1 00:00:02,520 --> 00:00:10,480 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. This is Bloomberg business 2 00:00:10,480 --> 00:00:14,400 Speaker 1: Week Daily reporting from the magazine that helps global leaders 3 00:00:14,400 --> 00:00:18,280 Speaker 1: stay ahead with insight on the people, companies, and trends 4 00:00:18,360 --> 00:00:23,360 Speaker 1: shaping today's complex economy. Plus global business finance and tech 5 00:00:23,440 --> 00:00:27,240 Speaker 1: news as it happens. The Bloomberg Business Week Daily Podcast 6 00:00:27,640 --> 00:00:31,720 Speaker 1: with Carol Masser and Tim Stenebeck on Bloomberg Radio. 7 00:00:32,240 --> 00:00:34,120 Speaker 2: On the call this morning, Carol, you drew our attention 8 00:00:34,240 --> 00:00:37,720 Speaker 2: to this story Jim Chanos criticizing the company for effectively 9 00:00:37,760 --> 00:00:40,080 Speaker 2: bankrolling quote, roughly two thirds of the cost of its 10 00:00:40,120 --> 00:00:43,520 Speaker 2: own hardware sales in a reported aideal. This is Jim 11 00:00:43,600 --> 00:00:45,040 Speaker 2: Chanos's criticism. 12 00:00:44,720 --> 00:00:46,720 Speaker 3: Correction note, But to be fair, we see it play 13 00:00:46,720 --> 00:00:48,400 Speaker 3: out in the trade off and of investors getting a 14 00:00:48,400 --> 00:00:51,720 Speaker 3: little bit more nervous about these very closely connected companies 15 00:00:51,760 --> 00:00:55,320 Speaker 3: that are basically doing investments, and some of that investment's 16 00:00:55,400 --> 00:00:58,760 Speaker 3: going to be buying something that they make, like the chips. 17 00:00:59,480 --> 00:01:01,639 Speaker 3: So let's see what Robert Schiffman has to say. He's 18 00:01:01,640 --> 00:01:03,120 Speaker 3: been in the hot seat, he's been following all of this. 19 00:01:03,120 --> 00:01:06,520 Speaker 3: He's Bloomberg Intelligence senior technology credit analyst. He joins us 20 00:01:06,520 --> 00:01:09,840 Speaker 3: here in the Bloomberg BusinessWeek Studio. The longer this goes on, 21 00:01:11,319 --> 00:01:13,520 Speaker 3: do you get more nervous or do you feel like, Okay, 22 00:01:13,600 --> 00:01:15,960 Speaker 3: this is all making sense though, because we do see 23 00:01:15,959 --> 00:01:16,880 Speaker 3: the demand that's real. 24 00:01:17,240 --> 00:01:20,000 Speaker 4: Yeah, I don't get nervous. I'm pretty confident in my 25 00:01:20,040 --> 00:01:22,880 Speaker 4: bullish views. I'd love to be the voice of reason 26 00:01:22,920 --> 00:01:25,920 Speaker 4: at least for thirty seconds. Okay, if you take a 27 00:01:25,959 --> 00:01:28,000 Speaker 4: step back. So in video is in the news today 28 00:01:28,160 --> 00:01:31,400 Speaker 4: most read article the sky is falling. But what has 29 00:01:31,480 --> 00:01:34,520 Speaker 4: Nvidia done over the last five years? It's stock. I'm 30 00:01:34,520 --> 00:01:37,680 Speaker 4: a credit guy. It stock is up one thousand percent. 31 00:01:38,000 --> 00:01:40,199 Speaker 4: Its stock is still up five percent year to date. 32 00:01:40,600 --> 00:01:42,720 Speaker 4: S and P's up six to seven percent, NASCX up 33 00:01:42,760 --> 00:01:46,160 Speaker 4: six or seven percent. We don't go up every single 34 00:01:46,280 --> 00:01:49,520 Speaker 4: day in equity markets. We don't go tighter every single 35 00:01:49,560 --> 00:01:51,880 Speaker 4: day in credit markets. So we're going to be a 36 00:01:51,920 --> 00:01:54,440 Speaker 4: little bit bouncy. But that being said, what gives me 37 00:01:54,480 --> 00:01:58,640 Speaker 4: my bullish viewpoint is, quite frankly, the fundamentals. The evidence 38 00:01:58,800 --> 00:02:02,240 Speaker 4: that growth is and it's only getting bigger and better 39 00:02:02,440 --> 00:02:05,320 Speaker 4: and it's going to stay hasn't gone away. And the 40 00:02:05,360 --> 00:02:08,680 Speaker 4: evidence is it's only getting bigger and better. Now from 41 00:02:08,720 --> 00:02:11,400 Speaker 4: the credit markets. It scares people a little bit because 42 00:02:11,440 --> 00:02:13,320 Speaker 4: you have to finance it. You know, you've got to 43 00:02:13,320 --> 00:02:15,560 Speaker 4: do that, put in the work, the time, the effort, 44 00:02:15,600 --> 00:02:17,520 Speaker 4: and the money up front, and you don't see it 45 00:02:17,560 --> 00:02:18,239 Speaker 4: for a few years. 46 00:02:18,360 --> 00:02:21,080 Speaker 2: Yeah, hello Alphabet, last week cash flow negative. 47 00:02:21,240 --> 00:02:23,840 Speaker 4: Yeah, you know, I would argue listen, I said this 48 00:02:23,960 --> 00:02:26,640 Speaker 4: with you guys just three months ago when then video reported, 49 00:02:26,760 --> 00:02:28,480 Speaker 4: I thought it was the best print potentially in the 50 00:02:28,520 --> 00:02:30,800 Speaker 4: history of the stock market. And the stock was down. 51 00:02:30,840 --> 00:02:34,320 Speaker 4: Alphabet's numbers were enormous. Right, you've heard it time. You've 52 00:02:34,320 --> 00:02:36,880 Speaker 4: heard so many people take say the story again today. 53 00:02:36,880 --> 00:02:39,480 Speaker 4: You know, cloud Ai growth was eighty two percent in 54 00:02:39,480 --> 00:02:41,800 Speaker 4: the quarter, but they boosted cap x again by another 55 00:02:41,840 --> 00:02:44,760 Speaker 4: ten or fifteen billion dollars. So the world starts to 56 00:02:44,800 --> 00:02:46,959 Speaker 4: freak out that they can't afford it, that there's not 57 00:02:47,000 --> 00:02:49,440 Speaker 4: going to be enough money to lend to these guys. 58 00:02:49,760 --> 00:02:52,200 Speaker 4: The cost of capital is getting way too high, and 59 00:02:52,240 --> 00:02:54,919 Speaker 4: this guy is falling, and quite frankly, it just isn't. 60 00:02:56,680 --> 00:02:58,680 Speaker 3: But as some of these companies, we've always talked about 61 00:02:58,680 --> 00:03:00,160 Speaker 3: their balance sheet and how much cash is on their 62 00:03:00,200 --> 00:03:02,560 Speaker 3: balance sheet, and it feels like things are shifting. Is 63 00:03:02,560 --> 00:03:05,200 Speaker 3: that a worrisome. Should we be concerned. 64 00:03:04,800 --> 00:03:07,000 Speaker 4: About that, Well, we should be worried that. 65 00:03:07,200 --> 00:03:09,800 Speaker 3: Means less buybacks and things that investors have enjoined. But 66 00:03:10,200 --> 00:03:11,639 Speaker 3: I would push that aside. 67 00:03:11,760 --> 00:03:14,960 Speaker 4: The technicals in the market have clearly gotten weaker. So 68 00:03:15,639 --> 00:03:17,960 Speaker 4: if we just also take a step back and think 69 00:03:17,960 --> 00:03:21,480 Speaker 4: about how trading desk, corporate bond trading desk work today 70 00:03:21,560 --> 00:03:23,360 Speaker 4: versus how they worked five or seven years ago. Is 71 00:03:23,360 --> 00:03:27,320 Speaker 4: that desks used to take risk. So when you had sellers, 72 00:03:27,639 --> 00:03:31,000 Speaker 4: you actually had the banks buying back their deals, sitting 73 00:03:31,080 --> 00:03:34,120 Speaker 4: on maybe tens hundreds of billions of dollars of bonds 74 00:03:34,600 --> 00:03:39,360 Speaker 4: and helping reduce volatility in spreads. Nowadays, no bank takes 75 00:03:39,440 --> 00:03:42,560 Speaker 4: risk anymore. So when you have sellers come out, you 76 00:03:42,640 --> 00:03:45,640 Speaker 4: see exaggerated spread movements. On top of that, when you 77 00:03:45,680 --> 00:03:48,280 Speaker 4: see deal after deal after deal, and we've heard it, 78 00:03:48,320 --> 00:03:52,280 Speaker 4: there's fatigue when there's long dated BONDI after long dated 79 00:03:52,320 --> 00:03:54,000 Speaker 4: bond deal and we think that's going to happen again 80 00:03:54,520 --> 00:03:57,680 Speaker 4: next year. Just the cost of having to do business 81 00:03:57,840 --> 00:04:01,200 Speaker 4: is going to go up. If you're selling something today 82 00:04:01,520 --> 00:04:04,120 Speaker 4: and you're going to sell another one hundred of those tomorrow, 83 00:04:04,200 --> 00:04:06,320 Speaker 4: the cost is going to change. So the costs are 84 00:04:06,360 --> 00:04:09,000 Speaker 4: going up, but if you think about cash, there's a 85 00:04:09,040 --> 00:04:13,120 Speaker 4: lot of cash that's sitting around still. Look at Alphabet's 86 00:04:13,160 --> 00:04:16,960 Speaker 4: balance sheet. They have two hundred and forty billion dollars 87 00:04:17,000 --> 00:04:19,000 Speaker 4: of cash on the books and they still have another 88 00:04:19,120 --> 00:04:21,360 Speaker 4: thirty or forty odd of equity to issue that they 89 00:04:21,400 --> 00:04:24,600 Speaker 4: haven't issued yet, so they have effectively pre funded themselves. 