1 00:00:02,440 --> 00:00:11,119 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. This is Bloomberg Intelligence 2 00:00:11,160 --> 00:00:12,879 Speaker 1: with Alex Steel and Paul Sweeney. 3 00:00:13,039 --> 00:00:16,239 Speaker 2: The real app performance has been the US corporate high yield. 4 00:00:16,400 --> 00:00:18,800 Speaker 3: Are the companies lean enough? Have they trimmed all the fats? 5 00:00:18,840 --> 00:00:22,640 Speaker 2: The semiconductor business is a really cyclical business. 6 00:00:22,120 --> 00:00:25,720 Speaker 1: Breaking market headlines and corporate news from across the globe. 7 00:00:25,760 --> 00:00:28,400 Speaker 3: Do investors like the M and A that we've seen? 8 00:00:28,600 --> 00:00:31,680 Speaker 2: These are two big time blue chip companies. 9 00:00:31,840 --> 00:00:35,440 Speaker 3: The window between the peak and cut changing super fast. 10 00:00:35,600 --> 00:00:40,200 Speaker 1: Bloomberg Intelligence with Alex Steel and Paul Sweeney on Bloomberg Radio. 11 00:00:41,680 --> 00:00:44,560 Speaker 2: Today's Bloomberg Intelligence Show, we dig inside the big business 12 00:00:44,560 --> 00:00:46,760 Speaker 2: stories impacting Wall Street and the global marketings. 13 00:00:46,880 --> 00:00:48,800 Speaker 3: Each and every week we provide in depth research and 14 00:00:48,880 --> 00:00:50,640 Speaker 3: data on some of the two thousand companies and one 15 00:00:50,680 --> 00:00:53,360 Speaker 3: hundred and thirty industries our analysts cover worldwide. 16 00:00:53,479 --> 00:00:55,920 Speaker 2: Today, we'll look at why Microsoft and Apple have dropped 17 00:00:55,960 --> 00:00:58,360 Speaker 2: plans to take board seats at OpenAI. 18 00:00:58,480 --> 00:01:01,640 Speaker 3: Plus, we'll discuss research from bloom Intelligence on ten companies 19 00:01:01,640 --> 00:01:03,000 Speaker 3: to watch during the third. 20 00:01:02,800 --> 00:01:06,479 Speaker 2: Quarter, But first we dive into the pharmaceutical space. This week, 21 00:01:06,520 --> 00:01:10,320 Speaker 2: Eli Lilly reread to buy US gut drug maker Morphic 22 00:01:10,680 --> 00:01:12,120 Speaker 2: for about three point two billion dollars. 23 00:01:12,360 --> 00:01:14,920 Speaker 3: Lily will pay fifty seven dollars a share in cash, 24 00:01:14,920 --> 00:01:17,920 Speaker 3: and this comes as eli Lilly's CEO, Dave Riggs, has 25 00:01:17,959 --> 00:01:21,039 Speaker 3: promised more early stage deals to acquire new technologies. 26 00:01:21,240 --> 00:01:22,800 Speaker 2: For more on all of this, we were joined by 27 00:01:22,800 --> 00:01:26,360 Speaker 2: Sam Fazzelli, Bloomberg Intelligence, Director of Research for Global Industries 28 00:01:26,400 --> 00:01:27,640 Speaker 2: and Senior Pharmaceuticals. 29 00:01:27,680 --> 00:01:29,959 Speaker 3: We first asked Sam about his thoughts on this deal. 30 00:01:30,400 --> 00:01:34,679 Speaker 4: This deal is about adding to their immunology franchise. Of course, 31 00:01:34,720 --> 00:01:39,880 Speaker 4: everybody knows Lily for the endless the headlines that are 32 00:01:40,000 --> 00:01:43,760 Speaker 4: related to GLP ones and obesity and cancer. Today we 33 00:01:43,840 --> 00:01:47,200 Speaker 4: have apparently ten cancers that are not cured but risk 34 00:01:47,319 --> 00:01:50,480 Speaker 4: is reduced with those types of drugs. But the reality 35 00:01:50,520 --> 00:01:52,200 Speaker 4: is there's a lot more to this company before the 36 00:01:52,280 --> 00:01:57,600 Speaker 4: GLP one business ballooned with regards to obesity. And one 37 00:01:57,600 --> 00:01:59,960 Speaker 4: of the areas they're in is immunology or otherwise known 38 00:02:00,040 --> 00:02:04,400 Speaker 4: as immunology and inflammation or inflammation and immunology I and 39 00:02:04,480 --> 00:02:07,000 Speaker 4: I and I and I is also a very attractive 40 00:02:07,000 --> 00:02:10,200 Speaker 4: area because these are areas where we all have issues 41 00:02:10,400 --> 00:02:15,399 Speaker 4: with arthritis, psoriasis, Crow's disease, if elamentary bowel disease. All 42 00:02:15,480 --> 00:02:19,280 Speaker 4: these things are stuff that we have been suffering from 43 00:02:19,360 --> 00:02:23,040 Speaker 4: for years. Obsitly probably increases the risk too. So there've 44 00:02:23,080 --> 00:02:25,840 Speaker 4: been a very active company in that space with three 45 00:02:25,919 --> 00:02:28,480 Speaker 4: drugs four drugs on the market already and they've been 46 00:02:28,480 --> 00:02:29,720 Speaker 4: doing deals adding to it. 47 00:02:29,919 --> 00:02:32,359 Speaker 2: SAM three point two billion dollars is not a big, 48 00:02:32,400 --> 00:02:36,239 Speaker 2: big deal for Lily, But is this typical of what 49 00:02:36,280 --> 00:02:38,280 Speaker 2: we see at a big pharmer companies in terms of 50 00:02:38,360 --> 00:02:41,760 Speaker 2: if they see a therapeutic or just a piece of 51 00:02:41,800 --> 00:02:45,760 Speaker 2: science as interesting to them, it's better to buy than develop. 52 00:02:45,800 --> 00:02:49,359 Speaker 4: Internally, I would say they're around thirty to forty percent 53 00:02:49,400 --> 00:02:55,800 Speaker 4: of pharmaceutical companies pipelines comes from this type of interaction, either. 54 00:02:55,600 --> 00:02:57,239 Speaker 5: An m and a deal. I e. 55 00:02:57,520 --> 00:03:01,000 Speaker 4: Bought the whole thing lock stock and Barrel I license 56 00:03:01,080 --> 00:03:02,679 Speaker 4: a specific product in this case. 57 00:03:02,720 --> 00:03:04,920 Speaker 5: So I'm looking at Lily. We have a database. 58 00:03:05,000 --> 00:03:06,720 Speaker 4: Of of course, we have the MAA function in the 59 00:03:06,760 --> 00:03:11,079 Speaker 4: Bloomberg terminal, but we've taken that and dissected a little 60 00:03:11,120 --> 00:03:16,120 Speaker 4: bit more and added on the BI dashboard and detail 61 00:03:16,160 --> 00:03:19,040 Speaker 4: about the types of drugs that are in those deals, 62 00:03:19,400 --> 00:03:20,520 Speaker 4: and MNA is one of that. 63 00:03:20,600 --> 00:03:22,640 Speaker 5: So I'm looking at twelve deals that Lily has done 64 00:03:22,680 --> 00:03:22,919 Speaker 5: in the. 65 00:03:22,880 --> 00:03:27,800 Speaker 4: Past five years, and I'd say that only like three 66 00:03:27,840 --> 00:03:31,079 Speaker 4: of them are in the cardiovascular metabolic space, I either 67 00:03:31,120 --> 00:03:35,360 Speaker 4: of diabetes obesity. The rest are oncology CNS, and of 68 00:03:35,400 --> 00:03:38,960 Speaker 4: course two are inflammation and immunology, and this is one 69 00:03:38,960 --> 00:03:39,280 Speaker 4: of them. 70 00:03:39,480 --> 00:03:42,160 Speaker 5: So now it becomes three, right because that's not quite 71 00:03:42,200 --> 00:03:44,600 Speaker 5: updated yet. And they're all in that sort of range 72 00:03:44,680 --> 00:03:48,600 Speaker 5: eight billion for lockso one point one eight hundred eighty million, 73 00:03:48,840 --> 00:03:51,240 Speaker 5: two point four billion, So we've got a good bunch 74 00:03:51,280 --> 00:03:53,920 Speaker 5: of deals and they're all in that level which the 75 00:03:53,920 --> 00:03:57,160 Speaker 5: farmer company is called Bolton Acquisitions, and that's their sweet 76 00:03:57,160 --> 00:03:58,000 Speaker 5: spot of M and A. 77 00:03:58,160 --> 00:04:01,360 Speaker 2: See how everybody thinks that the smart people in bi 78 00:04:01,880 --> 00:04:04,880 Speaker 2: pharma healthcare researcher guys people like Sam faz Elliot, that's 79 00:04:04,920 --> 00:04:07,640 Speaker 2: not really the case. It's this young lady named Grace 80 00:04:07,720 --> 00:04:12,360 Speaker 2: and she's crazy and she maintains a world class model 81 00:04:12,400 --> 00:04:15,440 Speaker 2: that tracks the millions of drugs that are in various 82 00:04:15,440 --> 00:04:19,600 Speaker 2: stages of you know, reviews around the world, and clients 83 00:04:20,040 --> 00:04:23,080 Speaker 2: put huge value on that work that she does, and 84 00:04:23,080 --> 00:04:25,160 Speaker 2: that allows Sam and some of the other animals to 85 00:04:25,160 --> 00:04:26,760 Speaker 2: go out there and talk about these drugs. So Grace, 86 00:04:27,520 --> 00:04:28,440 Speaker 2: great job. 87 00:04:28,560 --> 00:04:30,160 Speaker 3: As always, we love the Paul shout out. 88 00:04:30,200 --> 00:04:34,000 Speaker 4: That was awesome, so true, and he needs this particular 89 00:04:34,000 --> 00:04:36,559 Speaker 4: shout out goes to another great lady who's called Mila 90 00:04:36,640 --> 00:04:39,280 Speaker 4: Mila ban who's also part of our team. 91 00:04:39,600 --> 00:04:42,039 Speaker 5: But nobody matches up to Grace. Of course, Grace has 92 00:04:42,120 --> 00:04:43,880 Speaker 5: been in the catlist. 