1 00:00:01,440 --> 00:00:06,760 Speaker 1: From Mahard where Innovations, Money and Power Collie in Silicon Valley, NBN. 2 00:00:07,040 --> 00:00:11,559 Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow. 3 00:00:24,920 --> 00:00:27,040 Speaker 3: Live from Los Angeles and San Francisco. 4 00:00:27,280 --> 00:00:30,360 Speaker 4: This is Bloomberg Technology coming up, cracking down on big tech. 5 00:00:30,680 --> 00:00:33,920 Speaker 4: The DOJ considering a historic breakup of Google. 6 00:00:34,760 --> 00:00:38,200 Speaker 5: More than a dozen US states filing lawsuits against TikTok 7 00:00:38,520 --> 00:00:40,960 Speaker 5: will be joined by New Jersey's Attorney general. 8 00:00:41,680 --> 00:00:45,280 Speaker 4: And we're live from Citadel's Global Macro Conference in New York. 9 00:00:45,520 --> 00:00:48,760 Speaker 4: A conversation with the CEO, Pengzau is coming up. 10 00:00:49,440 --> 00:00:52,240 Speaker 3: First, Let's go to our top story. Shares of alphabet 11 00:00:52,280 --> 00:00:53,159 Speaker 3: are lower. 12 00:00:52,800 --> 00:00:55,640 Speaker 4: Today by one point six percent. That's after the DOJ 13 00:00:55,840 --> 00:00:59,279 Speaker 4: is weighing a breakup of Google over its monopolistic dominance 14 00:00:59,320 --> 00:01:00,480 Speaker 4: of online search. 15 00:01:00,800 --> 00:01:02,720 Speaker 3: Be goes straight to the report. Who's been all over this? 16 00:01:02,720 --> 00:01:07,000 Speaker 4: Bloomberg's Leah Lyle and Leah. You reported this back in 17 00:01:07,040 --> 00:01:10,160 Speaker 4: August that this might be a consideration and the DOJ 18 00:01:10,360 --> 00:01:13,440 Speaker 4: would put this to the judge. What's moved on from 19 00:01:13,440 --> 00:01:18,080 Speaker 4: that reporting, Leah. 20 00:01:16,200 --> 00:01:19,600 Speaker 6: Yes, so now we are actually getting into the revenues phase. 21 00:01:19,680 --> 00:01:22,319 Speaker 6: So last night the Justice Department put its first filing 22 00:01:22,360 --> 00:01:24,959 Speaker 6: in it actually just lead out a framework of various 23 00:01:24,959 --> 00:01:28,000 Speaker 6: things that it's thinking about as it is crafting a 24 00:01:28,040 --> 00:01:32,040 Speaker 6: remedy proposal. They're going to have an official proposal that 25 00:01:32,160 --> 00:01:34,640 Speaker 6: lays out everything that they want Google to do on 26 00:01:34,720 --> 00:01:38,000 Speaker 6: November twentieth. But this was just sort of like, here's 27 00:01:38,000 --> 00:01:41,280 Speaker 6: what we're thinking. These are some of the options. And 28 00:01:41,440 --> 00:01:43,480 Speaker 6: the big one, of course, was the breakup. 29 00:01:44,319 --> 00:01:46,920 Speaker 5: Okay, so let's get into that timeline you mentioned November 30 00:01:46,959 --> 00:01:49,440 Speaker 5: twenty if we'll bring it up on the screen. The 31 00:01:49,480 --> 00:01:52,400 Speaker 5: first is the sort of firming of the proposals. Then 32 00:01:52,480 --> 00:01:55,560 Speaker 5: Google gets a chance next April we'll have a trial, 33 00:01:56,000 --> 00:01:59,000 Speaker 5: and then by August I think of twenty twenty five, 34 00:01:59,400 --> 00:02:01,120 Speaker 5: we might get some sort of decision. 35 00:02:01,240 --> 00:02:04,320 Speaker 7: Explain all of that, please, Leah. Yes. 36 00:02:04,440 --> 00:02:07,440 Speaker 6: So DOJ is going to put its filing in that 37 00:02:07,480 --> 00:02:09,960 Speaker 6: says this is exactly what we want, you know, whether 38 00:02:10,000 --> 00:02:13,359 Speaker 6: that's a breakup, data sharing, all those things, and then 39 00:02:13,440 --> 00:02:16,080 Speaker 6: Google gets a chance to respond. Over the next couple months, 40 00:02:16,120 --> 00:02:20,000 Speaker 6: they're going to be doing a lot more discovery again, 41 00:02:20,040 --> 00:02:22,040 Speaker 6: so they're going to do interviews with Google folks, They're 42 00:02:22,040 --> 00:02:24,480 Speaker 6: going to get more documents all leading up to this 43 00:02:24,600 --> 00:02:28,200 Speaker 6: big two week remedy trial that will take place late 44 00:02:28,240 --> 00:02:32,240 Speaker 6: April in that they're going to have witnesses testify before 45 00:02:32,240 --> 00:02:35,160 Speaker 6: the judge about what would actually happen to Google's business 46 00:02:35,160 --> 00:02:38,720 Speaker 6: if he takes any of these particular actions. And then 47 00:02:38,760 --> 00:02:41,320 Speaker 6: he has promised that he will issue a decision in 48 00:02:41,360 --> 00:02:44,320 Speaker 6: August of next year that officially wraps up the case 49 00:02:45,000 --> 00:02:47,800 Speaker 6: at the trial court, and then Google can start its appeal. 50 00:02:48,240 --> 00:02:51,040 Speaker 6: The appeal, you know, takes like eighteen months to two years, 51 00:02:51,320 --> 00:02:54,600 Speaker 6: so we're looking at like August for the sort of 52 00:02:54,639 --> 00:02:57,080 Speaker 6: like first big deadline, and then we'll go into the 53 00:02:57,080 --> 00:02:59,720 Speaker 6: appeals and then you know, maybe some of this would 54 00:02:59,720 --> 00:03:02,320 Speaker 6: be take place like as eighteen months to two years 55 00:03:02,360 --> 00:03:02,760 Speaker 6: from now. 56 00:03:02,919 --> 00:03:08,960 Speaker 4: From then, Let's just go to Google's own response, because 57 00:03:09,000 --> 00:03:11,799 Speaker 4: the US judge is saying that Google's distribution agreements full 58 00:03:11,840 --> 00:03:15,280 Speaker 4: close a substantial portion of the general search services market 59 00:03:15,320 --> 00:03:17,400 Speaker 4: and impair rivals opportunities to compete. 60 00:03:17,440 --> 00:03:18,440 Speaker 3: That's the judges take. 61 00:03:19,120 --> 00:03:22,320 Speaker 4: Google's take, Is it this is pretty radical right near? 62 00:03:23,639 --> 00:03:23,919 Speaker 7: Yes? 63 00:03:24,240 --> 00:03:27,080 Speaker 6: I mean Google said what you found was illegal is 64 00:03:27,080 --> 00:03:30,080 Speaker 6: these specific contracts. So DOJ should be focusing on the 65 00:03:30,120 --> 00:03:32,160 Speaker 6: contracts and just looking at those. 66 00:03:33,320 --> 00:03:34,040 Speaker 7: They say, you. 67 00:03:33,960 --> 00:03:36,400 Speaker 6: Know that these these things that the Justice Department is 68 00:03:36,400 --> 00:03:39,520 Speaker 6: proposing go way beyond those contracts. They're talking about, you know, 69 00:03:39,680 --> 00:03:42,000 Speaker 6: breaking up our company. They're talking about making us sell 70 00:03:42,040 --> 00:03:44,880 Speaker 6: off Chrome, which wasn't even really part of the case 71 00:03:44,920 --> 00:03:48,320 Speaker 6: that much because Google owns Chrome, and so it is 72 00:03:48,360 --> 00:03:51,160 Speaker 6: pushing back pretty hard on a lot of these remedies, 73 00:03:51,240 --> 00:03:55,520 Speaker 6: the breakup in particular. The other thing that they have 74 00:03:55,640 --> 00:03:58,200 Speaker 6: said is, you know, the Justice Department says that AI 75 00:03:58,520 --> 00:04:00,760 Speaker 6: is a very big issue here because a lot of 76 00:04:00,800 --> 00:04:04,480 Speaker 6: the data that Google uses to build its search results 77 00:04:04,600 --> 00:04:06,920 Speaker 6: is the same data that is used to build its 78 00:04:07,000 --> 00:04:10,320 Speaker 6: AI products. And the Justice Department says that Google shouldn't 79 00:04:10,320 --> 00:04:13,120 Speaker 6: sort of get to benefit from the illegal conduct in 80 00:04:13,160 --> 00:04:15,480 Speaker 6: the search market, in the AI market, and so it 81 00:04:15,560 --> 00:04:17,800 Speaker 6: wants to put some limits on that. And Google says, 82 00:04:17,960 --> 00:04:21,159 Speaker 6: wait a second, we were talking about search, that's not AI. 83 00:04:21,400 --> 00:04:23,920 Speaker 6: You shouldn't get to like make some limits on us 84 00:04:23,920 --> 00:04:27,760 Speaker 6: in this completely other different field. So that will be 85 00:04:27,839 --> 00:04:29,839 Speaker 6: a big issue for the judge to decide next year. 86 00:04:30,800 --> 00:04:33,159 Speaker 5: Bloombos lea nil in a late night for you in 87 00:04:33,240 --> 00:04:37,120 Speaker 5: DC in an early morning too important reporting, but the 88 00:04:37,120 --> 00:04:40,480 Speaker 5: stocks on the move. Meanwhile, Google CEO sind the pitch 89 00:04:40,560 --> 00:04:43,680 Speaker 5: I sat down with David Rubinstein for his show Pid 90 00:04:43,680 --> 00:04:46,760 Speaker 5: to Peer Conversations. He's a reminder about what he had 91 00:04:46,800 --> 00:04:50,320 Speaker 5: to say about the mounting legal woes and antitrust suits 92 00:04:50,520 --> 00:04:51,279 Speaker 5: from the DOJ. 93 00:04:52,720 --> 00:04:55,480 Speaker 8: We definitely disagree with the ruling, but be still in 94 00:04:55,480 --> 00:04:59,039 Speaker 8: the middle of the di remedys phase and you know 95 00:04:59,080 --> 00:05:02,279 Speaker 8: we will appeal. This process will likely take many years, 96 00:05:02,360 --> 00:05:07,640 Speaker 8: and you know, I'm confident given that you know, VR 97 00:05:07,920 --> 00:05:12,960 Speaker 8: focused on innovating using technology will do well in the 98 00:05:13,000 --> 00:05:13,599 Speaker 8: long run. 99 00:05:15,480 --> 00:05:17,919 Speaker 5: You can see that full interview tonight on the David 100 00:05:17,960 --> 00:05:22,240 Speaker 5: Rubinstein Show, Peer to Peer Conversations, nine pm New York Time. 101 00:05:22,320 --> 00:05:26,080 Speaker 4: Caroline, let's just dig into anti trust the risk to 102 00:05:26,160 --> 00:05:29,479 Speaker 4: big tech right now. Jason Bett's and Meerorprice Financial Private 103 00:05:29,520 --> 00:05:32,640 Speaker 4: wealth Advisor is with us. And look, the stock is 104 00:05:32,680 --> 00:05:36,000 Speaker 4: down for alphabet but by one point six percent, the 105 00:05:36,000 --> 00:05:39,160 Speaker 4: biggest move since all October the seventh. It doesn't feel 106 00:05:39,200 --> 00:05:41,520 Speaker 4: like many people are pricing in a breakup to this 107 00:05:41,600 --> 00:05:42,560 Speaker 4: extent right now? 108 00:05:42,680 --> 00:05:44,719 Speaker 3: Is it a risk? Anti trust issues? 