1 00:00:02,520 --> 00:00:13,280 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is a 2 00:00:13,360 --> 00:00:17,120 Speaker 1: live from coast to coast with Caroline Hide in New 3 00:00:17,200 --> 00:00:19,720 Speaker 1: York and Ed Lovelow in San Francisco. 4 00:00:23,440 --> 00:00:26,160 Speaker 2: This is Bloomberg Tech coming up. Alphabet looking to tap 5 00:00:26,200 --> 00:00:29,040 Speaker 2: the debt markets with fifteen billion dollars in US high 6 00:00:29,040 --> 00:00:33,639 Speaker 2: grade and a super rare one hundred year Sterling denominated note. 7 00:00:33,640 --> 00:00:34,520 Speaker 2: We had the details. 8 00:00:34,640 --> 00:00:37,800 Speaker 3: Plus Bitcoin slips back below seventy thousand dollars after a 9 00:00:37,920 --> 00:00:40,360 Speaker 3: roller coaster ride at the end of last week. 10 00:00:40,560 --> 00:00:41,680 Speaker 4: We'll discuss where it can go. 11 00:00:41,600 --> 00:00:44,720 Speaker 2: From here, and Apple set to debut a slew of 12 00:00:44,760 --> 00:00:47,720 Speaker 2: new products in the coming weeks, including a new iPhone 13 00:00:47,800 --> 00:00:51,159 Speaker 2: seventeen E and updated iPads and max A. 14 00:00:51,240 --> 00:00:53,559 Speaker 3: First, we check in on these markets that bounce back 15 00:00:53,600 --> 00:00:56,400 Speaker 3: for a second day. What a Friday close for the 16 00:00:56,480 --> 00:00:58,280 Speaker 3: last that one hundred, and we build on that two 17 00:00:58,280 --> 00:01:01,160 Speaker 3: and a half percent higher with another six tens percent. 18 00:01:01,000 --> 00:01:02,800 Speaker 4: Rebound as we really try to. 19 00:01:02,760 --> 00:01:05,759 Speaker 3: Digest where the risks are in the tech markets, and 20 00:01:05,880 --> 00:01:07,160 Speaker 3: of course, as we look ahead to some of that 21 00:01:07,240 --> 00:01:09,520 Speaker 3: job's data later in the week. I'm looking at crypto 22 00:01:09,560 --> 00:01:12,440 Speaker 3: though rollercoaster if you were training it this weekend we're 23 00:01:12,480 --> 00:01:15,160 Speaker 3: back below seventy thousand, having eclipsed it for a moment 24 00:01:15,200 --> 00:01:17,280 Speaker 3: on the weekend training End'll dig into that a little 25 00:01:17,280 --> 00:01:19,200 Speaker 3: bit later, But you're looking at the equity side of 26 00:01:19,200 --> 00:01:21,200 Speaker 3: the equation and debt. 27 00:01:21,480 --> 00:01:23,600 Speaker 2: Yeah, Alphabet, but actually I'm going to do something a 28 00:01:23,640 --> 00:01:27,160 Speaker 2: little unusual and go to the corporate debt and bomb market. 29 00:01:27,280 --> 00:01:30,959 Speaker 2: Really interesting Alphabet looking to raise fifteen billion dollars from 30 00:01:30,959 --> 00:01:33,720 Speaker 2: a US high grade dollar bond sale. Bloomberg reporting that 31 00:01:33,800 --> 00:01:36,840 Speaker 2: siting sources, but also going to the banks for a 32 00:01:36,880 --> 00:01:41,199 Speaker 2: mandate maybe to look at Swiss frank denominated and then 33 00:01:41,520 --> 00:01:47,120 Speaker 2: a super rare one hundred year note Sterling denominated British pound. 34 00:01:47,200 --> 00:01:49,720 Speaker 2: We haven't seen a one hundred year note since like 35 00:01:49,920 --> 00:01:53,000 Speaker 2: dot com era late nineties. But the bigger picture is 36 00:01:53,000 --> 00:01:56,640 Speaker 2: pretty clear, right Taro, that we've seen big tech companies 37 00:01:56,720 --> 00:02:01,400 Speaker 2: use debt monket markets to fund what's happening in capital expenditures. 38 00:02:01,440 --> 00:02:02,040 Speaker 4: A lot more to. 39 00:02:02,000 --> 00:02:05,040 Speaker 3: Discuss, and a lot more bond sales probably to be digesting. 40 00:02:05,120 --> 00:02:07,919 Speaker 3: Let's do it all with the Robert Schiffman from Bloomberg Intelligence. 41 00:02:08,400 --> 00:02:12,120 Speaker 3: We knew they had to finance the extraordinary amounts of 42 00:02:12,240 --> 00:02:16,360 Speaker 3: AI capital expenditure Is there enough demand to support these 43 00:02:16,600 --> 00:02:17,680 Speaker 3: mega bond sales? 44 00:02:17,919 --> 00:02:18,119 Speaker 5: Yeah? 45 00:02:18,120 --> 00:02:20,720 Speaker 6: I think listen, let's start from the beginning. Do they 46 00:02:20,760 --> 00:02:23,720 Speaker 6: actually need any money? My injurers know. I think they're 47 00:02:23,720 --> 00:02:26,520 Speaker 6: borrowing money because they can, because it's super cheap, and 48 00:02:26,520 --> 00:02:29,760 Speaker 6: that there's a concept that demand for not just AI 49 00:02:30,120 --> 00:02:32,639 Speaker 6: but bonds are so insatiable that they can go out 50 00:02:32,639 --> 00:02:36,080 Speaker 6: and do one hundred year maturity. So yeah, there's tons 51 00:02:36,120 --> 00:02:38,720 Speaker 6: of demand. If Oracle is able to build one hundred 52 00:02:38,720 --> 00:02:41,280 Speaker 6: and thirty billion dollar book, Google can build whatever book 53 00:02:41,320 --> 00:02:41,760 Speaker 6: it wants. 54 00:02:43,040 --> 00:02:46,320 Speaker 2: This is why going back to basics is probably a 55 00:02:46,320 --> 00:02:47,079 Speaker 2: good place to start. 56 00:02:47,120 --> 00:02:47,880 Speaker 7: I agree with you. 57 00:02:48,160 --> 00:02:50,760 Speaker 2: People would say, well, why is there a good idea? 58 00:02:50,880 --> 00:02:52,920 Speaker 2: You know, they look at some of the mag seven 59 00:02:53,000 --> 00:02:55,520 Speaker 2: names and they be cash on their balance sheet and say, 60 00:02:56,040 --> 00:02:58,600 Speaker 2: you know why is that a useful mechanism for them? 61 00:02:59,000 --> 00:02:59,200 Speaker 8: Yeah? 62 00:02:59,440 --> 00:03:01,360 Speaker 6: This is what they taught me in math camp, the 63 00:03:01,440 --> 00:03:06,080 Speaker 6: way that average cost of debt capital for all these names, 64 00:03:06,200 --> 00:03:11,200 Speaker 6: whether it's Meta Alphabet, Microsoft, Apple, Amazon, is effectively zero. 65 00:03:12,440 --> 00:03:14,240 Speaker 6: You know, why do you have double A and triple 66 00:03:14,280 --> 00:03:16,160 Speaker 6: A balance sheets if you're not going to use them? 67 00:03:16,200 --> 00:03:19,639 Speaker 6: I think this is extraordinarily visionary. You know, these companies 68 00:03:19,680 --> 00:03:23,360 Speaker 6: have been prepping for years for greater investment opportunities, and 69 00:03:23,360 --> 00:03:26,320 Speaker 6: now they finally see it. I think it's just such 70 00:03:26,320 --> 00:03:29,240 Speaker 6: a bullish sign for this market. And from again the 71 00:03:29,280 --> 00:03:34,119 Speaker 6: bondholder perspective, this is not equity holders being wary about multiples. 72 00:03:34,280 --> 00:03:36,080 Speaker 6: Bondholders I don't think are going to be able to 73 00:03:36,080 --> 00:03:37,400 Speaker 6: get enough, and they're going to be able to do 74 00:03:37,440 --> 00:03:39,800 Speaker 6: it along every single part of the curve. And like 75 00:03:39,840 --> 00:03:42,200 Speaker 6: you said, this isn't just going to be dollars. They're 76 00:03:42,240 --> 00:03:45,360 Speaker 6: going to the Swiss frank market, the pound market. I 77 00:03:45,360 --> 00:03:48,119 Speaker 6: wouldn't be shocked if they went back to the euro 78 00:03:48,280 --> 00:03:50,320 Speaker 6: market or even to issue yen. I think there's going 79 00:03:50,360 --> 00:03:52,800 Speaker 6: to be demand all over the globe for high quality 80 00:03:52,840 --> 00:03:54,440 Speaker 6: Mount Rushmore style credits like this. 81 00:03:55,600 --> 00:03:57,040 Speaker 3: I want to go to whatever in math camp you 82 00:03:57,040 --> 00:03:59,440 Speaker 3: were going to where you're talking about Swiss Yen sterling 83 00:03:59,520 --> 00:04:03,200 Speaker 3: denominate corporate debt. But look, the demand's there. We've seen 84 00:04:03,280 --> 00:04:06,640 Speaker 3: in other parts of the AI sector, Infinian in Europe 85 00:04:06,640 --> 00:04:10,200 Speaker 3: tapping the market. It's a chip maker. We've seen IBM 86 00:04:10,280 --> 00:04:13,320 Speaker 3: come to the market. There's four hundred billion dollars that 87 00:04:13,360 --> 00:04:16,240 Speaker 3: could get done in corporate bonds, just the investment grade 88 00:04:16,279 --> 00:04:20,479 Speaker 3: sector alone JP Morgan forecast for this year. How do 89 00:04:20,520 --> 00:04:22,359 Speaker 3: you think steady will be for the year or do 90 00:04:22,360 --> 00:04:24,080 Speaker 3: you think we're going to be frontloading this? Are we 91 00:04:24,120 --> 00:04:26,480 Speaker 3: awaiting Amazon to come straight out the gates given you've 92 00:04:26,520 --> 00:04:29,640 Speaker 3: just powered a note about there really strong fundamentals. 93 00:04:29,880 --> 00:04:32,200 Speaker 6: Yeah, listen, I think this is the tip of the iceberg. 94 00:04:32,360 --> 00:04:35,040 Speaker 6: I actually think in Bloomberg News is underestimating how much 95 00:04:35,120 --> 00:04:37,040 Speaker 6: hyperscaler spending is going to be this year. They put 96 00:04:37,080 --> 00:04:39,240 Speaker 6: on a number of six hundred and fifty billion dollars 97 00:04:39,320 --> 00:04:40,039 Speaker 6: just for this year alone. 98 00:04:40,080 --> 00:04:41,200 Speaker 4: I think just the four. 99 00:04:41,080 --> 00:04:42,680 Speaker 6: Right, I think it's going to be closer to seven 100 00:04:42,839 --> 00:04:45,800 Speaker 6: fifty when you include names like Oracle and Core Week 101 00:04:46,000 --> 00:04:48,560 Speaker 6: And if you think about culatively how much spending has 102 00:04:48,600 --> 00:04:51,280 Speaker 6: gone up. In the beginning of last year, we estimated 103 00:04:51,440 --> 00:04:54,840 Speaker 6: twenty twenty five to twenty through twenty thirty where you're 104 00:04:54,839 --> 00:04:57,520 Speaker 6: going to see two trillion dollars of cumulative spending. We 105 00:04:57,600 --> 00:04:59,760 Speaker 6: rose that, we brought that number to three trillion in 106 00:04:59,800 --> 00:05:02,159 Speaker 6: the all the year, and now we're up above four 107 00:05:02,240 --> 00:05:05,479 Speaker 6: trillion dollars. So these numbers are astronomical. What do you 108 00:05:05,520 --> 00:05:06,960 Speaker 6: do on the back end of that? You're going to 109 00:05:06,960 --> 00:05:09,320 Speaker 6: see a lot of bond deals. Why not borrow when 110 00:05:09,360 --> 00:05:11,840 Speaker 6: your cost of capital is so low. So I think 111 00:05:11,880 --> 00:05:14,240 Speaker 6: you're going to see Amazon, You're going to see Microsoft, 112 00:05:14,440 --> 00:05:16,800 Speaker 6: and even though Apple is not in this hyperscaler game, 113 00:05:16,839 --> 00:05:18,240 Speaker 6: you're going to see them come back as well. 114 00:05:19,560 --> 00:05:23,920 Speaker 2: Robert Schiffman on the credit Corporate Corporate Credit Watch, Mathcamp, 115 00:05:24,279 --> 00:05:29,000 Speaker 2: Bloomberg Intelligence CV love It. Another movie today is Oracle shares. 