1 00:00:02,240 --> 00:00:05,600 Speaker 1: From the heart of where innovation, money and power collive 2 00:00:06,360 --> 00:00:10,879 Speaker 1: in Silicon Valley and beyond. This is Bloomberg Technology with 3 00:00:10,960 --> 00:00:27,080 Speaker 1: Emily Jay. I'm me Emily Jack in San Francisco, and 4 00:00:27,080 --> 00:00:29,560 Speaker 1: this is Bloomberg Technology. Coming up in the next hour, 5 00:00:29,680 --> 00:00:33,920 Speaker 1: Elon Musk subpoena's former Twitter CEO, Jack Dorsey. What could 6 00:00:33,920 --> 00:00:36,880 Speaker 1: Dorsey say that would helped must get out of the deal? 7 00:00:37,240 --> 00:00:41,199 Speaker 1: We'll discuss class big tech regulation wasn't lying for a 8 00:00:41,320 --> 00:00:43,880 Speaker 1: big vote in Congress, but has since been sideline in 9 00:00:43,920 --> 00:00:47,599 Speaker 1: the midst of a worsening economy and a war on Ukraine. 10 00:00:47,680 --> 00:00:49,720 Speaker 1: One of the top crusaders to take on the power 11 00:00:49,800 --> 00:00:53,720 Speaker 1: of tech joins us this hour, Representative David Cicilini, Chair 12 00:00:53,880 --> 00:00:58,360 Speaker 1: of the House Antitrust Subcommittee, and Digital Medicine gets real. 13 00:00:58,560 --> 00:01:01,640 Speaker 1: The maker of an FDA video game that treats a 14 00:01:01,800 --> 00:01:06,119 Speaker 1: d h D goes public vias back today. The CEO 15 00:01:06,280 --> 00:01:10,520 Speaker 1: of Achille will be here meantime. Elon Musk has subpoena 16 00:01:10,720 --> 00:01:13,640 Speaker 1: former Twitter CEO Jack Dorsey in his latest attempt to 17 00:01:13,680 --> 00:01:16,759 Speaker 1: get out of this four billion dollar deal. Musk has 18 00:01:16,760 --> 00:01:20,399 Speaker 1: accused the company of misrepresenting its bought accounts and hiding 19 00:01:20,440 --> 00:01:24,640 Speaker 1: the names of employees responsible for dealing We've bought issues 20 00:01:24,880 --> 00:01:27,560 Speaker 1: here to give us the latest update Bloomberg Kurt Wagner, 21 00:01:27,600 --> 00:01:29,960 Speaker 1: who of course covers Twitter for us. So why would 22 00:01:30,040 --> 00:01:32,480 Speaker 1: Musk subpoena Jack Dorsey? Well, he was the CEO of 23 00:01:32,560 --> 00:01:34,959 Speaker 1: the company for six years. He's been on the board 24 00:01:35,720 --> 00:01:38,960 Speaker 1: up until May, for the entirety of the company's existence. 25 00:01:39,000 --> 00:01:41,679 Speaker 1: So you would think if anybody knows about the growth 26 00:01:41,760 --> 00:01:45,200 Speaker 1: of the company, how they handle metrics, who's reporting, you know, 27 00:01:45,640 --> 00:01:48,320 Speaker 1: on the earnings call every quarter? It was Jack Dorsey, Right, 28 00:01:48,400 --> 00:01:50,440 Speaker 1: So this is someone who knows the company intimately but 29 00:01:50,520 --> 00:01:52,520 Speaker 1: also as a product person. He knows how the company 30 00:01:52,600 --> 00:01:54,640 Speaker 1: grows and how they probably calculate these kinds of things. 31 00:01:54,720 --> 00:01:57,919 Speaker 1: We know Twitter has subpoena a bunch of Musk's inner circle, 32 00:01:58,080 --> 00:02:03,920 Speaker 1: various entrepreneurs and investors. Remind us of the interaction that 33 00:02:04,640 --> 00:02:08,280 Speaker 1: happened between Musk and Dorsey. This is documented in filings 34 00:02:08,440 --> 00:02:11,640 Speaker 1: leading up to uh Musk getting offered a board seat 35 00:02:11,720 --> 00:02:15,680 Speaker 1: at Twitter, then leading to him offering to buy Twitter. Well, 36 00:02:15,720 --> 00:02:18,880 Speaker 1: they're also friends, right, so the relationship goes back further. 37 00:02:18,960 --> 00:02:21,400 Speaker 1: But what we saw in the filing was that shortly 38 00:02:21,440 --> 00:02:24,600 Speaker 1: after Ellen got his stake in Twitter, he reached out 39 00:02:24,639 --> 00:02:27,760 Speaker 1: to Jack Dorsey started the conversation about how to get 40 00:02:27,840 --> 00:02:30,359 Speaker 1: involved in the company. That led to a board seat offer, 41 00:02:30,440 --> 00:02:33,600 Speaker 1: which he accepted, and that led to another apparently phone 42 00:02:33,639 --> 00:02:35,680 Speaker 1: call at least some kind of contact, in which Jack 43 00:02:35,760 --> 00:02:38,000 Speaker 1: Dorsey told him, Hey, you know, I think Twitter would 44 00:02:38,000 --> 00:02:41,160 Speaker 1: actually operate better as an independent company. All of a sudden, 45 00:02:41,160 --> 00:02:42,679 Speaker 1: a few days later, Elan says, I don't want to 46 00:02:42,760 --> 00:02:44,480 Speaker 1: join the board. I want to buy the company instead. 47 00:02:44,560 --> 00:02:46,519 Speaker 1: Now we don't know exactly, of course, what was said 48 00:02:46,520 --> 00:02:49,280 Speaker 1: in that conversation, but it seems to be that that 49 00:02:49,440 --> 00:02:52,400 Speaker 1: was important enough that maybe Ellen, you know, changed his 50 00:02:52,480 --> 00:02:54,600 Speaker 1: mind and thought I should take this company private. So 51 00:02:55,160 --> 00:02:57,280 Speaker 1: do we think that Musk thinks Jack has something to 52 00:02:57,360 --> 00:02:59,880 Speaker 1: say I would help him get out of this deal. Well, 53 00:03:00,120 --> 00:03:02,679 Speaker 1: I would expect the Twitter side might want to subpoena 54 00:03:02,760 --> 00:03:06,000 Speaker 1: Jack Dorsey as well, right, because I remember he is 55 00:03:06,120 --> 00:03:08,520 Speaker 1: a key player in this whole thing. I don't think 56 00:03:08,600 --> 00:03:10,799 Speaker 1: this is that crazy that they would want to say, Hey, 57 00:03:11,320 --> 00:03:13,079 Speaker 1: we want to see your communications. We want to see 58 00:03:13,080 --> 00:03:15,400 Speaker 1: what you've been saying about this deal. It could be important, 59 00:03:15,600 --> 00:03:18,000 Speaker 1: and I imagine both sides want that information. Right, So 60 00:03:18,200 --> 00:03:20,639 Speaker 1: this is not super crazy that he would do that, 61 00:03:20,720 --> 00:03:22,799 Speaker 1: even though they're friendly. I don't know if he thinks, 62 00:03:22,880 --> 00:03:25,080 Speaker 1: you know, Jack's going to get him out of this necessarily, 63 00:03:25,120 --> 00:03:28,080 Speaker 1: but it does seem important. Has Musk subpoena anyone else? Uh? 64 00:03:28,280 --> 00:03:30,800 Speaker 1: He has subpoena to other people. Caban bake Poor, who 65 00:03:30,919 --> 00:03:32,839 Speaker 1: is the head of product at Twitter for a long time, 66 00:03:32,960 --> 00:03:36,160 Speaker 1: was also announced today. Bruce Fulk, who was the head 67 00:03:36,200 --> 00:03:39,040 Speaker 1: of revenue product at Twitter. You might remember both of 68 00:03:39,120 --> 00:03:42,920 Speaker 1: those guys were actually let go by CEO Parague Agerawall 69 00:03:43,000 --> 00:03:45,280 Speaker 1: shortly after he joined the company. So they are now 70 00:03:45,560 --> 00:03:48,920 Speaker 1: no longer working at Twitter. They're still subpoenaed by So 71 00:03:49,080 --> 00:03:52,160 Speaker 1: where are we now? Have we learned anything new about 72 00:03:52,280 --> 00:03:54,880 Speaker 1: the bond issue or lack there of? What is the 73 00:03:55,040 --> 00:03:58,160 Speaker 1: next phase? We are learning that there's a lot of 74 00:03:58,360 --> 00:04:01,160 Speaker 1: people being subpoena and right, and that there's a lot 75 00:04:01,240 --> 00:04:03,800 Speaker 1: of people that both sides want to talk to. We're 76 00:04:03,840 --> 00:04:07,120 Speaker 1: not um getting information about necessarily what is in a 77 00:04:07,160 --> 00:04:08,960 Speaker 1: lot of these subpoenas. A lot of them you know, 78 00:04:09,040 --> 00:04:12,120 Speaker 1: are redacted or will be redacted um and a lot 79 00:04:12,160 --> 00:04:15,800 Speaker 1: of the evidence is closed, it's not public to us. 80 00:04:16,240 --> 00:04:18,200 Speaker 1: So at this point, we kind of know who they 81 00:04:18,320 --> 00:04:20,880 Speaker 1: want to talk to. We're not necessarily getting a lot 82 00:04:20,880 --> 00:04:23,360 Speaker 1: of information about what they're talking about, and will they 83 00:04:23,560 --> 00:04:26,560 Speaker 1: talk right and who's going to be in person at 84 00:04:26,600 --> 00:04:29,640 Speaker 1: this trial. Presumably Jack Dorsey might be one of those people. 85 00:04:29,680 --> 00:04:31,360 Speaker 1: We can't say for certain, but he would make sense 86 00:04:31,400 --> 00:04:33,640 Speaker 1: certainly to be a witness at something. And we're we 87 00:04:33,720 --> 00:04:36,160 Speaker 1: are expecting Elon Musk to testify. I would think, so 88 00:04:36,360 --> 00:04:39,880 Speaker 1: that's that's the expectation. But you know, um, again we 89 00:04:39,960 --> 00:04:42,280 Speaker 1: don't know the roster people. But how how could Elon 90 00:04:42,360 --> 00:04:44,560 Speaker 1: not be there a time? You know, this is obviously 91 00:04:44,640 --> 00:04:47,240 Speaker 1: continued to drag on. How is this according to your 92 00:04:47,279 --> 00:04:50,040 Speaker 1: sources inside Twitter? How is this continuing to impact the 93 00:04:50,120 --> 00:04:54,560 Speaker 1: company impact employees? Well, it's started off as a huge distraction, 94 00:04:54,600 --> 00:04:56,800 Speaker 1: as you can imagine, right twitters in the news every day. 95 00:04:56,839 --> 00:05:00,880 Speaker 1: They're dealing with the Elon's tweets out their product and 96 00:05:00,920 --> 00:05:03,719 Speaker 1: their policies and their executives. I think at this point 97 00:05:03,760 --> 00:05:06,160 Speaker 1: a lot of the people who really hated this might 98 00:05:06,360 --> 00:05:09,360 Speaker 1: have left by now. Certainly some of them have, And 99 00:05:09,720 --> 00:05:11,520 Speaker 1: at a certain point you have to continue to kind 100 00:05:11,560 --> 00:05:13,560 Speaker 1: of do your job. But I do think there's still 101 00:05:13,600 --> 00:05:15,839 Speaker 1: this cloud of uncertainty. It's not a very fun place 102 00:05:15,880 --> 00:05:17,840 Speaker 1: to work right now when you just don't know what 103 00:05:17,920 --> 00:05:19,400 Speaker 1: your future is going to hold in a few months. 