1 00:00:02,720 --> 00:00:09,080 Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. 2 00:00:10,240 --> 00:00:13,440 Speaker 2: Good morning, I'm Nathan Hager and I'm Karen Moscow. Here 3 00:00:13,440 --> 00:00:15,160 Speaker 2: are the stories we're following today. 4 00:00:15,360 --> 00:00:18,840 Speaker 3: Karen, we begin with the Chinese artificial intelligence startup that 5 00:00:19,040 --> 00:00:21,599 Speaker 3: royal the global markets and led to the biggest one 6 00:00:21,680 --> 00:00:25,639 Speaker 3: day individual stock sell off in history. For the latest 7 00:00:25,640 --> 00:00:28,600 Speaker 3: on Deep Seek, let's bring in Bloomberg's John Tucker. 8 00:00:28,680 --> 00:00:31,800 Speaker 4: John Nathan, the Deep Seek frenzy e raised five hundred 9 00:00:31,800 --> 00:00:35,400 Speaker 4: and eighty nine billion dollars from Invidious market cap, the 10 00:00:35,520 --> 00:00:39,400 Speaker 4: largest route in market history. The stock plunge seventeen percent. 11 00:00:39,800 --> 00:00:43,000 Speaker 4: The techa A Nastak tumbled nearly three percent. Jordan Klin 12 00:00:43,120 --> 00:00:45,280 Speaker 4: is managing director at Mazouoho Securities. 13 00:00:45,800 --> 00:00:49,279 Speaker 3: It's a beginning of probably a consolidation phase and some 14 00:00:49,320 --> 00:00:50,000 Speaker 3: profit taking. 15 00:00:50,040 --> 00:00:50,480 Speaker 5: For sure. 16 00:00:50,600 --> 00:00:53,960 Speaker 4: Deep Seek is sparking fear over US tech dominance. Aaron 17 00:00:54,080 --> 00:00:56,800 Speaker 4: Kennon of Clear Harbor Asset Management sees it this way. 18 00:00:57,080 --> 00:00:59,080 Speaker 6: We're seeing what I would call sort of the gradual 19 00:00:59,120 --> 00:01:01,920 Speaker 6: commoditizing of artificial intelligence. 20 00:01:02,040 --> 00:01:05,800 Speaker 4: Deep Seek's low cost approach has reignited concerns that big 21 00:01:05,920 --> 00:01:09,240 Speaker 4: US companies have poured too much money into developing artificial 22 00:01:09,280 --> 00:01:13,560 Speaker 4: intelligence and Victoria Fernandez of Crossmarked Global Investment weigh in. 23 00:01:14,040 --> 00:01:16,480 Speaker 5: Obviously, the tech game can turn on a dime. 24 00:01:16,680 --> 00:01:19,360 Speaker 2: We've seen it over the last twenty four hours. I 25 00:01:19,480 --> 00:01:22,800 Speaker 2: do think that the US is probably still a little 26 00:01:22,800 --> 00:01:23,440 Speaker 2: bit of head. 27 00:01:23,959 --> 00:01:27,200 Speaker 4: Deep Seek even drew praise from Nvidia. In Vidia set 28 00:01:27,240 --> 00:01:30,040 Speaker 4: in a statement that deep Sex model is an excellent 29 00:01:30,120 --> 00:01:34,839 Speaker 4: AI advancement, and deep See's progress suggests Chinese AI engineers 30 00:01:35,080 --> 00:01:38,360 Speaker 4: have found a way to work around US semiconductor export bands, 31 00:01:38,720 --> 00:01:43,039 Speaker 4: focusing on greater efficiency with limited resources. The latest AI 32 00:01:43,120 --> 00:01:46,400 Speaker 4: model of deep Seek, it's called Uri, is now at 33 00:01:46,400 --> 00:01:49,280 Speaker 4: the top of Apple's App Store rankings, and being in 34 00:01:49,280 --> 00:01:51,720 Speaker 4: the spotlight all of a sudden also does bring problems. 35 00:01:51,960 --> 00:01:54,560 Speaker 4: The companies had to limit signups due to large scale 36 00:01:54,600 --> 00:01:58,320 Speaker 4: malicious attacks on its services, and even this morning the 37 00:01:58,440 --> 00:02:02,600 Speaker 4: company reports degraded performance. In this morning, Nathan and Karen 38 00:02:02,760 --> 00:02:05,880 Speaker 4: in videos shares we should point out they're up five percent. 39 00:02:06,560 --> 00:02:08,760 Speaker 2: All right, John, thank you well. The Deepseak sell off 40 00:02:08,760 --> 00:02:11,360 Speaker 2: on Wall Street also hit the world's elite, and we 41 00:02:11,400 --> 00:02:13,680 Speaker 2: get that story with Bloomberg's Gino Cervetti. 42 00:02:13,919 --> 00:02:16,760 Speaker 7: The world's five hundred richest people lost to combined one 43 00:02:16,880 --> 00:02:20,720 Speaker 7: hundred eight billion on Monday. Billionaires whose fortunes are linked 44 00:02:20,720 --> 00:02:24,520 Speaker 7: to artificial intelligence were the biggest losers, and Vidio's CEO 45 00:02:24,639 --> 00:02:28,400 Speaker 7: Jensen Wang saw his fortune fall more than twenty billion dollars, 46 00:02:28,480 --> 00:02:32,040 Speaker 7: or a twenty percent drop. Oracle co founder Larry Ellison's 47 00:02:32,080 --> 00:02:35,000 Speaker 7: twenty two point six billion dollar loss was larger in 48 00:02:35,080 --> 00:02:38,960 Speaker 7: absolute terms, but represented twelve percent of his fortune. Dell's 49 00:02:39,040 --> 00:02:43,040 Speaker 7: Michael Dell lost at thirteen billion. Soaring valuations for so 50 00:02:43,160 --> 00:02:48,240 Speaker 7: called AI hyperscalers including Meta, Alphabet and Microsoft have generated 51 00:02:48,280 --> 00:02:51,640 Speaker 7: billions in wealth for their owners since open Ai unveiled 52 00:02:51,720 --> 00:02:55,639 Speaker 7: chat GPT in November of twenty twenty two. These companies 53 00:02:55,680 --> 00:02:59,119 Speaker 7: have spent huge sums to develop and run AI systems 54 00:02:59,160 --> 00:03:02,320 Speaker 7: by hoarding top of the line semiconductors and the energy 55 00:03:02,360 --> 00:03:06,519 Speaker 7: supplies needed to run them. Gina Cervetti Bloomberg Radio. 