1 00:00:00,080 --> 00:00:12,879 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. This is the Bloomberg 2 00:00:12,960 --> 00:00:16,960 Speaker 1: Surveillance Podcast. I'm Tom Keene along with Paul Sweeney. Join 3 00:00:17,040 --> 00:00:21,000 Speaker 1: us each day for insight from the best in economics, finance, investment, 4 00:00:21,200 --> 00:00:24,840 Speaker 1: and international relations. You can also watch the show live 5 00:00:25,079 --> 00:00:29,400 Speaker 1: on YouTube. Visit the Bloomberg Podcast channel on YouTube to 6 00:00:29,520 --> 00:00:32,920 Speaker 1: see the show weekday mornings from seven to ten am 7 00:00:32,960 --> 00:00:37,000 Speaker 1: Eastern from our global headquarters in New York City. Subscribe 8 00:00:37,000 --> 00:00:40,760 Speaker 1: to the podcast on Apple, Spotify, or anywhere else you listen, 9 00:00:41,080 --> 00:00:44,720 Speaker 1: and always I'm Bloomberg Radio, the Bloomberg Terminal, and the 10 00:00:44,760 --> 00:00:48,520 Speaker 1: Bloomberg Business App. It's been a great honor to know him, 11 00:00:48,720 --> 00:00:51,440 Speaker 1: his public commitment to the United States from coming out 12 00:00:51,440 --> 00:00:54,680 Speaker 1: of San Diego. Is a young buck out of Annapolis. 13 00:00:54,760 --> 00:00:58,000 Speaker 1: James Travetus joins us now and addmirl and of course 14 00:00:58,040 --> 00:01:02,840 Speaker 1: his work Carlisle is noted Emeralds Tavitas. I want to 15 00:01:02,880 --> 00:01:05,000 Speaker 1: get down to the granular because I don't think enough 16 00:01:05,040 --> 00:01:09,440 Speaker 1: of the granulars talked. Somebody has to pay for a 17 00:01:09,560 --> 00:01:15,080 Speaker 1: Magura V five drone so it can sink a modestized 18 00:01:15,120 --> 00:01:19,640 Speaker 1: ship of the Russian Navy. Is Washington saying to Ukraine 19 00:01:19,680 --> 00:01:23,160 Speaker 1: as a generalization that we're not going to pay for 20 00:01:23,280 --> 00:01:27,520 Speaker 1: a Magura V five drone or whatever so that we 21 00:01:27,600 --> 00:01:28,360 Speaker 1: can assist you. 22 00:01:29,480 --> 00:01:32,520 Speaker 2: Yeah, that's the message being delivered to Kiev right now. 23 00:01:32,840 --> 00:01:37,560 Speaker 2: It's immensely frustrating to anybody who cares about the security 24 00:01:37,560 --> 00:01:41,200 Speaker 2: of the country. Tom And it's not just drones, it's 25 00:01:41,400 --> 00:01:46,480 Speaker 2: artillery shells, it's eight tacums long range missiles, it's getting 26 00:01:46,080 --> 00:01:51,440 Speaker 2: the F sixteens onto the battlefield. All of that, we 27 00:01:51,560 --> 00:01:56,320 Speaker 2: are failing the cause of freedom. Final thought, it's sixty 28 00:01:56,360 --> 00:02:01,120 Speaker 2: billion dollars. That's okay an amount of money. Our defense 29 00:02:01,160 --> 00:02:05,400 Speaker 2: budget is nine hundred billion dollars. So for five percent 30 00:02:05,440 --> 00:02:08,320 Speaker 2: of our defense budget we break the Russian armed forces 31 00:02:08,400 --> 00:02:11,840 Speaker 2: defeat Vladimir Putin. There's a business show that sounds like 32 00:02:11,880 --> 00:02:13,639 Speaker 2: a pretty good ROI to me. 33 00:02:14,360 --> 00:02:17,920 Speaker 1: How close are we to lend lease or before lend 34 00:02:17,960 --> 00:02:23,520 Speaker 1: Lea's nineteen thirty eight, nineteen thirty nine, we're basically isolationists. 35 00:02:23,680 --> 00:02:26,880 Speaker 1: America said we don't want to participate at that time 36 00:02:27,200 --> 00:02:30,280 Speaker 1: in a European war. Is this just nothing more than 37 00:02:30,320 --> 00:02:33,400 Speaker 1: an isolationist debate of a global America? 38 00:02:34,400 --> 00:02:35,079 Speaker 3: I think it is. 39 00:02:35,200 --> 00:02:38,680 Speaker 2: It feels eerily like the nineteen thirties. Go back and 40 00:02:38,720 --> 00:02:44,200 Speaker 2: read the first volume of Winston Churchill's magisterial six volume 41 00:02:44,400 --> 00:02:48,519 Speaker 2: set the Second World War. It's called The Gathering Storm. 42 00:02:49,000 --> 00:02:50,200 Speaker 2: That's what it feels like. 43 00:02:50,160 --> 00:02:51,960 Speaker 1: To me, and it feels like to me folks if 44 00:02:52,000 --> 00:02:53,680 Speaker 1: you want to read it, particularly the kids out there. 45 00:02:53,680 --> 00:02:57,480 Speaker 1: Warren Remembrance Hermann Valuk, which is just shocking on nineteen 46 00:02:57,520 --> 00:03:00,160 Speaker 1: thirty eight, is a fiction. Paul jump in here, withever. 47 00:03:00,680 --> 00:03:03,160 Speaker 4: Admiral, can you give us, based upon your sourcing kind 48 00:03:03,200 --> 00:03:07,000 Speaker 4: of the latest on the battlefield in Ukraine today? 49 00:03:07,960 --> 00:03:13,519 Speaker 2: I can no surprise as supplies dwindle to the Ukrainians. 50 00:03:13,880 --> 00:03:18,520 Speaker 2: It puts real lift in the Russian armed forces, so 51 00:03:18,560 --> 00:03:22,440 Speaker 2: they're moving forward. It's not yet the end of the 52 00:03:22,520 --> 00:03:26,320 Speaker 2: road for Ukraine, but you can feel the wind behind 53 00:03:26,360 --> 00:03:29,919 Speaker 2: the sales of Vladimir Putin. And by the way, it's 54 00:03:29,960 --> 00:03:35,000 Speaker 2: all connected to his arrogance, his impunity and killing Alexander 55 00:03:35,120 --> 00:03:38,920 Speaker 2: Navalni over the last few days. All of this is 56 00:03:38,960 --> 00:03:42,240 Speaker 2: giving real lyft on the battlefield to the Russians. We 57 00:03:42,440 --> 00:03:45,880 Speaker 2: better get this military aid to the Ukrainians or we're 58 00:03:45,880 --> 00:03:48,640 Speaker 2: going to see more losses and the hole that's being 59 00:03:48,800 --> 00:03:52,680 Speaker 2: dug will be much harder to get out of, Admiral. 60 00:03:52,720 --> 00:03:56,320 Speaker 4: I think most students of history take away that boy. 61 00:03:56,480 --> 00:04:00,400 Speaker 4: The Russian people, the Russian army can take un told 62 00:04:00,400 --> 00:04:04,080 Speaker 4: amounts of pain and time. Is there any sense that 63 00:04:04,760 --> 00:04:08,160 Speaker 4: Russia will bend here at all other than you know, 64 00:04:08,240 --> 00:04:10,720 Speaker 4: I guess superior military. 65 00:04:11,320 --> 00:04:15,800 Speaker 2: I think it's going to require a continued significant aid 66 00:04:15,880 --> 00:04:16,640 Speaker 2: from the West. 67 00:04:16,839 --> 00:04:20,000 Speaker 3: And yes, Russians can take a lot of pain. 68 00:04:20,080 --> 00:04:22,520 Speaker 2: Go back and read One Day in the Life of 69 00:04:22,560 --> 00:04:26,880 Speaker 2: Ivan Denisovich by the Nobel Laureate Alexander Solzanis. 70 00:04:26,920 --> 00:04:28,520 Speaker 3: It's someone in goolag. 71 00:04:28,839 --> 00:04:32,760 Speaker 2: These are tough people, and Putin is a tough long 72 00:04:32,880 --> 00:04:36,880 Speaker 2: range player, but his soldiers are dying. 73 00:04:37,000 --> 00:04:38,640 Speaker 3: In the hundreds of thousands. 74 00:04:39,400 --> 00:04:42,600 Speaker 2: Hundreds of thousands of young men have departed the country 75 00:04:42,680 --> 00:04:45,839 Speaker 2: Russia to avoid the draft long term. It's not a 76 00:04:45,839 --> 00:04:48,520 Speaker 2: good hand of cards. We just need to keep our 77 00:04:48,560 --> 00:04:50,080 Speaker 2: foot on the accelerator. 78 00:04:50,839 --> 00:04:54,800 Speaker 1: James Trevitis with US the former NATO Supreme Commander program 79 00:04:54,839 --> 00:04:58,839 Speaker 1: Note here the new Foreign Affairs magazine is extraordinary. Neil Ferguson, 80 00:04:59,360 --> 00:05:04,200 Speaker 1: the and controversial historian, with a definitive essay there on 81 00:05:04,400 --> 00:05:07,680 Speaker 1: just what the Edmund was talking about. Which is the 82 00:05:07,760 --> 00:05:10,520 Speaker 1: detent the new kind of theme that's out there of 83 00:05:10,560 --> 00:05:14,479 Speaker 1: a Kissinger realist policy versus whatever the new policy is 84 00:05:14,480 --> 00:05:16,960 Speaker 1: that we're making up as we go. I want to 85 00:05:16,960 --> 00:05:20,160 Speaker 1: go to our conversation Admiral on Bloomberg surveillance moments ago 86 00:05:20,360 --> 00:05:23,839 Speaker 1: with a member of the Biden administration, and John Farrell 87 00:05:23,960 --> 00:05:28,279 Speaker 1: asked the money question, what about India? I have hockey 88 00:05:28,360 --> 00:05:33,719 Speaker 1: stick charts of exports from Kazakhstan in India into Russia. 89 00:05:34,360 --> 00:05:39,720 Speaker 1: What is our political and military leverage with mister Mody 90 00:05:39,800 --> 00:05:41,640 Speaker 1: as he faces a new election. 