116 00:05:29,080 --> 00:05:31,240 Speaker 2: We're on a bit of a tear. This comes after 117 00:05:31,680 --> 00:05:34,080 Speaker 2: a tear up nine percent. This comes after DA Davison 118 00:05:34,080 --> 00:05:37,680 Speaker 2: released the note saying improvements from open ai would lift 119 00:05:37,720 --> 00:05:41,400 Speaker 2: the shares of public companies in the chat GPT Baker's Orbit, 120 00:05:41,560 --> 00:05:45,679 Speaker 2: particularly Oracle. Let's bring in DA Davidson Managing director Gil Luria. 121 00:05:45,720 --> 00:05:47,960 Speaker 2: We're just showing the kind of top line of your research, 122 00:05:48,080 --> 00:05:50,880 Speaker 2: and clearly you know that there's some read through right 123 00:05:50,920 --> 00:05:54,040 Speaker 2: in the move we've seen in Oracle this morning. Why 124 00:05:54,200 --> 00:05:57,880 Speaker 2: is Oracle such a key beneficiary if open ai is 125 00:05:57,920 --> 00:06:02,360 Speaker 2: basically able to monetize better, offer more products, and particularly 126 00:06:02,400 --> 00:06:03,880 Speaker 2: strengthen its enterprise business. 127 00:06:05,800 --> 00:06:10,480 Speaker 9: Yeah, most of Oracle's backlog is open ai. So they're 128 00:06:10,480 --> 00:06:13,800 Speaker 9: building up their whole infrastructure now for open ai. And 129 00:06:13,839 --> 00:06:16,599 Speaker 9: the reason the stock has performed so poorly over the 130 00:06:16,640 --> 00:06:19,359 Speaker 9: last few months is that there was a concern that 131 00:06:19,400 --> 00:06:22,120 Speaker 9: open ai wouldn't be able to pay for it, and 132 00:06:22,160 --> 00:06:25,320 Speaker 9: now things have changed. We got to a point last 133 00:06:25,400 --> 00:06:28,640 Speaker 9: week where the market decided that Google was the only 134 00:06:28,720 --> 00:06:30,880 Speaker 9: winner in AI, and you can see that by the 135 00:06:30,920 --> 00:06:34,920 Speaker 9: relative performance of Google versus the open ai complex, which 136 00:06:34,960 --> 00:06:39,120 Speaker 9: is Microsoft and Video, Oracle and core Weave. And it 137 00:06:39,200 --> 00:06:44,160 Speaker 9: got to be too the pendulum swung too far. What's 138 00:06:44,200 --> 00:06:46,760 Speaker 9: happened is open ai has now become more focused on 139 00:06:46,839 --> 00:06:50,360 Speaker 9: chid GPT. It's going to start monetizing more through ads 140 00:06:51,240 --> 00:06:53,320 Speaker 9: within the next couple of weeks. It's going to introduce 141 00:06:53,320 --> 00:06:56,080 Speaker 9: a much better model that will become state of the 142 00:06:56,200 --> 00:07:01,840 Speaker 9: art again, will overtake Google's Gemini and accordantly, because it 143 00:07:01,880 --> 00:07:05,719 Speaker 9: now looks like Google is going to win, that created 144 00:07:05,760 --> 00:07:09,920 Speaker 9: a panic at Microsoft, Amazon and Nvidia, who are now 145 00:07:09,960 --> 00:07:12,760 Speaker 9: going to invest one hundred billion dollars in open Ai 146 00:07:13,480 --> 00:07:18,400 Speaker 9: so they can keep a counterbalance to Google. So with 147 00:07:18,520 --> 00:07:20,600 Speaker 9: that investment, open eye is going to have one hundred, 148 00:07:20,600 --> 00:07:24,120 Speaker 9: one hundred and forty billion dollars of cash. They'll be 149 00:07:24,160 --> 00:07:27,520 Speaker 9: able to pay Microsoft, and then they'll have money to 150 00:07:27,560 --> 00:07:31,800 Speaker 9: pay Oracle which again has the biggest exposure to open Ai. 151 00:07:32,360 --> 00:07:33,800 Speaker 5: That's why we're upgrading today. 152 00:07:34,560 --> 00:07:38,400 Speaker 2: Okay, I appreciate that math on what's changed about the 153 00:07:38,440 --> 00:07:41,120 Speaker 2: situation open ai being good for it? You know that's 154 00:07:41,160 --> 00:07:43,120 Speaker 2: been a question for a long time. You just heard 155 00:07:43,160 --> 00:07:46,440 Speaker 2: bloon Bag Intelligence is Robert Schiffman, Right. Oracle has been 156 00:07:46,480 --> 00:07:50,400 Speaker 2: at the heart of this question on debt versus payoff. 157 00:07:50,440 --> 00:07:52,600 Speaker 2: They've had a lot of demand when they've gone to 158 00:07:52,640 --> 00:07:55,240 Speaker 2: the market, but we are worried. Right they've swung to 159 00:07:55,280 --> 00:07:58,080 Speaker 2: negative free cash flow. They are taking on a lot 160 00:07:58,080 --> 00:08:00,600 Speaker 2: of burden. You seem sang win about that. 161 00:08:02,840 --> 00:08:03,760 Speaker 5: It's still risky. 162 00:08:03,960 --> 00:08:07,200 Speaker 9: To be clear, Oracle really painted themselves in a corner 163 00:08:07,280 --> 00:08:09,960 Speaker 9: when they took on this much business from open Ai, 164 00:08:10,080 --> 00:08:11,200 Speaker 9: and there were two risks. 165 00:08:11,600 --> 00:08:14,760 Speaker 5: One is would Oracle be able to get the capital. 166 00:08:14,440 --> 00:08:17,520 Speaker 9: To start the build out and the second risk was 167 00:08:17,560 --> 00:08:21,280 Speaker 9: would open Ai have the capital and the wherewithal to 168 00:08:21,480 --> 00:08:25,960 Speaker 9: pay Oracle for those services. It now looks like Oracle 169 00:08:26,120 --> 00:08:30,640 Speaker 9: will be successful in the fundrais it'll cause it'll stretch them, 170 00:08:30,960 --> 00:08:33,920 Speaker 9: but it looks like they'll be successful. And now it 171 00:08:33,960 --> 00:08:36,600 Speaker 9: looks like open Ai will also be successful in their 172 00:08:36,640 --> 00:08:37,400 Speaker 9: own fundraise. 173 00:08:37,800 --> 00:08:39,240 Speaker 5: So they'll be able to pay for it. 174 00:08:39,320 --> 00:08:42,600 Speaker 9: So those two risks that we've had up until really 175 00:08:42,640 --> 00:08:45,400 Speaker 9: a few weeks ago, up until a couple of weeks ago, 176 00:08:45,559 --> 00:08:48,720 Speaker 9: really are now looked like they're going to go away, 177 00:08:49,160 --> 00:08:51,760 Speaker 9: and Oracle will be able to build the facilities and 178 00:08:51,880 --> 00:08:53,520 Speaker 9: open ai I will be able to pay for them. 179 00:08:54,640 --> 00:08:55,679 Speaker 4: Who else. 180 00:08:56,880 --> 00:09:00,360 Speaker 3: Benefits in the scenario because I'm saying notes out today 181 00:09:00,480 --> 00:09:04,000 Speaker 3: saying actually, they don't like in video, they don't like AMD, 182 00:09:04,040 --> 00:09:06,760 Speaker 3: I'm talking about link secuities, for example, because they are 183 00:09:06,840 --> 00:09:09,040 Speaker 3: worried that open ai isn't going to be there with 184 00:09:09,120 --> 00:09:11,760 Speaker 3: a better update with enough conviction to be able to 185 00:09:11,760 --> 00:09:13,640 Speaker 3: be perched in the chips that go inside the Oracle 186 00:09:13,679 --> 00:09:14,360 Speaker 3: data sendagil. 187 00:09:15,679 --> 00:09:15,880 Speaker 8: Well. 188 00:09:15,920 --> 00:09:18,120 Speaker 9: So now it looks like open i will remain in 189 00:09:18,160 --> 00:09:21,760 Speaker 9: the race for at least the foreseeable future. And the 190 00:09:21,760 --> 00:09:26,040 Speaker 9: two biggest beneficiars by far are Microsoft and in Vidia. Right, 191 00:09:26,120 --> 00:09:29,520 Speaker 9: Oracle is a marginal play on open AI because of 192 00:09:29,600 --> 00:09:32,400 Speaker 9: how much of it is of their exposure. But really, 193 00:09:32,440 --> 00:09:34,560 Speaker 9: if you look at the stock performance of Google versus 194 00:09:34,640 --> 00:09:38,120 Speaker 9: Nvidia and Microsoft, that diversion over the last few months 195 00:09:38,520 --> 00:09:40,960 Speaker 9: is a result of the market deciding Google's. 196 00:09:40,559 --> 00:09:43,320 Speaker 5: One and open AI is lost. That is not the case. 197 00:09:43,559 --> 00:09:47,760 Speaker 9: The race is still on, which means that that open 198 00:09:47,880 --> 00:09:50,280 Speaker 9: I will spend the two hundred and fifty billion dollars 199 00:09:50,280 --> 00:09:54,520 Speaker 9: on Microsoft, which now has by far the biggest backlog 200 00:09:54,600 --> 00:09:59,560 Speaker 9: in AI compute, and then Microsoft, Amazon, Google and others 201 00:09:59,600 --> 00:10:01,400 Speaker 9: will turn around and spend. 202 00:10:01,120 --> 00:10:02,680 Speaker 5: That on Nvidia chips. 203 00:10:03,360 --> 00:10:06,000 Speaker 9: And so we have Nvidia and Microsoft with the best 204 00:10:06,080 --> 00:10:09,040 Speaker 9: business they've ever had. For Microsoft maybe in twenty five years, 205 00:10:09,040 --> 00:10:12,800 Speaker 9: for Nvidia forever. They're both trading in the low twenties 206 00:10:12,800 --> 00:10:16,880 Speaker 9: on earnings which are historically low multiples. So it's a 207 00:10:17,080 --> 00:10:21,160 Speaker 9: historic opportunity in Nvidia and Microsoft precisely because Opening Eye 208 00:10:21,200 --> 00:10:22,080 Speaker 9: will stay in the race. 209 00:10:22,520 --> 00:10:25,040 Speaker 3: What's interesting is that we've heard a lot about the 210 00:10:25,080 --> 00:10:29,000 Speaker 3: potential of open AI having their own chips. Why not 211 00:10:29,120 --> 00:10:31,480 Speaker 3: more of a broadcom win? Why do they even stay 212 00:10:31,480 --> 00:10:32,240 Speaker 3: with video here? 213 00:10:34,280 --> 00:10:36,000 Speaker 5: Everybody still needs Nvidia. 214 00:10:36,040 --> 00:10:40,840 Speaker 9: All this AI compute will overwhelmingly be built on Nvidia chips. 215 00:10:41,200 --> 00:10:44,240 Speaker 9: There will be some other chips because all these customers 216 00:10:44,240 --> 00:10:47,960 Speaker 9: of Nvidia want desperately to diversify, but they can't do 217 00:10:48,080 --> 00:10:50,760 Speaker 9: it right now because they're building out their capacity so quickly. 218 00:10:51,120 --> 00:10:56,360 Speaker 10: In Vidia has the best chip, has the capacity it works. 