56 00:03:06,400 --> 00:03:07,520 Speaker 5: All right, Gina, thank you. 57 00:03:07,639 --> 00:03:10,560 Speaker 3: One of deep Seek's biggest competitors in the US could 58 00:03:10,560 --> 00:03:13,080 Speaker 3: be open Ai, and in a post on x the 59 00:03:13,080 --> 00:03:16,320 Speaker 3: company CEO Sam Aldman said deep seeks are one is 60 00:03:16,400 --> 00:03:19,680 Speaker 3: an impressive model. He added quote we will obviously deliver 61 00:03:19,800 --> 00:03:23,160 Speaker 3: much better models, and also it's legit invigorating to have 62 00:03:23,200 --> 00:03:26,000 Speaker 3: a new competitor end quote. Meanwhile, we caught up with 63 00:03:26,040 --> 00:03:29,000 Speaker 3: tech investor Cathy Wood to get her reaction about Deep Seek. 64 00:03:29,560 --> 00:03:31,840 Speaker 1: I think what it's telling us is the cost of 65 00:03:31,840 --> 00:03:35,480 Speaker 1: innovation is collapsing, which it has been doing. I mean, 66 00:03:35,520 --> 00:03:41,080 Speaker 1: the cost of AI training is dropping before this seventy 67 00:03:41,120 --> 00:03:45,119 Speaker 1: five percent per year, the cost for inference eighty five 68 00:03:45,160 --> 00:03:49,360 Speaker 1: to ninety percent. I think it throws the weight more 69 00:03:49,440 --> 00:03:53,800 Speaker 1: towards inference chips from training chips, and so in Vidia's 70 00:03:53,960 --> 00:03:57,560 Speaker 1: highly exalted and deservedly so in the training chip space. 71 00:03:57,840 --> 00:04:00,680 Speaker 3: Our Investments CEO Kathy Would made the comments in an 72 00:04:00,720 --> 00:04:03,000 Speaker 3: interview with Bloomberg earlier this morning in London. 73 00:04:03,400 --> 00:04:03,880 Speaker 5: On Nathan. 74 00:04:03,960 --> 00:04:06,680 Speaker 2: President Trump also weighing in on deep Seek. 75 00:04:06,960 --> 00:04:12,160 Speaker 8: The release of Deepseek AI from a Chinese company should 76 00:04:12,200 --> 00:04:14,600 Speaker 8: be a wake up call for our industries that we 77 00:04:14,720 --> 00:04:17,960 Speaker 8: need to be laser focused on competing to win because 78 00:04:18,000 --> 00:04:19,839 Speaker 8: we have the greatest scientists in the world. 79 00:04:20,200 --> 00:04:23,359 Speaker 2: And Trump also sees deep Seek's apparent breakthrough as good 80 00:04:23,480 --> 00:04:26,320 Speaker 2: because quote, you don't have to spend as much money. 81 00:04:26,240 --> 00:04:26,520 Speaker 9: Thank care. 82 00:04:26,560 --> 00:04:29,040 Speaker 3: And the President's also weighing in on the future of 83 00:04:29,160 --> 00:04:33,160 Speaker 3: another Chinese company, TikTok, he told reporters on air Force 84 00:04:33,240 --> 00:04:36,279 Speaker 3: one that Microsoft is in talks to acquire the hugely 85 00:04:36,320 --> 00:04:37,000 Speaker 3: popular app. 86 00:04:37,240 --> 00:04:39,000 Speaker 8: I think somebody's going to buy it, pay a lot 87 00:04:39,040 --> 00:04:42,480 Speaker 8: of money, have a lot of jobs, keep a platform. 88 00:04:42,160 --> 00:04:44,000 Speaker 1: Open, and having to be very secure. 89 00:04:44,279 --> 00:04:46,279 Speaker 2: If I don't sign that, it closes. 90 00:04:47,200 --> 00:04:51,000 Speaker 3: Following the President's comments, Microsoft declined to comment on the 91 00:04:51,080 --> 00:04:54,120 Speaker 3: company's involvement in any possible deal Well Nathan. 92 00:04:54,200 --> 00:04:56,760 Speaker 2: President Trump is also laying out more details on his 93 00:04:56,880 --> 00:04:59,480 Speaker 2: tariff plans. At a speech to House Republicans at his 94 00:04:59,600 --> 00:05:02,920 Speaker 2: direlt golf club, the President said he plans to impose 95 00:05:03,040 --> 00:05:07,719 Speaker 2: duties on computer chips, pharmaceuticals, and metals to encourage foreign 96 00:05:07,800 --> 00:05:08,840 Speaker 2: production in the US. 97 00:05:09,120 --> 00:05:10,920 Speaker 8: We want them to come back, and we don't want 98 00:05:10,920 --> 00:05:13,640 Speaker 8: to give them billions of dollars, like this ridiculous program 99 00:05:13,760 --> 00:05:16,159 Speaker 8: that Biden has give everybody billions of dollars. They already 100 00:05:16,200 --> 00:05:18,840 Speaker 8: have billions of dollars. They've got nothing but money. 101 00:05:18,960 --> 00:05:19,159 Speaker 9: Joe. 102 00:05:19,720 --> 00:05:22,440 Speaker 2: Later, the President told reporters he wants to enact across 103 00:05:22,480 --> 00:05:25,080 Speaker 2: the board tariffs that are quote much bigger than two 104 00:05:25,120 --> 00:05:28,080 Speaker 2: and a half percent. Trump was responding to a Financial 105 00:05:28,120 --> 00:05:31,680 Speaker 2: Times report that is newly confirmed Treasury Secretary Scott Besant 106 00:05:32,040 --> 00:05:35,159 Speaker 2: supports starting with a global two and a half percent 107 00:05:35,320 --> 00:05:38,200 Speaker 2: tariff rate, then raising it by the same amount each 108 00:05:38,320 --> 00:05:39,200 Speaker 2: month and Karen. 