1 00:00:01,480 --> 00:00:02,360 Speaker 1: From Mahart. 2 00:00:02,360 --> 00:00:06,760 Speaker 2: We're Innovation, Money and Power Collie in Silicon Valley, NBN. 3 00:00:07,120 --> 00:00:11,160 Speaker 3: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow. 4 00:00:25,680 --> 00:00:28,440 Speaker 4: I'm Caroline Hyde at Bloomberg's world headquarters in New York. 5 00:00:28,560 --> 00:00:32,080 Speaker 4: Ed Ludlow is at Google Io and joins us shortly. 6 00:00:32,400 --> 00:00:34,400 Speaker 5: This is Blombag Technology coming up. 7 00:00:34,760 --> 00:00:38,320 Speaker 4: Full earnings coverage ahead, we have Airbnb suffering its worst 8 00:00:38,400 --> 00:00:40,680 Speaker 4: day ever as a public company, and an interview with 9 00:00:40,720 --> 00:00:44,319 Speaker 4: the Akama CEO on its report. Details they follow. Plus 10 00:00:44,440 --> 00:00:46,960 Speaker 4: we'll cover the world of electric vehicles from Rivian earnings 11 00:00:46,960 --> 00:00:49,159 Speaker 4: to the conversation with CEO of Blink Charging. 12 00:00:49,440 --> 00:00:50,320 Speaker 5: We've got you covered. 13 00:00:50,760 --> 00:00:53,760 Speaker 4: And we cover the latest in artificial intelligence with the 14 00:00:53,800 --> 00:00:56,840 Speaker 4: CEO of Scale AI and go live of course to 15 00:00:56,920 --> 00:01:00,040 Speaker 4: Google Io event. Our our own Ed Ludlow is on 16 00:01:00,040 --> 00:01:01,800 Speaker 4: the gram. At first, let's check in on these markets 17 00:01:01,800 --> 00:01:04,200 Speaker 4: as we assess a little bit of a mood shift today, 18 00:01:04,480 --> 00:01:07,880 Speaker 4: money moving into tech stocks. Why because the inflationary pressure 19 00:01:07,920 --> 00:01:10,640 Speaker 4: dials down a bit CPI print coming in below that 20 00:01:10,680 --> 00:01:13,399 Speaker 4: five percent handle. We therefore have NASDAC of course interest 21 00:01:13,880 --> 00:01:17,400 Speaker 4: straight sensitive tech stocks on the up seven tenths of 22 00:01:17,440 --> 00:01:20,240 Speaker 4: a percent two year yield on the down as we expect, 23 00:01:20,280 --> 00:01:22,600 Speaker 4: maybe the Federal Reserve won't have to hike so hard 24 00:01:22,880 --> 00:01:23,520 Speaker 4: going forward. 25 00:01:23,520 --> 00:01:25,040 Speaker 5: Maybe a pause is on the agenda. 26 00:01:25,200 --> 00:01:27,039 Speaker 4: We're off by almost eight basis points on the two 27 00:01:27,080 --> 00:01:28,600 Speaker 4: year yield the front end of the curve. The US 28 00:01:28,600 --> 00:01:31,000 Speaker 4: dollar index also drops on that view that we get 29 00:01:31,000 --> 00:01:32,440 Speaker 4: a more dubbish tone going forward. 30 00:01:32,480 --> 00:01:33,200 Speaker 5: Move it on, and. 31 00:01:33,240 --> 00:01:34,640 Speaker 4: Let's have a little look at what's happening in the 32 00:01:34,640 --> 00:01:37,399 Speaker 4: world of crypto, because we are indeed seeing dollar lower, 33 00:01:37,480 --> 00:01:39,319 Speaker 4: so crypto on the upside, we're up by one point 34 00:01:39,400 --> 00:01:41,800 Speaker 4: nine percent on the OG that is Bitcoin twenty eight 35 00:01:41,840 --> 00:01:44,480 Speaker 4: thousand is currently where we trade. Though it's interesting that 36 00:01:44,520 --> 00:01:46,560 Speaker 4: we're still seeing some of the moon music around crypto 37 00:01:47,080 --> 00:01:49,200 Speaker 4: just being on the dour side, Let's stick with it. 38 00:01:49,280 --> 00:01:52,320 Speaker 4: Jane Street Group Jump Crypto two of the world's top 39 00:01:52,400 --> 00:01:56,000 Speaker 4: market making firms. They're actually pulling back from trading digital 40 00:01:56,040 --> 00:01:58,800 Speaker 4: assets here in the United States. That's as regulators crack 41 00:01:58,880 --> 00:02:01,960 Speaker 4: down on the industry. Look, Jane Street is going even further. 