219 00:10:55,559 --> 00:11:00,120 Speaker 10: It's available, everybody else will start their own chips, but 220 00:11:00,160 --> 00:11:03,400 Speaker 10: the only company that really has made any significant progress 221 00:11:03,440 --> 00:11:06,040 Speaker 10: on their own ships is Google, and that's because they 222 00:11:06,040 --> 00:11:08,960 Speaker 10: started ten years ago. That's how long it takes to 223 00:11:09,000 --> 00:11:11,840 Speaker 10: have a good chip. Ask Amazon, they're five years and 224 00:11:11,880 --> 00:11:13,880 Speaker 10: then their chip is just starting. 225 00:11:13,400 --> 00:11:13,960 Speaker 5: To get good. 226 00:11:14,000 --> 00:11:16,520 Speaker 4: Didn't look too bad at the Meta. 227 00:11:17,200 --> 00:11:20,120 Speaker 9: Microsoft Meta and opening I can start building their own ships, 228 00:11:20,120 --> 00:11:23,520 Speaker 9: but they're very far away from those being any significant 229 00:11:23,559 --> 00:11:24,920 Speaker 9: portion of their compute. 230 00:11:25,000 --> 00:11:27,720 Speaker 5: It's going to be overwhelmingly in video Gilia. 231 00:11:27,760 --> 00:11:29,880 Speaker 3: It's always great to have you on the show. Yay Davison, 232 00:11:30,000 --> 00:11:32,440 Speaker 3: thanks for ringing us the latest on your research. Mean 233 00:11:32,440 --> 00:11:35,880 Speaker 3: while coming up, we're going to discuss bitcoin slump's future 234 00:11:35,920 --> 00:11:40,120 Speaker 3: in the macroeconomic environment. Would you elect Toberputra from Future 235 00:11:40,240 --> 00:11:41,040 Speaker 3: perfect Mentures? 236 00:11:41,080 --> 00:11:42,559 Speaker 4: That's next us is Bloomberg Tech. 237 00:11:51,920 --> 00:11:54,800 Speaker 3: Bitcoin when it's slipped back below seventy thousand, as you 238 00:11:54,800 --> 00:11:57,760 Speaker 3: can see on the day following a pretty rollercoaster ride 239 00:11:57,760 --> 00:11:59,719 Speaker 3: at the end of last week, a slump from a 240 00:11:59,760 --> 00:12:02,320 Speaker 3: peak of one hundred and twenty six thousand dollars in 241 00:12:02,360 --> 00:12:05,440 Speaker 3: October last year, remember, which comes in spite of crypto 242 00:12:05,440 --> 00:12:08,240 Speaker 3: friendly White House surging institutional adoption. Let's just set the 243 00:12:08,240 --> 00:12:11,400 Speaker 3: scene mobly. Most cross asset reporter Isabelle. Often on the 244 00:12:11,400 --> 00:12:14,280 Speaker 3: weekend there's thinner liquidity, so we see bigger moves and it. 245 00:12:14,240 --> 00:12:17,000 Speaker 11: Seemed to be to the upside, it could be too upset, 246 00:12:17,040 --> 00:12:18,920 Speaker 11: but to the downside as well. But now we saw 247 00:12:18,960 --> 00:12:21,000 Speaker 11: bitcoin kind of studying, which is great because it's now 248 00:12:21,080 --> 00:12:23,800 Speaker 11: hovering around sixty nine thousand, which is a big side 249 00:12:23,800 --> 00:12:26,000 Speaker 11: of relief. Last week it did below as much as 250 00:12:26,080 --> 00:12:29,680 Speaker 11: sixty thousand dollars and that's sixteen percent decline was a 251 00:12:29,679 --> 00:12:33,520 Speaker 11: lot because there's a there's a gage of implied volatility index. 252 00:12:33,760 --> 00:12:36,040 Speaker 11: It jumped to ninety seven percent, which is the highest 253 00:12:36,240 --> 00:12:39,560 Speaker 11: since the Sandbagman freed FTX days in twenty twenty two. 254 00:12:39,600 --> 00:12:41,520 Speaker 11: But beyond the price movement, I think it's really just 255 00:12:41,559 --> 00:12:42,360 Speaker 11: about a reckoning. 256 00:12:42,679 --> 00:12:43,480 Speaker 4: What is bitcoin? 257 00:12:43,559 --> 00:12:46,319 Speaker 11: Is it a hedge against inflation, hedge against centralized government, 258 00:12:46,640 --> 00:12:48,960 Speaker 11: against a hedge against a dollar? And I feel like 259 00:12:49,160 --> 00:12:50,640 Speaker 11: a lot of people are feeling confused. 260 00:12:51,559 --> 00:12:54,440 Speaker 2: Is about what's the flows data? The most recent flows 261 00:12:54,520 --> 00:12:55,680 Speaker 2: data telling us. 262 00:12:56,000 --> 00:12:58,480 Speaker 11: We are seeing some inflows, at least with US Bitcoin 263 00:12:58,520 --> 00:13:00,720 Speaker 11: ETF they recorded an inflow of two undred twenty one 264 00:13:00,800 --> 00:13:03,960 Speaker 11: million on February six, So you could think of that 265 00:13:04,040 --> 00:13:06,920 Speaker 11: as maybe optimism again or maybe just dip buying. But 266 00:13:06,920 --> 00:13:09,400 Speaker 11: then still it's really kind of at least to the 267 00:13:09,440 --> 00:13:11,160 Speaker 11: people I talk to, they're like, what is this. 268 00:13:11,200 --> 00:13:12,600 Speaker 4: It's a structural. 269 00:13:12,160 --> 00:13:14,679 Speaker 11: Change, it's a philosophical change. I want to dip more 270 00:13:14,679 --> 00:13:17,760 Speaker 11: into the structural because we know that bitcoin is kind 271 00:13:17,760 --> 00:13:20,640 Speaker 11: of being institutionalized, and this may in itself be the 272 00:13:20,679 --> 00:13:23,560 Speaker 11: problem because on October ten, fondly known as ten ten, 273 00:13:23,760 --> 00:13:27,000 Speaker 11: that's when we saw billions of dollars liquidated because of 274 00:13:27,480 --> 00:13:30,760 Speaker 11: leverage and derivative traits. And last week we also saw 275 00:13:30,800 --> 00:13:34,079 Speaker 11: the same two point five billion dollars in forced liquidations 276 00:13:34,080 --> 00:13:36,640 Speaker 11: according to coin Glass, So maybe bitcoin is also kind 277 00:13:36,679 --> 00:13:39,280 Speaker 11: of possibly becoming a victim of its own success. 278 00:13:40,600 --> 00:13:43,880 Speaker 2: Bloombergs is welly, terrific reporting. Thank you very much. Let's 279 00:13:43,920 --> 00:13:47,160 Speaker 2: keep the discussion going. Which a Lacavamputra founder and managing 280 00:13:47,200 --> 00:13:51,160 Speaker 2: partner of Future Perfect Ventures, early stage VC firm focused 281 00:13:51,160 --> 00:13:56,600 Speaker 2: on cryptocurrency and blockchain technology. Something identified in the Bloomberg 282 00:13:56,679 --> 00:13:59,680 Speaker 2: story that Isabelle was just discussing is that all of 283 00:13:59,720 --> 00:14:02,880 Speaker 2: this has been happening in an environment where we have 284 00:14:02,960 --> 00:14:07,480 Speaker 2: an administration and policy makers who are perceived to be 285 00:14:07,600 --> 00:14:11,880 Speaker 2: more supportive of the underlying technology and the industry than 286 00:14:11,920 --> 00:14:16,680 Speaker 2: prior administrations. Why would this movement and this market action 287 00:14:16,840 --> 00:14:18,680 Speaker 2: happen therefore in that environment. 288 00:14:20,840 --> 00:14:25,960 Speaker 12: Well, isabel pointed to the maturation of bitcoin, and while 289 00:14:26,320 --> 00:14:29,520 Speaker 12: we have a very friendly administration, a lot of that 290 00:14:29,640 --> 00:14:33,160 Speaker 12: was priced into that run up that we saw to 291 00:14:33,280 --> 00:14:36,160 Speaker 12: the one hundred and twenty six thousand, and we're really 292 00:14:36,200 --> 00:14:40,600 Speaker 12: seeing bitcoin act more like a risk asset these days 293 00:14:40,720 --> 00:14:44,040 Speaker 12: rather than that digital goal narrative that we saw in 294 00:14:44,080 --> 00:14:48,200 Speaker 12: the earlier days of bitcoin. And I'd also point to 295 00:14:48,360 --> 00:14:52,080 Speaker 12: there's a market structure bill previously known as a Clarity 296 00:14:52,120 --> 00:14:56,240 Speaker 12: Act that is still under consideration in the Senate, so 297 00:14:56,280 --> 00:14:58,800 Speaker 12: that has not moved as quickly as those of us 298 00:14:58,880 --> 00:15:02,480 Speaker 12: in the industry had, and I think that's causing a 299 00:15:02,480 --> 00:15:07,240 Speaker 12: little uncertainty around what the guardrails around bitcoin and other 300 00:15:07,280 --> 00:15:08,600 Speaker 12: crypto assets are going to be. 301 00:15:10,200 --> 00:15:12,840 Speaker 2: The words that Isabelle Lee just outline are ringing in 302 00:15:12,880 --> 00:15:17,280 Speaker 2: my head. What is this? Is this structural or is 303 00:15:17,360 --> 00:15:20,760 Speaker 2: this philosophical? That is one of the great soundbites. Good 304 00:15:20,840 --> 00:15:23,240 Speaker 2: job as well, but it is a question that comes 305 00:15:23,320 --> 00:15:25,640 Speaker 2: up a lot. Maybe we should phone David Sachs and 306 00:15:25,720 --> 00:15:28,200 Speaker 2: ask him to your point about the progress of this bill. 307 00:15:28,480 --> 00:15:30,800 Speaker 2: But again you mentioned the structural part. What is the 308 00:15:30,800 --> 00:15:32,960 Speaker 2: philosophical part, Isabelle was alluding to. 309 00:15:33,760 --> 00:15:37,560 Speaker 12: Well, the philosophical part, and I've been invested in the 310 00:15:37,600 --> 00:15:41,040 Speaker 12: sector since twenty thirteen is in the early days, you 311 00:15:41,400 --> 00:15:44,239 Speaker 12: had a lot of long term holders, people who believed 312 00:15:44,400 --> 00:15:48,120 Speaker 12: in the self sovereign currency, the self sovereign asset that 313 00:15:48,200 --> 00:15:49,280 Speaker 12: was not controlled by. 314 00:15:49,160 --> 00:15:50,560 Speaker 5: Any government and. 315 00:15:52,600 --> 00:15:56,760 Speaker 12: Was particularly useful to those people in hyperinflationary environment. So 316 00:15:56,800 --> 00:15:58,800 Speaker 12: that's where that digital goal narrative came. 317 00:15:58,840 --> 00:15:59,360 Speaker 5: Where it was. 318 00:16:02,160 --> 00:16:05,760 Speaker 12: And what we've seen now and as Isabelle said, it 319 00:16:05,800 --> 00:16:07,920 Speaker 12: could be a victim of its own success. I don't 320 00:16:08,000 --> 00:16:12,160 Speaker 12: quite say it's a victim quite yet. But we're seeing 321 00:16:12,200 --> 00:16:16,640 Speaker 12: more institutional holding, and so the institutions have determined that 322 00:16:16,680 --> 00:16:19,160 Speaker 12: this will be more of a risk asset. It will 323 00:16:19,280 --> 00:16:23,920 Speaker 12: trade more in tune with assets like the text stocks, 324 00:16:24,200 --> 00:16:29,080 Speaker 12: not commodities, and so that's where that philosophical divide has happened. 325 00:16:29,760 --> 00:16:33,120 Speaker 12: You know, it's great that we have more institutions, we 326 00:16:33,160 --> 00:16:36,560 Speaker 12: have more acceptance of the sector of bitcoin as an 327 00:16:36,640 --> 00:16:39,920 Speaker 12: asset class, but it may not hold as that digital 328 00:16:39,960 --> 00:16:42,160 Speaker 12: goal and narrative or it may hold. Is that narrative 329 00:16:42,200 --> 00:16:44,840 Speaker 12: in emerging markets and not in developed markets? 