1 00:00:01,560 --> 00:00:05,880 Speaker 1: From Mahard where Innovations, Money and Power Collie in Silicon 2 00:00:05,960 --> 00:00:06,880 Speaker 1: Vallet NBN. 3 00:00:07,200 --> 00:00:11,240 Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow. 4 00:00:24,640 --> 00:00:27,000 Speaker 3: I'm Caroline Hyde at Bloomberg's world headquarters in New York 5 00:00:27,440 --> 00:00:29,320 Speaker 3: and I met Ludlow in San Francisco. 6 00:00:29,480 --> 00:00:31,240 Speaker 4: This is Bloomberg Technology coming up. 7 00:00:31,320 --> 00:00:35,159 Speaker 3: Semiconductors slide. That's on reports that China has told telecom 8 00:00:35,159 --> 00:00:38,680 Speaker 3: carries to drop foreign chips. They'll bring you the details. 9 00:00:39,400 --> 00:00:43,200 Speaker 5: Plus Apple plans to overhaul its entire line of Mac 10 00:00:43,280 --> 00:00:46,800 Speaker 5: computers to add an AI focused in house processor or 11 00:00:46,840 --> 00:00:49,280 Speaker 5: break down our exclusive Bloomberg reporting. 12 00:00:49,479 --> 00:00:52,320 Speaker 3: And Kathy Wood buys into chatchybt Boom with a stake 13 00:00:52,360 --> 00:00:54,920 Speaker 3: in Open AI. We'll discuss that and so much more 14 00:00:54,960 --> 00:00:56,880 Speaker 3: throughout the hour, but first let's get over to these 15 00:00:56,920 --> 00:00:59,960 Speaker 3: public trading markets. From a macro context, this is one 16 00:01:00,080 --> 00:01:02,240 Speaker 3: we're seeing a search for safety today. There is warriors 17 00:01:02,240 --> 00:01:05,800 Speaker 3: regarding Iran Israel. We're seeing geopolitical risks heightened, and maybe 18 00:01:05,880 --> 00:01:08,680 Speaker 3: just as squaring away of certain volatility that we've seen 19 00:01:08,680 --> 00:01:11,240 Speaker 3: throughout the week when it comes to concerns about CPIPPI. 20 00:01:11,560 --> 00:01:13,839 Speaker 3: As we move towards the weekend, we're currently seeing, for once, 21 00:01:13,959 --> 00:01:16,560 Speaker 3: equity is actually moving at the opposite way of a 22 00:01:16,560 --> 00:01:18,520 Speaker 3: bomb market. Even though the bond market has been selling 23 00:01:18,520 --> 00:01:20,440 Speaker 3: off and equities is still managed to ride higher. Today 24 00:01:20,440 --> 00:01:22,840 Speaker 3: it's the opposite. Were actually seeing bond markets move higher. 25 00:01:22,880 --> 00:01:24,959 Speaker 3: We're seeing money move into the havens that are the 26 00:01:25,000 --> 00:01:27,639 Speaker 3: tenure yield. We're off by also eight nine basis points, 27 00:01:27,800 --> 00:01:29,720 Speaker 3: so we're seeing money move there, money move into the 28 00:01:29,720 --> 00:01:32,240 Speaker 3: Bloomberg Dollar Index, in fact, the highest level that since 29 00:01:32,240 --> 00:01:35,080 Speaker 3: we've seen twenty twenty four. Head are up another seven 30 00:01:35,120 --> 00:01:37,560 Speaker 3: tenths of a percent, but money coming out of equities 31 00:01:37,600 --> 00:01:39,840 Speaker 3: as we worry about geopolitical tensions. We're off by one 32 00:01:39,840 --> 00:01:41,840 Speaker 3: point four percent on the NASDAK and of course that 33 00:01:41,920 --> 00:01:43,880 Speaker 3: key chip story that we're will be digging into in 34 00:01:43,920 --> 00:01:46,160 Speaker 3: a moment. Move on, have a little look what's happening 35 00:01:46,400 --> 00:01:49,800 Speaker 3: in another key risk asset, and actually surprisingly flat for 36 00:01:49,880 --> 00:01:52,120 Speaker 3: bitcoin over all over the course of a week now. 37 00:01:52,320 --> 00:01:54,280 Speaker 3: The volatility has been there to see on a day 38 00:01:54,280 --> 00:01:56,400 Speaker 3: to day basis, and we rode higher at the start 39 00:01:56,480 --> 00:01:58,120 Speaker 3: where we've just come off with some of those highs. 40 00:01:58,120 --> 00:02:00,560 Speaker 3: Of course, a dollar strength is going to mean a 41 00:02:00,560 --> 00:02:02,600 Speaker 3: bit of a bitcoin weakness, But what are you watching. 42 00:02:03,240 --> 00:02:05,240 Speaker 5: We have a lot of technology stories to bring you 43 00:02:05,320 --> 00:02:08,160 Speaker 5: this Friday. Apple is an interesting one, up seven ten 44 00:02:08,200 --> 00:02:12,519 Speaker 5: to one percent after a four percent jump Thursday, which 45 00:02:12,560 --> 00:02:14,919 Speaker 5: I think was the biggest jump since May of last year. 46 00:02:15,240 --> 00:02:16,520 Speaker 4: Bloombos Mark German. 47 00:02:16,360 --> 00:02:19,520 Speaker 5: Is reporting a complete overhaul of the Mac line, and 48 00:02:19,560 --> 00:02:21,960 Speaker 5: we'll talk to Mark a little bit later in the program. 49 00:02:22,120 --> 00:02:24,519 Speaker 5: Alphabet Paarent of Google down a percentage twenty is giving 50 00:02:24,600 --> 00:02:26,919 Speaker 5: us a little bit back after hitting the two trillion 51 00:02:26,960 --> 00:02:32,240 Speaker 5: dollar market cap mark Thursday. Recently, a lot more optimism 52 00:02:32,440 --> 00:02:35,240 Speaker 5: that Google's starting to get it right on AI. They'll 53 00:02:35,280 --> 00:02:39,480 Speaker 5: actually have products, particularly in the enterprise or commercial use case. 54 00:02:39,760 --> 00:02:41,840 Speaker 5: But pulling back a little bit this Friday after a 55 00:02:41,919 --> 00:02:43,520 Speaker 5: key milestone, we're keeping our. 56 00:02:43,400 --> 00:02:44,360 Speaker 4: Eyes on the banks. 57 00:02:44,560 --> 00:02:48,760 Speaker 5: Bank earnings kind of kick us off for earnings. Overall, 58 00:02:48,800 --> 00:02:50,840 Speaker 5: you can see us kind of mixed fortunes, all of 59 00:02:50,880 --> 00:02:54,320 Speaker 5: these three names moving to the downside going into it 60 00:02:54,360 --> 00:02:57,240 Speaker 5: for us, so Blomow Technology AI. What's happening with aim 61 00:02:57,320 --> 00:02:58,880 Speaker 5: banks was a big theme, but they all have their 62 00:02:58,880 --> 00:02:59,880 Speaker 5: own individual stories. 63 00:03:00,120 --> 00:03:01,520 Speaker 4: I'm not going to tell you the story. 64 00:03:01,840 --> 00:03:06,079 Speaker 5: Bloomberg Shnali Bassak the correct person to bring us the banks, 65 00:03:06,160 --> 00:03:07,920 Speaker 5: Rap joins us on set in New York and she 66 00:03:07,960 --> 00:03:10,920 Speaker 5: brings you this story Snali, three big names, both moving lower, 67 00:03:10,960 --> 00:03:11,600 Speaker 5: all moving lower. 68 00:03:11,680 --> 00:03:13,480 Speaker 6: Yeah, all moving lower. And remember that is a little 69 00:03:13,480 --> 00:03:16,920 Speaker 6: bit of a reversal. City Group had beat profit estimates 70 00:03:16,919 --> 00:03:19,560 Speaker 6: here and we did see an earlier gain. Remember the 71 00:03:19,560 --> 00:03:21,360 Speaker 6: market is lower on the day, but some of the 72 00:03:21,360 --> 00:03:24,200 Speaker 6: declines they're seeing are quite stark. JP Morgan, for example, 73 00:03:24,240 --> 00:03:27,480 Speaker 6: Intra Day is having its worst day since March of 74 00:03:27,560 --> 00:03:30,080 Speaker 6: twenty twenty three, when we know times are very different. 75 00:03:30,160 --> 00:03:31,600 Speaker 3: Remember ed we have JP. 76 00:03:31,480 --> 00:03:35,720 Speaker 6: Morgan coming off six consecutive years of record revenue. So 77 00:03:35,800 --> 00:03:38,560 Speaker 6: the big question is when analysts had expected them to 78 00:03:38,640 --> 00:03:41,400 Speaker 6: raise the bar on that interest income, are they just 79 00:03:41,440 --> 00:03:44,560 Speaker 6: being conservative when they have not done so, or are 80 00:03:44,560 --> 00:03:47,600 Speaker 6: we seeing a consumer that is starting to, if not 81 00:03:47,800 --> 00:03:50,640 Speaker 6: tap out, start to slow down a little bit in 82 00:03:50,720 --> 00:03:53,000 Speaker 6: the way that they are starting to borrow and spend 83 00:03:53,080 --> 00:03:57,440 Speaker 6: on those credit card businesses in particular. Now, some positive 84 00:03:57,440 --> 00:04:00,520 Speaker 6: news for anyone watching Woomberg Technology in particular is you 85 00:04:00,560 --> 00:04:04,000 Speaker 6: do see an uptick here in those underwriting businesses. IPOs 86 00:04:04,080 --> 00:04:06,440 Speaker 6: are back baby, and you are seeing it in the 87 00:04:06,520 --> 00:04:10,320 Speaker 6: number of big banks, and certainly you don't see the 88 00:04:10,360 --> 00:04:13,840 Speaker 6: advisory fees jumping back just as strong yet, but they're 89 00:04:14,000 --> 00:04:16,800 Speaker 6: pretty optimistic over there at JP Morgan what things are 90 00:04:16,800 --> 00:04:18,600 Speaker 6: starting to look like in investment banking. 91 00:04:18,520 --> 00:04:21,200 Speaker 3: And you didn't even mention Ai Shanana Bassec. We thank 92 00:04:21,240 --> 00:04:22,720 Speaker 3: you so much for bring us the latest on and 93 00:04:22,800 --> 00:04:24,960 Speaker 3: earnings context, and of course we brace ourselves for the 94 00:04:24,960 --> 00:04:27,040 Speaker 3: technology earnings to start coming thick and fast at the 95 00:04:27,120 --> 00:04:29,120 Speaker 3: end of next week. But for now we're focused in 96 00:04:29,440 --> 00:04:32,000 Speaker 3: on basically all of the chip set to under propressure. 97 00:04:32,040 --> 00:04:34,000 Speaker 3: We shine a light on Intel off by three point 98 00:04:34,040 --> 00:04:36,800 Speaker 3: four percent, AMD, one of your worst performers, off by 99 00:04:36,839 --> 00:04:40,000 Speaker 3: almost four percent. But in fact, every single member of 100 00:04:40,040 --> 00:04:43,159 Speaker 3: the Semiconductor Index of Philadelphia Semiconductor Index is in the 101 00:04:43,200 --> 00:04:45,560 Speaker 3: red on Semi off by more than four percent. But 102 00:04:45,600 --> 00:04:47,680 Speaker 3: really this is as we see the reporting coming from 103 00:04:47,680 --> 00:04:50,279 Speaker 3: the Wall Street Journal at the moment ed Beijing ordering 104 00:04:50,279 --> 00:04:53,000 Speaker 3: Telecoon carriage, China Mobile and the likes to say no 105 00:04:53,760 --> 00:04:57,240 Speaker 3: to foreign chips in their core networks by twenty twenty seven. 