109 00:05:46,000 --> 00:05:51,680 Speaker 9: Anti trust issues in general make a very, very an 110 00:05:51,760 --> 00:05:54,880 Speaker 9: eye catching headline. Certainly, it's what all of us are 111 00:05:54,880 --> 00:05:58,400 Speaker 9: talking about right now. We see this play out every 112 00:05:58,400 --> 00:06:01,520 Speaker 9: several years in the technology space and in pharmaceuticals and 113 00:06:01,520 --> 00:06:05,440 Speaker 9: and energy with the anti trust issues. My feeling is 114 00:06:05,600 --> 00:06:08,839 Speaker 9: it is it's such a long timeline and there's so 115 00:06:08,960 --> 00:06:11,200 Speaker 9: many what ifs that we can speculate on. But as 116 00:06:11,240 --> 00:06:14,280 Speaker 9: actual investors looking at fundamentals and trying to navigate this, 117 00:06:14,880 --> 00:06:17,240 Speaker 9: I really don't think there's anything that we should be 118 00:06:17,279 --> 00:06:21,960 Speaker 9: thinking about doing differently as we approach our investment portfolios. 119 00:06:20,920 --> 00:06:26,359 Speaker 5: Well, hold on the stocks down one point six percent 120 00:06:26,560 --> 00:06:29,720 Speaker 5: in a market that's up, and we showed that timeline, 121 00:06:30,160 --> 00:06:32,720 Speaker 5: so you get to August the next year, and a 122 00:06:32,839 --> 00:06:38,479 Speaker 5: hypothetical the judge orders the breakup. Now they'll counter it 123 00:06:38,480 --> 00:06:40,800 Speaker 5: in court, but let's say it happens. 124 00:06:41,200 --> 00:06:42,360 Speaker 7: How do you prepare for that? 125 00:06:44,160 --> 00:06:46,560 Speaker 9: I mean, you prepare for it like you prepare for 126 00:06:46,600 --> 00:06:48,640 Speaker 9: anything else, in my opinion, which is making sure that 127 00:06:48,680 --> 00:06:51,320 Speaker 9: everything within the investment portfolio looks okay under the hood, 128 00:06:51,800 --> 00:06:56,159 Speaker 9: and whether you know, regardless of any individual security, you 129 00:06:56,240 --> 00:06:58,279 Speaker 9: want to make sure that you don't have too much 130 00:06:58,279 --> 00:07:00,560 Speaker 9: exposure in anyone individual secure already. 131 00:07:00,279 --> 00:07:02,800 Speaker 2: Where if the worst case scenario does play out, that it. 132 00:07:02,720 --> 00:07:05,599 Speaker 9: Could have somewhat in reparable consequences on your financial future 133 00:07:05,680 --> 00:07:09,000 Speaker 9: or your wealth other than that, you know, with our firm, 134 00:07:09,040 --> 00:07:11,040 Speaker 9: we take a really holistic approach and we take a 135 00:07:11,040 --> 00:07:14,560 Speaker 9: discipline approach. So while this is a it's a very 136 00:07:14,600 --> 00:07:17,320 Speaker 9: eye catching headline today, it's something that we're going to 137 00:07:17,360 --> 00:07:19,240 Speaker 9: be talking about, certainly for the next couple of days, 138 00:07:19,240 --> 00:07:20,480 Speaker 9: if not for the next few weeks. 139 00:07:20,920 --> 00:07:22,320 Speaker 2: It's going to be a long process. 140 00:07:22,320 --> 00:07:24,720 Speaker 9: And the idea of trying to do anything differently with 141 00:07:24,800 --> 00:07:28,040 Speaker 9: positioning right now other than making sure that your that 142 00:07:28,120 --> 00:07:33,160 Speaker 9: your positions are not overweighted or underweighted for that matter, 143 00:07:33,760 --> 00:07:36,080 Speaker 9: I just don't really see anything else that that that 144 00:07:36,200 --> 00:07:38,360 Speaker 9: requires material attention right now today. 145 00:07:39,320 --> 00:07:42,000 Speaker 5: Well, it's interesting you use the phrase single security, but 146 00:07:42,840 --> 00:07:46,320 Speaker 5: basically most of the megacap tech names have some form 147 00:07:46,360 --> 00:07:51,000 Speaker 5: of antitrust scrutiny on them in multiple jurisdictions, and so 148 00:07:51,120 --> 00:07:54,720 Speaker 5: in aggregate, how much of an anxiety is it then, 149 00:07:54,760 --> 00:07:56,840 Speaker 5: if you think about it through that lens. 150 00:07:57,520 --> 00:08:00,000 Speaker 9: Yeah, I mean, if you're properly diversified, not that much 151 00:08:00,040 --> 00:08:02,360 Speaker 9: much of anxiety. Because if the worst case scenario is 152 00:08:02,360 --> 00:08:04,400 Speaker 9: what you see is some sort of shift in leadership 153 00:08:04,800 --> 00:08:09,560 Speaker 9: within you know, the more specialized technology sectors. So again, 154 00:08:09,600 --> 00:08:12,760 Speaker 9: it's just at these stages right now, Like I said, 155 00:08:12,760 --> 00:08:15,520 Speaker 9: we see this time and time again over my last 156 00:08:15,520 --> 00:08:18,160 Speaker 9: twenty seven years in this industry. Certainly with technology and 157 00:08:18,200 --> 00:08:20,920 Speaker 9: AI these stakes are higher, but we've seed it in 158 00:08:21,000 --> 00:08:24,640 Speaker 9: pharma and energy and technology in the past. Generally speaking, 159 00:08:25,800 --> 00:08:29,480 Speaker 9: we don't see a whole lot of you know, movement 160 00:08:29,880 --> 00:08:33,480 Speaker 9: materially within the markets or sometimes within the sectors as 161 00:08:33,480 --> 00:08:35,240 Speaker 9: a result of these anti trust headlines. 162 00:08:35,280 --> 00:08:37,120 Speaker 2: But time will tell. 163 00:08:37,520 --> 00:08:38,240 Speaker 7: Time will tell. 164 00:08:38,280 --> 00:08:40,320 Speaker 4: The anxiety here and now for the market in many 165 00:08:40,320 --> 00:08:44,319 Speaker 4: ways is what revenue, what profitability looks. 166 00:08:44,120 --> 00:08:46,360 Speaker 3: Like right here, right now for AI. 167 00:08:46,800 --> 00:08:49,080 Speaker 4: I know you've been thinking writing a lot on this, Jason, 168 00:08:49,440 --> 00:08:52,480 Speaker 4: and we actually get another good sign. T SMC's numbers 169 00:08:52,480 --> 00:08:54,200 Speaker 4: come in and they come in strong. We'll be digging 170 00:08:54,240 --> 00:08:54,680 Speaker 4: into that. 171 00:08:54,600 --> 00:08:55,120 Speaker 3: In a moment. 172 00:08:55,240 --> 00:08:57,600 Speaker 4: But what are you getting in terms of a gut 173 00:08:57,679 --> 00:08:59,920 Speaker 4: check on the valuations of these mega caps? 174 00:09:00,880 --> 00:09:01,080 Speaker 1: Yeah? 175 00:09:01,120 --> 00:09:04,760 Speaker 9: Absolutely, My gut check is that valuations are stretched. 176 00:09:04,840 --> 00:09:05,000 Speaker 2: Now. 177 00:09:05,000 --> 00:09:07,000 Speaker 9: Having said that, it's the markets, and the markets do 178 00:09:07,160 --> 00:09:08,720 Speaker 9: things that we don't expect. 179 00:09:08,400 --> 00:09:09,040 Speaker 2: All the time. 180 00:09:09,720 --> 00:09:13,679 Speaker 9: But if I look at the valuations and I look 181 00:09:13,720 --> 00:09:16,160 Speaker 9: at what, in my opinion is kind of a more 182 00:09:16,280 --> 00:09:18,960 Speaker 9: or less a best case scenario that's playing out in 183 00:09:19,040 --> 00:09:21,400 Speaker 9: terms of the expectations on future earnings. 184 00:09:21,960 --> 00:09:22,719 Speaker 2: It's tough to. 185 00:09:24,160 --> 00:09:27,080 Speaker 9: It's tough to see these levels go materially higher without 186 00:09:27,160 --> 00:09:30,520 Speaker 9: continued breakout positive data. That said, we've had that to 187 00:09:30,559 --> 00:09:33,720 Speaker 9: your point, and we may see that moving forward. But 188 00:09:33,760 --> 00:09:36,320 Speaker 9: I would just take it back again to making sure, 189 00:09:36,440 --> 00:09:40,280 Speaker 9: regardless of what happens moving forward, look under the hood 190 00:09:40,280 --> 00:09:42,720 Speaker 9: of the portfolio, make sure that you're not too overweighted 191 00:09:42,760 --> 00:09:45,720 Speaker 9: in any individual names or in any one particular sector. 192 00:09:47,240 --> 00:09:51,320 Speaker 4: What about therefore, the macro picture, if you're thinking about 193 00:09:51,320 --> 00:09:54,280 Speaker 4: anyone sector, Look, it's been impossible not to be overweight 194 00:09:54,360 --> 00:09:57,400 Speaker 4: and to be extraordinarily heavily weighted towards technology because of 195 00:09:57,400 --> 00:09:58,760 Speaker 4: the year valuations. 