1 00:00:02,720 --> 00:00:09,040 Speaker 1: Bloomberg Audio Studios, podcasts, radio news, and Android auto with 2 00:00:09,119 --> 00:00:12,240 Speaker 1: the Bloomberg Business App. Listen on demand wherever you get 3 00:00:12,240 --> 00:00:15,040 Speaker 1: your podcasts, or watch us live on YouTube. 4 00:00:15,640 --> 00:00:17,159 Speaker 2: One of the big stories that come out of this 5 00:00:17,720 --> 00:00:20,239 Speaker 2: trip to the Middle East, at least for the Boeing company, 6 00:00:20,360 --> 00:00:23,919 Speaker 2: Boeing won the single biggest deal in US planemaker's history, 7 00:00:23,960 --> 00:00:27,000 Speaker 2: with Qatar Airways placing in order for at least one 8 00:00:27,040 --> 00:00:29,600 Speaker 2: hundred and sixty wide body aircraft during. 9 00:00:29,320 --> 00:00:33,040 Speaker 3: A visit to Doha by US President Donald Trump. So 10 00:00:33,080 --> 00:00:34,160 Speaker 3: we're going to dig into that story. 11 00:00:34,200 --> 00:00:37,559 Speaker 2: Sid, Philip joints his deputy team leader for Global Aviation 12 00:00:38,400 --> 00:00:41,159 Speaker 2: a good day for Boeing here, what do you make 13 00:00:41,200 --> 00:00:41,400 Speaker 2: of it? 14 00:00:41,440 --> 00:00:43,919 Speaker 3: Sid's what's Boeing saying about this? 15 00:00:44,520 --> 00:00:46,519 Speaker 4: So Boeing hasn't already said a whole lot about this, 16 00:00:46,600 --> 00:00:49,280 Speaker 4: But I mean, this is a significant deal for Boeing 17 00:00:49,360 --> 00:00:52,480 Speaker 4: because they can sort of add another sort of milestone 18 00:00:52,600 --> 00:00:55,360 Speaker 4: order to their backlog, especially for their seven eighty seven, 19 00:00:55,800 --> 00:00:58,040 Speaker 4: which is the sort of state of the odd white 20 00:00:58,080 --> 00:01:01,480 Speaker 4: Buddy jet, as well as potential for the Triple seven X, 21 00:01:01,520 --> 00:01:04,120 Speaker 4: which is again a jet that Katara Airways has ordered 22 00:01:04,120 --> 00:01:07,520 Speaker 4: and is still to be certified and so as airlines 23 00:01:07,560 --> 00:01:09,880 Speaker 4: sort of look to the next generation of aircraft that 24 00:01:09,880 --> 00:01:12,520 Speaker 4: they're looking to order, this is sort of these are 25 00:01:12,560 --> 00:01:14,360 Speaker 4: these You're going to see these mega deals coming up 26 00:01:14,400 --> 00:01:17,640 Speaker 4: where everyone's looking to sort of replace their current generation 27 00:01:17,720 --> 00:01:21,360 Speaker 4: planes with newer models which are more advanced, better fuel economy, 28 00:01:21,600 --> 00:01:23,720 Speaker 4: and that sort of great for Boeing in terms of 29 00:01:23,800 --> 00:01:26,000 Speaker 4: just building out that backlog and sort of selling out 30 00:01:26,040 --> 00:01:28,240 Speaker 4: aircraft past the end of the decade. 31 00:01:29,120 --> 00:01:32,039 Speaker 5: What is the delivery time for something like this, but 32 00:01:32,080 --> 00:01:35,240 Speaker 5: when it's clearly had some operational execution issues exactly. 33 00:01:35,280 --> 00:01:37,240 Speaker 4: I mean Boeing has been struggling to deliver both the 34 00:01:37,280 --> 00:01:39,720 Speaker 4: seven eight seven as well as seven three seven Max 35 00:01:39,800 --> 00:01:42,520 Speaker 4: and get the seven Triple seven X, which is their 36 00:01:42,600 --> 00:01:46,160 Speaker 4: latest sort of generation aircraft certified. So it is we're 37 00:01:46,160 --> 00:01:48,320 Speaker 4: still not clear on the details for what the sort 38 00:01:48,360 --> 00:01:51,760 Speaker 4: of intricacies of this Qatara deal are, but potentially these 39 00:01:51,800 --> 00:01:53,760 Speaker 4: will sort of play out and go out into the 40 00:01:53,800 --> 00:01:56,560 Speaker 4: next decade because I mean, they've got a significant backlog 41 00:01:56,560 --> 00:01:59,040 Speaker 4: of aircraft that need to deliver in the short term. 42 00:01:59,120 --> 00:02:00,960 Speaker 4: So this is not going to be aircraft deal that 43 00:02:01,000 --> 00:02:03,280 Speaker 4: sort of happens in the next two or three years. 44 00:02:03,440 --> 00:02:06,160 Speaker 4: Is going to be a drawnout deal that goes into 45 00:02:06,200 --> 00:02:07,840 Speaker 4: the next into the next decade. 46 00:02:08,160 --> 00:02:09,400 Speaker 3: Well, stock market likes it. 47 00:02:09,440 --> 00:02:11,960 Speaker 2: Stocks up one point four percent today, Boeing is hitting 48 00:02:12,000 --> 00:02:14,000 Speaker 2: a fifty two week HI. It's up sixteen and a 49 00:02:14,000 --> 00:02:17,000 Speaker 2: half percent year to date, So maybe Boeing's finally digging 50 00:02:17,000 --> 00:02:19,200 Speaker 2: itself out of its hole from the last several years. 51 00:02:19,360 --> 00:02:21,600 Speaker 2: So that kind of goes to the big question said, 52 00:02:22,080 --> 00:02:25,200 Speaker 2: it's all about production, you know, getting planes off, and 53 00:02:25,240 --> 00:02:27,800 Speaker 2: people just say, like George Fergus from Bloomberg Intelligence says, 54 00:02:27,840 --> 00:02:30,359 Speaker 2: just focus on the seven thirty seven Max deliveries. That's 55 00:02:30,400 --> 00:02:34,320 Speaker 2: the number. Is there a sense that Boeing's making improvements there? 56 00:02:34,760 --> 00:02:37,560 Speaker 4: We have seen Boeing deliveries inch up and we've sort 57 00:02:37,600 --> 00:02:40,400 Speaker 4: of they've had sort of milestone in terms of just 58 00:02:40,480 --> 00:02:43,919 Speaker 4: hitting better production levels on the sevent three seven, And 59 00:02:44,280 --> 00:02:47,440 Speaker 4: we've heard from Aline customers, including United Airlines yesterday saying 60 00:02:47,480 --> 00:02:49,840 Speaker 4: that the deliveries of the seven three seven Max are 61 00:02:49,880 --> 00:02:52,080 Speaker 4: sort of going up and they're waiting on the seven 62 00:02:52,200 --> 00:02:54,799 Speaker 4: eighty seven, which is the aircraft that we understand that 63 00:02:54,880 --> 00:02:57,840 Speaker 4: Katara Airways ordered. That's also going to be sort of 64 00:02:57,919 --> 00:03:00,760 Speaker 4: key to getting production and profitability going. 65 00:03:01,840 --> 00:03:04,840 Speaker 5: What other kind of pitch can Boeing make to outstrip 66 00:03:04,919 --> 00:03:07,440 Speaker 5: Airbus because in a duopoly market, and I appreciate that 67 00:03:07,520 --> 00:03:09,400 Speaker 5: China has some smaller players, but if you're dealing with 68 00:03:09,440 --> 00:03:12,680 Speaker 5: a duopoly, like I mean, people got to buy your 69 00:03:12,720 --> 00:03:14,160 Speaker 5: planes exactly. 