1 00:00:01,360 --> 00:00:06,600 Speaker 1: From hard where Innovation, Money and Power Collie in Silicon Valley, NBR. 2 00:00:06,960 --> 00:00:11,000 Speaker 1: This is Bloomberg Technology with Caroline Hide and Ed Lovedlow 3 00:00:24,960 --> 00:00:27,360 Speaker 1: in Caroline Hide every Bloomberg's World headquarters in New York, 4 00:00:27,760 --> 00:00:30,280 Speaker 1: and I'm Ed Lovelow in San Francisco. This is Bloomberg 5 00:00:30,320 --> 00:00:34,000 Speaker 1: Technology iming our Bitcoin tops thirty thousand dollars. We'll discuss 6 00:00:34,120 --> 00:00:37,080 Speaker 1: what's driving the gains the assets getting a boost on 7 00:00:37,120 --> 00:00:40,000 Speaker 1: those moves. Class will take a deep dive into one 8 00:00:40,000 --> 00:00:43,519 Speaker 1: of the biggest US intelligence leaks in recent history. More 9 00:00:43,560 --> 00:00:47,000 Speaker 1: details on the breach ahead, and we'll be all across 10 00:00:47,040 --> 00:00:50,519 Speaker 1: the race for artificial intelligence dominance capital g Anous is 11 00:00:50,520 --> 00:00:54,000 Speaker 1: one hundred million dollar funding round for an AI research platform, 12 00:00:54,040 --> 00:00:58,000 Speaker 1: Alpha Sense. But first let's check in on these public markets, 13 00:00:58,040 --> 00:01:01,080 Speaker 1: because actually tech is feeling little less love than the 14 00:01:01,080 --> 00:01:02,680 Speaker 1: rest of the benchmarks. Today we're up by four ten 15 00:01:02,800 --> 00:01:05,200 Speaker 1: percent on the NASAC all important data point. You heard 16 00:01:05,200 --> 00:01:07,920 Speaker 1: it from Alex Guy just earlier. The CPI print tomorrow. 17 00:01:07,920 --> 00:01:10,360 Speaker 1: A little bit of nervousness therefore around owning big tech. 18 00:01:10,600 --> 00:01:12,560 Speaker 1: Some of the key tech names as will drill into 19 00:01:12,600 --> 00:01:15,120 Speaker 1: a little bit later, But All Country World Index interesting 20 00:01:15,160 --> 00:01:17,240 Speaker 1: me on the higher side. Europe came back after the 21 00:01:17,280 --> 00:01:20,160 Speaker 1: Easter holiday, the extended break and managed to put a 22 00:01:20,160 --> 00:01:22,119 Speaker 1: little bit of fuel under that fire. Two year yield though, 23 00:01:22,160 --> 00:01:24,240 Speaker 1: just rises up some five basis points. As we all 24 00:01:24,360 --> 00:01:26,480 Speaker 1: attention on CPI and what it means for the federals 25 00:01:26,480 --> 00:01:29,160 Speaker 1: EVE move it on. What's happening in terms of crypto 26 00:01:29,440 --> 00:01:32,639 Speaker 1: thirty thousand dollars well above Now we managed to break 27 00:01:32,760 --> 00:01:35,199 Speaker 1: three of that trading range at the twenty eight thousand. 28 00:01:35,240 --> 00:01:38,080 Speaker 1: We were generally languishing around for the past few weeks, 29 00:01:38,080 --> 00:01:41,640 Speaker 1: and what does it mean some really psychological levels being hit? Now? 30 00:01:41,720 --> 00:01:44,560 Speaker 1: Are we going back to eclipsing the prices where we 31 00:01:44,600 --> 00:01:47,800 Speaker 1: saw the three hours capital disintegration where you saw Terra 32 00:01:47,880 --> 00:01:50,400 Speaker 1: Luna de marcle. We're now up seven percent over the 33 00:01:50,440 --> 00:01:53,200 Speaker 1: last two days. Yeah, the big question is still why. 34 00:01:53,520 --> 00:01:56,160 Speaker 1: But the what is playing out in equity markets as well? 35 00:01:56,200 --> 00:01:59,240 Speaker 1: You look at crypto related stocks, we're markedly higher in 36 00:01:59,280 --> 00:02:01,680 Speaker 1: a number of actually want to go to micro Strategy 37 00:02:01,960 --> 00:02:05,120 Speaker 1: because the four billion dollar bet that it made on bitcoin. 38 00:02:05,240 --> 00:02:08,240 Speaker 1: That company is now back in the black because bitcoin 39 00:02:08,360 --> 00:02:12,119 Speaker 1: is trading above the average transaction price. There's so much 40 00:02:12,120 --> 00:02:14,840 Speaker 1: out there today about well, what happens if the FED 41 00:02:15,080 --> 00:02:17,720 Speaker 1: brings rates back down? What does that mean for Bitcoin? 42 00:02:17,919 --> 00:02:20,000 Speaker 1: What happens if we enter a recession? Then you look 43 00:02:20,000 --> 00:02:23,520 Speaker 1: at the relative performance of Bitcoin to other I guess 44 00:02:23,800 --> 00:02:26,079 Speaker 1: risk assets, you know, in terms of the best performance 45 00:02:26,080 --> 00:02:28,040 Speaker 1: of the year. I still don't have a great sense 46 00:02:28,080 --> 00:02:31,600 Speaker 1: on what is happening. Luckily, we've got a couple of guests, 47 00:02:31,639 --> 00:02:33,600 Speaker 1: so go be perfectly placed to discuss it all as 48 00:02:33,600 --> 00:02:36,280 Speaker 1: well as the upgrade as soon as tomorrow. But in begs, 49 00:02:36,360 --> 00:02:40,160 Speaker 1: Katie Greifeld kicks us off, Katie, what are you seeing 50 00:02:40,240 --> 00:02:42,040 Speaker 1: around the world of crypto at the moment? What don't 51 00:02:42,040 --> 00:02:44,760 Speaker 1: you There are so many narratives as to what could 52 00:02:44,760 --> 00:02:47,720 Speaker 1: be pushing bitcoin higher. In particular, there's a lot of narratives. 53 00:02:47,720 --> 00:02:51,079 Speaker 1: There's no satisfying answer other than the one that this 54 00:02:51,120 --> 00:02:54,200 Speaker 1: is a macro asset. It tends to follow sort of 55 00:02:54,200 --> 00:02:57,959 Speaker 1: the macro narrative that's of the day and of the day. 56 00:02:58,000 --> 00:03:00,359 Speaker 1: Of the past few weeks, the narrative has been that 57 00:03:00,400 --> 00:03:02,280 Speaker 1: the FED is going to be forced to cut rates 58 00:03:02,360 --> 00:03:05,520 Speaker 1: at some point this year. That would obviously be good 59 00:03:05,520 --> 00:03:08,000 Speaker 1: news for the likes of tech, for the likes of crypto. 60 00:03:08,040 --> 00:03:10,520 Speaker 1: When you think about that low interest rate environment that 61 00:03:10,680 --> 00:03:13,919 Speaker 1: really pushed investors out the risk spectrum. What's been interesting 62 00:03:14,160 --> 00:03:16,120 Speaker 1: over the past few days is that you've seen bitcoin 63 00:03:16,200 --> 00:03:18,959 Speaker 1: sort of break apart from tech. Today is a great 64 00:03:18,960 --> 00:03:21,799 Speaker 1: example of Bitcoin up what almost four percent. Then you 65 00:03:21,840 --> 00:03:24,160 Speaker 1: look at the NAZAC one hundred down about half a 66 00:03:24,200 --> 00:03:27,720 Speaker 1: percent or so, so maybe those correlations coming apart a 67 00:03:27,760 --> 00:03:31,080 Speaker 1: bit to the benefit of bitcoin. I would say, though, 68 00:03:31,080 --> 00:03:33,840 Speaker 1: that liquidity in this space is still very, very low 69 00:03:33,880 --> 00:03:36,680 Speaker 1: despite this rebound. I think it's also a question of 70 00:03:36,680 --> 00:03:39,280 Speaker 1: who is in this market, who is buying right where 71 00:03:39,480 --> 00:03:42,360 Speaker 1: the thirty thousand US dollar potoken mark for the first 72 00:03:42,400 --> 00:03:45,960 Speaker 1: time since June of last year, but still significantly far 73 00:03:46,000 --> 00:03:48,720 Speaker 1: from the November twenty twenty one high. What are the 74 00:03:48,760 --> 00:03:53,240 Speaker 1: big forces in terms of institutions names driving this market, Katie, 75 00:03:53,760 --> 00:03:55,800 Speaker 1: None to speak of, really, and that's part of the 76 00:03:55,840 --> 00:03:58,440 Speaker 1: reason why you have liquidity so low right now. According 77 00:03:58,520 --> 00:04:02,320 Speaker 1: to some measures, bitcoin equidity hovering near a ten month low. 78 00:04:02,360 --> 00:04:06,400 Speaker 1: You haven't really seen a big institutional push with this rebound, 79 00:04:06,400 --> 00:04:08,400 Speaker 1: and if you look at some of the retail flows 80 00:04:08,440 --> 00:04:11,160 Speaker 1: I like to track exchange traded products both in the 81 00:04:11,280 --> 00:04:14,880 Speaker 1: US and Europe, you really haven't seen any meaningful influence 82 00:04:15,080 --> 00:04:17,680 Speaker 1: to speak of. So the tourists are gone from this market, 83 00:04:17,680 --> 00:04:20,800 Speaker 1: the institutions are gone from this market. You're left with 84 00:04:20,880 --> 00:04:24,279 Speaker 1: sort of the crypto believers who are pushing the price 85 00:04:24,360 --> 00:04:26,800 Speaker 1: higher again in very low liquidity, which has helped to 86 00:04:26,880 --> 00:04:29,599 Speaker 1: the upside. But if we get some sort of upset, 87 00:04:29,680 --> 00:04:32,920 Speaker 1: perhaps in the form of a more hawkish FED than expected, 88 00:04:32,960 --> 00:04:36,200 Speaker 1: that low liquidity could exacerbate things to the downside as well. 89 00:04:36,839 --> 00:04:39,240 Speaker 1: All right, bloom bows, Katie Greyfeld, thank you very much. 90 00:04:39,320 --> 00:04:42,640 Speaker 1: Welcome now Spencive bog At Blockchain Capital or general partner 91 00:04:42,760 --> 00:04:46,599 Speaker 1: here with me in San Francisco. You are essentially a 92 00:04:46,640 --> 00:04:52,159 Speaker 1: fundamental investment analysts. You lead research. What did the fundamentals 93 00:04:52,160 --> 00:04:54,120 Speaker 1: tell you about what on earth is happening with bitcoin 94 00:04:54,279 --> 00:04:56,200 Speaker 1: right now? So most the fundamentals that we deal with 95 00:04:56,240 --> 00:05:00,800 Speaker 1: are early stage, But which fundamentals are there any fundamentals point? So, 96 00:05:00,839 --> 00:05:02,799 Speaker 1: most of the fundamentals we work with for early stage 97 00:05:02,800 --> 00:05:04,680 Speaker 1: startups are related to all the things you'd see in 98 00:05:04,720 --> 00:05:07,280 Speaker 1: any traditional software startup. Right We're looking at user growth, 99 00:05:07,320 --> 00:05:10,840 Speaker 1: we're looking at transaction activity depending on the particular company. 