196 00:09:58,280 --> 00:09:59,040 Speaker 3: Of these companies. 197 00:09:59,440 --> 00:10:02,640 Speaker 4: How do you continue to rebalance, particularly when you're thinking 198 00:10:02,679 --> 00:10:04,360 Speaker 4: about what interest rates are up to? 199 00:10:05,559 --> 00:10:09,120 Speaker 9: Yeah, well, I mean, regardless of interest rates, when we're rebalanced, 200 00:10:09,120 --> 00:10:11,760 Speaker 9: and obviously we need to you know, we want to 201 00:10:11,760 --> 00:10:13,920 Speaker 9: do that. I think investors have actually gotten away from 202 00:10:13,920 --> 00:10:15,880 Speaker 9: that a lot over the last year or two, and 203 00:10:15,880 --> 00:10:19,600 Speaker 9: that's part of the reason why we've probably seen this 204 00:10:20,200 --> 00:10:24,760 Speaker 9: excessive leadership in these megacap technology stocks. But in terms 205 00:10:24,800 --> 00:10:27,360 Speaker 9: of other septors that I may like in the markets 206 00:10:27,440 --> 00:10:31,559 Speaker 9: right now, you know, I've said this for about the 207 00:10:31,640 --> 00:10:33,760 Speaker 9: last six to twelve months that I really like utilities, 208 00:10:33,840 --> 00:10:35,720 Speaker 9: not because I thought utilities would be out performing the 209 00:10:35,760 --> 00:10:37,400 Speaker 9: S and P over the last year year to date, 210 00:10:37,679 --> 00:10:39,839 Speaker 9: but just simply because they were so undervalued and the 211 00:10:40,320 --> 00:10:43,959 Speaker 9: valuations were delicious, and I think they're still attractive and 212 00:10:44,040 --> 00:10:45,439 Speaker 9: there's still room for growth there. 213 00:10:45,720 --> 00:10:47,000 Speaker 2: I like healthcare because of it. 214 00:10:47,440 --> 00:10:50,240 Speaker 9: It's because it has actually underperformed, and I think it 215 00:10:50,320 --> 00:10:53,040 Speaker 9: might be due for some mean reversion. And to your point, 216 00:10:53,040 --> 00:10:56,520 Speaker 9: with interest rates, if and when they continue to come down, 217 00:10:57,000 --> 00:10:59,679 Speaker 9: then that sets the table again for conversation about it. 218 00:10:59,760 --> 00:11:03,040 Speaker 9: More active mergers and acquisitions market that's good for healthcarecter, 219 00:11:03,080 --> 00:11:04,240 Speaker 9: especially good for biotech. 220 00:11:05,559 --> 00:11:06,880 Speaker 7: You mentioned utilities. 221 00:11:07,440 --> 00:11:10,160 Speaker 5: Are you one of many that are now interested in 222 00:11:10,160 --> 00:11:14,160 Speaker 5: this groundbreaking new field called nuclear energy that could be 223 00:11:14,320 --> 00:11:18,679 Speaker 5: powering all of the AI infrastructure investment that we'll see. 224 00:11:19,640 --> 00:11:22,200 Speaker 9: At this moment, I would say I would say no, 225 00:11:22,240 --> 00:11:25,400 Speaker 9: not in any above average fashion. We're obviously looking at 226 00:11:25,440 --> 00:11:27,719 Speaker 9: and considering all the information in the news and the 227 00:11:27,800 --> 00:11:33,000 Speaker 9: data points, but there's not any particular over over the 228 00:11:33,120 --> 00:11:35,360 Speaker 9: level over excitement, for lack of a better way to 229 00:11:35,360 --> 00:11:38,160 Speaker 9: put it, this time concerning that all right? 230 00:11:38,160 --> 00:11:40,320 Speaker 5: Oh, thanks to Jason Betts for Ameror Price. Good to 231 00:11:40,320 --> 00:11:42,839 Speaker 5: catch up and have you here on Bloomberg Technology. Now 232 00:11:42,840 --> 00:11:46,079 Speaker 5: coming up on the show, two DeepMind scientists and now 233 00:11:46,559 --> 00:11:52,160 Speaker 5: no Bell Prize winners for their research using artificial intelligence. 234 00:11:52,360 --> 00:12:09,319 Speaker 5: Fascinating conversation to come. This is Bloomberg Technology to Google 235 00:12:09,400 --> 00:12:14,080 Speaker 5: DeepMind scientists and now Nobel Prize winners. They're sharing the 236 00:12:14,160 --> 00:12:18,280 Speaker 5: twenty twenty four Nobel Prize in Chemistry with US professors 237 00:12:18,280 --> 00:12:23,000 Speaker 5: for their breakthrough research into proteins, which were developed through AI. 238 00:12:23,280 --> 00:12:27,320 Speaker 5: Bloomberg's Mark Bergen reported on it and joins us from London. 239 00:12:27,360 --> 00:12:31,720 Speaker 5: I've never seen you Mark so excited about the intersection 240 00:12:31,840 --> 00:12:33,959 Speaker 5: of science and technology. 241 00:12:34,920 --> 00:12:38,880 Speaker 7: What have you been writing about? Oh, tremendously excited. 242 00:12:39,320 --> 00:12:41,360 Speaker 10: This is you know, this has actually come earlier than 243 00:12:41,400 --> 00:12:43,599 Speaker 10: we expected, but we knew it was something that the 244 00:12:44,559 --> 00:12:47,839 Speaker 10: co founder and CEO deep Mind, Demis Hassabis, who was 245 00:12:47,920 --> 00:12:52,040 Speaker 10: one of the award winners. This morning we've reported this 246 00:12:52,040 --> 00:12:53,280 Speaker 10: to something he's told colleagues. 247 00:12:53,280 --> 00:12:54,960 Speaker 7: This has been an ambition of his. 248 00:12:55,960 --> 00:12:58,560 Speaker 10: Our colleague from the Bloomberg Opinion side, Primie also and 249 00:12:58,760 --> 00:13:00,640 Speaker 10: her great book. It just came out, I think she 250 00:13:01,160 --> 00:13:03,160 Speaker 10: said like he told people he wanted the company to 251 00:13:03,200 --> 00:13:05,520 Speaker 10: win at least three to five over the course in 252 00:13:05,559 --> 00:13:08,000 Speaker 10: the next few years. So perhaps this is the first 253 00:13:08,000 --> 00:13:08,400 Speaker 10: of many. 254 00:13:09,600 --> 00:13:12,320 Speaker 4: Let's just go into John Jumper of deep Mind and 255 00:13:12,360 --> 00:13:13,320 Speaker 4: Demis Haseb. 256 00:13:14,360 --> 00:13:14,800 Speaker 7: What is it. 257 00:13:14,800 --> 00:13:16,760 Speaker 3: It's the Alpha fold work that they did. 258 00:13:16,880 --> 00:13:20,160 Speaker 4: Is that really what's pushed them to this first of 259 00:13:20,200 --> 00:13:22,800 Speaker 4: what maybe Demis hopes will be many Nobel prizes. 260 00:13:24,080 --> 00:13:26,000 Speaker 10: I think so, I mean, this is my understanding of Demosis. 261 00:13:26,080 --> 00:13:31,160 Speaker 10: Priority has been using AI for science. You know, it's 262 00:13:31,200 --> 00:13:35,480 Speaker 10: certainly been overshadowed by chat, Gibt and generative AI. And 263 00:13:35,520 --> 00:13:37,920 Speaker 10: there's some when we've done some reporting about how some 264 00:13:37,960 --> 00:13:40,679 Speaker 10: of this work has been overshadowed inside of Google and 265 00:13:40,760 --> 00:13:43,760 Speaker 10: deep Mind right where they have I think for commercial 266 00:13:43,760 --> 00:13:48,120 Speaker 10: reasons shifted a lot of their research priorities towards Gemini 267 00:13:48,320 --> 00:13:49,400 Speaker 10: and towards generative AI. 268 00:13:50,040 --> 00:13:51,439 Speaker 7: But they obviously I still have as a. 269 00:13:51,440 --> 00:13:55,080 Speaker 10: Team working on on Alpha Fold. They've commercialized or trying 270 00:13:55,120 --> 00:13:59,000 Speaker 10: to commercialize that rather with this new alphabet company Isomorphic 271 00:13:59,080 --> 00:14:02,319 Speaker 10: Labs that Demis and his spare time also runs. 272 00:14:03,320 --> 00:14:04,160 Speaker 7: And that's when we said. 273 00:14:04,160 --> 00:14:06,880 Speaker 10: They did a press conference Demis and John Jumper this 274 00:14:06,920 --> 00:14:09,840 Speaker 10: afternoon about this prize, and you know, one of the 275 00:14:09,840 --> 00:14:12,680 Speaker 10: things they talked about was just was the continued work 276 00:14:12,679 --> 00:14:13,800 Speaker 10: around drug discovery. 277 00:14:15,240 --> 00:14:18,640 Speaker 5: Elsewhere in Nobel Prize winners, Jeffrey Hinton won the prize 278 00:14:18,640 --> 00:14:21,880 Speaker 5: for physics his work on neural nets, and in a 279 00:14:21,920 --> 00:14:24,600 Speaker 5: presser he threw a bit of shade listen to this. 280 00:14:26,040 --> 00:14:31,520 Speaker 11: So I was particularly fortunate to have many very clever students, 281 00:14:31,600 --> 00:14:35,760 Speaker 11: much cleverer than me, who actually made things work. They've 282 00:14:35,800 --> 00:14:39,520 Speaker 11: gone on to do great things. I'm particularly proud of 283 00:14:39,560 --> 00:14:42,080 Speaker 11: the fact that one of my students fired Sam Oltman. 284 00:14:43,240 --> 00:14:45,720 Speaker 5: Particularly proud that one of his students fired Sam Outman. 285 00:14:45,920 --> 00:14:48,280 Speaker 5: You've got a free pass. Just your comment on that, Mark. 286 00:14:50,680 --> 00:14:52,160 Speaker 7: I mean, you know, I guess the karma. 