this something that concerns you? 326 00:18:34,359 --> 00:18:36,000 Speaker 1: If you look at our FRET reporting over the last 327 00:18:36,000 --> 00:18:38,480 Speaker 1: few years, we've taken down operations from around the world. 328 00:18:38,520 --> 00:18:43,639 Speaker 1: We have seen operations from China, Iran, India, um. I 329 00:18:43,640 --> 00:18:45,880 Speaker 1: think it's more than fifty different countries that we've We've 330 00:18:45,920 --> 00:18:49,320 Speaker 1: seen operations coming in from more than two dozen different languages, 331 00:18:49,920 --> 00:18:51,879 Speaker 1: and it seems like the idea is out there that 332 00:18:51,920 --> 00:18:54,520 Speaker 1: influence operations are a thing. There's something that many different 333 00:18:54,520 --> 00:18:57,960 Speaker 1: countries come run. And our job is threatned investigators, is 334 00:18:58,000 --> 00:19:00,800 Speaker 1: to go and find them, and particularly really to shine 335 00:19:00,800 --> 00:19:03,159 Speaker 1: a light on them and to share information about them 336 00:19:03,000 --> 00:19:05,280 Speaker 1: as widely as we can, because the more different lies 337 00:19:05,320 --> 00:19:08,000 Speaker 1: we can get on this, the more we can try 338 00:19:08,040 --> 00:19:10,000 Speaker 1: and catch them. With the Russian troll Farm, it was 339 00:19:10,000 --> 00:19:12,840 Speaker 1: really interesting the way it was exposed was the troll 340 00:19:12,880 --> 00:19:14,800 Speaker 1: farm was trying to hire people off the street and 341 00:19:14,840 --> 00:19:16,879 Speaker 1: telling them, Hey, come and work for us. One of 342 00:19:16,880 --> 00:19:18,399 Speaker 1: the first people they hired turned out to be an 343 00:19:18,440 --> 00:19:24,560 Speaker 1: undercover journalists to expose the whole operation. Fascinating Meta executive 344 00:19:24,640 --> 00:19:28,679 Speaker 1: Bennimo Global Threat Intelligencely, thank you Ben for sharing all 345 00:19:28,760 --> 00:19:39,000 Speaker 1: that with us. Welcome back to Bloomberg Technology. I'm emily 346 00:19:39,080 --> 00:19:42,040 Speaker 1: changing San Francisco legacy names and streaming and media out 347 00:19:42,040 --> 00:19:44,480 Speaker 1: with more earnings results are and Ludlow back with the 348 00:19:44,560 --> 00:19:48,280 Speaker 1: latest and Warner Brothers Discovery. Yeah interesting, I mean doesn't 349 00:19:48,280 --> 00:19:50,920 Speaker 1: look great right down in after hours. They had a 350 00:19:51,000 --> 00:19:53,520 Speaker 1: net loss in the quarter, which they attribute the costs 351 00:19:53,520 --> 00:19:57,159 Speaker 1: relating to the merger between Warner Media and Discovery. Of 352 00:19:57,200 --> 00:19:58,920 Speaker 1: course that closed in April, and this was the first 353 00:19:58,920 --> 00:20:00,800 Speaker 1: time investors really got a look under the hood of 354 00:20:00,800 --> 00:20:05,600 Speaker 1: this combined entity. And I'm zeroing in on subscribers across 355 00:20:05,760 --> 00:20:09,080 Speaker 1: HBO Max other properties like Discovery Plus. They added one 356 00:20:09,080 --> 00:20:12,560 Speaker 1: point seven million subscribers net new subscribers in the quarter. 357 00:20:13,000 --> 00:20:15,480 Speaker 1: So let's compare and contrast, because they weren't the only 358 00:20:15,520 --> 00:20:19,280 Speaker 1: streaming name to report earnings this Thursday. Paramount up one 359 00:20:19,280 --> 00:20:22,120 Speaker 1: percent in regular trading. Actually, Warner Brothers are almost five 360 00:20:22,119 --> 00:20:26,320 Speaker 1: percent before its earnings. But Paramount across Paramount Plus added 361 00:20:26,480 --> 00:20:30,120 Speaker 1: three point seven million subscribers in the quarter, so actually, 362 00:20:30,359 --> 00:20:32,440 Speaker 1: even though it's a relative minnow in what we call 363 00:20:32,520 --> 00:20:36,119 Speaker 1: the streaming wars, it's seeming to get some traction in 364 00:20:36,160 --> 00:20:38,320 Speaker 1: its user based and adding new users. What they both 365 00:20:38,320 --> 00:20:41,600 Speaker 1: had in common was the ad business is really underperformed, 366 00:20:41,600 --> 00:20:44,159 Speaker 1: which is interesting given what we've heard in the mixed 367 00:20:44,160 --> 00:20:47,640 Speaker 1: picture of the global advertising market in recent weeks. Where 368 00:20:47,640 --> 00:20:49,840 Speaker 1: do we stand here today, m with all these different 369 00:20:49,920 --> 00:20:52,159 Speaker 1: names with zeroed in on who's doing well who's doing not? 370 00:20:52,280 --> 00:20:54,560 Speaker 1: If you look at the share prices, actually Paramount is 371 00:20:54,600 --> 00:20:58,119 Speaker 1: the relative outperformer, down just sixteen percent year today. But 372 00:20:58,320 --> 00:21:02,399 Speaker 1: Netflix still really ug down sixty two percent year today. 373 00:21:02,440 --> 00:21:04,600 Speaker 1: Of course, they had a shock in the first half 374 00:21:04,600 --> 00:21:07,600 Speaker 1: of this year with the shock loss of its subscribe 375 00:21:07,600 --> 00:21:09,440 Speaker 1: It based a more positive outlook for the second half 376 00:21:09,520 --> 00:21:11,639 Speaker 1: this year. But there's still a big questions right in 377 00:21:11,680 --> 00:21:14,720 Speaker 1: the face of great inflation, what's the consumer of doing? 