70 00:03:13,880 --> 00:03:16,239 Speaker 4: I mean, we have adopoly in at the moment. 71 00:03:16,360 --> 00:03:19,000 Speaker 6: And does that change it all? You think? It sort 72 00:03:19,000 --> 00:03:19,480 Speaker 6: of has. 73 00:03:19,440 --> 00:03:22,320 Speaker 4: Changed a little bit in terms of just the sort 74 00:03:22,320 --> 00:03:24,880 Speaker 4: of there's a lot of politics behind aircraft orders again, 75 00:03:24,919 --> 00:03:27,880 Speaker 4: and that's something that we've seen where Trump's been announcing 76 00:03:27,960 --> 00:03:30,680 Speaker 4: these mega Boeing orders. I mean, yesterday announced the deal 77 00:03:30,760 --> 00:03:34,120 Speaker 4: for thirty planes in Saudi Arabia, and so there is 78 00:03:34,160 --> 00:03:36,320 Speaker 4: a lot of politics attached to aircraft orders. But at 79 00:03:36,320 --> 00:03:39,040 Speaker 4: the same time, both Airbus and Boeing are sort of 80 00:03:39,080 --> 00:03:41,320 Speaker 4: sold out of aircraft until the end of the decades. 81 00:03:41,400 --> 00:03:44,920 Speaker 4: So it is sort of you're notching up all these orders. 82 00:03:44,960 --> 00:03:47,320 Speaker 4: But at the same time, the biggest thing that airlines 83 00:03:47,320 --> 00:03:49,920 Speaker 4: are talking about is give me my plane, because that's 84 00:03:50,000 --> 00:03:53,120 Speaker 4: really the biggest question where airlines are saying that plane 85 00:03:53,120 --> 00:03:56,160 Speaker 4: deliveries are delayed, and the air Bus has repeatedly talked 86 00:03:56,160 --> 00:03:59,280 Speaker 4: about how supply chain issues continue to haunt the industry 87 00:03:59,760 --> 00:04:01,680 Speaker 4: now five years after the pandemic. 88 00:04:01,760 --> 00:04:04,880 Speaker 2: Yeah, which I can't imagine, although again I'm what I 89 00:04:04,960 --> 00:04:09,080 Speaker 2: understand is one of the bottlenecks is labor getting the 90 00:04:09,360 --> 00:04:11,880 Speaker 2: This is not just you know, sitting an assembly line 91 00:04:11,920 --> 00:04:14,720 Speaker 2: and hitting a hammer. You've got to be really, really 92 00:04:14,760 --> 00:04:17,120 Speaker 2: skilled at labor, and during the pandemic you lost a 93 00:04:17,160 --> 00:04:19,960 Speaker 2: lot of that and retraining these folks are getting new 94 00:04:20,000 --> 00:04:22,000 Speaker 2: people in it. I'm hearing that's a big problem. 95 00:04:22,120 --> 00:04:24,080 Speaker 4: Labor is a major problem as well as I mean, 96 00:04:24,600 --> 00:04:28,360 Speaker 4: just one part being short holds up the entire production line. 97 00:04:28,360 --> 00:04:30,159 Speaker 4: I mean, you have millions of parts that go into 98 00:04:30,200 --> 00:04:33,600 Speaker 4: an aircraft, and Evers and Boeing are the final assembly 99 00:04:33,640 --> 00:04:35,960 Speaker 4: lines where the plane actually gets put together. But then 100 00:04:36,279 --> 00:04:39,240 Speaker 4: if parts are not available in the sort of process, 101 00:04:39,640 --> 00:04:42,000 Speaker 4: you can't actually build those planes. And that's where the 102 00:04:42,000 --> 00:04:45,560 Speaker 4: bottlenecks come up. Because you have smaller suppliers who are 103 00:04:45,600 --> 00:04:49,520 Speaker 4: struggling financially, You've got parts in short supply. I mean 104 00:04:49,640 --> 00:04:51,839 Speaker 4: EBUS talks about it's sort of it's whack a mole 105 00:04:51,920 --> 00:04:55,560 Speaker 4: where you get one part sorted out and something else breaks, 106 00:04:55,600 --> 00:04:58,279 Speaker 4: and so it's it's really a question of getting that 107 00:04:58,360 --> 00:05:00,680 Speaker 4: supply chain to sort of hum along nicely and then 108 00:05:00,760 --> 00:05:03,839 Speaker 4: actually building those planes and delivering those planes because you've 109 00:05:03,880 --> 00:05:06,920 Speaker 4: now got record backlogs at both Boeing and Airbus. 110 00:05:07,120 --> 00:05:09,760 Speaker 6: So are they exempt from tariff issues? 111 00:05:10,279 --> 00:05:13,159 Speaker 4: That's again a really important question. No one's quite clear 112 00:05:13,240 --> 00:05:15,880 Speaker 4: about in terms of what the tariff impact is going 113 00:05:15,960 --> 00:05:18,839 Speaker 4: to be because for fifty years almost that the aviation 114 00:05:18,920 --> 00:05:22,520 Speaker 4: industry has largely functioned tariff free, and the tariffs added 115 00:05:22,560 --> 00:05:26,080 Speaker 4: complexity to it because now everyone's not quite sure if 116 00:05:26,120 --> 00:05:29,160 Speaker 4: aircraft are example. I mean, you've seen like all sorts 117 00:05:29,160 --> 00:05:33,080 Speaker 4: of industry players and industry groups making representations to President 118 00:05:33,120 --> 00:05:35,960 Speaker 4: Trump saying that we would like to have tariffs removed 119 00:05:35,960 --> 00:05:38,919 Speaker 4: on aircraft and aircraft parts, and so we're trying to 120 00:05:38,920 --> 00:05:42,560 Speaker 4: see where that sort of actually lands up, because potentially 121 00:05:42,720 --> 00:05:46,039 Speaker 4: aircraft manufacturers and airlines may have to pay tariffs on 122 00:05:46,120 --> 00:05:48,480 Speaker 4: planes depending on what they're mean and what parts they have. 123 00:05:48,680 --> 00:05:51,240 Speaker 5: Right, which makes all of this that much more complicated 124 00:05:51,240 --> 00:05:51,920 Speaker 5: and more difficult. 125 00:05:51,960 --> 00:05:53,279 Speaker 6: All right, should be great to say that. 126 00:05:53,320 --> 00:05:56,479 Speaker 5: Thanks very much joining us here, said Phillip, Deputy Team 127 00:05:56,560 --> 00:05:59,160 Speaker 5: leader for Global Aviation. We appreciate that. Always good to 128 00:05:59,160 --> 00:06:02,320 Speaker 5: see you in New York too. Thank you. 129 00:06:02,320 --> 00:06:06,039 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 130 00:06:06,120 --> 00:06:09,200 Speaker 1: weekdays at ten am Eastern on Apple Cocklay and Android 131 00:06:09,200 --> 00:06:12,520 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 132 00:06:12,560 --> 00:06:16,120 Speaker 1: you get your podcasts, or watch us live on YouTube. 