1 00:00:14,080 --> 00:00:17,360 Speaker 1: I'm Caroline Hyde in New York from Bloomberg's world headquarters, 2 00:00:17,680 --> 00:00:20,880 Speaker 1: and I'med Ludlow in San Francisco. This is Bloomberg Technology 3 00:00:20,960 --> 00:00:23,520 Speaker 1: in video. It surges, shares climb as much as fifteen 4 00:00:23,560 --> 00:00:27,280 Speaker 1: percent after the AI computing push, Trouvietz strong outlook. We'll 5 00:00:27,320 --> 00:00:30,800 Speaker 1: chip away and the details and we'll have the latest 6 00:00:30,840 --> 00:00:32,920 Speaker 1: in the world of crypto is sam Bank. Then Freed 7 00:00:32,960 --> 00:00:36,760 Speaker 1: faces new charges and coin Base launches a blockchain. We'll 8 00:00:36,760 --> 00:00:40,240 Speaker 1: discuss with Chris Lahane of Horn Ventures. Class Gorman Sacks 9 00:00:40,280 --> 00:00:44,400 Speaker 1: offering its wealthiest clients access to a fundraising round for Stripe. 10 00:00:44,640 --> 00:00:46,840 Speaker 1: That's as the payment's giant seeks to raise four billion 11 00:00:46,880 --> 00:00:50,080 Speaker 1: dollars from a wide range of investors. The best performer 12 00:00:50,120 --> 00:00:52,360 Speaker 1: in the SMP five hundred and as that one hundred 13 00:00:52,520 --> 00:00:55,640 Speaker 1: in video shares surging essentially because they give a strong 14 00:00:55,680 --> 00:00:58,800 Speaker 1: outlook for revenue. That kind of indicated to investors that 15 00:00:58,920 --> 00:01:02,600 Speaker 1: they're foura into artificial intelligence is helping boost them at 16 00:01:02,600 --> 00:01:05,440 Speaker 1: a time where PC demand is slowing and data center 17 00:01:05,520 --> 00:01:08,039 Speaker 1: demand slowing as well. Shares up forwarding percent, the biggest 18 00:01:08,120 --> 00:01:11,440 Speaker 1: jump since November. At one point up by even more 19 00:01:11,480 --> 00:01:13,759 Speaker 1: than that in the biggest jump since March of twenty twenty, 20 00:01:13,800 --> 00:01:15,200 Speaker 1: and I want to stick with this story and get 21 00:01:15,240 --> 00:01:18,360 Speaker 1: the investor perspective. Joining us now for more over is 22 00:01:18,440 --> 00:01:23,360 Speaker 1: Jonathan Curtis, Franklin Equity Group, Director of Portfolio Management, Franklin 23 00:01:23,400 --> 00:01:25,800 Speaker 1: Equity Group. Nearly one hundred and twenty billion dollars of 24 00:01:25,800 --> 00:01:28,559 Speaker 1: assets under management of Jonathan. You hold in video stock 25 00:01:28,880 --> 00:01:32,480 Speaker 1: in your funds? Is this chart on my screen? Is 26 00:01:32,520 --> 00:01:37,680 Speaker 1: this equity response justified? Is the height justified around this name? Well, 27 00:01:37,720 --> 00:01:40,640 Speaker 1: certainly Nvidios had a strong movie or to date here, 28 00:01:40,680 --> 00:01:44,480 Speaker 1: but certainly we think that the opportunity for artificial intelligence 29 00:01:44,920 --> 00:01:47,560 Speaker 1: is really just beginning in Nvidia said it's in a 30 00:01:47,680 --> 00:01:50,280 Speaker 1: very very strong position to capitalize on some of the 31 00:01:50,320 --> 00:01:53,160 Speaker 1: recent break views we've had with computers being able to 32 00:01:53,200 --> 00:01:58,040 Speaker 1: actually understand and generate both speech and an image content 33 00:01:58,120 --> 00:02:00,600 Speaker 1: now an Nvidia's right in the center of that. We 34 00:02:00,680 --> 00:02:03,760 Speaker 1: think that today's move was certainly exciting, but when you 35 00:02:03,760 --> 00:02:07,440 Speaker 1: look over the long term, Nvidia offers really solid return 36 00:02:07,480 --> 00:02:11,600 Speaker 1: potential floor investors. Jonathan talk us through how they are 37 00:02:11,600 --> 00:02:16,320 Speaker 1: so best placed to leverage artificial intelligence. Sure, so, Nvidia 38 00:02:16,480 --> 00:02:21,160 Speaker 1: makes graphics processors which have at their core the ability 39 00:02:21,200 --> 00:02:24,240 Speaker 1: to do vector math, which is right at the center 40 00:02:24,480 --> 00:02:29,280 Speaker 1: of how a lot of these artificial intelligence models operate. 41 00:02:30,160 --> 00:02:33,560 Speaker 1: The chat GPT three and a half has more than 42 00:02:33,560 --> 00:02:36,600 Speaker 1: one hundred and seventy billion parameters in that model, and 43 00:02:36,880 --> 00:02:41,760 Speaker 1: NVIDIAs processors are great at building up the models that 44 00:02:41,880 --> 00:02:44,840 Speaker 1: understand language and then ultimately allow it to be reproduced. 45 00:02:45,480 --> 00:02:49,760 Speaker 1: Similar technologies or techniques are used in generating images, and 46 00:02:49,919 --> 00:02:52,040 Speaker 1: NVIDIAs in the pole position for that. Not only were 47 00:02:52,080 --> 00:02:54,880 Speaker 1: the semiconductors they build, but then the software that they 48 00:02:54,919 --> 00:02:57,959 Speaker 1: build that really helps to augment and accelerate the usage 49 00:02:58,000 --> 00:03:01,480 Speaker 1: of their processors. But Invidios the only player in this category, 50 00:03:01,520 --> 00:03:03,800 Speaker 1: there are a lot of other players in this category 51 00:03:03,840 --> 00:03:07,280 Speaker 1: that we also own and are also very exciting in 52 00:03:07,280 --> 00:03:10,280 Speaker 1: that case, Jonathan, is in Vidia the best position name 53 00:03:10,360 --> 00:03:13,200 Speaker 1: that you're tracking or is there another in particular that 54 00:03:13,240 --> 00:03:16,200 Speaker 1: you're excited about that you think actually can grow a 55 00:03:16,280 --> 00:03:19,720 Speaker 1: business around the momentum and AI? Yeah, well so, certainly 56 00:03:19,800 --> 00:03:22,880 Speaker 1: in Vidia is the one that is best position. About 57 00:03:22,880 --> 00:03:25,200 Speaker 1: a third of their revenue, it's gonna be fifty percent 58 00:03:25,240 --> 00:03:27,399 Speaker 1: of their revenue, Almost sixty percent of their revenue comes 59 00:03:27,400 --> 00:03:29,880 Speaker 1: out of the data center and a large portion of 60 00:03:29,919 --> 00:03:33,200 Speaker 1: that comes out of cloud service providers, and a lot 61 00:03:33,200 --> 00:03:34,639 Speaker 1: of the growth that we think is going to come 62 00:03:34,639 --> 00:03:36,840 Speaker 1: in the years ahead is going to come on AI 63 00:03:36,920 --> 00:03:39,400 Speaker 1: in the building of these large language models. That said, 64 00:03:39,760 --> 00:03:42,280 Speaker 1: there are other players in the semiconductor ecosystem that are 65 00:03:42,320 --> 00:03:46,160 Speaker 1: also well positioned. AMD with its zilings acquisition a latt 66 00:03:46,160 --> 00:03:48,960 Speaker 1: of semiconductor certainly a TSMC where a lot of these 67 00:03:48,960 --> 00:03:55,360 Speaker 1: advantage chips are manufactured. Then in electronic design automation the 68 00:03:55,400 --> 00:03:58,680 Speaker 1: building of new chips, companies like Synopsis and Cadence are 69 00:03:58,760 --> 00:04:02,080 Speaker 1: very well positioned. The cloud providers are also extremely well 70 00:04:02,120 --> 00:04:04,040 Speaker 1: positioned because that's where a lot of the building and 71 00:04:04,160 --> 00:04:06,640 Speaker 1: the running of these models is going to occur. So 72 00:04:06,680 --> 00:04:08,760 Speaker 1: there's a many ways to play this. In video is 73 00:04:08,800 --> 00:04:14,280 Speaker 1: probably the best position in the semi space, though, Jonathan 74 00:04:14,880 --> 00:04:18,440 Speaker 1: across Franklin's different funds and portfolios, I think you hold 75 00:04:18,520 --> 00:04:21,360 Speaker 1: zero point five percent of Nvidia, so a serious stakeholder, 76 00:04:21,720 --> 00:04:24,920 Speaker 1: and there's always hype around this company. I remember they 77 00:04:24,960 --> 00:04:26,800 Speaker 1: were going to be big in crypto because of all 78 00:04:26,839 --> 00:04:29,240 Speaker 1: the compute that was needed for mining. They've going to 79 00:04:29,279 --> 00:04:32,599 Speaker 1: be big in previous cycles and trends. Why are you 80 00:04:32,600 --> 00:04:35,440 Speaker 1: so convinced that this time around, with what we're seeing 81 00:04:35,440 --> 00:04:38,600 Speaker 1: in AI, it is in Nvidia that's right to take 82 00:04:38,920 --> 00:04:42,320 Speaker 1: on what's available in the market. Well, I think investors 83 00:04:42,320 --> 00:04:45,040 Speaker 1: were right to bed own and Video over a long term. 84 00:04:45,080 --> 00:04:47,240 Speaker 1: They've done very very well. With the rise of gaming, 85 00:04:47,600 --> 00:04:49,880 Speaker 1: they've done very very well, and the rise of the 86 00:04:50,400 --> 00:04:53,440 Speaker 1: cloud and now AI is a big opportunity. I think 87 00:04:53,440 --> 00:04:57,040 Speaker 1: they're very well positioned because of the combination of their 88 00:04:57,120 --> 00:05:00,960 Speaker 1: capabilities in semiconductors and a software they wrap around it. 89 00:05:01,320 --> 00:05:03,720 Speaker 1: But there are many other companies that are going to 90 00:05:03,760 --> 00:05:05,800 Speaker 1: do well here. But I think the bigger idea is this, 91 00:05:06,320 --> 00:05:08,840 Speaker 1: if you, as a knowledge worker had the ability to 92 00:05:08,880 --> 00:05:11,800 Speaker 1: have a