378 00:21:14,960 --> 00:21:17,320 Speaker 1: That's a lot of option. Personally, I got a lot 379 00:21:17,320 --> 00:21:19,040 Speaker 1: of choices. I subscribed to all these. I don't know 380 00:21:19,040 --> 00:21:22,080 Speaker 1: if you saw a top gun great movie that boosted Paramount, 381 00:21:22,800 --> 00:21:25,680 Speaker 1: Can we have them all forever? I haven't seen it 382 00:21:25,760 --> 00:21:27,359 Speaker 1: yet and I don't have time to go to the 383 00:21:27,400 --> 00:21:30,640 Speaker 1: movie theater, But I will try to make it. Thank you. Okay, 384 00:21:30,760 --> 00:21:34,560 Speaker 1: let's continue this conversation with Julia Alexander, director of Strategy 385 00:21:34,680 --> 00:21:37,400 Speaker 1: at Parrot Analytics. Juliet, look, you know there's a lot 386 00:21:37,440 --> 00:21:40,040 Speaker 1: to talk about here. Let's start with Warner Brothers Discovery. 387 00:21:40,400 --> 00:21:44,399 Speaker 1: You know clearly they're they're making changes, planning to make 388 00:21:44,400 --> 00:21:47,920 Speaker 1: a lot more changes, and there's you know, some uncertainty 389 00:21:47,920 --> 00:21:50,960 Speaker 1: about where this is all going. What's your take, right, 390 00:21:51,119 --> 00:21:52,720 Speaker 1: I mean, the first thing we have to do is, 391 00:21:52,880 --> 00:21:57,000 Speaker 1: I think almost stepped back from the amount of subscribers gained. 392 00:21:57,200 --> 00:21:58,880 Speaker 1: So we look at the subs gained, right, they gained 393 00:21:58,920 --> 00:22:01,680 Speaker 1: one point seven million. It's not much. They actually, according 394 00:22:01,720 --> 00:22:04,280 Speaker 1: to their new way that they report, they lost about 395 00:22:04,280 --> 00:22:06,760 Speaker 1: three hundred thousand in the domestic market. But I think 396 00:22:06,800 --> 00:22:09,119 Speaker 1: we have to look at and what David Zaslab CEO 397 00:22:09,200 --> 00:22:12,240 Speaker 1: David zas Laws real game is is what is the 398 00:22:12,280 --> 00:22:15,000 Speaker 1: actual value of this content? How do we go through 399 00:22:15,119 --> 00:22:18,080 Speaker 1: HBO Max and call some of it and Discovery Plus 400 00:22:18,080 --> 00:22:20,200 Speaker 1: and call some of it in order to really ensure 401 00:22:20,240 --> 00:22:23,040 Speaker 1: that we're hitting profitability on the fastest path that we 402 00:22:23,119 --> 00:22:26,400 Speaker 1: can for our shareholders. When we talk about David Zaslav 403 00:22:26,480 --> 00:22:29,119 Speaker 1: and his team's approach to streaming. It's different from what 404 00:22:29,160 --> 00:22:31,200 Speaker 1: Netflix is doing and what Disney is doing, where they're 405 00:22:31,240 --> 00:22:34,880 Speaker 1: increasing their content spend constantly and constantly, and David zas 406 00:22:34,960 --> 00:22:36,800 Speaker 1: Lab does not want to be in the content spanned 407 00:22:36,840 --> 00:22:39,200 Speaker 1: wars as he likes to say it. Instead, he wants 408 00:22:39,200 --> 00:22:41,160 Speaker 1: to say, we want to get to profitability. We want 409 00:22:41,160 --> 00:22:43,560 Speaker 1: to get the most value for our dollar. And so 410 00:22:43,600 --> 00:22:45,360 Speaker 1: what we're really going to see play out is how 411 00:22:45,440 --> 00:22:48,399 Speaker 1: well that um ibada and how well that obada really 412 00:22:48,440 --> 00:22:51,760 Speaker 1: comes into the case for Discovery going for Warner Brothers 413 00:22:51,760 --> 00:22:55,120 Speaker 1: Discovery going forward. What are you expecting Zaslav to do 414 00:22:55,240 --> 00:22:58,000 Speaker 1: as they work to merge these two platforms. You know, 415 00:22:58,080 --> 00:23:01,240 Speaker 1: there's talk about a big calling potentially of HBO Max. 416 00:23:01,280 --> 00:23:05,000 Speaker 1: They're taking movies out of the rotation that are already 417 00:23:05,000 --> 00:23:07,680 Speaker 1: filmed because they don't want to spend money on marketing. 418 00:23:07,720 --> 00:23:10,879 Speaker 1: I'm thinking of the new Backgirl movie, which as I 419 00:23:10,960 --> 00:23:14,520 Speaker 1: understand it has already been shot. Right. I mean, the 420 00:23:14,600 --> 00:23:19,000 Speaker 1: key horde right now is amortization. Amortization. Amortization. When you're 421 00:23:19,040 --> 00:23:21,320 Speaker 1: looking at the amount of debt that David Zazo and 422 00:23:21,359 --> 00:23:22,920 Speaker 1: his team brought in, you're looking at what you can 423 00:23:22,960 --> 00:23:25,600 Speaker 1: do um specifically with HBO Max. I think what we're 424 00:23:25,600 --> 00:23:28,280 Speaker 1: going to see happen is less of culling than press 425 00:23:28,359 --> 00:23:30,199 Speaker 1: made it, you know, to be that rumors made out 426 00:23:30,200 --> 00:23:31,840 Speaker 1: to be. Over the last two days, it's been a 427 00:23:31,840 --> 00:23:34,399 Speaker 1: lot on Twitter as analysts and industry in centers and 428 00:23:34,400 --> 00:23:36,840 Speaker 1: reporters try to guess at what's going to happen with 429 00:23:37,280 --> 00:23:40,000 Speaker 1: HBO Max. This report, the earnings report to it was 430 00:23:40,040 --> 00:23:42,400 Speaker 1: actually a little bit beneficial in that way. What we're 431 00:23:42,400 --> 00:23:45,240 Speaker 1: seeing is that HBO Max use mail. We're seeing that 432 00:23:45,480 --> 00:23:48,640 Speaker 1: Discovery Plus use female. And before Discovery Plus came in, 433 00:23:48,720 --> 00:23:51,919 Speaker 1: the HBO Max idea was to invest in more female 434 00:23:51,920 --> 00:23:54,800 Speaker 1: oriented contests. We have like the Cooking Show with Lena Gomez, 435 00:23:54,840 --> 00:23:56,840 Speaker 1: and you have um the New Gossip Girl, and you 436 00:23:56,840 --> 00:23:58,240 Speaker 1: have all these such of shows that appeal to a 437 00:23:58,280 --> 00:24:00,399 Speaker 1: different audience to really, why do that? Why didn't that 438 00:24:00,440 --> 00:24:03,879 Speaker 1: total addressable market? But as Discovery Plus comes in, they're saying, well, 439 00:24:03,920 --> 00:24:06,240 Speaker 1: we're already making this content. It's doing well on cable. 