133 00:06:16,600 --> 00:06:18,359 Speaker 2: Alex Deal, Paul Swiney, we are live here in our 134 00:06:18,360 --> 00:06:21,200 Speaker 2: Bloomberg Interactive Brokers studio in New York City, or streaming 135 00:06:21,240 --> 00:06:23,719 Speaker 2: live on YouTube as well. I'm looking at the S 136 00:06:23,760 --> 00:06:26,760 Speaker 2: and P five hundred, absolutely flat on the year. So 137 00:06:27,160 --> 00:06:30,440 Speaker 2: you know, we were down thirteen fourteen percent of the year, 138 00:06:30,640 --> 00:06:35,360 Speaker 2: peaked the trough twenty percent, climbed, you know, crawled out 139 00:06:35,360 --> 00:06:35,920 Speaker 2: of that hole. 140 00:06:35,839 --> 00:06:37,120 Speaker 3: Right here, and we'll see where we go from here. 141 00:06:37,120 --> 00:06:38,200 Speaker 3: Sean oh Harry joins US. 142 00:06:38,360 --> 00:06:43,279 Speaker 2: President Pastry Ets join us via zoom from Florida. Hey Sean, 143 00:06:44,040 --> 00:06:46,680 Speaker 2: what do you do now? I mean, you're we were 144 00:06:46,760 --> 00:06:51,120 Speaker 2: really selling off hard. Recession talk was getting pretty heated. 145 00:06:51,600 --> 00:06:54,039 Speaker 2: Now the President has kind of walked back seemingly some 146 00:06:54,200 --> 00:06:57,480 Speaker 2: of the tariff uncertainty in the marketplaces, and that seems 147 00:06:57,480 --> 00:07:00,520 Speaker 2: to be enough for investors that come back into the markets. 148 00:07:00,560 --> 00:07:01,200 Speaker 3: What do you guys see? 149 00:07:02,360 --> 00:07:04,440 Speaker 7: Yeah, thanks for having me. I think there was three 150 00:07:04,480 --> 00:07:07,120 Speaker 7: things that were sort of headwinds into the market earlier 151 00:07:07,120 --> 00:07:10,080 Speaker 7: this year. One was the tariff stuff. I think, you know, 152 00:07:10,120 --> 00:07:11,960 Speaker 7: I don't think anybody was surprised that he was going 153 00:07:12,000 --> 00:07:13,120 Speaker 7: to make an issue of it. 154 00:07:13,200 --> 00:07:13,600 Speaker 8: I think the. 155 00:07:16,160 --> 00:07:19,560 Speaker 7: Severity, if you will, sort of spooked people a little bit. 156 00:07:19,640 --> 00:07:21,320 Speaker 7: I never thought they were ever going to come in 157 00:07:21,320 --> 00:07:23,000 Speaker 7: at that rate, you know, I always thought this was 158 00:07:23,000 --> 00:07:24,840 Speaker 7: going to be a negotiation, and as you see, where 159 00:07:24,840 --> 00:07:27,280 Speaker 7: are in the midst of a lot of negotiations. I 160 00:07:27,280 --> 00:07:32,160 Speaker 7: think the second sort of headwind was uncertainly about tax policy, 161 00:07:32,720 --> 00:07:34,520 Speaker 7: and hopefully that will get itself resolved. 162 00:07:34,560 --> 00:07:35,400 Speaker 8: And then the third ist. 163 00:07:35,400 --> 00:07:38,760 Speaker 7: Has always been the Fed and whether they're being too 164 00:07:38,840 --> 00:07:43,640 Speaker 7: slow in terms of their approach to interest rates. One 165 00:07:43,680 --> 00:07:46,880 Speaker 7: of those tailwinds I think has turned into a I 166 00:07:46,920 --> 00:07:48,960 Speaker 7: mean headwinds has turned into a tailwind, and that's the 167 00:07:49,000 --> 00:07:49,800 Speaker 7: tariff policy. 168 00:07:49,840 --> 00:07:50,880 Speaker 8: I think we're seeing. 169 00:07:51,840 --> 00:07:55,520 Speaker 7: Terrific progress there across the board, and I think we'll 170 00:07:55,560 --> 00:07:59,480 Speaker 7: continue to see that. Hopefully, you know, Congress will get 171 00:07:59,480 --> 00:08:02,480 Speaker 7: their act together and they'll get the quote unquote big 172 00:08:02,520 --> 00:08:05,440 Speaker 7: beautiful bill done, and then we'll wait and see with 173 00:08:05,440 --> 00:08:08,640 Speaker 7: regard to what's going with with with with Sherman Pale. 174 00:08:08,800 --> 00:08:11,440 Speaker 7: So I think the environment has changed from a somewhat 175 00:08:12,120 --> 00:08:13,960 Speaker 7: die or you know, oh gosh, we're going to have 176 00:08:14,000 --> 00:08:16,320 Speaker 7: it in a recession and inflation is going to be 177 00:08:16,320 --> 00:08:19,320 Speaker 7: horrible because of all these tariffs, to an environment where 178 00:08:19,600 --> 00:08:23,040 Speaker 7: I think there's less talk of a recession and less 179 00:08:23,040 --> 00:08:27,960 Speaker 7: concerned about the potential inflation regarding terrorists. There is, you know, 180 00:08:28,040 --> 00:08:29,840 Speaker 7: some good news in this market, and that is that 181 00:08:30,000 --> 00:08:32,320 Speaker 7: energy prices are down and energy has a big input 182 00:08:32,320 --> 00:08:34,160 Speaker 7: to inflation. And we saw a really nice print the 183 00:08:34,160 --> 00:08:37,480 Speaker 7: other day, So I think you can be somewhat optimistic now, 184 00:08:37,520 --> 00:08:40,679 Speaker 7: whereas I think earlier, with those three headwinds, you had 185 00:08:40,679 --> 00:08:41,920 Speaker 7: to be a little bit more cautious. 186 00:08:42,480 --> 00:08:44,520 Speaker 6: Do we still see the buy the mentality? 187 00:08:45,840 --> 00:08:49,440 Speaker 7: Uh? You know, it's interesting, Alex. We're seeing two different 188 00:08:49,440 --> 00:08:53,360 Speaker 7: camps here. The big institutional investors in the hedge funders 189 00:08:53,400 --> 00:08:57,800 Speaker 7: are have been net short, and so I'm looking for 190 00:08:57,880 --> 00:08:59,800 Speaker 7: some kind of a short rally it's, you know, as 191 00:08:59,840 --> 00:09:03,520 Speaker 7: they finally capitulate on their short positions. But the retail 192 00:09:03,520 --> 00:09:05,760 Speaker 7: investor has been really, really strong, and so I think 193 00:09:05,800 --> 00:09:08,400 Speaker 7: the retail investor is sort of thinking about this differently 194 00:09:08,440 --> 00:09:13,040 Speaker 7: than the big institutional investors and putting money in every 195 00:09:13,040 --> 00:09:15,960 Speaker 7: time they get a chance to and that's probably, you know, 196 00:09:16,000 --> 00:09:17,840 Speaker 7: the smarter move in the long run. I mean, in 197 00:09:17,840 --> 00:09:19,920 Speaker 7: the short run, nobody knows what the market's going to do. 198 00:09:19,960 --> 00:09:21,520 Speaker 7: But in the long run, over time, you know, you 199 00:09:21,520 --> 00:09:23,920 Speaker 7: could describe this dock market in eight simple words. The 200 00:09:23,960 --> 00:09:27,040 Speaker 7: advance is permanent and all declines are temporary. So we're 201 00:09:27,080 --> 00:09:28,600 Speaker 7: seeing sort of two camps out there. 