1 00:00:02,520 --> 00:00:13,200 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is a 2 00:00:13,280 --> 00:00:17,040 Speaker 1: live from coast to coast with Caroline Hide in New 3 00:00:17,120 --> 00:00:20,759 Speaker 1: York and Eva Low in San Francisco. 4 00:00:22,920 --> 00:00:25,560 Speaker 2: This is Bloomberg Tech coming up. Can Apple be the 5 00:00:25,560 --> 00:00:29,200 Speaker 2: AI comeback kid? Details on the company's push into robots 6 00:00:29,320 --> 00:00:30,440 Speaker 2: and a lifelike Siri. 7 00:00:30,600 --> 00:00:33,840 Speaker 3: Plus, we talked to the Cisco CEO, Chuck Robins, fresh 8 00:00:33,880 --> 00:00:37,400 Speaker 3: off earnings, the company seeing AI sales pick up but 9 00:00:37,600 --> 00:00:39,159 Speaker 3: remains cautious on its outlook. 10 00:00:39,159 --> 00:00:43,400 Speaker 2: Perhaps and Bitcoin retreats from record highs are reminder to 11 00:00:43,479 --> 00:00:46,599 Speaker 2: investors that the ditital asset remains a volatile. 12 00:00:46,240 --> 00:00:48,920 Speaker 3: One and it's AI that that is story for Apple 13 00:00:49,320 --> 00:00:52,640 Speaker 3: because as tech giants are really trying to plot their 14 00:00:52,680 --> 00:00:56,760 Speaker 3: AI focus, it's plotting it's comeback. The efforts centers on robotics, 15 00:00:56,760 --> 00:01:00,720 Speaker 3: on lifelike syriad as you said, and home security. Yesterday, 16 00:01:01,280 --> 00:01:04,280 Speaker 3: some two percent as investors bet this move could really 17 00:01:04,280 --> 00:01:06,200 Speaker 3: help Apple and get its mojo back. Let's go to 18 00:01:06,200 --> 00:01:09,120 Speaker 3: Mark German, who breaks the story yesterday on the future 19 00:01:09,120 --> 00:01:12,679 Speaker 3: of AI. Today, we're going into blood Oxygen readings as well, 20 00:01:12,720 --> 00:01:14,720 Speaker 3: but start with the AI focus. 21 00:01:14,800 --> 00:01:15,640 Speaker 4: What can we expect? 22 00:01:16,600 --> 00:01:19,000 Speaker 5: You know, Apple is a hardware company, right, all these 23 00:01:19,000 --> 00:01:23,480 Speaker 5: companies Chat, GPT, Google, Gemini, Microsoft, they have all these 24 00:01:23,560 --> 00:01:27,639 Speaker 5: AI features, but from a consumer standpoint, it really hasn't 25 00:01:27,680 --> 00:01:31,000 Speaker 5: been monetized. How does Apple monetize its products well by 26 00:01:31,319 --> 00:01:34,040 Speaker 5: selling hardware, getting people to go to Apple stores and 27 00:01:34,080 --> 00:01:36,600 Speaker 5: buy new stuff every year or two. And so they're 28 00:01:36,640 --> 00:01:39,720 Speaker 5: going to replay that strategy when it comes to artificial intelligence, 29 00:01:40,080 --> 00:01:42,959 Speaker 5: and the way they see AI is by integrating it 30 00:01:43,080 --> 00:01:47,760 Speaker 5: and creating devices around the smart home, home cameras and robotics. 31 00:01:48,040 --> 00:01:50,040 Speaker 5: So the company is working on several items that are 32 00:01:50,040 --> 00:01:54,120 Speaker 5: reported yesterday. The centerpiece of the strategy is a tabletop robot. 33 00:01:54,440 --> 00:01:57,080 Speaker 5: This is essentially a virtual companion that you would have 34 00:01:57,120 --> 00:01:59,480 Speaker 5: in your bedroom on your nightstand, you could have in 35 00:01:59,520 --> 00:02:01,800 Speaker 5: your office on your desk, can have on a kitchen counter. 36 00:02:02,280 --> 00:02:05,200 Speaker 5: It uses a robotic arm to move around in space. 37 00:02:05,520 --> 00:02:06,200 Speaker 6: It's like an. 38 00:02:06,080 --> 00:02:09,680 Speaker 5: iPad that can move through thin air on that robotic limb. 39 00:02:09,760 --> 00:02:11,600 Speaker 5: He could help you get things done through your day. 40 00:02:11,919 --> 00:02:14,680 Speaker 5: You can hold conversations with it. If you're having a 41 00:02:14,720 --> 00:02:17,840 Speaker 5: conversation with another human being, it can even interject and 42 00:02:17,960 --> 00:02:20,919 Speaker 5: jump in as if it's a third person in the room. 43 00:02:21,360 --> 00:02:22,960 Speaker 6: You can consume video on it. 44 00:02:22,960 --> 00:02:24,000 Speaker 7: It has FaceTime. 45 00:02:24,600 --> 00:02:28,440 Speaker 5: There's also a smart home POB basically a home pod 46 00:02:28,480 --> 00:02:32,000 Speaker 5: with a screen coming out next spring. This is going 47 00:02:32,080 --> 00:02:35,560 Speaker 5: to have similar functionality to that device, without the conversational 48 00:02:35,600 --> 00:02:39,200 Speaker 5: abilities and without the robotic arm. And they're developing a 49 00:02:39,200 --> 00:02:43,440 Speaker 5: suite of home security in home automation products designed to 50 00:02:43,520 --> 00:02:46,440 Speaker 5: rival what Amazon has been doing with a ring and 51 00:02:46,639 --> 00:02:49,040 Speaker 5: Blink and what Google has been doing with Nest and 52 00:02:49,080 --> 00:02:52,760 Speaker 5: other companies of course in the space include ADT and Roku. 53 00:02:54,440 --> 00:02:56,720 Speaker 7: There is a software component, and that is Siri. 54 00:02:57,200 --> 00:03:01,239 Speaker 2: You write about a lifelike Siri, sources describe it to 55 00:03:01,320 --> 00:03:02,079 Speaker 2: you park. 56 00:03:02,600 --> 00:03:05,880 Speaker 5: Well, the lifelike Siri is the ability to hold conversations, 57 00:03:06,240 --> 00:03:10,079 Speaker 5: help you get things done, interject into conversations with other 58 00:03:10,200 --> 00:03:12,320 Speaker 5: human beings as if it's another person in the room, 59 00:03:12,880 --> 00:03:15,560 Speaker 5: very similar to what you're seeing on voice mode from Chat, 60 00:03:15,639 --> 00:03:19,079 Speaker 5: GPT and from Gemini and some of these other LM 61 00:03:19,160 --> 00:03:22,880 Speaker 5: based assistants. There's also a revamp next year to Siri 62 00:03:23,280 --> 00:03:26,079 Speaker 5: on the iPhone, the iPad and the Mac that's coming. 63 00:03:26,160 --> 00:03:30,600 Speaker 5: It's an underlying infrastructural change, but there's also a redesign, 64 00:03:30,760 --> 00:03:33,400 Speaker 5: like a visual redesign to Siri coming as well to 65 00:03:33,440 --> 00:03:37,720 Speaker 5: the iPhone and iPad on the home devices. Specifically, they're 66 00:03:37,760 --> 00:03:42,240 Speaker 5: going to be creating a visual personality for Siri. Obviously Siri, 67 00:03:42,280 --> 00:03:45,320 Speaker 5: obviously you heard it and you spoke to it. Now 68 00:03:45,320 --> 00:03:47,400 Speaker 5: you're going to be able to see it too. If 69 00:03:47,400 --> 00:03:50,640 Speaker 5: you remember Microsoft Clippy's Clippy from the nineties and the 70 00:03:50,640 --> 00:03:54,480 Speaker 5: early two thousands in Microsoft Suite of Office apps, including Word, 71 00:03:54,960 --> 00:03:58,160 Speaker 5: something similar to that. It floats around your display. You 72 00:03:58,160 --> 00:04:01,080 Speaker 5: can interact with it at any time. They're actually trying 73 00:04:01,120 --> 00:04:04,760 Speaker 5: to create a virtual character, either based on a memoji 74 00:04:05,320 --> 00:04:08,400 Speaker 5: or the finder icon that's the filesystem logo that Apple's 75 00:04:08,440 --> 00:04:10,280 Speaker 5: used for years on the Mac. 76 00:04:11,200 --> 00:04:16,000 Speaker 3: Very briefly mark the Blood Oxygen the workaround versus Messimo's 77 00:04:16,040 --> 00:04:16,920 Speaker 3: fight on Apple. 78 00:04:17,440 --> 00:04:18,760 Speaker 4: Is it going to make much of an effect in 79 00:04:18,760 --> 00:04:19,160 Speaker 4: the long term? 80 00:04:20,160 --> 00:04:23,560 Speaker 5: You know, it's interesting because this workaround is, like you said, 81 00:04:23,600 --> 00:04:26,000 Speaker 5: a real workaround. You're not going to have the blood 82 00:04:26,040 --> 00:04:29,560 Speaker 5: Oxygen app like you had before on the Apple Watch. Instead, 83 00:04:29,600 --> 00:04:32,640 Speaker 5: the sensors will be used and that will allow you 84 00:04:32,720 --> 00:04:35,680 Speaker 5: to read that data on the phone itself through the 85 00:04:35,720 --> 00:04:36,200 Speaker 5: health app. 86 00:04:36,279 --> 00:04:38,040 Speaker 6: So it took them two years. 87 00:04:38,320 --> 00:04:40,599 Speaker 5: The US Customs Agency finally allowed them to do this 88 00:04:40,640 --> 00:04:43,320 Speaker 5: workaround and it comes at a pretty opportune time. In 89 00:04:43,360 --> 00:04:45,640 Speaker 5: a few weeks they'll be announcing the next Apple watches, 90 00:04:45,920 --> 00:04:47,080 Speaker 5: and now they'll be able. 91 00:04:46,880 --> 00:04:50,040 Speaker 6: To market in the US. Blood oxygen saturation tracking is 92 00:04:50,080 --> 00:04:50,520 Speaker 6: part of that. 93 00:04:51,880 --> 00:04:55,160 Speaker 2: Bloomberg's Mark Guerman, who leads our coverage of consumer electrolics 94 00:04:55,160 --> 00:04:57,839 Speaker 2: and broke detail on what happens next on Apple for 95 00:04:57,920 --> 00:05:01,000 Speaker 2: more and what Apple's doing than I's web Bush joins us. 96 00:05:01,200 --> 00:05:01,360 Speaker 6: Look. 97 00:05:01,680 --> 00:05:04,039 Speaker 2: Mark's reporting moves the needle right. We know that this 98 00:05:04,160 --> 00:05:07,760 Speaker 2: tabletop robot will be the centerpiece on the hardware side. 99 00:05:08,000 --> 00:05:11,159 Speaker 2: We know that Siri will be made more lifelike. Has 100 00:05:11,200 --> 00:05:14,039 Speaker 2: this changed things for you, Dan in what you're modeling 101 00:05:14,040 --> 00:05:17,400 Speaker 2: for Apple? And to kind of comeback that many think 102 00:05:17,400 --> 00:05:21,000 Speaker 2: that Apple needs to have in the AI domain, Look. 103 00:05:21,000 --> 00:05:23,919 Speaker 8: In their AI strategy has been a disaster, and you 104 00:05:23,920 --> 00:05:27,280 Speaker 8: know it's if you look at every other big tech company, 105 00:05:28,000 --> 00:05:31,840 Speaker 8: you know Apple is massively behind. And I think when 106 00:05:31,839 --> 00:05:34,920 Speaker 8: you look at this as a potential opportunity, I think 107 00:05:35,320 --> 00:05:39,760 Speaker 8: Street is basically shrugged the shoulders. I mean robotics, Apple's 108 00:05:39,800 --> 00:05:42,880 Speaker 8: going to come out in another device. Look look it 109 00:05:43,000 --> 00:05:46,359 Speaker 8: up in AI Bok, a Microsoft book and meta. I 110 00:05:46,360 --> 00:05:48,960 Speaker 8: mean it speaks to our view right now, it's an 111 00:05:49,080 --> 00:05:54,280 Speaker 8: F one race and Manza. It's all passing thereby an 112 00:05:54,320 --> 00:05:58,719 Speaker 8: Apple and cooker watch from a park bench drinking a cappuccino. 