1 00:00:02,720 --> 00:00:10,559 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 00:00:14,600 --> 00:00:17,880 Speaker 1: Eastern on Apple, Cocklay and Android Auto with the Bloomberg 4 00:00:17,920 --> 00:00:21,040 Speaker 1: Business App. Listen on demand wherever you get your podcasts, 5 00:00:21,360 --> 00:00:23,520 Speaker 1: or watch us live on YouTube. 6 00:00:24,079 --> 00:00:26,680 Speaker 2: The newest company to get into the energy sphere of 7 00:00:27,000 --> 00:00:31,360 Speaker 2: admittedly in nuclear energy, is the Trump Media and Technology Group. 8 00:00:31,600 --> 00:00:35,040 Speaker 2: DJT is the ticker, of course, and it's President Trump's company. 9 00:00:35,360 --> 00:00:38,760 Speaker 2: Basically social media company because it owns truth social but 10 00:00:38,800 --> 00:00:42,199 Speaker 2: they are now in nuclear fusion. So we want to 11 00:00:42,280 --> 00:00:45,360 Speaker 2: understand what's going on here. Simon Casey is Bloomberg News 12 00:00:45,400 --> 00:00:49,720 Speaker 2: is managing editor for Energy and Commodities. Simon Trump Media 13 00:00:49,720 --> 00:00:53,240 Speaker 2: and Technology is now a nuclear fusion company. 14 00:00:53,280 --> 00:00:54,040 Speaker 3: How does this work? 15 00:00:54,520 --> 00:00:56,400 Speaker 4: Yeah, I didn't think anybody had this on that bingo 16 00:00:56,480 --> 00:01:00,000 Speaker 4: cod this morning. We certainly didn't. It appears they are 17 00:01:00,080 --> 00:01:02,760 Speaker 4: fusion company as much as they're social media company or 18 00:01:02,800 --> 00:01:07,039 Speaker 4: a crypto company. Now they're merging with a company called TAE. 19 00:01:07,480 --> 00:01:11,080 Speaker 4: It's a far as we can see, a credible fusion player. 20 00:01:11,080 --> 00:01:14,119 Speaker 4: They've been around for over two decades. They've raised money 21 00:01:14,160 --> 00:01:16,160 Speaker 4: from the likes of Gold and sacks from Google and 22 00:01:16,240 --> 00:01:21,000 Speaker 4: various other big investors. I think Chevron. Chevron, the old 23 00:01:21,000 --> 00:01:23,399 Speaker 4: company's venture capital arm, has put money in as well. 24 00:01:24,840 --> 00:01:27,240 Speaker 5: This deal gives them. 25 00:01:27,160 --> 00:01:29,319 Speaker 4: I believe, something in the region of two hundred million 26 00:01:29,360 --> 00:01:36,600 Speaker 4: dollars of a cash infusion to continue their work for DJT. 27 00:01:37,520 --> 00:01:40,160 Speaker 4: They are touting this as a pivot to the exciting 28 00:01:40,160 --> 00:01:44,600 Speaker 4: world of nuclear fusion, which is the future of cheap, affordable, 29 00:01:44,640 --> 00:01:49,080 Speaker 4: abundant energy for everybody, and that's been the dream for decades. 30 00:01:49,120 --> 00:01:52,320 Speaker 4: Of course, there was a breakthrough in twenty twenty two 31 00:01:52,360 --> 00:01:55,960 Speaker 4: where fusion was actually created for a brief moment in 32 00:01:56,000 --> 00:01:59,680 Speaker 4: a laboratory. It's Lawrence with a multi laboratory, and that 33 00:01:59,760 --> 00:02:04,160 Speaker 4: was a fairly significant achievement. And it's been recreated since, 34 00:02:04,200 --> 00:02:07,280 Speaker 4: but only sort of sporadically and not at commercial scale. 35 00:02:07,320 --> 00:02:10,399 Speaker 4: We're a long way off, you know. It's it's it's 36 00:02:10,680 --> 00:02:14,560 Speaker 4: very technically challenging to do this, let alone commercially. 37 00:02:15,600 --> 00:02:18,360 Speaker 5: I'll ask the elephant in the room question, where are 38 00:02:18,360 --> 00:02:20,360 Speaker 5: we in conflicts of interest with this president and this 39 00:02:20,400 --> 00:02:23,600 Speaker 5: administration and investments in business and that type of thing. 40 00:02:23,639 --> 00:02:26,520 Speaker 5: Where's the market kind of evolved to? This is this 41 00:02:26,600 --> 00:02:29,639 Speaker 5: is before the Trump administration. This stuff, I would say, 42 00:02:29,720 --> 00:02:30,480 Speaker 5: rarely happened. 43 00:02:31,160 --> 00:02:34,600 Speaker 4: It almost I struggle to remember it happening. Now It's commonplace, 44 00:02:34,639 --> 00:02:37,160 Speaker 4: isn't it. And you know, we let's be clear, the 45 00:02:37,200 --> 00:02:41,119 Speaker 4: Trump administration has a very very robust I would say, 46 00:02:41,200 --> 00:02:44,880 Speaker 4: very sort of clearly outlined energy agenda and energy dominance agenda. 47 00:02:45,560 --> 00:02:49,880 Speaker 4: They are profoss or fuel. They also support the nuclear industry, 48 00:02:50,040 --> 00:02:53,480 Speaker 4: and the nuclear industry has taken has gained a lot 49 00:02:53,480 --> 00:02:57,080 Speaker 4: of momentum since that discussion discovery I mentioned in twenty 50 00:02:57,120 --> 00:02:59,359 Speaker 4: twenty two. But since Trump has come in, he's been 51 00:02:59,480 --> 00:03:04,760 Speaker 4: very support of the nuclear industry to build new nuclear reactors. Look, 52 00:03:04,800 --> 00:03:08,160 Speaker 4: we have serious issues here in this country with nuclear, 53 00:03:08,280 --> 00:03:10,639 Speaker 4: with power demand from the AI industry and how we're 54 00:03:10,639 --> 00:03:13,440 Speaker 4: going to service that demand and keeping a lid on prices. 