1 00:00:02,520 --> 00:00:15,240 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is live 2 00:00:15,360 --> 00:00:18,800 Speaker 1: from the heart of Silicon Valley with ed La though 3 00:00:18,960 --> 00:00:20,960 Speaker 1: in San Francisco. 4 00:00:22,560 --> 00:00:24,240 Speaker 2: This is Bloomberg Tech coming up. 5 00:00:24,320 --> 00:00:27,440 Speaker 3: Rocket Lab makes its biggest bet yet, buying a Ridium 6 00:00:27,680 --> 00:00:30,639 Speaker 3: in an eight billion dollar deal to challenge SpaceX in 7 00:00:30,680 --> 00:00:31,760 Speaker 3: the orbital economy. 8 00:00:31,880 --> 00:00:33,960 Speaker 2: We'll speak with CEO Peter Beck. 9 00:00:34,440 --> 00:00:37,879 Speaker 3: Plus South Korean firms including Samsung and sk Heinix, will 10 00:00:37,920 --> 00:00:41,120 Speaker 3: spend at least eight hundred and eighty billion on chips 11 00:00:41,159 --> 00:00:44,400 Speaker 3: and data centers as the country seeks to maintain its 12 00:00:44,479 --> 00:00:48,360 Speaker 3: edge in the AI era and anthropic wins US approval 13 00:00:48,440 --> 00:00:51,960 Speaker 3: to restore some access to its Meethos five AI model 14 00:00:52,200 --> 00:00:58,120 Speaker 3: after resolving concerns about the technology's potential threats to national security. 15 00:00:58,360 --> 00:01:01,000 Speaker 3: M and A Monday is blast off into orbit here 16 00:01:01,040 --> 00:01:04,560 Speaker 3: on Bloomberg Tech. Rocket Lab making its biggest acquisition ever, 17 00:01:04,680 --> 00:01:07,959 Speaker 3: agreeing spy Iridium in an eight billion dollar deal. Is 18 00:01:08,000 --> 00:01:11,360 Speaker 3: it looks to challenge SpaceX in the rapidly growing low 19 00:01:11,400 --> 00:01:12,680 Speaker 3: Earth orbit economy. 20 00:01:12,720 --> 00:01:14,039 Speaker 2: This is how the shares are reacting. 21 00:01:14,080 --> 00:01:16,920 Speaker 3: The deal terms fifty four dollars a share in a 22 00:01:16,959 --> 00:01:21,080 Speaker 3: cash and stock transaction for the satellite telephone pioneer, valuing 23 00:01:21,160 --> 00:01:24,520 Speaker 3: a ridium at an enterprise value of about eight billion. 24 00:01:24,840 --> 00:01:26,160 Speaker 2: The offer fifty four dollars. 25 00:01:26,200 --> 00:01:29,240 Speaker 3: That's about a twenty seven percent premium. Friday's close, we 26 00:01:29,400 --> 00:01:31,840 Speaker 3: just showed a Ridium shares just a little shy of 27 00:01:31,920 --> 00:01:32,520 Speaker 3: fifty four. 28 00:01:32,600 --> 00:01:34,320 Speaker 2: But why joining us now? 29 00:01:34,600 --> 00:01:38,360 Speaker 3: Is Peter Beck, Rocket Labs, founder and CEO, live from Auckland, 30 00:01:38,400 --> 00:01:38,840 Speaker 3: New Zealand. 31 00:01:38,920 --> 00:01:42,000 Speaker 2: Let's start there. Peter, why buy iridium and why now? 32 00:01:43,360 --> 00:01:46,520 Speaker 4: Yeah, it's great to talk to you, but look, I 33 00:01:46,520 --> 00:01:49,040 Speaker 4: think it's become pretty obvious, and we've talked about it 34 00:01:49,080 --> 00:01:52,360 Speaker 4: for quite some time that the really large space companies 35 00:01:52,760 --> 00:01:54,680 Speaker 4: of the future are going to be a little bit 36 00:01:54,720 --> 00:01:57,920 Speaker 4: blurry about what a space company, even as in rocket 37 00:01:58,000 --> 00:02:01,040 Speaker 4: Lab today with a sick and most frequently lawn rocket 38 00:02:01,280 --> 00:02:04,160 Speaker 4: and we have a large spacecraft business and component's business, 39 00:02:04,520 --> 00:02:06,440 Speaker 4: but really the third letter leg of the store was 40 00:02:06,480 --> 00:02:10,320 Speaker 4: always an application. And by combining rocket Lab and Iridium 41 00:02:10,360 --> 00:02:13,720 Speaker 4: together we really make that complete picture. And what that 42 00:02:14,040 --> 00:02:17,760 Speaker 4: essentially means is we are a self launching company. And 43 00:02:17,840 --> 00:02:19,600 Speaker 4: I think if you look at other companies that have 44 00:02:19,680 --> 00:02:22,640 Speaker 4: their own rockets and can build their own satellites, it's 45 00:02:22,639 --> 00:02:23,840 Speaker 4: a pretty powerful combination. 46 00:02:24,680 --> 00:02:26,680 Speaker 3: I think, you know, very early this morning, people got 47 00:02:26,720 --> 00:02:29,240 Speaker 3: very quickly to this deeper level of vertical integration. 48 00:02:30,800 --> 00:02:32,440 Speaker 2: The basics of it. There's also the. 49 00:02:32,400 --> 00:02:36,200 Speaker 3: Idea of spectrum, right, so ridium has valuable but a 50 00:02:36,280 --> 00:02:41,360 Speaker 3: limited source of spectrum. Can you just quantify that for us, 51 00:02:41,400 --> 00:02:44,920 Speaker 3: how much spectrum we get access to and kind of 52 00:02:44,960 --> 00:02:48,600 Speaker 3: like how you leverage that to rocket labs advantage. 53 00:02:49,160 --> 00:02:50,720 Speaker 2: Yeah, look, you're exactly right. 54 00:02:50,760 --> 00:02:52,560 Speaker 4: I mean, you can have all the spacecraft and all 55 00:02:52,560 --> 00:02:54,920 Speaker 4: the rockets and the hangars you want, but if you 56 00:02:54,960 --> 00:02:59,280 Speaker 4: don't have the spectrum to actually utilize them, especially for communications. 57 00:02:59,040 --> 00:02:59,960 Speaker 2: Then it's all for nothing. 58 00:03:00,240 --> 00:03:03,079 Speaker 4: And the very unique thing about a ridium spectrum it 59 00:03:03,160 --> 00:03:06,200 Speaker 4: is it's our band spectrum. So you know, our band 60 00:03:06,360 --> 00:03:11,519 Speaker 4: is particularly effective in those very difficult and harsh conditions. 61 00:03:11,800 --> 00:03:14,520 Speaker 4: So not surprisingly, you know, Iridium has built a very 62 00:03:14,600 --> 00:03:18,920 Speaker 4: very strong business for you know, service servicing, safety critical 63 00:03:18,960 --> 00:03:23,480 Speaker 4: things and the defense uh you know, the defense network, 64 00:03:24,320 --> 00:03:27,600 Speaker 4: and so you know this this obviously enables us to 65 00:03:27,600 --> 00:03:29,360 Speaker 4: build on this. You know, it's a it's a very 66 00:03:29,440 --> 00:03:33,840 Speaker 4: established and profitable business to date, but you know, the 67 00:03:33,880 --> 00:03:37,440 Speaker 4: spectrum is an incredibly valuable asset for sure. 68 00:03:38,320 --> 00:03:41,960 Speaker 3: Peter, going forward, does rocket Lab just more generally become 69 00:03:42,040 --> 00:03:45,040 Speaker 3: a buyer of spectrum and an acquirer of assets that. 70 00:03:45,040 --> 00:03:48,480 Speaker 2: Give you access to more spectrum. No, no, not at all. 71 00:03:48,600 --> 00:03:49,400 Speaker 2: I think I mean this. 72 00:03:49,560 --> 00:03:53,680 Speaker 4: The spectrum gives us a fantastic you know, baseline and 73 00:03:54,440 --> 00:03:57,720 Speaker 4: headstart if you think about the opposite. You know, we've 74 00:03:57,720 --> 00:03:59,600 Speaker 4: always said we want to do an application that would 75 00:03:59,600 --> 00:04:02,320 Speaker 4: take years and years and years to first build the 76 00:04:02,320 --> 00:04:06,560 Speaker 4: constellations of satellites, deploy them, and then then of course 77 00:04:06,640 --> 00:04:08,000 Speaker 4: you know that's before you even see. 78 00:04:07,880 --> 00:04:09,160 Speaker 2: Your first dollar of revenue. 79 00:04:09,600 --> 00:04:13,360 Speaker 4: So this really supercharges, you know, our kind of interest 80 00:04:13,400 --> 00:04:16,400 Speaker 4: into applications, and you know, it's it's a wonderful business 81 00:04:16,440 --> 00:04:18,880 Speaker 4: to build upon. But our intention here is to to 82 00:04:19,160 --> 00:04:21,960 Speaker 4: you know, leverage the spectrum and what already are built 83 00:04:21,960 --> 00:04:24,200 Speaker 4: to provide a whole bunch of new services. 84 00:04:25,120 --> 00:04:28,520 Speaker 3: Okay, so we have launch, we have satellite manufacturing, and 85 00:04:28,560 --> 00:04:31,359 Speaker 3: now communications. One of the questions I got from the 86 00:04:31,400 --> 00:04:34,440 Speaker 3: audience is for you, Peter, is how do you take 87 00:04:34,520 --> 00:04:38,680 Speaker 3: Iridium's technology and improve it? You know, they themselves have 88 00:04:38,760 --> 00:04:43,240 Speaker 3: been very focused on chips right in their own custom electronics. 89 00:04:43,360 --> 00:04:45,080 Speaker 3: What can you do to kind of make best use 90 00:04:45,080 --> 00:04:46,359 Speaker 3: of it? But also make them better. 91 00:04:47,480 --> 00:04:47,720 Speaker 2: Yeah. 92 00:04:47,760 --> 00:04:50,159 Speaker 4: Sure, So, I mean I think, you know, just the 93 00:04:50,240 --> 00:04:53,440 Speaker 4: economics alone and that the synergies alone, when you have 94 00:04:54,240 --> 00:04:57,840 Speaker 4: you know, control over the most expensive and the most 95 00:04:57,880 --> 00:05:01,719 Speaker 4: longest lead time items being launched and spacecraft manufacture, I 96 00:05:01,720 --> 00:05:03,840 Speaker 4: think that just puts you know, that that level of evento 97 00:05:03,880 --> 00:05:07,839 Speaker 4: vertical integration just puts everybody into a totally different league. So, 98 00:05:08,200 --> 00:05:10,440 Speaker 4: you know, instead of scratching out business plans on a 99 00:05:10,480 --> 00:05:12,760 Speaker 4: whiteboard where you have to spend billions of dollars on 100 00:05:12,839 --> 00:05:15,760 Speaker 4: launch in spacecraft manufacturing, when all of a sudden that 101 00:05:15,839 --> 00:05:19,280 Speaker 4: those costs evaporate, you know, your ability to innovate and 102 00:05:20,600 --> 00:05:23,719 Speaker 4: execute different business plans becomes, you know, vastly superior. 