100 00:05:11,240 --> 00:05:14,359 Speaker 1: Now here for bitcoin, when we're trying to describe or 101 00:05:14,400 --> 00:05:16,880 Speaker 1: explain the price action. We always want to come back 102 00:05:16,880 --> 00:05:19,680 Speaker 1: to one reason, but the reality is that there's a 103 00:05:19,720 --> 00:05:24,359 Speaker 1: wide variety of market participants in crypto, and so I 104 00:05:24,360 --> 00:05:27,760 Speaker 1: think that there's myriad factors at play simultaneously. You already 105 00:05:27,800 --> 00:05:29,920 Speaker 1: touched on a few of those, but one of them 106 00:05:29,960 --> 00:05:32,440 Speaker 1: is the lingering inflation. Say, I want to channel my 107 00:05:32,520 --> 00:05:37,080 Speaker 1: inner Katie Greifeld, Sure, because she lives bitcoin second by second. Yeah, 108 00:05:37,360 --> 00:05:41,159 Speaker 1: and she basically points out no earnings, no cash flow, 109 00:05:41,800 --> 00:05:44,919 Speaker 1: no underlying business for you to analyze. You actually just 110 00:05:45,000 --> 00:05:47,599 Speaker 1: pointed out the opposite. Those are exactly the sort of 111 00:05:47,640 --> 00:05:52,320 Speaker 1: criteria looking at when assessing bitcoins. Push higher. Sure, So 112 00:05:52,360 --> 00:05:53,880 Speaker 1: I mean for a lot of people looking at this, 113 00:05:54,000 --> 00:05:57,440 Speaker 1: I think they're seeing there's still some concerns about inflation. 114 00:05:57,560 --> 00:05:59,680 Speaker 1: So the idea of a scarce asset with a fixed 115 00:05:59,680 --> 00:06:05,000 Speaker 1: supply has appeal. There's still some lingering banking concerns, even 116 00:06:05,040 --> 00:06:08,240 Speaker 1: though the peak of the concerns have died down. But 117 00:06:08,320 --> 00:06:11,840 Speaker 1: that increases demand for an asset that people can securely 118 00:06:11,920 --> 00:06:14,960 Speaker 1: self custody as owners. Right. So those are two of 119 00:06:15,000 --> 00:06:18,440 Speaker 1: maybe the four reasons I'd say that are driving bitcoin higher. Hey, Caro, 120 00:06:18,680 --> 00:06:22,520 Speaker 1: In the technology sector, whether it's equities, whether it's crypto. 121 00:06:22,600 --> 00:06:25,440 Speaker 1: If in doubt go back to inflation in the FED. 122 00:06:26,400 --> 00:06:28,320 Speaker 1: I mean that was always the argument. Was it an 123 00:06:28,320 --> 00:06:30,960 Speaker 1: inflation hedge that didn't seem to bear out from the 124 00:06:31,080 --> 00:06:33,680 Speaker 1: numbers when we saw inflation spencer. But we do see 125 00:06:33,720 --> 00:06:36,560 Speaker 1: it more of a buffeted about by the Federal Reserve 126 00:06:36,600 --> 00:06:40,680 Speaker 1: and risk tolerance. What about institutional players we're talking to 127 00:06:40,760 --> 00:06:42,840 Speaker 1: Katie about that, are they starting to be tempted to 128 00:06:42,880 --> 00:06:47,440 Speaker 1: come end back in when we see a thirty thousand level. Absolutely, 129 00:06:47,480 --> 00:06:49,920 Speaker 1: I think for the institutional players, I mean, listen, we 130 00:06:50,000 --> 00:06:52,680 Speaker 1: run a venture capital fund that invest in early stage companies. 131 00:06:52,720 --> 00:06:55,040 Speaker 1: A lot of our limited partners in our fund are 132 00:06:55,160 --> 00:06:59,679 Speaker 1: large institutional allocators, endowments and pension funds in an increasing 133 00:06:59,760 --> 00:07:04,200 Speaker 1: number of them own cryptodirectly, primarily bitcoin and or ether, 134 00:07:04,680 --> 00:07:07,680 Speaker 1: but then they also want additional exposure via venture capital funds. 135 00:07:07,680 --> 00:07:10,360 Speaker 1: They're invested in the space, so there is absolutely an 136 00:07:10,360 --> 00:07:13,280 Speaker 1: appetite from them, But overall, I would say that most 137 00:07:13,280 --> 00:07:15,200 Speaker 1: of them allocated over the past couple of years and 138 00:07:15,200 --> 00:07:18,720 Speaker 1: have not been adding more recently. Go to eighth for us, 139 00:07:18,760 --> 00:07:21,640 Speaker 1: because we are looking towards what is the continuation of 140 00:07:21,680 --> 00:07:24,720 Speaker 1: the upgrade to more of a proof of state concept. 141 00:07:24,800 --> 00:07:28,920 Speaker 1: We're having the Shanghai upgrade tomorrow. In Layman's terms, what 142 00:07:28,960 --> 00:07:31,000 Speaker 1: does that mean? Do you expect there to be more 143 00:07:31,080 --> 00:07:35,840 Speaker 1: volatility around the space. I don't expect a lot of volatility, 144 00:07:35,880 --> 00:07:38,080 Speaker 1: but in Layman's terms, what's going on here is that 145 00:07:38,360 --> 00:07:41,400 Speaker 1: the way that the Ethereum network is secured is by 146 00:07:41,440 --> 00:07:45,720 Speaker 1: people providing or staking their capital their ether into the 147 00:07:45,760 --> 00:07:50,440 Speaker 1: protocol itself. They're rewarded for doing so financially. And what 148 00:07:50,560 --> 00:07:54,160 Speaker 1: happens tomorrow is people are now able to withdraw the 149 00:07:54,160 --> 00:07:56,960 Speaker 1: ether that they have stated. So this only started a 150 00:07:57,000 --> 00:07:59,680 Speaker 1: little over a year ago when we had the merge, 151 00:07:59,720 --> 00:08:02,880 Speaker 1: that of stake really came into into being, and now 152 00:08:02,880 --> 00:08:04,960 Speaker 1: we're about to see is that people can withdraw the 153 00:08:05,040 --> 00:08:08,920 Speaker 1: assets that they have staked. That said, from our conversations 154 00:08:08,960 --> 00:08:11,120 Speaker 1: around the market, we're not seen a lot of demand 155 00:08:11,160 --> 00:08:14,200 Speaker 1: for people to unstake their assets, so we mostly think 156 00:08:14,200 --> 00:08:16,440 Speaker 1: that this will be a non event tomorrow. Yes, when 157 00:08:16,480 --> 00:08:19,120 Speaker 1: so many have been saying it feels as though the 158 00:08:19,200 --> 00:08:22,040 Speaker 1: players who stake there, if they're long term committed to 159 00:08:22,040 --> 00:08:25,480 Speaker 1: the space, but ed whether or not vench capital remains 160 00:08:25,560 --> 00:08:28,240 Speaker 1: long term committed to the space amid some of the 161 00:08:28,280 --> 00:08:31,240 Speaker 1: debacles of last year. That's still the key question, particularly 162 00:08:31,240 --> 00:08:34,400 Speaker 1: as they know much more nervous to write checks. Yeah, 163 00:08:34,440 --> 00:08:36,760 Speaker 1: and that's where I would go to Spencer next. Because 164 00:08:37,040 --> 00:08:40,800 Speaker 1: we've been distracted by artificial intelligence, we've looked at volatility. 165 00:08:40,840 --> 00:08:44,040 Speaker 1: I mean, as an asset class, bitcoin still carries a 166 00:08:44,080 --> 00:08:47,360 Speaker 1: lot of volatility. Spenser. The root of my question is 167 00:08:47,880 --> 00:08:50,480 Speaker 1: have any of the sort of psychological drivers in this 168 00:08:50,559 --> 00:08:52,880 Speaker 1: market change so far in twenty twenty three when you 169 00:08:52,880 --> 00:08:55,600 Speaker 1: think about the SVB fallout, or has the cryptoc community 170 00:08:55,720 --> 00:08:57,880 Speaker 1: kind of just got on with it. Mostly people have 171 00:08:57,960 --> 00:08:59,600 Speaker 1: just gotten on with it, right, I mean, there are 172 00:08:59,640 --> 00:09:02,800 Speaker 1: some new headwinds I think from FTX collapse that are 173 00:09:02,880 --> 00:09:06,720 Speaker 1: presenting regulatory headwinds, but overall, the industry is just pushing forward. 174 00:09:06,840 --> 00:09:09,199 Speaker 1: It is much more organized than it has been historically, 175 00:09:09,240 --> 00:09:12,319 Speaker 1: at least in terms of tackling some of these regulatory 176 00:09:12,320 --> 00:09:15,480 Speaker 1: and political issues. So overall, what we're seeing is for 177 00:09:15,600 --> 00:09:18,400 Speaker 1: venture capital firms, they're following the talent and they're watching 178 00:09:18,480 --> 00:09:20,680 Speaker 1: there continues to be a flow of high quality talent 179 00:09:21,040 --> 00:09:24,400 Speaker 1: into cryptocompanies and crypto markets. Spencie, you just mentioned that 180 00:09:24,520 --> 00:09:27,040 Speaker 1: though that got on with it amid the collapse of 181 00:09:27,440 --> 00:09:32,440 Speaker 1: signature of Silva Silva Gate. I'm interested in the banking 182 00:09:32,520 --> 00:09:37,040 Speaker 1: rails though, and how much that has impacted liquidity. It's 183 00:09:37,080 --> 00:09:39,280 Speaker 1: certainly been an impact. I mean, several of the largest 184 00:09:39,280 --> 00:09:43,320 Speaker 1: banks that were servicing crypto companies provided critical infrastructure for 185 00:09:43,400 --> 00:09:46,400 Speaker 1: all of those companies to be able to exchange capital 186 00:09:46,400 --> 00:09:49,680 Speaker 1: on a twenty four seven basis. That's particularly important for 187 00:09:49,760 --> 00:09:52,920 Speaker 1: crypto markets that operate twenty four seven three sixty five. 188 00:09:53,480 --> 00:09:55,760 Speaker 1: Now some of those banks have been put out of business, 189 00:09:56,160 --> 00:09:59,360 Speaker 1: and there is an open opportunity for someone to recreate 