113 00:06:00,600 --> 00:06:03,640 Speaker 2: That's actually a really interesting I think maybe veiled dan 114 00:06:03,680 --> 00:06:08,480 Speaker 2: reference to WWDC, which opened up with the F one sequence. 115 00:06:08,520 --> 00:06:11,520 Speaker 2: If you remember, then that puts the emphasis back on Siri. 116 00:06:12,279 --> 00:06:14,599 Speaker 2: What how much better does Siri need to be then? 117 00:06:14,880 --> 00:06:17,080 Speaker 2: If it is to be a tool use daily by 118 00:06:17,120 --> 00:06:19,159 Speaker 2: technology users around the world in the same way that 119 00:06:19,200 --> 00:06:20,920 Speaker 2: chat GPT is an Apple on my iPhone? 120 00:06:21,839 --> 00:06:25,719 Speaker 6: Look, what's just call it? It is like Siri. 121 00:06:26,160 --> 00:06:29,400 Speaker 8: Nothing's going to happen internally, I mean internally, this has 122 00:06:29,440 --> 00:06:32,159 Speaker 8: been a disaster. Right If you go back to WWDC, 123 00:06:32,839 --> 00:06:35,480 Speaker 8: it felt like Michael J. Fox back to the future 124 00:06:35,520 --> 00:06:39,280 Speaker 8: moment in twenty sixteen. They continue to promise what's on 125 00:06:39,320 --> 00:06:42,520 Speaker 8: the come, what's next? They're going to have to do 126 00:06:42,560 --> 00:06:45,080 Speaker 8: an acquisition. I mean, look, it's just it's the reality 127 00:06:45,120 --> 00:06:49,000 Speaker 8: of the situation. It's not happening internally, and there's no 128 00:06:49,040 --> 00:06:53,240 Speaker 8: one on the street that believes any innovation is coming 129 00:06:53,279 --> 00:06:56,720 Speaker 8: out of Apple when it comes to AI organically. 130 00:06:57,080 --> 00:07:00,040 Speaker 3: Dan, you still got an outperform and a two and 131 00:07:00,160 --> 00:07:01,920 Speaker 3: seventy dollars price target on Apple. 132 00:07:02,279 --> 00:07:03,520 Speaker 4: You're sounding way more. 133 00:07:03,480 --> 00:07:07,000 Speaker 3: Cautious than your money perspective is leading us. 134 00:07:07,760 --> 00:07:11,080 Speaker 8: Yeah, look to get to two seventies. No, AI, this 135 00:07:11,160 --> 00:07:13,040 Speaker 8: is a stock that's going to move higher. And even 136 00:07:13,120 --> 00:07:16,440 Speaker 8: saw what happened last week with the tariffs, Cook obviously 137 00:07:16,440 --> 00:07:19,360 Speaker 8: playing nice in the sandbox with Trump, that was a 138 00:07:19,400 --> 00:07:21,160 Speaker 8: huge relief and the stocks had to move. And I 139 00:07:21,200 --> 00:07:23,160 Speaker 8: think there's a stock that could go to two seventy 140 00:07:23,240 --> 00:07:26,920 Speaker 8: or potentially two eighty without AI. But for this to 141 00:07:27,000 --> 00:07:30,680 Speaker 8: be a three point fifty four hundred, four hundred and 142 00:07:30,680 --> 00:07:35,840 Speaker 8: fifty dollars stock, it's AI and it's not happening internally. 143 00:07:36,640 --> 00:07:39,920 Speaker 8: And I think that's the problem that the street has 144 00:07:40,080 --> 00:07:43,720 Speaker 8: is that things like robotics next Gen or three thousand 145 00:07:43,720 --> 00:07:46,560 Speaker 8: dollars buys to four thousand dollars. It's all about software 146 00:07:47,040 --> 00:07:50,600 Speaker 8: and it comes down to like they need two essentially, 147 00:07:50,600 --> 00:07:53,560 Speaker 8: and we've talked about perplexity. Other acquisitions are going to 148 00:07:53,640 --> 00:07:58,640 Speaker 8: have to do. It's not happening internally. That's just the reality. 149 00:07:59,640 --> 00:08:02,240 Speaker 3: What's interesting, Dan is the notes you have been putting out, 150 00:08:02,480 --> 00:08:05,239 Speaker 3: for example today, have been more around. As you just said, 151 00:08:05,280 --> 00:08:08,520 Speaker 3: there was a relief when Tim Cook was alongside President 152 00:08:08,560 --> 00:08:10,760 Speaker 3: Trump last week. Well, this week it's all been about 153 00:08:10,800 --> 00:08:13,240 Speaker 3: what President Trump has meant for in video of AMD 154 00:08:13,440 --> 00:08:16,240 Speaker 3: and for paying to play. What do you make of 155 00:08:16,280 --> 00:08:18,760 Speaker 3: the moves that we've seen and to gain access in China. 156 00:08:19,640 --> 00:08:23,360 Speaker 8: Look, it speaks to I mean, you know a godfather quote, right, 157 00:08:23,400 --> 00:08:25,760 Speaker 8: I mean it's a deal you can't refuse. And I 158 00:08:25,800 --> 00:08:29,480 Speaker 8: think the reality is is that big tech CEOs are 159 00:08:29,560 --> 00:08:31,000 Speaker 8: learning the new rules. 160 00:08:30,680 --> 00:08:31,120 Speaker 6: Of the game. 161 00:08:31,280 --> 00:08:34,200 Speaker 8: Now, of course it's wed godfather of AI, Jensen and video. 162 00:08:34,679 --> 00:08:39,160 Speaker 8: They need to do with fifteen percent, it's breadcrumbs relative 163 00:08:39,200 --> 00:08:41,520 Speaker 8: to getting into a China market. They can't give this 164 00:08:41,679 --> 00:08:44,480 Speaker 8: the fall in a silver platter, and I viewed as 165 00:08:44,559 --> 00:08:47,120 Speaker 8: bullish and it's going to put more fuel in the 166 00:08:47,160 --> 00:08:48,520 Speaker 8: engine of this AI round. 167 00:08:49,800 --> 00:08:51,040 Speaker 7: Dan super quickly. 168 00:08:51,480 --> 00:08:54,360 Speaker 2: We broke the story last week that Dojo is no 169 00:08:54,480 --> 00:08:56,959 Speaker 2: more at Tesla, and Musk has come out on x 170 00:08:57,040 --> 00:08:59,600 Speaker 2: ray and kind of explained it the focus on AI 171 00:08:59,640 --> 00:09:00,679 Speaker 2: five and a six. 172 00:09:01,040 --> 00:09:02,719 Speaker 7: But how did you react to that. I don't think 173 00:09:02,760 --> 00:09:03,400 Speaker 7: I saw a note. 174 00:09:03,679 --> 00:09:05,960 Speaker 2: And what do you think about the stop gap between 175 00:09:06,000 --> 00:09:07,760 Speaker 2: those generations of customs silicon? 176 00:09:08,559 --> 00:09:11,120 Speaker 8: Yeah, that that's a great story that you guys, Broke, 177 00:09:11,200 --> 00:09:13,440 Speaker 8: I mean I view it as this is to me, 178 00:09:13,520 --> 00:09:16,240 Speaker 8: it's more certainty that Xai. They're going to have a 179 00:09:16,320 --> 00:09:19,920 Speaker 8: massive investment XAI. That'll come at the shareholder meeting, but 180 00:09:20,040 --> 00:09:22,320 Speaker 8: it speaks to our view. It's why Tesla stocklifting. I 181 00:09:22,320 --> 00:09:25,000 Speaker 8: think more and more recognizing this is going to be 182 00:09:25,000 --> 00:09:28,040 Speaker 8: a holistic strategy Tesla Xai. 183 00:09:28,040 --> 00:09:30,040 Speaker 6: It's all about autonomous and robotics. 184 00:09:30,080 --> 00:09:32,280 Speaker 8: And I think that was a view you kind of 185 00:09:32,280 --> 00:09:34,880 Speaker 8: read through the tea leaves that that was my view. 186 00:09:35,920 --> 00:09:38,440 Speaker 4: That nice web Bush. Great to catch up with you. 187 00:09:38,559 --> 00:09:38,960 Speaker 4: Thank you. 188 00:09:39,080 --> 00:09:42,960 Speaker 3: Meanwhile, coming up, ciscosio Chuck Robbins joining us to discuss 189 00:09:42,960 --> 00:09:45,520 Speaker 3: the company's earnings, the state of AI infrastructure demand. 190 00:09:46,280 --> 00:09:47,320 Speaker 4: This is Bloomberg Tech. 191 00:10:00,080 --> 00:10:03,160 Speaker 2: So Cisco shares it down about one point two one 192 00:10:03,160 --> 00:10:05,079 Speaker 2: point three percent. They've made an effort earlier in the 193 00:10:05,120 --> 00:10:07,680 Speaker 2: session to kind of bounce back. We got this full 194 00:10:07,760 --> 00:10:11,000 Speaker 2: year revenue outlook for fiscal twenty six. Some analysts felt 195 00:10:11,040 --> 00:10:13,680 Speaker 2: it was a little cautious, but we're seeing AI infrastructure 196 00:10:13,800 --> 00:10:17,000 Speaker 2: orders pick up. Delighted to say that we're joined now 197 00:10:17,160 --> 00:10:20,560 Speaker 2: by Cisco CEO Chuck Robins, and actually, Chuck, I'm going 198 00:10:20,640 --> 00:10:22,320 Speaker 2: to ask you something that I felt like the analyst 199 00:10:22,360 --> 00:10:25,120 Speaker 2: community didn't really get to, and that is that there 200 00:10:25,200 --> 00:10:30,280 Speaker 2: is this big products refresh happening mere term overcoming years. 