1 00:00:02,720 --> 00:00:10,600 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:10,600 --> 00:00:14,560 Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am 3 00:00:14,640 --> 00:00:17,880 Speaker 1: Eastern on Apple Coarclay and Android Auto with the Bloomberg 4 00:00:17,920 --> 00:00:21,000 Speaker 1: Business App. Listen on demand wherever you get your podcasts, 5 00:00:21,360 --> 00:00:23,920 Speaker 1: or watch us live on YouTube. 6 00:00:24,520 --> 00:00:25,800 Speaker 2: We had some FDA approvals. 7 00:00:25,800 --> 00:00:29,200 Speaker 3: They're pushing gains in some part of pharmaceutical companies, specifically 8 00:00:29,400 --> 00:00:32,159 Speaker 3: Novo nor Disk. So here to break that down, and 9 00:00:32,200 --> 00:00:34,600 Speaker 3: a whole lot more news that's coming out about Novo 10 00:00:35,159 --> 00:00:37,920 Speaker 3: is Madison Miller, She's Bloomberg Health reporter. But the big 11 00:00:37,960 --> 00:00:39,680 Speaker 3: news so the weight loss drugg we go. We got 12 00:00:39,680 --> 00:00:43,479 Speaker 3: this use approval to treat a form of liver disease. 13 00:00:43,520 --> 00:00:45,200 Speaker 3: So what does this mean for the company. 14 00:00:45,400 --> 00:00:49,400 Speaker 4: Yeah, so on Friday afternoon, late on Friday, Nova artists 15 00:00:49,440 --> 00:00:52,000 Speaker 4: got approval for Regovi, which is its weight loss drug 16 00:00:52,040 --> 00:00:55,440 Speaker 4: to treat a liver disease called MASH. And this sort 17 00:00:55,480 --> 00:00:58,160 Speaker 4: of is a we've seen over the last couple of years. 18 00:00:58,200 --> 00:01:01,560 Speaker 4: So many studies come out show the potential health benefits 19 00:01:01,600 --> 00:01:04,360 Speaker 4: of these weight loss drugs beyond just you know, the 20 00:01:04,400 --> 00:01:07,040 Speaker 4: reducing the number on the scale. And we knew from 21 00:01:07,080 --> 00:01:10,160 Speaker 4: studies that there was some benefit to the liver from 22 00:01:10,200 --> 00:01:12,800 Speaker 4: taking these drugs, and so Nova was able to notch 23 00:01:12,800 --> 00:01:16,440 Speaker 4: and approval for that, which helps one with insurance coverage. 24 00:01:16,880 --> 00:01:19,720 Speaker 4: Wigov and then Eli Lilly's drug zet Bound are still 25 00:01:19,760 --> 00:01:24,280 Speaker 4: not super widely covered by insurance companies for weight loss, 26 00:01:24,319 --> 00:01:27,560 Speaker 4: but having some of these other health benefits shown and 27 00:01:27,600 --> 00:01:30,640 Speaker 4: proven in studies helps them convince insures that they are 28 00:01:30,680 --> 00:01:33,800 Speaker 4: worth covering, and so this gives them an edge against Lily. 29 00:01:33,840 --> 00:01:37,520 Speaker 4: Lily's drug, Zetbound is not approved yet for this indication, 30 00:01:37,720 --> 00:01:41,200 Speaker 4: and so it gives them sort of a leg up there, 31 00:01:41,959 --> 00:01:46,280 Speaker 4: and then it also gets I mean it sort of 32 00:01:46,680 --> 00:01:52,280 Speaker 4: is another benefit for Novo because they've been struggling over 33 00:01:52,320 --> 00:01:56,200 Speaker 4: the last year. Just with zet Bound sort of making 34 00:01:56,920 --> 00:01:59,840 Speaker 4: waves in the market and taking market share from Wagov. 35 00:02:00,120 --> 00:02:03,320 Speaker 4: This gives them a leg up there as well. And 36 00:02:03,440 --> 00:02:06,800 Speaker 4: just with the tumultuousness of the last few weeks, they 37 00:02:06,800 --> 00:02:10,720 Speaker 4: had a CEO ouster and a few other moving pieces. 38 00:02:10,760 --> 00:02:15,480 Speaker 4: So this is good news for them and we'll we'll see, 39 00:02:15,800 --> 00:02:18,239 Speaker 4: but it will maybe help them gain back some market share. 40 00:02:20,200 --> 00:02:22,000 Speaker 2: One of the issues for these weight loss drugs is 41 00:02:22,040 --> 00:02:24,760 Speaker 2: the cost and if you're not covered by insurance. They 42 00:02:24,919 --> 00:02:28,720 Speaker 2: really are expensive. So by slashing the cost of a 43 00:02:28,800 --> 00:02:31,480 Speaker 2: zempic in half, does a company believe that's going to 44 00:02:31,520 --> 00:02:35,360 Speaker 2: open up a big new vein of new customers. Maybe. 