1 00:00:02,600 --> 00:00:09,880 Speaker 1: Bloomberg Audio Studios, podcasts, radio news from. 2 00:00:09,720 --> 00:00:13,159 Speaker 2: The heart where innovation, money and power co lie in 3 00:00:13,240 --> 00:00:14,200 Speaker 2: Silicon Valley. 4 00:00:14,320 --> 00:00:14,720 Speaker 3: NBN. 5 00:00:15,080 --> 00:00:19,600 Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow. 6 00:00:33,080 --> 00:00:36,080 Speaker 4: Live from New York and San Francisco. This is Bloomberg Technology. 7 00:00:36,400 --> 00:00:39,400 Speaker 5: Coming up, we'll have full coverage on the aftermath the 8 00:00:39,479 --> 00:00:41,479 Speaker 5: attack on former President Donald Trump. 9 00:00:41,720 --> 00:00:44,520 Speaker 4: That says the RNC kicks off in Milwaukee. 10 00:00:44,560 --> 00:00:46,440 Speaker 6: And we'll turn our attention to M and A. 11 00:00:46,440 --> 00:00:49,600 Speaker 7: It's Google Eyes Whiz for its biggest ever acquisition. 12 00:00:49,880 --> 00:00:52,440 Speaker 5: Plus we bring you the latest on Apple as shares 13 00:00:52,760 --> 00:00:55,680 Speaker 5: hit a record high. For now, look, let's go on 14 00:00:55,720 --> 00:00:59,160 Speaker 5: the ground to Milwaukee where former President Trump, we understand 15 00:00:59,240 --> 00:01:02,480 Speaker 5: has arrived for the Republican National Convention joining us now 16 00:01:02,640 --> 00:01:05,120 Speaker 5: in most Kayley lines, a lot of breaking news to 17 00:01:05,160 --> 00:01:06,040 Speaker 5: continue to digest. 18 00:01:06,080 --> 00:01:09,520 Speaker 8: Kayley, Yeah, there is, of course, the utmost being what 19 00:01:09,640 --> 00:01:12,240 Speaker 8: happened over the weekend at Israelly in Pennsylvania, in which 20 00:01:12,280 --> 00:01:14,920 Speaker 8: the president was shot former president in the right year, 21 00:01:14,959 --> 00:01:18,320 Speaker 8: obviously an attash assassination attempt that he survived, but very 22 00:01:18,400 --> 00:01:20,679 Speaker 8: much changes the tenor of what is going down in 23 00:01:20,760 --> 00:01:24,160 Speaker 8: Milwaukee this week. There is an incredibly intense security. Donald 24 00:01:24,200 --> 00:01:27,280 Speaker 8: Trump himself admitted that he was considering postponing his trip here, 25 00:01:27,319 --> 00:01:30,399 Speaker 8: but did indeed come early, in fact, yesterday afternoon, and 26 00:01:30,480 --> 00:01:32,760 Speaker 8: is preparing, we understand according to an interview he just 27 00:01:32,800 --> 00:01:35,759 Speaker 8: gave to Fox News to announce his vice presidential pick today. 28 00:01:35,800 --> 00:01:37,880 Speaker 8: But of course the news does not stop there. We 29 00:01:38,000 --> 00:01:40,560 Speaker 8: learned just this morning that the judge in the criminal 30 00:01:40,560 --> 00:01:43,080 Speaker 8: case brought against him in Florida, the Document's case, a 31 00:01:43,160 --> 00:01:46,240 Speaker 8: judge appointed by him, Eiland Cannon, has now completely dismissed 32 00:01:46,240 --> 00:01:48,640 Speaker 8: that case against him on the grounds and the appointment 33 00:01:48,680 --> 00:01:50,840 Speaker 8: of special counsel Jack Smith, who of course brought that 34 00:01:50,960 --> 00:01:54,880 Speaker 8: case was unconstitutional. Essentially went around Congress, is what the 35 00:01:55,000 --> 00:01:57,840 Speaker 8: judge has ruled here. Obviously, there is room for an appeal. 36 00:01:57,880 --> 00:02:00,320 Speaker 8: The Justice Department is probably likely to do so. But 37 00:02:00,400 --> 00:02:02,400 Speaker 8: that's just another piece of news that works in the 38 00:02:02,440 --> 00:02:05,160 Speaker 8: former president's favor. As the proceedings at the convention here 39 00:02:05,160 --> 00:02:06,320 Speaker 8: get underway in Milwaukee. 40 00:02:07,840 --> 00:02:10,840 Speaker 7: Later in the program, Kelly, We're going to discuss some 41 00:02:10,919 --> 00:02:13,760 Speaker 7: of the big names from the technology world who have 42 00:02:13,840 --> 00:02:16,560 Speaker 7: either come out and endorse President Trump following the events 43 00:02:16,560 --> 00:02:21,120 Speaker 7: of the weekend, or weighed in frankly over what happened. 44 00:02:21,160 --> 00:02:24,880 Speaker 7: The other story, of course, is the response from President Biden. 45 00:02:25,520 --> 00:02:27,799 Speaker 7: What is that playing out like in the news cycle 46 00:02:27,800 --> 00:02:28,600 Speaker 7: where you are. 47 00:02:30,720 --> 00:02:33,480 Speaker 8: Well, The President clearly is still trying to keep himself 48 00:02:33,520 --> 00:02:34,480 Speaker 8: in the news cycle. 49 00:02:34,560 --> 00:02:34,640 Speaker 9: Ed. 50 00:02:34,680 --> 00:02:37,800 Speaker 8: We have heard from him addressing cameras three times since 51 00:02:37,840 --> 00:02:40,400 Speaker 8: that shooting on Saturday. He of course first made remarks 52 00:02:40,400 --> 00:02:42,799 Speaker 8: from Delaware the same day that it happened. He gave 53 00:02:42,800 --> 00:02:46,640 Speaker 8: brief remarks to the press in the early hours Sunday rather, 54 00:02:46,880 --> 00:02:49,400 Speaker 8: and then of course gave that Oval Office address at 55 00:02:49,400 --> 00:02:53,240 Speaker 8: primetime eight pm Eastern last night, basically calling for unity, 56 00:02:53,360 --> 00:02:56,160 Speaker 8: calling on Americans to turn down the temperature, tone down 57 00:02:56,520 --> 00:02:58,440 Speaker 8: some of the rhetoric in the aftermath of what he 58 00:02:58,520 --> 00:03:01,080 Speaker 8: said is something that shouldn't be taking place in America, 59 00:03:01,160 --> 00:03:03,320 Speaker 8: political violence. He said that there is no place for 60 00:03:03,400 --> 00:03:05,880 Speaker 8: it in this country, even as he was giving that speech, 61 00:03:05,919 --> 00:03:08,000 Speaker 8: not just as a president, but a presidential candidate who 62 00:03:08,040 --> 00:03:10,160 Speaker 8: was running against the very man who, of course was 63 00:03:10,440 --> 00:03:13,160 Speaker 8: shot at a rally on Saturday during the usual course 64 00:03:13,200 --> 00:03:15,360 Speaker 8: of the democratic process. So we're likely to see a 65 00:03:15,400 --> 00:03:17,800 Speaker 8: tone shift to from the Biden campaign, who have pulled 66 00:03:17,800 --> 00:03:20,760 Speaker 8: down their advertisements in the aftermath of this assassination. 67 00:03:20,800 --> 00:03:21,160 Speaker 4: Attempt. 68 00:03:21,200 --> 00:03:24,600 Speaker 8: They're probably going to be retooling their messaging. And Donald Trump, 69 00:03:24,680 --> 00:03:26,440 Speaker 8: we understand is as well. He of course will be 70 00:03:26,480 --> 00:03:29,639 Speaker 8: addressing the convention on Thursday evening, and an interview to 71 00:03:29,680 --> 00:03:32,440 Speaker 8: the Washington Examiner after the shooting, he said he is 72 00:03:32,520 --> 00:03:34,600 Speaker 8: reworking that speech. He said it was going to be 73 00:03:34,639 --> 00:03:37,080 Speaker 8: a humdigger and dinger, and now he's going to be 74 00:03:37,120 --> 00:03:39,560 Speaker 8: used as an opportunity to call for national unity. 75 00:03:40,440 --> 00:03:43,760 Speaker 7: Bloombo's Katie Lyons in Milwaukee, thank you. Meanwhile, we want 76 00:03:43,760 --> 00:03:48,200 Speaker 7: to hone in now on social media and disinformation online 77 00:03:48,640 --> 00:03:52,080 Speaker 7: following the attack on President Trump. We heard earlier today 78 00:03:52,160 --> 00:03:55,120 Speaker 7: from former National Security Advisors to the US John Bolton 79 00:03:55,200 --> 00:03:59,040 Speaker 7: on the attack, but also on how conspiracy theories will 80 00:03:59,080 --> 00:03:59,920 Speaker 7: remain in its way. 81 00:04:00,880 --> 00:04:03,240 Speaker 10: We need to do the review of this in a 82 00:04:03,360 --> 00:04:04,280 Speaker 10: calm way. 83 00:04:04,960 --> 00:04:05,800 Speaker 11: I think do it. 84 00:04:05,760 --> 00:04:09,240 Speaker 10: Quickly as well, because there are already conspiracy theories about 85 00:04:09,240 --> 00:04:12,800 Speaker 10: what happened on Saturday that I think are learning tunes. 86 00:04:12,840 --> 00:04:14,640 Speaker 10: But I don't think they're going to go away until 87 00:04:14,640 --> 00:04:16,720 Speaker 10: we have an independent objective review. 88 00:04:18,920 --> 00:04:21,840 Speaker 7: I want to bring in Bloomberg's Davy Alba, who was 89 00:04:21,880 --> 00:04:24,400 Speaker 7: on duty this weekend, and Davey, you wrote a really 90 00:04:24,480 --> 00:04:29,720 Speaker 7: important report Saturday into Sunday about how quickly misinformation spread 91 00:04:30,160 --> 00:04:33,880 Speaker 7: on key social media platforms, in particular, X, just summarize 92 00:04:33,920 --> 00:04:35,000 Speaker 7: your reporting for us. 93 00:04:35,960 --> 00:04:36,239 Speaker 11: Yeah. 94 00:04:36,279 --> 00:04:36,919 Speaker 3: Absolutely. 95 00:04:37,080 --> 00:04:40,359 Speaker 1: I mean this is kind of to be expected after 96 00:04:40,480 --> 00:04:44,880 Speaker 1: any major news event that there will be information flying 97 00:04:44,920 --> 00:04:50,240 Speaker 1: from all sides as the facts become clear. But the 98 00:04:50,320 --> 00:04:52,800 Speaker 1: thing that we've seen over and over at this point 99 00:04:53,000 --> 00:04:56,560 Speaker 1: is that people are all too willing to share conspiracy 100 00:04:56,600 --> 00:04:58,039 Speaker 1: theories as well. 101 00:04:57,880 --> 00:04:59,560 Speaker 3: About what actually happened. 