190 00:09:59,360 --> 00:10:03,319 Speaker 1: the infrastruct the previously existed. All Right, Spencer Boga blockchain 191 00:10:03,400 --> 00:10:06,800 Speaker 1: capital with bitcoin and around thirty thousand, two hundred and 192 00:10:06,800 --> 00:10:17,360 Speaker 1: fifty nine dollars per token. The US is facing tough 193 00:10:17,480 --> 00:10:20,640 Speaker 1: questions from allies after a trove of classified documents were 194 00:10:20,679 --> 00:10:24,200 Speaker 1: leaked online to the global public. Former US National security 195 00:10:24,240 --> 00:10:26,559 Speaker 1: advisor that's John Bolton spoke about the league earlier on 196 00:10:26,600 --> 00:10:30,840 Speaker 1: Bags of Valence Taken Listen. I would also caution at 197 00:10:30,840 --> 00:10:34,360 Speaker 1: this point that we not draw too many conclusions that 198 00:10:34,480 --> 00:10:38,520 Speaker 1: this could be an influence operation by somebody we don't 199 00:10:38,559 --> 00:10:41,040 Speaker 1: know who And once you get into the world of 200 00:10:41,120 --> 00:10:45,720 Speaker 1: counter intelligence, it makes being in a whole mirrors look easy. 201 00:10:45,880 --> 00:10:50,240 Speaker 1: It's very complicated. Let's try and break down some of 202 00:10:50,280 --> 00:10:53,000 Speaker 1: the complexities with our own. Nick Wadhams, he's Bloomberg News 203 00:10:53,080 --> 00:10:56,480 Speaker 1: National Security editor, just how big a trove of information 204 00:10:56,600 --> 00:11:01,480 Speaker 1: is this ening? Well, it's pretty darn and it really 205 00:11:01,520 --> 00:11:04,200 Speaker 1: confirms in a lot of ways what we had known 206 00:11:04,360 --> 00:11:08,000 Speaker 1: and what US officials had been telling us publicly about 207 00:11:08,040 --> 00:11:10,199 Speaker 1: what their really biggest fears are. And the big one 208 00:11:10,240 --> 00:11:14,320 Speaker 1: there is Ukraine and specifically the possibility that Ukraine will 209 00:11:14,440 --> 00:11:17,960 Speaker 1: run out of ammunition in the fight against Russia, both 210 00:11:18,080 --> 00:11:23,160 Speaker 1: artillery shells but also air defenses. So it seems to 211 00:11:23,200 --> 00:11:25,560 Speaker 1: be we're really peeling back the veneer a bit and 212 00:11:25,640 --> 00:11:28,720 Speaker 1: getting into the real nitty gritty of just how worried 213 00:11:29,240 --> 00:11:32,400 Speaker 1: US officials are about how Ukraine's going to be able 214 00:11:32,440 --> 00:11:35,720 Speaker 1: to defend itself against Russia. Nick, when we look over 215 00:11:35,880 --> 00:11:39,400 Speaker 1: history at leaks of this kind, the questions quickly become 216 00:11:39,880 --> 00:11:44,600 Speaker 1: where the documents originated from and they're authenticity? Right? What 217 00:11:44,640 --> 00:11:48,800 Speaker 1: have officials I'd said on that? Well, this is really 218 00:11:48,840 --> 00:11:51,360 Speaker 1: the big question that we're all trying to figure out, 219 00:11:51,400 --> 00:11:53,680 Speaker 1: So how authentic are they and in what ways were 220 00:11:53,720 --> 00:11:57,839 Speaker 1: these documents potentially manipulated. You had John Bolton on saying, 221 00:11:57,840 --> 00:12:01,280 Speaker 1: you know, this could have been a counter intelligence operation itself, 222 00:12:01,600 --> 00:12:04,320 Speaker 1: and you know, so there is a big question about 223 00:12:04,400 --> 00:12:08,240 Speaker 1: how authentic these documents are and what the reason was 224 00:12:08,320 --> 00:12:10,720 Speaker 1: for their leak. So if this is someone on the 225 00:12:10,760 --> 00:12:13,600 Speaker 1: inside saying this has to get out to expose what's 226 00:12:13,640 --> 00:12:16,040 Speaker 1: really going on behind the scenes, well that's one thing, 227 00:12:16,080 --> 00:12:19,439 Speaker 1: sort of an Edward Snowden Chelsea Manning type of situation. 228 00:12:19,559 --> 00:12:22,400 Speaker 1: Or if this is Russia that got those documents and 229 00:12:22,440 --> 00:12:25,720 Speaker 1: then manipulated some of the numbers in there to create 230 00:12:25,760 --> 00:12:28,000 Speaker 1: a false impression, you know, I mean this is again 231 00:12:28,040 --> 00:12:31,080 Speaker 1: that hall of mirrors at John Bolton referenced Nick. So, actually, 232 00:12:31,320 --> 00:12:36,400 Speaker 1: when we're sitting here as technology consumers of information, is 233 00:12:36,440 --> 00:12:40,280 Speaker 1: this a cyber threatened hack or actually is when will 234 00:12:40,320 --> 00:12:42,360 Speaker 1: we understand whether this is something that the US could 235 00:12:42,360 --> 00:12:46,480 Speaker 1: have protected. Well, it's a great question because it's it's 236 00:12:46,520 --> 00:12:49,719 Speaker 1: going to again run us up against what US officials 237 00:12:50,120 --> 00:12:53,200 Speaker 1: tell us and what the truth may actually be. So 238 00:12:53,280 --> 00:12:55,920 Speaker 1: we know there is an investigation going on right now. 239 00:12:56,559 --> 00:12:59,240 Speaker 1: The big question will be Okay, it was this a leak? 240 00:12:59,480 --> 00:13:01,440 Speaker 1: Was this some on the inside who got this? Else? 241 00:13:01,679 --> 00:13:05,320 Speaker 1: Was this a hack? Was this some sort of counterintelligence operation? 242 00:13:05,600 --> 00:13:08,560 Speaker 1: There's so much we don't know, and so much likely 243 00:13:08,600 --> 00:13:11,520 Speaker 1: they're not going to tell us because to tell us 244 00:13:11,600 --> 00:13:14,600 Speaker 1: what exactly happened here is in turn going to expose 245 00:13:15,000 --> 00:13:17,840 Speaker 1: US sources and methods. So we're still trying to sift 246 00:13:17,840 --> 00:13:21,040 Speaker 1: through all of that stuff. My suspicion is, given the 247 00:13:21,080 --> 00:13:23,320 Speaker 1: gravity of this and what US officials have been willing 248 00:13:23,320 --> 00:13:25,600 Speaker 1: to say about how grave this leak is, that it 249 00:13:25,760 --> 00:13:27,600 Speaker 1: was in fact a leak or a hack and not 250 00:13:28,240 --> 00:13:32,520 Speaker 1: some sort of influence operation. All right, our thanks to 251 00:13:32,559 --> 00:13:36,200 Speaker 1: Bloomberg Nick quadens out of DC on Bloomberg Technology here 252 00:13:36,480 --> 00:13:39,200 Speaker 1: now Over in the UK, m I five, which is 253 00:13:39,240 --> 00:13:43,640 Speaker 1: Britain's domestic intelligence service, is appointing its first female head 254 00:13:43,800 --> 00:13:48,760 Speaker 1: of its cyber spying agency GCHQ. Ankist Butler, the current 255 00:13:48,840 --> 00:13:51,840 Speaker 1: Deputy Director General, will take up her new posts in May. 256 00:13:52,080 --> 00:13:54,800 Speaker 1: The change in leadership comes at a pretty sensitive time 257 00:13:54,880 --> 00:13:57,000 Speaker 1: is the US and its allies, as we've just discussed, 258 00:13:57,240 --> 00:14:00,120 Speaker 1: continue to deal with the fallout of the series of 259 00:14:00,160 --> 00:14:04,000 Speaker 1: intelligence leaks have emerged online in recent days. She will 260 00:14:04,040 --> 00:14:06,920 Speaker 1: replace the outgoing director Sir Jeremy Fleming, who's held that 261 00:14:07,000 --> 00:14:10,439 Speaker 1: position for the last six years. Caroline, stick with Cybersecurity 262 00:14:10,480 --> 00:14:12,439 Speaker 1: for a moment, because we're going to look at shares 263 00:14:12,480 --> 00:14:15,880 Speaker 1: of Acami right now after being upgraded by Papisanla to overweight, 264 00:14:16,200 --> 00:14:17,719 Speaker 1: managing to tick up two and a half percent. The 265 00:14:17,720 --> 00:14:20,280 Speaker 1: analyst sighting and recent Paul black and shares the offering 266 00:14:20,280 --> 00:14:22,400 Speaker 1: an opportunity to get into the stock as the company 267 00:14:22,480 --> 00:14:25,160 Speaker 1: is likely to refocus its profit strategy and speaking to 268 00:14:25,200 --> 00:14:28,840 Speaker 1: some analyst calls, look at NASDAK the company Nazdac Inc. 269 00:14:29,080 --> 00:14:31,680 Speaker 1: The shares of you know, the stock exchange operator is 270 00:14:31,680 --> 00:14:34,480 Speaker 1: downgraded to equal weight from overweight over Morgan Stanley. The 271 00:14:34,480 --> 00:14:38,440 Speaker 1: analyst sees risks to growth for the outlook of Nasdac Solutions. 272 00:14:38,520 --> 00:14:40,720 Speaker 1: It's the business that makes up actually seventy percent of 273 00:14:40,760 --> 00:14:44,600 Speaker 1: the company's revenue. Nevertheless, trading flat on the day coming up, 274 00:14:45,200 --> 00:14:48,200 Speaker 1: and we'll wonder how banks stack up when it comes 275 00:14:48,240 --> 00:14:51,320 Speaker 1: to well how they use artificial intelligence. We'll speak with 276 00:14:51,400 --> 00:14:56,080 Speaker 1: Evidence CEO about all the firm's recent report analyzing AI 277 00:14:56,200 --> 00:14:58,760 Speaker 1: in financial services. Even got a shout out from the 278 00:14:58,800 --> 00:15:21,680 Speaker 1: one I know need, Jamie Diamond it's bring back. This 279 00:15:21,800 --> 00:15:25,880 Speaker 1: is a incredibly disruptive new technology. I think we're seeing 280 00:15:25,920 --> 00:15:29,840 Speaker 1: opportunity and potential platform shift that we haven't seen in 281 00:15:29,840 --> 00:15:33,200 Speaker 1: a long time. Regulation can put us where we need 282 00:15:33,240 --> 00:15:35,920 Speaker 1: to be if we have the strength to put it 283 00:15:35,960 --> 00:15:38,640 Speaker 1: in place. I do think it's just impossible to regulate. 