103 00:05:25,279 --> 00:05:28,040 Speaker 3: Let's talk about the economics real quick. Is debt going 104 00:05:28,040 --> 00:05:29,919 Speaker 3: to play a role in financing this? 105 00:05:31,360 --> 00:05:32,520 Speaker 2: Yeah? Initially for sure. 106 00:05:32,960 --> 00:05:35,320 Speaker 4: You know, rocket Lab is is a very strong balance sheet, 107 00:05:36,120 --> 00:05:39,480 Speaker 4: and you know, Iridium historically has had had some debt, 108 00:05:40,160 --> 00:05:41,880 Speaker 4: but of course you know it's throwing off a lot 109 00:05:41,880 --> 00:05:44,960 Speaker 4: of cash to service it. But you know, you know, 110 00:05:45,000 --> 00:05:47,360 Speaker 4: we we have a you know, a debt bridge that 111 00:05:47,880 --> 00:05:48,880 Speaker 4: we intend to take out. 112 00:05:50,560 --> 00:05:53,400 Speaker 3: I get a lot of questions for you about Neutron 113 00:05:53,680 --> 00:05:56,839 Speaker 3: next gen launch system that you're working on. I think 114 00:05:56,880 --> 00:05:59,479 Speaker 3: one reason we get a lot of questions from the 115 00:05:59,480 --> 00:06:02,520 Speaker 3: audience now about Neutron is is that people want you 116 00:06:02,600 --> 00:06:06,039 Speaker 3: to kind of explain how dependent this this future business 117 00:06:06,080 --> 00:06:10,240 Speaker 3: line is on Neutron constellation based connectivity. 118 00:06:11,360 --> 00:06:15,560 Speaker 4: Look, I mean the Achilles Hill in space applications and 119 00:06:15,600 --> 00:06:17,080 Speaker 4: space infrastructure. 120 00:06:16,560 --> 00:06:17,400 Speaker 2: Right now is launch. 121 00:06:18,120 --> 00:06:21,120 Speaker 4: You know, launch is an incredibly valuable and rare asset. 122 00:06:21,279 --> 00:06:23,920 Speaker 4: And you know, as I mentioned before, where we launched 123 00:06:23,920 --> 00:06:26,359 Speaker 4: the Electron rocket, which is the second most frequently launched 124 00:06:26,400 --> 00:06:28,960 Speaker 4: rocket in the world, and Neutrons coming online by the 125 00:06:29,080 --> 00:06:33,159 Speaker 4: end of the year, and you know, luckily also, you 126 00:06:33,160 --> 00:06:36,120 Speaker 4: know they're ready in constellation. It's a relatively fresh constellation, 127 00:06:36,240 --> 00:06:39,159 Speaker 4: so it doesn't require immediate launch. There's a number of 128 00:06:39,240 --> 00:06:43,400 Speaker 4: years left in that constellationally over a decade, so we've 129 00:06:43,400 --> 00:06:45,440 Speaker 4: got a little bit of time to refresh the constellation. 130 00:06:45,600 --> 00:06:48,200 Speaker 4: But I mean, you know, we can throw stuff up 131 00:06:48,680 --> 00:06:52,720 Speaker 4: with either Electron or Neutron to experiment and develop new 132 00:06:52,720 --> 00:06:54,160 Speaker 4: technologies almost immediately. 133 00:06:55,200 --> 00:06:59,599 Speaker 3: Okay, the big question is rocket Lab developing the sort 134 00:06:59,640 --> 00:07:04,680 Speaker 3: of make a scale constellation specifically to take on SpaceX 135 00:07:05,160 --> 00:07:09,960 Speaker 3: Amazon as T not just direct to sell satellite based 136 00:07:10,000 --> 00:07:11,440 Speaker 3: Internet connectivity, et cetera. 137 00:07:12,960 --> 00:07:18,160 Speaker 4: Well, certainly you know Iridium has a director device system 138 00:07:18,200 --> 00:07:20,480 Speaker 4: and planning that they're rolling out later on this year. 139 00:07:21,320 --> 00:07:24,280 Speaker 4: And look, this is the very beginning for us. This 140 00:07:24,360 --> 00:07:27,360 Speaker 4: is our first foray into applications. We've talked about it 141 00:07:27,360 --> 00:07:29,240 Speaker 4: for a long time, and I think this is a 142 00:07:29,360 --> 00:07:32,920 Speaker 4: very smart deal where you know, we're not We're not 143 00:07:33,960 --> 00:07:37,720 Speaker 4: you know, acquiring a field of dreams and starting from scratch. 144 00:07:37,760 --> 00:07:41,560 Speaker 4: We are acquiring a very valuable spectrum, a profitable business. 145 00:07:42,360 --> 00:07:44,840 Speaker 4: And you know it's a very typical smart rocket Lab deal. 146 00:07:44,920 --> 00:07:47,960 Speaker 4: But you know, can our clear intention here is to 147 00:07:48,000 --> 00:07:51,640 Speaker 4: not stop we're at this acquisition and continue to grow. 148 00:07:51,680 --> 00:07:54,000 Speaker 2: For sure, a lot of folks. 149 00:07:53,720 --> 00:07:55,640 Speaker 3: This morning kind of pointed the idea that you know, 150 00:07:55,760 --> 00:07:59,520 Speaker 3: Starlink has has a lead in terms of bandwidth speed 151 00:07:59,600 --> 00:08:02,240 Speaker 3: late in see. So I think people would love to 152 00:08:02,360 --> 00:08:05,600 Speaker 3: just hear you be very granular and specific about the 153 00:08:05,680 --> 00:08:08,360 Speaker 3: niches that you can go after. What you see, it's 154 00:08:08,400 --> 00:08:11,640 Speaker 3: the total addressable market, but also like definition of that 155 00:08:11,680 --> 00:08:15,280 Speaker 3: total adjustable market that rocket Lab is like zeroed in 156 00:08:15,360 --> 00:08:17,280 Speaker 3: on as opposed to like going after all of it. 157 00:08:18,160 --> 00:08:21,120 Speaker 4: Yeah, look, I mean to your point before you know, 158 00:08:21,160 --> 00:08:23,920 Speaker 4: spectrum is key, and this spectrum, the alband spectrum, is 159 00:08:24,000 --> 00:08:27,080 Speaker 4: very very unique in the fact that it's ineffected by 160 00:08:27,320 --> 00:08:29,760 Speaker 4: weather and harsh conditions, and as a result, you know, 161 00:08:29,800 --> 00:08:33,400 Speaker 4: this alband spectrum is widely used in all the safety 162 00:08:33,440 --> 00:08:37,400 Speaker 4: critical stuff you would imagine, whether it be mariners, pilot's 163 00:08:37,520 --> 00:08:41,120 Speaker 4: defense forces. I mean, I'm my perhaps self personally, you know, 164 00:08:41,200 --> 00:08:44,760 Speaker 4: a user of the Iridium network. I'm a helicopter pilot. 165 00:08:44,760 --> 00:08:46,760 Speaker 4: When I get like ten minutes of my own time, 166 00:08:47,280 --> 00:08:49,360 Speaker 4: and you know, there's a little little thing on the 167 00:08:49,360 --> 00:08:51,240 Speaker 4: top of my desh with an Iridium logo that I 168 00:08:51,280 --> 00:08:52,720 Speaker 4: push the button that I know if I have a 169 00:08:52,720 --> 00:08:55,240 Speaker 4: super bad day and end up in the bushes, someone's 170 00:08:55,280 --> 00:08:56,960 Speaker 4: going to come and get me for sure. 171 00:08:57,520 --> 00:08:59,000 Speaker 2: So so you know. 172 00:08:59,120 --> 00:09:03,600 Speaker 4: Our focus and then you know, initially is on maintaining 173 00:09:04,040 --> 00:09:07,440 Speaker 4: you know, that super important constellation. I mean it is 174 00:09:07,640 --> 00:09:10,800 Speaker 4: completely global, so no matter where you are on the 175 00:09:10,800 --> 00:09:16,679 Speaker 4: planet ac land, where you are connected, and that's something 176 00:09:16,720 --> 00:09:19,160 Speaker 4: that really only Iridium has. 177 00:09:20,080 --> 00:09:23,559 Speaker 3: Two final quick questions. I guess that given the landscape, 178 00:09:24,160 --> 00:09:27,120 Speaker 3: the regulatory risk on this, you guys feel confident that 179 00:09:27,160 --> 00:09:29,280 Speaker 3: this deal will close and that all get done. 180 00:09:30,080 --> 00:09:32,400 Speaker 4: Yeah, No, I think I think from a regultary standpoint. 181 00:09:32,400 --> 00:09:35,800 Speaker 4: This is pretty straightforward. I mean it's it's you know, 182 00:09:36,200 --> 00:09:40,920 Speaker 4: a very very strong deal and you know, not controversial 183 00:09:40,920 --> 00:09:41,199 Speaker 4: at all. 184 00:09:42,440 --> 00:09:44,720 Speaker 3: And then just for twenty twenty six, the balance of 185 00:09:44,760 --> 00:09:48,640 Speaker 3: this year next year, has rocket Lab got a refreshed 186 00:09:48,800 --> 00:09:51,640 Speaker 3: launch target for what we could see on Electron and 187 00:09:51,640 --> 00:09:52,840 Speaker 3: then Neutron in aggregate. 188 00:09:54,280 --> 00:09:58,000 Speaker 4: Yeah, look, you know, certainly Electron is launching a crazy 189 00:09:58,000 --> 00:09:59,920 Speaker 4: flat out. You know, we just broke the world rec 190 00:10:00,040 --> 00:10:02,800 Speaker 4: called for the fastest time that someone calls up a 191 00:10:02,880 --> 00:10:05,400 Speaker 4: rocket and launchers, so we did dead and sixteen hours 192 00:10:05,440 --> 00:10:08,880 Speaker 4: forty two minutes for the Space Force, and Neutron comes 193 00:10:08,880 --> 00:10:09,960 Speaker 4: online by the end of the year. 194 00:10:11,480 --> 00:10:14,680 Speaker 3: Rocket Lub CEO Peter Beck live from Auckland, New Zealand, 195 00:10:14,720 --> 00:10:17,080 Speaker 3: where it's the middle of the night, back on Bloomberg Tech. 196 00:10:17,280 --> 00:10:18,160 Speaker 2: Thank you very much. 197 00:10:18,760 --> 00:10:20,199 Speaker 3: Sticking with M and A, I want to take a 198 00:10:20,240 --> 00:10:23,680 Speaker 3: look at shares of Comcast now up seven percent, kind 199 00:10:23,720 --> 00:10:26,880 Speaker 3: of off session highs for the company unveiled plans to 200 00:10:26,920 --> 00:10:31,280 Speaker 3: split itself in two, spinning off NBC Universal and Sky 201 00:10:31,880 --> 00:10:36,120 Speaker 3: into a standalone public company, while leaving Comcast focused on 202 00:10:36,160 --> 00:10:39,720 Speaker 3: its broadband, wireless and cable businesses. The company says the 203 00:10:39,760 --> 00:10:44,080 Speaker 3: separations designed to sharpen each business is strategic focus and 204 00:10:44,160 --> 00:10:47,720 Speaker 3: create more value for shareholders who remain shareholders in both. 205 00:10:47,720 --> 00:10:51,719 Speaker 3: It's about a year away from that vision being realized. 206 00:10:51,840 --> 00:10:52,640 Speaker 2: Okay, still ahead. 