45 00:02:35,639 --> 00:02:38,639 Speaker 4: So it's interesting because if patients are on ozempic, they 46 00:02:39,080 --> 00:02:40,880 Speaker 4: are usually on it. It's you know, a type two 47 00:02:40,919 --> 00:02:42,920 Speaker 4: diabetes treatment and usually. 48 00:02:42,520 --> 00:02:46,640 Speaker 2: That's covered by diabetes. But does it have a side 49 00:02:46,680 --> 00:02:48,160 Speaker 2: benefit I guess of weight loss? 50 00:02:48,400 --> 00:02:48,640 Speaker 5: Yes? 51 00:02:48,760 --> 00:02:51,359 Speaker 4: So, I mean there are two different drugs, right, There's ozembic, 52 00:02:51,400 --> 00:02:54,120 Speaker 4: which is the diabetes drug wigov. They both use the 53 00:02:54,160 --> 00:02:57,480 Speaker 4: exact same active ingredient, which is semiglue tide. Wigov is 54 00:02:57,480 --> 00:03:01,040 Speaker 4: a higher dose version if you're on azempa gets lower doses, 55 00:03:01,080 --> 00:03:03,200 Speaker 4: so it's not quite as strong, but there is that 56 00:03:03,240 --> 00:03:08,360 Speaker 4: weight loss side effect on both drugs. Previously, Novo actually 57 00:03:08,360 --> 00:03:11,320 Speaker 4: did cut the cost of wigo V down to about 58 00:03:11,320 --> 00:03:14,000 Speaker 4: the same price five hundred dollars a month back in March, 59 00:03:14,360 --> 00:03:16,720 Speaker 4: and now they are doing the same for ozempic. 60 00:03:16,840 --> 00:03:19,119 Speaker 5: But it's interesting because the question. 61 00:03:18,840 --> 00:03:21,120 Speaker 4: Of whether or not this is going to expand access 62 00:03:21,120 --> 00:03:23,919 Speaker 4: for more patients sort of remains to be seen. Because again, 63 00:03:23,960 --> 00:03:27,560 Speaker 4: if you have ozempic, you usually are covered by insurance 64 00:03:27,600 --> 00:03:27,919 Speaker 4: for it. 65 00:03:28,760 --> 00:03:31,480 Speaker 3: Now something I also said, there are partnering in this article, 66 00:03:31,480 --> 00:03:33,679 Speaker 3: it said with good Rx to offer ozempic, we go 67 00:03:33,800 --> 00:03:37,160 Speaker 3: before the same price as pharmacies. But didn't Novo try 68 00:03:37,200 --> 00:03:39,680 Speaker 3: the partnership thing with Hymns and Hers and that didn't 69 00:03:39,720 --> 00:03:40,680 Speaker 3: work out so well. 70 00:03:40,520 --> 00:03:43,360 Speaker 4: Yeah, yeah, So Hyms was one of several partners that 71 00:03:43,440 --> 00:03:45,760 Speaker 4: Novo has sort of worked with over the last couple 72 00:03:45,800 --> 00:03:49,600 Speaker 4: of months again to really make waves and get into 73 00:03:49,680 --> 00:03:53,040 Speaker 4: this market or gain back market share because it's really 74 00:03:53,240 --> 00:03:54,880 Speaker 4: lost ground to Eli Lilly. 75 00:03:55,560 --> 00:03:57,440 Speaker 5: Hyms was one of the companies that they've partnered with. 76 00:03:57,480 --> 00:04:00,480 Speaker 4: They've partnered with a couple of other telehealth companies as 77 00:04:00,520 --> 00:04:03,680 Speaker 4: well as CVS to make this cash pay price more 78 00:04:03,720 --> 00:04:06,520 Speaker 4: widely available, but this is the first time that they're 79 00:04:06,600 --> 00:04:09,560 Speaker 4: dropping the price of ozempic as well. So this partnership 80 00:04:09,560 --> 00:04:12,920 Speaker 4: with good Rx, you know, any patient is essentially a coupon, 81 00:04:13,000 --> 00:04:16,480 Speaker 4: like any patient who goes to a pharmacy uses GoodRx 82 00:04:16,640 --> 00:04:18,719 Speaker 4: is going to be able to get this cash pay 83 00:04:18,760 --> 00:04:19,840 Speaker 4: price for ozempic. 84 00:04:19,880 --> 00:04:24,320 Speaker 2: And Wigov mentioned that the Hymns and Hers, those compound drugs, 85 00:04:24,520 --> 00:04:29,240 Speaker 2: how effective are they visa v the golp ones themselves, 86 00:04:29,279 --> 00:04:31,480 Speaker 2: because that would be a if I were like Novo Nordics, 87 00:04:31,480 --> 00:04:33,240 Speaker 2: I spent all this money to develop, that would be 88 00:04:33,240 --> 00:04:34,240 Speaker 2: a bummerp receise yes. 89 00:04:34,560 --> 00:04:37,440 Speaker 4: And that's a really good question actually, that question of 90 00:04:37,480 --> 00:04:40,560 Speaker 4: how effective are these drugs, because that's the problem is 91 00:04:40,600 --> 00:04:44,160 Speaker 4: we don't know. There are studies that drug makers are 92 00:04:44,200 --> 00:04:46,039 Speaker 4: required to do. They have to go through a length 93 00:04:46,080 --> 00:04:49,080 Speaker 4: the FDA approval process to prove that their medications are 94 00:04:49,120 --> 00:04:52,120 Speaker 4: safe and effective. Compounded drugs don't go through that same 95 00:04:52,120 --> 00:04:55,919 Speaker 4: approval process, so there's no actual studies showing how effective 96 00:04:56,000 --> 00:04:57,279 Speaker 4: those medications are. 97 00:04:57,320 --> 00:04:58,760 Speaker 5: And it's a little bit of a gamble. 