284 00:15:38,680 --> 00:15:43,600 Speaker 1: All the leading AI lebs know they're creating something dangerous, 285 00:15:43,720 --> 00:15:45,680 Speaker 1: but none of them really want to stop it. The 286 00:15:45,800 --> 00:15:48,840 Speaker 1: way that Chinese companies go about the AI space is different. 287 00:15:48,880 --> 00:15:52,760 Speaker 1: They just don't have the same approach toward the morality 288 00:15:52,800 --> 00:15:55,120 Speaker 1: around these technologies that we do in the US. The 289 00:15:55,160 --> 00:15:58,120 Speaker 1: impact on jobs is real, but it doesn't have a 290 00:15:58,200 --> 00:16:01,040 Speaker 1: super intelligence that will have mine of its own. It's 291 00:16:01,080 --> 00:16:03,840 Speaker 1: on all of us and particularly investors to think about 292 00:16:03,880 --> 00:16:07,520 Speaker 1: the questions and the potential falls, you know, as well 293 00:16:07,560 --> 00:16:11,520 Speaker 1: as of the opportunity and value it creates. The debates 294 00:16:11,520 --> 00:16:14,040 Speaker 1: are still clear our previous guests. They're weighing in on 295 00:16:14,080 --> 00:16:16,000 Speaker 1: what are the risks, what are the opportunities that come 296 00:16:16,000 --> 00:16:19,680 Speaker 1: when using particularly generative AI in various sectors? How will 297 00:16:19,720 --> 00:16:22,840 Speaker 1: AI we shape the competitive landscape? In particular? Go focus 298 00:16:22,880 --> 00:16:25,640 Speaker 1: in on banking right now is to help answer that question. 299 00:16:25,720 --> 00:16:28,120 Speaker 1: Alexandra musa is Ada. She is a CEO and co 300 00:16:28,200 --> 00:16:32,640 Speaker 1: founder of Evidence, which tracks AI integration in financial services. Alexandra, 301 00:16:32,840 --> 00:16:34,640 Speaker 1: you've got a bit of a shout out and JP 302 00:16:34,680 --> 00:16:38,600 Speaker 1: Morgan's annual letter Jamie Diamonds in particular, what is it 303 00:16:38,680 --> 00:16:41,560 Speaker 1: that you're doing? How are you measuring what AI is 304 00:16:41,680 --> 00:16:45,400 Speaker 1: being adopted by banks? So we are published about eight 305 00:16:45,440 --> 00:16:49,160 Speaker 1: weeks ago the first public benchmark on AI adoption for 306 00:16:49,280 --> 00:16:52,280 Speaker 1: banks and what we do it has not been done 307 00:16:52,320 --> 00:16:56,440 Speaker 1: before in terms of taking outside in view by holding 308 00:16:56,440 --> 00:16:59,640 Speaker 1: a mirror up to the banks and looking at the 309 00:16:59,760 --> 00:17:03,840 Speaker 1: AI capabilities. So what we do is that we go 310 00:17:03,880 --> 00:17:07,560 Speaker 1: and we measure the banks on the strength of their 311 00:17:07,560 --> 00:17:11,840 Speaker 1: AI ecosystem and then we rank them according to the 312 00:17:11,920 --> 00:17:15,240 Speaker 1: scores that they get against their strengths of this ecosystem, 313 00:17:15,280 --> 00:17:19,920 Speaker 1: which we break down into four areas talent, innovation, leadership, 314 00:17:19,920 --> 00:17:24,159 Speaker 1: and responsible AI. Okay, so talent bringing on the right 315 00:17:24,200 --> 00:17:25,879 Speaker 1: people the right parts of the banks you need to 316 00:17:25,880 --> 00:17:29,840 Speaker 1: build up. What about responsible AI? What are banks doing 317 00:17:29,840 --> 00:17:32,720 Speaker 1: about that at the moment? Yeah, it is, I mean 318 00:17:32,800 --> 00:17:36,639 Speaker 1: on the on the talent and the leadership and innovation side, 319 00:17:36,640 --> 00:17:38,600 Speaker 1: that's sort of really in the engine room. You know, 320 00:17:38,600 --> 00:17:42,920 Speaker 1: have you got the right talent AI? You know dev 321 00:17:43,119 --> 00:17:46,320 Speaker 1: ops and mL ops, and you look at implementation talent 322 00:17:46,400 --> 00:17:50,080 Speaker 1: and so on and on. The innovation is whether you're 323 00:17:50,080 --> 00:17:52,880 Speaker 1: sort of following a build or buy approach, whether you're 324 00:17:53,040 --> 00:17:56,879 Speaker 1: looking at research and patents or what sort of partnerships 325 00:17:56,920 --> 00:18:01,080 Speaker 1: you have, also what you're investing in or acquiring. But 326 00:18:01,240 --> 00:18:04,120 Speaker 1: on the doing all that is great way looking at 327 00:18:04,119 --> 00:18:06,960 Speaker 1: the raw horsepower, but doing it in a responsible manner 328 00:18:07,040 --> 00:18:11,200 Speaker 1: is really critical, and especially now given the release of 329 00:18:11,280 --> 00:18:13,920 Speaker 1: chat GPT and a lot of banks and a lot 330 00:18:13,960 --> 00:18:16,479 Speaker 1: of other sectors too, but banks looking at how to 331 00:18:16,520 --> 00:18:22,200 Speaker 1: incorporate large language models. The responsible aid is really important 332 00:18:22,240 --> 00:18:27,560 Speaker 1: in terms of making sure that your clients customers are 333 00:18:27,720 --> 00:18:30,520 Speaker 1: comfortable with the handling of all of this data and 334 00:18:30,640 --> 00:18:33,679 Speaker 1: with the use of AI tools on that data. And 335 00:18:33,720 --> 00:18:37,960 Speaker 1: it's really important to show that you're following frameworks of 336 00:18:38,080 --> 00:18:41,679 Speaker 1: responsible and ethical AI as you use it. Yeah, alexandre 337 00:18:41,840 --> 00:18:44,600 Speaker 1: I appreciate the depth of the methodology. You know. In 338 00:18:44,640 --> 00:18:47,240 Speaker 1: recent weeks, Caroline and I have name checked a number 339 00:18:47,280 --> 00:18:50,120 Speaker 1: of banking ceo is. Brian moynihan first week of March 340 00:18:50,240 --> 00:18:53,200 Speaker 1: was talking about how they're dabbling. There's work to do 341 00:18:53,640 --> 00:18:57,359 Speaker 1: when it comes to modernizing banking technology with regards to AI. So, 342 00:18:57,440 --> 00:18:59,960 Speaker 1: who are the winners and losers on your index? Who's 343 00:19:00,040 --> 00:19:03,640 Speaker 1: scores highly, who scores poorly? Yeah, well we have as 344 00:19:03,720 --> 00:19:06,880 Speaker 1: you know, we have JP Morgan top the index, came 345 00:19:06,920 --> 00:19:11,280 Speaker 1: out number one in the index. Interestingly, a raw bank 346 00:19:11,320 --> 00:19:16,840 Speaker 1: of Canada came second, a smaller bank, but predominantly we're 347 00:19:16,880 --> 00:19:20,199 Speaker 1: seeing the North American banks in the top ten, with 348 00:19:20,320 --> 00:19:25,399 Speaker 1: the European banks lagging somewhat and the UK banks lagging 349 00:19:25,440 --> 00:19:29,040 Speaker 1: the European banks. That brings me my next question, which 350 00:19:29,160 --> 00:19:32,240 Speaker 1: is we learned in the aftermath of Silicon Valley Bank 351 00:19:33,240 --> 00:19:36,879 Speaker 1: or relearned how global the banking industry is. How close 352 00:19:37,040 --> 00:19:40,320 Speaker 1: is the coordination that you see between different geographies and 353 00:19:40,359 --> 00:19:43,879 Speaker 1: regions in the banking system on how to implement AI 354 00:19:43,960 --> 00:19:48,560 Speaker 1: across borders. Well, there's there's no real coordination between the 355 00:19:48,640 --> 00:19:52,199 Speaker 1: banks across. The way that implementation is happening in the 356 00:19:52,240 --> 00:19:55,359 Speaker 1: European banks is quite different from the way that is 357 00:19:55,400 --> 00:19:59,520 Speaker 1: being done in the northern North American banks. The North 358 00:19:59,560 --> 00:20:03,760 Speaker 1: American banks take an approach much more looking at how 359 00:20:03,800 --> 00:20:06,400 Speaker 1: big tech is organized, so having R and D centers 360 00:20:06,600 --> 00:20:11,240 Speaker 1: and being much using AI across the banks, whereas the 361 00:20:11,320 --> 00:20:14,760 Speaker 1: European banks take more of an engineering approach where they're 362 00:20:14,800 --> 00:20:20,640 Speaker 1: going in silos and implementing AIM more in a siloed approach. 363 00:20:21,119 --> 00:20:24,000 Speaker 1: So you do see differences in the approaches that the 364 00:20:24,040 --> 00:20:27,520 Speaker 1: banks are taking whether you be in Europe or North 365 00:20:27,560 --> 00:20:30,119 Speaker 1: America and Amaxandra, does any of that come down to 366 00:20:30,359 --> 00:20:36,720 Speaker 1: how governments or cross institutional viewpoints are of how to 367 00:20:36,800 --> 00:20:40,080 Speaker 1: regulate how to ethically build AI, because many would say, actually, 368 00:20:40,080 --> 00:20:42,359 Speaker 1: when you think of the regulation being developed around it, 369 00:20:42,440 --> 00:20:45,119 Speaker 1: actually Asia or indeed Europe really leaves the pack in 370 00:20:45,160 --> 00:20:50,159 Speaker 1: this way. Yes, I mean the interesting aspect here is 371 00:20:50,160 --> 00:20:54,360 Speaker 1: actually that the North American Canadian banks were very visible 372 00:20:54,880 --> 00:21:00,080 Speaker 1: around the guard rails that they're putting in place. And 373 00:21:00,080 --> 00:21:02,360 Speaker 1: now we have to remember that banks are heavily regulated 374 00:21:02,400 --> 00:21:05,000 Speaker 1: to begin with, so a lot of this is happening internally. 