109 00:05:39,200 --> 00:05:41,920 Speaker 3: President Trump also says he hopes House Republicans will pass 110 00:05:42,040 --> 00:05:45,640 Speaker 3: legislation to complete the border wall and step up deportation efforts, 111 00:05:45,680 --> 00:05:49,239 Speaker 3: while also extending his twenty seventeen tax cuts and boosting 112 00:05:49,320 --> 00:05:52,560 Speaker 3: oil and gas production. But the President's leaving the details 113 00:05:52,800 --> 00:05:53,240 Speaker 3: up to them. 114 00:05:53,720 --> 00:05:56,000 Speaker 8: Whether it's one bill, two bills, I don't care. Let 115 00:05:56,120 --> 00:05:57,560 Speaker 8: these guys are going to work it out. They're going 116 00:05:57,640 --> 00:05:59,080 Speaker 8: to work it out one way or the other. But 117 00:05:59,160 --> 00:06:01,400 Speaker 8: the bottom line, the result is going to be the same. 118 00:06:01,480 --> 00:06:04,200 Speaker 8: We want to have all of those benefits, and we 119 00:06:04,279 --> 00:06:07,599 Speaker 8: want to keep people's taxes low and actually make them lower. 120 00:06:07,839 --> 00:06:10,960 Speaker 3: Following President Trump's speech, one GOP lawmaker called it not 121 00:06:11,200 --> 00:06:14,240 Speaker 3: helpful that the President wouldn't be more specific. House Speaker 122 00:06:14,279 --> 00:06:16,560 Speaker 3: Mike Johnson says lawmakers will spend much of their two 123 00:06:16,640 --> 00:06:19,560 Speaker 3: day retreat behind closed doors to come up with a strategy. 124 00:06:20,080 --> 00:06:22,480 Speaker 2: Well. Nathan returned now to the latest developments in the 125 00:06:22,520 --> 00:06:25,360 Speaker 2: Middle East. To Bloomberg News has learned Israeli Prime Minister 126 00:06:25,480 --> 00:06:28,840 Speaker 2: Benjamin nettan Yahoo, is planning to visit Washington next week 127 00:06:28,920 --> 00:06:31,400 Speaker 2: to meet with President Trump. The sit down would come 128 00:06:31,440 --> 00:06:33,440 Speaker 2: at a critical time, just weeks until the end of 129 00:06:33,480 --> 00:06:36,080 Speaker 2: the first phase of the pause in fighting in Gaza. 130 00:06:36,440 --> 00:06:39,120 Speaker 2: Skeptics have questioned whether the deal will hold through its 131 00:06:39,200 --> 00:06:42,279 Speaker 2: second phase, which could ultimately lead to a permanent end 132 00:06:42,360 --> 00:06:47,720 Speaker 2: to the war in Gaza. Time now for a look 133 00:06:47,720 --> 00:06:49,440 Speaker 2: at some of the other stories making news in New 134 00:06:49,520 --> 00:06:51,240 Speaker 2: York and around the world. And for that we're joined 135 00:06:51,240 --> 00:06:54,279 Speaker 2: by Bloomberg's Michael Barr. Michael, Good Morning, Good morning, Karen. 136 00:06:54,360 --> 00:06:58,320 Speaker 9: After rain extinguished the last of the big Palisades fire 137 00:06:58,440 --> 00:07:01,320 Speaker 9: in Los Angeles, the city is now allowing everybody to 138 00:07:01,360 --> 00:07:03,960 Speaker 9: go back in to see what remains of their homes 139 00:07:04,480 --> 00:07:07,280 Speaker 9: for the first time since the Palisades fire started in 140 00:07:07,440 --> 00:07:12,040 Speaker 9: days after President Trump visited, Los Angeles, Mayor Karen Bass 141 00:07:12,160 --> 00:07:14,280 Speaker 9: announced all evacuees can return. 142 00:07:14,600 --> 00:07:19,160 Speaker 4: Today is really about focusing on the recovery and getting 143 00:07:19,240 --> 00:07:20,640 Speaker 4: people back home. 144 00:07:21,280 --> 00:07:24,160 Speaker 9: This woman says some residents advised there not to go 145 00:07:24,360 --> 00:07:25,840 Speaker 9: back because there's nothing left. 146 00:07:26,120 --> 00:07:29,760 Speaker 5: It's a lot to lose everything that you've collected. I 147 00:07:29,800 --> 00:07:32,040 Speaker 5: think over the last you know, your adult life and 148 00:07:32,080 --> 00:07:32,960 Speaker 5: even your childhood. 149 00:07:33,400 --> 00:07:36,440 Speaker 9: The neighborhoods are only open to residents from six am 150 00:07:36,520 --> 00:07:39,040 Speaker 9: to six pm because there is no power and some 151 00:07:39,240 --> 00:07:43,240 Speaker 9: areas require a police escort to get in. The Centers 152 00:07:43,280 --> 00:07:46,200 Speaker 9: for Disease Control and Prevention staff have been ordered to 153 00:07:46,240 --> 00:07:50,320 Speaker 9: cut off all communications with the World Health Organization. This 154 00:07:50,480 --> 00:07:54,040 Speaker 9: comes following an executive order from President Trump last week. 155 00:07:54,520 --> 00:07:59,280 Speaker 9: A CDC's deputy director sent the directive in an email, 156 00:07:59,720 --> 00:08:02,920 Speaker 9: which which also said CDC staff to sign to work 157 00:08:03,040 --> 00:08:06,240 Speaker 9: for the who are also being told not to come 158 00:08:06,320 --> 00:08:11,400 Speaker 9: into the office. Peter Mayberduke is Access to Medicine's director 159 00:08:11,720 --> 00:08:12,840 Speaker 9: at Public Citizen. 