202 00:09:29,240 --> 00:09:32,640 Speaker 2: So Sean as president Pacer ETFs, where are you guys 203 00:09:32,640 --> 00:09:34,160 Speaker 2: seeing fun flows? 204 00:09:34,200 --> 00:09:35,440 Speaker 3: Is it different maybe this. 205 00:09:35,400 --> 00:09:37,520 Speaker 2: Week versus a couple of weeks ago when we had 206 00:09:37,520 --> 00:09:41,000 Speaker 2: companies pulling guidance and again real angst in the marketplace. 207 00:09:42,120 --> 00:09:44,360 Speaker 7: Well, it's funny, you know, Paul. A couple of weeks ago, 208 00:09:44,480 --> 00:09:47,680 Speaker 7: our volumes were insane, like three four times the average 209 00:09:47,720 --> 00:09:50,120 Speaker 7: down volume on ours across the board, and so that 210 00:09:50,280 --> 00:09:52,200 Speaker 7: was to me a sign of panic in the market. 211 00:09:52,600 --> 00:09:54,800 Speaker 7: They've now sort of settled down. We're seeing, you know, 212 00:09:55,120 --> 00:09:58,520 Speaker 7: surprisingly some good flows into international and global as you know, 213 00:09:59,040 --> 00:10:01,400 Speaker 7: those markets have done better. I think our global fund 214 00:10:01,440 --> 00:10:03,680 Speaker 7: is up somewhere around nine or ten percent year to date. 215 00:10:04,080 --> 00:10:06,120 Speaker 7: I just looked at emerging markets the other day. It's 216 00:10:06,160 --> 00:10:08,760 Speaker 7: up pretty handily as well. So we're seeing flows there 217 00:10:08,840 --> 00:10:12,240 Speaker 7: we're seeing consistent flows into the cash Cow series on 218 00:10:12,280 --> 00:10:14,720 Speaker 7: the value side, so you know, those are high quality 219 00:10:14,760 --> 00:10:18,079 Speaker 7: stocks that generate higher return on assets and traded a discount, 220 00:10:18,160 --> 00:10:21,240 Speaker 7: so that's sort of a more conservative quality play. And 221 00:10:21,240 --> 00:10:24,559 Speaker 7: then we're seeing really significant flows into one of our 222 00:10:24,600 --> 00:10:27,800 Speaker 7: growth ETFs that uses free cash flow margin. And then 223 00:10:27,840 --> 00:10:30,760 Speaker 7: there's a little bit of sort of in the financial 224 00:10:30,800 --> 00:10:33,480 Speaker 7: advisor community, there's really two camps as well, those that 225 00:10:33,559 --> 00:10:35,280 Speaker 7: sort of want to tap the brakes a little bit 226 00:10:35,280 --> 00:10:36,920 Speaker 7: and those that want to put their foot on the gas. 227 00:10:37,400 --> 00:10:39,160 Speaker 7: For those that want to tap their brakes a little bit, 228 00:10:39,200 --> 00:10:42,199 Speaker 7: we're seeing flows into some of the risk management strategies. 229 00:10:41,679 --> 00:10:42,080 Speaker 8: That we have. 230 00:10:42,800 --> 00:10:44,640 Speaker 5: Interesting so, I mean, guess is how you make a market? 231 00:10:45,000 --> 00:10:47,640 Speaker 5: I mean you have two different directions and then and 232 00:10:47,640 --> 00:10:49,920 Speaker 5: then you move around that really interesting stuff. Thank you 233 00:10:49,920 --> 00:10:52,760 Speaker 5: so much, Sean Shaan O'Hair, president of Pacer ETFs, joining 234 00:10:52,840 --> 00:10:55,720 Speaker 5: us about all the flows within the market. 235 00:10:57,400 --> 00:11:01,120 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 236 00:11:01,200 --> 00:11:04,280 Speaker 1: weekdays at ten am Eastern on Apple Cocklay and Android 237 00:11:04,280 --> 00:11:07,600 Speaker 1: Auto with the Bloomberg Business app. Listen on demand wherever 238 00:11:07,640 --> 00:11:10,720 Speaker 1: you get your podcasts, or watch us live on YouTube. 239 00:11:11,520 --> 00:11:13,000 Speaker 6: This is Bloomberg Intelligence Radio. 240 00:11:13,160 --> 00:11:15,120 Speaker 5: We bring you all the top news and business, economics 241 00:11:15,160 --> 00:11:17,640 Speaker 5: and finance through a lens of our Bloomberg Intelligence folks 242 00:11:17,679 --> 00:11:19,520 Speaker 5: take over two thousand companies and one hundred and thirty 243 00:11:19,559 --> 00:11:21,160 Speaker 5: industries all around the world. 244 00:11:21,320 --> 00:11:24,280 Speaker 6: We're also privileged to speak to a lot of CEOs. 245 00:11:23,800 --> 00:11:25,720 Speaker 5: From all around the world, and one of us joins 246 00:11:25,800 --> 00:11:29,520 Speaker 5: us in the studio right now, EOS Energy Enterprise. It 247 00:11:29,640 --> 00:11:33,880 Speaker 5: is a zinc powered grid scale batteries. We know we 248 00:11:33,960 --> 00:11:37,120 Speaker 5: need updates to the grid. We know we need batteries 249 00:11:37,160 --> 00:11:39,800 Speaker 5: and storage, and how we make them and where the 250 00:11:39,840 --> 00:11:43,640 Speaker 5: supply chains are are also a key. Now this company 251 00:11:43,720 --> 00:11:46,760 Speaker 5: is interesting because it has a US manufacturing plant and 252 00:11:47,000 --> 00:11:49,480 Speaker 5: supply chain. Joining us now in the studio is a CEO, 253 00:11:49,800 --> 00:11:52,280 Speaker 5: Joe Mastragello mass Strandgello. 254 00:11:52,440 --> 00:11:54,959 Speaker 6: There we go, I got it. Welcome, It's good me 255 00:11:54,960 --> 00:11:56,120 Speaker 6: withee you. 256 00:11:56,480 --> 00:11:58,679 Speaker 5: So basically you're looking at a seven hundred and twenty 257 00:11:58,679 --> 00:12:01,280 Speaker 5: percent increase in your stock in the last year. 258 00:12:02,240 --> 00:12:05,360 Speaker 6: What is a zinc powered grid scale battery. Let's start there. 259 00:12:05,480 --> 00:12:09,559 Speaker 9: Yeah, so when you think about this, think of think 260 00:12:09,600 --> 00:12:11,920 Speaker 9: about the battery you see in your car. So we 261 00:12:12,000 --> 00:12:16,439 Speaker 9: have a plastic enclosure that has the active materials of 262 00:12:16,480 --> 00:12:21,560 Speaker 9: the battery inside of it, the zinc, so zinc, bromine 263 00:12:21,640 --> 00:12:24,480 Speaker 9: based water based electrolyte base on what you're doing. You 264 00:12:24,480 --> 00:12:26,840 Speaker 9: put a charge in the zinc and the bromine separate. 265 00:12:26,880 --> 00:12:28,880 Speaker 9: When the charge goes in the zinc plates onto a 266 00:12:28,920 --> 00:12:32,960 Speaker 9: conductive plastic, the bromine is absorbed into a carbonized felt 267 00:12:33,280 --> 00:12:34,800 Speaker 9: and then you discharge it. And you can do that 268 00:12:34,880 --> 00:12:38,040 Speaker 9: anywhere from two hours up to fifteen hours. It's all 269 00:12:38,080 --> 00:12:42,360 Speaker 9: common core raw materials, highly flexible in its operation and 270 00:12:43,360 --> 00:12:45,120 Speaker 9: at scale, is very cost competitive. 