55 00:03:14,600 --> 00:03:17,680 Speaker 4: The Energy Secretary, Chris Riot is also very pro nuclear, 56 00:03:17,720 --> 00:03:21,760 Speaker 4: being very vocal on that front. But yeah, it's it's, it's, 57 00:03:21,760 --> 00:03:25,359 Speaker 4: it's it's kind of amazing. Nevertheless, to see this kind 58 00:03:25,360 --> 00:03:26,320 Speaker 4: of deal this morning. 59 00:03:26,520 --> 00:03:30,639 Speaker 5: Well, just looking at the dees function for DJT twelve employees, 60 00:03:31,600 --> 00:03:35,000 Speaker 5: that's I guess in the trailing twelve months three point 61 00:03:35,040 --> 00:03:38,160 Speaker 5: seven million of revenue one point three billion of cash 62 00:03:38,160 --> 00:03:41,440 Speaker 5: though nine hundred and fifty million of total debt. So 63 00:03:41,480 --> 00:03:46,160 Speaker 5: what does Donald Trump company, Trump Media and Technology Group cooperation? 64 00:03:46,280 --> 00:03:48,200 Speaker 5: What is that? What did they really bring to this 65 00:03:49,280 --> 00:03:50,960 Speaker 5: deal other than maybe some cash? 66 00:03:51,080 --> 00:03:53,880 Speaker 4: The name, I guess, the ticker. Yeah, it's It's, It's, 67 00:03:53,760 --> 00:03:55,680 Speaker 4: It's so a large extent, it is a memestock, I 68 00:03:55,680 --> 00:03:58,280 Speaker 4: think it's fair to say. And with a cash pile, 69 00:03:58,400 --> 00:03:59,960 Speaker 4: and if they can use some of that cash pile 70 00:04:00,680 --> 00:04:04,080 Speaker 4: to fund nuclear research and development, and maybe that's a 71 00:04:04,120 --> 00:04:05,280 Speaker 4: sensible use of that cash. 72 00:04:05,360 --> 00:04:07,040 Speaker 3: Yeah. Name recognition goes a long way. 73 00:04:08,040 --> 00:04:11,040 Speaker 2: In twenty twenty five, in twenty twenty six, Simon, how 74 00:04:11,080 --> 00:04:14,480 Speaker 2: big is the investable universe of nuclear companies right now? 75 00:04:14,800 --> 00:04:16,680 Speaker 4: That's a good question. I mean that in terms of 76 00:04:16,680 --> 00:04:19,080 Speaker 4: fusion companies, I think this is the first, This will 77 00:04:19,120 --> 00:04:21,839 Speaker 4: be the first company fusion developer that's actually listed on 78 00:04:21,880 --> 00:04:24,920 Speaker 4: a stock exchange. So there's a handful of these companies, 79 00:04:26,120 --> 00:04:28,480 Speaker 4: some of them on the East coast here, there's a 80 00:04:28,480 --> 00:04:34,039 Speaker 4: big there's a cluster around the Boston area, and they're 81 00:04:34,080 --> 00:04:37,840 Speaker 4: all privately held apart from this one. In terms of 82 00:04:37,960 --> 00:04:40,839 Speaker 4: other nuclear stocks, there's a handful of them. There's a 83 00:04:40,839 --> 00:04:43,240 Speaker 4: company called Fermi which has got had a lot of 84 00:04:43,279 --> 00:04:47,320 Speaker 4: interest recently, which is trying to develop a campus down 85 00:04:47,360 --> 00:04:51,120 Speaker 4: in West Texas that would include AI data centers and 86 00:04:51,480 --> 00:04:56,560 Speaker 4: potentially a new nuclear reactor to power those that data center. 87 00:04:56,839 --> 00:05:01,479 Speaker 4: That's a very ambitious project. Then you have a handful, 88 00:05:01,839 --> 00:05:04,479 Speaker 4: as I say, of other companies that are developed trying 89 00:05:04,480 --> 00:05:07,560 Speaker 4: to develop small, medium sized nuclear reactors. And this is 90 00:05:07,600 --> 00:05:10,360 Speaker 4: the other thing that the Trump administration is very keen 91 00:05:10,440 --> 00:05:13,760 Speaker 4: on to to kind of lower the cost of entry, 92 00:05:13,760 --> 00:05:15,560 Speaker 4: if you like, into the nuclear industry. 93 00:05:15,839 --> 00:05:19,240 Speaker 5: What can you tell us about the timetable associated with 94 00:05:19,920 --> 00:05:24,720 Speaker 5: commercially deploying utility scale fusion power companies? 95 00:05:25,200 --> 00:05:28,960 Speaker 4: So well, if we're talking fusion, it hasn't been proved 96 00:05:28,960 --> 00:05:32,400 Speaker 4: at commercial scale, so we're probably talking decades before I 97 00:05:32,440 --> 00:05:33,240 Speaker 4: would say it's fair. 98 00:05:33,400 --> 00:05:35,640 Speaker 5: So I'm just looking at the Bloomberg reporting and it's 99 00:05:35,960 --> 00:05:39,120 Speaker 5: the combined company plans to begin construction next construction next 100 00:05:39,160 --> 00:05:42,520 Speaker 5: year on the world's first utility scale fusion power plants. 101 00:05:42,480 --> 00:05:45,640 Speaker 5: So that's going to take a long time to construct that. 102 00:05:45,680 --> 00:05:48,039 Speaker 4: I mean, we don't even know if it can work 103 00:05:48,040 --> 00:05:50,000 Speaker 4: at a commercial scale. Now they can, they can pour 104 00:05:50,080 --> 00:05:53,240 Speaker 4: the concrete and build the foundations. Nothing to stop them 105 00:05:53,320 --> 00:05:53,800 Speaker 4: doing that, and. 106 00:05:53,760 --> 00:05:56,880 Speaker 5: This sounds like a multi billion dollar type of plant 107 00:05:57,080 --> 00:05:57,719 Speaker 5: for these things. 