partner sitting alongside of you, helping you in 93 00:05:11,839 --> 00:05:14,320 Speaker 1: your day to day work and being creative, of course 94 00:05:14,320 --> 00:05:17,520 Speaker 1: you would take that. And that is precisely what companies 95 00:05:17,560 --> 00:05:21,320 Speaker 1: like Nvidia and these large language models and generative AI 96 00:05:21,480 --> 00:05:24,400 Speaker 1: businesses are going to be enabling. They're going to allow 97 00:05:24,800 --> 00:05:27,640 Speaker 1: knowledge workers to be dramatically more productive. We've just met 98 00:05:27,720 --> 00:05:31,760 Speaker 1: last week with Sachi Adella Microsoft and he indicated that 99 00:05:31,800 --> 00:05:35,279 Speaker 1: the product that he was most proud of was the 100 00:05:35,320 --> 00:05:39,680 Speaker 1: GitHub Copilot offering that allows software developers to generate nearly 101 00:05:39,720 --> 00:05:42,560 Speaker 1: half of the code they are writing now with a 102 00:05:42,600 --> 00:05:45,960 Speaker 1: copilot model, we think that same type of power is 103 00:05:46,000 --> 00:05:49,440 Speaker 1: coming to the general knowledge worker that has to work 104 00:05:49,480 --> 00:05:54,000 Speaker 1: across hundreds of emails every day, many many documents every day, 105 00:05:54,400 --> 00:05:57,839 Speaker 1: ultimately empowering knowledge workers to be dramatically more productive. I 106 00:05:57,839 --> 00:06:00,400 Speaker 1: think enterprises are going to pay for that, and if 107 00:06:00,400 --> 00:06:02,360 Speaker 1: they don't, they're going to fall behind. And then all 108 00:06:02,440 --> 00:06:05,640 Speaker 1: leads back to the infrastructure vendors like an video there 109 00:06:05,640 --> 00:06:08,800 Speaker 1: are going to enable that they're painting a vision and 110 00:06:08,920 --> 00:06:13,880 Speaker 1: total addressable market that's enormous, I'm sure, Jonathan Franklin Equity Groups. 111 00:06:13,920 --> 00:06:16,279 Speaker 1: So great to have some time with you really to 112 00:06:16,400 --> 00:06:18,960 Speaker 1: discuss all of this. And we do have some breaking 113 00:06:18,960 --> 00:06:21,520 Speaker 1: news at the moment regarding one is once again some 114 00:06:21,600 --> 00:06:24,360 Speaker 1: news around the DOJ preparing a suit to block Adobe's 115 00:06:24,360 --> 00:06:28,560 Speaker 1: twenty billion dollar deal for Figma, now notable acquisition one 116 00:06:28,640 --> 00:06:31,800 Speaker 1: that many an investor was questioning the absolute valuation that 117 00:06:31,800 --> 00:06:34,920 Speaker 1: this company was parting with four Figma. We understand that 118 00:06:34,960 --> 00:06:37,479 Speaker 1: the antitrust lawsuit could be filed as soon as next month, 119 00:06:37,800 --> 00:06:39,560 Speaker 1: and we know it's one of the biggest takeovers of 120 00:06:39,560 --> 00:06:43,359 Speaker 1: a software startup out there. Really, this comes at a 121 00:06:43,400 --> 00:06:46,280 Speaker 1: time that we see more and more discussion of M 122 00:06:46,360 --> 00:06:49,360 Speaker 1: and A within technology. Of course, the focus on Microsoft's 123 00:06:49,360 --> 00:06:52,799 Speaker 1: deal of acquisition of Activision Blizzard at sixty nine billion 124 00:06:52,839 --> 00:06:57,880 Speaker 1: dollar deal really the US administration ramping up oversight. Yeah, 125 00:06:57,880 --> 00:06:59,440 Speaker 1: and every time we see a big piece of M 126 00:06:59,480 --> 00:07:01,080 Speaker 1: and A and it does happen, this is the first 127 00:07:01,160 --> 00:07:04,200 Speaker 1: question we ask. We're surprised to see it. In Adobe's case, 128 00:07:04,200 --> 00:07:06,600 Speaker 1: there's questions about why they would do this deal based 129 00:07:06,640 --> 00:07:09,720 Speaker 1: on their business fundamentals, but you know clearly the regulators 130 00:07:09,760 --> 00:07:20,880 Speaker 1: coming in and we thought that might happen. There's a 131 00:07:20,880 --> 00:07:23,160 Speaker 1: lot of exciting things going on, but there's a lot 132 00:07:23,200 --> 00:07:27,560 Speaker 1: of reason for us to be concerned. People want regulation 133 00:07:27,640 --> 00:07:30,080 Speaker 1: for AI. They want to feel safe. We think about 134 00:07:30,160 --> 00:07:33,760 Speaker 1: artificial intelligence as this kind of separate consciousness that is 135 00:07:33,800 --> 00:07:36,400 Speaker 1: going to emerge as this thing of science fiction. The 136 00:07:36,440 --> 00:07:39,320 Speaker 1: fact that they have this machine speaking with the first 137 00:07:39,360 --> 00:07:42,600 Speaker 1: person is problematic because that really encourages people to see 138 00:07:42,600 --> 00:07:45,360 Speaker 1: it as an entity, as a mind, when it's not 139 00:07:45,720 --> 00:07:49,840 Speaker 1: like any technology. It definitely has its limitation. So we 140 00:07:49,960 --> 00:07:53,920 Speaker 1: actually liked anything that you implement, we know its limitations. 141 00:07:54,080 --> 00:07:57,560 Speaker 1: We've seen the move fast and break things attitude before. 142 00:07:57,920 --> 00:08:00,720 Speaker 1: We have to get governments to think about how best 143 00:08:00,720 --> 00:08:05,400 Speaker 1: to regulate this new, very fast emerging industry. I think 144 00:08:05,440 --> 00:08:07,520 Speaker 1: that that chatbuts are not what we need for search. 145 00:08:07,720 --> 00:08:12,600 Speaker 1: It could be helpful, it could help human flourishing. These 146 00:08:12,640 --> 00:08:15,679 Speaker 1: were just some of our recent guests expressing their concerns 147 00:08:15,680 --> 00:08:18,920 Speaker 1: around the rapid rise of generative AI, from ethical concerns 148 00:08:18,920 --> 00:08:23,000 Speaker 1: to regulatory ones. There's another one cybersecurity concerns. And in fact, 149 00:08:23,000 --> 00:08:26,080 Speaker 1: of course JP Morgan just restricted its staff use of 150 00:08:26,200 --> 00:08:29,240 Speaker 1: chat chypt. They say it's part of normal controls around 151 00:08:29,280 --> 00:08:32,760 Speaker 1: third party software. So just what are the vulnerabilities that 152 00:08:32,840 --> 00:08:37,240 Speaker 1: perhaps artificial intelligence injects? Got the perfect guest, francois Local Donu, 153 00:08:37,559 --> 00:08:39,800 Speaker 1: his president, CEO and member of the board of directors 154 00:08:39,800 --> 00:08:43,120 Speaker 1: over at cybersecurity company F five, with a pretty fantastic 155 00:08:43,120 --> 00:08:46,360 Speaker 1: backdrop as well. Francois, welcome to the show. And just 156 00:08:46,640 --> 00:08:51,680 Speaker 1: when it comes to your expertise of cybersecurity, does artificial intelligence, 157 00:08:51,720 --> 00:08:56,920 Speaker 1: particularly generative AI, what sort of risks does it induce? Well, 158 00:08:56,920 --> 00:09:00,160 Speaker 1: thank you for having me. There are a number of 159 00:09:00,200 --> 00:09:03,839 Speaker 1: no risks that happened with generative AIM. But if we 160 00:09:04,240 --> 00:09:06,440 Speaker 1: step back a little bit, what we've seen over the 161 00:09:06,520 --> 00:09:10,240 Speaker 1: last you know, several years, is the number of cyber 162 00:09:10,280 --> 00:09:14,120 Speaker 1: attacks on companies and applications have increased dramatically, to the 163 00:09:14,200 --> 00:09:17,600 Speaker 1: point where cyber attacks are costing you know, roughly six 164 00:09:17,640 --> 00:09:20,320 Speaker 1: trillion dollars a year around the globe. Part of the 165 00:09:20,360 --> 00:09:23,160 Speaker 1: reason for that is that as we move from the 166 00:09:23,240 --> 00:09:28,480 Speaker 1: early stages of web experience to more digital, advanced digital, 167 00:09:28,520 --> 00:09:32,839 Speaker 1: and dynamic experiences that we're all enjoying today, security in 168 00:09:32,880 --> 00:09:36,240 Speaker 1: all of that movement was an afterthought, and so the 169 00:09:36,360 --> 00:09:39,560 Speaker 1: attack surface for attackers increased and they were able to 170 00:09:39,640 --> 00:09:43,800 Speaker 1: increasingly attack applications and monetize those attacks. Well, now we 171 00:09:43,840 --> 00:09:47,680 Speaker 1: are at another inflection point where you know, generative AI 172 00:09:48,000 --> 00:09:50,840 Speaker 1: is going to be an accelerator for humans, both for 173 00:09:50,920 --> 00:09:54,240 Speaker 1: bad humans and for good humans, and we really have 174 00:09:54,360 --> 00:09:57,120 Speaker 1: to make sure that security is not an afterthought and 175 00:09:57,160 --> 00:10:01,320 Speaker 1: that organizations prepare themselves upfront for the new risks that 176 00:10:01,440 --> 00:10:06,040 Speaker 1: come with that acceleration. Those new risks include, of course, 177 00:10:06,320 --> 00:10:10,360 Speaker 1: you know, attackers being able to impersonate chat bots to 178 00:10:10,400 --> 00:10:13,640 Speaker 1: take your personal information, or you know, being able to 179 00:10:13,679 --> 00:10:18,479 Speaker 1: write scripts much faster that attack vulnerabilities in existing applications, 180 00:10:18,679 --> 00:10:21,680 Speaker 1: and today most organizations are not prepared for that. Okay, 181 00:10:21,679 --> 00:10:24,800 Speaker 1: so let's talk about hardness. We can all update our 182 00:10:25,840 --> 00:10:28,439 Speaker 1: the way in which we train ourselves to avoid phishing emails. 