90 00:04:24,640 --> 00:04:26,559 Speaker 4: I think for a couple of years. They're just taking 91 00:04:26,560 --> 00:04:30,520 Speaker 4: advantage of there's still a bid for corporate bonds these days, 92 00:04:30,839 --> 00:04:33,240 Speaker 4: albeit at a higher costs. And the other cash and 93 00:04:34,160 --> 00:04:36,760 Speaker 4: is just in Video. Why is in Vidia? You know how? 94 00:04:36,920 --> 00:04:38,760 Speaker 4: You know they're the rich uncle that comes to the 95 00:04:38,760 --> 00:04:41,840 Speaker 4: house and is dolling out twenty one hundred dollars bills. 96 00:04:41,960 --> 00:04:43,919 Speaker 4: You know, is that necessarily a bad thing? Take a 97 00:04:43,960 --> 00:04:46,600 Speaker 4: look at the FA screen on the terminal. The market 98 00:04:46,640 --> 00:04:49,320 Speaker 4: believes in Video is going to generate two hundred billion 99 00:04:49,360 --> 00:04:52,040 Speaker 4: dollars of free cash next year. So it's a little 100 00:04:52,040 --> 00:04:54,479 Speaker 4: bit I don't want to say Robinhood, but it's it's 101 00:04:54,520 --> 00:04:57,440 Speaker 4: the rich giving money to the wealthy right now. So 102 00:04:57,480 --> 00:04:59,920 Speaker 4: it's just a sort of a temporary shift in ask. 103 00:05:00,360 --> 00:05:03,600 Speaker 2: I know we're talking credit here, but I want to 104 00:05:03,920 --> 00:05:06,200 Speaker 2: broach something that we broch with that Vodlo a little earlier, 105 00:05:06,200 --> 00:05:08,760 Speaker 2: and that's that's sort of like the the end game 106 00:05:08,800 --> 00:05:12,040 Speaker 2: here when it comes to these companies in this world 107 00:05:12,080 --> 00:05:14,840 Speaker 2: that they're trying to create. From where you're sitting on 108 00:05:14,880 --> 00:05:18,039 Speaker 2: the credit side, just what does the world look like 109 00:05:18,760 --> 00:05:21,880 Speaker 2: if these investments work out? Like, what are we doing differently? 110 00:05:22,240 --> 00:05:24,760 Speaker 2: How are we getting to work differently? Are we working 111 00:05:24,760 --> 00:05:27,240 Speaker 2: four days a week because we're so productive? Like what 112 00:05:27,279 --> 00:05:30,000 Speaker 2: are the promises that have to play out in order 113 00:05:30,000 --> 00:05:32,280 Speaker 2: for this invest these investments to be successful. 114 00:05:32,320 --> 00:05:34,080 Speaker 4: Well, b I credit works seven days a week. I 115 00:05:34,080 --> 00:05:35,279 Speaker 4: don't see that that changing. 116 00:05:35,920 --> 00:05:38,279 Speaker 2: So wait until we have twenty four seven trading. 117 00:05:38,320 --> 00:05:41,599 Speaker 4: Financially, what does it look like. I think it looks 118 00:05:41,680 --> 00:05:46,919 Speaker 4: like where we were three years ago when the hyperscalers 119 00:05:47,000 --> 00:05:51,120 Speaker 4: which were previously you know, mag seven I had a 120 00:05:51,160 --> 00:05:55,239 Speaker 4: lot of other different names. We're just generating so much cash, 121 00:05:55,400 --> 00:05:57,520 Speaker 4: they just were buying back tons and tons of stock. 122 00:05:57,600 --> 00:05:59,360 Speaker 4: I actually think we're going to get to that point 123 00:05:59,400 --> 00:06:01,800 Speaker 4: again where they're going to be in Nvidia, like where 124 00:06:01,839 --> 00:06:03,960 Speaker 4: there's going to be so much excess cash flow they're 125 00:06:03,960 --> 00:06:06,360 Speaker 4: going to have nothing to do with it but buybackstock. Now, 126 00:06:06,400 --> 00:06:09,760 Speaker 4: I don't think that inflection point starts probably until late 127 00:06:09,800 --> 00:06:12,160 Speaker 4: twenty twenty eight or twenty twenty nine. When you think 128 00:06:12,200 --> 00:06:15,159 Speaker 4: about the world that we live in, clearly listen, that's 129 00:06:15,160 --> 00:06:17,480 Speaker 4: going to change. All of our jobs are going to change, 130 00:06:18,160 --> 00:06:20,440 Speaker 4: and some for the better, some for the worse. Like 131 00:06:20,800 --> 00:06:23,839 Speaker 4: everything that we do at Bloomberg is changing. Now. We're 132 00:06:23,920 --> 00:06:28,160 Speaker 4: utilizing ask B, we're utilizing automated research, and it's not 133 00:06:28,200 --> 00:06:31,040 Speaker 4: to replace analysts. It's to make us better and more efficient. 134 00:06:31,279 --> 00:06:32,719 Speaker 4: And I think that's what's going to happen with the 135 00:06:32,720 --> 00:06:34,320 Speaker 4: rest of the world, is everyone's going to get better 136 00:06:34,360 --> 00:06:36,400 Speaker 4: and more efficient. But some of the moves we're seeing 137 00:06:36,400 --> 00:06:39,719 Speaker 4: today are exaggerated. There's other names like IBM, for instance, 138 00:06:40,240 --> 00:06:44,280 Speaker 4: they fell twenty five percent after earnings and when they 139 00:06:44,360 --> 00:06:47,720 Speaker 4: actually guided preliminarily, we didn't know what they were going 140 00:06:47,760 --> 00:06:51,080 Speaker 4: to come out with full guidance. The guidance prior was 141 00:06:51,160 --> 00:06:53,400 Speaker 4: revenue growth of over five percent. Then they guided to 142 00:06:53,480 --> 00:06:55,880 Speaker 4: four to five percent revenue growth without a change in 143 00:06:55,920 --> 00:06:58,559 Speaker 4: free cash flow. You know, is that company worth twenty 144 00:06:58,560 --> 00:07:01,040 Speaker 4: five percent less? I'm not an inequity and so I'll 145 00:07:01,040 --> 00:07:03,680 Speaker 4: tell you from the credit standpoint, spread shouldn't be very 146 00:07:03,760 --> 00:07:04,599 Speaker 4: much wider and they're not. 147 00:07:05,720 --> 00:07:08,400 Speaker 3: You know, it's interesting kind of related, I guess if 148 00:07:08,440 --> 00:07:10,640 Speaker 3: you will. But there's a story on the Bloomberg today 149 00:07:10,680 --> 00:07:14,280 Speaker 3: about Morgan Stanley saying AI adopter set for solid profit margins. 150 00:07:14,280 --> 00:07:17,360 Speaker 3: So they say, use companies that are integrating AI capabilities 151 00:07:17,440 --> 00:07:19,200 Speaker 3: or pois for stronger profit margins. 152 00:07:18,960 --> 00:07:21,960 Speaker 2: Because we're becoming more productive or because they're replacing people. 153 00:07:22,880 --> 00:07:25,600 Speaker 3: Mike Wilson and his team said margining expectations are improving 154 00:07:25,600 --> 00:07:27,560 Speaker 3: most clearly for companies where AI is central to their 155 00:07:27,560 --> 00:07:31,160 Speaker 3: investment thesis and pricing power is neutral to strung you know. 156 00:07:32,440 --> 00:07:34,640 Speaker 3: So you know, I guess this is where when we 157 00:07:34,680 --> 00:07:36,680 Speaker 3: go through the earning season to find out exactly what 158 00:07:36,720 --> 00:07:39,040 Speaker 3: folks are doing, think about everybody we bring on, and 159 00:07:39,120 --> 00:07:41,960 Speaker 3: we ask them, like CEOs or even like investment folk, 160 00:07:42,040 --> 00:07:44,360 Speaker 3: like are you using it? Everybody seems to be using it. 161 00:07:44,480 --> 00:07:46,560 Speaker 3: There is a point though, where people are starting to say, 162 00:07:46,880 --> 00:07:48,840 Speaker 3: do we need all the models? Do we need all 163 00:07:48,880 --> 00:07:51,280 Speaker 3: the expensive models? Just everybody need to us that. 164 00:07:51,360 --> 00:07:53,280 Speaker 2: Too much for the right reasons, Like are we spending 165 00:07:53,280 --> 00:07:54,160 Speaker 2: too much in tokens? 166 00:07:54,320 --> 00:07:54,600 Speaker 1: Yeah? 167 00:07:54,760 --> 00:07:56,960 Speaker 4: Like I don't think we are. I think the real 168 00:07:57,040 --> 00:08:00,480 Speaker 4: question is are we spending too much money on something 169 00:08:00,520 --> 00:08:03,440 Speaker 4: today that we can spend half as much on tomorrow. 170 00:08:03,720 --> 00:08:06,280 Speaker 4: That's the real fear is that China comes in and 171 00:08:06,400 --> 00:08:11,200 Speaker 4: just creates a better, cheaper mousetrap. And everyone's sitting now 172 00:08:11,320 --> 00:08:13,600 Speaker 4: on you know, trillions of dollars of spending and if 173 00:08:13,600 --> 00:08:15,680 Speaker 4: they just would have waited a couple of years, they 174 00:08:15,680 --> 00:08:17,280 Speaker 4: could have spent helf the amount. 175 00:08:17,120 --> 00:08:19,679 Speaker 3: We've already talked about. This is it the Chinese model 176 00:08:19,680 --> 00:08:21,400 Speaker 3: where some companies are playing around with it? 177 00:08:21,720 --> 00:08:24,040 Speaker 2: Yeah, I mean this is the Deep Seek scare from 178 00:08:24,120 --> 00:08:25,840 Speaker 2: last year that we spoke about. 