108 00:05:57,640 --> 00:06:00,000 Speaker 4: Potentially, no one's ever built one before, so I don't 109 00:06:00,080 --> 00:06:02,440 Speaker 4: we don't really know. I mean we know that, you know, 110 00:06:02,560 --> 00:06:06,039 Speaker 4: conventional fission reactors, which have been around since the end 111 00:06:06,080 --> 00:06:08,520 Speaker 4: of the Second World War. They take the last one 112 00:06:08,560 --> 00:06:10,240 Speaker 4: built in this country went over budget and it was 113 00:06:10,240 --> 00:06:11,320 Speaker 4: about over ten billion dollars. 114 00:06:11,360 --> 00:06:14,240 Speaker 3: I believe who's going to provide the financing on all that? 115 00:06:14,960 --> 00:06:17,279 Speaker 4: I think if it can work at scale, then you 116 00:06:17,400 --> 00:06:19,680 Speaker 4: might a lot of more investors might take a look 117 00:06:19,680 --> 00:06:24,800 Speaker 4: at this, including mainstream investors. But it's so it's so 118 00:06:24,839 --> 00:06:27,440 Speaker 4: sort of hypothetical at the moment, it's almost impossible to 119 00:06:27,440 --> 00:06:29,120 Speaker 4: say what is the return on investment going. 120 00:06:29,040 --> 00:06:31,120 Speaker 2: To be for something like it's early innings, not even 121 00:06:31,200 --> 00:06:32,400 Speaker 2: first inning them very early. 122 00:06:32,680 --> 00:06:35,080 Speaker 4: I mean, the sort of the well worn joke it's 123 00:06:35,120 --> 00:06:37,800 Speaker 4: not even funny anymore, that nuclear fusion. It's the future, 124 00:06:38,240 --> 00:06:41,160 Speaker 4: and it's always been. It's the future thirty years out 125 00:06:41,200 --> 00:06:43,120 Speaker 4: and it always will be thirty years out. That's kind 126 00:06:43,160 --> 00:06:47,120 Speaker 4: of where we've always been. It exists in the textbooks, 127 00:06:47,480 --> 00:06:49,680 Speaker 4: it now exists in the laboratory, which, don't get me wrong, 128 00:06:49,760 --> 00:06:53,320 Speaker 4: is a big step forward, but transferring that, you know, 129 00:06:53,720 --> 00:06:56,200 Speaker 4: creating nuclear fusion for a fraction of a second and 130 00:06:56,240 --> 00:07:00,240 Speaker 4: then evolving that to where it's on all the time 131 00:07:00,480 --> 00:07:02,960 Speaker 4: and being able to power a town or a city 132 00:07:03,200 --> 00:07:04,680 Speaker 4: is a quantum leap. 133 00:07:05,640 --> 00:07:11,440 Speaker 5: SMR Small modular reactors. Yes, how that seems like pretty 134 00:07:11,480 --> 00:07:13,720 Speaker 5: cool technology to me, but that's still years out. 135 00:07:14,080 --> 00:07:17,440 Speaker 4: That is again probably years out because it's technically challenging, 136 00:07:17,440 --> 00:07:19,800 Speaker 4: but it does exist. I mean, we use them in 137 00:07:19,840 --> 00:07:24,040 Speaker 4: nuclear submarines and aircraft carriers, so there's nothing to stop 138 00:07:24,080 --> 00:07:26,040 Speaker 4: you taking one of those out of out of a 139 00:07:26,080 --> 00:07:29,400 Speaker 4: ship and having it on land. The challenge there is 140 00:07:29,400 --> 00:07:33,360 Speaker 4: actually possibly more regulatory, and again that's something that Trump 141 00:07:33,360 --> 00:07:35,920 Speaker 4: administration is actually trying to address in terms of permitting 142 00:07:36,000 --> 00:07:40,400 Speaker 4: reform and so forth. So there are companies listed that 143 00:07:40,480 --> 00:07:44,080 Speaker 4: are developing these things. We haven't seen one yet that's 144 00:07:44,280 --> 00:07:47,000 Speaker 4: been sort of produced and it's been proven it can 145 00:07:47,040 --> 00:07:50,240 Speaker 4: be manufactured at scale, but it's more it's more achievable. 146 00:07:50,240 --> 00:07:54,520 Speaker 5: I would say, stay with us. More from Bloomberg Intelligence 147 00:07:54,520 --> 00:07:55,560 Speaker 5: coming up after this. 148 00:07:59,160 --> 00:08:02,880 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 149 00:08:02,960 --> 00:08:06,040 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 150 00:08:06,080 --> 00:08:09,360 Speaker 1: Auto with the Bloomberg Business App, listen on demand wherever 151 00:08:09,440 --> 00:08:12,560 Speaker 1: you get your podcasts, or watch us live on YouTube. 152 00:08:13,320 --> 00:08:15,040 Speaker 2: Paul, I think we need to take a closer look 153 00:08:15,040 --> 00:08:18,400 Speaker 2: at Micron given the roaring comeback gets made this year. 154 00:08:18,680 --> 00:08:21,080 Speaker 2: I mean, memory chip maker. That's an old school product, 155 00:08:21,280 --> 00:08:23,520 Speaker 2: but it's having its day. Let's bring in Jake Silverman, 156 00:08:23,520 --> 00:08:27,720 Speaker 2: Bloomberg Intelligence Semiconductor analysts to recap these results. Jake, let's 157 00:08:27,720 --> 00:08:30,600 Speaker 2: start just with the big massive gain Micron has seen 158 00:08:30,600 --> 00:08:33,840 Speaker 2: this year, up two hundred percent. What were investors pricing 159 00:08:33,880 --> 00:08:35,920 Speaker 2: in and did they get what they wanted with today? 