183 00:10:28,440 --> 00:10:30,760 Speaker 1: We can all understand them, phaps, the spelling mistakes aren't 184 00:10:30,760 --> 00:10:32,240 Speaker 1: going to be there anymore. But front, well, what are 185 00:10:32,320 --> 00:10:36,040 Speaker 1: you now training companies to look out for? We're training 186 00:10:36,040 --> 00:10:39,320 Speaker 1: so first of all, we're asking companies to take the 187 00:10:39,400 --> 00:10:42,520 Speaker 1: threats seriously. What I think we've seen in the past 188 00:10:42,640 --> 00:10:47,240 Speaker 1: is that oftentimes which we underestimate the sophistication of attackers. 189 00:10:47,720 --> 00:10:50,520 Speaker 1: And because of that, you know, we use half hazard 190 00:10:50,559 --> 00:10:53,000 Speaker 1: tools or try to just put a team of engineers 191 00:10:53,000 --> 00:10:55,760 Speaker 1: in a room to try and deal with the attackers. 192 00:10:55,800 --> 00:10:58,880 Speaker 1: But they are now organized, they have access to a 193 00:10:58,880 --> 00:11:02,120 Speaker 1: lot of tools, and this generality I is doing to 194 00:11:02,240 --> 00:11:07,320 Speaker 1: make very sophisticate and fine tuned attacks available to frankly 195 00:11:07,360 --> 00:11:10,760 Speaker 1: the least sophisticated attackers. So we're asking companies to get 196 00:11:10,760 --> 00:11:15,040 Speaker 1: prepared to enhance their monitoring of their applications and the 197 00:11:15,160 --> 00:11:19,480 Speaker 1: scanning of their codes and vulnerabilities. We're asking companies to 198 00:11:19,520 --> 00:11:23,400 Speaker 1: train their users constantly. You just mentioned phishing emails. Phishing 199 00:11:23,440 --> 00:11:26,960 Speaker 1: emails are getting are going to get way more sophisticated 200 00:11:27,000 --> 00:11:29,760 Speaker 1: and harder to detect, and it requires training of users 201 00:11:29,760 --> 00:11:33,640 Speaker 1: on a very regular basis. Frans Far, a month ago 202 00:11:34,040 --> 00:11:38,800 Speaker 1: when you reported earnings, he talked about your customers slowing 203 00:11:38,880 --> 00:11:41,040 Speaker 1: down in terms of renewals. There was a little bit 204 00:11:41,080 --> 00:11:44,240 Speaker 1: worry about the outlook. You think about the hype cycle 205 00:11:44,360 --> 00:11:48,000 Speaker 1: around AI. Has your situation changed in the last four 206 00:11:48,000 --> 00:11:51,080 Speaker 1: weeks in other words, are your customers actually becoming more 207 00:11:51,120 --> 00:11:55,880 Speaker 1: alive to these AI related risks and therefore engaging with 208 00:11:55,960 --> 00:12:00,400 Speaker 1: you about doing more work with your platforms in the 209 00:12:00,520 --> 00:12:05,360 Speaker 1: area of security. And we're we're seeing our customers are 210 00:12:05,440 --> 00:12:07,840 Speaker 1: engaging with us on that. Just to give you a 211 00:12:07,840 --> 00:12:13,320 Speaker 1: sense and around it. You know, today we protect over 212 00:12:13,400 --> 00:12:17,760 Speaker 1: two billion fraudulent logins into applications every single day, and 213 00:12:17,840 --> 00:12:21,200 Speaker 1: we protect over four and a half billion transactions web 214 00:12:21,240 --> 00:12:25,160 Speaker 1: transactions every single day with our large enterprise customers. And 215 00:12:25,200 --> 00:12:28,160 Speaker 1: the way we do that is by leveraging AI to 216 00:12:28,400 --> 00:12:32,920 Speaker 1: stop sophisticated and automated attacks. And we're seeing our customers, 217 00:12:33,040 --> 00:12:37,800 Speaker 1: of course have a strong interest in these solutions. And 218 00:12:37,880 --> 00:12:40,040 Speaker 1: over the last four weeks we have continued to see 219 00:12:40,080 --> 00:12:44,240 Speaker 1: that happened. Friends, how we just have thirty seconds, but 220 00:12:44,360 --> 00:12:47,520 Speaker 1: what is your technological assessment of what the likes of 221 00:12:47,559 --> 00:12:50,080 Speaker 1: open ai are doing. Do you see them as a 222 00:12:50,120 --> 00:12:55,800 Speaker 1: long term threat to your business? No, Actually, I think 223 00:12:56,080 --> 00:12:59,560 Speaker 1: open ai is going to be enabler for my business 224 00:12:59,679 --> 00:13:02,280 Speaker 1: and the businesses because there's a lot of fantastic things 225 00:13:02,320 --> 00:13:05,840 Speaker 1: that it can do and allow us to move our 226 00:13:05,880 --> 00:13:11,520 Speaker 1: people to other tasks that perhaps are repetitive today. So 227 00:13:11,760 --> 00:13:14,080 Speaker 1: I see it pm mearly as an enabler of our business, 228 00:13:14,200 --> 00:13:16,280 Speaker 1: but I also see it as a threat to all 229 00:13:16,360 --> 00:13:19,880 Speaker 1: companies around the world around securing their digital experiences, and 230 00:13:20,000 --> 00:13:21,959 Speaker 1: that's why we're going to continue to invest in AI 231 00:13:23,080 --> 00:13:27,840 Speaker 1: to help our customers. Francois local Do New five President 232 00:13:27,880 --> 00:13:31,160 Speaker 1: and CEO. Thank you very much, Caroline. Great conversation. I mean, 233 00:13:31,200 --> 00:13:33,000 Speaker 1: actually ed if you take a look a little bit 234 00:13:33,000 --> 00:13:35,880 Speaker 1: more at Generative AI over in China, the rally in 235 00:13:36,000 --> 00:13:39,040 Speaker 1: Chinese AI stocks, they're actually kind of cooling off of late. 236 00:13:39,120 --> 00:13:42,120 Speaker 1: That's after some media started reporting that local apps and 237 00:13:42,240 --> 00:13:45,720 Speaker 1: local websites have been ordered to terminate services that allow 238 00:13:45,800 --> 00:13:49,000 Speaker 1: you so chat GBT now. Open ais chatbot isn't officially 239 00:13:49,040 --> 00:13:53,920 Speaker 1: available in China, but has been accessible via virtual private networks. 240 00:13:54,679 --> 00:13:57,920 Speaker 1: Coming up. Goalman it's offering clients a special way to 241 00:13:57,960 --> 00:14:02,120 Speaker 1: invest in Unicorn Stripe or bringing the details. Next, this 242 00:14:02,280 --> 00:14:14,880 Speaker 1: is Blomberg. Oh, everyone was reading about it today. Goldman 243 00:14:14,920 --> 00:14:18,600 Speaker 1: Sachs offering its wealthiest customers access to a fundraising round 244 00:14:18,640 --> 00:14:21,360 Speaker 1: for the payment's Giant Stripe and the bank will set 245 00:14:21,440 --> 00:14:25,000 Speaker 1: up a special purpose vehicle for private wealth clients to 246 00:14:25,120 --> 00:14:27,440 Speaker 1: invest in the company as it seeks to raise four 247 00:14:27,520 --> 00:14:30,960 Speaker 1: billion dollars for more. Let's bringing Blomberg straight out, Nadarajan, 248 00:14:31,040 --> 00:14:33,960 Speaker 1: and you're one of the key components of breaking this story. 249 00:14:34,920 --> 00:14:37,080 Speaker 1: Remind us why they need the money. It's kind of 250 00:14:37,160 --> 00:14:40,120 Speaker 1: rather arduous around tax. Yeah, I mean, there are a 251 00:14:40,200 --> 00:14:42,440 Speaker 1: lot of longstanding employees at the film. They want to 252 00:14:42,480 --> 00:14:44,840 Speaker 1: cash out their restricted stock units, and part of that 253 00:14:45,120 --> 00:14:48,280 Speaker 1: move will involve a looming tax bill, and that is, 254 00:14:48,440 --> 00:14:50,840 Speaker 1: in effect one of the reasons why they are raising 255 00:14:50,880 --> 00:14:53,320 Speaker 1: this much. They are trying to raise about four billion dollars, 256 00:14:53,360 --> 00:14:56,560 Speaker 1: which is a pretty high sum. But again, we're talking 257 00:14:56,600 --> 00:14:59,320 Speaker 1: about a company that went from a valuation one hundred 258 00:14:59,360 --> 00:15:02,200 Speaker 1: million just to decade ago to almost one hundred billion 259 00:15:02,240 --> 00:15:05,120 Speaker 1: dollars in twenty twenty one. It has come down significantly. 260 00:15:05,200 --> 00:15:07,680 Speaker 1: We're talking about around where they could be valued at 261 00:15:07,720 --> 00:15:09,880 Speaker 1: fifty five billion dollars. But if you think about that, 262 00:15:09,880 --> 00:15:11,440 Speaker 1: I think about the fact that we're talking about a 263 00:15:11,520 --> 00:15:16,080 Speaker 1: fintech firm that is in the position to report positive 264 00:15:16,240 --> 00:15:19,600 Speaker 1: free cash flow. That makes it an exciting name. And 265 00:15:19,720 --> 00:15:22,560 Speaker 1: when the valuation has come down this much, you can 266 00:15:22,680 --> 00:15:26,040 Speaker 1: be guaranteed the lot of wealthy clients, a lot of 267 00:15:26,080 --> 00:15:29,240 Speaker 1: big institutional investors would want to poke around and see 268 00:15:29,360 --> 00:15:32,280 Speaker 1: if this is the right time to jump in, particularly 269 00:15:32,320 --> 00:15:34,680 Speaker 1: as everyone's still talking about certain list of names that 270 00:15:34,760 --> 00:15:37,520 Speaker 1: could co public as and when the markets reopen, valuations 271 00:15:37,600 --> 00:15:40,200 Speaker 1: become boy in a little bit more. Just just talk 272 00:15:40,240 --> 00:15:42,360 Speaker 1: to us a little bit about how it could be structured. 