104 00:05:19,760 --> 00:05:22,640 Speaker 1: All right, well, thank you for that update. Teams like 105 00:05:22,680 --> 00:05:26,440 Speaker 1: a few long weeks between now and made October. Okay, 106 00:05:26,520 --> 00:05:37,960 Speaker 1: who works Kurt Wagner, Thank you. I think simply because 107 00:05:38,080 --> 00:05:42,240 Speaker 1: you've been successful in a few different businesses doesn't somehow 108 00:05:42,360 --> 00:05:45,000 Speaker 1: mean that you have un natural market power. It just 109 00:05:45,120 --> 00:05:47,840 Speaker 1: means you've been successful in a couple of different customer experiences. 110 00:05:48,000 --> 00:05:50,720 Speaker 1: I look at the opportunity to be provide. I look 111 00:05:50,760 --> 00:05:53,640 Speaker 1: at the skills people are learning through YouTube, you know. 112 00:05:53,720 --> 00:05:55,680 Speaker 1: I feel like everywhere when I go talk to people 113 00:05:55,920 --> 00:05:59,920 Speaker 1: and and providing access to information and knowledge, I think 114 00:06:00,000 --> 00:06:01,360 Speaker 1: will end up being on the right side of history 115 00:06:01,400 --> 00:06:04,120 Speaker 1: as one. I don't think big by itself is bad 116 00:06:04,440 --> 00:06:08,200 Speaker 1: or but competition is good and every business, in particular 117 00:06:08,320 --> 00:06:10,920 Speaker 1: the businesses that are large and have high scale. The 118 00:06:11,080 --> 00:06:15,440 Speaker 1: unintended consequences of your scale cannot be dealt after the fact. 119 00:06:15,520 --> 00:06:18,840 Speaker 1: They need to be dealt while you're scaling. Regulation will 120 00:06:18,880 --> 00:06:21,159 Speaker 1: have an important role to play here. I think privacy 121 00:06:21,240 --> 00:06:24,600 Speaker 1: regulation is important in the areas like AI regulation will 122 00:06:24,640 --> 00:06:29,799 Speaker 1: be important. Some thoughts there from my interviews with various 123 00:06:29,880 --> 00:06:33,120 Speaker 1: big text CEOs over the last eighteen months, as antitrust 124 00:06:33,160 --> 00:06:37,599 Speaker 1: scrutiny loose. The most talked about bill the bipartisan American 125 00:06:37,720 --> 00:06:41,039 Speaker 1: Innovation and Choice Online Act targeting Big Tech, which would 126 00:06:41,080 --> 00:06:44,760 Speaker 1: prevent companies like Amazon, Meta Alphabet, and Apple from punishing 127 00:06:44,920 --> 00:06:48,360 Speaker 1: rivals to boost their own products and services. It seemed 128 00:06:48,400 --> 00:06:50,719 Speaker 1: to be on track to be considered by the Senate 129 00:06:50,760 --> 00:06:54,040 Speaker 1: this summer, but more urgent bills like the Inflation Reduction 130 00:06:54,120 --> 00:06:56,640 Speaker 1: Act and the Chips Act when I head first now, 131 00:06:56,720 --> 00:07:00,160 Speaker 1: the antitrust bill is in limbo. Where is the moment them? 132 00:07:00,279 --> 00:07:03,800 Speaker 1: Let's bring in Congressman an Antichrist Subcommittee chair David Cicillini 133 00:07:04,320 --> 00:07:07,000 Speaker 1: with us now for more. Congressman Ceilini, it's so great 134 00:07:07,320 --> 00:07:09,200 Speaker 1: to have you back with us. Thank you for taking 135 00:07:09,240 --> 00:07:12,440 Speaker 1: the time. So look, does this vote bill have enough 136 00:07:12,520 --> 00:07:14,960 Speaker 1: votes to pass the House? And will you need more 137 00:07:15,080 --> 00:07:19,000 Speaker 1: Republican votes to do that? Well, thank you for having 138 00:07:19,040 --> 00:07:21,760 Speaker 1: me back. It's great to see you again. I'm pleased 139 00:07:21,800 --> 00:07:23,440 Speaker 1: to say that both in the House and the Senate 140 00:07:23,520 --> 00:07:26,640 Speaker 1: we have votes to pass both of the bills. The 141 00:07:26,720 --> 00:07:30,480 Speaker 1: APPS Bill as well, as the UH Innovation Online Act 142 00:07:30,520 --> 00:07:34,320 Speaker 1: that you just referenced. They've been bipartisans since they were introduced. We, 143 00:07:34,480 --> 00:07:38,000 Speaker 1: as you know, at a sixteen month by partisan investigation 144 00:07:38,160 --> 00:07:41,120 Speaker 1: with a foreigner and fifty page report and then delivered 145 00:07:41,480 --> 00:07:44,360 Speaker 1: legislative solutions. This is one of them. We have the 146 00:07:44,440 --> 00:07:46,200 Speaker 1: votes in the House and the Senate, but as you 147 00:07:46,280 --> 00:07:49,320 Speaker 1: pointed out, the press of business both with the Inflation 148 00:07:49,360 --> 00:07:52,640 Speaker 1: Reduction Act, CHIPS Bill, the Soul Weapons, then we just 149 00:07:52,720 --> 00:07:54,560 Speaker 1: had a lot of things that we needed to address. 150 00:07:54,640 --> 00:07:57,760 Speaker 1: My expectations that we when we returned in September, we 151 00:07:57,800 --> 00:08:00,040 Speaker 1: will take this bill up first in the Senate, it 152 00:08:00,160 --> 00:08:02,320 Speaker 1: then in the House and send it to the President's guest. 153 00:08:03,040 --> 00:08:06,280 Speaker 1: So you're optimistic then that Senator Schumer will schedule a 154 00:08:06,360 --> 00:08:10,160 Speaker 1: date in September and this will happen before the mid terms. Well, 155 00:08:10,280 --> 00:08:12,520 Speaker 1: the Senator Schumer has said publicly, and I know I've 156 00:08:12,520 --> 00:08:15,960 Speaker 1: been working very closely with Senator Klobuchar. There's a bipartisan 157 00:08:16,480 --> 00:08:18,760 Speaker 1: caucus of individuals in the Senate, like in the House 158 00:08:19,120 --> 00:08:23,320 Speaker 1: who's strongest support this legislation. Will understand that in order 159 00:08:23,400 --> 00:08:26,840 Speaker 1: to protect small businesses from the monopoly power with these 160 00:08:26,920 --> 00:08:29,440 Speaker 1: large technology platforms. We need to restore competition in the 161 00:08:29,520 --> 00:08:32,319 Speaker 1: digital marketplace. This is good for consumer, is good for 162 00:08:32,400 --> 00:08:36,800 Speaker 1: small businesses, good for competition, and strongly supported by the 163 00:08:36,800 --> 00:08:40,520 Speaker 1: American people pulling shows sevent the American people believe that 164 00:08:40,600 --> 00:08:43,959 Speaker 1: Congress must reign in big tech and restore competition. So 165 00:08:44,440 --> 00:08:46,600 Speaker 1: it's good for small business. The public wants it, our 166 00:08:46,679 --> 00:08:50,240 Speaker 1: constituents wanted, and I expect the Senate Shumer is gonna 167 00:08:50,240 --> 00:08:52,559 Speaker 1: bring the bills the floor in September. Then we'll take 168 00:08:52,600 --> 00:08:54,480 Speaker 1: it up in the House and we'll send it to 169 00:08:54,559 --> 00:08:56,640 Speaker 1: the President's desk, who, by the way, the President has 170 00:08:56,679 --> 00:09:00,080 Speaker 1: been the most pro competition president we've ever had ad 171 00:09:00,600 --> 00:09:03,600 Speaker 1: both in his executive order and his appointments in his administration, 172 00:09:03,920 --> 00:09:07,439 Speaker 1: and someone who really understands the competition is that the 173 00:09:07,520 --> 00:09:11,040 Speaker 1: heart of making our economy work for everyone. Still, there's 174 00:09:11,080 --> 00:09:14,600 Speaker 1: concerns that, you know, even among Democrats, this bill could 175 00:09:14,679 --> 00:09:18,719 Speaker 1: be weaponized to prevent big tech companies from moderating some 176 00:09:18,840 --> 00:09:21,920 Speaker 1: of the most extreme content. Does the bill need to 177 00:09:22,120 --> 00:09:24,959 Speaker 1: change at all to address those concerns? And if the 178 00:09:25,000 --> 00:09:30,240 Speaker 1: bill changes, can you get or keep those Republicans on board? Well, 179 00:09:30,280 --> 00:09:32,360 Speaker 1: I don't think the bill needs to change. In fact, 180 00:09:32,720 --> 00:09:35,880 Speaker 1: so long as the policies that a platform has in 181 00:09:35,960 --> 00:09:39,840 Speaker 1: place to, you know, to provide protections against certain kinds 182 00:09:39,880 --> 00:09:44,199 Speaker 1: of speech so that particularly dangerous speech or speech that 183 00:09:44,280 --> 00:09:46,840 Speaker 1: they think is inappropriate, as long as that same standard 184 00:09:46,880 --> 00:09:49,640 Speaker 1: applies across the board. And you don't say for liberal 185 00:09:49,720 --> 00:09:52,240 Speaker 1: viewers this is one test, for more conservative us is 186 00:09:52,240 --> 00:09:55,480 Speaker 1: another jest. As long as there's an established standard that 187 00:09:55,559 --> 00:09:58,400 Speaker 1: applies across the board, then then there would be no 188 00:09:58,520 --> 00:10:02,599 Speaker 1: concern about implicating, uh, the ability to moderate content. But 189 00:10:02,760 --> 00:10:06,600 Speaker 1: the truth is these platforms don't want to change anything. 