287 00:14:52,160 --> 00:14:54,120 Speaker 10: It would be a great luxury to be one of 288 00:14:54,120 --> 00:14:57,200 Speaker 10: the most senior respected scientists in your field, pretty much 289 00:14:57,440 --> 00:14:58,440 Speaker 10: quite blancheous anything. 290 00:14:58,440 --> 00:15:00,960 Speaker 7: But even then, I think, I mean, he was at Google. 291 00:15:01,040 --> 00:15:04,240 Speaker 10: He has fascinating history, right he left left Google and 292 00:15:04,280 --> 00:15:07,880 Speaker 10: talked about kind of gave a really adamant warning about 293 00:15:08,120 --> 00:15:10,720 Speaker 10: some of the dangers and risks of AI. My sense 294 00:15:10,800 --> 00:15:13,000 Speaker 10: is that, and I haven't actually spoken the jeff hinted 295 00:15:13,000 --> 00:15:15,240 Speaker 10: about this, but like he sees Demis Hasibus as a 296 00:15:15,240 --> 00:15:18,520 Speaker 10: scientist and maybe a certainly researcher, some researchers in the 297 00:15:18,560 --> 00:15:22,800 Speaker 10: field as being a scientist and some being executives and CEOs, 298 00:15:22,840 --> 00:15:25,200 Speaker 10: and maybe putting that to Camp and that's you know, 299 00:15:25,240 --> 00:15:28,360 Speaker 10: we are. Google obviously wants to marry those both those worlds, 300 00:15:28,400 --> 00:15:30,520 Speaker 10: and we'll see there's always going to be tension between 301 00:15:30,520 --> 00:15:30,800 Speaker 10: those two. 302 00:15:30,840 --> 00:15:35,720 Speaker 12: Obviously, AI really cleaning up on these Nobel Prizes, and 303 00:15:35,760 --> 00:15:38,920 Speaker 12: of course Jeffrey Hinton was mentioning about Elias at Skiver, 304 00:15:39,480 --> 00:15:42,920 Speaker 12: of course in his role within the Sam Altman Auster matt. 305 00:15:42,680 --> 00:15:45,120 Speaker 3: Berg and we thank you so much. Also in the 306 00:15:45,160 --> 00:15:46,800 Speaker 3: AI space, let's talk about it. 307 00:15:46,880 --> 00:15:49,880 Speaker 4: Some Alman's Open Ai being accused by even Mask of 308 00:15:49,880 --> 00:15:52,560 Speaker 4: harassment in a legal fight that's unfolding as a startup 309 00:15:52,600 --> 00:15:55,400 Speaker 4: ways a plan to shift to a for profit business model. 310 00:15:55,800 --> 00:15:58,240 Speaker 4: Musk filed a complaint in August claiming that open AI's 311 00:15:58,280 --> 00:16:02,000 Speaker 4: co founders manipulated him into investing in the startup, which 312 00:16:02,040 --> 00:16:06,000 Speaker 4: at the start was a nonprofit. Numbers Multinag now joins 313 00:16:06,040 --> 00:16:10,160 Speaker 4: us to explain that back and forth here because there 314 00:16:10,200 --> 00:16:13,760 Speaker 4: have been other legal wranglings between en Or Musk and 315 00:16:14,000 --> 00:16:17,360 Speaker 4: open Ai and open AI now saying, look, you're harassing us. 316 00:16:19,200 --> 00:16:21,720 Speaker 13: Yes, you know, open AI and Musk are now added again. 317 00:16:22,000 --> 00:16:25,400 Speaker 13: This time open AI is lashing back at Musk's lawsuit 318 00:16:25,440 --> 00:16:28,240 Speaker 13: which was fired in August, and saying, you know this 319 00:16:28,680 --> 00:16:34,640 Speaker 13: is harassment. You know, we've been accused of corruption and 320 00:16:34,800 --> 00:16:38,120 Speaker 13: racketeering here. And what they're seeing is that actually Musk 321 00:16:38,280 --> 00:16:41,800 Speaker 13: is doing this to gain a competitive advantage with this XAI. 322 00:16:42,320 --> 00:16:43,480 Speaker 3: So they're saying we're being. 323 00:16:43,440 --> 00:16:46,800 Speaker 13: Harris chair and they've asked a judge actually to throw 324 00:16:46,840 --> 00:16:50,600 Speaker 13: out this lawsuit. So yeah, this sort of saga continues, 325 00:16:50,840 --> 00:16:53,320 Speaker 13: and we'll have to see what happens in terms of 326 00:16:53,680 --> 00:16:56,320 Speaker 13: whether this suit survives in quote or not. 327 00:16:58,280 --> 00:17:03,360 Speaker 5: Multi So open AI is accusing Elon Mask of harassment, 328 00:17:03,520 --> 00:17:07,440 Speaker 5: and Elon Musk is saying that this is a textbook 329 00:17:07,480 --> 00:17:11,360 Speaker 5: tale of altruism versus greed. The bit that I'm struggling 330 00:17:11,480 --> 00:17:15,119 Speaker 5: with is what is Elon Musk trying to achieve? What 331 00:17:15,320 --> 00:17:17,879 Speaker 5: is his end goal in the suits that he is 332 00:17:18,040 --> 00:17:20,240 Speaker 5: filing against open ai. 333 00:17:21,520 --> 00:17:21,680 Speaker 1: God. 334 00:17:21,880 --> 00:17:24,880 Speaker 13: So what he says is he feels like he's been deceived, 335 00:17:25,040 --> 00:17:27,960 Speaker 13: and you know, his lawsuit talked about deceit of Shakespeare 336 00:17:28,040 --> 00:17:31,400 Speaker 13: in proportions. So I think he appears to be hurt 337 00:17:31,440 --> 00:17:34,120 Speaker 13: here and says I've been deceived. You know, you manipulated 338 00:17:34,200 --> 00:17:37,640 Speaker 13: me into investing here. You started off with this founding 339 00:17:37,760 --> 00:17:43,320 Speaker 13: mission of being this you know, company that would benefit 340 00:17:43,440 --> 00:17:45,800 Speaker 13: human good and here you are now sort of shifting 341 00:17:45,880 --> 00:17:48,600 Speaker 13: to this for profit model. So it definitely seems like 342 00:17:48,760 --> 00:17:52,399 Speaker 13: he appears hurt in seat of the words that are 343 00:17:52,440 --> 00:17:56,960 Speaker 13: being used in the lawsuit. And what openI says is, Hey, 344 00:17:57,080 --> 00:18:00,320 Speaker 13: you're just using legal warfare here to hurt us in benefit. 345 00:18:00,240 --> 00:18:01,000 Speaker 2: Your own company. 346 00:18:01,640 --> 00:18:06,119 Speaker 13: Because this new lawsuit which was filing August, Open thee 347 00:18:06,160 --> 00:18:11,080 Speaker 13: I says, is adding on some extra more intense claim 348 00:18:11,200 --> 00:18:14,479 Speaker 13: such as racketeering and corruption. So yeah, so Open thee 349 00:18:14,480 --> 00:18:16,560 Speaker 13: Eye says, you know you're just doing this for your 350 00:18:16,600 --> 00:18:19,119 Speaker 13: own benefit and trying to court us and using the 351 00:18:19,240 --> 00:18:21,359 Speaker 13: court system to basically get. 352 00:18:21,280 --> 00:18:21,800 Speaker 3: Back at us. 353 00:18:23,320 --> 00:18:34,960 Speaker 7: Bloomberg's multi Nayek, thank you very much. Time now for 354 00:18:35,119 --> 00:18:35,880 Speaker 7: AI and action. 355 00:18:36,040 --> 00:18:39,840 Speaker 5: Let's bring in pre Cyprosord, co founder and general partner 356 00:18:39,920 --> 00:18:43,080 Speaker 5: of the newly founded venture firm Touring Capital, for a 357 00:18:43,200 --> 00:18:47,400 Speaker 5: take on how to identify the best industries for AI 358 00:18:47,560 --> 00:18:49,880 Speaker 5: investment and prayer. A lot of my work has been 359 00:18:50,359 --> 00:18:53,800 Speaker 5: looking at a wide range of let's say tech sector 360 00:18:53,840 --> 00:18:56,120 Speaker 5: subdivisions where AI is having an impact. 361 00:18:56,200 --> 00:18:57,160 Speaker 7: It can be anything from. 362 00:18:57,119 --> 00:19:02,760 Speaker 5: Software to hardware, industrial, ev, robotics, healthcare. And right now 363 00:19:03,000 --> 00:19:06,280 Speaker 5: everyone in anyone is slapping a sticker on themselves saying 364 00:19:06,760 --> 00:19:09,760 Speaker 5: we are somehow AI adjacent. But that can be an 365 00:19:09,760 --> 00:19:13,400 Speaker 5: opportunity for you. You've setting yourselves up to invest where 366 00:19:13,400 --> 00:19:14,200 Speaker 5: do you start. 367 00:19:16,080 --> 00:19:16,639 Speaker 14: Right? Right? 368 00:19:16,760 --> 00:19:19,720 Speaker 15: Definitely, Actually thank you for mentioning that. So you know, 369 00:19:19,840 --> 00:19:22,520 Speaker 15: our thesis at touring is to really partner with entrepreneurs 370 00:19:22,560 --> 00:19:26,639 Speaker 15: who are building AI enabled aidjacent software that really solves 371 00:19:26,760 --> 00:19:31,000 Speaker 15: real world problems and enhancas productivity across different industries. But 372 00:19:31,160 --> 00:19:33,280 Speaker 15: you know the answer is, how do you actually choose 373 00:19:33,320 --> 00:19:36,359 Speaker 15: which industries that are so ripe for AI? And we 374 00:19:36,520 --> 00:19:39,880 Speaker 15: typically look for industries that are general laggards and sort 375 00:19:39,920 --> 00:19:43,119 Speaker 15: of that initial wave of digital transformation and who in 376 00:19:43,200 --> 00:19:46,320 Speaker 15: a lot of cases still rely on pen, paper and excel, 377 00:19:46,760 --> 00:19:50,119 Speaker 15: and we think those are the opportunities for the most advancement, 378 00:19:50,440 --> 00:19:53,840 Speaker 15: at least the low hanging fruit that AI can initially tell. 379 00:19:55,119 --> 00:19:57,960 Speaker 4: Looking at some of the startups that you've already invested in, 380 00:19:58,119 --> 00:20:00,520 Speaker 4: we've got your put Photio up for us. Now, Pixis 381 00:20:00,600 --> 00:20:06,000 Speaker 4: that's marketing, de Looper, that's financial services, car dealership with NUMA. 382 00:20:06,119 --> 00:20:08,439 Speaker 4: I can understand why that's perhaps slow to pick up 383 00:20:08,480 --> 00:20:12,120 Speaker 4: on AI. But why do you feel that these areas are. 384 00:20:12,119 --> 00:20:14,160 Speaker 3: Right for disruption from artificial intelligence? 