106 00:04:57,600 --> 00:04:59,880 Speaker 3: This is really notable, but perhaps. 107 00:04:59,640 --> 00:05:04,479 Speaker 5: Unsupp Yeah, it is another development in China's effort to 108 00:05:05,279 --> 00:05:08,760 Speaker 5: onshore their own semiconductor industry. Right, so the journal one 109 00:05:08,839 --> 00:05:11,560 Speaker 5: key part of their report is that actually the Ministry 110 00:05:11,600 --> 00:05:15,320 Speaker 5: for Industry and Information Technology has given a timeline, call 111 00:05:15,360 --> 00:05:18,880 Speaker 5: it a timeline or a deadline for not just China Mobile, 112 00:05:18,920 --> 00:05:22,640 Speaker 5: but China Unicorn and China Telecom Corp. To swap out 113 00:05:22,680 --> 00:05:26,400 Speaker 5: foreign chips, those being US chipmakers AMD Intel get twenty 114 00:05:26,400 --> 00:05:29,960 Speaker 5: five percent revenue historically from China on the more commercial 115 00:05:30,080 --> 00:05:32,599 Speaker 5: use case for chips and put in a domestic one. 116 00:05:32,600 --> 00:05:35,599 Speaker 5: The question really is is there a domestic supply chain 117 00:05:35,640 --> 00:05:36,719 Speaker 5: ready to support that. 118 00:05:36,960 --> 00:05:39,479 Speaker 3: By twenty twenty seven They often might well hope so. 119 00:05:39,560 --> 00:05:41,960 Speaker 3: And it's interesting and that almost front running. This was 120 00:05:42,000 --> 00:05:44,400 Speaker 3: a great piece out of Bloomberg Intelligence to showing that 121 00:05:44,920 --> 00:05:49,000 Speaker 3: Chinese export curbs are actually more of a risk the 122 00:05:49,240 --> 00:05:51,719 Speaker 3: US export curbs at the moment. This is a tip 123 00:05:51,760 --> 00:05:53,280 Speaker 3: for tat that you and I have been reporting on 124 00:05:53,440 --> 00:05:56,599 Speaker 3: since we start first got together back in twenty twenty 125 00:05:56,600 --> 00:05:59,520 Speaker 3: two of this technology show and really thinking about how 126 00:05:59,680 --> 00:06:02,360 Speaker 3: US trying to restrain some of its own technology going 127 00:06:02,400 --> 00:06:04,719 Speaker 3: into China. Well, unsurprisingly China is going to be doing 128 00:06:04,880 --> 00:06:07,800 Speaker 3: the same in reverse, but this time actually BI saying 129 00:06:07,880 --> 00:06:10,400 Speaker 3: China's export restrictions is going to be key policy risk 130 00:06:10,680 --> 00:06:13,320 Speaker 3: to some of the US chip manufacturers that have in 131 00:06:13,400 --> 00:06:17,200 Speaker 3: recent years built up their overall supply chain dependency on China. 132 00:06:17,320 --> 00:06:19,799 Speaker 3: So I think that's a really another interesting shoot drop 133 00:06:19,839 --> 00:06:22,800 Speaker 3: at the moment, whether it's export restrictions, whether it's at 134 00:06:22,839 --> 00:06:27,120 Speaker 3: the moment import restrictions coming from China of US tech, I. 135 00:06:27,040 --> 00:06:28,880 Speaker 5: Think we should just get to someone who's got skin 136 00:06:28,960 --> 00:06:31,480 Speaker 5: in the game joining us now is Alison Porter, portfolio 137 00:06:31,560 --> 00:06:35,400 Speaker 5: manager on the Global Technology Leaders and Sustainable Future Technology 138 00:06:35,400 --> 00:06:38,000 Speaker 5: Funds at Janis Henderson, and I think I'm right in 139 00:06:38,040 --> 00:06:40,279 Speaker 5: saying if we just pick out AMD as an example, 140 00:06:41,040 --> 00:06:41,919 Speaker 5: it's one name. 141 00:06:41,760 --> 00:06:43,679 Speaker 4: That you have exposure to, it that you hold. 142 00:06:44,120 --> 00:06:49,760 Speaker 5: You know, the journal is reporting one specific industry case 143 00:06:50,120 --> 00:06:53,600 Speaker 5: of a much broader thing where China wants its domestic 144 00:06:53,720 --> 00:06:55,839 Speaker 5: entities to use domestic chips. 145 00:06:57,240 --> 00:06:58,080 Speaker 4: Your response to. 146 00:06:58,040 --> 00:07:01,160 Speaker 1: That, well, you know, I would put a little bit 147 00:07:01,160 --> 00:07:06,080 Speaker 1: of this into context. China top down are doing foreign 148 00:07:06,160 --> 00:07:10,440 Speaker 1: chips and tailcos. We don't see it as being, you know, 149 00:07:10,800 --> 00:07:15,280 Speaker 1: a huge change because essentially that's a market that has 150 00:07:15,360 --> 00:07:19,120 Speaker 1: been dominated by WAWI and the use of those and 151 00:07:19,200 --> 00:07:21,720 Speaker 1: the use of in house chips has been around for 152 00:07:22,120 --> 00:07:26,760 Speaker 1: a number of years now since chip companies were banned 153 00:07:26,760 --> 00:07:31,640 Speaker 1: from supporting Bowies five G rollout and really in terms 154 00:07:31,720 --> 00:07:35,200 Speaker 1: of China tail Co five D spend that actually peaked 155 00:07:35,960 --> 00:07:40,160 Speaker 1: some time ago, and other areas like f PGAs you know, 156 00:07:40,200 --> 00:07:43,200 Speaker 1: they've had a significant inventry correction. 157 00:07:43,960 --> 00:07:47,440 Speaker 7: And for you know China who may want to replace 158 00:07:49,200 --> 00:07:50,320 Speaker 7: US chips, but. 159 00:07:50,480 --> 00:07:55,240 Speaker 1: Again you know actually using seven nanometer chips domestically, they 160 00:07:55,240 --> 00:07:57,560 Speaker 1: don't have that supply yet. 161 00:07:57,640 --> 00:07:59,800 Speaker 7: So I think for them to get to five and 162 00:08:00,120 --> 00:08:02,320 Speaker 7: meter athena animeter, you're. 163 00:08:02,120 --> 00:08:04,840 Speaker 1: Going to need You're going to need those for sixty deployment, 164 00:08:04,880 --> 00:08:08,480 Speaker 1: which will ultimately need US chips by that time period. 165 00:08:08,560 --> 00:08:11,880 Speaker 1: So you know, we think this is ongoing and wrangling, 166 00:08:11,880 --> 00:08:14,360 Speaker 1: but in terms of the end markets, it's not hugely 167 00:08:14,400 --> 00:08:17,320 Speaker 1: significant for the areas that we're focused on. 168 00:08:17,960 --> 00:08:20,240 Speaker 3: Let's go to where you're focused there for Allison, because 169 00:08:20,240 --> 00:08:23,240 Speaker 3: all of this comes in a current context of a 170 00:08:23,360 --> 00:08:27,080 Speaker 3: threat over supply. We are all envisioning a whole new 171 00:08:27,080 --> 00:08:28,840 Speaker 3: world on which we're going to be living in thanks 172 00:08:28,840 --> 00:08:33,079 Speaker 3: to generative artificial intelligence. But we need the chips, need 173 00:08:33,120 --> 00:08:34,959 Speaker 3: the supply chain, we need to be building these things, 174 00:08:35,040 --> 00:08:37,920 Speaker 3: We need the energy. Alison, what chip names are going 175 00:08:37,960 --> 00:08:40,760 Speaker 3: to be doing well in spite of geopolitical headwinds. 176 00:08:41,760 --> 00:08:45,840 Speaker 1: Well, you know, when I started looking at technology stocks 177 00:08:45,840 --> 00:08:49,880 Speaker 1: back in nineteen eighty six, I think about over a 178 00:08:50,040 --> 00:08:53,800 Speaker 1: third of chip supply and was actually built in the 179 00:08:53,920 --> 00:08:58,840 Speaker 1: US over thirty percent, and way forward to the pandemic. 180 00:08:58,960 --> 00:09:00,880 Speaker 7: And that was down to twelve percent. 181 00:09:01,559 --> 00:09:05,480 Speaker 1: So we see this ongoing focus of deglobalization. That's part 182 00:09:05,559 --> 00:09:10,400 Speaker 1: of national security, it's part of national interest for AI. 183 00:09:10,920 --> 00:09:14,520 Speaker 7: It's also part of the overall focus. 184 00:09:14,000 --> 00:09:19,840 Speaker 1: On improving supply chain standards ESDUY standards throughout the technology 185 00:09:19,920 --> 00:09:20,880 Speaker 1: resupply chain. 186 00:09:21,559 --> 00:09:22,800 Speaker 7: And therefore we. 187 00:09:22,800 --> 00:09:27,640 Speaker 1: Think that actually manufacturing is becoming a more competitive advantage 188 00:09:27,679 --> 00:09:34,160 Speaker 1: more difficult to replicate. Many contract manufacturers, for example Jabel, 189 00:09:34,600 --> 00:09:38,800 Speaker 1: Flixtronic the ability to be able to manufacture at scale. 190 00:09:39,200 --> 00:09:42,440 Speaker 1: These companies have much lower margins and traditionally that could 191 00:09:42,440 --> 00:09:45,920 Speaker 1: be easily moved around from competitors, but that's now becoming 192 00:09:46,040 --> 00:09:50,640 Speaker 1: much more difficult at scale for many of the large 193 00:09:50,640 --> 00:09:54,160 Speaker 1: OEMs to actually move their manufacturing capacity stay around. 194 00:09:54,600 --> 00:09:57,079 Speaker 7: So we think that's one way that we see deglobalization. 195 00:09:57,960 --> 00:10:02,360 Speaker 1: The chips AC actually play into year companies manufacture. 196 00:10:02,679 --> 00:10:07,199 Speaker 3: As a global technology leaders and sustainable future tech fund 197 00:10:07,240 --> 00:10:09,680 Speaker 3: Then do you worry that you're going to have to 198 00:10:09,679 --> 00:10:11,880 Speaker 3: be sacrificing margin on some of the companies that you 199 00:10:11,880 --> 00:10:14,640 Speaker 3: are investing in globally because they're having to you know, 200 00:10:15,040 --> 00:10:19,199 Speaker 3: manufacture in more expensive places to secure supply chain or 201 00:10:19,600 --> 00:10:23,679 Speaker 3: can you play start to play out well opportunities more 202 00:10:23,679 --> 00:10:25,880 Speaker 3: globally that are being overlooked as we've all just focused 203 00:10:25,920 --> 00:10:27,400 Speaker 3: in on a so called Magnificent seven. 