160 00:08:36,000 --> 00:08:38,160 Speaker 3: With yesterday's earnings report, Yeah, I. 161 00:08:38,080 --> 00:08:40,280 Speaker 6: Think investors were expecting a little bit more of a 162 00:08:40,280 --> 00:08:43,720 Speaker 6: subdued outlook for the first physical sorry, second fiscal quarter, 163 00:08:44,320 --> 00:08:48,240 Speaker 6: primarily just due to typical little bit of conservatism for management, 164 00:08:48,320 --> 00:08:51,439 Speaker 6: but also you know, the February ended quarter tends to 165 00:08:51,520 --> 00:08:53,840 Speaker 6: be a little bit more seasonally weak. You get December 166 00:08:53,960 --> 00:08:58,280 Speaker 6: portion of that, but usually consumer products PCs and smartphones 167 00:08:58,640 --> 00:09:00,840 Speaker 6: tend to see a little bit of a squad decline 168 00:09:00,880 --> 00:09:04,880 Speaker 6: just off of strong holiday seasonality. We all kind of 169 00:09:04,960 --> 00:09:08,000 Speaker 6: knew that pricing was going to be the most important 170 00:09:08,000 --> 00:09:11,280 Speaker 6: factor going into the quarter, And obviously demand from AI 171 00:09:11,480 --> 00:09:15,000 Speaker 6: is pretty strong, but there are areas like high bandwidth 172 00:09:15,000 --> 00:09:18,120 Speaker 6: memory where they're actually Micron is actually somewhat constrained in 173 00:09:18,200 --> 00:09:20,880 Speaker 6: terms of their ability to supply, just simply because they 174 00:09:20,920 --> 00:09:23,679 Speaker 6: haven't invested in that much additional capacity and. 175 00:09:23,640 --> 00:09:24,880 Speaker 7: They need to improve yields. 176 00:09:24,920 --> 00:09:27,880 Speaker 6: And they're transitioning over from HBM three to E to four, 177 00:09:28,320 --> 00:09:31,560 Speaker 6: which is to support Nvidia's next architecture and other customers. 178 00:09:31,559 --> 00:09:33,480 Speaker 6: So there's a few factors going on here that I 179 00:09:33,520 --> 00:09:37,000 Speaker 6: think had investors a little bit more maybe conservative, in 180 00:09:37,080 --> 00:09:38,480 Speaker 6: terms of what they were expecting. 181 00:09:38,880 --> 00:09:40,760 Speaker 5: I don't know a lot about SEMy conductors, and I 182 00:09:40,800 --> 00:09:42,760 Speaker 5: want to keep it that way, But what I do 183 00:09:42,920 --> 00:09:46,959 Speaker 5: know is it's a cyclical business. Has this AI spending 184 00:09:47,080 --> 00:09:49,920 Speaker 5: thing kind of even out the cycles or just throw 185 00:09:49,960 --> 00:09:50,920 Speaker 5: the cycles out the window. 186 00:09:51,920 --> 00:09:53,720 Speaker 7: It's a little unprecedented. 187 00:09:54,000 --> 00:09:56,520 Speaker 6: I don't think that we're necessarily at that point where 188 00:09:56,559 --> 00:09:59,319 Speaker 6: we can say that there aren't going to be cycles, 189 00:09:59,360 --> 00:10:01,720 Speaker 6: or at least not in the next I don't know, 190 00:10:02,440 --> 00:10:06,560 Speaker 6: call it five ten years something like that. Typically, what 191 00:10:06,600 --> 00:10:09,640 Speaker 6: we see with memory, I'll just focus on that Specifically, 192 00:10:10,360 --> 00:10:12,959 Speaker 6: we send tend to see something like seven to ten 193 00:10:13,040 --> 00:10:17,480 Speaker 6: quarters about two years plus of upcycles, and then what 194 00:10:17,600 --> 00:10:20,600 Speaker 6: happens from there is that we tend to see some 195 00:10:20,640 --> 00:10:23,840 Speaker 6: sort of cyclical decline, and that really is because of 196 00:10:24,640 --> 00:10:28,040 Speaker 6: supply ending up being a little bit more, a little 197 00:10:28,080 --> 00:10:32,120 Speaker 6: bit more supply growth relative to demand growth. AI is 198 00:10:32,200 --> 00:10:35,600 Speaker 6: structurally limiting some of that. We're seeing AI inferencing demand 199 00:10:36,000 --> 00:10:40,000 Speaker 6: being really strong. That's both for DRAM and land. At 200 00:10:40,000 --> 00:10:43,520 Speaker 6: this point, DRAM is more important for Micron. It's a 201 00:10:43,600 --> 00:10:46,080 Speaker 6: much more it's a much larger percentage of their sales 202 00:10:46,120 --> 00:10:50,959 Speaker 6: and that's where high bandwidth memory is included in their revenue. 203 00:10:51,840 --> 00:10:52,199 Speaker 7: And so. 204 00:10:53,960 --> 00:10:56,360 Speaker 6: What this does to the cycle, it's definitely extending it. 205 00:10:56,360 --> 00:10:58,760 Speaker 6: It's elongating what we would expect, and it's making it 206 00:10:58,800 --> 00:11:01,800 Speaker 6: a lot more difficult for investors, I think, to capture 207 00:11:02,360 --> 00:11:05,040 Speaker 6: what will be the ultimate peak of the cycle. But 208 00:11:05,720 --> 00:11:07,440 Speaker 6: on the other hand, we have to look at what's 209 00:11:07,440 --> 00:11:12,720 Speaker 6: happening with pricing. If customers like PC, smartphone, automotive run 210 00:11:12,760 --> 00:11:17,240 Speaker 6: the gamut, if they can't get supply, someone need to 211 00:11:17,280 --> 00:11:20,280 Speaker 6: meet that, which means that Micron or their peers are 212 00:11:20,360 --> 00:11:22,720 Speaker 6: going to at some point need to expand capacity. 