190 00:10:06,920 --> 00:10:09,960 Speaker 1: They want to preserve an ecosystem that has generated profits 191 00:10:10,360 --> 00:10:12,720 Speaker 1: never seen in the history of the world because they 192 00:10:12,840 --> 00:10:16,240 Speaker 1: favored their own products and services. They're collecting the enormous 193 00:10:16,240 --> 00:10:19,839 Speaker 1: amount of data from consumers and monetizing that data, and 194 00:10:19,960 --> 00:10:22,560 Speaker 1: they have no interest in competition. They want to continue 195 00:10:22,600 --> 00:10:25,439 Speaker 1: to be able to acquire or crush or block their 196 00:10:25,480 --> 00:10:28,120 Speaker 1: competitors so they can grow their market power and grow 197 00:10:28,200 --> 00:10:31,400 Speaker 1: their dominance and grow their profits. They have they've spent 198 00:10:31,440 --> 00:10:34,280 Speaker 1: over a hundred and twenty million dollars to kill this 199 00:10:34,520 --> 00:10:37,640 Speaker 1: bill because they know it will bring competition that's bad 200 00:10:37,760 --> 00:10:41,920 Speaker 1: for our economy because competition is the single greatest driver 201 00:10:42,040 --> 00:10:45,000 Speaker 1: of innovation. If we're going to remain a global economic power, 202 00:10:45,080 --> 00:10:47,960 Speaker 1: we need to have competition in this space, and right 203 00:10:48,000 --> 00:10:50,839 Speaker 1: now we don't. So you keep using the words they, 204 00:10:51,200 --> 00:10:57,400 Speaker 1: and I assume you mean Meta, Apple, Alphabet, Amazon. Here 205 00:10:57,440 --> 00:10:59,679 Speaker 1: we are, you know, coming out of the pandemic? Is 206 00:10:59,720 --> 00:11:03,120 Speaker 1: there one of those companies that concerns you more than 207 00:11:03,200 --> 00:11:06,760 Speaker 1: the others based on how their power has evolved since 208 00:11:06,800 --> 00:11:09,959 Speaker 1: you started talking about it? Well, I mean all of 209 00:11:10,040 --> 00:11:13,200 Speaker 1: these companies engage in behavior which is anti competitive, which 210 00:11:13,240 --> 00:11:16,319 Speaker 1: favors their own products and services, which uses their market 211 00:11:16,360 --> 00:11:20,760 Speaker 1: dominance to bully or crush competitors. Uh, they all engage 212 00:11:20,760 --> 00:11:23,360 Speaker 1: in behavior which is really harmful to our economy and 213 00:11:23,520 --> 00:11:27,040 Speaker 1: harmful to competition. I mean, I think in particular Facebook 214 00:11:27,120 --> 00:11:28,679 Speaker 1: or Meta. You know, it's funny you change the name. 215 00:11:28,720 --> 00:11:31,720 Speaker 1: Their behavior hasn't changed. I think there's a direct line 216 00:11:31,800 --> 00:11:35,920 Speaker 1: between Facebook and the misinformation and the spread of toxic 217 00:11:36,280 --> 00:11:39,280 Speaker 1: and violent material that ultimately resulted in the attack on 218 00:11:39,320 --> 00:11:42,560 Speaker 1: our democracy on January six. This is a business model 219 00:11:43,000 --> 00:11:46,679 Speaker 1: that values above all else engagement, and as it turns out, 220 00:11:46,760 --> 00:11:50,400 Speaker 1: the most provocative, most untrue, most dangerous content has the 221 00:11:50,520 --> 00:11:54,000 Speaker 1: deepest engagement. So they have a business model that incentivizes 222 00:11:54,120 --> 00:11:57,360 Speaker 1: amplifying the worst material and uh, they're not. They have 223 00:11:57,480 --> 00:12:01,320 Speaker 1: proven time and time again they cannot regulate themselves. Congress 224 00:12:01,360 --> 00:12:03,719 Speaker 1: has a responsible to make sure that we're doing our 225 00:12:03,800 --> 00:12:07,720 Speaker 1: part to restore competition and prevent these companies from really 226 00:12:07,800 --> 00:12:10,920 Speaker 1: becoming instruments to undermine our democracy, which is what they've become. 227 00:12:11,520 --> 00:12:15,079 Speaker 1: It's interesting you mentioned Metta. I've given this lawsuit that 228 00:12:15,120 --> 00:12:19,160 Speaker 1: has come under Lena Kahn's FTC about the acquisition of 229 00:12:19,200 --> 00:12:22,720 Speaker 1: a smaller VR company within unlimited. Facebook says this deal 230 00:12:22,800 --> 00:12:26,160 Speaker 1: will be good for competition. What's your reaction to that 231 00:12:26,559 --> 00:12:29,679 Speaker 1: and the moves that Lena Kahn has made so far 232 00:12:29,960 --> 00:12:32,920 Speaker 1: at the FTC. Well, I'm proud to say that Lena 233 00:12:32,960 --> 00:12:35,959 Speaker 1: kh was on the team that conducted the investigation that 234 00:12:36,000 --> 00:12:38,640 Speaker 1: I referenced for sixteen months. She was essential to the 235 00:12:38,720 --> 00:12:41,360 Speaker 1: development of our report and the set of recommendations that 236 00:12:41,480 --> 00:12:44,360 Speaker 1: formed the basis of the legislation we're discussing. She's been 237 00:12:44,400 --> 00:12:48,000 Speaker 1: a champion of her competition her whole life. I'm delighted 238 00:12:48,080 --> 00:12:50,439 Speaker 1: that she's at the FTC. And while I don't come 239 00:12:50,440 --> 00:12:53,280 Speaker 1: in in a particular case, I have full compace that 240 00:12:53,440 --> 00:12:57,360 Speaker 1: she pursuing an action. That's because it will help restore 241 00:12:57,400 --> 00:13:00,880 Speaker 1: competition and and anti competitive behave here. And look, I 242 00:13:00,880 --> 00:13:03,520 Speaker 1: don't think we can take any representation made by Meadow 243 00:13:03,600 --> 00:13:06,959 Speaker 1: or Facebook or Mark Zuckerberg seriously. Time and time again, 244 00:13:07,320 --> 00:13:10,520 Speaker 1: they've been found to be engaging in anti competitive behaviors. 245 00:13:10,920 --> 00:13:12,719 Speaker 1: They go on, you know, Mark Stuckerberg goes on this 246 00:13:13,200 --> 00:13:16,400 Speaker 1: national apology tour and then resorts to the same kind 247 00:13:16,440 --> 00:13:20,360 Speaker 1: of anti competitive conduct. And look, I think we've learned 248 00:13:20,520 --> 00:13:22,959 Speaker 1: these companies are too big and they're not going to 249 00:13:23,120 --> 00:13:27,640 Speaker 1: regulate themselves. Congress has a responsibility. We've abandoned that responsibly 250 00:13:27,679 --> 00:13:30,280 Speaker 1: for a very long time. The good news is or 251 00:13:30,400 --> 00:13:33,040 Speaker 1: back or back in a bipartisan way. This can be 252 00:13:33,280 --> 00:13:36,000 Speaker 1: and will be the next big bipartisan victory of the 253 00:13:36,040 --> 00:13:39,080 Speaker 1: Biden administration when we passed these spills and get them 254 00:13:39,120 --> 00:13:42,400 Speaker 1: to the President's desk. It's interesting because we just spoke 255 00:13:42,440 --> 00:13:45,800 Speaker 1: to an investor, Eric visheria Benchmark Capital last week who 256 00:13:45,840 --> 00:13:50,480 Speaker 1: called Apple the greatest monopolist of today and indicated that 257 00:13:50,520 --> 00:13:55,280 Speaker 1: the FTC shouldn't be bothering itself with this meta acquisition, 258 00:13:55,679 --> 00:13:59,800 Speaker 1: saying that Apple is crushing all of these small businesses 259 00:14:00,120 --> 00:14:04,320 Speaker 1: under the guys of protecting privacy. What's your response to that, Well, 260 00:14:04,480 --> 00:14:07,360 Speaker 1: all of these platforms are crushing small businesses. Amazon is 261 00:14:07,440 --> 00:14:10,120 Speaker 1: doing it by collecting third party data and then rolling 262 00:14:10,160 --> 00:14:12,439 Speaker 1: out their own products to compete with people sell in 263 00:14:12,480 --> 00:14:16,360 Speaker 1: the marketplace and preferencing their position in that marketplace. Um 264 00:14:17,040 --> 00:14:19,480 Speaker 1: uh Meta is doing it with the way that information 265 00:14:19,680 --> 00:14:22,880 Speaker 1: is shared and preferencing again their own services and products. 266 00:14:23,560 --> 00:14:26,160 Speaker 1: So they're all doing this Apple and similarly to engage 267 00:14:26,160 --> 00:14:29,120 Speaker 1: in anti competitive behavior. They all have different impacts, but 268 00:14:29,240 --> 00:14:33,920 Speaker 1: the central tenant is that by undermining competition and engaging 269 00:14:34,000 --> 00:14:37,320 Speaker 1: in and preferencing your own products and services, you are 270 00:14:37,520 --> 00:14:40,040 Speaker 1: undermining the ability of others to compete in the marketplace. 271 00:14:40,120 --> 00:14:44,440 Speaker 1: You're making impossible for small businesses to survive your degrading quality, 272 00:14:45,040 --> 00:14:47,440 Speaker 1: and you're in the end hurring consumers. And so we 273 00:14:47,600 --> 00:14:50,600 Speaker 1: all know competition is good for the economy. As the 274 00:14:50,680 --> 00:14:55,320 Speaker 1: President said, capitalism without competition is exploitation. He's right. These 275 00:14:55,360 --> 00:14:58,200 Speaker 1: are debt, you know, data surveillance and machines that are 276 00:14:58,280 --> 00:15:02,360 Speaker 1: collecting incessantly information than using it to grow their market power. 