440 00:24:06,320 --> 00:24:08,359 Speaker 1: It is a brand and of itself, so we're gonna 441 00:24:08,359 --> 00:24:10,639 Speaker 1: bring some of that to HBO Max and Casey Boys, 442 00:24:10,720 --> 00:24:13,680 Speaker 1: the visionary leader who oversees content for HBO, HBO Max 443 00:24:13,840 --> 00:24:16,600 Speaker 1: can focus on scripted content and scripted fair that works. 444 00:24:16,880 --> 00:24:18,639 Speaker 1: So I actually think we're not going to see as 445 00:24:18,760 --> 00:24:21,560 Speaker 1: much of a call as reports made it out to be. 446 00:24:21,720 --> 00:24:23,800 Speaker 1: But that being said, I mean, I think when we 447 00:24:23,880 --> 00:24:27,280 Speaker 1: talk about streaming services there is far too much confident content. 448 00:24:27,320 --> 00:24:30,160 Speaker 1: We're in an oversaturated market and it's never been easier 449 00:24:30,320 --> 00:24:32,760 Speaker 1: for a subscriber to say this is mediocre and this 450 00:24:32,840 --> 00:24:35,840 Speaker 1: is great. So if content isn't performing, why keep it 451 00:24:35,920 --> 00:24:39,240 Speaker 1: on the platform? Is kind of the thought strategy that 452 00:24:39,280 --> 00:24:42,520 Speaker 1: Warner brother Discovery executive seem to be having. Okay, so 453 00:24:42,600 --> 00:24:45,320 Speaker 1: let's talk about Paramount Plus. As Ed said this, you 454 00:24:45,359 --> 00:24:47,919 Speaker 1: know service has has been a minnows thus far, but 455 00:24:48,000 --> 00:24:52,040 Speaker 1: it is racking up subscribers. The bottom line doesn't necessarily 456 00:24:52,280 --> 00:24:55,560 Speaker 1: look great so far. You know, Top Gun, Yellowstone, which 457 00:24:55,560 --> 00:24:58,320 Speaker 1: is one of my favorite shows. Are people going to 458 00:24:58,640 --> 00:25:04,879 Speaker 1: pay for four streaming services? Though before inflation, before interest 459 00:25:04,960 --> 00:25:08,360 Speaker 1: rates started hiking, I would say yes in the United States. Globally, 460 00:25:08,440 --> 00:25:10,919 Speaker 1: we don't know. I think now we're looking at closer 461 00:25:10,960 --> 00:25:12,560 Speaker 1: to two to three over the next little bit, as 462 00:25:12,600 --> 00:25:16,160 Speaker 1: people choose where they want to put their credit card dollars. 463 00:25:16,200 --> 00:25:19,560 Speaker 1: Every single month, But that being said, I would say 464 00:25:19,560 --> 00:25:22,200 Speaker 1: that Paramount. Everyone has kind of looked at Paramount and said, 465 00:25:22,200 --> 00:25:24,359 Speaker 1: you know, we don't really know. We're really m bearish 466 00:25:24,400 --> 00:25:26,120 Speaker 1: on Paramount and what they want to do with their streaming. 467 00:25:26,280 --> 00:25:28,119 Speaker 1: When I think Paramount really has going for them is 468 00:25:28,119 --> 00:25:30,680 Speaker 1: that not only are they a great streaming service and 469 00:25:30,720 --> 00:25:32,760 Speaker 1: they're building a great streaming services and their numbers are 470 00:25:32,840 --> 00:25:35,959 Speaker 1: increasing every single quarter, but they're also a great seller. 471 00:25:36,200 --> 00:25:39,119 Speaker 1: There's someone who can license really in demand content to 472 00:25:39,240 --> 00:25:41,920 Speaker 1: Netflix and to other players and charge a hefty feet 473 00:25:41,960 --> 00:25:44,120 Speaker 1: for that because their content is so in demand, which 474 00:25:44,119 --> 00:25:46,560 Speaker 1: means that people will pay to have access to it. 475 00:25:46,800 --> 00:25:48,560 Speaker 1: So when I think we look at Paramount, you know, 476 00:25:49,280 --> 00:25:51,960 Speaker 1: the question three or four years ago, not even you know, 477 00:25:52,000 --> 00:25:53,920 Speaker 1: two years ago. So question was which are the three 478 00:25:53,920 --> 00:25:55,639 Speaker 1: services that people sign up for? And it used to 479 00:25:55,680 --> 00:25:58,800 Speaker 1: be Disney plus Netflix and HBO Max. And I think 480 00:25:58,920 --> 00:26:02,240 Speaker 1: as the stream wars, which is really just a colloquial 481 00:26:02,400 --> 00:26:05,719 Speaker 1: term for proper uh competition in the marketplace, that as 482 00:26:05,720 --> 00:26:08,800 Speaker 1: opposed to Netflix having a almost monopolization on the on 483 00:26:08,840 --> 00:26:11,080 Speaker 1: the entire industry, I think what you'll start to see 484 00:26:11,080 --> 00:26:13,760 Speaker 1: is a company like Paramount that can offer really great 485 00:26:13,800 --> 00:26:16,480 Speaker 1: pricing on the ad front and also on the subfront, 486 00:26:16,680 --> 00:26:19,000 Speaker 1: that has shows that people really want, that has the 487 00:26:19,000 --> 00:26:21,600 Speaker 1: film franchises that people really want. I think you'll start 488 00:26:21,640 --> 00:26:24,320 Speaker 1: to see them emerge as a really strong contender in 489 00:26:24,359 --> 00:26:26,399 Speaker 1: the same way that I really have faith at HBO 490 00:26:26,440 --> 00:26:29,720 Speaker 1: Max unders As Lab and even HBO Max under Jason Clark, 491 00:26:29,760 --> 00:26:31,919 Speaker 1: the former CEO. I think that's a great product in 492 00:26:32,000 --> 00:26:35,240 Speaker 1: combining Discovery and HBO Max offerings in a really smart, 493 00:26:35,280 --> 00:26:38,760 Speaker 1: strategic way that feels curated and human but also scalable 494 00:26:38,760 --> 00:26:41,040 Speaker 1: and accessible. Um. I think that's really going to help 495 00:26:41,119 --> 00:26:44,159 Speaker 1: them even not maybe not surpass Netflix in terms of 496 00:26:44,200 --> 00:26:47,320 Speaker 1: subscribers in the next two years, but definitely be worthwhile contenders. 