201 00:10:30,320 --> 00:10:32,640 Speaker 2: And I feel like you've been trying to talk about 202 00:10:32,679 --> 00:10:35,839 Speaker 2: Cisco as a platform offering for a while and if 203 00:10:35,840 --> 00:10:38,319 Speaker 2: we look at that fiscal twenty six outlook is that 204 00:10:38,440 --> 00:10:41,679 Speaker 2: baked into that where Cisco is a platform offering and 205 00:10:41,720 --> 00:10:44,079 Speaker 2: you folded security into it. That's kind of what I 206 00:10:44,120 --> 00:10:45,080 Speaker 2: think people want to know. 207 00:10:46,240 --> 00:10:48,200 Speaker 9: Yes, well, first of all, thanks for having me, and 208 00:10:48,400 --> 00:10:50,600 Speaker 9: I do I want to thank the team and all 209 00:10:50,920 --> 00:10:53,400 Speaker 9: of the Cisco folks for just a great year. We 210 00:10:54,320 --> 00:10:56,880 Speaker 9: obviously had good order growth in Q four we had 211 00:10:56,920 --> 00:11:01,679 Speaker 9: the great performance in the AI infrastructure order. We actually 212 00:11:02,280 --> 00:11:05,439 Speaker 9: reported that we had taken down a approximately a billion 213 00:11:05,440 --> 00:11:07,640 Speaker 9: dollars of revenue from those orders, which was something that 214 00:11:07,679 --> 00:11:10,560 Speaker 9: everybody wanted to talk about. We talked through how we 215 00:11:10,720 --> 00:11:14,160 Speaker 9: filled the progress kicking in on security, and then to 216 00:11:14,200 --> 00:11:17,320 Speaker 9: your point, this product refresh cycle that we are beginning 217 00:11:18,400 --> 00:11:24,040 Speaker 9: will happen over years, and honestly, we just turned on orderability. 218 00:11:24,640 --> 00:11:27,600 Speaker 9: Large customers take a lot of time to evaluate put 219 00:11:27,600 --> 00:11:28,920 Speaker 9: these things in labs before they. 220 00:11:28,880 --> 00:11:30,360 Speaker 6: Put it in their critical infrastructure. 221 00:11:30,679 --> 00:11:32,800 Speaker 9: But the points you make about the platform is really 222 00:11:32,880 --> 00:11:38,120 Speaker 9: important because as we get into agentic AI, with the 223 00:11:38,160 --> 00:11:42,559 Speaker 9: low latency constant communication that's going to occur, we're going 224 00:11:42,600 --> 00:11:44,920 Speaker 9: to have to do security in the network. 225 00:11:45,360 --> 00:11:46,680 Speaker 6: There is no other alternative. 226 00:11:46,720 --> 00:11:49,920 Speaker 9: You cannot introduce latency by sending it to a security appliance, 227 00:11:50,480 --> 00:11:53,040 Speaker 9: and we are the only company that has both networking 228 00:11:53,160 --> 00:11:55,920 Speaker 9: and security technology to fuse it together to create that 229 00:11:55,960 --> 00:11:57,400 Speaker 9: platform effect that you're describing. 230 00:11:59,200 --> 00:12:03,760 Speaker 2: AI is a double edged sword, Chuck, It's margin dilutive. 231 00:12:05,040 --> 00:12:06,160 Speaker 2: How do you think about that? 232 00:12:07,600 --> 00:12:09,600 Speaker 9: Well, I think we have always had a portfolio of 233 00:12:09,640 --> 00:12:12,880 Speaker 9: products that had various margin profiles. I mean, we had 234 00:12:12,880 --> 00:12:15,120 Speaker 9: a point in our history where the Tolco and the 235 00:12:15,160 --> 00:12:17,520 Speaker 9: service provider world was as much as thirty five thirty 236 00:12:17,559 --> 00:12:19,280 Speaker 9: six percent of our business, and that was a different 237 00:12:19,280 --> 00:12:23,200 Speaker 9: margin profile than the enterprise and so we just manage 238 00:12:23,200 --> 00:12:25,080 Speaker 9: it the same way we have all along. 239 00:12:25,200 --> 00:12:26,800 Speaker 6: So I'm not too worried about that. 240 00:12:27,520 --> 00:12:31,120 Speaker 3: Meanwhile, Chuck, that massive opportunity ahead that you articulate with 241 00:12:31,200 --> 00:12:34,320 Speaker 3: AI infrastructure, that bringing in of two billion of orders, 242 00:12:34,360 --> 00:12:37,640 Speaker 3: the billion dollars of revenue already. Is it the platform 243 00:12:37,679 --> 00:12:40,320 Speaker 3: offering that helps you push out and fend against some 244 00:12:40,360 --> 00:12:42,240 Speaker 3: of the other competitors that want in on that. 245 00:12:42,360 --> 00:12:44,199 Speaker 4: Of course HPE is trying to get in. You've got 246 00:12:44,200 --> 00:12:46,280 Speaker 4: broad Com. Is that how you set yourself apart? 247 00:12:47,440 --> 00:12:49,319 Speaker 9: Well, I think the key to remember with this is 248 00:12:49,360 --> 00:12:52,240 Speaker 9: that it's networking systems and it's optics. That's primarily what 249 00:12:52,360 --> 00:12:56,200 Speaker 9: we're selling for AI infrastructure, and there's really only three 250 00:12:56,600 --> 00:12:59,440 Speaker 9: companies on the planet that can deliver the networking silicon 251 00:12:59,559 --> 00:13:03,040 Speaker 9: that these customers require, and we're one of them. And so, 252 00:13:03,800 --> 00:13:06,040 Speaker 9: you know, they're looking for low power requirements, they're looking 253 00:13:06,040 --> 00:13:09,319 Speaker 9: for meeting their dates, they're looking for speed, bandwidth deployment, 254 00:13:09,800 --> 00:13:12,880 Speaker 9: you know, and we're hitting that right now with them. 255 00:13:12,880 --> 00:13:15,400 Speaker 9: And we've really built great relationships. If you if you 256 00:13:15,440 --> 00:13:16,959 Speaker 9: go back five or six years ago, I had to 257 00:13:17,040 --> 00:13:19,600 Speaker 9: try to convince people that we were rebuilding relationships here. 258 00:13:19,600 --> 00:13:21,920 Speaker 9: And even if you go back fifty twelve fourteen months 259 00:13:21,960 --> 00:13:24,440 Speaker 9: ago when we gave them the target of one billion 260 00:13:24,440 --> 00:13:25,840 Speaker 9: dollars in orders, I think there were a lot of 261 00:13:25,840 --> 00:13:28,640 Speaker 9: skeptics and the team actually delivered really well and we 262 00:13:28,679 --> 00:13:30,480 Speaker 9: have great relationships with these customers. 263 00:13:30,559 --> 00:13:34,400 Speaker 3: Now we are joined by Chuck Robins, Cisco CEO, and 264 00:13:34,760 --> 00:13:37,920 Speaker 3: you know, you beat your things that previously others were 265 00:13:37,960 --> 00:13:40,800 Speaker 3: cynical of, but the market moves with you. Many wanted 266 00:13:40,960 --> 00:13:44,600 Speaker 3: even more in terms of your full year revenue guidance. 267 00:13:44,960 --> 00:13:46,360 Speaker 3: Some are even going as far as to say that 268 00:13:46,400 --> 00:13:48,480 Speaker 3: maybe you're suggesting a little bit of a cautious it 269 00:13:48,800 --> 00:13:50,360 Speaker 3: spend for the next fiscal year. 270 00:13:50,520 --> 00:13:53,559 Speaker 7: Do you abide by that, Chuck, No, we don't see that. 271 00:13:53,640 --> 00:13:56,560 Speaker 9: We see we haven't seen any sort of slowdown at all. 272 00:13:57,000 --> 00:13:59,880 Speaker 9: The only place we've seen that challenge, as has been reported, 273 00:14:00,160 --> 00:14:03,920 Speaker 9: in US Federal our product order growth was seven percent. 274 00:14:03,960 --> 00:14:06,400 Speaker 9: If you take out US Federal, we grew ten percent. 275 00:14:07,400 --> 00:14:09,839 Speaker 9: And if you think about security, same thing. If we 276 00:14:09,880 --> 00:14:12,800 Speaker 9: take out a US federal we grew double digits and 277 00:14:12,840 --> 00:14:16,440 Speaker 9: security on orders. And I also talked about the fact 278 00:14:16,440 --> 00:14:18,120 Speaker 9: that if we look at the fiscal year that we 279 00:14:18,240 --> 00:14:22,000 Speaker 9: just entered, our US Federal team is actually forecasting a 280 00:14:22,040 --> 00:14:23,960 Speaker 9: return to growth, so hopefully that won't be a head 281 00:14:23,960 --> 00:14:26,760 Speaker 9: win in the next year. So we haven't seen anything meaningful, 282 00:14:26,800 --> 00:14:29,680 Speaker 9: but we're also cognizant that we were operating in a 283 00:14:29,720 --> 00:14:31,720 Speaker 9: pretty complex and dynamic environment. 284 00:14:33,480 --> 00:14:33,680 Speaker 7: Chuck. 285 00:14:33,720 --> 00:14:37,240 Speaker 2: We love to talk about the big projects on Bloomberg Tech, 286 00:14:37,280 --> 00:14:40,600 Speaker 2: the big data center projects. Are there any specific examples 287 00:14:40,640 --> 00:14:43,120 Speaker 2: of projects you're involved in that do you think are 288 00:14:43,120 --> 00:14:44,560 Speaker 2: really needle moving for Cisco? 289 00:14:46,040 --> 00:14:49,560 Speaker 9: Well, all the cloud providers are needle moving, and over 290 00:14:49,640 --> 00:14:51,960 Speaker 9: time the neo cloud segment as well as the sovereign 291 00:14:52,000 --> 00:14:54,480 Speaker 9: clouds we think are going to will be a big 292 00:14:54,480 --> 00:14:58,040 Speaker 9: part of our business. Also we're just getting started in those. 293 00:14:58,440 --> 00:15:01,440 Speaker 9: If I hit on a few of those. The sovereign 294 00:15:01,520 --> 00:15:04,920 Speaker 9: AI data centers that we talked about in UAE as 295 00:15:04,960 --> 00:15:06,760 Speaker 9: well as in Saudi are the early ones. We're having 296 00:15:06,760 --> 00:15:11,240 Speaker 9: discussions in other Asian countries, in Africa, in Europe, you 297 00:15:11,280 --> 00:15:15,920 Speaker 9: have this push for on prem sovereign applications, So from 298 00:15:16,000 --> 00:15:19,280 Speaker 9: geopolitical perspective and a risk perspective, they want more control 299 00:15:19,320 --> 00:15:21,200 Speaker 9: over the tech stack that they have in their countries. 300 00:15:21,200 --> 00:15:23,440 Speaker 9: So that's more of a sovereign play, and we're one 301 00:15:23,480 --> 00:15:27,000 Speaker 9: of the unique companies who can actually deliver say Splunk 302 00:15:27,040 --> 00:15:31,040 Speaker 9: on prem or they're asking for WebEx on prem, which 303 00:15:31,080 --> 00:15:33,320 Speaker 9: we can do so. And then the neo clouds we 304 00:15:33,360 --> 00:15:35,840 Speaker 9: could talk about as well, but that's another emerging opportunity 305 00:15:35,840 --> 00:15:36,200 Speaker 9: for US. 306 00:15:37,680 --> 00:15:42,200 Speaker 2: I don't think many appreciate the scale of Cisco. Sometimes 307 00:15:43,000 --> 00:15:44,240 Speaker 2: you've got a lot of credit by the way, on 308 00:15:44,240 --> 00:15:47,240 Speaker 2: this program at least about how you've communicated tariff's impact. 