42 00:02:02,240 --> 00:02:05,520 Speaker 4: It's scaling back at scrypto ambissions globally because regulatorly uncertainty 43 00:02:05,520 --> 00:02:07,720 Speaker 4: has made it difficult for the firm to operate the 44 00:02:07,720 --> 00:02:10,960 Speaker 4: business so much in the world of crypto, so much 45 00:02:11,000 --> 00:02:13,200 Speaker 4: in the world of tech handings. More broadly, let's get 46 00:02:13,240 --> 00:02:17,000 Speaker 4: to it, because Airbnb shares wow volatility there worst day 47 00:02:17,040 --> 00:02:20,480 Speaker 4: in fact on record as after reporting pretty muted Outlook, 48 00:02:20,680 --> 00:02:23,000 Speaker 4: let's get the inside track with Tom White's DA Davidson's 49 00:02:23,000 --> 00:02:25,960 Speaker 4: senior research analyst, And do you think what we heard 50 00:02:26,120 --> 00:02:29,720 Speaker 4: from the company in terms of its forwardlooking guidance vindicates 51 00:02:29,960 --> 00:02:31,400 Speaker 4: the plunge in the share price today? 52 00:02:32,000 --> 00:02:32,400 Speaker 6: Yeah? 53 00:02:32,440 --> 00:02:36,320 Speaker 7: Look, I think you know Airbnb is it's a stock 54 00:02:36,480 --> 00:02:39,560 Speaker 7: that's got a premium valuation relative to its peers, and 55 00:02:39,600 --> 00:02:44,399 Speaker 7: with a premium valuation typically you get elevated expectations, particularly 56 00:02:44,480 --> 00:02:47,520 Speaker 7: around Coraly or ningx prints. So look, we're not surprised 57 00:02:47,520 --> 00:02:50,280 Speaker 7: to see the stock sell off a bit today, you know. 58 00:02:50,320 --> 00:02:53,080 Speaker 7: I think the debate around the shares now is whether 59 00:02:53,160 --> 00:02:57,960 Speaker 7: the guidance, which shows basically increased marketing investment relative to 60 00:02:58,000 --> 00:03:00,520 Speaker 7: what the street was expecting, you know, whether that increase 61 00:03:00,960 --> 00:03:03,680 Speaker 7: spend is really just a timing related issue and just 62 00:03:03,680 --> 00:03:06,480 Speaker 7: sort of a pull forward of marketing from later in 63 00:03:06,520 --> 00:03:08,320 Speaker 7: the year to the beginning of the year, or if 64 00:03:08,360 --> 00:03:12,079 Speaker 7: it's something more structural, so you know, near term numbers 65 00:03:12,080 --> 00:03:14,040 Speaker 7: are going down. You know, that's why the staff is 66 00:03:14,080 --> 00:03:15,839 Speaker 7: going down a bit. But you know, we still see 67 00:03:15,919 --> 00:03:18,440 Speaker 7: value and share of Airbnb over a longer term time horizon. 68 00:03:18,720 --> 00:03:21,680 Speaker 4: I mean overall, when you put together all the analyst 69 00:03:21,720 --> 00:03:25,280 Speaker 4: recommendations and price targets are still they think it's going 70 00:03:25,320 --> 00:03:25,840 Speaker 4: to go high. 71 00:03:25,680 --> 00:03:26,960 Speaker 5: One hundred and thirty two dollars. 72 00:03:26,960 --> 00:03:30,120 Speaker 4: The general price target was seeing seventeen buyers, only fourteen 73 00:03:30,160 --> 00:03:32,839 Speaker 4: cells on the stock overall, and from your perspective, when 74 00:03:32,840 --> 00:03:35,680 Speaker 4: you have a by rating one hundred and twenty seven dollars, 75 00:03:35,680 --> 00:03:38,760 Speaker 4: it is in one hundred and forty dollars price target. Tom, 76 00:03:38,960 --> 00:03:41,360 Speaker 4: What do you make of the macro environment. We're just 77 00:03:41,400 --> 00:03:44,760 Speaker 4: hearing about inflation, the pressure rolling over, But it looks 78 00:03:44,800 --> 00:03:47,680 Speaker 4: as though airline prices are coming down, hotel prices are 79 00:03:47,680 --> 00:03:48,200 Speaker 4: coming down. 80 00:03:48,560 --> 00:03:50,200 Speaker 5: Is that good or bad for Airbnb? 