497 00:26:47,800 --> 00:26:49,720 Speaker 1: So are you saying, if you're a betting person, you 498 00:26:49,720 --> 00:26:52,960 Speaker 1: should be spreading your bets right now. I would spread 499 00:26:53,000 --> 00:26:54,920 Speaker 1: my bets a little bit. Yeah, I think it's too early. 500 00:26:54,960 --> 00:26:56,879 Speaker 1: You know, it's funny. I think we're trying to declare 501 00:26:56,880 --> 00:26:59,119 Speaker 1: a winner in the streaming wars again that term that 502 00:26:59,160 --> 00:27:02,280 Speaker 1: really just means competition is happening. It's far too early. 503 00:27:02,520 --> 00:27:04,160 Speaker 1: We really need to see what a lot of these 504 00:27:04,320 --> 00:27:07,959 Speaker 1: companies that have the theatrical studio components that have linear networks. 505 00:27:07,960 --> 00:27:10,119 Speaker 1: We need to see what their strategy is for handling 506 00:27:10,160 --> 00:27:12,639 Speaker 1: all that type of content across a bunch of different 507 00:27:12,680 --> 00:27:15,159 Speaker 1: revenue streams. And I think the key takeaway from what 508 00:27:15,200 --> 00:27:17,680 Speaker 1: we're seeing as a subscriber growth in the the United States 509 00:27:17,760 --> 00:27:20,240 Speaker 1: kind of slows down a little bit, um kind of hits. 510 00:27:20,240 --> 00:27:22,120 Speaker 1: It's a bit of a peak for certain streaming services. 511 00:27:22,400 --> 00:27:25,000 Speaker 1: I do think the takeaway is that streaming is not 512 00:27:25,080 --> 00:27:27,680 Speaker 1: necessarily the end game for a lot of these companies, 513 00:27:27,720 --> 00:27:30,399 Speaker 1: but it is a very important support system for a 514 00:27:30,400 --> 00:27:32,959 Speaker 1: lot of its other different investment areas. And I think 515 00:27:33,000 --> 00:27:34,679 Speaker 1: that's really key because it used to be that streaming 516 00:27:34,760 --> 00:27:36,640 Speaker 1: was the only option. You know, two three years ago, 517 00:27:36,720 --> 00:27:40,399 Speaker 1: everything was streaming, and now it's well, everything is also 518 00:27:40,440 --> 00:27:44,359 Speaker 1: includes streaming. What about Disney coming up next week? What 519 00:27:44,400 --> 00:27:46,320 Speaker 1: are you expecting there? It's been it's been a tough 520 00:27:46,440 --> 00:27:49,280 Speaker 1: ride for Bob j Peck. It's been a ride a 521 00:27:49,359 --> 00:27:52,080 Speaker 1: ride for Bob Jeck. My major concern with Disney is 522 00:27:52,400 --> 00:27:54,800 Speaker 1: the promise or the projection. I should say that Bob 523 00:27:54,840 --> 00:27:56,159 Speaker 1: j Peck and his team gave to the street of 524 00:27:56,200 --> 00:27:59,359 Speaker 1: two to two and sixty million subscribers globally by a 525 00:27:59,359 --> 00:28:02,960 Speaker 1: fiscal year. It's ambitious. That's an average with about ten 526 00:28:03,000 --> 00:28:06,160 Speaker 1: million subscribers per quarter being added, and eventually you run 527 00:28:06,160 --> 00:28:08,080 Speaker 1: out of countries to launching, right, that's kind of a 528 00:28:08,080 --> 00:28:10,960 Speaker 1: guarantee subscriber based when you launch a new country, customers 529 00:28:10,960 --> 00:28:14,080 Speaker 1: will sign up. So my biggest concern is what Disney 530 00:28:14,119 --> 00:28:16,000 Speaker 1: will have to do on the Disney Plus front to 531 00:28:16,080 --> 00:28:18,320 Speaker 1: really hit those projections, unless they come in, you know, 532 00:28:18,400 --> 00:28:20,639 Speaker 1: next week and say we're changing our projections. But I 533 00:28:20,720 --> 00:28:22,760 Speaker 1: really don't think that's going to be the case. You know, 534 00:28:22,800 --> 00:28:26,200 Speaker 1: as long as Disney has families and Marvel fans and 535 00:28:26,200 --> 00:28:28,480 Speaker 1: Star Wars fans are going to continue to be a 536 00:28:28,560 --> 00:28:31,280 Speaker 1: well supported streaming service. But I think the bigger question 537 00:28:31,320 --> 00:28:33,679 Speaker 1: now is to hit those numbers, you have to increase 538 00:28:33,680 --> 00:28:37,840 Speaker 1: your total addressable market, which means bringing more UM Hamilton's right, 539 00:28:37,880 --> 00:28:39,800 Speaker 1: bringing more of that, bringing more the West Side story 540 00:28:39,880 --> 00:28:41,920 Speaker 1: into into the Disney Plus sphere so that people can 541 00:28:41,920 --> 00:28:43,840 Speaker 1: watch it. And I think in the United States, when 542 00:28:43,880 --> 00:28:46,680 Speaker 1: you have Hulu, that becomes a really interesting conversation with 543 00:28:46,760 --> 00:28:49,280 Speaker 1: what goes to Hulu, what goes to Disney Plus UM 544 00:28:49,320 --> 00:28:52,320 Speaker 1: and both are designed to support the bundle, and so globally, 545 00:28:52,400 --> 00:28:53,680 Speaker 1: I think is where we're going to see what the 546 00:28:53,680 --> 00:28:56,040 Speaker 1: future of Disney Plus really looks like under the Star 547 00:28:56,120 --> 00:28:58,600 Speaker 1: and Star Plus banner, where we can see how Disney, 548 00:28:59,000 --> 00:29:03,000 Speaker 1: a much more four quadrant designed Disney Plus can operate 549 00:29:03,080 --> 00:29:08,000 Speaker 1: in both acquiring subscribers and then retaining them. Okay, Julia Alexander, 550 00:29:08,040 --> 00:29:10,840 Speaker 1: thanks for breaking up all that down for us. Appreciated. 