213 00:11:22,760 --> 00:11:23,720 Speaker 7: They're kind of working on it. 214 00:11:23,760 --> 00:11:27,760 Speaker 6: They hinted at it with the additional capex increases for 215 00:11:27,840 --> 00:11:31,000 Speaker 6: the fiscal twenty six gone up from eighteen to twenty billion. 216 00:11:31,440 --> 00:11:34,520 Speaker 6: But it's just a question of how fast and to 217 00:11:34,559 --> 00:11:38,480 Speaker 6: what magnitude can they actually increase capacity. 218 00:11:38,320 --> 00:11:40,720 Speaker 2: Right, And I'm glad you bring that up because we 219 00:11:40,840 --> 00:11:44,040 Speaker 2: know that the industry's shifting production to the more advanced 220 00:11:44,040 --> 00:11:47,000 Speaker 2: technology for AA data centers and therefore there's a short 221 00:11:47,040 --> 00:11:50,560 Speaker 2: account this less sophisticated memory chips for PCs. Doesn't that 222 00:11:50,600 --> 00:11:52,640 Speaker 2: mean that Micron has the upper hand when it comes 223 00:11:52,640 --> 00:11:55,960 Speaker 2: to Dell or HP and they can call the shots more. 224 00:11:56,000 --> 00:11:58,240 Speaker 2: I mean, what does a Dell What does an HP do? 225 00:11:58,320 --> 00:11:59,880 Speaker 2: Then if they can't get what they need. 226 00:12:00,080 --> 00:12:01,080 Speaker 7: Yeah, it's complicated. 227 00:12:01,120 --> 00:12:03,640 Speaker 6: So Micron has to decide how they want to allocate 228 00:12:03,679 --> 00:12:05,960 Speaker 6: that capacity that they have, whether that goes to PC. 229 00:12:06,160 --> 00:12:09,000 Speaker 6: I think that when you're a larger customer like Dell HP, 230 00:12:09,440 --> 00:12:11,760 Speaker 6: you kind of have to just take the product at 231 00:12:11,800 --> 00:12:12,439 Speaker 6: the price that. 232 00:12:12,679 --> 00:12:14,320 Speaker 7: Micron is offering it now. 233 00:12:14,440 --> 00:12:17,240 Speaker 6: I do think if you can buy in large volumes, 234 00:12:17,280 --> 00:12:20,319 Speaker 6: you can you know, mitigate some of those price increases, 235 00:12:20,360 --> 00:12:22,400 Speaker 6: But at the end of the day, you're kind of 236 00:12:23,480 --> 00:12:27,480 Speaker 6: you're being dictated by the market demand. The market forces 237 00:12:27,679 --> 00:12:31,320 Speaker 6: but also when prices have declined in the past, PC 238 00:12:31,440 --> 00:12:33,800 Speaker 6: makers have also benefited from that. So if there is 239 00:12:33,840 --> 00:12:36,920 Speaker 6: a cyclical decline, which I expect to happen at some point, 240 00:12:37,559 --> 00:12:42,160 Speaker 6: they'll also benefit from a decline in memory pricing as well. 241 00:12:42,440 --> 00:12:45,760 Speaker 5: Where does Micron manufactures chips? 242 00:12:46,240 --> 00:12:49,920 Speaker 6: Yeah, so it's primarily in Taiwan, but also in Japan 243 00:12:50,040 --> 00:12:52,760 Speaker 6: as well, and they have some They have a fab 244 00:12:52,920 --> 00:12:57,960 Speaker 6: in Manassas, Virginia, but they're also expanding now to Boise, Idaho, 245 00:12:58,040 --> 00:13:00,560 Speaker 6: and they're eventually going to bring a fab online in 246 00:13:00,600 --> 00:13:01,000 Speaker 6: New York. 247 00:13:01,080 --> 00:13:03,920 Speaker 7: So it's pretty gen Where in New Yorkers we know Clay, 248 00:13:03,960 --> 00:13:04,400 Speaker 7: New York. 249 00:13:04,640 --> 00:13:05,640 Speaker 3: Where's Clay, New York. 250 00:13:05,760 --> 00:13:08,000 Speaker 5: I'm gonna say Upstate Coelle. 251 00:13:07,800 --> 00:13:10,240 Speaker 3: Upstate Okay, yeah, so not not near us. 252 00:13:10,360 --> 00:13:12,920 Speaker 5: No, Upstate. There's you know, I didn't know there's Upstate, 253 00:13:13,280 --> 00:13:15,760 Speaker 5: and I think there's mid State for some people call it. 254 00:13:15,800 --> 00:13:19,160 Speaker 2: Well everyone in Manhattan thinks Upstate is like Westchester, so right. 255 00:13:19,320 --> 00:13:22,760 Speaker 5: Yes, but I learned this during the pandemic. There's different 256 00:13:22,760 --> 00:13:24,120 Speaker 5: regions of the state of New York and I have to 257 00:13:24,160 --> 00:13:25,120 Speaker 5: go google that now. 258 00:13:25,400 --> 00:13:26,280 Speaker 7: I wasn't aware of that. 259 00:13:26,480 --> 00:13:28,280 Speaker 2: Well, you're a New Jersey guy, so there's just a 260 00:13:28,320 --> 00:13:29,160 Speaker 2: city and then that's it. 261 00:13:29,240 --> 00:13:32,720 Speaker 5: That's exactly exactly right. Stay with us. More from Bloomberg 262 00:13:32,760 --> 00:13:34,360 Speaker 5: Intelligence coming up after this. 263 00:13:38,240 --> 00:13:41,959 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 264 00:13:42,040 --> 00:13:45,080 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 265 00:13:45,120 --> 00:13:48,439 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 266 00:13:48,480 --> 00:13:51,800 Speaker 1: you get your podcasts, or watch us live on YouTube. 