179 00:08:25,920 --> 00:08:26,080 Speaker 3: Yeah. 180 00:08:26,120 --> 00:08:27,600 Speaker 4: I think the answer is no. If we look back 181 00:08:27,640 --> 00:08:30,320 Speaker 4: at what happened with Deep Seek, right, it was this 182 00:08:30,400 --> 00:08:33,559 Speaker 4: sort of moment where everyone was panicky, and then what 183 00:08:33,640 --> 00:08:36,079 Speaker 4: happened We hit all time highs again. So I think 184 00:08:36,120 --> 00:08:38,960 Speaker 4: that's eventually going to end up happening. I do think. Listen, 185 00:08:39,080 --> 00:08:42,040 Speaker 4: the credit markets are deep enough to finance all this. 186 00:08:42,080 --> 00:08:44,600 Speaker 4: There's a variety of different things that are happening. There's 187 00:08:44,600 --> 00:08:46,800 Speaker 4: a host of SPVs that are being priced now they're 188 00:08:46,800 --> 00:08:49,439 Speaker 4: off balance sheet, and you know, that's an interesting sort 189 00:08:49,480 --> 00:08:51,520 Speaker 4: of trade. But there's tens of billions of dollars of 190 00:08:51,559 --> 00:08:55,800 Speaker 4: private capital that's around, there's tremendous amounts of non US 191 00:08:55,840 --> 00:08:58,560 Speaker 4: dollar currency that's still likely to be raised. That helps 192 00:08:58,559 --> 00:09:01,240 Speaker 4: with technicals. And then I think the other step, and 193 00:09:01,280 --> 00:09:03,560 Speaker 4: this is bad for the equity markets. I guess, is 194 00:09:03,559 --> 00:09:05,320 Speaker 4: that I think you're going to see more equity issuance. 195 00:09:05,360 --> 00:09:07,480 Speaker 4: You know, we saw massive issuance out of Alphabet. We've 196 00:09:07,480 --> 00:09:10,480 Speaker 4: actually seen that out of Oracle. Obviously, SpaceX did a 197 00:09:10,480 --> 00:09:12,840 Speaker 4: big deal, and I think others are going to follow. 198 00:09:12,880 --> 00:09:15,080 Speaker 4: And by the way, with things like SpaceX, which are wider, 199 00:09:15,559 --> 00:09:19,120 Speaker 4: nothing's changed zero reporting their one hundred basis points wider. 200 00:09:19,200 --> 00:09:21,480 Speaker 3: Robert Schiffman, this is Bloomberg. 201 00:09:22,600 --> 00:09:25,400 Speaker 2: Stay with us. More from Bloomberg Business Week Daily coming 202 00:09:25,440 --> 00:09:26,400 Speaker 2: up after this. 203 00:09:30,800 --> 00:09:34,640 Speaker 1: You're listening to the Bloomberg Business Week Daily podcast. Catch 204 00:09:34,720 --> 00:09:37,400 Speaker 1: us Live weekday afternoons from two to five e's during 205 00:09:37,600 --> 00:09:41,560 Speaker 1: Listen on Applecarplay and Android Auto with the Bloomberg Business app, 206 00:09:41,720 --> 00:09:43,600 Speaker 1: or watch us Live on YouTube. 207 00:09:43,880 --> 00:09:45,640 Speaker 2: There is a lot to talk to Cat Doherty about. 208 00:09:45,679 --> 00:09:47,400 Speaker 2: Traders are getting a new tool to wager on the 209 00:09:47,440 --> 00:09:51,199 Speaker 2: Vegas US stocks. Also, Fanatics and BGC are thinking a 210 00:09:51,240 --> 00:09:53,920 Speaker 2: prediction markets deal with the sale of an exchange. Cat 211 00:09:53,920 --> 00:09:56,240 Speaker 2: Doherty is here she's Bloomberg News Finance reporter. She joins 212 00:09:56,280 --> 00:09:59,120 Speaker 2: us in the Bloomberg Business Week Studio. I want to 213 00:09:59,160 --> 00:10:01,520 Speaker 2: talk about this new two that you and Bernard wrote 214 00:10:01,520 --> 00:10:05,760 Speaker 2: about over the weekend, Single stock Futures. It allows investors 215 00:10:05,760 --> 00:10:07,480 Speaker 2: to head your speculate on more than fifty of the 216 00:10:07,559 --> 00:10:10,760 Speaker 2: largest US companies. For people who are hearing this or watching, 217 00:10:10,800 --> 00:10:12,920 Speaker 2: they're saying, wait a second, this sounds familiar. Haven't they 218 00:10:12,960 --> 00:10:15,880 Speaker 2: done this before? Apparently this time is different. 219 00:10:16,160 --> 00:10:19,200 Speaker 5: Well, it's different for a number of reasons. I would say, 220 00:10:19,480 --> 00:10:24,000 Speaker 5: first and foremost retail participation. When this was tried years ago, 221 00:10:24,360 --> 00:10:29,400 Speaker 5: there wasn't as much of the retail or individual investor. 222 00:10:29,559 --> 00:10:31,440 Speaker 2: We didn't have phones that we could just place trade on. 223 00:10:31,559 --> 00:10:36,040 Speaker 5: Aslue and think about the SpaceX Ipo that just happened 224 00:10:36,080 --> 00:10:41,040 Speaker 5: and the emphasis on retail trader participation. This new tool 225 00:10:41,640 --> 00:10:45,479 Speaker 5: is going to be another way that retail can participate. 226 00:10:46,280 --> 00:10:50,320 Speaker 5: Even if they weren't able to buy a stock of 227 00:10:50,440 --> 00:10:53,840 Speaker 5: the SpaceX ipo because it was oversubscribed, they couldn't get in, 228 00:10:53,920 --> 00:10:58,679 Speaker 5: they couldn't get an allocation, they can now place a 229 00:10:58,880 --> 00:11:03,440 Speaker 5: wager through the single stock futures and it will give 230 00:11:03,480 --> 00:11:07,319 Speaker 5: them exposure to the price of SpaceX, but not owning 231 00:11:07,440 --> 00:11:10,880 Speaker 5: the underlying shares. It's just another way to place your 232 00:11:10,880 --> 00:11:14,320 Speaker 5: bet on where you're seeing this name or other names 233 00:11:15,200 --> 00:11:16,640 Speaker 5: move in terms of their price. 234 00:11:17,240 --> 00:11:19,319 Speaker 2: I'm really glad you brought up SpaceX. Rick Worster was 235 00:11:19,360 --> 00:11:21,319 Speaker 2: on last week. What did you tell us? He told 236 00:11:21,400 --> 00:11:24,280 Speaker 2: us nobody. None of our clients got what they wanted 237 00:11:24,320 --> 00:11:26,559 Speaker 2: in terms of the amount of SpaceX stock that they 238 00:11:26,559 --> 00:11:30,040 Speaker 2: wanted or the allocation that they wanted. But everybody got something, 239 00:11:30,160 --> 00:11:31,840 Speaker 2: but none of them got as much as they wanted. 240 00:11:32,000 --> 00:11:34,160 Speaker 3: Right. There was incredible interest. So is that what this 241 00:11:34,240 --> 00:11:37,079 Speaker 3: is all about? Essentially is giving people access to something 242 00:11:37,120 --> 00:11:40,319 Speaker 3: that you know, new issue ins IPOs? Is that really 243 00:11:40,360 --> 00:11:40,959 Speaker 3: what I think? 244 00:11:41,000 --> 00:11:44,600 Speaker 5: That's one one piece of the puzzle. CME is touting 245 00:11:44,600 --> 00:11:48,120 Speaker 5: this as a hedging tool, So it's not just for 246 00:11:48,360 --> 00:11:52,120 Speaker 5: the retail participant that couldn't get into SpaceX's IPO or 247 00:11:52,160 --> 00:11:56,280 Speaker 5: future IPOs. It's meant to be another avenue think for 248 00:11:56,320 --> 00:12:00,120 Speaker 5: the institutional investor that has exposure and if you on 249 00:12:00,120 --> 00:12:01,880 Speaker 5: a hedge your bets and you want to just like 250 00:12:01,960 --> 00:12:05,240 Speaker 5: you would use options. But they are touting this also 251 00:12:05,679 --> 00:12:08,960 Speaker 5: as a tool similar to options. It gives you exposure. 252 00:12:09,600 --> 00:12:12,520 Speaker 5: What is different from options is that this is somewhat 253 00:12:12,520 --> 00:12:15,000 Speaker 5: of an easier tool because you don't have to take 254 00:12:15,040 --> 00:12:19,199 Speaker 5: into account the gamma or any of the Greek considerations 255 00:12:19,280 --> 00:12:22,520 Speaker 5: that are an advanced form of investing. 256 00:12:22,800 --> 00:12:27,320 Speaker 2: By reading your story funny, yeah, I mean yeah, I 257 00:12:27,320 --> 00:12:29,120 Speaker 2: have no idea how any of that stuff works. The 258 00:12:29,200 --> 00:12:30,960 Speaker 2: question though that I think Carol brought this up on 259 00:12:30,960 --> 00:12:32,760 Speaker 2: our call this morning. We were talking about this is 260 00:12:33,000 --> 00:12:35,960 Speaker 2: what's potential downside here for people who are you know, 261 00:12:36,120 --> 00:12:39,320 Speaker 2: have easier ways to do this stuff, but doesn't mean 262 00:12:39,360 --> 00:12:40,760 Speaker 2: easier ways to part with their money. 263 00:12:40,760 --> 00:12:42,839 Speaker 3: Well, and on that you've got this is to give 264 00:12:42,880 --> 00:12:45,840 Speaker 3: it access to retail investors, but you have institutional investors 265 00:12:45,840 --> 00:12:48,160 Speaker 3: playing with it too, So retail investors beware. 