1 00:00:01,480 --> 00:00:04,840 Speaker 1: From the heart of We're Innovation, Money and Power Collie 2 00:00:05,040 --> 00:00:09,760 Speaker 1: in Silicon Valley, NBR. This is Bloomberg Technology with Caroline 3 00:00:09,840 --> 00:00:26,720 Speaker 1: Hide and Ed Ludlow. I'm Caroline Hide and Bloomberg's world 4 00:00:26,760 --> 00:00:29,520 Speaker 1: headquarters in New York, and I'med Lovelow in San Francisco. 5 00:00:29,600 --> 00:00:32,840 Speaker 1: This is Bloomberg Technology, back together and coming up. Full 6 00:00:32,880 --> 00:00:35,440 Speaker 1: market coverage ahead. We're going to kick off the second 7 00:00:35,520 --> 00:00:38,200 Speaker 1: quarter then USA one hundred. Is it a bill market? 8 00:00:38,280 --> 00:00:41,400 Speaker 1: But will it stay Morgan Stanley, well, it thinks maybe 9 00:00:41,800 --> 00:00:45,080 Speaker 1: you should be warning about this tech valley last Tesla. 10 00:00:45,159 --> 00:00:47,800 Speaker 1: One name weighing on the market is Deliveries full short 11 00:00:47,840 --> 00:00:50,760 Speaker 1: of Elon Musk's own expectations. Will bring you the details. 12 00:00:50,760 --> 00:00:52,959 Speaker 1: And speaking of Mask, we'll get their latest on its 13 00:00:52,960 --> 00:00:55,080 Speaker 1: spat with The New York Times as the newspaper loses 14 00:00:55,120 --> 00:00:58,760 Speaker 1: it's verified badge on Twitter. That so much more coming up, 15 00:00:58,800 --> 00:01:01,240 Speaker 1: But first, I mean we got to delve into the 16 00:01:01,280 --> 00:01:03,760 Speaker 1: market moves. When it comes to the NASTAC one hundred. 17 00:01:03,800 --> 00:01:05,880 Speaker 1: Of course, we're just saying soaring into a bullmark in 18 00:01:05,880 --> 00:01:09,880 Speaker 1: the first quarter. But Morgan Stanley's Mike Wilson, he's been 19 00:01:09,920 --> 00:01:12,840 Speaker 1: warning that the rally maybe is overdone. Let's bring in 20 00:01:13,560 --> 00:01:16,280 Speaker 1: Isabel Lee just to talk about the technicals at play. 21 00:01:16,360 --> 00:01:20,319 Speaker 1: Some of the reasoning behind Isabel the movement into big tech. 22 00:01:20,480 --> 00:01:22,760 Speaker 1: It was almost like a search of safety right now, 23 00:01:23,240 --> 00:01:26,640 Speaker 1: people particularly Morgan Stanley and also JP Morgan saying that 24 00:01:26,800 --> 00:01:29,560 Speaker 1: might be time to pull back from that trade exactly. 25 00:01:29,560 --> 00:01:31,840 Speaker 1: So Morgan Stanley said it's overdone. So last week the 26 00:01:31,880 --> 00:01:34,280 Speaker 1: tech sector hit the bull market, which means it was 27 00:01:34,360 --> 00:01:36,640 Speaker 1: up twenty percent from US in December lows. But for 28 00:01:36,880 --> 00:01:38,959 Speaker 1: Mike Wilson that was just a bit too much, and 29 00:01:39,000 --> 00:01:41,160 Speaker 1: he said it's just because people were treating it as 30 00:01:41,160 --> 00:01:44,399 Speaker 1: a traditional defensive place amidst all the banking turmoil. But 31 00:01:44,440 --> 00:01:47,639 Speaker 1: he still recommends safer areas like utilities like a zoomer 32 00:01:47,680 --> 00:01:50,880 Speaker 1: sector because he also said that when something hits its trufugh, 33 00:01:51,240 --> 00:01:53,440 Speaker 1: the likelihood is it'll just rally back up. So he 34 00:01:53,440 --> 00:01:56,440 Speaker 1: said he would prefer to see more durable lows before 35 00:01:56,680 --> 00:01:59,720 Speaker 1: investors piling aggressively, but for now it's kind of an 36 00:01:59,760 --> 00:02:02,559 Speaker 1: over for him. Hey is about There's one thing, Karen, 37 00:02:02,600 --> 00:02:04,840 Speaker 1: I've learned in recent weeks around the tech sector. It's 38 00:02:04,880 --> 00:02:07,760 Speaker 1: one session a market does not make. But we're kind 39 00:02:07,760 --> 00:02:10,520 Speaker 1: of looking at economic data again. Right, we're still going 40 00:02:10,560 --> 00:02:13,240 Speaker 1: back to the same discussion around inflation and the FED. 41 00:02:14,040 --> 00:02:17,360 Speaker 1: That's exactly right, which is why people are probably thinking that, Okay, 42 00:02:17,440 --> 00:02:20,000 Speaker 1: you know, that's that's a risk. Assets are rallying because 43 00:02:20,040 --> 00:02:22,600 Speaker 1: they're like, inflation is over. We'd probably not over, but 44 00:02:22,680 --> 00:02:25,760 Speaker 1: we've hit the peak FED. We'll start cutting sometimes this year. 45 00:02:25,840 --> 00:02:28,760 Speaker 1: People have various estimates, but it's kind of bullish overall, 46 00:02:28,800 --> 00:02:31,520 Speaker 1: which is a risk. Assets are rallying now. Bitcoin is up, 47 00:02:31,560 --> 00:02:35,440 Speaker 1: It's enjoyed its best quarter seventy two percent or seventy 48 00:02:35,480 --> 00:02:39,040 Speaker 1: four percent in the past two years. All risk assets 49 00:02:39,080 --> 00:02:41,280 Speaker 1: are really up and they're just really enjoying the bounce. 50 00:02:41,360 --> 00:02:43,760 Speaker 1: And here's some good news for the bitcoin lovers. April 51 00:02:43,840 --> 00:02:47,320 Speaker 1: is usually a good month for bitcoin, actually even for stocks, 52 00:02:47,320 --> 00:02:50,639 Speaker 1: and by some measures, bitcoin was up in six out 53 00:02:50,639 --> 00:02:54,120 Speaker 1: of the last ten years. Isabelle dig in here because 54 00:02:54,160 --> 00:02:58,160 Speaker 1: you've been writing great stories together with Aldanna about well, 55 00:02:58,160 --> 00:02:59,959 Speaker 1: the lack of liquidity and bitcoin, even though we see 56 00:03:00,000 --> 00:03:02,680 Speaker 1: it's run up in price, Yes, and because there's lack 57 00:03:02,720 --> 00:03:05,840 Speaker 1: of liquidity, then the prices are more pronto volatility because 58 00:03:05,919 --> 00:03:09,119 Speaker 1: one big whale or one big move can just pull 59 00:03:09,200 --> 00:03:11,560 Speaker 1: the price lower or higher, and that's kind of been 60 00:03:11,600 --> 00:03:14,680 Speaker 1: the danger in this sector. But for now, especially with 61 00:03:14,720 --> 00:03:17,640 Speaker 1: the banking termoil, people are celebrating it because this is 62 00:03:17,680 --> 00:03:22,600 Speaker 1: why bitcoin was made. It's to circumvent all the intermediaries 63 00:03:22,639 --> 00:03:24,400 Speaker 1: to just put their trust into the thing that they 64 00:03:24,440 --> 00:03:26,920 Speaker 1: trust and not trust Wall Street. Bitcoin was born right 65 00:03:26,960 --> 00:03:29,560 Speaker 1: after the GFC, when people were mad at banks, when 66 00:03:29,560 --> 00:03:32,320 Speaker 1: people didn't trust anyone. So now it's kind of their 67 00:03:32,400 --> 00:03:35,320 Speaker 1: victory lab but it still remains to be seen whether 68 00:03:35,360 --> 00:03:39,640 Speaker 1: the banking turmoil actually push bitcoin higher. It's that's why 69 00:03:39,680 --> 00:03:42,000 Speaker 1: I love carving the space. You'll never just know why. 70 00:03:42,400 --> 00:03:44,720 Speaker 1: In particular, I'm gonna be delving into who else is 71 00:03:44,720 --> 00:03:47,120 Speaker 1: winning amid the bank tim all and wow, we've got 72 00:03:47,120 --> 00:03:49,560 Speaker 1: a VC name on talking that it's fintech in fact 73 00:03:49,560 --> 00:03:51,560 Speaker 1: as well as welly, great to have you on all 74 00:03:51,640 --> 00:03:54,240 Speaker 1: things risk assets. Let's stick with the markets though, because 75 00:03:54,280 --> 00:03:57,080 Speaker 1: actually one risk asset monkey player in the technology space, Tesla, 76 00:03:57,400 --> 00:04:00,800 Speaker 1: well it actually didn't perform particularly well in March. Today 77 00:04:00,840 --> 00:04:04,680 Speaker 1: it's weighing on the broader indices once again, Led you 78 00:04:04,760 --> 00:04:06,960 Speaker 1: are the first and foremost person I think of when 79 00:04:06,960 --> 00:04:09,160 Speaker 1: I think of Tesla. Just dig in a little bit 80 00:04:09,240 --> 00:04:13,040 Speaker 1: about why we're seeing Musk full shorten his delivery issues 81 00:04:13,080 --> 00:04:15,560 Speaker 1: even though we see the price cuts coming. Yeah. Yeah, 82 00:04:15,640 --> 00:04:18,279 Speaker 1: record deliveries in the first quarter of twenty twenty three, 83 00:04:18,400 --> 00:04:22,120 Speaker 1: four hundred and twenty three thousand evs in the first 84 00:04:22,120 --> 00:04:24,200 Speaker 1: three months of the year. It's a modest growth, right. 