102 00:05:00,000 --> 00:05:03,360 Speaker 1: I think there was an advantage in this particular moment. 103 00:05:03,200 --> 00:05:06,440 Speaker 3: That there were live cameras and so. 104 00:05:06,560 --> 00:05:11,640 Speaker 1: Much documentation of what actually happened when the president was 105 00:05:11,920 --> 00:05:16,200 Speaker 1: shot in the ear to the former president, I should say, However, 106 00:05:16,800 --> 00:05:22,480 Speaker 1: you know that didn't stop some others from spreading unfounded narratives, 107 00:05:22,520 --> 00:05:27,359 Speaker 1: such as, you know, some actual people who have hold 108 00:05:27,400 --> 00:05:32,000 Speaker 1: elected office who said that President Biden ordered the shooting. 109 00:05:33,000 --> 00:05:37,120 Speaker 1: There were rumors flying about the identity of the shooter 110 00:05:37,400 --> 00:05:40,920 Speaker 1: that were completely unconfirmed, but people were pointing figures at 111 00:05:41,360 --> 00:05:46,640 Speaker 1: specific individuals, And there were also tons of rumors about 112 00:05:46,680 --> 00:05:50,640 Speaker 1: this event being staged when there is no evidence that. 113 00:05:51,320 --> 00:05:53,960 Speaker 5: I just want to hone in on that fact because 114 00:05:54,000 --> 00:05:57,599 Speaker 5: your story really brings it to light Davy. Ultimately, these 115 00:05:57,640 --> 00:06:03,080 Speaker 5: aren't just average uses social media. These are sitting law makers, 116 00:06:03,400 --> 00:06:06,560 Speaker 5: these are elected officials, and I want to understand how 117 00:06:06,640 --> 00:06:11,160 Speaker 5: much more complex that makes the role of social media. 118 00:06:11,400 --> 00:06:14,640 Speaker 1: Yes, that's a really great question, and I think what 119 00:06:14,800 --> 00:06:18,800 Speaker 1: comes into play here is that we've seen content moderation 120 00:06:19,040 --> 00:06:24,520 Speaker 1: efforts over the past year get weakened. You know, the 121 00:06:25,279 --> 00:06:30,440 Speaker 1: idea that social media platforms are in a position of 122 00:06:31,279 --> 00:06:35,119 Speaker 1: basically deciding what speech can remain up and what should 123 00:06:35,160 --> 00:06:39,240 Speaker 1: be taken down is something that was very controversial over 124 00:06:39,279 --> 00:06:42,560 Speaker 1: the past few years and really took root I think 125 00:06:42,600 --> 00:06:47,480 Speaker 1: this year with many Republicans sort of saying that there 126 00:06:47,520 --> 00:06:50,360 Speaker 1: are these social media platforms are in a position of 127 00:06:50,560 --> 00:06:55,240 Speaker 1: censoring speech. So I think the platforms are in a tough. 128 00:06:55,040 --> 00:06:56,839 Speaker 3: Position right now. You know, they have. 129 00:06:56,760 --> 00:07:00,560 Speaker 1: To make these calls about whether someone who actually holds 130 00:07:00,600 --> 00:07:05,480 Speaker 1: elected office can continue to post essentially whatever they want, 131 00:07:06,720 --> 00:07:11,760 Speaker 1: or if the speech is so false that, you know, 132 00:07:12,600 --> 00:07:15,920 Speaker 1: the facts simply don't bear the out, do they do 133 00:07:15,960 --> 00:07:18,720 Speaker 1: something about it? And I think that the answer in 134 00:07:18,800 --> 00:07:23,000 Speaker 1: this presidential election cycle is still not clear, and these 135 00:07:23,000 --> 00:07:24,880 Speaker 1: companies continued to be in a tough place. 136 00:07:25,320 --> 00:07:27,080 Speaker 4: Devi Alba brilliant reporting. 137 00:07:27,400 --> 00:07:29,960 Speaker 5: We thank you working throughout the weekend, but we can 138 00:07:30,000 --> 00:07:32,400 Speaker 5: now talk about someone who has deep experience what it's 139 00:07:32,440 --> 00:07:34,720 Speaker 5: like to work within one of those social media platforms 140 00:07:34,880 --> 00:07:36,800 Speaker 5: and indeed has a bird's eye perspective of it. Now, 141 00:07:36,880 --> 00:07:39,680 Speaker 5: Kara Frederick's with us from the Heritage Foundation research and 142 00:07:39,800 --> 00:07:43,720 Speaker 5: educational institution with air mission to promote conservative public policies. Kara, 143 00:07:43,800 --> 00:07:46,800 Speaker 5: you served as director of the Tech Policy Center, with 144 00:07:46,960 --> 00:07:50,440 Speaker 5: research focusing on big tech emerging technology policy. What's so 145 00:07:50,560 --> 00:07:54,360 Speaker 5: fascinating is your prioral at Facebook as well. Facebook's Global 146 00:07:54,360 --> 00:07:56,640 Speaker 5: Security counter Terrorism Analysis program. 147 00:07:56,920 --> 00:07:58,920 Speaker 4: You helped create it, you lead it. 148 00:07:59,560 --> 00:08:02,160 Speaker 5: Give us the sense of what ultimately the social media 149 00:08:02,160 --> 00:08:06,000 Speaker 5: platforms are doing right now to respond to the weekend, Well. 150 00:08:05,880 --> 00:08:07,760 Speaker 9: It's a farcrive from what I used to do starting 151 00:08:07,800 --> 00:08:11,080 Speaker 9: in twenty sixteen, where we were essentially building an airplane 152 00:08:11,080 --> 00:08:14,200 Speaker 9: in midflight. So what happens in a situation like this. 153 00:08:14,360 --> 00:08:18,160 Speaker 9: I was specifically devoted to foreign Islamist terrorism, so it 154 00:08:18,200 --> 00:08:21,679 Speaker 9: was a very different animal. But at the same time, 155 00:08:22,240 --> 00:08:24,600 Speaker 9: what all of these teams are working together with it 156 00:08:24,800 --> 00:08:28,239 Speaker 9: and companies are doing. They're working with their community operations teams, 157 00:08:28,280 --> 00:08:31,400 Speaker 9: they're working with their engineers, usually the trust and safety engineers. 158 00:08:31,600 --> 00:08:33,920 Speaker 9: They're working with their policy teams, they're working with people 159 00:08:33,920 --> 00:08:36,320 Speaker 9: in global security, like the team that I led, and 160 00:08:36,360 --> 00:08:40,240 Speaker 9: they're trying to identify if the attacker, attacker was on 161 00:08:40,280 --> 00:08:42,680 Speaker 9: the platform, if he has active accounts, if he was 162 00:08:42,720 --> 00:08:45,679 Speaker 9: ever on the platform, if he posted anything. 163 00:08:45,679 --> 00:08:47,880 Speaker 3: They're trying to potentially. 164 00:08:47,360 --> 00:08:50,080 Speaker 9: Take down some of that information for so the public 165 00:08:50,080 --> 00:08:54,400 Speaker 9: can't necessarily see it and instigate copycat attacks and whatnot. 166 00:08:54,440 --> 00:08:55,880 Speaker 3: But ultimately they. 167 00:08:55,720 --> 00:08:58,679 Speaker 9: Are trying to identify the perpetrator in the minutes after 168 00:08:58,679 --> 00:09:01,720 Speaker 9: those attacks that happened and get them off the platform. 169 00:09:01,800 --> 00:09:04,800 Speaker 9: The whole mo of these teams is to make the 170 00:09:04,880 --> 00:09:08,160 Speaker 9: platform hostile to these types of actors, and that's what 171 00:09:08,160 --> 00:09:10,200 Speaker 9: they're going to be doing in the moments after an 172 00:09:10,240 --> 00:09:11,960 Speaker 9: attack breaks on the news. 173 00:09:11,760 --> 00:09:15,000 Speaker 7: Like this, Cura, good morning, and thank you for coming 174 00:09:15,000 --> 00:09:18,400 Speaker 7: on Bloombay Technology. I'd like to just focus on what 175 00:09:18,520 --> 00:09:21,840 Speaker 7: happened the last forty eight hours, the social media discussion 176 00:09:22,600 --> 00:09:26,520 Speaker 7: immediately following the attack on former President Trump, but also 177 00:09:26,559 --> 00:09:29,360 Speaker 7: the sort of continued sharing of content. And one thing 178 00:09:29,400 --> 00:09:32,280 Speaker 7: that I noticed or I reflect on, is how many 179 00:09:32,280 --> 00:09:37,240 Speaker 7: people discussing the platform X and how they were pleased 180 00:09:37,280 --> 00:09:40,120 Speaker 7: basically to be able to get information so quickly. But 181 00:09:40,200 --> 00:09:43,600 Speaker 7: as Davies just pointed out in her reporting, within the 182 00:09:43,640 --> 00:09:46,520 Speaker 7: stuff shared on x much of it was misinformation. 183 00:09:47,120 --> 00:09:47,880 Speaker 6: It was false. 184 00:09:48,200 --> 00:09:51,440 Speaker 7: How do you balance speed of access to information to 185 00:09:51,600 --> 00:09:53,400 Speaker 7: the check that you have to get it right. 186 00:09:55,080 --> 00:09:57,480 Speaker 3: It is a very, very difficult question. 187 00:09:57,640 --> 00:10:00,920 Speaker 9: And my best advice, having been a camera terrorism analysts 188 00:10:00,960 --> 00:10:03,520 Speaker 9: for the Department of Defense for six years and then 189 00:10:03,640 --> 00:10:06,800 Speaker 9: having worked in counter terrorism at the platform level at 190 00:10:06,800 --> 00:10:09,960 Speaker 9: a big tech company, is to wait to be very 191 00:10:10,000 --> 00:10:13,880 Speaker 9: prudent about number one even identifying the attacker. We knew 192 00:10:14,040 --> 00:10:17,640 Speaker 9: in the couple minutes after this there were different pictures 193 00:10:17,720 --> 00:10:20,000 Speaker 9: of who it could have potentially been floating around on 194 00:10:20,040 --> 00:10:20,680 Speaker 9: social media. 