375 00:21:05,480 --> 00:21:10,080 Speaker 1: What we're capturing is what is expressed externally in terms 376 00:21:10,280 --> 00:21:15,159 Speaker 1: of you know, principles around explainability responsible AI in general 377 00:21:15,600 --> 00:21:18,240 Speaker 1: and the people they're putting in place and the lines 378 00:21:18,240 --> 00:21:21,760 Speaker 1: of defense across the banks that they're visible about. In Europe, 379 00:21:21,760 --> 00:21:25,520 Speaker 1: you've got GDPR regulation right, and so there's a different 380 00:21:25,600 --> 00:21:28,280 Speaker 1: that sits slightly differently in the banks, and they're expressing 381 00:21:28,680 --> 00:21:30,720 Speaker 1: the guard rails that they're putting around it in slightly 382 00:21:30,760 --> 00:21:35,840 Speaker 1: different ways. But you could say that there are advanced 383 00:21:35,840 --> 00:21:38,280 Speaker 1: thinking at the European level with the AI Act in 384 00:21:38,720 --> 00:21:44,040 Speaker 1: motion right now, but because of the GDPR regulation in place, 385 00:21:44,480 --> 00:21:46,879 Speaker 1: there is there's a lot of thinking that has been 386 00:21:46,880 --> 00:21:49,360 Speaker 1: done in the European banking system. Great house and time 387 00:21:49,400 --> 00:21:52,320 Speaker 1: with you. We thank you, Alexandra, Thank you a CEO 388 00:21:52,400 --> 00:22:03,439 Speaker 1: and co founder of Evidence. Welcome actively Meg Technology. I'm 389 00:22:03,480 --> 00:22:06,720 Speaker 1: Karain Hide in New York, loved in San Francisco. It's 390 00:22:06,760 --> 00:22:08,880 Speaker 1: just quickly checking on these markets because we had seen 391 00:22:09,200 --> 00:22:11,840 Speaker 1: broadly technology stocks in the US under pressure. We still 392 00:22:11,840 --> 00:22:13,720 Speaker 1: remain as that one hundred of the big benchmark that 393 00:22:13,720 --> 00:22:16,080 Speaker 1: remembers up about ninety percent so far this year, down 394 00:22:16,320 --> 00:22:19,000 Speaker 1: half percent six out of seven days trading. That is 395 00:22:19,040 --> 00:22:21,160 Speaker 1: on the lower side the Fang index. This is about 396 00:22:21,240 --> 00:22:24,160 Speaker 1: big tech getting sold off today, the Microsoft, the alphabets 397 00:22:24,240 --> 00:22:26,400 Speaker 1: we see across the board just under pressures. Who worry 398 00:22:26,440 --> 00:22:30,159 Speaker 1: about that CPI, that inflation print tomorrow? Bitcoin though, shogging 399 00:22:30,200 --> 00:22:32,560 Speaker 1: off any of the risk asset concerns. Another three percent 400 00:22:32,600 --> 00:22:35,840 Speaker 1: as we hit some key technical levels thirty thousand swift 401 00:22:35,840 --> 00:22:39,080 Speaker 1: shot on let's go micro for a moment, individual movers. 402 00:22:39,359 --> 00:22:42,720 Speaker 1: Microsoft getting a bit of a analyst concern coming from 403 00:22:42,800 --> 00:22:44,760 Speaker 1: UBS saying that maybe Azure is going to be more 404 00:22:44,800 --> 00:22:47,800 Speaker 1: under pressure amid these economic headwinds that we see. And 405 00:22:47,840 --> 00:22:49,919 Speaker 1: actually you see a lot of these cloud companies on 406 00:22:49,960 --> 00:22:53,160 Speaker 1: the downside today, Snowflake and Data Dog Ali Baba off 407 00:22:53,160 --> 00:22:55,720 Speaker 1: by one point four percent. Keep a close eye eye 408 00:22:55,720 --> 00:22:58,320 Speaker 1: on Barba because plenty of news to come out overnight 409 00:22:58,400 --> 00:23:01,040 Speaker 1: in terms of its own AI cheap Jack GBT like 410 00:23:01,240 --> 00:23:03,359 Speaker 1: service being integrated across this products. We're more on that 411 00:23:03,400 --> 00:23:06,399 Speaker 1: in a moment. Virgin Orbit. Look, I mean at Penny 412 00:23:06,840 --> 00:23:09,320 Speaker 1: stock now thirty one percent lower as it filed for 413 00:23:09,359 --> 00:23:11,199 Speaker 1: bankruptcy and the NASDAK says, look, they're going to have 414 00:23:11,200 --> 00:23:15,679 Speaker 1: to delist this stockhead Yeah, big driver in that market 415 00:23:15,720 --> 00:23:18,840 Speaker 1: being AI as well, and the race in AI continues 416 00:23:18,880 --> 00:23:21,960 Speaker 1: to heat up. Alphabet doubling down on its own generative 417 00:23:21,960 --> 00:23:25,280 Speaker 1: AI ambitions, but this time by investing in the startup 418 00:23:25,320 --> 00:23:28,560 Speaker 1: World Capital g which is Alphabet's venture ARM announced a 419 00:23:28,600 --> 00:23:31,240 Speaker 1: one hundred million dollar funding round that it led into 420 00:23:31,280 --> 00:23:34,480 Speaker 1: B to B research platform Alpha Sense that brings Alpha 421 00:23:34,560 --> 00:23:37,720 Speaker 1: Senses valuation to one point eight billion dollars in the 422 00:23:37,720 --> 00:23:42,160 Speaker 1: company's CEO co founder Jack Coco joins us. Now, Jack, 423 00:23:42,240 --> 00:23:44,639 Speaker 1: this is interesting. It's an extension of around you did 424 00:23:44,760 --> 00:23:50,560 Speaker 1: last summer. Why why did you need these additional funds? Well, 425 00:23:51,520 --> 00:23:55,399 Speaker 1: great question and thanks for having me. We weren't actually 426 00:23:55,400 --> 00:23:58,359 Speaker 1: looking for financing, but we had been talking to Capitology 427 00:23:58,440 --> 00:24:02,040 Speaker 1: for sir role URIs would certainly viewed them as an 428 00:24:02,040 --> 00:24:06,760 Speaker 1: amazing potential investor for us, and we just had a 429 00:24:06,920 --> 00:24:11,280 Speaker 1: catch up conversation a few months ago and that led 430 00:24:11,320 --> 00:24:13,960 Speaker 1: to a quick meeting of the minds. And while we 431 00:24:14,040 --> 00:24:16,560 Speaker 1: didn't need the capital, we were looking for the capital. 432 00:24:17,200 --> 00:24:20,200 Speaker 1: It was such an opportunity we didn't want to pass 433 00:24:20,200 --> 00:24:24,640 Speaker 1: it up. Caroline, I find this incredibly interesting in this environment, 434 00:24:24,760 --> 00:24:29,400 Speaker 1: essentially a flat round interesting some of the other investors, 435 00:24:29,400 --> 00:24:32,639 Speaker 1: including Goldman Sexes asset management unit. Yeah, and I think 436 00:24:33,040 --> 00:24:35,080 Speaker 1: a lot of this comes around a market that is 437 00:24:35,200 --> 00:24:38,960 Speaker 1: deeply energized by all things AI, generative AI, in particular, 438 00:24:39,520 --> 00:24:42,840 Speaker 1: what is Alpha cens actually doing? What are you currently providing? 439 00:24:43,600 --> 00:24:47,600 Speaker 1: So our platform is really a market intelligence and search 440 00:24:47,800 --> 00:24:51,280 Speaker 1: by a form for enterprise customers. It's basically helping this 441 00:24:51,480 --> 00:24:56,080 Speaker 1: big company's financial firms and corporations find the right data 442 00:24:56,119 --> 00:24:58,600 Speaker 1: points and insights to make the big decisions that really 443 00:24:58,640 --> 00:25:01,320 Speaker 1: matter in the businesses. When if you think about it, 444 00:25:01,720 --> 00:25:05,600 Speaker 1: for every company that enter enterprise value is a cumulative 445 00:25:05,600 --> 00:25:07,960 Speaker 1: sumwhere the decisions that they make, and we help them 446 00:25:08,000 --> 00:25:10,520 Speaker 1: make every one of those better by having the right 447 00:25:10,600 --> 00:25:14,840 Speaker 1: access to data points and insights so they can make 448 00:25:14,920 --> 00:25:17,840 Speaker 1: a little bit better decisions more quickly and confidently. And 449 00:25:17,960 --> 00:25:20,320 Speaker 1: this was just really hard to do before people were 450 00:25:20,440 --> 00:25:22,760 Speaker 1: control f searching and still are today out there in 451 00:25:22,840 --> 00:25:26,200 Speaker 1: the market pdf documents or searching on the web for 452 00:25:26,560 --> 00:25:30,640 Speaker 1: critical business insights that drive million dollars sometimes billion dollar decisions. 453 00:25:31,200 --> 00:25:34,560 Speaker 1: So really, what we're bringing to them is thousands of 454 00:25:34,720 --> 00:25:37,720 Speaker 1: high value sources in one place where you can search 455 00:25:37,760 --> 00:25:40,159 Speaker 1: across them really powerfully and find the insights that you 456 00:25:40,160 --> 00:25:43,399 Speaker 1: can rely on. And you know, that's that's we've found 457 00:25:43,680 --> 00:25:45,800 Speaker 1: to be really a solution that resonates in the market. 458 00:25:45,840 --> 00:25:49,040 Speaker 1: More than half of the Fortune five hundred companies are 459 00:25:49,160 --> 00:25:54,240 Speaker 1: today using this, so yeah, you know that's Google using it, Merkshell, 460 00:25:54,359 --> 00:25:57,800 Speaker 1: Bank of America, raytheon. There is a lot of debate 461 00:25:57,800 --> 00:26:00,360 Speaker 1: though when you're thinking about the data trove that you're 462 00:26:00,440 --> 00:26:02,680 Speaker 1: using to bring this sort of analysis and to speed 463 00:26:02,760 --> 00:26:05,920 Speaker 1: up hip one's productivity. Is how reliable can the data 464 00:26:06,000 --> 00:26:09,320 Speaker 1: be and how is it ethically being used? How much 465 00:26:09,320 --> 00:26:11,440 Speaker 1: are you feeding into that sort of conversation right now, 466 00:26:11,520 --> 00:26:16,080 Speaker 1: there's a really really important conversation. It's um. You know, 467 00:26:16,080 --> 00:26:19,879 Speaker 1: in our case, we've always built our platform in a 468 00:26:19,920 --> 00:26:24,240 Speaker 1: way that the we're sourcing information from really truly high 469 00:26:24,320 --> 00:26:29,200 Speaker 1: value content from equity research companies, own disclosures, news media 470 00:26:29,320 --> 00:26:32,880 Speaker 1: and expert interviews of people in the trenches in business, 471 00:26:33,720 --> 00:26:38,160 Speaker 1: sharing insights with investment analysts on costs that we transcribe. 