1 00:00:01,440 --> 00:00:05,120 Speaker 1: From the heart where Innovation, money and power colle in 2 00:00:05,240 --> 00:00:06,720 Speaker 1: Silicon Valley, NBN. 3 00:00:07,080 --> 00:00:11,120 Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed loved Love. 4 00:00:24,239 --> 00:00:26,440 Speaker 3: I'm Karen hide A Bloomberg's Voltec quarters in New York. 5 00:00:26,520 --> 00:00:29,560 Speaker 3: Ed Ludlow is on assignment. This is Broomberg Technology coming up. 6 00:00:29,640 --> 00:00:32,920 Speaker 3: T SMC shares jump the most. It's February despite a 7 00:00:32,960 --> 00:00:36,000 Speaker 3: global slump and chip demand and warnings of softness but 8 00:00:36,080 --> 00:00:40,440 Speaker 3: size of stabilization. We discuss Tesla risking margins in order 9 00:00:40,479 --> 00:00:43,120 Speaker 3: to boost sales volumes. The company has been cutting car 10 00:00:43,159 --> 00:00:46,200 Speaker 3: prices on a near monthly basis, and Elon Musk hinted 11 00:00:46,400 --> 00:00:49,480 Speaker 3: and more cuts to come. And SpaceX is one step 12 00:00:49,520 --> 00:00:52,480 Speaker 3: closer to getting humans to Mars after getting its starship 13 00:00:52,560 --> 00:00:55,480 Speaker 3: off the ground. We'll break down the surprise ending to 14 00:00:55,520 --> 00:00:58,400 Speaker 3: the historic launch the first. As always, we check in 15 00:00:58,440 --> 00:01:01,440 Speaker 3: on these markets and as you see, we're actually getting 16 00:01:01,440 --> 00:01:03,880 Speaker 3: some reprieve to some of the individual movers today. We 17 00:01:03,920 --> 00:01:05,880 Speaker 3: wanted to go more broad to start, but I'll go 18 00:01:05,920 --> 00:01:08,240 Speaker 3: in on the micro for the first and foremost. IBM 19 00:01:08,680 --> 00:01:11,360 Speaker 3: currently up nine tens percent as it gave a forecast 20 00:01:11,360 --> 00:01:14,360 Speaker 3: for annual revenue in line with analyst projections delivering of 21 00:01:14,400 --> 00:01:18,600 Speaker 3: cautiously optimistic sign perhaps amid this uncertain economy, LAM Research 22 00:01:18,680 --> 00:01:22,080 Speaker 3: up seven point seven percent, really managing to outperform as 23 00:01:22,080 --> 00:01:25,240 Speaker 3: some of those China curbs aren't impacting the company quite 24 00:01:25,280 --> 00:01:27,520 Speaker 3: as much as it had anticipated. Remember this has come 25 00:01:27,640 --> 00:01:30,240 Speaker 3: as we have breaking news that Biden is to unveil 26 00:01:30,400 --> 00:01:34,360 Speaker 3: China investment curbs before the G seven summit in May. 27 00:01:34,640 --> 00:01:36,720 Speaker 3: We moved back to the broader in the season nasdakov 28 00:01:36,760 --> 00:01:39,600 Speaker 3: by five tenths seven percent. We're still worried about the economy. 29 00:01:39,640 --> 00:01:42,720 Speaker 3: The headwinds we see actually signs more of those recessionary 30 00:01:42,840 --> 00:01:45,200 Speaker 3: headwinds upon us, some of the jobless claims coming in 31 00:01:45,280 --> 00:01:49,640 Speaker 3: higher than expecting, some of those business macro data not 32 00:01:49,840 --> 00:01:52,000 Speaker 3: ringing quite so strong. Today. We see the two year 33 00:01:52,040 --> 00:01:55,120 Speaker 3: yield therefore fall on the back of perhaps potential for 34 00:01:55,160 --> 00:01:57,080 Speaker 3: the Federal Reserve not have to hike quite so far 35 00:01:57,160 --> 00:01:59,680 Speaker 3: so fast. We're at four point one six bitcoin as 36 00:01:59,680 --> 00:02:01,840 Speaker 3: we see some risk aversion down by two and a 37 00:02:01,880 --> 00:02:04,760 Speaker 3: half percent. Now, all of this is as we try 38 00:02:04,800 --> 00:02:07,320 Speaker 3: to digest what's happening in LAM Research on the higher 39 00:02:07,360 --> 00:02:10,360 Speaker 3: side of things in terms of chips. But what we 40 00:02:10,400 --> 00:02:14,280 Speaker 3: saw interestingly is moved some TSMC in particular actually rising 41 00:02:14,639 --> 00:02:18,400 Speaker 3: even though perhaps we saw well signs of concern around 42 00:02:18,440 --> 00:02:21,160 Speaker 3: this business, seeing am places to say, is here with us, 43 00:02:21,400 --> 00:02:25,400 Speaker 3: just walk us through the ADRs of TSMC up even 44 00:02:25,440 --> 00:02:27,919 Speaker 3: though what we're still bottoming when it comes to the 45 00:02:27,960 --> 00:02:29,400 Speaker 3: chip cycle. According to the CEO. 46 00:02:29,720 --> 00:02:32,080 Speaker 4: Yeah, and the results were much better than feared. You 47 00:02:32,080 --> 00:02:35,919 Speaker 4: could see their pricing actually grew eleven percent, even though 48 00:02:35,960 --> 00:02:38,960 Speaker 4: way for shipments were down fifteen percent. But the pricing 49 00:02:39,000 --> 00:02:42,200 Speaker 4: held up quite nicely, which is reflected in the gross margin. 50 00:02:42,280 --> 00:02:46,440 Speaker 4: So compare TSMC's gross margin versus microns. Microns was the 51 00:02:46,520 --> 00:02:49,799 Speaker 4: worst quarter in the history of the company negative thirty 52 00:02:50,080 --> 00:02:53,000 Speaker 4: one percent in the case of TSMC, two to three 53 00:02:53,080 --> 00:02:56,040 Speaker 4: hundred basis point decline, and the pricing, like I said, 54 00:02:56,080 --> 00:02:59,040 Speaker 4: held up very well. So and they didn't cut capex 55 00:02:59,080 --> 00:03:01,760 Speaker 4: ahead of the ear there will speculation they're going to 56 00:03:01,919 --> 00:03:04,880 Speaker 4: cut their capex. That didn't happen. The room for the 57 00:03:04,960 --> 00:03:06,640 Speaker 4: reaffirm the capex for this year. 58 00:03:06,720 --> 00:03:09,160 Speaker 3: And the reason they're spending is because they have to 59 00:03:09,200 --> 00:03:12,560 Speaker 3: diversify their own supply chain for their end user, largely 60 00:03:12,600 --> 00:03:14,919 Speaker 3: because of what Joe Biden's doing in terms of executive 61 00:03:15,000 --> 00:03:17,079 Speaker 3: orders to target China US relations. 62 00:03:17,120 --> 00:03:21,040 Speaker 4: Absolutely, they have to open overseas fabs. One in Arizona, 63 00:03:21,200 --> 00:03:25,079 Speaker 4: one in Japan. They're talking about, you know, production being 64 00:03:25,160 --> 00:03:29,160 Speaker 4: live by twenty twenty four, So clearly they are diversifying. 65 00:03:29,160 --> 00:03:31,560 Speaker 4: They have no choice, and that is where the gross 66 00:03:31,560 --> 00:03:35,080 Speaker 4: margin impact may show up, because those fabs aren't going 67 00:03:35,120 --> 00:03:37,160 Speaker 4: to be as profitable as the ones they have in 68 00:03:37,200 --> 00:03:40,400 Speaker 4: Taiwan right now. So that's the longer term risk they 69 00:03:40,440 --> 00:03:44,160 Speaker 4: have because as they diversify their locations and the factories, 70 00:03:45,040 --> 00:03:47,280 Speaker 4: it will have an impact on their pricing and you 71 00:03:47,280 --> 00:03:49,560 Speaker 4: know the cost structure. So clearly that's a risk. But 72 00:03:50,000 --> 00:03:53,440 Speaker 4: they have the visibility and the commemits from their you know, 73 00:03:53,520 --> 00:03:57,520 Speaker 4: strategic partners like Apple, like Nvidia, these are the customers 74 00:03:57,520 --> 00:04:00,840 Speaker 4: of PSMC, and they have visibility for you know, demand 75 00:04:00,920 --> 00:04:05,080 Speaker 4: on like the three nanometer node, the two nanimeter node, 76 00:04:05,600 --> 00:04:09,000 Speaker 4: they will run at full utilization. I'm worried about Intel 77 00:04:09,120 --> 00:04:12,440 Speaker 4: and you know what will happen to them because of 78 00:04:12,480 --> 00:04:15,400 Speaker 4: what we solve with Micron. And I think if you 79 00:04:15,520 --> 00:04:18,480 Speaker 4: are diversified right now, you are in a good spot. 80 00:04:18,680 --> 00:04:23,159 Speaker 4: TSMC's exposure to high performance computing was forty four percent 81 00:04:23,160 --> 00:04:26,640 Speaker 4: of their revenue. Remember smartphones was the largest segment. Now 82 00:04:26,640 --> 00:04:30,479 Speaker 4: it's high performance computing. That's where the AI chips come 83 00:04:30,480 --> 00:04:32,960 Speaker 4: into play. And I think if you're not diversified right 84 00:04:33,000 --> 00:04:35,680 Speaker 4: now as a chip manufacturer, you have a problem. 85 00:04:35,720 --> 00:04:38,760 Speaker 3: So you push us perfectly forward. It's trying to sort 86 00:04:38,760 --> 00:04:40,720 Speaker 3: of read the tea leaves when an IBM is out 87 00:04:40,720 --> 00:04:43,400 Speaker 3: there saying, actually, we're a bit more upbeat despite and 88 00:04:44,040 --> 00:04:46,920 Speaker 3: you know, slowing and headwind economy. We've got companies. You 89 00:04:47,000 --> 00:04:48,120 Speaker 3: just have to be in the right place at the 90 00:04:48,160 --> 00:04:50,120 Speaker 3: right time to weather this current quarter right. 91 00:04:50,200 --> 00:04:54,120 Speaker 4: Absolutely, Autos again, Bryce autos revenue grew thirty eight percent. 92 00:04:54,240 --> 00:04:56,520 Speaker 4: Is still small, but it could be the next high 93 00:04:56,560 --> 00:05:00,680 Speaker 4: performance computing segment. Remember high performance computing was much smaller 94 00:05:00,720 --> 00:05:04,240 Speaker 4: three years back. So that's where if you're a manufacturer 95 00:05:04,560 --> 00:05:07,400 Speaker 4: you need to diversify. And I think Intel that's what 96 00:05:07,440 --> 00:05:09,120 Speaker 4: they need to show when they report earnings. 