330 00:16:45,480 --> 00:16:47,120 Speaker 4: Does that matter to your investments? 331 00:16:47,400 --> 00:16:51,040 Speaker 3: Will you building on bitcoin as the OG and as 332 00:16:51,160 --> 00:16:54,120 Speaker 3: rails to future infrastructure? Are you broader thinking, Actually, we 333 00:16:54,160 --> 00:16:58,120 Speaker 3: don't need bitcoin in and of itself to remain a 334 00:16:58,160 --> 00:17:01,280 Speaker 3: buy and hold asset. I'm more interested in the underlying technology. 335 00:17:01,360 --> 00:17:03,320 Speaker 3: To use an overuse phrase, I'm more interested in the 336 00:17:03,360 --> 00:17:04,840 Speaker 3: stable coin side of the equation. 337 00:17:06,480 --> 00:17:10,120 Speaker 12: Right when I first saw bitcoin, I was really interested 338 00:17:10,160 --> 00:17:14,240 Speaker 12: in it as a self sovereign currency, having been raised 339 00:17:14,400 --> 00:17:18,160 Speaker 12: in emerging markets. However, I was even more excited by 340 00:17:18,320 --> 00:17:23,720 Speaker 12: blotching technology. So this concept of having data or assets 341 00:17:23,840 --> 00:17:30,640 Speaker 12: on chain, that could create more efficiency in the trading 342 00:17:30,720 --> 00:17:33,159 Speaker 12: of data. So if you're going to step away and look. 343 00:17:33,000 --> 00:17:35,040 Speaker 7: At AI and we look at AI. 344 00:17:34,920 --> 00:17:38,560 Speaker 12: Agents and for them to communicate and transact with each other, 345 00:17:38,600 --> 00:17:41,320 Speaker 12: it's much more efficient if they can do it in 346 00:17:41,359 --> 00:17:44,480 Speaker 12: an on chain environment. Now that's much further in the future. 347 00:17:44,840 --> 00:17:48,840 Speaker 12: We're starting to see tokenized securities. We're starting to see 348 00:17:48,920 --> 00:17:53,000 Speaker 12: real world assets, so private credit going on chain. We're 349 00:17:53,000 --> 00:17:57,160 Speaker 12: seeing money market funds go on chain, and we're going 350 00:17:57,160 --> 00:18:02,639 Speaker 12: to continue to see already regulated assets moving on chain. 351 00:18:03,600 --> 00:18:06,639 Speaker 12: ICE from the New York Stock Exchange has talked about 352 00:18:06,680 --> 00:18:11,919 Speaker 12: their initiatives around tokenized equities. So that's all happening regardless 353 00:18:11,960 --> 00:18:14,639 Speaker 12: of what happens to the bitcoin price. So we're really 354 00:18:14,680 --> 00:18:20,120 Speaker 12: seeing the financial infrastructure being rebuilt by blockchain technology, which 355 00:18:20,160 --> 00:18:24,199 Speaker 12: also powers bitcoin. I don't think either is going away. 356 00:18:24,480 --> 00:18:27,040 Speaker 12: I think we just have to separate the two and 357 00:18:27,240 --> 00:18:34,440 Speaker 12: of note stable coins which are run on chain. Those 358 00:18:34,520 --> 00:18:37,640 Speaker 12: were regulated by the Genius Act which passed last year, 359 00:18:37,680 --> 00:18:41,959 Speaker 12: and then we've seen a proliferation of activity in that sector. 360 00:18:42,160 --> 00:18:43,920 Speaker 4: So not because of that regulation. 361 00:18:44,040 --> 00:18:47,760 Speaker 3: Do you continue to call yourself crypto first VC briefly 362 00:18:47,960 --> 00:18:49,200 Speaker 3: or do you become an AI VC. 363 00:18:50,760 --> 00:18:54,480 Speaker 12: Well, our thesis has always been around the intersection of blockchain, 364 00:18:54,520 --> 00:18:58,919 Speaker 12: crypto assets, and AI forming the basis of the next Internet. 365 00:19:00,080 --> 00:19:03,840 Speaker 12: We've seen the development of these different areas at different times. 366 00:19:03,880 --> 00:19:06,760 Speaker 12: I think they're all very important to our future. I 367 00:19:06,800 --> 00:19:10,480 Speaker 12: think that cryptoside may take a bit longer to really, 368 00:19:10,640 --> 00:19:14,639 Speaker 12: you know, form or validate itself. 369 00:19:14,280 --> 00:19:15,080 Speaker 13: In that narrative. 370 00:19:15,720 --> 00:19:19,280 Speaker 3: Jilac Jowin Putcher of Future Perfect Ventures, we appreciate it. 371 00:19:19,320 --> 00:19:19,719 Speaker 4: Thank you. 372 00:19:20,440 --> 00:19:23,520 Speaker 3: Now coming up, Apple prepares for an update to its iPhone. 373 00:19:23,520 --> 00:19:26,359 Speaker 4: It's iPads, it's Max. More on that next. This is 374 00:19:26,400 --> 00:19:27,160 Speaker 4: Bloomberg Tech. 375 00:19:36,400 --> 00:19:38,800 Speaker 2: Apple is set to debut a slew of new products 376 00:19:38,800 --> 00:19:41,840 Speaker 2: in the coming weeks, including a new iPhone seventeen E 377 00:19:42,400 --> 00:19:45,639 Speaker 2: and updated iPads and Max. Here with the breakdown Bloomberg's 378 00:19:45,640 --> 00:19:48,439 Speaker 2: Apple and consumer tech editor Mark German the power on 379 00:19:48,520 --> 00:19:52,280 Speaker 2: drop Sunday, and you basically give us the products release 380 00:19:52,440 --> 00:19:55,760 Speaker 2: roadmap for the early part of this year. What do 381 00:19:55,800 --> 00:19:56,320 Speaker 2: we need to know? 382 00:19:57,600 --> 00:19:59,600 Speaker 13: Yes, there's a new eyes some one coming pretty eminently 383 00:19:59,640 --> 00:20:00,520 Speaker 13: in the next few weeks. 384 00:20:00,520 --> 00:20:02,120 Speaker 7: It's the iPhone seventeen E. 385 00:20:02,240 --> 00:20:04,760 Speaker 13: It's a successor to the sixteen E that launched about 386 00:20:04,760 --> 00:20:08,239 Speaker 13: a year ago last year. This new version is going 387 00:20:08,280 --> 00:20:10,560 Speaker 13: to have the same chip as the iPhone seventeen, so 388 00:20:10,600 --> 00:20:13,560 Speaker 13: moving from the A eighteen to the A nineteen. And 389 00:20:13,600 --> 00:20:15,840 Speaker 13: it addresses one of the quirks of the first model, 390 00:20:15,880 --> 00:20:18,760 Speaker 13: which was the lack of MagSafe, which means no magnetic 391 00:20:18,800 --> 00:20:22,000 Speaker 13: wireless charging within Apple's mag Safe ecosystem. 392 00:20:22,040 --> 00:20:24,480 Speaker 7: So that's coming as well. 393 00:20:24,560 --> 00:20:27,760 Speaker 13: Also an updated in housemodem, an updated in house wireless 394 00:20:27,840 --> 00:20:32,080 Speaker 13: chip to match the iPhone Air from September. You're also 395 00:20:32,119 --> 00:20:34,960 Speaker 13: going to see some new iPads in the next month 396 00:20:35,040 --> 00:20:38,360 Speaker 13: or so. That includes a new version of the iPad 397 00:20:38,440 --> 00:20:40,479 Speaker 13: AIR with the M four chip, so a bet if 398 00:20:40,520 --> 00:20:44,560 Speaker 13: the faster processor there, matching the iPad pro sew from 399 00:20:44,680 --> 00:20:48,200 Speaker 13: twenty twenty four. And then you're also going to see 400 00:20:48,240 --> 00:20:51,480 Speaker 13: a new entry level iPad moving to the A eighteen chip. 401 00:20:51,520 --> 00:20:52,719 Speaker 7: Now why is that significant? 402 00:20:52,720 --> 00:20:55,200 Speaker 13: It will be the first iPad from the entry level 403 00:20:55,520 --> 00:20:58,639 Speaker 13: batch to support Apple Intelligence. And you're also going to 404 00:20:58,640 --> 00:21:01,280 Speaker 13: see new high end map book pro and netbook airs 405 00:21:01,320 --> 00:21:04,480 Speaker 13: in the coming month as well, So a lots alike 406 00:21:04,520 --> 00:21:08,760 Speaker 13: if you're into new low end iPhones, iPads as well 407 00:21:08,800 --> 00:21:09,480 Speaker 13: as MacBooks. 408 00:21:09,560 --> 00:21:10,720 Speaker 4: So who's into it? Mark? 409 00:21:10,760 --> 00:21:12,880 Speaker 3: On that note, I can see a lower price point 410 00:21:12,920 --> 00:21:15,200 Speaker 3: being attractive. It's interesting that you are pushing forward the 411 00:21:15,880 --> 00:21:18,040 Speaker 3: view that enterprises might well be interested. 412 00:21:18,880 --> 00:21:22,240 Speaker 13: Yeah, two tent poles this year for Apple Education and enterprise. 413 00:21:22,359 --> 00:21:26,679 Speaker 13: Apple is I would say tripling down on moving units 414 00:21:26,680 --> 00:21:29,159 Speaker 13: into both of those segments. They have a lot of 415 00:21:29,160 --> 00:21:32,000 Speaker 13: the consumers already, they're trying to break into other areas 416 00:21:32,240 --> 00:21:34,639 Speaker 13: that they've struggled to break into in the past, and 417 00:21:34,760 --> 00:21:37,720 Speaker 13: all these products have price points and feature sets that 418 00:21:37,760 --> 00:21:40,640 Speaker 13: are going to be heavily applicable to business use cases 419 00:21:40,680 --> 00:21:44,199 Speaker 13: and bulk purchases. Also, a low cost MacBook with an 420 00:21:44,200 --> 00:21:47,400 Speaker 13: iPhone chip coming as well. This will be sub eight 421 00:21:47,480 --> 00:21:50,160 Speaker 13: hundred dollars, so this is going to be pretty fancy 422 00:21:50,359 --> 00:21:53,040 Speaker 13: and compelling for both those segments as well. 423 00:21:53,200 --> 00:21:56,280 Speaker 2: Mark, I'm running at twenty nineteen twenty twenty macare with 424 00:21:56,320 --> 00:22:00,440 Speaker 2: an m one ship. Just on the macpart update right 425 00:22:00,480 --> 00:22:02,040 Speaker 2: times upgrade you have thirty seconds? 426 00:22:02,080 --> 00:22:05,160 Speaker 13: Why well, because your laptop is seven years old, time 427 00:22:05,240 --> 00:22:05,840 Speaker 13: to get a new one. 428 00:22:05,840 --> 00:22:09,399 Speaker 7: But now in reality is that the chips have the 429 00:22:09,480 --> 00:22:10,879 Speaker 7: chips have gotten much more advanced. 