207 00:10:52,679 --> 00:10:57,040 Speaker 3: AI spending is booming, but will those investments deliver? We 208 00:10:57,080 --> 00:11:01,280 Speaker 3: are seven am Shanty Kellerman that question. This is Glomberg Tech. 209 00:11:15,760 --> 00:11:19,320 Speaker 5: South Korea has laid out an ambitious plan to cement 210 00:11:19,400 --> 00:11:23,680 Speaker 5: its status as a global tech powerhouse. Among the mega 211 00:11:23,720 --> 00:11:27,079 Speaker 5: investment pledges, Samsung Electronics and eske Heinix, the world's two 212 00:11:27,120 --> 00:11:30,840 Speaker 5: biggest memory makers, are set to build four chip fabs 213 00:11:31,080 --> 00:11:33,920 Speaker 5: in a roughly five hundred and eighteen billion dollar project 214 00:11:34,000 --> 00:11:37,880 Speaker 5: in the country's southwest. Now, Korea aims to double its 215 00:11:37,960 --> 00:11:41,920 Speaker 5: DRAM production capability in the next five years. They're also 216 00:11:41,960 --> 00:11:46,440 Speaker 5: built chip packaging facilities in the south central region, and 217 00:11:46,720 --> 00:11:49,880 Speaker 5: Korea plans to spend about six hundred and fifty billion 218 00:11:49,920 --> 00:11:54,880 Speaker 5: dollars in AI data centers by twenty thirty five. Now, 219 00:11:54,960 --> 00:11:57,840 Speaker 5: what stands out from the investment pledsure so far is 220 00:11:57,880 --> 00:12:03,120 Speaker 5: how different regions will focus on specific technologies and industries, 221 00:12:03,200 --> 00:12:07,640 Speaker 5: which underscores the need for more balanced regional development. At 222 00:12:07,679 --> 00:12:10,839 Speaker 5: the time where there are concerns that the benefits from 223 00:12:10,880 --> 00:12:14,960 Speaker 5: the AI boom are not being spread evenly across the country. 224 00:12:15,440 --> 00:12:18,840 Speaker 5: President Niche Jong said Korea needs to accelerate building its 225 00:12:18,960 --> 00:12:21,520 Speaker 5: chip base to meet demand and that Career has to 226 00:12:21,559 --> 00:12:24,720 Speaker 5: move faster than its rivals. You can almost hear the 227 00:12:24,760 --> 00:12:28,719 Speaker 5: sense of urgency for Korea to maintain its competitive edge, 228 00:12:28,760 --> 00:12:32,040 Speaker 5: and of course this comes a mad questions of sustainability 229 00:12:32,080 --> 00:12:36,080 Speaker 5: of profits as competition heats up. All in the numbers 230 00:12:36,080 --> 00:12:38,319 Speaker 5: are more or less in line with what Eskehiinix and 231 00:12:38,360 --> 00:12:43,720 Speaker 5: Samsongi Electronics have already committed to spend for twenty twenty seven, 232 00:12:44,080 --> 00:12:47,600 Speaker 5: and underscores how CAREA is looking to capitalize on the 233 00:12:47,640 --> 00:12:51,240 Speaker 5: AI boom with chips and AI front and center as 234 00:12:51,280 --> 00:12:56,400 Speaker 5: part of Korea's long term industrial strategy. Abral Hon Bloomberg 235 00:12:56,440 --> 00:12:58,000 Speaker 5: News Singapore. 236 00:12:59,360 --> 00:13:02,000 Speaker 3: Bergs Abrahan reporting that brings us to the bigger question 237 00:13:02,080 --> 00:13:05,680 Speaker 3: for global investors, can the current AI trade last joining 238 00:13:05,760 --> 00:13:08,400 Speaker 3: us now? As Shanty Kellerman, co chief investment officer at 239 00:13:08,400 --> 00:13:11,800 Speaker 3: seven i AM, who says markets have rewarded the beneficiaries 240 00:13:11,800 --> 00:13:15,840 Speaker 3: of AI spending while penalizing the company's funding. It that 241 00:13:15,960 --> 00:13:20,320 Speaker 3: dynamic isn't sustainable if those investments fail to generate real value. 242 00:13:20,360 --> 00:13:23,000 Speaker 3: Senty welcome back to the program. I think in recent 243 00:13:23,080 --> 00:13:25,120 Speaker 3: days and weeks, we've been talking about this idea that 244 00:13:25,160 --> 00:13:30,560 Speaker 3: there is a distinction between capital expenditure deployers and capital 245 00:13:30,559 --> 00:13:33,520 Speaker 3: expenditure recipients, and that seems to be very top of 246 00:13:33,520 --> 00:13:34,080 Speaker 3: mind for you. 247 00:13:35,040 --> 00:13:36,360 Speaker 2: South Korea is a case study. 248 00:13:36,800 --> 00:13:39,720 Speaker 3: But why do you think that that psychological approach to 249 00:13:39,760 --> 00:13:41,120 Speaker 3: the trade is not sustainable? 250 00:13:42,320 --> 00:13:44,440 Speaker 6: Well, I think in the long run, the investments will 251 00:13:44,440 --> 00:13:47,280 Speaker 6: stop at some point if they aren't delivering value. A 252 00:13:47,280 --> 00:13:49,600 Speaker 6: lot of those companies that are investing in AI, they 253 00:13:49,640 --> 00:13:52,559 Speaker 6: do have very long term time prizes. I don't think, 254 00:13:52,920 --> 00:13:54,120 Speaker 6: you know, they're not going to get out of the 255 00:13:54,120 --> 00:13:57,960 Speaker 6: game anytime soon, but if you start looking ahead, you know, three, five, 256 00:13:58,240 --> 00:14:00,760 Speaker 6: ten years, there will be pint where it has to 257 00:14:00,800 --> 00:14:03,360 Speaker 6: deliver returns. I think we're at the point where you're 258 00:14:03,360 --> 00:14:06,040 Speaker 6: starting to see that across the corporate world. You're starting 259 00:14:06,040 --> 00:14:09,200 Speaker 6: to see more companies focus on what's the ROI from 260 00:14:09,360 --> 00:14:12,480 Speaker 6: an adoption. So I think there's you know, there's certainly risks, 261 00:14:12,520 --> 00:14:14,760 Speaker 6: but I think the early signs that it can deliver 262 00:14:14,880 --> 00:14:15,560 Speaker 6: value were there. 263 00:14:17,000 --> 00:14:17,880 Speaker 2: What is A seven. 264 00:14:17,920 --> 00:14:20,880 Speaker 3: IM's attitude towards those South Korean names. I mean principally 265 00:14:20,920 --> 00:14:24,240 Speaker 3: it's Samsung and Skhinex, but the cost b had had 266 00:14:24,280 --> 00:14:27,640 Speaker 3: some real outperformance so far this year on the idea 267 00:14:27,640 --> 00:14:29,440 Speaker 3: that a lot in the AI trade is happening in 268 00:14:29,440 --> 00:14:30,000 Speaker 3: South Korea. 269 00:14:31,320 --> 00:14:33,640 Speaker 6: Yeah, I think a really interesting demic has been how 270 00:14:33,840 --> 00:14:37,200 Speaker 6: emerging markets has kind of been a beneficiary of the 271 00:14:37,240 --> 00:14:40,280 Speaker 6: AI trade, where historically the US and emerging market equities 272 00:14:40,280 --> 00:14:43,080 Speaker 6: were a little bit uncorrelated. So that's been to change 273 00:14:43,080 --> 00:14:46,760 Speaker 6: for this year. In our strategy, we run strategies they're 274 00:14:46,760 --> 00:14:49,560 Speaker 6: linked to different global sectors as well as doing general 275 00:14:49,560 --> 00:14:53,040 Speaker 6: acid allocation, and so we've had more in technology companies 276 00:14:53,080 --> 00:14:56,480 Speaker 6: for some time, and also communications services, so things like 277 00:14:56,640 --> 00:14:59,520 Speaker 6: Meta and Alphabet have done really well. I think what 278 00:14:59,560 --> 00:15:01,440 Speaker 6: we see we look at it is though even though 279 00:15:01,440 --> 00:15:04,040 Speaker 6: we've had a lot of growth, the valuations are still 280 00:15:04,160 --> 00:15:07,920 Speaker 6: fairly attractive because earnings growth has been so strong. So 281 00:15:07,960 --> 00:15:11,600 Speaker 6: you throw together the momentum the earnings growth, there's certainly 282 00:15:11,600 --> 00:15:14,320 Speaker 6: our risk and we've had so much momentum so quickly, 283 00:15:14,840 --> 00:15:17,440 Speaker 6: but when you look at those quantitative factors, it's still 284 00:15:17,440 --> 00:15:20,240 Speaker 6: a pretty strong case to be in technology stocks. 285 00:15:21,160 --> 00:15:23,440 Speaker 3: That's the other story that we've been really focused in. 286 00:15:23,440 --> 00:15:26,760 Speaker 3: Like Micron as a case study, has had really interesting 287 00:15:26,800 --> 00:15:30,880 Speaker 3: performance but actually trades at a pretty reasonable multiple. Sk 288 00:15:31,040 --> 00:15:33,880 Speaker 3: heinez looking at a US listing in part because they 289 00:15:33,920 --> 00:15:37,360 Speaker 3: want to bridge the valuation gap with Micron. 290 00:15:37,640 --> 00:15:38,960 Speaker 2: Could you talk a little bit more about that. 291 00:15:40,360 --> 00:15:42,200 Speaker 6: Yeah, I think, you know, if you look at the 292 00:15:42,320 --> 00:15:45,960 Speaker 6: Russell one thousand value index, that's now like tech is 293 00:15:45,960 --> 00:15:47,880 Speaker 6: the second highest weight and it's got you know, some 294 00:15:47,920 --> 00:15:50,840 Speaker 6: of those companies you're like, I think Microns in it, Intel, 295 00:15:51,000 --> 00:15:53,400 Speaker 6: you know, So I think kind of those distinctions between 296 00:15:53,440 --> 00:15:56,320 Speaker 6: value and growth don't work so well anymore because you've 297 00:15:56,360 --> 00:15:59,440 Speaker 6: had huge growth, but also that earnings growth. I think 298 00:15:59,520 --> 00:16:02,760 Speaker 6: the discount on valuations from the US versus other places 299 00:16:02,840 --> 00:16:04,720 Speaker 6: is you know, is a perpetual thing, and some of 300 00:16:04,720 --> 00:16:07,080 Speaker 6: that will be linked to corporate governance that you have 301 00:16:07,240 --> 00:16:09,760 Speaker 6: where there probably is still you know, more that can 302 00:16:09,800 --> 00:16:11,960 Speaker 6: be done in some of those nations like Korea and 303 00:16:12,040 --> 00:16:15,040 Speaker 6: Japan who have been improving dramatically, But some of it's 304 00:16:15,040 --> 00:16:18,120 Speaker 6: also about where the capital is and where people want 305 00:16:18,120 --> 00:16:19,240 Speaker 6: to allocate their money to. 306 00:16:19,760 --> 00:16:23,640 Speaker 3: So, yeah, a lot of new equities fooding the market, 307 00:16:23,680 --> 00:16:26,160 Speaker 3: but it's not just IPOs, right, And later in the program, 308 00:16:26,240 --> 00:16:28,200 Speaker 3: we're going to look at the data to kind of 309 00:16:28,200 --> 00:16:31,200 Speaker 3: where we are so far in twenty twenty six. SpaceX 310 00:16:31,240 --> 00:16:34,640 Speaker 3: the easy example. But what do you make of that dynamic, 311 00:16:34,880 --> 00:16:39,000 Speaker 3: the relationship between wall streets fundraising activity in public markets 312 00:16:39,000 --> 00:16:42,080 Speaker 3: and like what is happening in private markets still being 313 00:16:42,160 --> 00:16:42,880 Speaker 3: pretty insane. 