91 00:05:43,160 --> 00:05:45,960 Speaker 2: First, let's let him get through his election. You know, 92 00:05:46,120 --> 00:05:49,120 Speaker 2: nine hundred million people literally are going to go to 93 00:05:49,160 --> 00:05:51,000 Speaker 2: the polls and vote in India. 94 00:05:51,080 --> 00:05:55,239 Speaker 3: I think he'll win a strong, strong poll. 95 00:05:55,800 --> 00:05:59,320 Speaker 2: Then he'll come back with real confidence in his third term. 96 00:05:59,680 --> 00:06:02,200 Speaker 2: I think that's when we can go to him off 97 00:06:02,200 --> 00:06:05,839 Speaker 2: stage and say, what will it take? Can we pull 98 00:06:05,920 --> 00:06:09,919 Speaker 2: you away from this support line you are providing to Russia? 99 00:06:09,960 --> 00:06:12,240 Speaker 3: You're right, Tom, India is the key. 100 00:06:12,480 --> 00:06:16,680 Speaker 2: China is going to continue to support Putin. India is 101 00:06:16,720 --> 00:06:18,800 Speaker 2: the swing vote here we need to focus on. 102 00:06:18,920 --> 00:06:21,120 Speaker 1: Okay, I'm going to go there, folks. You're gonna rip 103 00:06:21,160 --> 00:06:24,279 Speaker 1: up the scripture with James Trubus. Ramatana Guoh's, a definitive 104 00:06:24,320 --> 00:06:30,400 Speaker 1: Gandhi biographer, has a blistering essay here begging the United 105 00:06:30,400 --> 00:06:34,600 Speaker 1: States to impart its policy over to India. Is they 106 00:06:34,640 --> 00:06:38,800 Speaker 1: actually become somewhat dominant with the struggling China. Do we 107 00:06:38,839 --> 00:06:42,040 Speaker 1: have any military presence over there, Admiral? Do we exist 108 00:06:42,520 --> 00:06:46,760 Speaker 1: in the Indian Sea of the South whatever this ocean 109 00:06:46,880 --> 00:06:50,039 Speaker 1: is there from South Africa Durban on the way over 110 00:06:50,200 --> 00:06:51,479 Speaker 1: to Indonesia. 111 00:06:52,400 --> 00:06:56,120 Speaker 2: Yeah, Tom, that would be the Indian Ocean, the largest ocean. 112 00:06:56,279 --> 00:06:59,240 Speaker 1: That's why I will you were on the boat and 113 00:06:59,360 --> 00:07:00,919 Speaker 1: I was driving the taxicab. 114 00:07:01,960 --> 00:07:06,560 Speaker 2: So we have a strong level of presence there because 115 00:07:06,680 --> 00:07:09,480 Speaker 2: we sail through it both from the Pacific side and 116 00:07:09,680 --> 00:07:13,480 Speaker 2: from the Red Sea side into the Arabian Gulf. We 117 00:07:13,640 --> 00:07:16,480 Speaker 2: could do a lot more militarily with the Indians and 118 00:07:16,600 --> 00:07:20,520 Speaker 2: the Indian military. I assure you would like to come 119 00:07:20,960 --> 00:07:24,400 Speaker 2: more into focus with the United States by more of 120 00:07:24,520 --> 00:07:28,760 Speaker 2: our systems. For decades they've been reliant on Russia. That's 121 00:07:28,880 --> 00:07:32,880 Speaker 2: another piece of this. If we can insert US military 122 00:07:32,960 --> 00:07:36,360 Speaker 2: cooperation with our Indian colleagues, I think we would go 123 00:07:36,520 --> 00:07:39,040 Speaker 2: a long way toward pulling India in our direction. 124 00:07:39,520 --> 00:07:43,080 Speaker 4: Ada, Well, let's pivot slightly to the Middle East. Boy, 125 00:07:43,720 --> 00:07:47,040 Speaker 4: talk about another challenging situation there. What is your most 126 00:07:47,160 --> 00:07:49,440 Speaker 4: up to date view of how this is playing out 127 00:07:49,840 --> 00:07:51,520 Speaker 4: as likely to play out over the coming weeks. 128 00:07:52,800 --> 00:07:57,840 Speaker 2: Humanitarian crisis most obviously hostages on top of it, that 129 00:07:58,560 --> 00:08:01,920 Speaker 2: is going to continue to fester for probably two to 130 00:08:02,080 --> 00:08:07,080 Speaker 2: three more months while the Israelis fully consolidate control. They're 131 00:08:07,280 --> 00:08:12,040 Speaker 2: trying to reduce collateral damage. They're succeeding somewhat in doing so. 132 00:08:13,120 --> 00:08:16,320 Speaker 2: That frame is going to freeze in two to three months, 133 00:08:16,360 --> 00:08:19,480 Speaker 2: than a peacekeeping force will come in. Things will de 134 00:08:19,680 --> 00:08:22,720 Speaker 2: accelerate at that point. The one I'm watching from an 135 00:08:22,760 --> 00:08:26,800 Speaker 2: investment perspective are the attacks the Red Sea the potential 136 00:08:26,880 --> 00:08:30,280 Speaker 2: effective closure of the Suez Canal by the Hoothys. 137 00:08:30,560 --> 00:08:31,720 Speaker 3: We're going to need to put. 138 00:08:31,680 --> 00:08:37,840 Speaker 2: More military missiles on targets ashore in order to stop 139 00:08:38,000 --> 00:08:40,800 Speaker 2: that and keep the global commerce open. 140 00:08:41,120 --> 00:08:43,280 Speaker 3: Those are the two main things I'm watching. 141 00:08:43,520 --> 00:08:46,680 Speaker 4: Are you surprised that maybe we haven't had more success 142 00:08:47,200 --> 00:08:51,240 Speaker 4: in that area in gaining greater control over the Red 143 00:08:51,320 --> 00:08:52,600 Speaker 4: Sea and its shipping lanes. 144 00:08:53,520 --> 00:08:59,600 Speaker 2: I'm not surprised, simply because Iran continues to refuel, recharge, organize, 145 00:08:59,640 --> 00:09:03,680 Speaker 2: training and equip. The houthis right now, we're striking Kuthy 146 00:09:03,840 --> 00:09:04,720 Speaker 2: targets ashore. 147 00:09:05,240 --> 00:09:06,840 Speaker 3: If Iran does not get the. 148 00:09:06,920 --> 00:09:09,760 Speaker 2: Message to cease and desist, we're going to have to 149 00:09:09,840 --> 00:09:15,920 Speaker 2: start going after Iranian maritime targets, their ships, their warships, 150 00:09:16,080 --> 00:09:19,880 Speaker 2: their platforms. I hope we don't get there, but that 151 00:09:20,080 --> 00:09:22,520 Speaker 2: message has to get to Tayron. It's not going to 152 00:09:22,559 --> 00:09:24,440 Speaker 2: get solved in Yemen, Edmirald, with. 153 00:09:24,559 --> 00:09:28,440 Speaker 1: Great respect to the British, their ships can't get out 154 00:09:28,480 --> 00:09:31,320 Speaker 1: of the harbor. I mean, I'm not going to mince words. 155 00:09:31,320 --> 00:09:34,160 Speaker 1: And we have a prime Minister out of Southampton with 156 00:09:34,320 --> 00:09:37,640 Speaker 1: all that heritage, our pride going and this goes to 157 00:09:37,720 --> 00:09:41,599 Speaker 1: the Admirals Book of Stravetas. I'm so sorry. Remind me 158 00:09:41,600 --> 00:09:43,400 Speaker 1: of the name of your book where you line up 159 00:09:43,440 --> 00:09:45,080 Speaker 1: ten admirals in a row. 160 00:09:45,920 --> 00:09:47,880 Speaker 3: It's called Sailing True North. 161 00:09:48,040 --> 00:09:50,920 Speaker 1: Sailing True North. Rickover sail True North because he had 162 00:09:50,960 --> 00:09:55,000 Speaker 1: a budget. Zoom, weall sail True North because he had 163 00:09:55,040 --> 00:09:58,079 Speaker 1: a budget. Does our present navy have a budget? Are 164 00:09:58,120 --> 00:10:01,000 Speaker 1: we going to be stuck in Southampton or Portsmouth like 165 00:10:01,080 --> 00:10:02,839 Speaker 1: the British Navy? Yeah? 166 00:10:02,960 --> 00:10:07,959 Speaker 2: On a scale that runs from the British challenges you're 167 00:10:08,000 --> 00:10:12,640 Speaker 2: talking about, which are very real, to a fully sourced 168 00:10:13,000 --> 00:10:16,880 Speaker 2: US Navy that can undertake its global mission. We're about 169 00:10:17,040 --> 00:10:19,400 Speaker 2: three quarters of the way to where we should be, 170 00:10:19,720 --> 00:10:22,880 Speaker 2: meaning we have about three hundred warships. I'll put it 171 00:10:22,880 --> 00:10:25,880 Speaker 2: in really round numbers. We need about three hundred and 172 00:10:26,040 --> 00:10:29,959 Speaker 2: fifty warships that would match what China has. China has 173 00:10:30,040 --> 00:10:32,199 Speaker 2: the largest fleet in the world. If you ask me, 174 00:10:32,280 --> 00:10:34,920 Speaker 2: as an admiral, which fleet would I rather have in 175 00:10:35,040 --> 00:10:38,000 Speaker 2: a fight, I'd still take the American fleet because of 176 00:10:38,080 --> 00:10:41,520 Speaker 2: our experience, our nuclear carriers, our submarine technology. 177 00:10:41,920 --> 00:10:44,120 Speaker 3: But that edge we have is dwindling. 178 00:10:44,240 --> 00:10:44,440 Speaker 4: Tom. 179 00:10:44,840 --> 00:10:48,080 Speaker 2: We need to put emphasis on the maritime because everything 180 00:10:48,200 --> 00:10:51,559 Speaker 2: we've talked about goes back to the sea and the 181 00:10:51,720 --> 00:10:55,000 Speaker 2: oceans and the ability to keep global commerce moving. 