385 00:20:15,000 --> 00:20:18,359 Speaker 15: Yeah, no, that's a great question. So we typically use 386 00:20:18,400 --> 00:20:20,879 Speaker 15: a framework when we think of whether a particular vertical 387 00:20:20,960 --> 00:20:23,960 Speaker 15: or an industry is right for AI transformation. The first 388 00:20:23,960 --> 00:20:27,480 Speaker 15: thing that we look for is a large total addressable market, 389 00:20:27,840 --> 00:20:30,640 Speaker 15: an actual sort of friction or pain point that's really 390 00:20:30,760 --> 00:20:34,440 Speaker 15: experienced in that market. And then we again prefer relatively 391 00:20:34,520 --> 00:20:37,960 Speaker 15: old school industries who still rely on pen, paper and 392 00:20:38,080 --> 00:20:40,760 Speaker 15: excel for the most part, but are now sort of 393 00:20:40,960 --> 00:20:43,720 Speaker 15: forced to deal head on with the tailwinds from AI 394 00:20:43,840 --> 00:20:47,400 Speaker 15: adoption in order to actually remain competitive in that industry. 395 00:20:48,000 --> 00:20:50,960 Speaker 15: And lastly, we look for sort of immediate ROI that's 396 00:20:51,040 --> 00:20:54,560 Speaker 15: delivered from the product to the end user in that market, 397 00:20:54,960 --> 00:20:58,320 Speaker 15: creating sort of this strong propensity to pay. And I 398 00:20:58,400 --> 00:21:02,320 Speaker 15: always say, the best opportunities an AI often seem niche 399 00:21:02,400 --> 00:21:05,960 Speaker 15: to the industry outsider, but are sort of life changing 400 00:21:06,080 --> 00:21:09,520 Speaker 15: to that end user. And you know, as you pointed out, yeah, 401 00:21:09,840 --> 00:21:12,880 Speaker 15: as you pointed out, our investment in Numa is sort 402 00:21:12,920 --> 00:21:15,359 Speaker 15: of a great example of all of this. It's an 403 00:21:15,440 --> 00:21:19,639 Speaker 15: AI communication platform that's sort of purpose built for service 404 00:21:19,720 --> 00:21:22,000 Speaker 15: professionals like car dealerships to use. 405 00:21:23,520 --> 00:21:26,680 Speaker 5: Really really quick, not just a media ROI. But I 406 00:21:26,840 --> 00:21:29,240 Speaker 5: kind of find that companies are shrinking. You can have 407 00:21:29,320 --> 00:21:33,760 Speaker 5: a five or ten person operation that's doing well. Would 408 00:21:33,760 --> 00:21:34,560 Speaker 5: you invest there. 409 00:21:36,600 --> 00:21:38,440 Speaker 15: A five or ten person company? 410 00:21:38,520 --> 00:21:43,640 Speaker 7: You mean a start? Yeah, yeah, I have with serious money. Yeah, yeah, 411 00:21:43,720 --> 00:21:44,440 Speaker 7: absolutely So. 412 00:21:44,600 --> 00:21:47,800 Speaker 15: We typically are touring invest in Series B companies, so 413 00:21:47,960 --> 00:21:50,960 Speaker 15: companies in that early inflection growth point where you have 414 00:21:51,040 --> 00:21:54,600 Speaker 15: about three to ten million of revenues, right, so you know, 415 00:21:54,720 --> 00:21:56,560 Speaker 15: in a lot of cases it can be companies as 416 00:21:56,640 --> 00:21:59,600 Speaker 15: small as call it, fifteen employees, twenty employees. 417 00:22:00,240 --> 00:22:02,440 Speaker 7: So for sure, absolutely we're. 418 00:22:02,240 --> 00:22:03,639 Speaker 3: Going to have to wrap it up. I'm afraid. 419 00:22:03,840 --> 00:22:05,960 Speaker 4: Pria Cyprisad, thank you so much for your time. Co 420 00:22:06,119 --> 00:22:17,080 Speaker 4: founder and general partner at Touring Capital. Welcome back to 421 00:22:17,119 --> 00:22:19,840 Speaker 4: Blue Meg Technology. I'm Caroline Hyde in Los Angeles. 422 00:22:19,840 --> 00:22:21,520 Speaker 7: And Amed Lovelow in San Francisco. 423 00:22:21,640 --> 00:22:24,200 Speaker 5: A quick check in on the markets we are i'd 424 00:22:24,200 --> 00:22:27,000 Speaker 5: say modestly higher and technology is kind of leading the 425 00:22:27,040 --> 00:22:31,159 Speaker 5: way CPI data is what we're all waiting for. Semiconductors 426 00:22:31,200 --> 00:22:34,360 Speaker 5: doing well the names you'd expect, and that makes alphabet 427 00:22:34,400 --> 00:22:37,520 Speaker 5: the parent of Google's decline all the more pronounced. We've 428 00:22:37,560 --> 00:22:40,320 Speaker 5: gone big on that story in the show the preliminary 429 00:22:40,440 --> 00:22:43,840 Speaker 5: proposal of the DOJ to a judge that one option 430 00:22:44,000 --> 00:22:46,320 Speaker 5: is to break up Google in the context of antitrust. 431 00:22:46,359 --> 00:22:48,720 Speaker 5: Will continue to track it, and as we said, it 432 00:22:48,760 --> 00:22:50,960 Speaker 5: will be over a number of months that that process 433 00:22:51,080 --> 00:22:54,080 Speaker 5: plays out. Another name that I'm looking at is Tesla. 434 00:22:54,600 --> 00:22:57,760 Speaker 5: Earlier today, I broke a story with my colleague Dana 435 00:22:57,800 --> 00:23:00,520 Speaker 5: Holr and Karra Coulson that one of the things that 436 00:23:00,600 --> 00:23:04,080 Speaker 5: Elon Musk will talk about at we robot the Robotaxi 437 00:23:04,160 --> 00:23:07,119 Speaker 5: event is the pathway for FSD to be used with 438 00:23:07,200 --> 00:23:09,280 Speaker 5: semi truck. And if you look at that kind of 439 00:23:10,160 --> 00:23:13,600 Speaker 5: ten am Eastern time mark, the start went from negative 440 00:23:13,640 --> 00:23:16,679 Speaker 5: to positive territory. I think there's a lot of interest 441 00:23:16,800 --> 00:23:19,200 Speaker 5: around that story about the future of semi truck. 442 00:23:19,480 --> 00:23:21,080 Speaker 7: But we're waiting what are we going to get. 443 00:23:21,240 --> 00:23:23,639 Speaker 5: We're going to get a purpose built robotaxi of some 444 00:23:23,880 --> 00:23:27,400 Speaker 5: description that is the markets if you're just joining us elsewhere, 445 00:23:27,720 --> 00:23:30,160 Speaker 5: let's turn our attention to New York where the Citadel 446 00:23:30,200 --> 00:23:34,440 Speaker 5: Securities Global Macro Conference is underway. Bloombergsh and Ali Bassak 447 00:23:34,800 --> 00:23:37,840 Speaker 5: is with Citadel's security CEO, Pengjau. 448 00:23:37,680 --> 00:23:38,400 Speaker 7: Listening. 449 00:23:39,800 --> 00:23:44,119 Speaker 1: Through that are already had in many of these ins listens. 450 00:23:44,280 --> 00:23:47,320 Speaker 1: So I think we will see at least for this 451 00:23:47,600 --> 00:23:52,840 Speaker 1: next period an increased adoption of using AI as productivity 452 00:23:52,880 --> 00:23:56,640 Speaker 1: of tools. Internally, we're still some distance away both farm 453 00:23:56,680 --> 00:24:01,000 Speaker 1: and technological perspective, but also importantly if a regulation and 454 00:24:01,160 --> 00:24:04,679 Speaker 1: even legal perspective, and you have further clarity and perhaps 455 00:24:04,800 --> 00:24:09,680 Speaker 1: wee a few of these cases now would test our 456 00:24:09,920 --> 00:24:12,520 Speaker 1: court system and regulatory system in term of what is 457 00:24:12,600 --> 00:24:15,359 Speaker 1: going to be okay, what is going to be acceptable 458 00:24:15,640 --> 00:24:17,600 Speaker 1: when it comes down to actually bringing in generative via 459 00:24:17,760 --> 00:24:20,880 Speaker 1: technology all the way through to the user. We're still 460 00:24:20,960 --> 00:24:22,000 Speaker 1: some distance away from them. 461 00:24:22,080 --> 00:24:23,720 Speaker 14: I want to get into what would kind of break 462 00:24:23,720 --> 00:24:26,440 Speaker 14: down those limitations, what it would unlock. But before that, 463 00:24:26,800 --> 00:24:29,520 Speaker 14: you mentioned open AI. Another thing about a year ago 464 00:24:29,680 --> 00:24:32,440 Speaker 14: is many financial companies would say we are hesitant to 465 00:24:32,480 --> 00:24:35,000 Speaker 14: work with a third party because of the liability, because 466 00:24:35,000 --> 00:24:37,080 Speaker 14: of the risks, and more and more you've seen more 467 00:24:37,160 --> 00:24:40,119 Speaker 14: financial services companies work with open ai, work with the 468 00:24:40,200 --> 00:24:44,080 Speaker 14: anthropic what have you? Are you working with open ai 469 00:24:44,440 --> 00:24:45,800 Speaker 14: and other players as well. 470 00:24:46,080 --> 00:24:50,600 Speaker 1: We use we partner with most of the top providers 471 00:24:50,680 --> 00:24:54,000 Speaker 1: open ai, you know, I think from our perspective, it's 472 00:24:54,840 --> 00:24:58,680 Speaker 1: they've been valuable partners. And then the other part of 473 00:24:58,760 --> 00:25:02,200 Speaker 1: this is it's crucially important for us to be informed 474 00:25:02,280 --> 00:25:06,720 Speaker 1: on the cutting edge, even if not every upgrade and 475 00:25:06,960 --> 00:25:10,639 Speaker 1: every release every week is necessarily going to lead to 476 00:25:11,320 --> 00:25:13,920 Speaker 1: real changes for us internally, we want to be on 477 00:25:14,000 --> 00:25:16,920 Speaker 1: that releational We want to be examining that. We want 478 00:25:17,000 --> 00:25:22,480 Speaker 1: to stay up today. What is becoming possible and that's 479 00:25:22,640 --> 00:25:25,320 Speaker 1: moving every week, that's moving every week. 480 00:25:25,480 --> 00:25:26,840 Speaker 3: What is becoming possible? 