195 00:10:21,080 --> 00:10:23,880 Speaker 3: They were wrong. There are other pictures they were wrong. 196 00:10:23,960 --> 00:10:26,559 Speaker 9: So I think the act of prudence in this case 197 00:10:26,679 --> 00:10:29,560 Speaker 9: is to wait to try to get the full picture. 198 00:10:29,880 --> 00:10:31,720 Speaker 3: And you know what's really interesting too. 199 00:10:31,920 --> 00:10:35,880 Speaker 9: Is there is a cohort of open source analysts who 200 00:10:35,960 --> 00:10:37,720 Speaker 9: are digging through a lot of these information. 201 00:10:37,960 --> 00:10:39,800 Speaker 3: They're working many times on their own. 202 00:10:40,320 --> 00:10:43,440 Speaker 9: They were not necessarily employed by these big tech companies. 203 00:10:43,440 --> 00:10:46,200 Speaker 9: They're not even vendors or contracted out, but they're digging 204 00:10:46,280 --> 00:10:48,960 Speaker 9: through a lot of the information. They're putting the pieces together. 205 00:10:49,240 --> 00:10:52,559 Speaker 9: But my advice to everyone, just people that are looking 206 00:10:52,760 --> 00:10:56,600 Speaker 9: at vowyeers, just wait the full story eventually comes out. 207 00:10:56,720 --> 00:10:59,880 Speaker 9: But in terms of waiting, the scales in either way, 208 00:11:00,120 --> 00:11:02,320 Speaker 9: I think big tech platforms have to do a much 209 00:11:02,360 --> 00:11:05,800 Speaker 9: better job of showing that they are more neutral arbiters 210 00:11:05,800 --> 00:11:09,520 Speaker 9: of information, because, as the Bloomberg reporter said, prior to this, 211 00:11:09,800 --> 00:11:12,520 Speaker 9: you know, tech has been under a microscope because they 212 00:11:12,559 --> 00:11:15,480 Speaker 9: haven't gotten so many of the calls. Right look at 213 00:11:15,480 --> 00:11:18,360 Speaker 9: the Hunter Biden laptop story when Twitter was breaking the 214 00:11:18,440 --> 00:11:21,480 Speaker 9: links to the dms for that legitimate story in the 215 00:11:21,520 --> 00:11:24,280 Speaker 9: twenty twenty campaign. So big tech has a lot of 216 00:11:24,320 --> 00:11:26,079 Speaker 9: making up to do when it comes to this. They 217 00:11:26,080 --> 00:11:27,720 Speaker 9: don't have the trust of the people, and I would 218 00:11:27,720 --> 00:11:28,200 Speaker 9: say rightly. 219 00:11:28,240 --> 00:11:31,240 Speaker 5: So it was interesting that ahead of all of this, 220 00:11:31,440 --> 00:11:33,920 Speaker 5: Meta did, indeed as it had said it would do, 221 00:11:34,000 --> 00:11:36,600 Speaker 5: lift all restrictions on Trump's accounts ahead of the US election, 222 00:11:36,640 --> 00:11:39,640 Speaker 5: and it was understood car and I'm interested is as 223 00:11:39,640 --> 00:11:42,880 Speaker 5: we do try and gain trust, it's also at a 224 00:11:42,880 --> 00:11:46,199 Speaker 5: time where we've got artificial intelligence and technology working against 225 00:11:46,240 --> 00:11:49,640 Speaker 5: us in terms of really understanding the true nature of things. 226 00:11:49,679 --> 00:11:51,960 Speaker 5: How much is that making life ever more difficult. 227 00:11:53,120 --> 00:11:56,720 Speaker 9: I think it's exacerbating it to the nth degree. I mean, 228 00:11:56,840 --> 00:11:59,040 Speaker 9: you look at AI, and I'm a big fan of AI. 229 00:11:59,120 --> 00:12:01,640 Speaker 9: I'm a big fan and pro innovation. When it comes 230 00:12:01,679 --> 00:12:04,600 Speaker 9: to open sourcing these models and these AI tools, I 231 00:12:04,640 --> 00:12:06,760 Speaker 9: think that's going to take us farther than our foreign 232 00:12:06,800 --> 00:12:10,320 Speaker 9: adversary counterparts who are working on more closed models of 233 00:12:10,360 --> 00:12:13,040 Speaker 9: these large language models, et cetera, et cetera. So I 234 00:12:13,080 --> 00:12:14,839 Speaker 9: am a big fan of AI. I want to get 235 00:12:14,840 --> 00:12:17,840 Speaker 9: that out front. But as we say in the tech community, 236 00:12:18,200 --> 00:12:21,480 Speaker 9: if you build it, they will come. Bad actors are 237 00:12:21,520 --> 00:12:25,240 Speaker 9: always going to co opt technology that outpaces attempts to 238 00:12:25,280 --> 00:12:28,600 Speaker 9: govern it. This technology is developing even more rapidly than 239 00:12:28,640 --> 00:12:31,000 Speaker 9: I even foresaw when I was working with it in 240 00:12:31,040 --> 00:12:34,520 Speaker 9: twenty seventeen and then researching it in twenty eighteen. Now 241 00:12:34,640 --> 00:12:37,280 Speaker 9: we were talking of an AI winter back then another 242 00:12:37,360 --> 00:12:40,760 Speaker 9: AI winter, and yet with the explosion of GPT four 243 00:12:40,920 --> 00:12:44,040 Speaker 9: now called chat GPT. I mean it looks like these 244 00:12:44,080 --> 00:12:49,520 Speaker 9: technologies because they can tailor information, amplify information, and do 245 00:12:49,720 --> 00:12:53,640 Speaker 9: all of this at machine speed and scale. That's the kicker, 246 00:12:53,800 --> 00:12:56,800 Speaker 9: machine speed and scale. We are going to see a 247 00:12:56,840 --> 00:12:59,440 Speaker 9: world of synthetic media, where the truth is going to 248 00:12:59,440 --> 00:13:01,960 Speaker 9: be harder and harder to discern, and that puts a 249 00:13:01,960 --> 00:13:03,640 Speaker 9: lot of onus on the platform to get it right. 250 00:13:03,679 --> 00:13:06,880 Speaker 7: At the abset car, we have a question from one 251 00:13:06,880 --> 00:13:09,080 Speaker 7: of our audience members, which is how much of Project 252 00:13:09,160 --> 00:13:12,840 Speaker 7: twenty twenty five will actually make it into the GOP platform. 253 00:13:13,040 --> 00:13:15,600 Speaker 7: But let's answer that in the lens of technology, please. 254 00:13:16,760 --> 00:13:20,160 Speaker 9: Yeah. So we don't know what's in Trump's mind or 255 00:13:20,240 --> 00:13:23,760 Speaker 9: Trump's campaign's mind, but we do know what the platform 256 00:13:23,800 --> 00:13:27,360 Speaker 9: has said. The platform is pro crypto, the platform is 257 00:13:27,440 --> 00:13:29,800 Speaker 9: pro AI development, and the platform. 258 00:13:29,440 --> 00:13:30,240 Speaker 3: Is pro space. 259 00:13:30,559 --> 00:13:33,319 Speaker 9: So I think when it comes to what the Trump 260 00:13:33,440 --> 00:13:37,800 Speaker 9: campaign and potential Trump presidency, second Trump presidency is going 261 00:13:37,880 --> 00:13:39,800 Speaker 9: to do, I don't speak for them, but it looks 262 00:13:39,840 --> 00:13:43,719 Speaker 9: like they're trying to paint an affirmative agenda, an affirmative 263 00:13:43,800 --> 00:13:46,080 Speaker 9: vision of the things that they are for when it 264 00:13:46,080 --> 00:13:49,520 Speaker 9: comes to technology, rather than the things that they are against. 265 00:13:49,679 --> 00:13:51,640 Speaker 3: So I would expect a lot of. 266 00:13:51,720 --> 00:13:56,960 Speaker 9: Pro innovation to take place under a potential second Trump presidency. 267 00:13:57,520 --> 00:13:59,640 Speaker 4: An extraordinary voice to have join us today. 268 00:14:00,160 --> 00:14:03,680 Speaker 5: Frederick Tech Policy Center, Director at the Heritage Foundation and 269 00:14:04,000 --> 00:14:07,320 Speaker 5: decent Experience, having worked at Facebook, and indeed in counter terrorism. 270 00:14:07,360 --> 00:14:07,840 Speaker 4: We thank you. 271 00:14:16,800 --> 00:14:19,240 Speaker 7: Let's keep talking about the Trump trade that's kind of 272 00:14:19,240 --> 00:14:21,840 Speaker 7: intensified following the events of the last forty eight hours. 273 00:14:21,920 --> 00:14:26,680 Speaker 7: We spoke about DJT, but crypto related names, not just 274 00:14:26,720 --> 00:14:29,240 Speaker 7: coinbases is sort of exchanged, but some of the miners 275 00:14:29,280 --> 00:14:32,120 Speaker 7: also doing well. The idea being that Trump had been 276 00:14:32,160 --> 00:14:34,960 Speaker 7: scheduled to speak at crypto events. He's seen as the 277 00:14:34,960 --> 00:14:39,040 Speaker 7: more crypto friendly of the two candidates. I'd also point out, Caro, 278 00:14:39,400 --> 00:14:41,480 Speaker 7: there are other stocks in other areas moving to the 279 00:14:41,560 --> 00:14:43,720 Speaker 7: upside on the same logic, and. 280 00:14:44,120 --> 00:14:47,480 Speaker 5: Certainly it's not only crypto names that are moving today. 281 00:14:47,600 --> 00:14:53,280 Speaker 5: Investors reassessing assets across the board. Ed the price in 282 00:14:53,320 --> 00:14:56,080 Speaker 5: what a Trump win in November really does mean across 283 00:14:56,120 --> 00:14:58,600 Speaker 5: asset classes with us to regul all down bluemgs just 284 00:14:58,680 --> 00:15:02,200 Speaker 5: mentu Shanali Bassek No, we can talk crypto more Volueishnati, 285 00:15:02,280 --> 00:15:04,960 Speaker 5: but just dig into some of the industry utes power 286 00:15:05,040 --> 00:15:07,320 Speaker 5: the S and P five hundred thirty eighth record. 287 00:15:07,440 --> 00:15:07,880 Speaker 4: That's right. 288 00:15:08,000 --> 00:15:10,560 Speaker 12: So of course ED just brought up crypto related stocks. 