551 00:29:10,880 --> 00:29:15,040 Speaker 1: Director of Strategy at Parrot Analytics, appreciate it. Another story 552 00:29:15,040 --> 00:29:18,480 Speaker 1: we are following American basketball star Britney Griner is nine 553 00:29:18,520 --> 00:29:21,840 Speaker 1: and a half year prison sentence in Russia. President Biden 554 00:29:21,920 --> 00:29:24,520 Speaker 1: is calling her sentence quote unacceptable and says the White 555 00:29:24,520 --> 00:29:27,760 Speaker 1: House will worked tirelessly for her release. Grinder was sound 556 00:29:27,760 --> 00:29:30,640 Speaker 1: guilty of drug possession and smuggling after she was arrested 557 00:29:30,880 --> 00:29:34,600 Speaker 1: at a Moscow airport with vape cartridges containing cannabis oil. 558 00:29:34,920 --> 00:29:36,800 Speaker 1: The United States has been trying to broke her a 559 00:29:36,840 --> 00:29:53,520 Speaker 1: prisoner swap for her return, no deal so far. One 560 00:29:53,520 --> 00:29:56,120 Speaker 1: of Wall Street's biggest traditional finance players is making a 561 00:29:56,160 --> 00:29:58,800 Speaker 1: big bet on crypto, black Rock teaming up with coin 562 00:29:58,840 --> 00:30:02,480 Speaker 1: based to make it easier for institutional investors to trade bitcoin. 563 00:30:02,720 --> 00:30:04,920 Speaker 1: Black Rock chose to partner with coin base because of 564 00:30:04,920 --> 00:30:07,360 Speaker 1: its scale in the market. You're gonna break it all down. 565 00:30:07,360 --> 00:30:11,160 Speaker 1: Our crypto CONTRIBUTORTIONALI Bostic Shine. Coin based investors loved this 566 00:30:11,240 --> 00:30:13,960 Speaker 1: new It's so interesting, Emily because if you look at 567 00:30:14,040 --> 00:30:16,520 Speaker 1: coin based shares, they really took a leg higher today 568 00:30:16,600 --> 00:30:19,400 Speaker 1: it's up about ten percent on the day. Pre market 569 00:30:19,440 --> 00:30:21,760 Speaker 1: that jump was much bigger, so appaired some of those 570 00:30:21,800 --> 00:30:25,000 Speaker 1: games for the day. But it's so interesting, especially because 571 00:30:25,280 --> 00:30:30,160 Speaker 1: coin Basis shares have gained almost forty more than over 572 00:30:30,320 --> 00:30:33,400 Speaker 1: three days, so you're really seeing some of the gains 573 00:30:33,760 --> 00:30:36,240 Speaker 1: come back to coin Basis stock that's down still more 574 00:30:36,240 --> 00:30:38,560 Speaker 1: than sixty this year. I want to flip up the 575 00:30:38,600 --> 00:30:40,360 Speaker 1: board a little bit and talk about what Wall Street 576 00:30:40,400 --> 00:30:42,560 Speaker 1: really feels about coin base, because you're seeing some one 577 00:30:42,560 --> 00:30:45,320 Speaker 1: of the biggest players come into it. The twelve month 578 00:30:45,360 --> 00:30:48,320 Speaker 1: price target for coin base has also come down meaningfully 579 00:30:48,640 --> 00:30:52,320 Speaker 1: among some of these larger challenges, even with uh some 580 00:30:52,560 --> 00:30:55,320 Speaker 1: love from people like black Rock, you have coin Basis 581 00:30:55,320 --> 00:30:57,720 Speaker 1: twelve month price target was so really flying at around 582 00:30:57,720 --> 00:31:00,600 Speaker 1: a hundred dollars a hundred and one dollars her share. 583 00:31:00,880 --> 00:31:03,560 Speaker 1: If you look at it today, it's just below ninety. 584 00:31:04,080 --> 00:31:06,160 Speaker 1: If you flip up the board again, you still see 585 00:31:06,200 --> 00:31:09,240 Speaker 1: again with all the challenges, still love from Wall Street. 586 00:31:09,520 --> 00:31:13,880 Speaker 1: About fifty percent of folks say by stay hold, which 587 00:31:13,920 --> 00:31:15,640 Speaker 1: is basically, you know, we don't really know how to 588 00:31:15,640 --> 00:31:19,280 Speaker 1: feel about things given all the volatility, six said sell. 589 00:31:19,440 --> 00:31:21,560 Speaker 1: So there's been a lot of questions around whether the 590 00:31:21,680 --> 00:31:24,400 Speaker 1: momentum would move to the downside for coin base. Emily, 591 00:31:24,400 --> 00:31:26,440 Speaker 1: I have to say, what it's also interesting is the 592 00:31:26,480 --> 00:31:30,040 Speaker 1: opportunity provided here from black Rock because this partnership not 593 00:31:30,120 --> 00:31:31,680 Speaker 1: just with black Rock, but with a part of black 594 00:31:31,760 --> 00:31:34,440 Speaker 1: Rock that's called Aladdin. It gives you exposure not just 595 00:31:34,480 --> 00:31:37,200 Speaker 1: to big institutional investors. Aladdin works with a lot of 596 00:31:37,240 --> 00:31:41,120 Speaker 1: wealth management platforms across Wall Street and around the globe. 