309 00:15:47,600 --> 00:15:50,360 Speaker 2: But you're basically one of the biggest and leading network 310 00:15:50,440 --> 00:15:54,960 Speaker 2: chip producers globally, and this is an administration that wants 311 00:15:55,000 --> 00:15:57,920 Speaker 2: more US manufacturing. So you have the volume of gear, 312 00:15:57,960 --> 00:16:00,360 Speaker 2: you design your own chips, TSMC makes them for you. 313 00:16:00,400 --> 00:16:03,240 Speaker 2: The economics kind of works in your favor. Have you 314 00:16:03,360 --> 00:16:06,360 Speaker 2: made some commitment to do what this administration is trying 315 00:16:06,400 --> 00:16:09,800 Speaker 2: to do, which is take that process that you've mastered, 316 00:16:10,000 --> 00:16:12,600 Speaker 2: but just bring it to the States in some form. 317 00:16:13,520 --> 00:16:18,400 Speaker 9: Well, I think that much like you know, Nvidia, AMDUS others, 318 00:16:18,800 --> 00:16:21,400 Speaker 9: there are a lot of companies that actually rely on 319 00:16:21,480 --> 00:16:25,960 Speaker 9: TSMC the for the fabrication of the silicon, and they've 320 00:16:26,000 --> 00:16:29,240 Speaker 9: obviously made commitments on their side to actually build out 321 00:16:29,280 --> 00:16:32,280 Speaker 9: capacity in the United States, and so we're happy to 322 00:16:32,320 --> 00:16:35,920 Speaker 9: see that happening. The thing that people don't really realize 323 00:16:36,000 --> 00:16:39,480 Speaker 9: is that we've maintained a US manufacturing footprint all along, 324 00:16:40,040 --> 00:16:42,560 Speaker 9: and so we have a footprint in the US today 325 00:16:42,600 --> 00:16:46,760 Speaker 9: that we can look at expanding. But I think it's 326 00:16:46,800 --> 00:16:49,800 Speaker 9: just important for us right now to wait and see 327 00:16:49,800 --> 00:16:51,880 Speaker 9: exactly where all this stuff lands. If you go back 328 00:16:51,880 --> 00:16:56,240 Speaker 9: to twenty eighteen when the China tariffs hit. Our teams 329 00:16:56,000 --> 00:16:59,520 Speaker 9: have made moves and mitigated roughly eighty percent or so 330 00:16:59,640 --> 00:17:02,760 Speaker 9: of those, and so we just continue to look at 331 00:17:02,760 --> 00:17:04,639 Speaker 9: these things as they come out, figure out what the 332 00:17:04,640 --> 00:17:06,399 Speaker 9: best plan of action is, and then we act. 333 00:17:07,480 --> 00:17:11,200 Speaker 3: When you think about planning ahead a business continuity, Chuck, 334 00:17:11,280 --> 00:17:14,159 Speaker 3: when you see what's happened with MD and Video and 335 00:17:14,240 --> 00:17:16,600 Speaker 3: the deal they've cut to access China, when you think 336 00:17:16,640 --> 00:17:20,000 Speaker 3: about exporting more broadly, you're thinking that might come your 337 00:17:20,040 --> 00:17:21,560 Speaker 3: way of pay to play in the future. 338 00:17:23,200 --> 00:17:24,200 Speaker 6: I have no idea. 339 00:17:24,400 --> 00:17:26,399 Speaker 9: We wake up every day and we try to figure 340 00:17:26,440 --> 00:17:29,320 Speaker 9: out what's transpired and what's happening in the world, and 341 00:17:29,320 --> 00:17:32,760 Speaker 9: how do we react to it. I've talked about over 342 00:17:32,800 --> 00:17:35,920 Speaker 9: time that the current crop of CEOs in the United 343 00:17:35,960 --> 00:17:40,119 Speaker 9: States have basically been operating in times of uncertainty or 344 00:17:40,160 --> 00:17:45,080 Speaker 9: crisis or certainly very dynamic environments, and so we're all 345 00:17:45,160 --> 00:17:48,000 Speaker 9: used to just dealing with whatever changes are coming our way. 346 00:17:49,200 --> 00:17:52,160 Speaker 9: You know, there's the old saying that you can deal 347 00:17:52,200 --> 00:17:53,600 Speaker 9: with the world as it is or how you'd like 348 00:17:53,640 --> 00:17:55,680 Speaker 9: it to be, and just we just wake up and 349 00:17:56,080 --> 00:17:59,359 Speaker 9: we deal with what comes at us and try to 350 00:17:59,400 --> 00:18:03,040 Speaker 9: plan a accordingly, try to do scenario planning, but then 351 00:18:03,080 --> 00:18:03,480 Speaker 9: deal with. 352 00:18:03,440 --> 00:18:04,000 Speaker 6: It as it is. 353 00:18:04,760 --> 00:18:06,840 Speaker 3: And when you're controlling your own destiny. You've been doing 354 00:18:06,880 --> 00:18:08,040 Speaker 3: a bit of M and A and you mentioned the 355 00:18:08,080 --> 00:18:10,639 Speaker 3: Sprung coffering and how that helps you access the likes 356 00:18:10,680 --> 00:18:13,159 Speaker 3: of view Up for example. Anymore M and A on 357 00:18:13,160 --> 00:18:14,680 Speaker 3: the rise in particularly when it comes to AI. 358 00:18:16,359 --> 00:18:20,760 Speaker 9: We're always looking Our strategy hasn't changed. Obviously, valuations are 359 00:18:20,800 --> 00:18:25,000 Speaker 9: quite frothy in that space. But if there's something that 360 00:18:25,320 --> 00:18:29,119 Speaker 9: helps us advance our strategy more effectively, then we're always 361 00:18:29,119 --> 00:18:31,200 Speaker 9: willing to take a look at it. I would say 362 00:18:31,240 --> 00:18:34,159 Speaker 9: that M and A is not the strategy. We have 363 00:18:34,280 --> 00:18:38,160 Speaker 9: our product strategy and our solution strategy for our customers, 364 00:18:38,200 --> 00:18:40,639 Speaker 9: and if there's an acquisition that helps us accelerate that, 365 00:18:41,040 --> 00:18:43,280 Speaker 9: then that's what we're really interested in. And you think 366 00:18:43,280 --> 00:18:46,520 Speaker 9: about places like AI, infrastructure or security or observability. 367 00:18:46,520 --> 00:18:48,520 Speaker 6: In those kind of areas, they're always interesting to us. 368 00:18:49,840 --> 00:18:53,639 Speaker 2: Chuck, how's the relationship with Nvidia evolving since it was 369 00:18:53,680 --> 00:18:54,320 Speaker 2: all announced? 370 00:18:55,400 --> 00:18:55,879 Speaker 6: It's great. 371 00:18:56,600 --> 00:18:59,160 Speaker 9: Our team and their team's execs had dinner last night 372 00:18:59,280 --> 00:19:04,720 Speaker 9: and we're working on architectures for Neocloud architectures for the enterprise. 373 00:19:05,640 --> 00:19:08,840 Speaker 9: We're working on go to market, joint go to market together. 374 00:19:09,640 --> 00:19:11,600 Speaker 9: So I'd say it just continues to get stronger. And 375 00:19:11,800 --> 00:19:13,399 Speaker 9: we're really on the front end now of a lot 376 00:19:13,440 --> 00:19:16,560 Speaker 9: of the technology integrations that we've been working on, and 377 00:19:16,600 --> 00:19:19,919 Speaker 9: we're on the front end of the real enterprise wave 378 00:19:20,160 --> 00:19:22,639 Speaker 9: of this AI. If you think about it, it started 379 00:19:22,680 --> 00:19:25,240 Speaker 9: in the back end networks of the cloud providers. 380 00:19:25,720 --> 00:19:26,240 Speaker 6: It's moving. 381 00:19:26,280 --> 00:19:27,880 Speaker 9: It's obviously going to have an impact on the front 382 00:19:27,920 --> 00:19:29,879 Speaker 9: end networks, it's going to have an impact on the 383 00:19:29,960 --> 00:19:34,399 Speaker 9: enterprise and even the telco business that we saw this quarter. 384 00:19:34,520 --> 00:19:37,119 Speaker 9: We had telco and cable. Our orders were up greater 385 00:19:37,200 --> 00:19:40,040 Speaker 9: than twenty percent, and a lot of that was attributed 386 00:19:40,080 --> 00:19:41,679 Speaker 9: to their preparation for AI. 387 00:19:42,600 --> 00:19:49,520 Speaker 3: Chuck Robins, Cisco CEO and Fantastic speak with you today, 388 00:19:52,160 --> 00:19:54,200 Speaker 3: Time Now for Talking Tech and First Up and Video 389 00:19:54,240 --> 00:19:57,119 Speaker 3: partner on HI. But it's expecting sales of its servers 390 00:19:57,160 --> 00:19:59,720 Speaker 3: to more than double this quarter. The company sees one 391 00:19:59,760 --> 00:20:02,560 Speaker 3: hundred seventy percent rise in revenue just from its AI service, 392 00:20:02,720 --> 00:20:05,720 Speaker 3: but executives are warning look that consumer electronics business could 393 00:20:05,760 --> 00:20:09,480 Speaker 3: shrink this year as it faces potential US tariffs plus 394 00:20:09,480 --> 00:20:12,280 Speaker 3: Oracle is coming back. Jobs in its cloud unit are 395 00:20:12,280 --> 00:20:14,680 Speaker 3: coming in the latest company to take steps to control 396 00:20:14,760 --> 00:20:18,159 Speaker 3: costs amid heavy spending on AI infrastructure. Now, according to sources, 397 00:20:18,200 --> 00:20:19,800 Speaker 3: more than one hundred and fifty jobs work cut in 398 00:20:19,800 --> 00:20:23,359 Speaker 3: the Seattle area, which traditionally the unit's hub. Oracle said 399 00:20:23,440 --> 00:20:26,440 Speaker 3: last year it was moving its headquarters to Nashville, and 400 00:20:26,520 --> 00:20:29,159 Speaker 3: the company currently has more jobs listed in Tennessee and 401 00:20:29,359 --> 00:20:32,160 Speaker 3: any other stake And Airbnb will. 402 00:20:31,960 --> 00:20:32,960 Speaker 4: Now allow guests to. 403 00:20:32,960 --> 00:20:35,960 Speaker 3: Reserve some US trips without paying up front, and a 404 00:20:36,000 --> 00:20:36,520 Speaker 3: feature is. 405 00:20:36,440 --> 00:20:37,840 Speaker 4: Called reserve now, Pay later. 