289 00:15:10,560 --> 00:15:12,640 Speaker 12: So if you look at the bitwise ETF that tracks 290 00:15:12,680 --> 00:15:14,960 Speaker 12: those crypto stocks, which I know SHNAI is going to 291 00:15:14,960 --> 00:15:17,080 Speaker 12: get more to the bitcoin side of things, but of 292 00:15:17,080 --> 00:15:19,600 Speaker 12: course that houses stocks like if you're looking at Marathon 293 00:15:19,640 --> 00:15:22,240 Speaker 12: Digital right platforms, Coinbase. We did see a pop in 294 00:15:22,280 --> 00:15:25,280 Speaker 12: that today because if you're thinking about President Trump, who 295 00:15:25,320 --> 00:15:28,560 Speaker 12: has been very pro a crypto exposure and things like that, 296 00:15:28,600 --> 00:15:29,520 Speaker 12: you're seeing a pop there. 297 00:15:29,560 --> 00:15:32,480 Speaker 4: But then also beyond just that too, if you're looking at. 298 00:15:32,360 --> 00:15:36,480 Speaker 12: Maybe more regulated type sectors with financials as well as healthcare. 299 00:15:36,680 --> 00:15:38,680 Speaker 12: Those are two key areas to watch as far as 300 00:15:38,680 --> 00:15:41,200 Speaker 12: what that means, because usually if there's say a Republican 301 00:15:41,240 --> 00:15:44,120 Speaker 12: potential sweep there, that would be more easy policy toward. 302 00:15:44,160 --> 00:15:46,560 Speaker 12: When you're looking at banks and financials, and then as 303 00:15:46,600 --> 00:15:49,160 Speaker 12: well as the healthcare side of things, especially those insurers. 304 00:15:49,160 --> 00:15:52,200 Speaker 12: If you're thinking about CBS obviously owns Etna, and then 305 00:15:52,560 --> 00:15:55,320 Speaker 12: obviously when you think about other insurers like that too, 306 00:15:55,440 --> 00:15:57,600 Speaker 12: those are some industries keeping a close eye on. And 307 00:15:57,640 --> 00:15:59,760 Speaker 12: then also when it comes to fossil fuels, but then 308 00:15:59,800 --> 00:16:03,120 Speaker 12: we're renewable energy or solar stocks too because those have 309 00:16:03,240 --> 00:16:06,720 Speaker 12: been more prominent and gotten a support under a democratic presidency. 310 00:16:06,760 --> 00:16:09,400 Speaker 12: But if you're thinking about sun solar sunrun in stocks 311 00:16:09,440 --> 00:16:11,600 Speaker 12: like that, that's something to watch too, because they could 312 00:16:11,600 --> 00:16:14,520 Speaker 12: have potentially more restrictions. There thing's going undone if there 313 00:16:14,560 --> 00:16:15,600 Speaker 12: is a Republican president. 314 00:16:15,720 --> 00:16:17,960 Speaker 7: Well, the exception is that rule probably Tesla that's up 315 00:16:17,960 --> 00:16:20,640 Speaker 7: almost six percent in a bit of a Trump Shinali. 316 00:16:20,720 --> 00:16:23,160 Speaker 7: The macro view here is that the market's trying to 317 00:16:23,160 --> 00:16:25,920 Speaker 7: assess who's going to be president and by extension, what 318 00:16:26,080 --> 00:16:29,000 Speaker 7: policy will be to various parts of the economy and 319 00:16:29,040 --> 00:16:30,080 Speaker 7: different industry groups. 320 00:16:30,160 --> 00:16:32,400 Speaker 13: Yeah, let's take a look across what that means across 321 00:16:32,440 --> 00:16:34,960 Speaker 13: asset classes, because of course it is of course impacting 322 00:16:34,960 --> 00:16:38,800 Speaker 13: the stock market and certain sectors, as Jess was saying, energy, financials, 323 00:16:38,880 --> 00:16:42,400 Speaker 13: places that Trump would be expected to have a massive 324 00:16:42,880 --> 00:16:45,400 Speaker 13: mark on policy. But then also you're seeing a really 325 00:16:45,440 --> 00:16:47,600 Speaker 13: big move here, as we've been saying, in bitcoin, of 326 00:16:48,000 --> 00:16:50,560 Speaker 13: roughly ten percent or more since Friday. 327 00:16:50,800 --> 00:16:52,000 Speaker 6: It ended well below. 328 00:16:51,840 --> 00:16:55,880 Speaker 13: Sixty thousand, closer to fifty seven thousand on Friday, and 329 00:16:55,920 --> 00:16:59,200 Speaker 13: now you're watching it surge past sixty three thousand. Remember, 330 00:16:59,440 --> 00:17:02,680 Speaker 13: Trump is largely seen as more of a pro crypto candidate, 331 00:17:02,920 --> 00:17:06,200 Speaker 13: bitcoins not alone. You see the dollar also rising as well, 332 00:17:06,240 --> 00:17:09,720 Speaker 13: because you are watching this expectation that in a Trump administration, 333 00:17:10,080 --> 00:17:12,080 Speaker 13: what you would have as the odds rise. Is of 334 00:17:12,080 --> 00:17:15,600 Speaker 13: course that tariff policy and therefore potentially a stronger dollar. 335 00:17:15,760 --> 00:17:18,879 Speaker 13: I would also add point to the curve steepener. When 336 00:17:18,880 --> 00:17:20,880 Speaker 13: you think about the bond market, it's not the front 337 00:17:21,000 --> 00:17:23,480 Speaker 13: end of the curve really that's moving. It's the tail 338 00:17:23,600 --> 00:17:25,520 Speaker 13: end of the curve. You're seeing a bigger sell off. 339 00:17:25,840 --> 00:17:30,359 Speaker 13: Think here, taxes being looser in the future, potentially think 340 00:17:30,400 --> 00:17:34,520 Speaker 13: here this idea that you might have a more of 341 00:17:34,560 --> 00:17:36,920 Speaker 13: a fiscal burden on the United States. Of course, you're 342 00:17:36,960 --> 00:17:40,359 Speaker 13: seeing that thirty year really sell off. Briefly today you've 343 00:17:40,440 --> 00:17:45,199 Speaker 13: seen that two thirty curve disinvert and steepen, and of 344 00:17:45,240 --> 00:17:47,760 Speaker 13: course that is that short end staying flat and that 345 00:17:47,880 --> 00:17:50,080 Speaker 13: sell off in the long end starting to be pronounced. 346 00:17:50,119 --> 00:17:52,040 Speaker 13: There are a lot of factors under the surface here, 347 00:17:52,040 --> 00:17:56,439 Speaker 13: but just significantly many asset classes really moving into today. 348 00:17:56,960 --> 00:18:00,840 Speaker 5: Perfect summary from Shananibase and just Ment. 349 00:18:08,240 --> 00:18:12,280 Speaker 7: Google parent Alphabets in talks to acqui cyber security startup Whiz, 350 00:18:12,320 --> 00:18:14,640 Speaker 7: according to a source, a deal that may be worth 351 00:18:14,680 --> 00:18:17,440 Speaker 7: as much as twenty three billion dollars, which would make 352 00:18:17,480 --> 00:18:21,000 Speaker 7: it the tech giant's largest acquisition to date. Bloomberg's mark 353 00:18:21,040 --> 00:18:23,720 Speaker 7: Bergen's here from London. Give me the rest of the details. 354 00:18:23,760 --> 00:18:24,600 Speaker 7: This was a surprise. 355 00:18:26,720 --> 00:18:30,040 Speaker 14: It was a surprise, although if you're following Google and 356 00:18:30,080 --> 00:18:33,200 Speaker 14: their cloud market over the past maybe five years, it's 357 00:18:33,320 --> 00:18:37,960 Speaker 14: not their last big acquisition. Mandient in similar space cybersecurity 358 00:18:38,080 --> 00:18:39,920 Speaker 14: slider right under Google Cloud. 359 00:18:40,080 --> 00:18:41,359 Speaker 6: Looks like they're trying to do it again. 360 00:18:41,440 --> 00:18:43,399 Speaker 14: This is something where you know they have been this 361 00:18:43,520 --> 00:18:48,040 Speaker 14: sort of perpetual third place in the market behind aws 362 00:18:48,080 --> 00:18:50,960 Speaker 14: in Microsoft. Microsoft in particular has been really pushing the 363 00:18:50,960 --> 00:18:54,240 Speaker 14: album up on cybersecurity, making that the case that sort 364 00:18:54,240 --> 00:18:56,600 Speaker 14: of that's their advantage Azure. But at the same time 365 00:18:56,600 --> 00:19:01,639 Speaker 14: Microsoft has some pretty noticeable and public flaws and the 366 00:19:01,720 --> 00:19:05,520 Speaker 14: mistakes around cybersecurity that Google, I think is trying to exploit. 367 00:19:06,359 --> 00:19:08,320 Speaker 14: So it is an aberration in the sense that it's 368 00:19:08,320 --> 00:19:10,640 Speaker 14: the biggest deal by a long measure in something where 369 00:19:10,680 --> 00:19:13,960 Speaker 14: Google has stayed away from deals for anti trust reasons lately. 370 00:19:14,520 --> 00:19:18,119 Speaker 5: Some vcs could be making a sizable return and recent 371 00:19:18,320 --> 00:19:21,119 Speaker 5: Lightspeed Ventures Thrive Capital in the latest round. We understand 372 00:19:21,160 --> 00:19:23,840 Speaker 5: of wiz, but is that regulatory risk ki Mark. 373 00:19:25,119 --> 00:19:28,600 Speaker 14: So for sure is that this company's started in twenty twenty, 374 00:19:28,720 --> 00:19:32,320 Speaker 14: so it's remarkable this twenty three billion would be almost 375 00:19:32,359 --> 00:19:36,080 Speaker 14: twice its last valuation, so it's a pretty massive returns. 376 00:19:36,760 --> 00:19:38,639 Speaker 14: I think the argument that Google's going to make. I 377 00:19:38,640 --> 00:19:41,000 Speaker 14: won't speak for the FTC and the TJ on this, 378 00:19:41,040 --> 00:19:43,040 Speaker 14: but the argument that Google's going to make is we 379 00:19:43,119 --> 00:19:46,280 Speaker 14: are not in any way monopoly in the cloud market. 380 00:19:46,400 --> 00:19:48,880 Speaker 14: But the Google will cite that they're in third position. 381 00:19:49,640 --> 00:19:52,120 Speaker 14: That Mandy a deal I believe was about five billion. 