97 00:05:09,520 --> 00:05:11,520 Speaker 3: Don't tell me Internet of Things is actually becoming a 98 00:05:11,560 --> 00:05:13,839 Speaker 3: reality man, deep thing. We love them on there, just 99 00:05:13,880 --> 00:05:15,400 Speaker 3: pushing us forward to what you need to be worried 100 00:05:15,440 --> 00:05:18,000 Speaker 3: about with the next set of earnings. Let's go from 101 00:05:18,120 --> 00:05:20,880 Speaker 3: chips to evs now in terms of earnings and Tesla 102 00:05:21,200 --> 00:05:23,760 Speaker 3: actually down quite hard today after its first quarter margins 103 00:05:23,800 --> 00:05:26,000 Speaker 3: were hit by a slew of price cuts. 104 00:05:26,560 --> 00:05:30,800 Speaker 5: While we reduced prices considerably in early Q one, it's 105 00:05:30,800 --> 00:05:33,240 Speaker 5: worth noting that our operating margin remains among the best 106 00:05:33,240 --> 00:05:36,039 Speaker 5: in the industry. We've taken a view that pushing for 107 00:05:36,080 --> 00:05:39,040 Speaker 5: higher volumes and a larger fleet is the right choice 108 00:05:39,040 --> 00:05:43,160 Speaker 5: here versus a lower volume and higher margin. 109 00:05:43,560 --> 00:05:46,040 Speaker 3: Let's bring in the Wesley Group managing partner and former 110 00:05:46,120 --> 00:05:48,880 Speaker 3: Tesla board member Steve Wesley for more on this. So 111 00:05:49,440 --> 00:05:52,080 Speaker 3: is this the right course of action short term pain 112 00:05:52,560 --> 00:05:53,800 Speaker 3: for long term market share? 113 00:05:55,000 --> 00:05:56,200 Speaker 6: Well, I think it absolutely is. 114 00:05:56,279 --> 00:05:58,719 Speaker 7: I mean, look at the solid Q and results record 115 00:05:58,720 --> 00:06:01,680 Speaker 7: deliveries sold to four hundred twenty three thousand units on 116 00:06:01,760 --> 00:06:04,000 Speaker 7: a way to doing one point nine to two million 117 00:06:04,080 --> 00:06:07,359 Speaker 7: units this year. That's studying twenty three point three billion 118 00:06:07,360 --> 00:06:11,280 Speaker 7: in revenues, slightly above forecast net profit two point five 119 00:06:11,360 --> 00:06:15,560 Speaker 7: billion for the fifteenth consecutive profitable quarter, share price up 120 00:06:15,600 --> 00:06:18,680 Speaker 7: fifty one percent for the year. Aren't argue with those numbers, 121 00:06:18,920 --> 00:06:21,440 Speaker 7: but I think they're doing the right thing, cutting costs, 122 00:06:21,880 --> 00:06:23,039 Speaker 7: expanding market share. 123 00:06:23,200 --> 00:06:24,320 Speaker 6: That is a smart move. 124 00:06:24,680 --> 00:06:26,640 Speaker 3: I mean, as you say, revenue is rising it raise 125 00:06:26,680 --> 00:06:29,680 Speaker 3: twenty four percent. But you say it's hard to argue, 126 00:06:30,120 --> 00:06:33,680 Speaker 3: but investors are arguing they're cutting the overall market capitalization 127 00:06:33,720 --> 00:06:36,680 Speaker 3: of this company on the day pretty hard. What do 128 00:06:36,720 --> 00:06:38,400 Speaker 3: you think investor has got wrong? Do they just get 129 00:06:38,400 --> 00:06:40,039 Speaker 3: too ambitious in the short term? 130 00:06:40,880 --> 00:06:42,920 Speaker 7: I think there is probably a bit of a billion's 131 00:06:42,960 --> 00:06:45,000 Speaker 7: in the marketplace. But I think as people step back 132 00:06:45,000 --> 00:06:49,760 Speaker 7: and look at this, as Elon said, this is essentially 133 00:06:49,760 --> 00:06:52,080 Speaker 7: one of the most profitable auto companies in the world. 134 00:06:52,160 --> 00:06:54,960 Speaker 7: They can afford to trigger a global price for it, 135 00:06:55,000 --> 00:06:57,400 Speaker 7: and that is just what they're doing. They're taking price cuts, 136 00:06:58,200 --> 00:07:01,960 Speaker 7: prices down six times this year, already twice more in 137 00:07:02,000 --> 00:07:05,200 Speaker 7: the last thirty days. That's stunning. But they can afford 138 00:07:05,240 --> 00:07:09,000 Speaker 7: to do it. Others can't. What's interesting here people need 139 00:07:09,040 --> 00:07:12,240 Speaker 7: to understand, they say, is there a demand issue? 140 00:07:12,440 --> 00:07:15,240 Speaker 6: Absolutely not. The entire world is going all electric. 141 00:07:16,040 --> 00:07:20,840 Speaker 7: Customers bought ten million electric vehicles last year. They're projected 142 00:07:20,880 --> 00:07:23,880 Speaker 7: to be at twenty million vehicles a year within just 143 00:07:24,040 --> 00:07:26,440 Speaker 7: three years, so there's not going to be a shortage 144 00:07:26,480 --> 00:07:30,000 Speaker 7: of demand. Elon I think is smart. He's buying market 145 00:07:30,040 --> 00:07:32,160 Speaker 7: share when they can, and I think that move's. 146 00:07:31,880 --> 00:07:32,520 Speaker 6: Going to pay off. 147 00:07:32,680 --> 00:07:35,880 Speaker 3: I mean it's worth reatrating yet operating margin is down, 148 00:07:35,920 --> 00:07:38,320 Speaker 3: but it's still above eleven percent. You look at GM's 149 00:07:38,520 --> 00:07:40,720 Speaker 3: that's just six point six percent. You look at Forwards, 150 00:07:40,800 --> 00:07:44,800 Speaker 3: that's just four percent. What is there any concern around 151 00:07:44,920 --> 00:07:47,640 Speaker 3: Elon and his navigation of this company at the moment, 152 00:07:47,720 --> 00:07:51,320 Speaker 3: He's meant to be giving us the Cyberdrup production pretty soon, 153 00:07:51,640 --> 00:07:53,840 Speaker 3: but he is still kind of distracted, it feels like, 154 00:07:53,960 --> 00:07:56,680 Speaker 3: with what's going on with Twitter, and he's also got 155 00:07:56,720 --> 00:07:59,400 Speaker 3: a space company that is running and making big strides 156 00:07:59,400 --> 00:08:00,720 Speaker 3: on Well. 157 00:08:00,720 --> 00:08:05,720 Speaker 7: Look, who knows how distracted he is. Just looking at 158 00:08:05,760 --> 00:08:08,400 Speaker 7: the numbers, you've got to be pleased. Where the car 159 00:08:08,440 --> 00:08:11,360 Speaker 7: company that's going from one point three to one million 160 00:08:11,440 --> 00:08:14,360 Speaker 7: in vehicle sales last year to one point nine or 161 00:08:14,400 --> 00:08:17,520 Speaker 7: two million this year. Factually, they're just growing faster than 162 00:08:17,560 --> 00:08:22,000 Speaker 7: anybody else out there. Second, because Tesla has been smarter 163 00:08:22,360 --> 00:08:26,760 Speaker 7: and executed better on the profitability issue because of three things. First, 164 00:08:26,800 --> 00:08:30,320 Speaker 7: to bring battery production in house that lowers costs. Second, 165 00:08:30,360 --> 00:08:33,760 Speaker 7: the clear Leader and what's called Ota software. They're miles 166 00:08:33,800 --> 00:08:36,920 Speaker 7: ahead of anybody else on that. Third, the clear Leader 167 00:08:36,960 --> 00:08:40,720 Speaker 7: and the robotization of the manufacturing process. They get cars 168 00:08:40,840 --> 00:08:43,560 Speaker 7: produced in a fraction of the time of others. What 169 00:08:43,640 --> 00:08:46,000 Speaker 7: does that lead to two ex The gross margins of 170 00:08:46,040 --> 00:08:48,440 Speaker 7: Old So I get three ex. The gross margins of Toyota, 171 00:08:48,720 --> 00:08:52,520 Speaker 7: almost five x the gross margins of Ford. Now those 172 00:08:52,600 --> 00:08:54,559 Speaker 7: numbers will come down a little bit, but as long 173 00:08:54,600 --> 00:08:58,400 Speaker 7: as he can expand the Tesla name, I think Tesla's 174 00:08:58,440 --> 00:08:59,520 Speaker 7: going to be looking awfully good. 175 00:08:59,559 --> 00:09:01,439 Speaker 6: Ian's a move. 176 00:09:01,280 --> 00:09:03,040 Speaker 7: That may hurt him a little bit for the short term, 177 00:09:03,040 --> 00:09:05,440 Speaker 7: but it's going to pay big dividends for the long term. 178 00:09:05,559 --> 00:09:08,240 Speaker 3: Steve, you talk about how demand is not the issue here. 179 00:09:08,280 --> 00:09:10,760 Speaker 3: I just want to bring in another viewpoint from a 180 00:09:11,120 --> 00:09:14,800 Speaker 3: key senior equity strategist that federated Hermes. That's one Linda Distil. 181 00:09:14,880 --> 00:09:16,120 Speaker 3: Just have it Listen to what she had to say. 182 00:09:16,880 --> 00:09:19,040 Speaker 8: As we know in these last couple of years with COVID, 183 00:09:19,120 --> 00:09:21,080 Speaker 8: first she couldn't find a car, and then there were 184 00:09:21,120 --> 00:09:23,320 Speaker 8: too many cars, you know, there was a glut of 185 00:09:23,400 --> 00:09:26,040 Speaker 8: used cars, et cetera. And so now and now we 186 00:09:26,120 --> 00:09:30,040 Speaker 8: have Tesla saying basically saying, we'll sacrifice margins in the 187 00:09:30,160 --> 00:09:33,320 Speaker 8: name of using this factory space that we have. So 188 00:09:33,440 --> 00:09:37,920 Speaker 8: as long as the consumer still has money, then yeah, 189 00:09:37,960 --> 00:09:41,360 Speaker 8: that's a blessing. That's a piece of disinflation, and they'll 190 00:09:41,360 --> 00:09:43,040 Speaker 8: probably take them up on it too. 191 00:09:43,400 --> 00:09:47,520 Speaker 3: Anything Steve would make you second guess that the consumer 192 00:09:47,600 --> 00:09:50,480 Speaker 3: has money, not at all. 193 00:09:50,559 --> 00:09:52,800 Speaker 7: Look, I generally agree with what she said, but what 194 00:09:52,840 --> 00:09:55,080 Speaker 7: you've got to remember here is when Tesla first bout 195 00:09:55,080 --> 00:09:58,560 Speaker 7: out the Model three, for example, all out the door, 196 00:09:58,679 --> 00:10:02,120 Speaker 7: it was about a sixt car. Today it's at forty thousand, 197 00:10:02,200 --> 00:10:05,080 Speaker 7: and with government stimulus, it's really down to and state 198 00:10:05,120 --> 00:10:07,560 Speaker 7: stimulus that are also available down to about thirty two 199 00:10:07,559 --> 00:10:10,160 Speaker 7: to thirty three thousand. This is getting pretty close to 200 00:10:10,160 --> 00:10:14,320 Speaker 7: where Honda Accord is. At those prices, there is not 201 00:10:14,480 --> 00:10:17,440 Speaker 7: going to be any demand issue, and I think that's 202 00:10:17,440 --> 00:10:20,880 Speaker 7: why long term, Elon's making the right move. 203 00:10:21,160 --> 00:10:22,680 Speaker 3: What do you want to see from Elon in terms 204 00:10:22,679 --> 00:10:25,840 Speaker 3: of his own investment now in terms of continuing to 205 00:10:25,920 --> 00:10:30,080 Speaker 3: expand production, because when they had their sort of great 206 00:10:30,280 --> 00:10:33,240 Speaker 3: master plan that they just came out with earlier this year, 207 00:10:33,400 --> 00:10:36,160 Speaker 3: it felt like some of the production levels were just extraordinary. 