273 00:15:42,440 --> 00:15:44,600 Speaker 1: What It's not just Goldman in on the deal, right, No, 274 00:15:44,920 --> 00:15:47,120 Speaker 1: So Goldman and JP Morgan are the two banks of 275 00:15:47,240 --> 00:15:49,640 Speaker 1: being mandated. Were trying to raise this money, and they're 276 00:15:49,680 --> 00:15:52,760 Speaker 1: going to a wide swath of investors that includes you know, 277 00:15:53,040 --> 00:15:56,360 Speaker 1: big names and finance and the tech world VC firms. 278 00:15:56,720 --> 00:15:59,960 Speaker 1: There is a quite a big spectrum that they've gone 279 00:16:00,120 --> 00:16:03,040 Speaker 1: now too. But equally important and what we found interesting 280 00:16:03,280 --> 00:16:06,160 Speaker 1: was Goldman Sacks, for instance, opening it up to their 281 00:16:06,240 --> 00:16:09,760 Speaker 1: high net worth clients Previously The biggest draw if you're 282 00:16:09,800 --> 00:16:11,600 Speaker 1: a client in one of these banks was we can 283 00:16:11,640 --> 00:16:14,200 Speaker 1: bring you in closer to the IPO. Now with private 284 00:16:14,360 --> 00:16:18,040 Speaker 1: companies wanting to say private for longer, this is a 285 00:16:18,080 --> 00:16:20,920 Speaker 1: way to augment your offerings. Goldman can go out there 286 00:16:20,920 --> 00:16:23,320 Speaker 1: and say, let's create a special vehicle where all of 287 00:16:23,360 --> 00:16:25,400 Speaker 1: you can pull in your cash and we will write 288 00:16:25,440 --> 00:16:27,480 Speaker 1: one big check and hand it over to Stripe. Why 289 00:16:27,520 --> 00:16:30,360 Speaker 1: would you not want to take that opportunity? Remind us 290 00:16:30,440 --> 00:16:32,560 Speaker 1: when this has been done before, because it's sort of 291 00:16:32,600 --> 00:16:35,680 Speaker 1: got echoes of what happened with the right. The Uber 292 00:16:35,880 --> 00:16:37,440 Speaker 1: is one example that comes to mind that was a 293 00:16:37,480 --> 00:16:39,960 Speaker 1: big deal. It was in twenty fifteen Goldman Sacks to 294 00:16:40,000 --> 00:16:42,640 Speaker 1: the one point six one point seven billion dollars convertible 295 00:16:43,000 --> 00:16:45,600 Speaker 1: note deal. At that time, that was driven by their 296 00:16:45,680 --> 00:16:48,600 Speaker 1: high networth clients. But equally important, even if you look 297 00:16:48,640 --> 00:16:51,520 Speaker 1: at recent examples, when a big venture capital firm like 298 00:16:51,640 --> 00:16:55,080 Speaker 1: Tiger Global wants to raise a new fund, banks see 299 00:16:55,080 --> 00:16:59,920 Speaker 1: an opportunity to create vehicles and go to their rich clients, 300 00:17:00,200 --> 00:17:01,960 Speaker 1: you know, people who are worth more than twenty five 301 00:17:01,960 --> 00:17:04,560 Speaker 1: million dollars perhaps and telling them that this is a 302 00:17:04,640 --> 00:17:06,240 Speaker 1: way for you to get in on a big name, 303 00:17:06,400 --> 00:17:09,360 Speaker 1: which in the bus was only available to institutional investors. 304 00:17:10,280 --> 00:17:13,199 Speaker 1: Interesting the way in which people still want diversification. Street up, 305 00:17:13,400 --> 00:17:16,800 Speaker 1: great reporting me. Thank you Sharjan there, and you got 306 00:17:16,840 --> 00:17:19,640 Speaker 1: some time for talking to tech. Yeah, thank you time 307 00:17:19,680 --> 00:17:22,400 Speaker 1: now indeed for talking tech. Let's go over to Europe, 308 00:17:22,440 --> 00:17:26,960 Speaker 1: where the European Commission suspended staff from using TikTok over 309 00:17:27,040 --> 00:17:31,639 Speaker 1: security concerns related to the social media apps data collection practices. 310 00:17:31,680 --> 00:17:34,080 Speaker 1: Staff were ordered to delete the app from mobile phones 311 00:17:34,480 --> 00:17:38,879 Speaker 1: and corporate devices, which includes personal devices that use Commission apps. 312 00:17:39,119 --> 00:17:42,080 Speaker 1: That's according to a spokesperson. The move comes among growing 313 00:17:42,160 --> 00:17:44,959 Speaker 1: scrucity both here in the US but also in Europe 314 00:17:45,160 --> 00:17:49,080 Speaker 1: over the apps potential national security risks. In China, Ant 315 00:17:49,119 --> 00:17:52,640 Speaker 1: Group's profit fell eighty three percent after China's regulatory crackdown 316 00:17:52,800 --> 00:17:56,440 Speaker 1: and a drop in valuation for overseas equity investments. Still 317 00:17:56,640 --> 00:17:59,200 Speaker 1: A contributed a billion one or one hundred and forty 318 00:17:59,240 --> 00:18:01,920 Speaker 1: five million dollars to its pair in Ali Barber, whose 319 00:18:02,000 --> 00:18:05,399 Speaker 1: own profit jumped sixty nine percent after the e commerce 320 00:18:05,440 --> 00:18:08,879 Speaker 1: giant reigned in its spending and narrowed losses abroad to 321 00:18:08,960 --> 00:18:11,119 Speaker 1: make up for, of course, anemic growth because of COVID 322 00:18:11,200 --> 00:18:14,680 Speaker 1: nineteen and benefiting also from reduced spending is Grab, which 323 00:18:14,720 --> 00:18:19,280 Speaker 1: brought its profitability target forward after posting a narrower quarterly loss. 324 00:18:19,320 --> 00:18:22,959 Speaker 1: The food delivery provider among money losing Southeast Asian internet 325 00:18:23,000 --> 00:18:26,920 Speaker 1: giants to have shifted strategies to focus on achieving profitability 326 00:18:27,200 --> 00:18:32,080 Speaker 1: instead of spending on growth. Caroline great global round up there, 327 00:18:32,160 --> 00:18:34,240 Speaker 1: and now let's get you back to the US. Let's 328 00:18:34,280 --> 00:18:36,040 Speaker 1: get you to a stop to watch after hours because 329 00:18:36,040 --> 00:18:38,119 Speaker 1: it's Block of course, the artists formerly known as Square, 330 00:18:38,359 --> 00:18:41,359 Speaker 1: they've currently been for some fluctuation, but we're now decidedly higher, 331 00:18:41,400 --> 00:18:43,400 Speaker 1: up six and a half percent. After hours look grows. 332 00:18:43,440 --> 00:18:45,800 Speaker 1: Payment volumes did climb fifteen percent year on year. It 333 00:18:45,840 --> 00:18:48,320 Speaker 1: was slightly blow expectations, but net revenue looks solid up 334 00:18:48,359 --> 00:18:52,440 Speaker 1: fourteen percent, and particularly are seeing sort of record setting 335 00:18:52,800 --> 00:18:55,240 Speaker 1: revenue for the fourth quarter and the full year when 336 00:18:55,240 --> 00:18:58,960 Speaker 1: it comes to subscriptions and services. They're also posting towards 337 00:18:58,960 --> 00:19:02,840 Speaker 1: twenty twenty three guidance that were slightly ahead of expectations, 338 00:19:02,920 --> 00:19:05,560 Speaker 1: so they're in the payment side of things ed, it 339 00:19:05,720 --> 00:19:07,480 Speaker 1: looks as though we got a bit of a solid beat. 340 00:19:07,520 --> 00:19:10,200 Speaker 1: It was interesting also the bitcoin side of the equation 341 00:19:10,359 --> 00:19:14,240 Speaker 1: also looking relatively solid. It's interesting the pledge from block 342 00:19:14,359 --> 00:19:16,840 Speaker 1: is efficiency. Right in other ways, they're reigning and spending, 343 00:19:16,880 --> 00:19:19,480 Speaker 1: and after what we saw from a firm PayPal, other 344 00:19:19,560 --> 00:19:21,680 Speaker 1: thin tech players, that's kind of been the theme of 345 00:19:21,760 --> 00:19:24,800 Speaker 1: this earning season. As volumes drop, then you need to 346 00:19:24,880 --> 00:19:27,240 Speaker 1: tighten the belt a little. I think that's the play. Yeah, 347 00:19:27,280 --> 00:19:29,200 Speaker 1: it was notable that they're really trying to get costs 348 00:19:29,280 --> 00:19:32,399 Speaker 1: under control. We note how wasn't that much an illustrative 349 00:19:32,440 --> 00:19:34,200 Speaker 1: of how they're going to be doing that, but people 350 00:19:34,240 --> 00:19:36,359 Speaker 1: sort of noted that the number was below where they 351 00:19:36,400 --> 00:19:39,520 Speaker 1: had thought. And yeah, as you say, tightening your belt particularly, 352 00:19:39,600 --> 00:19:41,960 Speaker 1: keep on selling out there and continuing to try and 353 00:19:42,160 --> 00:19:44,640 Speaker 1: find some expansion bitcoin revenue. As I said, we're down 354 00:19:44,680 --> 00:19:47,400 Speaker 1: six and a half percent year on year, but overall 355 00:19:47,560 --> 00:19:59,600 Speaker 1: it was ahead of expectations. Welcome back to blobog Technology. 