481 00:25:26,920 --> 00:25:29,639 Speaker 14: What does working with open ai do for you that 482 00:25:29,680 --> 00:25:31,040 Speaker 14: you wouldn't have been able to do before. 483 00:25:32,400 --> 00:25:36,320 Speaker 1: I think some of the there's a lot of different examples. 484 00:25:36,400 --> 00:25:40,560 Speaker 1: I think some of the key workflows that was viewed 485 00:25:40,760 --> 00:25:46,800 Speaker 1: as uniquely possible if you had a lot of certain 486 00:25:46,800 --> 00:25:52,440 Speaker 1: type of talent are now being transferred from a heavily 487 00:25:53,280 --> 00:25:58,800 Speaker 1: high value, human labor intensive part of the workflow to 488 00:25:59,119 --> 00:26:06,320 Speaker 1: being heavily optimals automated. Even things like debugging right, things 489 00:26:06,560 --> 00:26:11,879 Speaker 1: like hey cold reviews, Those were things that consume the 490 00:26:12,000 --> 00:26:16,040 Speaker 1: very large amount of high value developer resources today that's 491 00:26:16,480 --> 00:26:21,199 Speaker 1: being somewhat replaced even in core areas of our model building. 492 00:26:21,359 --> 00:26:23,119 Speaker 1: I'm not going to get into a level of details. 493 00:26:23,160 --> 00:26:26,159 Speaker 1: There's a certain part of the workflow that consumes a 494 00:26:26,280 --> 00:26:31,600 Speaker 1: lot of our most valuable researcher time are also becoming 495 00:26:31,800 --> 00:26:35,880 Speaker 1: a much more automated. So again, I come back from 496 00:26:36,400 --> 00:26:44,800 Speaker 1: the perspective, less revolutionary change from the product offering perspective, 497 00:26:45,320 --> 00:26:49,959 Speaker 1: but more of a change from a productivity perspective. If 498 00:26:50,040 --> 00:26:52,320 Speaker 1: I can get if I can take this group of 499 00:26:52,920 --> 00:26:58,439 Speaker 1: thirty of the brightest, smartest, most innovative researchers in capital 500 00:26:58,480 --> 00:27:01,800 Speaker 1: market and get twenty percent of activity getting out of 501 00:27:01,800 --> 00:27:06,480 Speaker 1: these thirty, that's like hiring six international math on empirical 502 00:27:06,560 --> 00:27:09,560 Speaker 1: medalists just like that, and I'll do that every day. 503 00:27:10,040 --> 00:27:10,560 Speaker 2: Incredible. 504 00:27:10,680 --> 00:27:14,360 Speaker 14: So what does this mean in terms of your performance 505 00:27:14,400 --> 00:27:17,480 Speaker 14: as a company. You know that's been rumored forever that 506 00:27:17,880 --> 00:27:21,560 Speaker 14: Citadel Securities would seek an IPO at some juncture, And 507 00:27:21,760 --> 00:27:24,280 Speaker 14: so is this helping you kind of grow your margins 508 00:27:24,359 --> 00:27:28,080 Speaker 14: much much faster into a moment like that? 509 00:27:30,359 --> 00:27:33,360 Speaker 1: So there's two things. So well, first of all, we'll 510 00:27:33,400 --> 00:27:36,960 Speaker 1: make sure Bloomberg is well informed if we ever seriously 511 00:27:37,119 --> 00:27:43,320 Speaker 1: a considered ipel are you seriously considering no, and you 512 00:27:43,440 --> 00:27:49,760 Speaker 1: all will read it Bloomberg first, I'm sure, and putting 513 00:27:49,800 --> 00:27:51,920 Speaker 1: that aside, I like how you slip that in there, 514 00:27:54,440 --> 00:27:58,320 Speaker 1: But putting that aside, I think it goes in both ways. 515 00:27:58,560 --> 00:28:02,920 Speaker 1: I think for companies, there's certainly I would say there's 516 00:28:02,960 --> 00:28:07,679 Speaker 1: a risk for firms to not stay with the speed 517 00:28:07,840 --> 00:28:13,479 Speaker 1: of innovation, and it's not necessarily generative. Ass companies are 518 00:28:13,600 --> 00:28:17,040 Speaker 1: spending time and resources in figuring out how they can 519 00:28:17,119 --> 00:28:21,920 Speaker 1: leverage more automation and technology in increasing their productivity to 520 00:28:22,080 --> 00:28:25,600 Speaker 1: stay on that frontier, right, And the firms that cannot 521 00:28:25,680 --> 00:28:29,040 Speaker 1: keep up in doing that, not only will they not win, 522 00:28:29,119 --> 00:28:32,439 Speaker 1: they will lose. Okay, And I think the top firms 523 00:28:32,640 --> 00:28:37,879 Speaker 1: in every field, including our field, are spending a really 524 00:28:38,040 --> 00:28:41,600 Speaker 1: high quality time being very intentional in thinking about where 525 00:28:41,640 --> 00:28:45,200 Speaker 1: they're going to allocate their resources to keep up with 526 00:28:45,440 --> 00:28:50,200 Speaker 1: that innovation. At the same time, I also believe firms 527 00:28:50,280 --> 00:28:53,880 Speaker 1: like ourselves on the other end of this will win 528 00:28:54,160 --> 00:28:59,200 Speaker 1: based on our understanding of the market, Based on our understanding, 529 00:28:59,520 --> 00:29:03,440 Speaker 1: yet again, on what are the most important and most 530 00:29:03,560 --> 00:29:06,800 Speaker 1: valuable problems our clients want to solve and that market 531 00:29:06,880 --> 00:29:11,320 Speaker 1: want to solve. We are building better tools, but those 532 00:29:11,400 --> 00:29:15,720 Speaker 1: better tools will not be nearly valuable enough unless we 533 00:29:15,880 --> 00:29:18,640 Speaker 1: use them to solve the most valuable problems. And we 534 00:29:18,760 --> 00:29:22,680 Speaker 1: do need those humans going back to that to be 535 00:29:22,840 --> 00:29:23,680 Speaker 1: all things AI. 536 00:29:23,800 --> 00:29:27,560 Speaker 4: We've blue mentioned Ali, Bassek and Beans out of citydel securities. 537 00:29:27,360 --> 00:29:28,520 Speaker 1: Ed studying the market. 538 00:29:28,560 --> 00:29:30,600 Speaker 5: All right, let's get some more news in today's talking 539 00:29:30,720 --> 00:29:33,960 Speaker 5: tech and first up, social media platform X has been 540 00:29:34,040 --> 00:29:37,480 Speaker 5: ordered to release old data from twenty twenty two on 541 00:29:37,720 --> 00:29:40,880 Speaker 5: fake users that Elon Musk tried to use to back 542 00:29:40,920 --> 00:29:43,760 Speaker 5: out of the deal to buy Twitter. A Delaware judge 543 00:29:43,760 --> 00:29:47,760 Speaker 5: has ordered X to file unredacted versions of several documents, 544 00:29:47,960 --> 00:29:49,640 Speaker 5: as well as some Slack messages. 545 00:29:50,000 --> 00:29:50,240 Speaker 7: Plus. 546 00:29:50,360 --> 00:29:53,560 Speaker 5: Shares of chip maker TSMC higher today after the company 547 00:29:53,600 --> 00:29:57,160 Speaker 5: posted a better than expected thirty nine percent rise in 548 00:29:57,240 --> 00:30:00,400 Speaker 5: quarterly revenue. The main chip maker to envis year and 549 00:30:00,560 --> 00:30:04,400 Speaker 5: Apple reported September quarter sales of twenty three point six 550 00:30:04,480 --> 00:30:09,280 Speaker 5: billion dollars, calling analyst concerns that AI spending is tapering off, 551 00:30:09,400 --> 00:30:13,080 Speaker 5: and Nvidio CEO Jensen Jang says the future of AI 552 00:30:13,200 --> 00:30:17,080 Speaker 5: will be in services that can quote reason. Speaking on 553 00:30:17,160 --> 00:30:21,240 Speaker 5: a podcast hosted by arm Holding CEO Rene hass Huang 554 00:30:21,320 --> 00:30:23,560 Speaker 5: says next gent tools will be able to respond to 555 00:30:23,680 --> 00:30:27,640 Speaker 5: queries by searching and reflecting on their own conclusions, but 556 00:30:27,800 --> 00:30:30,120 Speaker 5: prefaces that it all requires. 557 00:30:29,720 --> 00:30:32,120 Speaker 7: The cost of computing to come down. 558 00:30:32,240 --> 00:30:37,120 Speaker 4: First, Caroline coming up the search for more energy maybe 559 00:30:37,600 --> 00:30:40,440 Speaker 4: in space. We speak with the co found Robin hood 560 00:30:40,760 --> 00:30:44,040 Speaker 4: Age that about his new company. He for Flux, that's 561 00:30:44,160 --> 00:31:03,520 Speaker 4: next to Bloomberg Technology. TikTok It has been sued by 562 00:31:03,640 --> 00:31:07,080 Speaker 4: over a dozen states for allegedly deceiving users about its 563 00:31:07,120 --> 00:31:09,960 Speaker 4: safety for children and for using addictive features to keep 564 00:31:10,040 --> 00:31:13,720 Speaker 4: kids on the platform longer to maximize profits. One of 565 00:31:13,760 --> 00:31:16,880 Speaker 4: those states is New Jersey, As Attorney General Matt Platkin 566 00:31:17,280 --> 00:31:20,520 Speaker 4: joins US now for more. Attorney General, why pick this 567 00:31:20,640 --> 00:31:23,320 Speaker 4: particular fight with TikTok It's already being sued by the 568 00:31:23,400 --> 00:31:26,520 Speaker 4: FEDS for child privacy issues. It might even be banned 569 00:31:26,560 --> 00:31:30,640 Speaker 4: in the United States. Tell us the underlying reason for pursuing. 