182 00:10:55,280 --> 00:10:57,840 Speaker 4: And that's the subject of a recent column of yours. Admiral. 183 00:10:57,960 --> 00:11:01,319 Speaker 4: Russia's new threat is under not in space. Can you 184 00:11:01,360 --> 00:11:01,800 Speaker 4: explain that. 185 00:11:02,760 --> 00:11:05,920 Speaker 2: Yeah, we had a week where we were all shocked 186 00:11:06,080 --> 00:11:11,000 Speaker 2: to hear from the intelligence community that Russia's thinking about 187 00:11:11,040 --> 00:11:12,760 Speaker 2: putting a nuclear weapon in space. 188 00:11:13,120 --> 00:11:16,080 Speaker 3: That would be bad. They haven't done it yet. They 189 00:11:16,120 --> 00:11:17,880 Speaker 3: don't really have that technology. 190 00:11:18,000 --> 00:11:20,800 Speaker 2: Yet what they do have is the ability to disrupt 191 00:11:21,120 --> 00:11:26,319 Speaker 2: underwater cables that carry the entire Internet. Only five hundred 192 00:11:26,400 --> 00:11:31,040 Speaker 2: cables carried the entire global Internet, all the commerce ten 193 00:11:31,120 --> 00:11:33,760 Speaker 2: trillion transactions a day. 194 00:11:34,400 --> 00:11:37,200 Speaker 3: Those are vulnerable targets on the bottom of the sea. 195 00:11:37,559 --> 00:11:39,320 Speaker 3: Russia could go after them today. 196 00:11:39,800 --> 00:11:42,960 Speaker 1: I have to end with a delicate question in given 197 00:11:43,040 --> 00:11:46,479 Speaker 1: his public service for all Americans, whatever their political persuasion, 198 00:11:46,559 --> 00:11:51,120 Speaker 1: it's delicate. Should the Secretary of Defense Admiral's so ill? 199 00:11:51,960 --> 00:11:52,800 Speaker 1: Should he resign? 200 00:11:54,600 --> 00:11:58,200 Speaker 2: He should do what his health demands. If he has 201 00:11:58,280 --> 00:12:01,120 Speaker 2: the health and the vigor to act as Secretary of Defense. 202 00:12:01,559 --> 00:12:06,160 Speaker 2: Lloyd Austin, a contemporary of mine, he should remain in 203 00:12:06,440 --> 00:12:09,040 Speaker 2: office as long as his health permits. 204 00:12:09,600 --> 00:12:12,120 Speaker 1: James Trevitis, thank you so much. Can't say enough about 205 00:12:12,200 --> 00:12:15,640 Speaker 1: Leader's bookshelf. It's just one of my favorite favorite books. 206 00:12:15,679 --> 00:12:18,040 Speaker 1: I'll put that out here in the blur today is 207 00:12:18,080 --> 00:12:21,560 Speaker 1: well the former Supreme NATO commander. Just a terrific brief 208 00:12:21,600 --> 00:12:34,920 Speaker 1: there joining us now the tennis player from Princeton, Andrew 209 00:12:34,960 --> 00:12:37,880 Speaker 1: Howsby here on the economics of the moments of a 210 00:12:37,960 --> 00:12:40,559 Speaker 1: small French trin do you get, Andrew? I'm going to 211 00:12:40,640 --> 00:12:42,680 Speaker 1: cut to the chase. Forget about the b MP Perry 212 00:12:42,720 --> 00:12:46,720 Speaker 1: By US Open tickets. Are you over in Paris at 213 00:12:46,760 --> 00:12:49,800 Speaker 1: the best tennis court in the world. Are you watching 214 00:12:50,040 --> 00:12:54,480 Speaker 1: out of the BMP perry By box the French Open 215 00:12:54,640 --> 00:12:56,400 Speaker 1: with a just gorgeous green that they have. 216 00:12:58,880 --> 00:13:03,559 Speaker 5: Unfortunately, Tom, I'm not but certainly missing out on that 217 00:13:03,640 --> 00:13:04,400 Speaker 5: experience right now. 218 00:13:04,640 --> 00:13:07,800 Speaker 1: It's great. I wandered into the courts one day when 219 00:13:07,840 --> 00:13:10,440 Speaker 1: I was like fifteen years old. It's like magical, It's 220 00:13:10,480 --> 00:13:13,679 Speaker 1: like surreal. Would be of us in Carl Ricadonna, Andrew 221 00:13:13,760 --> 00:13:16,719 Speaker 1: Husby with us this morning. Andrew, Paul and I have 222 00:13:17,000 --> 00:13:20,400 Speaker 1: completely ignored the parlor game. Give us an update on 223 00:13:20,520 --> 00:13:23,000 Speaker 1: what you believe this FED would do? 224 00:13:26,080 --> 00:13:28,800 Speaker 5: Sure well, thanks Tom So. At the moment, we think 225 00:13:29,240 --> 00:13:31,040 Speaker 5: this is a FED and we're hearing it in the 226 00:13:31,080 --> 00:13:34,360 Speaker 5: FED speak we've seen really since the December meeting, this 227 00:13:34,559 --> 00:13:37,920 Speaker 5: is a FED that is very cautious about cutting too 228 00:13:38,040 --> 00:13:41,200 Speaker 5: early here coming into this year. Think about the narrative. 229 00:13:41,520 --> 00:13:43,000 Speaker 5: A lot of folks were thinking we might get a 230 00:13:43,040 --> 00:13:46,040 Speaker 5: cut as soon as March, maybe even January, but the 231 00:13:46,120 --> 00:13:50,280 Speaker 5: narrative is really shifted here. Our team did not subscribe 232 00:13:50,320 --> 00:13:53,560 Speaker 5: to the March cut view. Yes, we had been up 233 00:13:53,640 --> 00:13:57,240 Speaker 5: until last year, been up until last week rather been 234 00:13:57,440 --> 00:14:00,880 Speaker 5: in the May camp. But we do think the January 235 00:14:00,960 --> 00:14:06,040 Speaker 5: CPI report, along with the accumulation of stronger data, really 236 00:14:06,360 --> 00:14:08,040 Speaker 5: does make us think that the Fed is going to 237 00:14:08,080 --> 00:14:09,880 Speaker 5: move even a bit later than that. So we think 238 00:14:10,240 --> 00:14:13,720 Speaker 5: ultimately it will be a June cut and a shallower 239 00:14:13,840 --> 00:14:16,280 Speaker 5: path this year of cuts than we had previously envisioned. 240 00:14:16,320 --> 00:14:18,319 Speaker 5: We see about one hundred basis points of cuts this 241 00:14:18,480 --> 00:14:22,760 Speaker 5: year as the FED kind of eyes again the stronger 242 00:14:22,800 --> 00:14:27,160 Speaker 5: inflation backdrop and most importantly, a stronger economic growth backdrop, 243 00:14:27,240 --> 00:14:29,920 Speaker 5: which you know, there's an argument to be made that 244 00:14:30,400 --> 00:14:33,480 Speaker 5: stronger growth itself can be disinflationary if the supply side 245 00:14:33,520 --> 00:14:36,240 Speaker 5: is coming back, but it's hard to bet too strongly 246 00:14:36,320 --> 00:14:38,880 Speaker 5: on that. So we think in that environment, the FED 247 00:14:38,960 --> 00:14:39,840 Speaker 5: stays pretty cautious. 248 00:14:39,840 --> 00:14:39,960 Speaker 2: Here. 249 00:14:40,080 --> 00:14:42,800 Speaker 1: Well, what's so important here, folks, is the overlay of stimulus. 250 00:14:43,120 --> 00:14:46,080 Speaker 1: Are we through the stimulus? Because I've had whispers this week. 251 00:14:46,560 --> 00:14:49,920 Speaker 1: You know, I'm sorry, Andrew, we're distracted with Nvidia. I apologize, 252 00:14:50,400 --> 00:14:54,560 Speaker 1: but with it, and Andrew, are we beyond the stimulus? 253 00:14:54,920 --> 00:14:55,840 Speaker 1: I'm not so sure. 254 00:14:58,720 --> 00:15:02,280 Speaker 5: It doesn't feel like it's all fully run off, whether 255 00:15:02,360 --> 00:15:06,560 Speaker 5: you're thinking about the excess savings built up over the pandemic, Yes, 256 00:15:06,640 --> 00:15:08,440 Speaker 5: a lot of that is run down, but you look 257 00:15:08,480 --> 00:15:12,040 Speaker 5: at the after effects on say the equity market, there's 258 00:15:12,080 --> 00:15:17,240 Speaker 5: a tendant wealth effect still coming through there. And as 259 00:15:17,280 --> 00:15:20,480 Speaker 5: we're looking ahead to you know, just again where deficits are, 260 00:15:20,920 --> 00:15:23,360 Speaker 5: they're still high. And as we come look ahead to 261 00:15:23,400 --> 00:15:26,600 Speaker 5: the election, you're still looking at potential catalysts that could 262 00:15:26,640 --> 00:15:31,360 Speaker 5: catalyze a more expansionary fiscal policy after the election too. 263 00:15:31,480 --> 00:15:34,000 Speaker 5: So all of that suggests, you know, it certainly hasn't 264 00:15:34,080 --> 00:15:35,400 Speaker 5: all run out just yet. 265 00:15:35,840 --> 00:15:38,680 Speaker 4: Hey, Andrew, I think since the January inflation data, the 266 00:15:38,760 --> 00:15:41,440 Speaker 4: CPI and a PPI data came out, we've actually had 267 00:15:41,520 --> 00:15:44,040 Speaker 4: some people come into the studio and say, hey, you 268 00:15:44,280 --> 00:15:47,360 Speaker 4: have to have in your scenario analysis a scenario where 269 00:15:47,400 --> 00:15:50,720 Speaker 4: the Fed actually hikes rates this year. What do you 270 00:15:50,760 --> 00:15:51,160 Speaker 4: think about that? 271 00:15:53,480 --> 00:15:55,920 Speaker 5: Yeah, so, certainly at the moment, you know, we're thinking 272 00:15:57,080 --> 00:16:01,280 Speaker 5: that sort of a scenario involves the just staying on 273 00:16:01,480 --> 00:16:05,560 Speaker 5: hold for longer unless we really think that the so 274 00:16:05,760 --> 00:16:09,080 Speaker 5: called neutral rate in the economy is really substantially higher 275 00:16:09,120 --> 00:16:12,720 Speaker 5: and really remains substantially higher for this year next year. 276 00:16:13,560 --> 00:16:16,320 Speaker 5: You know, it still feels as though policy is restrictive. 