93 00:04:43,400 --> 00:04:46,400 Speaker 4: Calendar that should I don't match up to her, nobody matches. 94 00:04:46,200 --> 00:04:46,560 Speaker 5: On to her. 95 00:04:46,680 --> 00:04:49,000 Speaker 3: Okay, So based on that, what are some of the 96 00:04:49,040 --> 00:04:51,680 Speaker 3: cool things that are out there, like cool drugs that 97 00:04:51,880 --> 00:04:53,440 Speaker 3: we should be talking about. We never get to talk 98 00:04:53,480 --> 00:04:55,760 Speaker 3: to you when there's no crisis, really, so what are 99 00:04:55,760 --> 00:04:56,760 Speaker 3: some cool things out there? 100 00:04:57,680 --> 00:05:02,360 Speaker 4: Yeah, So obviously the OBC space, there's there's breakneck evolution 101 00:05:02,920 --> 00:05:05,920 Speaker 4: of different modalities being combined, trying to make it much 102 00:05:05,960 --> 00:05:09,560 Speaker 4: more focused on fat, preserving some muscle, making it work 103 00:05:09,600 --> 00:05:11,920 Speaker 4: better for the liver part of the disease. And that's 104 00:05:11,960 --> 00:05:14,120 Speaker 4: all going to come to fruition over the next two 105 00:05:14,200 --> 00:05:16,839 Speaker 4: or three years. Oncology, as have been saying all along, 106 00:05:17,200 --> 00:05:21,200 Speaker 4: is seeing amazing developments. You know, we're developing these disease hubs, 107 00:05:21,240 --> 00:05:24,320 Speaker 4: as you might know, and just for lung cancer, we're 108 00:05:24,320 --> 00:05:29,680 Speaker 4: developing almost thirteen different subgroupings of lung cancer, and it 109 00:05:29,800 --> 00:05:32,159 Speaker 4: just shows you where treatment. 110 00:05:31,760 --> 00:05:33,440 Speaker 5: Of these diseases have got to. 111 00:05:33,640 --> 00:05:36,760 Speaker 4: And the same applies in inflammation and immunology, and in 112 00:05:36,800 --> 00:05:40,440 Speaker 4: that space we're dealing with technology that is really cool. 113 00:05:40,480 --> 00:05:43,760 Speaker 4: This particular acquisition and the one that they recently did 114 00:05:44,240 --> 00:05:47,240 Speaker 4: almost exactly a year ago, called dice therapeutics are all 115 00:05:47,279 --> 00:05:51,080 Speaker 4: about dealing with proteins that are very intractable to inhibition 116 00:05:51,880 --> 00:05:55,680 Speaker 4: and normal drug discovery, and these two companies have developed 117 00:05:55,839 --> 00:05:59,440 Speaker 4: oral drugs, small molecules that interact with these targets. 118 00:06:00,000 --> 00:06:02,720 Speaker 5: The beauty of this, of course, is you remember all 119 00:06:02,760 --> 00:06:03,440 Speaker 5: that worry that what. 120 00:06:03,480 --> 00:06:06,960 Speaker 4: People were having about what happens with the IRA inflection 121 00:06:07,080 --> 00:06:11,039 Speaker 4: reduction actions and its impact on small molecule development, because 122 00:06:11,040 --> 00:06:15,160 Speaker 4: it specifically puts them out saying after nine years, irrespective 123 00:06:15,160 --> 00:06:16,760 Speaker 4: of your patterns, we're going to come back in and 124 00:06:16,760 --> 00:06:20,200 Speaker 4: negotiate prices. Well, here's Lily who's done two deals that 125 00:06:20,320 --> 00:06:24,919 Speaker 4: are specifically small molecule deals. When the biology is interesting, 126 00:06:25,000 --> 00:06:28,360 Speaker 4: when the drugs are interesting, I think the deals happen. Now, 127 00:06:28,400 --> 00:06:30,520 Speaker 4: whether these will get to market or not, who knows. 128 00:06:30,560 --> 00:06:33,039 Speaker 4: I mean, pharma isn't infallible when it comes. 129 00:06:32,880 --> 00:06:33,680 Speaker 5: To these deals. 130 00:06:34,000 --> 00:06:38,720 Speaker 4: But at this shows that when they they see something interesting, 131 00:06:38,760 --> 00:06:41,200 Speaker 4: they go for it, irrespective of small or big. 132 00:06:41,000 --> 00:06:44,360 Speaker 2: Molecule sam People are, for better or worse, are living 133 00:06:44,640 --> 00:06:48,560 Speaker 2: longer and longer lives. Which makes every family seems like 134 00:06:48,560 --> 00:06:51,640 Speaker 2: it's dealing with some type of dementia, Alzheimer's and things 135 00:06:51,680 --> 00:06:54,640 Speaker 2: like that. How does the farmer industry, healthcare austry, how 136 00:06:54,640 --> 00:06:57,159 Speaker 2: do they think about that? How are they kind of 137 00:06:57,160 --> 00:06:57,880 Speaker 2: getting ready for that? 138 00:06:59,440 --> 00:07:02,680 Speaker 5: Yeah, so you know the beginnings. Can I just give 139 00:07:02,720 --> 00:07:03,320 Speaker 5: you an example. 140 00:07:03,560 --> 00:07:07,040 Speaker 4: An analogue for Alzheimer's disease is obesity. 141 00:07:07,560 --> 00:07:09,560 Speaker 5: We've been at this obesity. 142 00:07:09,040 --> 00:07:12,720 Speaker 4: Game for a year, ten years, fifteen years, twenty years. 143 00:07:12,920 --> 00:07:15,840 Speaker 4: I remember one of the old drugs from Rush Pharmaceuticals 144 00:07:16,000 --> 00:07:20,360 Speaker 4: that's still around, called ally that reduced the amount of 145 00:07:20,400 --> 00:07:23,600 Speaker 4: fat you absorb as you eat. Of course, what does 146 00:07:23,640 --> 00:07:27,640 Speaker 4: that create? Fat left in your stomach, lubrication. I'm going 147 00:07:27,680 --> 00:07:30,320 Speaker 4: to leave the rest of it to your imagination, right, So, 148 00:07:30,360 --> 00:07:32,120 Speaker 4: that was the idea that was going to be helping 149 00:07:32,120 --> 00:07:34,680 Speaker 4: you lose weight maybe three percent, four percent, five percent. 150 00:07:35,360 --> 00:07:38,040 Speaker 4: And then it took a lot of time before somebody 151 00:07:38,080 --> 00:07:40,240 Speaker 4: started discovering these things saying, oh, gosh, we can get 152 00:07:40,280 --> 00:07:42,440 Speaker 4: to fifteen twenty percent. If you're a two hundred and 153 00:07:42,440 --> 00:07:45,000 Speaker 4: fifty pound person, we can help you drop seventy pounds. 154 00:07:45,280 --> 00:07:46,400 Speaker 5: That happened in obesity. 155 00:07:46,760 --> 00:07:51,560 Speaker 4: I'm hopeful that the same happens in dementia and neurodegeneratic diseases. 156 00:07:51,960 --> 00:07:53,440 Speaker 5: It's very much tougher. 157 00:07:54,080 --> 00:07:57,080 Speaker 4: I mean, all biology is tough, but CNS is tougher 158 00:07:57,120 --> 00:07:59,720 Speaker 4: because it's a black box. It's a disease that evolves 159 00:07:59,760 --> 00:08:03,040 Speaker 4: over twenty years, thirty years, and by the time you 160 00:08:03,480 --> 00:08:06,760 Speaker 4: your disease manifests, you've already had a lot of organic 161 00:08:06,840 --> 00:08:09,400 Speaker 4: change to your brain. But there is the first products 162 00:08:09,400 --> 00:08:12,040 Speaker 4: that are approved. With the first products approved, you do 163 00:08:12,200 --> 00:08:15,200 Speaker 4: get a bit more incentive to develop the next one. 164 00:08:15,400 --> 00:08:18,840 Speaker 4: Go better, go another mile further. And that's where I'm hoping. 165 00:08:19,040 --> 00:08:22,040 Speaker 4: At the very least in Alzheimer's disease and Parkinson's, we're 166 00:08:22,080 --> 00:08:22,840 Speaker 4: going to be going there. 167 00:08:22,880 --> 00:08:24,200 Speaker 5: Other diseases are a bit tougher. 168 00:08:24,240 --> 00:08:26,320 Speaker 3: Still, do you think that we'll ever have a preventative 169 00:08:26,400 --> 00:08:28,600 Speaker 3: drug for Alzheimer's or just a treatment to. 170 00:08:28,640 --> 00:08:32,000 Speaker 4: Delay well, I think it's very tough to prevent because 171 00:08:32,240 --> 00:08:33,880 Speaker 4: how do you know who's going to get it? That 172 00:08:33,920 --> 00:08:37,200 Speaker 4: means you and I especially I, because you guys are 173 00:08:37,320 --> 00:08:41,839 Speaker 4: much longer than me. Paul is he's just coming out 174 00:08:41,840 --> 00:08:45,440 Speaker 4: of school, right, So at what point do you start 175 00:08:45,440 --> 00:08:46,360 Speaker 4: taking these drugs? 