570 00:31:30,240 --> 00:31:34,600 Speaker 16: This, Well, we know we're facing a youth mental health 571 00:31:34,640 --> 00:31:37,560 Speaker 16: crisis in this country, and unfortunately New Jersey is no exception. 572 00:31:38,160 --> 00:31:40,520 Speaker 16: And as we have shown in a number of actions, 573 00:31:40,960 --> 00:31:44,640 Speaker 16: we know that social media companies have knowingly targeted our 574 00:31:44,720 --> 00:31:47,680 Speaker 16: youth in ways that have damaged their mental health and 575 00:31:47,840 --> 00:31:50,840 Speaker 16: caused them real harm. And then, to make matters worse, 576 00:31:51,200 --> 00:31:53,400 Speaker 16: they've told the public that these products are safe when 577 00:31:53,400 --> 00:31:56,120 Speaker 16: they themselves know they are not. So the lawsuits that 578 00:31:56,400 --> 00:31:59,880 Speaker 16: New Jersey and several other states filed yesterday are meaning 579 00:32:00,280 --> 00:32:03,200 Speaker 16: different than the lawsuit that you reference that the Department. 580 00:32:02,920 --> 00:32:03,800 Speaker 7: Of Justices filed. 581 00:32:03,880 --> 00:32:08,000 Speaker 16: It's for violation of our state consumer laws for again 582 00:32:08,280 --> 00:32:11,240 Speaker 16: misleading the public about the safety of their products and 583 00:32:11,440 --> 00:32:16,280 Speaker 16: deliberately treating our youngest residents as nothing more than commodities. 584 00:32:18,200 --> 00:32:22,040 Speaker 4: Let's talk about what's materially different from October twenty fourth 585 00:32:22,200 --> 00:32:26,800 Speaker 4: last year, when New Jersey and other states also sued Meta, 586 00:32:26,880 --> 00:32:31,640 Speaker 4: the parent company of Instagram or Facebook, again to protect children, 587 00:32:32,000 --> 00:32:33,120 Speaker 4: mental health and the like. 588 00:32:33,760 --> 00:32:36,280 Speaker 3: How are the two actions different. What do you see 589 00:32:36,280 --> 00:32:37,360 Speaker 3: in particular with TikTok. 590 00:32:39,320 --> 00:32:43,239 Speaker 16: Well, legally, they're distinct lawsuits, and these investigations have been 591 00:32:43,400 --> 00:32:47,200 Speaker 16: underway for some time, and investigations of these kinds take time. 592 00:32:47,720 --> 00:32:51,040 Speaker 16: But as a general matter, we know that social media 593 00:32:51,120 --> 00:32:56,440 Speaker 16: companies like Meta and TikTok have targeted our youth, have 594 00:32:57,120 --> 00:33:01,720 Speaker 16: deliberately taken steps to keep our youth on their platforms 595 00:33:02,080 --> 00:33:08,480 Speaker 16: for long periods of time, have implemented features like TikTok 596 00:33:08,560 --> 00:33:11,800 Speaker 16: has with respect to body image, features that allow you 597 00:33:11,920 --> 00:33:15,280 Speaker 16: to put yourself on TikTok as if you had plastic 598 00:33:15,320 --> 00:33:19,760 Speaker 16: surgery or extensive makeup that cause real harm to kids' 599 00:33:19,760 --> 00:33:25,160 Speaker 16: mental health. That's created body dysmorphia crises and mental health crises, 600 00:33:25,200 --> 00:33:28,160 Speaker 16: particularly amongst young girls. And so in that sense, the 601 00:33:28,240 --> 00:33:31,760 Speaker 16: lawsuits are similar in that you see similar patterns across them, 602 00:33:32,440 --> 00:33:36,040 Speaker 16: but they are distinct lawsuits and Meta because the Department 603 00:33:36,080 --> 00:33:40,200 Speaker 16: of Justice had not filed a federal claim about children's 604 00:33:40,240 --> 00:33:45,040 Speaker 16: privacy in Meta, we filed a claim there under that law, 605 00:33:45,560 --> 00:33:47,960 Speaker 16: whereas the Department of Justice, as you noted, had stepped 606 00:33:48,000 --> 00:33:49,800 Speaker 16: in on TikTok, so we did not need. 607 00:33:49,800 --> 00:33:50,880 Speaker 7: To file a federal claim. 608 00:33:51,320 --> 00:33:54,640 Speaker 16: But otherwise there are some similarities across the two complaints. 609 00:33:55,600 --> 00:33:59,360 Speaker 5: Well to any general plat kid forgive me for many 610 00:33:59,440 --> 00:34:02,440 Speaker 5: of you'll constituents that that's a fair question. 611 00:34:02,800 --> 00:34:03,560 Speaker 7: What's the point. 612 00:34:04,120 --> 00:34:08,040 Speaker 5: There is a federal suit against TikTok, there's a legislative 613 00:34:08,080 --> 00:34:11,200 Speaker 5: effort to get it banned in this country, and you've 614 00:34:11,400 --> 00:34:16,360 Speaker 5: chosen a long path with this specific initiative, Why do 615 00:34:16,520 --> 00:34:18,719 Speaker 5: it if there are all those others already in place, 616 00:34:18,840 --> 00:34:21,799 Speaker 5: some of which have analogous skulls with what you're trying 617 00:34:21,840 --> 00:34:22,320 Speaker 5: to achieve. 618 00:34:23,920 --> 00:34:27,560 Speaker 16: Well, the federal lawsuit plain and simple covers different conduct. Here. 619 00:34:27,640 --> 00:34:30,840 Speaker 16: We're talking about deliberately misleading the public about the safety 620 00:34:30,880 --> 00:34:34,040 Speaker 16: of their products, about telling people that their product is 621 00:34:34,080 --> 00:34:37,279 Speaker 16: safe when they know it's not, when the United States 622 00:34:37,320 --> 00:34:40,279 Speaker 16: Surgeon General has said publicly it's not that they should 623 00:34:40,280 --> 00:34:42,800 Speaker 16: have a warning label on it. And kids are using 624 00:34:43,440 --> 00:34:46,839 Speaker 16: TikTok in particular, for hours and hours a day, when 625 00:34:46,880 --> 00:34:49,319 Speaker 16: we know just a few hours of TikTok a day 626 00:34:49,760 --> 00:34:53,759 Speaker 16: can cause significant mental health harms to our kids. Now, 627 00:34:53,800 --> 00:34:56,320 Speaker 16: I'm the state's attorney general. I'm the chief law enforcement 628 00:34:56,400 --> 00:34:59,200 Speaker 16: officer for nine point three million people. My job is 629 00:34:59,280 --> 00:35:02,520 Speaker 16: to keep them safe. And when I see a company 630 00:35:02,680 --> 00:35:06,120 Speaker 16: peddling a product targeting our youngest residents, treating them for 631 00:35:06,280 --> 00:35:09,719 Speaker 16: nothing more than dollar signs, and putting profit ahead of 632 00:35:09,760 --> 00:35:12,040 Speaker 16: their mental health, then I have an obligation to step 633 00:35:12,120 --> 00:35:15,360 Speaker 16: in and protect them. And that's what this lawsuit and 634 00:35:15,400 --> 00:35:17,239 Speaker 16: the lawsuit against Meta is doing. 635 00:35:18,280 --> 00:35:20,920 Speaker 7: Mister Patkin. If this proceeds and goes before a jury. 636 00:35:21,560 --> 00:35:26,520 Speaker 5: How will you show that what TikTok does is intentional, 637 00:35:26,800 --> 00:35:32,960 Speaker 5: that it is malicious in your accusation that they are 638 00:35:33,080 --> 00:35:34,640 Speaker 5: profiting off young users. 639 00:35:37,520 --> 00:35:40,280 Speaker 16: Well, I'm not going to speak to what we'd eventually 640 00:35:40,360 --> 00:35:42,680 Speaker 16: show at a trial, but I think our complaint lays 641 00:35:42,719 --> 00:35:48,160 Speaker 16: out very clearly what TikTok knew and the harms that 642 00:35:48,239 --> 00:35:49,640 Speaker 16: their products have caused. 643 00:35:50,040 --> 00:35:50,560 Speaker 7: Including the. 644 00:35:52,200 --> 00:35:56,680 Speaker 16: Result is that we have essentially compulsive users of TikTok 645 00:35:56,760 --> 00:36:00,800 Speaker 16: products ages thirteen to seventeen throughout our state and throughout 646 00:36:00,840 --> 00:36:03,759 Speaker 16: this country, and we know at the same time we're 647 00:36:03,800 --> 00:36:11,480 Speaker 16: experiencing a massive spike in mental health challenges for our youths, suicidal, ideation, depression, anxiety, 648 00:36:11,719 --> 00:36:15,880 Speaker 16: all up at historic levels. So we're very confident in 649 00:36:15,960 --> 00:36:18,440 Speaker 16: the case that we've brought against TikTok. We obviously wouldn't 650 00:36:18,719 --> 00:36:21,839 Speaker 16: bring a lawsuit like this if we didn't feel very 651 00:36:21,920 --> 00:36:24,960 Speaker 16: confident in our case and if we weren't prepared to 652 00:36:25,080 --> 00:36:27,080 Speaker 16: take on what is as with Meta, one of the 653 00:36:27,160 --> 00:36:30,240 Speaker 16: largest companies in the world. And my message is simple, 654 00:36:30,560 --> 00:36:31,759 Speaker 16: we're ready for that fight. 655 00:36:33,640 --> 00:36:36,359 Speaker 5: New Jersey Attorney General Matt Platkin, thank you very much 656 00:36:36,400 --> 00:36:48,240 Speaker 5: for your time. The answer to the world's energy problems 657 00:36:48,320 --> 00:36:50,960 Speaker 5: may be in space. A for Flux is a new 658 00:36:51,000 --> 00:36:55,520 Speaker 5: company with the aims of harnessing solar energy using lasers 659 00:36:55,719 --> 00:37:00,960 Speaker 5: and low Earth orbit satellites in order to deliver renewable globally. 