208 00:10:37,200 --> 00:10:38,319 Speaker 6: Well they are extraordinary. 209 00:10:38,559 --> 00:10:41,359 Speaker 7: You've got to look at most of the other competitors, 210 00:10:41,480 --> 00:10:44,280 Speaker 7: GM four, they have one or two EV plants up 211 00:10:44,320 --> 00:10:47,680 Speaker 7: and running. Tesla already has four gigafactories, a new one 212 00:10:47,679 --> 00:10:50,240 Speaker 7: in moderate coming which will be up literally in less 213 00:10:50,280 --> 00:10:54,640 Speaker 7: than twelve months. New battery plants in Shanghai and later 214 00:10:54,760 --> 00:10:59,000 Speaker 7: have already online. So Tesla, simply put, is just moving 215 00:10:59,200 --> 00:11:01,400 Speaker 7: faster than other You got to give them credit for that. 216 00:11:01,760 --> 00:11:04,680 Speaker 7: Just look at the numbers of comparison. You know, in 217 00:11:04,720 --> 00:11:10,800 Speaker 7: the honorable mentioned category of Bard announced ten thousand evy 218 00:11:10,960 --> 00:11:13,400 Speaker 7: unit sales compared to four hundred and twenty three thousand 219 00:11:13,480 --> 00:11:18,280 Speaker 7: for Tesla General Motors at twenty thousand. They're not catching up, 220 00:11:18,400 --> 00:11:21,840 Speaker 7: they're falling further behind. The fascinating news if we step 221 00:11:21,880 --> 00:11:24,280 Speaker 7: back and look at it is the major competitors to 222 00:11:24,320 --> 00:11:29,479 Speaker 7: Tesla are two Chinese companies, buyd and Sais. 223 00:11:29,760 --> 00:11:33,000 Speaker 6: This is a global changing of the guard, and. 224 00:11:32,960 --> 00:11:37,560 Speaker 7: I think investors should look back and see really three things. First, 225 00:11:37,760 --> 00:11:42,560 Speaker 7: Tesla's extending their lead. Second, the Chinese are coming quickly, 226 00:11:43,040 --> 00:11:47,320 Speaker 7: and third, a lot of these smaller firms Canoe and 227 00:11:47,400 --> 00:11:50,480 Speaker 7: Fisker and so on Lordstown, they're just going to have 228 00:11:50,520 --> 00:11:53,800 Speaker 7: a hard time making the cut. I think Ewe is 229 00:11:53,880 --> 00:11:56,880 Speaker 7: pressing consolidation in the industry, and I think he's going 230 00:11:56,920 --> 00:11:58,319 Speaker 7: to be the winner when all is said and. 231 00:11:58,280 --> 00:12:00,080 Speaker 3: Done, Steve, I just want to drill it on that 232 00:12:00,240 --> 00:12:02,560 Speaker 3: really interesting point about China. We know that actually some 233 00:12:02,679 --> 00:12:05,560 Speaker 3: Chinese demands and frustrated by the price cuts, but the 234 00:12:05,640 --> 00:12:09,160 Speaker 3: Chinese investment is there. We know commitment to Shanghai, for example, 235 00:12:09,200 --> 00:12:12,360 Speaker 3: not only with car production but battery production. Are you 236 00:12:12,480 --> 00:12:15,360 Speaker 3: worried about geopolitics here? We just hear that President Biden 237 00:12:15,400 --> 00:12:18,760 Speaker 3: will unveil China investment curbs before the G seven summit. 238 00:12:18,800 --> 00:12:21,640 Speaker 3: He doesn't want US companies like Tesla investing in China. 239 00:12:22,400 --> 00:12:24,760 Speaker 6: Yeh, Look, there's a tailor two cities here. 240 00:12:25,559 --> 00:12:30,440 Speaker 7: On the upside, China's the world's largest auto market, and 241 00:12:30,559 --> 00:12:34,440 Speaker 7: Tesla has moved quickly put to manufacturing facility there, and 242 00:12:34,520 --> 00:12:36,199 Speaker 7: Tesla is killing it in China. 243 00:12:37,600 --> 00:12:40,800 Speaker 6: The flip side of that curve is, if there's. 244 00:12:40,679 --> 00:12:45,520 Speaker 7: Ever a real estrangement, a geopolitical crisis, and anything like 245 00:12:45,559 --> 00:12:48,400 Speaker 7: what happened in the Ukraine where Russia nationalized a lot 246 00:12:48,400 --> 00:12:50,120 Speaker 7: of our companies, Tesla would be in a world of 247 00:12:50,200 --> 00:12:53,880 Speaker 7: hurt because forty percent of their capacity comes from China today. 248 00:12:54,160 --> 00:12:56,200 Speaker 7: But in the meantime, if you want to win in 249 00:12:56,240 --> 00:12:58,400 Speaker 7: the auto industry, you've got to be playing in China. 250 00:12:58,559 --> 00:13:00,000 Speaker 6: It is the largest market in the world. 251 00:13:00,000 --> 00:13:04,360 Speaker 7: World seven of the top ten bigger selling evs are 252 00:13:04,480 --> 00:13:08,280 Speaker 7: Chinese names. So right now, Tesla's played the game well. 253 00:13:08,320 --> 00:13:09,959 Speaker 7: And I think if you're elin Mask, you have to 254 00:13:10,000 --> 00:13:13,120 Speaker 7: be going to bed every night playing praying that the 255 00:13:13,960 --> 00:13:15,800 Speaker 7: cord work with China doesn't get worse. 256 00:13:16,160 --> 00:13:18,360 Speaker 6: Right now, he's looking awfully smart. We'll see. 257 00:13:18,440 --> 00:13:19,800 Speaker 3: I'm not sure he's in a bed. I think he's 258 00:13:19,840 --> 00:13:23,120 Speaker 3: on a sofa somewhere on a Twitter. Obviously, we'll be 259 00:13:23,360 --> 00:13:26,480 Speaker 3: in the factory maybe when he gets his few hours asleep. 260 00:13:26,520 --> 00:13:28,880 Speaker 3: We thank you so much, the Wesley Group managing partner, 261 00:13:29,000 --> 00:13:32,559 Speaker 3: Steve Wesley, They're great to have you. Meanwhile, let's talk 262 00:13:32,559 --> 00:13:35,120 Speaker 3: about it. President Joe Biden aiming to sign an executive 263 00:13:35,160 --> 00:13:37,960 Speaker 3: order in the coming weeks there will limit investment in 264 00:13:38,040 --> 00:13:41,520 Speaker 3: key parts of China's economy by US businesses. And that's all. 265 00:13:41,520 --> 00:13:44,360 Speaker 3: According to sources, the administration has been debating the measure 266 00:13:44,400 --> 00:13:46,640 Speaker 3: for almost two years now, and it plans to take 267 00:13:46,679 --> 00:13:49,120 Speaker 3: action before a summit of the Group of Seven that's 268 00:13:49,160 --> 00:14:01,480 Speaker 3: true to start on May nineteenth. In Japan. SpaceX's Starship 269 00:14:01,600 --> 00:14:04,480 Speaker 3: Rocket I didn't quite complete its mission on a second 270 00:14:04,520 --> 00:14:08,240 Speaker 3: launch attempt starship appeared to explode in the sky several 271 00:14:08,240 --> 00:14:11,280 Speaker 3: minutes after lifting off from the facility over at Bocachico 272 00:14:11,320 --> 00:14:14,520 Speaker 3: in Texas. More on these events, we joined Bublomgg's law 273 00:14:14,559 --> 00:14:17,200 Speaker 3: and Grush, who was just at the launch site earlier, 274 00:14:17,240 --> 00:14:20,160 Speaker 3: and Elon Musk himself set expectation. He said, look, as 275 00:14:20,200 --> 00:14:22,280 Speaker 3: long as we don't blow up the launch pad, and 276 00:14:22,560 --> 00:14:24,160 Speaker 3: they didn't know they didn't. 277 00:14:24,200 --> 00:14:26,720 Speaker 9: They actually got pretty far away from the launch pad, 278 00:14:26,720 --> 00:14:28,760 Speaker 9: and I will say from the ground it was a 279 00:14:29,120 --> 00:14:33,320 Speaker 9: spec spectacular site well before the explosion happened. I mean, 280 00:14:33,360 --> 00:14:35,920 Speaker 9: we could feel the rumble in our chest of those 281 00:14:35,920 --> 00:14:38,240 Speaker 9: thirty three engines. Though I think when I looked at 282 00:14:38,280 --> 00:14:40,680 Speaker 9: the livestream later not all of those thirty three engines 283 00:14:40,680 --> 00:14:42,400 Speaker 9: you can see on the screen were actually a light. 284 00:14:42,520 --> 00:14:45,440 Speaker 10: So there were some engine problems. I think apparently we'd 285 00:14:45,520 --> 00:14:49,280 Speaker 10: like some more confirmation from SpaceX. But yes, they did. 286 00:14:49,120 --> 00:14:52,320 Speaker 9: Get valuable data, hopefully just from being able to clear 287 00:14:52,400 --> 00:14:53,160 Speaker 9: the launch pad. 288 00:14:53,360 --> 00:14:55,200 Speaker 10: But yeah, something didn't quite go right. 289 00:14:55,280 --> 00:14:59,440 Speaker 9: Around two and a half minutes into flight, the stages 290 00:14:59,480 --> 00:15:02,920 Speaker 9: were host to separate and instead the rockets. 291 00:15:02,600 --> 00:15:06,200 Speaker 10: Seemed to vere wildly for. 292 00:15:08,440 --> 00:15:12,280 Speaker 3: Sit there. Oh, I think we're taking some hits on 293 00:15:12,320 --> 00:15:14,120 Speaker 3: this line, Lauren, I'll just ask one more question and 294 00:15:14,160 --> 00:15:17,000 Speaker 3: hopefully your line stabilizes a little bit. But SpaceX did 295 00:15:17,120 --> 00:15:21,960 Speaker 3: say the experience a rapid unscheduled disassembly before stage separation, 296 00:15:22,240 --> 00:15:25,680 Speaker 3: So nuance there push us forward. We knew that there 297 00:15:25,720 --> 00:15:28,400 Speaker 3: was a delay. They then came on four twenty, which 298 00:15:28,440 --> 00:15:30,000 Speaker 3: we know is a key day for you, a musk 299 00:15:30,080 --> 00:15:33,000 Speaker 3: in many ways. What do we expect next? A little 300 00:15:33,040 --> 00:15:35,360 Speaker 3: bit more description of what went wrong and then the 301 00:15:35,360 --> 00:15:35,960 Speaker 3: next test light. 