314 00:16:44,360 --> 00:16:46,520 Speaker 6: Yeah, I mean there is still a lot of cash 315 00:16:46,640 --> 00:16:49,280 Speaker 6: on the sidelines in private markets, and that is cash 316 00:16:49,360 --> 00:16:52,280 Speaker 6: you know, that could go into private markets or public markets. 317 00:16:52,760 --> 00:16:54,760 Speaker 6: The amount of money that's kind of waiting in the 318 00:16:54,800 --> 00:16:57,040 Speaker 6: pipeline for the IPOs is you know, if it does 319 00:16:57,080 --> 00:16:59,760 Speaker 6: all come through, will be one of the biggest issue, 320 00:16:59,760 --> 00:17:01,880 Speaker 6: you know, years ever. And I think we need to 321 00:17:01,960 --> 00:17:05,040 Speaker 6: indedicake account that people will put cash into those but 322 00:17:05,080 --> 00:17:07,240 Speaker 6: they probably will also reduce a bit of what they're 323 00:17:07,280 --> 00:17:09,919 Speaker 6: already holding to make space for those things. So I 324 00:17:09,920 --> 00:17:12,440 Speaker 6: think that's a little bit of a downward pressure on markets. 325 00:17:12,640 --> 00:17:14,320 Speaker 6: And I think it's also you know, keeps in mind 326 00:17:14,359 --> 00:17:16,879 Speaker 6: that I think investors will scrutinize some of these deals. 327 00:17:17,200 --> 00:17:19,159 Speaker 6: I think the interesting thing is less some of the 328 00:17:19,200 --> 00:17:22,000 Speaker 6: equity issuance and more the bond issuance with. 329 00:17:22,000 --> 00:17:23,080 Speaker 2: The equity issuance, you. 330 00:17:23,040 --> 00:17:24,760 Speaker 6: Do have a bit of you know, you can have 331 00:17:24,800 --> 00:17:28,359 Speaker 6: retail fanfare around it. With the bond issuance, there's no 332 00:17:28,560 --> 00:17:30,959 Speaker 6: you know, index inclusion. It's just kind of you know, 333 00:17:31,080 --> 00:17:33,520 Speaker 6: looking at the credit risk. So I think that's been interesting, 334 00:17:33,600 --> 00:17:36,400 Speaker 6: the divergence between performs we've had some of the bond 335 00:17:36,440 --> 00:17:38,160 Speaker 6: issuance and also the equity. 336 00:17:37,840 --> 00:17:43,440 Speaker 3: Issuance, SpaceX bond market, Nvidia bond market. Are you saying 337 00:17:43,480 --> 00:17:45,320 Speaker 3: that that's something that worries you or you think that's 338 00:17:46,200 --> 00:17:49,320 Speaker 3: a good mechanism for funding what's happening in AI. 339 00:17:50,640 --> 00:17:52,760 Speaker 6: I think right now the amount of funding that's going 340 00:17:52,800 --> 00:17:56,440 Speaker 6: to bond markets is very healthy. It's by no means overstretched, 341 00:17:56,760 --> 00:17:59,440 Speaker 6: and a lot of those companies have very solid long 342 00:17:59,560 --> 00:18:01,680 Speaker 6: term cash flows. I think more what I'm saying is 343 00:18:01,680 --> 00:18:03,199 Speaker 6: if you look at I think some of the equity 344 00:18:03,200 --> 00:18:05,320 Speaker 6: markets can get caught up in a bit of the hype, 345 00:18:05,440 --> 00:18:07,960 Speaker 6: whereas the bond markets you have a bit less of that, 346 00:18:08,000 --> 00:18:10,159 Speaker 6: and I think you get sometimes a truer picture of 347 00:18:10,200 --> 00:18:10,800 Speaker 6: the outlook. 348 00:18:11,920 --> 00:18:14,600 Speaker 3: Chanty Kelleman of seven Am back on Bloomberg Tech, Thank 349 00:18:14,640 --> 00:18:18,440 Speaker 3: you very much. Indeed, coming up, Bob Eiger and Joshua 350 00:18:18,560 --> 00:18:22,080 Speaker 3: Kushner a considering a bid for an NBA expansion team 351 00:18:22,119 --> 00:18:24,720 Speaker 3: in Las Vegas, got the Bloomberg exclusive. 352 00:18:24,760 --> 00:18:25,920 Speaker 2: Next, This is Bloomberg Tech. 353 00:18:39,160 --> 00:18:41,600 Speaker 7: It's time now for talking tech. I'm your Hi, Rahna 354 00:18:41,600 --> 00:18:45,240 Speaker 7: and first up. Millennium Management is stepping up its AI drive, 355 00:18:45,320 --> 00:18:49,040 Speaker 7: launching a dedicated lab to accelerate early access to cutting 356 00:18:49,119 --> 00:18:51,760 Speaker 7: edge tech tools. A new lab will go live over 357 00:18:51,800 --> 00:18:55,840 Speaker 7: the next few weeks and coincides with weeping changes in 358 00:18:55,880 --> 00:18:59,840 Speaker 7: the hedge fund industry to adopt AI capabilities. Plus where 359 00:19:00,440 --> 00:19:03,200 Speaker 7: is taking a heavy hit to grow a global footprint. 360 00:19:03,280 --> 00:19:06,760 Speaker 7: The Telecom Giants projects his second quarter losses up to 361 00:19:06,800 --> 00:19:10,080 Speaker 7: eight hundred million dollars after striking a deal with the 362 00:19:10,200 --> 00:19:14,359 Speaker 7: UK's BT Group to merge their international businesses. The new 363 00:19:14,560 --> 00:19:17,440 Speaker 7: four billion dollar joint venture includes a six hundred and 364 00:19:17,480 --> 00:19:22,200 Speaker 7: twenty five million dollar equalization payment from Verizon to BT 365 00:19:23,240 --> 00:19:27,280 Speaker 7: and Hollywood animation industry is facing an AI reckoning. Some 366 00:19:27,320 --> 00:19:31,320 Speaker 7: predict the tech will elevate storytelling, but others expressed it 367 00:19:31,320 --> 00:19:34,919 Speaker 7: will slash production costs by thirty to ninety percent and 368 00:19:35,000 --> 00:19:39,760 Speaker 7: eliminate many jobs. Leading major players like Disney, DreamWorks and 369 00:19:39,880 --> 00:19:41,680 Speaker 7: Netflix proceed with caution. 370 00:19:42,200 --> 00:19:42,280 Speaker 8: Ed. 371 00:19:43,040 --> 00:19:44,200 Speaker 2: So we're really focused right now. 372 00:19:44,320 --> 00:19:48,359 Speaker 3: Media entertainment and sports former Disney CEO Bob Ayga and 373 00:19:48,480 --> 00:19:52,440 Speaker 3: Thrive Capital founder Joshua Kushner the joining forces the two 374 00:19:52,840 --> 00:19:56,159 Speaker 3: discussing making a bid for an MBA expansion team in 375 00:19:56,240 --> 00:20:00,000 Speaker 3: Las Vegas. According to sources, Clombergs and Tashi and Mascarnis 376 00:20:00,440 --> 00:20:02,960 Speaker 3: break the story. Okay, give me the details here. This 377 00:20:03,080 --> 00:20:07,120 Speaker 3: is interesting. I don't know the historic relationship between mister 378 00:20:07,200 --> 00:20:08,840 Speaker 3: Kushner and bobaiga. 379 00:20:09,920 --> 00:20:11,639 Speaker 2: An expansion team. What have you learned? 380 00:20:12,040 --> 00:20:14,600 Speaker 9: Yeah, I mean absolutely not on my bingo board this year. 381 00:20:14,680 --> 00:20:18,280 Speaker 9: But this is a really interesting extension of a relationship 382 00:20:18,280 --> 00:20:20,640 Speaker 9: that the two have actually had for quite some time. 383 00:20:20,720 --> 00:20:24,200 Speaker 9: So Bob Iger has previously been a venture partner at 384 00:20:24,200 --> 00:20:28,359 Speaker 9: Thrive in between both of his stints as CEO of 385 00:20:28,520 --> 00:20:32,080 Speaker 9: Walt Disney Company. He stepped down from that CEO role 386 00:20:32,119 --> 00:20:35,760 Speaker 9: earlier this year and rejoined Thrive as an advisor. Now 387 00:20:35,760 --> 00:20:40,120 Speaker 9: we're seeing both Bob and Josh team up together as 388 00:20:40,160 --> 00:20:42,399 Speaker 9: they discuss whether they want to make a bid for 389 00:20:42,600 --> 00:20:45,600 Speaker 9: the NBA expansion team in Las Vegas through Thrive Eternal, 390 00:20:45,640 --> 00:20:48,760 Speaker 9: another new effort which Bob is advising on, and the 391 00:20:48,800 --> 00:20:51,720 Speaker 9: whole idea between Thrive Eternal is that they want to 392 00:20:51,760 --> 00:20:57,280 Speaker 9: invest in iconic franchises, cultural assets, everything from collectibles. Two 393 00:20:57,400 --> 00:20:58,720 Speaker 9: sports teams in this case. 394 00:20:59,520 --> 00:21:03,879 Speaker 3: Okay, look, I am a fair weather Warriors fan at best. 395 00:21:03,920 --> 00:21:06,919 Speaker 3: The Bleed Tech team in New York is still pretty 396 00:21:07,000 --> 00:21:10,119 Speaker 3: high on the NIXT success. What I do know is 397 00:21:10,119 --> 00:21:13,520 Speaker 3: that the NBA has looked at the idea of a 398 00:21:13,560 --> 00:21:15,879 Speaker 3: potential franchise expansion in Las Vegas. 399 00:21:15,920 --> 00:21:17,880 Speaker 2: Where is that process at. 400 00:21:18,920 --> 00:21:21,840 Speaker 9: Yeah, I mean this is something that they have approved, 401 00:21:22,040 --> 00:21:24,280 Speaker 9: you know, the actual expiration of doing this. And so 402 00:21:24,320 --> 00:21:27,080 Speaker 9: this would mean that they would be expanding the NBA 403 00:21:27,160 --> 00:21:31,119 Speaker 9: to include teams in both Las Vegas and Seattle. In 404 00:21:31,200 --> 00:21:35,360 Speaker 9: this case, the bid is for a majority investment. It's 405 00:21:35,440 --> 00:21:38,399 Speaker 9: yet to be submitted according to my sources, but this 406 00:21:38,680 --> 00:21:41,960 Speaker 9: is an attempt at taking a controlling stake in that 407 00:21:42,040 --> 00:21:45,080 Speaker 9: potential team. And what's also interesting here is it's not 408 00:21:45,840 --> 00:21:49,560 Speaker 9: Thrive's first investment in sports. Earlier this year, we reported 409 00:21:49,640 --> 00:21:53,040 Speaker 9: that Thrive was making a smaller investment in the San 410 00:21:53,040 --> 00:21:55,240 Speaker 9: Francisco Giants, a little bit closer to home for both 411 00:21:55,240 --> 00:21:57,200 Speaker 9: of us, and so this is, you. 412 00:21:57,160 --> 00:21:58,480 Speaker 2: Know, a bigger deal. 413 00:21:58,359 --> 00:22:01,800 Speaker 9: Literally, but really it kind of show is interesting given 414 00:22:01,840 --> 00:22:03,720 Speaker 9: that they have made a few bats in sports. 