204 00:10:28,880 --> 00:10:32,000 Speaker 1: Yeah, I mean, I think there's you know, a significant 205 00:10:32,000 --> 00:10:35,720 Speaker 1: focus on margins and efficiency. You know, the Morgan Stanley 206 00:10:35,760 --> 00:10:39,560 Speaker 1: Technology Conference in March showed that where you know, the 207 00:10:39,640 --> 00:10:43,280 Speaker 1: two most name terms from all of the presentations at 208 00:10:43,280 --> 00:10:48,160 Speaker 1: that conference, it weren't AI, it wasn't chipsacked, it was 209 00:10:48,280 --> 00:10:51,920 Speaker 1: in fact, margins and efficiency. And you see, you know, 210 00:10:51,960 --> 00:10:54,280 Speaker 1: I think that's one of the really interesting aspects of 211 00:10:54,320 --> 00:10:55,960 Speaker 1: where we are just now because we have a major 212 00:10:56,040 --> 00:10:59,079 Speaker 1: new technology weave. But that's also hesting at a time 213 00:10:59,160 --> 00:11:01,760 Speaker 1: when you know, we have this rising cost of capital 214 00:11:01,800 --> 00:11:06,280 Speaker 1: and companies are really focused on efficiencies and improving margins, 215 00:11:06,320 --> 00:11:09,960 Speaker 1: and that creates really interesting opportunities for investors. 216 00:11:10,280 --> 00:11:12,920 Speaker 7: And it's a real stockpickers market, so it's. 217 00:11:12,760 --> 00:11:16,400 Speaker 1: Not easy to generalize on sub sectors. It's very much 218 00:11:16,440 --> 00:11:19,319 Speaker 1: about you know, active management, which is quite typical when 219 00:11:19,360 --> 00:11:24,600 Speaker 1: we hit these technology inflection points. 220 00:11:23,200 --> 00:11:28,280 Speaker 5: In this stock pickers market. Should you pick Apple? Apple 221 00:11:28,760 --> 00:11:33,920 Speaker 5: is becoming increasingly attractive, it seems to you, guys, twelve 222 00:11:33,960 --> 00:11:38,480 Speaker 5: month forward pay of twenty five times it had been downtrodden. 223 00:11:39,080 --> 00:11:40,280 Speaker 5: Now is it a good name? 224 00:11:42,400 --> 00:11:47,680 Speaker 1: We own Apple within our portfolio, but it's not been 225 00:11:47,960 --> 00:11:51,520 Speaker 1: one of our largest holdings for quite some time. 226 00:11:52,120 --> 00:11:53,720 Speaker 7: Apple's a tremendous company. 227 00:11:53,920 --> 00:11:58,480 Speaker 1: It led technology in each of the last three ways, 228 00:11:58,600 --> 00:12:01,440 Speaker 1: you know, through the PC wave, the mobile Internet. They 229 00:12:01,440 --> 00:12:05,320 Speaker 1: were all really started by catalysts from product catalysts from Apple. 230 00:12:05,760 --> 00:12:06,240 Speaker 7: Let's AI. 231 00:12:06,400 --> 00:12:10,559 Speaker 1: We've was started by the product catalysts of Microsoft Chat, 232 00:12:10,679 --> 00:12:14,880 Speaker 1: GPT and Open AI, and also in Vidia on Silicon 233 00:12:15,080 --> 00:12:18,840 Speaker 1: and Apple's role and AI has yet to be defined, 234 00:12:18,880 --> 00:12:22,199 Speaker 1: and we're sure that over the longer term they will 235 00:12:22,240 --> 00:12:24,920 Speaker 1: continue to innovate, but right now they're not one of 236 00:12:25,000 --> 00:12:29,200 Speaker 1: the early drivers of their genera to the IWAVE as. 237 00:12:29,040 --> 00:12:31,720 Speaker 3: A sumporter, just a joy to have you on. Thank 238 00:12:31,760 --> 00:12:34,520 Speaker 3: you Janis Henderson talking us through the winners and the 239 00:12:34,520 --> 00:12:36,320 Speaker 3: losers you're looking at in the moment. And look, we 240 00:12:36,360 --> 00:12:38,840 Speaker 3: were just finishing there on Apple and its focus or 241 00:12:38,920 --> 00:12:41,520 Speaker 3: like thereof on AI. Let's just talk about Apple overhauling 242 00:12:41,520 --> 00:12:45,800 Speaker 3: therefore its entire magline with in house processes that, guess what, 243 00:12:45,920 --> 00:12:48,240 Speaker 3: focus on artificial intelligence. We're going to bring you the 244 00:12:48,320 --> 00:13:01,480 Speaker 3: details next. This is BLUEBG Technology. It's looking to boost 245 00:13:01,520 --> 00:13:04,360 Speaker 3: some lagging computer sales with an overhaul of its entire 246 00:13:04,440 --> 00:13:08,400 Speaker 3: Mac line, planning to unveil an AI focused M four processor. 247 00:13:08,760 --> 00:13:11,760 Speaker 3: Apple is aiming to release the updated computers beginning actually 248 00:13:11,840 --> 00:13:14,600 Speaker 3: late this year extending into early next year. Joining us 249 00:13:14,679 --> 00:13:17,720 Speaker 3: now with this scoop of course, Roomberg's Mark German and Mark, 250 00:13:18,080 --> 00:13:21,160 Speaker 3: this is a very quick upgrade. Basically the cycle is 251 00:13:21,160 --> 00:13:21,680 Speaker 3: so short. 252 00:13:22,800 --> 00:13:24,160 Speaker 8: Yeah, good morning, thank you for having me. 253 00:13:24,200 --> 00:13:26,360 Speaker 9: I mean, Apple Silicon started off on about a one 254 00:13:26,400 --> 00:13:28,720 Speaker 9: point five year, one and a half year upgrade cycle, 255 00:13:29,080 --> 00:13:31,800 Speaker 9: and they've accelerated that. The M three chips came a 256 00:13:31,840 --> 00:13:35,960 Speaker 9: little sooner than anticipated in October of twenty twenty three. 257 00:13:35,960 --> 00:13:38,480 Speaker 8: So just about six months ago. Now the M four. 258 00:13:38,400 --> 00:13:40,199 Speaker 9: Chips are going to be coming even sooner than that, 259 00:13:40,360 --> 00:13:43,640 Speaker 9: coming about one year after the M three processors. So 260 00:13:43,679 --> 00:13:47,920 Speaker 9: they're planning new Imax Macminie's low and macropros high end 261 00:13:47,920 --> 00:13:51,199 Speaker 9: nec pros. Like you said, for release between the end 262 00:13:51,200 --> 00:13:53,760 Speaker 9: of twenty four and early twenty five. So this is 263 00:13:53,800 --> 00:13:57,319 Speaker 9: an accelerated timeline. And it's interesting because this is now 264 00:13:57,400 --> 00:14:01,200 Speaker 9: matching the timeline of processor upgrades that you see on 265 00:14:01,320 --> 00:14:04,120 Speaker 9: the iPhone and that you once saw on the iPad 266 00:14:04,160 --> 00:14:04,920 Speaker 9: but no longer. 267 00:14:05,320 --> 00:14:06,880 Speaker 8: And this is pretty significant. 268 00:14:07,040 --> 00:14:10,360 Speaker 9: In house silicon is becoming an even more important part 269 00:14:10,480 --> 00:14:13,720 Speaker 9: of the company's story. There are other companies that are 270 00:14:13,720 --> 00:14:15,760 Speaker 9: so hyper focused on the cloud and such. 271 00:14:15,800 --> 00:14:18,280 Speaker 8: Apple is still focused on in device chips. 272 00:14:19,320 --> 00:14:21,600 Speaker 4: I think that's where we should focus mark. 273 00:14:21,640 --> 00:14:25,560 Speaker 5: Our last guest, Alison Porter at Janis, is an Apple shareholder, 274 00:14:26,000 --> 00:14:28,320 Speaker 5: and what she just told us is that to her mind, 275 00:14:28,400 --> 00:14:32,280 Speaker 5: Apple's role in AI has yet to be defined. But 276 00:14:32,360 --> 00:14:35,000 Speaker 5: I look at where the stock closed Thursday after you 277 00:14:35,080 --> 00:14:39,200 Speaker 5: published your report, and again the momentum today, and I 278 00:14:39,200 --> 00:14:42,200 Speaker 5: think the market sees an AI story. What are you 279 00:14:42,240 --> 00:14:44,640 Speaker 5: hearing internally at Apple about this side of it? 280 00:14:46,960 --> 00:14:50,800 Speaker 9: The AI story at Apple exists, and it's almost the 281 00:14:50,880 --> 00:14:53,360 Speaker 9: complete opposite of what you're seeing from other companies. 282 00:14:53,680 --> 00:14:54,680 Speaker 8: There's so much hype. 283 00:14:54,520 --> 00:14:58,240 Speaker 9: Around in Nvidia because of their cloud infrastructure that powers 284 00:14:58,320 --> 00:14:59,320 Speaker 9: artificial intelligence. 285 00:14:59,360 --> 00:15:02,640 Speaker 8: There's Chat, g ABT and Gemini. Those are all cloud products. 286 00:15:02,760 --> 00:15:06,360 Speaker 9: Apple's LM is an on device approach, meaning it runs 287 00:15:06,480 --> 00:15:09,440 Speaker 9: entirely on the device, which makes it more privacy centric, 288 00:15:09,480 --> 00:15:13,160 Speaker 9: but also in some cases it can perform actions far 289 00:15:13,240 --> 00:15:15,640 Speaker 9: quickly there is no lag time because it's on the 290 00:15:15,680 --> 00:15:18,960 Speaker 9: devices themselves. And these new AI chips are the upgraded 291 00:15:19,000 --> 00:15:22,280 Speaker 9: AI components that you're seeing on the M four during 292 00:15:22,320 --> 00:15:25,400 Speaker 9: later this year, as well as the aaighteen pro chip 293 00:15:26,080 --> 00:15:29,360 Speaker 9: that you'll see in the iPhone sixteen Pro and Promax 294 00:15:29,440 --> 00:15:34,480 Speaker 9: Leader this year. Upgraded neural engines, improved processing, improved microphones 295 00:15:34,760 --> 00:15:38,800 Speaker 9: to really optimize artificial intelligence and serri on a device. Now, 296 00:15:38,960 --> 00:15:41,520 Speaker 9: we should note that Apple has been shipping neural engines 297 00:15:41,560 --> 00:15:44,640 Speaker 9: those AI blocks inside of their chips for several years now, 298 00:15:44,680 --> 00:15:47,920 Speaker 9: but this is going to be dubbed the biggest upgrade 299 00:15:47,920 --> 00:15:50,400 Speaker 9: to the neural engine since that component was first released 300 00:15:50,400 --> 00:15:51,040 Speaker 9: several years ago. 301 00:15:52,000 --> 00:15:55,240 Speaker 5: Blue bos Mark German brilliant, thank you. Coming up on 302 00:15:55,280 --> 00:15:58,360 Speaker 5: the show Docu sign unveiling a new platform and an 303 00:15:58,360 --> 00:16:01,120 Speaker 5: expansion of his company's rategy. We're going to discuss that 304 00:16:01,160 --> 00:16:04,760 Speaker 5: with the CEO, Alan Tigerson. That's next. This is Bloomberg, 305 00:16:19,720 --> 00:16:22,120 Speaker 5: this is Talking Tech and in the news Tokyo based 306 00:16:22,160 --> 00:16:27,280 Speaker 5: startup Sakana AI is capitalizing on surging interest from Japanese firms. 