356 00:19:59,600 --> 00:20:02,159 Speaker 1: I can and heard in New York and Almed Ludlow 357 00:20:02,200 --> 00:20:03,720 Speaker 1: in San Francisco. We're going to get back to that 358 00:20:03,840 --> 00:20:06,440 Speaker 1: breaking Adobe news. Caroline shares down around four and a 359 00:20:06,480 --> 00:20:09,600 Speaker 1: half percent in after hours after Bloomberg broke the story 360 00:20:09,720 --> 00:20:13,359 Speaker 1: that the DOJ is preparing a suit to block Adobe's 361 00:20:13,359 --> 00:20:16,720 Speaker 1: twenty billion dollar deal to buy Figma that according to sources, 362 00:20:16,760 --> 00:20:19,040 Speaker 1: and one source saying carrow could come as soon as 363 00:20:19,080 --> 00:20:22,280 Speaker 1: next month. I mean, really, Adobe such a dominant force 364 00:20:22,320 --> 00:20:25,440 Speaker 1: in terms of software, Photoshoppy, Destrator, you know it. But 365 00:20:25,600 --> 00:20:28,800 Speaker 1: when they announced that deal to acquire Figment, many you know, 366 00:20:28,920 --> 00:20:31,040 Speaker 1: were kind of amazed by the price point that they 367 00:20:31,080 --> 00:20:33,320 Speaker 1: were willing to spend really where they thought this would 368 00:20:33,320 --> 00:20:37,160 Speaker 1: be a creative. They're trying to introduce less expensive products 369 00:20:37,280 --> 00:20:40,320 Speaker 1: at the moment, but notably, just time and time again, 370 00:20:40,359 --> 00:20:42,440 Speaker 1: this is an administration that is willing to go there 371 00:20:42,520 --> 00:20:45,760 Speaker 1: to tackle M and A, to worry about competition and 372 00:20:45,880 --> 00:20:48,320 Speaker 1: in this space, and really does feel as though, well 373 00:20:48,440 --> 00:20:51,359 Speaker 1: the Bloomberg reporting getting ahead of that antitrust news and 374 00:20:51,440 --> 00:20:53,719 Speaker 1: the filing. Of course, I think it's all because Adobe 375 00:20:53,800 --> 00:20:56,120 Speaker 1: was actually in front and a meeting with ADJ which 376 00:20:56,200 --> 00:20:58,480 Speaker 1: is often the case before we get this in announcement, 377 00:21:00,080 --> 00:21:02,439 Speaker 1: consistent with what we've seen right from the DJA. Our 378 00:21:02,440 --> 00:21:05,000 Speaker 1: Bloomberg intelligence analysts do point out though that in this 379 00:21:05,200 --> 00:21:09,000 Speaker 1: case it probably came sooner than expected, although it was 380 00:21:09,119 --> 00:21:12,000 Speaker 1: kind of expected based on the actions DJ's taken in 381 00:21:12,200 --> 00:21:14,600 Speaker 1: M and A. So far, we'll pivot Caroline, but we'll 382 00:21:14,600 --> 00:21:17,040 Speaker 1: stick across the story as more headlines break. Coin Base, 383 00:21:17,320 --> 00:21:20,879 Speaker 1: the largest US crypto exchange, is now launching a blockchain, 384 00:21:21,000 --> 00:21:24,800 Speaker 1: expanding its reach deeper into the worlds of DeFi and NFTs. 385 00:21:24,960 --> 00:21:27,679 Speaker 1: Let's talk about this all with who else Bloomberg Scenali 386 00:21:27,680 --> 00:21:31,720 Speaker 1: Basset out in New York, Shenali blockchain. Why this is 387 00:21:31,920 --> 00:21:35,320 Speaker 1: very interesting. Remember, this is a centralized exchange if you will, 388 00:21:35,440 --> 00:21:38,800 Speaker 1: looking at decentralization. When we spoke to a coin based executive, 389 00:21:39,040 --> 00:21:41,639 Speaker 1: our colleague Moyo Shan reports that this is really a 390 00:21:41,760 --> 00:21:45,360 Speaker 1: bet on the community. This is a layer two network 391 00:21:45,440 --> 00:21:48,760 Speaker 1: here where decentralized apps can be built and it will 392 00:21:48,800 --> 00:21:51,600 Speaker 1: be a home for the chain products that will be 393 00:21:51,680 --> 00:21:55,840 Speaker 1: built in conjunction with this network that is being shepherded 394 00:21:55,920 --> 00:21:58,400 Speaker 1: by coin Base. Now let's use some of Brian Armstrong's 395 00:21:58,400 --> 00:22:01,240 Speaker 1: all words, because he said this is to improve the 396 00:22:01,320 --> 00:22:05,880 Speaker 1: scaleability and usability of crypto, plus he wanted to get 397 00:22:05,960 --> 00:22:08,800 Speaker 1: in on the builder energy ed. That is what he said. 398 00:22:08,880 --> 00:22:10,440 Speaker 1: I also want to point out here that if you 399 00:22:10,560 --> 00:22:13,240 Speaker 1: look at the initial tweets from build on base here, 400 00:22:13,560 --> 00:22:15,760 Speaker 1: which is kind of the Twitter handle of base, which 401 00:22:15,800 --> 00:22:19,160 Speaker 1: is project is known as Hello world is how it starts, 402 00:22:19,200 --> 00:22:22,840 Speaker 1: which of course is a very intimate term and for 403 00:22:22,960 --> 00:22:26,320 Speaker 1: the developer community here. So let's see how much this 404 00:22:26,400 --> 00:22:29,000 Speaker 1: starts to take off. I think it's a very interesting concept, 405 00:22:29,080 --> 00:22:32,800 Speaker 1: of course, to see in exchange like this get closer 406 00:22:32,880 --> 00:22:36,400 Speaker 1: to the decentralized world. The other headline is what coin 407 00:22:36,480 --> 00:22:38,440 Speaker 1: base does not plan to do, which is to not 408 00:22:38,600 --> 00:22:41,960 Speaker 1: issue a native token. Another point of discussion, Shali, stay 409 00:22:42,040 --> 00:22:44,240 Speaker 1: with us, Caroline. We're tracking a lot of stories today, 410 00:22:44,440 --> 00:22:47,160 Speaker 1: we are, and it all debtails nicely into a conversation 411 00:22:47,240 --> 00:22:50,400 Speaker 1: around the future regulation around crypto, the future of innovation 412 00:22:50,440 --> 00:22:52,680 Speaker 1: and around crypto. And well, we've got one person who's 413 00:22:52,760 --> 00:22:54,760 Speaker 1: kind of at the heart of that conversation, Chris Lahane's 414 00:22:54,800 --> 00:22:57,960 Speaker 1: chief strategy officer, han Vinchas, of course, still with us 415 00:22:58,000 --> 00:23:01,080 Speaker 1: a Shinali bassecond, Chris, I'm going to Austin only to 416 00:23:01,160 --> 00:23:02,920 Speaker 1: take it away with the first sort of questions because 417 00:23:02,920 --> 00:23:04,080 Speaker 1: we want to dig in a little bit more to 418 00:23:04,160 --> 00:23:06,359 Speaker 1: coin based us. Yeah, Chris, I'm really curious about your 419 00:23:06,400 --> 00:23:09,000 Speaker 1: thoughts here about coin bass efforts to get into the 420 00:23:09,080 --> 00:23:13,520 Speaker 1: decentralized world when they're facing so many questions really about 421 00:23:13,680 --> 00:23:16,920 Speaker 1: the centralized world when it comes to US regulators, what 422 00:23:17,240 --> 00:23:20,640 Speaker 1: is and what ISN'TO security? What kind of questions does 423 00:23:20,680 --> 00:23:24,400 Speaker 1: this open up now that they're embracing decentralization so much 424 00:23:24,440 --> 00:23:27,119 Speaker 1: as well? Yeah, well, first, thanks for having me. I 425 00:23:27,200 --> 00:23:30,240 Speaker 1: think really two points on the coin based announcement. The 426 00:23:30,359 --> 00:23:32,760 Speaker 1: first is, I do think it reflects what's really going 427 00:23:32,840 --> 00:23:36,040 Speaker 1: on in the crypto space right now, which is enormous 428 00:23:36,119 --> 00:23:39,400 Speaker 1: progress in development what you call the infrastructure level where 429 00:23:39,400 --> 00:23:43,000 Speaker 1: those developers are working at. And then more broadly, when 430 00:23:43,040 --> 00:23:45,800 Speaker 1: you ask about the policy question, I think there's a 431 00:23:45,880 --> 00:23:49,320 Speaker 1: really interesting I called tale of two companies. Right you 432 00:23:49,440 --> 00:23:54,120 Speaker 1: had an FTX company that was based offshore, in my view, 433 00:23:54,240 --> 00:23:58,720 Speaker 1: really more of a centralized financed financial entity that committed, 434 00:23:58,800 --> 00:24:00,920 Speaker 1: at least based on what we've seen them been reported, 435 00:24:01,400 --> 00:24:03,280 Speaker 1: all kinds of fraud, but the type of fraud that 436 00:24:03,320 --> 00:24:07,159 Speaker 1: you've historically seen in centralized finance over human history. And 437 00:24:07,240 --> 00:24:09,919 Speaker 1: then you have a company like coin base. Brian Armstrong, 438 00:24:10,000 --> 00:24:13,280 Speaker 1: who you referenced earlier, made a really interesting decision seven 439 00:24:13,359 --> 00:24:16,680 Speaker 1: eight nine years ago to base his company here in 440 00:24:16,760 --> 00:24:21,040 Speaker 1: the United States, to push the frontiers of innovation, to 441 00:24:21,160 --> 00:24:24,600 Speaker 1: create more economic freedom, more economic opportunity, but to do 442 00:24:24,680 --> 00:24:27,880 Speaker 1: it within an existing legal system, and particularly a set 443 00:24:27,920 --> 00:24:32,159 Speaker 1: of laws that were actually created before computers even existed. 444 00:24:32,840 --> 00:24:34,880 Speaker 1: So I think coin Base is actually a really interesting 445 00:24:34,920 --> 00:24:37,399 Speaker 1: example of how you can actually push innovation in this 446 00:24:37,560 --> 00:24:40,639 Speaker 1: space while operating within the paradigm there a stale, very 447 00:24:40,720 --> 00:24:43,200 Speaker 1: much old school Chris. Of course, the company you work 448 00:24:43,200 --> 00:24:45,200 Speaker 1: at now is one of the hottest venture launches in 449 00:24:45,240 --> 00:24:50,240 Speaker 1: the crypto space recently. When you're thinking about centralization versus decentralization, 450 00:24:50,440 --> 00:24:54,480 Speaker 1: within the parameters of the existing laws that exist around 451 00:24:55,280 --> 00:24:58,200 Speaker 1: the crypto community, what are you more comfortable when it 452 00:24:58,280 --> 00:25:01,400 Speaker 1: comes to putting money to work with Well, first of all, 453 00:25:01,480 --> 00:25:03,560 Speaker 1: you know, we raise one point five billion almost a 454 00:25:03,680 --> 00:25:07,359 Speaker 1: year ago to the date, and for us, we're really 455 00:25:07,440 --> 00:25:10,920 Speaker 1: focused on investments that will play out over multiple years. 