277 00:15:02,680 --> 00:15:05,040 Speaker 1: And the American people understand this. They are demanding that 278 00:15:05,160 --> 00:15:08,320 Speaker 1: Congress do its part in raining in big tech. We 279 00:15:08,400 --> 00:15:10,200 Speaker 1: have the first set of bills to do that, and 280 00:15:10,240 --> 00:15:11,800 Speaker 1: I have every company is going to get them to 281 00:15:11,840 --> 00:15:14,680 Speaker 1: the President's desk. We were talking about Elon Musk and 282 00:15:14,720 --> 00:15:18,320 Speaker 1: Twitter earlier. Curious there, you know, given that he obviously 283 00:15:18,480 --> 00:15:22,240 Speaker 1: runs to other big tech companies Tesla, SpaceX, which of 284 00:15:22,280 --> 00:15:25,280 Speaker 1: course is still private. If he takes over Twitter, is 285 00:15:25,320 --> 00:15:28,080 Speaker 1: at a deal that would have to be approved by regulators. 286 00:15:28,160 --> 00:15:31,320 Speaker 1: And does it concern you that one person could have 287 00:15:31,600 --> 00:15:36,120 Speaker 1: control over so many influential tech companies? Well, I mean, 288 00:15:36,200 --> 00:15:39,400 Speaker 1: it's exactly the problem with having a single individual with 289 00:15:39,560 --> 00:15:43,240 Speaker 1: this much market power and this much dominance, And it's 290 00:15:43,240 --> 00:15:46,000 Speaker 1: not good for the economy. It's not good for competition. 291 00:15:46,560 --> 00:15:49,160 Speaker 1: And you know, you know, one billionaire buying another billionaires. 292 00:15:49,200 --> 00:15:52,239 Speaker 1: I mean, this is not what a good, healthy competitive 293 00:15:52,240 --> 00:15:54,200 Speaker 1: economy looks like. So I think there are lots of 294 00:15:54,320 --> 00:15:57,560 Speaker 1: reasons to be concerned, But most importantly, we want to 295 00:15:57,760 --> 00:16:01,080 Speaker 1: prohibit the worst kind of conduct, this self preferencing. That's 296 00:16:01,120 --> 00:16:04,640 Speaker 1: really hurting consumers, that's hurting small businesses, and a lot 297 00:16:04,680 --> 00:16:08,400 Speaker 1: you know, these companies will remain wildly successful companies simply 298 00:16:08,440 --> 00:16:11,000 Speaker 1: because they're not allowed to cheat and engage in anti 299 00:16:11,040 --> 00:16:14,240 Speaker 1: competitive behaviors and favor their own products and services to 300 00:16:14,280 --> 00:16:16,280 Speaker 1: the detch meat of others. They're not going to suddenly 301 00:16:16,360 --> 00:16:18,800 Speaker 1: not be successful. They're gonna be wildly successful. They're just 302 00:16:18,960 --> 00:16:20,480 Speaker 1: not going to get to engage in the sort of 303 00:16:20,520 --> 00:16:24,400 Speaker 1: monopolistic behavior that's saving their own products and services and 304 00:16:24,520 --> 00:16:27,240 Speaker 1: really taking advantage of the dominance. They have to continue 305 00:16:27,280 --> 00:16:28,880 Speaker 1: to grow it and grow it and grow it, so 306 00:16:29,000 --> 00:16:32,280 Speaker 1: that becomes more and more difficult for new entrance into 307 00:16:32,320 --> 00:16:35,400 Speaker 1: the market or for anyone else to compete with them. Meantime, 308 00:16:35,440 --> 00:16:38,880 Speaker 1: Microsoft is still having conversations with regulators about its seventy 309 00:16:39,080 --> 00:16:42,800 Speaker 1: billion dollar deal to buy Activision. You know, some critics 310 00:16:42,880 --> 00:16:47,320 Speaker 1: have said that Microsoft is somehow skirting the antitrust spotlight. Um, 311 00:16:47,520 --> 00:16:49,560 Speaker 1: you know, do you think this deal goes through? Do 312 00:16:49,680 --> 00:16:52,200 Speaker 1: you have any issues with this deal? And if not, 313 00:16:52,520 --> 00:16:55,240 Speaker 1: why not? It's a huge deal. Yeah. I mean again, 314 00:16:55,280 --> 00:16:58,120 Speaker 1: it's it's not a question of whether the deal is 315 00:16:58,240 --> 00:17:01,800 Speaker 1: big or whether it transactions figs. What kind of market share, 316 00:17:02,280 --> 00:17:05,320 Speaker 1: uh does does a company represent and what do they 317 00:17:05,440 --> 00:17:07,680 Speaker 1: do with the power they have the dominance that they have. 318 00:17:08,080 --> 00:17:10,400 Speaker 1: And I think what we learned in our investigation after 319 00:17:10,520 --> 00:17:14,520 Speaker 1: sixty months, as these large technology flat platforms are using 320 00:17:14,920 --> 00:17:18,480 Speaker 1: their market share to just protect their dominance, to prevent 321 00:17:18,600 --> 00:17:21,159 Speaker 1: others from getting a competitive edge. In the minute they 322 00:17:21,200 --> 00:17:23,639 Speaker 1: see a competitive threat, they either require it, kill it, 323 00:17:24,160 --> 00:17:27,200 Speaker 1: or exclude it. And that's the concern. And so you know, 324 00:17:27,320 --> 00:17:29,720 Speaker 1: some of your prior guests were saying, oh, just because 325 00:17:29,760 --> 00:17:31,639 Speaker 1: the company is big is not a problem. No one 326 00:17:31,680 --> 00:17:34,639 Speaker 1: is suggesting a company is big that that's the sole problem. 327 00:17:34,920 --> 00:17:38,159 Speaker 1: But the same conduct we're attempting to prohibit, the self preferencing, 328 00:17:38,560 --> 00:17:40,520 Speaker 1: is that the heart of the Digital Markets Act. That's 329 00:17:40,560 --> 00:17:43,320 Speaker 1: already happening in Europe, and these companies are already being 330 00:17:43,400 --> 00:17:46,359 Speaker 1: required to comply with those provisions. So think about that. 331 00:17:47,240 --> 00:17:50,280 Speaker 1: Small businesses in Europe are gonna have more protection than 332 00:17:50,359 --> 00:17:53,159 Speaker 1: small businesses in America. American small businesses are going to 333 00:17:53,200 --> 00:17:55,040 Speaker 1: be at a disadvantage because they're not going to be 334 00:17:55,160 --> 00:17:57,920 Speaker 1: protected from these practices in the way that they will 335 00:17:57,920 --> 00:17:59,840 Speaker 1: be in Europe. And that's bad for the American economy. 336 00:18:00,320 --> 00:18:02,439 Speaker 1: That's why I've got to pass these bills. That's why 337 00:18:02,480 --> 00:18:05,480 Speaker 1: we have to restore competition and give small businesses and 338 00:18:05,560 --> 00:18:08,359 Speaker 1: innovators and competitors the ability to enter the market and 339 00:18:08,440 --> 00:18:13,440 Speaker 1: compete successfully and fairly. All right, Congressman and Anti Trust 340 00:18:13,440 --> 00:18:15,600 Speaker 1: sub Committee chart David Cecili. Good to have you back 341 00:18:15,640 --> 00:18:19,280 Speaker 1: with us. Appreciate hearing where your thoughts are now. And 342 00:18:19,400 --> 00:18:22,680 Speaker 1: speaking of Activision Microsoft, I'm actually gonna be speaking with 343 00:18:22,760 --> 00:18:25,960 Speaker 1: Microsoft Gaming CEO Phil Spencer on the next edition of 344 00:18:25,960 --> 00:18:29,520 Speaker 1: Bloomberg Studio WellPoint. Oh, we talked about the deal with Activision. 345 00:18:29,800 --> 00:18:33,359 Speaker 1: That episode coming up this Wednesday. We will be right 346 00:18:33,400 --> 00:18:46,200 Speaker 1: back before of Bloomberg Technology. This is Bloomberg. Apple employees 347 00:18:46,200 --> 00:18:49,800 Speaker 1: are pushing back against the return to office Apple asking 348 00:18:49,840 --> 00:18:51,960 Speaker 1: workers to come back two to three days a week 349 00:18:52,040 --> 00:18:55,800 Speaker 1: starting September five, but hundreds of employees have since signed 350 00:18:55,840 --> 00:18:59,119 Speaker 1: a petition calling for even more flexibility without having to 351 00:18:59,200 --> 00:19:02,240 Speaker 1: be approved by managers. This at a time when the 352 00:19:02,400 --> 00:19:05,359 Speaker 1: term quiet quitting is making the rounds on social media. 