382 00:19:52,480 --> 00:19:56,760 Speaker 14: That one cleared. I don't expect Whiz will be approved 383 00:19:56,840 --> 00:20:00,240 Speaker 14: on day two. These things typically take some time if 384 00:20:00,280 --> 00:20:03,680 Speaker 14: it goes through, but it's you know, Microsoft is clearly 385 00:20:03,720 --> 00:20:06,199 Speaker 14: has some issues around around the anti trust, so you 386 00:20:06,240 --> 00:20:08,600 Speaker 14: can't rule that out. But I think Google's case is 387 00:20:08,640 --> 00:20:11,439 Speaker 14: going to be in this market, we are far from 388 00:20:11,720 --> 00:20:13,600 Speaker 14: the market leader and far from a monopoly. 389 00:20:14,119 --> 00:20:16,000 Speaker 5: And as we know, the agreement hasn't been reached and 390 00:20:16,040 --> 00:20:18,639 Speaker 5: talks could still end without one. But for now, interesting 391 00:20:18,680 --> 00:20:27,280 Speaker 5: to talk with the Matt Bergen. We really appreciate it. 392 00:20:29,320 --> 00:20:32,320 Speaker 6: Welcome back to Bloomberg Technology. Ed Lovelow here in San Francisco, 393 00:20:32,400 --> 00:20:33,360 Speaker 6: Caroline hid in New York. 394 00:20:33,520 --> 00:20:36,200 Speaker 5: An interesting one in Tesla more than five percent higher. 395 00:20:36,359 --> 00:20:38,600 Speaker 5: It's got a solar business, a sizable one. 396 00:20:39,040 --> 00:20:39,080 Speaker 15: Ed. 397 00:20:39,280 --> 00:20:42,600 Speaker 5: It is like the name that encapsulates green policy. But 398 00:20:42,640 --> 00:20:46,040 Speaker 5: it is also of course perhaps a Trump trade here 399 00:20:46,240 --> 00:20:49,560 Speaker 5: with Elon Musk going in Previously, we understood the reporting 400 00:20:49,560 --> 00:20:53,560 Speaker 5: happening on the weekend, Ed that indeed we saw being 401 00:20:53,640 --> 00:20:55,359 Speaker 5: backed by Trump is Elon Musk. 402 00:20:55,359 --> 00:20:57,159 Speaker 4: Max Traffckin is here to discuss a little bit more. 403 00:20:57,200 --> 00:20:58,840 Speaker 4: But Ed, can you just dwell on the fact that. 404 00:20:58,800 --> 00:21:02,760 Speaker 5: Almost before occurred this weekend an extraordinary set of circumstances 405 00:21:02,960 --> 00:21:03,800 Speaker 5: in Pennsylvania. 406 00:21:03,880 --> 00:21:06,399 Speaker 4: We had reporting that indeed. 407 00:21:06,080 --> 00:21:08,560 Speaker 5: Elon Musk was going to be supporting a super pac. 408 00:21:09,400 --> 00:21:09,760 Speaker 6: Correct. 409 00:21:09,760 --> 00:21:13,200 Speaker 7: So Musk made this public endorsement following the assassination tempt 410 00:21:13,320 --> 00:21:15,440 Speaker 7: on former President Trump. But late Friday night, and you 411 00:21:15,520 --> 00:21:20,080 Speaker 7: may have missed it, Bloomberg reported, citing sources, that Musk 412 00:21:20,119 --> 00:21:24,399 Speaker 7: had made what we're characterizing as a sizeable donation to 413 00:21:24,680 --> 00:21:29,080 Speaker 7: a low profile organization called the America Pack, which is 414 00:21:29,080 --> 00:21:33,240 Speaker 7: actually due to to do disclose its funding today July fifteenth. 415 00:21:33,280 --> 00:21:36,000 Speaker 7: So depending on the timing of when Musk made that donation, 416 00:21:37,440 --> 00:21:39,560 Speaker 7: we will get some more information about it. But let's 417 00:21:39,600 --> 00:21:42,680 Speaker 7: bring in bloombergs Max Chafkin, because I find this really interesting, 418 00:21:42,760 --> 00:21:46,840 Speaker 7: you know, the history of Musk's relationship with former President Trump. 419 00:21:47,359 --> 00:21:51,400 Speaker 7: Maybe it doesn't matter now he's endorsed Trump publicly through 420 00:21:51,400 --> 00:21:52,320 Speaker 7: the platform X. 421 00:21:52,800 --> 00:21:53,560 Speaker 6: Yeah, absolutely. 422 00:21:53,640 --> 00:21:57,960 Speaker 16: I mean Elon Musk in twenty sixteen did kind of 423 00:21:58,280 --> 00:22:02,080 Speaker 16: start to drift towards Trump. Mean, he was initially on 424 00:22:02,200 --> 00:22:05,240 Speaker 16: a couple of these executive councils and then broke with 425 00:22:05,560 --> 00:22:09,159 Speaker 16: the former president over the Paris Climate Accord. But what 426 00:22:09,200 --> 00:22:12,439 Speaker 16: we've seen over the last five or so years is 427 00:22:12,520 --> 00:22:15,560 Speaker 16: a thawing of those relations. Even as they've insulted each other, 428 00:22:15,600 --> 00:22:18,639 Speaker 16: you know, often publicly, there has been a cooling and 429 00:22:19,359 --> 00:22:21,520 Speaker 16: definitely an ideological convergence. 430 00:22:21,560 --> 00:22:23,520 Speaker 6: When you look at sort of what. 431 00:22:23,359 --> 00:22:26,399 Speaker 16: Elon Musk is saying on his you know, ex page 432 00:22:26,400 --> 00:22:29,320 Speaker 16: and what the former president is saying on the campaign trail, 433 00:22:29,560 --> 00:22:32,159 Speaker 16: there are a lot of commonalities. And on top of that, 434 00:22:32,200 --> 00:22:34,760 Speaker 16: of course, Elon Musk has what I'd say is a 435 00:22:34,800 --> 00:22:37,840 Speaker 16: pretty bad relationship with the Biden administration. Right you have 436 00:22:37,960 --> 00:22:42,280 Speaker 16: multiple federal agencies investigating various aspects of his business. Elon 437 00:22:42,320 --> 00:22:45,480 Speaker 16: Musk has had all sorts of extremely negative things to 438 00:22:45,520 --> 00:22:47,960 Speaker 16: say about the current president. So you can see a 439 00:22:47,960 --> 00:22:50,240 Speaker 16: lot of reasons why they would be able to find 440 00:22:50,280 --> 00:22:53,760 Speaker 16: common ground. And of course, until recently President Trump's former 441 00:22:53,760 --> 00:22:55,960 Speaker 16: President Trump's finances have started to look a lot better, 442 00:22:56,000 --> 00:22:59,120 Speaker 16: but until recently he really needed money. So they both 443 00:22:59,200 --> 00:23:00,000 Speaker 16: kind of need each other. 444 00:23:00,200 --> 00:23:02,479 Speaker 5: And I think that's what we're seeing when you go 445 00:23:02,520 --> 00:23:06,760 Speaker 5: to the Elil Musk needing each other, needing Trump or 446 00:23:06,840 --> 00:23:10,040 Speaker 5: indeed anyone who's in the White House. Remind us of 447 00:23:10,080 --> 00:23:13,240 Speaker 5: the government contracts that Elol Musk basically sits a top of. 448 00:23:13,400 --> 00:23:16,040 Speaker 16: Yeah, so Elon Musk is I mean, of course, he 449 00:23:16,119 --> 00:23:18,240 Speaker 16: is known as an innovator, but he's also been a 450 00:23:18,440 --> 00:23:22,080 Speaker 16: very successful government contractor. You know, many of his businesses, 451 00:23:22,119 --> 00:23:25,399 Speaker 16: most of much of his business depends on relationships with 452 00:23:25,400 --> 00:23:28,439 Speaker 16: the government, either in terms of direct contracts with SpaceX 453 00:23:28,720 --> 00:23:31,320 Speaker 16: or Tesla of course depends on these text credits and 454 00:23:31,400 --> 00:23:34,000 Speaker 16: has for the entirety of its existence. So you can 455 00:23:34,040 --> 00:23:36,159 Speaker 16: sort of see why he has an interest. And of 456 00:23:36,160 --> 00:23:38,600 Speaker 16: course he's got a lot more planned right. SpaceX is 457 00:23:38,640 --> 00:23:41,639 Speaker 16: hoping to go to Mars, wants to be involved with that. 458 00:23:41,680 --> 00:23:44,240 Speaker 16: And if you look at the GOP platform, which we're 459 00:23:44,240 --> 00:23:46,280 Speaker 16: going to see at the convention, it does bring up 460 00:23:46,320 --> 00:23:50,760 Speaker 16: commercial space Mars, it brings up AI, the fears of 461 00:23:50,800 --> 00:23:52,879 Speaker 16: sort of the wokeness in AI or it implies that, 462 00:23:52,920 --> 00:23:56,000 Speaker 16: which is another pet elon Musk issue. On the other hand, 463 00:23:56,040 --> 00:23:59,000 Speaker 16: President Forum President Trump has said very negative things about 464 00:23:59,000 --> 00:24:03,280 Speaker 16: the EV industries, so there is potential tension there as well. 465 00:24:03,400 --> 00:24:06,200 Speaker 7: Max I wrote in my hyperdrive Newslader last week about 466 00:24:06,200 --> 00:24:09,639 Speaker 7: the idea of what happens to public funding or IRA 467 00:24:09,920 --> 00:24:12,320 Speaker 7: funds in the event of ivor White House. And no 468 00:24:12,400 --> 00:24:14,399 Speaker 7: one I've spoken to would say if Trump wins the 469 00:24:14,440 --> 00:24:17,200 Speaker 7: presidency that would just go away. But I just wanted 470 00:24:17,240 --> 00:24:19,720 Speaker 7: to remind our audience of the New York Times reporting 471 00:24:20,000 --> 00:24:23,120 Speaker 7: from earlier this year that Trump met with oil executives 472 00:24:23,119 --> 00:24:26,280 Speaker 7: and basically said, if you help fund my campaign, I 473 00:24:26,359 --> 00:24:29,480 Speaker 7: will be, let's say, less supportive of evs. 474 00:24:29,680 --> 00:24:30,840 Speaker 6: So then we bring in Musk. 475 00:24:31,000 --> 00:24:34,480 Speaker 7: It doesn't really add up Trump's sort of historic attitude 476 00:24:34,480 --> 00:24:38,520 Speaker 7: towards electric vehicles and Musk and Tesla is the market incumbent, 477 00:24:38,760 --> 00:24:40,920 Speaker 7: the company that paved the way for electrification. 