267 00:13:52,480 --> 00:13:55,280 Speaker 5: Activist investor Elie Investment Management has built a stake of 268 00:13:55,280 --> 00:13:58,800 Speaker 5: more than one billion dollars in Lululemon Athletica. The stock 269 00:13:58,840 --> 00:14:00,280 Speaker 5: is up six and a half percent to but I 270 00:14:00,280 --> 00:14:03,559 Speaker 5: think the problem is it's down forty two percent year 271 00:14:03,640 --> 00:14:05,760 Speaker 5: to date. So let's see see what's going on over 272 00:14:05,760 --> 00:14:09,240 Speaker 5: there at Lulu. Putum Goyle Senior, a US e commerce 273 00:14:09,280 --> 00:14:12,559 Speaker 5: and retail analyst Bloomberg Intelligence. She's based down there in 274 00:14:12,600 --> 00:14:15,080 Speaker 5: for instance, she joins us, put them what's going on 275 00:14:15,320 --> 00:14:18,120 Speaker 5: with Lulu Lemon? What's the problem here? And what do 276 00:14:18,160 --> 00:14:21,320 Speaker 5: you think Elliott believes it can do to fix it? 277 00:14:22,720 --> 00:14:25,880 Speaker 8: The problem is that they've had plenty of execution missteps 278 00:14:25,880 --> 00:14:29,240 Speaker 8: over the past two years, led directly to product innovation, 279 00:14:29,880 --> 00:14:34,560 Speaker 8: and as a search for a new leader, the candidate 280 00:14:34,600 --> 00:14:37,720 Speaker 8: that he's outlined seems like a strong one. You know, 281 00:14:37,800 --> 00:14:41,120 Speaker 8: she's led a turnaround or helply to turnaround at Ralph 282 00:14:41,160 --> 00:14:45,320 Speaker 8: Lauren in the past, that coach both iconic brands that 283 00:14:45,440 --> 00:14:48,440 Speaker 8: struggled in that time, and she helped lead that turnaround. 284 00:14:48,440 --> 00:14:51,720 Speaker 8: So I think Lula Lemon roll a different turnaround. She 285 00:14:52,040 --> 00:14:55,600 Speaker 8: has the track record if she is at the lead 286 00:14:56,080 --> 00:14:57,720 Speaker 8: to really help drive this turnaround. 287 00:14:59,240 --> 00:15:01,080 Speaker 2: Punam tell us a little bit more about the role 288 00:15:01,080 --> 00:15:04,160 Speaker 2: of Chip Wilson. He founded Lululemon and he's been making 289 00:15:04,200 --> 00:15:09,440 Speaker 2: comments really agitating for change, accusing Calvin McDonald of killing 290 00:15:09,480 --> 00:15:13,800 Speaker 2: innovation and some serious strategic missteps. But he is not 291 00:15:14,280 --> 00:15:17,240 Speaker 2: part of management at Lulu Lemon. So why does this 292 00:15:17,320 --> 00:15:18,240 Speaker 2: voice carry such weight? 293 00:15:19,800 --> 00:15:23,320 Speaker 8: I mean, he was the founder, right, He did find 294 00:15:23,320 --> 00:15:27,040 Speaker 8: this brand, he did grow this brand very quickly into 295 00:15:27,120 --> 00:15:31,520 Speaker 8: a strong, loved, well known brand, and I think the 296 00:15:31,560 --> 00:15:35,760 Speaker 8: brand emerged by having great product. Like if you think 297 00:15:35,800 --> 00:15:38,440 Speaker 8: about Lulu Lemon in the past, it was all about product. 298 00:15:38,760 --> 00:15:42,880 Speaker 8: You could not find Lululemon product or something like it 299 00:15:43,080 --> 00:15:47,040 Speaker 8: anywhere else. Leggings that made you feel good, leggings that performed. 300 00:15:47,200 --> 00:15:49,960 Speaker 8: That's how they made their mark. And the question is 301 00:15:50,080 --> 00:15:53,320 Speaker 8: what's next? Have they been able to innovate fast enough 302 00:15:53,680 --> 00:15:56,800 Speaker 8: to prevent competition from encroaching that space. And the answer 303 00:15:56,880 --> 00:15:59,600 Speaker 8: is no. And that's the struggle that they're having right now. 304 00:16:00,320 --> 00:16:02,920 Speaker 5: Is it just a question of money, putting more money 305 00:16:02,920 --> 00:16:05,560 Speaker 5: into I don't know, research and development of leggings. I 306 00:16:05,600 --> 00:16:06,320 Speaker 5: don't know how that works. 307 00:16:07,160 --> 00:16:09,880 Speaker 8: I think it's execution right. It's about staying ahead of 308 00:16:09,960 --> 00:16:14,720 Speaker 8: trends and really innovating faster than competition. Clearly today with 309 00:16:14,840 --> 00:16:18,360 Speaker 8: AI and up their mediums, there is the ability for 310 00:16:18,480 --> 00:16:21,120 Speaker 8: a competition to come on faster. But that said, Little 311 00:16:21,160 --> 00:16:23,520 Speaker 8: Lemon was ahead of the game and they've kind of 312 00:16:23,560 --> 00:16:26,760 Speaker 8: fallen behind. So they do need someone who knows the 313 00:16:26,840 --> 00:16:29,840 Speaker 8: product story and can lead a product let turnaround. 314 00:16:30,840 --> 00:16:33,960 Speaker 5: Stay with us. More from Bloomberg Intelligence coming up after this. 315 00:16:37,880 --> 00:16:41,560 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 316 00:16:41,640 --> 00:16:44,720 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 317 00:16:44,760 --> 00:16:48,040 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 318 00:16:48,120 --> 00:16:51,240 Speaker 1: you get your podcasts, or watch us live on YouTube. 