660 00:37:02,280 --> 00:37:05,239 Speaker 5: CEO by Jubart joins us in San Francisco for more. 661 00:37:05,600 --> 00:37:09,160 Speaker 5: It's out of science fiction, but you can kind of 662 00:37:09,239 --> 00:37:12,120 Speaker 5: see it. So explain the basics of the technology, how 663 00:37:12,160 --> 00:37:12,719 Speaker 5: this would work. 664 00:37:13,120 --> 00:37:15,759 Speaker 17: Yeah, so thanks for having me on. Like I said, 665 00:37:15,800 --> 00:37:17,440 Speaker 17: the name of the company is Ether or Flux, and 666 00:37:17,520 --> 00:37:20,280 Speaker 17: the mission is to take this idea of space solar power, 667 00:37:20,719 --> 00:37:24,080 Speaker 17: which is an old NASA Department of Energy idea, and 668 00:37:24,200 --> 00:37:26,760 Speaker 17: make it a real life thing. And the basic concept 669 00:37:26,920 --> 00:37:30,279 Speaker 17: is you collect solar power and orbit and by doing 670 00:37:30,360 --> 00:37:35,520 Speaker 17: so you're able to be met down to locations virtually globally, 671 00:37:35,880 --> 00:37:38,480 Speaker 17: and by doing so address a lot of the limitations 672 00:37:38,520 --> 00:37:41,160 Speaker 17: of renewable energy and the INNERMITZI. 673 00:37:41,120 --> 00:37:43,920 Speaker 5: To address what the audience might be wondering. I know 674 00:37:44,000 --> 00:37:45,960 Speaker 5: you as one of the co founders of Robin Hoods. 675 00:37:46,719 --> 00:37:49,160 Speaker 5: Your background, though, is in physics. You have a family 676 00:37:49,239 --> 00:37:51,920 Speaker 5: tie to NASA. How did this company come about? 677 00:37:52,400 --> 00:37:56,040 Speaker 17: Yeah, so, my love of physics and space industry actually 678 00:37:56,120 --> 00:37:57,279 Speaker 17: goes back really long. 679 00:37:57,440 --> 00:37:58,600 Speaker 7: So I grew up with my. 680 00:37:58,680 --> 00:38:01,880 Speaker 17: Dad studying the United States. He worked at NASA as 681 00:38:02,320 --> 00:38:04,480 Speaker 17: when I was a kid, and I studied physics and 682 00:38:04,600 --> 00:38:07,520 Speaker 17: math at Stanford, And so I've kind of had a 683 00:38:07,640 --> 00:38:12,239 Speaker 17: love of the space industry from childhood and through building robinhood. 684 00:38:12,680 --> 00:38:16,440 Speaker 17: The passion for looking for commercial opportunities in space, how 685 00:38:16,520 --> 00:38:19,319 Speaker 17: can we make space technology useful for people on Earth 686 00:38:20,120 --> 00:38:21,880 Speaker 17: has kind of been a love of mine for a 687 00:38:21,960 --> 00:38:26,120 Speaker 17: long time, and in particular asking the question about how 688 00:38:26,160 --> 00:38:30,200 Speaker 17: can we bring natural resources from space down to Earth? 689 00:38:30,719 --> 00:38:33,560 Speaker 17: And I think energy is one of the natural choices 690 00:38:33,600 --> 00:38:35,560 Speaker 17: for that bringing it. 691 00:38:35,719 --> 00:38:37,200 Speaker 3: Down from space to Earth. 692 00:38:37,400 --> 00:38:40,239 Speaker 4: You said, beam it down, like get into the nity 693 00:38:40,320 --> 00:38:42,239 Speaker 4: and gritty, how does one beam it down? 694 00:38:43,320 --> 00:38:46,360 Speaker 17: Yeah, So the way that we're going to be transferring 695 00:38:46,400 --> 00:38:50,000 Speaker 17: power from space to Earth is actually using a constellation 696 00:38:50,080 --> 00:38:53,040 Speaker 17: of satellites in low Earth orbit, and each one collects 697 00:38:53,120 --> 00:38:56,880 Speaker 17: power and then uses infrared lasers to find a ground 698 00:38:56,920 --> 00:39:00,279 Speaker 17: station and actually transmit power down to it in the 699 00:39:00,360 --> 00:39:03,400 Speaker 17: same way that you know you collect solar power with 700 00:39:05,360 --> 00:39:08,520 Speaker 17: solar power traditional panels. With this, you'll have a bespoke 701 00:39:08,600 --> 00:39:11,719 Speaker 17: ground station that forms a connection with a satellite and 702 00:39:11,840 --> 00:39:17,400 Speaker 17: receives power from space. So where companies like SpaceX have 703 00:39:17,520 --> 00:39:21,880 Speaker 17: launched a constellation of communications satellites, this would be a 704 00:39:22,000 --> 00:39:23,680 Speaker 17: constellation of energy satellites. 705 00:39:24,960 --> 00:39:27,960 Speaker 4: You're financially backing this by you obviously, with the help 706 00:39:28,040 --> 00:39:31,400 Speaker 4: of a very successful startup you were co CEO of previously. 707 00:39:32,200 --> 00:39:34,640 Speaker 4: What is the funding that will be necessary, who will 708 00:39:34,719 --> 00:39:35,480 Speaker 4: you bring on board? 709 00:39:35,800 --> 00:39:36,799 Speaker 3: How much will this cost? 710 00:39:37,960 --> 00:39:40,640 Speaker 17: So right now the company is funded by me, but 711 00:39:40,800 --> 00:39:43,600 Speaker 17: as we grow the company, you know, we're talking about 712 00:39:43,600 --> 00:39:46,719 Speaker 17: building a large number of satellites, so it'll take more 713 00:39:46,760 --> 00:39:50,680 Speaker 17: capital to do that. In terms of the scaling of 714 00:39:50,760 --> 00:39:53,600 Speaker 17: the business. One of the opportunities that we're looking at 715 00:39:53,800 --> 00:39:56,799 Speaker 17: in the near term is going to be how can 716 00:39:56,880 --> 00:39:59,919 Speaker 17: we solve problems that are real on planet Earth today? 717 00:40:00,480 --> 00:40:03,279 Speaker 17: And the stuff that we're focusing on is how can 718 00:40:03,360 --> 00:40:07,040 Speaker 17: we deliver power to places that are either contested or 719 00:40:07,160 --> 00:40:11,320 Speaker 17: difficult to reach. So think military applications like for deployed 720 00:40:11,360 --> 00:40:14,040 Speaker 17: bases or things like remote mining applications. 721 00:40:14,160 --> 00:40:19,000 Speaker 5: Got to ask, sounds amazing, but are we talking theoretical 722 00:40:19,080 --> 00:40:21,400 Speaker 5: physics or are we talking applied physics? 723 00:40:21,680 --> 00:40:24,160 Speaker 17: Yeah, So this was one of the core ideas behind 724 00:40:24,200 --> 00:40:28,600 Speaker 17: this approach, which is we view this as a primarily 725 00:40:28,640 --> 00:40:32,400 Speaker 17: an engineering and economics problem, not a hard science problem. 726 00:40:32,560 --> 00:40:34,839 Speaker 17: So this is not the sort of company where we're 727 00:40:34,880 --> 00:40:38,080 Speaker 17: looking to make a breakthrough in science, but rather, how 728 00:40:38,120 --> 00:40:41,480 Speaker 17: can we take technologies that exist today, where even other 729 00:40:41,600 --> 00:40:45,560 Speaker 17: industries are maturing them, and use those technologies to create 730 00:40:45,640 --> 00:40:46,800 Speaker 17: something that can happen today. 731 00:40:47,440 --> 00:40:49,600 Speaker 7: You will need a launch provider to put you to 732 00:40:49,719 --> 00:40:50,000 Speaker 7: all bit. 733 00:40:50,160 --> 00:40:54,239 Speaker 5: What is your relationship with SpaceX, rocket Lab the other 734 00:40:54,440 --> 00:40:55,239 Speaker 5: providers out there? 735 00:40:55,400 --> 00:40:57,759 Speaker 17: Yeah, so we're talking to launch providers right now. We're 736 00:40:57,800 --> 00:41:02,000 Speaker 17: still in the early stages. We're talking to SpaceX, as 737 00:41:02,040 --> 00:41:06,120 Speaker 17: you mentioned, and we're targeting a launch of our first mission, 738 00:41:06,200 --> 00:41:10,560 Speaker 17: which we'll aim to demonstrate this capability Q four of 739 00:41:10,680 --> 00:41:12,160 Speaker 17: next year, Q one the year after. 740 00:41:14,440 --> 00:41:16,200 Speaker 7: Hey for flux, Sorry car go ahead. 741 00:41:17,600 --> 00:41:18,680 Speaker 3: Great to have some time with them. 742 00:41:18,880 --> 00:41:22,359 Speaker 4: I'm just envisaging lasers beaming down from space Infra red. 743 00:41:22,800 --> 00:41:27,359 Speaker 3: We appreciate it. Thank you for explaining you this edition 744 00:41:27,560 --> 00:41:29,160 Speaker 3: of Bloomberg Technology. 745 00:41:28,800 --> 00:41:34,440 Speaker 5: Ed tomorrow Bloomberg Technology is live from Los Angeles for 746 00:41:34,600 --> 00:41:35,759 Speaker 5: Bloomberg screen time. 747 00:41:36,360 --> 00:41:39,320 Speaker 7: You do not want to miss that. Just stunning lineup 748 00:41:39,400 --> 00:41:39,840 Speaker 7: of guests. 749 00:41:40,520 --> 00:41:42,960 Speaker 5: Pretty stunning lineup of guests Today's show as well, recap 750 00:41:43,040 --> 00:41:45,359 Speaker 5: it on the podcast. You know exactly where to find 751 00:41:45,400 --> 00:41:49,239 Speaker 5: it online, Apple, Spotify, iHeart, and all of the Bloomberg platforms. 752 00:41:49,920 --> 00:41:52,080 Speaker 5: The team is out in La right now. I've got 753 00:41:52,120 --> 00:41:54,759 Speaker 5: to catch a flight and join them. A few big 754 00:41:54,880 --> 00:41:57,880 Speaker 5: days of shows to come. This is Bloomberg Technology. 755 00:42:00,560 --> 00:42:04,920 Speaker 2: When he didn't show, when he didn't he