176 00:08:46,520 --> 00:08:49,760 Speaker 5: Right? How do I do that? So that becomes difficult? 177 00:08:49,760 --> 00:08:50,439 Speaker 5: Who pays for it? 178 00:08:50,720 --> 00:08:53,000 Speaker 4: And if they're preventative, how long do I have to 179 00:08:53,040 --> 00:08:54,040 Speaker 4: take them before I know? 180 00:08:54,160 --> 00:08:55,840 Speaker 5: I mean, how do you even do a trial there? 181 00:08:56,480 --> 00:08:58,959 Speaker 4: So don't forget though in Alzheimer's disease, you can go 182 00:08:59,080 --> 00:09:02,280 Speaker 4: into the early mild dementia and try and slow down 183 00:09:02,360 --> 00:09:04,760 Speaker 4: the disease. But step at the time, at a step 184 00:09:04,760 --> 00:09:07,360 Speaker 4: at the time, and I think we'll have something. Might 185 00:09:07,360 --> 00:09:10,480 Speaker 4: take a decade or two, but hopefully we'll have them. 186 00:09:10,800 --> 00:09:12,720 Speaker 2: Is this something if we see announcements on this front, 187 00:09:12,720 --> 00:09:15,560 Speaker 2: will likely be, you know, the big farmer companies that 188 00:09:15,600 --> 00:09:19,120 Speaker 2: you cover, making and acquisitions of some of these smaller 189 00:09:19,120 --> 00:09:21,520 Speaker 2: companies that are just focused on this one particular thing. 190 00:09:22,960 --> 00:09:25,520 Speaker 4: Probably, and don't forget that also, the large farmer companies. 191 00:09:25,600 --> 00:09:27,440 Speaker 4: I mean, then the two drugs that we have on 192 00:09:27,480 --> 00:09:31,280 Speaker 4: the market today, let can be and I forget what 193 00:09:31,320 --> 00:09:33,760 Speaker 4: the nanamaps call. It has just been approved, so I 194 00:09:33,800 --> 00:09:38,120 Speaker 4: can't remember his A branded name I'm sorry, Illily. They 195 00:09:38,160 --> 00:09:43,440 Speaker 4: both came from within either the farmer company or the 196 00:09:44,040 --> 00:09:47,240 Speaker 4: a Japanese partner. However, in the case of the can 197 00:09:47,280 --> 00:09:51,920 Speaker 4: be that came from a Scandinavian biotech So both of 198 00:09:51,960 --> 00:09:56,040 Speaker 4: these are true. The question is who's got the firepower, 199 00:09:56,200 --> 00:09:59,400 Speaker 4: the money to spend the billions required to develop these 200 00:10:00,080 --> 00:10:02,040 Speaker 4: That's often ends up being a farmer company. 201 00:10:02,080 --> 00:10:03,439 Speaker 5: It's the large farmer companies. 202 00:10:03,720 --> 00:10:06,440 Speaker 3: Do you feel like, no matter who gets to be 203 00:10:06,559 --> 00:10:09,840 Speaker 3: president in here in November, here in the US, are 204 00:10:09,840 --> 00:10:12,760 Speaker 3: we going to see massive drug pushback? Like I realized 205 00:10:12,760 --> 00:10:15,679 Speaker 3: it's probably a campaign tactic. But President Biden coming out 206 00:10:16,080 --> 00:10:18,880 Speaker 3: last week and talking about how all the things were 207 00:10:18,920 --> 00:10:21,600 Speaker 3: so expensive and really blaming like Novo Nordous. He wrote 208 00:10:21,600 --> 00:10:24,360 Speaker 3: an app that with Bernie Sanders in USA today, what 209 00:10:24,440 --> 00:10:24,640 Speaker 3: do you. 210 00:10:24,640 --> 00:10:29,480 Speaker 4: Think I think this is a hot potato. I don't 211 00:10:29,520 --> 00:10:32,720 Speaker 4: think they are aiming their guns at the right group 212 00:10:32,760 --> 00:10:36,400 Speaker 4: of companies. I think you could always argue that drug 213 00:10:36,440 --> 00:10:39,080 Speaker 4: pricing because it's the easiest thing. It's a drug that 214 00:10:39,120 --> 00:10:41,920 Speaker 4: people have to buy, and it says Lily on it right, is. 215 00:10:42,160 --> 00:10:45,240 Speaker 5: Difficult for some people. A lot of people can't afford them. 216 00:10:45,600 --> 00:10:48,800 Speaker 4: But there's a lot of middlemen that need to be 217 00:10:48,800 --> 00:10:52,080 Speaker 4: looked at to where the increasing cost comes from. And 218 00:10:52,160 --> 00:10:55,640 Speaker 4: you know what, the best way to entice people to 219 00:10:55,679 --> 00:10:58,200 Speaker 4: develop obcity drugs, to bring down the price, to bring 220 00:10:58,280 --> 00:11:02,240 Speaker 4: up competition is to allow the market to do his job. 221 00:11:02,840 --> 00:11:05,400 Speaker 4: The market will do it already. These things are not 222 00:11:05,480 --> 00:11:08,079 Speaker 4: costing tenth one thousand dollars a month. 223 00:11:08,160 --> 00:11:10,319 Speaker 5: We're more. You're closer to five hundred net. 224 00:11:10,559 --> 00:11:12,719 Speaker 4: Let the market to the job, bring more drugs on 225 00:11:13,000 --> 00:11:15,199 Speaker 4: the volume goes up, you can drop the price. 226 00:11:15,400 --> 00:11:18,400 Speaker 2: Our thanks to Sam Fazzelli, Bloomberg Intelligence, director of Research 227 00:11:18,400 --> 00:11:20,840 Speaker 2: for Global Industries and senior pharmaceuticals analysts. 228 00:11:20,960 --> 00:11:23,080 Speaker 3: Coming up, we're going to break down Delta airline earnings 229 00:11:23,120 --> 00:11:24,640 Speaker 3: and what they mean for summer travel. 230 00:11:24,920 --> 00:11:28,120 Speaker 2: We're listening to Bloomberg Intelligence on Bloomberg Radio, providing in 231 00:11:28,120 --> 00:11:30,400 Speaker 2: their research and data on two thousand companies and one 232 00:11:30,440 --> 00:11:33,520 Speaker 2: hundred and thirty industries. You can access Bloomberg Intelligence via 233 00:11:33,600 --> 00:11:36,280 Speaker 2: b I go on the terminal on Paul Sweeney. 234 00:11:36,040 --> 00:11:38,160 Speaker 3: And I am Alex Steel and this is Bloomberg. 235 00:11:48,120 --> 00:11:52,000 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 236 00:11:52,080 --> 00:11:54,800 Speaker 1: weekdays at ten am Eastern on Apple Car Playing and 237 00:11:54,920 --> 00:11:57,800 Speaker 1: broud Otto with the Bloomberg Business app. Listen on demand 238 00:11:57,840 --> 00:12:01,559 Speaker 1: wherever you get your podcasts, or just live on YouTube. 239 00:12:03,160 --> 00:12:05,199 Speaker 3: We moved now to big tech. This week we heard 240 00:12:05,240 --> 00:12:08,040 Speaker 3: that Microsoft and Apple drop plans to take board roles 241 00:12:08,040 --> 00:12:08,680 Speaker 3: at open Ai. 242 00:12:09,080 --> 00:12:11,640 Speaker 2: It's a surprise decision that comes as regulators in the 243 00:12:11,720 --> 00:12:15,160 Speaker 2: US and Europe have expressed concerns about microsoft sway over 244 00:12:15,200 --> 00:12:15,680 Speaker 2: open Ai. 245 00:12:16,080 --> 00:12:18,040 Speaker 3: For more, we were joined by man Deep saying Bloomberg 246 00:12:18,040 --> 00:12:20,679 Speaker 3: Intelligence and your tech industry analysts. We first asked man 247 00:12:20,679 --> 00:12:22,760 Speaker 3: Deep for some more context on the story. 248 00:12:23,120 --> 00:12:25,960 Speaker 6: I mean, if you roll back to last year when 249 00:12:26,000 --> 00:12:29,280 Speaker 6: we had the open Ai drama, you know, the board 250 00:12:29,320 --> 00:12:34,679 Speaker 6: firing Sam Altman and then open Ai adding four new members, 251 00:12:35,320 --> 00:12:40,720 Speaker 6: and I think everyone so far has been just sort 252 00:12:40,760 --> 00:12:44,640 Speaker 6: of interested in how open ai has evolved since then 253 00:12:44,840 --> 00:12:46,880 Speaker 6: in the sense that they have even though they have 254 00:12:47,040 --> 00:12:52,160 Speaker 6: added independent board members. Microsoft, you know, and now Apple 255 00:12:52,559 --> 00:12:55,559 Speaker 6: probably would have joined the board. It doesn't make sense, 256 00:12:55,679 --> 00:12:59,720 Speaker 6: like when you have vested interests. In the case of 257 00:12:59,760 --> 00:13:02,680 Speaker 6: Micro they have a forty nine percent stake in open 258 00:13:02,720 --> 00:13:07,520 Speaker 6: ai and they're the primary cloud provider for open Ai. 259 00:13:07,880 --> 00:13:10,520 Speaker 6: How can you do a good job of being an 260 00:13:10,520 --> 00:13:13,920 Speaker 6: independent board member and That's where you know the regulatory 261 00:13:13,960 --> 00:13:18,079 Speaker 6: scrutiny comes into play, because the regulators obviously are concerned 262 00:13:18,120 --> 00:13:21,640 Speaker 6: about how Microsoft bought inflection Ai, even though it wasn't 263 00:13:21,679 --> 00:13:25,160 Speaker 6: an acquisition, they got all the employees of inflection Ai. 264 00:13:25,440 --> 00:13:28,960 Speaker 3: Breakdown for me again, what the relationship is now with 265 00:13:29,040 --> 00:13:32,160 Speaker 3: open ai and Apple versus open Ai and Microsoft. 