430 00:22:10,920 --> 00:22:14,720 Speaker 13: They have AI capabilities now, oh, better graphics processor. So 431 00:22:14,720 --> 00:22:17,159 Speaker 13: if you're on an m one machine or an Intel machine, 432 00:22:17,640 --> 00:22:19,680 Speaker 13: definitely think about getting something new. I'm going to m 433 00:22:19,720 --> 00:22:23,080 Speaker 13: one myself and I'm looking forward to the touchscreen MacBook 434 00:22:23,080 --> 00:22:25,560 Speaker 13: Pro overhaul coming in the fall, so that'll be pretty 435 00:22:25,600 --> 00:22:26,240 Speaker 13: nifty as well. 436 00:22:26,600 --> 00:22:30,000 Speaker 4: Get on Ed Bloomberg's Markoman, so great to have you on. 437 00:22:30,200 --> 00:22:31,200 Speaker 4: Thank you very much. Adin. 438 00:22:31,240 --> 00:22:34,800 Speaker 3: Now coming up, investors, look beyond the AI data center 439 00:22:34,840 --> 00:22:38,480 Speaker 3: play Apparently Cowash Life of Femo Private Wealth joins us 440 00:22:38,840 --> 00:22:42,200 Speaker 3: see how she's looking past them as a Bloomberg Tech. 441 00:22:51,880 --> 00:22:54,000 Speaker 2: Welcome back, to Bloomberg Tech. I'm zeroed in on the 442 00:22:54,080 --> 00:22:57,840 Speaker 2: chip sector. In the session so far, the Philadelphia Semiconductor 443 00:22:57,880 --> 00:23:00,480 Speaker 2: Index or SOCKS is swung from a decline of about 444 00:23:00,520 --> 00:23:02,400 Speaker 2: one percent at the open to a gain of now 445 00:23:02,440 --> 00:23:05,600 Speaker 2: one point six percent. Really, it's in Vidia as the 446 00:23:05,600 --> 00:23:08,080 Speaker 2: biggest points gainer that's pushing higher, And there was a 447 00:23:08,119 --> 00:23:11,840 Speaker 2: lot over the weekend about how confident in video is 448 00:23:11,920 --> 00:23:13,720 Speaker 2: right now in the infrastructure build out. One of the 449 00:23:13,800 --> 00:23:17,200 Speaker 2: laggards though, is Micron down two point five percent. There 450 00:23:17,240 --> 00:23:18,879 Speaker 2: was a report over the weekend, we'll bring you the 451 00:23:18,880 --> 00:23:22,399 Speaker 2: details later in the show, that Samsung, its rival in 452 00:23:22,480 --> 00:23:25,120 Speaker 2: high bandwidth memory, is going to start shipping Latest Gen 453 00:23:25,200 --> 00:23:28,600 Speaker 2: to in Vidia this month. Our own colleagues at Bloomberg 454 00:23:28,600 --> 00:23:31,880 Speaker 2: Intelligence have weighed in this morning saying that actually what's 455 00:23:31,920 --> 00:23:34,760 Speaker 2: going on with Mike Cron and high bandwidth latest generation 456 00:23:34,920 --> 00:23:37,679 Speaker 2: four is kind of muted, but right now that seems 457 00:23:37,680 --> 00:23:39,639 Speaker 2: to be a story in the market, And again bringing 458 00:23:39,680 --> 00:23:41,359 Speaker 2: those deats a little bit later in the program. 459 00:23:41,359 --> 00:23:43,400 Speaker 3: Current, Yeah, you're looking at the hardware, Let's go more 460 00:23:43,440 --> 00:23:45,840 Speaker 3: broad and look at software and all parts of big tech, 461 00:23:45,920 --> 00:23:49,080 Speaker 3: the movers there in Bloomberg TV Markets correspondent Normlenda's with 462 00:23:49,160 --> 00:23:51,159 Speaker 3: us nor to take us away because it was a 463 00:23:51,240 --> 00:23:52,560 Speaker 3: volatile previous week. 464 00:23:52,720 --> 00:23:55,160 Speaker 4: How this week started last week was quite the week. 465 00:23:55,200 --> 00:23:56,720 Speaker 14: I mean, we're looking at this week, We're seeing the 466 00:23:56,760 --> 00:23:59,720 Speaker 14: Nazeq one hundred rebounding for a second stay in a row. 467 00:24:00,080 --> 00:24:02,600 Speaker 14: Also seeing a lot of those software stocks rebounding. I'm 468 00:24:02,600 --> 00:24:05,000 Speaker 14: taking a look at app Lovin, We've got Palenteer and 469 00:24:05,040 --> 00:24:08,320 Speaker 14: Focus Microsoft. As I'm speaking to my sources, we're hearing 470 00:24:08,359 --> 00:24:10,160 Speaker 14: that people are really trying to buy the dip. They're 471 00:24:10,160 --> 00:24:12,439 Speaker 14: really trying to figure out where the risks are in 472 00:24:12,480 --> 00:24:15,520 Speaker 14: this market and figure out where to best position themselves now. 473 00:24:15,760 --> 00:24:17,760 Speaker 14: So we are seeing app Levin in particular. We did 474 00:24:17,880 --> 00:24:20,800 Speaker 14: see that City did mention that their e commerce clients 475 00:24:20,800 --> 00:24:23,320 Speaker 14: are up about three percent from the prior week, so 476 00:24:23,359 --> 00:24:25,760 Speaker 14: that of course is also boing the shares in particular. 477 00:24:26,000 --> 00:24:28,840 Speaker 14: But we really are seeing these stocks trying to map 478 00:24:28,880 --> 00:24:31,520 Speaker 14: out chart a turnaround story here as a lot of 479 00:24:31,560 --> 00:24:34,040 Speaker 14: people are trying to figure out which stocks maybe perhaps 480 00:24:34,080 --> 00:24:36,159 Speaker 14: have the least exposure to some of these risks that 481 00:24:36,200 --> 00:24:38,560 Speaker 14: we've really been seeing laid out last week. And people 482 00:24:38,600 --> 00:24:41,239 Speaker 14: are really seeing microsoftware instance, and we think about them 483 00:24:41,240 --> 00:24:43,840 Speaker 14: as a potential bell weather in this space. It really 484 00:24:43,880 --> 00:24:46,960 Speaker 14: shows that this rally isn't necessarily just exclusive to software stocks, 485 00:24:47,160 --> 00:24:50,080 Speaker 14: but really just a broad based rebound for all of tech. 486 00:24:53,200 --> 00:24:56,000 Speaker 2: Laura and me, Linda, with the market shrapp Microsoft up 487 00:24:56,080 --> 00:24:58,480 Speaker 2: three percent, I don't know, Like I'm trying to think 488 00:24:58,640 --> 00:25:00,560 Speaker 2: that the anxiety that I was so it in on 489 00:25:00,600 --> 00:25:03,480 Speaker 2: at the end of last week faded with the super Bowl. 490 00:25:03,560 --> 00:25:07,159 Speaker 2: The technology story is broadening, expanding past just AI in 491 00:25:07,240 --> 00:25:10,280 Speaker 2: data centers. In a recent note, Carol Schlife, chief market 492 00:25:10,320 --> 00:25:14,200 Speaker 2: strategists at BEMO Private Wealth, rights that the real focus 493 00:25:14,320 --> 00:25:17,600 Speaker 2: is shifting to who's using the technology and how it's 494 00:25:17,640 --> 00:25:19,920 Speaker 2: being applied. She adds that rising M and A activity, 495 00:25:20,040 --> 00:25:24,320 Speaker 2: IPOs and ongoing innovation could help fuel continued interests and 496 00:25:24,359 --> 00:25:27,560 Speaker 2: momentum in the year ahead. Carol joins us, now, I 497 00:25:27,600 --> 00:25:29,959 Speaker 2: want to start with the shift part and we'll get 498 00:25:30,000 --> 00:25:32,200 Speaker 2: to IPOs, because of course it's been a big story 499 00:25:32,200 --> 00:25:33,159 Speaker 2: for us here on the show. 500 00:25:33,680 --> 00:25:34,600 Speaker 7: What is it that you're. 501 00:25:34,480 --> 00:25:37,159 Speaker 2: Seeing in a shift? You're seeing the psychology of the 502 00:25:37,200 --> 00:25:40,719 Speaker 2: market shift, You're seeing the attention of the market shift, 503 00:25:41,240 --> 00:25:43,280 Speaker 2: or you're seeing people's understanding shift. 504 00:25:43,320 --> 00:25:43,840 Speaker 8: Which is it? 505 00:25:44,880 --> 00:25:47,280 Speaker 15: I think it's it's a piece of all of those things, 506 00:25:47,280 --> 00:25:50,360 Speaker 15: because it's a natural evolution. You know, when we first 507 00:25:50,480 --> 00:25:53,960 Speaker 15: year an innovation, take it back to when chat GPT 508 00:25:54,240 --> 00:25:56,199 Speaker 15: was first announced a couple of years ago, and then 509 00:25:56,240 --> 00:25:59,359 Speaker 15: the deep seek as well convestors figure out what's my 510 00:25:59,440 --> 00:26:03,000 Speaker 15: shorthand way to play this. But it's really more impactful 511 00:26:03,040 --> 00:26:07,200 Speaker 15: from that and getting investors, particularly our longer term oriented clients, 512 00:26:07,480 --> 00:26:10,320 Speaker 15: focused on the issue that we're building infrastructure in the 513 00:26:10,400 --> 00:26:13,639 Speaker 15: United States. It's putting capital investment in which we haven't 514 00:26:13,680 --> 00:26:16,440 Speaker 15: done actually in a big macro way in a very 515 00:26:16,480 --> 00:26:18,960 Speaker 15: long period of time, and it's teeing up all of 516 00:26:19,000 --> 00:26:23,480 Speaker 15: these really important evolutions. And you've got a lot of 517 00:26:23,520 --> 00:26:28,560 Speaker 15: recent examples, for example, in the healthcare industry where you've 518 00:26:28,560 --> 00:26:31,800 Speaker 15: had Newly an Vidia announced a joint venture, you had 519 00:26:31,840 --> 00:26:35,240 Speaker 15: Mayo Clinic and Nvidia announce a joint venture. In terms 520 00:26:35,280 --> 00:26:38,320 Speaker 15: of processing that data and how science will be done 521 00:26:38,320 --> 00:26:41,320 Speaker 15: and how diagnostic imaging will be done, and those use 522 00:26:41,400 --> 00:26:44,600 Speaker 15: cases are getting investors to focus more on those, But 523 00:26:44,720 --> 00:26:47,200 Speaker 15: it's tough from an investor standpoint because they want to 524 00:26:47,240 --> 00:26:49,200 Speaker 15: what can I buy today that's going to be higher 525 00:26:49,200 --> 00:26:50,040 Speaker 15: by the end of the week. 526 00:26:51,680 --> 00:26:54,720 Speaker 2: Carol you heard Bluemstrea of a Linda kind of outline 527 00:26:54,880 --> 00:26:57,560 Speaker 2: the events of the last five days, you know, Friday. 528 00:26:57,960 --> 00:27:00,280 Speaker 2: We always say like one session of market does not 529 00:27:00,359 --> 00:27:04,200 Speaker 2: make but clearly there are some deep rooted concerns that 530 00:27:04,359 --> 00:27:07,240 Speaker 2: corners of the technology industry. I kind of like legacy 531 00:27:07,280 --> 00:27:12,080 Speaker 2: software are at severe risk. Here does your research reflect 532 00:27:12,160 --> 00:27:12,800 Speaker 2: that as well? 533 00:27:14,240 --> 00:27:17,160 Speaker 15: I think the issue is it's also important to remember 534 00:27:17,240 --> 00:27:20,640 Speaker 15: from a use case scenario, it's not like big corporations 535 00:27:20,720 --> 00:27:24,040 Speaker 15: or even medium sized corporations can ditch the software they had. 536 00:27:24,080 --> 00:27:25,280 Speaker 7: People aren't going to give. 537 00:27:25,200 --> 00:27:30,480 Speaker 15: Up their client service processing or their routines. It takes 538 00:27:30,520 --> 00:27:33,159 Speaker 15: a while to get that stuff iterated in and I 539 00:27:33,160 --> 00:27:35,400 Speaker 15: heard one of our analysts this morning just talking about 540 00:27:35,400 --> 00:27:38,119 Speaker 15: it. It's not like someone sitting at the kitchen table is 541 00:27:38,200 --> 00:27:41,080 Speaker 15: going to replace a lot of that macro software that 542 00:27:41,119 --> 00:27:44,119 Speaker 15: we've been using. But a repricing of a do you 543 00:27:44,200 --> 00:27:46,920 Speaker 15: discount the kinds of growth rates they've seen for thirty 544 00:27:47,000 --> 00:27:49,840 Speaker 15: years or is it five or ten years? That's partly 545 00:27:49,880 --> 00:27:52,440 Speaker 15: what the markets are trying to deal with too, is figuring. 