160 00:08:13,320 --> 00:08:17,560 Speaker 6: It's sometimes underappreciated how deeply the United States is involved 161 00:08:17,600 --> 00:08:22,560 Speaker 6: in scientific collaboration internationally. There are more than seventy who 162 00:08:22,720 --> 00:08:27,240 Speaker 6: collaborating centers in the United States. The United States pulls out, 163 00:08:27,600 --> 00:08:32,240 Speaker 6: our new political competitors are waiting to fill that gap. 164 00:08:32,760 --> 00:08:35,599 Speaker 9: Maybordew Can Other experts say the sudden stoppage is a 165 00:08:35,679 --> 00:08:38,760 Speaker 9: surprise and will set back work on investigating and trying 166 00:08:38,800 --> 00:08:43,840 Speaker 9: to stop outbreaks of certain viruses in Africa. The MTA 167 00:08:43,960 --> 00:08:48,040 Speaker 9: next month will begin releasing monthly review collection figures from 168 00:08:48,120 --> 00:08:51,560 Speaker 9: New York City's new congestion pricing toll as. The transit 169 00:08:51,600 --> 00:08:55,000 Speaker 9: agency plans to borrow five hundred million dollars of short 170 00:08:55,160 --> 00:08:59,880 Speaker 9: term debt that the tolling program will ultimately repay. ZIPATL, 171 00:09:00,120 --> 00:09:03,360 Speaker 9: the MTA's deputy Chief Financial officers said the authority will 172 00:09:03,440 --> 00:09:07,360 Speaker 9: release at its Finance Committee meeting that it is so 173 00:09:07,559 --> 00:09:11,760 Speaker 9: much collected so far in pricing revenue that the agency 174 00:09:11,800 --> 00:09:16,520 Speaker 9: collected in January. New York City's congestion pricing program is 175 00:09:16,600 --> 00:09:19,640 Speaker 9: the first in the nation in charges most motorist nine 176 00:09:19,679 --> 00:09:22,719 Speaker 9: dollars when they interparts in Manhattan Global News twenty four 177 00:09:22,760 --> 00:09:24,840 Speaker 9: hours a day and whenever you want it with Bloomberg 178 00:09:24,880 --> 00:09:27,200 Speaker 9: News Now, Michael Barn, this is Bloomberg, Karen. 179 00:09:27,480 --> 00:09:28,600 Speaker 5: Sorry, Malcolm Barr, thank you. 180 00:09:33,480 --> 00:09:35,679 Speaker 2: Time now for the Bloomberg Sports Update brought to you 181 00:09:35,720 --> 00:09:38,480 Speaker 2: if I try stayed out. Eagre's John stash Hour, John 182 00:09:38,520 --> 00:09:39,319 Speaker 2: good Nortek. 183 00:09:39,040 --> 00:09:41,440 Speaker 10: Good morning, Karen. If you score one hundred and forty 184 00:09:41,559 --> 00:09:43,920 Speaker 10: three points in an NBA game, you're going to win 185 00:09:44,000 --> 00:09:46,000 Speaker 10: the next did that Saturday. It was the most points 186 00:09:46,040 --> 00:09:48,600 Speaker 10: they had scored in a non overtime game in forty 187 00:09:48,720 --> 00:09:51,720 Speaker 10: five years. Two nights later, again at the Garden, they 188 00:09:51,840 --> 00:09:55,160 Speaker 10: scored one hundred and forty three points, again beat Memphis 189 00:09:55,240 --> 00:09:58,680 Speaker 10: by thirty seven, seven nicks and double figures. Michael Bridges 190 00:09:58,720 --> 00:10:01,120 Speaker 10: the high mand with twenty eight nixt rolling four straight 191 00:10:01,160 --> 00:10:04,000 Speaker 10: wins sixteen to the last twenty two, and the Celtics 192 00:10:04,080 --> 00:10:07,120 Speaker 10: lost at home to Houston. Amen Thompson thirty three points 193 00:10:07,160 --> 00:10:08,760 Speaker 10: for the Rockets at a game when he shot out 194 00:10:08,760 --> 00:10:11,880 Speaker 10: the buzzer niterion, only a game behind Boston first second 195 00:10:11,920 --> 00:10:14,559 Speaker 10: place in the East. Cleveland's in first cans for thirty 196 00:10:14,679 --> 00:10:17,000 Speaker 10: seven and nine. They beat Detroit. The Nets lost at 197 00:10:17,040 --> 00:10:20,640 Speaker 10: Barkleys to Sacramento one ten to ninety six for Brooklyn. 198 00:10:20,760 --> 00:10:23,160 Speaker 10: That's seven losses in a row, twelve the last thirteen. 199 00:10:23,240 --> 00:10:27,319 Speaker 10: Miami won in double overtime without Jimmy Butler, suspended for 200 00:10:27,440 --> 00:10:30,319 Speaker 10: a third time. He walked out of practice after learning 201 00:10:30,720 --> 00:10:34,000 Speaker 10: he wasn't going to start the game. Certainly appears Butler's 202 00:10:34,000 --> 00:10:36,400 Speaker 10: gonna get traded before the deadline. Devils lost four to 203 00:10:36,520 --> 00:10:41,280 Speaker 10: at Philadelphia. Nothing like overtime in indoor partially simulated golf 204 00:10:41,400 --> 00:10:45,320 Speaker 10: Tiger Woods. His team beat Rory McElroy's team in TGL. 205 00:10:45,480 --> 00:10:48,400 Speaker 10: Aaron Glenn introduced as the new coach of the Jets. 206 00:10:48,440 --> 00:10:51,320 Speaker 10: Here was his message to his team to any players. 207 00:10:51,360 --> 00:10:51,640 Speaker 2: That's here. 208 00:10:51,760 --> 00:10:54,560 Speaker 9: Now put your seatbelts on and get ready for the ride. 209 00:10:55,000 --> 00:10:56,760 Speaker 11: Put your seatbelt zone and get ready for the ride. 210 00:10:56,880 --> 00:10:57,160 Speaker 9: Listen. 211 00:10:57,480 --> 00:10:59,960 Speaker 7: There are going to be some challenges, but what challenges 212 00:11:00,000 --> 00:11:01,760 Speaker 7: this becomes opportunity gets opportunity. 213 00:11:02,240 --> 00:11:04,360 Speaker 9: But here's what I do know. We're the freaking New 214 00:11:04,440 --> 00:11:05,000 Speaker 9: York jit so. 215 00:11:05,040 --> 00:11:07,920 Speaker 10: Who haven't made the playoffs in fifteen years. Gland was 216 00:11:08,040 --> 00:11:11,160 Speaker 10: vague when asked about whether Aaron Rodgers will return. John 217 00:11:11,200 --> 00:11:13,320 Speaker 10: stashiell Er Bloomberg Sports, Kearny Meek. 218 00:11:15,640 --> 00:11:20,000 Speaker 7: Coast to Coast on Bloomberg Radio nationwide on Serious Exam and. 219 00:11:20,120 --> 00:11:23,319 Speaker 1: Around the world on Bloomberg dot Com and the Bloomberg 220 00:11:23,400 --> 00:11:24,000 Speaker 1: Business app. 221 00:11:24,320 --> 00:11:25,880 Speaker 5: This is Bloomberg Daybreak. 