319 00:16:51,920 --> 00:16:54,000 Speaker 5: More earnings out there, this time from our friends at 320 00:16:54,120 --> 00:16:58,480 Speaker 5: Darden Restaurants put out some I think surprisingly pretty good 321 00:16:58,560 --> 00:17:01,680 Speaker 5: news out there. On the Rachel Flour she covers the 322 00:17:01,720 --> 00:17:04,680 Speaker 5: restaurants for Bloomberg New She joints us here in our studio, Rachel, 323 00:17:04,680 --> 00:17:06,520 Speaker 5: what do we hear from Darden today? 324 00:17:06,800 --> 00:17:10,440 Speaker 9: Yeah, so the company has done well today. It saw 325 00:17:10,440 --> 00:17:13,840 Speaker 9: the same store sales rise. It actually raised sales forecast, 326 00:17:14,520 --> 00:17:17,400 Speaker 9: and stock is up as much as four point five 327 00:17:17,400 --> 00:17:21,479 Speaker 9: percent today, which is the biggest game in almost seven months. 328 00:17:22,840 --> 00:17:26,840 Speaker 9: And I mean while sales are up, though, it's profits 329 00:17:26,880 --> 00:17:29,800 Speaker 9: have kind of taken a hit because of high beef prices. 330 00:17:29,840 --> 00:17:32,760 Speaker 9: You know, we've been hearing about that. That has affected 331 00:17:32,800 --> 00:17:35,119 Speaker 9: their earnings for a little bit. But now they do 332 00:17:35,240 --> 00:17:38,439 Speaker 9: expect beef prices to hopefully come down in the near future. 333 00:17:38,680 --> 00:17:43,080 Speaker 5: Okay, I guess they're fast casual is kind of their stuff. 334 00:17:43,119 --> 00:17:46,040 Speaker 5: So like the I'm sitting down, I've got a waitress'm 335 00:17:46,040 --> 00:17:48,240 Speaker 5: doing on that stuff. But it's it's talk to us 336 00:17:48,240 --> 00:17:50,400 Speaker 5: about their brands and what they're saying about their brands. 337 00:17:50,600 --> 00:17:52,600 Speaker 9: Sure, yeah, so I guess they will call themselves a 338 00:17:52,640 --> 00:17:55,440 Speaker 9: bit more more casual dining and a fast casual. I 339 00:17:55,440 --> 00:17:59,560 Speaker 9: guess you know this this industry has yeah terms, but yeah, 340 00:17:59,560 --> 00:18:01,600 Speaker 9: they actually kind of saying that. It's it's just still 341 00:18:01,640 --> 00:18:04,439 Speaker 9: been pretty pretty resilient you know, their target audience are 342 00:18:04,480 --> 00:18:07,879 Speaker 9: these like middle and high income customers, and those haven't 343 00:18:07,920 --> 00:18:10,240 Speaker 9: been so much affected by the economy. Maybe they're a 344 00:18:10,240 --> 00:18:12,760 Speaker 9: bit more worried, but they that hasn't really stopped them 345 00:18:12,760 --> 00:18:15,240 Speaker 9: from spending. And you know, they see these restaurants as 346 00:18:15,400 --> 00:18:18,000 Speaker 9: kind of a treat to them. And you know, for 347 00:18:18,200 --> 00:18:20,440 Speaker 9: many consumers too, I think they're starting to see these 348 00:18:20,760 --> 00:18:23,960 Speaker 9: restaurants like Olive Garden and Longhound Stakhouse as a place 349 00:18:24,000 --> 00:18:26,399 Speaker 9: where they can kind of get pretty good food for 350 00:18:27,000 --> 00:18:29,480 Speaker 9: you know, a pretty good price right now, especially when 351 00:18:29,480 --> 00:18:33,359 Speaker 9: you see places that Cover and Chipotle, which those are 352 00:18:33,359 --> 00:18:36,920 Speaker 9: your fast casual places, and you know they're pretty expensive 353 00:18:36,920 --> 00:18:40,119 Speaker 9: now with inflation, and so the comparison is you know, 354 00:18:40,520 --> 00:18:42,440 Speaker 9: like as a consumer, you know, why not just pay 355 00:18:42,440 --> 00:18:43,880 Speaker 9: a little bit more and I can get a better 356 00:18:43,880 --> 00:18:45,320 Speaker 9: experience and an Olive Garden. 357 00:18:45,680 --> 00:18:48,560 Speaker 5: So they're they're raising there for your forecast. Is that 358 00:18:48,640 --> 00:18:51,359 Speaker 5: more on the revenue side or is that costs or 359 00:18:51,440 --> 00:18:52,280 Speaker 5: what are they doing there? 360 00:18:52,320 --> 00:18:56,160 Speaker 9: So they actually increase the same store sales, the comparable sales, 361 00:18:56,880 --> 00:18:59,760 Speaker 9: and so they do expect, you know, consumers to keep coming. 362 00:18:59,840 --> 00:19:03,359 Speaker 9: You know, they have other tools in their belt to 363 00:19:03,520 --> 00:19:05,960 Speaker 9: kind of keep drawing consumers like they are smaller, they 364 00:19:05,960 --> 00:19:08,920 Speaker 9: introduce like smaller portions. They are on uber Eats now. 365 00:19:09,400 --> 00:19:13,280 Speaker 9: But yeah, they actually maintain their earnings for share guidance 366 00:19:13,400 --> 00:19:15,520 Speaker 9: just because of commodity prices. 