472 00:26:38,160 --> 00:26:41,360 Speaker 1: So it's it's really higher value business information. So grounding 473 00:26:42,040 --> 00:26:45,760 Speaker 1: the information that our search engine finds in those high 474 00:26:45,840 --> 00:26:49,639 Speaker 1: value sources is really important, and then we're able to 475 00:26:49,680 --> 00:26:56,800 Speaker 1: deliver really the the value back to the content providers. 476 00:26:57,160 --> 00:27:00,440 Speaker 1: When somebody's content is being used more, they also get 477 00:27:00,440 --> 00:27:03,440 Speaker 1: paid more as a content provider. So it's really important 478 00:27:03,480 --> 00:27:07,960 Speaker 1: debate around whether that's happening appropriately with large language models. 479 00:27:08,240 --> 00:27:12,359 Speaker 1: As we add language model capabilities on top off this 480 00:27:12,760 --> 00:27:14,720 Speaker 1: high valul content, we kind of built a system in 481 00:27:14,760 --> 00:27:16,880 Speaker 1: a way that content owner is actually good paid as 482 00:27:16,880 --> 00:27:20,040 Speaker 1: they should, and it really feels that this debate will 483 00:27:20,119 --> 00:27:21,960 Speaker 1: run and run. But I like the way in which 484 00:27:21,960 --> 00:27:24,080 Speaker 1: we're starting to really try and see the application. We 485 00:27:24,200 --> 00:27:26,840 Speaker 1: keep questioning what layer of AI is going to be 486 00:27:26,880 --> 00:27:29,560 Speaker 1: the most valuable? Is it or the infrastructure that sort 487 00:27:29,560 --> 00:27:31,600 Speaker 1: of Jack is building. Is it The companies that own 488 00:27:31,720 --> 00:27:34,760 Speaker 1: some of the data troths as well. And as Jack 489 00:27:34,800 --> 00:27:37,000 Speaker 1: would point out, you know, the inputs for the large 490 00:27:37,080 --> 00:27:39,840 Speaker 1: language model, the data set you're relying on is important. 491 00:27:40,240 --> 00:27:42,800 Speaker 1: It leads me to Alphabet. Jack and Google. You know, 492 00:27:42,880 --> 00:27:45,840 Speaker 1: Capital G would kind of point out they run independently 493 00:27:45,880 --> 00:27:48,720 Speaker 1: as the growth venture arm. But I wonder how close 494 00:27:48,800 --> 00:27:52,600 Speaker 1: this does bring you to Alphabet into Google, What partnerships 495 00:27:52,680 --> 00:27:56,719 Speaker 1: you can explore, what advantage from access to data that 496 00:27:56,800 --> 00:27:59,840 Speaker 1: might give you as you work on your own product. Well, 497 00:28:00,080 --> 00:28:02,240 Speaker 1: certainly a big part of the motivation of partnering with 498 00:28:02,320 --> 00:28:06,359 Speaker 1: Capital G is the opportunity partner with the broader Alphabet umbrella. 499 00:28:06,520 --> 00:28:10,399 Speaker 1: They have a really large portion of the world's AI 500 00:28:10,480 --> 00:28:14,320 Speaker 1: scientists and developers working for the business, and this certainly 501 00:28:14,320 --> 00:28:17,719 Speaker 1: does give us opportunities to partner with them, have conversations 502 00:28:17,720 --> 00:28:21,080 Speaker 1: with them, and also have conversations with people where we 503 00:28:21,160 --> 00:28:24,800 Speaker 1: can just advance our business and go to market. So 504 00:28:25,680 --> 00:28:27,800 Speaker 1: that was certainly a big part of the motivation of 505 00:28:28,080 --> 00:28:31,080 Speaker 1: inviting them in as an investor. At a moment where 506 00:28:31,200 --> 00:28:35,000 Speaker 1: we were looking for the capital, Jack, many might then think, oh, 507 00:28:35,040 --> 00:28:38,640 Speaker 1: there might be a quite useful owner. What is your view, 508 00:28:38,760 --> 00:28:40,960 Speaker 1: your direction to travel for the business? You want to 509 00:28:41,000 --> 00:28:47,000 Speaker 1: remain independent on IPO. We really see this as a 510 00:28:47,120 --> 00:28:52,040 Speaker 1: huge market opportunity and we're building this with the timescale 511 00:28:52,040 --> 00:28:56,200 Speaker 1: of the next ten years, twenty years and to gain 512 00:28:56,280 --> 00:28:59,080 Speaker 1: the resources to really build the kind of company that 513 00:28:59,160 --> 00:29:02,720 Speaker 1: we're building. We see IPO as an inevitable step along 514 00:29:02,760 --> 00:29:05,400 Speaker 1: the way. So that's the path that we're on. I'm 515 00:29:05,400 --> 00:29:07,680 Speaker 1: sure the hundred million satisfies you for the time may 516 00:29:07,720 --> 00:29:09,520 Speaker 1: make Jack's great to have some time with you, Jack 517 00:29:09,600 --> 00:29:12,720 Speaker 1: coco In, CEO of Alpha sense there and you've got 518 00:29:12,720 --> 00:29:16,520 Speaker 1: some more techniws. Yeah, time now for talking tech. Billionaire 519 00:29:16,520 --> 00:29:19,480 Speaker 1: twins Tyler and Camera winkle Voss made a one hundred 520 00:29:19,480 --> 00:29:22,800 Speaker 1: million dollar loan to support their crypto exchange Gemini. This 521 00:29:22,920 --> 00:29:26,160 Speaker 1: comes after Gemini had sought funding from outside investors in 522 00:29:26,200 --> 00:29:29,680 Speaker 1: recent months but didn't come to any agreement that According 523 00:29:29,720 --> 00:29:33,320 Speaker 1: to sources, Elizabeth Holmes has to report to prison as 524 00:29:33,360 --> 00:29:37,240 Speaker 1: scheduled later this month after a judge rejected her request 525 00:29:37,320 --> 00:29:41,200 Speaker 1: to remain free on bail as she appeals a fraud conviction. 526 00:29:41,240 --> 00:29:45,360 Speaker 1: And finally, Twitter has stopped being an independent company after 527 00:29:45,480 --> 00:29:49,040 Speaker 1: merging with the newly formed shell firm called X Corp. 528 00:29:49,160 --> 00:29:52,120 Speaker 1: It's unclear what the change means for Twitter, though Elon 529 00:29:52,240 --> 00:29:55,000 Speaker 1: Musk has in the past suggested that Twitter could lead 530 00:29:55,040 --> 00:29:58,880 Speaker 1: to X, which he dubbed as an everything app. Caroline, 531 00:29:59,160 --> 00:30:01,840 Speaker 1: let's ta Coelo, Well, let's stick on things he owns, 532 00:30:01,880 --> 00:30:04,120 Speaker 1: because for a moment, we also want to think about 533 00:30:04,160 --> 00:30:07,280 Speaker 1: where he's taking his other company, Tesla. In fact, we 534 00:30:07,360 --> 00:30:10,040 Speaker 1: saw shares of Tesla sort of in an interesting move today. 535 00:30:10,080 --> 00:30:11,800 Speaker 1: We're up about a percentage point coming off of those 536 00:30:11,880 --> 00:30:15,280 Speaker 1: highs and new proposal. We understand. Federal class action sued 537 00:30:15,440 --> 00:30:19,240 Speaker 1: against the company says Tesla employees viewed and shared videos 538 00:30:19,240 --> 00:30:22,240 Speaker 1: and images of car owners in violation with its privacy 539 00:30:22,400 --> 00:30:25,719 Speaker 1: promises and of California state laws and the state constitution. 540 00:30:25,760 --> 00:30:28,520 Speaker 1: Tesla has not responded immediately to request the comment. But 541 00:30:28,560 --> 00:30:29,960 Speaker 1: we are coming off of those highs that we've got 542 00:30:30,000 --> 00:30:32,640 Speaker 1: a little bit earlier coming up let's talk about investing 543 00:30:32,720 --> 00:30:35,320 Speaker 1: even more in cybersecurity. What a hot topic on the day, 544 00:30:35,320 --> 00:30:37,400 Speaker 1: and what kind of new risks are there to be 545 00:30:37,400 --> 00:30:40,080 Speaker 1: considered at the moment, particularly with the raise and rise 546 00:30:40,120 --> 00:30:42,880 Speaker 1: and rise of AI. More on that with Ballistic Ventures, 547 00:30:43,200 --> 00:30:57,240 Speaker 1: Go mac Meftter, that's next. This is blue. Let's continued 548 00:30:57,280 --> 00:31:00,120 Speaker 1: to talk about cybersecurity, the space of course booming the 549 00:31:00,200 --> 00:31:02,640 Speaker 1: last few years. Just think about the focus that we 550 00:31:02,680 --> 00:31:05,200 Speaker 1: had during the pandemic. Just think about today's newsflow as 551 00:31:05,240 --> 00:31:07,720 Speaker 1: we worry that maybe the lead documents that pose a 552 00:31:07,760 --> 00:31:10,520 Speaker 1: serious national security threat to the United States according to 553 00:31:10,560 --> 00:31:13,280 Speaker 1: the Pentagon, is that in some way related to a 554 00:31:13,400 --> 00:31:16,400 Speaker 1: hack or cyber attack. Let's talk about way you can 555 00:31:16,520 --> 00:31:18,880 Speaker 1: invest as well. Is it the right time to be 556 00:31:18,960 --> 00:31:21,960 Speaker 1: investing in all these sorts of companies. So we can 557 00:31:21,960 --> 00:31:24,920 Speaker 1: turn to our next m a guest who perhaps has 558 00:31:24,920 --> 00:31:27,120 Speaker 1: a bit of skin in the game. Palmac Mefter is 559 00:31:27,160 --> 00:31:30,600 Speaker 1: with us insight on today's VC spotlight. He's co founder 560 00:31:30,640 --> 00:31:34,360 Speaker 1: general partner of at Ballistic Ventures. And but Mac, you 561 00:31:34,440 --> 00:31:37,960 Speaker 1: have a life dedication to cyber in particular working over 562 00:31:37,960 --> 00:31:40,479 Speaker 1: an eight and T for years. What now you're seeing 563 00:31:40,640 --> 00:31:43,600 Speaker 1: in smaller companies areas that you can invest in making 564 00:31:43,640 --> 00:31:46,880 Speaker 1: sure that the cyber threats can be defeated. Yeah, thank 565 00:31:46,920 --> 00:31:48,560 Speaker 1: you very much for having you guys. By the way, 566 00:31:49,240 --> 00:31:52,120 Speaker 1: let's see, one of the great things about cybersecurity that 567 00:31:52,160 --> 00:31:56,560 Speaker 1: we've enjoyed is it's very resilient to economic upturns and 568 00:31:56,760 --> 