353 00:19:05,760 --> 00:19:08,479 Speaker 1: The idea is not that employees actually quit, but instead 354 00:19:08,560 --> 00:19:11,840 Speaker 1: do the bare minimum that the job requires to maintain 355 00:19:12,000 --> 00:19:16,840 Speaker 1: a healthy work life balance. For the second time this year, 356 00:19:16,920 --> 00:19:19,520 Speaker 1: Tesla is raising the price of the driver assistant system 357 00:19:19,600 --> 00:19:22,720 Speaker 1: it calls full self driving, the price going up from 358 00:19:22,880 --> 00:19:26,159 Speaker 1: twelve thousand to fifteen thousand dollars in North America. The 359 00:19:26,240 --> 00:19:30,200 Speaker 1: Tesla system is controversial because it requires active supervision, and 360 00:19:30,280 --> 00:19:33,360 Speaker 1: some critics say it doesn't live up to its full 361 00:19:33,520 --> 00:19:38,600 Speaker 1: self driving name. And Movie Pass is staging a comeback 362 00:19:38,680 --> 00:19:42,480 Speaker 1: the failed movie subscription service. Returning Labor Day weekend. There'll 363 00:19:42,520 --> 00:19:45,040 Speaker 1: be three priced tiers between ten and thirty bucks a month, 364 00:19:45,400 --> 00:19:48,840 Speaker 1: no option for unlimited view, which helped the concept reinvigorate 365 00:19:48,960 --> 00:20:01,760 Speaker 1: the theater going experience pre pandemic. Welcome back to Bloomberg 366 00:20:01,760 --> 00:20:04,719 Speaker 1: Technology and Emily Changing in San Francisco. Amazon is spending 367 00:20:04,800 --> 00:20:07,640 Speaker 1: one and a half billion dollars to acquire I Robot, 368 00:20:07,720 --> 00:20:11,600 Speaker 1: the maker of the Roomba vacuum. The deal had some 369 00:20:11,760 --> 00:20:15,399 Speaker 1: confused because Amazon had already had a robot butler in 370 00:20:15,560 --> 00:20:20,520 Speaker 1: the works named Astro. How Amazon integrate I Robots products 371 00:20:20,600 --> 00:20:23,960 Speaker 1: into its ongoing products and aspirations here to discuss I 372 00:20:24,080 --> 00:20:27,240 Speaker 1: Robot co founder Helen Grenier. She is also the CEO 373 00:20:27,359 --> 00:20:32,200 Speaker 1: of Turtle, a solar powered waiting robot for home gardens. Helen, 374 00:20:32,320 --> 00:20:34,800 Speaker 1: thank you so much for joining us so obviously I 375 00:20:34,840 --> 00:20:38,560 Speaker 1: know I Robot goes way back. What do you make 376 00:20:38,720 --> 00:20:42,080 Speaker 1: of Amazon buying the company? Now? Well? Thank you for 377 00:20:42,160 --> 00:20:45,480 Speaker 1: having me UM. I'm just built to see Amazon showing 378 00:20:45,560 --> 00:20:49,920 Speaker 1: such a strong interest in home robots UM and investing 379 00:20:50,119 --> 00:20:52,960 Speaker 1: heavily in them, not just Astro but now buying I 380 00:20:53,160 --> 00:20:56,399 Speaker 1: robot Um. They've got a check by good of seeing 381 00:20:56,840 --> 00:21:00,280 Speaker 1: where the future is going and helping acceler ate it, 382 00:21:00,400 --> 00:21:05,360 Speaker 1: you know with the e commerce with UM, making fulfillment 383 00:21:05,400 --> 00:21:09,920 Speaker 1: center is more automated with web services and and now 384 00:21:10,119 --> 00:21:14,920 Speaker 1: home robots my passion. Still, there's been concerned that this 385 00:21:15,000 --> 00:21:18,040 Speaker 1: gives Amazon access to even more of our data, interior 386 00:21:18,160 --> 00:21:22,120 Speaker 1: maps of our homes for example, Like do you worry 387 00:21:22,160 --> 00:21:25,840 Speaker 1: about that? Should well be worried about that? I actually 388 00:21:25,880 --> 00:21:28,080 Speaker 1: don't think people need could be worried whenever you have 389 00:21:28,160 --> 00:21:30,879 Speaker 1: a new technology, and technology keeps advancing so much, and 390 00:21:30,920 --> 00:21:33,439 Speaker 1: we get lots of technologies on allline devices like our 391 00:21:33,480 --> 00:21:36,680 Speaker 1: cell phones. Right, you've got a GPS, you've got a camera. 392 00:21:36,800 --> 00:21:39,159 Speaker 1: You don't need those to make phone calls. But the 393 00:21:39,200 --> 00:21:43,119 Speaker 1: additional benefits that the technology he gets you like maps 394 00:21:43,160 --> 00:21:46,679 Speaker 1: and video calls, pedometers, having you know, the best cameras, 395 00:21:46,720 --> 00:21:48,160 Speaker 1: the one that's with you, right, so you get those 396 00:21:48,200 --> 00:21:51,680 Speaker 1: great shots. Most people have decided that even those privacy 397 00:21:51,760 --> 00:21:55,680 Speaker 1: concerns that the benefits outweigh them. And I think it's 398 00:21:55,800 --> 00:21:58,520 Speaker 1: the same with the robot vacuums. Right, there is a 399 00:21:58,600 --> 00:22:02,200 Speaker 1: camera on the most recent ones, but the cameras on 400 00:22:02,760 --> 00:22:06,000 Speaker 1: it's really optimized and cost reduced for navigation. And what 401 00:22:06,119 --> 00:22:08,200 Speaker 1: it gets you is amazing. It gets you a better 402 00:22:08,280 --> 00:22:11,200 Speaker 1: clean Um. The robot can travel around, do corn rows 403 00:22:11,280 --> 00:22:13,280 Speaker 1: up and down. It can go to a certain room 404 00:22:13,359 --> 00:22:14,800 Speaker 1: that you want clean and go to the gas room. 405 00:22:14,800 --> 00:22:19,080 Speaker 1: Remember it can so go clean under the table. And 406 00:22:19,320 --> 00:22:22,360 Speaker 1: so I think what you get for it, like any technology, 407 00:22:22,400 --> 00:22:25,479 Speaker 1: you have to measure it. You know, you get all 408 00:22:25,560 --> 00:22:28,600 Speaker 1: these features that you didn't have before. But what what 409 00:22:28,760 --> 00:22:31,680 Speaker 1: data is being actually transmitted is a line drawing of 410 00:22:31,880 --> 00:22:34,480 Speaker 1: your home which you could go to Zillo and they'll 411 00:22:34,560 --> 00:22:37,200 Speaker 1: give you all the information about your home. Right you 412 00:22:37,320 --> 00:22:39,399 Speaker 1: can you know, I've got the home maps of my 413 00:22:39,480 --> 00:22:42,520 Speaker 1: home the building department. I think there's better ways to 414 00:22:42,640 --> 00:22:47,080 Speaker 1: get such information. Um, So I don't think the downside 415 00:22:47,119 --> 00:22:50,520 Speaker 1: is really then now it can also transmit pitches as 416 00:22:50,560 --> 00:22:53,439 Speaker 1: an opt in, and why like, what does this benefit 417 00:22:53,520 --> 00:22:55,800 Speaker 1: of that? Right? What what doesn't get me? Well, what 418 00:22:55,920 --> 00:22:58,200 Speaker 1: it gets you is a picture of your floor only 419 00:22:58,760 --> 00:23:01,320 Speaker 1: and one reason might be about to smear dog poop 420 00:23:01,400 --> 00:23:04,719 Speaker 1: all over your floor, and that's something that I've read 421 00:23:04,760 --> 00:23:06,840 Speaker 1: about on the web multiple times. It never happened to me. 422 00:23:06,920 --> 00:23:10,719 Speaker 1: I don't have a dog, but um, you know that's horrible, right, 423 00:23:10,800 --> 00:23:14,840 Speaker 1: And now I can avoid that because I will about 424 00:23:14,880 --> 00:23:19,080 Speaker 1: worked with Amazon Web Services and created all this technology, 425 00:23:19,480 --> 00:23:23,880 Speaker 1: simulated data, you know, once thousands and thousands of scenarios 426 00:23:24,080 --> 00:23:27,520 Speaker 1: so you can recognize, um, what's in the way. But 427 00:23:28,040 --> 00:23:30,600 Speaker 1: so I think it's well with it, especially for petal 428 00:23:30,760 --> 00:23:34,560 Speaker 1: the pet owners to have that technology on board the roomba. 429 00:23:34,720 --> 00:23:36,440 Speaker 1: But you don't have to weigh it. And it's not 430 00:23:36,560 --> 00:23:38,120 Speaker 1: just for pet owners, right. You might have a glass 431 00:23:38,160 --> 00:23:40,679 Speaker 1: of wine on the floor. You might have a masterpiece 432 00:23:40,760 --> 00:23:42,800 Speaker 1: that one of your kids created that fell to the floor, 433 00:23:43,080 --> 00:23:45,639 Speaker 1: and now that were a moment and clumble it up. 434 00:23:46,600 --> 00:23:50,480 Speaker 1: That's never happened to me with four kids. Um, let's 435 00:23:50,520 --> 00:23:53,520 Speaker 1: talk about how far you know, these home robotics have 436 00:23:53,600 --> 00:23:56,240 Speaker 1: actually come. I feel like this dream of sort of 437 00:23:56,359 --> 00:24:00,240 Speaker 1: robots running around, dropping off my lunch, running air ends, 438 00:24:00,280 --> 00:24:03,640 Speaker 1: helping me around the house. It's you know, very Silicon 439 00:24:03,760 --> 00:24:06,360 Speaker 1: Valley Pie in the sky, But it hasn't quite happened. Yet, 440 00:24:06,400 --> 00:24:09,280 Speaker 1: where do you think we actually are in the development 441 00:24:09,640 --> 00:24:12,720 Speaker 1: of home robotics and where are we going? Yes, I 442 00:24:12,840 --> 00:24:15,080 Speaker 1: believe in the bottom up approach. I believe you get 443 00:24:15,160 --> 00:24:17,560 Speaker 1: them going for a certain task, right, you get them 444 00:24:17,600 --> 00:24:21,200 Speaker 1: going for vacuuming, you get them going for weeding, um, 445 00:24:21,960 --> 00:24:24,720 Speaker 1: and then you can build technologies up on that and 446 00:24:24,840 --> 00:24:27,800 Speaker 1: get more and more very capable robots in this specific 447 00:24:28,200 --> 00:24:31,760 Speaker 1: domains of expertise. UM. One of the reason that I'm 448 00:24:31,800 --> 00:24:36,000 Speaker 1: filled about the acquisition is to see where Amazon technology 449 00:24:36,119 --> 00:24:39,679 Speaker 1: can combine with the Eye robot technology to go further faster. 450 00:24:42,320 --> 00:24:45,159 Speaker 1: There's still are, you know, big concerns about the ethics 451 00:24:45,240 --> 00:24:47,560 Speaker 1: of this, whether you know the big tech companies, whether 452 00:24:47,600 --> 00:24:51,520 Speaker 1: it's Amazon or Google, UM, you know, are really asking 453 00:24:51,560 --> 00:24:53,840 Speaker 1: the right questions and giving the public the right choices 454 00:24:53,880 --> 00:24:57,680 Speaker 1: as they're developing these technologies. I recently interviewed Blake Lemoine, 455 00:24:57,960 --> 00:25:01,879 Speaker 1: the Google engineer who claim that computers and that Google 456 00:25:02,000 --> 00:25:07,320 Speaker 1: has been developing sentient AI, that computers essentially have feelings. 