98 00:04:58,800 --> 00:05:02,960 Speaker 4: I mean, we've seen losing weight on these compounded medications, 99 00:05:03,320 --> 00:05:07,719 Speaker 4: and we haven't seen a tremendous amount of side effects 100 00:05:07,720 --> 00:05:12,240 Speaker 4: that are really different from the branded medications. So the 101 00:05:12,279 --> 00:05:14,360 Speaker 4: problem is just more that we don't actually have a 102 00:05:14,400 --> 00:05:17,560 Speaker 4: lot of visibility into that compounded market and don't know 103 00:05:18,440 --> 00:05:21,960 Speaker 4: how those drugs stack up to the branded medications. 104 00:05:22,200 --> 00:05:24,520 Speaker 3: In the last thirty seconds or so we have where 105 00:05:24,560 --> 00:05:26,360 Speaker 3: does this all put Eli Lilly then, I mean they 106 00:05:26,400 --> 00:05:28,680 Speaker 3: already had the setback with the weight loss pill, So 107 00:05:29,040 --> 00:05:30,880 Speaker 3: so now we're hearing all this about Nova, where does 108 00:05:30,920 --> 00:05:31,360 Speaker 3: this put. 109 00:05:31,240 --> 00:05:33,640 Speaker 4: Them Yeah, yeah, I mean it's been it's interesting. Like 110 00:05:33,720 --> 00:05:37,000 Speaker 4: the two companies, I think last year it was just 111 00:05:37,080 --> 00:05:39,360 Speaker 4: they were so red hot and there was like nothing, 112 00:05:39,400 --> 00:05:41,719 Speaker 4: The expectations were sky high. There was really nothing that 113 00:05:41,839 --> 00:05:44,599 Speaker 4: seemingly could bring them down. But now we're seeing a 114 00:05:44,600 --> 00:05:46,560 Speaker 4: couple of stumbles and I think that that, you know, 115 00:05:46,720 --> 00:05:50,119 Speaker 4: shows again how high the expectations are for this market. 116 00:05:50,160 --> 00:05:53,240 Speaker 4: There's just no room for failure. But we'll see what 117 00:05:53,320 --> 00:05:54,359 Speaker 4: happens next to Lily. 118 00:05:55,120 --> 00:05:58,320 Speaker 2: When is the pill going to be available day? Twelve 119 00:05:58,360 --> 00:05:59,120 Speaker 2: months year? 120 00:05:59,200 --> 00:06:01,800 Speaker 4: Sometime twenty six So they said that they're planning to 121 00:06:01,960 --> 00:06:04,240 Speaker 4: file for afday approval by the end of the year 122 00:06:04,400 --> 00:06:06,320 Speaker 4: and then hopefully launch next year. 123 00:06:07,160 --> 00:06:10,280 Speaker 2: Stay with us more from Bloomberg Intelligence coming up after this. 124 00:06:12,440 --> 00:06:16,159 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 125 00:06:16,240 --> 00:06:19,280 Speaker 1: weekdays at ten am Eastern on Apple, Cockplay and Android 126 00:06:19,320 --> 00:06:22,640 Speaker 1: Auto with the Bloomberg Business app. Listen on demand wherever 127 00:06:22,680 --> 00:06:25,800 Speaker 1: you get your podcasts, or watch us live on YouTube. 128 00:06:26,640 --> 00:06:29,719 Speaker 3: We do have some possible dealmaking news, so sources saying 129 00:06:29,760 --> 00:06:33,000 Speaker 3: to Mobravo when talks about human resources management software provider 130 00:06:33,120 --> 00:06:36,320 Speaker 3: day Force and take the company private. So what does 131 00:06:36,360 --> 00:06:38,600 Speaker 3: this all mean, we'll be the right person to break 132 00:06:38,640 --> 00:06:41,200 Speaker 3: it all down for us. It's Narage Batllities, Bloomberg Intelligence, 133 00:06:41,240 --> 00:06:45,240 Speaker 3: Senior software analyst, Nearaje. You're joining us from Princeton. Thanks 134 00:06:45,279 --> 00:06:47,440 Speaker 3: for joining. I want you to see if you can 135 00:06:47,480 --> 00:06:49,800 Speaker 3: talk to us about day force because I'm reading through 136 00:06:49,800 --> 00:06:52,600 Speaker 3: the article says shares a falling about sixty percent from 137 00:06:52,640 --> 00:06:55,920 