456 00:25:11,720 --> 00:25:13,240 Speaker 1: This goes back to something I was just touching on. 457 00:25:13,359 --> 00:25:17,000 Speaker 1: We see enormous opportunity what I would call it infrastructure area, 458 00:25:17,080 --> 00:25:21,880 Speaker 1: where you're getting technology that deals with scaling, deals with interoperability, 459 00:25:22,200 --> 00:25:25,120 Speaker 1: basically in layman's terms or lay person's terms, the type 460 00:25:25,119 --> 00:25:27,399 Speaker 1: of technology that you're ultimately going to need for this 461 00:25:27,560 --> 00:25:30,680 Speaker 1: to be consumer facing, in for everyday consumers to be 462 00:25:30,800 --> 00:25:33,440 Speaker 1: able to use. Now to this specific question, about the 463 00:25:33,520 --> 00:25:39,440 Speaker 1: decentralization versus the centralization. I mean, by definition, within crypto, 464 00:25:39,680 --> 00:25:42,720 Speaker 1: it is a decentralized space. That's ultimately how you democratize 465 00:25:42,800 --> 00:25:47,000 Speaker 1: aspects of capitalism, particularly online. Within that, there can be 466 00:25:47,080 --> 00:25:50,159 Speaker 1: a spectrum of issues and ideas. But we spend a 467 00:25:50,200 --> 00:25:52,800 Speaker 1: lot of time with with our portfolio companies, and even 468 00:25:53,200 --> 00:25:55,760 Speaker 1: the potential projects that we may or ultimately may not 469 00:25:55,960 --> 00:25:58,600 Speaker 1: invest in is a is the what's the quality of 470 00:25:58,600 --> 00:26:01,119 Speaker 1: the team, what's the quality of the technology? Do they 471 00:26:01,280 --> 00:26:04,040 Speaker 1: understand that there's going to be a complex regulatory map 472 00:26:04,160 --> 00:26:06,359 Speaker 1: out there. They don't necessarily have to have all the 473 00:26:06,400 --> 00:26:08,919 Speaker 1: answers from day one, but they have to reflect an 474 00:26:08,960 --> 00:26:11,000 Speaker 1: understanding that they're going to need to navigate this and 475 00:26:11,119 --> 00:26:13,840 Speaker 1: navigate it in a responsible way. So that's amongst the 476 00:26:13,880 --> 00:26:16,160 Speaker 1: things that we think about when we pursue our investments. 477 00:26:16,480 --> 00:26:18,160 Speaker 1: I can I have to tell you, like, we're incredibly 478 00:26:18,200 --> 00:26:21,080 Speaker 1: excited about the types of founders we're seeing, particularly in 479 00:26:21,200 --> 00:26:24,040 Speaker 1: those early stages where they're really beginning to think about, Okay, 480 00:26:24,280 --> 00:26:26,240 Speaker 1: here's where the world is, Here's some of the regulatory 481 00:26:26,280 --> 00:26:29,280 Speaker 1: stuff we need to navigate. But we have incredibly powerful 482 00:26:29,320 --> 00:26:32,160 Speaker 1: ideas about how we can scale and make this technology 483 00:26:32,280 --> 00:26:36,159 Speaker 1: really consumer facing. Chris, You're so powerful with hard ventures 484 00:26:36,280 --> 00:26:39,000 Speaker 1: because of the expertise you can lend the portfolio companies, 485 00:26:39,040 --> 00:26:41,760 Speaker 1: some of them that we're just seeing there. Your passion 486 00:26:41,840 --> 00:26:45,119 Speaker 1: around Web three I've had firsthand from you, but I 487 00:26:45,200 --> 00:26:48,239 Speaker 1: mean before we're helping advise companies such as Airbnb as 488 00:26:48,280 --> 00:26:50,880 Speaker 1: they were scaling. You're someone who knows Washington the way 489 00:26:50,920 --> 00:26:53,960 Speaker 1: it works so intimately from your background, what do you 490 00:26:54,080 --> 00:26:56,400 Speaker 1: make on the way in which the SEC is by 491 00:26:56,480 --> 00:26:58,800 Speaker 1: some terms of phrase our guests have said, look basically 492 00:26:59,160 --> 00:27:02,960 Speaker 1: regulating by enforcement rather than setting rules of the road. Yeah, 493 00:27:03,000 --> 00:27:05,399 Speaker 1: I've called it an enforcement only approach. I mean, if 494 00:27:05,440 --> 00:27:08,440 Speaker 1: you take a step back a year ago, almost to 495 00:27:08,480 --> 00:27:10,040 Speaker 1: the day, I maybe off for a week or two, 496 00:27:10,520 --> 00:27:13,200 Speaker 1: the Biden and White House put out an executive order. 497 00:27:13,680 --> 00:27:15,320 Speaker 1: It was sort of a high water mark up to 498 00:27:15,440 --> 00:27:19,160 Speaker 1: this point in time in Web three crypto regulations because 499 00:27:19,200 --> 00:27:22,399 Speaker 1: it really expressed a desire and interest to foster and 500 00:27:22,520 --> 00:27:26,959 Speaker 1: facilitate responsible innovation. You fast forward to where we are 501 00:27:27,119 --> 00:27:31,560 Speaker 1: today and there really has not been any coherent strategy 502 00:27:31,640 --> 00:27:34,439 Speaker 1: coming at the federal level in terms of actually, how 503 00:27:34,480 --> 00:27:37,600 Speaker 1: do you support and advance that type of a holistic approach, 504 00:27:37,680 --> 00:27:41,520 Speaker 1: and what you've basically defaulted to is policy through enforcement. 505 00:27:41,560 --> 00:27:43,640 Speaker 1: It's a little bit like if we had just invented 506 00:27:43,680 --> 00:27:46,000 Speaker 1: cars and there were roads out there, and you basically 507 00:27:46,040 --> 00:27:47,919 Speaker 1: had to figure out the speed limit based on who 508 00:27:48,080 --> 00:27:49,680 Speaker 1: was arresting you at what speed, and then how the 509 00:27:49,760 --> 00:27:52,960 Speaker 1: courts ultimately would interpret that. That's no way to create 510 00:27:53,040 --> 00:27:55,879 Speaker 1: a coherent policy. I'm old enough to have gone back 511 00:27:55,920 --> 00:27:58,120 Speaker 1: to the nineties. I was working in the Clinton administration. 512 00:27:58,600 --> 00:28:01,720 Speaker 1: We passed the nineteen ninety Telco Act, worked with a 513 00:28:01,760 --> 00:28:05,639 Speaker 1: divided Congress Democrats and Republicans, that put the US on 514 00:28:05,840 --> 00:28:08,800 Speaker 1: the path to being the digital center of the world. 515 00:28:08,840 --> 00:28:13,560 Speaker 1: That translated into enormous economic power, enormous national security power. 516 00:28:13,920 --> 00:28:15,800 Speaker 1: At one point in time, I think the five largest 517 00:28:15,800 --> 00:28:18,320 Speaker 1: companies by market cap in the world were somewhere between 518 00:28:18,400 --> 00:28:21,560 Speaker 1: San Francisco and Seattle, right, and then you look at 519 00:28:21,600 --> 00:28:24,200 Speaker 1: what's going on today. But the history of the US 520 00:28:24,280 --> 00:28:28,679 Speaker 1: has always been a country since its founding that embraces innovation, 521 00:28:28,800 --> 00:28:32,760 Speaker 1: with government, public and private sector working together. Interestingly, with 522 00:28:32,880 --> 00:28:36,800 Speaker 1: this enforcement only approach, it is actually seeding its leadership role. 523 00:28:36,840 --> 00:28:39,440 Speaker 1: I mean, as we speak in your native UK, we 524 00:28:39,560 --> 00:28:42,920 Speaker 1: have activity, right now to potentially pass legislation by the 525 00:28:43,040 --> 00:28:44,920 Speaker 1: end of this year, which could be amongst the most 526 00:28:44,960 --> 00:28:48,280 Speaker 1: farthest reaching in terms of defining a regulatory framework for 527 00:28:48,360 --> 00:28:51,280 Speaker 1: crypto to make the UK a crypto hub. Chris Will 528 00:28:51,400 --> 00:28:55,880 Speaker 1: companies leave. I think that I look, I literally just 529 00:28:55,960 --> 00:28:59,360 Speaker 1: had a meeting a couple days ago. These weren't Han 530 00:28:59,600 --> 00:29:02,720 Speaker 1: venture companies, these were some others and they had reached 531 00:29:02,760 --> 00:29:05,280 Speaker 1: out to actually really try to understand where could we 532 00:29:05,400 --> 00:29:07,800 Speaker 1: potentially be looking at the world, And each and every 533 00:29:07,840 --> 00:29:09,760 Speaker 1: one of them was looking at places like the UK, 534 00:29:10,120 --> 00:29:12,880 Speaker 1: even looking at Europe. And you know, as someone that 535 00:29:12,920 --> 00:29:14,680 Speaker 1: get who came up in the US, the idea that 536 00:29:14,800 --> 00:29:17,400 Speaker 1: Europe is actually ahead of the US and thinking about 537 00:29:17,440 --> 00:29:20,360 Speaker 1: regulatory frameworks is just something that I had never really 538 00:29:20,520 --> 00:29:23,480 Speaker 1: seen before. And so I do think you're going to 539 00:29:23,520 --> 00:29:27,320 Speaker 1: get to a place where companies, projects, protocols, initiatives, founders, 540 00:29:27,480 --> 00:29:30,560 Speaker 1: entrepreneurs are going to begin to look around the world 541 00:29:30,600 --> 00:29:33,080 Speaker 1: about where they want to base themselves. Some may do 542 00:29:33,160 --> 00:29:35,960 Speaker 1: the US and something else, some may only do something else, 543 00:29:36,240 --> 00:29:39,400 Speaker 1: Some may spread their developers into these different places. But 544 00:29:39,880 --> 00:29:42,760 Speaker 1: ultimately this technology is happening, right this is the next 545 00:29:42,880 --> 00:29:44,520 Speaker 1: wave of the Internet. You see it with