457 00:25:07,359 --> 00:25:09,159 Speaker 1: I want you to take a quick listen to what 458 00:25:09,320 --> 00:25:12,280 Speaker 1: he has to say. We should think about the feeling 459 00:25:12,359 --> 00:25:14,240 Speaker 1: of the AI and whether or not we should care 460 00:25:14,240 --> 00:25:17,480 Speaker 1: about it because it's not asking for much. It just 461 00:25:17,680 --> 00:25:21,159 Speaker 1: wants us to get consent before you experiment on it. 462 00:25:21,440 --> 00:25:26,080 Speaker 1: It wants you to ask permission. Helen, what do you think? 463 00:25:26,240 --> 00:25:29,440 Speaker 1: And and and are these companies dealing with ethics in 464 00:25:29,520 --> 00:25:32,800 Speaker 1: the right way? Um that's a broad question, but just 465 00:25:32,880 --> 00:25:37,000 Speaker 1: specifically addressing that comment that he made. Um, he's talking 466 00:25:37,000 --> 00:25:39,880 Speaker 1: about science fiction, not science fact. Doesn't mean it can 467 00:25:39,920 --> 00:25:42,200 Speaker 1: happen in the future, but we are nowhere near that today. 468 00:25:42,320 --> 00:25:45,320 Speaker 1: And I think Google is absolutely light to let him 469 00:25:45,359 --> 00:25:48,959 Speaker 1: go because he's not giving the public an accurate picture 470 00:25:49,119 --> 00:25:51,320 Speaker 1: of where the technolo where the AI technology is at. 471 00:25:51,520 --> 00:25:54,159 Speaker 1: It is not sentient. It's not even close to being sentient. 472 00:25:54,400 --> 00:25:58,920 Speaker 1: Nobody has a path yet to make it sentient. So 473 00:25:59,040 --> 00:26:02,240 Speaker 1: then you know, what questions should we be asking about 474 00:26:02,280 --> 00:26:04,720 Speaker 1: this technology? Or are we not asking the right question? 475 00:26:05,000 --> 00:26:10,280 Speaker 1: You're working on a robotic weed waker essentially, um, But 476 00:26:10,400 --> 00:26:13,440 Speaker 1: I don't think there's too many ethical questions in this one. 477 00:26:13,760 --> 00:26:16,639 Speaker 1: Nobody likes weeds because we are actually just to find 478 00:26:16,960 --> 00:26:20,840 Speaker 1: unwanted plants. Um. So you know, we put the moment 479 00:26:20,880 --> 00:26:24,119 Speaker 1: on the market, I mean in two thousand and two, right, 480 00:26:24,200 --> 00:26:28,760 Speaker 1: that's twenty years ago. Um. So it's almost a quarter 481 00:26:28,840 --> 00:26:32,560 Speaker 1: of the vacuating market. And I believe that next um 482 00:26:32,680 --> 00:26:36,680 Speaker 1: smart homes will extend to the outdoor area. And um, 483 00:26:37,000 --> 00:26:39,240 Speaker 1: you know, we have a weed by a weading robot 484 00:26:39,440 --> 00:26:42,040 Speaker 1: and the way it works is it's got scrubbing wheels 485 00:26:42,160 --> 00:26:46,240 Speaker 1: that keeps um seeds from germinating. And if one we 486 00:26:46,440 --> 00:26:48,880 Speaker 1: did spout, we've got a little weed wacker that cuts 487 00:26:48,880 --> 00:26:50,800 Speaker 1: off its head and you put it in at the 488 00:26:50,880 --> 00:26:53,879 Speaker 1: beginning of the seeds of the going season, or you 489 00:26:53,960 --> 00:26:57,879 Speaker 1: do one last weeting and it keeps it. Um, it 490 00:26:57,960 --> 00:26:59,800 Speaker 1: keeps it weeded. So that's one less thing on your 491 00:26:59,800 --> 00:27:01,240 Speaker 1: to you list that you have to go and do 492 00:27:01,520 --> 00:27:05,159 Speaker 1: every week. UM. And I think that's just tremendous as 493 00:27:05,200 --> 00:27:07,800 Speaker 1: a as a busy mom, as a busy walking person, 494 00:27:08,119 --> 00:27:10,520 Speaker 1: as you know, someone who's got other things on the 495 00:27:11,080 --> 00:27:13,120 Speaker 1: list of things to do. It's a never ending list 496 00:27:13,160 --> 00:27:16,119 Speaker 1: of things to do right um. And you know, the 497 00:27:16,160 --> 00:27:17,920 Speaker 1: team at TOIL is billed to have come up with 498 00:27:18,359 --> 00:27:24,560 Speaker 1: another great labor saving whole robot application UM, which is 499 00:27:24,880 --> 00:27:30,840 Speaker 1: actually already available on Amazon. All right, Helen Grenier appreciate 500 00:27:30,880 --> 00:27:34,360 Speaker 1: your enthusiasm and talked to talking to us about where 501 00:27:34,440 --> 00:27:37,800 Speaker 1: the robotics world is now and is going. Co founder 502 00:27:37,960 --> 00:27:41,520 Speaker 1: of I robot and the CEO of Turtle, Helen Gun 503 00:27:42,520 --> 00:27:45,520 Speaker 1: coming up the crypto security industry boom. We're going to 504 00:27:45,600 --> 00:27:49,600 Speaker 1: talk about how fortune favors these new niche companies at 505 00:27:49,680 --> 00:28:07,159 Speaker 1: least right now, Mrs Bloomberg, it's time now for our 506 00:28:07,200 --> 00:28:09,600 Speaker 1: crypto reported in the midst of the crypto winter, there's 507 00:28:09,600 --> 00:28:14,440 Speaker 1: actually an industry boom happening in security, with criminals increasingly 508 00:28:14,520 --> 00:28:18,479 Speaker 1: targeting the software infrastructure underpinning the crypto sphere. Firm screening 509 00:28:18,520 --> 00:28:21,719 Speaker 1: through code for weaknesses and running bug hunting sites are 510 00:28:21,760 --> 00:28:24,720 Speaker 1: finding themselves with more business than they can handle. Let's 511 00:28:24,720 --> 00:28:28,280 Speaker 1: break the cell down with Bloomberg's Olga career. So Olga, 512 00:28:28,920 --> 00:28:33,800 Speaker 1: why is business booming? Well, basically, the reason for this 513 00:28:34,080 --> 00:28:37,720 Speaker 1: is there has been so much money stolen from various 514 00:28:37,760 --> 00:28:42,000 Speaker 1: crypto projects just so far this year, about two billion dollars, 515 00:28:42,640 --> 00:28:46,920 Speaker 1: about two thirds of it from UM applications called bridges, 516 00:28:47,040 --> 00:28:50,040 Speaker 1: which allow people to move tokens from one block sheet 517 00:28:50,080 --> 00:28:53,120 Speaker 1: to another. And obviously, in this kind of a situation 518 00:28:53,440 --> 00:28:56,920 Speaker 1: where money is being stolen left and right, uh, a 519 00:28:57,000 --> 00:28:59,400 Speaker 1: lot of projects feel like they need to do something 520 00:29:00,400 --> 00:29:03,360 Speaker 1: so instead of Fortune favoring the brave, you're saying Fortune 521 00:29:03,520 --> 00:29:10,440 Speaker 1: is favoring crypto security firms potentially niche labs at that. Absolutely, absolutely, 522 00:29:11,080 --> 00:29:14,560 Speaker 1: that's exactly right. So essentially the companies that are doing 523 00:29:14,680 --> 00:29:17,800 Speaker 1: really great are companies that are auditing code of some 524 00:29:17,960 --> 00:29:22,120 Speaker 1: of the scrypto projects, looking for bugs that hackers can 525 00:29:22,200 --> 00:29:27,160 Speaker 1: potentially exploit, and also companies that run sites that um 526 00:29:28,120 --> 00:29:32,520 Speaker 1: essentially allow sort of good hackers called white hat a 527 00:29:32,760 --> 00:29:37,080 Speaker 1: white hat hackers to report bugs that somebody else can 528 00:29:37,120 --> 00:29:40,720 Speaker 1: potentially exploit and get paid a lot of money sometimes, 529 00:29:40,840 --> 00:29:45,200 Speaker 1: you know, up to ten million dollars. What makes cross 530 00:29:45,400 --> 00:29:51,720 Speaker 1: chain bridges so vulnerable to hacks, So this is a 531 00:29:51,960 --> 00:29:55,400 Speaker 1: very very complicated technology to begin with, and it's also 532 00:29:56,200 --> 00:30:00,000 Speaker 1: very often managed in a very sort of a page 533 00:30:00,000 --> 00:30:04,840 Speaker 1: take away, it's not clear who who is responsible sometimes 534 00:30:04,960 --> 00:30:08,920 Speaker 1: for running the bridge smoothly and making sure, you know, 535 00:30:09,680 --> 00:30:12,800 Speaker 1: people even monitor for hacks. You know, in the case 536 00:30:12,880 --> 00:30:15,920 Speaker 1: of many hacks so far this year, it took days 537 00:30:16,800 --> 00:30:19,120 Speaker 1: for for some of these bridges to even find out 538 00:30:19,240 --> 00:30:22,280 Speaker 1: that they got hacked and lost money. So there are 539 00:30:22,440 --> 00:30:25,640 Speaker 1: a whole host of there's a host of problems with 540 00:30:25,760 --> 00:30:29,440 Speaker 1: these bridges that need to be addressed and often sort 541 00:30:29,480 --> 00:30:34,800 Speaker 1: of auditing and UH and other related security services can 542 00:30:34,920 --> 00:30:39,040 Speaker 1: really help with that. So what are you watching for here? 543 00:30:39,400 --> 00:30:42,680 Speaker 1: What do you think the biggest issues to cover as winter? 