Speaker 3: their twenty twenty one peak through Friday. Can you talk 138 00:06:55,960 --> 00:06:57,680 Speaker 3: about some of the things that this company has been 139 00:06:57,680 --> 00:06:58,280 Speaker 3: struggling with? 140 00:06:59,080 --> 00:07:02,920 Speaker 6: Yeah, Hi, Lisa, this has been even beyond a day 141 00:07:02,960 --> 00:07:06,520 Speaker 6: force struggling point. The HCM industry which they play in 142 00:07:06,560 --> 00:07:10,120 Speaker 6: the HR and payroll software that has been under pressure 143 00:07:10,320 --> 00:07:13,680 Speaker 6: along with application software. And just for a little bit 144 00:07:13,720 --> 00:07:19,360 Speaker 6: of valuation perspective, application software companies, they're in the seventeenth 145 00:07:19,400 --> 00:07:23,960 Speaker 6: percentile of their historical range and day forces at an 146 00:07:24,000 --> 00:07:28,960 Speaker 6: all time low. And this is telling because they are 147 00:07:29,000 --> 00:07:31,680 Speaker 6: facing a lot of deceleration on the top line. They 148 00:07:32,080 --> 00:07:34,120 Speaker 6: in twenty twenty one, twenty twenty two, they are at 149 00:07:34,160 --> 00:07:38,440 Speaker 6: twenty two percent sales growth. Now we're looking at eleven 150 00:07:38,480 --> 00:07:41,200 Speaker 6: percent for this year and next year, and there's a 151 00:07:41,240 --> 00:07:43,400 Speaker 6: lot of factors coming into play here. They have a 152 00:07:43,440 --> 00:07:47,040 Speaker 6: lot of competition. The customers are slowing in terms of 153 00:07:47,120 --> 00:07:50,600 Speaker 6: new ads as well as the upsell and cross sell 154 00:07:50,720 --> 00:07:52,000 Speaker 6: to existing customers. 155 00:07:52,480 --> 00:07:56,240 Speaker 2: So is this just the spending and in human resources 156 00:07:56,680 --> 00:08:00,360 Speaker 2: part of the pie. Is that slowing or is it 157 00:08:00,400 --> 00:08:04,080 Speaker 2: competition here? What's the problem for some of these companies. 158 00:08:05,240 --> 00:08:10,280 Speaker 6: Yeah, their competition push is limited. They play in the 159 00:08:10,440 --> 00:08:15,440 Speaker 6: larger enterprise segment, so they run into UKG or workday, 160 00:08:16,520 --> 00:08:18,840 Speaker 6: so it's not so much competition, but it's a little 161 00:08:18,840 --> 00:08:22,280 Speaker 6: bit of a macro trend. You have US labor non 162 00:08:22,680 --> 00:08:27,280 Speaker 6: farm payroll additions which discel Ray significantly and that's growing 163 00:08:27,400 --> 00:08:30,680 Speaker 6: at about a one percent pace. It averages two to 164 00:08:30,760 --> 00:08:34,920 Speaker 6: three percent, so we have a macro factor. Second, they 165 00:08:34,960 --> 00:08:37,559 Speaker 6: have a portfolio which is common to a lot of peers, 166 00:08:37,559 --> 00:08:40,400 Speaker 6: so there's a lot of portfolio convergence in HR software. 167 00:08:40,800 --> 00:08:49,000 Speaker 6: It's covering like payroll scope, account administration, workforce management, talent management, 168 00:08:49,120 --> 00:08:52,200 Speaker 6: learning management. So these players have all converged on the 169 00:08:52,200 --> 00:08:55,680 Speaker 6: same portfolio. They're trying to push that sale, but there's 170 00:08:55,720 --> 00:08:59,320 Speaker 6: only a limiting sale per customer that they're able to 171 00:08:59,400 --> 00:09:03,400 Speaker 6: translate to. For example, they're selling about thirteen dollars of 172 00:09:03,480 --> 00:09:06,719 Speaker 6: software per employee and it's only growing at a five 173 00:09:06,760 --> 00:09:07,439 Speaker 6: percent pace. 174 00:09:08,320 --> 00:09:11,160 Speaker 3: Now, No, Reij, were you surprised by this report, because 175 00:09:11,160 --> 00:09:12,640 Speaker 3: it seems like from how you were talking, I mean 176 00:09:12,720 --> 00:09:15,120 Speaker 3: kind of this path was leading to the way it 177 00:09:15,200 --> 00:09:16,800 Speaker 3: is that this report came out today. 