307 00:16:27,320 --> 00:16:30,160 Speaker 4: Founded by ex Google researchers. 308 00:16:29,680 --> 00:16:34,240 Speaker 5: Sicana won government supercomputer grants and partnerships with blue chip companies. 309 00:16:34,280 --> 00:16:38,080 Speaker 5: This isn't an effort to build out Japan's AI ecosystem. 310 00:16:38,280 --> 00:16:42,520 Speaker 5: Sakana uses small data sets to train low cost GENAI 311 00:16:42,600 --> 00:16:45,160 Speaker 5: models that could be used to ramp up a company's 312 00:16:45,400 --> 00:16:46,680 Speaker 5: AI capabilities. 313 00:16:46,760 --> 00:16:48,240 Speaker 4: Plus, Samsung is. 314 00:16:48,160 --> 00:16:50,800 Speaker 5: Set to unveil a forty four billion dollar push into 315 00:16:51,000 --> 00:16:54,600 Speaker 5: US chip making as soon as next week. According to sources, 316 00:16:54,960 --> 00:16:58,440 Speaker 5: they're going to outline a project in Taylor, Texas, after 317 00:16:58,520 --> 00:17:00,200 Speaker 5: securing more than six billion. 318 00:17:00,520 --> 00:17:01,520 Speaker 4: From government grants. 319 00:17:01,600 --> 00:17:04,440 Speaker 5: The award marks the latest push from the Biden administration 320 00:17:04,760 --> 00:17:08,439 Speaker 5: to revitalize chip making in the United States, and the 321 00:17:08,480 --> 00:17:12,120 Speaker 5: House is set to try again on advancing the reauthorization 322 00:17:12,280 --> 00:17:16,280 Speaker 5: of a US spy bill. The Foreign Intelligent Surveillance Act, 323 00:17:16,320 --> 00:17:19,639 Speaker 5: failed to reach the floor on Wednesday over GOP concerns 324 00:17:19,640 --> 00:17:23,719 Speaker 5: of privacy and section seven zero two that provision allows 325 00:17:23,760 --> 00:17:28,360 Speaker 5: the surveillance of foreign targets and the potential to warrant 326 00:17:28,400 --> 00:17:31,399 Speaker 5: leslie survey americans in contact with them. 327 00:17:31,440 --> 00:17:33,280 Speaker 4: The bill underwent a revision. 328 00:17:33,200 --> 00:17:36,320 Speaker 5: To a two year period from five in an attempt 329 00:17:36,480 --> 00:17:38,879 Speaker 5: to swing its Republican critics. 330 00:17:38,920 --> 00:17:43,200 Speaker 3: Caroline, let's move away from politics to product announcements. Now 331 00:17:43,280 --> 00:17:46,800 Speaker 3: dog you sign holdings and it's just annual Momentum Music 332 00:17:46,840 --> 00:17:49,439 Speaker 3: conference this week, and it set us up with some 333 00:17:49,480 --> 00:17:53,960 Speaker 3: new products that include an intelligent agreement management platform. I'll 334 00:17:53,960 --> 00:17:57,160 Speaker 3: stick into exactly what that is, Doc sign CEO Alan Tinkerson, 335 00:17:57,200 --> 00:18:01,640 Speaker 3: and please to welcome you, thanks for joining category. It's 336 00:18:01,680 --> 00:18:03,840 Speaker 3: different from what people already experience. 337 00:18:04,680 --> 00:18:07,840 Speaker 2: Well, so people know us mostly for a signature and 338 00:18:07,880 --> 00:18:10,200 Speaker 2: that will continue. But if you think about agreements, they 339 00:18:10,240 --> 00:18:13,159 Speaker 2: go to an entire journey, and there is pain and 340 00:18:13,200 --> 00:18:15,560 Speaker 2: inefficiency at every point in that journey. If you think 341 00:18:15,560 --> 00:18:18,959 Speaker 2: about salespeople from when they maybe reach agreement and principle 342 00:18:19,000 --> 00:18:21,240 Speaker 2: to when they can finally sign an agreement, or a 343 00:18:21,280 --> 00:18:23,800 Speaker 2: purchasing manager who's trying to figure out whether their vendors 344 00:18:23,840 --> 00:18:26,600 Speaker 2: are living up to their obligations, or a recruiter trying 345 00:18:26,640 --> 00:18:29,080 Speaker 2: to close a candidate, those are all at their core 346 00:18:29,280 --> 00:18:33,480 Speaker 2: agreement problems. And we are delivering a suite to help 347 00:18:33,600 --> 00:18:37,880 Speaker 2: companies solve their entire range of agreement problems and so. 348 00:18:37,800 --> 00:18:40,199 Speaker 3: I'm a company, I have suddenly a central depository. I 349 00:18:40,240 --> 00:18:42,800 Speaker 3: know exactly where all of my legal agreements are, and 350 00:18:42,840 --> 00:18:46,080 Speaker 3: I can use generative AI to summarize them to ensure 351 00:18:46,119 --> 00:18:48,640 Speaker 3: that I'm learning the most see whether ensure that they're 352 00:18:48,640 --> 00:18:52,359 Speaker 3: basically following a theme, all in line and purpose. Why 353 00:18:52,440 --> 00:18:54,760 Speaker 3: is this different from what perhaps when you unveil it 354 00:18:54,800 --> 00:18:57,000 Speaker 3: in late May, what box cauld suddenly bring us with 355 00:18:57,080 --> 00:18:59,960 Speaker 3: their central repository system and suddenly bring in GENAI. 356 00:19:00,240 --> 00:19:02,400 Speaker 2: Yes, well, there are lots of folks who do storage 357 00:19:02,760 --> 00:19:05,760 Speaker 2: and more generally manage documents. 358 00:19:05,359 --> 00:19:07,240 Speaker 10: But agreements are very, very unique. 359 00:19:07,359 --> 00:19:09,520 Speaker 2: They have a particular structure, there's a tremendous amount of 360 00:19:09,560 --> 00:19:12,199 Speaker 2: data in and you need to understand the context. And 361 00:19:12,240 --> 00:19:14,879 Speaker 2: so we are I think experts are that the largest players. 362 00:19:14,880 --> 00:19:17,639 Speaker 2: So they've focused on agreements and have a tremendous amount 363 00:19:17,640 --> 00:19:21,040 Speaker 2: of domain knowledge, understanding of the intricacy of agreements. And 364 00:19:21,119 --> 00:19:24,160 Speaker 2: there's also workflow associated agreements, and then we're bringing out 365 00:19:24,200 --> 00:19:27,280 Speaker 2: tools to help companies deliver those in a much more 366 00:19:27,280 --> 00:19:28,720 Speaker 2: delightful and digitally neative way. 367 00:19:30,160 --> 00:19:34,399 Speaker 5: Alan, Good morning, Zed in San Francisco. In the history 368 00:19:34,400 --> 00:19:38,200 Speaker 5: of technology, there are companies that completely reinvent themselves, right. 369 00:19:38,200 --> 00:19:39,680 Speaker 4: Take BlackBerry as an example. 370 00:19:40,119 --> 00:19:44,160 Speaker 5: You used to make smartphones, it now largely makes automotive software. 371 00:19:45,440 --> 00:19:49,119 Speaker 5: The E signature product is still everything for you guys. 372 00:19:49,400 --> 00:19:51,600 Speaker 5: But I wonder if you are trying to tell your 373 00:19:51,600 --> 00:19:54,440 Speaker 5: investors you're used as your audience, that you see a 374 00:19:54,480 --> 00:19:58,200 Speaker 5: future for DocuSign where it's something different beyond E signature, 375 00:19:58,480 --> 00:20:00,960 Speaker 5: where the main business is not E signature. 376 00:20:01,720 --> 00:20:04,960 Speaker 2: Well, certainly beyond these signature, but E Signature will be 377 00:20:05,200 --> 00:20:07,600 Speaker 2: critical to docu sign for years to come. It's such 378 00:20:07,600 --> 00:20:10,720 Speaker 2: a valuable product, solves such a unique pain point very well, 379 00:20:11,119 --> 00:20:13,720 Speaker 2: and after all, the signature moment is a pivotal to 380 00:20:13,720 --> 00:20:17,000 Speaker 2: have the highest value moment in that agreement journey. What 381 00:20:17,040 --> 00:20:19,360 Speaker 2: we're doing here is where we are expanding and providing 382 00:20:19,359 --> 00:20:22,680 Speaker 2: a full suite of offerings related to every step in 383 00:20:22,720 --> 00:20:25,240 Speaker 2: the agreement journey. No one has done that before. I 384 00:20:25,240 --> 00:20:27,399 Speaker 2: think we're the best position to do it. We have 385 00:20:27,480 --> 00:20:29,840 Speaker 2: the trust, we have the customer reach and the expertise, 386 00:20:30,280 --> 00:20:33,080 Speaker 2: and we're benefiting from recent developments in AI and so 387 00:20:33,119 --> 00:20:35,200 Speaker 2: we're bringing all that to the table and I think 388 00:20:35,240 --> 00:20:36,000 Speaker 2: now it's our moment. 389 00:20:37,119 --> 00:20:39,280 Speaker 5: Alan, You've told a lot about doc You sign being 390 00:20:39,320 --> 00:20:43,160 Speaker 5: in transition. In considering where you are in that transition, 391 00:20:43,280 --> 00:20:47,480 Speaker 5: give yourself a scorecard ABC on your performance and where 392 00:20:47,480 --> 00:20:50,479 Speaker 5: you've been in delivering that well. 393 00:20:50,600 --> 00:20:53,080 Speaker 2: I like to measure outcomes, so I was certainly wouldn't 394 00:20:53,119 --> 00:20:55,639 Speaker 2: hear myself at a yet. I think we are making 395 00:20:55,680 --> 00:20:56,520 Speaker 2: really good progress. 396 00:20:56,600 --> 00:20:57,080 Speaker 10: Give it a bit. 397 00:20:57,160 --> 00:21:00,679 Speaker 2: We have done I think an excellent job idolizing the 398 00:21:00,720 --> 00:21:04,680 Speaker 2: innovation engine now bringing out a really really robust suite 399 00:21:04,760 --> 00:21:08,640 Speaker 2: of products informed by years of customer feedback and tremendous 400 00:21:08,680 --> 00:21:11,840 Speaker 2: engagement for beta customers. And now it's time to take 401 00:21:11,880 --> 00:21:13,960 Speaker 2: that to market and roll it out across all of 402 00:21:14,000 --> 00:21:17,359 Speaker 2: the customer segments and geographies and industries that Docu Science serves, 403 00:21:17,560 --> 00:21:20,000 Speaker 2: and that will be a multi year journey. So certainly 404 00:21:20,000 --> 00:21:22,760 Speaker 2: not job's not done yet, but this is a major 405 00:21:22,800 --> 00:21:25,520 Speaker 2: milestone for us, and we're very excited about what the 406 00:21:25,520 --> 00:21:26,159 Speaker 2: future holds. 