222 00:11:26,040 --> 00:11:26,520 Speaker 4: Good morning. 223 00:11:26,600 --> 00:11:29,480 Speaker 3: I'm Nathan Hager. It was the biggest single day drop 224 00:11:29,559 --> 00:11:31,680 Speaker 3: for one American company and it is thanks to an 225 00:11:31,760 --> 00:11:36,319 Speaker 3: AI startup in China. Nvidia plunged seventeen percent yesterday, wiping 226 00:11:36,320 --> 00:11:39,160 Speaker 3: away five hundred and eighty nine billion dollars in market 227 00:11:39,280 --> 00:11:42,640 Speaker 3: value on concern about deep seek and it's in competitive 228 00:11:42,720 --> 00:11:46,679 Speaker 3: AI model with less advanced chips for more. Ark Investment 229 00:11:46,760 --> 00:11:50,000 Speaker 3: Management CEO Kathy Wood joined Bloomberg Stephen, Carol and Lizzie 230 00:11:50,040 --> 00:11:52,800 Speaker 3: burden in our London bureau. Let's listen to that conversation. 231 00:11:53,000 --> 00:11:55,160 Speaker 5: Now, big question, you buying the dip. 232 00:11:56,480 --> 00:12:00,320 Speaker 1: Well, we're fully invested and we're very comfortable being fully invaded. 233 00:12:01,200 --> 00:12:03,280 Speaker 5: I think our confidence in the. 234 00:12:04,760 --> 00:12:08,640 Speaker 1: Bull market broadening out has increased in the last few days. 235 00:12:09,559 --> 00:12:13,000 Speaker 1: So sure the megacaps we think will continue to do well. 236 00:12:13,880 --> 00:12:20,360 Speaker 1: Maybe in Vidia there are some questions about its exalted position. 237 00:12:20,440 --> 00:12:22,080 Speaker 5: In the training chip market. 238 00:12:23,240 --> 00:12:26,760 Speaker 1: We think inference is going to become more important with 239 00:12:26,880 --> 00:12:30,280 Speaker 1: these new reasoning models, and that is a more competitive 240 00:12:30,320 --> 00:12:31,040 Speaker 1: part of the market. 241 00:12:31,920 --> 00:12:35,520 Speaker 5: But we think that what's happening here is the. 242 00:12:35,679 --> 00:12:38,040 Speaker 1: Collapse in the cost of innovation. 243 00:12:39,000 --> 00:12:41,760 Speaker 5: Deep seek is adding to it. It has been happening though. 244 00:12:41,840 --> 00:12:46,880 Speaker 1: AI training costs have been dropping, led by Nvidia seventy 245 00:12:46,920 --> 00:12:51,880 Speaker 1: five percent per year, and AI inference costs have been 246 00:12:51,960 --> 00:12:55,839 Speaker 1: dropping eighty five to ninety percent per year. Deep seek 247 00:12:56,120 --> 00:12:59,880 Speaker 1: is just putting those very rapid declines into. 248 00:12:59,720 --> 00:13:00,880 Speaker 5: A bit of overdrive here. 249 00:13:01,360 --> 00:13:03,679 Speaker 12: So I wonder, if you see in Vidia falling much further, 250 00:13:03,800 --> 00:13:05,319 Speaker 12: is this an attractive price to be buying it? 251 00:13:05,400 --> 00:13:05,719 Speaker 9: Do you think? 252 00:13:06,600 --> 00:13:11,839 Speaker 5: Well, we own it in some of our portfolios. We 253 00:13:11,920 --> 00:13:14,480 Speaker 5: are not buying the dip yet. 254 00:13:14,800 --> 00:13:17,719 Speaker 1: We do want to learn more about deep seek and 255 00:13:17,960 --> 00:13:21,880 Speaker 1: more about how the market or the demand for inference 256 00:13:22,720 --> 00:13:27,559 Speaker 1: chips might outpace those for training chips. We think the 257 00:13:27,640 --> 00:13:31,439 Speaker 1: whole area is going to be vibrant. We just think 258 00:13:31,520 --> 00:13:34,319 Speaker 1: there might be a little bit more of an adjustment 259 00:13:34,520 --> 00:13:36,160 Speaker 1: to this new reality. 260 00:13:36,080 --> 00:13:38,520 Speaker 11: Where you say that what deep seek shows is kind 261 00:13:38,559 --> 00:13:41,559 Speaker 11: of that you can do more with less kap X. 262 00:13:42,320 --> 00:13:44,959 Speaker 11: Who do you think that's going to motivate in the 263 00:13:45,120 --> 00:13:47,679 Speaker 11: US most as Donald Trump is kind of saying, who's 264 00:13:47,720 --> 00:13:48,679 Speaker 11: going to be best. 265 00:13:48,600 --> 00:13:49,679 Speaker 5: At doing more with less? 266 00:13:50,720 --> 00:13:57,120 Speaker 1: Well, anyone using AI. We are focused on the productivity 267 00:13:57,160 --> 00:13:59,920 Speaker 1: gains for knowledge workers, which are going to be mass 268 00:14:00,320 --> 00:14:03,480 Speaker 1: that's the biggest impact of AI. But if we're looking 269 00:14:03,520 --> 00:14:08,720 Speaker 1: at sectors and spaces generally where this acceleration and innovation 270 00:14:09,000 --> 00:14:14,240 Speaker 1: is going to be meaningful, we think autonomous mobility, so robotaxis. 271 00:14:15,800 --> 00:14:18,280 Speaker 1: We think that's going to scale from essentially nothing now 272 00:14:18,400 --> 00:14:22,360 Speaker 1: to an eight to ten trillion dollar global opportunity including China. 273 00:14:23,040 --> 00:14:27,800 Speaker 1: But the sleeper here is healthcare, and we're seeing the 274 00:14:27,960 --> 00:14:34,640 Speaker 1: convergence of sequencing technologies, all kinds of sequencing technologies, artificial intelligence, 275 00:14:35,240 --> 00:14:38,960 Speaker 1: and then gene editing technologies like Crisper cast nine. 276 00:14:39,720 --> 00:14:43,320 Speaker 5: That combination we believe is going to cure disease. 