266 00:12:48,320 --> 00:12:51,800 Speaker 5: Yes, So I think in terms of the potential downsides 267 00:12:51,880 --> 00:12:55,560 Speaker 5: or the risks that have been identified, people have brought 268 00:12:55,600 --> 00:13:00,960 Speaker 5: up volatility. If there is major price swings in these names, 269 00:13:01,440 --> 00:13:04,240 Speaker 5: the futures are going to be Again it's a tool 270 00:13:04,280 --> 00:13:09,440 Speaker 5: to help offset some price wings, but if there's more 271 00:13:09,520 --> 00:13:12,960 Speaker 5: movement and there's more volatility overall, the products are going 272 00:13:13,040 --> 00:13:16,400 Speaker 5: to be harder to price or to at least hedge 273 00:13:16,440 --> 00:13:19,040 Speaker 5: your bets in a way that has more certainty. So 274 00:13:19,280 --> 00:13:21,400 Speaker 5: I think that that's one thing that has been brought up. 275 00:13:22,400 --> 00:13:24,840 Speaker 5: This is a new tool. So for any tool that 276 00:13:24,960 --> 00:13:28,760 Speaker 5: is being released into the market, there's a question of liquidity, 277 00:13:29,120 --> 00:13:32,000 Speaker 5: how much activities are going to be, who's going to 278 00:13:32,000 --> 00:13:34,840 Speaker 5: support it, who are the market makers that are going 279 00:13:34,920 --> 00:13:37,280 Speaker 5: to support it. But presumably there is a lot of 280 00:13:37,320 --> 00:13:40,400 Speaker 5: demand for this, and again the tool is not so 281 00:13:40,760 --> 00:13:44,000 Speaker 5: dissimilar to options, so it's not as if you are 282 00:13:44,040 --> 00:13:47,880 Speaker 5: putting out an entirely new asset class that is being tested. 283 00:13:48,679 --> 00:13:51,200 Speaker 5: There's a lot of use case for putting out tools 284 00:13:51,240 --> 00:13:55,560 Speaker 5: like this. Always, whenever there's a new product, that's going 285 00:13:55,640 --> 00:13:58,960 Speaker 5: to mean more dollar signs for a venue like CME 286 00:13:59,080 --> 00:14:00,319 Speaker 5: that offers these products. 287 00:14:00,520 --> 00:14:02,559 Speaker 2: So does everybody think it's going to work this time 288 00:14:02,600 --> 00:14:04,240 Speaker 2: even though it didn't work twenty five years ago. 289 00:14:04,600 --> 00:14:08,040 Speaker 5: I think that there's a lot of evidence to support it. 290 00:14:08,120 --> 00:14:13,080 Speaker 5: Again from the just growth of the retail investor, we 291 00:14:13,240 --> 00:14:17,160 Speaker 5: have seen a lot of their micro or mini products 292 00:14:17,200 --> 00:14:21,040 Speaker 5: as they call them, outside of just these single stock futures, 293 00:14:22,240 --> 00:14:24,080 Speaker 5: those have got a lot of demand. And when I 294 00:14:24,080 --> 00:14:27,480 Speaker 5: say mini micro, it just means that they're in smaller sizes, 295 00:14:27,520 --> 00:14:30,160 Speaker 5: so that they're more accessible to folks that have less 296 00:14:30,200 --> 00:14:34,320 Speaker 5: money to trade with. So we've seen interest from other 297 00:14:35,040 --> 00:14:39,280 Speaker 5: again of the smaller products, so that gives evidence to 298 00:14:39,720 --> 00:14:42,600 Speaker 5: point to the fact that this could be more successful 299 00:14:42,600 --> 00:14:43,760 Speaker 5: on its second launch. 300 00:14:44,160 --> 00:14:48,200 Speaker 3: There's a lot of also competition right increasingly among exchanges. 301 00:14:48,440 --> 00:14:52,000 Speaker 5: There is new products, you have prediction markets that are 302 00:14:52,280 --> 00:14:57,080 Speaker 5: launching perps. It's just becoming which tool is going to 303 00:14:57,120 --> 00:15:00,240 Speaker 5: be I think a lot of times these venues like 304 00:15:00,320 --> 00:15:03,880 Speaker 5: to point to the ease at which some of these tools, 305 00:15:04,520 --> 00:15:06,480 Speaker 5: and ease can mean a number of things, but first 306 00:15:06,520 --> 00:15:09,200 Speaker 5: and foremost, if you're talking about a retail investor, it's 307 00:15:09,480 --> 00:15:13,520 Speaker 5: do you understand the underlying product, what what your exposures 308 00:15:13,560 --> 00:15:15,920 Speaker 5: and the risks are, and how do you use it. 309 00:15:16,520 --> 00:15:20,359 Speaker 5: I think that education for products that are more advanced 310 00:15:20,560 --> 00:15:23,120 Speaker 5: is something that the venues like to tout. They like 311 00:15:23,200 --> 00:15:27,040 Speaker 5: to say, we educate our investors and they know what 312 00:15:27,080 --> 00:15:29,760 Speaker 5: they're what they're buying into. That's why we've seen the 313 00:15:29,840 --> 00:15:33,920 Speaker 5: rise and options. You've got more sophisticated retail participation. But 314 00:15:34,120 --> 00:15:36,840 Speaker 5: when you have new products that are touted because of 315 00:15:36,840 --> 00:15:40,360 Speaker 5: how easy they are to understand and to use, that 316 00:15:40,440 --> 00:15:42,200 Speaker 5: becomes their their new tagline. 317 00:15:42,320 --> 00:15:44,160 Speaker 2: You know, I describe you as a financi reporter who 318 00:15:44,200 --> 00:15:45,920 Speaker 2: covers markets, and I didn't mean to say you cover 319 00:15:45,960 --> 00:15:48,040 Speaker 2: the ins and outs of the daily moves on markets. 320 00:15:48,080 --> 00:15:49,800 Speaker 2: What I mean is you actually literally. 321 00:15:49,440 --> 00:15:52,680 Speaker 5: Cover the market structure, and the market structure, the types, 322 00:15:52,800 --> 00:15:53,520 Speaker 5: the plumbing. 323 00:15:53,720 --> 00:15:56,000 Speaker 2: The plumbing is everybody likes to say yes and there's 324 00:15:56,080 --> 00:15:57,480 Speaker 2: you know, it doesn't get a lot of attention until 325 00:15:57,480 --> 00:15:59,520 Speaker 2: there's an issue and they need to call the plumber, 326 00:15:59,600 --> 00:16:01,600 Speaker 2: that's right. But these days it is getting a lot 327 00:16:01,600 --> 00:16:03,960 Speaker 2: of attention because you have the rise of prediction markets 328 00:16:04,000 --> 00:16:05,760 Speaker 2: and we're going to talk about some prediction markets in 329 00:16:05,920 --> 00:16:09,240 Speaker 2: just a second, and some sort of like very strange bedfellows. 330 00:16:09,320 --> 00:16:13,120 Speaker 2: I think some people would say, but I'm curious how 331 00:16:13,160 --> 00:16:15,880 Speaker 2: your beat has changed just over the last few months, 332 00:16:15,880 --> 00:16:18,760 Speaker 2: now that everybody is kind of getting in on cmme's turf, 333 00:16:18,840 --> 00:16:21,280 Speaker 2: like CME and CBO. For years, they were the only 334 00:16:21,280 --> 00:16:23,920 Speaker 2: ones that were doing this sort of thing, an intercontinental exchange. 335 00:16:24,000 --> 00:16:25,880 Speaker 2: But now there's like all these upstarts. 336 00:16:25,920 --> 00:16:30,280 Speaker 5: Well it's innovation, right, We're in a new regulatory regime. 337 00:16:30,760 --> 00:16:34,040 Speaker 5: And what it has meant is, in the last year 338 00:16:34,160 --> 00:16:37,880 Speaker 5: or so, you've seen upstarts that have really gained traction 339 00:16:38,040 --> 00:16:40,840 Speaker 5: because they're able to actually launch products. They're not just 340 00:16:41,240 --> 00:16:45,080 Speaker 5: asking permission or asking for forgiveness. They're they're given the 341 00:16:45,120 --> 00:16:47,800 Speaker 5: green light to just go ahead. And because of that, 342 00:16:47,920 --> 00:16:50,800 Speaker 5: when you see these new products and some of these upstarts, 343 00:16:51,200 --> 00:16:55,320 Speaker 5: their benefit is that they can come at this with 344 00:16:55,680 --> 00:16:57,280 Speaker 5: new products, but they also. 345 00:16:57,080 --> 00:16:58,120 Speaker 3: Have new technology. 