407 00:21:26,840 --> 00:21:28,800 Speaker 3: It comes to bear and you may come and tell 408 00:21:28,840 --> 00:21:30,720 Speaker 3: us how it all goes. Antikason, it's so great to 409 00:21:30,760 --> 00:21:32,320 Speaker 3: have some time with you. Thank you for stopping by 410 00:21:32,320 --> 00:21:40,160 Speaker 3: the studio. Docu Signed CEO. 411 00:21:42,040 --> 00:21:45,159 Speaker 5: Welcome back to Bloomberg Technology. Ed Ludlow here in San Francisco, 412 00:21:45,240 --> 00:21:45,919 Speaker 5: car and Hid. 413 00:21:45,800 --> 00:21:46,200 Speaker 10: In New York. 414 00:21:46,320 --> 00:21:48,360 Speaker 3: Quick check on these markets as we head towards the weekend, 415 00:21:48,400 --> 00:21:51,040 Speaker 3: and some caution in those markets risk aversion as we 416 00:21:51,320 --> 00:21:54,480 Speaker 3: worry about geopolitical risks Israel around front of mind for many. 417 00:21:54,480 --> 00:21:57,400 Speaker 3: We're seeing tech slocks all the benchmarks and in equities 418 00:21:57,440 --> 00:21:59,920 Speaker 3: actually down amid some of that taking risk of the 419 00:22:00,040 --> 00:22:01,919 Speaker 3: table as money goes into the one market, into the 420 00:22:01,960 --> 00:22:04,280 Speaker 3: US dollar for example, or off by some seven basis points. 421 00:22:04,400 --> 00:22:07,000 Speaker 3: But tech also getting dragged down by Chips. I'll speak 422 00:22:07,000 --> 00:22:09,080 Speaker 3: to that in a moment. Looking at Bitcoin, another key 423 00:22:09,160 --> 00:22:11,760 Speaker 3: risk asset, just lower as the dollar goes higher. On 424 00:22:11,760 --> 00:22:13,560 Speaker 3: some of this risker version. We're off by more than 425 00:22:13,600 --> 00:22:15,600 Speaker 3: a percentage point, but basically flat over the last five 426 00:22:15,600 --> 00:22:17,840 Speaker 3: trading days. Move on, have a little look what's happening 427 00:22:17,880 --> 00:22:20,480 Speaker 3: on the individual movers because for once, actually Apple is 428 00:22:20,520 --> 00:22:22,560 Speaker 3: on the higher side. We're still one hundred and seventy 429 00:22:22,600 --> 00:22:24,680 Speaker 3: six there or thereabouts. But this as we understand, thanks 430 00:22:24,720 --> 00:22:27,600 Speaker 3: to Mark German, they are looking to overhaul the processes 431 00:22:27,640 --> 00:22:29,720 Speaker 3: within some of their Mac lineup and four coming to 432 00:22:29,760 --> 00:22:33,160 Speaker 3: the fore and indeed AI front and center on your computer. 433 00:22:33,400 --> 00:22:36,159 Speaker 3: We're up by seven tens of percent. Socks, so Chip stocks. 434 00:22:36,160 --> 00:22:38,760 Speaker 3: In fact, every single member of this particular index is 435 00:22:38,800 --> 00:22:41,719 Speaker 3: in the red today. Why Wall Street Journal reporting that 436 00:22:41,840 --> 00:22:43,720 Speaker 3: China is now looking to fight back when it comes 437 00:22:43,720 --> 00:22:45,720 Speaker 3: to that tip for TAT and chip access and they're 438 00:22:45,760 --> 00:22:48,960 Speaker 3: saying to their Chinese cellcom giants, don't have foreign made 439 00:22:49,000 --> 00:22:52,240 Speaker 3: chips by twenty twenty seven into your overall networks. That's 440 00:22:52,320 --> 00:22:56,560 Speaker 3: sending AMD Intel in particular to the downside. This one's interesting. 441 00:22:56,680 --> 00:22:59,120 Speaker 3: It's basically been a mean stock of choice of late 442 00:22:59,320 --> 00:23:03,280 Speaker 3: Destiny one hundred d XYZ. It's a closed then fund 443 00:23:03,320 --> 00:23:06,000 Speaker 3: that gets you access to privately held companies if you 444 00:23:06,040 --> 00:23:08,840 Speaker 3: want to gain access to the likes of Malplaid or 445 00:23:09,240 --> 00:23:12,720 Speaker 3: whether it's Stripe, whether it's Open Ai, whether it's SpaceX. Well, 446 00:23:12,760 --> 00:23:14,960 Speaker 3: this has been a way of doing it, but it's 447 00:23:14,960 --> 00:23:18,760 Speaker 3: made itself a mean frenzy retail investors piling in one 448 00:23:18,840 --> 00:23:21,879 Speaker 3: thousand percent increase at one percent at point, having just 449 00:23:21,920 --> 00:23:23,879 Speaker 3: listed in the last month or so, we're down by 450 00:23:23,920 --> 00:23:26,560 Speaker 3: twenty two percent. But ed, it's not the only investment 451 00:23:26,640 --> 00:23:27,199 Speaker 3: vehicle doing this. 452 00:23:27,640 --> 00:23:30,439 Speaker 5: Yeah, hold that thought on Destiny Tech one hundred. We 453 00:23:30,480 --> 00:23:33,800 Speaker 5: will come back to it. Kafe Woods Arc Investment Management 454 00:23:34,119 --> 00:23:36,720 Speaker 5: has also announced that it holds a stake in open 455 00:23:36,760 --> 00:23:40,000 Speaker 5: Ai through its venture fund in a bet that the 456 00:23:40,040 --> 00:23:43,560 Speaker 5: AI industry will remake the tech landscape. Joining us now 457 00:23:44,000 --> 00:23:48,359 Speaker 5: is Brett Winton, who is our chief futurists also a 458 00:23:48,400 --> 00:23:50,520 Speaker 5: member of the investment committee. And Brett, you and I 459 00:23:50,640 --> 00:23:54,000 Speaker 5: volte last night you got access to open ai, which 460 00:23:54,080 --> 00:23:57,760 Speaker 5: is a private company with a closed profit structure through 461 00:23:57,760 --> 00:24:01,320 Speaker 5: a special purpose vehicle SPV. But it's part of a 462 00:24:01,359 --> 00:24:04,480 Speaker 5: broader thesis around foundation models. 463 00:24:04,880 --> 00:24:07,160 Speaker 4: Give me the short version of the thesis. 464 00:24:08,320 --> 00:24:13,879 Speaker 11: Sure, AI software is going to revolutionize knowledge work and 465 00:24:15,840 --> 00:24:19,040 Speaker 11: thirteen trillion dollars is going to be spent on AI software, 466 00:24:19,160 --> 00:24:22,040 Speaker 11: and three trillion of that is going to flow into 467 00:24:22,480 --> 00:24:24,600 Speaker 11: kind of what we think of as foundation model. So 468 00:24:24,800 --> 00:24:27,920 Speaker 11: open ai and Andropic are the two most prominent examples 469 00:24:27,920 --> 00:24:30,360 Speaker 11: with the best models in the marketplace, both of which 470 00:24:30,359 --> 00:24:35,280 Speaker 11: are in the venture fund. And three trillion dollars translates 471 00:24:35,280 --> 00:24:38,679 Speaker 11: into an expectation for around sixteen trillion dollars in marketcap 472 00:24:39,080 --> 00:24:40,920 Speaker 11: attributable to those foundation models. 473 00:24:40,960 --> 00:24:41,480 Speaker 12: So to give you. 474 00:24:41,440 --> 00:24:44,040 Speaker 11: Context, the global equity market is a little more than 475 00:24:44,080 --> 00:24:47,880 Speaker 11: one hundred trillion dollars as of the end of last year, 476 00:24:48,480 --> 00:24:51,639 Speaker 11: and so sixteen trillion. You know, it's a big chunk, 477 00:24:52,440 --> 00:24:56,960 Speaker 11: almost sector sized in terms of our expectations for enterprise 478 00:24:57,080 --> 00:24:57,800 Speaker 11: value foot print. 479 00:24:58,720 --> 00:25:02,080 Speaker 5: Our venture fund is an interval fund which is made 480 00:25:02,119 --> 00:25:07,120 Speaker 5: of eighty percent eight zero percent private companies twenty percent public. 481 00:25:07,840 --> 00:25:10,200 Speaker 5: You can get access not just only to open AI, 482 00:25:10,280 --> 00:25:15,760 Speaker 5: but SpaceX and anthropic. Why is it different or not 483 00:25:16,040 --> 00:25:19,879 Speaker 5: the same as the Destiny Tech one hundred that Caroline 484 00:25:19,960 --> 00:25:23,120 Speaker 5: was just explaining at the start of the segment. 485 00:25:24,119 --> 00:25:30,320 Speaker 11: Because our interval fund is continuously offered. The price that 486 00:25:30,400 --> 00:25:33,239 Speaker 11: you pay when you buy it is reflective of the 487 00:25:33,359 --> 00:25:36,399 Speaker 11: value of the underlying securities in it. So if you 488 00:25:36,440 --> 00:25:40,560 Speaker 11: buy one hundred dollars of an interval fund, you get 489 00:25:40,560 --> 00:25:44,159 Speaker 11: one hundred dollars of net asset value. The Destiny Fund 490 00:25:45,119 --> 00:25:49,040 Speaker 11: has a net asset value of less than five dollars, 491 00:25:49,320 --> 00:25:52,720 Speaker 11: and they don't issue additional shares even if there's access demand. 492 00:25:53,080 --> 00:25:56,040 Speaker 11: So if you buy the Destiny Fund at fifty dollars, 493 00:25:56,400 --> 00:26:00,879 Speaker 11: you're paying, you know, fifty dollars for five five dollars 494 00:26:00,920 --> 00:26:05,320 Speaker 11: worth of exposure. Like that fund, roughly a little more 495 00:26:05,359 --> 00:26:08,800 Speaker 11: than a third is SpaceX, but by one hundred dollars 496 00:26:08,800 --> 00:26:12,600 Speaker 11: of that versus one hundred dollars of our venture fund, 497 00:26:12,720 --> 00:26:16,119 Speaker 11: you actually end up with more exposure to SpaceX and 498 00:26:16,200 --> 00:26:19,320 Speaker 11: our venture fund, which is just four point four percent 499 00:26:19,480 --> 00:26:22,600 Speaker 11: or roughly four percent of the venture fund. So it's 500 00:26:22,640 --> 00:26:26,280 Speaker 11: really actually understand people want to get access to innovation. 