85 00:04:24,279 --> 00:04:26,120 Speaker 1: You look at the end of twenty twenty two, four 86 00:04:26,200 --> 00:04:29,279 Speaker 1: hundred and five thousand, it's about four percent sequentially quarter 87 00:04:29,400 --> 00:04:33,640 Speaker 1: on quarter, above street expectations. But the bigger picture is 88 00:04:33,680 --> 00:04:35,920 Speaker 1: that it does not put Tester on track for that 89 00:04:36,040 --> 00:04:38,800 Speaker 1: fifty percent annual average growth rate that Elon Musk has 90 00:04:38,839 --> 00:04:41,520 Speaker 1: talked about. It's not enough to show that demand is 91 00:04:41,560 --> 00:04:44,680 Speaker 1: still there. There are still demand concerns for the street, right, 92 00:04:44,680 --> 00:04:47,760 Speaker 1: And one point here is that Elon must talked in 93 00:04:47,800 --> 00:04:50,200 Speaker 1: the first two weeks of January about demands running at 94 00:04:50,200 --> 00:04:52,799 Speaker 1: twice the rate of production. You dig into the data 95 00:04:52,960 --> 00:04:55,159 Speaker 1: kind of seems like demand might have tapered off towards 96 00:04:55,200 --> 00:04:57,600 Speaker 1: the end of the quarter, even though the prices have 97 00:04:57,680 --> 00:05:00,799 Speaker 1: been pulled back, even though we've got well then firing 98 00:05:00,800 --> 00:05:04,040 Speaker 1: on all cylinders, which actually making the autos. What does 99 00:05:04,080 --> 00:05:08,159 Speaker 1: a backlog of potential of cars sitting around me. Yeah, 100 00:05:08,279 --> 00:05:11,520 Speaker 1: it's a profitability that's certainly the right days point. Look 101 00:05:11,520 --> 00:05:13,640 Speaker 1: at the three orange bars four inche bars here, four 102 00:05:13,720 --> 00:05:17,279 Speaker 1: straight quarter where production is greater than the number of 103 00:05:17,360 --> 00:05:20,840 Speaker 1: vehicles that Tessa's delivered. One explanation from Tesla is they're 104 00:05:20,880 --> 00:05:23,760 Speaker 1: still trying to get the mix of where these vehicles 105 00:05:23,760 --> 00:05:27,039 Speaker 1: are produced more even which results in particularly the model 106 00:05:27,120 --> 00:05:29,440 Speaker 1: Essent Model X being in transit at the end of 107 00:05:29,440 --> 00:05:32,400 Speaker 1: the quarter. You can't consider those delivered vehicles because they're 108 00:05:32,400 --> 00:05:34,359 Speaker 1: on the back of a truck. Essentially, it was the 109 00:05:34,400 --> 00:05:36,520 Speaker 1: lowest delivery level for S and X in that quarter 110 00:05:36,680 --> 00:05:38,760 Speaker 1: just gone going back to the third quarter of twenty 111 00:05:38,839 --> 00:05:42,160 Speaker 1: twenty one, So something's not quite working there. What analysts 112 00:05:42,200 --> 00:05:45,120 Speaker 1: are saying is we're worried that actually there is still 113 00:05:45,200 --> 00:05:48,320 Speaker 1: demand issue here. Remember Elon Musk has pledged that if 114 00:05:48,320 --> 00:05:51,159 Speaker 1: there is a deep recession this year, Tessa's happy to 115 00:05:51,240 --> 00:05:55,200 Speaker 1: sacrifice profit margin because they've got that strong balance sheet 116 00:05:55,320 --> 00:05:57,359 Speaker 1: and they want to keep up that steady rate of growth. 117 00:05:57,400 --> 00:05:59,960 Speaker 1: It's just that we're not seeing that steady rate of growth, 118 00:06:00,320 --> 00:06:04,279 Speaker 1: and many still worry maybe in some part that he's distracted, right, 119 00:06:04,400 --> 00:06:07,240 Speaker 1: he's distracted with the other key company that's under his 120 00:06:07,680 --> 00:06:11,000 Speaker 1: overview is Twitter, and we know that at the moment 121 00:06:11,200 --> 00:06:14,400 Speaker 1: he's in particular spot with New York Times resulted in 122 00:06:14,440 --> 00:06:17,479 Speaker 1: the paper losing its verified badge over its refusal to 123 00:06:17,560 --> 00:06:21,240 Speaker 1: pay for that one important checkmark, joining us now Bloomberg's 124 00:06:21,279 --> 00:06:24,799 Speaker 1: Asia accounts. Just how important is that checkmark for something 125 00:06:25,040 --> 00:06:29,000 Speaker 1: like New York Times the yellow badge. It's critical for 126 00:06:29,080 --> 00:06:31,240 Speaker 1: an organization like The New York Times to have that 127 00:06:31,320 --> 00:06:34,240 Speaker 1: badge because it verifies that they are, in fact a 128 00:06:34,279 --> 00:06:37,400 Speaker 1: news institution. You can imagine the challenges that could arise 129 00:06:37,600 --> 00:06:40,200 Speaker 1: if another account were to impersonate the New York Times 130 00:06:40,400 --> 00:06:43,480 Speaker 1: and start spreading false news or misinformation. So it's really 131 00:06:43,520 --> 00:06:45,680 Speaker 1: critical that they have that checkmark. I think we point 132 00:06:45,680 --> 00:06:48,359 Speaker 1: out Caroline right that Bloomberg News has said that it 133 00:06:48,400 --> 00:06:54,000 Speaker 1: won't reimburse staff to get their own Twitter Blue method 134 00:06:54,000 --> 00:06:57,240 Speaker 1: of verification. Bloomberg News and its various newsroom accounts does 135 00:06:57,279 --> 00:07:00,880 Speaker 1: have verification. What's really difficult understand is if you go 136 00:07:00,920 --> 00:07:03,000 Speaker 1: on someone's profile and hover over the blue check mark, 137 00:07:03,640 --> 00:07:07,560 Speaker 1: it's either a Twitter Blue account or it's a legacy 138 00:07:07,640 --> 00:07:09,920 Speaker 1: verified account that may or may not be notable. They 139 00:07:09,960 --> 00:07:12,080 Speaker 1: haven't taken the action that they said they would no, 140 00:07:12,240 --> 00:07:14,160 Speaker 1: and that's actually a change. Right if you were to 141 00:07:14,240 --> 00:07:16,160 Speaker 1: look a week ago, when you would hover over the badge, 142 00:07:16,160 --> 00:07:18,880 Speaker 1: you could see very clearly this person paid for Twitter 143 00:07:18,880 --> 00:07:23,200 Speaker 1: Blue or this person was a legacy verified institution or individual. 144 00:07:23,440 --> 00:07:26,720 Speaker 1: So it's actually created more confusion and we really don't know. 145 00:07:26,840 --> 00:07:29,440 Speaker 1: And they haven't taken away some of those like checkmarks 146 00:07:29,440 --> 00:07:31,920 Speaker 1: that they said they were Unapril first. They've taken away some, 147 00:07:32,040 --> 00:07:34,040 Speaker 1: but some are still out there, Kara. One thing we 148 00:07:34,080 --> 00:07:36,720 Speaker 1: discussed with Elisha on Friday was the idea that also 149 00:07:36,760 --> 00:07:39,800 Speaker 1: advertisers are kind of not very convinced by Musk. They've 150 00:07:39,880 --> 00:07:44,040 Speaker 1: kind of fled the platform. Where does this platform stand 151 00:07:44,040 --> 00:07:45,920 Speaker 1: in terms of its health because you have Elon Musk 152 00:07:46,000 --> 00:07:48,320 Speaker 1: on the other hand saying we're at record levels of 153 00:07:48,440 --> 00:07:51,240 Speaker 1: use right in terms of using numbers, Yeah, that's what's 154 00:07:51,240 --> 00:07:54,360 Speaker 1: been really interesting. They do have more daily users since 155 00:07:54,480 --> 00:07:57,160 Speaker 1: according to Musk's numbers, since the last time he released them, 156 00:07:57,400 --> 00:07:59,960 Speaker 1: but you're losing advertisers and that was about eighty nine 157 00:08:00,000 --> 00:08:02,760 Speaker 1: percent of revenue, and so Twitter Blue is seen as 158 00:08:02,760 --> 00:08:04,720 Speaker 1: a way to make back some of that revenue. But 159 00:08:05,040 --> 00:08:07,440 Speaker 1: their subscriber numbers are also really low. It's less than 160 00:08:07,480 --> 00:08:09,920 Speaker 1: one percent I think according to the last numbers. So 161 00:08:10,160 --> 00:08:12,760 Speaker 1: it's Twitter is in a really challenging position right now 162 00:08:12,760 --> 00:08:15,120 Speaker 1: and they have to either convince people to subscribe or 163 00:08:15,200 --> 00:08:17,120 Speaker 1: they're going to have to woo back those advertisers, and 164 00:08:17,160 --> 00:08:19,440 Speaker 1: neither one of those has really been going well. Do 165 00:08:19,480 --> 00:08:22,840 Speaker 1: we know any updated numbers on subscribers. I mean, this 166 00:08:22,920 --> 00:08:25,000 Speaker 1: is the joy of it being a privately held business, 167 00:08:25,080 --> 00:08:27,640 Speaker 1: But do we know if eventually people will be pushed 168 00:08:27,640 --> 00:08:30,760 Speaker 1: to make that payment. You know, analysts I've talked to 169 00:08:30,760 --> 00:08:32,719 Speaker 1: you and people in industry don't think that it will 170 00:08:32,760 --> 00:08:35,960 Speaker 1: really push the needle. We don't really know the latest numbers. Again, 171 00:08:35,960 --> 00:08:37,960 Speaker 1: it is a private company, so it's hard to tell. 172 00:08:38,120 --> 00:08:41,480 Speaker 1: There's some independent researchers that are tracking it, but from 173 00:08:41,520 --> 00:08:43,600 Speaker 1: what we know, it's less than three hundred thousand people. 174 00:08:44,160 --> 00:08:46,000 Speaker 1: We want to thank you staying on top of all 175 00:08:46,040 --> 00:08:47,839 Speaker 1: things social and I accounts. Great to have you one 176 00:08:47,920 --> 00:08:51,160 Speaker 1: once again. Meanwhile, let's talk about another form of social communication. 177 00:08:51,200 --> 00:08:54,720 Speaker 1: Former President Donald Trump said on truth Social a post 178 00:08:54,800 --> 00:08:57,160 Speaker 1: that he plans to leave mar Alago at noon today 179 00:08:57,240 --> 00:09:00,720 Speaker 1: to fly to New York ahead of his historic arraignment Inhattan. Courtroom. 