478 00:24:41,400 --> 00:24:43,800 Speaker 16: Yeah, it's hard to know how to parse that, And 479 00:24:43,880 --> 00:24:46,720 Speaker 16: of course what Canada's say on the campaign trail is 480 00:24:46,960 --> 00:24:49,400 Speaker 16: necessarily what ends up happening. 481 00:24:50,160 --> 00:24:53,760 Speaker 6: From the sort of Musk point of view. Two points one. 482 00:24:53,560 --> 00:24:56,399 Speaker 16: Is that I think Trump making those comments and then 483 00:24:56,440 --> 00:24:59,359 Speaker 16: those comments leaking could be read as a sort of 484 00:24:59,600 --> 00:25:02,480 Speaker 16: blink read you know, orange light for somebody like Elon 485 00:25:02,600 --> 00:25:03,280 Speaker 16: Musk to donate. 486 00:25:03,320 --> 00:25:03,960 Speaker 6: It will be. 487 00:25:03,920 --> 00:25:07,919 Speaker 16: Interesting to see if President Trump foreign President Trump softens 488 00:25:07,960 --> 00:25:11,240 Speaker 16: his attitude to the EV industry. The second thing is 489 00:25:11,280 --> 00:25:14,840 Speaker 16: that Tesla is the market leader. It doesn't necessarily hurt 490 00:25:14,880 --> 00:25:19,320 Speaker 16: the company if if the Trump, if a hypothetical second 491 00:25:19,359 --> 00:25:22,600 Speaker 16: Trump presidency, you know, kind of cracks down on the 492 00:25:22,600 --> 00:25:24,360 Speaker 16: EV industry or gets rid of a lot of subsidies, 493 00:25:24,400 --> 00:25:27,360 Speaker 16: it might even just sort of lock in Tesla's position. 494 00:25:27,440 --> 00:25:29,320 Speaker 16: Now that's not something you want to hear if your 495 00:25:29,359 --> 00:25:32,080 Speaker 16: interest is in growing the EV industry in a big way. 496 00:25:32,280 --> 00:25:34,879 Speaker 16: But it's not clear that that's even Musk's goal at 497 00:25:34,880 --> 00:25:35,320 Speaker 16: this point. 498 00:25:36,160 --> 00:25:39,520 Speaker 7: Max Tefkin's written so much care about the history of 499 00:25:39,560 --> 00:25:42,760 Speaker 7: mask and politics. We just showed that graphic of some 500 00:25:42,840 --> 00:25:45,760 Speaker 7: of the other names over the weekend that publicly endorsed 501 00:25:45,760 --> 00:25:49,560 Speaker 7: officially endorsed President Trump, and for me, this is a 502 00:25:49,600 --> 00:25:52,280 Speaker 7: big story. Cara, I find it so interesting. 503 00:25:52,760 --> 00:25:57,160 Speaker 5: Notable that people are now willingly taking to social platforms, 504 00:25:57,359 --> 00:26:00,119 Speaker 5: many of them will a prevalent user of etel musk 505 00:26:00,119 --> 00:26:03,040 Speaker 5: Sex as well. To make these sorts of endorsements and statements, 506 00:26:03,200 --> 00:26:05,680 Speaker 5: it has to be reflected, and of course many CEOs 507 00:26:05,680 --> 00:26:08,639 Speaker 5: within technology were coming out and condemning the violence that 508 00:26:08,680 --> 00:26:11,879 Speaker 5: we saw this weekend as well, and using social platforms 509 00:26:11,880 --> 00:26:13,920 Speaker 5: of which to do that. But Max just the last 510 00:26:13,920 --> 00:26:17,040 Speaker 5: take on ultimately, whether we see more money weighing in 511 00:26:17,080 --> 00:26:19,719 Speaker 5: here and any clarity on the extent that we hear 512 00:26:19,760 --> 00:26:21,040 Speaker 5: of DA must support. 513 00:26:20,920 --> 00:26:25,399 Speaker 16: You know, Silicon Valley entrepreneurs and CEOs and investors they 514 00:26:25,400 --> 00:26:28,040 Speaker 16: want to back winner. So I don't think it's totally surprising. 515 00:26:28,160 --> 00:26:32,200 Speaker 16: You know, even before this assassination attempt, Trump had had 516 00:26:32,240 --> 00:26:34,119 Speaker 16: a very good couple of weeks. So I don't think 517 00:26:34,160 --> 00:26:36,399 Speaker 16: it's surprising that we're seeing the corporate money flow in 518 00:26:36,560 --> 00:26:39,480 Speaker 16: because that the way these guys think, right is they 519 00:26:39,600 --> 00:26:42,359 Speaker 16: want a voice in whichever they judge to be the 520 00:26:43,119 --> 00:26:46,359 Speaker 16: likely winner. So I think that's part of what's going on, 521 00:26:46,640 --> 00:26:48,800 Speaker 16: And it would not surprise me if we see more 522 00:26:49,200 --> 00:26:52,320 Speaker 16: money from Silicon Valley, and in fact we could see 523 00:26:52,359 --> 00:26:54,720 Speaker 16: you one must take a potentially active role here, either 524 00:26:54,920 --> 00:26:57,159 Speaker 16: you know, just on his X platform or with you know, 525 00:26:57,240 --> 00:27:00,480 Speaker 16: further donations we'll see, But nothing would supper at this 526 00:27:00,520 --> 00:27:02,639 Speaker 16: point as far as Mask and Trump coming closer together, 527 00:27:03,200 --> 00:27:03,920 Speaker 16: nice chef can. 528 00:27:04,000 --> 00:27:07,240 Speaker 5: The perfect voice and all things in learning, we appreciate it. 529 00:27:07,359 --> 00:27:09,639 Speaker 5: Coming up, we're going to be talking to a CEO 530 00:27:09,720 --> 00:27:12,840 Speaker 5: about a further integration in AI. Tell Tom Sebel, founder 531 00:27:12,840 --> 00:27:16,040 Speaker 5: and CEO of C three AI a partnership with Google Cloud. 532 00:27:16,240 --> 00:27:32,240 Speaker 5: This has been by technology. We want to talk about 533 00:27:32,640 --> 00:27:36,440 Speaker 5: AI partnerships. Another one being announced. Tom Sebel of C 534 00:27:36,520 --> 00:27:38,760 Speaker 5: three AI the CEO there to talk us through. What 535 00:27:38,880 --> 00:27:42,320 Speaker 5: is your partnership with Google Cloud, the launcher new AI 536 00:27:42,440 --> 00:27:47,000 Speaker 5: programs and most notably AI for government programs AI, Generative AI. 537 00:27:47,040 --> 00:27:49,639 Speaker 5: We're talking here, Tom, can you just stick into what 538 00:27:49,680 --> 00:27:53,000 Speaker 5: has driven this partnership with Google Cloud ultimately how it 539 00:27:53,200 --> 00:27:56,520 Speaker 5: enables you to serve with government and consumers that little 540 00:27:56,520 --> 00:27:56,880 Speaker 5: bit more. 541 00:27:57,920 --> 00:28:01,280 Speaker 2: Google Cloud has been a great partner and we've been 542 00:28:01,320 --> 00:28:06,560 Speaker 2: working with them at massive scale in state local government, 543 00:28:06,720 --> 00:28:10,480 Speaker 2: Okay to bring solutions there associated with property appraition that 544 00:28:10,520 --> 00:28:14,200 Speaker 2: will associate with law enforcement, and now in state government 545 00:28:14,320 --> 00:28:17,360 Speaker 2: and federal government. We've come up with a very unique 546 00:28:17,359 --> 00:28:24,439 Speaker 2: solution utilizing generative AI to make all the complexities associated 547 00:28:24,480 --> 00:28:29,800 Speaker 2: with things like the Affordable Care Act okay, and all 548 00:28:29,840 --> 00:28:31,760 Speaker 2: of the services that come out of health and human 549 00:28:31,800 --> 00:28:38,000 Speaker 2: services of medicare Medicaid CMS. What have you immediately. 550 00:28:37,320 --> 00:28:38,520 Speaker 3: Accessible to the public. 551 00:28:38,880 --> 00:28:45,080 Speaker 2: We've solved all the difficult problems associated with data expiltration, cybersecurity, hallucination, 552 00:28:45,200 --> 00:28:48,240 Speaker 2: those are gone, and now we deal with these you know, 553 00:28:48,360 --> 00:28:52,120 Speaker 2: these programs that are biblically in scale, in the complexity, 554 00:28:52,400 --> 00:28:54,800 Speaker 2: and you can ask any question in one hundred and 555 00:28:54,840 --> 00:28:58,320 Speaker 2: thirty three languages and get the answer immediately, the correct 556 00:28:58,360 --> 00:29:02,320 Speaker 2: answer the first time in the language that you inquired. 557 00:29:02,400 --> 00:29:05,360 Speaker 2: So it's really it makes it so that governments can 558 00:29:05,400 --> 00:29:10,400 Speaker 2: provide better services at lower cost into more certified constituents. 559 00:29:10,920 --> 00:29:13,440 Speaker 5: And indeed government has been a real strength of C 560 00:29:13,560 --> 00:29:16,880 Speaker 5: three AI. What's also notable is well the fact that 561 00:29:16,880 --> 00:29:18,920 Speaker 5: you're teaming with Google's cloud. 562 00:29:18,960 --> 00:29:19,240 Speaker 4: Here. 563 00:29:19,400 --> 00:29:24,400 Speaker 5: Many might say that actually Microsoft as you and Amazon AWS, well, 564 00:29:24,400 --> 00:29:28,320 Speaker 5: Amazon will broadly these hyperscalers might be your own competition. 565 00:29:28,560 --> 00:29:30,920 Speaker 4: Do you have to do the deal for infrastructure with Google? 566 00:29:31,960 --> 00:29:37,640 Speaker 2: These are all partners. Microsoft is a great partner. AWS 567 00:29:37,720 --> 00:29:39,640 Speaker 2: is a great partner. We do a ton of work 568 00:29:39,640 --> 00:29:44,160 Speaker 2: in the defense and intelligence community with AWS. But let's remember, 569 00:29:44,320 --> 00:29:46,760 Speaker 2: I know that people like to focus on the defense 570 00:29:46,800 --> 00:29:50,560 Speaker 2: and intelligence community. You know, it's roughly twenty percent of 571 00:29:50,600 --> 00:29:52,880 Speaker 2: the federal budget. You know, most of the budget. Is 572 00:29:52,920 --> 00:29:57,880 Speaker 2: it benefits programs, social security, health, insurance, retirement programs, and 573 00:29:57,960 --> 00:30:01,120 Speaker 2: we can use generative AI to allow government to provide 574 00:30:01,160 --> 00:30:04,520 Speaker 2: you know, much higher service requiality services at lower cost. 575 00:30:04,800 --> 00:30:06,760 Speaker 2: This applies not only in the United States. I mean, 576 00:30:06,800 --> 00:30:09,240 Speaker 2: this applies to the National Health Service of the UK. 577 00:30:09,400 --> 00:30:11,400 Speaker 2: This applies to have a sight. 