501 00:26:26,400 --> 00:26:28,080 Speaker 12: I think that's absolutely the right thing to. 502 00:26:28,040 --> 00:26:31,119 Speaker 11: Do, and you need to be careful about how you 503 00:26:31,200 --> 00:26:33,320 Speaker 11: get access to innovation. You should do so in a 504 00:26:33,359 --> 00:26:36,040 Speaker 11: way where you're not buying, you know, ten cents worth 505 00:26:36,119 --> 00:26:38,880 Speaker 11: of stuff for a dollar worth of spending, so. 506 00:26:38,840 --> 00:26:41,600 Speaker 3: It's kind of down to structure and huge premium that 507 00:26:41,600 --> 00:26:44,880 Speaker 3: you're currently seeing on dxyz. Do you also think it's 508 00:26:44,920 --> 00:26:48,840 Speaker 3: something to do with the narrative this blew up on 509 00:26:49,160 --> 00:26:54,160 Speaker 3: Reddit and other like minded, sort of retail focused areas. 510 00:26:54,600 --> 00:26:57,400 Speaker 3: Do you think that your own ARC venture investment fund 511 00:26:57,440 --> 00:26:58,040 Speaker 3: will do the same. 512 00:27:00,359 --> 00:27:04,639 Speaker 11: I mean I think that, you know, I think that 513 00:27:04,720 --> 00:27:08,040 Speaker 11: people are excited about innovation and they're looking for ways 514 00:27:08,040 --> 00:27:11,399 Speaker 11: to access it, and this happened to kind of flash 515 00:27:11,440 --> 00:27:15,000 Speaker 11: across social media channels in a way that inspired them 516 00:27:15,040 --> 00:27:17,480 Speaker 11: to be like, oh, yes, I want access to that company, 517 00:27:18,280 --> 00:27:21,920 Speaker 11: and conceptually they are, and actually practically there are much 518 00:27:22,040 --> 00:27:25,840 Speaker 11: much more efficient and better ways to express that point. 519 00:27:25,840 --> 00:27:30,680 Speaker 11: Of view, and I think you can't, Like, you can't 520 00:27:30,720 --> 00:27:35,240 Speaker 11: tell beforehand what's going to you know, take off on Reddit, 521 00:27:35,480 --> 00:27:37,960 Speaker 11: but you can tell when something is going to end 522 00:27:37,960 --> 00:27:41,760 Speaker 11: in tears for people. And so when you're buying ten 523 00:27:41,840 --> 00:27:44,439 Speaker 11: cents for a dollar, you end up at the end 524 00:27:44,480 --> 00:27:47,160 Speaker 11: of the day with something close to ten cents, even 525 00:27:47,160 --> 00:27:49,040 Speaker 11: if it doesn't trade that Like, there's all kinds of 526 00:27:49,040 --> 00:27:53,720 Speaker 11: ways in which that premium should diminish over the time. 527 00:27:54,320 --> 00:27:57,200 Speaker 11: And so I would advise you to pay at a dollar 528 00:27:57,200 --> 00:27:58,560 Speaker 11: and get the dollars worth of stuff. 529 00:28:00,240 --> 00:28:04,679 Speaker 3: Well said, sixteen trillion dollars by twenty thirty. That's an 530 00:28:04,800 --> 00:28:07,600 Speaker 3: arresting figure when you think of the overall market valuation 531 00:28:07,920 --> 00:28:10,600 Speaker 3: for these foundational models, do you wish you could access 532 00:28:10,680 --> 00:28:14,520 Speaker 3: more open AI and ultimately anthropic as well? When you're 533 00:28:14,520 --> 00:28:16,400 Speaker 3: thinking of the rest that makes up the fund. When 534 00:28:16,440 --> 00:28:19,120 Speaker 3: I'm looking at SpaceX, but epic games as well, free 535 00:28:19,160 --> 00:28:22,320 Speaker 3: noome holdings, relation therapeutics, how much do you want foundational 536 00:28:22,359 --> 00:28:24,600 Speaker 3: models the AI bet to take up of this fund. 537 00:28:26,119 --> 00:28:27,919 Speaker 11: Well, the way we think about it is there are 538 00:28:28,040 --> 00:28:32,000 Speaker 11: five major technology platforms entering the marketplace, and each has 539 00:28:32,160 --> 00:28:35,680 Speaker 11: the potential for amazing compounding returns. And you're better off 540 00:28:35,760 --> 00:28:42,200 Speaker 11: constructing a portfolio that has yes AI exposure and autonomous 541 00:28:42,280 --> 00:28:48,720 Speaker 11: mobility exposure and multio mix exposure, because those exposures could 542 00:28:48,760 --> 00:28:51,720 Speaker 11: independently fail. Like are we one hundred percent right on AI? 543 00:28:51,960 --> 00:28:54,560 Speaker 11: I think it's going to be amazing and amazing revolution. 544 00:28:55,040 --> 00:28:58,360 Speaker 11: But if that that drags out to the right, it's 545 00:28:58,440 --> 00:29:01,960 Speaker 11: unlikely that currencies also will drag out to the right. 546 00:29:02,040 --> 00:29:05,400 Speaker 11: So by exposing yourself to a number of innovation platforms, 547 00:29:05,520 --> 00:29:08,480 Speaker 11: you actually end up with a more efficient exposure to 548 00:29:08,600 --> 00:29:12,360 Speaker 11: innovation as a whole that delivers better returns Brett. 549 00:29:12,480 --> 00:29:19,280 Speaker 5: Last night, Bloomberg reported that Xai Musk's AI company is 550 00:29:19,400 --> 00:29:21,920 Speaker 5: trying to raise between three and four billion dollars at 551 00:29:21,920 --> 00:29:26,680 Speaker 5: around an eighteen billion dollar valuation. According to Frankly, our sources, 552 00:29:26,680 --> 00:29:30,560 Speaker 5: but also a copy of the prospectus will arc through 553 00:29:30,600 --> 00:29:34,840 Speaker 5: the venture funds try and add XAI given your coverage 554 00:29:34,840 --> 00:29:36,480 Speaker 5: of SpaceX and Tesla already. 555 00:29:37,960 --> 00:29:42,680 Speaker 11: I can't comment on future decisions. I will say that 556 00:29:42,920 --> 00:29:46,840 Speaker 11: actually ownership in x confers a twenty five percent pro 557 00:29:46,920 --> 00:29:51,800 Speaker 11: rat ownership in Xai, and I think that the company's 558 00:29:52,480 --> 00:29:57,120 Speaker 11: future is actually closely intermingled. Xai's competitive advantage is it 559 00:29:57,160 --> 00:30:00,840 Speaker 11: has real time access to everything that happens on X 560 00:30:00,880 --> 00:30:03,080 Speaker 11: which is where our news effectively breaks. 561 00:30:03,400 --> 00:30:06,720 Speaker 12: And in a world in which historical data. 562 00:30:06,600 --> 00:30:09,719 Speaker 11: Is commoditized, which is part of what AI models are 563 00:30:09,760 --> 00:30:13,680 Speaker 11: going to do, real time data becomes more valuable and dear, 564 00:30:14,000 --> 00:30:16,880 Speaker 11: and so having a real time decision engine sitting at 565 00:30:16,880 --> 00:30:19,120 Speaker 11: the front end of X I think is a really 566 00:30:19,160 --> 00:30:22,720 Speaker 11: interesting and compelling value proposition for XAI. 567 00:30:23,760 --> 00:30:24,080 Speaker 4: Brett. 568 00:30:24,360 --> 00:30:26,680 Speaker 5: As you know, last night, I learned a lot about 569 00:30:26,720 --> 00:30:29,360 Speaker 5: the venture fund, the mechanics of how it works. It's actually, 570 00:30:29,840 --> 00:30:33,560 Speaker 5: I told you, very confusing. If you're a retail investor, 571 00:30:33,600 --> 00:30:38,720 Speaker 5: you can access through Fidelity Titan and I'm blanking. 572 00:30:38,360 --> 00:30:39,120 Speaker 4: There's a third one. 573 00:30:39,240 --> 00:30:43,720 Speaker 5: So fine, but my point so far, give me a 574 00:30:43,880 --> 00:30:47,080 Speaker 5: sense of how your announcement that you've built a pretty 575 00:30:47,080 --> 00:30:49,960 Speaker 5: small stake in open Ai has moved the needle for 576 00:30:50,000 --> 00:30:54,240 Speaker 5: that fund overnight this morning. Have you seen new customers 577 00:30:54,240 --> 00:30:57,800 Speaker 5: an investment try to rush in because they now know 578 00:30:57,920 --> 00:30:59,600 Speaker 5: that they can have some exposure there. 579 00:31:00,640 --> 00:31:02,440 Speaker 11: I mean, the honest answer is, I don't know, because 580 00:31:02,480 --> 00:31:06,320 Speaker 11: we don't get flows with you know that high degree 581 00:31:06,480 --> 00:31:12,560 Speaker 11: of frequency, and the decision to invest in these companies 582 00:31:12,680 --> 00:31:16,480 Speaker 11: is not a decision based upon how it's gonna attract attention. 583 00:31:16,880 --> 00:31:20,200 Speaker 11: It's because we underwrite the positions and we think they 584 00:31:20,240 --> 00:31:26,000 Speaker 11: deliver you know, outsized returns even relative to public market exposures. 585 00:31:26,000 --> 00:31:28,560 Speaker 11: So one of the benefits of this fund is, you know, 586 00:31:28,600 --> 00:31:31,480 Speaker 11: we can look at, hey, this is an interesting company, 587 00:31:31,600 --> 00:31:35,640 Speaker 11: and there's a comparable public company that that this is 588 00:31:35,680 --> 00:31:39,720 Speaker 11: actually cheaper than. And so I think that the the 589 00:31:40,600 --> 00:31:45,120 Speaker 11: you know, the potential for returns across all these technology 590 00:31:45,160 --> 00:31:49,000 Speaker 11: platforms is really profound, and we want every investor, not 591 00:31:49,120 --> 00:31:52,000 Speaker 11: just accredited investors, to be able to have access to 592 00:31:52,040 --> 00:31:52,760 Speaker 11: those returns. 