271 00:12:45,800 --> 00:12:47,800 Speaker 2: All right, I'm looking you are a Puppety Trader company, 272 00:12:47,800 --> 00:12:49,960 Speaker 2: and we'll set your income statement on the Bloomberg terminal 273 00:12:50,320 --> 00:12:52,439 Speaker 2: twenty twenty four. You at like fifteen million of revenue. 274 00:12:52,520 --> 00:12:54,880 Speaker 2: Consensus looks like the analysts are looking for a one hundred 275 00:12:54,920 --> 00:12:57,600 Speaker 2: and sixty million this year, maybe four or fifty million 276 00:12:57,640 --> 00:12:58,440 Speaker 2: and twenty twenty six. 277 00:12:59,080 --> 00:13:01,200 Speaker 3: What are you guys doing helping your business? 278 00:13:01,440 --> 00:13:05,560 Speaker 9: So we are scaling up the manufacturing of our battery modules. 279 00:13:05,600 --> 00:13:09,600 Speaker 9: So basically we manufacturer battery modules that go into an enclosure. 280 00:13:09,640 --> 00:13:12,960 Speaker 9: The enclosure goes out into the into the field. It's 281 00:13:13,080 --> 00:13:15,679 Speaker 9: coupled with some energy source. It could be coupled direct 282 00:13:15,679 --> 00:13:18,320 Speaker 9: to the grid to help with grid firming or peak shaving. 283 00:13:18,400 --> 00:13:21,400 Speaker 9: It could be coupled with a power generating source wind 284 00:13:21,640 --> 00:13:25,360 Speaker 9: solar or traditional fossil fuels, or could be put and 285 00:13:25,800 --> 00:13:30,280 Speaker 9: a microgrid for a commercial and industrial application. The growth 286 00:13:30,320 --> 00:13:33,720 Speaker 9: that you're seeing is basically taking our manufacturing process and 287 00:13:33,760 --> 00:13:36,840 Speaker 9: going from a semi automated manufacturing line to a fully 288 00:13:36,880 --> 00:13:40,480 Speaker 9: automated manufacturer manufacturing. So we manufacture in Turtle Creek and 289 00:13:40,640 --> 00:13:43,840 Speaker 9: outside Pittsburgh, Pennsylvania, and our headquarters is in Edison, New Jersey. 290 00:13:43,960 --> 00:13:45,320 Speaker 8: Edison, there you go. 291 00:13:45,559 --> 00:13:48,959 Speaker 6: There is this You mentioned it's cost competitive at scale? 292 00:13:49,000 --> 00:13:49,800 Speaker 6: Are you at scale? 293 00:13:50,120 --> 00:13:52,840 Speaker 8: We're getting there. So we first the way we did 294 00:13:52,840 --> 00:13:54,120 Speaker 8: this was we. 295 00:13:54,040 --> 00:13:56,640 Speaker 9: Went in and got the assembly of the battery automated, 296 00:13:56,640 --> 00:14:00,000 Speaker 9: and now we're doing our upfront parts to automate those. 297 00:14:00,160 --> 00:14:02,680 Speaker 9: That gets our line to two gigawat hours a year 298 00:14:03,120 --> 00:14:03,679 Speaker 9: of production. 299 00:14:03,800 --> 00:14:05,040 Speaker 8: From there, you take the lines. 300 00:14:05,080 --> 00:14:07,480 Speaker 9: The way we designed this was you cut and paste 301 00:14:07,480 --> 00:14:09,760 Speaker 9: lines to expand capacity, and we have plans to get 302 00:14:09,960 --> 00:14:12,320 Speaker 9: our Pittsburgh facility, our Turtle Creek facility up to eight 303 00:14:12,320 --> 00:14:13,640 Speaker 9: gigawat hours a year in production. 304 00:14:14,080 --> 00:14:15,920 Speaker 3: Who's your customer, generally. 305 00:14:16,200 --> 00:14:20,360 Speaker 9: Type utility utilities, utility scale developers. We also have a 306 00:14:20,440 --> 00:14:23,560 Speaker 9: large segment now that's emerging with data centers for all 307 00:14:23,560 --> 00:14:24,440 Speaker 9: the energy needs they have. 308 00:14:25,520 --> 00:14:26,600 Speaker 6: So we can now I get it. 309 00:14:26,920 --> 00:14:29,800 Speaker 3: This is another play on the AI story. 310 00:14:29,880 --> 00:14:31,920 Speaker 2: Is that the investment call out there, it's one of them, 311 00:14:32,200 --> 00:14:33,120 Speaker 2: one of yes. 312 00:14:33,480 --> 00:14:34,960 Speaker 9: Well, when you think, when you think about so, it 313 00:14:35,000 --> 00:14:37,120 Speaker 9: took me a while to understand this, right, I'm a 314 00:14:37,160 --> 00:14:39,800 Speaker 9: simple guy, right, So I always saw the hey, data 315 00:14:39,800 --> 00:14:41,320 Speaker 9: centers go up and they run of the EU power. 316 00:14:41,320 --> 00:14:44,240 Speaker 9: But there's a lot of fluctuations in the power demands 317 00:14:44,240 --> 00:14:44,640 Speaker 9: that you have. 318 00:14:45,040 --> 00:14:46,400 Speaker 8: So we help smooth those out and. 319 00:14:46,320 --> 00:14:48,280 Speaker 9: We make it more efficient and give them, give them 320 00:14:48,360 --> 00:14:50,280 Speaker 9: lower cost energy to run their operation. 321 00:14:50,200 --> 00:14:51,960 Speaker 6: Which which is sort of the whole deal with intermitt 322 00:14:51,960 --> 00:14:53,520 Speaker 6: and power. You need the batteries that go with it. 323 00:14:53,680 --> 00:14:55,760 Speaker 5: You can have intermittent power, but you need the batteries 324 00:14:55,880 --> 00:14:59,280 Speaker 5: or a variety. Right, Okay, So talk to me about 325 00:14:59,320 --> 00:15:02,640 Speaker 5: then your costs. How are they looking? Are they coming down? 326 00:15:02,720 --> 00:15:05,960 Speaker 5: When you sign contracts with customers? What does that look like? 327 00:15:06,000 --> 00:15:07,640 Speaker 5: How hard is it to get to agreements? 328 00:15:07,840 --> 00:15:08,040 Speaker 8: Yeah? 329 00:15:08,120 --> 00:15:10,480 Speaker 9: So on the on the product cost side, you know, 330 00:15:10,520 --> 00:15:14,000 Speaker 9: we designed when we designed this battery as a small startup, 331 00:15:14,120 --> 00:15:17,560 Speaker 9: we only used materials that are used somewhere else. 332 00:15:17,560 --> 00:15:19,720 Speaker 8: So we basically drafted. 333 00:15:19,360 --> 00:15:22,320 Speaker 9: Off of other supply chains and said there's another supply chain, 334 00:15:22,440 --> 00:15:24,840 Speaker 9: use that material, don't put anything custom in the battery. 