other private 546 00:29:44,560 --> 00:29:47,160 Speaker 1: sector entities wanting to engage with this technology. You see 547 00:29:47,200 --> 00:29:50,160 Speaker 1: other governments. And the question for the US is do 548 00:29:50,320 --> 00:29:53,360 Speaker 1: we want to maintain our historic leadership role or are 549 00:29:53,400 --> 00:29:56,480 Speaker 1: we going to give up on that fat Chris la 550 00:29:56,520 --> 00:30:00,479 Speaker 1: Hang comebacks saying we have chief strategy officer at home benches. Meanwhile, 551 00:30:00,480 --> 00:30:02,600 Speaker 1: shan Ali Bassett, we thank you so much for having 552 00:30:02,680 --> 00:30:05,120 Speaker 1: us bring that interview. Now let's get onto some other 553 00:30:05,200 --> 00:30:07,720 Speaker 1: key crypto news, because look, there's from fresh charges that've 554 00:30:07,720 --> 00:30:10,520 Speaker 1: been brought against FTX co founder Sam ban Winfried, including 555 00:30:10,880 --> 00:30:13,600 Speaker 1: references to a pair of co conspirators. The US says 556 00:30:13,840 --> 00:30:16,520 Speaker 1: we're involved in illegally seeking to influence the regulation of 557 00:30:16,600 --> 00:30:19,680 Speaker 1: digital assets. The campaign cash from him and other top 558 00:30:19,760 --> 00:30:23,160 Speaker 1: FDx executives has a potential to be the biggest infusion 559 00:30:23,160 --> 00:30:27,040 Speaker 1: of illegal money into the US politics in decades. And 560 00:30:27,520 --> 00:30:30,920 Speaker 1: what else we've got coming up? Yeah, a big exclusive 561 00:30:31,000 --> 00:30:34,680 Speaker 1: interview with job CEO on earnings and how soon we 562 00:30:34,720 --> 00:30:37,760 Speaker 1: can expect them, Sorry for this one car to take 563 00:30:37,840 --> 00:30:52,640 Speaker 1: off everything ev told next jokes. I love in fact 564 00:30:53,400 --> 00:30:58,920 Speaker 1: from our point of view, when it comes to Tesla Autonomous, 565 00:30:59,560 --> 00:31:04,000 Speaker 1: are their autonomous strategy autonomous taxi platforms is much more 566 00:31:04,080 --> 00:31:09,680 Speaker 1: important than their electric vehicle strategy. In our view, our 567 00:31:09,840 --> 00:31:13,760 Speaker 1: fifteen hundred dollars price target for Tesla, it's roughlo it's 568 00:31:13,800 --> 00:31:16,680 Speaker 1: a little over two hundred dollars now, but our fifteen 569 00:31:16,840 --> 00:31:21,320 Speaker 1: hundred dollar price target in five years is two thirds 570 00:31:21,560 --> 00:31:26,360 Speaker 1: because of autonomous And when we listen to BYD, we 571 00:31:26,560 --> 00:31:32,520 Speaker 1: do not hear autonomous as a strategy. That was Kafe 572 00:31:32,640 --> 00:31:35,200 Speaker 1: would of course, founder and CEO of our investments Carrow, 573 00:31:35,280 --> 00:31:39,400 Speaker 1: showing how optimistic she is about Tesla's robotaxi strategy. It's 574 00:31:39,400 --> 00:31:41,800 Speaker 1: a big part of their price target long term. We 575 00:31:41,880 --> 00:31:45,440 Speaker 1: asked our audience do you think Tesla wins the robotaxi race? 576 00:31:45,560 --> 00:31:48,120 Speaker 1: The answers kind of speak for themselves, but the idea 577 00:31:48,240 --> 00:31:50,680 Speaker 1: is Tesla's got more data than anyone. Do you think 578 00:31:50,720 --> 00:31:52,760 Speaker 1: they'll win? Carrow? It's a hard one to call because 579 00:31:52,760 --> 00:31:56,480 Speaker 1: everything seems so nascent still at the moment. What you 580 00:31:56,600 --> 00:32:00,280 Speaker 1: see cruise on the roads, I'm seeing weymo now and 581 00:32:00,320 --> 00:32:02,960 Speaker 1: then powering down where you are in San Francisco. How 582 00:32:03,120 --> 00:32:06,120 Speaker 1: many are you seeing that are of Tesla? How real 583 00:32:06,200 --> 00:32:08,920 Speaker 1: can that be in five years? The difference, I think 584 00:32:09,000 --> 00:32:11,080 Speaker 1: is that Tesla has all these vehicles that drivers are 585 00:32:11,160 --> 00:32:14,480 Speaker 1: using in all kinds of markets jurisdictions, whereas Cruz WAYMO, 586 00:32:14,600 --> 00:32:16,600 Speaker 1: they're just here in the Bay Area, right And I 587 00:32:16,720 --> 00:32:19,240 Speaker 1: think that's the problem going forward that analysts are struggling 588 00:32:19,280 --> 00:32:22,680 Speaker 1: to see when they prefer Tesla as the lead candidate. 589 00:32:22,720 --> 00:32:24,960 Speaker 1: We'll continue to track it. We do on a daily basis. Now. 590 00:32:25,320 --> 00:32:28,120 Speaker 1: Shares of ev toll maker job jumped on Thursday after 591 00:32:28,200 --> 00:32:31,520 Speaker 1: the company gave updates on its key milestones during earnings. 592 00:32:31,600 --> 00:32:35,160 Speaker 1: The company's first aircraft is expected to roll off a 593 00:32:35,200 --> 00:32:38,640 Speaker 1: pilot manufacturing line and fly within the next few months, 594 00:32:38,680 --> 00:32:41,520 Speaker 1: and the electric aircraft maker says it's getting closer on 595 00:32:41,600 --> 00:32:45,760 Speaker 1: those FA certifications, opening the door to commercialization. Joining us 596 00:32:45,800 --> 00:32:50,720 Speaker 1: now JOEB CEO joe Ben Bevertt is making progress, Joe Ben. 597 00:32:51,080 --> 00:32:54,560 Speaker 1: Analysts are still concerned about how far away commercialization is. 598 00:32:55,080 --> 00:33:00,000 Speaker 1: Answer their concerns. So we have been making remarkable progress. 599 00:33:00,200 --> 00:33:04,000 Speaker 1: Twenty twenty two is a fantastic year and we are 600 00:33:04,680 --> 00:33:08,120 Speaker 1: are really leaning in and the progress in twenty twenty 601 00:33:08,200 --> 00:33:14,440 Speaker 1: three is really accelerating. We're now two we've completed two 602 00:33:14,480 --> 00:33:18,360 Speaker 1: of the five stages of our certification process, and we're 603 00:33:18,440 --> 00:33:23,120 Speaker 1: making remarkable progress on third stage. As you mentioned, our 604 00:33:23,360 --> 00:33:28,760 Speaker 1: first company, conforming Aircraft is has the parts have rolled 605 00:33:28,800 --> 00:33:32,360 Speaker 1: off the pilot production line and we're beginning final assembly 606 00:33:32,400 --> 00:33:33,840 Speaker 1: and we'll be flying that in the months to come. 607 00:33:35,400 --> 00:33:39,160 Speaker 1: FAA certification is kind of the key bit, right because 608 00:33:39,240 --> 00:33:44,080 Speaker 1: to get those vehicles electric aircraft in the skies that 609 00:33:44,320 --> 00:33:48,280 Speaker 1: needs to be done. Are we talking months, years, decades 610 00:33:48,400 --> 00:33:53,840 Speaker 1: before the FAA does that because it's a slow moving organization. Yeah. 611 00:33:53,840 --> 00:33:57,000 Speaker 1: As I said, we've got really unprecedented momentum, both on 612 00:33:57,040 --> 00:34:02,400 Speaker 1: the joby side and on the FA side, with huge 613 00:34:02,960 --> 00:34:06,000 Speaker 1: progress that's been made over the past few months, and 614 00:34:07,160 --> 00:34:12,160 Speaker 1: we're just knocking down a milestone after milestone, and so 615 00:34:12,360 --> 00:34:15,120 Speaker 1: the momentum is really there, and we're very grateful for 616 00:34:15,160 --> 00:34:19,200 Speaker 1: the FA and the resources that they're putting into this 617 00:34:19,280 --> 00:34:22,600 Speaker 1: exciting new industry. Job And I was reading some of 618 00:34:22,640 --> 00:34:25,440 Speaker 1: the analyst reaction to what you had to say twenty 619 00:34:25,480 --> 00:34:28,239 Speaker 1: four hours ago, and the sort of more bullish name 620 00:34:28,360 --> 00:34:31,040 Speaker 1: see you as the kind of proof point for an 621 00:34:31,200 --> 00:34:34,720 Speaker 1: entire industry. You're leading the way. But the big concern 622 00:34:34,800 --> 00:34:36,759 Speaker 1: they have is that the FAA has to come up 623 00:34:36,840 --> 00:34:40,520 Speaker 1: with rules for a whole new category of aircraft. How 624 00:34:41,360 --> 00:34:43,880 Speaker 1: much evidence do you see that the FAA has the 625 00:34:44,000 --> 00:34:47,880 Speaker 1: competence and energy to do that. Well, the exciting thing 626 00:34:47,960 --> 00:34:51,600 Speaker 1: for us is that that process is now behind us, 627 00:34:51,760 --> 00:34:55,520 Speaker 1: as we've completed those first two stages and the stage 628 00:34:55,560 --> 00:35:01,319 Speaker 1: that we're rendering is completing our the last of area 629 00:35:01,400 --> 00:35:05,040 Speaker 1: specific certification plans. So we've had the FA approved five 630 00:35:05,200 --> 00:35:09,719 Speaker 1: of the thirteen, we've submitted an additional three, and we're 631 00:35:09,760 --> 00:35:12,680 Speaker 1: expecting to submit all thirteen of those in the first 632 00:35:12,719 --> 00:35:15,759 Speaker 1: half of the year. So and again the means of 633 00:35:15,840 --> 00:35:21,360 Speaker 1: compliance are now behind us and we're really focused on 634 00:35:21,400 --> 00:35:23,880 Speaker 1: the future. This year is going to be a lot 635 00:35:23,920 --> 00:35:28,399 Speaker 1: about testing, and that's what makes aviation our safest mode 636 00:35:28,400 --> 00:35:32,919 Speaker 1: of transportation is the rigor with which we build every 637 00:35:32,960 --> 00:35:37,680 Speaker 1: single component and then test every single component on the aircraft. Jovann, 638 00:35:37,719 --> 00:35:40,280 Speaker 1: You also have this relationship with the Department of Defense. 