597 00:31:41,160 --> 00:31:44,400 Speaker 1: And the reason that's interesting is it potentially exposes you 598 00:31:44,480 --> 00:31:47,280 Speaker 1: not just institutional clients, which is a growth area for 599 00:31:47,400 --> 00:31:50,840 Speaker 1: coin base, but more people that can really fly into 600 00:31:50,920 --> 00:31:53,560 Speaker 1: the more traditional retail business at a time when rivals 601 00:31:53,600 --> 00:31:57,280 Speaker 1: like robin Hood are under a lot more pressure. What 602 00:31:57,320 --> 00:31:59,840 Speaker 1: does this mean for coin based longer term? Obviously, the 603 00:32:00,080 --> 00:32:03,000 Speaker 1: the winter is not over, you know, maybe maybe this 604 00:32:03,080 --> 00:32:06,760 Speaker 1: is the beginning of something, But how much further, how 605 00:32:06,800 --> 00:32:09,440 Speaker 1: how much colder, how cold is the road going to get? 606 00:32:09,920 --> 00:32:12,680 Speaker 1: So that's a question because it's all correlated to bitcoin prices, 607 00:32:12,680 --> 00:32:15,720 Speaker 1: and you saw something similar when it came to Blocks 608 00:32:15,720 --> 00:32:19,640 Speaker 1: earnings that reported after the market closed today. This idea 609 00:32:19,680 --> 00:32:22,400 Speaker 1: that transactions have really slowed. Remember a lot of the 610 00:32:22,400 --> 00:32:25,720 Speaker 1: retail investors that got into cryptocurrencies at the end of 611 00:32:25,800 --> 00:32:28,360 Speaker 1: last year are very much in the red, and so 612 00:32:28,400 --> 00:32:30,560 Speaker 1: how much powder is there left on the sidelines for 613 00:32:30,600 --> 00:32:33,080 Speaker 1: investors to get back into it in volumes to come 614 00:32:33,080 --> 00:32:36,120 Speaker 1: back again. The good news for coin base is and 615 00:32:36,200 --> 00:32:38,600 Speaker 1: you saw it here with Robin Hood just this week 616 00:32:38,880 --> 00:32:41,320 Speaker 1: when you see some of the rivals under pressure here, 617 00:32:41,640 --> 00:32:43,640 Speaker 1: it is good news for coin base, and you saw 618 00:32:43,680 --> 00:32:46,800 Speaker 1: it reflected in coin bases stock. But just for a 619 00:32:46,880 --> 00:32:48,960 Speaker 1: sense of how far we fall in for coin based, 620 00:32:48,960 --> 00:32:50,600 Speaker 1: I mean, this is still a company that's under twenty 621 00:32:50,640 --> 00:32:54,200 Speaker 1: billion dollars in market cap. This was once seventy five 622 00:32:54,360 --> 00:32:57,800 Speaker 1: billion dollars in market cap, and that was at the 623 00:32:57,880 --> 00:33:00,760 Speaker 1: end of last year. So how quickly you can bitcoin 624 00:33:00,880 --> 00:33:03,960 Speaker 1: recover get back to sixty seventy thousand. I think it 625 00:33:04,000 --> 00:33:06,560 Speaker 1: has a lot to do with whether coin base can 626 00:33:06,560 --> 00:33:09,560 Speaker 1: regain its former glory, and whether that even matters if 627 00:33:09,560 --> 00:33:12,960 Speaker 1: people see enough crypto adoption moving forward among the big institutions, 628 00:33:13,160 --> 00:33:16,600 Speaker 1: like you said today with a black rock. So, you know, 629 00:33:16,760 --> 00:33:19,400 Speaker 1: what are you looking for next year? Obviously we've seen 630 00:33:19,440 --> 00:33:22,440 Speaker 1: a wave of you know, difficulties for you know, there's 631 00:33:22,480 --> 00:33:25,440 Speaker 1: been bankruptcies, there's been increasing regulatory scrutiny. There has been 632 00:33:25,440 --> 00:33:29,840 Speaker 1: this big letter from you know, hundreds of skeptics to Congress. 633 00:33:29,920 --> 00:33:32,200 Speaker 1: You know, what's going to be the next inflection point 634 00:33:32,440 --> 00:33:34,440 Speaker 1: in the story of crypto. You know, we've been talking 635 00:33:34,480 --> 00:33:36,240 Speaker 1: about it a lot. You and I this idea of 636 00:33:36,440 --> 00:33:40,080 Speaker 1: coin base versus the SEC. Why does that matter so much? 637 00:33:40,160 --> 00:33:43,960 Speaker 1: Because exchanges coin based f t X, the more that they, 638 00:33:44,720 --> 00:33:46,840 Speaker 1: you know, don't heart with the SEC. You wonder if 639 00:33:46,840 --> 00:33:49,760 Speaker 1: they look more like traditional exchanges like the New York 640 00:33:49,800 --> 00:33:54,120 Speaker 1: Stock Exchange, like the Chicago CEBO, the Board Options Exchange. 641 00:33:54,320 --> 00:33:57,280 Speaker 1: F t X has been highly regulated, working with a 642 00:33:57,320 --> 00:34:01,240 Speaker 1: lot more traditional players here, and you wonder if there's 643 00:34:01,280 --> 00:34:05,760 Speaker 1: a future where people list to token, they go public, 644 00:34:06,040 --> 00:34:08,520 Speaker 1: they don't necessarily choose between the two, or do both. 645 00:34:09,160 --> 00:34:12,000 Speaker 1: The world's are merging. So the question to me is 646 00:34:12,040 --> 00:34:15,239 Speaker 1: how much does coin based embrace that again like you 647 00:34:15,280 --> 00:34:19,239 Speaker 1: see today with a big institutional partnership, or how much 648 00:34:19,600 --> 00:34:21,680 Speaker 1: do they stick to kind of the heart of crypto, 649 00:34:21,760 --> 00:34:26,359 Speaker 1: which was very focused on a decentralized finance and things 650 00:34:26,400 --> 00:34:29,160 Speaker 1: that were so far away from Wall Street as we 651 00:34:29,200 --> 00:34:42,480 Speaker 1: know it. Alright, thank you. As always. As much as 652 00:34:43,160 --> 00:34:47,680 Speaker 1: food produced in the United States is never eaten, that 653 00:34:47,760 --> 00:34:50,719 Speaker 1: is according to the National Resources Defense Counsel, enter a 654 00:34:50,800 --> 00:34:53,320 Speaker 1: Fresh Technology is a startup that is hoping it's AI 655 00:34:53,440 --> 00:34:58,120 Speaker 1: software will help grocery stores massively reduce food waste. They 656 00:34:58,160 --> 00:35:00,960 Speaker 1: just raised fift million dollars in new funding and they're 657 00:35:01,000 --> 00:35:03,720 Speaker 1: on track to save thirty four million pounds of food 658 00:35:03,719 --> 00:35:06,799 Speaker 1: waste by the end of match. Schwartz is a co 659 00:35:06,840 --> 00:35:09,759 Speaker 1: founder and CEO of A Fresh Technologies and it's here 660 00:35:09,800 --> 00:35:11,560 Speaker 1: with us in the studio. Thank you for having me. 661 00:35:11,719 --> 00:35:14,719 Speaker 1: So how does this say I technology work? So? Out 