180 00:09:00,760 --> 00:09:03,920 Speaker 1: That's tomorrow. Make Simone, Foxman is outside of the court house, 181 00:09:03,960 --> 00:09:05,800 Speaker 1: and Simone, do we know if in that fact he 182 00:09:05,920 --> 00:09:10,400 Speaker 1: is on route. As of yet, we haven't seen any 183 00:09:10,480 --> 00:09:13,079 Speaker 1: reports from the pool that he has actually moved out 184 00:09:13,160 --> 00:09:16,080 Speaker 1: of Marrow Lago, but we do expect him to fly 185 00:09:16,200 --> 00:09:19,560 Speaker 1: to New York later today and then come here to 186 00:09:19,679 --> 00:09:22,640 Speaker 1: Trump Tower behind me, and this is really where some 187 00:09:22,679 --> 00:09:26,240 Speaker 1: of the political theatrics could kick off. You may be 188 00:09:26,320 --> 00:09:30,120 Speaker 1: able to see there are some banners behind me. We've 189 00:09:30,120 --> 00:09:32,760 Speaker 1: seen in the last couple of minutes some Trump supporters 190 00:09:32,800 --> 00:09:35,600 Speaker 1: walking with banners and kind of lining up over there, 191 00:09:35,640 --> 00:09:38,920 Speaker 1: but there are barricades all around us. Then, of course, 192 00:09:39,280 --> 00:09:42,360 Speaker 1: the big event is when he goes south to the 193 00:09:42,559 --> 00:09:48,400 Speaker 1: DA's office to the courthouse to be arraigned, expected tomorrow afternoon. Simone, 194 00:09:48,480 --> 00:09:51,120 Speaker 1: as you say, now, moved across to Trump Tower and 195 00:09:51,160 --> 00:09:55,040 Speaker 1: looks busy. It looks like people embracing themselves. And this 196 00:09:55,120 --> 00:09:57,480 Speaker 1: is something that you've continued to report on throughout the show. 197 00:09:57,559 --> 00:09:59,679 Speaker 1: It does become a technology story in many ways, just 198 00:09:59,760 --> 00:10:02,760 Speaker 1: the in which news is consume nowadays, well very much 199 00:10:03,000 --> 00:10:05,040 Speaker 1: because you look at the stock reaction in those sort 200 00:10:05,080 --> 00:10:08,280 Speaker 1: of conservative social media platforms. They will rose Friday. I 201 00:10:08,320 --> 00:10:10,320 Speaker 1: think some of the games being given up. Now, what 202 00:10:10,360 --> 00:10:13,360 Speaker 1: we were discussing is that Trump is using true socials 203 00:10:13,440 --> 00:10:15,960 Speaker 1: communicate in real time. The rest of the world is 204 00:10:15,960 --> 00:10:19,600 Speaker 1: discussing this Simon on Twitter. Go back to the basis 205 00:10:19,640 --> 00:10:22,080 Speaker 1: for what's to come. His lawyer was pretty clear he 206 00:10:22,160 --> 00:10:28,120 Speaker 1: will hand himself in essentially, and what process happens after that. Yeah, 207 00:10:28,160 --> 00:10:32,440 Speaker 1: so essentially we're expecting him to go to the Supreme 208 00:10:32,480 --> 00:10:36,599 Speaker 1: Court House downtown. There. We don't know actually whether or 209 00:10:36,640 --> 00:10:38,679 Speaker 1: not he will walk in the front door, whether he's 210 00:10:38,679 --> 00:10:41,400 Speaker 1: going to try and stage some sort of perp walk 211 00:10:41,440 --> 00:10:45,080 Speaker 1: that he could use again for those fundraising efforts to 212 00:10:45,080 --> 00:10:46,959 Speaker 1: try and paint himself as a victim. But he will 213 00:10:47,040 --> 00:10:51,160 Speaker 1: go in there, we'll get fingerprinted, He'll likely have to 214 00:10:51,160 --> 00:10:53,480 Speaker 1: take some sort of mugshot photo, and then he'll go 215 00:10:53,559 --> 00:10:57,320 Speaker 1: upstairs where this arrangement will take place. After that, he 216 00:10:57,360 --> 00:11:01,000 Speaker 1: intends to leave New York City pretty quickly though, fly 217 00:11:01,120 --> 00:11:04,400 Speaker 1: back tomorrow lago, and then there will be a press 218 00:11:04,440 --> 00:11:07,720 Speaker 1: conference tomorrow evening, and of course at that time we'll 219 00:11:07,760 --> 00:11:10,760 Speaker 1: actually know what these charges are. They remain under seal, 220 00:11:11,080 --> 00:11:15,680 Speaker 1: and surely thereafter we will get Donald Trump's response, we 221 00:11:15,760 --> 00:11:19,560 Speaker 1: will cover every development here on Bloomberg Television, Bloomberg's own Foxman, 222 00:11:19,640 --> 00:11:29,839 Speaker 1: thank you. Out in the field reporting M and A 223 00:11:29,960 --> 00:11:33,560 Speaker 1: Monday shares a WWE sliding after Endeavor agreed to buy 224 00:11:33,600 --> 00:11:35,440 Speaker 1: the company from nine point three billion dollars if that's 225 00:11:35,480 --> 00:11:39,880 Speaker 1: including debt. WWE will combine with Endeava's Ultimate Fighting Championship 226 00:11:40,120 --> 00:11:41,880 Speaker 1: to form a new company that's going to be listed 227 00:11:41,880 --> 00:11:44,240 Speaker 1: on the New York Stock Exchange, joining US. Now for 228 00:11:44,360 --> 00:11:46,959 Speaker 1: more Spoomberg's Lucas Shaw, who, unfortunately for him, had a 229 00:11:47,000 --> 00:11:50,760 Speaker 1: busy weekend. I'm sure Lucas for the scoopman Ari Emmanuel 230 00:11:50,880 --> 00:11:53,480 Speaker 1: of Endeavor saying they will create a global life sports 231 00:11:53,480 --> 00:11:56,559 Speaker 1: and entertainment peel Play built where the industry is headed. 232 00:11:56,600 --> 00:12:01,120 Speaker 1: Where's it's headed? Well, look, they have the biggest mixed 233 00:12:01,120 --> 00:12:04,120 Speaker 1: martial arts league in the world in the Ultimate Fighting Championship, 234 00:12:04,160 --> 00:12:07,320 Speaker 1: and they now have WWE, which, while not technically a sport, 235 00:12:07,360 --> 00:12:10,360 Speaker 1: you know, it's scripted entertainment. It performs much in the 236 00:12:10,400 --> 00:12:13,600 Speaker 1: same way from a media perspective because people do show 237 00:12:13,679 --> 00:12:15,720 Speaker 1: up to watch it live, and then the ways it 238 00:12:15,720 --> 00:12:18,120 Speaker 1: makes money are very similar to UFC. You know, you 239 00:12:18,120 --> 00:12:20,319 Speaker 1: think about it. In UFC makes money from media deals, 240 00:12:20,320 --> 00:12:22,079 Speaker 1: it makes money from ticket sales, and it makes money 241 00:12:22,120 --> 00:12:25,040 Speaker 1: from sponsorships. WWE is the exact same way, and I 242 00:12:25,040 --> 00:12:27,560 Speaker 1: think they see an opportunity to sort of leverage that 243 00:12:27,760 --> 00:12:32,320 Speaker 1: combine scale in negotiations with sponsorships, certainly, and then to 244 00:12:32,360 --> 00:12:35,760 Speaker 1: find efficiencies and things like staging the events. I think 245 00:12:35,800 --> 00:12:38,240 Speaker 1: when you think about the media landscape, Lucas, you know, 246 00:12:38,280 --> 00:12:42,040 Speaker 1: many of the broadcast networks fight over being able to 247 00:12:42,040 --> 00:12:44,839 Speaker 1: show WWE. Do we have any sense of how things 248 00:12:44,920 --> 00:12:47,880 Speaker 1: now change, how they expand the offering, how they make 249 00:12:47,920 --> 00:12:52,040 Speaker 1: it more digital. You know, it's too soon to know that, 250 00:12:52,240 --> 00:12:54,800 Speaker 1: But if you look back in time, there was a 251 00:12:54,840 --> 00:12:58,520 Speaker 1: point where the WWE created its own streaming service and 252 00:12:58,600 --> 00:13:01,240 Speaker 1: then after a couple of years, decided that that wasn't 253 00:13:01,240 --> 00:13:03,600 Speaker 1: the best idea and was better to just distribute it 254 00:13:03,800 --> 00:13:06,640 Speaker 1: via the major players. So it has deals on linear 255 00:13:06,679 --> 00:13:09,440 Speaker 1: TV with the USA Network and Fox, and then it 256 00:13:09,480 --> 00:13:12,679 Speaker 1: has a streaming deal with Peacock. The TV deals are 257 00:13:12,760 --> 00:13:16,000 Speaker 1: coming up, the negotiations or we're actually supposed to start 258 00:13:16,080 --> 00:13:20,000 Speaker 1: kind of this past weekend with WrestleMania. I imagine that 259 00:13:20,040 --> 00:13:22,800 Speaker 1: now the endeavor folks will have a lot of thoughts 260 00:13:22,800 --> 00:13:24,760 Speaker 1: on what that should do. But if you look in 261 00:13:25,280 --> 00:13:27,760 Speaker 1: kind of Ri Emmanuel's track record and Mark Shapiro, who's 262 00:13:27,760 --> 00:13:29,840 Speaker 1: the president of Endeavor, you know, one of the ways 263 00:13:29,840 --> 00:13:32,280 Speaker 1: they built USC into a huge business because there were 264 00:13:32,320 --> 00:13:35,000 Speaker 1: doubts people thought that maybe they had overpaid for UFC. 265 00:13:35,440 --> 00:13:39,120 Speaker 1: Was they struct these huge deals with ESPN, And I 266 00:13:39,120 --> 00:13:41,840 Speaker 1: think they'll be able to do something similar with WWE, 267 00:13:41,840 --> 00:13:43,880 Speaker 1: depending on who the partner is. When I talk about 268 00:13:43,880 --> 00:13:46,720 Speaker 1: the owner of ESPN, because it's an all important annual 269 00:13:46,720 --> 00:13:51,760 Speaker 1: general meeting about to be upon us Lucas. Yeah. You know, look, 270 00:13:52,080 --> 00:13:55,400 Speaker 1: Disney is going through a very strange moment right now, 271 00:13:55,600 --> 00:13:59,359 Speaker 1: or perhaps an unsettling moment for investors and for employees. 