302 00:15:36,040 --> 00:15:37,520 Speaker 10: I guess yeah. 303 00:15:37,520 --> 00:15:40,080 Speaker 9: For me personally, I really want to know what actually 304 00:15:40,160 --> 00:15:42,840 Speaker 9: caused the mishap, you know, why did the stage separation 305 00:15:43,000 --> 00:15:44,280 Speaker 9: not occur as planned? 306 00:15:44,640 --> 00:15:46,720 Speaker 10: What was going on with those engines that appeared to 307 00:15:46,720 --> 00:15:47,160 Speaker 10: be out? 308 00:15:47,400 --> 00:15:49,800 Speaker 9: And then also I'd like to know from SpaceX whether 309 00:15:49,880 --> 00:15:52,320 Speaker 9: or not, you know, the rocket broke up on its own, 310 00:15:52,400 --> 00:15:55,360 Speaker 9: or if they terminated the rocket personally with the flight 311 00:15:55,440 --> 00:15:57,960 Speaker 9: termination system. It's a system they can use to blow 312 00:15:58,040 --> 00:16:00,720 Speaker 9: up the rocket to protect you know, the un public. 313 00:16:01,080 --> 00:16:03,280 Speaker 9: And then yes, you know, how will they incorporate the 314 00:16:03,360 --> 00:16:06,320 Speaker 9: lessons learned from this flight into the next flight that 315 00:16:06,360 --> 00:16:08,480 Speaker 9: they do, which I believe Elon said would happen in 316 00:16:08,480 --> 00:16:11,120 Speaker 9: the next few months. So very much, looking forward to 317 00:16:11,160 --> 00:16:13,480 Speaker 9: the timeline, and then I'll show the root cars of 318 00:16:13,520 --> 00:16:14,960 Speaker 9: this issue. 319 00:16:15,200 --> 00:16:19,240 Speaker 3: Extraordinary. We continue to keep across all of it with 320 00:16:19,240 --> 00:16:21,240 Speaker 3: our own layngrase. We thank you so much for making 321 00:16:21,280 --> 00:16:24,880 Speaker 3: the time. Meanwhile, let's turn our attention to the financial 322 00:16:24,880 --> 00:16:27,640 Speaker 3: world for a moment, because the American Express set aside 323 00:16:27,760 --> 00:16:30,040 Speaker 3: well a little bit more cash to cover any possible 324 00:16:30,120 --> 00:16:33,280 Speaker 3: loan losses as the economy starts to slow. That did 325 00:16:33,440 --> 00:16:35,680 Speaker 3: ultimately weigh on some of the earnings. Even though the 326 00:16:35,680 --> 00:16:39,240 Speaker 3: CEO would say, look, this is just a normalization. Shares 327 00:16:39,360 --> 00:16:43,080 Speaker 3: fell despite expending volume still climbing fourteen percent. I got 328 00:16:43,120 --> 00:16:46,000 Speaker 3: to have a chat with ceosd squay about investments in 329 00:16:46,080 --> 00:16:48,760 Speaker 3: financial technology in particular, and he said, no, we had 330 00:16:48,880 --> 00:16:51,600 Speaker 3: AI in our models forever, in our credit models and 331 00:16:51,600 --> 00:16:55,080 Speaker 3: our four models. How we market to our customer. Where 332 00:16:55,080 --> 00:16:57,800 Speaker 3: we're thinking about AI even more now is in our 333 00:16:57,840 --> 00:17:01,640 Speaker 3: customer service. And of course sort of maybe chuckle with 334 00:17:01,640 --> 00:17:03,400 Speaker 3: the fact that look, the new technology a couple of 335 00:17:03,480 --> 00:17:05,640 Speaker 3: years ago was all about blockchain. Now it's all about 336 00:17:05,680 --> 00:17:08,720 Speaker 3: new tech that is GPT. And he in particularly is 337 00:17:08,720 --> 00:17:11,200 Speaker 3: saying they're looking at the stuff for a while, and oh, 338 00:17:11,200 --> 00:17:13,240 Speaker 3: we'll just have to do it in a controlled way 339 00:17:13,400 --> 00:17:16,399 Speaker 3: and make sure you find the right business case. Have 340 00:17:16,520 --> 00:17:18,200 Speaker 3: much more on what anx CEO had to say a 341 00:17:18,200 --> 00:17:20,359 Speaker 3: little bit later in the two pm hour mean while 342 00:17:20,359 --> 00:17:23,320 Speaker 3: coming up and look at today's big take, which I 343 00:17:23,359 --> 00:17:26,560 Speaker 3: have to say exposes the dangers of TikTok's algorithm to 344 00:17:26,640 --> 00:17:59,720 Speaker 3: troubled teams. This is a Bloomberg Today's Bloombog big take. 345 00:18:00,040 --> 00:18:02,560 Speaker 3: It's an emotional one. It sheds light on the ways 346 00:18:02,560 --> 00:18:05,600 Speaker 3: in which TikTok's personal feed can actually be a never 347 00:18:05,720 --> 00:18:09,119 Speaker 3: ending stream of anxiety of negativity. As part of her 348 00:18:09,200 --> 00:18:12,040 Speaker 3: series on TikTok and it's trust and safety issues Bloombags, 349 00:18:12,080 --> 00:18:15,200 Speaker 3: Olivia Carvill writes that the app's algorithm has led teenagers 350 00:18:15,640 --> 00:18:19,760 Speaker 3: down rabbit holes related to self harm, to depression, human suicide. 351 00:18:20,080 --> 00:18:23,840 Speaker 3: Lisa Say Olivia joins me now and it's heart wrenching 352 00:18:23,840 --> 00:18:26,199 Speaker 3: this story a mother having to after the death of 353 00:18:26,200 --> 00:18:29,520 Speaker 3: her child, look at what terms he searched for on 354 00:18:29,640 --> 00:18:33,959 Speaker 3: an app such as TikTok, He's search for Batman, basketball, weightlifting. 355 00:18:34,720 --> 00:18:35,640 Speaker 3: What did he get instead? 356 00:18:36,680 --> 00:18:40,400 Speaker 1: What Chase nescal was seen as a stream of content 357 00:18:40,480 --> 00:18:45,600 Speaker 1: about anxiety, depression, unrequired love, self harm and in some 358 00:18:45,680 --> 00:18:50,560 Speaker 1: cases suicide. I actually watched this account and it's still 359 00:18:50,600 --> 00:18:55,640 Speaker 1: sending their content today. It was really difficult to see 360 00:18:56,040 --> 00:18:58,280 Speaker 1: what he would have seen in to try and put 361 00:18:58,320 --> 00:19:00,920 Speaker 1: yourself in the shows of a teenage boy watching never 362 00:19:01,040 --> 00:19:03,960 Speaker 1: ending streams of really sad videos. 363 00:19:04,840 --> 00:19:08,760 Speaker 3: What there for does this say about an algorithm that 364 00:19:09,840 --> 00:19:12,840 Speaker 3: in many ways people turn to TikTok for joy, for hilarity, 365 00:19:12,960 --> 00:19:16,760 Speaker 3: for fun. Why is this happening to vulnerable teenage children? 366 00:19:17,080 --> 00:19:19,480 Speaker 1: And that's what his parents kept asking is they thought 367 00:19:19,520 --> 00:19:22,919 Speaker 1: TikTok was about creating joy, that's the company's slogan. They 368 00:19:22,960 --> 00:19:26,200 Speaker 1: thought it was funny, happy dance videos. And when I 369 00:19:26,320 --> 00:19:29,160 Speaker 1: went to meet them in Long Island earlier this year, 370 00:19:29,680 --> 00:19:32,320 Speaker 1: they asked that question of where are the happy videos? 371 00:19:32,640 --> 00:19:34,679 Speaker 1: You know, we were looking at his account together and 372 00:19:34,760 --> 00:19:36,919 Speaker 1: what it's still being sent today and there are no 373 00:19:37,080 --> 00:19:40,840 Speaker 1: happy videos coming through. TikTok said that it has worked 374 00:19:40,840 --> 00:19:43,320 Speaker 1: on this specific issue, and it's been working on it 375 00:19:43,359 --> 00:19:48,080 Speaker 1: for years, trying to break up repetitive videos about sad topics, 376 00:19:48,359 --> 00:19:52,800 Speaker 1: whether that's depression or eating disorders or suicide related content. 377 00:19:53,200 --> 00:19:56,400 Speaker 1: But effectively, what this account shows us is that those 378 00:19:56,440 --> 00:19:59,960 Speaker 1: efforts have fallen short. In some cases they haven't worked. 379 00:20:00,640 --> 00:20:04,480 Speaker 3: TikTok have responded. You've had a spokesmen in particular speech 380 00:20:04,520 --> 00:20:06,760 Speaker 3: to you seeing they're committed to safety the well being 381 00:20:06,800 --> 00:20:11,800 Speaker 3: of its users, but especially teens. Researchers and child's coologists. 382 00:20:11,840 --> 00:20:13,840 Speaker 3: They're getting more and more anxious about this, aren't they? 383 00:20:14,119 --> 00:20:17,880 Speaker 3: What steps? Can anything be done? From a regulatory perspective? 384 00:20:17,880 --> 00:20:20,040 Speaker 3: Where next goes in your reporting journey? 385 00:20:20,760 --> 00:20:22,720 Speaker 1: Well, I think one of the biggest concerns for child 386 00:20:22,720 --> 00:20:27,760 Speaker 1: psychologists and researchers is that we're seeing this looming youth 387 00:20:27,840 --> 00:20:31,600 Speaker 1: mental health crisis. We're seeing new data showing that kids 388 00:20:31,640 --> 00:20:36,639 Speaker 1: are experiencing higher levels of hopelessness, of suicidal thoughts, of anxiety, 389 00:20:37,080 --> 00:20:40,879 Speaker 1: and alongside that we're seeing explosive use of social media. 390 00:20:41,040 --> 00:20:44,280 Speaker 1: So while causation is very hard to prove, the correlation 391 00:20:44,480 --> 00:20:47,399 Speaker 1: is right there in front of us, and that begs 392 00:20:47,400 --> 00:20:50,400 Speaker 1: the question of what more can be done. TikTok isn't 393 00:20:50,440 --> 00:20:53,240 Speaker 1: the only platform that has a recommendation engine that is 394 00:20:53,280 --> 00:20:56,520 Speaker 1: pushing harmful content to kids, and one of the calls 395 00:20:56,560 --> 00:20:59,679 Speaker 1: that we've seen time and time again from researchers is 396 00:20:59,720 --> 00:21:03,760 Speaker 1: given us transparency, let us study your algorithm. Let us 397 00:21:03,840 --> 00:21:07,080 Speaker 1: understand how it works, what drives it, what powers it. 398 00:21:07,520 --> 00:21:10,440 Speaker 1: Right now, these companies aren't willing to provide that kind 399 00:21:10,480 --> 00:21:14,640 Speaker 1: of transparency to researchers, and that is frustrating the academic community. 400 00:21:14,680 --> 00:21:18,560 Speaker 1: They feel locked out from studying a phenomenon that is 401 00:21:18,640 --> 00:21:21,399 Speaker 1: impacting millions of kids around the world. 