335 00:15:24,840 --> 00:15:26,720 Speaker 8: Because it is a small company, we can't afford it. 336 00:15:26,800 --> 00:15:29,040 Speaker 9: So that allows you as you scale, the cost comes down, 337 00:15:29,080 --> 00:15:31,640 Speaker 9: Like we've taken our cost down from launch of our 338 00:15:31,680 --> 00:15:34,600 Speaker 9: new product. The cost is down over seventy five percent 339 00:15:34,680 --> 00:15:36,960 Speaker 9: since we launched the product. When you think about on 340 00:15:37,000 --> 00:15:40,480 Speaker 9: the flipping that over to like the seal side in 341 00:15:40,520 --> 00:15:42,840 Speaker 9: the industry, you know, like like the miracle of flipping 342 00:15:42,840 --> 00:15:44,600 Speaker 9: your light switch, there's a lot of technology and a 343 00:15:44,640 --> 00:15:46,920 Speaker 9: lot of safety that goes into that. Customers want to 344 00:15:46,920 --> 00:15:48,840 Speaker 9: make sure that the product works. We've gone through the 345 00:15:48,840 --> 00:15:52,840 Speaker 9: process of qualifying that technology, improving that it works, and 346 00:15:52,880 --> 00:15:54,680 Speaker 9: showing people where it is. So like what we're doing 347 00:15:54,760 --> 00:15:57,080 Speaker 9: is we go out, we sell the product, show the 348 00:15:57,200 --> 00:15:59,160 Speaker 9: use case, and when they see the use case. 349 00:15:59,040 --> 00:16:00,480 Speaker 8: In the return, they wind up purchasing. 350 00:16:00,520 --> 00:16:03,640 Speaker 9: Right now, our backlog in order stands above six hundred 351 00:16:03,680 --> 00:16:06,640 Speaker 9: and fifty million dollars in backlog with an opportunity pipeline, 352 00:16:06,680 --> 00:16:07,720 Speaker 9: that's over fifteen billion. 353 00:16:08,200 --> 00:16:08,480 Speaker 8: Wow. 354 00:16:08,600 --> 00:16:11,200 Speaker 3: How are you capitalizing the company this growth? 355 00:16:11,600 --> 00:16:15,160 Speaker 9: So we're publicly traded. We we got an investment last 356 00:16:15,240 --> 00:16:20,960 Speaker 9: year from Service Capital, very very good strategic strategic partner 357 00:16:21,000 --> 00:16:21,880 Speaker 9: that's helping us grow. 358 00:16:22,280 --> 00:16:24,680 Speaker 8: We have a loan from the Loan Program's. 359 00:16:24,240 --> 00:16:26,360 Speaker 9: Office and the DOE which will help us expand the 360 00:16:26,400 --> 00:16:29,640 Speaker 9: manufacturing in the United States. And then we're starting to 361 00:16:29,680 --> 00:16:31,400 Speaker 9: get the company as we scale. And getting back to 362 00:16:31,440 --> 00:16:33,800 Speaker 9: Alex's question on the cost is that you know we're 363 00:16:33,800 --> 00:16:36,840 Speaker 9: going to we're targeting to fund ourselves from operations as 364 00:16:36,840 --> 00:16:38,880 Speaker 9: we get into into twenty twenty six. 365 00:16:39,120 --> 00:16:42,360 Speaker 5: So you've also had a Department of loan three hundred 366 00:16:42,360 --> 00:16:44,240 Speaker 5: and three point five million dollars to fund some new 367 00:16:44,280 --> 00:16:45,920 Speaker 5: production lines, new. 368 00:16:45,840 --> 00:16:49,320 Speaker 6: Administration, different world. Is that loan still intact? 369 00:16:49,680 --> 00:16:52,400 Speaker 8: It is? And look, I think, like anybody. 370 00:16:52,240 --> 00:16:53,720 Speaker 6: Do confidence that will stay intact? 371 00:16:54,360 --> 00:16:54,640 Speaker 8: I do? 372 00:16:54,680 --> 00:16:57,320 Speaker 9: I Well, Look, I think when you look at the company, 373 00:16:58,040 --> 00:17:01,600 Speaker 9: this company at fifty employees in twenty eighteen, we have 374 00:17:01,680 --> 00:17:05,439 Speaker 9: over six hundred. Now we created four hundred manufacturing jobs 375 00:17:05,560 --> 00:17:07,960 Speaker 9: in an area that lost a lot of manufacturing jobs. 376 00:17:08,119 --> 00:17:09,840 Speaker 8: It's right down the fairway. What we want to do 377 00:17:10,040 --> 00:17:11,359 Speaker 8: as a country. 378 00:17:11,640 --> 00:17:14,760 Speaker 2: Is, so how do you guys, what's the future of 379 00:17:14,760 --> 00:17:16,640 Speaker 2: the company just just grow internally. 380 00:17:16,720 --> 00:17:17,560 Speaker 3: Is that kind of the play? 381 00:17:18,080 --> 00:17:18,640 Speaker 8: Yeah? Maybe. 382 00:17:18,720 --> 00:17:22,199 Speaker 9: Look, I think there's a lot of opportunities, opportunities to 383 00:17:22,240 --> 00:17:23,160 Speaker 9: think a little bit bigger. 384 00:17:23,200 --> 00:17:24,400 Speaker 8: The way we thought about the strategy. 385 00:17:24,440 --> 00:17:28,359 Speaker 9: The company is a differentiated battery technology packaged really well 386 00:17:28,600 --> 00:17:31,920 Speaker 9: with software around it to optimize operations when you think 387 00:17:31,960 --> 00:17:34,240 Speaker 9: about what customers buy. There are other opportunities there, but 388 00:17:34,320 --> 00:17:37,399 Speaker 9: right now we're focused on get factory one at scale, 389 00:17:37,480 --> 00:17:39,520 Speaker 9: get factory two launch, and then look from there. 390 00:17:39,720 --> 00:17:41,800 Speaker 2: All right, great stuff, great story, Joe, appreciate you. It's 391 00:17:41,840 --> 00:17:44,560 Speaker 2: taking a few minutes coming to the studio. Joe Masta Angelo, 392 00:17:44,840 --> 00:17:47,720 Speaker 2: he's the CEO of EOS Energy Enterprises, joining us here 393 00:17:47,720 --> 00:17:50,000 Speaker 2: in our Bloomberg and Directive Broker studio talking about the 394 00:17:50,040 --> 00:17:54,200 Speaker 2: smart battery stuff. It's chemistry. I did take chemistry, but not. 395 00:17:54,200 --> 00:17:56,280 Speaker 3: Really that good at it. So that's why. 396 00:17:56,640 --> 00:17:59,000 Speaker 6: Which is girt Because you like numbers, well, like. 397 00:17:59,240 --> 00:18:01,760 Speaker 3: Wall Street numbers. Ok yeah, like big round numbers. You'll 398 00:18:01,800 --> 00:18:02,760 Speaker 3: be a bonus of X. 399 00:18:03,280 --> 00:18:04,320 Speaker 6: Okay, so that number. 400 00:18:04,880 --> 00:18:07,760 Speaker 3: See I'm charging you for this option. That is why 401 00:18:08,119 --> 00:18:08,760 Speaker 3: you get paid that. 402 00:18:10,640 --> 00:18:14,320 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us Live 403 00:18:14,400 --> 00:18:17,800 Speaker 1: weekdays at ten am Eastern on Applecarclay, and Android Auto 404 00:18:17,920 --> 00:18:20,960 Speaker 1: with the Bloomberg Business App. Listen on demand wherever you 405 00:18:21,000 --> 00:18:24,000 Speaker 1: get your podcasts, or watch us live on YouTube. 406 00:18:24,480 --> 00:18:27,879 Speaker 2: Remember before all this towers tariff in discussion over the 407 00:18:27,960 --> 00:18:30,600 Speaker 2: last several months, we were talking about something called AI 408 00:18:30,880 --> 00:18:32,760 Speaker 2: that was kind of a big topic for the market. 