277 00:16:16,400 --> 00:16:18,880 Speaker 5: We're seeing it in the data flow. We're seeing it, 278 00:16:19,760 --> 00:16:22,880 Speaker 5: certainly in the inflation data itself. Inflation has come down 279 00:16:23,040 --> 00:16:25,720 Speaker 5: pretty substantially, so it tells us that things are moving 280 00:16:26,080 --> 00:16:28,920 Speaker 5: in the right direction. But certainly, you know, could the 281 00:16:28,960 --> 00:16:32,360 Speaker 5: Fed hike again. You can entertain scenarios, but that's far 282 00:16:32,480 --> 00:16:34,560 Speaker 5: from our base case at the moment. Again, we're focused 283 00:16:34,560 --> 00:16:38,640 Speaker 5: on duration at the current level, not added hikes. 284 00:16:38,840 --> 00:16:41,800 Speaker 4: So how about the one of the aspects of this 285 00:16:41,920 --> 00:16:44,200 Speaker 4: economy that continues to amaze me as the labor market. 286 00:16:44,320 --> 00:16:48,440 Speaker 4: How strong the labor market remains. Some are saying that 287 00:16:48,520 --> 00:16:51,080 Speaker 4: the Fed really needs to see the unemployment rate, you know, 288 00:16:51,160 --> 00:16:53,880 Speaker 4: maybe move above four percent, maybe four and a half percent. 289 00:16:54,760 --> 00:16:56,640 Speaker 4: How are you guys thinking about this US labor market. 290 00:16:58,640 --> 00:17:02,760 Speaker 5: Yeah, it's been surprised both in terms of the strength 291 00:17:02,840 --> 00:17:04,760 Speaker 5: we saw in the last two jobs reports, are seeing 292 00:17:04,840 --> 00:17:08,000 Speaker 5: job growth above three hundred thousand a month, and it's 293 00:17:08,080 --> 00:17:10,760 Speaker 5: also surprising in that some of the revisions we've seen 294 00:17:10,840 --> 00:17:13,400 Speaker 5: kind of reshape the path. So not only is recent 295 00:17:13,480 --> 00:17:15,399 Speaker 5: job growth stronger, but it was stronger at the end 296 00:17:15,400 --> 00:17:18,600 Speaker 5: of last year, and that's meant more income more spending 297 00:17:18,640 --> 00:17:20,800 Speaker 5: and the like. Now the question for us, you know, 298 00:17:20,840 --> 00:17:24,160 Speaker 5: when you look at factors like labor supply, we've seen 299 00:17:24,200 --> 00:17:28,960 Speaker 5: a pretty substantial rebound in labor supply, and recently even 300 00:17:29,000 --> 00:17:31,240 Speaker 5: the CBO had come out with a report saying, actually 301 00:17:31,320 --> 00:17:34,760 Speaker 5: the labor force potential labor force is actually potentially much 302 00:17:34,840 --> 00:17:38,000 Speaker 5: larger on account of immigration and the like. So you know, 303 00:17:38,160 --> 00:17:41,000 Speaker 5: to us it says strong job growth. It's in part 304 00:17:41,080 --> 00:17:44,320 Speaker 5: a function of businesses being a bit more confident as 305 00:17:44,560 --> 00:17:48,160 Speaker 5: recession risk has faded, as the risk of further FED 306 00:17:48,240 --> 00:17:51,360 Speaker 5: hikes has faded, so there's an incentive to potentially hire 307 00:17:51,359 --> 00:17:51,960 Speaker 5: a bit more here. 308 00:17:52,800 --> 00:17:55,920 Speaker 1: Yeah, go ahead, Well, I mean to go ahead, but 309 00:17:56,000 --> 00:17:59,320 Speaker 1: the research node is extraordinary. I mean the ricodonic, you know, 310 00:17:59,440 --> 00:18:02,320 Speaker 1: the concision of what Husby's doing with Rick and Donna 311 00:18:02,320 --> 00:18:06,399 Speaker 1: and the team over there is extraordinary. Into the weekend, Andrew, 312 00:18:06,880 --> 00:18:09,920 Speaker 1: what's the item of inflation that we need to think 313 00:18:09,960 --> 00:18:14,080 Speaker 1: about when you sort out X number of components? What's 314 00:18:14,160 --> 00:18:16,480 Speaker 1: the one year watching into March? 315 00:18:19,640 --> 00:18:21,679 Speaker 5: So at the moment, you know, I know it's been 316 00:18:21,800 --> 00:18:23,760 Speaker 5: a refrain for some time now, but it is really 317 00:18:23,840 --> 00:18:28,199 Speaker 5: that services number x X. Housing. We've seen a lot 318 00:18:28,240 --> 00:18:30,480 Speaker 5: of progress on goods. We expect that to continue through 319 00:18:30,480 --> 00:18:32,760 Speaker 5: the first part of this year. But we think that 320 00:18:32,840 --> 00:18:37,040 Speaker 5: there is a relationship between labor slack and that core 321 00:18:37,119 --> 00:18:40,359 Speaker 5: services component of inflation, and in the January report that 322 00:18:40,640 --> 00:18:43,320 Speaker 5: was quite strong pointing to you know, there may be 323 00:18:43,440 --> 00:18:46,840 Speaker 5: some quirks here. It's the start of the year, businesses 324 00:18:46,920 --> 00:18:48,640 Speaker 5: reset prices and the like, so we'll need to see 325 00:18:48,640 --> 00:18:51,240 Speaker 5: a few more reports here to really be thinking about 326 00:18:51,240 --> 00:18:53,960 Speaker 5: a dramatically different outlook here. But it really is services 327 00:18:54,040 --> 00:18:55,719 Speaker 5: prices for us. 328 00:18:56,000 --> 00:18:58,320 Speaker 1: I can't sign up about this. Interhusby, thank you so much, 329 00:18:58,400 --> 00:19:01,040 Speaker 1: don't be a stranger with BMV Pery, their senior US 330 00:19:01,480 --> 00:19:08,800 Speaker 1: economist with our question for Global Wall Street. This is 331 00:19:08,880 --> 00:19:12,520 Speaker 1: the conversation of the day gene Monster with us across 332 00:19:12,880 --> 00:19:16,720 Speaker 1: the next half hour. I can't say enough about his 333 00:19:16,960 --> 00:19:20,680 Speaker 1: work from Piper Jeffrey long ago. It was research that 334 00:19:20,840 --> 00:19:23,680 Speaker 1: made you stop, and we're thrilled that he could join 335 00:19:23,800 --> 00:19:27,960 Speaker 1: us today from deep Water Asset Management Gene I quote 336 00:19:28,000 --> 00:19:34,719 Speaker 1: from pre pandemic, pre pandemic capex Microsoft fifteen billion, twenty one, 337 00:19:34,840 --> 00:19:38,159 Speaker 1: twenty three, twenty eight thirty five and they're going to 338 00:19:38,200 --> 00:19:41,240 Speaker 1: buy from Nvidia enough where we've got a modeled CAPEX 339 00:19:41,320 --> 00:19:45,920 Speaker 1: out fourteen months, fifteen months of forty five billion dollars. 340 00:19:46,760 --> 00:19:49,240 Speaker 1: Do you have a vision of how that money spent, 341 00:19:49,960 --> 00:19:53,399 Speaker 1: the efficacy of it, the safety of it. For our 342 00:19:53,520 --> 00:19:58,000 Speaker 1: listeners and viewers, this global capex off Nvidia. 343 00:20:00,119 --> 00:20:03,639 Speaker 6: Topic time, and it's not just Microsoft, it's Google, it's Apple. 344 00:20:03,880 --> 00:20:06,919 Speaker 6: They haven't said as much. Meta has said this thirty percent. 345 00:20:07,040 --> 00:20:10,400 Speaker 6: That's kind of the benchmark. Thirty percent increase, and they compute. 346 00:20:11,119 --> 00:20:14,800 Speaker 6: And so when we think about this these layers of AI, 347 00:20:15,280 --> 00:20:17,639 Speaker 6: there's two parts of the question. One is what does 348 00:20:17,720 --> 00:20:20,439 Speaker 6: the ramp look like? And this is a thirty percent 349 00:20:20,760 --> 00:20:24,159 Speaker 6: step up. If you look at Jensen Wong's comments from 350 00:20:24,240 --> 00:20:27,960 Speaker 6: Nvidia this week, he talked about the chip, the GPU 351 00:20:28,680 --> 00:20:31,680 Speaker 6: market being several hundred billion dollars over the next few years. 352 00:20:31,720 --> 00:20:35,240 Speaker 6: It's about one hundred billion dollars today. So that kind 353 00:20:35,240 --> 00:20:38,119 Speaker 6: of plays along this trajectory of twenty five percent growth. 