81 00:03:50,560 --> 00:03:53,360 Speaker 7: Well, look, I think any kind of pressure on the consumer, 82 00:03:53,440 --> 00:03:57,400 Speaker 7: any pressure on discretionary spending, is not good for travel 83 00:03:57,400 --> 00:04:01,040 Speaker 7: spending overall. What we've seen though, over the course of 84 00:04:01,080 --> 00:04:05,200 Speaker 7: you know, prior downturns, is that leisure travel spending is 85 00:04:05,200 --> 00:04:07,720 Speaker 7: is quite a resilient category, particularly if you look on 86 00:04:08,080 --> 00:04:10,800 Speaker 7: a global basis. You know, even when times are tough, 87 00:04:10,840 --> 00:04:12,360 Speaker 7: people still like to get away. I still like to 88 00:04:12,400 --> 00:04:13,880 Speaker 7: take vacations. 89 00:04:13,440 --> 00:04:13,600 Speaker 8: You know. 90 00:04:13,600 --> 00:04:16,880 Speaker 7: I think in some ways, Airbnb's recent announcement of their 91 00:04:16,960 --> 00:04:20,080 Speaker 7: Airbnb Rooms offering, it's maybe a little bit of a 92 00:04:20,080 --> 00:04:22,039 Speaker 7: way to kind of get get ahead of that. Airbnb 93 00:04:22,160 --> 00:04:24,640 Speaker 7: Rooms is sort of an example of Airbnb kind of 94 00:04:24,640 --> 00:04:28,120 Speaker 7: disrupting itself a little bit by offering a significantly lower 95 00:04:28,120 --> 00:04:32,520 Speaker 7: priced offerings in single rooms in people's homes or apartments. 96 00:04:32,920 --> 00:04:34,680 Speaker 7: I think they said last night, eighty percent of that 97 00:04:34,720 --> 00:04:38,560 Speaker 7: inventory is less than one hundred dollars per night. So, 98 00:04:38,680 --> 00:04:41,040 Speaker 7: you know, we think overall travel is going to be resilient, 99 00:04:41,160 --> 00:04:44,279 Speaker 7: and we think Airbnb, because of the variety of the 100 00:04:44,279 --> 00:04:46,640 Speaker 7: listings it has, is probably going to be more resilient 101 00:04:46,640 --> 00:04:48,240 Speaker 7: than other online travel assets. 102 00:04:48,279 --> 00:04:50,480 Speaker 4: Interesting, what about the market share that seems to being 103 00:04:50,520 --> 00:04:53,360 Speaker 4: eked out a little bit by booking dot Com, by vlbo, 104 00:04:53,440 --> 00:04:55,240 Speaker 4: by some of the competitors out there, not to mention 105 00:04:55,480 --> 00:04:57,120 Speaker 4: the old hotel industry as well. 106 00:04:58,000 --> 00:05:00,680 Speaker 7: Yeah, look, I think, you know, talking about marketing shares 107 00:05:00,800 --> 00:05:03,320 Speaker 7: right now is a little bit tricky just because of 108 00:05:03,360 --> 00:05:06,279 Speaker 7: the comps, the differences in the comps. Right you know, 109 00:05:06,360 --> 00:05:10,200 Speaker 7: Airbnb is camping you know, over the last few years 110 00:05:10,200 --> 00:05:12,560 Speaker 7: has had explosive growth. Right during the pandemic, they were 111 00:05:12,600 --> 00:05:14,360 Speaker 7: sort of the only game in town. People didn't feel 112 00:05:14,360 --> 00:05:16,520 Speaker 7: comfortable going to big cities or going into hotels where 113 00:05:16,560 --> 00:05:16,920 Speaker 7: they had. 114 00:05:16,839 --> 00:05:19,240 Speaker 9: To you know, mingle with other folks. 115 00:05:20,440 --> 00:05:25,000 Speaker 7: Airbnb's comps are relatively tougher now, whereas the traditional kind 116 00:05:25,000 --> 00:05:27,840 Speaker 7: of OTAs or the hotel industry comps are a little 117 00:05:27,839 --> 00:05:29,800 Speaker 7: bit easier. So just looking at the growth rates kind 118 00:05:29,839 --> 00:05:32,679 Speaker 7: of you know, this quarter, next quarter, I think doesn't 119 00:05:32,720 --> 00:05:35,359 Speaker 7: tell you know, kind of the entire story. You know, 120 00:05:35,400 --> 00:05:37,279 Speaker 7: the bottom line is is a lot of these online 121 00:05:37,279 --> 00:05:40,279 Speaker 7: travel assets all continue to grow, you know, significantly quickly. 