402 00:21:22,200 --> 00:21:25,040 Speaker 3: Olivia, you keep bringing us transparency and we thank you 403 00:21:25,080 --> 00:21:28,160 Speaker 3: for it. It's an amazing read, heart wrenching one. Olivia 404 00:21:28,200 --> 00:21:39,000 Speaker 3: Carvill Welcome back to remote technology. I'm Caroline Hider, New York. 405 00:21:39,040 --> 00:21:41,359 Speaker 3: Let's go quick check on these markets for you, because 406 00:21:41,359 --> 00:21:43,720 Speaker 3: we are still under pressure from a big tech perspective. 407 00:21:43,760 --> 00:21:45,160 Speaker 3: Now it's that one hundred coming off of its lows. 408 00:21:45,200 --> 00:21:46,880 Speaker 3: We're still off by a quarter of percent. We're worried 409 00:21:46,920 --> 00:21:50,600 Speaker 3: about economic gloom, the jobless claims to king Hire, some 410 00:21:50,680 --> 00:21:53,439 Speaker 3: of the business, macro data not looking quite as pretty. 411 00:21:53,520 --> 00:21:56,080 Speaker 3: So instead of that bad news being good news in 412 00:21:56,160 --> 00:21:58,240 Speaker 3: terms of the FED, today's bad news is bad news 413 00:21:58,280 --> 00:22:00,720 Speaker 3: and we're worried about the economy. Money off the table, 414 00:22:00,760 --> 00:22:02,600 Speaker 3: we take money off out of Microsoft, off by a 415 00:22:02,640 --> 00:22:04,760 Speaker 3: quarter of percent, not big move. Remember, just after the 416 00:22:04,760 --> 00:22:07,359 Speaker 3: World yesterday, We've got some news that Elon Musk was 417 00:22:07,400 --> 00:22:10,960 Speaker 3: potentially threatening Microsoft with a lawsuit over Twitter's data use 418 00:22:10,960 --> 00:22:13,800 Speaker 3: when it's training its AI algorithms. But we're off by 419 00:22:13,800 --> 00:22:15,720 Speaker 3: a quarter of percent. More broadly with the market today, 420 00:22:15,760 --> 00:22:18,480 Speaker 3: Alphabet Cherzo on the flip side. Remember they've sort of 421 00:22:18,480 --> 00:22:20,600 Speaker 3: been the underdog when it comes to AI, but Alphabet 422 00:22:20,640 --> 00:22:22,600 Speaker 3: seems to be on the rise a little bit. Maybe 423 00:22:22,760 --> 00:22:25,520 Speaker 3: plan to use generative AI to create ad campaigns according 424 00:22:25,560 --> 00:22:27,360 Speaker 3: to the ft or up one and a quarter. Let's 425 00:22:27,359 --> 00:22:30,480 Speaker 3: move it on to look at the other previous area 426 00:22:30,520 --> 00:22:32,639 Speaker 3: of exuberance when it came to tech, and it was 427 00:22:32,680 --> 00:22:35,080 Speaker 3: all about crypto. Of course, Bitcoin off by two point 428 00:22:35,119 --> 00:22:38,200 Speaker 3: three percent, were sub thirty thousand afterwards. Been a spectacular 429 00:22:38,240 --> 00:22:40,480 Speaker 3: run up so far this year. Maybe some calm coming 430 00:22:40,480 --> 00:22:42,760 Speaker 3: out of as we start seeing some resiliency to the 431 00:22:42,840 --> 00:22:45,520 Speaker 3: financial market, in particularly the banking market here in the 432 00:22:45,600 --> 00:22:48,560 Speaker 3: United States. There's those earnings come in and we see 433 00:22:48,600 --> 00:22:50,600 Speaker 3: a little bit of weakness just in the world of 434 00:22:50,640 --> 00:22:53,200 Speaker 3: eth we're off by one and a half percent, down 435 00:22:53,200 --> 00:22:56,119 Speaker 3: below that two thousand mark. Let's talk a little bit 436 00:22:56,119 --> 00:22:58,320 Speaker 3: more about crypto, not so much the price moves on 437 00:22:58,320 --> 00:23:00,280 Speaker 3: the day, but the future of regulation. I need to 438 00:23:00,280 --> 00:23:02,840 Speaker 3: say emmel Na Cole joins us for what is some 439 00:23:03,560 --> 00:23:06,280 Speaker 3: movement at last when it comes to regulation. But over 440 00:23:06,359 --> 00:23:08,520 Speaker 3: in Europe, can you talk us through what's being decided 441 00:23:08,560 --> 00:23:10,920 Speaker 3: at the moment in terms of the first EU sort 442 00:23:10,960 --> 00:23:14,320 Speaker 3: of package that seems to be coming towards tech and 443 00:23:14,400 --> 00:23:15,760 Speaker 3: crypto startups over there. 444 00:23:17,680 --> 00:23:17,880 Speaker 11: Yeah. 445 00:23:17,960 --> 00:23:21,040 Speaker 2: So, the EU has been working on its crypto legislative 446 00:23:21,080 --> 00:23:24,160 Speaker 2: package for the last three years and it's finally here. 447 00:23:24,760 --> 00:23:27,960 Speaker 2: The European Parliament formally approved the final text of the 448 00:23:28,000 --> 00:23:31,320 Speaker 2: Markets in Crypto Assets Regulation also known as MEKA MICA 449 00:23:31,440 --> 00:23:36,080 Speaker 2: depending on your pronunciation earlier today, and what that includes 450 00:23:36,160 --> 00:23:38,399 Speaker 2: is basically a bill of rules that means that now 451 00:23:38,440 --> 00:23:41,680 Speaker 2: crypto company is seeking to operate from the EU will 452 00:23:41,720 --> 00:23:44,119 Speaker 2: need to register in one of the member states and 453 00:23:44,160 --> 00:23:47,119 Speaker 2: that then allows them the right to passport those approvals 454 00:23:47,119 --> 00:23:49,919 Speaker 2: across the entire block. It also seeks to put in 455 00:23:49,960 --> 00:23:53,760 Speaker 2: place some risk management and corporate governance structures so that 456 00:23:53,840 --> 00:23:56,440 Speaker 2: companies are able to kind of operate within the EU 457 00:23:56,600 --> 00:24:00,000 Speaker 2: under the purview of supervisory authorities and in a bid 458 00:24:00,040 --> 00:24:02,280 Speaker 2: to avoid another FTX style collapse. 459 00:24:02,640 --> 00:24:05,439 Speaker 3: Yeah, it felt like the talk was pretty tough coming 460 00:24:05,560 --> 00:24:08,720 Speaker 3: from the shadow representative of micro or micro or how 461 00:24:08,760 --> 00:24:10,680 Speaker 3: have you set saying, you know, to provide a safe 462 00:24:10,680 --> 00:24:14,560 Speaker 3: haven no longer to forsters and criminal organizations. But really 463 00:24:14,600 --> 00:24:17,760 Speaker 3: a unified way of regulating crypto has got to be 464 00:24:17,880 --> 00:24:20,200 Speaker 3: joy to many founder's ears in some way. 465 00:24:21,960 --> 00:24:25,320 Speaker 2: The crypto industry as a whole is generally very happy 466 00:24:25,359 --> 00:24:28,239 Speaker 2: about MECA because in their eyes it's any rules at 467 00:24:28,240 --> 00:24:30,679 Speaker 2: all are good rules. And when we say that, we mean, 468 00:24:30,720 --> 00:24:32,840 Speaker 2: you know, bespoke cause to crypto. In the eyes of 469 00:24:32,880 --> 00:24:35,480 Speaker 2: the industry it's something that doesn't really fit into existing 470 00:24:35,520 --> 00:24:36,480 Speaker 2: financial services. 471 00:24:36,680 --> 00:24:39,000 Speaker 10: But not every regulator agrees those proposed. 472 00:24:39,040 --> 00:24:41,160 Speaker 2: In the UK, for example, the rules that were set 473 00:24:41,200 --> 00:24:43,840 Speaker 2: up by the government earlier this year, those would seek 474 00:24:43,840 --> 00:24:46,800 Speaker 2: to fit crypto under existing financial services rules. And we'd 475 00:24:46,840 --> 00:24:49,399 Speaker 2: heard Gary Genza in the US earlier this week saying 476 00:24:49,400 --> 00:24:52,920 Speaker 2: that crypto should fit under the existing financial services rules 477 00:24:52,960 --> 00:24:55,360 Speaker 2: in the US. But the companies when they come into 478 00:24:55,359 --> 00:24:57,000 Speaker 2: the SEC and talk to them about it, just don't 479 00:24:57,040 --> 00:24:58,000 Speaker 2: really like what they're hear it. 480 00:24:58,359 --> 00:25:00,320 Speaker 3: Yeah, and no wonder Therefore, Europe's been taking bit of 481 00:25:00,359 --> 00:25:03,800 Speaker 3: market share in terms of crypto venture funding. Emily Nicole, 482 00:25:04,040 --> 00:25:07,399 Speaker 3: we thank you so much, and really for crypto the 483 00:25:07,880 --> 00:25:11,240 Speaker 3: real cloud has been regulatarly uncertainty here in the US. 484 00:25:11,320 --> 00:25:14,639 Speaker 3: But sticking on crypto, we've had a lot about the 485 00:25:14,640 --> 00:25:17,879 Speaker 3: cryptosphere choosing Miami if you are building in the US 486 00:25:18,200 --> 00:25:20,120 Speaker 3: to be one of its key hubs. In fact, Bitcoin 487 00:25:20,160 --> 00:25:23,040 Speaker 3: Miami is around the corner. It's not just crypto has 488 00:25:23,080 --> 00:25:25,720 Speaker 3: emerged as one of several rising hubs and take at large. 489 00:25:25,760 --> 00:25:29,359 Speaker 3: It's born about by the pandemic shifting work trends, of course. 490 00:25:29,560 --> 00:25:31,359 Speaker 3: So today we want to focus in on Miami a 491 00:25:31,400 --> 00:25:34,080 Speaker 3: little bit. The Emerge America's conference is kicking off in 492 00:25:34,400 --> 00:25:38,280 Speaker 3: Miami right now. Bring vcs, tech entrepreneurs together for two days. 493 00:25:38,600 --> 00:25:43,280 Speaker 3: Let's bring in the Emerge America CEO Flucio Garrado, wonderful 494 00:25:43,280 --> 00:25:44,960 Speaker 3: tab some time with you. You've also been nominated as 495 00:25:45,000 --> 00:25:46,800 Speaker 3: the US representative on the board of the World Bank 496 00:25:46,840 --> 00:25:50,520 Speaker 3: Group by President Joe Biden. So some big tasks at hand. 497 00:25:50,640 --> 00:25:54,280 Speaker 3: Fluccio Filicia, talk to us a little bit about what's 498 00:25:54,280 --> 00:25:56,760 Speaker 3: happening about the signature event. You launched it back in 499 00:25:56,760 --> 00:25:58,920 Speaker 3: twenty fourteen. How many people are you expecting? 