409 00:18:32,840 --> 00:18:35,399 Speaker 2: So we had this Deep Seek come out of China 410 00:18:35,440 --> 00:18:38,199 Speaker 2: and really throw a wrench into the narrative, which is 411 00:18:38,760 --> 00:18:41,680 Speaker 2: more tech growth, more growth overall, were riding this thing 412 00:18:41,920 --> 00:18:44,400 Speaker 2: to the moon than the Deep Seat came out. 413 00:18:44,880 --> 00:18:45,600 Speaker 3: Let's rethink this. 414 00:18:45,560 --> 00:18:45,959 Speaker 8: A little bit. 415 00:18:46,040 --> 00:18:47,960 Speaker 3: Let's go revisit that story. We can do that. 416 00:18:48,040 --> 00:18:51,120 Speaker 2: Austin Krb, Bloomberg Technology Reporter. Now he's got the big 417 00:18:51,160 --> 00:18:54,680 Speaker 2: take story here. It's in Bloomberg BusinessWeek. Deep sakes tech 418 00:18:55,000 --> 00:18:58,320 Speaker 2: madman is threatening us dominance over AI. 419 00:18:58,560 --> 00:19:00,400 Speaker 3: That got my attention. I clicked on it. 420 00:19:00,520 --> 00:19:04,800 Speaker 2: Austin, talk to us about your column here in Bloomberg BusinessWeek. 421 00:19:04,840 --> 00:19:06,200 Speaker 3: Talk to us about Deep Seek. 422 00:19:06,280 --> 00:19:10,760 Speaker 2: What do we know about them and the individual behind them? 423 00:19:11,440 --> 00:19:14,040 Speaker 10: So Deep Seek, as you'll recall, gained a lot of 424 00:19:14,040 --> 00:19:16,320 Speaker 10: attention a few months ago when it released its new 425 00:19:16,520 --> 00:19:18,920 Speaker 10: R one reasoning model as well as another one called 426 00:19:19,000 --> 00:19:21,840 Speaker 10: V three, And the big deal about this was they 427 00:19:21,960 --> 00:19:24,679 Speaker 10: sort of claimed to have trained it without access to 428 00:19:24,720 --> 00:19:27,439 Speaker 10: a lot of the most cutting edge Nvidia chips, and 429 00:19:27,480 --> 00:19:30,720 Speaker 10: they also trained their models for a lot less, at 430 00:19:30,800 --> 00:19:33,000 Speaker 10: least on the surface than a lot of the model's 431 00:19:33,440 --> 00:19:36,320 Speaker 10: equivalent models here have been trained in the US, and 432 00:19:36,359 --> 00:19:39,159 Speaker 10: that raised a lot of questions about some of the 433 00:19:39,200 --> 00:19:42,520 Speaker 10: fundamental notions about how many chips are needed to train 434 00:19:42,600 --> 00:19:44,960 Speaker 10: these big AI models and how much it's going to 435 00:19:45,000 --> 00:19:49,240 Speaker 10: cost to develop them. The reason it was also a 436 00:19:49,240 --> 00:19:51,199 Speaker 10: big deal was just because the startup was sort of 437 00:19:51,440 --> 00:19:54,720 Speaker 10: very mysterious. There had not been much written about them 438 00:19:54,720 --> 00:19:58,120 Speaker 10: before sort of January twenty twenty five, and we spent 439 00:19:58,200 --> 00:20:00,520 Speaker 10: a lot of time the last couple of months talking 440 00:20:00,520 --> 00:20:03,479 Speaker 10: to about a dozen former employees that worked for this company, 441 00:20:03,480 --> 00:20:07,000 Speaker 10: it's founder Leong Win Feg, as well as forty sources 442 00:20:07,040 --> 00:20:10,200 Speaker 10: close to the Chinese AI scene, to really just give 443 00:20:10,240 --> 00:20:12,760 Speaker 10: you a sense of how their sort of market is 444 00:20:12,800 --> 00:20:16,040 Speaker 10: developing very differently than what's happening in the US, which 445 00:20:16,080 --> 00:20:18,480 Speaker 10: is they're doing a lot more with less and sort 446 00:20:18,480 --> 00:20:21,639 Speaker 10: of just trying to innovate despite the constraints that the 447 00:20:21,720 --> 00:20:24,800 Speaker 10: US has placed on it with all its export controls. 448 00:20:25,000 --> 00:20:25,840 Speaker 6: How did he do it? 449 00:20:26,600 --> 00:20:29,600 Speaker 5: How is he able to undercut the price in such 450 00:20:29,600 --> 00:20:30,360 Speaker 5: a tremendous way. 451 00:20:31,520 --> 00:20:34,119 Speaker 10: Well, I think that's one of the big topics that 452 00:20:34,160 --> 00:20:36,320 Speaker 10: we explore in the story. We trace it actually back 453 00:20:36,320 --> 00:20:39,240 Speaker 10: to the history. Leong Win Fang had started a quant 454 00:20:39,280 --> 00:20:43,160 Speaker 10: fund back in about fifteen twenty sixteen, and you actually 455 00:20:43,200 --> 00:20:46,320 Speaker 10: see a lot of those sort of quant sensibilities looking 456 00:20:46,320 --> 00:20:50,240 Speaker 10: for efficiencies in the market, which they later applied to 457 00:20:50,720 --> 00:20:53,480 Speaker 10: their AI models. It was sort of a sort of 458 00:20:53,480 --> 00:20:55,280 Speaker 10: spin off of what they were doing with that quant 459 00:20:55,320 --> 00:20:57,840 Speaker 10: fund that became Deep Seek. One of the big things 460 00:20:57,880 --> 00:21:01,000 Speaker 10: they did was called mixture of experts, basically a lot 461 00:21:01,040 --> 00:21:03,200 Speaker 10: of the sort of when you used CHATCHVT back in 462 00:21:03,240 --> 00:21:05,480 Speaker 10: the day, you asked it a question, it activated the 463 00:21:05,640 --> 00:21:08,760 Speaker 10: entire model. So think of that like your entire brain 464 00:21:08,800 --> 00:21:11,480 Speaker 10: is activated just for the question two plus two. What 465 00:21:11,880 --> 00:21:13,639 Speaker 10: Deep Seat did that was a little bit different was 466 00:21:13,720 --> 00:21:16,160 Speaker 10: chop it up into what are called experts. So every 467 00:21:16,160 --> 00:21:18,199 Speaker 10: time you ask a question, it actually routes that to 468 00:21:18,280 --> 00:21:21,240 Speaker 10: the particular part of the brain that is expert in math, 469 00:21:21,359 --> 00:21:23,879 Speaker 10: or expert in physics, or expert in cooking, what have you. 470 00:21:24,240 --> 00:21:26,840 Speaker 10: So it's a lot more efficient approach. But the downside 471 00:21:26,880 --> 00:21:29,560 Speaker 10: is it risks hallucinating more or perhaps sending the question 472 00:21:29,600 --> 00:21:31,400 Speaker 10: to the wrong part of the brain. But that's one 473 00:21:31,400 --> 00:21:33,280 Speaker 10: of the techniques that they use to really bring this 474 00:21:33,640 --> 00:21:36,639 Speaker 10: model to life for a lot cheaper and according to 475 00:21:36,680 --> 00:21:38,400 Speaker 10: the Deep Seek, with a lot less or a lot 476 00:21:38,440 --> 00:21:41,040 Speaker 10: fewer