354 00:20:38,600 --> 00:20:41,480 Speaker 6: I think what your listeners should take away here is 355 00:20:41,600 --> 00:20:46,000 Speaker 6: that there is a significant investment, a massive investment going 356 00:20:46,040 --> 00:20:49,840 Speaker 6: on from these hyperscalers, these big tech companies. This is 357 00:20:50,000 --> 00:20:53,360 Speaker 6: the first of four waves of investment that will probably 358 00:20:53,480 --> 00:20:56,399 Speaker 6: last a decade and as far as what it means 359 00:20:56,520 --> 00:20:58,520 Speaker 6: for our lives. I think it's going to be the 360 00:20:58,560 --> 00:21:01,840 Speaker 6: most profound change, much more than what the Internet was 361 00:21:01,960 --> 00:21:04,960 Speaker 6: last time we spoke about this. The spectrum that I 362 00:21:05,040 --> 00:21:07,960 Speaker 6: have in terms of how to think about AI relative 363 00:21:08,040 --> 00:21:10,760 Speaker 6: to our lives, I put a spectrum of zero one 364 00:21:10,840 --> 00:21:15,280 Speaker 6: hundred electricities one hundred. The PC was a twenty mobile, 365 00:21:15,320 --> 00:21:19,399 Speaker 6: twenty five Internet fifty and AI's ninety nine, and it 366 00:21:19,440 --> 00:21:21,879 Speaker 6: would be one hundred if not for needing electricity. So 367 00:21:23,119 --> 00:21:25,240 Speaker 6: it's a big This is a big deal, and I'm 368 00:21:25,880 --> 00:21:28,560 Speaker 6: I think that your listeners just take away that the 369 00:21:28,960 --> 00:21:32,760 Speaker 6: significance of this change is going to be more profound 370 00:21:32,800 --> 00:21:33,320 Speaker 6: than the Internet. 371 00:21:33,600 --> 00:21:36,960 Speaker 1: Jane. I want to frame this as something maybe we understand, 372 00:21:37,119 --> 00:21:39,480 Speaker 1: unlike experts like you. I think of all the other 373 00:21:39,600 --> 00:21:43,080 Speaker 1: compatriots and tech dana ives and such, and that is. 374 00:21:43,359 --> 00:21:45,679 Speaker 1: There was the Model T, which was like, okay, well 375 00:21:45,720 --> 00:21:48,919 Speaker 1: that's a fad, and then in nineteen twenty seven, nineteen 376 00:21:49,080 --> 00:21:52,919 Speaker 1: thirty ish, the Model A showed up and Alfred Sloan 377 00:21:53,080 --> 00:21:56,080 Speaker 1: was over at GM trying to make magic happen, and 378 00:21:56,200 --> 00:21:58,680 Speaker 1: it was like, whoa wait, this automobile is going to 379 00:21:58,720 --> 00:22:02,240 Speaker 1: be a real deal. It's actually going to work. Where 380 00:22:02,320 --> 00:22:05,080 Speaker 1: are we within that continuum? Are we looking at AI 381 00:22:05,200 --> 00:22:08,440 Speaker 1: as a fad? Are we to the model A, Are 382 00:22:08,480 --> 00:22:10,880 Speaker 1: we to the Ford F one fifty pickup truck where 383 00:22:10,880 --> 00:22:14,000 Speaker 1: it's entrenched. AI is entrenched in society. 384 00:22:16,280 --> 00:22:19,600 Speaker 6: So from the impact of society right now, it's a 385 00:22:19,800 --> 00:22:24,320 Speaker 6: model T and it is we're just still scratching the surface. 386 00:22:24,359 --> 00:22:26,760 Speaker 6: And just to put some context on that, is that 387 00:22:27,000 --> 00:22:29,560 Speaker 6: most of that spend when we see this just breath 388 00:22:29,640 --> 00:22:32,399 Speaker 6: taking change in vidious business. And I want to just 389 00:22:32,520 --> 00:22:35,240 Speaker 6: take a pause for a moment and put how breathtaking 390 00:22:35,280 --> 00:22:38,520 Speaker 6: of a change this is. In Vidia's business for the 391 00:22:38,680 --> 00:22:43,000 Speaker 6: previous three quarters before the AI lift off was down 392 00:22:43,040 --> 00:22:46,520 Speaker 6: in averages seventeen percent per quarter. This business was in 393 00:22:46,840 --> 00:22:50,119 Speaker 6: the toilet. And it has now since the three quarters 394 00:22:50,160 --> 00:22:52,399 Speaker 6: that it's taken a step up. It is up two 395 00:22:52,520 --> 00:22:55,720 Speaker 6: hundred percent on average per quarter. And so what we're 396 00:22:55,760 --> 00:22:58,720 Speaker 6: seeing is this dramatic step up. And when we think 397 00:22:58,760 --> 00:23:01,080 Speaker 6: about most of that spend, and the vast majority of 398 00:23:01,119 --> 00:23:04,280 Speaker 6: it has been related to those hyperscalers building the Model T. 399 00:23:04,840 --> 00:23:09,120 Speaker 6: It's related to but there has been an important data 400 00:23:09,160 --> 00:23:11,440 Speaker 6: point that Jensen Wong talked about in the Nvidia call 401 00:23:11,960 --> 00:23:14,880 Speaker 6: is a forty percent. They now believe of this, their 402 00:23:15,000 --> 00:23:18,600 Speaker 6: current sales of chips are going to power our currently 403 00:23:18,720 --> 00:23:22,399 Speaker 6: powering inference. Inference is what comes out of the model 404 00:23:22,440 --> 00:23:25,480 Speaker 6: when you go into JGPT and put in a prompt 405 00:23:25,560 --> 00:23:27,480 Speaker 6: and you get something back out. That's something that you 406 00:23:27,640 --> 00:23:30,200 Speaker 6: get back out is called an inference. And so what 407 00:23:30,359 --> 00:23:33,560 Speaker 6: that means is that it's actually people are actually using this. 408 00:23:34,119 --> 00:23:37,520 Speaker 6: This is not big tech spending a bunch of money 409 00:23:37,600 --> 00:23:40,320 Speaker 6: to build something that they hope people will come. This 410 00:23:40,600 --> 00:23:45,040 Speaker 6: is big tech recognizing that the behavior is already there. 411 00:23:45,080 --> 00:23:47,760 Speaker 6: Even though it's nascent, it is still it's taking off 412 00:23:48,359 --> 00:23:52,800 Speaker 6: in concert, in lockstep with what their investment is. And 413 00:23:52,920 --> 00:23:55,160 Speaker 6: so when I think about we're going to go from 414 00:23:55,200 --> 00:23:57,840 Speaker 6: the Model T to the F one fifty to the 415 00:23:57,960 --> 00:24:01,000 Speaker 6: cyber truck and about three to five years, and I 416 00:24:01,040 --> 00:24:04,520 Speaker 6: think when you put that type of a scope and scale, 417 00:24:05,119 --> 00:24:07,920 Speaker 6: most of the commentary I hear is this, this is 418 00:24:07,960 --> 00:24:12,119 Speaker 6: an video led rally, and this is are we getting 419 00:24:12,200 --> 00:24:15,760 Speaker 6: bubble ish? We're not even close to bubble. Bubble is 420 00:24:15,840 --> 00:24:18,680 Speaker 6: when the market trades at one hundred times earnings, we're 421 00:24:18,720 --> 00:24:20,280 Speaker 6: at twenty eight times. 422 00:24:20,520 --> 00:24:24,960 Speaker 1: Paul Microsoft four hundred and fifteen dollars. For sure. 423 00:24:25,119 --> 00:24:27,040 Speaker 4: It's been another great way to play. Jenda. I have 424 00:24:27,119 --> 00:24:30,520 Speaker 4: to admit here in cocktail parties, I definitely use your 425 00:24:30,720 --> 00:24:33,880 Speaker 4: kind of spectrum thing. They're talking about electricity where AI 426 00:24:33,960 --> 00:24:35,520 Speaker 4: fits in. I give you full credit though. 427 00:24:35,359 --> 00:24:37,480 Speaker 6: I want you to know but appreciate that. Yeah, thank you, Paul. 428 00:24:37,640 --> 00:24:40,600 Speaker 4: It works. It really takes people's breathway to just give 429 00:24:40,600 --> 00:24:42,600 Speaker 4: it some context. So, Gene, I want to talk about 430 00:24:42,680 --> 00:24:45,400 Speaker 4: a competition here. When are the AMDs of the world 431 00:24:45,520 --> 00:24:47,960 Speaker 4: or the other chip makers going to step up and 432 00:24:48,040 --> 00:24:50,600 Speaker 4: be real competitive here? Maybe even maybe some of the 433 00:24:50,680 --> 00:24:53,119 Speaker 4: customers like an Apple saying hey, we can build our 434 00:24:53,119 --> 00:24:55,360 Speaker 4: own chips. Talk to us about how you think competition 435 00:24:55,480 --> 00:24:56,040 Speaker 4: is going to evolve. 436 00:24:57,400 --> 00:24:59,800 Speaker 6: So look for competition to start to have a meaningful 437 00:24:59,880 --> 00:25:02,320 Speaker 6: end packed at least on in Nvidia's business, probably in 438 00:25:02,440 --> 00:25:06,080 Speaker 6: two to three years. And specifically as we think about AMD, 439 00:25:06,200 --> 00:25:08,920 Speaker 6: they're actually getting some traction. They're actually putting a significant 440 00:25:08,920 --> 00:25:12,320 Speaker 6: effort into GPUs. Intel has just started that, but it's 441 00:25:12,359 --> 00:25:15,320 Speaker 6: still just too nascent, and we're talking about low single 442 00:25:15,359 --> 00:25:18,840 Speaker 6: digit percent market share of GPUs AMDs kind of around 443 00:25:18,840 --> 00:25:22,119 Speaker 6: that ten percent in videas around eighty five percent, and 444 00:25:22,240 --> 00:25:24,919 Speaker 6: so what it is the most important point to your 445 00:25:25,040 --> 00:25:27,440 Speaker 6: question is it's not just about what the absolute market 446 00:25:27,480 --> 00:25:29,040 Speaker 6: share is today, it's about what the trend in the 447 00:25:29,080 --> 00:25:31,560 Speaker 6: market share is. Is AMD going to gain share? And 448 00:25:31,960 --> 00:25:35,119 Speaker 6: my expectations is over the next couple of years, in 449 00:25:35,240 --> 00:25:37,439 Speaker 6: Vidia's market share is probably going to be seventy percent 450 00:25:37,520 --> 00:25:39,360 Speaker 6: or above. They may lose a little bit, they'll lose 451 00:25:39,680 --> 00:25:42,280 Speaker 6: probably most of it to AMD, but it's still going 452 00:25:42,359 --> 00:25:45,800 Speaker 6: to be huge share in what is a quickly growing market. 