406 00:20:38,240 --> 00:20:40,760 Speaker 3: It lets use this book in advance without the need 407 00:20:40,800 --> 00:20:43,359 Speaker 3: to pay the full amount till eight days before the 408 00:20:43,440 --> 00:20:45,960 Speaker 3: end of the listening's cancelation period. Now, the move comes 409 00:20:45,960 --> 00:20:48,600 Speaker 3: after the company of horse worn last week of moderate 410 00:20:48,720 --> 00:20:50,680 Speaker 3: gains through the remainder of the year. 411 00:20:50,960 --> 00:20:54,600 Speaker 2: And if we got okay coming up prices a Bitcoin 412 00:20:54,720 --> 00:20:58,159 Speaker 2: and ether down following stronger than anticipated inflation. But crypto 413 00:20:58,200 --> 00:21:00,600 Speaker 2: and crypto related companies, it's been on a bit of 414 00:21:00,640 --> 00:21:02,919 Speaker 2: a tear recently to talk about what is going on 415 00:21:03,040 --> 00:21:05,840 Speaker 2: in the crypto market. Next, let's think about some of 416 00:21:05,840 --> 00:21:07,600 Speaker 2: the names you've been looking at. Apple had a really 417 00:21:07,640 --> 00:21:11,720 Speaker 2: strong day yesterday, a little softer today, nine percent. 418 00:21:11,840 --> 00:21:12,240 Speaker 7: Cisco. 419 00:21:12,320 --> 00:21:14,159 Speaker 2: We've just had that conversation with Chuck Robbins and the 420 00:21:14,200 --> 00:21:17,639 Speaker 2: market will digest his outlook. Core weaves down eleven percent. 421 00:21:17,760 --> 00:21:21,840 Speaker 2: It fell twenty one percent yesterday. Is basically the cost 422 00:21:21,880 --> 00:21:24,919 Speaker 2: of its build out in its scaling is spooking investors. 423 00:21:25,280 --> 00:21:27,520 Speaker 2: Check out our interview from yesterday. It was a big one. 424 00:21:27,760 --> 00:21:41,920 Speaker 2: This is Bloomberg Tech. Welcome back to Bloomberg Tech. I'm 425 00:21:41,920 --> 00:21:45,560 Speaker 2: looking at the crypto frankly and also sort of the 426 00:21:45,560 --> 00:21:47,520 Speaker 2: industry at large. It's been like a very heavy news 427 00:21:47,520 --> 00:21:49,840 Speaker 2: flow twenty four hours. If you take about bitcoin and 428 00:21:49,840 --> 00:21:53,200 Speaker 2: ether in particular, we were pushing fresh record highs. Largely 429 00:21:53,359 --> 00:21:55,600 Speaker 2: is like this appetite for risk assets. But then we 430 00:21:55,720 --> 00:21:59,399 Speaker 2: got this PPI print or wholesale inflation print that that 431 00:21:59,560 --> 00:22:01,640 Speaker 2: was high and there was a little jitter. And it's 432 00:22:01,680 --> 00:22:04,080 Speaker 2: not just stocks. You see that in the specific digital 433 00:22:04,080 --> 00:22:06,679 Speaker 2: currencies as well. Bullish in its second day of trading 434 00:22:06,760 --> 00:22:09,840 Speaker 2: up another nine percent after an astonishing day yesterday. We 435 00:22:09,920 --> 00:22:12,640 Speaker 2: just throw that in there, given you know, it's sort 436 00:22:12,640 --> 00:22:16,560 Speaker 2: of an adjacent crypto platform, but that would indicate that 437 00:22:16,640 --> 00:22:18,840 Speaker 2: in that single name, at least Caroline there's still a 438 00:22:18,880 --> 00:22:21,280 Speaker 2: lot of bullish sentiment out there. I can't believe I 439 00:22:21,320 --> 00:22:22,000 Speaker 2: did that gross. 440 00:22:22,160 --> 00:22:26,000 Speaker 3: Let's move on, will excuse you and pardon you the pun. 441 00:22:26,119 --> 00:22:29,200 Speaker 3: Let's stick with a crypto market and bullish sentiment across 442 00:22:29,200 --> 00:22:31,200 Speaker 3: the world. Cavitagupta is with us, founder and general partner 443 00:22:31,200 --> 00:22:33,600 Speaker 3: of Delta Blockchain Fund. It's a venture firm focusing on 444 00:22:33,640 --> 00:22:37,159 Speaker 3: early stage blockchain innovation and computer to that end, is 445 00:22:37,160 --> 00:22:40,080 Speaker 3: it helpful or not that there is a lot of 446 00:22:40,280 --> 00:22:42,280 Speaker 3: risk on attitude in the market that is pushing us 447 00:22:42,280 --> 00:22:45,800 Speaker 3: into new IPOs, into the cryptosphere when also it is 448 00:22:45,960 --> 00:22:48,960 Speaker 3: dictated by macro perspective and where interest rates are going. 449 00:22:49,040 --> 00:22:51,080 Speaker 4: Is it helpful for the formation of new businesses right 450 00:22:51,119 --> 00:22:52,479 Speaker 4: now or one hundred percent? 451 00:22:52,640 --> 00:22:55,760 Speaker 10: But what's happening with digital asset treasures in the market 452 00:22:55,880 --> 00:22:59,200 Speaker 10: like five hundred million dollar new digital asset TRUSS three, 453 00:22:59,200 --> 00:23:02,280 Speaker 10: five hundred million dollar for hyper liquids for also assets 454 00:23:02,280 --> 00:23:05,320 Speaker 10: which are not luted coming into the market directly at 455 00:23:05,400 --> 00:23:09,800 Speaker 10: NASDAK now listed having access is creating a very interesting 456 00:23:10,000 --> 00:23:12,000 Speaker 10: by pressure for the first time in. 457 00:23:12,000 --> 00:23:13,040 Speaker 4: The history EAT. 458 00:23:13,200 --> 00:23:16,639 Speaker 10: Actually we have a shortage of EAT available in the 459 00:23:16,720 --> 00:23:20,640 Speaker 10: market to buy because we have over four billion dollar 460 00:23:20,720 --> 00:23:23,800 Speaker 10: treasuries coming into the market to buy eat. That's it, 461 00:23:24,240 --> 00:23:26,119 Speaker 10: and so we are seeing a lot of changes. 462 00:23:26,200 --> 00:23:28,880 Speaker 3: Let's move into that because this is the micro strategy 463 00:23:28,960 --> 00:23:31,680 Speaker 3: or now strategy strategy of basically being able to hold 464 00:23:31,960 --> 00:23:35,800 Speaker 3: bitcoin initially, now moving to eat Salana other assets on 465 00:23:36,040 --> 00:23:39,200 Speaker 3: basically your balance sheet using it as a treasury. It's 466 00:23:39,280 --> 00:23:43,200 Speaker 3: starting to trickle down into slightly more riskier asset paths. 467 00:23:43,400 --> 00:23:45,840 Speaker 3: I mean, just look at what listed yesterday or five 468 00:23:45,920 --> 00:23:48,800 Speaker 3: on the NASTAC. They've done a spac where we're seeing 469 00:23:48,800 --> 00:23:51,880 Speaker 3: now they're going to be buying up World's Liberty coin, 470 00:23:52,119 --> 00:23:56,920 Speaker 3: yes one that you can't trade freely anyway as a crypto, 471 00:23:57,520 --> 00:24:00,880 Speaker 3: and now they're having a publicly traded entity that's going 472 00:24:00,920 --> 00:24:03,040 Speaker 3: to be there eventually to buy up a. 473 00:24:02,960 --> 00:24:03,959 Speaker 4: Load of that asset. 474 00:24:04,359 --> 00:24:07,680 Speaker 3: It's got, you know, the Trump's involved, the wickoffs involved. 475 00:24:08,280 --> 00:24:10,639 Speaker 4: Is it good to see that happen in your ecosystem? 476 00:24:11,160 --> 00:24:13,240 Speaker 10: I think it's good and bad at the same time. 477 00:24:13,400 --> 00:24:15,680 Speaker 10: The good is that there is an appetite. There are 478 00:24:15,720 --> 00:24:18,720 Speaker 10: people who are pumping in a billion dollars into entities 479 00:24:18,800 --> 00:24:21,359 Speaker 10: like this, right, so there is definitely a demand for it, 480 00:24:21,400 --> 00:24:24,160 Speaker 10: which is really good for the crypto market. The downside 481 00:24:24,280 --> 00:24:26,159 Speaker 10: is where does the buck stop? 482 00:24:26,600 --> 00:24:26,840 Speaker 4: Right? 483 00:24:27,200 --> 00:24:31,120 Speaker 10: And so we are now seeing assets which don't even 484 00:24:31,119 --> 00:24:33,560 Speaker 10: have a billion dollar FTV in the market coming in 485 00:24:33,600 --> 00:24:37,040 Speaker 10: and raising three hundred million, four hundred millions and completely 486 00:24:37,040 --> 00:24:38,360 Speaker 10: going crazy, and not only. 487 00:24:38,160 --> 00:24:40,080 Speaker 4: In US and reads how investory they're raising. 488 00:24:40,240 --> 00:24:43,440 Speaker 10: A bunch of them are crypto investors, like most of 489 00:24:43,480 --> 00:24:45,800 Speaker 10: the crypto funds, including ours, are now doing a lot 490 00:24:45,840 --> 00:24:50,280 Speaker 10: of digital asset tressrees. But apart from that also a 491 00:24:50,359 --> 00:24:53,280 Speaker 10: lot of retail investors and institution investors who do not 492 00:24:53,440 --> 00:24:56,040 Speaker 10: have access still because there is no ATF of Salana, 493 00:24:56,080 --> 00:24:59,000 Speaker 10: there is no ETF of Souis, so where do they 494 00:24:59,040 --> 00:25:03,160 Speaker 10: get access to these? And that does raise a question, Hey, 495 00:25:03,480 --> 00:25:05,639 Speaker 10: is it another pump and dump on the Wall Street 496 00:25:05,720 --> 00:25:08,199 Speaker 10: from crypto market to now Wall Street? And who is 497 00:25:08,280 --> 00:25:11,600 Speaker 10: really going to have a real exit liquidity here? It's 498 00:25:11,640 --> 00:25:14,840 Speaker 10: still going to be the insider circle or outsider or 499 00:25:15,200 --> 00:25:17,280 Speaker 10: is it the new landscape for it at least for 500 00:25:17,320 --> 00:25:18,960 Speaker 10: next two and a half three years till we have 501 00:25:19,040 --> 00:25:19,800 Speaker 10: the Trump government. 502 00:25:21,440 --> 00:25:24,719 Speaker 2: KIVIDA, you invest at the earliest stage, at the bottom 503 00:25:24,760 --> 00:25:28,960 Speaker 2: of the curve, those founded on the technological underpinning of everything. 504 00:25:28,960 --> 00:25:29,800 Speaker 7: We're talking about. 505 00:25:29,880 --> 00:25:31,960 Speaker 2: But I see robin Hood and Stripe and the bigger 506 00:25:32,000 --> 00:25:35,280 Speaker 2: FinTechs and the banks looking at stable coin in particular 507 00:25:36,119 --> 00:25:39,399 Speaker 2: wanting to do their own thing. How disrupted is that 508 00:25:39,440 --> 00:25:41,760 Speaker 2: to you? You know, if you at that scale that 509 00:25:41,800 --> 00:25:43,960 Speaker 2: activity is happening and you have all of your portfolio 510 00:25:44,000 --> 00:25:46,360 Speaker 2: companies doing something at a different scale. 