546 00:27:52,160 --> 00:27:53,520 Speaker 13: Out how does this go forward? 547 00:27:54,440 --> 00:27:57,600 Speaker 15: And similar to the first internet build out in ninety 548 00:27:57,600 --> 00:28:01,080 Speaker 15: five to two, thousand. You have the iteration where everyone's 549 00:28:01,119 --> 00:28:02,880 Speaker 15: trying to figure out how to use it, and it's 550 00:28:02,920 --> 00:28:06,800 Speaker 15: those companies, those managements, those industries that can lean into 551 00:28:06,840 --> 00:28:08,760 Speaker 15: the fact that there's a lot of change. How are 552 00:28:08,800 --> 00:28:12,280 Speaker 15: we going to participate in it versus sit back and 553 00:28:12,359 --> 00:28:13,720 Speaker 15: let it be done to them? 554 00:28:14,400 --> 00:28:16,439 Speaker 3: Do you clients want is it back and let it 555 00:28:16,440 --> 00:28:17,040 Speaker 3: be done to them? 556 00:28:17,080 --> 00:28:18,480 Speaker 4: Or do they want to buy? 557 00:28:19,600 --> 00:28:22,760 Speaker 15: I think they're trying to figure out how to participate 558 00:28:22,760 --> 00:28:24,679 Speaker 15: in it. And we've been warning for some period of 559 00:28:24,720 --> 00:28:26,639 Speaker 15: time that you needed to see a broadening in the 560 00:28:26,680 --> 00:28:30,720 Speaker 15: markets because hanging everything on six or seven stocks is 561 00:28:30,760 --> 00:28:33,520 Speaker 15: not healthy in the long run. And we had talked 562 00:28:33,560 --> 00:28:36,480 Speaker 15: about and given them a heads up that some of 563 00:28:36,520 --> 00:28:39,600 Speaker 15: that transition may be volatile. Doesn't mean that people have 564 00:28:39,680 --> 00:28:41,880 Speaker 15: to sell the seven and go buy the four ninety three. 565 00:28:41,920 --> 00:28:45,360 Speaker 15: It can mean the seven broaden out or flatten out, 566 00:28:45,440 --> 00:28:47,760 Speaker 15: if you will, and the others catch up. Do some 567 00:28:47,840 --> 00:28:50,640 Speaker 15: catch up. So we've been warning clients about that volatility, 568 00:28:50,920 --> 00:28:54,360 Speaker 15: and our clients tend to be pretty sanguine, if you will, 569 00:28:54,480 --> 00:28:58,160 Speaker 15: about that in terms of letting us do repositioning as 570 00:28:58,560 --> 00:29:01,680 Speaker 15: prices are up. You know, investing is one of those 571 00:29:01,720 --> 00:29:05,200 Speaker 15: activities where it's more comfortable to run with the crowd, 572 00:29:05,200 --> 00:29:07,720 Speaker 15: which is typically the wrong situation to have from a 573 00:29:07,760 --> 00:29:08,720 Speaker 15: long term standpoint. 574 00:29:08,920 --> 00:29:10,800 Speaker 3: And what we always do is get secked into just 575 00:29:10,840 --> 00:29:13,360 Speaker 3: talking about equities a lot because there real lies the 576 00:29:13,400 --> 00:29:15,920 Speaker 3: price point. But the wall market's exciting as well. We've 577 00:29:15,920 --> 00:29:18,440 Speaker 3: got huge amount on deck. When you think about alf 578 00:29:18,480 --> 00:29:21,040 Speaker 3: of that taping we had Oracle last week, we got plenty. 579 00:29:20,760 --> 00:29:22,320 Speaker 4: More's short to come. 580 00:29:22,960 --> 00:29:25,440 Speaker 3: Is that an area that you're seeing more diversification coming, 581 00:29:25,480 --> 00:29:27,960 Speaker 3: more interesting corporate debt as well. 582 00:29:28,120 --> 00:29:28,280 Speaker 5: Well. 583 00:29:28,320 --> 00:29:31,120 Speaker 15: I think there is the interesting corporate debt, but it's 584 00:29:31,120 --> 00:29:34,280 Speaker 15: also important to remember that technology in general has prided 585 00:29:34,320 --> 00:29:37,360 Speaker 15: themselves on how under levered they've been, so coming up 586 00:29:37,360 --> 00:29:40,360 Speaker 15: to using some of that cash flow or balancing off 587 00:29:40,880 --> 00:29:44,400 Speaker 15: and reserving some cash flow and accessing the debt market 588 00:29:44,440 --> 00:29:46,880 Speaker 15: and its higher quality debt. So there's that piece of 589 00:29:46,920 --> 00:29:50,360 Speaker 15: it too. But there's a lot of different ways to 590 00:29:50,400 --> 00:29:53,600 Speaker 15: play this, and not just the focus on technology itself, 591 00:29:53,680 --> 00:29:56,520 Speaker 15: but who's making the best use cases of it. New 592 00:29:56,560 --> 00:29:59,520 Speaker 15: as the most potential. You're seeing small and mid cap 593 00:29:59,520 --> 00:30:02,880 Speaker 15: stocks really played too, because they don't get all locked 594 00:30:02,960 --> 00:30:05,120 Speaker 15: up in having to approve new software, per se they 595 00:30:05,120 --> 00:30:08,280 Speaker 15: really can lean into leap frogging some of the advances 596 00:30:08,280 --> 00:30:10,280 Speaker 15: that they have access to now. 597 00:30:10,400 --> 00:30:14,880 Speaker 4: Caroash Life keeping US diversified. We appreciate it. BMO Private Wealth. 598 00:30:15,520 --> 00:30:19,000 Speaker 3: Now coming up, tech dominates the Super Bowl ad space. 599 00:30:19,040 --> 00:30:22,920 Speaker 3: Did you notice AHI was definitely in focus that discussion. Next, 600 00:30:23,440 --> 00:30:35,560 Speaker 3: this is bluembg Tech, an Australian AI startup back by 601 00:30:35,600 --> 00:30:37,640 Speaker 3: and Video just secured a ten billion dollar loan from 602 00:30:37,640 --> 00:30:40,120 Speaker 3: a group that includes Blackstone Lead Funds. 603 00:30:39,960 --> 00:30:41,479 Speaker 4: To boost US data center rollout. 604 00:30:41,640 --> 00:30:44,800 Speaker 3: Now is one of the country's largest private credit financings, 605 00:30:44,840 --> 00:30:48,320 Speaker 3: called Firmus Technologies, the startup plans to construct data centers 606 00:30:48,320 --> 00:30:51,200 Speaker 3: with a combined capacity up to one point six gigawads 607 00:30:51,360 --> 00:30:53,200 Speaker 3: across Australia by twenty twenty eight. 608 00:30:53,240 --> 00:30:57,360 Speaker 2: Lead okay to the private markets and Propic is finalizing 609 00:30:57,400 --> 00:30:59,760 Speaker 2: the details of a funding round of more than twenty 610 00:31:00,000 --> 00:31:03,200 Speaker 2: billion dollars, which would nearly double its valuation to three 611 00:31:03,280 --> 00:31:05,880 Speaker 2: hundred and fifty billion dollars. Let's get the details Bloomberg's 612 00:31:05,880 --> 00:31:09,360 Speaker 2: Bench Capital Reporter and Natasha mescarinus here in SF. This 613 00:31:09,400 --> 00:31:12,600 Speaker 2: is something we broke just before the weekend, chased over 614 00:31:12,640 --> 00:31:15,000 Speaker 2: the weekend, and we think it's coming this week, right, 615 00:31:15,440 --> 00:31:16,080 Speaker 2: where are they at? 616 00:31:16,280 --> 00:31:18,640 Speaker 16: Yeah, I mean exactly a month ago, Anthropic came out 617 00:31:18,640 --> 00:31:21,520 Speaker 16: of the gate targeting around ten billion. Now we're seeing 618 00:31:21,560 --> 00:31:24,400 Speaker 16: that amount could go even higher than twenty billion. 619 00:31:24,560 --> 00:31:25,840 Speaker 4: And this is not just a. 620 00:31:25,760 --> 00:31:29,120 Speaker 16: Funding round that's going to include money from Nvidia and Microsoft, 621 00:31:29,120 --> 00:31:32,320 Speaker 16: although they are expecting to put up to fifteen billion 622 00:31:32,360 --> 00:31:35,600 Speaker 16: into the company. This is around where traditional investors are 623 00:31:35,640 --> 00:31:38,560 Speaker 16: actually putting in new money into the deal as well. 624 00:31:38,560 --> 00:31:43,560 Speaker 16: We're thinking Menlo light speed Altimeter Sequoia, it runs the gamut. 625 00:31:43,760 --> 00:31:46,800 Speaker 3: It's interesting that you didn't mention there the typical crossover 626 00:31:46,840 --> 00:31:50,720 Speaker 3: funds as well. Natasha and we are all racing for 627 00:31:51,000 --> 00:31:53,920 Speaker 3: Anthropic and indeed Key Rifle open Ai to be tapping 628 00:31:53,920 --> 00:31:55,400 Speaker 3: the public market at some point. 629 00:31:55,160 --> 00:31:57,400 Speaker 4: This year exactly. 630 00:31:57,440 --> 00:32:00,480 Speaker 16: It's actually a fascinating example of how invest you're thinking 631 00:32:00,520 --> 00:32:03,400 Speaker 16: about a company, two companies really to your point, and 632 00:32:03,480 --> 00:32:07,760 Speaker 16: investing in them before that initial public debut. So this 633 00:32:07,840 --> 00:32:10,960 Speaker 16: time we're also seeing Anthropic line up investors for an 634 00:32:10,960 --> 00:32:14,000 Speaker 16: employee tender, which will give employees a chance to liquidate 635 00:32:14,040 --> 00:32:17,440 Speaker 16: some of their equity holdings and again cash out before 636 00:32:17,560 --> 00:32:19,280 Speaker 16: a future public offering. 637 00:32:19,560 --> 00:32:22,000 Speaker 3: Natasha and Mascarine is is going to be a busy 638 00:32:22,040 --> 00:32:25,240 Speaker 3: week for you. We say appreciate you starting it with us. Meanwhile, 639 00:32:25,440 --> 00:32:28,160 Speaker 3: it was busy with this year's Super Bowl. Ads leaned 640 00:32:28,240 --> 00:32:31,120 Speaker 3: heavily into AI, of course, with tech companies using the 641 00:32:31,160 --> 00:32:33,640 Speaker 3: big stage to showcase their latest tools and ideas. Now, 642 00:32:33,680 --> 00:32:37,760 Speaker 3: according to analytics firm Edo, AI dot Com led the 643 00:32:37,800 --> 00:32:41,240 Speaker 3: pack and consumer engagement, generating roughly nine point one times 644 00:32:41,240 --> 00:32:44,680 Speaker 3: the interaction of a median Super Bowl ad. Joining us 645 00:32:44,720 --> 00:32:46,720 Speaker 3: now to break it all down, as Kevin Crimany's president 646 00:32:46,760 --> 00:32:50,960 Speaker 3: and CEO of Edo, what's more birds eye perspective is 647 00:32:50,960 --> 00:32:54,440 Speaker 3: that tech dominated just the ad spend, the ad that. 648 00:32:54,400 --> 00:32:55,000 Speaker 4: Were out there. 649 00:32:55,280 --> 00:32:57,960 Speaker 17: It was the Tech super Bowl and Natasha in Carolina. 