500 00:26:00,440 --> 00:26:03,000 Speaker 12: Yeah, well, thank you first Caroline for having me on. 501 00:26:03,720 --> 00:26:07,960 Speaker 12: Emerge America's was founded in twenty fourteen with a singular 502 00:26:07,960 --> 00:26:13,280 Speaker 12: focus to transform Miami into me a global tech hub. 503 00:26:13,359 --> 00:26:16,120 Speaker 12: And we do that by convening all stakeholders that make 504 00:26:16,200 --> 00:26:20,879 Speaker 12: up any thriving tech ecosystem, from government to higher startups 505 00:26:20,920 --> 00:26:24,400 Speaker 12: to investors, and we connect the dots between the entrepreneurs, 506 00:26:24,440 --> 00:26:27,400 Speaker 12: the capital, and the talent, and we tell the stories 507 00:26:27,440 --> 00:26:28,720 Speaker 12: of how South Florida. 508 00:26:28,359 --> 00:26:30,400 Speaker 11: And the rehole is transforming. 509 00:26:31,359 --> 00:26:36,080 Speaker 12: We're doing this specifically to capitalize on this very moment, 510 00:26:36,640 --> 00:26:39,760 Speaker 12: and so today we have more than twenty thousand attendees 511 00:26:39,760 --> 00:26:42,840 Speaker 12: from all around the world that are convenient here to 512 00:26:42,880 --> 00:26:49,040 Speaker 12: showcase their new startups, their investments, and to make those 513 00:26:49,520 --> 00:26:52,800 Speaker 12: connections to help take their businesses to the next level. 514 00:26:53,680 --> 00:26:56,600 Speaker 12: I would say, you know, talking a little bit about 515 00:26:57,400 --> 00:27:02,520 Speaker 12: or dovetailing from your previous speaker. If last year was 516 00:27:02,560 --> 00:27:08,040 Speaker 12: all about blockchain, this year is all out AI. We've 517 00:27:08,040 --> 00:27:12,200 Speaker 12: got literally the guy who wrote the Bible on AI, 518 00:27:12,520 --> 00:27:16,080 Speaker 12: the former CEO and chairman of Google SMID, who will 519 00:27:16,080 --> 00:27:20,760 Speaker 12: be keynoting tomorrow. And I just got on stage with 520 00:27:21,880 --> 00:27:27,280 Speaker 12: the seventh time football champion, real entrepreneur and best selling 521 00:27:27,320 --> 00:27:31,280 Speaker 12: author Tom Brady, who was our opening keynote this morning. 522 00:27:31,280 --> 00:27:34,120 Speaker 3: Okay, but interestingly, Felicia of course I would associate Tom 523 00:27:34,160 --> 00:27:37,760 Speaker 3: Brady more with crypto with blockchain, so is he pivoting 524 00:27:37,800 --> 00:27:40,280 Speaker 3: to AI as well? I mean, how are you seeing 525 00:27:40,600 --> 00:27:43,240 Speaker 3: what has been real build up in VC money being 526 00:27:43,280 --> 00:27:46,600 Speaker 3: allocated to Miami perhaps taking a hit from twenty twenty 527 00:27:46,600 --> 00:27:49,480 Speaker 3: two like the rest of the tech world because of 528 00:27:49,520 --> 00:27:51,840 Speaker 3: the pullback in crypto VC money. 529 00:27:53,400 --> 00:27:55,879 Speaker 12: Well that's a great question, but it's actually more of 530 00:27:55,880 --> 00:27:57,920 Speaker 12: a myth. The reality is the data. 531 00:27:57,760 --> 00:27:58,920 Speaker 11: Speaks for itself. 532 00:27:59,440 --> 00:28:02,080 Speaker 12: Miami has led the nation in terms of venture growth, 533 00:28:02,240 --> 00:28:05,720 Speaker 12: being number one in the nation for venture activity since 534 00:28:05,760 --> 00:28:08,000 Speaker 12: the start of the pandemic. While the rest of the 535 00:28:08,000 --> 00:28:12,240 Speaker 12: world to be contracting, Miami actually only continues to expand. 536 00:28:12,720 --> 00:28:15,200 Speaker 12: We've grown about two hundred and forty eight percents since 537 00:28:15,200 --> 00:28:19,600 Speaker 12: the start of the pandemic. And while investments as continue 538 00:28:19,640 --> 00:28:22,800 Speaker 12: to focus on fintech, we also have been one of 539 00:28:23,119 --> 00:28:25,760 Speaker 12: the leading health tech hubs, and I would say and 540 00:28:25,920 --> 00:28:31,840 Speaker 12: argue also for climate tech, with this being also incredibly 541 00:28:31,840 --> 00:28:35,800 Speaker 12: important to our community and to the region as a whole. 542 00:28:35,960 --> 00:28:39,280 Speaker 3: But surely money must be pulling back and in a way, 543 00:28:39,400 --> 00:28:42,240 Speaker 3: I mean, has the money that in terms of sponsorship 544 00:28:42,280 --> 00:28:45,040 Speaker 3: coming for your event pulled back any compared to twenty 545 00:28:45,080 --> 00:28:45,520 Speaker 3: twenty two. 546 00:28:47,000 --> 00:28:49,600 Speaker 12: That's actually a great question, and the reality is no, 547 00:28:50,360 --> 00:28:54,680 Speaker 12: we are actually pacing ahead of where we were in 548 00:28:54,760 --> 00:29:02,040 Speaker 12: twenty twenty two. We've have more enterprise tech companies like Microsoft, 549 00:29:02,080 --> 00:29:05,720 Speaker 12: Google and delf for startups who've taken up more space 550 00:29:05,760 --> 00:29:09,520 Speaker 12: on our expo floor, who also partner with us year round. 551 00:29:10,120 --> 00:29:12,840 Speaker 12: We're not just an event, we're a platform, and so 552 00:29:12,920 --> 00:29:17,560 Speaker 12: we organize start a pitch competitions, innovation challenges, investor summits 553 00:29:17,880 --> 00:29:18,400 Speaker 12: year round. 554 00:29:18,760 --> 00:29:21,320 Speaker 11: And these tech leaders are. 555 00:29:21,200 --> 00:29:24,600 Speaker 12: Not just planting a flag here in South Florida, they're 556 00:29:24,600 --> 00:29:27,000 Speaker 12: looking to also expand their footprint. 557 00:29:27,240 --> 00:29:30,280 Speaker 3: Apparently resilient to the macro trends. We thank you so much. 558 00:29:30,320 --> 00:29:35,560 Speaker 3: Emerging America CEO Felicio Garado there. Meanwhile, coming up, we'll 559 00:29:35,560 --> 00:29:38,000 Speaker 3: take a further look at the Miami VC scene. Actually, 560 00:29:38,000 --> 00:29:41,240 Speaker 3: Sapphire Adventures, one of the partners, Casba Wang's over there 561 00:29:41,240 --> 00:29:43,160 Speaker 3: at the event. We're going to talk about or whether 562 00:29:43,160 --> 00:29:46,400 Speaker 3: they're putting boots on the ground in Miami. Plus particularly 563 00:29:46,520 --> 00:29:50,760 Speaker 3: look at one particular Latin company, Marcardo Libra. The shares 564 00:29:51,200 --> 00:29:53,640 Speaker 3: well of a quarter of a percent, but some interesting 565 00:29:53,680 --> 00:29:55,520 Speaker 3: moves in terms of how much they're building up. It's 566 00:29:55,520 --> 00:29:58,040 Speaker 3: the largest e commerce company over there in Latin America 567 00:29:58,120 --> 00:30:02,240 Speaker 3: and it's fucking tech layoffs, adding thirteen thousand workers this year. 568 00:30:02,840 --> 00:30:27,640 Speaker 3: This is a bloomberg time now for our VC roundup. Starting 569 00:30:27,640 --> 00:30:30,400 Speaker 3: with Tiger Global top point seven billion dollar benure fund 570 00:30:30,440 --> 00:30:33,160 Speaker 3: that has is recording a twenty percent paper loss as 571 00:30:33,240 --> 00:30:35,800 Speaker 3: of December twenty twenty two. That's all according to the information. 572 00:30:36,240 --> 00:30:38,520 Speaker 3: It's taking a hit of course from the FTX fancracy, 573 00:30:38,640 --> 00:30:41,480 Speaker 3: so as the NFTs in the company's portfolio. On the 574 00:30:41,520 --> 00:30:45,200 Speaker 3: positive side, JP Morgan is closing its inaugural Growth Equity 575 00:30:45,240 --> 00:30:47,960 Speaker 3: Fund with over one billion dollars in aggregate capital commitments 576 00:30:48,280 --> 00:30:51,280 Speaker 3: eighty percent which is available to deploy in new investment 577 00:30:51,280 --> 00:30:55,440 Speaker 3: opportunities and to help its portfolio companies scale. And let's 578 00:30:55,480 --> 00:30:58,200 Speaker 3: stick with the VC scene a little bit more and funding. 579 00:30:58,440 --> 00:31:00,840 Speaker 3: Let's get back to Emerge America's comfort Over in Miami, 580 00:31:01,040 --> 00:31:04,800 Speaker 3: Crypto tech workers moving there, so did VC deals. Therefore, 581 00:31:05,160 --> 00:31:06,920 Speaker 3: so Miami is not at the level of the biggest 582 00:31:06,960 --> 00:31:08,480 Speaker 3: hubs like here in New York or over in the 583 00:31:08,480 --> 00:31:11,360 Speaker 3: Bay Area. I'm bringing only a fraction of the deals 584 00:31:11,360 --> 00:31:14,600 Speaker 3: compared to these major hubs. According to pitchbook will bring 585 00:31:14,640 --> 00:31:17,520 Speaker 3: in more. That's our someone on underground, Kasba Wang's their 586 00:31:17,560 --> 00:31:21,080 Speaker 3: partner at Safire Adventures. We want you to read about 587 00:31:21,120 --> 00:31:24,160 Speaker 3: what the opportunities are in Miami because Safi Adventures doesn't 588 00:31:24,200 --> 00:31:27,040 Speaker 3: have an office there, right, but are you making investments there? 589 00:31:28,440 --> 00:31:30,560 Speaker 11: Thanks first, well, thanks for having me on Caroline. 590 00:31:31,360 --> 00:31:33,680 Speaker 13: You know, we don't have offers in Miami, but we 591 00:31:33,720 --> 00:31:36,280 Speaker 13: constantly look for opportunities that are outside of the Bay 592 00:31:36,320 --> 00:31:38,960 Speaker 13: Area and New York and some of the core tech markets. 