of in vidio chips than to them a lot 477 00:21:41,080 --> 00:21:44,320 Speaker 10: of the Western players like open Ai have access to. 478 00:21:45,200 --> 00:21:47,200 Speaker 2: I guess one of the things that surprised people, maybe 479 00:21:47,520 --> 00:21:50,200 Speaker 2: scared some people, is how deep Seat was able to 480 00:21:50,240 --> 00:21:55,000 Speaker 2: make so much progress when supposedly all these Western sanctions 481 00:21:55,040 --> 00:21:57,520 Speaker 2: on technology going to China didn't really seem to slow 482 00:21:57,560 --> 00:21:58,160 Speaker 2: it down at all. 483 00:21:58,560 --> 00:22:00,680 Speaker 10: What's the status saying, I think that's that's one of 484 00:22:00,720 --> 00:22:04,160 Speaker 10: the big ironies actually, if incidentally, I had interviewed Jensen 485 00:22:04,200 --> 00:22:07,640 Speaker 10: Huang from the CEO of Nvidia in May twenty twenty three, 486 00:22:07,720 --> 00:22:10,960 Speaker 10: and that was the very month, coincidentally that you know, 487 00:22:11,000 --> 00:22:13,560 Speaker 10: on the other side of the world, China was, you know, 488 00:22:13,600 --> 00:22:16,239 Speaker 10: getting started with deep Seek, and Jensen told me at 489 00:22:16,240 --> 00:22:18,440 Speaker 10: the time, you know, one of his big concerns about 490 00:22:18,480 --> 00:22:21,920 Speaker 10: export controls is it's actually just going to incentivive Chinese 491 00:22:22,119 --> 00:22:24,440 Speaker 10: chip makers to work a lot harder to develop chips 492 00:22:24,440 --> 00:22:27,480 Speaker 10: that can compete within videas. But the other near term 493 00:22:27,520 --> 00:22:31,600 Speaker 10: threat is actually software makers sort of their constraints from 494 00:22:31,600 --> 00:22:33,440 Speaker 10: the sources that we've talked too close to Deep Seek 495 00:22:33,640 --> 00:22:37,080 Speaker 10: are actually what really drove this company to develop workarounds 496 00:22:37,280 --> 00:22:39,159 Speaker 10: do a lot more with less, and that's become a 497 00:22:39,200 --> 00:22:41,560 Speaker 10: sort of founding DNA of a lot of the Chinese 498 00:22:41,560 --> 00:22:43,439 Speaker 10: startups that we've talked to, a lot of these what 499 00:22:43,480 --> 00:22:46,880 Speaker 10: are called AI dragons across Beijing and Hangzhou that are 500 00:22:46,920 --> 00:22:50,400 Speaker 10: doing a lot more with a less access to compute. 501 00:22:50,480 --> 00:22:52,480 Speaker 10: And I think that that's you know, I think the 502 00:22:52,520 --> 00:22:54,600 Speaker 10: other sort of component of that is they almost have 503 00:22:54,720 --> 00:22:58,560 Speaker 10: this national pride that we've heard resonate throughout our interviews 504 00:22:58,720 --> 00:23:00,920 Speaker 10: that really doesn't exist in the US in quite the 505 00:23:00,960 --> 00:23:04,000 Speaker 10: same way. No one's you know, quite as excited or 506 00:23:04,119 --> 00:23:06,879 Speaker 10: you know, we don't think of Sam Altman necessarily as 507 00:23:06,920 --> 00:23:09,560 Speaker 10: a celebrity as the same way as in China. People 508 00:23:10,000 --> 00:23:13,040 Speaker 10: descend on that campus, the Deep Seek office just to 509 00:23:13,080 --> 00:23:15,280 Speaker 10: see pictures of him. It seems like a national hero 510 00:23:15,680 --> 00:23:18,840 Speaker 10: they are, just because he's over able to overcome these constraints, 511 00:23:19,359 --> 00:23:21,359 Speaker 10: And I think that's a really interesting component of the 512 00:23:21,680 --> 00:23:23,879 Speaker 10: AI scene in China, which we don't have puite in 513 00:23:23,880 --> 00:23:24,320 Speaker 10: the US. 514 00:23:24,640 --> 00:23:27,520 Speaker 5: So about forty five seconds here, what's to prevent the 515 00:23:27,560 --> 00:23:29,720 Speaker 5: AI companies here in the US doing the same thing 516 00:23:29,720 --> 00:23:30,520 Speaker 5: that deep Seek does. 517 00:23:32,440 --> 00:23:34,600 Speaker 10: There's really not I mean, that's one of the things 518 00:23:34,640 --> 00:23:37,800 Speaker 10: that you know, they did make their models open source 519 00:23:37,840 --> 00:23:40,800 Speaker 10: for so the most part they did, you know, unveil 520 00:23:40,840 --> 00:23:42,879 Speaker 10: some of their secret sauce, but they didn't quite explain 521 00:23:42,920 --> 00:23:45,600 Speaker 10: all the techniques and how they did them under the hood. 522 00:23:45,800 --> 00:23:47,320 Speaker 10: But that said, yes, I mean that was part of 523 00:23:47,320 --> 00:23:49,840 Speaker 10: the really compelling things. By making this model open source, 524 00:23:50,160 --> 00:23:52,439 Speaker 10: they really have this ethos. One of the first quotes 525 00:23:52,480 --> 00:23:56,440 Speaker 10: they put with their first public announcement was takis cheap, 526 00:23:56,480 --> 00:23:58,960 Speaker 10: show me the code. And so they have this really aggressive, 527 00:23:59,200 --> 00:24:01,280 Speaker 10: let me prove it to you attitude that I think 528 00:24:01,320 --> 00:24:04,240 Speaker 10: in the in the US space, with these proprietary models, 529 00:24:04,320 --> 00:24:07,160 Speaker 10: they're not willing to do. And I think the difference 530 00:24:07,160 --> 00:24:09,360 Speaker 10: here is that Deep Seek having an open source approach 531 00:24:09,400 --> 00:24:13,399 Speaker 10: is really putting the pressure on Google and OpenEye to 532 00:24:13,720 --> 00:24:16,960 Speaker 10: do something similar or at least undercut the costs of 533 00:24:17,000 --> 00:24:19,560 Speaker 10: their models, and you can get the same completing power 534 00:24:19,760 --> 00:24:22,080 Speaker 10: for thirty six dollars through deep Seek, as it would 535 00:24:22,119 --> 00:24:23,680 Speaker 10: cost one thousand dollars in open AI. 536 00:24:24,200 --> 00:24:25,440 Speaker 3: All right, Austin, thank you so much. 537 00:24:25,440 --> 00:24:29,480 Speaker 2: Fascinating story, Austin Car Technology Reporter four Bloomberg, Bloomberg News, 538 00:24:30,480 --> 00:24:32,320 Speaker 2: and you can read all that story on the Bloomberg 539 00:24:32,359 --> 00:24:34,240 Speaker 2: termin on Bloomberg dot com slash Big Take. 540 00:24:34,800 --> 00:24:39,480 Speaker 1: This is the Bloomberg Intelligence podcast, available on Apple, Spotify, 541 00:24:39,680 --> 00:24:43,160 Speaker 1: and anywhere else you get your podcasts. 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