593 00:31:53,480 --> 00:31:56,160 Speaker 3: R going back to the open AI thesis as one 594 00:31:56,200 --> 00:31:59,560 Speaker 3: of the winners of the six trillion dollar market. One 595 00:31:59,600 --> 00:32:03,000 Speaker 3: are themtions of it going up into the right because 596 00:32:03,560 --> 00:32:07,320 Speaker 3: there are concerns about ultimately supply chain this coalition that's 597 00:32:07,400 --> 00:32:10,400 Speaker 3: being built because we're worried about energy not only just 598 00:32:10,400 --> 00:32:12,640 Speaker 3: the amount of chips that are necessary that are going 599 00:32:12,680 --> 00:32:15,360 Speaker 3: to be building this future of generative AI, but also 600 00:32:15,640 --> 00:32:18,680 Speaker 3: is a competitive space right now. And also there's a 601 00:32:18,720 --> 00:32:21,120 Speaker 3: weird corporate governance structure that goes on over over AI. 602 00:32:21,240 --> 00:32:23,000 Speaker 3: What are the risks for you on that name? 603 00:32:23,880 --> 00:32:24,880 Speaker 12: Sure, I mean are. 604 00:32:25,040 --> 00:32:28,560 Speaker 11: There are corporate governance structures risks, and you know you 605 00:32:28,600 --> 00:32:31,600 Speaker 11: can underwrite those, so we've gone through and assess them, 606 00:32:31,640 --> 00:32:35,239 Speaker 11: but there is a degree of uncertainty there. There are 607 00:32:35,240 --> 00:32:39,120 Speaker 11: regulatory risks across all of technology exposures. I think that 608 00:32:40,520 --> 00:32:43,360 Speaker 11: we look back to even like nuclear power is an 609 00:32:43,400 --> 00:32:48,360 Speaker 11: amazing technology that was effectively derailed because of kind of 610 00:32:48,000 --> 00:32:52,600 Speaker 11: the regulatory burdens put upon it back in the nineteen seventies, 611 00:32:52,960 --> 00:32:55,800 Speaker 11: and there's the potential that that could happen with AI 612 00:32:55,880 --> 00:32:58,280 Speaker 11: as well, where we're worried about something and so we 613 00:32:59,120 --> 00:33:02,360 Speaker 11: deny ourselves all the benefits of it, but still take 614 00:33:02,400 --> 00:33:03,479 Speaker 11: on all of the risks. 615 00:33:04,720 --> 00:33:08,120 Speaker 12: And we think that there's a room for commercial. 616 00:33:07,600 --> 00:33:10,960 Speaker 11: Models like open AI and anthropics and open source models 617 00:33:11,000 --> 00:33:12,440 Speaker 11: like what Meta is developing. 618 00:33:12,480 --> 00:33:14,160 Speaker 12: I think that the market will have a. 619 00:33:14,080 --> 00:33:18,240 Speaker 11: Handful of solutions, any one of which could be profoundly valuable. 620 00:33:18,480 --> 00:33:21,760 Speaker 11: And when you have this much market opportunity ahead of you, 621 00:33:21,760 --> 00:33:25,520 Speaker 11: you know, you go for that asymmetric return where kind 622 00:33:25,520 --> 00:33:30,120 Speaker 11: of like the one or two winners here are going 623 00:33:30,160 --> 00:33:32,840 Speaker 11: to be profoundly valuable. And so we think an exposure 624 00:33:32,920 --> 00:33:35,640 Speaker 11: is appropriate and actually necessary. 625 00:33:36,960 --> 00:33:40,560 Speaker 5: Brett Winston, the Bench Investmental Walk Investment Management is great 626 00:33:40,560 --> 00:33:41,360 Speaker 5: to have you on the program. 627 00:33:41,400 --> 00:33:43,600 Speaker 4: Thank you very much for your time. We'll be right back. 628 00:33:43,600 --> 00:33:44,080 Speaker 4: Stay changed. 629 00:33:44,080 --> 00:34:00,680 Speaker 5: This is butting Back Technology. 630 00:33:58,560 --> 00:34:01,320 Speaker 3: New York based adicle. It's just announced it's raised two 631 00:34:01,360 --> 00:34:04,680 Speaker 3: hundred and fifty million dollars in taking on external investors 632 00:34:04,720 --> 00:34:08,000 Speaker 3: for the first time. The person behind Ali Corn is 633 00:34:08,000 --> 00:34:10,960 Speaker 3: known as the godfather of VC here in New York, 634 00:34:11,040 --> 00:34:13,680 Speaker 3: Kevin Ryan, founder CEO of that business. We welcome into 635 00:34:13,719 --> 00:34:18,400 Speaker 3: VC Spotlight. And before you spent a lot of time 636 00:34:18,880 --> 00:34:22,640 Speaker 3: and focus on small sized businesses investing your own money 637 00:34:22,640 --> 00:34:24,480 Speaker 3: because you had a huge exit back in the day, 638 00:34:24,520 --> 00:34:27,160 Speaker 3: having of course been the CEO co founder of double 639 00:34:27,160 --> 00:34:31,480 Speaker 3: Click sold it to Google. Now, what is the reason 640 00:34:31,480 --> 00:34:33,040 Speaker 3: you're bringing on external LPs. 641 00:34:33,480 --> 00:34:34,960 Speaker 10: Yeah, it's more thinking long term. 642 00:34:35,000 --> 00:34:37,640 Speaker 13: You know, I'm still a very important LP in this 643 00:34:37,719 --> 00:34:39,600 Speaker 13: fun But when I think over the next twenty twenty 644 00:34:39,600 --> 00:34:41,520 Speaker 13: five years, I think ALLI Corp. Will be a firm 645 00:34:41,560 --> 00:34:43,880 Speaker 13: that is here, that is very present, that is going 646 00:34:43,960 --> 00:34:45,640 Speaker 13: to be one of the leading firms. And to do that, 647 00:34:45,680 --> 00:34:48,680 Speaker 13: you want to have sustainable source of money for the 648 00:34:48,719 --> 00:34:49,760 Speaker 13: next seven funds. 649 00:34:49,920 --> 00:34:51,960 Speaker 10: And so this is the beginning step for. 650 00:34:51,960 --> 00:34:55,760 Speaker 3: That beginning step in taking bets on beginning businesses seeds 651 00:34:56,000 --> 00:34:57,000 Speaker 3: and theeries. A. 652 00:34:57,120 --> 00:34:58,640 Speaker 13: Yeah, it's not changing what we're doing yet. We do 653 00:34:58,680 --> 00:35:01,040 Speaker 13: two things. We start companies from scratch, so I start 654 00:35:01,160 --> 00:35:03,680 Speaker 13: six to eight companies a year, and then we invest 655 00:35:03,719 --> 00:35:05,920 Speaker 13: in probably fifteen to twenty. So we have a portfolio 656 00:35:05,920 --> 00:35:08,000 Speaker 13: of over one hundred companies and I have a twenty 657 00:35:08,000 --> 00:35:09,920 Speaker 13: four person team, and so we've been doing that. We're 658 00:35:09,920 --> 00:35:11,880 Speaker 13: going to continue to do that, and we're still seeing 659 00:35:12,120 --> 00:35:13,640 Speaker 13: incredible opportunities out there. 660 00:35:14,120 --> 00:35:17,279 Speaker 3: Many would know you for helping seed Mongo d B, 661 00:35:17,480 --> 00:35:19,640 Speaker 3: which of course Big Exit traded hair in New York. 662 00:35:19,719 --> 00:35:21,440 Speaker 3: But is that still the kind of company you want 663 00:35:21,480 --> 00:35:23,200 Speaker 3: to be getting into. We're all talking about general to 664 00:35:23,239 --> 00:35:25,160 Speaker 3: AI at the moment, but you're also focused on healthcare. 665 00:35:25,239 --> 00:35:26,839 Speaker 3: Tell us the theses that you want to get. 666 00:35:26,920 --> 00:35:28,719 Speaker 13: Yes, we have a couple different industry groups that we're 667 00:35:28,719 --> 00:35:31,440 Speaker 13: focused on, so AI is definitely important thing. I just 668 00:35:31,520 --> 00:35:33,919 Speaker 13: started a company with some people on my team called 669 00:35:34,040 --> 00:35:38,000 Speaker 13: Radical that is a company focused on AI for material science. 670 00:35:38,320 --> 00:35:41,320 Speaker 13: There's a very specific, very technical area and an enormous, 671 00:35:41,520 --> 00:35:44,200 Speaker 13: enormous area, so that's a fundamental trend. Last year we 672 00:35:44,239 --> 00:35:47,200 Speaker 13: started a company in assisted fertility. You and I both 673 00:35:47,239 --> 00:35:49,399 Speaker 13: know that twenty years ago, none of our friends were 674 00:35:49,400 --> 00:35:52,319 Speaker 13: having their eggs frozen or IVF. That's growing, it will 675 00:35:52,320 --> 00:35:54,520 Speaker 13: continue to grow for the next ten years. We have 676 00:35:54,560 --> 00:35:57,040 Speaker 13: a big healthcare portfolio, so president in a lot of 677 00:35:57,040 --> 00:36:00,840 Speaker 13: different areas, mental health areas in particular, psychedelic in particular. 678 00:36:01,120 --> 00:36:04,440 Speaker 13: Started one company that's raised over fifty million dollars already, 679 00:36:04,600 --> 00:36:06,880 Speaker 13: and I'm looking to start another company in that space. 680 00:36:07,160 --> 00:36:10,040 Speaker 13: So the point is there are pockets and things to 681 00:36:10,080 --> 00:36:13,600 Speaker 13: be done. Technology is continuing to change the world and 682 00:36:13,640 --> 00:36:15,560 Speaker 13: make it a better place, and we just want to 683 00:36:15,840 --> 00:36:18,280 Speaker 13: think of these ideas or recognize them and help build 684 00:36:18,280 --> 00:36:18,840 Speaker 13: these companies. 685 00:36:20,400 --> 00:36:23,680 Speaker 5: Kevin, you called them pockets, but I kind of recognize 686 00:36:23,800 --> 00:36:26,400 Speaker 5: outliers of activity. You know, you see a lot of 687 00:36:26,440 --> 00:36:29,479 Speaker 5: rounds being done in AI. Actually I'm starting to see 688 00:36:29,520 --> 00:36:35,160 Speaker 5: some in industrial technology. But I guess the commonality of 689 00:36:35,200 --> 00:36:38,520 Speaker 5: the last four months is that each round, the check 690 00:36:38,600 --> 00:36:41,080 Speaker 5: size is getting bigger. Yeah, and I wondered if you 691 00:36:41,160 --> 00:36:43,960 Speaker 5: needed that two hundred and fifty million from outside investors 692 00:36:44,400 --> 00:36:46,520 Speaker 5: because you've got to write bigger checks. 693 00:36:47,239 --> 00:36:50,400 Speaker 13: No, our check size isn't really changing that much, you know, 694 00:36:50,640 --> 00:36:52,880 Speaker 13: I had invested over two hundred fifty million dollars in 695 00:36:52,880 --> 00:36:55,680 Speaker 13: the last several years, so this is a continuation of that. 696 00:36:56,360 --> 00:36:58,480 Speaker 13: These some of the you know, some of the companies 697 00:36:58,520 --> 00:37:01,680 Speaker 13: like Mango. You know, we started at fifteen years ago 698 00:37:01,760 --> 00:37:05,440 Speaker 13: with a million dollars. Dwight Merriman and I put that 699 00:37:05,520 --> 00:37:07,839 Speaker 13: money in, but we raised four hundred million dollars as 700 00:37:07,840 --> 00:37:09,960 Speaker 13: a private company and then spend another six hundred million 701 00:37:10,000 --> 00:37:11,839 Speaker 13: dollars as a public company to get to break even. 702 00:37:12,160 --> 00:37:14,440 Speaker 13: So large companies do take a lot of capital. We're 703 00:37:14,480 --> 00:37:16,440 Speaker 13: not going to provide all of it. Early stage investors 704 00:37:16,440 --> 00:37:18,880 Speaker 13: are taking the most risk and getting the most return 705 00:37:19,320 --> 00:37:21,480 Speaker 13: by coming up with that idea in the very beginning. 