415 00:22:05,240 --> 00:22:06,080 Speaker 2: Just to point out that. 416 00:22:06,160 --> 00:22:09,760 Speaker 3: For the story, representatives for Thrive Capital and Bobaiger declined 417 00:22:09,760 --> 00:22:11,840 Speaker 3: to comment, but I we'd check out and Attasha's story 418 00:22:12,040 --> 00:22:14,600 Speaker 3: one of the most read things today on bloombergs on 419 00:22:14,600 --> 00:22:18,680 Speaker 3: attashm mascarinas, thank you very much. Coming up, SpaceX helps 420 00:22:18,720 --> 00:22:21,520 Speaker 3: hower a record year for Wall Street fundraising. We look 421 00:22:21,560 --> 00:22:25,960 Speaker 3: at how AI is driving the deal boom. We're about 422 00:22:25,960 --> 00:22:29,119 Speaker 3: halfway through the program and right now we're in a 423 00:22:29,160 --> 00:22:32,480 Speaker 3: place where market's filling pretty good. Now's that one hundred 424 00:22:32,560 --> 00:22:36,720 Speaker 3: upper percentage point. Semiconductors up almost a percentage point. Just 425 00:22:36,720 --> 00:22:41,520 Speaker 3: to quick check on bitcoin, fifty nine dollars per token 426 00:22:41,960 --> 00:22:44,560 Speaker 3: a little softer, but there's nothing in the news cycle 427 00:22:44,600 --> 00:22:47,560 Speaker 3: really driving that. As I said, it's half time. We'll 428 00:22:47,560 --> 00:22:50,280 Speaker 3: be right back from San Francisco. This is Bloomberg Tech. 429 00:22:57,960 --> 00:22:59,920 Speaker 3: Welcome back to Bloomberg Tech. I want to get back 430 00:22:59,920 --> 00:23:03,600 Speaker 3: to that Comcast deal. So Comcast is going to spin 431 00:23:03,680 --> 00:23:09,240 Speaker 3: off NBC Universal and Sky, basically separating into two separate 432 00:23:09,280 --> 00:23:11,400 Speaker 3: public company. This is something that's about a year out 433 00:23:11,680 --> 00:23:14,520 Speaker 3: and existing investors will have exposure to both. But it's 434 00:23:14,560 --> 00:23:17,680 Speaker 3: really interesting to see how the streets. 435 00:23:17,359 --> 00:23:18,159 Speaker 2: Kind of reacting to this. 436 00:23:18,200 --> 00:23:21,040 Speaker 3: In fact, Bloomberg Intelligence and our own analysts kind of 437 00:23:21,080 --> 00:23:24,359 Speaker 3: see this as something that opens up and sets the 438 00:23:24,400 --> 00:23:28,360 Speaker 3: stage for more M and A in the cable media space. Right, 439 00:23:28,400 --> 00:23:31,359 Speaker 3: so you have a separate entity that is focused on 440 00:23:31,800 --> 00:23:35,000 Speaker 3: the media business NBC Universal, while Comcast doubles down on 441 00:23:35,040 --> 00:23:37,320 Speaker 3: more of that kind of legacy infrastructure business and as 442 00:23:37,480 --> 00:23:42,560 Speaker 3: Hetherranger Nation rights, the transaction also enhances strategic flexibility and 443 00:23:42,600 --> 00:23:45,560 Speaker 3: can pave the way for M and A. Interesting, it's 444 00:23:45,640 --> 00:23:48,200 Speaker 3: kind of like what happens next. Let's take a look 445 00:23:48,200 --> 00:23:50,960 Speaker 3: at today's big number as well, five hundred and seventy 446 00:23:51,000 --> 00:23:54,680 Speaker 3: billion dollars. That's the amount of market value Microsoft is 447 00:23:54,720 --> 00:23:57,600 Speaker 3: set to shed in the month of June, with the 448 00:23:57,640 --> 00:24:00,280 Speaker 3: stock at one point down as much as twenty percent 449 00:24:00,640 --> 00:24:03,119 Speaker 3: during the month. So right now it's on track for 450 00:24:03,160 --> 00:24:07,320 Speaker 3: its worst monthly drop since December of two thousand, or 451 00:24:07,800 --> 00:24:11,360 Speaker 3: its worst month of performance in almost twenty six years. 452 00:24:11,840 --> 00:24:12,040 Speaker 2: One. 453 00:24:12,080 --> 00:24:15,480 Speaker 3: We're tracking a wave of fundraising tied to the AI 454 00:24:15,560 --> 00:24:19,760 Speaker 3: buildout has pushed us IPOs and share sales to record 455 00:24:19,760 --> 00:24:22,560 Speaker 3: two hundred and fifty one billion dollars this year so far, 456 00:24:23,000 --> 00:24:26,560 Speaker 3: blockbuster offerings from SpaceX and Alphabet have led the way, 457 00:24:26,560 --> 00:24:30,119 Speaker 3: and bankers say there's plenty more in the pipeline for 458 00:24:30,200 --> 00:24:34,199 Speaker 3: more most Baily Lipshaltzer here on the IPO inequity beat, like, 459 00:24:34,400 --> 00:24:36,440 Speaker 3: the big picture story is one we've talked about, right, 460 00:24:36,640 --> 00:24:40,240 Speaker 3: lots of equity is going to flood the market. But 461 00:24:40,840 --> 00:24:42,720 Speaker 3: the line of what I just read that it's interesting 462 00:24:42,960 --> 00:24:45,480 Speaker 3: is that you know, the bankers hope and the bankers 463 00:24:45,520 --> 00:24:46,879 Speaker 3: see that there's more to come. 464 00:24:47,160 --> 00:24:50,040 Speaker 10: What do we know bankers get paid to be optimistices, 465 00:24:50,119 --> 00:24:51,720 Speaker 10: so we got to take everything they say with a 466 00:24:51,760 --> 00:24:54,119 Speaker 10: grain of salt. But when you look at the record 467 00:24:54,240 --> 00:24:56,840 Speaker 10: year so far, the record half we've already seen again 468 00:24:57,200 --> 00:24:59,600 Speaker 10: north of two hundred and fifty one billion dollars raised, 469 00:24:59,640 --> 00:25:03,120 Speaker 10: that doesn't even fully encapsulate that Google raise because it's 470 00:25:03,119 --> 00:25:05,760 Speaker 10: an ATM, which means at the market offering, which it 471 00:25:05,840 --> 00:25:08,400 Speaker 10: technically hasn't been fully penciled in, so that number should 472 00:25:08,440 --> 00:25:11,000 Speaker 10: be even larger. Again, we're looking at numbers we have 473 00:25:11,119 --> 00:25:14,320 Speaker 10: never seen before, beating twenty twenty one. The expectation for 474 00:25:14,520 --> 00:25:17,480 Speaker 10: the weeks and months ahead, s k Heiinez expected in 475 00:25:17,480 --> 00:25:20,680 Speaker 10: the coming weeks that's going to be potentially thirty billion 476 00:25:20,720 --> 00:25:22,960 Speaker 10: dollar fundraise here in the US, So that'll take the 477 00:25:22,960 --> 00:25:23,760 Speaker 10: baton and get. 478 00:25:23,680 --> 00:25:25,119 Speaker 2: Us off to a quick start in July. 479 00:25:25,520 --> 00:25:27,800 Speaker 10: Expectations do broaden out quite a bit as we look 480 00:25:27,840 --> 00:25:31,000 Speaker 10: for the likes of private equity, maybe in the retail 481 00:25:31,000 --> 00:25:34,080 Speaker 10: consumer space. Jersey Mics is a name that continues to 482 00:25:34,119 --> 00:25:36,600 Speaker 10: come to mind, but certainly continuing to keep an eye 483 00:25:36,680 --> 00:25:40,120 Speaker 10: on anything and everything around artificial intelligence. I also want 484 00:25:40,119 --> 00:25:42,119 Speaker 10: to call out that we're expecting c Square, which is 485 00:25:42,160 --> 00:25:44,919 Speaker 10: a data center company, to kickstart its process on the 486 00:25:44,920 --> 00:25:45,520 Speaker 10: other side. 487 00:25:45,320 --> 00:25:46,399 Speaker 2: Of the fourth of July holiday. 488 00:25:46,440 --> 00:25:49,320 Speaker 3: It's gonna say thank you for bringing it back to tech, 489 00:25:49,359 --> 00:25:50,600 Speaker 3: bringing Jersey. 490 00:25:50,240 --> 00:25:51,960 Speaker 2: Mics to the show. Unbelievable. 491 00:25:53,200 --> 00:25:55,200 Speaker 3: Part of it is like we're showing this amazing chart. 492 00:25:55,920 --> 00:25:58,560 Speaker 3: Let's go back to the number so far in twenty 493 00:25:58,600 --> 00:26:02,200 Speaker 3: twenty six. This is a big number. This is something 494 00:26:02,240 --> 00:26:05,680 Speaker 3: that we have not seen for quite a few number 495 00:26:05,720 --> 00:26:06,600 Speaker 3: of years now. 496 00:26:06,920 --> 00:26:09,159 Speaker 10: No, we've never seen it, and I think when you 497 00:26:09,200 --> 00:26:12,399 Speaker 10: look at the breadth So we're talking about obviously the 498 00:26:12,440 --> 00:26:16,159 Speaker 10: big fundraise from SpaceX again, record setting number kind of 499 00:26:16,200 --> 00:26:19,959 Speaker 10: bolsters this as Kahinich would potentially be the second largest 500 00:26:20,000 --> 00:26:23,399 Speaker 10: IPO ever. So these would be two deals in consecutive months, 501 00:26:23,400 --> 00:26:25,960 Speaker 10: something we've never seen before. Again, going back to the 502 00:26:26,000 --> 00:26:29,720 Speaker 10: broader equity issuance, whether that's regular way equity or convertible debt, 503 00:26:29,760 --> 00:26:34,040 Speaker 10: that big fundraising from Alphabet potentially puts the pressure on 504 00:26:34,119 --> 00:26:37,680 Speaker 10: other hyperscalers to sell equity, so diverting away from debt, 505 00:26:37,680 --> 00:26:39,520 Speaker 10: which has kind of been the bread and butter for 506 00:26:39,640 --> 00:26:42,840 Speaker 10: the build out of this AI boom, this data center boom, 507 00:26:42,840 --> 00:26:45,479 Speaker 10: and the expectations that there will be more lying on 508 00:26:45,520 --> 00:26:47,639 Speaker 10: the other side of the midway point again on the 509 00:26:47,640 --> 00:26:49,639 Speaker 10: other side of the fourth of July holiday. Again, just 510 00:26:49,640 --> 00:26:52,119 Speaker 10: want to call out things have been working across the 511 00:26:52,160 --> 00:26:54,959 Speaker 10: AI ecosystem Sarah Bras again not really trading as well 512 00:26:55,000 --> 00:26:57,240 Speaker 10: as many had expected, or it certainly was day one, 513 00:26:57,320 --> 00:26:59,600 Speaker 10: But that's a north of six billion dollar IPO, and 514 00:26:59,640 --> 00:27:01,240 Speaker 10: then you just go down the list, there's about a 515 00:27:01,280 --> 00:27:04,800 Speaker 10: dozen raising a billion dollars or more. Bankers expect that 516 00:27:05,000 --> 00:27:07,119 Speaker 10: number to continue and be matched in the second half, 517 00:27:07,200 --> 00:27:10,280 Speaker 10: and even some of these conversations with these big bankers 518 00:27:10,280 --> 00:27:12,160 Speaker 10: at the likes of a Morgan Stanley or Goldman Sachs, 519 00:27:12,240 --> 00:27:14,879 Speaker 10: they expect the third quarter to be critical. As we 520 00:27:15,040 --> 00:27:18,160 Speaker 10: kind of get towards potentially Anthropic coming in the fall 521 00:27:18,240 --> 00:27:18,879 Speaker 10: towards year. 522 00:27:18,840 --> 00:27:22,280 Speaker 2: End the most faded Upsheltz, thank you very much. 523 00:27:22,359 --> 00:27:26,400 Speaker 3: Now coming up, and Thropic wins US approval to restore 524 00:27:26,560 --> 00:27:30,840 Speaker 3: some access to its powerful Mythos five AI model. 