593 00:31:39,280 --> 00:31:42,280 Speaker 13: I would say the invasion here at Emerge as well 594 00:31:42,280 --> 00:31:45,520 Speaker 13: as the broader Miami city has been amazing, and I've 595 00:31:45,520 --> 00:31:48,240 Speaker 13: got the opportunity to title a lot of founders INBC, 596 00:31:48,480 --> 00:31:53,120 Speaker 13: specifically in certain areas like crypto, AI and developer tools 597 00:31:53,120 --> 00:31:53,440 Speaker 13: and all that. 598 00:31:54,120 --> 00:31:59,160 Speaker 3: Of course, you're largely sort of focusing on bigger, later 599 00:31:59,240 --> 00:32:02,320 Speaker 3: stage company is what are the opportunities for that in AI? 600 00:32:02,400 --> 00:32:05,080 Speaker 3: We were just hearing from the CEO of Emerged saying 601 00:32:05,120 --> 00:32:07,520 Speaker 3: this year it's pivoted from all things crypto into all 602 00:32:07,560 --> 00:32:10,760 Speaker 3: things artificial intelligence. What sort of companies attract you? 603 00:32:11,960 --> 00:32:15,000 Speaker 13: Yeah, one hundred andtent So, you know, we think AI 604 00:32:15,200 --> 00:32:18,360 Speaker 13: is a super trend for the decade, next decade to come. 605 00:32:18,920 --> 00:32:21,920 Speaker 13: In the short term though, however, you know, the processes 606 00:32:22,040 --> 00:32:25,080 Speaker 13: that are being disrupted by AI in the short term 607 00:32:25,200 --> 00:32:28,480 Speaker 13: from a value creation perspective, are actually better captured by 608 00:32:28,480 --> 00:32:31,400 Speaker 13: incumbents to some extent. Right, So let's say, you know, 609 00:32:31,800 --> 00:32:34,920 Speaker 13: if you're trying to build the next generation salesforce, salesforce 610 00:32:35,000 --> 00:32:36,520 Speaker 13: by adding AI on top. 611 00:32:36,440 --> 00:32:38,200 Speaker 11: Coul potentially do better than a company. 612 00:32:38,400 --> 00:32:40,800 Speaker 13: So I look for companies and founders that are a 613 00:32:40,880 --> 00:32:44,000 Speaker 13: unique take on AI and how to apply AI to 614 00:32:44,080 --> 00:32:45,320 Speaker 13: certain business processes. 615 00:32:45,640 --> 00:32:46,520 Speaker 11: And the way I think. 616 00:32:46,320 --> 00:32:49,560 Speaker 13: About this is, you know, compared to let's say the Internet, right, 617 00:32:49,960 --> 00:32:53,920 Speaker 13: we don't have new speed as a way of consuming 618 00:32:54,000 --> 00:32:56,160 Speaker 13: content from the Internet all the way onto your Facebook 619 00:32:56,400 --> 00:32:59,360 Speaker 13: came up the content news feed, So we're still waiting 620 00:32:59,360 --> 00:33:02,120 Speaker 13: for that big more for long term value creation. I 621 00:33:02,120 --> 00:33:05,040 Speaker 13: can already see multiple pockets where AI could really come 622 00:33:05,080 --> 00:33:09,640 Speaker 13: in and create real value and disrupt existing business prophecies. 623 00:33:10,000 --> 00:33:13,760 Speaker 3: Casmer, lend us your expertise as to how you're sorting 624 00:33:13,800 --> 00:33:16,720 Speaker 3: week from chaff, because there's an awful lot of people 625 00:33:16,760 --> 00:33:20,000 Speaker 3: who is suddenly an AI company or an AI startup 626 00:33:20,120 --> 00:33:23,200 Speaker 3: that weren't a few months ago. So how you ensuring 627 00:33:23,240 --> 00:33:26,920 Speaker 3: that what they're building is really changing the way in 628 00:33:26,960 --> 00:33:28,320 Speaker 3: which productivity could be. 629 00:33:29,360 --> 00:33:32,720 Speaker 13: Yeah, Caroline, this is a great question. This space is emerging, 630 00:33:32,760 --> 00:33:35,280 Speaker 13: sol fask. Frankly, it's very hard at track, even from 631 00:33:35,320 --> 00:33:38,920 Speaker 13: an investment perspective, right we at Saftware Adventures, we've started, 632 00:33:38,960 --> 00:33:41,960 Speaker 13: We've been investing in AI for last decade almost, So 633 00:33:42,040 --> 00:33:44,320 Speaker 13: this is not a brand new thing. It's just the 634 00:33:44,400 --> 00:33:48,080 Speaker 13: GENERVD models themselves have been a new way to interact 635 00:33:48,120 --> 00:33:52,200 Speaker 13: with human beings and add certain chat functions that are familiar, 636 00:33:52,440 --> 00:33:55,360 Speaker 13: familiar to the users themselves. So for me, I really 637 00:33:55,400 --> 00:33:57,720 Speaker 13: look for one again, a founder that has a unique 638 00:33:57,760 --> 00:34:01,360 Speaker 13: take on a specific problem, So not necessarily just starting 639 00:34:01,360 --> 00:34:05,560 Speaker 13: from technology, but starting from the business problem itself. That's 640 00:34:05,680 --> 00:34:07,640 Speaker 13: that's probably number one, and the number two from a 641 00:34:07,680 --> 00:34:11,640 Speaker 13: pure technological standpoint, I'd like to understand how they differentiate 642 00:34:11,760 --> 00:34:15,600 Speaker 13: from the incombent solutions. Right, Better it's a distribution advantage. Better, 643 00:34:15,680 --> 00:34:18,319 Speaker 13: it's you know, pure technological advantage. Do they have a 644 00:34:18,360 --> 00:34:20,680 Speaker 13: new take on distribution Because at the end of the day, 645 00:34:20,719 --> 00:34:24,040 Speaker 13: again going back to my point earlier, AI, you know, 646 00:34:24,160 --> 00:34:27,680 Speaker 13: just applying to existing business process doesn't solve the distribution 647 00:34:27,800 --> 00:34:32,080 Speaker 13: problem and in Combent's own distribution, So that's a big thing. 648 00:34:32,280 --> 00:34:34,440 Speaker 13: I keep seeing companies and then I keep trying to 649 00:34:34,520 --> 00:34:38,080 Speaker 13: challenge founders on what's their unique take on this Ksber. 650 00:34:38,480 --> 00:34:41,360 Speaker 3: What's interesting is what seems to have the crypto world 651 00:34:41,440 --> 00:34:45,759 Speaker 3: really concern right now is regulatory lack of clarity. And 652 00:34:46,360 --> 00:34:48,480 Speaker 3: we still have a lot of concerns. Let's say, in 653 00:34:48,520 --> 00:34:50,560 Speaker 3: the way in which AI is currently being built, the 654 00:34:50,560 --> 00:34:53,319 Speaker 3: ethical nature in which it can be scaled. Do you 655 00:34:53,360 --> 00:34:56,560 Speaker 3: worry about regulation? How do you see the CEOs, the 656 00:34:56,560 --> 00:34:58,480 Speaker 3: founders you're talking to navigate that one. 657 00:34:59,719 --> 00:35:01,440 Speaker 11: Yeah, that's a that's a great question. 658 00:35:01,800 --> 00:35:04,200 Speaker 13: Again, I think, you know, first of all, I think 659 00:35:04,200 --> 00:35:06,920 Speaker 13: AI statey should be top of mind for both. 660 00:35:06,760 --> 00:35:09,040 Speaker 11: Regulators and builders at the same time. 661 00:35:09,360 --> 00:35:11,799 Speaker 13: I think in the value there's the sense of, you know, 662 00:35:12,040 --> 00:35:14,200 Speaker 13: you try to build first and ask for forgiveness later 663 00:35:14,320 --> 00:35:17,000 Speaker 13: sort of thing. And I think that philosophy and mentality 664 00:35:17,360 --> 00:35:21,239 Speaker 13: doesn't necessarily apply to AI. Now we are, you know, 665 00:35:21,360 --> 00:35:23,640 Speaker 13: despite the fact that in some sense we're kind of 666 00:35:23,640 --> 00:35:27,319 Speaker 13: closed to AGI, you know, we're not that closed yet, 667 00:35:27,400 --> 00:35:29,120 Speaker 13: So we are we do have some time to. 668 00:35:29,080 --> 00:35:31,560 Speaker 11: Figure this out from a framework perspective. 669 00:35:31,920 --> 00:35:34,440 Speaker 13: Well, we do want to see some real clarity around. 670 00:35:34,760 --> 00:35:37,200 Speaker 13: You know, regulars come in and draw the lane for 671 00:35:37,640 --> 00:35:41,440 Speaker 13: companies and founders to play within that lane. And you 672 00:35:41,480 --> 00:35:44,560 Speaker 13: know that just takes time and takes practice, and given 673 00:35:44,600 --> 00:35:48,160 Speaker 13: how fast is spaced is evolving, I'm assuming the regulations 674 00:35:48,160 --> 00:35:50,839 Speaker 13: probably will come not this year, but that year. 675 00:35:51,560 --> 00:35:54,280 Speaker 3: You specialize partnering the B to be SaaS companies as well. 676 00:35:55,160 --> 00:35:58,320 Speaker 3: That isn't just all things AI. There's things like cybersecurity. 677 00:35:58,440 --> 00:36:02,080 Speaker 3: You go to old, good old kind of almost economic 678 00:36:02,160 --> 00:36:06,239 Speaker 3: resilient building of cyber companies. Where else is attracting you? 679 00:36:06,239 --> 00:36:08,439 Speaker 3: Because it can't just be checks being written to AI, 680 00:36:08,560 --> 00:36:09,080 Speaker 3: or can. 681 00:36:08,920 --> 00:36:10,760 Speaker 11: It one hundred percent? 682 00:36:10,800 --> 00:36:13,040 Speaker 13: Look, I would say, going back to my point on AI, 683 00:36:14,000 --> 00:36:16,920 Speaker 13: you know I don't think about AI specific companies. I 684 00:36:16,960 --> 00:36:21,440 Speaker 13: think about how people apply AI into cyber marketing, sales 685 00:36:21,560 --> 00:36:23,560 Speaker 13: and all the other pockets and B to B SaaS. Right, 686 00:36:23,560 --> 00:36:25,520 Speaker 13: it's today you don't you don't find a company and 687 00:36:25,520 --> 00:36:27,960 Speaker 13: say we're mobile, right just like tomorrow, I don't think 688 00:36:27,960 --> 00:36:31,360 Speaker 13: we'll see companies who say their AI only and cyber 689 00:36:31,440 --> 00:36:34,759 Speaker 13: to me is an incredible, you know, incredibly exciting space, right. 690 00:36:34,800 --> 00:36:37,880 Speaker 13: I think you know number one, cyber has been the 691 00:36:37,880 --> 00:36:41,239 Speaker 13: top priority for enterprise spending, but everybody is looking to 692 00:36:41,280 --> 00:36:43,600 Speaker 13: get less get more out of last. 693 00:36:43,719 --> 00:36:43,879 Speaker 11: Right. 694 00:36:44,239 --> 00:36:46,960 Speaker 13: It's the analogy I uses like our iPhone. You know, 695 00:36:47,000 --> 00:36:48,759 Speaker 13: when we first got our iPhone, we've got you know, 696 00:36:48,800 --> 00:36:50,360 Speaker 13: ten apps on this we can keep down on the 697 00:36:50,440 --> 00:36:53,600 Speaker 13: new apps. Now we've had a thousand apps on iPhone, 698 00:36:53,600 --> 00:36:55,799 Speaker 13: we're not going to download new apps. And similar thing 699 00:36:55,920 --> 00:36:58,799 Speaker 13: is happening in cyber too, where the ce cells, the 700 00:36:58,880 --> 00:37:02,920 Speaker 13: key buyers, they're looking for consolidation in real time. And secondly, 701 00:37:02,960 --> 00:37:06,000 Speaker 13: I think what's incredibly interesting exciting is you know, the 702 00:37:06,040 --> 00:37:09,320 Speaker 13: talent shortage in cybers unfortunately not going away and you 703 00:37:09,680 --> 00:37:10,759 Speaker 13: know anytime soon. 704 00:37:10,880 --> 00:37:13,120 Speaker 11: So there's going to be opportunities. 