578 00:30:11,480 --> 00:30:12,920 Speaker 6: Let me jump in here for a second. 579 00:30:13,040 --> 00:30:16,080 Speaker 7: I think that Tom may have some zoom issues, which 580 00:30:16,360 --> 00:30:18,320 Speaker 7: we forget is kind of normal in the day and 581 00:30:18,360 --> 00:30:20,720 Speaker 7: age that we live in. I mean, when we get 582 00:30:20,760 --> 00:30:22,240 Speaker 7: him back and we'll work on that car, I think 583 00:30:22,480 --> 00:30:25,040 Speaker 7: what I want to ask him and understand is like, 584 00:30:25,640 --> 00:30:28,800 Speaker 7: is this a vote of confidence in C three AI 585 00:30:28,920 --> 00:30:31,840 Speaker 7: being a technology provider? In other words, Google Cloud are 586 00:30:31,840 --> 00:30:33,959 Speaker 7: like they're quite good. So, mister Cebo, I think you're 587 00:30:34,000 --> 00:30:36,800 Speaker 7: back with us. Thank you for joining us on bloombow technology. Okay, 588 00:30:36,880 --> 00:30:39,280 Speaker 7: so let me give that question to you. Is this 589 00:30:39,360 --> 00:30:42,360 Speaker 7: a sales channel thing where you guys can go to 590 00:30:42,400 --> 00:30:45,800 Speaker 7: a certain customer demographic or is this Google Cloud saying 591 00:30:45,840 --> 00:30:49,320 Speaker 7: actually C three AI has really got something here from 592 00:30:49,360 --> 00:30:51,400 Speaker 7: a product level that we don't have. 593 00:30:52,280 --> 00:30:55,440 Speaker 2: Well, this is a deep technology partnership. We've been working 594 00:30:55,480 --> 00:30:58,280 Speaker 2: with Google Cloud very closely for years. Surely a deep 595 00:30:58,400 --> 00:31:02,000 Speaker 2: technology partnership. Take advantage of the important work they're doing 596 00:31:02,040 --> 00:31:05,280 Speaker 2: with Generative AI and Gemini and make that, you know, 597 00:31:05,520 --> 00:31:10,880 Speaker 2: more accessible using the C three AI platform, which represents 598 00:31:10,920 --> 00:31:12,800 Speaker 2: I don't know, two or three billion dollars for the 599 00:31:12,840 --> 00:31:15,960 Speaker 2: software engineering. So this is a technology partnership that goes 600 00:31:16,000 --> 00:31:21,200 Speaker 2: back some years, and we are partnering technologically. Yes, we 601 00:31:21,280 --> 00:31:25,400 Speaker 2: are jointly developing, and yes, we are jointly servicing and 602 00:31:25,680 --> 00:31:27,960 Speaker 2: selling and servicing customers all around the world. 603 00:31:29,240 --> 00:31:29,920 Speaker 6: Mister Cebel. 604 00:31:30,480 --> 00:31:33,640 Speaker 7: One story recovered earlier in the program was reporting that 605 00:31:34,160 --> 00:31:37,080 Speaker 7: Alphabet or Google are looking at wiz in the m 606 00:31:37,120 --> 00:31:41,560 Speaker 7: and a context you've just partnered with them. It's interesting 607 00:31:41,600 --> 00:31:44,840 Speaker 7: to consider the antitrust repercussions of that. But have you 608 00:31:44,920 --> 00:31:46,520 Speaker 7: seen the report and what do you make of that? 609 00:31:48,000 --> 00:31:50,280 Speaker 2: Well? I think that you know, I mean, one of 610 00:31:50,320 --> 00:31:54,040 Speaker 2: the existential threats that we have to the world relates 611 00:31:54,040 --> 00:31:56,560 Speaker 2: to cybersecurity, and I think that any one of these 612 00:31:56,640 --> 00:32:03,000 Speaker 2: hyperscalers that are beefing up their their cybersecurity capabilities makes 613 00:32:03,000 --> 00:32:05,000 Speaker 2: the world a safer place, So I think it's a 614 00:32:05,000 --> 00:32:05,400 Speaker 2: good thing. 615 00:32:06,120 --> 00:32:08,479 Speaker 5: Tom c Will can't even get onto your thoughts of 616 00:32:08,920 --> 00:32:10,960 Speaker 5: AI in the world of fake news. It's something that 617 00:32:11,000 --> 00:32:12,520 Speaker 5: I know that you've been thinking a lot about. We 618 00:32:12,560 --> 00:32:14,600 Speaker 5: look forward to having you back on the show. Tom Cewill, 619 00:32:14,680 --> 00:32:17,280 Speaker 5: founder and CEO of C three AI, on that partnership 620 00:32:17,280 --> 00:32:19,240 Speaker 5: with Google and what are you looking at now? 621 00:32:19,880 --> 00:32:22,280 Speaker 7: Some of the other news stories today in Talking Tech. 622 00:32:22,360 --> 00:32:25,960 Speaker 7: First up, AutoNation warns of a big hit to second 623 00:32:26,040 --> 00:32:29,440 Speaker 7: quarter earnings. The US car dealership chain says profits could 624 00:32:29,480 --> 00:32:32,120 Speaker 7: be lower by a dollar fifty as shared this after 625 00:32:32,160 --> 00:32:35,760 Speaker 7: a cyber attack left the auto retail industry crippled for 626 00:32:35,840 --> 00:32:39,280 Speaker 7: weeks earlier this month. AutoNation says it does not expect 627 00:32:39,280 --> 00:32:41,480 Speaker 7: to the attack to have a material impact on its 628 00:32:41,520 --> 00:32:46,040 Speaker 7: financial conditions going forward. Plus, smartphone shipments are on the rise. 629 00:32:46,080 --> 00:32:49,680 Speaker 7: That's according to IDC. Global smartphone shipments rows six point 630 00:32:49,720 --> 00:32:54,440 Speaker 7: five percent in the latest quarter. Apple iPhone shipments stabilized 631 00:32:54,640 --> 00:32:57,440 Speaker 7: with forty five point two million handset ship The rise 632 00:32:57,480 --> 00:33:01,400 Speaker 7: comes as smartphone makers including waway In's Roalm, slash prices 633 00:33:01,400 --> 00:33:04,720 Speaker 7: in China to entice consumers in the biggest mobile market, 634 00:33:04,760 --> 00:33:08,280 Speaker 7: and Finally, spending on Korean cultural products is forecast is 635 00:33:08,360 --> 00:33:10,960 Speaker 7: nearly double to one hundred and forty three billion dollars 636 00:33:11,000 --> 00:33:13,720 Speaker 7: by twenty thirty. That's according to new research release by 637 00:33:13,760 --> 00:33:18,440 Speaker 7: TikTok and analytics company Kantar. The sry popularity of the 638 00:33:18,520 --> 00:33:22,360 Speaker 7: k culture products sought an amplificator by social media, which 639 00:33:22,360 --> 00:33:26,320 Speaker 7: has become gathering place for K pop fans who are online. 640 00:33:26,160 --> 00:33:27,400 Speaker 4: Caroy staying in Asia. 641 00:33:27,440 --> 00:33:31,880 Speaker 5: Panasonic CEO Yuki Kasumi spoke to UMG Ryan in Tokyo 642 00:33:32,040 --> 00:33:34,640 Speaker 5: about the need for company managers to feel more of 643 00:33:34,680 --> 00:33:38,080 Speaker 5: a sense of crisis given a low profitability. Kasumi also 644 00:33:38,080 --> 00:33:40,600 Speaker 5: discussed the outlook for Panasonics EE battery business. 645 00:33:40,760 --> 00:33:42,400 Speaker 4: Just take a listen my key. 646 00:33:42,520 --> 00:33:43,160 Speaker 6: You can't do me. 647 00:33:43,200 --> 00:33:45,840 Speaker 15: You are in terms of the sense of crisis, we 648 00:33:45,920 --> 00:33:50,040 Speaker 15: have not fulfilled our commitments and improved our earnings. As 649 00:33:50,080 --> 00:33:53,280 Speaker 15: a result, the group as a whole has not achieved 650 00:33:53,280 --> 00:33:57,560 Speaker 15: a level of profits that meets expectations of investors. This 651 00:33:57,640 --> 00:34:00,200 Speaker 15: has led to a slump in the stock price. Has 652 00:34:00,240 --> 00:34:03,760 Speaker 15: also led to the price to book ratio falling below one. 653 00:34:04,640 --> 00:34:07,360 Speaker 15: I would like to emphasize that all of our management 654 00:34:07,400 --> 00:34:11,400 Speaker 15: team must recognize that this is a critical situation and 655 00:34:11,440 --> 00:34:13,560 Speaker 15: we must manage our businesses accordingly. 656 00:34:14,360 --> 00:34:17,759 Speaker 17: The Evy battery business has been a focus for you, 657 00:34:17,880 --> 00:34:21,240 Speaker 17: but that's been really affected by external demand. 658 00:34:21,320 --> 00:34:21,520 Speaker 4: Right. 659 00:34:21,920 --> 00:34:24,239 Speaker 17: When are you expecting to see a turnaround? And do 660 00:34:24,280 --> 00:34:29,240 Speaker 17: you see any positive signals coming from your strategic partner, Tessa. 661 00:34:30,640 --> 00:34:34,880 Speaker 15: When we start supplying batteries to for example, Mazda and Superu, 662 00:34:35,560 --> 00:34:38,879 Speaker 15: our plant in Japan will be in full operation as 663 00:34:38,920 --> 00:34:42,200 Speaker 15: well as in the US. We will continue to expand 664 00:34:42,200 --> 00:34:44,960 Speaker 15: our business in the US, and we will follow the 665 00:34:44,960 --> 00:34:49,080 Speaker 15: demand of US automakers and invest according to the growth 666 00:34:49,080 --> 00:34:52,120 Speaker 15: of that demand. So in that sense, we will make 667 00:34:52,160 --> 00:34:55,040 Speaker 15: our investments in such a way that the plants will 668 00:34:55,040 --> 00:34:56,840 Speaker 15: not be forced to stop operating. 