272 00:14:00,000 --> 00:14:01,880 Speaker 1: You know, they're in the midst of laying off about 273 00:14:01,920 --> 00:14:04,280 Speaker 1: seven thousand employees. They did sort of one round of 274 00:14:04,320 --> 00:14:06,400 Speaker 1: that in the past couple of weeks, with much bigger 275 00:14:06,440 --> 00:14:09,640 Speaker 1: rounds to come. And then you know, current CEO Bob 276 00:14:09,760 --> 00:14:13,280 Speaker 1: Iger is both trying to restructure the company and restore 277 00:14:13,400 --> 00:14:16,160 Speaker 1: faith in it after some of the damage done by 278 00:14:16,200 --> 00:14:19,320 Speaker 1: his predecessor, Bob Chapeck, while simultaneously thinking about who his 279 00:14:19,400 --> 00:14:23,800 Speaker 1: successor should be. All Right, Bloomberg's Lucas Shure, who leads 280 00:14:24,040 --> 00:14:27,240 Speaker 1: our streaming screen time coverage. Thank you. Now, coming up 281 00:14:27,280 --> 00:14:30,120 Speaker 1: from byte Dance to Micron, Apple and beyond, we'll bring 282 00:14:30,120 --> 00:14:32,920 Speaker 1: you the headlines that you need to know in talking tech. 283 00:14:33,080 --> 00:14:36,080 Speaker 1: Speaking of take a look at shares of Micron. What 284 00:14:36,080 --> 00:14:39,000 Speaker 1: we've seen Caro in the last four sessions or so 285 00:14:39,200 --> 00:14:43,280 Speaker 1: is retaliation from China in terms of pushing back on 286 00:14:43,360 --> 00:14:46,520 Speaker 1: technology restrictions, a sort of tip attack. What the United 287 00:14:46,560 --> 00:14:50,360 Speaker 1: States is doing. Micron lower by one and a half percent. 288 00:14:50,400 --> 00:15:10,360 Speaker 1: This is Bloomberg time for talking tech, Starting with Apple 289 00:15:10,600 --> 00:15:14,080 Speaker 1: basing a billion dollar trial over its Apple Watch secrets 290 00:15:14,120 --> 00:15:17,280 Speaker 1: medical devices make a Massimo is taking the case before 291 00:15:17,320 --> 00:15:20,480 Speaker 1: a federal jury in California this week after claiming Apple 292 00:15:20,560 --> 00:15:24,880 Speaker 1: used confidential information from two former executives it hired in 293 00:15:24,960 --> 00:15:27,920 Speaker 1: certain functions and designs of its flagship Apple Watch. We 294 00:15:27,960 --> 00:15:31,480 Speaker 1: will track that trial. Revenue of TikTok's parent company, Bite 295 00:15:31,560 --> 00:15:35,120 Speaker 1: Dance surge more than thirty percent to surpass eighty billion 296 00:15:35,240 --> 00:15:37,880 Speaker 1: US dollars in twenty twenty two. That matches the tally 297 00:15:38,120 --> 00:15:41,800 Speaker 1: at arch rival ten Cent and surpasses many internet firms. 298 00:15:41,840 --> 00:15:45,360 Speaker 1: That pace of expansion underscores the resilience of Bite Dance 299 00:15:45,520 --> 00:15:48,080 Speaker 1: this business, even at a time when Washington's threatened to 300 00:15:48,200 --> 00:15:52,320 Speaker 1: join India in banning TikTok and Beijing launching a probe 301 00:15:52,320 --> 00:15:55,720 Speaker 1: into Micron, opening a new front in Beijing's chip war 302 00:15:56,000 --> 00:15:58,800 Speaker 1: with the US and Chinese chip related stocks really advancing 303 00:15:58,960 --> 00:16:02,080 Speaker 1: amid optimism that they will benefit from the nation's growing 304 00:16:02,360 --> 00:16:05,600 Speaker 1: self reliance and it's push after Beijing launched that probe 305 00:16:05,800 --> 00:16:10,040 Speaker 1: into Micron technology, Caroline well from China to the Bay 306 00:16:10,080 --> 00:16:11,840 Speaker 1: Area because we want to dig in a little bit 307 00:16:11,880 --> 00:16:15,320 Speaker 1: more and where you are currently well residing in because 308 00:16:15,360 --> 00:16:18,000 Speaker 1: it's been hit hard. We know San Francisco by the pandemic. 309 00:16:18,080 --> 00:16:20,200 Speaker 1: It's had a half time coming back as tech workers 310 00:16:20,320 --> 00:16:22,800 Speaker 1: just kept working from home. They left many of the 311 00:16:22,840 --> 00:16:25,520 Speaker 1: downtown perhaps emptier than many would have liked. And now 312 00:16:26,000 --> 00:16:28,440 Speaker 1: that old school bang run that turned the tech hub 313 00:16:28,520 --> 00:16:31,640 Speaker 1: into the center of the financial termil has just of 314 00:16:31,680 --> 00:16:35,280 Speaker 1: course still hit a city when it's down. Bloomberg San 315 00:16:35,320 --> 00:16:38,800 Speaker 1: Francisco Bureau chief Karen Breslau is with us for more 316 00:16:38,920 --> 00:16:41,480 Speaker 1: on what does this mean for San Francisco's future. You've 317 00:16:41,480 --> 00:16:44,240 Speaker 1: got a beautifully written, really thought provoking peace on the 318 00:16:44,320 --> 00:16:48,280 Speaker 1: terminal today. Thank you, Caroline. I think the storms that 319 00:16:48,320 --> 00:16:51,880 Speaker 1: have pounded the city NonStop since January really are a 320 00:16:51,920 --> 00:16:55,480 Speaker 1: metaphor for the storm of bad news that just has 321 00:16:55,560 --> 00:16:58,000 Speaker 1: hit this city over and over. I mean talked about 322 00:16:58,840 --> 00:17:01,760 Speaker 1: the you know, the bus hitting the city. Obviously, the 323 00:17:01,760 --> 00:17:05,600 Speaker 1: tech downturn was one thing, but then we had SVB 324 00:17:06,119 --> 00:17:10,000 Speaker 1: and the shakiness and the banking sector. We have the 325 00:17:10,040 --> 00:17:16,399 Speaker 1: affordability crisis, a public safety crisis and it is and 326 00:17:16,480 --> 00:17:19,119 Speaker 1: the fact that this is a city where, you know, 327 00:17:19,160 --> 00:17:22,000 Speaker 1: return to office rates are the lowest in the United States. 328 00:17:22,040 --> 00:17:24,520 Speaker 1: So it's just all hit the city at once. It's 329 00:17:24,560 --> 00:17:27,200 Speaker 1: a triple whammy. We're looking at live pictures facing down 330 00:17:27,200 --> 00:17:31,800 Speaker 1: the embarked arrow towards downtown. Two key data points, occupancy 331 00:17:32,160 --> 00:17:34,840 Speaker 1: and unemployment. What have you learned in our report take, Well, 332 00:17:34,840 --> 00:17:37,760 Speaker 1: there's a paradox there. Occupancy is a is a really 333 00:17:37,920 --> 00:17:41,640 Speaker 1: shocking twenty nine point seven percent, the highest anywhere, right, 334 00:17:41,680 --> 00:17:44,040 Speaker 1: twenty nine point seven percent of those buildings, nearly a 335 00:17:44,119 --> 00:17:47,919 Speaker 1: third are empty, and yet the unemployment rate in the 336 00:17:47,960 --> 00:17:51,959 Speaker 1: city is two point eight percent. So that is the 337 00:17:51,960 --> 00:17:55,119 Speaker 1: paradox of San Francisco. That you have so much innovation 338 00:17:55,280 --> 00:18:00,280 Speaker 1: self employment startups, and those typically are not company in 339 00:18:00,280 --> 00:18:03,160 Speaker 1: those early stages that need these giant officers. I've called 340 00:18:03,200 --> 00:18:06,160 Speaker 1: this city home for five years now, Caroline has lived 341 00:18:06,160 --> 00:18:09,760 Speaker 1: in this city. We ask ourselves the same questions, one 342 00:18:09,840 --> 00:18:12,000 Speaker 1: crisis at a different time. You spoke to the mayor, 343 00:18:12,680 --> 00:18:14,840 Speaker 1: what's her proposal to fix all of this in the 344 00:18:14,880 --> 00:18:17,400 Speaker 1: long term health? Well, her proposal, I mean she heard 345 00:18:17,480 --> 00:18:20,040 Speaker 1: her job is to be the cheerleader, and I thought 346 00:18:20,080 --> 00:18:22,680 Speaker 1: she she she gave a you know, a noble effort. 347 00:18:23,600 --> 00:18:28,080 Speaker 1: What she has talked about relentlessly is diversification. She has 348 00:18:28,200 --> 00:18:33,040 Speaker 1: always argued that this overreliance on the tech sector is 349 00:18:33,119 --> 00:18:35,680 Speaker 1: dangerous for San Francisco's economy. Of course she's right, She's 350 00:18:35,680 --> 00:18:39,120 Speaker 1: not the first person to have that observation, But she 351 00:18:39,760 --> 00:18:46,280 Speaker 1: wants to attract bioscience, life science. Tourism converts some of 352 00:18:46,280 --> 00:18:51,240 Speaker 1: these empty towers into housing, which would you know, basically 353 00:18:51,560 --> 00:18:54,679 Speaker 1: deal with two crises at once, yet is incredibly expensive 354 00:18:55,280 --> 00:18:59,520 Speaker 1: and doesn't always pencil out, so um, you know in 355 00:18:59,640 --> 00:19:01,600 Speaker 1: lord tourists. So all of that is going to take 356 00:19:01,640 --> 00:19:03,560 Speaker 1: a clean up and a perception that this is a 357 00:19:03,600 --> 00:19:07,280 Speaker 1: safe and beautiful city, and it certainly is beautiful can't 358 00:19:07,320 --> 00:19:09,760 Speaker 1: argue with that. It is it's going to take a 359 00:19:09,760 --> 00:19:13,119 Speaker 1: big marketing campaign to remind everyone of that. And the 360 00:19:13,160 --> 00:19:16,840 Speaker 1: tourists are back, ye coming, and it feels like and 361 00:19:16,920 --> 00:19:19,159 Speaker 1: that's what's sort of Also the juxtaposition here is that 362 00:19:19,200 --> 00:19:21,440 Speaker 1: when you're in some of the areas that tourists are busy, 363 00:19:21,480 --> 00:19:24,159 Speaker 1: it feels thriving, the restaurants are busy and humming. But 364 00:19:24,200 --> 00:19:27,160 Speaker 1: then you go to downtown and does feel emptier? Will 365 00:19:27,480 --> 00:19:30,480 Speaker 1: somehow the neighborhoods are hopping, well, will they feel even 366 00:19:30,480 --> 00:19:33,320 Speaker 1: emptier if you're getting meta againting some of the key 367 00:19:33,440 --> 00:19:37,560 Speaker 1: tech companies doing layoffs as well. I think it is 368 00:19:37,600 --> 00:19:40,040 Speaker 1: so empty right now, it's hard to imagine, you know, 369 00:19:40,119 --> 00:19:45,479 Speaker 1: another few thousand missing from downtown. And those employees are 370 00:19:45,480 --> 00:19:47,679 Speaker 1: also distributed, some of them in San Francisco, some of 371 00:19:47,720 --> 00:19:50,639 Speaker 1: them are at the company's headquarters south of here in 372 00:19:50,680 --> 00:19:54,960 Speaker 1: San Mateo County. But I think what has to happen is, 373 00:19:55,600 --> 00:19:58,679 Speaker 1: you know, pretty soon as the prices plummet right for 374 00:19:58,720 --> 00:20:01,719 Speaker 1: this commercial will estate, there will be a value proposition 375 00:20:01,880 --> 00:20:05,199 Speaker 1: and somebody, you know, some companies will move in the 376 00:20:05,280 --> 00:20:08,119 Speaker 1: neighborhoods are hopping. We talk about that in the story, 377 00:20:08,880 --> 00:20:12,119 Speaker 1: particularly around Hayes Valley, which is now AI Valley or 378 00:20:12,320 --> 00:20:16,159 Speaker 1: Cerebral Valley pick the brain part. Yeah, but there is action, 379 00:20:16,280 --> 00:20:19,680 Speaker 1: as Karen Bresler, who leads our coverage to California, thank 380 00:20:19,720 --> 00:20:22,240 Speaker 1: you know, coming up all things AI experts calling for 381 00:20:22,240 --> 00:20:25,439 Speaker 1: a whole to next gen development. Europe growing more cautious. 