511 00:25:46,640 --> 00:25:49,359 Speaker 10: Yeah, it's very fascinating. Thanks it for that question, because 512 00:25:49,400 --> 00:25:52,359 Speaker 10: now we are completely as an early stage investment fund. 513 00:25:52,760 --> 00:25:54,800 Speaker 10: We are going into a space where we have demand 514 00:25:54,840 --> 00:25:57,560 Speaker 10: for so many acquisitions of our companies and so many 515 00:25:58,359 --> 00:26:02,520 Speaker 10: brain powermand Like some of the top banking CEOs, which 516 00:26:02,560 --> 00:26:05,360 Speaker 10: four years back would not even give me a day, 517 00:26:05,440 --> 00:26:08,120 Speaker 10: give me a second in their schedule, are now hosting 518 00:26:08,160 --> 00:26:11,280 Speaker 10: us for dinners trying to understand how are these cross 519 00:26:11,359 --> 00:26:14,480 Speaker 10: chain stable coins gonna settle, How are the money markets 520 00:26:14,520 --> 00:26:17,359 Speaker 10: and reposts and all these eels are gonna happen, And 521 00:26:17,560 --> 00:26:21,600 Speaker 10: everybody wants to do their own stable coin settlement platform 522 00:26:21,800 --> 00:26:22,919 Speaker 10: and want to issue. 523 00:26:22,680 --> 00:26:25,160 Speaker 4: Their own stable coin. I have a feeling in next. 524 00:26:25,000 --> 00:26:27,239 Speaker 10: Year and a half, not only Circle, We're gonna have 525 00:26:27,320 --> 00:26:30,800 Speaker 10: like twenty IPOs of some of the top companies, try Probinhood. 526 00:26:31,040 --> 00:26:32,920 Speaker 10: I'm pretty sure Square is gonna come on the block 527 00:26:32,960 --> 00:26:36,000 Speaker 10: for that Facebook and Instagram will have their own stable coin. 528 00:26:36,080 --> 00:26:38,359 Speaker 10: It's only going to be about who's going to have 529 00:26:38,400 --> 00:26:41,960 Speaker 10: a distribution and everybody's gonna have their stable cooin blockchain platform. 530 00:26:42,000 --> 00:26:46,760 Speaker 3: Now, okay, more Proaly, if everyone's getting into the spaces 531 00:26:46,760 --> 00:26:49,800 Speaker 3: stable coins, if we're seeing companies being developed more and 532 00:26:49,800 --> 00:26:53,720 Speaker 3: more activity in the space, how do you protect any 533 00:26:53,760 --> 00:26:55,880 Speaker 3: downside here? Or is it just doing your due diliges 534 00:26:55,920 --> 00:26:58,040 Speaker 3: and showing that you understand how tradable the asset is 535 00:26:58,080 --> 00:27:01,040 Speaker 3: that you're getting into. And indeed the future of actually 536 00:27:01,119 --> 00:27:03,760 Speaker 3: the digital asset is. From a project perspective, I. 537 00:27:03,720 --> 00:27:07,159 Speaker 10: Think the fundamental of investing in digital assets will always 538 00:27:07,160 --> 00:27:08,560 Speaker 10: remain the same technology. 539 00:27:08,920 --> 00:27:09,720 Speaker 4: Is it scalable? 540 00:27:09,920 --> 00:27:12,159 Speaker 10: Of course, now we have a new Now we have 541 00:27:12,200 --> 00:27:15,320 Speaker 10: a new exit place acquisitions by some of the top companies. 542 00:27:15,560 --> 00:27:18,840 Speaker 10: So is it an institutional adoption product? Can the founders 543 00:27:18,880 --> 00:27:21,200 Speaker 10: take it to let's say a top bank and say, hey, 544 00:27:21,240 --> 00:27:24,199 Speaker 10: we can settle all your repos on this. But the 545 00:27:24,320 --> 00:27:26,280 Speaker 10: other part of this is if I just look at 546 00:27:26,280 --> 00:27:28,240 Speaker 10: the liquid fund, which is doing way better than a 547 00:27:28,280 --> 00:27:31,359 Speaker 10: lot of early stage investment in the technology platform just 548 00:27:31,400 --> 00:27:35,080 Speaker 10: because where the market is today, I'm realizing that digital 549 00:27:35,119 --> 00:27:38,439 Speaker 10: assets restrend is not done yet. It's going to go, 550 00:27:38,480 --> 00:27:40,560 Speaker 10: and it's still not there at the peak because more 551 00:27:40,600 --> 00:27:43,760 Speaker 10: and more people in Hong Kong market, UK market, a 552 00:27:43,800 --> 00:27:46,760 Speaker 10: lot of smaller European and Asian markets are now suddenly 553 00:27:46,840 --> 00:27:49,359 Speaker 10: waking up to it, and that's the demand we are getting. 554 00:27:49,400 --> 00:27:52,320 Speaker 10: Anything under billion dollar FTV is now going into those 555 00:27:52,359 --> 00:27:57,240 Speaker 10: Asian markets and completely raising another layer of investments, and 556 00:27:57,320 --> 00:28:01,680 Speaker 10: that excites me, bothers me and makes me very curious. 557 00:28:01,720 --> 00:28:05,320 Speaker 7: At the same time, tov to go to. 558 00:28:05,280 --> 00:28:07,520 Speaker 2: A general partner at Delta Blockchain Fund. It's great to 559 00:28:07,520 --> 00:28:09,280 Speaker 2: have you back on the show. Thank you very much. 560 00:28:09,320 --> 00:28:13,960 Speaker 2: Now coming up, parag Agrowole, the former CEO of Twitter 561 00:28:14,240 --> 00:28:15,960 Speaker 2: who's squared off against Elon Musk. 562 00:28:16,000 --> 00:28:16,679 Speaker 7: Well he's back. 563 00:28:16,840 --> 00:28:19,359 Speaker 2: He's got a new AI startup and he's going to 564 00:28:19,440 --> 00:28:21,640 Speaker 2: join us to talk about that experience and what he's 565 00:28:21,640 --> 00:28:37,199 Speaker 2: doing now. This is Bloomberg Tech, the former CEO of 566 00:28:37,280 --> 00:28:40,760 Speaker 2: what was then known as Twitter. Parag Agrowole has moved 567 00:28:40,800 --> 00:28:43,600 Speaker 2: on from his days sparring with Elon Musk and he 568 00:28:43,680 --> 00:28:47,160 Speaker 2: stepped into the world of AI startups. Agrowyle's new company, 569 00:28:47,400 --> 00:28:50,480 Speaker 2: Parallel Web Systems is building a tool to help AI 570 00:28:50,640 --> 00:28:52,000 Speaker 2: agents navigate the web. 571 00:28:52,560 --> 00:28:53,920 Speaker 7: Parag Agroyle joins us. 572 00:28:53,960 --> 00:28:56,200 Speaker 2: Now, it's good to see you back in the world 573 00:28:56,240 --> 00:28:58,959 Speaker 2: of technology, at least publicly, back in the world of technology. 574 00:28:59,360 --> 00:29:01,560 Speaker 2: You know, I was reading about parallel web systems, the 575 00:29:01,600 --> 00:29:05,000 Speaker 2: idea that the customer is the AI agent, and it's 576 00:29:05,080 --> 00:29:07,840 Speaker 2: just a place to start. Tell us about this startup, 577 00:29:08,000 --> 00:29:09,480 Speaker 2: what you're doing, why you're doing it. 578 00:29:10,720 --> 00:29:12,760 Speaker 11: Hey, Ed, First of all, thank you so much for 579 00:29:12,800 --> 00:29:16,840 Speaker 11: having me after leaving Twitter. One of the things I 580 00:29:16,880 --> 00:29:20,400 Speaker 11: was doing was this writing a bunch of code, tinkering around. 581 00:29:20,960 --> 00:29:24,240 Speaker 11: I was actually building AI agents a couple of years 582 00:29:24,280 --> 00:29:29,320 Speaker 11: ago that were mostly collecting information from the web, bringing 583 00:29:29,320 --> 00:29:31,840 Speaker 11: it back to me so that I could create it. 584 00:29:32,760 --> 00:29:35,920 Speaker 11: And I had a couple of realizations doing so. One 585 00:29:36,560 --> 00:29:41,040 Speaker 11: that the AI agents are going to be the primary 586 00:29:41,320 --> 00:29:44,840 Speaker 11: customer of the web going forward. They will use the 587 00:29:44,880 --> 00:29:48,040 Speaker 11: web a lot more than humans ever have. And two, 588 00:29:48,640 --> 00:29:51,600 Speaker 11: the web that exists isn't built for them. It's not 589 00:29:51,640 --> 00:29:54,880 Speaker 11: ready for them. Everything I and so many people have 590 00:29:54,880 --> 00:29:56,680 Speaker 11: built over the last thirty years has been built for 591 00:29:56,760 --> 00:30:00,920 Speaker 11: humans and for eis. Their needs are different, and that's 592 00:30:00,960 --> 00:30:03,360 Speaker 11: the problem that we're starting at Parallel, and. 593 00:30:03,320 --> 00:30:05,360 Speaker 6: That's why we describe EI. 594 00:30:05,240 --> 00:30:08,880 Speaker 11: Agents as a primary customer for all the technology that 595 00:30:08,920 --> 00:30:09,400 Speaker 11: we're building. 596 00:30:10,800 --> 00:30:12,760 Speaker 2: There is actually some news that we're breaking here right 597 00:30:12,800 --> 00:30:15,800 Speaker 2: which is that you've raised around thirty million dollars for Parallel. 598 00:30:16,640 --> 00:30:18,280 Speaker 2: You know, that's a lot out the gate. Just tell 599 00:30:18,360 --> 00:30:20,640 Speaker 2: us about about how that went, that came about and 600 00:30:20,680 --> 00:30:21,600 Speaker 2: the team that you've built. 601 00:30:24,920 --> 00:30:28,880 Speaker 11: We when we've started with this vision or visions like 602 00:30:29,640 --> 00:30:34,000 Speaker 11: a big vision in order to really transform what the open. 603 00:30:33,760 --> 00:30:34,520 Speaker 6: Web looks like. 604 00:30:35,320 --> 00:30:41,040 Speaker 11: Doing so requires reimagining from the ground up every part 605 00:30:41,080 --> 00:30:46,000 Speaker 11: of the infrastructure that spans the crawl, the index ranking systems, 606 00:30:46,040 --> 00:30:50,000 Speaker 11: reasoning systems, completely new interfaces built for a systems. And 607 00:30:50,080 --> 00:30:52,360 Speaker 11: as we sort of thought about what it would take 608 00:30:52,680 --> 00:30:55,560 Speaker 11: to build all of this, I think that was the 609 00:30:55,600 --> 00:30:59,680 Speaker 11: appropriate amount of money to raise. The team we have 610 00:31:00,600 --> 00:31:04,400 Speaker 11: is also the one needed to take on this problem. 