346 00:16:58,320 --> 00:17:00,200 Speaker 5: Some of the interface is a little bit more or 347 00:17:01,160 --> 00:17:06,040 Speaker 5: it is exactly tailored to the retail investor, Whereas if 348 00:17:06,040 --> 00:17:10,920 Speaker 5: you think about CME, especially and somewhat CEBO, they have 349 00:17:11,000 --> 00:17:14,439 Speaker 5: come from the place of serving institutions. Those institutions are 350 00:17:14,520 --> 00:17:18,440 Speaker 5: used to certain products and also certain interfaces that might 351 00:17:18,480 --> 00:17:22,879 Speaker 5: seem outdated to a retail customer that is coming to 352 00:17:22,920 --> 00:17:25,560 Speaker 5: the market fresh and is looking for an app that 353 00:17:25,720 --> 00:17:29,840 Speaker 5: again easy to use, easy to understand. They want to 354 00:17:29,960 --> 00:17:34,040 Speaker 5: have it's both ease and accessibility. So they want to 355 00:17:34,040 --> 00:17:35,840 Speaker 5: be able to see certain buttons are going to work 356 00:17:35,840 --> 00:17:38,399 Speaker 5: in certain ways, and it's and it's not complicated, and 357 00:17:38,440 --> 00:17:40,399 Speaker 5: you know exactly which interface you need to go to. 358 00:17:41,359 --> 00:17:44,280 Speaker 5: So I think that if you are an incumbent like CME, 359 00:17:44,560 --> 00:17:46,800 Speaker 5: you're coming at it with the benefit of you have 360 00:17:46,880 --> 00:17:50,440 Speaker 5: the foundation, you have the years of trust and partnerships 361 00:17:50,480 --> 00:17:53,680 Speaker 5: and clients that you have been serving. That's a huge 362 00:17:53,720 --> 00:17:57,040 Speaker 5: They've they've rested on those laurels for for many, many years, 363 00:17:57,320 --> 00:17:59,840 Speaker 5: and now you have these these new players coming and 364 00:18:00,280 --> 00:18:03,640 Speaker 5: they are fresh and they're building their brand and they 365 00:18:03,760 --> 00:18:08,399 Speaker 5: are using the retail customer as an entryway and they 366 00:18:08,440 --> 00:18:10,560 Speaker 5: want to bring the institutions in too. I will always 367 00:18:10,600 --> 00:18:13,360 Speaker 5: say that both players are coming at this that it's 368 00:18:13,359 --> 00:18:15,520 Speaker 5: not as if CM is saying, oh, we serve institutions. 369 00:18:15,520 --> 00:18:20,320 Speaker 5: We're only going to serve institutions. They're building their retail clients, 370 00:18:20,480 --> 00:18:23,560 Speaker 5: and in the same capacity, you have a Calshi that 371 00:18:23,680 --> 00:18:27,119 Speaker 5: is serving the retail investor. They're primarily in sports, but 372 00:18:27,200 --> 00:18:29,479 Speaker 5: they want the institutions to come in and start trading 373 00:18:29,520 --> 00:18:30,720 Speaker 5: things outside of sports. 374 00:18:30,960 --> 00:18:35,520 Speaker 3: Well, then there's Fanatics. Tell us about this back to stories, Yeah, yes, 375 00:18:35,280 --> 00:18:37,200 Speaker 3: go back there, Yes, tell us about this deal. 376 00:18:37,400 --> 00:18:40,560 Speaker 5: So Fanatics has been in prediction markets. They've been working 377 00:18:40,640 --> 00:18:44,880 Speaker 5: with Crypto dot Com, and again you think of Fanatics 378 00:18:44,920 --> 00:18:51,199 Speaker 5: as this customer client. First, they're selling sports jerseys and 379 00:18:51,240 --> 00:18:55,439 Speaker 5: they have all of these partnerships with the major sports leagues, 380 00:18:56,480 --> 00:18:58,399 Speaker 5: and then they got into prediction markets. It's a natural 381 00:18:58,440 --> 00:19:02,040 Speaker 5: extension for them. They're they're keeping it in the sports arena, 382 00:19:02,480 --> 00:19:05,719 Speaker 5: serving clients that want to bet on sports games. And 383 00:19:05,840 --> 00:19:11,119 Speaker 5: now today's announcement, they're partnering with one of the brokerage 384 00:19:11,119 --> 00:19:16,160 Speaker 5: firms that many of our Bloomberg readers, BBC is selling. 385 00:19:16,200 --> 00:19:20,199 Speaker 5: They sold their licenses to operate and exchange that fanatics 386 00:19:20,240 --> 00:19:25,440 Speaker 5: will now use to list and eventually trade their own 387 00:19:25,480 --> 00:19:28,520 Speaker 5: prediction market contracts. So they can still work with crypto 388 00:19:28,560 --> 00:19:32,639 Speaker 5: dot com in offering prediction market contracts through them, but 389 00:19:32,880 --> 00:19:37,240 Speaker 5: now they have their own exchange where they can list 390 00:19:37,400 --> 00:19:40,600 Speaker 5: trade prediction markets. They're going to start with sports, eventually 391 00:19:40,720 --> 00:19:46,359 Speaker 5: they could expand beyond that. But these two unlikely partners, 392 00:19:46,600 --> 00:19:49,520 Speaker 5: they actually see this as a very likely pair to them. 393 00:19:49,560 --> 00:19:52,679 Speaker 5: They see this as a natural extension for both firms. 394 00:19:52,920 --> 00:19:57,520 Speaker 5: The reason being for fanatics, they want the support, and 395 00:19:57,560 --> 00:20:00,600 Speaker 5: when I say support, the liquidity, the trading, the pricing 396 00:20:01,119 --> 00:20:06,280 Speaker 5: that a Wall Street firm can bring. Like BGCGC wants 397 00:20:06,640 --> 00:20:08,879 Speaker 5: exposure to retail. They also want to give some of 398 00:20:08,920 --> 00:20:12,440 Speaker 5: their big clients exposure to prediction markets which they don't 399 00:20:12,440 --> 00:20:14,760 Speaker 5: currently offer. So now they can say, hey, look we 400 00:20:14,800 --> 00:20:18,240 Speaker 5: have this partnership with fanatics. They're operating this exchange that 401 00:20:18,240 --> 00:20:21,400 Speaker 5: we just sold to them, the licensing that is, and 402 00:20:21,520 --> 00:20:25,200 Speaker 5: here's another asset class that you can trade with us. 403 00:20:25,800 --> 00:20:27,440 Speaker 3: How many prediction markets do we need? 404 00:20:28,720 --> 00:20:32,360 Speaker 5: There's just going to keeping a SLU. But it's really 405 00:20:32,359 --> 00:20:34,119 Speaker 5: the question of who will dominate the space? 406 00:20:34,359 --> 00:20:39,080 Speaker 3: Yeah, ultimately right, that already unbelievable, great stuff Finance Reporter, 407 00:20:39,359 --> 00:20:42,480 Speaker 3: as we said, really kind of the infrastructure, the nuts 408 00:20:42,480 --> 00:20:46,240 Speaker 3: and bolts of how all of the activity happens here 409 00:20:46,280 --> 00:20:47,160 Speaker 3: at Bloomberg News. 410 00:20:48,440 --> 00:20:51,240 Speaker 2: Stay with us. More from Bloomberg Business Week Daily coming 411 00:20:51,320 --> 00:20:52,239 Speaker 2: up after this. 412 00:20:56,400 --> 00:21:00,280 Speaker 1: You're listening to the Bloomberg Business Week Daily Podcast. Catch 413 00:21:00,359 --> 00:21:03,000 Speaker 1: us live weekday afternoons from two to five e's during 414 00:21:03,000 --> 00:21:06,440 Speaker 1: this listen on Applecarplay and Android Otto with the Bloomberg 415 00:21:06,480 --> 00:21:09,040 Speaker 1: Business app, or watch us live on YouTube. 416 00:21:10,320 --> 00:21:12,560 Speaker 3: Hey, ahead of that, there's some research out from KPMG 417 00:21:12,680 --> 00:21:16,240 Speaker 3: and UT Austin's McCombs School. It was published in the 418 00:21:16,280 --> 00:21:20,600 Speaker 3: Harvard Business Review, and the research found that workers don't 419 00:21:20,680 --> 00:21:23,359 Speaker 3: all need to be nervous over AI taking their jobs. 420 00:21:23,359 --> 00:21:25,960 Speaker 3: There are some thoughts, some caveats, so to it here 421 00:21:26,000 --> 00:21:27,000 Speaker 3: to explain AI. 422 00:21:27,160 --> 00:21:31,320 Speaker 2: Right, that's Hey, don't worry, Hey, don't worry about this. 423 00:21:31,560 --> 00:21:37,040 Speaker 3: I'm good a good person. Rossan shares as AI Enterprise 424 00:21:37,080 --> 00:21:42,240 Speaker 3: Transformation leader at KPMG US. She joins us from Atlanta. Raissan, 425 00:21:42,480 --> 00:21:44,240 Speaker 3: nice to have you here with Tim and me here 426 00:21:44,280 --> 00:21:46,800 Speaker 3: on Bloomberg Business Week Daily. Briefly, tell us what you 427 00:21:46,880 --> 00:21:50,200 Speaker 3: guys looked at, how the study and research was conducted, 428 00:21:50,240 --> 00:21:51,800 Speaker 3: and what were some of the key findings. 429 00:21:52,840 --> 00:21:56,280 Speaker 6: Absolutely, we started with a look at over five hundred 430 00:21:56,320 --> 00:21:59,520 Speaker 6: of our early career professionals, those who have been working 431 00:21:59,600 --> 00:22:03,199 Speaker 6: less than eighteen months, and we really broke apart the 432 00:22:03,240 --> 00:22:07,439 Speaker 6: work that they need to do between planning, integrating and 433 00:22:07,640 --> 00:22:12,000 Speaker 6: monitoring work and then set out to study really what 434 00:22:12,119 --> 00:22:15,200 Speaker 6: makes you most impactful and effective in working with AI, 435 00:22:15,840 --> 00:22:20,399 Speaker 6: particularly for this demographic because their work is more disrupted 436 00:22:20,480 --> 00:22:24,520 Speaker 6: by AI than maybe other segments of the industry. But 437 00:22:24,600 --> 00:22:29,080 Speaker 6: we wanted to understand how we could continue to drive 438 00:22:29,240 --> 00:22:33,000 Speaker 6: value in this segment of our workforce. What we found 439 00:22:33,160 --> 00:22:36,200 Speaker 6: in this study with the University of Texas is that 440 00:22:36,400 --> 00:22:41,399 Speaker 6: our participants fell into three categories. Amplifiers those who really 441 00:22:41,440 --> 00:22:45,800 Speaker 6: know how to achieve an outcome that exceeds the AI baseline. 