382 00:20:25,480 --> 00:20:27,360 Speaker 1: We're gonna have all the details. Were quite a big 383 00:20:27,440 --> 00:20:41,720 Speaker 1: name in the sector, Caroline, this is Bloomberg. I really 384 00:20:41,720 --> 00:20:45,000 Speaker 1: care about access and also a reinforcement of bias. But 385 00:20:45,320 --> 00:20:48,040 Speaker 1: the thing to do is to address these concerns in 386 00:20:48,200 --> 00:20:51,399 Speaker 1: like a open and transparent way, not to call for 387 00:20:51,440 --> 00:20:56,359 Speaker 1: a hall to development. Welcome back to Boomberg Technology. I'm Caroline, 388 00:20:56,400 --> 00:20:59,399 Speaker 1: had a Niel and I made Ludlow in San Francisco. 389 00:20:59,480 --> 00:21:02,440 Speaker 1: That was Fiction founder Sarah Gaw. They're saying it's important 390 00:21:02,440 --> 00:21:06,239 Speaker 1: to keep experimentation open and going in generative AI. Her 391 00:21:06,240 --> 00:21:10,120 Speaker 1: comment comes after more than a thousand AI experts industry 392 00:21:10,160 --> 00:21:13,639 Speaker 1: participants signed a petition calling for a temporary halt to 393 00:21:13,720 --> 00:21:17,920 Speaker 1: developing the next generation of AI tools. One of them 394 00:21:18,080 --> 00:21:21,439 Speaker 1: Kevin Barragoner, founder of the artificial intelligence text to image 395 00:21:21,440 --> 00:21:24,600 Speaker 1: generator deep AI, who joins me on set in San Francisco. 396 00:21:25,400 --> 00:21:30,000 Speaker 1: Why did you sign the petition? So the petition calls 397 00:21:30,200 --> 00:21:34,480 Speaker 1: for a halt to the development of extremely large generative 398 00:21:34,520 --> 00:21:37,960 Speaker 1: models like the GPD five that's in development, and this 399 00:21:40,160 --> 00:21:44,480 Speaker 1: is an incredibly disruptive technology. We don't even really know 400 00:21:44,600 --> 00:21:46,800 Speaker 1: what it will be capable of, but what we do 401 00:21:46,920 --> 00:21:52,879 Speaker 1: know is most likely advanced reasoning capabilities similar to the 402 00:21:52,960 --> 00:21:56,480 Speaker 1: human brain. So in a sense, this is just too disruptive. 403 00:21:56,800 --> 00:21:59,560 Speaker 1: I think for the current moment, there's no reason we 404 00:21:59,600 --> 00:22:03,160 Speaker 1: should really be building it right now. What's being proposed 405 00:22:03,280 --> 00:22:06,480 Speaker 1: is a six month halt in order to established a 406 00:22:06,560 --> 00:22:09,720 Speaker 1: shared set of safety protocols. There are names from all 407 00:22:09,720 --> 00:22:12,040 Speaker 1: at around the world. How do you make a six 408 00:22:12,080 --> 00:22:16,840 Speaker 1: month holt happen where all the stakeholders comply. It's an 409 00:22:16,920 --> 00:22:21,760 Speaker 1: uphill battle, certainly. I don't think even the creators of 410 00:22:21,800 --> 00:22:26,439 Speaker 1: the letter are overly optimistic. It's a big coordination problem. 411 00:22:26,560 --> 00:22:32,320 Speaker 1: But we're hopeful that all the parties around the world 412 00:22:32,359 --> 00:22:34,960 Speaker 1: will see the benefit of this type of pause, which 413 00:22:34,960 --> 00:22:37,760 Speaker 1: I don't think holds back technology more broadly. You know, 414 00:22:37,960 --> 00:22:41,400 Speaker 1: Caroline Kevin is a participant in this industry. Last week 415 00:22:41,400 --> 00:22:44,160 Speaker 1: we had VCS academics who all basically said the same, 416 00:22:44,640 --> 00:22:47,800 Speaker 1: This is really hard to pull off six months get 417 00:22:47,800 --> 00:22:52,119 Speaker 1: everyone to participate. Can I be Kevin? Therefore, just digging 418 00:22:52,119 --> 00:22:55,320 Speaker 1: a little bit as to why you, a founder of DPAI, 419 00:22:55,440 --> 00:22:58,840 Speaker 1: are saying this because could I be led to believe 420 00:22:58,880 --> 00:23:01,440 Speaker 1: that in some way open ar is a competitive threat 421 00:23:01,480 --> 00:23:05,639 Speaker 1: to you? Well, certainly they are a competitor, We have 422 00:23:05,720 --> 00:23:11,840 Speaker 1: many competitors. I don't think it's because they're a competitive threat. 423 00:23:13,000 --> 00:23:15,680 Speaker 1: And I think that this technology is so powerful it's 424 00:23:15,720 --> 00:23:19,960 Speaker 1: not going to matter who owns it or even which 425 00:23:20,040 --> 00:23:22,840 Speaker 1: country it's built in. What matters most is that it's 426 00:23:23,000 --> 00:23:26,680 Speaker 1: built at all. This is such an incredibly powerful technology 427 00:23:26,840 --> 00:23:31,280 Speaker 1: that I've started calling it the nuclear weapons of software. Okay, Kevin, 428 00:23:31,600 --> 00:23:33,280 Speaker 1: I'm going to dive back from that a little bit 429 00:23:33,359 --> 00:23:37,320 Speaker 1: because we've had academics like Emily Bender of University of 430 00:23:37,400 --> 00:23:40,280 Speaker 1: Washington on saying, look, when you are using even the 431 00:23:40,359 --> 00:23:45,040 Speaker 1: turn of phrase artificial intelligence, it just keeps doubling down 432 00:23:45,119 --> 00:23:47,720 Speaker 1: on the hype. It keeps reinforcing of you that this 433 00:23:47,880 --> 00:23:51,600 Speaker 1: is in some way a competitive to human thought. And 434 00:23:51,680 --> 00:23:55,680 Speaker 1: then actually, look, this is a worry about disinformation, yes, 435 00:23:56,160 --> 00:23:59,520 Speaker 1: but the overall power of large language models, it's Basically, 436 00:24:00,119 --> 00:24:03,560 Speaker 1: it makes sense to usk because we make it intelligent. 437 00:24:04,200 --> 00:24:07,080 Speaker 1: What do you say to that, to the stochastic power argument, 438 00:24:07,160 --> 00:24:12,080 Speaker 1: for example, I think they're rather hollow. I think these 439 00:24:12,200 --> 00:24:16,320 Speaker 1: models are absolutely intelligent. They're very general, they have advanced 440 00:24:16,440 --> 00:24:21,800 Speaker 1: reasoning capabilities in many ways that are already superhuman, and 441 00:24:22,160 --> 00:24:25,879 Speaker 1: it won't be long before they're superhuman and almost everything, 442 00:24:26,000 --> 00:24:31,000 Speaker 1: just predicting the next word, we might use, hm, that's correct, 443 00:24:32,200 --> 00:24:39,440 Speaker 1: How is that superhuman? Well, these models they know more 444 00:24:39,520 --> 00:24:43,440 Speaker 1: than any single human, and they can recall the information 445 00:24:43,560 --> 00:24:48,000 Speaker 1: much quicker, and then they have very similar reasoning capabilities 446 00:24:49,359 --> 00:24:52,879 Speaker 1: to a human. Kevin, you're a signature to Petitian. We 447 00:24:53,000 --> 00:24:55,680 Speaker 1: thank you for coming on answering our questions. Many of 448 00:24:55,760 --> 00:24:59,719 Speaker 1: those signatories did not. There is an argument I'm going 449 00:24:59,760 --> 00:25:02,840 Speaker 1: back to this Is this, sour great? Is this you 450 00:25:02,960 --> 00:25:06,879 Speaker 1: collectively recognizing open ai is so far ahead that you 451 00:25:07,000 --> 00:25:10,119 Speaker 1: need a six month period to catch up? Oh? Absolutely not. 452 00:25:12,240 --> 00:25:15,520 Speaker 1: We're super impressed with what they've built. We're actually huge 453 00:25:15,600 --> 00:25:19,320 Speaker 1: fans of them. We don't like view them as a threat. Particularly, 454 00:25:21,080 --> 00:25:24,639 Speaker 1: we just think that this technology is way too disruptive 455 00:25:24,680 --> 00:25:28,119 Speaker 1: for its own good in the present moment. Well, quickly, 456 00:25:28,160 --> 00:25:29,960 Speaker 1: I want to ask you what good has come out 457 00:25:30,000 --> 00:25:33,320 Speaker 1: of this in the last five days. I think it's 458 00:25:33,600 --> 00:25:37,760 Speaker 1: a great conversation starter. It's getting the world thinking in 459 00:25:37,880 --> 00:25:41,399 Speaker 1: the right terms because this is this is not just 460 00:25:41,600 --> 00:25:45,280 Speaker 1: like creating a new social network. This is a incredibly 461 00:25:45,480 --> 00:25:49,399 Speaker 1: disruptive new technology. I would almost like in the global issue, 462 00:25:50,200 --> 00:25:52,440 Speaker 1: almost like climate change, and that we have like a 463 00:25:52,880 --> 00:25:57,400 Speaker 1: tragedy of the comments where all of the leading AI 464 00:25:57,520 --> 00:26:00,719 Speaker 1: labs know they're creating something dangerous, but none of them 465 00:26:00,800 --> 00:26:04,760 Speaker 1: really want to stop it. Really thoughtful and thought provoking. 