277 00:14:43,520 --> 00:14:47,280 Speaker 1: It's already curing disease, sickle cell disease and beta thlocemia. 278 00:14:47,720 --> 00:14:52,680 Speaker 1: That's Chrisper therapeutics. But we think they're aiming now for 279 00:14:52,960 --> 00:14:57,240 Speaker 1: type one and type two diabetes. That would be a 280 00:14:57,440 --> 00:15:01,120 Speaker 1: category killer, you know, So think about that curing disease, 281 00:15:01,320 --> 00:15:07,960 Speaker 1: AI helping us decode the secrets of life, death health. 282 00:15:08,640 --> 00:15:11,680 Speaker 12: Those are two areas where regulation plays a big part. 283 00:15:11,960 --> 00:15:15,080 Speaker 12: You've spoken about your optimism about deregulation under Donald Trump. 284 00:15:15,120 --> 00:15:16,920 Speaker 12: Do you think those are two areas we should expect 285 00:15:16,960 --> 00:15:21,160 Speaker 12: to see big deregulation about what technology can get involved in. 286 00:15:22,040 --> 00:15:25,560 Speaker 1: Yes, I think in both safety first and I think 287 00:15:25,640 --> 00:15:29,560 Speaker 1: anyone moving into this market or these markets would agree 288 00:15:29,600 --> 00:15:34,640 Speaker 1: with that. So sensible regulation. But in the US, the 289 00:15:35,360 --> 00:15:40,240 Speaker 1: robotaxi field is regulated by fifty states. We think that 290 00:15:40,400 --> 00:15:45,360 Speaker 1: will change to one regulator, the federal government. After all, 291 00:15:45,520 --> 00:15:50,560 Speaker 1: transportation does cross states, so that makes sense. In the 292 00:15:50,880 --> 00:15:56,760 Speaker 1: healthcare realm, that is where the thicket of regulations has 293 00:15:57,000 --> 00:16:02,680 Speaker 1: really strangled the industry. And even more than the outright regulations, 294 00:16:02,880 --> 00:16:07,840 Speaker 1: it was the FTC, the Federal Trade Commission not allowing 295 00:16:08,400 --> 00:16:14,760 Speaker 1: mergers and acquisitions and therefore not allowing strategic buyers, big 296 00:16:14,880 --> 00:16:22,960 Speaker 1: biotech companies, not allowing them to buy the smaller companies, 297 00:16:23,440 --> 00:16:26,520 Speaker 1: so that we had price discovery. Now we're going to 298 00:16:26,600 --> 00:16:30,400 Speaker 1: see price discovery. How much are these companies that are 299 00:16:30,520 --> 00:16:36,360 Speaker 1: curing disease worth to these large strategic buyers now and 300 00:16:36,520 --> 00:16:39,240 Speaker 1: saying that I don't necessarily want our companies to be 301 00:16:39,360 --> 00:16:41,640 Speaker 1: taken out. We think they have miles to go, but 302 00:16:41,800 --> 00:16:44,920 Speaker 1: we do want price discovery back in the market. 303 00:16:45,120 --> 00:16:47,560 Speaker 11: Where you talk about your excitement about autonomous vehicles. Of 304 00:16:47,600 --> 00:16:49,960 Speaker 11: course your biggest holding is Tesla, I think yes, And 305 00:16:50,040 --> 00:16:53,240 Speaker 11: we've callt elon Musk's first earnings call tomorrow since Trump's 306 00:16:53,280 --> 00:16:55,240 Speaker 11: returned to the White House January. 307 00:16:55,440 --> 00:16:57,880 Speaker 5: Typically a call that's a look ahead. What do you 308 00:16:57,920 --> 00:16:59,000 Speaker 5: need to hear from Mosque? 309 00:17:00,040 --> 00:17:05,040 Speaker 1: We need to hear a continuation of we're about to 310 00:17:05,240 --> 00:17:11,640 Speaker 1: launch our autonomous driving system. I mean, in effect, they've 311 00:17:11,720 --> 00:17:14,760 Speaker 1: launched it. I have a full self driving I know 312 00:17:14,840 --> 00:17:18,040 Speaker 1: it's not allowed here in the UK or in Europe. 313 00:17:19,359 --> 00:17:24,760 Speaker 1: But the improvements you feel safe, oh yes, yes, yes, yes, 314 00:17:25,480 --> 00:17:28,280 Speaker 1: way more really has broken through a lot of barriers. 315 00:17:29,400 --> 00:17:32,840 Speaker 1: I feel even though a Waymo vehicle is not safer 316 00:17:33,600 --> 00:17:36,800 Speaker 1: than a human driven vehicle, it. 317 00:17:37,040 --> 00:17:38,439 Speaker 5: Knows its roads. 318 00:17:38,680 --> 00:17:43,119 Speaker 1: It's narrow roads, meaning there are narrow territories. 319 00:17:43,840 --> 00:17:46,680 Speaker 5: I think Tesla is going to go national. That's going 320 00:17:46,760 --> 00:17:48,280 Speaker 5: to be and we'll. 321 00:17:48,160 --> 00:17:51,960 Speaker 1: Be able to do so because it has effectively seven. 322 00:17:51,800 --> 00:17:53,680 Speaker 5: Million robots roaming the roads. 323 00:17:53,760 --> 00:17:55,600 Speaker 1: Right now, I have two of them, a Y and 324 00:17:55,680 --> 00:17:59,080 Speaker 1: A three, and they're learning all about Connecticut and Florida 325 00:17:59,200 --> 00:18:04,200 Speaker 1: worlddes So it has a huge competitive advantage in terms 326 00:18:04,280 --> 00:18:08,760 Speaker 1: of proprietary data that nobody else has about the roads, 327 00:18:09,160 --> 00:18:12,359 Speaker 1: not only in the US, but in many places around 328 00:18:12,359 --> 00:18:12,720 Speaker 1: the world. 329 00:18:13,119 --> 00:18:15,360 Speaker 12: Do you worry that Elon Musk is taking on too much? 330 00:18:15,480 --> 00:18:17,320 Speaker 12: If he's got his new job in the US government, 331 00:18:17,440 --> 00:18:21,359 Speaker 12: he's got sharp developments coming in Tesla, lots going on 332 00:18:21,440 --> 00:18:23,880 Speaker 12: with US other businesses as well. Is he spreading himself 333 00:18:23,920 --> 00:18:24,199 Speaker 12: too thin? 334 00:18:24,840 --> 00:18:28,560 Speaker 1: If you look at the way Elon Musk behaves as 335 00:18:28,600 --> 00:18:30,560 Speaker 1: a CEO, he's a sharpshooter. 