122 00:05:40,320 --> 00:05:42,719 Speaker 7: I think, you know, discussions about market share you know, 123 00:05:42,800 --> 00:05:44,640 Speaker 7: need to be looked at in sort of a longer 124 00:05:44,720 --> 00:05:45,520 Speaker 7: term perspective. 125 00:05:46,400 --> 00:05:48,560 Speaker 4: Well said, it's great to have some time Tony, Tom. 126 00:05:48,680 --> 00:05:50,760 Speaker 4: Thank you so much, Tom White of DA Davidson, as 127 00:05:50,760 --> 00:05:53,400 Speaker 4: we say, the biggest drop on records of the Airbnb, 128 00:05:53,520 --> 00:05:56,120 Speaker 4: but still got a seventy to seventy three billion dollar 129 00:05:56,400 --> 00:05:57,400 Speaker 4: market capitalization. 130 00:05:57,960 --> 00:05:59,000 Speaker 5: Let's talk about the. 131 00:05:58,920 --> 00:06:03,000 Speaker 4: Macro environment, which BMB is currently well working within inflation data, 132 00:06:03,000 --> 00:06:05,039 Speaker 4: as we said, without today showing signs of actually a 133 00:06:05,040 --> 00:06:07,400 Speaker 4: bit of a cooling CPI rising just by four point 134 00:06:07,520 --> 00:06:10,000 Speaker 4: nine percent on a year on year basis. But let's 135 00:06:10,000 --> 00:06:12,280 Speaker 4: go into the insight of how you and I are spending. 136 00:06:12,560 --> 00:06:14,800 Speaker 4: Are we looking at luxury? Are we holding back our 137 00:06:14,839 --> 00:06:18,280 Speaker 4: purchases Rackaton President, I'm pleased to say, Kristin gull is 138 00:06:18,320 --> 00:06:21,640 Speaker 4: with us and Rakuton is an online shopping platform partners 139 00:06:21,640 --> 00:06:25,240 Speaker 4: in thousands of stores to provide data, expertise, technology both 140 00:06:25,279 --> 00:06:27,800 Speaker 4: businesses and consumers. And also you give cash back, and 141 00:06:27,839 --> 00:06:31,480 Speaker 4: that's a key draw Kristin. What are you seeing in 142 00:06:32,279 --> 00:06:35,000 Speaker 4: consumers desire to be spending right now, particularly on the 143 00:06:35,080 --> 00:06:36,039 Speaker 4: luxury side of things. 144 00:06:37,040 --> 00:06:39,479 Speaker 3: We were very worried coming into this year that with 145 00:06:39,680 --> 00:06:42,400 Speaker 3: all of the inflation pressure, that consumers were going to 146 00:06:42,400 --> 00:06:45,680 Speaker 3: spend significantly less than they'd spent last year. And actually, 147 00:06:45,720 --> 00:06:49,560 Speaker 3: on the contrary, we've seen a relatively stable spending environment, 148 00:06:50,200 --> 00:06:52,720 Speaker 3: both on the lower end and the world of marketplaces 149 00:06:52,760 --> 00:06:54,680 Speaker 3: and in the world of mid tier department stores. But 150 00:06:54,839 --> 00:06:58,760 Speaker 3: luxury has been booming, and really that luxury thread carried 151 00:06:58,800 --> 00:07:01,480 Speaker 3: throughout the pandemic and has continued into this year in 152 00:07:01,839 --> 00:07:04,919 Speaker 3: a significant strength. And how people are spending despite the 153 00:07:04,920 --> 00:07:08,640 Speaker 3: fact that the economy makes them a little nervous. 154 00:07:07,839 --> 00:07:11,320 Speaker 4: So all day in some ways buying on the luxury 155 00:07:11,400 --> 00:07:13,760 Speaker 4: en because it's deemed an investment in some way if 156 00:07:13,760 --> 00:07:16,440 Speaker 4: I'm thinking of actual, real tangible goods. 