453 00:25:46,680 --> 00:25:49,360 Speaker 6: Beyond that, three to five years, that's when things start 454 00:25:49,400 --> 00:25:51,520 Speaker 6: to get more difficult. And I believe that AMB is 455 00:25:51,600 --> 00:25:54,200 Speaker 6: going higher. I believe eventually three to five years it's 456 00:25:54,200 --> 00:25:56,760 Speaker 6: going to hit the wall because of what you talked about. Ultimately, 457 00:25:57,160 --> 00:26:00,280 Speaker 6: these hyper scalers are going to back off. One of 458 00:26:00,359 --> 00:26:05,280 Speaker 6: the benefits that Nvidia has here is that they will 459 00:26:05,359 --> 00:26:07,639 Speaker 6: lose business to the hyperscalers and they come out with 460 00:26:07,720 --> 00:26:10,800 Speaker 6: their own chips, but it's unlikely those hyperscalers sell their 461 00:26:10,880 --> 00:26:13,720 Speaker 6: chips to third parties. And if you think about these 462 00:26:13,840 --> 00:26:17,280 Speaker 6: four waves of AI, there's still three more waves that 463 00:26:17,400 --> 00:26:22,359 Speaker 6: need to be powered by publicly available GPUs, like in 464 00:26:22,440 --> 00:26:23,399 Speaker 6: video Paul to. 465 00:26:23,520 --> 00:26:26,760 Speaker 1: Frame in VIDIAT four hundred and the quiet of November 466 00:26:26,920 --> 00:26:31,240 Speaker 1: last year to surge now to eight twenty, up nicely 467 00:26:31,320 --> 00:26:35,200 Speaker 1: from yesterday. All this is critical, folks, It's only two 468 00:26:35,280 --> 00:26:39,320 Speaker 1: point six standard deviations. That goes to mister Munster's comments 469 00:26:39,560 --> 00:26:43,800 Speaker 1: that the exuberance really isn't there technically like you'd think 470 00:26:43,880 --> 00:26:45,480 Speaker 1: given the light in the uproar. 471 00:26:45,800 --> 00:26:46,639 Speaker 3: Exactly so. 472 00:26:46,880 --> 00:26:49,679 Speaker 4: But Invindia at its core a gene it's a chip company, 473 00:26:49,680 --> 00:26:51,359 Speaker 4: and what I've learned I'm not a tech honist, but 474 00:26:51,400 --> 00:26:53,520 Speaker 4: what I've learned from reading tech research is that's a 475 00:26:53,600 --> 00:26:56,119 Speaker 4: really cyclical business. So once I sell a chip to 476 00:26:56,200 --> 00:26:58,800 Speaker 4: a customer, it's not like a software as a service 477 00:26:58,800 --> 00:27:01,040 Speaker 4: where they're going to get me recurring red. That's kind 478 00:27:01,080 --> 00:27:03,400 Speaker 4: of it for a while. So is there a tail 479 00:27:03,560 --> 00:27:04,119 Speaker 4: end to this thing? 480 00:27:06,119 --> 00:27:06,359 Speaker 3: There is? 481 00:27:06,640 --> 00:27:09,120 Speaker 6: That's why you see that I think three to five 482 00:27:09,200 --> 00:27:11,400 Speaker 6: years is that in video is going to hit the wall. 483 00:27:11,440 --> 00:27:13,359 Speaker 6: There's going to be a very dark day. We're going 484 00:27:13,440 --> 00:27:15,520 Speaker 6: to have this boom and bust I wanted to highlight 485 00:27:15,640 --> 00:27:17,880 Speaker 6: kind of that scar tissue in terms of what their 486 00:27:17,880 --> 00:27:20,760 Speaker 6: business has done before because of that dynamic that you 487 00:27:20,880 --> 00:27:24,840 Speaker 6: talked about, and that eventually will come the question isn't not. 488 00:27:25,520 --> 00:27:28,000 Speaker 6: I see the question more as what's the duration of 489 00:27:28,560 --> 00:27:30,920 Speaker 6: this run? And I would come back to those four 490 00:27:31,000 --> 00:27:33,720 Speaker 6: pillars just to recap. We're currently in right now the 491 00:27:34,320 --> 00:27:37,359 Speaker 6: infrastructure build phase. Then we're going to go to applications 492 00:27:37,440 --> 00:27:41,000 Speaker 6: that's like co pilots service now Salesforce, and then it's 493 00:27:41,040 --> 00:27:43,480 Speaker 6: going to be heavy industry doing General of AI and 494 00:27:43,480 --> 00:27:46,680 Speaker 6: the lastly countries with sovereigny I. And so there's I 495 00:27:46,800 --> 00:27:52,760 Speaker 6: think that yes, there once everybody's full, but it's it's 496 00:27:52,960 --> 00:27:54,560 Speaker 6: we're still got a long way to go before we 497 00:27:54,680 --> 00:27:55,720 Speaker 6: get full with these chips. 498 00:27:55,800 --> 00:27:58,440 Speaker 1: We're with Gene Monster of deep Water and it is 499 00:27:58,480 --> 00:28:01,080 Speaker 1: a great thrill I think a harsh Over and Slot 500 00:28:01,200 --> 00:28:04,359 Speaker 1: genius to have at Piper of Minnesota. Good morning to 501 00:28:04,400 --> 00:28:07,200 Speaker 1: all of you listening up at Piper, Jeffrey Country and 502 00:28:07,320 --> 00:28:10,360 Speaker 1: Gene Muster. It's like the Muppets thing. One of these 503 00:28:10,440 --> 00:28:12,720 Speaker 1: teams is not playing like the other teams or whatever 504 00:28:12,800 --> 00:28:16,679 Speaker 1: the Muppets song is. I got Microsoft up at Vidia 505 00:28:16,760 --> 00:28:19,280 Speaker 1: up the whole thing, and Apple's given me no love 506 00:28:19,359 --> 00:28:22,000 Speaker 1: at all. I mean, you know, Harsh has a neutral 507 00:28:22,080 --> 00:28:25,600 Speaker 1: on it over at Piper. Whither Apple are they under 508 00:28:25,640 --> 00:28:28,920 Speaker 1: a pressure to do something given the tech nirvana of 509 00:28:28,960 --> 00:28:30,000 Speaker 1: the last three months. 510 00:28:31,520 --> 00:28:36,760 Speaker 6: Yeah, yes, excruciating pressure. Of course, Tim Cook did not 511 00:28:36,920 --> 00:28:39,600 Speaker 6: utter those two letters in all of twenty twenty three. 512 00:28:39,680 --> 00:28:42,920 Speaker 6: He did proactively talk about AI for the first time 513 00:28:43,000 --> 00:28:46,000 Speaker 6: and their December earnings call. I think that was a 514 00:28:46,120 --> 00:28:49,000 Speaker 6: marked moment, and they're going to have something to say 515 00:28:49,080 --> 00:28:52,239 Speaker 6: about AI, he said this year. Most likely that's going 516 00:28:52,280 --> 00:28:54,760 Speaker 6: to be in June at their developer conference, and most 517 00:28:54,880 --> 00:28:58,120 Speaker 6: likely they will announce a foundation model. These are really 518 00:28:58,200 --> 00:29:01,440 Speaker 6: the core engines that always applications are built on. So 519 00:29:02,520 --> 00:29:05,160 Speaker 6: Apple is the big challenge with Apple is they haven't 520 00:29:05,200 --> 00:29:07,800 Speaker 6: grown for the past six quarters basically as a flat 521 00:29:07,880 --> 00:29:10,360 Speaker 6: business if you kind of average it all out, and 522 00:29:10,600 --> 00:29:12,960 Speaker 6: they haven't said anything about AI, and I think that 523 00:29:13,080 --> 00:29:15,840 Speaker 6: they're in a great place to surprise people on AI 524 00:29:15,960 --> 00:29:16,280 Speaker 6: this year. 525 00:29:16,600 --> 00:29:19,760 Speaker 1: Let's surprise people Paul, and Paul's has been leading on this. 526 00:29:19,840 --> 00:29:22,760 Speaker 1: He's been screaming about this his first gray hair. Paul 527 00:29:23,400 --> 00:29:26,280 Speaker 1: free cash flow seventy billion is now one hundred and 528 00:29:26,360 --> 00:29:30,200 Speaker 1: thirteen revenue two hundred and seventy four million is four 529 00:29:30,280 --> 00:29:34,320 Speaker 1: hundred and thirteen million from the pandemic. And the answer 530 00:29:34,480 --> 00:29:38,880 Speaker 1: here is their minting profit as mister Munter says, they're 531 00:29:38,920 --> 00:29:39,360 Speaker 1: not growing. 