525 00:27:30,920 --> 00:27:31,680 Speaker 2: We'll discuss what. 526 00:27:31,560 --> 00:27:35,040 Speaker 3: That means for model development and AI regulation with Hugging 527 00:27:35,080 --> 00:27:36,800 Speaker 3: Face CEO clemd Along. 528 00:27:36,880 --> 00:27:39,120 Speaker 2: That's next. This is Bloomberg Tech. 529 00:27:47,680 --> 00:27:51,360 Speaker 3: Late on Friday, and Thropic won US approval to restore 530 00:27:51,480 --> 00:27:54,919 Speaker 3: some access to its powerful Mythos five AI. 531 00:27:55,160 --> 00:27:55,440 Speaker 2: Now. 532 00:27:55,480 --> 00:27:58,920 Speaker 3: You may remember two weeks ago the US government abruptly 533 00:27:58,960 --> 00:28:02,840 Speaker 3: barred Anthropic from letting foreign nationals have access to its 534 00:28:02,880 --> 00:28:07,760 Speaker 3: most powerful models over cybersecurity concerns. In response, and Thropic 535 00:28:07,840 --> 00:28:11,800 Speaker 3: disabled all access to those models. And right now, after 536 00:28:12,000 --> 00:28:17,280 Speaker 3: furious negotiations, Mythos five is back, sort of. In a 537 00:28:17,359 --> 00:28:20,800 Speaker 3: letter to the company seen by Bloomberg News, Commerce Secretary 538 00:28:20,880 --> 00:28:23,679 Speaker 3: Howard Lutnick wrote the model could be released to quote 539 00:28:23,960 --> 00:28:29,240 Speaker 3: certain trusted partners. The Fable five model or variant wasn't mentioned. 540 00:28:29,800 --> 00:28:32,760 Speaker 3: Let's get into it, starting with the business impact. Teresa Payton. 541 00:28:33,160 --> 00:28:36,280 Speaker 3: She is the CEO of Cybersecurity Advisor for Delice Solutions 542 00:28:36,560 --> 00:28:39,160 Speaker 3: and a former White House CEO during. 543 00:28:38,920 --> 00:28:40,360 Speaker 2: The George W. Bush administration. 544 00:28:40,480 --> 00:28:43,920 Speaker 3: I rely on both your expertise in industry and experience 545 00:28:44,000 --> 00:28:47,480 Speaker 3: of being on the government side of the table. The 546 00:28:47,600 --> 00:28:53,360 Speaker 3: June twelfth Export Control the parameters of it are very interesting, 547 00:28:53,400 --> 00:28:55,120 Speaker 3: and maybe you can unpack them a little. But what 548 00:28:55,160 --> 00:28:58,800 Speaker 3: they said was there's been significant progress in risk mitigation, 549 00:28:59,320 --> 00:29:02,360 Speaker 3: and I'm finding out to understand what that progress looks like. 550 00:29:04,920 --> 00:29:07,160 Speaker 11: I mean, where do we begin. I mean, the greatest 551 00:29:07,200 --> 00:29:10,200 Speaker 11: AI breakthrough is one that people can actually use. And 552 00:29:10,200 --> 00:29:13,560 Speaker 11: what we're saying in this instance is it's the greatest breakthrough. 553 00:29:13,680 --> 00:29:15,880 Speaker 11: It scares us, but we're not gonna let people use it. 554 00:29:16,320 --> 00:29:20,560 Speaker 11: But my understanding of what's been reported is that there 555 00:29:20,560 --> 00:29:23,760 Speaker 11: will now be roughly more than one hundred but not 556 00:29:23,840 --> 00:29:27,680 Speaker 11: much more than that, federal departments and agencies, private sector 557 00:29:27,720 --> 00:29:30,440 Speaker 11: companies that have already been vetted, which will have access 558 00:29:30,480 --> 00:29:33,320 Speaker 11: to this model, and they will not have sort of 559 00:29:33,360 --> 00:29:37,080 Speaker 11: the constraints around foreign employees to be able to use 560 00:29:37,120 --> 00:29:39,600 Speaker 11: this model. And then I guess more to come. It's 561 00:29:39,600 --> 00:29:41,320 Speaker 11: sort of a stay tuned and let's see. 562 00:29:43,000 --> 00:29:46,920 Speaker 3: The thing the tension here is that because of the 563 00:29:46,960 --> 00:29:51,160 Speaker 3: capabilities of the model industry wants access to it right, 564 00:29:51,200 --> 00:29:54,240 Speaker 3: they want to use it for its benefits. 565 00:29:55,200 --> 00:29:56,280 Speaker 2: From the government. 566 00:29:55,960 --> 00:29:58,920 Speaker 3: Side of the table, how do they hear that? How 567 00:29:58,920 --> 00:30:00,200 Speaker 3: do they get that part right? 568 00:30:00,040 --> 00:30:04,440 Speaker 11: I think this is a tough one, and you know, 569 00:30:04,480 --> 00:30:07,000 Speaker 11: this should be a wake up call for everybody, not 570 00:30:07,240 --> 00:30:11,240 Speaker 11: just the AI companies who are producing you know, agentic AI, 571 00:30:11,400 --> 00:30:15,800 Speaker 11: generative AI and frontier AI models, as well as businesses 572 00:30:15,840 --> 00:30:19,719 Speaker 11: implementing them that you know, we saw open AI actually 573 00:30:19,800 --> 00:30:22,520 Speaker 11: just got told recently that they needed to limit model 574 00:30:22,680 --> 00:30:25,920 Speaker 11: access for new capability. So what we need to do 575 00:30:26,040 --> 00:30:28,760 Speaker 11: here is, you know, we know that the rest of 576 00:30:28,800 --> 00:30:33,480 Speaker 11: the world, including China, is investing aggressively increasingly. There's capable 577 00:30:33,640 --> 00:30:37,240 Speaker 11: open source, in some cases free models that are narrowing 578 00:30:37,280 --> 00:30:40,760 Speaker 11: the gap. So leadership in this moment really depends on 579 00:30:40,840 --> 00:30:45,680 Speaker 11: responsibly getting these breakthroughs as fast as possible into the users. 580 00:30:46,040 --> 00:30:46,880 Speaker 2: So what's going to. 581 00:30:46,800 --> 00:30:50,520 Speaker 11: Have to happen here is a much faster vetting process 582 00:30:50,560 --> 00:30:53,640 Speaker 11: for allowing these incredible capabilities to be in the hands 583 00:30:54,040 --> 00:30:56,560 Speaker 11: of people in business who need to have this to 584 00:30:56,640 --> 00:30:59,000 Speaker 11: protect and defend their enterprises. 585 00:31:00,120 --> 00:31:01,840 Speaker 3: So you teed us up really nicely for our next 586 00:31:01,840 --> 00:31:04,600 Speaker 3: conversation with hugging Face CEO clemmed Along in a moment 587 00:31:04,840 --> 00:31:08,600 Speaker 3: particular focus on open source. You said, what needs to happen. 588 00:31:08,680 --> 00:31:11,360 Speaker 3: I guess there's a distinction with what is likely to happen, 589 00:31:11,800 --> 00:31:14,280 Speaker 3: and so you know, again reflects you on your experience. 590 00:31:14,640 --> 00:31:18,920 Speaker 3: Do we need to expect tighter US restrictions, particularly on 591 00:31:18,960 --> 00:31:22,880 Speaker 3: the frontier labs each generation of powerful model they put out. 592 00:31:24,400 --> 00:31:26,480 Speaker 11: I think we run a huge risk if we don't 593 00:31:26,520 --> 00:31:30,959 Speaker 11: create a framework that provides certainty in the process and 594 00:31:31,000 --> 00:31:34,280 Speaker 11: fairness in the process. And you know, so if you 595 00:31:34,320 --> 00:31:36,760 Speaker 11: don't create a framework and we don't know who's next. 596 00:31:37,080 --> 00:31:38,280 Speaker 2: You know, the markets don't like. 597 00:31:38,360 --> 00:31:43,320 Speaker 11: Uncertainty, and certainly our you know, global partners don't like uncertainty. 598 00:31:43,360 --> 00:31:45,840 Speaker 11: You're already starting to see global partners say, well, maybe 599 00:31:45,880 --> 00:31:48,240 Speaker 11: we need to develop our own models, Maybe we need 600 00:31:48,280 --> 00:31:50,080 Speaker 11: to do things our own way, maybe we need to 601 00:31:50,160 --> 00:31:54,240 Speaker 11: install open source models here within our country. So we 602 00:31:54,320 --> 00:31:57,720 Speaker 11: really need to see leadership come out from Washington, d C. 603 00:31:58,240 --> 00:32:00,960 Speaker 11: To say this is the framework, this is the certainty, 604 00:32:01,000 --> 00:32:03,720 Speaker 11: here's the process. It may change, but at least publish 605 00:32:03,720 --> 00:32:07,000 Speaker 11: a process so we all know what the test looks 606 00:32:07,080 --> 00:32:10,360 Speaker 11: like and we can all perform according to the test. 607 00:32:10,600 --> 00:32:12,640 Speaker 3: Let's recap where we stand from Friday. There are one 608 00:32:12,680 --> 00:32:15,840 Speaker 3: hundred US companies and federal agencies that will have been 609 00:32:15,840 --> 00:32:19,600 Speaker 3: approved for access. They don't require an export license for 610 00:32:19,720 --> 00:32:23,440 Speaker 3: themselves or for their non US employees. But how much 611 00:32:23,440 --> 00:32:26,480 Speaker 3: scrutiny will that group of one hundred be under how 612 00:32:26,560 --> 00:32:28,600 Speaker 3: they use the model, what they were able to get 613 00:32:28,640 --> 00:32:32,440 Speaker 3: from it, rather than just anthropic itself sort of being 614 00:32:32,480 --> 00:32:34,320 Speaker 3: under the microscope of this administration. 