662 00:35:14,719 --> 00:35:17,800 Speaker 1: of fresh We believe that food, more so than anything else, 663 00:35:17,880 --> 00:35:21,279 Speaker 1: shapes the health of people and our planet, and specifically 664 00:35:21,280 --> 00:35:23,720 Speaker 1: within that, we think that fresh food is really driving 665 00:35:23,719 --> 00:35:26,600 Speaker 1: the future of the grocery business and what people want 666 00:35:26,640 --> 00:35:29,720 Speaker 1: to eat. At the same time, though, in building the company, 667 00:35:29,760 --> 00:35:32,520 Speaker 1: we observed that most, if not all, of the technology 668 00:35:32,719 --> 00:35:35,040 Speaker 1: was built for non fresh stuff. It was built for 669 00:35:35,080 --> 00:35:36,359 Speaker 1: things that come in a box. And have a bar 670 00:35:36,440 --> 00:35:38,440 Speaker 1: code and last a long time. And the result of 671 00:35:38,440 --> 00:35:40,560 Speaker 1: that intern is that there was all these processes that 672 00:35:40,600 --> 00:35:43,239 Speaker 1: were not built for fresh and that in turn would 673 00:35:43,320 --> 00:35:45,800 Speaker 1: cause hundreds of billions of dollars of food waste across 674 00:35:45,840 --> 00:35:47,960 Speaker 1: the world and a bunch of other problems. How can 675 00:35:48,000 --> 00:35:51,360 Speaker 1: AI help in the produce categories. So what we're doing 676 00:35:51,560 --> 00:35:55,480 Speaker 1: is building technology specifically for fresh food, and what that 677 00:35:55,600 --> 00:35:58,920 Speaker 1: enables us to do is optimize the quantity of food 678 00:35:59,040 --> 00:36:01,239 Speaker 1: that goes into differ in parts of the supply chain 679 00:36:01,640 --> 00:36:04,680 Speaker 1: to be as fresh as possible, order just the right 680 00:36:04,719 --> 00:36:06,880 Speaker 1: amount and not too little, and that causes us to 681 00:36:06,880 --> 00:36:09,680 Speaker 1: be able to prevent food waste while keeping grocers in stock. 682 00:36:09,800 --> 00:36:11,719 Speaker 1: How do you do that? I mean, even me, as 683 00:36:11,760 --> 00:36:14,520 Speaker 1: a mom, I it's either too much or not enough 684 00:36:14,840 --> 00:36:17,360 Speaker 1: whatever I buy at the store. It's a classic balancing 685 00:36:17,360 --> 00:36:19,960 Speaker 1: act and it's really, really, really tough. The way that 686 00:36:20,000 --> 00:36:22,960 Speaker 1: we do it is we empower store employees at grocery 687 00:36:23,000 --> 00:36:25,560 Speaker 1: stores with an app that's served on a tablet and 688 00:36:25,560 --> 00:36:28,560 Speaker 1: that's powered in the background by artificial intelligence that's trying 689 00:36:28,560 --> 00:36:30,960 Speaker 1: to predict the future, how much is going to be sold, 690 00:36:31,360 --> 00:36:33,799 Speaker 1: understand how much is in the store, right now, and 691 00:36:33,840 --> 00:36:37,320 Speaker 1: then use all that information to create a profit, maximizing waste, 692 00:36:37,320 --> 00:36:40,920 Speaker 1: minimizing order, keeping the shelves full, while minimizing the inventory 693 00:36:40,960 --> 00:36:43,440 Speaker 1: that's in the back room. So you're basically trying to 694 00:36:43,680 --> 00:36:46,319 Speaker 1: figure out how to get groceries not to overorder. That's right. 695 00:36:46,560 --> 00:36:48,760 Speaker 1: You don't want them to overorder. At the same time, 696 00:36:48,840 --> 00:36:50,680 Speaker 1: you don't want them to under order because the other 697 00:36:50,680 --> 00:36:53,640 Speaker 1: problem we're seeing with the supply chain is those empty shelves. 698 00:36:53,800 --> 00:36:55,239 Speaker 1: So what we really want to do is find that 699 00:36:55,280 --> 00:36:57,000 Speaker 1: sweet spot where you go to the store and the 700 00:36:57,000 --> 00:37:00,160 Speaker 1: shelf is full, but the food is they didn't or 701 00:37:00,200 --> 00:37:03,040 Speaker 1: too much that they are going to cause waste. Why 702 00:37:03,200 --> 00:37:06,319 Speaker 1: is getting fresh food so difficult? I mean even when 703 00:37:06,400 --> 00:37:09,000 Speaker 1: picking produce out at the store, sometimes it's it's already 704 00:37:09,040 --> 00:37:11,960 Speaker 1: going bad by the time I pick it up. Yeah, well, 705 00:37:12,120 --> 00:37:13,960 Speaker 1: a lot of this is going back to the original 706 00:37:14,000 --> 00:37:16,360 Speaker 1: thesis of the company. We think fresh is the future, 707 00:37:16,520 --> 00:37:19,360 Speaker 1: but fresh is just so tricky. When you pick a berry, 708 00:37:19,400 --> 00:37:21,840 Speaker 1: it's basically a race against the clock until it's moldy. 709 00:37:22,000 --> 00:37:24,200 Speaker 1: It's got to stay refrigerated, it's got to move quickly 710 00:37:24,200 --> 00:37:26,520 Speaker 1: through it. It's could be sold by weight, and so 711 00:37:26,640 --> 00:37:28,919 Speaker 1: the data structures aren't there. There's no best by date 712 00:37:28,960 --> 00:37:32,319 Speaker 1: on a strawberry, so everything in fresh is far more complicated, 713 00:37:32,520 --> 00:37:34,160 Speaker 1: and that's why we believe you have to build fresh 714 00:37:34,200 --> 00:37:36,120 Speaker 1: first technology to be able to handle it. You've got 715 00:37:36,200 --> 00:37:38,960 Speaker 1: nine grocery chains on board in the US, SAT do 716 00:37:39,040 --> 00:37:43,000 Speaker 1: you plan to get more? So we're demonstrating results. So 717 00:37:43,080 --> 00:37:45,439 Speaker 1: we've shown to date that we prevent waste by about 718 00:37:45,440 --> 00:37:50,440 Speaker 1: fift while also increasing sales by over three percent. And 719 00:37:50,480 --> 00:37:53,120 Speaker 1: so success like that is generating word of mouth and 720 00:37:53,160 --> 00:37:55,880 Speaker 1: happy reference customers for us that are really enabling us 721 00:37:55,920 --> 00:37:58,319 Speaker 1: to grow super rapidly. How do you plan to use 722 00:37:58,360 --> 00:38:01,799 Speaker 1: the new capital really scale? So at the end of 723 00:38:01,880 --> 00:38:04,399 Speaker 1: last year, we were live in two hundred stores and 724 00:38:04,560 --> 00:38:07,200 Speaker 1: we've signed now as of right now, over three thousands, 725 00:38:07,239 --> 00:38:09,440 Speaker 1: so we're growing by over fifteen x. So we're going 726 00:38:09,480 --> 00:38:11,359 Speaker 1: to use the capital to help us scale, and then 727 00:38:11,360 --> 00:38:13,719 Speaker 1: we're gonna go from our starting point in fruits and 728 00:38:13,800 --> 00:38:16,920 Speaker 1: vegetables to meet and seafood, Delhi Bakery, all the fresh 729 00:38:16,960 --> 00:38:19,080 Speaker 1: stuff around the grocery store, and then we plan to 730 00:38:19,080 --> 00:38:21,680 Speaker 1: make our initial forays internationally and up higher in the 731 00:38:21,719 --> 00:38:24,440 Speaker 1: supply chain. What was it like raising money in this environment. 732 00:38:24,440 --> 00:38:27,640 Speaker 1: I mean, it's a tough environment. Did that impact your valuation? 733 00:38:27,880 --> 00:38:29,840 Speaker 1: What is your valuation? We're in a we're in a 734 00:38:29,880 --> 00:38:32,200 Speaker 1: bit of a unique place at of Fresh where we're 735 00:38:32,200 --> 00:38:35,120 Speaker 1: of service to this mission critical industry of grocery. I 736 00:38:35,120 --> 00:38:37,799 Speaker 1: think during the pandemic everyone came to appreciate them. When 737 00:38:37,840 --> 00:38:40,279 Speaker 1: times are tough, grocers are what really feed us and 738 00:38:40,320 --> 00:38:42,839 Speaker 1: shareff stomach goes more towards eating in, and so we're 739 00:38:42,840 --> 00:38:45,000 Speaker 1: of service to that industry that kind of is a 740 00:38:45,120 --> 00:38:47,879 Speaker 1: cyclical or can even benefit from tough times. And then 741 00:38:47,920 --> 00:38:51,080 Speaker 1: we're tackling problems of inflation and supply chain and so 742 00:38:51,120 --> 00:38:53,560 Speaker 1: I think investors really saw all of that, and they 743 00:38:53,600 --> 00:38:55,120 Speaker 1: saw the traction that we had and they were willing 744 00:38:55,120 --> 00:38:57,719 Speaker 1: to be big on us, which I'm proud of. I 745 00:38:57,719 --> 00:38:59,560 Speaker 1: can't share that right now. Well, what are your longer 746 00:38:59,640 --> 00:39:02,200 Speaker 1: term play ends? I mean, are you looking to stay independent, 747 00:39:02,280 --> 00:39:06,040 Speaker 1: go public, get bought by a larger food distributor? What's 748 00:39:06,040 --> 00:39:09,040 Speaker 1: the goal. Our mission is to eliminate food waste and 749 00:39:09,040 --> 00:39:11,840 Speaker 1: make fresh food accessible to all. There's trillions of dollars 750 00:39:11,840 --> 00:39:14,400 Speaker 1: of fresh food sold around the world. Our mission, what 751 00:39:14,440 --> 00:39:16,000 Speaker 1: I believe we want to do is build a very 752 00:39:16,040 --> 00:39:19,320 Speaker 1: big company that eliminates that waste and proliferates across the 753 00:39:19,360 --> 00:39:21,880 Speaker 1: supply chaine. So whether that be a standalone company or 754 00:39:21,920 --> 00:39:24,279 Speaker 1: eventually I p owing, my plan really is just to 755 00:39:24,320 --> 00:39:26,520 Speaker 1: try to fulfill that mission. And how does this impact 756 00:39:26,520 --> 00:39:30,120 Speaker 1: the suppliers on the back end quickly? So is it 757 00:39:30,280 --> 00:39:32,719 Speaker 1: worse for them because you know, grocers are ordering less. 758 00:39:33,440 --> 00:39:36,160 Speaker 1: The dynamic we live in is that population is growing 759 00:39:36,239 --> 00:39:38,960 Speaker 1: from something like seven billion people to nine and ten 760 00:39:39,000 --> 00:39:44,920 Speaker 1: billion people. So we've got I mean, no comment, but 761 00:39:45,000 --> 00:39:46,920 Speaker 1: what I will say is that population is growing and 762 00:39:46,960 --> 00:39:49,640 Speaker 1: we're out of land. Uh we're burning down the rainforest 763 00:39:49,680 --> 00:39:52,600 Speaker 1: and create enough land to grow cowse and yields are 764 00:39:52,600 --> 00:39:54,319 Speaker 1: going to be impacted by climate change. So we have 765 00:39:54,400 --> 00:39:57,239 Speaker 1: to find ways to do more with less to be sustainable. 766 00:39:57,600 --> 00:39:59,560 Speaker 1: And so at the end of the day, when we 767 00:39:59,680 --> 00:40:02,759 Speaker 1: drive the ficiencies at the store, growers upstream are really 768 00:40:02,800 --> 00:40:05,960 Speaker 1: appreciative that as well. All right, Matchwarts, CEO and co 769 00:40:06,040 --> 00:40:09,480 Speaker 1: founder of a Fresh Technology. Thank you, really interesting, Thank 770 00:40:09,520 --> 00:40:11,320 Speaker 1: you keep your eyeing you all right? That does it 771 00:40:11,400 --> 00:40:14,160 Speaker 1: for this edition of Bloomberg Technology. I'm Emily Chang in 772 00:40:14,160 --> 00:40:17,000 Speaker 1: San Francisco. Great show coming up tomorrow. Lift co founder 773 00:40:17,040 --> 00:40:20,200 Speaker 1: John Zimmer will be here. Glenn Kelman of Redfinn and 774 00:40:20,640 --> 00:40:23,719 Speaker 1: Reed Hoffman always loved talking to him. That's tomorrow, right 775 00:40:23,719 --> 00:40:25,880 Speaker 1: here on Bloomberg Technology. This is Bloomberg