532 00:29:39,960 --> 00:29:41,880 Speaker 4: I know, and so I you know, how about a 533 00:29:41,920 --> 00:29:45,080 Speaker 4: dividend for some folks here a meaningful dividend, But that's 534 00:29:45,120 --> 00:29:47,920 Speaker 4: not in Tim Cook's wheelhouse. Hey, you know, Gene. One 535 00:29:47,920 --> 00:29:50,920 Speaker 4: of the things I'm looking for as this AI sector 536 00:29:51,040 --> 00:29:53,960 Speaker 4: industrymania kind of continues to evolve is kind of the 537 00:29:54,040 --> 00:29:56,480 Speaker 4: bell Weather IPO and I know at deep Water, you 538 00:29:56,520 --> 00:29:59,560 Speaker 4: guys see lots of early stage companies here, and I'm 539 00:29:59,560 --> 00:30:02,240 Speaker 4: looking for like an AOL America Online was for the 540 00:30:02,320 --> 00:30:07,120 Speaker 4: consumer internet search. We identified with Google Social, we identified 541 00:30:07,200 --> 00:30:09,320 Speaker 4: with Facebook. Do you think there's going to be an 542 00:30:09,400 --> 00:30:13,120 Speaker 4: AI company come public that just blows everybody away. 543 00:30:15,160 --> 00:30:18,280 Speaker 6: Yes, we're really excited about that. I think that's probably 544 00:30:18,320 --> 00:30:20,280 Speaker 6: a year two years away. But we're going to see 545 00:30:20,280 --> 00:30:24,120 Speaker 6: a cast of foundational AI companies. These are not companies 546 00:30:24,200 --> 00:30:27,040 Speaker 6: benefiting from AI. If you think about where AI sits 547 00:30:27,120 --> 00:30:29,120 Speaker 6: like with inside Microsoft or what it will be in 548 00:30:29,640 --> 00:30:32,240 Speaker 6: Apple or Meta, it's a small piece of it. But 549 00:30:32,320 --> 00:30:35,880 Speaker 6: these companies are entirely their companies. Like hugging Face, this 550 00:30:36,080 --> 00:30:39,040 Speaker 6: is an open platform for AI models. Many of you 551 00:30:39,200 --> 00:30:43,320 Speaker 6: haven't heard of them, and I think that there's other 552 00:30:43,360 --> 00:30:46,280 Speaker 6: companies like Androw, which uses a lot of AI with defense, 553 00:30:46,760 --> 00:30:50,280 Speaker 6: and then this is going to be the one. Potentially, 554 00:30:50,360 --> 00:30:53,240 Speaker 6: I think this will be the biggest surprise relative to 555 00:30:54,480 --> 00:30:57,680 Speaker 6: up and comers and will be one of these megacap 556 00:30:58,280 --> 00:31:01,960 Speaker 6: tech companies. Is x dot ai Elon's company, and what 557 00:31:02,240 --> 00:31:04,720 Speaker 6: he did is this is I put this in the 558 00:31:04,800 --> 00:31:09,640 Speaker 6: category of he's eighty percent genius, twenty percent luckiest man 559 00:31:09,720 --> 00:31:14,600 Speaker 6: on Earth. The Twitter purchase, you know this X dot 560 00:31:14,680 --> 00:31:16,840 Speaker 6: ai one's about twenty percent of that. They will use 561 00:31:16,960 --> 00:31:20,040 Speaker 6: that data, which is the world's best data when it 562 00:31:20,120 --> 00:31:23,200 Speaker 6: comes to real time intention that is critical data. They'll 563 00:31:23,320 --> 00:31:27,560 Speaker 6: use that to inform and build X dot ai foundation model, 564 00:31:28,000 --> 00:31:32,600 Speaker 6: and that is a massive opportunity. The message that Elon's 565 00:31:32,640 --> 00:31:36,120 Speaker 6: had he refers to this as a truth seeking AI. 566 00:31:36,200 --> 00:31:38,640 Speaker 6: There's been some comical things that have gone on and 567 00:31:38,760 --> 00:31:42,000 Speaker 6: the image generation AI space relative to Google this week, 568 00:31:42,320 --> 00:31:45,880 Speaker 6: which sets this X dot ai up for a massive opportunity. 569 00:31:46,520 --> 00:31:50,840 Speaker 6: I believe this will hands down be Elon's greatest source 570 00:31:50,880 --> 00:31:51,240 Speaker 6: of wealth. 571 00:31:51,440 --> 00:31:52,040 Speaker 1: X dot ai. 572 00:31:52,240 --> 00:31:55,560 Speaker 6: He's currently based on Bloomberg. He's he's worth two hundred 573 00:31:55,560 --> 00:31:59,360 Speaker 6: and ten billion dollars today. X dot ai I believe 574 00:31:59,360 --> 00:32:01,240 Speaker 6: will be a public company in the next three years, 575 00:32:01,640 --> 00:32:03,400 Speaker 6: and I think it's going to be one of those 576 00:32:03,480 --> 00:32:05,360 Speaker 6: megacap AI company. 577 00:32:05,440 --> 00:32:08,040 Speaker 4: That's good stuff. I mean, again Elon in the seemingly 578 00:32:08,240 --> 00:32:11,080 Speaker 4: in the nexus of everything of interest out there, all right, 579 00:32:11,160 --> 00:32:13,480 Speaker 4: So talk to When I see a market grow like 580 00:32:13,600 --> 00:32:16,360 Speaker 4: this is growing, and I see a mania around a 581 00:32:16,440 --> 00:32:19,640 Speaker 4: certain situation like AI, I guess in the back of 582 00:32:19,680 --> 00:32:22,760 Speaker 4: my mind, I also think, June gene boy, it just 583 00:32:22,840 --> 00:32:25,360 Speaker 4: feels like Washington is going to feel like it needs 584 00:32:25,400 --> 00:32:28,240 Speaker 4: to get involved here in regulating some of this. What 585 00:32:28,360 --> 00:32:30,760 Speaker 4: do you think, how do you think Washington views AI 586 00:32:31,080 --> 00:32:31,800 Speaker 4: and is that a risk? 587 00:32:33,600 --> 00:32:34,080 Speaker 1: It's a risk. 588 00:32:34,160 --> 00:32:36,960 Speaker 6: I mean, Washington has a genuine view that big tech, 589 00:32:37,040 --> 00:32:40,720 Speaker 6: of course needs to be regulated. The AI conversation has 590 00:32:40,960 --> 00:32:43,760 Speaker 6: more layers to it, of course, because of the national 591 00:32:43,880 --> 00:32:47,800 Speaker 6: security piece to it. Is when you think about national defense, 592 00:32:47,960 --> 00:32:50,080 Speaker 6: whether it's intelligence gathering, whether it's how some of these 593 00:32:50,120 --> 00:32:55,160 Speaker 6: systems work, whether it's just how our countries GDP evolves 594 00:32:55,680 --> 00:33:00,280 Speaker 6: powered by AI. Having a sovereign a strong AI, a 595 00:33:00,400 --> 00:33:03,440 Speaker 6: strong tech is something that benefits the government. So when 596 00:33:03,440 --> 00:33:06,600 Speaker 6: I think about government regulation over the past five years 597 00:33:06,680 --> 00:33:09,080 Speaker 6: relative to big tech, it has been things around like 598 00:33:09,160 --> 00:33:15,000 Speaker 6: the app store, or engagement around Instagram. They've been about 599 00:33:15,720 --> 00:33:22,320 Speaker 6: Microsoft buying Activision. These things are petty compared to what 600 00:33:22,680 --> 00:33:24,560 Speaker 6: is at stake when it comes to I think that 601 00:33:24,800 --> 00:33:28,760 Speaker 6: ultimately that significance is going to benefit big tech. 602 00:33:29,320 --> 00:33:32,360 Speaker 1: Gene. One final question, completely unfair. Let's go back to 603 00:33:32,440 --> 00:33:36,440 Speaker 1: Piper Jeffrey's single best buy buy holds SOE with Jeane Munster. 604 00:33:36,720 --> 00:33:39,600 Speaker 1: Can you acquire shares of Nvidia this morning? 605 00:33:42,000 --> 00:33:44,520 Speaker 6: Yes, I think Nvidia is going to go higher. I 606 00:33:44,600 --> 00:33:48,840 Speaker 6: think that if I based on my expectations, This is 607 00:33:48,920 --> 00:33:49,840 Speaker 6: not investment advice. 608 00:33:49,920 --> 00:33:50,960 Speaker 1: This is just how I see it. 609 00:33:51,280 --> 00:33:53,760 Speaker 6: I think that this should appreciate at about fifteen percent 610 00:33:53,840 --> 00:33:55,280 Speaker 6: a year for the next two to three years. I 611 00:33:55,320 --> 00:33:58,000 Speaker 6: don't think we're going to have this massive growth, but 612 00:33:58,080 --> 00:34:00,360 Speaker 6: I think this continues just to march higher based on 613 00:34:00,400 --> 00:34:01,440 Speaker 6: all the things we're talking about. 614 00:34:01,560 --> 00:34:03,160 Speaker 1: Most if you believe in AI. 615 00:34:03,320 --> 00:34:05,840 Speaker 6: Believe it's as big as I believe it is, in 616 00:34:05,960 --> 00:34:06,880 Speaker 6: Vidia is going higher. 617 00:34:07,680 --> 00:34:10,320 Speaker 1: This is the class act. Most people Paul would have 618 00:34:10,360 --> 00:34:14,279 Speaker 1: avoided their question. Yep, Genemunster nailed it. I honored to 619 00:34:14,320 --> 00:34:17,120 Speaker 1: have you for a half hour. Beyond this historic week, 620 00:34:17,200 --> 00:34:20,040 Speaker 1: this historic Thursday, and that we've seen gene monster with 621 00:34:20,120 --> 00:34:33,120 Speaker 1: deep water daily headlines. I'll look at the front page 622 00:34:33,120 --> 00:34:35,520 Speaker 1: as Lisa Matteo ave Lisia. 