266 00:13:32,480 --> 00:13:35,920 Speaker 6: So Microsoft has a forty nine percent stake in open Ai. 267 00:13:36,040 --> 00:13:38,560 Speaker 6: They made a ten billion dollar investment, and so you 268 00:13:38,600 --> 00:13:40,840 Speaker 6: could argue, if you're an investor in a company, you 269 00:13:40,840 --> 00:13:43,520 Speaker 6: should get a board set as a Sequoia and some 270 00:13:43,600 --> 00:13:46,840 Speaker 6: other private investors that open Ai has. Apple, on the 271 00:13:46,880 --> 00:13:50,840 Speaker 6: other hand, just partnered with open ai, which is going 272 00:13:50,920 --> 00:13:54,640 Speaker 6: to be one of the providers of Genai model on 273 00:13:54,760 --> 00:13:59,520 Speaker 6: their iOS and other devices, and so it's more of 274 00:13:59,559 --> 00:14:02,960 Speaker 6: a custustomer supplier relationship if you want to call it 275 00:14:02,960 --> 00:14:05,840 Speaker 6: that way. That Apple is using open ee as a supplier, 276 00:14:06,240 --> 00:14:08,320 Speaker 6: why were they getting a board seat. Well, you could 277 00:14:08,400 --> 00:14:11,360 Speaker 6: argue they could be an independent board member like Fijisimo 278 00:14:11,520 --> 00:14:14,800 Speaker 6: is one of the board members for open Ei. She's 279 00:14:14,840 --> 00:14:19,560 Speaker 6: the CEO of Instacart. Now, I think that's where the 280 00:14:19,720 --> 00:14:24,120 Speaker 6: fact that these technologies are so intertwined in terms of 281 00:14:24,400 --> 00:14:28,760 Speaker 6: AI being deployed on Apple devices, you could argue the 282 00:14:28,840 --> 00:14:32,520 Speaker 6: independence of the board comes into question, and given how 283 00:14:32,600 --> 00:14:36,680 Speaker 6: important AI ethics and guardrails and all the things that 284 00:14:36,800 --> 00:14:41,040 Speaker 6: regulators care about that everyone cares about, frankly, I think 285 00:14:41,120 --> 00:14:45,240 Speaker 6: the independence of the board was questionable and these companies 286 00:14:45,320 --> 00:14:49,280 Speaker 6: decided to proactively not join the board, which I think 287 00:14:49,880 --> 00:14:51,560 Speaker 6: is good for optics. 288 00:14:52,120 --> 00:14:57,440 Speaker 2: So Microsoft is under scrutiny in Europe and by US 289 00:14:57,680 --> 00:15:03,520 Speaker 2: regulators into I guess, their alleged dominance of AI. What's 290 00:15:03,560 --> 00:15:06,520 Speaker 2: the view on the street about that risk to Microsoft? 291 00:15:06,520 --> 00:15:08,480 Speaker 2: And I don't know because at some point maybe Apple 292 00:15:08,480 --> 00:15:09,680 Speaker 2: one on it, but certainly Microsoft. 293 00:15:10,040 --> 00:15:13,160 Speaker 6: I mean, the best way to look at it is 294 00:15:13,720 --> 00:15:17,800 Speaker 6: these companies require a lot of compute for training their models, 295 00:15:17,840 --> 00:15:21,640 Speaker 6: whether it's open ai and Tropic, any of the independent 296 00:15:21,760 --> 00:15:25,240 Speaker 6: GENI model providers, they need a lot of compute. Now, 297 00:15:25,320 --> 00:15:29,240 Speaker 6: in the case of Microsoft, the arrangement is really you know, 298 00:15:29,680 --> 00:15:33,200 Speaker 6: full of their interest because open ai ends up using 299 00:15:33,280 --> 00:15:37,040 Speaker 6: Microsoft Compute for training their models. 300 00:15:37,080 --> 00:15:39,160 Speaker 2: What does that mean? What is compute? 301 00:15:39,200 --> 00:15:43,400 Speaker 6: So think of all the Nvidia GPUs that open ai needs, 302 00:15:43,800 --> 00:15:48,160 Speaker 6: but it's deployed on Microsoft Cloud. So if I need 303 00:15:48,400 --> 00:15:52,160 Speaker 6: compute to train the models. I'm not setting up my 304 00:15:52,400 --> 00:15:55,480 Speaker 6: data center and tropic open ai. They're not setting up 305 00:15:55,560 --> 00:15:59,640 Speaker 6: data centers. They're using Microsoft data centers to get access 306 00:15:59,640 --> 00:16:02,920 Speaker 6: to that compute. And that's where they could have gone 307 00:16:02,920 --> 00:16:06,280 Speaker 6: to Amazon or Google to get that compute. The reason 308 00:16:06,320 --> 00:16:09,120 Speaker 6: they're going to Microsoft is because of the you know, 309 00:16:09,200 --> 00:16:12,000 Speaker 6: the stake they have and the board seed And so 310 00:16:12,400 --> 00:16:16,000 Speaker 6: if you are open ai and Microsoft is sitting in 311 00:16:16,040 --> 00:16:18,440 Speaker 6: that board, are you really going to pick any of 312 00:16:18,480 --> 00:16:22,360 Speaker 6: the alternative cloud providers for training your models? Probably not. 313 00:16:23,360 --> 00:16:27,480 Speaker 3: Do you feel like open ai will ever go public 314 00:16:27,920 --> 00:16:31,479 Speaker 3: or be bought by Microsoft? Like, how does that situation 315 00:16:31,680 --> 00:16:32,200 Speaker 3: play out? 316 00:16:32,520 --> 00:16:36,840 Speaker 6: I mean, everyone knows their antitrust concerns around bit tech 317 00:16:36,880 --> 00:16:39,880 Speaker 6: buying any of these companies, So the acquisition is definitely 318 00:16:39,920 --> 00:16:42,920 Speaker 6: out of the window. And that's why the way Microsoft 319 00:16:43,160 --> 00:16:46,080 Speaker 6: got all the employees of Inflection Ai, it was a 320 00:16:46,120 --> 00:16:49,680 Speaker 6: pseudo acquisition. You get all of the employees, you pay 321 00:16:49,720 --> 00:16:53,040 Speaker 6: six hundred million dollars, and you're not calling it an acquisition. 322 00:16:53,440 --> 00:16:56,200 Speaker 6: So in the case of OpenAI, obviously that's not going 323 00:16:56,280 --> 00:16:58,680 Speaker 6: to happen, but they Microsoft does have a forty nine 324 00:16:58,720 --> 00:17:02,840 Speaker 6: percent stake. Google bought DeepMind for six hundred million. Now 325 00:17:02,840 --> 00:17:05,199 Speaker 6: they bought it, you know, a few years back. But 326 00:17:05,320 --> 00:17:08,840 Speaker 6: it just goes to show how, you know, these companies 327 00:17:08,880 --> 00:17:12,320 Speaker 6: positioned themselves for the future and they end up buying 328 00:17:12,600 --> 00:17:14,960 Speaker 6: a lot of the startups. So I don't see an 329 00:17:15,000 --> 00:17:18,160 Speaker 6: acquisition on the cards. But my open ai is unique 330 00:17:18,160 --> 00:17:21,479 Speaker 6: in the sense it's a nonprofit and then they are 331 00:17:21,680 --> 00:17:24,280 Speaker 6: looking to build a business out of it. So their 332 00:17:24,320 --> 00:17:28,440 Speaker 6: structure was sort of very weird to begin with. And 333 00:17:28,880 --> 00:17:31,119 Speaker 6: now they had that board trouble where it was a 334 00:17:31,160 --> 00:17:34,600 Speaker 6: three percent board that fired their CEO. Now they're expanding 335 00:17:34,640 --> 00:17:37,680 Speaker 6: with independent board members. So I don't think they've got 336 00:17:37,720 --> 00:17:41,119 Speaker 6: it right still, but at least, you know, not having 337 00:17:41,160 --> 00:17:44,080 Speaker 6: Microsoft and Apple on the board is good in terms 338 00:17:44,080 --> 00:17:46,560 Speaker 6: of optics. And that's what I can conclude here. 339 00:17:46,640 --> 00:17:50,240 Speaker 2: Our thanks to man Deep Sing, Bloomberg Intelligence Senior Tech industry. 340 00:17:49,920 --> 00:17:52,640 Speaker 3: Analyst, we moved next to the airline industry. This week. 341 00:17:52,720 --> 00:17:55,520 Speaker 3: Delta Airlines reported worse than expected quarterly results, and the 342 00:17:55,520 --> 00:17:58,359 Speaker 3: airline also said that domestic carriers are struggling to fill 343 00:17:58,400 --> 00:18:00,400 Speaker 3: planes during the summer travel See in. 344 00:18:00,520 --> 00:18:02,479 Speaker 2: For more on this. We were joined by George Ferguson, 345 00:18:02,480 --> 00:18:05,719 Speaker 2: Bloomberg Intelligence Senior aerospace, defense, and airlines generalists. 