178 00:09:18,480 --> 00:09:20,920 Speaker 6: Yeah. No, this didn't catch us by surprise in the 179 00:09:20,960 --> 00:09:27,439 Speaker 6: sense that we're expecting more consolidation. Paycheck acquired Paycore in April, 180 00:09:27,840 --> 00:09:31,320 Speaker 6: and that was a smaller player that targeted more small 181 00:09:31,400 --> 00:09:35,520 Speaker 6: SMB segments. This player, day Force, they're targeting a large 182 00:09:35,559 --> 00:09:39,040 Speaker 6: mid market customer, so we're not surprised the valuations are 183 00:09:39,120 --> 00:09:42,520 Speaker 6: quite low. The one positive factor here is eight CM 184 00:09:42,800 --> 00:09:46,960 Speaker 6: ranking in terms of AI disruption across app software is 185 00:09:47,000 --> 00:09:49,599 Speaker 6: on the lower side. Sales and marketing is on the 186 00:09:49,679 --> 00:09:52,400 Speaker 6: higher end. It service management is on the higher end. 187 00:09:52,600 --> 00:09:54,440 Speaker 6: So that may be a little bit of the appeal 188 00:09:54,520 --> 00:09:58,520 Speaker 6: coming from Thomas Bravo's lens where the AI agents are 189 00:09:58,559 --> 00:10:02,000 Speaker 6: not going to take over the app function hr software, 190 00:10:02,120 --> 00:10:03,880 Speaker 6: So easily stay with us. 191 00:10:04,000 --> 00:10:06,360 Speaker 2: More from Bloomberg Intelligence coming up after this. 192 00:10:08,520 --> 00:10:12,240 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 193 00:10:12,320 --> 00:10:15,679 Speaker 1: weekdays at ten am Eastern on Applecarplay and Android Auto 194 00:10:15,800 --> 00:10:18,880 Speaker 1: with the Bloomberg Business app, listen on demand wherever you 195 00:10:18,920 --> 00:10:22,320 Speaker 1: get your podcasts, or watch us live on YouTube. 196 00:10:23,120 --> 00:10:25,640 Speaker 3: So Air Canada, right, they pulled their financial guidance through 197 00:10:25,640 --> 00:10:28,880 Speaker 3: a year, and thousands of Air Canada flight attendants they 198 00:10:28,880 --> 00:10:30,880 Speaker 3: walked out over the weekend. So what we want to 199 00:10:30,920 --> 00:10:33,680 Speaker 3: do is find out more behind the strikes, more behind 200 00:10:33,800 --> 00:10:36,120 Speaker 3: what's going on here with us to explain more as 201 00:10:36,200 --> 00:10:41,600 Speaker 3: francois to flow. He is US airline aerospace analyst here friends, 202 00:10:41,640 --> 00:10:43,800 Speaker 3: WI thanks for joining us over from the Princeton office. 203 00:10:43,920 --> 00:10:46,640 Speaker 3: First off, I mean this is the peak Trumble travel 204 00:10:46,760 --> 00:10:49,600 Speaker 3: summer season. How much of an impact is it going 205 00:10:49,640 --> 00:10:50,400 Speaker 3: to have for the company? 206 00:10:51,480 --> 00:10:55,160 Speaker 7: Yes, good morning, Yes exactly. That's the worst time that 207 00:10:55,240 --> 00:10:57,920 Speaker 7: it could happen. It's August, it's one of the busiest, 208 00:10:58,280 --> 00:11:01,520 Speaker 7: busiest months of the year. And when we look at 209 00:11:01,800 --> 00:11:05,600 Speaker 7: the number of consoliations during this weekend, almost eighty percent 210 00:11:05,640 --> 00:11:08,760 Speaker 7: of the flight and the seat we're concoled during this weekend, 211 00:11:08,880 --> 00:11:13,079 Speaker 7: So it's really significant. When we try to do the math, 212 00:11:14,040 --> 00:11:18,600 Speaker 7: we get to something around two hundred million impact revenues, 213 00:11:18,640 --> 00:11:21,679 Speaker 7: So that would be about three percent of the six 214 00:11:21,720 --> 00:11:25,880 Speaker 7: point two six point three billion all then you expected 215 00:11:25,960 --> 00:11:30,040 Speaker 7: for this quarter. So's it could be, it could be big. 216 00:11:30,080 --> 00:11:33,120 Speaker 7: And the question is how long does it take for 217 00:11:33,600 --> 00:11:38,160 Speaker 7: Canada to resume and get back to the full operation, 218 00:11:38,280 --> 00:11:41,400 Speaker 7: because it's not just the flights and the seats console 219 00:11:41,520 --> 00:11:45,240 Speaker 7: during the three days, but it's also our long does 220 00:11:45,240 --> 00:11:49,800 Speaker 7: it take to resume and return to a normal operation, 221 00:11:50,120 --> 00:11:52,880 Speaker 7: knowing that we are not even sure when flights and 222 00:11:52,880 --> 00:11:55,960 Speaker 7: attendance will go back to work. So that's the big question. 