336 00:18:31,200 --> 00:18:35,400 Speaker 5: He looks for pain points and he solves those right. 337 00:18:35,640 --> 00:18:40,040 Speaker 1: And he's for example, right now, where was in twenty eighteen, 338 00:18:40,520 --> 00:18:44,040 Speaker 1: where was the biggest pain point? It was manufacturing the 339 00:18:44,240 --> 00:18:49,399 Speaker 1: Model three, Scaling the Model three. He slept famously on 340 00:18:49,560 --> 00:18:53,119 Speaker 1: the factory floor. He's not doing that anymore. He's not 341 00:18:53,280 --> 00:18:56,720 Speaker 1: on the factory floor now, it's all about autonomous. He 342 00:18:57,080 --> 00:19:01,880 Speaker 1: is the first what we would call CEO who really 343 00:19:02,040 --> 00:19:07,640 Speaker 1: understands the convergence among technologies taking place right now, really 344 00:19:07,840 --> 00:19:12,320 Speaker 1: catalyzed by artificial intelligence each one of his businesses. And 345 00:19:12,440 --> 00:19:17,600 Speaker 1: he also understands how critically important proprietary data is. And 346 00:19:17,720 --> 00:19:22,320 Speaker 1: think about this, Each of those companies is generating proprietary 347 00:19:22,440 --> 00:19:24,560 Speaker 1: data that no one else has. 348 00:19:24,720 --> 00:19:26,320 Speaker 5: Well, maybe you should out to his plate. Should he 349 00:19:26,320 --> 00:19:28,320 Speaker 5: buy us TikTok Ah? 350 00:19:29,320 --> 00:19:29,560 Speaker 2: Yes? 351 00:19:29,680 --> 00:19:32,399 Speaker 1: I mean, I know there have been rumors about that 352 00:19:32,680 --> 00:19:34,600 Speaker 1: and about the government. 353 00:19:35,880 --> 00:19:38,600 Speaker 5: Sharing half, and that's kind. 354 00:19:38,440 --> 00:19:41,600 Speaker 1: Of anathema to the United States, you know, the government 355 00:19:41,680 --> 00:19:42,680 Speaker 1: getting involved like this. 356 00:19:43,160 --> 00:19:44,639 Speaker 5: I'd be surprised if that happens. 357 00:19:44,720 --> 00:19:48,320 Speaker 1: But I will also say the Trump administration is full 358 00:19:48,359 --> 00:19:49,000 Speaker 1: of surprises. 359 00:19:49,800 --> 00:19:51,560 Speaker 12: It certainly is, and we're only a weekend to it. 360 00:19:51,840 --> 00:19:53,760 Speaker 12: You're here with us in London and we're delighted to 361 00:19:53,800 --> 00:19:54,119 Speaker 12: see you. 362 00:19:54,520 --> 00:19:55,520 Speaker 5: What has you in London? 363 00:19:55,560 --> 00:19:57,920 Speaker 12: What opportunities are you excited about when you come to 364 00:19:57,960 --> 00:19:59,920 Speaker 12: the UK? Is this a good place to put your money? 365 00:20:01,200 --> 00:20:05,399 Speaker 1: Well, we have launched three funds. Our Europe has launched 366 00:20:05,480 --> 00:20:06,240 Speaker 1: three funds here. 367 00:20:07,200 --> 00:20:07,840 Speaker 5: One is our. 368 00:20:07,760 --> 00:20:12,600 Speaker 1: Flagship that is focused on all five innovation platforms, so robotics, 369 00:20:12,840 --> 00:20:20,720 Speaker 1: energy storage, artificial intelligence, multiomic sequencing and blockchain technology. So 370 00:20:20,840 --> 00:20:25,360 Speaker 1: that's the flagship AARKK a special one for Europe which 371 00:20:25,440 --> 00:20:29,760 Speaker 1: we do not have in the US because of overlaps 372 00:20:29,840 --> 00:20:33,040 Speaker 1: with other funds, but we have an AI and robotics 373 00:20:33,160 --> 00:20:40,720 Speaker 1: fund and that is ARKI. We think this convergence of 374 00:20:41,160 --> 00:20:47,240 Speaker 1: robotics and AI is going to lead to humanoid robots 375 00:20:47,440 --> 00:20:52,520 Speaker 1: and not just millions of them, but perhaps billions of 376 00:20:52,640 --> 00:20:56,359 Speaker 1: them longer term, which is going to be a key 377 00:20:56,800 --> 00:21:01,760 Speaker 1: productivity driver in both the home right now, we're not 378 00:21:01,880 --> 00:21:06,400 Speaker 1: paid for house cleaning, Let's get a robot. Let's pay 379 00:21:06,440 --> 00:21:10,679 Speaker 1: a robot to do it. And in the manufacturing plants 380 00:21:10,800 --> 00:21:11,400 Speaker 1: around the world. 381 00:21:11,560 --> 00:21:13,919 Speaker 12: Kathy, the Prime Minister was in the building earlier. Kris Starmer, 382 00:21:14,000 --> 00:21:15,760 Speaker 12: you're exactly the sort of person that he wants to 383 00:21:15,880 --> 00:21:18,520 Speaker 12: meet because he wants investments going into those sorts of 384 00:21:18,600 --> 00:21:21,280 Speaker 12: businesses in this country. Have you spoken to him, what 385 00:21:21,400 --> 00:21:23,080 Speaker 12: sort of device would you be giving him if he's 386 00:21:23,080 --> 00:21:24,080 Speaker 12: trying to grow the economy. 