346 00:18:05,760 --> 00:18:08,040 Speaker 3: We first asked George for his take on Delta's recent 347 00:18:08,119 --> 00:18:09,240 Speaker 3: earnings report. 348 00:18:09,560 --> 00:18:11,800 Speaker 7: What we do know is that the weakest part of 349 00:18:11,800 --> 00:18:14,040 Speaker 7: the business right now appears to be sort of basic 350 00:18:14,119 --> 00:18:17,680 Speaker 7: economy or those economy classes, and that's weighing it down. 351 00:18:17,760 --> 00:18:22,360 Speaker 7: So actually, I expect that Delta's earnings report will be 352 00:18:22,359 --> 00:18:26,080 Speaker 7: better than most this quarter. So I think it'll get 353 00:18:26,119 --> 00:18:28,040 Speaker 7: worse and worse as you get into the low costs 354 00:18:28,080 --> 00:18:30,800 Speaker 7: and ultra low cost carriers, because again that's I think 355 00:18:30,800 --> 00:18:32,760 Speaker 7: where the majority of the pain is in fairs. 356 00:18:33,080 --> 00:18:35,480 Speaker 3: Yeah, because you know, going through the quarter, like corporate 357 00:18:35,560 --> 00:18:38,840 Speaker 3: travel rose thirteen percent for Delta in the second quarter. 358 00:18:39,560 --> 00:18:43,280 Speaker 3: Revenue from international passengers also increased, and premium products just 359 00:18:43,440 --> 00:18:45,920 Speaker 3: ten percent. So basically, business people are traveling, we're going 360 00:18:45,960 --> 00:18:48,879 Speaker 3: overseas and we're buying business class or first class, So 361 00:18:49,160 --> 00:18:53,400 Speaker 3: like is no one going to Idaho and economy people 362 00:18:53,440 --> 00:18:53,920 Speaker 3: are going. 363 00:18:53,960 --> 00:18:56,720 Speaker 7: They're just they're going for lower fares right there. Load 364 00:18:56,760 --> 00:18:59,320 Speaker 7: factors were great on Delta, right they were like a 365 00:18:59,400 --> 00:19:03,520 Speaker 7: eighty seven percent, So they're filling airplanes as well as 366 00:19:03,560 --> 00:19:06,600 Speaker 7: they filled the year prior. I think, you know, Delta 367 00:19:06,640 --> 00:19:09,640 Speaker 7: will get a bit of a tailwind as business comes back. 368 00:19:09,680 --> 00:19:13,240 Speaker 7: That you know, that tailwin applies that Delta United American, 369 00:19:13,320 --> 00:19:17,000 Speaker 7: the big business airlines management always paints a really nice 370 00:19:17,040 --> 00:19:20,080 Speaker 7: picture of how everything is going. But every market but 371 00:19:20,160 --> 00:19:23,679 Speaker 7: Atlantic showed lower yields year of a year and yields 372 00:19:23,720 --> 00:19:25,680 Speaker 7: the price of the customer pace per mile they fly. 373 00:19:26,160 --> 00:19:29,119 Speaker 7: So to me, that's synonymous with fares. So what I 374 00:19:29,160 --> 00:19:32,080 Speaker 7: saw was weaker fares that were really bad. Into Latin 375 00:19:32,119 --> 00:19:34,399 Speaker 7: America down I think it was twelve percent or something 376 00:19:34,480 --> 00:19:38,040 Speaker 7: like that. They're down a couple percent for the domestic market. 377 00:19:38,560 --> 00:19:42,439 Speaker 7: Into Europe it was up up one percent. But if 378 00:19:42,520 --> 00:19:45,160 Speaker 7: you do it on a unit revenue basis, I don't 379 00:19:45,160 --> 00:19:47,040 Speaker 7: want to get too complicated about how that works, but 380 00:19:47,119 --> 00:19:50,920 Speaker 7: let's just say that factors in load factors there it 381 00:19:51,000 --> 00:19:53,520 Speaker 7: was down. And so what that's telling me is that 382 00:19:53,560 --> 00:19:56,159 Speaker 7: they're having a harder time filling airplanes going across to 383 00:19:56,240 --> 00:19:58,720 Speaker 7: Europe at the price point they want to fill. So 384 00:19:58,800 --> 00:20:02,520 Speaker 7: they notched back a little bit how full those airplanes were. 385 00:20:02,800 --> 00:20:06,040 Speaker 7: So I generally think, you know, from a revenue standpoint, 386 00:20:06,440 --> 00:20:08,119 Speaker 7: not boting well at all for the rest of the 387 00:20:08,119 --> 00:20:10,760 Speaker 7: airlines they're going to report. I didn't see any sort 388 00:20:10,800 --> 00:20:14,439 Speaker 7: of silver lining, you know, for three Q. I just 389 00:20:14,520 --> 00:20:16,040 Speaker 7: it looks like a weakening market to me. 390 00:20:17,200 --> 00:20:20,159 Speaker 2: So talk to us about capacity out there, George. I 391 00:20:20,200 --> 00:20:23,359 Speaker 2: thought that there's some capacity constraints out there which might 392 00:20:23,400 --> 00:20:27,080 Speaker 2: push fares higher because maybe Boeing wasn't delivering as many 393 00:20:27,080 --> 00:20:29,600 Speaker 2: aircraft that they want, maybe even airbus as well, So 394 00:20:29,640 --> 00:20:32,439 Speaker 2: the airlines didn't have as many aircraft as they really needed. 395 00:20:32,520 --> 00:20:34,280 Speaker 2: What is the capacity of the industry these days? 396 00:20:34,640 --> 00:20:36,640 Speaker 7: Yeah, So I think that's a narrative that's definitely been 397 00:20:36,680 --> 00:20:39,240 Speaker 7: going around the street, and I think that's pushed you know, 398 00:20:39,280 --> 00:20:43,040 Speaker 7: some investment in airlines. So we just really we haven't 399 00:20:43,040 --> 00:20:44,960 Speaker 7: seen that, right. I think there's a there's a couple 400 00:20:45,000 --> 00:20:47,560 Speaker 7: of things that are kind of working against that, and 401 00:20:47,600 --> 00:20:52,040 Speaker 7: I think one, I think US airlines in particular have 402 00:20:52,160 --> 00:20:56,480 Speaker 7: been taking plenty of deliveries they are prioritized by by Boeing. Right, 403 00:20:56,560 --> 00:20:59,800 Speaker 7: Boeing sort of lost business in China. China has been 404 00:21:00,320 --> 00:21:02,440 Speaker 7: so I don't even know if China needs as many 405 00:21:02,440 --> 00:21:05,400 Speaker 7: airplanes as Boeing used to send to them, but they 406 00:21:05,520 --> 00:21:06,840 Speaker 7: you know, they went around and got a bunch of 407 00:21:07,000 --> 00:21:12,760 Speaker 7: orders from Southwest, United Alaska and Boeing had been feeding 408 00:21:12,800 --> 00:21:15,639 Speaker 7: them airplanes before we had the you know that some 409 00:21:15,680 --> 00:21:19,320 Speaker 7: of the problems earlier this year with the Alaska you know. 410 00:21:19,480 --> 00:21:20,320 Speaker 1: Flight you know. 411 00:21:20,320 --> 00:21:22,800 Speaker 7: So that means most of the US airlines had the 412 00:21:22,840 --> 00:21:26,280 Speaker 7: airplanes they expected. We saw Delta. They added I think 413 00:21:26,320 --> 00:21:29,879 Speaker 7: five percent more seats and available seat miles they added 414 00:21:29,880 --> 00:21:33,160 Speaker 7: eight percent. When we look at this market, we see 415 00:21:33,200 --> 00:21:36,439 Speaker 7: in both two Q and three Q additions kind of 416 00:21:36,560 --> 00:21:40,800 Speaker 7: in that five five percent, six percent, seven percent range 417 00:21:41,200 --> 00:21:45,320 Speaker 7: for seats and domestics, seats in Latin America, seats going 418 00:21:45,359 --> 00:21:48,639 Speaker 7: into Europe, and that's well above GDP growth rates. And 419 00:21:48,640 --> 00:21:51,480 Speaker 7: so what I think also is going on here is 420 00:21:51,520 --> 00:21:53,439 Speaker 7: if you were an airline and you thought this bounce 421 00:21:53,480 --> 00:21:56,959 Speaker 7: back travel post pandemic, Hey, there's all this pent up demand, 422 00:21:57,359 --> 00:21:59,679 Speaker 7: they're all going to fly this summer and it's going 423 00:21:59,760 --> 00:22:03,640 Speaker 7: to be growth greater than GDP. I think you were wrong. Right. 