466 00:26:05,119 --> 00:26:09,000 Speaker 1: Thank you Kevin Barragona, his Deep ai founder core signatory 467 00:26:09,480 --> 00:26:21,439 Speaker 1: to that key piece to worry about. So the collapse 468 00:26:21,440 --> 00:26:23,680 Speaker 1: of Silicon Valley Bank has sent shock ways throughout the 469 00:26:23,760 --> 00:26:27,120 Speaker 1: banking ecosystem, and it also prompted many startups to seek 470 00:26:27,200 --> 00:26:30,800 Speaker 1: refuge in fintech solutions for support. Let's bringing Andrea Lamari 471 00:26:30,920 --> 00:26:34,639 Speaker 1: from Manhattan Ventures Partners for more on this. Now, and Andrew, 472 00:26:35,520 --> 00:26:38,920 Speaker 1: how much has fintech benefited or have we had to 473 00:26:39,000 --> 00:26:44,280 Speaker 1: raise questions about its foundations and well overall ability to 474 00:26:44,400 --> 00:26:49,840 Speaker 1: handle some of the inbound Yeah. So overall the world 475 00:26:49,880 --> 00:26:53,440 Speaker 1: of fintech and startups has really evolved quite frankly a 476 00:26:53,520 --> 00:26:56,440 Speaker 1: lot in the last few weeks. I would say generally, 477 00:26:56,520 --> 00:26:59,040 Speaker 1: which is so interesting is that we're facing what many 478 00:26:59,119 --> 00:27:02,880 Speaker 1: of us VC call the opposite of the sellery effect. 479 00:27:03,359 --> 00:27:08,159 Speaker 1: So prior to the SVB collapse, liquidity was running rampant, right, 480 00:27:08,280 --> 00:27:12,400 Speaker 1: startups were getting funding all over the place. Nowadays, startups 481 00:27:12,440 --> 00:27:16,399 Speaker 1: are being a lot more cautious around what credit and 482 00:27:16,600 --> 00:27:20,479 Speaker 1: debit looks like for them going forward, and that readily 483 00:27:20,560 --> 00:27:24,520 Speaker 1: available capital just doesn't look as liquid right going forward. 484 00:27:24,640 --> 00:27:27,879 Speaker 1: So jet generally it's a very hard time to be 485 00:27:28,000 --> 00:27:29,960 Speaker 1: a fintech, but there's a lot of solutions coming to 486 00:27:30,040 --> 00:27:32,520 Speaker 1: market that are really exciting. You of course have Clowner 487 00:27:32,560 --> 00:27:34,840 Speaker 1: on your portfolio, you'll have some other as a fintech, 488 00:27:35,160 --> 00:27:37,720 Speaker 1: which will you'll win out Because we've seen the inflows 489 00:27:37,760 --> 00:27:40,040 Speaker 1: to the likes of Brecks and to some of the 490 00:27:40,119 --> 00:27:42,280 Speaker 1: other Mercury banks, are they the ones that are going 491 00:27:42,320 --> 00:27:46,320 Speaker 1: to be winning Yeah, So I would say startups generally 492 00:27:46,400 --> 00:27:49,399 Speaker 1: have an amazing trend of trusting other startups, right. They 493 00:27:49,480 --> 00:27:52,320 Speaker 1: all know that they're in the trenches together. The solutions 494 00:27:52,400 --> 00:27:57,760 Speaker 1: like Klarna Mercury Brecks are offering really good low interest 495 00:27:57,960 --> 00:28:02,480 Speaker 1: rate products for artups to consider to support their banking 496 00:28:02,840 --> 00:28:05,600 Speaker 1: and charter that they need. So I think cash deposits 497 00:28:05,640 --> 00:28:08,520 Speaker 1: are key as well as offering just a really simple 498 00:28:08,560 --> 00:28:11,680 Speaker 1: solution to those end consumers. A lot of this, though, 499 00:28:11,760 --> 00:28:14,600 Speaker 1: of course, said it's about confidence, not only confidence in 500 00:28:14,680 --> 00:28:16,919 Speaker 1: the founders, confidence from the people putting money into these 501 00:28:16,960 --> 00:28:21,440 Speaker 1: fintech's founders, confidence from the VC's writing the checks. Yeah, 502 00:28:21,560 --> 00:28:23,600 Speaker 1: and there is a spectrum of confidence we've had on 503 00:28:23,680 --> 00:28:27,560 Speaker 1: this program, Andrea, across the bench capital community, many actually 504 00:28:27,600 --> 00:28:31,040 Speaker 1: saying no, I'm plowing on, I'm writing checks. Areas like 505 00:28:31,200 --> 00:28:35,000 Speaker 1: artificial intelligence fintech activity. It won't be at twenty twenty 506 00:28:35,040 --> 00:28:39,040 Speaker 1: one levels, but it's still there, is that what you're saying? Yeah, So, 507 00:28:39,400 --> 00:28:41,720 Speaker 1: as the job of a venture capitalist, right, if we 508 00:28:41,800 --> 00:28:43,960 Speaker 1: want to distill it down to its simplest form, our 509 00:28:44,000 --> 00:28:47,040 Speaker 1: job is to write money checks and deploy that capital 510 00:28:47,440 --> 00:28:49,840 Speaker 1: into startups. We can't just sit on it for too long. 511 00:28:50,080 --> 00:28:53,240 Speaker 1: Though the dry powder is still there, the cautious nature 512 00:28:53,280 --> 00:28:56,960 Speaker 1: of running a due diligence process has grown ever more present. 513 00:28:57,120 --> 00:29:00,160 Speaker 1: And I would say just generally the startup. If the 514 00:29:00,200 --> 00:29:03,080 Speaker 1: startups are getting the funding, I would say generally too, 515 00:29:03,160 --> 00:29:06,200 Speaker 1: though it's that they can't just rely on those depth 516 00:29:06,280 --> 00:29:10,280 Speaker 1: facilities anymore as a backstop relative to what they were 517 00:29:10,360 --> 00:29:14,200 Speaker 1: getting in venture equity dollars. So, yeah, the vcs are deploying, 518 00:29:14,480 --> 00:29:16,560 Speaker 1: they just aren't deploying as quickly as you said. Ed 519 00:29:17,960 --> 00:29:19,640 Speaker 1: later in the program, we're going to be talking about 520 00:29:19,680 --> 00:29:22,480 Speaker 1: man's return to the Moon around the moon, at least 521 00:29:22,480 --> 00:29:26,800 Speaker 1: with artemists too. You were quite early, relatively speaking into SpaceX. 522 00:29:27,280 --> 00:29:30,160 Speaker 1: Lots of reports at the moment about the saudis looking 523 00:29:30,160 --> 00:29:34,040 Speaker 1: at investing in SpaceX. What's your read on the valuation 524 00:29:34,120 --> 00:29:36,680 Speaker 1: of that company and why it's still attractive to you. 525 00:29:38,320 --> 00:29:41,480 Speaker 1: So SpaceX overall is one of the strongest companies we 526 00:29:41,680 --> 00:29:44,400 Speaker 1: see in deploying what is going to be some really 527 00:29:44,520 --> 00:29:48,120 Speaker 1: Michigan critical launches, and I think generally where the big 528 00:29:48,200 --> 00:29:52,360 Speaker 1: belief we have in seeing a massive upside potential, though 529 00:29:52,400 --> 00:29:54,400 Speaker 1: obviously it's still a private company and we have to 530 00:29:54,400 --> 00:29:57,640 Speaker 1: see where it goes, is their ability to deploy launches 531 00:29:57,760 --> 00:30:01,040 Speaker 1: successfully at a very high velocity in the coming years. 532 00:30:01,400 --> 00:30:04,959 Speaker 1: I think there's a lot of preeminent positivity around Elon's 533 00:30:04,960 --> 00:30:07,560 Speaker 1: ability to do so, and so far their success rate 534 00:30:07,880 --> 00:30:11,640 Speaker 1: relative to other companies building mission launches has been much 535 00:30:11,760 --> 00:30:15,560 Speaker 1: higher and much more repeatable than others. So overall that 536 00:30:15,720 --> 00:30:18,040 Speaker 1: overhead is still high. They're going to need to keep 537 00:30:18,120 --> 00:30:21,959 Speaker 1: raising money. We definitely imagine several more rounds of venture 538 00:30:22,040 --> 00:30:25,040 Speaker 1: funding to go there. But in terms of success and 539 00:30:25,120 --> 00:30:28,280 Speaker 1: conversion rate to successful launches, it's been elon and we 540 00:30:28,360 --> 00:30:31,040 Speaker 1: continue to believe. So when you are at the moment 541 00:30:31,600 --> 00:30:33,720 Speaker 1: seeing companies having to raise money, a lot of them 542 00:30:33,840 --> 00:30:36,239 Speaker 1: are doing it either at flat valuations, some of them 543 00:30:36,280 --> 00:30:39,200 Speaker 1: doing down rounds. We are hearing those of some companies 544 00:30:39,240 --> 00:30:41,280 Speaker 1: that have cut their valuations from a fourign nine a 545 00:30:41,400 --> 00:30:43,400 Speaker 1: perspective and then maybe trying to raise them again. I 546 00:30:43,480 --> 00:30:46,400 Speaker 1: know instacots in your portfolio. What do you make of well, 547 00:30:46,480 --> 00:30:49,640 Speaker 1: companies that are having to realign the benchmark of how 548 00:30:49,680 --> 00:30:53,040 Speaker 1: you value them. Yeah, so I would say generally, right, 549 00:30:53,320 --> 00:30:56,880 Speaker 1: that concept of the foreign nina or that internal valuation 550 00:30:57,080 --> 00:31:00,360 Speaker 1: that start upset is something that they utilize to create 551 00:31:00,440 --> 00:31:05,360 Speaker 1: a price to issue stock options to new incoming employees. Now, initially, 552 00:31:05,440 --> 00:31:09,600 Speaker 1: when startups start doing that value they do it typically 553 00:31:09,640 --> 00:31:12,240 Speaker 1: about once a year. Then, as a company grows and 554 00:31:12,280 --> 00:31:16,120 Speaker 1: it gets closer to a formal exit event, that valuation 