442 00:22:46,000 --> 00:22:49,879 Speaker 6: Delegators those who hand off their work, and really only 443 00:22:49,960 --> 00:22:54,360 Speaker 6: receive whatever the aceline does and perform at the AI baseline, 444 00:22:54,640 --> 00:22:58,879 Speaker 6: and apprentices those who in fact have the same based 445 00:22:58,920 --> 00:23:03,399 Speaker 6: skills and think, critical thinking, knowledge of industry, knowledge of 446 00:23:03,440 --> 00:23:08,240 Speaker 6: subject matter as the amplifiers, but lack the ability or 447 00:23:08,280 --> 00:23:10,600 Speaker 6: the understanding of how to apply that to the AI, 448 00:23:11,160 --> 00:23:13,840 Speaker 6: which put them in the apprentice category. The thing that 449 00:23:13,960 --> 00:23:17,040 Speaker 6: was the real unlock the AHA is that it wasn't 450 00:23:17,080 --> 00:23:20,720 Speaker 6: the core skills alone. It was really the connection to 451 00:23:20,800 --> 00:23:23,919 Speaker 6: how those skills are applied to the AI that really 452 00:23:23,960 --> 00:23:27,080 Speaker 6: delivered the most value showing in our viue and what 453 00:23:27,160 --> 00:23:31,320 Speaker 6: the UT study that learning is possible to help everyone move. 454 00:23:31,480 --> 00:23:33,320 Speaker 3: So I want to break in. You're sitting down with 455 00:23:33,359 --> 00:23:35,639 Speaker 3: your best buddy at a bar or not having a 456 00:23:35,680 --> 00:23:38,280 Speaker 3: non alcoholic or alcoholic verge and they say, is AI 457 00:23:38,320 --> 00:23:40,000 Speaker 3: going to take on my job? You're going to just say, 458 00:23:40,000 --> 00:23:40,760 Speaker 3: briefly what. 459 00:23:41,840 --> 00:23:44,720 Speaker 6: I'm going to say, No, those who get the most 460 00:23:44,760 --> 00:23:47,040 Speaker 6: out of AI are going to take the jobs. And 461 00:23:47,080 --> 00:23:50,600 Speaker 6: that's why helping more people learn how to use AI 462 00:23:50,640 --> 00:23:53,760 Speaker 6: as a thought partner and really exceed what the AI 463 00:23:53,800 --> 00:23:56,200 Speaker 6: baseline can do is where we want to get more 464 00:23:56,240 --> 00:23:58,960 Speaker 6: people to and the earlier you learn that in your 465 00:23:59,040 --> 00:24:01,600 Speaker 6: career and apply the better off that you're going to be. 466 00:24:01,720 --> 00:24:04,280 Speaker 2: So this is relevant for people in July of twenty 467 00:24:04,320 --> 00:24:07,080 Speaker 2: twenty six. But we've seen the pace of how things 468 00:24:07,280 --> 00:24:09,120 Speaker 2: how quickly things move here and in a world where 469 00:24:09,160 --> 00:24:13,359 Speaker 2: everybody's trying to achieve artificial general intelligence, I wonder how 470 00:24:13,480 --> 00:24:15,960 Speaker 2: relevant this research will be in just a couple of years. 471 00:24:16,000 --> 00:24:17,240 Speaker 2: How future proof do you think it is? 472 00:24:18,320 --> 00:24:20,520 Speaker 6: You know, it's a great perspective. We looked at this 473 00:24:20,640 --> 00:24:24,399 Speaker 6: research with ever increasing capacity in the AI, and what 474 00:24:24,480 --> 00:24:27,520 Speaker 6: we found in each case is that the human effect, 475 00:24:27,840 --> 00:24:31,600 Speaker 6: really the human using AI to provide additional context to it, 476 00:24:31,880 --> 00:24:34,720 Speaker 6: using it as a thought partner, continue to exceed the 477 00:24:34,760 --> 00:24:38,239 Speaker 6: AI baseline, showing clear evidence that as much as the 478 00:24:38,240 --> 00:24:42,320 Speaker 6: AI advances, the human difference continues to make a huge 479 00:24:42,359 --> 00:24:44,520 Speaker 6: impact in how you achieve value. 480 00:24:44,960 --> 00:24:47,440 Speaker 3: So help you know, there is a bunch of kids 481 00:24:47,480 --> 00:24:50,240 Speaker 3: coming out of college or getting ready to figure out 482 00:24:50,240 --> 00:24:52,480 Speaker 3: what to study and just say what do I do? 483 00:24:52,600 --> 00:24:55,320 Speaker 3: What do I do? So, first of all, how does 484 00:24:55,359 --> 00:25:00,399 Speaker 3: academia or all kinds of learning institutions have to do? 485 00:25:00,440 --> 00:25:02,760 Speaker 3: We even need four years anymore? Because AI is going 486 00:25:02,800 --> 00:25:04,239 Speaker 3: to be taking over a lot of skills or what 487 00:25:04,240 --> 00:25:08,159 Speaker 3: do we need and how should the next generation be 488 00:25:08,160 --> 00:25:09,400 Speaker 3: getting ready for the workforce. 489 00:25:10,400 --> 00:25:12,920 Speaker 6: What I think is really exciting that this research found 490 00:25:13,040 --> 00:25:16,119 Speaker 6: and what our colleagues at the University of Texas are 491 00:25:16,400 --> 00:25:19,880 Speaker 6: continuing to advance, is that teaching students and those who 492 00:25:19,920 --> 00:25:22,440 Speaker 6: are going back to up their skills how to use 493 00:25:22,520 --> 00:25:26,080 Speaker 6: AI as a thought partner, as a tool to get more, 494 00:25:26,680 --> 00:25:30,639 Speaker 6: to do more, to expand your capability. But providing the 495 00:25:31,320 --> 00:25:35,800 Speaker 6: opportunity to really immerse yourself in exercises and learning that 496 00:25:35,920 --> 00:25:39,480 Speaker 6: allow you to advance your skill of challenging using their 497 00:25:39,520 --> 00:25:43,520 Speaker 6: critical thinking to frame how you question and interrogate the 498 00:25:43,560 --> 00:25:46,280 Speaker 6: AI is what makes the difference. It's so funny that 499 00:25:46,400 --> 00:25:47,399 Speaker 6: things can be taught. 500 00:25:47,880 --> 00:25:49,399 Speaker 3: It's so funny. There was something my husband and I 501 00:25:49,440 --> 00:25:51,040 Speaker 3: were talking about and he was like, you know, I'm 502 00:25:51,080 --> 00:25:53,400 Speaker 3: gonna just ask A I mean, ask toucchipet or something, 503 00:25:53,400 --> 00:25:55,560 Speaker 3: and he like, did this very in depth question, Like 504 00:25:55,800 --> 00:25:58,320 Speaker 3: that's actually how you need to ask AI questions. 505 00:25:58,440 --> 00:25:58,880 Speaker 6: Is it right? 506 00:26:00,560 --> 00:26:02,240 Speaker 2: What was this about? I need to know more about this. 507 00:26:02,400 --> 00:26:05,840 Speaker 6: I have to I can't remember, but that was definitely 508 00:26:05,960 --> 00:26:08,960 Speaker 6: amplify your behavior and not a delegator because he didn't 509 00:26:09,000 --> 00:26:11,560 Speaker 6: just owe a simple question. You talked about the fact 510 00:26:11,600 --> 00:26:14,080 Speaker 6: that he asked a very in depth, intentional question, yes, 511 00:26:14,119 --> 00:26:16,240 Speaker 6: and that positions you to get the most out of AI. 512 00:26:16,520 --> 00:26:20,000 Speaker 3: It had to do with putting a stove fan in 513 00:26:20,040 --> 00:26:23,919 Speaker 3: a historic district on a really old home, but it 514 00:26:24,040 --> 00:26:26,159 Speaker 3: kind of went through all these different parameters and what 515 00:26:26,240 --> 00:26:28,400 Speaker 3: you need in terms of airflow and da da dah. 516 00:26:28,400 --> 00:26:29,880 Speaker 3: But he went through it, and I'm like, that's how 517 00:26:29,920 --> 00:26:31,160 Speaker 3: you ask a question on AI. 518 00:26:31,240 --> 00:26:32,520 Speaker 2: So we're going to so then when you bring the 519 00:26:32,520 --> 00:26:35,160 Speaker 2: plans to the city, they're going to say, this is raw, 520 00:26:36,200 --> 00:26:37,800 Speaker 2: this isn't going to work Juti. 521 00:26:37,880 --> 00:26:40,800 Speaker 6: Where he needs to provide additional context and make sure 522 00:26:41,080 --> 00:26:43,600 Speaker 6: that instruction is in the context of what you have 523 00:26:43,680 --> 00:26:44,480 Speaker 6: to take to the city. 524 00:26:45,520 --> 00:26:49,600 Speaker 3: So are people going to still learn all those critical 525 00:26:49,600 --> 00:26:51,640 Speaker 3: skills we learn in our first year? I think about 526 00:26:51,680 --> 00:26:54,359 Speaker 3: my first couple of years in this industry learning curve 527 00:26:54,400 --> 00:26:56,600 Speaker 3: with Steve. I got yelled at a couple times in 528 00:26:56,640 --> 00:27:00,960 Speaker 3: a control room, but I learned so much. Are people 529 00:27:01,000 --> 00:27:03,639 Speaker 3: going to have that experience still, which I think is 530 00:27:03,720 --> 00:27:04,560 Speaker 3: kind of important. 