424 00:22:03,960 --> 00:22:09,360 Speaker 7: We're basically saying we think growth in travel is recoupling 425 00:22:09,440 --> 00:22:13,080 Speaker 7: with GDP like it was prior to the pandemic. And 426 00:22:13,200 --> 00:22:15,840 Speaker 7: you can't add five percent seats to this market. The 427 00:22:16,000 --> 00:22:17,520 Speaker 7: US market isn't growing that fast. 428 00:22:18,640 --> 00:22:20,840 Speaker 3: What part of any of this? And you kind of 429 00:22:20,880 --> 00:22:23,520 Speaker 3: sort of answered it. It's just also tough comps because 430 00:22:23,560 --> 00:22:25,600 Speaker 3: we were expecting the scenario that you just lined out. 431 00:22:26,520 --> 00:22:26,680 Speaker 5: Well. 432 00:22:26,720 --> 00:22:29,320 Speaker 7: I mean, another thing we've put together recently, it's on 433 00:22:29,320 --> 00:22:32,440 Speaker 7: the Bloomberg terminal under a bi space AI r LN 434 00:22:33,040 --> 00:22:37,760 Speaker 7: dashboard and EROG dashboard. We looked at return on invested capital. 435 00:22:38,160 --> 00:22:41,879 Speaker 7: We looked at margins at US and global airlines and 436 00:22:41,920 --> 00:22:45,359 Speaker 7: you know they did you know, they did better last year, 437 00:22:45,520 --> 00:22:47,840 Speaker 7: but if you look at last year, those margins weren't 438 00:22:48,160 --> 00:22:50,840 Speaker 7: pre pandemic margins. I mean, Delta is a bit of 439 00:22:50,840 --> 00:22:53,800 Speaker 7: a standout. Their returns in invested capital are doing better 440 00:22:53,840 --> 00:22:56,600 Speaker 7: than a lot of their competitors, and at Bastian called 441 00:22:56,600 --> 00:22:59,040 Speaker 7: that out a bunch of times today on the call, 442 00:22:59,119 --> 00:23:02,520 Speaker 7: of course, but most airlines in the US market are 443 00:23:02,520 --> 00:23:05,640 Speaker 7: not getting returns in invested capitol or margins like they 444 00:23:05,640 --> 00:23:10,320 Speaker 7: were in you know, prior to the pandemic. So it 445 00:23:10,400 --> 00:23:12,560 Speaker 7: is a tougher copy that's coming out of the pandemic. 446 00:23:12,800 --> 00:23:16,159 Speaker 7: But this is not the airline industry we saw in 447 00:23:16,200 --> 00:23:20,080 Speaker 7: the past decade. And that's because we got record revenues. 448 00:23:20,119 --> 00:23:23,119 Speaker 7: But those pilots took a big chunk right when they 449 00:23:23,160 --> 00:23:26,600 Speaker 7: got their twenty percent increases and the airlines aren't pricing 450 00:23:26,640 --> 00:23:28,000 Speaker 7: to get that back our. 451 00:23:27,880 --> 00:23:31,119 Speaker 2: Thanks to George ferguson Bloomberg Intelligence, senior aerospace, defense and 452 00:23:31,160 --> 00:23:32,000 Speaker 2: airlines analysts. 453 00:23:32,080 --> 00:23:33,880 Speaker 3: Coming up on the program, we take a deep dive 454 00:23:33,920 --> 00:23:37,280 Speaker 3: into hydrogen and why it's important as we move towards 455 00:23:37,280 --> 00:23:38,000 Speaker 3: the green future. 456 00:23:38,240 --> 00:23:41,280 Speaker 2: They're listening to Bloomberg Intelligence on Bloomberg Radio, providing in 457 00:23:41,280 --> 00:23:43,560 Speaker 2: depth research and data on two thousand companies and one 458 00:23:43,680 --> 00:23:46,640 Speaker 2: hundred and thirty industries. You can access Bloomberg Intelligence via 459 00:23:46,720 --> 00:23:49,120 Speaker 2: b I go on the terminal upfull Sweening. 460 00:23:48,840 --> 00:23:52,160 Speaker 3: And I'm Alex Steel and this is Bloomberg. 461 00:23:54,840 --> 00:23:58,720 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 462 00:23:58,800 --> 00:24:02,320 Speaker 1: weekdays at ten am staring on applecar Play and Android 463 00:24:02,359 --> 00:24:05,119 Speaker 1: Otto with the Bloomberg Business app. You can also listen 464 00:24:05,240 --> 00:24:08,320 Speaker 1: live on Amazon Alexa from our flagship New York station. 465 00:24:08,720 --> 00:24:11,480 Speaker 1: Just say Alexa play Bloomberg eleven thirty. 466 00:24:13,680 --> 00:24:16,879 Speaker 3: Bloomberg Intelligence recently put out research on ten companies to 467 00:24:16,960 --> 00:24:19,040 Speaker 3: watch for in the third quarter of twenty twenty four, 468 00:24:19,400 --> 00:24:21,000 Speaker 3: and for more on the list. We were joined by 469 00:24:21,000 --> 00:24:24,520 Speaker 3: Tim craighead Bloomberg Intelligence, a global Chief Content officer. 470 00:24:24,280 --> 00:24:26,360 Speaker 2: Who first asked Tim about a couple of the companies 471 00:24:26,400 --> 00:24:27,960 Speaker 2: we should be watching for it in three Q. 472 00:24:28,520 --> 00:24:30,720 Speaker 8: I'll give you a smidge of a backdrop on this, 473 00:24:31,200 --> 00:24:34,160 Speaker 8: if that's okay to put it into context. These are 474 00:24:34,200 --> 00:24:36,840 Speaker 8: all part of what we call our focus ideas, which 475 00:24:36,920 --> 00:24:39,600 Speaker 8: is a list of companies that we have a strong 476 00:24:40,080 --> 00:24:43,200 Speaker 8: point of view on fundamentally that we think is different 477 00:24:43,240 --> 00:24:46,680 Speaker 8: from what the market currently believes, and there's catalysts ahead 478 00:24:46,800 --> 00:24:50,000 Speaker 8: to hopefully turn the market towards our view. The thing 479 00:24:50,040 --> 00:24:52,720 Speaker 8: that sets these ten off is that they all have 480 00:24:52,760 --> 00:24:55,480 Speaker 8: catalysts coming up in the third quarter. A lot the 481 00:24:55,520 --> 00:24:59,159 Speaker 8: ten companies to watch for this quarter, and I guess 482 00:24:58,960 --> 00:25:02,360 Speaker 8: the first group that you have to start. It seems 483 00:25:02,440 --> 00:25:06,320 Speaker 8: like with any conversation these days is AI, and there's 484 00:25:06,320 --> 00:25:10,240 Speaker 8: certainly a couple of AI related ideas here, even though 485 00:25:10,400 --> 00:25:14,200 Speaker 8: Nvidia is not on the list. Corning. 486 00:25:14,400 --> 00:25:17,240 Speaker 5: Oh interesting, visit fiber optic cable. 487 00:25:17,480 --> 00:25:21,720 Speaker 8: You can't have AI going through all of these data 488 00:25:21,720 --> 00:25:25,960 Speaker 8: centers if you can't connect the data centers together. And interestingly, 489 00:25:26,080 --> 00:25:29,399 Speaker 8: with fiber optic cable, there was actually a down cycle 490 00:25:29,480 --> 00:25:32,119 Speaker 8: over the course of the past year where there was 491 00:25:32,320 --> 00:25:34,439 Speaker 8: excess inventory and this, that and the other, with some 492 00:25:34,680 --> 00:25:39,080 Speaker 8: telco build related to five G that sort of has 493 00:25:39,119 --> 00:25:42,240 Speaker 8: worked its way through, and we expect data center build 494 00:25:42,280 --> 00:25:46,520 Speaker 8: out to really drive demand for fiber optic cables going forward, 495 00:25:46,600 --> 00:25:52,160 Speaker 8: allah the potential for positive surprise. There's another one called THCHK. 496 00:25:52,600 --> 00:25:55,400 Speaker 8: My guess is you've never heard of this one. It's 497 00:25:55,440 --> 00:25:59,159 Speaker 8: a machinery company out at Japan and they have a 498 00:25:59,240 --> 00:26:03,879 Speaker 8: fifty percent share in something called, now I'm going to 499 00:26:03,920 --> 00:26:07,840 Speaker 8: make sure I pronounce it correctly, linear motion guide rails. 500 00:26:07,960 --> 00:26:11,320 Speaker 8: And you're saying, what, Yeah, if if you think about 501 00:26:11,359 --> 00:26:15,760 Speaker 8: how you picture semiconductors being manufactured, there's the equipment that 502 00:26:16,320 --> 00:26:22,640 Speaker 8: buzzes across and etches these patterns into silicon. The rails 503 00:26:22,680 --> 00:26:25,720 Speaker 8: that they run on are these things, and they have 504 00:26:25,720 --> 00:26:27,679 Speaker 8: a fifty share, So. 505 00:26:27,640 --> 00:26:30,080 Speaker 3: It's it's like the things. 506 00:26:30,960 --> 00:26:34,040 Speaker 8: Yeah, so you know these are things that you can't 507 00:26:34,080 --> 00:26:38,199 Speaker 8: do AI unless you have these things. So we're looking 508 00:26:38,240 --> 00:26:42,520 Speaker 8: for those types of opportunities. You could you could draw 509 00:26:42,640 --> 00:26:46,199 Speaker 8: a little bit of a further sort of second or 510 00:26:46,240 --> 00:26:50,680 Speaker 8: third degree connection with Sandvik. This is another machinery company 511 00:26:50,720 --> 00:26:56,080 Speaker 8: based in Scandinavia. Fifty percent of their business is mining related, 512 00:26:56,119 --> 00:26:59,840 Speaker 8: and you're saying, what, well, the current hot topics these days, 513 00:26:59,840 --> 00:27:05,000 Speaker 8: and mining, among others is copper, and we're seeing a 514 00:27:05,080 --> 00:27:10,040 Speaker 8: capex cycle in copper. You can't dig and mine copper 515 00:27:10,240 --> 00:27:15,280 Speaker 8: without Sandi's stuff, so it's another adjunct play on AI. 516 00:27:15,720 --> 00:27:17,359 Speaker 5: So those are a couple of things. 