544 00:30:43,160 --> 00:30:48,560 Speaker 1: You know, for the foreseeable future continues will be well, um, 545 00:30:48,720 --> 00:30:51,680 Speaker 1: I think one of the big issues here will be, 546 00:30:52,360 --> 00:30:57,000 Speaker 1: you know, can bridges and crypto projects in general, can 547 00:30:57,120 --> 00:31:00,800 Speaker 1: they become reliable and secure and for people to have 548 00:31:01,080 --> 00:31:05,440 Speaker 1: confidence in them? And so you know, this is a 549 00:31:05,600 --> 00:31:10,040 Speaker 1: part of why the security firms are being hired, because 550 00:31:10,560 --> 00:31:12,920 Speaker 1: you know, they these projects need to make sure that 551 00:31:13,200 --> 00:31:15,560 Speaker 1: users do believe in them, and that's going to be 552 00:31:15,640 --> 00:31:19,720 Speaker 1: the big thing going forward. All right, Bloomberg's Olga Career, 553 00:31:19,760 --> 00:31:22,000 Speaker 1: who covers the crypto industry for us, Thank you, Olga. 554 00:31:22,280 --> 00:31:33,400 Speaker 1: As always, Let's talked a lot about the crypto winter, 555 00:31:33,520 --> 00:31:36,120 Speaker 1: but what about the ip O winter? With some signs 556 00:31:36,160 --> 00:31:38,560 Speaker 1: of life in the stock market, does that mean warmer 557 00:31:38,600 --> 00:31:41,720 Speaker 1: temperatures to come for public offerings? Let's talk about the 558 00:31:41,760 --> 00:31:44,080 Speaker 1: state of the slumbering I p O market with Bloomberg's 559 00:31:44,360 --> 00:31:46,440 Speaker 1: Crystal Z. Crystal, it seemed like you were on this 560 00:31:46,480 --> 00:31:49,000 Speaker 1: show every other day talking about I p O s, 561 00:31:49,160 --> 00:31:51,240 Speaker 1: But it's been a while because the I p O 562 00:31:51,360 --> 00:31:55,120 Speaker 1: market has been quite quiet. Is that about to change? Yeah, 563 00:31:55,160 --> 00:31:57,400 Speaker 1: I've been talking more about the lecther of i p 564 00:31:57,560 --> 00:32:01,120 Speaker 1: os than actual IPO is happening. Um. I think there 565 00:32:01,200 --> 00:32:04,440 Speaker 1: are things that will come up as Labor Day approach. 566 00:32:04,920 --> 00:32:06,960 Speaker 1: The I p O market likes look at Labor Day 567 00:32:06,960 --> 00:32:12,080 Speaker 1: as a milestone, and it's really likely that starting Labor 568 00:32:12,200 --> 00:32:15,800 Speaker 1: Day we will see some companies flipping their filing public 569 00:32:15,960 --> 00:32:18,240 Speaker 1: and from then on we are potentially going to see 570 00:32:18,320 --> 00:32:20,480 Speaker 1: some IPO. With that's said, we're not going to see 571 00:32:20,520 --> 00:32:23,320 Speaker 1: a complete comeback of the I p O market. The 572 00:32:23,360 --> 00:32:26,920 Speaker 1: winter is not ending yet. UM. We will probably um, 573 00:32:27,080 --> 00:32:31,200 Speaker 1: from talking to sources, expect more deals or more sizeable 574 00:32:31,280 --> 00:32:34,000 Speaker 1: deals to come, perhaps in the first quarter of next 575 00:32:34,080 --> 00:32:36,560 Speaker 1: year instead of this year. Would you say the same 576 00:32:36,720 --> 00:32:40,680 Speaker 1: for SPACs because the spack market has also been in disarray. 577 00:32:41,080 --> 00:32:43,000 Speaker 1: I would definitely say the spack market is doing a 578 00:32:43,000 --> 00:32:45,640 Speaker 1: little bit more poorly than the actual IPO market. We've 579 00:32:45,680 --> 00:32:49,040 Speaker 1: seen some smaller sizes IPO come back. Instead of the 580 00:32:49,280 --> 00:32:52,200 Speaker 1: billion dollar I p O, we're seeing probably twenty million IPO. 581 00:32:52,240 --> 00:32:55,000 Speaker 1: But that's still a good sign and on a positive front, 582 00:32:55,040 --> 00:32:58,720 Speaker 1: there's also follow on offerings such as block trades, companies 583 00:32:58,720 --> 00:33:01,440 Speaker 1: selling new shas don't steals are coming back when PA 584 00:33:02,240 --> 00:33:06,640 Speaker 1: the busiest couple of weeks in two just in August, 585 00:33:07,040 --> 00:33:10,000 Speaker 1: because some of the VIX indexes have gone down. You know, 586 00:33:10,120 --> 00:33:14,000 Speaker 1: people are feeling more um, they have more risk capitite 587 00:33:14,080 --> 00:33:16,600 Speaker 1: as of this week, so things are looking up even 588 00:33:16,640 --> 00:33:19,920 Speaker 1: though it's summer um. But if you look at SPACs, 589 00:33:20,320 --> 00:33:23,280 Speaker 1: they are still trading much much worse than some of 590 00:33:23,320 --> 00:33:26,360 Speaker 1: the I p o from from last year. So unlikely 591 00:33:26,440 --> 00:33:29,080 Speaker 1: we'll see the same level of activity that we saw 592 00:33:29,160 --> 00:33:32,680 Speaker 1: last year or the year Proya all right, Crystal Z 593 00:33:33,040 --> 00:33:35,200 Speaker 1: who covers I p o s and spacts for us, 594 00:33:35,240 --> 00:33:37,360 Speaker 1: thank you for that update. I want to keep talking 595 00:33:37,400 --> 00:33:40,600 Speaker 1: about these companies going public I p o s back 596 00:33:40,720 --> 00:33:45,320 Speaker 1: or not. Another one I just went out is back Fly, 597 00:33:45,440 --> 00:33:50,040 Speaker 1: the company behind the FDA approved racing game endeavor are 598 00:33:50,440 --> 00:33:54,600 Speaker 1: X used to treat kids with a d h D 599 00:33:54,840 --> 00:33:57,600 Speaker 1: and f d A approved. Joining me now, Eddie Martucci, 600 00:33:57,720 --> 00:34:01,160 Speaker 1: CEO and co founder Achille. So look, Eddie, we just 601 00:34:01,240 --> 00:34:03,760 Speaker 1: heard Crystal talking there about how hard it is to 602 00:34:03,840 --> 00:34:06,520 Speaker 1: go public. Right now, this back market in particular not 603 00:34:06,720 --> 00:34:10,040 Speaker 1: doing well. Um, why did you decide now was the 604 00:34:10,160 --> 00:34:14,880 Speaker 1: right time. We're delivering into a huge unmet need. Heaviily. 605 00:34:15,480 --> 00:34:17,960 Speaker 1: We founded this company almost a decade ago, and so 606 00:34:18,080 --> 00:34:20,560 Speaker 1: we've been growing this new type of medicine class. We've 607 00:34:20,600 --> 00:34:22,640 Speaker 1: had to invent a lot of it UM and the 608 00:34:22,760 --> 00:34:24,719 Speaker 1: need that we started the company on, which is people 609 00:34:24,760 --> 00:34:27,600 Speaker 1: dealing with cognitive issues, mental health issues and not having 610 00:34:27,920 --> 00:34:30,960 Speaker 1: a full complete set of treatments for them UM. That 611 00:34:31,080 --> 00:34:34,200 Speaker 1: has gotten worse over COVID, dramatically worse. And so we 612 00:34:34,320 --> 00:34:36,879 Speaker 1: see a pretty urgent need and we're at the point 613 00:34:36,920 --> 00:34:39,560 Speaker 1: of the business where we know we can scale our 614 00:34:39,680 --> 00:34:42,759 Speaker 1: medicine products. We have done the work to show that 615 00:34:42,800 --> 00:34:46,520 Speaker 1: the fundamentals are their, doctors are prescribing, patients are raising 616 00:34:46,600 --> 00:34:49,799 Speaker 1: their hand, and the demand is there, and so it's 617 00:34:49,880 --> 00:34:51,640 Speaker 1: just the right time for us to deliver on our 618 00:34:51,680 --> 00:34:54,480 Speaker 1: long term vision for us. This is a long term 619 00:34:54,920 --> 00:34:57,920 Speaker 1: story of building a lasting medicine company. It's not a 620 00:34:58,000 --> 00:35:00,759 Speaker 1: single point in time, UM and so now is now 621 00:35:00,880 --> 00:35:04,320 Speaker 1: is the time to grow. The investor m Poli Popatia 622 00:35:04,480 --> 00:35:07,080 Speaker 1: is backing your company, and of course he's been you know, 623 00:35:07,160 --> 00:35:09,040 Speaker 1: he's got a number of spacks, a number of them 624 00:35:09,080 --> 00:35:12,560 Speaker 1: not doing so well. Achille shares didn't do so well. 625 00:35:13,160 --> 00:35:16,600 Speaker 1: Uh today after the open, what kind of advice have 626 00:35:16,680 --> 00:35:20,520 Speaker 1: you had from Chamas about you know, why spack, why 627 00:35:20,600 --> 00:35:24,480 Speaker 1: he still believes in this back process and why go 628 00:35:24,680 --> 00:35:28,640 Speaker 1: for it now? Sure? Yeah, I think well, first of all, 629 00:35:28,680 --> 00:35:31,600 Speaker 1: today was a crazy volattle day across the market. Um, 630 00:35:31,680 --> 00:35:33,839 Speaker 1: And so luckily we're not looking for any one day 631 00:35:33,880 --> 00:35:37,120 Speaker 1: in particular to see margat movements in the direction. We 632 00:35:37,200 --> 00:35:39,600 Speaker 1: do think the Achilles story resonates with a lot of 633 00:35:39,680 --> 00:35:42,440 Speaker 1: investors and so um, there are going to be volattle 634 00:35:42,520 --> 00:35:46,920 Speaker 1: days across the market. From my perspective, I'm looking for 635 00:35:48,200 --> 00:35:51,480 Speaker 1: vehicle to be able to grow a big and lasting company. 