00:31:59,760 Speaker 1: down turns. So, in fact, if you take a look 569 00:31:59,800 --> 00:32:02,440 Speaker 1: at couple of the CIOs surveys that have come up, 570 00:32:02,480 --> 00:32:04,920 Speaker 1: cybers one of the areas that is actually increasing in 571 00:32:05,040 --> 00:32:09,640 Speaker 1: span during economic downturns because everybody's worried about risk. That's 572 00:32:09,720 --> 00:32:12,160 Speaker 1: kind of one thread which is which always makes cyber 573 00:32:12,280 --> 00:32:15,320 Speaker 1: very very exciting as an investment vehicle. The other thread 574 00:32:15,480 --> 00:32:19,360 Speaker 1: is these threats are ever evolving, so the adversaries don't 575 00:32:19,360 --> 00:32:22,720 Speaker 1: sit still. They're constantly inventing new threat vectors and as 576 00:32:22,760 --> 00:32:24,840 Speaker 1: a result, some of the old security controls have to 577 00:32:24,840 --> 00:32:27,720 Speaker 1: be reinvented on a constant basis. And of course with 578 00:32:27,760 --> 00:32:30,280 Speaker 1: the emerging new threats, there has to be new innovative 579 00:32:30,280 --> 00:32:33,480 Speaker 1: companies that are going to emerge to counteract those threats. So, 580 00:32:33,560 --> 00:32:37,400 Speaker 1: as a result, from a startup perspective, invention perspective is 581 00:32:37,400 --> 00:32:40,800 Speaker 1: a very interesting area to invest in. I would argue 582 00:32:40,800 --> 00:32:42,960 Speaker 1: with the current economic downturn. If you look at some 583 00:32:43,040 --> 00:32:45,800 Speaker 1: of the public equities today as well, and if you 584 00:32:45,840 --> 00:32:48,760 Speaker 1: took a look at some of the multiples of revenues 585 00:32:48,880 --> 00:32:52,239 Speaker 1: multiples of EVA, it'll make cyber very very exciting to 586 00:32:52,240 --> 00:32:56,280 Speaker 1: invest in. So you know, we like the sector quite 587 00:32:56,280 --> 00:32:59,040 Speaker 1: a bit. Of course, while MAC we're interested in where 588 00:32:59,080 --> 00:33:01,160 Speaker 1: the dulta is in the energy is coming from. When 589 00:33:01,160 --> 00:33:03,320 Speaker 1: I was at CS in January, which seems like a 590 00:33:03,360 --> 00:33:06,960 Speaker 1: lifetime ago now, Jen easily the directory of its CISA 591 00:33:07,040 --> 00:33:10,320 Speaker 1: basically made an appeal to Corporate America saying, do more 592 00:33:10,680 --> 00:33:15,000 Speaker 1: invest earlier in cybersecurity into great cybersecurity tools. At the 593 00:33:15,080 --> 00:33:17,720 Speaker 1: moment you design a new product or piece of software, 594 00:33:18,360 --> 00:33:19,800 Speaker 1: is that where the energy is coming from in the 595 00:33:19,840 --> 00:33:22,160 Speaker 1: form of your LPs. I'm just curious who's backing you 596 00:33:22,400 --> 00:33:25,760 Speaker 1: to make these investments. Yeah, absolutely so. I think one 597 00:33:25,760 --> 00:33:27,840 Speaker 1: of the things Jen pointed out your pointing out, which 598 00:33:27,880 --> 00:33:30,239 Speaker 1: is probably the most important thing in cybers cyber has 599 00:33:30,280 --> 00:33:33,720 Speaker 1: always been thought of as an afterthought. If you take 600 00:33:33,800 --> 00:33:36,760 Speaker 1: a look at the applications, for instance, applications are developed 601 00:33:36,800 --> 00:33:39,680 Speaker 1: without security in mind during the software development life cycle. 602 00:33:40,080 --> 00:33:42,400 Speaker 1: And we're seeing a shift happening, especially with the last 603 00:33:42,400 --> 00:33:45,640 Speaker 1: ten to fifteen years. There's an area course shift left 604 00:33:45,680 --> 00:33:49,280 Speaker 1: you probably have heard, which is equipping software developers so 605 00:33:49,320 --> 00:33:52,240 Speaker 1: they can build security into the fabric of the application 606 00:33:52,360 --> 00:33:54,880 Speaker 1: during the assembly process of the application. It's one of 607 00:33:54,880 --> 00:33:58,520 Speaker 1: the only areas that you can build a critical asset 608 00:33:58,880 --> 00:34:01,880 Speaker 1: and think of security as an afterthought. It's incredibly inefficient. 609 00:34:02,280 --> 00:34:07,600 Speaker 1: So to Jen's point, you know, software security, especially insecuting channel, 610 00:34:07,720 --> 00:34:10,319 Speaker 1: has to be thought of during the assembly process of 611 00:34:10,360 --> 00:34:13,960 Speaker 1: any artifact. It's certainly one theme or one area that 612 00:34:14,000 --> 00:34:17,319 Speaker 1: we see, there are many other themes that we're investing in. 613 00:34:18,080 --> 00:34:21,160 Speaker 1: When we look at our LP base, they kind of 614 00:34:21,160 --> 00:34:24,279 Speaker 1: share the same excitement and enthusiasm. You know, they've used 615 00:34:24,320 --> 00:34:28,000 Speaker 1: cybers very resilient to economic upturns and downturns. We're focused 616 00:34:28,000 --> 00:34:30,640 Speaker 1: in the early stages of investing, and I would argue 617 00:34:30,760 --> 00:34:33,920 Speaker 1: during economic downturn is a really good time to create 618 00:34:34,040 --> 00:34:37,879 Speaker 1: companies and hope you can catch the upturns cycle when 619 00:34:37,920 --> 00:34:40,480 Speaker 1: when the equity capital markets come back. And so the 620 00:34:40,640 --> 00:34:43,480 Speaker 1: LPs share that enthusiasm. They think the stage of our 621 00:34:43,520 --> 00:34:47,520 Speaker 1: investing is pretty exciting, right, It's pretty exciting. That's hey, 622 00:34:47,560 --> 00:34:51,560 Speaker 1: by mac, we're looking at your portfolio companies here. Concentrics 623 00:34:51,600 --> 00:34:56,200 Speaker 1: one name that jumps out. How is artificial intelligence impacting 624 00:34:56,239 --> 00:35:00,920 Speaker 1: how you invest? Yeah, definitely. So I would argue a 625 00:35:00,920 --> 00:35:05,880 Speaker 1: couple of areas. One, AI has made the business of 626 00:35:06,480 --> 00:35:09,680 Speaker 1: threat detection incident response a lot more automated. In the 627 00:35:09,719 --> 00:35:12,920 Speaker 1: case of Concentric, they focus on data security. So what 628 00:35:13,000 --> 00:35:15,960 Speaker 1: they go after is they look at unstructured data that 629 00:35:16,080 --> 00:35:19,120 Speaker 1: passes through your organization, either through your Slack Channels office 630 00:35:19,160 --> 00:35:24,000 Speaker 1: through sixty five confluent, and there's an inadvertent risk exposure 631 00:35:24,000 --> 00:35:28,719 Speaker 1: of that unstructured data to the outside world. Without artificial intelligence, 632 00:35:28,880 --> 00:35:33,480 Speaker 1: identifying that unstructured data and the risk exposure is almost impossible. 633 00:35:33,840 --> 00:35:38,480 Speaker 1: And so you can apply AI to areas of data accessing, governance, 634 00:35:38,560 --> 00:35:41,920 Speaker 1: You can apply AI to automating threat detection, incident response 635 00:35:42,320 --> 00:35:45,720 Speaker 1: and removing the scarce human capital resources that are available 636 00:35:45,760 --> 00:35:49,360 Speaker 1: so they can focus on higher important things. Having said that, 637 00:35:49,480 --> 00:35:52,280 Speaker 1: though you can't rely on AI to completely automate your business, 638 00:35:52,280 --> 00:35:56,319 Speaker 1: there's a lot of business context that into understanding, whether 639 00:35:56,360 --> 00:35:59,680 Speaker 1: your financial services company or an insurance company or healthcare company. 640 00:35:59,760 --> 00:36:02,160 Speaker 1: So it can take you eighty percent or eighty five 641 00:36:02,200 --> 00:36:04,959 Speaker 1: percent there the last ten to fifteen percent it still 642 00:36:05,000 --> 00:36:07,320 Speaker 1: requires some human touch to sort of apply the business 643 00:36:07,320 --> 00:36:09,640 Speaker 1: context to what you're trying to go after. You mentioned 644 00:36:09,760 --> 00:36:14,440 Speaker 1: varied industries that deploy cyber needs. What about the company's 645 00:36:14,480 --> 00:36:17,000 Speaker 1: building all of this by mac? Are you investing primarily 646 00:36:17,080 --> 00:36:21,960 Speaker 1: in American built companies? Is this truly gloiville? You know, 647 00:36:22,120 --> 00:36:25,440 Speaker 1: from a cyber perspective, I still argue the epicenter for 648 00:36:25,440 --> 00:36:28,640 Speaker 1: a lot of innovations here in America. I would say 649 00:36:28,960 --> 00:36:31,600 Speaker 1: Israel has has sort of come up over the last 650 00:36:31,600 --> 00:36:33,560 Speaker 1: five to seven years, is a new epicenter where it's 651 00:36:33,600 --> 00:36:36,920 Speaker 1: a lot of innovation that comes out of Israel, partly 652 00:36:36,960 --> 00:36:38,680 Speaker 1: out of Unit eighty two hundred, which is part of 653 00:36:38,680 --> 00:36:43,360 Speaker 1: the IDF. And so the vast majority you see between 654 00:36:43,400 --> 00:36:48,600 Speaker 1: those two areas, Amida and EU specifically is obviously coming 655 00:36:48,600 --> 00:36:51,280 Speaker 1: together in the last three to five years. My previous company, 656 00:36:51,320 --> 00:36:53,080 Speaker 1: Alien Bolt, was a company that was started out of 657 00:36:53,120 --> 00:36:56,080 Speaker 1: Space Spain and had moved their headquarters to the US. 658 00:36:56,160 --> 00:36:59,000 Speaker 1: So but I would say in America and Israel are 659 00:36:59,080 --> 00:37:02,920 Speaker 1: kind of the two main epi centers. All right, Barmacmefter, 660 00:37:03,040 --> 00:37:06,320 Speaker 1: co founder, general partner of Ballistic Ventures. Thank you. You 661 00:37:06,400 --> 00:37:09,800 Speaker 1: take two themes. Caroline Cybersecurity and then you match it 662 00:37:09,880 --> 00:37:12,399 Speaker 1: with the other big theme, AI. So let's stick with AI. 663 00:37:12,520 --> 00:37:16,000 Speaker 1: In China, the government plans to require a security review 664 00:37:16,080 --> 00:37:19,880 Speaker 1: of chat GPT like bots, providers of the generative artificial 665 00:37:19,920 --> 00:37:24,480 Speaker 1: intelligence services must ensure content is accurate and neither discriminates 666 00:37:24,560 --> 00:37:27,600 Speaker 1: nor in dangerous security. Chinese companies, from Ali Barber to 667 00:37:27,719 --> 00:37:30,160 Speaker 1: Sense Time to Buy do all want to build the 668 00:37:30,320 --> 00:37:43,400 Speaker 1: definitive next gen AI platform gaming bench capital funding has 669 00:37:43,440 --> 00:37:46,320 Speaker 1: returned to pre twenty twenty one level. So that's according 670 00:37:46,440 --> 00:37:49,160 Speaker 1: to Convoy Ventures latest gaming report for the first quarter 671 00:37:49,239 --> 00:37:52,120 Speaker 1: of this year, out today. Co founder and managing partner 672 00:37:52,239 --> 00:37:55,560 Speaker 1: Jason Chapman with us to go over the numbers. It's interesting, 673 00:37:55,600 --> 00:37:57,839 Speaker 1: we're kind of back to this pre twenty twenty one level. 