517 00:27:17,920 --> 00:27:20,119 Speaker 2: I like this. I mean that that's I like the 518 00:27:20,200 --> 00:27:21,800 Speaker 2: way you guys are thinking about this, you know, kind 519 00:27:21,840 --> 00:27:24,199 Speaker 2: of by the you know, kind of the tools of 520 00:27:24,240 --> 00:27:25,679 Speaker 2: AI as supposed to be, you know, kind of the 521 00:27:25,720 --> 00:27:28,800 Speaker 2: direct plays here. Another one is that I think about 522 00:27:28,840 --> 00:27:32,120 Speaker 2: the Olympics in Paris this summer, and I think it's 523 00:27:32,119 --> 00:27:35,879 Speaker 2: going to be just just a monster monster event. Fingers crossed. 524 00:27:35,880 --> 00:27:39,119 Speaker 2: Everything goes well, but that's good for all the companies 525 00:27:39,160 --> 00:27:42,000 Speaker 2: associated with the Olympics. You've got one here, Nike. Talk 526 00:27:42,040 --> 00:27:42,560 Speaker 2: to us about that. 527 00:27:43,080 --> 00:27:46,760 Speaker 8: Yeah, So Nike's interesting. You've got the Olympics coming up. 528 00:27:46,960 --> 00:27:50,520 Speaker 8: They've got new product that's going to be displayed there 529 00:27:50,680 --> 00:27:54,199 Speaker 8: and promoted there with all the advertisement and visibility that 530 00:27:54,320 --> 00:27:57,480 Speaker 8: happens running shoes like the new pegasusts. 531 00:27:57,480 --> 00:27:59,000 Speaker 5: There's other products as well. 532 00:27:59,280 --> 00:28:03,000 Speaker 8: They've lagged for two years in innovation, and Puma and 533 00:28:03,040 --> 00:28:06,000 Speaker 8: Adidas have taken share. You might remember we've talked about 534 00:28:06,000 --> 00:28:08,600 Speaker 8: Adidas before where we had a focus idea that Puna 535 00:28:08,640 --> 00:28:12,840 Speaker 8: mcgoyl was behind. She since closed that shifted gears towards 536 00:28:12,920 --> 00:28:16,399 Speaker 8: Nike because she sees market share recovery with Nike because 537 00:28:16,440 --> 00:28:19,520 Speaker 8: they finally got on board with some new innovation. So 538 00:28:20,080 --> 00:28:24,560 Speaker 8: interesting story there, and I would say similarly, you could 539 00:28:24,640 --> 00:28:27,359 Speaker 8: kind of throw into the same bucket Galaxy, which is 540 00:28:27,400 --> 00:28:31,560 Speaker 8: one of the big casino operators in Macau who think 541 00:28:31,600 --> 00:28:35,160 Speaker 8: about innovation and new product. They opened a big new 542 00:28:35,359 --> 00:28:41,760 Speaker 8: phase of their Cotai based resort and they're starting to 543 00:28:41,800 --> 00:28:44,560 Speaker 8: gain market share and summer is the big season for 544 00:28:44,640 --> 00:28:47,880 Speaker 8: travel China. Travel is back up, and there's a big 545 00:28:47,920 --> 00:28:52,680 Speaker 8: story there that again revolves around new product innovation, right time, 546 00:28:52,760 --> 00:28:53,280 Speaker 8: right place. 547 00:28:53,720 --> 00:28:55,080 Speaker 3: What do you also have on the list which is 548 00:28:55,080 --> 00:28:58,560 Speaker 3: interesting is our age? This is restoration hardware? Is that 549 00:28:58,600 --> 00:28:59,080 Speaker 3: what this is? 550 00:28:59,800 --> 00:28:59,960 Speaker 5: Yeah? 551 00:29:00,440 --> 00:29:03,400 Speaker 3: Okay, because the corn wasn't that good, right, and like 552 00:29:04,080 --> 00:29:06,480 Speaker 3: their stuff is so expensive but in a downturn, that 553 00:29:06,600 --> 00:29:07,880 Speaker 3: feels a little hard to. 554 00:29:07,880 --> 00:29:10,760 Speaker 2: Swallow a discount. You can't get a sales. 555 00:29:10,720 --> 00:29:14,240 Speaker 3: Okay, even the outlets store at Industry City, which is 556 00:29:14,240 --> 00:29:17,280 Speaker 3: they've outlet stores in Brooklyn and stuff is just insanely expensive. 557 00:29:17,320 --> 00:29:19,360 Speaker 3: You can get something for good quality that's not going 558 00:29:19,400 --> 00:29:21,440 Speaker 3: to be like eight grand for like a table. I 559 00:29:21,440 --> 00:29:21,760 Speaker 3: don't know. 560 00:29:22,280 --> 00:29:28,520 Speaker 8: Well, so you're playing into the idea here, Alex, and 561 00:29:28,560 --> 00:29:31,440 Speaker 8: I am going to date myself. I remember being an 562 00:29:31,480 --> 00:29:34,479 Speaker 8: equity research salesperson back at Goldman on the day and 563 00:29:34,560 --> 00:29:37,720 Speaker 8: we were doing the IPO for restoration hardware, and I 564 00:29:37,720 --> 00:29:41,840 Speaker 8: remember traveling around with management. But that's another story. RH 565 00:29:42,280 --> 00:29:47,200 Speaker 8: is one of our cautious ideas, along with HCA, the 566 00:29:47,200 --> 00:29:51,320 Speaker 8: big US hospital company, as well as Nintendo the gaming 567 00:29:51,360 --> 00:29:55,120 Speaker 8: software electronics company. We do have negative focus ideas as 568 00:29:55,120 --> 00:29:57,920 Speaker 8: well as positive focus ideas. And the thing with RH 569 00:29:58,600 --> 00:30:02,520 Speaker 8: management guidance and still consensus is guiding for a recovery 570 00:30:02,680 --> 00:30:05,840 Speaker 8: from what you're just talking about. But now, withstanding the 571 00:30:05,880 --> 00:30:12,360 Speaker 8: resilient US consumer, we still expect the recovery that's anticipated 572 00:30:12,440 --> 00:30:15,080 Speaker 8: to disappoint, you know, for int, your sales last year, 573 00:30:15,200 --> 00:30:19,920 Speaker 8: we're disappointing, notwithstanding the consumer, and we think a recovery 574 00:30:19,960 --> 00:30:22,400 Speaker 8: is going to be delayed and expectations are going to 575 00:30:22,480 --> 00:30:23,360 Speaker 8: be cut again. 576 00:30:24,200 --> 00:30:25,840 Speaker 5: So that's that one. 577 00:30:26,040 --> 00:30:28,920 Speaker 2: That's on the cautious side, right Yeah, Okay. 578 00:30:28,720 --> 00:30:33,479 Speaker 8: Yes, indeed, I would throw out similarly in terms of 579 00:30:34,000 --> 00:30:39,960 Speaker 8: we think overly optimistic expectations. And Nintendo obviously totally different story, 580 00:30:40,000 --> 00:30:42,920 Speaker 8: but we all know game Boy and Switch and. 581 00:30:42,760 --> 00:30:43,360 Speaker 6: Things like that. 582 00:30:43,600 --> 00:30:47,080 Speaker 8: Boy yeah, yeah, going back in the day. But you 583 00:30:47,120 --> 00:30:49,840 Speaker 8: know their current console is the Switch and there is 584 00:30:49,920 --> 00:30:53,200 Speaker 8: a new console coming out called Switch too. And Paul, 585 00:30:53,280 --> 00:30:57,000 Speaker 8: you know from your background these console stories are big deals, 586 00:30:57,040 --> 00:31:00,360 Speaker 8: whether it be for Nintendo or Microsoft or what have you. 587 00:31:01,200 --> 00:31:03,960 Speaker 8: This one is sort of like waiting for Goodough. 588 00:31:05,560 --> 00:31:07,120 Speaker 5: We hit that point. We thought. 589 00:31:08,720 --> 00:31:11,200 Speaker 8: We've been thinking they were going to announce a date, 590 00:31:11,360 --> 00:31:14,120 Speaker 8: but it still is yet to come, and we think 591 00:31:14,160 --> 00:31:17,880 Speaker 8: it causes room for disappointment relative to where consensus expectations 592 00:31:17,920 --> 00:31:19,320 Speaker 8: are still setting our. 593 00:31:19,240 --> 00:31:23,120 Speaker 2: Thanks to Tim Craig at Bloomberg Intelligence, Chief Global Content Officer, 594 00:31:23,400 --> 00:31:24,080 Speaker 2: we have something here. 595 00:31:24,040 --> 00:31:27,000 Speaker 3: At Bloomberg called Bloomberg New Energy Finance. The idea behind 596 00:31:27,040 --> 00:31:30,680 Speaker 3: it is to provide data on commodities, power, transport, industries, 597 00:31:30,760 --> 00:31:33,200 Speaker 3: buildings and agricultural plus new technology. 