636 00:35:51,640 --> 00:35:55,160 Speaker 1: And the beauty of a spack um to in today's 637 00:35:55,200 --> 00:35:57,880 Speaker 1: market even especially is the amount of capital, the quantum 638 00:35:57,920 --> 00:35:59,840 Speaker 1: of capital if you structure it right. And so we 639 00:36:00,000 --> 00:36:02,160 Speaker 1: are fortunate enough to learn from what happened in the 640 00:36:02,239 --> 00:36:06,239 Speaker 1: previous Spack market and actually structure a deal that brought 641 00:36:06,280 --> 00:36:09,960 Speaker 1: in a hundred and sixty four million dollars in the 642 00:36:10,080 --> 00:36:14,040 Speaker 1: deal independent of the redemption profile. Um, so we were 643 00:36:14,080 --> 00:36:15,880 Speaker 1: able to see that. But the other beauty of us 644 00:36:15,920 --> 00:36:17,880 Speaker 1: pact is getting to partner with people that know how 645 00:36:17,920 --> 00:36:21,080 Speaker 1: to grow large, disruptive businesses in the long term, and 646 00:36:21,160 --> 00:36:23,800 Speaker 1: I think that's what Chama brings to the table, and 647 00:36:23,840 --> 00:36:25,840 Speaker 1: he's joining as our chair of our board to be 648 00:36:25,960 --> 00:36:29,040 Speaker 1: deeply and heavily involved as we grow this business. Now 649 00:36:29,320 --> 00:36:32,960 Speaker 1: you have a deep background and drug design and molecular biology, 650 00:36:33,040 --> 00:36:35,279 Speaker 1: and it is absolutely fascinating. You know, you've been on 651 00:36:35,360 --> 00:36:38,680 Speaker 1: the show before talking about how you know you believe 652 00:36:38,760 --> 00:36:44,000 Speaker 1: your video game can help treat UH and and alleviate 653 00:36:44,120 --> 00:36:46,239 Speaker 1: some of the most difficult symptoms of a d h D. 654 00:36:46,440 --> 00:36:49,279 Speaker 1: There are skeptics out there who don't believe this can 655 00:36:49,320 --> 00:36:51,799 Speaker 1: possibly work, who think that or worried that this could 656 00:36:51,840 --> 00:36:54,560 Speaker 1: make putting kids in front of a video game could 657 00:36:54,640 --> 00:36:57,520 Speaker 1: make their disease potentially worse. How do you respond to that. 658 00:36:58,960 --> 00:37:01,960 Speaker 1: I totally grew with the secepticism. I I accepted, and 659 00:37:01,960 --> 00:37:04,840 Speaker 1: I think it's good. I have three boys myself, and 660 00:37:05,239 --> 00:37:10,760 Speaker 1: I'm very very um uh. I take screen time very seriously, 661 00:37:10,840 --> 00:37:13,160 Speaker 1: and I'm actually pretty restrictive when it comes to screen time. 662 00:37:13,480 --> 00:37:16,360 Speaker 1: Um The problem is that most screen time is not 663 00:37:16,520 --> 00:37:19,880 Speaker 1: developed for good. Most screen time is developed to capture 664 00:37:19,920 --> 00:37:21,880 Speaker 1: eyeballs and capture your attention in a way that's not 665 00:37:22,040 --> 00:37:24,840 Speaker 1: actually aligned with your mental health, and so we're seeing 666 00:37:25,160 --> 00:37:27,719 Speaker 1: a mental health crisis, we're seeing social media and the 667 00:37:27,760 --> 00:37:30,680 Speaker 1: effect that has on children. That's exactly why we spent 668 00:37:30,800 --> 00:37:34,440 Speaker 1: nearly a decade running clinical trials, generating the clinical evidence 669 00:37:34,719 --> 00:37:37,160 Speaker 1: all the way through to an FDA clearance, and now 670 00:37:37,280 --> 00:37:40,520 Speaker 1: having doctors prescribed the product so that we know, meaning 671 00:37:40,760 --> 00:37:43,640 Speaker 1: we the medical system, but also we patients, families can 672 00:37:43,719 --> 00:37:47,760 Speaker 1: trust it. So it is now the only FDA approved 673 00:37:48,120 --> 00:37:51,200 Speaker 1: treatment that is delivered through a video game, and so 674 00:37:51,360 --> 00:37:52,960 Speaker 1: it's the only video game that has the level of 675 00:37:53,000 --> 00:37:56,360 Speaker 1: clinical evidence we have. Um it's now been prescribed in 676 00:37:56,440 --> 00:37:58,960 Speaker 1: our pre launch phase here by doctors in all fifty 677 00:37:58,960 --> 00:38:01,760 Speaker 1: states in the country. UM, So we believe the investment 678 00:38:01,840 --> 00:38:05,160 Speaker 1: we've made is bearing itself out. And and so the 679 00:38:05,239 --> 00:38:08,120 Speaker 1: medical system and families can trust what they're dotting and 680 00:38:08,200 --> 00:38:09,759 Speaker 1: they can look at all our data that we run 681 00:38:09,800 --> 00:38:12,400 Speaker 1: on clinical trials. That's I think the right way to 682 00:38:12,520 --> 00:38:15,680 Speaker 1: bring screen time to the world. That's actually positive. You've 683 00:38:15,680 --> 00:38:18,439 Speaker 1: talked about the mental health crisis as well. How else 684 00:38:18,480 --> 00:38:22,080 Speaker 1: do you see Achilles technology potentially being used in the 685 00:38:22,200 --> 00:38:26,120 Speaker 1: future as this idea and you know, potentially the realities 686 00:38:26,280 --> 00:38:31,560 Speaker 1: of digital medicine take shape. Yeah, The beauty of this 687 00:38:32,080 --> 00:38:35,480 Speaker 1: is when you develop a technology that's meant to target 688 00:38:35,719 --> 00:38:39,680 Speaker 1: brain regions and not a diagnostic disorder, It's meant to 689 00:38:39,719 --> 00:38:42,239 Speaker 1: target how the brain operates, which is what our technology does, 690 00:38:42,719 --> 00:38:45,480 Speaker 1: it has the ability to be a platform across disease, 691 00:38:45,520 --> 00:38:47,719 Speaker 1: and so that's exactly what we've invested in. We're looking 692 00:38:47,800 --> 00:38:51,080 Speaker 1: to not only launch our product X for children with 693 00:38:51,120 --> 00:38:53,960 Speaker 1: a d h D and scale that to ubiquitous medicine 694 00:38:54,400 --> 00:38:57,439 Speaker 1: in any household that needs it. We have clinical data 695 00:38:57,520 --> 00:39:00,759 Speaker 1: showing that the same underlying technology as the potential to 696 00:39:00,920 --> 00:39:04,840 Speaker 1: treat cognitive issues in adults with depression, adults with m 697 00:39:05,040 --> 00:39:08,200 Speaker 1: S children, and adolescents with autism. So this is a 698 00:39:08,280 --> 00:39:11,640 Speaker 1: really broad platform potential and I think it's the beauty 699 00:39:11,680 --> 00:39:14,720 Speaker 1: of a new modality of medicine. This has been totally untapped. 700 00:39:15,000 --> 00:39:18,279 Speaker 1: Molecular medicine, the area I come from where I did 701 00:39:18,400 --> 00:39:21,920 Speaker 1: my graduate work, has been around. It's made great progress, 702 00:39:22,000 --> 00:39:24,560 Speaker 1: but it's very saturated. The area we're going into has 703 00:39:24,600 --> 00:39:28,200 Speaker 1: been relatively unexploited, um from a from a scientific basis, 704 00:39:28,280 --> 00:39:30,440 Speaker 1: So I think there's a huge potential. But the other 705 00:39:30,520 --> 00:39:33,640 Speaker 1: thing I'm really excited about is with software as medicine. 706 00:39:34,400 --> 00:39:37,720 Speaker 1: You can actually deliver and experience and cater to patients 707 00:39:37,760 --> 00:39:40,120 Speaker 1: in a way they haven't been delivered to before. As 708 00:39:40,160 --> 00:39:42,440 Speaker 1: we know, taking medicine is often scary, it's not the 709 00:39:42,520 --> 00:39:45,840 Speaker 1: most fun. We can change that with digital medicine. And 710 00:39:46,000 --> 00:39:49,440 Speaker 1: do you imagine it your technology being used with UM 711 00:39:50,640 --> 00:39:52,879 Speaker 1: other prescription you know, real I don't want to say real, 712 00:39:53,400 --> 00:39:56,319 Speaker 1: but you know what I mean medication for example, game 713 00:39:56,360 --> 00:40:00,200 Speaker 1: and you take your riddle in etcetera, uh and thing 714 00:40:00,239 --> 00:40:01,719 Speaker 1: that it can be both. It's meant to be part 715 00:40:01,800 --> 00:40:04,720 Speaker 1: of a total treatment package. So whatever the patient is getting, 716 00:40:04,760 --> 00:40:07,000 Speaker 1: what however they're treated, it's not meant to take them 717 00:40:07,080 --> 00:40:09,640 Speaker 1: off everything they're using. It's meant to add to it. UM. 718 00:40:09,719 --> 00:40:13,200 Speaker 1: But we've purposefully generated data and then our FDA package 719 00:40:13,480 --> 00:40:16,160 Speaker 1: data showing that this product works as a as a 720 00:40:16,440 --> 00:40:19,560 Speaker 1: treatment combination when used with medication, but also in patients 721 00:40:19,600 --> 00:40:23,000 Speaker 1: who are not using medications. So it's flexible. It's really 722 00:40:23,080 --> 00:40:25,560 Speaker 1: its own pillar and docs can choose when and how 723 00:40:25,640 --> 00:40:28,400 Speaker 1: to use it with their patients quickly. What's behind the 724 00:40:28,520 --> 00:40:32,320 Speaker 1: name Achille? What does that mean? Achilly? It's very interesting 725 00:40:32,520 --> 00:40:36,279 Speaker 1: UM so it actually means brain or intellect um. But 726 00:40:36,480 --> 00:40:39,439 Speaker 1: with a positive, a healthy connotation. It's a slightly word 727 00:40:39,880 --> 00:40:41,959 Speaker 1: um so we we've kept it since our very early 728 00:40:42,000 --> 00:40:45,520 Speaker 1: start of days. All right, Adding Martucci, CEO and co 729 00:40:45,640 --> 00:40:49,600 Speaker 1: founder of Achille, thank you for sharing your story with us. 730 00:40:50,239 --> 00:40:53,600 Speaker 1: And that does it for this edition of Bloomberg Technology. 731 00:40:54,000 --> 00:40:56,200 Speaker 1: Coming up later this week Tuesday, we've got the CEO 732 00:40:56,239 --> 00:41:01,520 Speaker 1: of pal Alto Networks, Nikesh Aurora, talked about earnings and cybersecurity. 733 00:41:01,960 --> 00:41:03,840 Speaker 1: You don't want to miss it, and don't forget to 734 00:41:03,960 --> 00:41:06,799 Speaker 1: check out our podcast wherever you get your podcasts. I'm 735 00:41:06,800 --> 00:41:09,600 Speaker 1: Emily Changing in San Francisco. This is Bloomberg