531 00:27:05,440 --> 00:27:08,520 Speaker 6: Absolutely, it's how they will learn it will change. So 532 00:27:08,720 --> 00:27:11,000 Speaker 6: instead of maybe being stuck in that moment, you're going 533 00:27:11,040 --> 00:27:13,359 Speaker 6: to be included in some immersive training that's going to 534 00:27:13,520 --> 00:27:16,400 Speaker 6: simulate that for you, so you can develop those same muscles, 535 00:27:16,840 --> 00:27:20,560 Speaker 6: learn the same techniques, and also actually prepare you to 536 00:27:20,600 --> 00:27:23,920 Speaker 6: then take that and challenge AI with it to extend 537 00:27:24,200 --> 00:27:28,000 Speaker 6: the value that you're able to deliver earlier in your career. So, yes, 538 00:27:28,160 --> 00:27:31,720 Speaker 6: those skills are really important, but what is becoming more 539 00:27:31,760 --> 00:27:34,359 Speaker 6: important is your ability to take that and translate it 540 00:27:34,400 --> 00:27:36,480 Speaker 6: to how you work with Ai Raissan. 541 00:27:36,760 --> 00:27:39,400 Speaker 3: Really interesting stuff. Thank you so much for dropping by. 542 00:27:39,520 --> 00:27:42,399 Speaker 3: Rassan she or she is AI Enterprise Transformation leader of 543 00:27:42,480 --> 00:27:46,119 Speaker 3: a KPMG us joining us from Atlanta. 544 00:27:46,280 --> 00:27:49,080 Speaker 2: Stay with us. More from Bloomberg Business Week Daily coming 545 00:27:49,119 --> 00:27:50,040 Speaker 2: up after this. 546 00:27:54,760 --> 00:27:58,640 Speaker 1: You're listening to the Bloomberg Business Week Daily Podcast. Catch 547 00:27:58,720 --> 00:28:01,400 Speaker 1: us live weekday afternoon from two to five these during 548 00:28:01,600 --> 00:28:05,520 Speaker 1: listen on Applecarplay and Android Auto with the Bloomberg Business app, 549 00:28:05,680 --> 00:28:07,560 Speaker 1: or watch us live on YouTube. 550 00:28:08,320 --> 00:28:10,640 Speaker 2: There is and one thing that investors have to deal 551 00:28:10,680 --> 00:28:15,840 Speaker 2: with now increasingly is change in weather as well climate risk. 552 00:28:15,880 --> 00:28:18,119 Speaker 2: That's where Mark Gonglof comes in. He's a columnist for 553 00:28:18,119 --> 00:28:21,520 Speaker 2: Bloomberg Opinion who covers climate change. Our plan, Mark was 554 00:28:21,680 --> 00:28:24,679 Speaker 2: to cover all these wildfires in Spain and France and 555 00:28:24,800 --> 00:28:27,919 Speaker 2: the way that El Nino is pushing global warming higher 556 00:28:27,960 --> 00:28:31,159 Speaker 2: in the short term. But you're also worked on this 557 00:28:31,200 --> 00:28:34,720 Speaker 2: piece about data center heat risk a little earlier today 558 00:28:34,720 --> 00:28:36,919 Speaker 2: that just came out, and we talked about this in 559 00:28:36,920 --> 00:28:41,680 Speaker 2: the context of, okay, the energy demand that these data 560 00:28:41,720 --> 00:28:44,840 Speaker 2: centers take, but also the cooling required to actually keep 561 00:28:44,880 --> 00:28:48,880 Speaker 2: them from overheating. What are what are what is data 562 00:28:48,880 --> 00:28:49,680 Speaker 2: center heat risk? 563 00:28:51,360 --> 00:28:54,880 Speaker 7: Well, it's a risk that data centers run just by 564 00:28:55,080 --> 00:28:59,720 Speaker 7: operating in an environment which ironically you could say is 565 00:28:59,720 --> 00:29:06,200 Speaker 7: going to be made more hot and volatile because of 566 00:29:06,240 --> 00:29:09,680 Speaker 7: the energy the fossil fuels being burned to power the 567 00:29:09,720 --> 00:29:14,960 Speaker 7: data centers. So you talk about circular trades, circular financing, 568 00:29:15,040 --> 00:29:20,240 Speaker 7: You've got circular climates, data stuff going on here. So 569 00:29:21,040 --> 00:29:24,640 Speaker 7: you know, ironically, a big kind of booming business secondary 570 00:29:24,680 --> 00:29:29,720 Speaker 7: to maybe chips and such and serving AI is keeping 571 00:29:29,920 --> 00:29:33,080 Speaker 7: these data centers cool. The part of their cooling and 572 00:29:33,160 --> 00:29:37,440 Speaker 7: also involves drinking lots of water in some cases. Again 573 00:29:37,560 --> 00:29:40,120 Speaker 7: we can talk about how that is relative to agriculture. 574 00:29:40,160 --> 00:29:43,400 Speaker 7: It's not that huge, but still it's an issue. And 575 00:29:43,480 --> 00:29:46,800 Speaker 7: when you are dry drying out the way the west 576 00:29:46,920 --> 00:29:48,360 Speaker 7: is the way a lot of the places where you're 577 00:29:48,400 --> 00:29:52,240 Speaker 7: putting data centers are doing. Then you it becomes a 578 00:29:52,280 --> 00:29:53,680 Speaker 7: problem for these data centers too. 579 00:29:54,360 --> 00:29:56,440 Speaker 3: So that's why they're going to the Nordic region, right, 580 00:29:56,480 --> 00:29:59,520 Speaker 3: it's colder, Like, what's going on there? Mark, what's going on. 581 00:30:01,040 --> 00:30:01,360 Speaker 1: There? 582 00:30:01,440 --> 00:30:04,080 Speaker 7: It's colder. I mean, they're trying to put them everywhere 583 00:30:04,120 --> 00:30:08,960 Speaker 7: it's colder, dryer. It's about infrastructure, it's about political support. 584 00:30:09,280 --> 00:30:10,840 Speaker 7: You know, they're putting them in the Nordic regions, but 585 00:30:10,840 --> 00:30:13,080 Speaker 7: they're putting a lot of them in the along the 586 00:30:13,120 --> 00:30:16,480 Speaker 7: I thirty five port or in Texas, which is, as 587 00:30:16,480 --> 00:30:19,280 Speaker 7: Bloomberg Intelligence pointed out this week, as one of the 588 00:30:19,320 --> 00:30:21,840 Speaker 7: most water stressed places in the country. And it's also 589 00:30:21,880 --> 00:30:25,120 Speaker 7: extremely hot. It's sitting under heat dome as we speak. 590 00:30:25,520 --> 00:30:28,080 Speaker 7: So they're going all over the place and sometimes it 591 00:30:28,080 --> 00:30:30,320 Speaker 7: doesn't make a lot of logical sense where they're going. 592 00:30:30,520 --> 00:30:33,640 Speaker 3: Yeah, I wonder if we're going to get to a 593 00:30:33,640 --> 00:30:35,920 Speaker 3: point where it's like, Okay, people have no access to 594 00:30:35,920 --> 00:30:38,080 Speaker 3: water because it's all going to the data centers. I mean, 595 00:30:38,120 --> 00:30:40,440 Speaker 3: we're kind of seeing that in some places, are we not? 596 00:30:40,960 --> 00:30:43,160 Speaker 3: Are we're getting there potentially. 597 00:30:43,840 --> 00:30:46,200 Speaker 7: In some places? And again it's very you got to 598 00:30:46,240 --> 00:30:50,600 Speaker 7: go point by point overall. As I mentioned, data centers 599 00:30:50,720 --> 00:30:54,760 Speaker 7: don't use as much water as some other uses. But 600 00:30:55,640 --> 00:30:58,600 Speaker 7: if you are in place that's already water stressed, why 601 00:30:58,720 --> 00:31:01,680 Speaker 7: add to your problems. Actually, when the problem of water 602 00:31:01,800 --> 00:31:04,200 Speaker 7: is going to just keep increasing and so it's an 603 00:31:04,200 --> 00:31:08,240 Speaker 7: engineering problem. There are cooling technologies, but right now those 604 00:31:08,440 --> 00:31:10,000 Speaker 7: have yet to be deployed at scale. 605 00:31:10,200 --> 00:31:13,240 Speaker 2: Well, speaking of water and the way that it is 606 00:31:13,280 --> 00:31:15,960 Speaker 2: a scarce resource, we're finding that out around the world 607 00:31:15,960 --> 00:31:18,160 Speaker 2: when it comes to trying to put out fires, whether 608 00:31:18,160 --> 00:31:20,640 Speaker 2: they're in the western part of the US and Canada 609 00:31:21,000 --> 00:31:24,120 Speaker 2: or whether they're in France and Spain. Wildfires in France 610 00:31:24,120 --> 00:31:26,280 Speaker 2: and Spain have forced the evacuation more than three hundred 611 00:31:26,280 --> 00:31:28,480 Speaker 2: thousand people. Those have stabilized, but the onset of the 612 00:31:28,480 --> 00:31:32,320 Speaker 2: summer's fourth heat wave means little respite for emergency services, 613 00:31:32,800 --> 00:31:35,160 Speaker 2: and things could get worse because a powerful al Ninho 614 00:31:35,240 --> 00:31:37,320 Speaker 2: already beginning to roil whether around the world, may push 615 00:31:37,320 --> 00:31:40,880 Speaker 2: the monthly global temperature past This is monthly global average 616 00:31:40,880 --> 00:31:43,760 Speaker 2: temperature past two degrees celsius of warming for the first 617 00:31:43,760 --> 00:31:46,720 Speaker 2: time on record. That's according to projections published by the 618 00:31:46,800 --> 00:31:49,880 Speaker 2: University of Miami based Ocean and Atmospheric Research Center, two 619 00:31:49,920 --> 00:31:53,640 Speaker 2: degree celsius is around three point six degrees fahrenheit. Mark, 620 00:31:53,680 --> 00:31:56,000 Speaker 2: Why is this a metric that we watch closely? 