223 00:11:56,040 --> 00:12:00,240 Speaker 7: And then obviously the impact, the lasting impact on booking things, 224 00:12:00,640 --> 00:12:03,440 Speaker 7: fairs and the brain name that the struck could have 225 00:12:03,760 --> 00:12:07,440 Speaker 7: through the rest of the year, because when this kind 226 00:12:07,480 --> 00:12:11,319 Speaker 7: of event happened, you usually end up having to discount 227 00:12:11,320 --> 00:12:16,439 Speaker 7: a little bit first to low customer back to your flight, 228 00:12:16,520 --> 00:12:21,320 Speaker 7: so there is also those questions. But that's the kind 229 00:12:21,320 --> 00:12:25,040 Speaker 7: of amount that we see for this quarter. And I 230 00:12:25,280 --> 00:12:28,520 Speaker 7: just to give a little bit also of context, this 231 00:12:28,640 --> 00:12:31,960 Speaker 7: happens at a time where Canada is it by the 232 00:12:32,200 --> 00:12:35,600 Speaker 7: US trade dispute that all not only impacts the GDP, 233 00:12:35,720 --> 00:12:40,080 Speaker 7: but also impact the travel patterns and Air Canada was 234 00:12:40,240 --> 00:12:45,920 Speaker 7: definitely facing big headings because of this and had to 235 00:12:45,960 --> 00:12:51,040 Speaker 7: relocate seats from the US to somewhere else, and that 236 00:12:51,200 --> 00:12:54,080 Speaker 7: had an additional impact on yells during two Q and 237 00:12:54,320 --> 00:12:55,079 Speaker 7: likely three. 238 00:12:54,960 --> 00:12:57,680 Speaker 2: Q Air Canada. What's the market how's the market share 239 00:12:57,760 --> 00:13:00,480 Speaker 2: shakeout in Canada? 240 00:13:00,840 --> 00:13:04,120 Speaker 7: Or in Canada they have almost fifty percent of the 241 00:13:04,200 --> 00:13:07,240 Speaker 7: market in terms of capacity, between forty five and fifty 242 00:13:07,280 --> 00:13:10,360 Speaker 7: depending on the market, depending on the quarter, but it's 243 00:13:10,679 --> 00:13:15,160 Speaker 7: very significant. And then you have a second competitor, west Jet, 244 00:13:15,200 --> 00:13:18,120 Speaker 7: which is about thirty percent. So you have a very 245 00:13:18,440 --> 00:13:23,920 Speaker 7: too strong airlines in Canada that have a sizeable share. 246 00:13:24,720 --> 00:13:27,440 Speaker 2: All right, friend, So what Canadians this winter when it 247 00:13:27,440 --> 00:13:29,120 Speaker 2: gets cold? You're telling me they're not going to fly 248 00:13:29,200 --> 00:13:30,959 Speaker 2: down to Arizona and Florida. 249 00:13:32,440 --> 00:13:33,360 Speaker 6: Probably less. 250 00:13:34,000 --> 00:13:39,920 Speaker 7: At least Air Canada cut travel to the US. They 251 00:13:39,960 --> 00:13:43,320 Speaker 7: cut eight percent into Q. They were likely to do 252 00:13:43,480 --> 00:13:46,840 Speaker 7: the same through the end of the year. That's the 253 00:13:46,960 --> 00:13:50,920 Speaker 7: only way in order to make sure that yield remain 254 00:13:51,240 --> 00:13:54,520 Speaker 7: kind of stable. They manage this in two Q. The 255 00:13:54,679 --> 00:13:57,160 Speaker 7: UPE was to do it again in three Q and 256 00:13:57,200 --> 00:14:00,520 Speaker 7: four Q. Will see if that can happen. We see 257 00:14:01,400 --> 00:14:06,680 Speaker 7: what kind of fright attendance can get during the negotiation, 258 00:14:06,800 --> 00:14:09,400 Speaker 7: because it's also some things that the market could be 259 00:14:09,440 --> 00:14:09,880 Speaker 7: looking at. 260 00:14:10,320 --> 00:14:13,439 Speaker 2: Stay with us. More from Bloomberg Intelligence coming up after this. 261 00:14:15,600 --> 00:14:19,280 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 262 00:14:19,360 --> 00:14:22,480 Speaker 1: weekdays at ten am Eastern on Apple Coarclay and Android 263 00:14:22,480 --> 00:14:25,800 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 264 00:14:25,840 --> 00:14:29,160 Speaker 1: you get your podcasts, or watch us live on YouTube. 265 00:14:29,880 --> 00:14:32,160 Speaker 2: Let's switch to tech. Like when I go to vacation, 266 00:14:32,400 --> 00:14:34,880 Speaker 2: I go to like the Jersey shore Man Deep sing, No, 267 00:14:35,440 --> 00:14:40,520 Speaker 2: the dude picks Calgary, like in Canada, Like, who does that? 268 00:14:40,680 --> 00:14:43,000 Speaker 2: I mean? I love skiing out there, so I don't. 269 00:14:43,000 --> 00:14:44,920 Speaker 2: Maybe he knows something we've done. It's beautiful out there. 