615 00:32:35,320 --> 00:32:36,120 Speaker 2: Yeah, you bring up. 616 00:32:36,080 --> 00:32:37,800 Speaker 11: A great point and sort of be careful what you 617 00:32:37,840 --> 00:32:40,040 Speaker 11: wish for. So now that you're in this group, if 618 00:32:40,040 --> 00:32:43,640 Speaker 11: you're in a heavily regulated private sector industry, your regulators 619 00:32:43,680 --> 00:32:45,720 Speaker 11: are going to ask you when did you run it, 620 00:32:45,840 --> 00:32:48,040 Speaker 11: what did you find, and did you fix what you found? 621 00:32:48,480 --> 00:32:51,040 Speaker 11: So there is going to be another layer of undue 622 00:32:51,040 --> 00:32:54,680 Speaker 11: scrutiny on kind of these businesses. But they also have 623 00:32:54,760 --> 00:32:57,760 Speaker 11: an advantage. They get to have access to this tool first. 624 00:32:58,160 --> 00:33:00,360 Speaker 11: I think the other reminder for people is is that 625 00:33:00,520 --> 00:33:04,080 Speaker 11: running this tool isn't free. It does require token, so 626 00:33:04,120 --> 00:33:07,440 Speaker 11: it does cost money. It costs computer resources, it costs 627 00:33:07,440 --> 00:33:10,040 Speaker 11: staffing resources to look at the results. I know, by 628 00:33:10,080 --> 00:33:12,440 Speaker 11: the way, if you find something, you definitely need to 629 00:33:12,480 --> 00:33:15,000 Speaker 11: get it fixed. Right away, and so having the capability 630 00:33:15,360 --> 00:33:19,000 Speaker 11: to actually mitigate and remediate anything that's found and doing 631 00:33:19,040 --> 00:33:21,960 Speaker 11: it at machine speed is not something that all businesses have. 632 00:33:23,680 --> 00:33:28,000 Speaker 3: Three Sepeton, CEO of Faughterly Solutions and former White House coio, 633 00:33:28,120 --> 00:33:30,520 Speaker 3: thank you very much. This isn't just about one company 634 00:33:30,800 --> 00:33:33,800 Speaker 3: or ONEAI model anymore. It's about what happens when government 635 00:33:33,880 --> 00:33:37,840 Speaker 3: scrutiny becomes a market signal. Our next guest has argued 636 00:33:37,880 --> 00:33:41,760 Speaker 3: that being labeled too dangerous may actually be good marketing 637 00:33:42,080 --> 00:33:44,880 Speaker 3: for frontier AI firms Joining us now is clemmed Along, 638 00:33:45,000 --> 00:33:48,680 Speaker 3: CEO of Hugging Face and if you're runfamiliar, Hugging Face 639 00:33:49,040 --> 00:33:52,160 Speaker 3: is where that more than seven million developers discover tests 640 00:33:52,280 --> 00:33:55,880 Speaker 3: deploy AI models from leading labs to open source, giving 641 00:33:56,040 --> 00:33:59,240 Speaker 3: Clem a pretty unique perspective on how AI is actually 642 00:33:59,280 --> 00:34:02,280 Speaker 3: being adopted across industry and clim. I want to start 643 00:34:02,560 --> 00:34:05,400 Speaker 3: with that post you put on X the idea that 644 00:34:05,400 --> 00:34:07,320 Speaker 3: that designation is good marketing. 645 00:34:07,640 --> 00:34:09,960 Speaker 2: Could you explain a little bit more why you think that? 646 00:34:11,239 --> 00:34:13,520 Speaker 12: Well, First, I want to point out that a lot 647 00:34:13,560 --> 00:34:17,800 Speaker 12: of people are saying that, you know, it's not completely 648 00:34:17,920 --> 00:34:21,839 Speaker 12: unfair for them to start being regulated, given that They've 649 00:34:21,880 --> 00:34:25,680 Speaker 12: been doing what we call doom marketing for quite many 650 00:34:25,760 --> 00:34:28,880 Speaker 12: years now. If you remember GPT two that was released 651 00:34:28,880 --> 00:34:31,640 Speaker 12: I think five six years ago, was already deemed like 652 00:34:31,719 --> 00:34:35,279 Speaker 12: two dangerous to release. So I feel like it's fair 653 00:34:35,320 --> 00:34:38,200 Speaker 12: for the US government to at least try to get 654 00:34:38,320 --> 00:34:42,480 Speaker 12: more transparency about what these models can and come to. 655 00:34:43,880 --> 00:34:46,799 Speaker 12: And you know, I think it's important to remember that 656 00:34:46,880 --> 00:34:51,760 Speaker 12: these are gigantic companies, you know, fastest growing in the world, 657 00:34:51,880 --> 00:34:54,600 Speaker 12: on their way to maybe be the most valuable companies 658 00:34:54,719 --> 00:34:57,239 Speaker 12: by the end of this year. So I feel like 659 00:34:57,320 --> 00:35:00,880 Speaker 12: they can take these kinds of regulation and an interaction 660 00:35:01,080 --> 00:35:04,440 Speaker 12: with the US government. I think one thing that we 661 00:35:04,480 --> 00:35:07,200 Speaker 12: need to be careful of is to kind of like 662 00:35:07,320 --> 00:35:11,080 Speaker 12: spread these constraints and these regulations to the rest of 663 00:35:11,120 --> 00:35:17,200 Speaker 12: the ecosystem, like startups, little tech university academia, who certainly 664 00:35:17,320 --> 00:35:20,719 Speaker 12: don't have the same kind of like legal and policy 665 00:35:20,920 --> 00:35:22,960 Speaker 12: capabilities than these companies have. 666 00:35:23,920 --> 00:35:26,399 Speaker 3: I want to get to that distinction of regulating sort 667 00:35:26,440 --> 00:35:28,960 Speaker 3: of the frontier labs and APIs and open source In 668 00:35:29,040 --> 00:35:34,280 Speaker 3: just a minute, but to end the conversation on that post, 669 00:35:34,440 --> 00:35:36,759 Speaker 3: do you think that the US government has handled this 670 00:35:36,920 --> 00:35:40,240 Speaker 3: correctly with anthropic and methos and fable. 671 00:35:41,800 --> 00:35:45,200 Speaker 12: Well, I think it's important to get more transparency for everyone, right, 672 00:35:45,440 --> 00:35:49,080 Speaker 12: the government needs to have more transparency about what these 673 00:35:49,120 --> 00:35:52,239 Speaker 12: models are capable or not capable of doing, which is 674 00:35:52,280 --> 00:35:55,200 Speaker 12: hard to do through APIs right because there are guad rails, 675 00:35:55,239 --> 00:35:58,040 Speaker 12: there are limitations that makes it hard to actually know 676 00:35:58,120 --> 00:36:00,880 Speaker 12: what they're capable and not capable of doing. 677 00:36:01,280 --> 00:36:02,360 Speaker 2: So I think it's it's. 678 00:36:02,200 --> 00:36:05,719 Speaker 12: It's quite quite fair for the US government to try 679 00:36:05,760 --> 00:36:10,360 Speaker 12: to get more transparency on this very complex black box system. 680 00:36:11,280 --> 00:36:14,880 Speaker 12: You know, obviously, like it's hard to do that perfectly, 681 00:36:15,040 --> 00:36:19,880 Speaker 12: given how fast the field is moving and how uncertain 682 00:36:19,960 --> 00:36:22,879 Speaker 12: some of these risks are. But I think it's it's 683 00:36:22,880 --> 00:36:24,440 Speaker 12: not it's not unfair overall. 684 00:36:25,960 --> 00:36:28,520 Speaker 3: You argue that there should be a distinction how governments 685 00:36:28,600 --> 00:36:34,760 Speaker 3: regulate frontier AI and open source. Why why should open 686 00:36:34,800 --> 00:36:38,680 Speaker 3: source be treated differently? What is it that the ecosystem 687 00:36:38,960 --> 00:36:41,160 Speaker 3: needs differently on the open source side? 688 00:36:42,400 --> 00:36:44,799 Speaker 12: Well, first, in terms of capabilities, I think it is 689 00:36:44,840 --> 00:36:51,200 Speaker 12: badly accepted that the most dangerous capabilities are concentrated behind 690 00:36:51,480 --> 00:36:55,960 Speaker 12: like in these kind of like frontier AI labs, where 691 00:36:56,120 --> 00:36:58,440 Speaker 12: the majority of kind of like open source models are 692 00:36:58,480 --> 00:37:03,160 Speaker 12: more like specialized aller more kind of like broadly beneficial 693 00:37:03,200 --> 00:37:09,000 Speaker 12: models that aren't really creating more risks. So there's a 694 00:37:09,040 --> 00:37:11,600 Speaker 12: different in terms of capabilities. There's a different in terms 695 00:37:11,600 --> 00:37:12,439 Speaker 12: of transparency. 696 00:37:12,719 --> 00:37:13,640 Speaker 2: You know, Like open. 697 00:37:13,400 --> 00:37:16,919 Speaker 12: Source models, it's really easy to evaluate and to look 698 00:37:16,960 --> 00:37:19,640 Speaker 12: at what they can and can't do from the get 699 00:37:19,640 --> 00:37:22,120 Speaker 12: go because you know, you get you get the models, 700 00:37:22,239 --> 00:37:25,000 Speaker 12: you can test it really easily. Versus an API, it's 701 00:37:25,040 --> 00:37:27,680 Speaker 12: really really hard to do that. So you need kind 702 00:37:27,719 --> 00:37:31,080 Speaker 12: of like some some more kind of like access, I 703 00:37:31,080 --> 00:37:36,200 Speaker 12: would say, to really assess them. And also, of course, 704 00:37:36,320 --> 00:37:40,040 Speaker 12: like the provenance is different, right Like open source is 705 00:37:40,120 --> 00:37:45,239 Speaker 12: like an ecosystem of smaller companies, smaller organizations, you know, 706 00:37:45,520 --> 00:37:48,600 Speaker 12: versus you know, the Frontier Labs is a couple of 707 00:37:48,840 --> 00:37:52,600 Speaker 12: companies that are concentrating a lot of power behind closed doors. 708 00:37:53,560 --> 00:37:55,759 Speaker 3: There's been a lot of press coverage of late and 709 00:37:56,080 --> 00:38:00,520 Speaker 3: other data points like your own revenue run rate, right sources, 710 00:38:00,520 --> 00:38:05,120 Speaker 3: your lifeblood. Open source models seem to be competitive in 711 00:38:05,440 --> 00:38:08,880 Speaker 3: a market against closed models. What else would you point 712 00:38:08,920 --> 00:38:10,320 Speaker 3: to to evidence. 