650 00:32:58,000 --> 00:33:03,680 Speaker 17: It was absolutely groundbreaking to see more AI product ads 651 00:33:04,080 --> 00:33:07,640 Speaker 17: than there were combined automotive and beer ads, the stalwarts 652 00:33:07,680 --> 00:33:09,120 Speaker 17: of your typical Super Bowl. 653 00:33:09,800 --> 00:33:13,640 Speaker 3: AI dot Com gains traction. Why because no one understands 654 00:33:13,680 --> 00:33:15,480 Speaker 3: what it actually is. I mean, we now will peel 655 00:33:15,480 --> 00:33:17,080 Speaker 3: back the onion and understand it's the guy who made 656 00:33:17,080 --> 00:33:18,719 Speaker 3: his money in crypto dot com has brought this very 657 00:33:18,720 --> 00:33:21,160 Speaker 3: expensive website and now wanting us to all put our 658 00:33:21,200 --> 00:33:23,640 Speaker 3: details into it and have an AI agent of the future. 659 00:33:23,680 --> 00:33:27,360 Speaker 3: But what was the recipe for getting us to convert. 660 00:33:27,720 --> 00:33:31,880 Speaker 17: Well, there's this heated rivalry going on between anthropic and OpenAI, 661 00:33:32,400 --> 00:33:34,680 Speaker 17: and then suddenly this dark Corse AI dot com that 662 00:33:34,720 --> 00:33:37,120 Speaker 17: no one had heard of comes in and is trolling 663 00:33:37,200 --> 00:33:40,479 Speaker 17: both of them, along with Mark Zuckerberg mentioning you all 664 00:33:40,520 --> 00:33:43,840 Speaker 17: these folks by name. And what you've got is that 665 00:33:43,920 --> 00:33:46,520 Speaker 17: perfect formula of introducing something totally new to people, but 666 00:33:46,560 --> 00:33:50,120 Speaker 17: it's completely on trend. This was the AI super Bowl 667 00:33:50,520 --> 00:33:54,040 Speaker 17: and so it surprised people. It cought people I and 668 00:33:54,200 --> 00:33:56,680 Speaker 17: they went. They crashed the website. It was down for 669 00:33:56,720 --> 00:34:00,960 Speaker 17: many minutes after after that ad aired and finally came 670 00:34:01,000 --> 00:34:04,000 Speaker 17: back online. But what I think you saw just writ 671 00:34:04,080 --> 00:34:07,080 Speaker 17: large was two things going on in the Super Bowl. 672 00:34:07,680 --> 00:34:08,360 Speaker 8: And we had idio. 673 00:34:08,480 --> 00:34:11,200 Speaker 17: We're measuring the outcomes generated by these ads, and. 674 00:34:11,160 --> 00:34:13,040 Speaker 8: You saw people either engaging with new. 675 00:34:12,960 --> 00:34:15,240 Speaker 17: Technology that could change their lives, whether it was AI 676 00:34:15,760 --> 00:34:19,520 Speaker 17: or healthcare. There was a lot of pharma and diagnostic 677 00:34:19,560 --> 00:34:23,160 Speaker 17: tests being promoted that all did well, and or you 678 00:34:23,200 --> 00:34:25,640 Speaker 17: saw people going back to the to the triad and 679 00:34:25,680 --> 00:34:29,240 Speaker 17: true nostalgia, heartwarming, celebrity driven pieces. 680 00:34:29,480 --> 00:34:30,840 Speaker 8: Those were the things that worked. 681 00:34:32,440 --> 00:34:34,960 Speaker 2: What's so interesting about The technology piece of this is 682 00:34:35,600 --> 00:34:38,480 Speaker 2: what was being advertised, right, So there's a lot on 683 00:34:38,520 --> 00:34:40,839 Speaker 2: social media about the who's who of tech being in 684 00:34:40,840 --> 00:34:43,840 Speaker 2: attendance of the Super Bowl or talking up their own ads, 685 00:34:44,280 --> 00:34:46,680 Speaker 2: and there were also some fake ads. But my main 686 00:34:46,719 --> 00:34:50,200 Speaker 2: point coming these are like enterprise facing things B to 687 00:34:50,320 --> 00:34:54,040 Speaker 2: B when you measure the engagement or outcomes, like, how 688 00:34:54,040 --> 00:34:57,520 Speaker 2: can we gauge if these were successful pieces of business 689 00:34:57,880 --> 00:34:59,960 Speaker 2: at the enterprise level that those companies put in play. 690 00:35:00,640 --> 00:35:03,520 Speaker 17: Yeah, so what we're measuring a EDOS, We're looking at 691 00:35:03,600 --> 00:35:06,000 Speaker 17: how many people searched for the brand, went to the 692 00:35:06,000 --> 00:35:08,640 Speaker 17: brand's website, used the brand's app in the minutes following 693 00:35:09,040 --> 00:35:12,239 Speaker 17: these ads on TV, and it's highly predictive of very 694 00:35:12,239 --> 00:35:17,040 Speaker 17: correlated with changes in market share, changes in sales enterprise. 695 00:35:17,280 --> 00:35:18,880 Speaker 8: It's an interesting way to market. 696 00:35:19,280 --> 00:35:21,640 Speaker 17: You've got to find needles and haystacks, but this is 697 00:35:21,719 --> 00:35:25,440 Speaker 17: by far the world's biggest haystack. It's the most engaged 698 00:35:25,480 --> 00:35:28,320 Speaker 17: audience you can find. You couldn't replicate this kind of 699 00:35:28,400 --> 00:35:32,840 Speaker 17: audience through targeted digital advertising over a month or many months, 700 00:35:33,560 --> 00:35:35,520 Speaker 17: even if you spent tens of millions of dollars like 701 00:35:35,560 --> 00:35:39,480 Speaker 17: it costs to advertising the Super Bowl. So for those 702 00:35:39,520 --> 00:35:41,920 Speaker 17: folks with an enterprise message, it's still one of the 703 00:35:42,000 --> 00:35:45,919 Speaker 17: best ways, most cost efficient ways, ironically to reach those 704 00:35:46,000 --> 00:35:48,799 Speaker 17: kinds of high end audiences, and the game being, as 705 00:35:48,800 --> 00:35:50,919 Speaker 17: you mentioned in the Bay Area in the home of Tech, 706 00:35:51,560 --> 00:35:52,280 Speaker 17: that much better. 707 00:35:53,520 --> 00:35:57,840 Speaker 2: Kevin, Ai was big, right, but so is Farma big Farma. 708 00:35:58,080 --> 00:36:00,280 Speaker 2: You know, as I sat on my couch well wishing 709 00:36:00,320 --> 00:36:02,200 Speaker 2: that something that struck me, what's the data behind that? 710 00:36:02,280 --> 00:36:02,560 Speaker 8: Please? 711 00:36:03,760 --> 00:36:06,800 Speaker 17: It mattered a lot to the people watching to see 712 00:36:07,520 --> 00:36:10,680 Speaker 17: Nova Noordisk promoting its will go v pill. That was 713 00:36:10,680 --> 00:36:14,320 Speaker 17: one of our top twenty most engaging ads of the game, 714 00:36:14,880 --> 00:36:19,520 Speaker 17: a very big performance for a pharmaceutical brand. You also 715 00:36:19,520 --> 00:36:22,400 Speaker 17: had Hymns and Hers with an edgier message late in 716 00:36:22,440 --> 00:36:25,920 Speaker 17: the game, which was a challenging placement overall, given that 717 00:36:25,960 --> 00:36:28,399 Speaker 17: the game wasn't that competitive at that point, and yet 718 00:36:28,440 --> 00:36:32,399 Speaker 17: Hymns and Hers performed very well and was also one 719 00:36:32,440 --> 00:36:35,400 Speaker 17: of our top twenty most performant ads in the game. 720 00:36:35,760 --> 00:36:40,360 Speaker 17: Obviously they're both in the news today with noven Ardisks 721 00:36:40,440 --> 00:36:41,960 Speaker 17: suing Hymns and Hers. 722 00:36:42,360 --> 00:36:44,839 Speaker 3: It's a hard one, Kevin, But your IDEO is all 723 00:36:44,880 --> 00:36:49,200 Speaker 3: about TV advertising. How much do we think actually is 724 00:36:49,239 --> 00:36:51,680 Speaker 3: just driven onto online. In these moments, you hear that. 725 00:36:51,680 --> 00:36:53,840 Speaker 4: Maybe someone caught an ad and you then go and 726 00:36:53,840 --> 00:36:54,840 Speaker 4: look at it on YouTube. 727 00:36:54,840 --> 00:36:57,560 Speaker 3: How are we being distinct about where they put their 728 00:36:57,560 --> 00:36:58,400 Speaker 3: money to work? 729 00:36:58,560 --> 00:36:58,759 Speaker 8: Right? 730 00:36:58,840 --> 00:37:01,160 Speaker 17: Well, what we're seeing is that the twenty first century 731 00:37:01,160 --> 00:37:04,280 Speaker 17: consumer lives their lives online and so whether they're watching 732 00:37:04,320 --> 00:37:09,120 Speaker 17: traditional TV or streaming television or social video, it triggers 733 00:37:09,160 --> 00:37:12,080 Speaker 17: these online digital behaviors. That is the customer journey in 734 00:37:12,120 --> 00:37:15,240 Speaker 17: the twenty first century. And so by picking up these signals, 735 00:37:15,239 --> 00:37:17,279 Speaker 17: you're able to really predict what's going to happen in 736 00:37:17,280 --> 00:37:21,000 Speaker 17: your business going forward. Now, should marketers be spending more 737 00:37:21,080 --> 00:37:26,320 Speaker 17: or less in TV or social video or other media? 738 00:37:26,400 --> 00:37:29,360 Speaker 17: I mean that is why companies like ours exist is 739 00:37:29,360 --> 00:37:32,640 Speaker 17: to help them find that right balance, the right marketers. 740 00:37:32,640 --> 00:37:35,759 Speaker 17: Though they know that there's moments to get a big 741 00:37:35,800 --> 00:37:38,200 Speaker 17: audience highly engaged, like the super Bowl, and then there's 742 00:37:38,239 --> 00:37:40,920 Speaker 17: moments to go with hyper targeting, and the right balance 743 00:37:40,960 --> 00:37:42,960 Speaker 17: typically is what we see does the best. 744 00:37:43,239 --> 00:37:46,240 Speaker 3: But they also know probably and why we see nostalgia, 745 00:37:46,239 --> 00:37:49,600 Speaker 3: where we see Ben Affleck, where we see the idea 746 00:37:49,680 --> 00:37:53,120 Speaker 3: of gen X millennial viewers, is that basically what the 747 00:37:53,160 --> 00:37:55,600 Speaker 3: Super Bowl is, it's targeting like the forty year olds 748 00:37:55,680 --> 00:37:56,120 Speaker 3: or something. 