623 00:34:35,640 --> 00:34:36,759 Speaker 3: Now it's pretty good. 624 00:34:37,840 --> 00:34:40,719 Speaker 7: I never took French. All right, So we're starting with 625 00:34:40,840 --> 00:34:43,360 Speaker 7: the Wall Street Journal. This is an interesting story because 626 00:34:43,360 --> 00:34:47,440 Speaker 7: it's saying Meta knew about parents exploiting their own children 627 00:34:47,560 --> 00:34:50,600 Speaker 7: with new paid subscription tools, and they did nothing about it. Now, 628 00:34:50,920 --> 00:34:52,960 Speaker 7: this is disturbing on so many levels. First of all, 629 00:34:53,040 --> 00:34:57,200 Speaker 7: the parents, these are parent managed accounts. They're using subscription 630 00:34:57,360 --> 00:35:02,200 Speaker 7: feature to sell exclusive content. Their daughters wearing bikinis, wearing 631 00:35:02,280 --> 00:35:05,239 Speaker 7: lear tards, no nudity, but it was sold to an 632 00:35:05,280 --> 00:35:09,239 Speaker 7: audience that's overwhelmingly male. Some expressed central interest in the 633 00:35:09,320 --> 00:35:11,319 Speaker 7: children and their comments and posts. So the parents knew 634 00:35:11,320 --> 00:35:14,240 Speaker 7: what was going on. Teams inside Meta, they started raising 635 00:35:14,280 --> 00:35:18,520 Speaker 7: alarms about this. They tried to warn Meta. Meta's response 636 00:35:18,640 --> 00:35:20,840 Speaker 7: is that they built this automated system to prevent it 637 00:35:20,880 --> 00:35:21,600 Speaker 7: from happening, but. 638 00:35:21,960 --> 00:35:22,839 Speaker 2: It just didn't work. 639 00:35:23,080 --> 00:35:25,759 Speaker 7: So this is just crazy on so many different levels. 640 00:35:25,840 --> 00:35:28,080 Speaker 4: Yeah, starting with the parents. Yeah, yeah, that's where it's 641 00:35:28,080 --> 00:35:28,360 Speaker 4: got to go. 642 00:35:28,400 --> 00:35:31,280 Speaker 7: All right, what else, So we've heard about the returning 643 00:35:31,320 --> 00:35:33,120 Speaker 7: to the moon right for the first time, all Right, 644 00:35:33,280 --> 00:35:37,200 Speaker 7: this one is another piece of history. It was college students. 645 00:35:37,600 --> 00:35:40,800 Speaker 7: The lander actually took a selfie as it landed. It 646 00:35:40,960 --> 00:35:44,400 Speaker 7: was made by graduate students. This camera from every Riddle 647 00:35:44,440 --> 00:35:48,000 Speaker 7: Aeronautical University in Daytona beachiev in Florida. And that is 648 00:35:48,200 --> 00:35:51,240 Speaker 7: actually the alma mater of Intuitive Machine CEO. 649 00:35:51,400 --> 00:35:52,279 Speaker 5: So that's the connection to. 650 00:35:52,280 --> 00:35:56,000 Speaker 4: The school aerospace program, the aerospace the aerospace program. 651 00:35:56,120 --> 00:35:57,719 Speaker 7: Yeah, it took him like four years to make it. 652 00:35:57,880 --> 00:36:00,000 Speaker 7: And so it's this little box ejected from the lane 653 00:36:00,719 --> 00:36:03,200 Speaker 7: and it was and it worked and they took the picture. 654 00:36:03,280 --> 00:36:05,160 Speaker 7: And what's crazy is that a lot of the graduate 655 00:36:05,200 --> 00:36:07,279 Speaker 7: students who did this, they weren't alive when you know, 656 00:36:07,360 --> 00:36:08,920 Speaker 7: the first landing happened. 657 00:36:08,960 --> 00:36:11,520 Speaker 4: I don't think we were taking selfie me as I 658 00:36:11,600 --> 00:36:14,120 Speaker 4: recall with our Instamatic or whatever we had, the Kodak, 659 00:36:14,600 --> 00:36:14,840 Speaker 4: it was. 660 00:36:15,400 --> 00:36:18,640 Speaker 1: It was something. And you know, I remember, I literally 661 00:36:18,760 --> 00:36:22,640 Speaker 1: remember the day up in Rochester when Hasselblad won the 662 00:36:22,760 --> 00:36:26,600 Speaker 1: contract to be the camera that the astronauts carried around. 663 00:36:26,680 --> 00:36:29,000 Speaker 1: That was a dark day. They were looking for the 664 00:36:29,080 --> 00:36:32,680 Speaker 1: instematic to be going. That didn't quite work out. What 665 00:36:32,800 --> 00:36:33,279 Speaker 1: else do you have? 666 00:36:33,760 --> 00:36:35,600 Speaker 7: Uh, this is the financial times we were talking about 667 00:36:35,640 --> 00:36:39,719 Speaker 7: the luxury market yesterday. So it says the LVMH is 668 00:36:39,760 --> 00:36:42,280 Speaker 7: trying to Hollywood to promote a lot of their brands. 669 00:36:42,880 --> 00:36:44,000 Speaker 3: It's a new venture. 670 00:36:44,200 --> 00:36:46,480 Speaker 7: It's called twenty two Montaigne. 671 00:36:46,640 --> 00:36:49,920 Speaker 4: My French accent is not as well as chilling. I 672 00:36:50,440 --> 00:36:54,120 Speaker 4: I Killed Yeah, Brooklyn Brooklyn. 673 00:36:54,200 --> 00:36:57,360 Speaker 1: That's a YouTube channel, but it's. 674 00:36:57,239 --> 00:37:00,640 Speaker 7: A collaboration with them and super connector Shoot. So this 675 00:37:00,800 --> 00:37:03,640 Speaker 7: is this company that connects brands to production companies. So 676 00:37:03,719 --> 00:37:08,080 Speaker 7: they want to start doing advertising, product placement, original products, 677 00:37:08,200 --> 00:37:10,960 Speaker 7: TV film and you've kind of seen it. Remember Breakfast 678 00:37:11,000 --> 00:37:13,080 Speaker 7: with Tiffany's. You've seen it there, Well that's first s 679 00:37:14,280 --> 00:37:15,560 Speaker 7: a Gucci, you've seen it. 680 00:37:16,120 --> 00:37:18,560 Speaker 1: You walked by Tiffany's and there's the Audrey window and 681 00:37:18,640 --> 00:37:20,800 Speaker 1: I think up second or third four John's got the 682 00:37:21,440 --> 00:37:25,279 Speaker 1: Audrey dress. Guess what, Beyonce, he's driving the ship. I mean, 683 00:37:25,960 --> 00:37:28,239 Speaker 1: the r No family is doing what you're saying. 684 00:37:28,239 --> 00:37:31,120 Speaker 4: And this will be overseen by twe Arnaut, who is 685 00:37:31,160 --> 00:37:34,920 Speaker 4: the eldest son the founder Bernard. So it's probably Bernard 686 00:37:35,040 --> 00:37:37,000 Speaker 4: saying I got to give my son something something. 687 00:37:37,280 --> 00:37:40,239 Speaker 1: So they have a whole bunch of the sons and 688 00:37:40,360 --> 00:37:42,600 Speaker 1: the daughter runs Christian dear, can I do a TV 689 00:37:42,719 --> 00:37:43,640 Speaker 1: shout out this weekend? 690 00:37:43,920 --> 00:37:45,239 Speaker 3: Yes, the new Look. 691 00:37:45,600 --> 00:37:47,960 Speaker 1: Can't say enough about on Apple TV. It's about all 692 00:37:48,000 --> 00:37:51,800 Speaker 1: that Lisa Matteo's talking about, folks, about Coco Chanel and 693 00:37:51,960 --> 00:37:54,640 Speaker 1: Christian Dior, and it's shocking how they hated each other. 694 00:37:55,360 --> 00:37:57,760 Speaker 1: And it was all in the background of the nineteen forties, 695 00:37:57,800 --> 00:38:00,319 Speaker 1: in the nineteen fifties. So it's just a whole run. 696 00:38:00,480 --> 00:38:01,319 Speaker 4: I gotta check it out. 697 00:38:01,760 --> 00:38:05,160 Speaker 1: Great, they'll wear bow tyes. Is that it? Or you're 698 00:38:05,200 --> 00:38:06,000 Speaker 1: done on more? 699 00:38:06,239 --> 00:38:08,479 Speaker 7: But you have to get to the vision pro users. Okay, 700 00:38:09,480 --> 00:38:13,240 Speaker 7: So yesterday from the San Diego Police, they are putting 701 00:38:13,280 --> 00:38:15,759 Speaker 7: out a warning. They're saying, don't use them when you're 702 00:38:15,760 --> 00:38:17,880 Speaker 7: crossing the street because apparently people are doing that. 703 00:38:18,200 --> 00:38:19,279 Speaker 4: Yeah, and they're getting run over. 704 00:38:20,480 --> 00:38:21,640 Speaker 3: It's dangerous. 705 00:38:22,120 --> 00:38:24,359 Speaker 7: And they posted a video. They're just warning people. They say, 706 00:38:24,480 --> 00:38:25,880 Speaker 7: keep the virtual experiences on. 707 00:38:25,960 --> 00:38:28,800 Speaker 3: The sidewalk, folks. But you've seen it. 708 00:38:28,840 --> 00:38:31,520 Speaker 7: You've seen that. You've seen pictures of people job driving 709 00:38:32,080 --> 00:38:33,640 Speaker 7: with the vision goggles on. 710 00:38:33,719 --> 00:38:35,040 Speaker 4: I I don't know how that works. 711 00:38:35,960 --> 00:38:36,560 Speaker 7: Very dangerous. 712 00:38:37,640 --> 00:38:40,799 Speaker 1: This is the Bloomberg Surveillance Podcast, bringing you the best 713 00:38:40,880 --> 00:38:45,600 Speaker 1: in economics, finance, investment, and international relations. You can also 714 00:38:45,719 --> 00:38:49,680 Speaker 1: watch the show live on YouTube. Visit the Bloomberg Podcast 715 00:38:49,880 --> 00:38:53,879 Speaker 1: channel on YouTube to see the show weekday mornings from 716 00:38:53,960 --> 00:38:57,160 Speaker 1: seven to ten am Eastern from our global headquarters in 717 00:38:57,280 --> 00:39:01,400 Speaker 1: New York City. Subscribe to the podcast on Spotify or 718 00:39:01,480 --> 00:39:05,120 Speaker 1: anywhere else you listen, and always I'm Bloomberg Radio, the 719 00:39:05,160 --> 00:39:08,239 Speaker 1: Bloomberg Terminal, and the Bloomberg Business app.