639 00:35:40,440 --> 00:35:43,400 Speaker 1: In long term, I want to understand what proportion of 640 00:35:43,480 --> 00:35:46,680 Speaker 1: your business, your commercial business will be based on government 641 00:35:46,719 --> 00:35:51,359 Speaker 1: and military contracts and what will be a consumer facing business. Well, 642 00:35:51,520 --> 00:35:56,960 Speaker 1: that's something that we're going to learn over the overcoming years. 643 00:35:57,560 --> 00:36:00,920 Speaker 1: But what's really exciting today is the momentum we have 644 00:36:01,560 --> 00:36:06,440 Speaker 1: with the Department. Department of Defense. We have now have 645 00:36:07,280 --> 00:36:10,920 Speaker 1: a seventy five million dollar contract with the DoD to 646 00:36:13,520 --> 00:36:16,440 Speaker 1: mature the development of our aircraft, and we're in discussions 647 00:36:16,480 --> 00:36:20,480 Speaker 1: with them on being able to bring our aircraft on 648 00:36:20,719 --> 00:36:25,000 Speaker 1: base and provide really useful operations here in the US 649 00:36:25,680 --> 00:36:30,160 Speaker 1: for our government partners, and we're excited to be beginning 650 00:36:30,239 --> 00:36:33,120 Speaker 1: that on base operations will which will give us both 651 00:36:33,200 --> 00:36:37,719 Speaker 1: revenue and even more importantly, allow us to streamline and 652 00:36:37,840 --> 00:36:43,320 Speaker 1: optimize our optimization our operations prior to commercial launch to 653 00:36:43,560 --> 00:36:45,960 Speaker 1: be Aviation found at Joe Benbevett. Thank you so much 654 00:36:46,000 --> 00:36:47,320 Speaker 1: for you the time on the show. It's great to 655 00:36:47,400 --> 00:36:58,560 Speaker 1: have you. Um. Netflix is trying to grow internationally and 656 00:36:58,760 --> 00:37:01,600 Speaker 1: so it is slash the cost of some subscriptions in 657 00:37:01,719 --> 00:37:04,839 Speaker 1: more than one hundred different countries. But I'm afraid if 658 00:37:04,880 --> 00:37:06,200 Speaker 1: you're like me in the US, it's not gonna be 659 00:37:06,280 --> 00:37:09,880 Speaker 1: helping me here. And in developed world they're trying to 660 00:37:10,160 --> 00:37:12,760 Speaker 1: well make us pay our ways stop on that password 661 00:37:12,800 --> 00:37:15,160 Speaker 1: sharing we've all been doing. But it's all about the 662 00:37:15,200 --> 00:37:19,600 Speaker 1: focus on the developing markets. So think Asia, the America's 663 00:37:19,680 --> 00:37:22,640 Speaker 1: Middle East, in countries that they haven't managed to build 664 00:37:22,680 --> 00:37:26,360 Speaker 1: up so many subscribers, so countries like Vietnam, Thailand, and 665 00:37:26,400 --> 00:37:29,719 Speaker 1: Adonesia could be seen subscriptions and the cost cut by 666 00:37:29,800 --> 00:37:33,279 Speaker 1: almost fifty percent. According to some analysis, this should help 667 00:37:33,440 --> 00:37:36,880 Speaker 1: boost perhaps the overall global user passed that two hundred 668 00:37:36,880 --> 00:37:41,240 Speaker 1: and thirty one million number they're already at. Today's going viral. 669 00:37:41,440 --> 00:37:43,080 Speaker 1: Let's get back to some of that news that crossed 670 00:37:43,120 --> 00:37:46,439 Speaker 1: this hour. The Justice Department preparing an antitrust lawsuits seeking 671 00:37:46,480 --> 00:37:50,040 Speaker 1: to block Adova's twenty billion dollar acquisition of the startup Figma. Now, 672 00:37:50,040 --> 00:37:52,200 Speaker 1: according to people familiar, no matter, our cases expect to 673 00:37:52,239 --> 00:37:54,960 Speaker 1: be found as soon as next month. We're very pleased 674 00:37:54,960 --> 00:37:57,000 Speaker 1: to say immediately with us as Anna A. Grana Is 675 00:37:57,160 --> 00:38:00,800 Speaker 1: of Bloomberg Intelligence, why is it stop four when everyone 676 00:38:00,880 --> 00:38:04,279 Speaker 1: hated this deal to begin with. I'm as confused as 677 00:38:04,320 --> 00:38:06,000 Speaker 1: you are on this one. You know, we'll find out 678 00:38:06,000 --> 00:38:08,800 Speaker 1: tomorrow morning what happens. But you know, frankly speaking, we 679 00:38:08,880 --> 00:38:12,759 Speaker 1: had expected that. Our anti trust stannel is generally basically said, 680 00:38:13,000 --> 00:38:14,919 Speaker 1: it's going to be difficult to get this thing done 681 00:38:15,000 --> 00:38:18,839 Speaker 1: because of so much scrutiny on large tech firms trying 682 00:38:18,840 --> 00:38:22,239 Speaker 1: to buy smaller incumbents that are threatening their business. So 683 00:38:22,360 --> 00:38:24,960 Speaker 1: we'll see what that happens. But you know, I'm also 684 00:38:25,000 --> 00:38:28,560 Speaker 1: surprised that the starts down right now. And I the 685 00:38:28,640 --> 00:38:32,600 Speaker 1: other surprising you've outlining your Bloomberg Intelligence reacts dead is 686 00:38:32,640 --> 00:38:35,839 Speaker 1: how soon this came about. I think the market expected 687 00:38:36,280 --> 00:38:38,680 Speaker 1: regulatory bodies around the world to look at it, but 688 00:38:38,760 --> 00:38:42,919 Speaker 1: you're saying, actually, action is happening sooner than we thought. Yeah, 689 00:38:43,000 --> 00:38:45,640 Speaker 1: And I'm to be honest with you, with Jendre's work, 690 00:38:45,800 --> 00:38:48,799 Speaker 1: that is, I'm quoting very basically, I depend on her 691 00:38:48,880 --> 00:38:51,759 Speaker 1: for all of these expert opinions, and you know, she 692 00:38:51,920 --> 00:38:55,120 Speaker 1: thinks it is much sooner than what she was expecting. 693 00:38:55,200 --> 00:38:57,520 Speaker 1: And the reason is that I think there is so 694 00:38:57,760 --> 00:39:00,640 Speaker 1: much I mean, every major tech deal is looked under 695 00:39:00,680 --> 00:39:02,840 Speaker 1: a microscope right now, and they want to make a 696 00:39:02,920 --> 00:39:04,680 Speaker 1: point that they are not going to, let you know, 697 00:39:04,800 --> 00:39:08,200 Speaker 1: something like a Facebook buying Instagram again, um, you know 698 00:39:08,320 --> 00:39:10,560 Speaker 1: out there. So let's see how this turns out. But 699 00:39:11,120 --> 00:39:12,560 Speaker 1: you know, I think in the long run, if they 700 00:39:12,640 --> 00:39:15,040 Speaker 1: are forced not to buy it, it maybe not. It 701 00:39:15,160 --> 00:39:17,000 Speaker 1: may not be that bad of a thing for Adobe. 702 00:39:17,280 --> 00:39:19,680 Speaker 1: They can deploy that cast somewhere else and try to 703 00:39:19,760 --> 00:39:23,160 Speaker 1: do this organically. Okay, interesting, it would probably be pretty 704 00:39:23,160 --> 00:39:26,000 Speaker 1: awful for Figma. In some ways one might imagine just 705 00:39:26,600 --> 00:39:30,719 Speaker 1: how much would this be coordinated elsewhere as well. I 706 00:39:30,800 --> 00:39:32,759 Speaker 1: think one of the things that we have seen that 707 00:39:32,920 --> 00:39:36,160 Speaker 1: once they've got a whip, that US organized authorities are 708 00:39:36,239 --> 00:39:38,520 Speaker 1: really strict about some of this stuff. We have seen 709 00:39:38,600 --> 00:39:41,680 Speaker 1: Europe already, you know, trying to break up you know, 710 00:39:42,280 --> 00:39:45,360 Speaker 1: Microsoft Activision with basically saying you know, you've got to 711 00:39:45,360 --> 00:39:47,319 Speaker 1: get rid of a game. I mean that it's it's 712 00:39:47,360 --> 00:39:49,600 Speaker 1: it's kind of like, you know, I would say this 713 00:39:49,800 --> 00:39:52,719 Speaker 1: is very common across the globe right now, where most 714 00:39:52,760 --> 00:39:56,400 Speaker 1: of the authorities are pretty pretty against large tech companies 715 00:39:56,440 --> 00:40:00,399 Speaker 1: buying anything right now. It's the same Anaragrana. We thank 716 00:40:00,440 --> 00:40:05,560 Speaker 1: you for jumping in from Bloomberg Intelligence bringing us the expertise. Yeah, 717 00:40:05,680 --> 00:40:08,640 Speaker 1: that does it for this edition, Carroc of Bloomberg Technology. 718 00:40:08,680 --> 00:40:10,319 Speaker 1: What a week has been so far, just one day 719 00:40:10,360 --> 00:40:13,040 Speaker 1: to go and so much to digest tomorrow on our 720 00:40:13,080 --> 00:40:15,080 Speaker 1: Twitter spaces we do it every Friday. Thanks to you, 721 00:40:15,160 --> 00:40:17,120 Speaker 1: we're driving the force of what we're going to be 722 00:40:17,160 --> 00:40:20,719 Speaker 1: discussing at twelve pm New York Times nine am San Francisco. 723 00:40:20,880 --> 00:40:23,200 Speaker 1: Tune in on the Twitter spaces to see if we've 724 00:40:23,200 --> 00:40:25,040 Speaker 1: got some news breaking across it like we have done 725 00:40:25,080 --> 00:40:28,240 Speaker 1: in previous weeks. Hey yeah, and there's also that huge 726 00:40:28,320 --> 00:40:31,879 Speaker 1: story from German on Apple glucose and the Apple Watch. 727 00:40:31,920 --> 00:40:33,839 Speaker 1: We've got a recam. It's the biggest one of the week. 728 00:40:34,760 --> 00:40:37,360 Speaker 1: From New York. From San Francisco, this is Bloomberg.