611 00:31:04,640 --> 00:31:08,680 Speaker 11: The team around me is the team that built a 612 00:31:08,720 --> 00:31:12,320 Speaker 11: lot of the key primitives of the current human web, 613 00:31:12,440 --> 00:31:15,000 Speaker 11: whether it be at social networks like Twitter and Snap, 614 00:31:15,320 --> 00:31:19,000 Speaker 11: or at scripe and even marketplaces at Airbnb and so 615 00:31:19,240 --> 00:31:21,680 Speaker 11: the best people who've sort of built the previous version 616 00:31:21,720 --> 00:31:25,280 Speaker 11: of the web, recognizing ways in which it does not 617 00:31:25,720 --> 00:31:28,960 Speaker 11: serve the needs of what's coming. Yes, have now come 618 00:31:29,000 --> 00:31:32,600 Speaker 11: together to build this future web aar We too. 619 00:31:33,000 --> 00:31:35,720 Speaker 3: Had started off by saying the customer is the agent here, 620 00:31:35,720 --> 00:31:37,280 Speaker 3: but who actually is the customer? 621 00:31:37,280 --> 00:31:38,720 Speaker 4: And seeing the integration with. 622 00:31:38,720 --> 00:31:41,720 Speaker 3: Lindy for example, with AI agents, but more broadly, who 623 00:31:41,760 --> 00:31:43,920 Speaker 3: buys you? Whose problems you solving? Is it those of 624 00:31:43,920 --> 00:31:47,520 Speaker 3: open AI and perplexity you are busy building the agentic platforms. 625 00:31:49,000 --> 00:31:51,800 Speaker 11: I think one way to think about our customer set 626 00:31:51,880 --> 00:31:55,080 Speaker 11: right if you think of any piece of software or 627 00:31:55,200 --> 00:31:59,640 Speaker 11: any workflow, both of those are changing. They're changing by 628 00:31:59,680 --> 00:32:05,800 Speaker 11: incoorporating models like lllms into them that give them intelligence. Now, 629 00:32:05,800 --> 00:32:08,400 Speaker 11: once you have those, it almost feel silly to not 630 00:32:08,560 --> 00:32:12,600 Speaker 11: have access to the open Web in order to serve 631 00:32:12,680 --> 00:32:13,959 Speaker 11: your customers or do your Workflorce. 632 00:32:14,040 --> 00:32:14,920 Speaker 6: Let me give you an example. 633 00:32:15,800 --> 00:32:20,760 Speaker 11: We work with an insurance a large insurance company. One 634 00:32:20,760 --> 00:32:25,280 Speaker 11: of the things they do is underwriting, wherein there's a 635 00:32:25,320 --> 00:32:29,360 Speaker 11: bunch of people that spend thirty minutes, perhaps even two hours, 636 00:32:29,480 --> 00:32:32,480 Speaker 11: understanding a business they're about to underwrite, to understand everything 637 00:32:32,480 --> 00:32:35,920 Speaker 11: about it and discover all long tail risk signals anywhere 638 00:32:35,960 --> 00:32:38,680 Speaker 11: on the web. Now they've been doing that with human 639 00:32:38,720 --> 00:32:43,400 Speaker 11: operations forever. As we started working with them and they 640 00:32:43,440 --> 00:32:47,640 Speaker 11: incorporated our APIs into how they do things, combining all 641 00:32:47,680 --> 00:32:49,440 Speaker 11: of the data from the web with all of the 642 00:32:49,560 --> 00:32:54,280 Speaker 11: internal proprietary information that they have collected, they're actually able 643 00:32:54,320 --> 00:32:59,520 Speaker 11: to outperform humans meaningfully, not just in terms of cost 644 00:32:59,560 --> 00:33:02,720 Speaker 11: and how you can do things, but in terms of quality, 645 00:33:03,000 --> 00:33:05,680 Speaker 11: because it turns out humans cellucinate it too. 646 00:33:06,560 --> 00:33:10,880 Speaker 3: Briefly, Parak, you built parallel web systems hot on the 647 00:33:10,920 --> 00:33:13,640 Speaker 3: heels of a very combative few years having led Twitter, 648 00:33:13,720 --> 00:33:16,920 Speaker 3: but you were known as building the machine learning systems 649 00:33:17,040 --> 00:33:18,600 Speaker 3: over Twitter and now X. 650 00:33:19,440 --> 00:33:21,920 Speaker 4: What lessons have you learned to bring to this new company. 651 00:33:23,600 --> 00:33:27,560 Speaker 11: One, A lot of the lessons from the past no 652 00:33:27,600 --> 00:33:32,160 Speaker 11: longer apply when you're thinking of building machine learning systems. 653 00:33:32,440 --> 00:33:35,680 Speaker 11: When we're building those at Twitter at twenty fourteen, they 654 00:33:35,720 --> 00:33:38,920 Speaker 11: look very very different from the systems we are now 655 00:33:39,000 --> 00:33:42,280 Speaker 11: able to build, velocity at which we were able to move, 656 00:33:42,800 --> 00:33:45,400 Speaker 11: and the kinds of problems we are able to take on. 657 00:33:45,880 --> 00:33:48,480 Speaker 11: What remains similar, though, for people who've been doing machine 658 00:33:48,560 --> 00:33:51,520 Speaker 11: learning for a while, is the mindset of solving problems 659 00:33:51,640 --> 00:33:57,440 Speaker 11: end to end, understanding evils, dealing with stochastics, systems, and 660 00:33:57,480 --> 00:33:59,880 Speaker 11: I think those are the lessons that truly inform us. 661 00:34:01,920 --> 00:34:06,719 Speaker 2: Parrague, Sun Valley twenty twenty two. I was there, I 662 00:34:06,760 --> 00:34:10,480 Speaker 2: remember seeing you there, and then everything that followed, just 663 00:34:11,280 --> 00:34:15,280 Speaker 2: for the first time, reflects a little bit on what happened. 664 00:34:14,920 --> 00:34:16,840 Speaker 7: In Yeah please. 665 00:34:20,120 --> 00:34:24,120 Speaker 11: What happened was we built over eleven years that I 666 00:34:24,200 --> 00:34:28,920 Speaker 11: was at Twitter, one of the most consequential platforms to exist. 667 00:34:29,600 --> 00:34:37,160 Speaker 11: It allowed everyone to speak and hear directly from others, 668 00:34:37,360 --> 00:34:40,840 Speaker 11: and there is nothing like it, and I'm very proud 669 00:34:40,960 --> 00:34:45,000 Speaker 11: of what I was able to achieve there with my years. Now, 670 00:34:45,040 --> 00:34:48,000 Speaker 11: of course there was a lot more to be done. 671 00:34:48,920 --> 00:34:53,200 Speaker 11: It remains a platform that matters in the world. 672 00:34:54,280 --> 00:34:56,160 Speaker 6: But my new mission pulls. 673 00:34:55,880 --> 00:34:59,000 Speaker 11: A thread from that, which is how do you keep 674 00:34:59,160 --> 00:35:06,360 Speaker 11: the web open. It's the same mission around allowing everyone 675 00:35:06,440 --> 00:35:10,279 Speaker 11: to publish openly on the web, around every AI being 676 00:35:10,320 --> 00:35:15,880 Speaker 11: able to access what everyone is publishing freely. There is 677 00:35:15,920 --> 00:35:18,920 Speaker 11: a risk on the open web, wherein we might have 678 00:35:18,960 --> 00:35:22,840 Speaker 11: a bunch of payballs and silos, and an AI model 679 00:35:22,920 --> 00:35:27,560 Speaker 11: from one vendor is able to access certain parts of 680 00:35:27,600 --> 00:35:30,200 Speaker 11: the web, while the agent you might run on your 681 00:35:30,239 --> 00:35:33,480 Speaker 11: computer using open source software cannot And that's not the 682 00:35:33,520 --> 00:35:36,839 Speaker 11: future I want and that's why we're building Parallel all. 683 00:35:36,840 --> 00:35:40,280 Speaker 3: Raight Agrowell, thanks for joining us, found our CEO Parallel 684 00:35:40,280 --> 00:35:42,200 Speaker 3: Web Systems and of course pre you to see the 685 00:35:42,239 --> 00:35:51,319 Speaker 3: CEO of Twitter. Fitness ban maker Woop is refusing to 686 00:35:51,360 --> 00:35:54,480 Speaker 3: disable it's blood pressure tracking tool following warnings from the 687 00:35:54,560 --> 00:35:58,040 Speaker 3: FDA saying that the company is operating as a medical device. 688 00:35:58,440 --> 00:36:02,560 Speaker 3: Joining us now to discuss CEO Will almed Will, what's 689 00:36:02,680 --> 00:36:05,719 Speaker 3: your view that the FDA does not have authority in 690 00:36:05,760 --> 00:36:08,640 Speaker 3: this moment. Your wellness not medical device. 691 00:36:10,200 --> 00:36:12,839 Speaker 12: Well, thanks for having me on you know Whoop spent 692 00:36:12,880 --> 00:36:16,960 Speaker 12: the last three years developing a very innovative feature called 693 00:36:17,040 --> 00:36:20,880 Speaker 12: blood Pressure Insights, and this takes our wrist worn wearable 694 00:36:21,560 --> 00:36:24,840 Speaker 12: alongside a calibration with a cuff and is allowed to 695 00:36:24,880 --> 00:36:28,040 Speaker 12: provide you with a daily estimate of your blood pressure 696 00:36:28,400 --> 00:36:30,920 Speaker 12: and in turn it also then gives you insights how 697 00:36:30,920 --> 00:36:34,440 Speaker 12: your blood pressure may be affecting other things in your wellness. 698 00:36:34,440 --> 00:36:37,960 Speaker 12: This could be sleep, stress, nutrition, a variety of different 699 00:36:38,000 --> 00:36:42,040 Speaker 12: wellness factors, and the FDA has come forward saying that 700 00:36:42,080 --> 00:36:46,120 Speaker 12: they believe that this should be regulated now. The twenty 701 00:36:46,160 --> 00:36:50,400 Speaker 12: first Century Cures Act makes it very clear that wellness 702 00:36:50,440 --> 00:36:54,400 Speaker 12: intended features are not supposed to be regulated by the FDA, 703 00:36:55,000 --> 00:36:58,960 Speaker 12: and the FDA is intended to actually just regulate medical 704 00:36:59,000 --> 00:37:03,040 Speaker 12: devices that are diagnosing something. So there's this key question 705 00:37:03,120 --> 00:37:06,279 Speaker 12: of intended use. And you can see this with other 706 00:37:06,320 --> 00:37:10,400 Speaker 12: physiological metrics like r A monitoring for example, where HORRY 707 00:37:10,520 --> 00:37:13,600 Speaker 12: monitoring has wellness applications and medical applications. 708 00:37:13,920 --> 00:37:15,920 Speaker 6: The wellness applications. 