621 00:31:58,000 --> 00:32:00,960 Speaker 7: When you say two degrees sell it doesn't sound like 622 00:32:01,040 --> 00:32:03,480 Speaker 7: much like a sixty eight degree day. Not doesn't feel 623 00:32:03,520 --> 00:32:05,240 Speaker 7: that much different to us than a seventy degree day. 624 00:32:05,240 --> 00:32:07,080 Speaker 7: But that's the wrong way of thinking about it. You're 625 00:32:07,080 --> 00:32:10,920 Speaker 7: talking about a global average temperature that includes everything from 626 00:32:11,400 --> 00:32:14,880 Speaker 7: the North Pole to a rock, okay, And so you 627 00:32:15,280 --> 00:32:18,120 Speaker 7: take all of that and you have an average surface temperature. 628 00:32:18,360 --> 00:32:22,000 Speaker 7: When that goes up by about four degrees fahrenheit, you 629 00:32:22,040 --> 00:32:25,959 Speaker 7: were talking about extremes going up by much more than that. 630 00:32:26,200 --> 00:32:29,720 Speaker 7: And when al Nino hits, it's hitting on a planet 631 00:32:30,000 --> 00:32:32,520 Speaker 7: that already is hotter by about one point three degrees 632 00:32:32,920 --> 00:32:35,800 Speaker 7: celsius or a little more than two degrees Fahrenheit's some 633 00:32:35,840 --> 00:32:38,880 Speaker 7: close to three degrees fahrenheit. And then you add on 634 00:32:38,920 --> 00:32:41,520 Speaker 7: top of that the heating effect that this hot water 635 00:32:41,600 --> 00:32:43,640 Speaker 7: in the Pacific, which is what al Nino is. It's 636 00:32:43,640 --> 00:32:46,080 Speaker 7: just hot water in the Pacific, but it affects the 637 00:32:46,160 --> 00:32:49,040 Speaker 7: jet stream and it affects temperatures around the world. And 638 00:32:49,080 --> 00:32:51,720 Speaker 7: what we saw with the last El Nino, which wasn't 639 00:32:51,720 --> 00:32:55,320 Speaker 7: even that hot. You know, it's just you measure the 640 00:32:55,320 --> 00:32:57,800 Speaker 7: strength of an alnino buy how hot the water it gets. Period. 641 00:32:58,440 --> 00:33:00,440 Speaker 7: It wasn't even that hot last time, but we got 642 00:33:00,520 --> 00:33:04,160 Speaker 7: record high temperatures of above one point five degrees celsius, 643 00:33:04,200 --> 00:33:06,360 Speaker 7: which used to be the stretch goal for the Paris 644 00:33:06,360 --> 00:33:08,440 Speaker 7: Climate Accords. That got blown out of the water and 645 00:33:09,160 --> 00:33:11,480 Speaker 7: it kind of went back down again, but not by 646 00:33:11,520 --> 00:33:13,120 Speaker 7: that much. So what you'd have is this sort of 647 00:33:13,200 --> 00:33:16,320 Speaker 7: ratcheting effect where it goes up during the El Nino 648 00:33:16,600 --> 00:33:19,120 Speaker 7: kind of stabilizes, but it really is plateauing rather than 649 00:33:19,160 --> 00:33:23,000 Speaker 7: going down. I hope that this two c forecast is wrong, 650 00:33:23,080 --> 00:33:26,840 Speaker 7: because that would be a really extreme measure to have 651 00:33:27,280 --> 00:33:31,480 Speaker 7: as soon as next year. It would certainly not last 652 00:33:31,480 --> 00:33:31,960 Speaker 7: that long. 653 00:33:32,520 --> 00:33:33,040 Speaker 1: It wouldn't. 654 00:33:33,200 --> 00:33:36,479 Speaker 7: When you talk about these target temperatures, you want them 655 00:33:36,520 --> 00:33:39,000 Speaker 7: to be long term averages rather than one month or so. 656 00:33:39,400 --> 00:33:42,640 Speaker 7: But two degrees celsius is again doesn't sound like much, 657 00:33:42,720 --> 00:33:45,920 Speaker 7: but it has tremendous effects on weather around the world. 658 00:33:46,360 --> 00:33:48,760 Speaker 3: But we've been talking about this right mark for a while, 659 00:33:48,840 --> 00:33:52,960 Speaker 3: so if indeed this holds, maybe tipping point isn't the 660 00:33:53,000 --> 00:33:55,520 Speaker 3: right thing to use. But that would be a very 661 00:33:55,560 --> 00:33:59,080 Speaker 3: significant thing when we think about climate and we think 662 00:33:59,120 --> 00:34:00,480 Speaker 3: about the future of our climate. 663 00:34:01,560 --> 00:34:04,480 Speaker 7: Yeah, I mean it's all significant. I mean, at the 664 00:34:04,560 --> 00:34:07,720 Speaker 7: same time we're talking about this. You just mentioned three 665 00:34:07,800 --> 00:34:10,080 Speaker 7: hundred and thirty thousand people had to be evacuated from 666 00:34:10,080 --> 00:34:13,640 Speaker 7: France and Spain because of these wildfires. Europe is under 667 00:34:13,640 --> 00:34:16,320 Speaker 7: its fourth heat wave and it doesn't have air conditioning, 668 00:34:16,320 --> 00:34:18,680 Speaker 7: as we've all discussed. The United States is under its 669 00:34:18,680 --> 00:34:22,760 Speaker 7: third heat dome of the season. Canada is on fire. 670 00:34:22,880 --> 00:34:25,680 Speaker 7: You have all of these emergencies happening as we speak, 671 00:34:25,719 --> 00:34:30,480 Speaker 7: and so these things can get worse. They can stabilize 672 00:34:30,520 --> 00:34:32,960 Speaker 7: if we make the right choices, but they can get worse. 673 00:34:32,960 --> 00:34:34,880 Speaker 7: And that's the thing when you talk about tipping points, 674 00:34:35,239 --> 00:34:39,080 Speaker 7: we don't fully understand what can happen when we start 675 00:34:39,120 --> 00:34:43,080 Speaker 7: to mess around with these global temperatures. Again, tiny increments 676 00:34:43,239 --> 00:34:46,239 Speaker 7: can make big differences, and even in the short term. 677 00:34:46,040 --> 00:34:47,919 Speaker 2: Mark, I want to just end shifting gears a little 678 00:34:47,920 --> 00:34:51,000 Speaker 2: bit to your latest column, and it's about the Ellisons 679 00:34:51,280 --> 00:34:54,880 Speaker 2: and the presidents what you call an anti Midas touch. 680 00:34:56,200 --> 00:34:58,319 Speaker 2: This is a little bit of a departure from what 681 00:34:58,520 --> 00:35:01,000 Speaker 2: you typically write about but talk to us a little 682 00:35:01,000 --> 00:35:04,360 Speaker 2: bit about I mean, Carol and I, you know, almost 683 00:35:04,360 --> 00:35:07,560 Speaker 2: a year ago were in California when Oracle stock reached 684 00:35:07,640 --> 00:35:09,919 Speaker 2: all time high and it's been on a steady state 685 00:35:10,000 --> 00:35:11,680 Speaker 2: down since then. You make the point in your piece 686 00:35:11,719 --> 00:35:13,759 Speaker 2: that it's gone nowhere since the president's inauguration. 687 00:35:14,600 --> 00:35:17,280 Speaker 7: Yeah, big round trip to nowhere. It's it's back below 688 00:35:17,320 --> 00:35:19,520 Speaker 7: where it was during the inauguration. And you would think 689 00:35:19,560 --> 00:35:22,800 Speaker 7: that nothing happened, but there was an enormous spike to 690 00:35:22,960 --> 00:35:26,279 Speaker 7: all time highs and then a big slow decline since then. 691 00:35:26,800 --> 00:35:29,320 Speaker 7: You know, I guess the Ellisons, I can't read their minds. 692 00:35:29,360 --> 00:35:34,360 Speaker 7: I assume that they thought embracing Donald Trump, who seemed 693 00:35:34,360 --> 00:35:36,480 Speaker 7: at the height of his powers coming back into office, 694 00:35:36,680 --> 00:35:38,720 Speaker 7: was going to help make them a lot more money. 695 00:35:39,520 --> 00:35:41,600 Speaker 7: And they did win, you know, a big seven billion 696 00:35:41,600 --> 00:35:45,719 Speaker 7: dollars Pentagon contract. Larry Elson's kind of running TikTok. They 697 00:35:45,760 --> 00:35:48,759 Speaker 7: got the Paramount deal done. Now they're almost about to 698 00:35:48,760 --> 00:35:51,239 Speaker 7: get this Warner Brothers deal done. In the meantime, this 699 00:35:51,320 --> 00:35:54,240 Speaker 7: AI spending issue has been chipping away at Oracles stock 700 00:35:54,680 --> 00:35:58,920 Speaker 7: and at its debt. It's debt trades that jump lew. Yeah, Pount, 701 00:35:58,960 --> 00:36:01,600 Speaker 7: the paramount. Warner brother deal has been postponed, and they've 702 00:36:01,600 --> 00:36:03,279 Speaker 7: got six hundred and fifty million a quarter. 703 00:36:03,480 --> 00:36:08,640 Speaker 2: Check out, check out Gonegloff's column Bloomberg Opinion at OPI, 704 00:36:08,760 --> 00:36:10,360 Speaker 2: and go on the terminal. This is Bloomberg. 705 00:36:11,480 --> 00:36:16,960 Speaker 1: This is the Bloomberg Business Weekdaily podcast, available on Apple, Spotify, 706 00:36:17,080 --> 00:36:21,160 Speaker 1: and anywhere else you get your podcasts. Listen live weekday 707 00:36:21,200 --> 00:36:25,360 Speaker 1: afternoons from two to five pm Eastern on Bloomberg dot Com, 708 00:36:25,480 --> 00:36:29,320 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business App. 709 00:36:29,480 --> 00:36:32,360 Speaker 1: You can also watch us live every weekday on YouTube 710 00:36:32,600 --> 00:36:34,760 Speaker 1: and always on the Bloomberg Terminal