270 00:14:44,920 --> 00:14:48,760 Speaker 2: I get it, Man Deep, sing, Bloomberg Intelligence Senior tech analyst, 271 00:14:49,560 --> 00:14:52,320 Speaker 2: Man Deep. Here's the story I want to get to. 272 00:14:52,760 --> 00:14:54,840 Speaker 2: Back in my day, if you were in a public 273 00:14:54,880 --> 00:14:57,480 Speaker 2: startup company and your stock was all tied up in 274 00:14:57,480 --> 00:14:59,520 Speaker 2: a private company, you had to wait for an IPO, 275 00:15:00,040 --> 00:15:01,880 Speaker 2: then you had to wait for the six month lockup, 276 00:15:02,040 --> 00:15:04,840 Speaker 2: then you could begin starting selling. That's not the case today. 277 00:15:04,880 --> 00:15:08,200 Speaker 2: The people open AI. There's something about six billion dollars 278 00:15:08,440 --> 00:15:10,920 Speaker 2: in stock here. This is becoming more and more common, 279 00:15:10,960 --> 00:15:12,080 Speaker 2: isn't for your tech companies? 280 00:15:13,240 --> 00:15:17,480 Speaker 8: It is, and I think Meta exacerbated that trend by 281 00:15:17,680 --> 00:15:21,000 Speaker 8: you know, the aquihiers. They've made in the last two 282 00:15:21,040 --> 00:15:24,320 Speaker 8: three months. I mean, there are startups that have just 283 00:15:24,360 --> 00:15:29,960 Speaker 8: disappeared without an outright acquisition because Meta acquired their top 284 00:15:30,040 --> 00:15:33,520 Speaker 8: five people or top ten people. And look, when you 285 00:15:33,680 --> 00:15:37,000 Speaker 8: have that sort of risk of losing talent, you got 286 00:15:37,000 --> 00:15:42,040 Speaker 8: to find ways to, you know, liquidate your stuff, the 287 00:15:42,120 --> 00:15:44,720 Speaker 8: stock that you have in your company. And for open Ai, 288 00:15:44,840 --> 00:15:47,760 Speaker 8: I mean, talent is paramount. This is a company that 289 00:15:47,880 --> 00:15:51,120 Speaker 8: may end up doing, you know, almost a twenty billion 290 00:15:51,200 --> 00:15:54,240 Speaker 8: dollar revenue run rate by the end of this year, 291 00:15:54,360 --> 00:15:58,120 Speaker 8: and the same thing for Entropic Andthropics started off the 292 00:15:58,200 --> 00:16:00,400 Speaker 8: year at a billion dollar round right now at a 293 00:16:00,480 --> 00:16:03,080 Speaker 8: five billion dollars round rate. When you five x your 294 00:16:03,120 --> 00:16:07,160 Speaker 8: revenue like that, you have to find ways to, you know, 295 00:16:07,480 --> 00:16:11,800 Speaker 8: keep your employees happy and retain them. And I think 296 00:16:12,080 --> 00:16:15,440 Speaker 8: this is their way of making sure the employees can 297 00:16:15,480 --> 00:16:16,760 Speaker 8: liquidate some of their stuff. 298 00:16:16,960 --> 00:16:20,600 Speaker 3: So is this a perk for all open ai employees? 299 00:16:20,640 --> 00:16:21,560 Speaker 3: I mean, do you have to be there a certain 300 00:16:21,600 --> 00:16:23,520 Speaker 3: amount of time or can anyone take part in this? 301 00:16:24,640 --> 00:16:28,080 Speaker 8: I mean, we don't know that level of detail, but 302 00:16:28,400 --> 00:16:33,040 Speaker 8: suffice to say, I think they've allocated a certain amount 303 00:16:33,840 --> 00:16:37,080 Speaker 8: and the private valuation of this company has gone from 304 00:16:37,280 --> 00:16:40,240 Speaker 8: almost two hundred and fifty to three hundred billion dollars 305 00:16:40,240 --> 00:16:45,400 Speaker 8: to five hundred billion dollars now, and so clearly there 306 00:16:45,480 --> 00:16:48,480 Speaker 8: is a lot of appetite for a company like open Ai, 307 00:16:48,720 --> 00:16:52,240 Speaker 8: which is at the frontier of everything that's going on 308 00:16:52,360 --> 00:16:55,640 Speaker 8: in generative AI, and you know there are buyers of 309 00:16:56,240 --> 00:16:57,160 Speaker 8: that kind of stuff. 310 00:16:57,440 --> 00:17:00,440 Speaker 2: I got to satisfy the banker gene in me. Is 311 00:17:00,480 --> 00:17:03,320 Speaker 2: there an open Ai IPO at some point? 