749 00:37:57,120 --> 00:37:59,880 Speaker 17: What it really shows is that boomers they're out of 750 00:37:59,920 --> 00:38:03,120 Speaker 17: the sweet spot of economic power. It's gen xers and 751 00:38:03,239 --> 00:38:07,200 Speaker 17: gen y, you know, those kind of younger gen xers 752 00:38:07,280 --> 00:38:11,239 Speaker 17: like me, the aging millennials who are right behind me. 753 00:38:11,800 --> 00:38:14,240 Speaker 17: We're in the sweet spot of economic power, and marketers 754 00:38:14,280 --> 00:38:16,759 Speaker 17: know that, and so they're talking to us. The nostalgia 755 00:38:16,840 --> 00:38:19,359 Speaker 17: that was quite effective in this game. It was all 756 00:38:19,400 --> 00:38:24,040 Speaker 17: about late eighties to early two thousands, the Backstreet Boys. 757 00:38:24,120 --> 00:38:27,160 Speaker 17: Twice you had that kind of effect. We had bon 758 00:38:27,280 --> 00:38:30,800 Speaker 17: Jovi several times. Green Day kicked off the game. It 759 00:38:30,960 --> 00:38:32,520 Speaker 17: was targeted at us. 760 00:38:33,800 --> 00:38:35,279 Speaker 2: The one thing that a lot of people struggle on 761 00:38:35,360 --> 00:38:37,719 Speaker 2: stand is with some of the bigger ads from some 762 00:38:37,719 --> 00:38:40,040 Speaker 2: of the bigger technology companies. A lot of them were 763 00:38:40,200 --> 00:38:43,160 Speaker 2: released in advance of the Super Bowl, right they're posted 764 00:38:43,239 --> 00:38:46,040 Speaker 2: wherever they're posted. What's the strategy behind that. 765 00:38:47,280 --> 00:38:49,640 Speaker 17: There's a lot of debate about what the right release 766 00:38:49,719 --> 00:38:53,480 Speaker 17: strategy is. We find that any one of them can work, 767 00:38:53,520 --> 00:38:56,120 Speaker 17: but surprises tend to do the best. If you're introducing 768 00:38:56,120 --> 00:39:00,359 Speaker 17: a new product teases of a fun idea where you're 769 00:39:00,360 --> 00:39:02,960 Speaker 17: building on the idea on social but leading to a 770 00:39:03,000 --> 00:39:05,239 Speaker 17: real unveil on at the super Bowl. 771 00:39:05,320 --> 00:39:06,560 Speaker 8: That's also quite effective. 772 00:39:07,560 --> 00:39:11,080 Speaker 17: Less effective is just put it all out there a 773 00:39:11,120 --> 00:39:14,320 Speaker 17: week ahead of time and then expect a part of 774 00:39:14,360 --> 00:39:14,879 Speaker 17: the Super Bowl. 775 00:39:15,239 --> 00:39:16,960 Speaker 8: It tends to not work as well that way. 776 00:39:18,520 --> 00:39:22,520 Speaker 2: Kevin Krim, CEO of Edo, and a long time ago, also, 777 00:39:22,560 --> 00:39:25,400 Speaker 2: i should say, was global head of Digital at Bloomberg. 778 00:39:25,719 --> 00:39:26,640 Speaker 7: Thank you very much. 779 00:39:26,680 --> 00:39:30,440 Speaker 2: Now coming up, Workday's co founder comes back for the 780 00:39:30,480 --> 00:39:34,160 Speaker 2: top job at the company. Effective immediately. We'll have that 781 00:39:34,200 --> 00:39:36,640 Speaker 2: surprise news next. This is Bloomberg Tech. 782 00:39:44,160 --> 00:39:45,200 Speaker 4: Time now for talking tech. 783 00:39:45,239 --> 00:39:48,040 Speaker 3: First up, Meta is facing a warning from the EU. Now, 784 00:39:48,040 --> 00:39:50,400 Speaker 3: a social media giant is under scrutiny of a policies 785 00:39:50,440 --> 00:39:52,680 Speaker 3: that restrict the use of rival AI. 786 00:39:52,440 --> 00:39:53,480 Speaker 4: Assistance on WhatsApp. 787 00:39:53,719 --> 00:39:56,400 Speaker 3: Now, the European Commission has issued a statement of objections, 788 00:39:56,640 --> 00:39:59,200 Speaker 3: cautioning that it may step in to prevent when it 789 00:39:59,280 --> 00:40:03,000 Speaker 3: described as serious and irreparable harm to the market. Now 790 00:40:03,000 --> 00:40:05,720 Speaker 3: Bluebogs Francy Lacqua sat down with the European Commission Executive 791 00:40:05,760 --> 00:40:07,320 Speaker 3: VP Teresa Ribera. 792 00:40:07,080 --> 00:40:11,640 Speaker 18: Particularsen I don't know how it may be read by 793 00:40:11,760 --> 00:40:14,360 Speaker 18: any government, but my sense is that this is not 794 00:40:14,560 --> 00:40:19,799 Speaker 18: connected to politics, but connected to well functioning markets. 795 00:40:19,840 --> 00:40:22,760 Speaker 4: And the protection of consumers plus. 796 00:40:22,800 --> 00:40:26,480 Speaker 3: Former Apple design chief Johnny I is unveiled a car 797 00:40:26,760 --> 00:40:31,040 Speaker 3: CO designed with Ferrari called the Ferrari Lucee. It features 798 00:40:31,200 --> 00:40:35,800 Speaker 3: tactile switches, physical controls, aluminium details and steering will and events. 799 00:40:35,920 --> 00:40:38,200 Speaker 4: Now the design is deliberately moving. 800 00:40:37,920 --> 00:40:40,840 Speaker 3: Away from a screen heavy aesthetic, embracing what I've described 801 00:40:40,920 --> 00:40:44,680 Speaker 3: as a more physical world approach and byte dance while 802 00:40:44,680 --> 00:40:47,000 Speaker 3: it's turning heads with this latest AI video model, The 803 00:40:47,040 --> 00:40:50,120 Speaker 3: TikTok Parent just rolled out seed Dance two point zero 804 00:40:50,239 --> 00:40:52,560 Speaker 3: and the quality of the clips has surprised both analysts 805 00:40:52,600 --> 00:40:55,520 Speaker 3: and industry watchers. Now the launch has generated plenty of 806 00:40:55,600 --> 00:40:58,439 Speaker 3: us and help lift shares across China's media and AI 807 00:40:58,520 --> 00:40:59,040 Speaker 3: app space. 808 00:40:59,440 --> 00:41:04,040 Speaker 2: Ed Okay, some news. Workday co founder and current executive 809 00:41:04,080 --> 00:41:07,880 Speaker 2: chair and Neil Bursrie is returning as CEO. He's replacing 810 00:41:08,080 --> 00:41:12,040 Speaker 2: Carl Eschenbach, with the change effective immediately. The news comes 811 00:41:12,080 --> 00:41:15,520 Speaker 2: just days after work Cup. Workday announced it's cutting about 812 00:41:15,520 --> 00:41:18,839 Speaker 2: four hundred jobs. Who's across it, Bloomberg's Brady Ford. It's 813 00:41:18,840 --> 00:41:22,000 Speaker 2: the Monday after the Super Bowl. The phone rings five am. 814 00:41:22,160 --> 00:41:24,320 Speaker 2: The editor is saying, Brody, get to your desk. 815 00:41:24,440 --> 00:41:24,960 Speaker 5: Workday. 816 00:41:26,440 --> 00:41:27,160 Speaker 4: What do we need to know? 817 00:41:27,200 --> 00:41:29,200 Speaker 2: I mean, this is a stock that's reacting negatively to 818 00:41:29,239 --> 00:41:30,359 Speaker 2: the news, but has been on. 819 00:41:30,320 --> 00:41:32,279 Speaker 7: A slide for some months out. 820 00:41:32,719 --> 00:41:33,319 Speaker 5: You need to know. 821 00:41:33,400 --> 00:41:37,319 Speaker 19: It's a really tough time to be an application software company, right. 822 00:41:37,400 --> 00:41:40,520 Speaker 19: I mean, whether you're a Salesforce or Adobe or Workday, 823 00:41:40,640 --> 00:41:42,759 Speaker 19: you can put up pretty good numbers, you can say 824 00:41:42,800 --> 00:41:44,920 Speaker 19: that a lot of people are using your AI tools, 825 00:41:44,960 --> 00:41:47,239 Speaker 19: But right now Wall Street is just not going to 826 00:41:47,280 --> 00:41:50,120 Speaker 19: believe you. And that's what's been happening with Workday. I mean, 827 00:41:50,120 --> 00:41:52,759 Speaker 19: they're down forty percent over the last year before this 828 00:41:52,920 --> 00:41:56,080 Speaker 19: event today, and it seemed they said, we need the 829 00:41:56,200 --> 00:41:59,000 Speaker 19: show and we need to make a step toward a 830 00:41:59,040 --> 00:42:02,560 Speaker 19: more product folks company. Maybe the last guy who we 831 00:42:02,640 --> 00:42:04,600 Speaker 19: thought was going to lead us to a new era 832 00:42:04,920 --> 00:42:07,399 Speaker 19: was seen as to sales. We need somebody who's really 833 00:42:07,400 --> 00:42:09,400 Speaker 19: going to focus on that AI R and D. 834 00:42:10,000 --> 00:42:11,880 Speaker 3: And so is it right to go back to the 835 00:42:11,880 --> 00:42:14,080 Speaker 3: co founder Brody? How does the market interpret that? 836 00:42:15,640 --> 00:42:17,640 Speaker 19: I think no matter who they've picked right now, the 837 00:42:17,760 --> 00:42:20,640 Speaker 19: market wouldn't have loved it right now. I think if 838 00:42:20,680 --> 00:42:24,960 Speaker 19: you do anything that's not exceptionally and unambiguously positive, the 839 00:42:25,000 --> 00:42:29,200 Speaker 19: market wants to sell application software stocks, right, I mean 840 00:42:29,200 --> 00:42:33,360 Speaker 19: the founder's a familiar face. I have seen some questions 841 00:42:33,400 --> 00:42:35,400 Speaker 19: around if you want to lead a company into a 842 00:42:35,440 --> 00:42:37,319 Speaker 19: new AI era, do you want to go back to 843 00:42:37,360 --> 00:42:41,799 Speaker 19: the same person. There's arguments both ways, but clearly investors 844 00:42:41,840 --> 00:42:42,640 Speaker 19: are not stoked. 845 00:42:43,239 --> 00:42:46,040 Speaker 2: The stock trading at its lowest level since November twenty 846 00:42:46,080 --> 00:42:49,040 Speaker 2: twenty two. Quite quite rightly, I'm going to ask you 847 00:42:49,080 --> 00:42:50,960 Speaker 2: what is workday and what does it do? 848 00:42:51,960 --> 00:42:52,160 Speaker 5: Right? 849 00:42:52,200 --> 00:42:54,960 Speaker 19: Well, when you look up your benefits for you know, 850 00:42:55,120 --> 00:42:58,640 Speaker 19: healthcare or vision, you're probably logging into a workday system 851 00:42:58,719 --> 00:43:03,040 Speaker 19: no matter what company you want. So their core application 852 00:43:03,239 --> 00:43:06,239 Speaker 19: is for human resource management, but of course, like everybody else, 853 00:43:06,280 --> 00:43:08,840 Speaker 19: they want to expand in the agents and other parts 854 00:43:08,840 --> 00:43:09,840 Speaker 19: of the software stack. 855 00:43:10,360 --> 00:43:12,799 Speaker 3: And we also know who's expanding into agents and the 856 00:43:12,880 --> 00:43:13,640 Speaker 3: enterprise area. 857 00:43:14,120 --> 00:43:17,839 Speaker 4: Pretty forward. Thank you so much. That does it from 858 00:43:17,840 --> 00:43:20,399 Speaker 4: this edition at Bloomberg Tech. And we've got a big 859 00:43:20,400 --> 00:43:20,960 Speaker 4: week ahead. 860 00:43:21,040 --> 00:43:23,120 Speaker 3: There's yet more earnings, think of fast but the bond 861 00:43:23,200 --> 00:43:25,160 Speaker 3: sales they're going to come to and we did it 862 00:43:25,200 --> 00:43:25,680 Speaker 3: all today. 863 00:43:26,440 --> 00:43:29,000 Speaker 2: Yeah, like big tech has looked to debt to fund 864 00:43:29,120 --> 00:43:32,040 Speaker 2: Capex and is Robert Schiffman outlined and recap it on 865 00:43:32,080 --> 00:43:34,840 Speaker 2: the podcast. It was a good conversation. You know, that's okay. 866 00:43:35,040 --> 00:43:39,040 Speaker 2: It's a good way of managing capital for them. Do 867 00:43:39,120 --> 00:43:40,799 Speaker 2: recap the podcast. You know where to find it. It's 868 00:43:40,840 --> 00:43:43,600 Speaker 2: on the Bloomberg terminal, it's online, it's on Apple, Spotify, 869 00:43:43,640 --> 00:43:46,600 Speaker 2: and iHeart from San Francisco and from New York. 870 00:43:46,880 --> 00:43:47,919 Speaker 5: This is Bloomberg Tech