706 00:37:21,520 --> 00:37:23,359 Speaker 13: But luckily there are lots of late stage funds that 707 00:37:23,400 --> 00:37:25,160 Speaker 13: step in to help fund these. 708 00:37:26,920 --> 00:37:30,200 Speaker 5: Were you able to be selective with LPs or were 709 00:37:30,280 --> 00:37:32,760 Speaker 5: these LPs that were kind of coming to you and saying, 710 00:37:33,640 --> 00:37:36,359 Speaker 5: I want some exposure to what's happening in AI right now, 711 00:37:36,400 --> 00:37:37,480 Speaker 5: can you offer that to me? 712 00:37:38,120 --> 00:37:40,560 Speaker 13: Yeah, we were. Fortunately, we were able to be pretty selective. 713 00:37:40,640 --> 00:37:43,279 Speaker 13: We really just went out to family offices. It's a 714 00:37:43,280 --> 00:37:46,200 Speaker 13: pretty small list of people. We wanted families that would 715 00:37:46,239 --> 00:37:48,359 Speaker 13: add value. So these are all people that had come 716 00:37:48,400 --> 00:37:51,440 Speaker 13: from the healthcare industry, the technology industry, something else. We 717 00:37:51,520 --> 00:37:54,040 Speaker 13: can call on them if we want to do some 718 00:37:54,160 --> 00:37:57,520 Speaker 13: due diligence. So we're pretty happy with that list of investors. 719 00:37:57,560 --> 00:38:01,040 Speaker 13: We didn't go very widely. There aren't large institutions. We 720 00:38:01,080 --> 00:38:03,759 Speaker 13: don't have pension funds, because at least at this point, 721 00:38:03,800 --> 00:38:06,400 Speaker 13: they would add less value than some of the family offices. 722 00:38:07,440 --> 00:38:11,120 Speaker 3: I started this conversation by calling the godfather of NYC Tech, 723 00:38:11,360 --> 00:38:15,720 Speaker 3: and it is because NYC Tech is now getting really serious. 724 00:38:15,760 --> 00:38:17,839 Speaker 3: People do feel that there's an about change. And you've 725 00:38:17,840 --> 00:38:20,320 Speaker 3: been there for a long time saying there are businesses 726 00:38:20,320 --> 00:38:22,960 Speaker 3: to be built here, in businesses to invest in. Are 727 00:38:23,000 --> 00:38:25,200 Speaker 3: we just drinking our own kool aid here at the moment? 728 00:38:25,560 --> 00:38:26,759 Speaker 10: You know, it's incredibly clear. 729 00:38:26,800 --> 00:38:28,920 Speaker 13: It's the fastest growing and has been the fastest growing 730 00:38:28,920 --> 00:38:31,480 Speaker 13: tech center in the United States. Because people forget today 731 00:38:31,520 --> 00:38:33,840 Speaker 13: that twenty five years ago there was no tech in 732 00:38:33,840 --> 00:38:36,279 Speaker 13: New York. People would ask me, why is Doubleicke in 733 00:38:36,280 --> 00:38:37,600 Speaker 13: New York and why not in Boston. 734 00:38:37,760 --> 00:38:38,960 Speaker 10: No one would say that today. 735 00:38:39,160 --> 00:38:41,760 Speaker 13: So today in New York already employees as many people 736 00:38:41,760 --> 00:38:44,319 Speaker 13: in tech as San Francisco. There is no doubt in 737 00:38:44,360 --> 00:38:46,640 Speaker 13: my mind that when we're sitting here. Ten years from now, 738 00:38:46,840 --> 00:38:49,440 Speaker 13: New York will be a much bigger center of employment 739 00:38:49,480 --> 00:38:51,480 Speaker 13: for tech and will start to have some of the 740 00:38:51,640 --> 00:38:54,040 Speaker 13: very biggest companies out here. This is a place that 741 00:38:54,120 --> 00:38:57,959 Speaker 13: has human talent, the top graduates from the entire IVY League. 742 00:38:58,080 --> 00:39:00,319 Speaker 10: Mit. Everyone where do they want to live? To live 743 00:39:00,320 --> 00:39:00,959 Speaker 10: in New York City? 744 00:39:01,400 --> 00:39:03,840 Speaker 13: And that's what drives our industry and will continue to 745 00:39:03,920 --> 00:39:04,720 Speaker 13: drive the industry. 746 00:39:06,000 --> 00:39:09,160 Speaker 3: Sorry, Ed, I'm pretty sure they're still run for both 747 00:39:09,200 --> 00:39:12,239 Speaker 3: of us. Kevin Ryan of Ali Cole absolutely wonderful to 748 00:39:12,239 --> 00:39:13,040 Speaker 3: have you here on the show. 749 00:39:21,600 --> 00:39:25,319 Speaker 5: When Adobe released its Firefly image generating model last year, 750 00:39:25,360 --> 00:39:28,880 Speaker 5: the company said the artificial intelligence model was trained mainly 751 00:39:29,320 --> 00:39:33,000 Speaker 5: on Adobe stock Images, its database of hundreds of millions 752 00:39:33,040 --> 00:39:37,080 Speaker 5: of licensed images, but behind the scenes, Adobe was relying 753 00:39:37,239 --> 00:39:42,600 Speaker 5: in part on AI generated content to train Firefly, including 754 00:39:42,680 --> 00:39:45,960 Speaker 5: from those same AI rivals that we've been talking about 755 00:39:45,960 --> 00:39:49,160 Speaker 5: for many months. Blue both Rachel Mets broke that story 756 00:39:49,360 --> 00:39:52,240 Speaker 5: with Brody Ford and joins us. Now, so let's focus 757 00:39:52,360 --> 00:39:55,000 Speaker 5: very clearly on what the reporting on Earth Tier, what 758 00:39:55,120 --> 00:39:57,880 Speaker 5: the new part is, and I think it's that we 759 00:39:58,000 --> 00:40:01,239 Speaker 5: learned a lot more about how Firefly trained, but it's 760 00:40:01,320 --> 00:40:05,600 Speaker 5: different to what Adobe had originally told us precisely. 761 00:40:05,719 --> 00:40:05,799 Speaker 1: So. 762 00:40:06,000 --> 00:40:09,440 Speaker 14: Adobe has spoken a lot very publicly about how Firefly 763 00:40:09,920 --> 00:40:14,279 Speaker 14: is really different from the east rival image generators. And 764 00:40:14,360 --> 00:40:18,400 Speaker 14: it turns out that it included a bunch of AI 765 00:40:18,480 --> 00:40:21,560 Speaker 14: generated images, some of which are from mid journey in 766 00:40:21,640 --> 00:40:25,799 Speaker 14: the training of Firefly. This was something I uncovered in 767 00:40:25,840 --> 00:40:29,160 Speaker 14: my reporting. Brody and I work together to pull this 768 00:40:29,239 --> 00:40:33,719 Speaker 14: story together and found that the company had done this. 769 00:40:33,960 --> 00:40:36,680 Speaker 14: I mean, it was clearly done on purpose. It is 770 00:40:37,040 --> 00:40:39,000 Speaker 14: not a huge amount of its training data, but it's 771 00:40:39,000 --> 00:40:39,279 Speaker 14: in there. 772 00:40:39,280 --> 00:40:43,760 Speaker 3: Nonetheless, what's important is, of course that this was deemed 773 00:40:43,920 --> 00:40:47,600 Speaker 3: the ethical version of AI that you're paying for IP. 774 00:40:48,320 --> 00:40:50,840 Speaker 3: And there's been some murkiness, to say the very least 775 00:40:50,960 --> 00:40:54,200 Speaker 3: in some of the other rival foundational models and generative 776 00:40:54,440 --> 00:40:58,120 Speaker 3: models that we've seen. I'm interested as to what Adobe 777 00:40:58,120 --> 00:41:01,120 Speaker 3: said in response, because I'm sure they're aware of some 778 00:41:01,200 --> 00:41:04,840 Speaker 3: of these synthetic images that they were bringing in. Is 779 00:41:04,880 --> 00:41:07,399 Speaker 3: there any risk of IP in this one? 780 00:41:08,760 --> 00:41:11,359 Speaker 8: Adobe was totally aware of what it was doing. 781 00:41:11,440 --> 00:41:15,120 Speaker 14: I mean, we were looking at discord groups that the 782 00:41:15,160 --> 00:41:15,960 Speaker 14: company runs. 783 00:41:16,600 --> 00:41:17,680 Speaker 8: It was talking. 784 00:41:17,920 --> 00:41:20,520 Speaker 14: It had people from the company talking on discord groups 785 00:41:21,200 --> 00:41:25,279 Speaker 14: about including these images. They paid out a bonus in 786 00:41:25,320 --> 00:41:29,120 Speaker 14: September to other people whose images were used to train 787 00:41:29,280 --> 00:41:32,879 Speaker 14: the first version of Firefly, and that included people such 788 00:41:32,920 --> 00:41:35,240 Speaker 14: as one of my sources who was in the story, 789 00:41:35,520 --> 00:41:39,040 Speaker 14: who only contributed AI generated images to Adobe stock and 790 00:41:39,080 --> 00:41:41,680 Speaker 14: most of those were mid journey made with mid journey. 791 00:41:43,280 --> 00:41:45,680 Speaker 3: Fascinating as to therefore, how far back that we'll go? 792 00:41:46,200 --> 00:41:48,680 Speaker 3: Rachel Metz is a great story, just so much coming 793 00:41:48,680 --> 00:41:50,600 Speaker 3: out on Adobe at the moment. We appreciate her for it. 794 00:41:50,640 --> 00:41:52,640 Speaker 3: That does it for this dedition of blumotechnology. What a 795 00:41:52,680 --> 00:41:54,600 Speaker 3: wide ranging set of conversations we've had ed. 796 00:41:55,000 --> 00:41:59,760 Speaker 5: Yeah, it's been a pretty intense week newsflow and markets wise. 797 00:42:00,360 --> 00:42:03,040 Speaker 5: Now earning season comes and hits you in the face. 798 00:42:03,120 --> 00:42:04,600 Speaker 5: What a lot of fun we still have to have 799 00:42:04,920 --> 00:42:06,880 Speaker 5: recap the show. There was a lot of great Bloomberg 800 00:42:06,920 --> 00:42:10,480 Speaker 5: reporting on Apple on Adobe's just heard in some pretty 801 00:42:10,520 --> 00:42:14,319 Speaker 5: insightful interviews Brett Winton from ARC in particular on that 802 00:42:14,520 --> 00:42:18,160 Speaker 5: unusual investment in Open Ai. Recap Apple, Spotify, iHeart, and 803 00:42:18,200 --> 00:42:20,200 Speaker 5: we put the pod on the Bloomberg platforms. 804 00:42:20,960 --> 00:42:22,840 Speaker 4: Happy Friday. This is Bloomberg Technology