674 00:37:57,880 --> 00:37:59,320 Speaker 1: But if you look at the court, are just gone 675 00:37:59,640 --> 00:38:03,000 Speaker 1: a horse roun court to bump in in venture dollars deployed, 676 00:38:03,280 --> 00:38:05,279 Speaker 1: but nothing like the court is that we did see 677 00:38:05,320 --> 00:38:07,839 Speaker 1: in twenty twenty one. What's the main driver right now 678 00:38:07,920 --> 00:38:12,239 Speaker 1: for backing startups in this industry? Yeah, I think I 679 00:38:12,320 --> 00:38:14,920 Speaker 1: think generally and thick you for having me is largely 680 00:38:15,360 --> 00:38:17,360 Speaker 1: the player data. You know, we look and see that 681 00:38:17,520 --> 00:38:20,600 Speaker 1: thirty point two billion people across the world continue to 682 00:38:20,600 --> 00:38:24,120 Speaker 1: play video games. That's nearly forty percent of the global population. 683 00:38:24,640 --> 00:38:26,840 Speaker 1: And this quarter we saw about seven hundred and sixty 684 00:38:26,880 --> 00:38:30,440 Speaker 1: one million dollars invested into gaming deals across venture that 685 00:38:30,640 --> 00:38:33,560 Speaker 1: is up twenty nine percent. And so I think generally 686 00:38:33,600 --> 00:38:36,320 Speaker 1: you see investors walk to areas that proved to be 687 00:38:36,480 --> 00:38:40,239 Speaker 1: resilient during economic difficulties, which gaming has proven during the 688 00:38:40,320 --> 00:38:43,160 Speaker 1: last two recessions to do so, and during this current 689 00:38:43,200 --> 00:38:46,240 Speaker 1: phase we expect it will do the same. You, of course, 690 00:38:46,560 --> 00:38:50,040 Speaker 1: often invest in the infrastructure around gaming. What about the building, 691 00:38:50,080 --> 00:38:53,560 Speaker 1: the making of gaming and games themselves and how they're 692 00:38:53,640 --> 00:38:58,239 Speaker 1: being offered because a lot of them are more streaming services. Now, yeah, 693 00:38:58,360 --> 00:39:00,440 Speaker 1: so I mean there's a lot there. I mean actually 694 00:39:00,560 --> 00:39:03,480 Speaker 1: talking about streaming. It's it's ironic given that Google Stadia 695 00:39:03,640 --> 00:39:06,960 Speaker 1: just closed officially this this actually this quarter in January. 696 00:39:07,920 --> 00:39:11,120 Speaker 1: You know, we are very excited to back the infrastructure 697 00:39:11,239 --> 00:39:13,640 Speaker 1: of how you deliver games, how you distribute games, how 698 00:39:13,680 --> 00:39:18,080 Speaker 1: you advertise games. Building a game is extremely expensive, you know, 699 00:39:18,200 --> 00:39:20,440 Speaker 1: looking at Triple A content, it often is north of 700 00:39:20,480 --> 00:39:23,400 Speaker 1: eighty million dollars to actually produce, and so for us, 701 00:39:23,520 --> 00:39:26,520 Speaker 1: we think the upside is definitely in the content in 702 00:39:26,840 --> 00:39:31,520 Speaker 1: the technologies versus the content interesting. So, given Stadia you 703 00:39:31,640 --> 00:39:34,640 Speaker 1: just mentioned it, do we think there's less desire by 704 00:39:34,880 --> 00:39:39,200 Speaker 1: some very well capitalized, big tech public companies to invest 705 00:39:39,280 --> 00:39:43,040 Speaker 1: in content at this moment. We're seeing a lot of 706 00:39:43,120 --> 00:39:47,240 Speaker 1: content funding today, a lot of excitement around content because 707 00:39:47,320 --> 00:39:49,960 Speaker 1: you know, as as we are seeing Hogwarts legacy has 708 00:39:50,040 --> 00:39:52,279 Speaker 1: has caught the world by storm, and hopefully you have 709 00:39:52,440 --> 00:39:55,960 Speaker 1: some players. They're actually at Bloomberg. You know, with content, 710 00:39:56,040 --> 00:39:59,279 Speaker 1: it's incredibly scalable and it can be delivered at ease 711 00:39:59,400 --> 00:40:02,560 Speaker 1: to the massive And something that is very lurrying about 712 00:40:02,600 --> 00:40:04,160 Speaker 1: this is that if you find a hit, you find 713 00:40:04,160 --> 00:40:07,200 Speaker 1: a huge hit. For us, we are much more comfortable 714 00:40:07,200 --> 00:40:10,680 Speaker 1: as a firm backing the things that make delivery content possible. 715 00:40:10,760 --> 00:40:13,760 Speaker 1: So we're betting on a category versus one piece of content. 716 00:40:14,320 --> 00:40:16,600 Speaker 1: We think it's a more prudent way to approach approach 717 00:40:16,640 --> 00:40:21,319 Speaker 1: the industry. You're a completely set to focus VC fund. 718 00:40:21,360 --> 00:40:23,400 Speaker 1: There is a big player in this industry right now, 719 00:40:23,440 --> 00:40:26,280 Speaker 1: which is Saudi Arabia. You look at the savvy scope 720 00:40:26,360 --> 00:40:29,200 Speaker 1: lea deal as one example, but also the fund, the 721 00:40:29,280 --> 00:40:32,439 Speaker 1: war chest they've amassed. What's your take on Saudi coming 722 00:40:32,520 --> 00:40:36,680 Speaker 1: in to sort of dominate this sector. Yeah, so you know, 723 00:40:36,800 --> 00:40:39,200 Speaker 1: the thirty eight billion dollars that have been earmarked for 724 00:40:39,360 --> 00:40:43,920 Speaker 1: gaming is a significant move. So historically speaking, they have 725 00:40:44,040 --> 00:40:46,600 Speaker 1: not been very active entertainment, but the government of Saudi 726 00:40:46,600 --> 00:40:48,560 Speaker 1: Arabia is determined that gaming will be a pillar of 727 00:40:48,719 --> 00:40:53,440 Speaker 1: entertainment for them going forward. And the acquisition of Scopelely 728 00:40:53,440 --> 00:40:55,920 Speaker 1: at four point nine billion dollar acquisitions a huge win 729 00:40:56,200 --> 00:40:59,200 Speaker 1: to for the Scope Lee end Savvy team, So the 730 00:40:59,200 --> 00:41:02,320 Speaker 1: whole Convoy team is extremely excited about this partnership. The 731 00:41:02,360 --> 00:41:04,920 Speaker 1: Savvy group with that acquisition have brought in one hundred 732 00:41:04,960 --> 00:41:08,640 Speaker 1: million monthly actives across their platform, which is a massive 733 00:41:08,680 --> 00:41:10,560 Speaker 1: deal in the gaming industry and a massive deal for 734 00:41:10,640 --> 00:41:13,640 Speaker 1: the Savvy platform. Hey, Jason, real quick, twenty twenty two 735 00:41:13,800 --> 00:41:16,839 Speaker 1: is all about online a multiplayer. What's twenty twenty three 736 00:41:16,840 --> 00:41:19,400 Speaker 1: you're going to be about? Twenty twenty three is going 737 00:41:19,440 --> 00:41:22,040 Speaker 1: to be your user generated content and the wars between 738 00:41:22,239 --> 00:41:26,880 Speaker 1: Roadblocks and Fortnite. Looking at the Creator platform just launched 739 00:41:26,880 --> 00:41:28,719 Speaker 1: and announced by Tim Sweeney a couple of weeks ago, 740 00:41:29,360 --> 00:41:31,600 Speaker 1: You're going to see a lot of creators be lured 741 00:41:31,600 --> 00:41:34,400 Speaker 1: to that platform from roadblocks as well as others, and 742 00:41:34,560 --> 00:41:36,320 Speaker 1: so we're very keen to watch this and it's a 743 00:41:36,400 --> 00:41:38,680 Speaker 1: trend that Convoy is paying a lot of attention to 744 00:41:38,800 --> 00:41:41,560 Speaker 1: and also to point a lot of money towards thanks 745 00:41:41,600 --> 00:41:43,960 Speaker 1: to bringing your trends as you see them. Convoy Ventures 746 00:41:44,000 --> 00:41:48,040 Speaker 1: co founder managing partner Jason Chapman, Well, that does it 747 00:41:48,080 --> 00:41:51,320 Speaker 1: for this edition. And Bloombag Technology, Yeah, real emphasis on 748 00:41:51,400 --> 00:41:54,120 Speaker 1: cybersecurity and AI in the market right now. Recap with 749 00:41:54,200 --> 00:41:58,960 Speaker 1: the podcast. You can find it on the terminal, on Apple, Spotify, Hut, 750 00:41:59,040 --> 00:42:02,000 Speaker 1: wherever you get your podcast. Caroline, I think I think 751 00:42:02,040 --> 00:42:04,719 Speaker 1: about these markets as well. We're bracin for Wednesday, We're 752 00:42:04,760 --> 00:42:07,680 Speaker 1: bracin for data and in the technology sector, we're always 753 00:42:07,719 --> 00:42:10,600 Speaker 1: looking at the FED from SF in New York. This 754 00:42:10,840 --> 00:42:11,480 Speaker 1: is Bloomberg