387 00:21:24,800 --> 00:21:28,520 Speaker 1: Well, half the solution is understanding the problem and just 388 00:21:28,840 --> 00:21:33,440 Speaker 1: making that statement suggests to me that he's saying, why 389 00:21:33,640 --> 00:21:37,080 Speaker 1: hasn't this happened? And I also over the weekend heard 390 00:21:37,800 --> 00:21:40,679 Speaker 1: one of the finance ministers, or maybe the Finance Minister 391 00:21:41,080 --> 00:21:43,800 Speaker 1: say the same thing. This is a mantra, and I 392 00:21:43,920 --> 00:21:47,320 Speaker 1: think it has been catalyzed by artificial intelligence as well. 393 00:21:47,640 --> 00:21:51,520 Speaker 5: If you think about the UK, you produced two. 394 00:21:51,440 --> 00:21:55,240 Speaker 1: Of the most important AI companies in the world, Deep Mind, 395 00:21:55,359 --> 00:22:01,960 Speaker 1: which Alphabet now owns, an arm which off Bank primarily owns. 396 00:22:03,400 --> 00:22:05,600 Speaker 5: By all rights, you should. 397 00:22:05,359 --> 00:22:10,760 Speaker 1: Be developing a deep venture capital pool here, feeding startups 398 00:22:10,920 --> 00:22:17,080 Speaker 1: and nourishing them and deepening your listed equity markets. And 399 00:22:17,240 --> 00:22:19,080 Speaker 1: so I think that's what they're going to do, which 400 00:22:19,119 --> 00:22:22,240 Speaker 1: is fantastic. It's fantastic for the UK. 401 00:22:22,520 --> 00:22:26,280 Speaker 11: Absolutely, they taught very ambitiously the UK leadership, but so 402 00:22:26,480 --> 00:22:31,000 Speaker 11: too do the European government's leadership, and Donald Trump, as 403 00:22:31,040 --> 00:22:34,840 Speaker 11: you say, is very passionate about deregulation. So yes, everybody's 404 00:22:34,880 --> 00:22:37,280 Speaker 11: on the same page, but it is a race. Is 405 00:22:37,359 --> 00:22:40,560 Speaker 11: the UK keeping up enough with the EU and the 406 00:22:40,760 --> 00:22:43,200 Speaker 11: US when it comes to deregulation for you to be 407 00:22:43,880 --> 00:22:45,880 Speaker 11: really confident, Kathy putting your money here. 408 00:22:46,880 --> 00:22:47,760 Speaker 5: I think that. 409 00:22:49,359 --> 00:22:52,800 Speaker 1: Europe is more tied up in regulatory nuts than the 410 00:22:52,960 --> 00:22:56,440 Speaker 1: UK is, and in fact, some of our companies Palenteer 411 00:22:56,520 --> 00:22:58,760 Speaker 1: has been very vocal, for example, and we think that's 412 00:22:58,800 --> 00:23:02,680 Speaker 1: one of the most important AI platform companies out there. 413 00:23:04,640 --> 00:23:08,160 Speaker 1: Alex Krp, the CEO, has said, I am pulling employees 414 00:23:08,359 --> 00:23:12,800 Speaker 1: out of Europe because you know, we're running into all 415 00:23:12,880 --> 00:23:15,960 Speaker 1: of these obstacles that could really harm us. You know, 416 00:23:16,200 --> 00:23:19,760 Speaker 1: being hit by a four percent fine four percent of 417 00:23:19,920 --> 00:23:24,159 Speaker 1: revenue and that's global revenue or seven percent of revenue 418 00:23:24,200 --> 00:23:24,920 Speaker 1: I heard recently. 419 00:23:26,000 --> 00:23:26,960 Speaker 5: That's crazy. 420 00:23:27,880 --> 00:23:32,520 Speaker 1: So I think Europe is going to be held back 421 00:23:32,760 --> 00:23:37,520 Speaker 1: until it gets its regulatory act together. I think the 422 00:23:37,680 --> 00:23:41,520 Speaker 1: UK is more more progressive from a regulatory point of view. 423 00:23:41,520 --> 00:23:46,040 Speaker 5: And as I said, I really believe that half the solution. 424 00:23:46,200 --> 00:23:48,080 Speaker 5: The fact that your. 425 00:23:47,960 --> 00:23:53,040 Speaker 1: Prime Minister, your Finance Minister in the same week are saying, 426 00:23:53,480 --> 00:23:55,760 Speaker 1: you know, we've got to figure this out. I think 427 00:23:55,960 --> 00:23:57,320 Speaker 1: that's a very good thing for the UK. 428 00:23:57,680 --> 00:24:00,639 Speaker 2: This is Bloombergy Daybreak, your morning pond podcast on the 429 00:24:00,720 --> 00:24:04,200 Speaker 2: stories making news from Wall Street to Washington and beyond. 430 00:24:04,520 --> 00:24:06,840 Speaker 3: Look for us on your podcast feed by six am 431 00:24:06,920 --> 00:24:10,320 Speaker 3: Eastern each morning on Apple, Spotify or anywhere else you listen. 432 00:24:10,560 --> 00:24:13,360 Speaker 2: You can also listen live each morning starting at five 433 00:24:13,400 --> 00:24:16,040 Speaker 2: am Wall Street Time on Bloomberg eleven three to zero 434 00:24:16,160 --> 00:24:19,000 Speaker 2: in New York, Bloomberg in ninety nine to one in Washington, 435 00:24:19,119 --> 00:24:23,000 Speaker 2: Bloomberg ninety two nine in Boston, and nationwide on serious 436 00:24:23,280 --> 00:24:24,800 Speaker 2: XM Channel one twenty one. 437 00:24:25,200 --> 00:24:27,920 Speaker 3: Plus listen coast to coast on the Bloomberg Business app 438 00:24:28,000 --> 00:24:30,720 Speaker 3: now with Apple CarPlay and Android Atto interfaces. 439 00:24:31,040 --> 00:24:34,040 Speaker 2: And don't forget to subscribe to Bloomberg News Now. It's 440 00:24:34,080 --> 00:24:36,800 Speaker 2: the latest news whenever you want it in five minutes 441 00:24:36,880 --> 00:24:39,960 Speaker 2: or less. Search Bloomberg News Now on your favorite podcast 442 00:24:40,040 --> 00:24:44,120 Speaker 2: platform to stay informed all day long. I'm Karen Moscow. 443 00:24:44,000 --> 00:24:44,960 Speaker 5: And I'm Nathan Hager. 444 00:24:45,119 --> 00:24:47,119 Speaker 3: Join us again tomorrow morning for all the news you 445 00:24:47,240 --> 00:24:49,760 Speaker 3: need to start your day right here on Bloomberg Day 446 00:24:49,840 --> 00:24:49,959 Speaker 3: Ray