713 00:38:09,920 --> 00:38:13,439 Speaker 12: That, well, it's not just us, right, Like, the whole 714 00:38:13,480 --> 00:38:19,000 Speaker 12: ecosystem right now is booming. We see tons of companies 715 00:38:19,000 --> 00:38:23,840 Speaker 12: doing super well, like the influence providers nail cloud or posting, 716 00:38:23,920 --> 00:38:30,320 Speaker 12: kind of like fantastic fantastic growth. A million new models 717 00:38:30,320 --> 00:38:32,479 Speaker 12: in data sets have been sued on hugging face just 718 00:38:32,600 --> 00:38:37,000 Speaker 12: the past past quarter. And you see that in usage too, right, 719 00:38:37,080 --> 00:38:42,920 Speaker 12: the usage of open source by American companies, American startups, 720 00:38:43,120 --> 00:38:47,919 Speaker 12: American small companies is also booming. So this is really 721 00:38:47,960 --> 00:38:53,640 Speaker 12: exciting because it basically enable empower more more people to 722 00:38:53,719 --> 00:38:58,480 Speaker 12: really own AI themselves, whether than renting it with APIs. 723 00:38:59,600 --> 00:39:02,640 Speaker 12: So this this is quite exciting Clem. 724 00:39:02,680 --> 00:39:05,200 Speaker 3: Another area of real focus of the show of late 725 00:39:05,239 --> 00:39:07,760 Speaker 3: it's been robotics. We had deep Utala from a video 726 00:39:07,840 --> 00:39:12,000 Speaker 3: on last week talking about Halo's hugging face is also 727 00:39:12,080 --> 00:39:14,600 Speaker 3: looking a lot at robotics. What I would be really 728 00:39:14,600 --> 00:39:17,600 Speaker 3: grateful for is to understand the role that open source 729 00:39:17,680 --> 00:39:21,120 Speaker 3: is playing in robotics and physical AI, but also like 730 00:39:21,160 --> 00:39:24,080 Speaker 3: the benefit of leaning on open source in that field. 731 00:39:25,120 --> 00:39:27,439 Speaker 12: I think it's even more important than in general AI, 732 00:39:27,680 --> 00:39:29,840 Speaker 12: just because you know, if you think of having a 733 00:39:29,960 --> 00:39:34,560 Speaker 12: robot at home that is interacting with your environment, with 734 00:39:34,600 --> 00:39:37,680 Speaker 12: your kids. I just got two daughters a few months ago, 735 00:39:37,920 --> 00:39:41,879 Speaker 12: so when I think about a robot interacting with my daughters, 736 00:39:42,680 --> 00:39:45,720 Speaker 12: like I don't want to have to trust a black 737 00:39:45,800 --> 00:39:50,600 Speaker 12: box controls by one megacorp being able to do anything. 738 00:39:51,320 --> 00:39:54,560 Speaker 12: I want to have some transparency about what's going on 739 00:39:54,560 --> 00:39:57,560 Speaker 12: on this robot, how is it built, how does it 740 00:39:58,600 --> 00:40:02,279 Speaker 12: decide to interact one way or another? And for that 741 00:40:03,160 --> 00:40:06,680 Speaker 12: open source is the only way, right Like, it gives 742 00:40:06,680 --> 00:40:08,480 Speaker 12: you transparency, it gives you control. 743 00:40:08,520 --> 00:40:09,440 Speaker 2: It creates an eco. 744 00:40:09,360 --> 00:40:11,839 Speaker 12: System of different companies that are going to be able 745 00:40:11,880 --> 00:40:16,000 Speaker 12: to build robots. So that's that's why we excited about it. 746 00:40:16,360 --> 00:40:19,919 Speaker 12: We created this loyal robot called Richie Mini, and we've 747 00:40:19,920 --> 00:40:23,080 Speaker 12: been really surprised by how into it people have been. 748 00:40:23,160 --> 00:40:25,239 Speaker 12: We've we shipped over ten thousand of them all over 749 00:40:25,280 --> 00:40:28,759 Speaker 12: the world in the past past few months. And that's 750 00:40:29,160 --> 00:40:33,960 Speaker 12: a testament to how excited people are by you more open, 751 00:40:34,040 --> 00:40:38,000 Speaker 12: more transparent, more open source approaches to robotics. 752 00:40:38,480 --> 00:40:41,520 Speaker 3: Claimed along hugging face CEO back on Bloomberg Tech, thank 753 00:40:41,560 --> 00:40:42,239 Speaker 3: you very much. 754 00:40:42,719 --> 00:40:43,920 Speaker 2: Indeed, now coming. 755 00:40:43,760 --> 00:40:48,319 Speaker 3: Out, AI bots are taking over remote meetings, creating new 756 00:40:48,400 --> 00:40:52,000 Speaker 3: challenges for the corporate's fare. We have a really interesting 757 00:40:52,000 --> 00:41:07,839 Speaker 3: one next this is Bloomberg Tech. AI note takers are 758 00:41:07,880 --> 00:41:11,560 Speaker 3: infiltrating the corporate world meant to increase productivity, AI bots 759 00:41:11,560 --> 00:41:15,520 Speaker 3: are instead posing privacy concerns and security risks. As AI 760 00:41:16,000 --> 00:41:19,360 Speaker 3: is increasingly incorporated into the workplace, the debate is growing 761 00:41:19,719 --> 00:41:24,120 Speaker 3: on what conversations constitute robots and which ones are strictly human. 762 00:41:24,480 --> 00:41:25,880 Speaker 2: Bloomberg BusinessWeek contributor to. 763 00:41:25,920 --> 00:41:30,279 Speaker 3: Issi Labowski has more brilliant BusinessWeek story than new etiquette 764 00:41:30,320 --> 00:41:34,000 Speaker 3: for navigating AI. Note takers start with the overview of the. 765 00:41:33,960 --> 00:41:37,400 Speaker 8: Story, right, So, I think we've all seen this happen 766 00:41:37,520 --> 00:41:41,000 Speaker 8: in our sort of virtual remote work world. We're joining 767 00:41:41,080 --> 00:41:44,520 Speaker 8: these Zoom calls and Google meets, and when you get 768 00:41:44,560 --> 00:41:46,600 Speaker 8: on the call, it's you and whoever you're supposed to 769 00:41:46,640 --> 00:41:49,880 Speaker 8: have a call with and their note taker. Sometimes that 770 00:41:50,000 --> 00:41:53,319 Speaker 8: says you know otter AI or read AI, or sometimes 771 00:41:53,400 --> 00:41:56,080 Speaker 8: it doesn't even announce itself at all. And what these 772 00:41:56,120 --> 00:41:58,680 Speaker 8: note takers do is kind of take a live transcript 773 00:41:58,719 --> 00:42:01,200 Speaker 8: of what you've talked about. Afterwards, they hand you back 774 00:42:01,239 --> 00:42:04,440 Speaker 8: a really handy summary, and a lot of people feel 775 00:42:04,440 --> 00:42:06,680 Speaker 8: like it's great, this is saving me time on doing 776 00:42:06,719 --> 00:42:08,759 Speaker 8: the whole recap, and I can go back and look 777 00:42:08,760 --> 00:42:11,399 Speaker 8: at my notes afterward. The question is, are people really 778 00:42:11,480 --> 00:42:13,279 Speaker 8: doing the work up front? To make sure the other 779 00:42:13,440 --> 00:42:16,040 Speaker 8: person on the other side of the screen is comfortable with. 780 00:42:16,000 --> 00:42:16,560 Speaker 2: That as well. 781 00:42:17,560 --> 00:42:20,080 Speaker 3: You know, that is also a question of human responsibility. 782 00:42:20,120 --> 00:42:22,640 Speaker 3: You make the piece in the point in the Business 783 00:42:22,640 --> 00:42:25,080 Speaker 3: Week piece that you know, the AI note take is 784 00:42:25,120 --> 00:42:28,240 Speaker 3: a quite commonplace. Now some of these tools have already 785 00:42:28,239 --> 00:42:30,560 Speaker 3: got millions of views as a piece, but it's up 786 00:42:30,600 --> 00:42:33,080 Speaker 3: to the shutdently to say how is this working? 787 00:42:34,440 --> 00:42:36,640 Speaker 8: Absolutely, I mean that's what the story is about. I 788 00:42:36,680 --> 00:42:39,239 Speaker 8: think we all know that there are legal invocations here 789 00:42:39,280 --> 00:42:43,040 Speaker 8: of having every single word recorded and shared and saved, 790 00:42:43,800 --> 00:42:47,120 Speaker 8: but there are also interpersonal consequences. Right when you are 791 00:42:47,120 --> 00:42:50,520 Speaker 8: the person who has your note taker, you know, plugged 792 00:42:50,520 --> 00:42:53,560 Speaker 8: into your calendar and it goes to every meeting and 793 00:42:53,600 --> 00:42:55,799 Speaker 8: sometimes you don't even show up because you forgot about 794 00:42:55,800 --> 00:42:58,440 Speaker 8: the meeting but your note taker didn't. That's a really 795 00:42:58,560 --> 00:43:01,520 Speaker 8: bad look. So this story is really about the norms 796 00:43:01,560 --> 00:43:04,040 Speaker 8: and common courtesy that we have to develop around these 797 00:43:04,080 --> 00:43:06,920 Speaker 8: AI note takers because we are not all at the 798 00:43:06,960 --> 00:43:09,879 Speaker 8: same place of comfort with regard to AI. We are 799 00:43:09,920 --> 00:43:14,080 Speaker 8: in some cases quite polarized, and these meetings, these AI 800 00:43:14,120 --> 00:43:17,080 Speaker 8: note takers are sort of the one place where my 801 00:43:17,400 --> 00:43:21,440 Speaker 8: drive for you know, AI enabled efficiency is running up 802 00:43:21,480 --> 00:43:24,600 Speaker 8: against your discomfort with having AI in your life, and 803 00:43:24,640 --> 00:43:27,400 Speaker 8: so we need to navigate those things on the human 804 00:43:27,440 --> 00:43:29,880 Speaker 8: to human level, and often that deals with issues of 805 00:43:29,960 --> 00:43:34,200 Speaker 8: consent and all of that and just personal responsibility. 806 00:43:35,719 --> 00:43:38,279 Speaker 3: That was Bloomberg BusinessWeek in tributy, Issie Lapowski, Thank you 807 00:43:38,480 --> 00:43:40,960 Speaker 3: very much. Indeed, let's go back one last time to 808 00:43:41,040 --> 00:43:44,479 Speaker 3: Comcast shares markedly high. There is a plan to spin 809 00:43:44,600 --> 00:43:49,280 Speaker 3: out NBC Universal and Sky in Europe into a standalone 810 00:43:49,320 --> 00:43:51,520 Speaker 3: public company, so there will be two and in a 811 00:43:51,640 --> 00:43:54,759 Speaker 3: year's time, if it all goes to planned, shareholders will 812 00:43:54,800 --> 00:43:57,680 Speaker 3: have exposure to both to stop up seven percent, on 813 00:43:57,800 --> 00:44:00,400 Speaker 3: track for its best day since mid April. That does 814 00:44:00,480 --> 00:44:03,200 Speaker 3: it for this edition of Bloomberg Tech. So much in 815 00:44:03,280 --> 00:44:05,880 Speaker 3: the program. Check out the podcast to recap all of it. 816 00:44:05,960 --> 00:44:07,840 Speaker 3: You know exactly where to find it. This is Bloomberg