555 00:31:16,360 --> 00:31:19,959 Speaker 1: and that four ownA is typically done typically more often 556 00:31:20,040 --> 00:31:21,959 Speaker 1: than once a year, two or three times a year. 557 00:31:22,320 --> 00:31:25,240 Speaker 1: So what that means is a company like instacart might 558 00:31:25,400 --> 00:31:28,680 Speaker 1: be doing their valuation reporting based on obviously the reports, 559 00:31:28,680 --> 00:31:31,360 Speaker 1: we're seeing a lot more than once a year in 560 00:31:31,520 --> 00:31:34,320 Speaker 1: that level of frequency. So with that said, we definitely 561 00:31:34,440 --> 00:31:39,400 Speaker 1: expect companies who experience high growth in quarterly increments or 562 00:31:39,440 --> 00:31:42,920 Speaker 1: even in half year increments to see that fluctuation in 563 00:31:43,040 --> 00:31:46,720 Speaker 1: their internal four and A valuations as material things and 564 00:31:47,320 --> 00:31:50,400 Speaker 1: milestones happen within a company, So I would definitely expect 565 00:31:50,440 --> 00:31:53,200 Speaker 1: that we see that kind of gyration happen across many 566 00:31:53,280 --> 00:31:55,920 Speaker 1: of the later stage startups that are doing more frequent 567 00:31:56,040 --> 00:32:01,160 Speaker 1: four ownin as how close for instacot is an exit? Therefore, 568 00:32:01,200 --> 00:32:04,520 Speaker 1: do you think? Well, generally, you know, as I said, 569 00:32:04,560 --> 00:32:06,440 Speaker 1: the closer you do get to an exit, the more 570 00:32:06,600 --> 00:32:10,760 Speaker 1: frequent these foreigner evaluations do occur internally. So I would 571 00:32:10,800 --> 00:32:13,240 Speaker 1: say typically companies that are on the cusp of a 572 00:32:13,480 --> 00:32:16,600 Speaker 1: one year out to give or take duration do make 573 00:32:16,720 --> 00:32:20,080 Speaker 1: sense to be doing those valuations at this level of frequency, 574 00:32:20,240 --> 00:32:23,480 Speaker 1: So that seems likely. I think a company like Instacart, 575 00:32:23,560 --> 00:32:25,880 Speaker 1: like many others in the late stage, have really stacked 576 00:32:25,920 --> 00:32:29,000 Speaker 1: their executive team and their product suite to be ready 577 00:32:29,080 --> 00:32:32,000 Speaker 1: to face the public market and provide a really compelling 578 00:32:32,320 --> 00:32:35,800 Speaker 1: narrative going into their IPO. So I think generally everyone's 579 00:32:35,800 --> 00:32:38,440 Speaker 1: just rooting for them, and if it's not them, then 580 00:32:38,560 --> 00:32:40,760 Speaker 1: one of the other large late stage companies to come 581 00:32:40,800 --> 00:32:43,680 Speaker 1: in and be a strong catalyst for the IPO growth 582 00:32:43,760 --> 00:32:47,440 Speaker 1: this year Manhattan, ben Ja Parton as Andrew Lamar, grateful 583 00:32:47,440 --> 00:32:50,880 Speaker 1: for your time coming rust from Frederico. Thank you now. 584 00:32:50,920 --> 00:32:54,320 Speaker 1: A bipartisan group of US lawmakers is taking their concerns 585 00:32:54,360 --> 00:32:57,120 Speaker 1: about China to California this week, where they plan to 586 00:32:57,160 --> 00:33:00,440 Speaker 1: meet with top tech and entertainment executives as well as 587 00:33:00,480 --> 00:33:03,880 Speaker 1: with Taiwan President sighing when. The group is being led 588 00:33:03,960 --> 00:33:07,040 Speaker 1: by Representative Mike Gallagher of Wisconsin, who chairs a new 589 00:33:07,120 --> 00:33:09,640 Speaker 1: House panel focused on China, and it will meet on 590 00:33:09,760 --> 00:33:13,880 Speaker 1: Thursday with some prominent vcs including Mark Andreeson and theod COOSLA, 591 00:33:14,120 --> 00:33:17,560 Speaker 1: as well as executives from Google, Microsoft and Palenter and 592 00:33:18,480 --> 00:33:21,600 Speaker 1: Apple Zone CEO Tim Kirk joining us with more. Bloomberg's 593 00:33:21,640 --> 00:33:24,680 Speaker 1: Dan Flatley out of Washington, folks, out of your neck 594 00:33:24,720 --> 00:33:26,200 Speaker 1: of the words, gone on the road to my neck 595 00:33:26,240 --> 00:33:29,520 Speaker 1: of the Woods. What will they talk about. Yeah, that's right. 596 00:33:29,560 --> 00:33:31,040 Speaker 1: I mean I think one of the ways to sort 597 00:33:31,080 --> 00:33:32,720 Speaker 1: of think about this is kind of like a soft 598 00:33:32,800 --> 00:33:36,120 Speaker 1: power tour. So Congress is in recess over the next 599 00:33:36,160 --> 00:33:38,880 Speaker 1: couple of weeks here in DC. Lawmakers are looking for 600 00:33:39,000 --> 00:33:41,200 Speaker 1: something to do, and they have kind of a natural 601 00:33:41,400 --> 00:33:44,440 Speaker 1: reason to be in California this week because the President 602 00:33:44,480 --> 00:33:48,240 Speaker 1: of Thailand excuse me, President of Taiwan and her visit 603 00:33:48,360 --> 00:33:52,720 Speaker 1: to California this week. So they are there in part 604 00:33:52,800 --> 00:33:55,640 Speaker 1: to meet with her, but also to sort of do 605 00:33:55,760 --> 00:33:57,480 Speaker 1: it a bit of, as I said, a soft power 606 00:33:57,560 --> 00:34:00,240 Speaker 1: tour and meet with some folks in Hollywood, eat with 607 00:34:00,320 --> 00:34:02,600 Speaker 1: some folks in Silicon Valley, and sort of make the 608 00:34:02,720 --> 00:34:06,840 Speaker 1: case to them that China represents a real threat in 609 00:34:06,880 --> 00:34:09,400 Speaker 1: their view, but also to listen to what they have 610 00:34:09,520 --> 00:34:11,520 Speaker 1: to say and sort of understand a bit more about 611 00:34:11,880 --> 00:34:14,680 Speaker 1: their market concerns and why they want to be certainly 612 00:34:14,719 --> 00:34:18,000 Speaker 1: in business in China, and how they're thinking about and 613 00:34:18,040 --> 00:34:21,120 Speaker 1: approaching their you know, their upcoming projects and things of 614 00:34:21,160 --> 00:34:23,080 Speaker 1: that nature. And don do we expect them to mainbe 615 00:34:23,080 --> 00:34:25,400 Speaker 1: be preaching to the converted. We know that Venokosla has 616 00:34:25,440 --> 00:34:28,880 Speaker 1: been in Washington for example, with Peter Teal flagging the 617 00:34:28,960 --> 00:34:32,959 Speaker 1: concerns that they share around China. Yeah, I think there's 618 00:34:33,080 --> 00:34:36,120 Speaker 1: definitely going to be an element of that. On Thursday, 619 00:34:36,200 --> 00:34:39,040 Speaker 1: they're going to be having lunch at Stanford University with 620 00:34:39,160 --> 00:34:41,960 Speaker 1: some folks that you know may have a more hawkish 621 00:34:42,040 --> 00:34:44,160 Speaker 1: view on China, but you know, when they're going to 622 00:34:44,200 --> 00:34:46,960 Speaker 1: be meeting with folks like Tim Cook or Bob Iger 623 00:34:47,320 --> 00:34:50,440 Speaker 1: at Disney and Tim Cook at Apple, they're going to 624 00:34:50,520 --> 00:34:53,640 Speaker 1: be talking to people who have really serious vested interests 625 00:34:53,800 --> 00:34:56,960 Speaker 1: in the Chinese marketplace, who may have a bit of 626 00:34:57,000 --> 00:35:00,560 Speaker 1: a different view and have the influence to talk to 627 00:35:00,760 --> 00:35:03,480 Speaker 1: lawmakers in a way that they may not be used 628 00:35:03,520 --> 00:35:05,760 Speaker 1: to being talked to, quite frankly, in a lot of respects, 629 00:35:05,800 --> 00:35:08,319 Speaker 1: because they're going to be hearing from folks who want 630 00:35:08,360 --> 00:35:11,279 Speaker 1: to continue those business lines into China and are going 631 00:35:11,360 --> 00:35:14,120 Speaker 1: to be talking to them in a way that you 632 00:35:14,200 --> 00:35:16,000 Speaker 1: know is going to be sort of informal. So it's 633 00:35:16,000 --> 00:35:18,160 Speaker 1: not going to be a congressional hearing, but it's going 634 00:35:18,200 --> 00:35:20,920 Speaker 1: to be i would say, probably a pretty strong exchange 635 00:35:20,960 --> 00:35:27,160 Speaker 1: of views down how bipartisan does this run? At this point, 636 00:35:27,239 --> 00:35:31,920 Speaker 1: I think concerns about China are about as bipartisan an 637 00:35:32,000 --> 00:35:35,000 Speaker 1: issue as you can find on Capitol Hill. Republicans and 638 00:35:35,080 --> 00:35:37,640 Speaker 1: Democrats don't agree on a lot these days, but they 639 00:35:37,760 --> 00:35:40,520 Speaker 1: certainly agree on that. I think that there are some 640 00:35:40,760 --> 00:35:46,040 Speaker 1: variations though, when you get down to how aggressive some 641 00:35:46,239 --> 00:35:50,279 Speaker 1: folks want to be. There are certainly no shortage of 642 00:35:50,360 --> 00:35:52,399 Speaker 1: hawks on the issue on either side of the aisle. 643 00:35:52,480 --> 00:35:54,919 Speaker 1: But the Republicans tend to be a little bit more 644 00:35:55,640 --> 00:35:57,520 Speaker 1: aggressive in terms of what they want to do, the 645 00:35:57,600 --> 00:36:00,680 Speaker 1: Democrats a little bit more circumspect. But as we saw 646 00:36:00,800 --> 00:36:03,000 Speaker 1: with TikTok recently, there was a hearing on that on 647 00:36:03,040 --> 00:36:05,640 Speaker 1: the Hills. I'm sure you remember a couple of weeks ago. 648 00:36:06,280 --> 00:36:09,280 Speaker 1: It goes pretty deep, and it goes across both parties, 649 00:36:10,200 --> 00:36:12,960 Speaker 1: Blue based down flatly. Thank you, Caroline. Speaking of Tim 650 00:36:13,080 --> 00:36:15,960 Speaker 1: kirk sly had caught my eye this Monday morning. The 651 00:36:16,120 --> 00:36:20,879 Speaker 1: front cover of GQ magazine Silicon Valley's quiet visionary Tim 652 00:36:21,000 --> 00:36:25,239 Speaker 1: Cook GQ Magazine, not known for his style, perhaps as 653 00:36:25,280 --> 00:36:28,600 Speaker 1: Steve Jobs, was really interesting. Read a guy starting his 654 00:36:28,680 --> 00:36:32,600 Speaker 1: day at five am, going through emails from customers the gym, 655 00:36:33,000 --> 00:36:35,040 Speaker 1: and then running the biggest tech company in the world. 