705 00:37:12,560 --> 00:37:15,200 Speaker 13: For companies to come in and provide not only just 706 00:37:15,680 --> 00:37:18,880 Speaker 13: you know, alerts and and and insights, for the companies 707 00:37:18,880 --> 00:37:22,759 Speaker 13: to provide a laugh nat solutions for those companies and 708 00:37:22,760 --> 00:37:25,640 Speaker 13: buyers who want to tackle cybersecurity challenges. 709 00:37:25,880 --> 00:37:27,760 Speaker 11: How so, I thought those are incredibly. 710 00:37:27,360 --> 00:37:31,120 Speaker 3: Exciting, all very exciting, but how much these founders are 711 00:37:31,120 --> 00:37:33,319 Speaker 3: having to get to grips with where valuations are now at, 712 00:37:33,480 --> 00:37:37,040 Speaker 3: even for something as exciting and exuberant as AI or cyber. 713 00:37:37,960 --> 00:37:40,680 Speaker 13: Yeah, look, Caroline, I think it's a great question. I 714 00:37:40,680 --> 00:37:42,879 Speaker 13: don't have a crystal of all. I would say, though, 715 00:37:42,920 --> 00:37:46,440 Speaker 13: I think valuation is coming down real time. You know, 716 00:37:46,520 --> 00:37:49,400 Speaker 13: it's bridging the public market and the product market is 717 00:37:49,400 --> 00:37:52,640 Speaker 13: bridging real time. Now, at what point, you know, do 718 00:37:52,960 --> 00:37:55,399 Speaker 13: we get to an equiliby room where we started seeing 719 00:37:55,400 --> 00:37:58,160 Speaker 13: a lot more deals happening. My personal gas is probably 720 00:37:58,160 --> 00:37:59,719 Speaker 13: we're still a couple of quarters away. 721 00:37:59,560 --> 00:38:00,520 Speaker 11: From that point. 722 00:38:00,920 --> 00:38:03,200 Speaker 13: But I would say, you know, efficient growth has been 723 00:38:03,640 --> 00:38:06,080 Speaker 13: a big, big carendy word this year in the value 724 00:38:06,440 --> 00:38:09,399 Speaker 13: for good reasons. And one of the key reasons and 725 00:38:09,440 --> 00:38:12,640 Speaker 13: one of the key online statement behind efficient growth is 726 00:38:13,000 --> 00:38:14,520 Speaker 13: not our growth is created equal. 727 00:38:14,640 --> 00:38:16,120 Speaker 11: Right, We're going to have high. 728 00:38:16,000 --> 00:38:19,799 Speaker 13: Growing eye probid companies that are flying today that might 729 00:38:19,800 --> 00:38:23,560 Speaker 13: not be a big public IPO, companies that could go, 730 00:38:24,000 --> 00:38:26,760 Speaker 13: you know, grow efficiently. And what happened now is investors 731 00:38:26,800 --> 00:38:29,880 Speaker 13: are looking for proof points for each efficient growth earlier 732 00:38:29,880 --> 00:38:32,680 Speaker 13: on in company cycle. So instead of just looking at 733 00:38:32,760 --> 00:38:35,680 Speaker 13: growth early on series A, series B, they're asking for 734 00:38:35,760 --> 00:38:40,680 Speaker 13: efficient growth stoner than later, which is not a phenomenon 735 00:38:40,680 --> 00:38:41,920 Speaker 13: that's impacting the funding market. 736 00:38:42,440 --> 00:38:44,880 Speaker 3: And how how much are you being impacted by the 737 00:38:44,920 --> 00:38:47,799 Speaker 3: fact that the exit market is pretty close? There's consolidation 738 00:38:48,040 --> 00:38:51,200 Speaker 3: as you said, but maybe not so much from a 739 00:38:51,280 --> 00:38:53,799 Speaker 3: regulatory perspective, from the big American companies being able to 740 00:38:53,800 --> 00:38:56,279 Speaker 3: buy up smaller ones as we've previously seen, and the 741 00:38:56,320 --> 00:38:57,680 Speaker 3: IPO market is still pretty short. 742 00:38:58,760 --> 00:38:59,800 Speaker 11: Yeah, yeah, totally. 743 00:39:00,160 --> 00:39:03,640 Speaker 13: Unfortunately, most of our propolic companies have you know, years 744 00:39:03,640 --> 00:39:05,880 Speaker 13: of cash on their on their balance sheet. We believe 745 00:39:05,880 --> 00:39:09,120 Speaker 13: most of our companies are building resilient, long term, sustainable 746 00:39:09,120 --> 00:39:11,560 Speaker 13: B to B businesses that they will always have a 747 00:39:11,600 --> 00:39:14,279 Speaker 13: demand right. The way I think about this is, you know, 748 00:39:14,480 --> 00:39:17,640 Speaker 13: economy is a function of productivity growth and B to 749 00:39:17,760 --> 00:39:22,360 Speaker 13: B SaaS is a big driver behind that increasing productivity growth, 750 00:39:22,680 --> 00:39:23,040 Speaker 13: and a. 751 00:39:23,080 --> 00:39:24,520 Speaker 11: Lot of our companies are index to that. 752 00:39:24,800 --> 00:39:26,759 Speaker 13: So you know, the way I think about is there's 753 00:39:26,920 --> 00:39:29,839 Speaker 13: n demand market, it's just how we get from point 754 00:39:29,840 --> 00:39:33,080 Speaker 13: A to point B while surviving this downturn. 755 00:39:34,200 --> 00:39:36,719 Speaker 3: Kasper, great to spend some time with you go have 756 00:39:37,200 --> 00:39:39,560 Speaker 3: you so Fana over at the conference. Caswa Wang, partner 757 00:39:39,560 --> 00:39:49,880 Speaker 3: at Saffar Adventures. We continue our coverage of the Emergent 758 00:39:49,920 --> 00:39:52,719 Speaker 3: America conference, where a look at the labor market gender economists. 759 00:39:52,719 --> 00:39:55,239 Speaker 3: Categor Roy joins us from Miami. She's a CEO and 760 00:39:55,280 --> 00:39:59,040 Speaker 3: founder of Pipeline Equity uses artificial intelligence to help companies 761 00:39:59,080 --> 00:40:02,400 Speaker 3: address and take action against gender biases in the workplace. 762 00:40:02,440 --> 00:40:05,719 Speaker 3: In Kostka, when we look at these more headlines that 763 00:40:06,239 --> 00:40:07,920 Speaker 3: BuzzFeed is going to be laying off people, we know 764 00:40:08,000 --> 00:40:10,400 Speaker 3: metas started to execute on this way. Are they thinking 765 00:40:10,560 --> 00:40:13,840 Speaker 3: about how they lay off people and how it affects 766 00:40:14,040 --> 00:40:17,360 Speaker 3: some of their overall gender equity and other areas of equity. 767 00:40:18,680 --> 00:40:20,440 Speaker 14: You know, what we've seen so far is that that 768 00:40:20,520 --> 00:40:24,200 Speaker 14: actually isn't true unfortunately. So for instance, the tech labor 769 00:40:24,239 --> 00:40:27,680 Speaker 14: for US is about twenty six percent women, and yet 770 00:40:27,880 --> 00:40:30,239 Speaker 14: so far they've been about sixty five percent of those 771 00:40:30,320 --> 00:40:33,480 Speaker 14: laid off, which is really unfortunate because we're actually taking 772 00:40:33,480 --> 00:40:36,560 Speaker 14: a step backward in terms of gender equity in tech 773 00:40:36,600 --> 00:40:39,120 Speaker 14: at a time when we actually need to be moving forward. 774 00:40:39,200 --> 00:40:42,160 Speaker 14: Given all the advancements in artificial intelligence. 775 00:40:41,600 --> 00:40:44,600 Speaker 3: And everyone's so excited about artificial intelligence, How does your 776 00:40:44,719 --> 00:40:47,239 Speaker 3: overall data work? What do you use the power of 777 00:40:47,239 --> 00:40:47,920 Speaker 3: AI to do? 778 00:40:49,200 --> 00:40:49,359 Speaker 6: Well? 779 00:40:49,360 --> 00:40:52,680 Speaker 14: What we actually do is ensure that every people decision 780 00:40:52,719 --> 00:40:57,080 Speaker 14: that companies make, so pay performance potential for instance, are 781 00:40:57,120 --> 00:41:01,040 Speaker 14: actually equitable before they're made. So companies for instance, to 782 00:41:01,680 --> 00:41:04,840 Speaker 14: pay gap analyzes and what we do is actually ensure 783 00:41:04,920 --> 00:41:07,160 Speaker 14: the pay gap is closed and keep it closed. 784 00:41:07,560 --> 00:41:10,560 Speaker 3: And how does AI take that a step forward? How 785 00:41:10,560 --> 00:41:12,640 Speaker 3: are you starting to see other companies develop on this? 786 00:41:13,760 --> 00:41:16,520 Speaker 14: Yeah, so what we're actually seeing is that, for instance, 787 00:41:16,640 --> 00:41:20,000 Speaker 14: if you look at performance reviews, what we do is 788 00:41:20,000 --> 00:41:23,520 Speaker 14: actually look at and we use natural language processing, and 789 00:41:23,560 --> 00:41:25,640 Speaker 14: we find about a third of all performance reviews can 790 00:41:25,719 --> 00:41:29,040 Speaker 14: came biased, so we can actually correct that before that 791 00:41:29,719 --> 00:41:33,400 Speaker 14: performance review becomes part of someone's permanent employment record, and 792 00:41:33,440 --> 00:41:38,080 Speaker 14: that actually catalyzes companies toward equity. We've seen, for instance, 793 00:41:38,120 --> 00:41:41,120 Speaker 14: on average that our customers increase equity by sixty seven 794 00:41:41,160 --> 00:41:43,760 Speaker 14: percent and the first three months on our platform. 795 00:41:43,480 --> 00:41:46,480 Speaker 3: We love how hearing how AI is actually practically being 796 00:41:46,600 --> 00:41:49,439 Speaker 3: used in here and now Kasika ROI enjoying Miami, which 797 00:41:49,480 --> 00:41:51,960 Speaker 3: is a pipeline equity. That is it for this edition 798 00:41:51,960 --> 00:41:53,960 Speaker 3: of blu Meg Technology. Do you not forget to check 799 00:41:54,000 --> 00:41:57,120 Speaker 3: out our podcast's on Apple Spotify and I heeart this 800 00:41:57,280 --> 00:42:01,000 Speaker 3: a Blitu Meg didn't they ta