312 00:17:04,680 --> 00:17:08,240 Speaker 8: Probably they will. And my hunch is, you know, when 313 00:17:08,320 --> 00:17:14,879 Speaker 8: you are a category leader in any sort of technology trend, 314 00:17:16,000 --> 00:17:19,040 Speaker 8: you want to be a public company because one, it 315 00:17:19,600 --> 00:17:24,840 Speaker 8: clearly helps you get more you know, long term investors 316 00:17:24,880 --> 00:17:28,320 Speaker 8: for your stock. And also it's it's great pr So 317 00:17:28,440 --> 00:17:32,720 Speaker 8: I can't imagine, you know, uh an open ai stay 318 00:17:33,440 --> 00:17:36,119 Speaker 8: private for very long. But that being said, you know, 319 00:17:37,480 --> 00:17:41,199 Speaker 8: their financials don't look great. I mean, from what we know, 320 00:17:41,480 --> 00:17:45,040 Speaker 8: they're burning a lot of cash right now, so it's 321 00:17:45,040 --> 00:17:47,760 Speaker 8: not a very profitable business model. But the top line 322 00:17:47,800 --> 00:17:52,159 Speaker 8: growth is really what is getting them all the attention 323 00:17:52,359 --> 00:17:54,679 Speaker 8: right now, so they will have to clean up that 324 00:17:55,280 --> 00:17:58,439 Speaker 8: op X side if they plan to go public. So 325 00:17:58,480 --> 00:18:01,720 Speaker 8: I don't think it's imminent in the near term, but 326 00:18:01,920 --> 00:18:04,120 Speaker 8: I would be surprised if it happens in the next 327 00:18:04,200 --> 00:18:04,680 Speaker 8: two years. 328 00:18:04,840 --> 00:18:06,680 Speaker 3: Hey, manap in the last minute we have here left. 329 00:18:06,720 --> 00:18:09,159 Speaker 3: Does this put you know, open ai as the world's 330 00:18:09,200 --> 00:18:13,000 Speaker 3: most valuable startup? I mean, does it push it past SpaceX? 331 00:18:13,119 --> 00:18:14,960 Speaker 3: Is it sustainable. 332 00:18:15,920 --> 00:18:16,400 Speaker 2: By far? 333 00:18:16,640 --> 00:18:19,120 Speaker 8: And look the top line growth. As I said, both 334 00:18:19,200 --> 00:18:22,280 Speaker 8: for open Ai and Tropic, this is not something we 335 00:18:22,359 --> 00:18:25,960 Speaker 8: see very often. So at their revenue base. I mean, 336 00:18:26,000 --> 00:18:30,359 Speaker 8: they are clearly the most coveted and the most talked 337 00:18:30,400 --> 00:18:33,320 Speaker 8: about name, and that's going to be the case for 338 00:18:33,359 --> 00:18:33,760 Speaker 8: a while. 339 00:18:34,359 --> 00:18:37,119 Speaker 2: Man, deep, what skill is the AI skill? 340 00:18:37,280 --> 00:18:37,399 Speaker 6: Like? 341 00:18:37,400 --> 00:18:40,040 Speaker 2: What are these people acquiring in these acquahiers? When are 342 00:18:40,040 --> 00:18:42,600 Speaker 2: pants as big packages? What's the is it coding? Is 343 00:18:42,640 --> 00:18:44,920 Speaker 2: it just engineering? Five oh five? 344 00:18:44,960 --> 00:18:45,399 Speaker 6: What is it? 345 00:18:46,600 --> 00:18:46,760 Speaker 4: So? 346 00:18:47,080 --> 00:18:50,440 Speaker 8: Right now, when you think about how GPT four and 347 00:18:50,520 --> 00:18:54,840 Speaker 8: five became smarter and smarter, it's about, you know, engineers 348 00:18:54,840 --> 00:18:58,280 Speaker 8: who can help these models become smarter and smarter in 349 00:18:58,359 --> 00:19:01,399 Speaker 8: terms of answering more questions. Is doing more types of 350 00:19:01,480 --> 00:19:06,600 Speaker 8: things and that requires a certain knowledge of probability, statistics, 351 00:19:06,680 --> 00:19:11,119 Speaker 8: tokenization that you know, the way large anglig models are built. 352 00:19:11,119 --> 00:19:13,919 Speaker 8: There is a neural net aspect to it, and that 353 00:19:14,080 --> 00:19:18,439 Speaker 8: refinement of LLM is what is making them more intelligent? 354 00:19:18,560 --> 00:19:21,600 Speaker 8: So you need to have that basic level understanding of 355 00:19:21,800 --> 00:19:26,119 Speaker 8: tokenization and what are the tokens that makes these LLM 356 00:19:26,200 --> 00:19:30,000 Speaker 8: smarter and smarter? And I think that's why they deserve 357 00:19:30,640 --> 00:19:32,200 Speaker 8: to get all that at tension. 358 00:19:33,040 --> 00:19:37,720 Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apple, Spotify, 359 00:19:37,920 --> 00:19:41,400 Speaker 1: and anywhere else you get your podcasts. Listen live each 360 00:19:41,440 --> 00:19:45,120 Speaker 1: weekday ten am to noon Eastern on Bloomberg dot com, 361 00:19:45,320 --> 00:19:48,840 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app. 362 00:19:49,280 --> 00:19:52,200 Speaker 1: You can also watch us live every weekday on YouTube 363 00:19:52,600 --> 00:19:55,560 Speaker 1: and always on the Bloomberg terminal