598 00:31:33,360 --> 00:31:35,760 Speaker 2: This week we looked at hydrogen and why it's important 599 00:31:35,800 --> 00:31:37,280 Speaker 2: as we move towards a green future. 600 00:31:37,520 --> 00:31:40,800 Speaker 3: For more. We were joined by Martin Tangler Bloomberg, THENEF 601 00:31:40,880 --> 00:31:43,080 Speaker 3: head of hydrogen Research, and we asked him first to 602 00:31:43,120 --> 00:31:45,640 Speaker 3: break down what green hydrogen. 603 00:31:45,160 --> 00:31:50,720 Speaker 9: Is green hydrogen is one way of producing hydrogen via electrolysis. 604 00:31:50,720 --> 00:31:55,880 Speaker 9: So that's splitting water into oxygen and hydrogen using green electricity. 605 00:31:55,960 --> 00:31:57,280 Speaker 9: So that's what green hydrogen is. 606 00:31:57,600 --> 00:32:02,640 Speaker 2: So explain to us where the technology green hydrogen? Where 607 00:32:02,680 --> 00:32:05,560 Speaker 2: are we in terms of the development of this technology. 608 00:32:05,960 --> 00:32:10,640 Speaker 9: Yeah, so this is a really it's an old technology. 609 00:32:10,880 --> 00:32:13,560 Speaker 9: At its core. We've used it for more than one 610 00:32:13,600 --> 00:32:16,959 Speaker 9: hundred years. We've done electrolysis of breaking up water molecules 611 00:32:17,240 --> 00:32:22,280 Speaker 9: into hydrogen oxygen. What's new, though, is that this time 612 00:32:22,320 --> 00:32:26,800 Speaker 9: we want to use green electricity in order to reduce 613 00:32:26,840 --> 00:32:31,480 Speaker 9: the emissions from the production of what's called gray hydrogen. 614 00:32:31,600 --> 00:32:36,320 Speaker 9: Gray hydrogen being hydrogen made from fossil fuels without any 615 00:32:36,440 --> 00:32:39,040 Speaker 9: capturing of the resulting CO two, which is how we 616 00:32:39,120 --> 00:32:41,920 Speaker 9: might make the vast majority of the hydrogen today, and 617 00:32:42,080 --> 00:32:46,520 Speaker 9: many countries, many governments have been incentivizing the production of 618 00:32:46,640 --> 00:32:50,720 Speaker 9: green and sometimes also so called blue hydrogen that's gray 619 00:32:50,760 --> 00:32:53,600 Speaker 9: with carbon capture and storage attached to that, so that 620 00:32:53,640 --> 00:32:58,440 Speaker 9: we can decarbonize a deproduction of the gray hydrogen that 621 00:32:58,480 --> 00:33:00,840 Speaker 9: we already produced today one hundred millions. It's a lot 622 00:33:00,880 --> 00:33:03,959 Speaker 9: of hydrogen we make. And also to use hydrogen in 623 00:33:04,000 --> 00:33:08,160 Speaker 9: some other sectors to decarbonize things like steel production for example, 624 00:33:08,240 --> 00:33:11,240 Speaker 9: or shipping where it's really hard to do electrification. 625 00:33:12,600 --> 00:33:15,920 Speaker 3: Why do we want hydrogen? It is very expensive to split. 626 00:33:16,240 --> 00:33:18,360 Speaker 3: It is more expensive if you are going to split 627 00:33:18,400 --> 00:33:22,720 Speaker 3: a hydrogen and oxygen using renewable energy. So why do 628 00:33:22,800 --> 00:33:25,120 Speaker 3: we want it? What's the end product? So awesome? 629 00:33:26,720 --> 00:33:29,720 Speaker 9: Yeah, so we want it, as I've said, in order 630 00:33:29,840 --> 00:33:34,360 Speaker 9: to reduce emissions. That's the only reason honestly. Today, making 631 00:33:34,360 --> 00:33:37,880 Speaker 9: green hydrogen, as you said, Alex, is more expensive than 632 00:33:37,920 --> 00:33:41,000 Speaker 9: making gray hydrogen, and in turn, making gray hydrogen is 633 00:33:41,040 --> 00:33:43,680 Speaker 9: more expensive than using fossil fuels because hydrogen is made 634 00:33:43,760 --> 00:33:46,200 Speaker 9: gray hydroen is made from those fossil fuels. So we 635 00:33:46,240 --> 00:33:49,320 Speaker 9: only use hydrogen in sectors where it is required for 636 00:33:49,360 --> 00:33:53,320 Speaker 9: the chemical properties of it today, so that's production of fertilizers, 637 00:33:53,560 --> 00:33:57,160 Speaker 9: things like ammonia NH three. You cannot make NH three 638 00:33:57,200 --> 00:34:00,800 Speaker 9: without putting H in there. Right, same goes for all refining. 639 00:34:01,280 --> 00:34:04,400 Speaker 9: You need hydrogen and for future as I've said, we're 640 00:34:04,400 --> 00:34:06,920 Speaker 9: going to need it for sectors that are going to 641 00:34:06,960 --> 00:34:11,319 Speaker 9: be really hard to decarbonize using electrification. For example, it's 642 00:34:11,360 --> 00:34:13,960 Speaker 9: really hard to run a ship that runs across half 643 00:34:14,000 --> 00:34:16,960 Speaker 9: the world on batteries, you just don't have enough batteries. 644 00:34:17,000 --> 00:34:19,280 Speaker 9: Batteries are too heavy, they take up too much space. 645 00:34:19,600 --> 00:34:22,560 Speaker 9: We need something denser, and one way we could do that, 646 00:34:22,640 --> 00:34:26,680 Speaker 9: for example, is to combine hydrogen and nitrogen into ammonia 647 00:34:27,200 --> 00:34:31,319 Speaker 9: or hydrogen carbon and oxygen into methanol and use those 648 00:34:31,360 --> 00:34:34,000 Speaker 9: to power the ship instead as a more energy dense fuel. 649 00:34:34,920 --> 00:34:37,919 Speaker 2: Martin Which countries or which parts of the world are 650 00:34:38,080 --> 00:34:40,480 Speaker 2: leading in this green hydrogen move. 651 00:34:42,440 --> 00:34:44,719 Speaker 9: This is a really hard one to say. If you 652 00:34:44,840 --> 00:34:47,120 Speaker 9: ask people five years ago, they tell you it's totally 653 00:34:47,200 --> 00:34:50,680 Speaker 9: Japan that's leading. Japan is the first country that had 654 00:34:50,719 --> 00:34:53,879 Speaker 9: a hydrogen strategy way back when, in twenty fourteen, when 655 00:34:53,920 --> 00:34:57,200 Speaker 9: nobody has even thought about hydrogen to the extent that 656 00:34:57,520 --> 00:35:01,120 Speaker 9: many people are today. But now we could say the 657 00:35:01,120 --> 00:35:06,120 Speaker 9: real leaders are the US and European Union and its 658 00:35:06,160 --> 00:35:09,319 Speaker 9: member states. In the US, as you're probably aware, the 659 00:35:09,320 --> 00:35:13,160 Speaker 9: Inflation Reduction Act was passed back in August twenty twenty two. 660 00:35:13,600 --> 00:35:16,720 Speaker 9: There were some pretty generous tax credits for the production 661 00:35:16,920 --> 00:35:21,000 Speaker 9: of green and blue hydrogen, and we're seeing especially the 662 00:35:21,000 --> 00:35:24,640 Speaker 9: blue hydrogen projects in the US now coming through because 663 00:35:24,640 --> 00:35:27,160 Speaker 9: the economics could actually work out on green It's a 664 00:35:27,200 --> 00:35:30,840 Speaker 9: bit more difficult because companies are still waiting on guidance 665 00:35:30,880 --> 00:35:34,280 Speaker 9: as to the rules under which they could claim these credits. 666 00:35:34,440 --> 00:35:37,360 Speaker 9: In Europe, there's a lot of excitement. Europe is the 667 00:35:37,360 --> 00:35:41,359 Speaker 9: one place since probably the most sincere desire to decarbonize 668 00:35:41,360 --> 00:35:44,440 Speaker 9: and the strongest policies to do that. We have carbon prices, 669 00:35:44,520 --> 00:35:47,279 Speaker 9: we have mandates to use hydrogen. There's very few other 670 00:35:47,320 --> 00:35:50,680 Speaker 9: places where we have actual mandates that require use of 671 00:35:50,719 --> 00:35:55,319 Speaker 9: hydrogen for for example, shipping or aviation. That's what we're 672 00:35:55,320 --> 00:35:56,319 Speaker 9: seeing in Europe. 673 00:35:56,320 --> 00:35:59,080 Speaker 3: Thanks to Martin Tangler. Bloomberg be any Head of Hydrogen 674 00:35:59,120 --> 00:36:00,600 Speaker 3: Research is. 675 00:36:00,560 --> 00:36:05,320 Speaker 1: The Bloomberg Intelligence podcast, available on apples, Spotify, and anywhere 676 00:36:05,360 --> 00:36:08,680 Speaker 1: else you get your podcasts. Listen live each weekday ten 677 00:36:08,719 --> 00:36:12,720 Speaker 1: am to noon Eastern on Bloomberg dot com, Beheartradio app, 678 00:36:12,840 --> 00:36:15,520 Speaker 1: tune In, and the Bloomberg Business app. You can also 679 00:36:15,600 --> 00:36:18,960 Speaker 1: watch us live every weekday on YouTube and always on 680 00:36:19,000 --> 00:36:20,040 Speaker 1: the Bloomberg terminal.