367 00:19:15,800 --> 00:19:18,119 Speaker 5: So again, what are some of the are you seeing 368 00:19:18,119 --> 00:19:21,040 Speaker 5: differences within the restaurant industry, you know, the the lower 369 00:19:21,119 --> 00:19:23,439 Speaker 5: end of the higher end about just sales trends, how 370 00:19:23,480 --> 00:19:25,960 Speaker 5: their customers are doing there is it a different discussion. 371 00:19:26,760 --> 00:19:28,119 Speaker 3: I think it's a different discussion. 372 00:19:28,200 --> 00:19:30,440 Speaker 9: I think we've heard a lot about how a lot 373 00:19:30,440 --> 00:19:32,520 Speaker 9: of the fast food chains, a lot of the fast 374 00:19:32,520 --> 00:19:35,960 Speaker 9: casual chains, you know, they're still getting hit by your 375 00:19:36,000 --> 00:19:39,520 Speaker 9: lower income consumers kind of pulling back, you know, like 376 00:19:39,680 --> 00:19:43,399 Speaker 9: inflation and commodity prices are highways your casual dining restaurants. 377 00:19:43,440 --> 00:19:46,080 Speaker 9: You know, they seem to still be pretty resilient. A 378 00:19:46,160 --> 00:19:51,200 Speaker 9: Chili's is another example. They're still able to draw that consumer, 379 00:19:51,240 --> 00:19:54,000 Speaker 9: which is are still able to spend a little bit more. 380 00:19:54,080 --> 00:19:56,520 Speaker 5: So, as a reporter covering the restaurant industry, you got 381 00:19:56,560 --> 00:19:58,040 Speaker 5: to get out in New York City because we don't 382 00:19:58,080 --> 00:20:00,359 Speaker 5: have a lot of that stuff. So you gotta travel 383 00:20:00,359 --> 00:20:02,520 Speaker 5: around the country, right go to where the cracker barrels 384 00:20:02,520 --> 00:20:03,520 Speaker 5: are and the Chilis are. 385 00:20:03,720 --> 00:20:06,600 Speaker 9: Yeah, you definitely have to, I think for most of us. 386 00:20:06,680 --> 00:20:09,399 Speaker 9: I mean in New York City unfortunately, you have to 387 00:20:09,400 --> 00:20:13,000 Speaker 9: try to get into Times Square just to get that. 388 00:20:13,440 --> 00:20:15,440 Speaker 3: But I want to get one faster, which is. 389 00:20:15,400 --> 00:20:16,160 Speaker 7: Not the most fun. 390 00:20:16,240 --> 00:20:20,760 Speaker 5: Yeah, exactly. So what's the format? You know, what are 391 00:20:21,160 --> 00:20:23,760 Speaker 5: what's the buzz within the restaurant industry these days? Like 392 00:20:23,760 --> 00:20:26,719 Speaker 5: maybe the format or is there a new cool company? 393 00:20:26,720 --> 00:20:28,639 Speaker 5: Like for a while there was shake Shack and all 394 00:20:28,640 --> 00:20:31,240 Speaker 5: the burger stuff and the smash Burgers and all that stuff. 395 00:20:31,600 --> 00:20:34,320 Speaker 9: I mean, I think Chili's was the cool company for 396 00:20:34,359 --> 00:20:37,399 Speaker 9: a bit. You know, they had a really good social media. 397 00:20:38,040 --> 00:20:41,080 Speaker 9: You know, a lot of the items were going viral. 398 00:20:42,119 --> 00:20:44,280 Speaker 9: I think with Olive Godden. You know, I think what 399 00:20:44,280 --> 00:20:48,240 Speaker 9: we've seen today is the popularity of smaller portions seem 400 00:20:48,320 --> 00:20:52,040 Speaker 9: to be something that consumers uh gravitating towards, you know, 401 00:20:52,760 --> 00:20:54,960 Speaker 9: especially with some of them, you know, going on we 402 00:20:55,160 --> 00:20:58,840 Speaker 9: lost drugs, you know, becoming more like half conscious. You know, 403 00:20:58,920 --> 00:21:00,960 Speaker 9: this might be actually a play for them. 404 00:21:01,119 --> 00:21:03,919 Speaker 5: Yeah, So was that ever a thing with the GLP 405 00:21:04,040 --> 00:21:07,000 Speaker 5: one drugs and restaurants ors that faded? 406 00:21:07,840 --> 00:21:10,119 Speaker 9: I think they're still trying to figure it out. I think, 407 00:21:10,640 --> 00:21:12,280 Speaker 9: you know, I think we are still trying to figure 408 00:21:12,280 --> 00:21:14,200 Speaker 9: out too, like how many people are actually really going 409 00:21:14,320 --> 00:21:15,119 Speaker 9: to go on a drugs? 410 00:21:15,119 --> 00:21:17,160 Speaker 3: How you know people are going to go off it? 411 00:21:18,080 --> 00:21:20,639 Speaker 3: So I think they are also watching it. 412 00:21:20,680 --> 00:21:23,280 Speaker 9: They did say they're slightly affected, like some they're seeing 413 00:21:23,320 --> 00:21:27,080 Speaker 9: some diners cutback on appetizers and desserts, But they also 414 00:21:27,080 --> 00:21:30,119 Speaker 9: say that it's mostly alcohol, which that they're pulling back on, 415 00:21:30,200 --> 00:21:31,879 Speaker 9: which is the longer term tread. 416 00:21:32,359 --> 00:21:37,080 Speaker 1: This is the Bloomberg Intelligence podcast, available on Apple, Spotify, 417 00:21:37,240 --> 00:21:40,760 Speaker 1: and anywhere else you get your podcasts. Listen live each 418 00:21:40,760 --> 00:21:44,520 Speaker 1: weekday ten am to noon Eastern on Bloomberg dot com, 419 00:21:44,640 --> 00:21:48,160 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app. 420 00:21:48,600 --> 00:21:51,520 Speaker 1: You can also watch us live every weekday on YouTube 421 00:21:51,920 --> 00:21:54,160 Speaker 1: and always on the Bloomberg terminal