669 00:34:56,880 --> 00:35:01,120 Speaker 17: Ayonna, what can you tell us then about the US 670 00:35:01,160 --> 00:35:06,279 Speaker 17: demand outlook, especially because you've been doing pretty well in 671 00:35:06,320 --> 00:35:08,800 Speaker 17: your business there. But it's also because of the Inflation 672 00:35:08,920 --> 00:35:13,640 Speaker 17: Reduction Act, Right, And I wonder what are your calculations 673 00:35:13,719 --> 00:35:17,280 Speaker 17: of what happens after the presidential elections if the incentives 674 00:35:17,320 --> 00:35:18,000 Speaker 17: are taken away? 675 00:35:18,200 --> 00:35:22,840 Speaker 15: Well, I have heard that the IRA will not disappear 676 00:35:22,920 --> 00:35:26,680 Speaker 15: immediately if Trump becomes president because of the way the 677 00:35:26,800 --> 00:35:30,120 Speaker 15: US legal system works. This means that it will take 678 00:35:30,120 --> 00:35:33,719 Speaker 15: a few more years. The spread of EVS is expected 679 00:35:33,760 --> 00:35:37,040 Speaker 15: to slow down not only because of the IRA, but 680 00:35:37,120 --> 00:35:41,520 Speaker 15: also because the charging infrastructure is not yet sufficient, and 681 00:35:41,560 --> 00:35:44,640 Speaker 15: I think there are other reasons as well. One reason 682 00:35:44,960 --> 00:35:48,719 Speaker 15: is that evs are expensive even with the IRA, and 683 00:35:48,760 --> 00:35:51,680 Speaker 15: as these issues are resolved, the spread of evs is 684 00:35:51,760 --> 00:35:55,240 Speaker 15: expected to increase in the long term. We will invest 685 00:35:55,280 --> 00:35:58,359 Speaker 15: accordingly and will manage our business in such a way 686 00:35:58,680 --> 00:36:01,560 Speaker 15: that the speed of EV A DOT will not directly 687 00:36:01,600 --> 00:36:02,880 Speaker 15: affect our business condition. 688 00:36:03,040 --> 00:36:05,759 Speaker 17: Are you expecting to see more price competition though in 689 00:36:05,840 --> 00:36:09,360 Speaker 17: the EV battery market, especially from the likes of giants 690 00:36:09,400 --> 00:36:13,080 Speaker 17: like China Coatl for example. Will you need to readjust 691 00:36:13,120 --> 00:36:14,040 Speaker 17: your cost structure. 692 00:36:15,760 --> 00:36:18,200 Speaker 15: There are different types of batteries that can be used 693 00:36:18,239 --> 00:36:23,000 Speaker 15: in cars that prioritize price and sacrifice some performance, and 694 00:36:23,080 --> 00:36:27,239 Speaker 15: those are thoroughly pursued performance and safety. Although there is 695 00:36:27,320 --> 00:36:31,200 Speaker 15: price competition, we will continue to supply equipment and vehicle 696 00:36:31,239 --> 00:36:34,280 Speaker 15: makers that recognize the quality of our batteries. 697 00:36:36,280 --> 00:36:39,960 Speaker 7: That was Bloomberg's Sherry Arms speaking to Panasonic CEO Yuki 698 00:36:40,080 --> 00:36:52,200 Speaker 7: Kasumi in Tokyo Bazu in on Apple The stock hit 699 00:36:52,280 --> 00:36:55,480 Speaker 7: fresh record highs today after an upgrade to buy at 700 00:36:55,520 --> 00:36:59,879 Speaker 7: Loop Capital on the iPhone's AI potential. Morgan Stanley's also 701 00:37:00,080 --> 00:37:03,400 Speaker 7: did the iPhone maker so its top pick list, with 702 00:37:03,520 --> 00:37:06,560 Speaker 7: AI also being seen as a catalyst. 703 00:37:06,640 --> 00:37:10,120 Speaker 5: Caroc Yeah, and I think we need to stick with AI. 704 00:37:10,400 --> 00:37:14,399 Speaker 5: But also revenue being generated internationally. Look in India, where 705 00:37:14,400 --> 00:37:17,040 Speaker 5: Bloomberg is reporting that Apple's revenue has searched thirty three 706 00:37:17,080 --> 00:37:18,840 Speaker 5: percent in the twelve months through March. 707 00:37:19,040 --> 00:37:20,480 Speaker 4: According to a Bloomberg. 708 00:37:20,120 --> 00:37:23,040 Speaker 5: Source, sales during the period were eight billion dollars, up 709 00:37:23,040 --> 00:37:25,400 Speaker 5: from six billion a year ago. Stuff into it, An 710 00:37:25,560 --> 00:37:29,160 Speaker 5: rag Rana of Bloomberg Intelligence, a lot of buoyancy around 711 00:37:29,160 --> 00:37:30,920 Speaker 5: this name today, Ana Ragan, what do you make of 712 00:37:30,960 --> 00:37:31,720 Speaker 5: the Indian sales? 713 00:37:32,760 --> 00:37:35,000 Speaker 11: Yeah, you know, Caroline, I'm in your camp. 714 00:37:35,080 --> 00:37:38,440 Speaker 18: I think the sales pushed from India and China are 715 00:37:38,520 --> 00:37:41,040 Speaker 18: far more important than my view in the you. 716 00:37:41,000 --> 00:37:42,759 Speaker 11: Know, both in the short run in the long run, 717 00:37:42,920 --> 00:37:44,080 Speaker 11: than than AI. 718 00:37:44,239 --> 00:37:47,919 Speaker 18: But you know, very very happy to see that India 719 00:37:48,000 --> 00:37:49,400 Speaker 18: is a very big market for Apple. 720 00:37:49,480 --> 00:37:52,360 Speaker 11: I mean, the end market is over six hundred million. 721 00:37:53,080 --> 00:37:56,360 Speaker 18: Smartphones and Apple has you know, less than five percent 722 00:37:56,400 --> 00:37:58,960 Speaker 18: market shared. So over the long term, I think India 723 00:37:59,000 --> 00:38:01,040 Speaker 18: is going to be a very exciting story for Apple, 724 00:38:01,360 --> 00:38:03,880 Speaker 18: but it's going to take some time because currently China 725 00:38:04,040 --> 00:38:07,680 Speaker 18: is eight times bigger than India. 726 00:38:07,320 --> 00:38:09,920 Speaker 11: In terms of units smartphones or iPhones. 727 00:38:10,160 --> 00:38:12,320 Speaker 18: So China still is the main story at this point 728 00:38:12,320 --> 00:38:13,600 Speaker 18: over the next two to three years. 729 00:38:13,800 --> 00:38:16,480 Speaker 11: But I think India is very exciting for the longer 730 00:38:16,560 --> 00:38:17,640 Speaker 11: future of Apple. 731 00:38:18,400 --> 00:38:19,879 Speaker 6: So it might be like early days. 732 00:38:19,920 --> 00:38:23,080 Speaker 7: But one interesting point of the reporting from Bloomberg was 733 00:38:23,120 --> 00:38:26,080 Speaker 7: that of that eight billion dollar figure, more than half 734 00:38:26,440 --> 00:38:29,920 Speaker 7: was iPhone sales rather than other devices or services. 735 00:38:30,080 --> 00:38:31,200 Speaker 6: How do you have to play. 736 00:38:31,000 --> 00:38:34,319 Speaker 7: The Indian market differently, like in terms of asps or 737 00:38:34,719 --> 00:38:37,960 Speaker 7: your patients for a growing or emerging middle class. 738 00:38:39,080 --> 00:38:41,480 Speaker 18: Yeah, so you know, Apple can truly gain a lot 739 00:38:41,480 --> 00:38:44,399 Speaker 18: of market share in India by you know, let's say 740 00:38:44,600 --> 00:38:46,960 Speaker 18: listening the price of their lower end model. 741 00:38:47,200 --> 00:38:49,040 Speaker 11: But they don't really, you know, play that game. 742 00:38:49,080 --> 00:38:52,480 Speaker 18: They are all about, you know, the margins, and you know, 743 00:38:52,680 --> 00:38:54,799 Speaker 18: they don't play the market share game, so we don't 744 00:38:55,120 --> 00:38:57,640 Speaker 18: see them launching a cheaper phone or anything. I think 745 00:38:57,680 --> 00:39:00,760 Speaker 18: Indian market is going to be gradual. I mean gradually, 746 00:39:00,760 --> 00:39:03,160 Speaker 18: And I say when I compared in China, China is 747 00:39:03,840 --> 00:39:06,400 Speaker 18: Apple market shared in the Chinese market is twenty percent 748 00:39:06,760 --> 00:39:08,359 Speaker 18: and in India it's less than five. 749 00:39:08,400 --> 00:39:12,279 Speaker 11: So you over time, as the Indian consumer becomes. 750 00:39:11,960 --> 00:39:15,840 Speaker 18: More affluent, when purchasing Baba becomes you better than what 751 00:39:15,920 --> 00:39:19,000 Speaker 18: it is right now. We think Apple is one area 752 00:39:19,040 --> 00:39:22,080 Speaker 18: where they'll gravitate to because of the luxury nature of 753 00:39:22,120 --> 00:39:26,040 Speaker 18: the product, because of the brand that's associated with the 754 00:39:26,239 --> 00:39:30,040 Speaker 18: quality it's associated with, and then the prestige. 755 00:39:30,160 --> 00:39:33,000 Speaker 5: And Agrana breaking down the international growth. It is a 756 00:39:33,000 --> 00:39:35,960 Speaker 5: new record high for Apple today. We thank you meanwhile 757 00:39:36,000 --> 00:39:38,040 Speaker 5: that does it for this addition of Bluemog technology. And 758 00:39:38,680 --> 00:39:40,800 Speaker 5: it has been quite the show to be digesting. 759 00:39:41,320 --> 00:39:43,280 Speaker 7: Yeah, and it's going to be a really big week 760 00:39:43,480 --> 00:39:46,400 Speaker 7: in America. You know, our colleagues will continue to broadcast 761 00:39:46,400 --> 00:39:49,160 Speaker 7: from a Walkery and R and C. And here there 762 00:39:49,160 --> 00:39:52,360 Speaker 7: are so many technology stories to tell recap on the podcast. 763 00:39:52,880 --> 00:39:55,600 Speaker 7: Many of you do listen to the podcasts every day. 764 00:39:55,600 --> 00:39:58,080 Speaker 7: You find it on Apple, Spotify, iHeart and of course 765 00:39:58,080 --> 00:40:00,680 Speaker 7: on the Bloomberg platforms as well in New York City 766 00:40:00,719 --> 00:40:01,640 Speaker 7: and San Francisco. 767 00:40:01,960 --> 00:40:03,879 Speaker 6: This is Bloomberg Technology