656 00:36:35,160 --> 00:36:37,759 Speaker 1: What do you make of that? Do tell me, you're 657 00:36:37,800 --> 00:36:39,960 Speaker 1: only halfway through the article because it's quite a long, 658 00:36:40,960 --> 00:36:43,399 Speaker 1: it's endlessly long. But the point of it is he's 659 00:36:43,400 --> 00:36:46,320 Speaker 1: so understated. Yeah, you know, we know very little about 660 00:36:46,360 --> 00:36:49,480 Speaker 1: the man. He's not a big social media user ala 661 00:36:49,640 --> 00:36:52,600 Speaker 1: Elon Musk or something like that, and someone who was 662 00:36:52,680 --> 00:36:56,400 Speaker 1: always very upfront the saying doesn't feel normal. He's often 663 00:36:56,520 --> 00:36:58,600 Speaker 1: been feeling like an outsider. But I think what was 664 00:36:58,680 --> 00:37:01,719 Speaker 1: interesting was the way in which he was totally surprised 665 00:37:01,760 --> 00:37:04,000 Speaker 1: by the journalist perspective that people might scatter when he 666 00:37:04,080 --> 00:37:07,760 Speaker 1: walks into a room. He clearly still has that approachable nature, 667 00:37:08,000 --> 00:37:10,560 Speaker 1: people wanting to sit near him, not being intimidated in 668 00:37:10,640 --> 00:37:12,640 Speaker 1: some way. Well, there was an anecdote from Eddie Q, 669 00:37:13,000 --> 00:37:15,560 Speaker 1: who leads the services, saying that he has four faces. 670 00:37:15,640 --> 00:37:18,160 Speaker 1: He'd be brilliant at poker if he played, And I 671 00:37:18,239 --> 00:37:20,759 Speaker 1: think that says everything. You never quite know, even to 672 00:37:20,880 --> 00:37:23,640 Speaker 1: his closest allies in that company, what he's thinking. Maybe 673 00:37:23,640 --> 00:37:25,399 Speaker 1: we should ask for a game. I'm quite into poker 674 00:37:25,400 --> 00:37:28,320 Speaker 1: at the moment. Meanwhile, coming up, we'll bring you the 675 00:37:28,440 --> 00:37:31,040 Speaker 1: details on the first of NASA's new mission to the Moon, 676 00:37:31,280 --> 00:37:33,840 Speaker 1: with the astronauts just being named this morning. We're on 677 00:37:33,960 --> 00:37:36,719 Speaker 1: that next and now earlier we are discussing AI. So 678 00:37:36,920 --> 00:37:39,600 Speaker 1: let's just take a quick look at Baidu China. The 679 00:37:39,680 --> 00:37:42,719 Speaker 1: skepticism we're just talking about, of course going to Capitol Hill, 680 00:37:42,800 --> 00:37:45,800 Speaker 1: Capitol Hill lawmakers coming to California to talk China. But 681 00:37:45,880 --> 00:37:48,319 Speaker 1: there's also skepticism around the power Baidu and it's chat 682 00:37:48,360 --> 00:37:52,239 Speaker 1: GPT competition of course, the only bot will it really 683 00:37:52,320 --> 00:37:54,040 Speaker 1: be able to substantiate some of the run up in 684 00:37:54,040 --> 00:37:56,120 Speaker 1: the shares that we've seen of late down percent of 685 00:37:56,120 --> 00:38:11,120 Speaker 1: the day. The Agremberg NASA's name, the group of astronauts 686 00:38:11,160 --> 00:38:14,160 Speaker 1: it's sending to venture around the Moon on Artemus too. 687 00:38:14,239 --> 00:38:17,080 Speaker 1: It's the first crewed mission on NASA's path to establishing 688 00:38:17,120 --> 00:38:20,000 Speaker 1: a long term presence on the Moon, and we'll launch 689 00:38:20,080 --> 00:38:22,480 Speaker 1: in November of twenty twenty four at the earliest spoon bags. 690 00:38:22,520 --> 00:38:25,800 Speaker 1: Lauren grush is out in Houston. Was the announcement. Who's 691 00:38:25,840 --> 00:38:28,840 Speaker 1: heading to the Moon? Lauren right, So it's actually a 692 00:38:28,960 --> 00:38:32,239 Speaker 1: really star stutted crew that announced a name. Today. We 693 00:38:32,360 --> 00:38:37,400 Speaker 1: have two mission specialists, Christina Cook and Jeremy Hanson of Canada, 694 00:38:37,600 --> 00:38:40,640 Speaker 1: and Christina's with a NASA astra and then we have 695 00:38:40,760 --> 00:38:45,320 Speaker 1: pilot Victor Glover and Commander Red Wiseman, and just some 696 00:38:45,760 --> 00:38:48,520 Speaker 1: notable things to point out about this crew. Christina Cook 697 00:38:48,600 --> 00:38:51,240 Speaker 1: will be the first woman to go to deep space, 698 00:38:51,600 --> 00:38:53,680 Speaker 1: Victor Glover the first person of color to go to 699 00:38:53,760 --> 00:38:57,759 Speaker 1: deep space, and Jeremy will be the first non American 700 00:38:57,800 --> 00:38:59,840 Speaker 1: astronaut to go to beeB space. So it's going to 701 00:38:59,880 --> 00:39:04,680 Speaker 1: be a very historical mission for sure, historical performing on 702 00:39:04,800 --> 00:39:07,640 Speaker 1: a Luna fly by. We understand schedule for next year. 703 00:39:07,760 --> 00:39:09,560 Speaker 1: Just tell us where we are in the process of 704 00:39:10,000 --> 00:39:14,480 Speaker 1: well getting back there, right. So last year I was 705 00:39:14,600 --> 00:39:16,920 Speaker 1: at the Artemis one launch, So that was the very 706 00:39:17,000 --> 00:39:20,360 Speaker 1: first mission, the main big mission in the Artemis program, 707 00:39:20,400 --> 00:39:22,600 Speaker 1: which is to get back to the Moon, and that 708 00:39:22,719 --> 00:39:26,560 Speaker 1: one tested out the main flight hardware that will be 709 00:39:26,719 --> 00:39:29,200 Speaker 1: sending humans into these days. And now it's time to 710 00:39:29,320 --> 00:39:32,920 Speaker 1: put people on that hardware. So now that that mission 711 00:39:32,960 --> 00:39:35,520 Speaker 1: went well, we're going on to Artemis two and these 712 00:39:35,560 --> 00:39:40,600 Speaker 1: four astronauts will ride inside NASA's O'Ryan capsule on top 713 00:39:40,640 --> 00:39:44,000 Speaker 1: of the massive SLS rocket and that will take them 714 00:39:44,320 --> 00:39:47,440 Speaker 1: around the Moon and back to test it out ahead 715 00:39:47,600 --> 00:39:51,640 Speaker 1: of the historical landing that will hopefully happen sometime this decade. 716 00:39:51,719 --> 00:39:54,200 Speaker 1: Right now, it's scheduled for twenty twenty five. We'll see 717 00:39:54,200 --> 00:39:57,360 Speaker 1: if that happens. But eventually that will be the landing 718 00:39:57,480 --> 00:40:00,680 Speaker 1: on the Moon. So unfortunately these astronauts won't be howd 719 00:40:00,760 --> 00:40:02,640 Speaker 1: you now in the service book, they'll still be paving 720 00:40:02,680 --> 00:40:06,000 Speaker 1: a really important road with the ash shot ahead. Lauren 721 00:40:06,200 --> 00:40:10,040 Speaker 1: great speaking with you. Try and call down tern of course, Texas, 722 00:40:10,160 --> 00:40:12,239 Speaker 1: Lauren Grush. We thank her, and I mean not the 723 00:40:12,320 --> 00:40:15,160 Speaker 1: only bit of aerospace news upon us. It feels as 724 00:40:15,200 --> 00:40:18,520 Speaker 1: though we're talking SpaceX earlier with Manhattan Ventures. And also 725 00:40:18,640 --> 00:40:20,400 Speaker 1: that looks like there's a competitor on the scene right 726 00:40:20,520 --> 00:40:23,520 Speaker 1: end when it comes to SpaceX. Hanwa am I saying 727 00:40:23,520 --> 00:40:27,600 Speaker 1: it right? Hanwa Aerospace bringing the South Korean's first commercial 728 00:40:27,760 --> 00:40:30,840 Speaker 1: rocket and it's a pretty ambitious target. Yeah, so they 729 00:40:30,920 --> 00:40:34,719 Speaker 1: want to match SpaceX in price, getting payload to orbit 730 00:40:34,760 --> 00:40:37,360 Speaker 1: at the same price. But this is really fascinating because 731 00:40:37,440 --> 00:40:39,759 Speaker 1: they are borne out of arms sales. This is an 732 00:40:39,800 --> 00:40:45,080 Speaker 1: aerospace conglomerate essentially that's making money selling arms to Ukraine 733 00:40:45,120 --> 00:40:50,840 Speaker 1: in that conflict and putting the proceeds back into space exploration. Ambitious, 734 00:40:50,920 --> 00:40:53,080 Speaker 1: but this is a sector Carr that we're going to 735 00:40:53,120 --> 00:40:55,680 Speaker 1: cover increasingly because it's not just the money that's going 736 00:40:55,680 --> 00:41:00,560 Speaker 1: into it, global interest taking off. Knew you'd get a 737 00:41:00,560 --> 00:41:03,080 Speaker 1: pun in there somehow, And what a joy to be 738 00:41:03,160 --> 00:41:06,000 Speaker 1: reconnected once again back on the show that this edition 739 00:41:06,040 --> 00:41:08,920 Speaker 1: of Bloomberg Technology. Yeah, and there is a lot to recap. 740 00:41:09,000 --> 00:41:12,240 Speaker 1: Don't forget the podcast wherever you get your podcast, Apple, Spotify. 741 00:41:12,320 --> 00:41:15,080 Speaker 1: I heart Bloomberg so much to discuss this week in 742 00:41:15,120 --> 00:41:16,560 Speaker 1: the world of tech. This is Bloomberg