709 00:37:15,280 --> 00:37:19,440 Speaker 12: Might be things like exercise or stress monitoring or sleep monitoring, 710 00:37:19,440 --> 00:37:22,879 Speaker 12: and we do all that and then alternatively, there could be, 711 00:37:23,280 --> 00:37:27,040 Speaker 12: you know, a diagnosis for a fib and that would 712 00:37:27,080 --> 00:37:28,120 Speaker 12: be an example where. 713 00:37:27,920 --> 00:37:32,239 Speaker 2: The fall will That's what the FDA is interpreted, right, 714 00:37:32,280 --> 00:37:34,200 Speaker 2: But you're a smart guy and you employ lots of 715 00:37:34,239 --> 00:37:37,280 Speaker 2: smart people, why not just go through the FDA process 716 00:37:37,480 --> 00:37:40,359 Speaker 2: in the first place, kind of foreseeing that this might 717 00:37:40,360 --> 00:37:40,759 Speaker 2: come up. 718 00:37:42,040 --> 00:37:44,600 Speaker 12: Well, you have to understand there's different use cases, right. 719 00:37:45,200 --> 00:37:48,000 Speaker 12: One use case for blood pressure is around wellness, and 720 00:37:48,040 --> 00:37:51,280 Speaker 12: there's other use cases that might be a medical diagnosis. 721 00:37:51,480 --> 00:37:55,160 Speaker 12: And we're certainly looking at you know, cleared products as 722 00:37:55,160 --> 00:37:58,239 Speaker 12: well on a longer term horizon. But we're providing a 723 00:37:58,239 --> 00:38:01,600 Speaker 12: lot of value today and following the law again the 724 00:38:01,640 --> 00:38:04,719 Speaker 12: twenty first century Cures Act makes it very clear if 725 00:38:04,719 --> 00:38:07,759 Speaker 12: a product is intended for a wellness use case, it's 726 00:38:07,800 --> 00:38:10,160 Speaker 12: not supposed to be regulated by the FDA. So then 727 00:38:10,160 --> 00:38:15,040 Speaker 12: the fundamental question becomes, does blood pressure have wellness intended 728 00:38:15,160 --> 00:38:18,640 Speaker 12: use cases? We believe it does, right, There's an avalanche 729 00:38:18,719 --> 00:38:22,239 Speaker 12: of pure reviewed research that shows that blood pressure, not 730 00:38:22,360 --> 00:38:27,040 Speaker 12: surprisingly is influenced and influences other aspects of your wealth. 731 00:38:27,080 --> 00:38:32,200 Speaker 4: Will why call it medical grade? Why market it that way? 732 00:38:32,960 --> 00:38:35,560 Speaker 12: Well, we recently came out with the Whoop five DOTZHO 733 00:38:35,560 --> 00:38:39,120 Speaker 12: and the Whoop MG, and a key distinguishing factor between 734 00:38:39,120 --> 00:38:41,279 Speaker 12: the WOOP five dot OHO and the MG is that 735 00:38:41,360 --> 00:38:44,600 Speaker 12: the MG has a medically cleared feature on it. Now, 736 00:38:44,640 --> 00:38:47,800 Speaker 12: both of those products have a number of wellness features 737 00:38:47,840 --> 00:38:51,239 Speaker 12: associated with it. The WOOP MG happens to have an 738 00:38:51,280 --> 00:38:55,160 Speaker 12: ECG monitor as part of that that can detect aphib 739 00:38:55,239 --> 00:38:56,960 Speaker 12: and by the way, we spent two and a half 740 00:38:57,120 --> 00:39:00,960 Speaker 12: years working with the FDA to have that cleared feature. 741 00:39:01,160 --> 00:39:04,880 Speaker 12: So that is the distinguishing factor between those two hardwares. 742 00:39:05,200 --> 00:39:07,600 Speaker 12: And I want to be very clear in the app 743 00:39:07,719 --> 00:39:12,120 Speaker 12: there's an enormous number of medical disclaimers explaining what is 744 00:39:12,239 --> 00:39:15,560 Speaker 12: for wellness and what is for medical capabilities. 745 00:39:16,800 --> 00:39:20,240 Speaker 2: Well, you've said this is a misunderstanding. What happens next? 746 00:39:20,560 --> 00:39:23,200 Speaker 2: Will you continue to fight the FDA on it or 747 00:39:23,760 --> 00:39:25,960 Speaker 2: in the background are you trying to reach some solution. 748 00:39:27,560 --> 00:39:29,200 Speaker 6: We have a lot of respect for the FDA. 749 00:39:29,280 --> 00:39:31,239 Speaker 12: I mean, we've engaged with them on a number of 750 00:39:31,280 --> 00:39:34,600 Speaker 12: different features over the years. We think in this specific 751 00:39:34,680 --> 00:39:36,560 Speaker 12: case they have it wrong, and so we're going to 752 00:39:36,560 --> 00:39:37,920 Speaker 12: continue engaging. 753 00:39:37,480 --> 00:39:38,040 Speaker 6: With them on it. 754 00:39:38,400 --> 00:39:42,760 Speaker 12: We've responded to their warning letter outlining how we feel 755 00:39:42,800 --> 00:39:45,719 Speaker 12: about this and why we think we're following the law, 756 00:39:46,400 --> 00:39:48,799 Speaker 12: and we look forward to continuing to engage with them 757 00:39:48,840 --> 00:39:49,080 Speaker 12: on it. 758 00:39:49,320 --> 00:39:52,400 Speaker 3: Well, that must take up headspace and ultimately your time. 759 00:39:52,840 --> 00:39:56,279 Speaker 3: How does that impact your future product roadmap? How does 760 00:39:56,320 --> 00:39:59,480 Speaker 3: more broadly, the FDA acting this way affect innovation more broadly? 761 00:39:59,520 --> 00:40:02,080 Speaker 4: Do you think ultimately? 762 00:40:02,160 --> 00:40:04,719 Speaker 12: I think that you know, innovation needs to be able 763 00:40:04,760 --> 00:40:07,040 Speaker 12: to thrive in the United States. Whoop is one of 764 00:40:07,080 --> 00:40:10,320 Speaker 12: the first wearables in the world that can measure blood 765 00:40:10,320 --> 00:40:13,160 Speaker 12: pressure accurately from the risk that's a really big deal, 766 00:40:13,960 --> 00:40:17,840 Speaker 12: and it's also being accepted in fifty other markets around 767 00:40:17,880 --> 00:40:18,360 Speaker 12: the world. 768 00:40:18,800 --> 00:40:20,360 Speaker 6: So, you know, we want. 769 00:40:20,120 --> 00:40:23,000 Speaker 12: To make sure that there's policies that are consistent here 770 00:40:23,000 --> 00:40:27,040 Speaker 12: in the US that really allow companies to innovate and 771 00:40:27,080 --> 00:40:30,000 Speaker 12: to operate. It's also worth noting, you know, we have 772 00:40:30,120 --> 00:40:32,560 Speaker 12: a lot of people using this every single day, and 773 00:40:32,680 --> 00:40:35,480 Speaker 12: overwhelmingly if you look at the feedback from our members, 774 00:40:35,800 --> 00:40:38,960 Speaker 12: they absolutely love this feature and they talk about how 775 00:40:38,960 --> 00:40:41,719 Speaker 12: accurate it is and how it's helping them understand their wellness. 776 00:40:42,200 --> 00:40:44,840 Speaker 12: So we feel like we're on the right side of history, 777 00:40:44,880 --> 00:40:47,239 Speaker 12: and we're going to continue educating the FDA on what 778 00:40:47,280 --> 00:40:47,719 Speaker 12: we're doing. 779 00:40:48,880 --> 00:40:49,040 Speaker 6: Well. 780 00:40:49,400 --> 00:40:51,960 Speaker 2: I'm very quickly I'm not a Whoop user, but I'm 781 00:40:52,040 --> 00:40:54,600 Speaker 2: very conscious that in the Premier League and other international 782 00:40:54,640 --> 00:40:58,360 Speaker 2: football players, it's very in the public conscience. I just wonder, like, 783 00:40:58,520 --> 00:41:01,279 Speaker 2: is this a good pr moment for you to fight 784 00:41:01,360 --> 00:41:02,480 Speaker 2: America's regulator. 785 00:41:05,040 --> 00:41:06,000 Speaker 6: I think in the long. 786 00:41:05,880 --> 00:41:07,880 Speaker 12: Run we'll be on the right side of history, and 787 00:41:08,200 --> 00:41:10,399 Speaker 12: that maybe in a very short period of time too. 788 00:41:10,920 --> 00:41:14,400 Speaker 12: I think that fighting for innovation, fighting for Americans access 789 00:41:14,400 --> 00:41:17,399 Speaker 12: to health data is the right thing to do. And 790 00:41:17,760 --> 00:41:21,040 Speaker 12: I've spent thirteen years building this company. When I first started, 791 00:41:21,280 --> 00:41:24,160 Speaker 12: the idea that you could measure sleep or heart rate 792 00:41:24,280 --> 00:41:28,000 Speaker 12: accurately from the wrist seemed impossible, and now we're able 793 00:41:28,000 --> 00:41:30,600 Speaker 12: to do blood pressure accurately from the risk. That's a 794 00:41:30,640 --> 00:41:33,440 Speaker 12: really big deal and I think it should be celebrated 795 00:41:33,760 --> 00:41:36,120 Speaker 12: as long as there's the right guidelines in place and 796 00:41:36,160 --> 00:41:39,279 Speaker 12: the right education in place for members to understand how 797 00:41:39,280 --> 00:41:41,920 Speaker 12: to use it. And that's what we've done with this feature, 798 00:41:41,920 --> 00:41:42,920 Speaker 12: and that's why we're proud of it. 799 00:41:44,560 --> 00:41:47,600 Speaker 7: Whip CEO Will Almed, Thank you very much, Caro. 800 00:41:48,000 --> 00:41:51,080 Speaker 3: Ah great conversation to round out. What is the end 801 00:41:51,080 --> 00:41:54,520 Speaker 3: of this edition of Bloomberg Tech Ed programming note, make 802 00:41:54,600 --> 00:41:56,840 Speaker 3: sure to check out the next edition of Bloomberg Tech Europe. 803 00:41:56,920 --> 00:41:59,520 Speaker 3: Tom McKenzie can be exploring how AI is changing the wing. 804 00:41:59,560 --> 00:42:03,000 Speaker 3: We work six thirty am London time on Friday. 805 00:42:04,080 --> 00:42:06,200 Speaker 2: And give and I have twenty seconds. I didn't expect. 806 00:42:06,320 --> 00:42:09,200 Speaker 2: We have a podcast and you know where to find it. 807 00:42:09,200 --> 00:42:11,840 Speaker 2: It's on the Internet and it's also on the Bloomberg 808 00:42:11,880 --> 00:42:15,040 Speaker 2: platforms and you should listen to it and to recap 809 00:42:15,080 --> 00:42:17,200 Speaker 2: the show from New York City and London. 810 00:42:17,560 --> 00:42:18,879 Speaker 7: This is Bloomberg Tech