157 00:07:17,560 --> 00:07:18,840 Speaker 5: That's exactly what it is. 158 00:07:19,000 --> 00:07:20,840 Speaker 3: We have a lot of data that's telling us that 159 00:07:20,880 --> 00:07:23,320 Speaker 3: people are spending differently now, and there's two ways that 160 00:07:23,360 --> 00:07:26,960 Speaker 3: they're spending differently. Number one, buying less but making it 161 00:07:27,040 --> 00:07:30,840 Speaker 3: count more. Number two dealing with things like sustainability, where 162 00:07:30,840 --> 00:07:33,520 Speaker 3: they want to buy fewer items with less impact on 163 00:07:33,560 --> 00:07:37,200 Speaker 3: the environment. And what that leads to is people investing 164 00:07:37,280 --> 00:07:41,240 Speaker 3: in either resale or luxury, and investing in luxury is 165 00:07:41,240 --> 00:07:45,760 Speaker 3: something that increasingly younger and younger audiences are playing in. 166 00:07:45,920 --> 00:07:47,760 Speaker 3: We are seeing a lot of data that gen Z 167 00:07:47,960 --> 00:07:52,120 Speaker 3: is buying luxury at a significantly earlier age than other generations, 168 00:07:52,160 --> 00:07:54,360 Speaker 3: and I think that really points to people changing the 169 00:07:54,400 --> 00:07:55,640 Speaker 3: way that they spend. 170 00:07:55,880 --> 00:07:58,240 Speaker 4: But also there's different offerings of the way in which 171 00:07:58,280 --> 00:08:01,720 Speaker 4: they spend. How much you seeing a competitive threat from 172 00:08:02,200 --> 00:08:04,760 Speaker 4: well the real reel or eBay or web paces you 173 00:08:04,800 --> 00:08:08,280 Speaker 4: can go and buy, se can hand or pre used 174 00:08:08,480 --> 00:08:11,280 Speaker 4: luxury items as an investment. Where do you see that 175 00:08:11,600 --> 00:08:13,440 Speaker 4: focus from Rackington in the moment. 176 00:08:14,480 --> 00:08:16,960 Speaker 3: I think right now that is a massive area of 177 00:08:16,960 --> 00:08:19,800 Speaker 3: growth in the retail industry is the world of resale, 178 00:08:19,840 --> 00:08:22,280 Speaker 3: and I think for a lot of these younger consumers 179 00:08:22,280 --> 00:08:25,280 Speaker 3: that was what brought them into into the luxury fold 180 00:08:25,320 --> 00:08:28,080 Speaker 3: in the first place. I think the interesting thing is 181 00:08:28,200 --> 00:08:31,560 Speaker 3: now luxury companies are trying to get in on this 182 00:08:31,800 --> 00:08:34,400 Speaker 3: volume and get in on that relationship. So you have 183 00:08:34,480 --> 00:08:39,080 Speaker 3: people like Gucci offering their own resale world on their 184 00:08:39,120 --> 00:08:41,760 Speaker 3: website right now, and basically what it means is that 185 00:08:41,840 --> 00:08:44,640 Speaker 3: they want to own the customer in a way that 186 00:08:44,800 --> 00:08:49,520 Speaker 3: isn't disintermediated by resale sites. So that's something that I 187 00:08:49,640 --> 00:08:53,320 Speaker 3: see as part of a massive growth story in retail 188 00:08:53,559 --> 00:08:57,760 Speaker 3: is resale overall, but not just on resale platforms, but 189 00:08:57,920 --> 00:08:58,960 Speaker 3: by brands. 190 00:08:59,559 --> 00:09:02,840 Speaker 4: How do you keep your market share in this environment 191 00:09:02,920 --> 00:09:05,520 Speaker 4: we're all talking about oltificial intelligence, We're all thinking about 192 00:09:05,520 --> 00:09:08,720 Speaker 4: how we can interact with a consumer more swiftly productively. 193 00:09:09,240 --> 00:09:11,600 Speaker 4: How are you looking at updating recuteon and what your 194 00:09:11,640 --> 00:09:14,760 Speaker 4: offering looks like when we're interfacing the e commerce platform. 195 00:09:15,320 --> 00:09:17,240 Speaker 3: At the end of the day, our job is to 196 00:09:17,360 --> 00:09:19,880 Speaker 3: drive growth for our retail partners, and we're doing that 197 00:09:19,960 --> 00:09:22,920 Speaker 3: in a number of different ways. The first is by 198 00:09:23,040 --> 00:09:25,880 Speaker 3: increasing the number of players on our site that appeal 199 00:09:25,920 --> 00:09:29,840 Speaker 3: to consumers, things like resale, things like more luxury players 200 00:09:29,840 --> 00:09:32,520 Speaker 3: are really really important to us. The second is there's 201 00:09:32,559 --> 00:09:36,199 Speaker 3: a level of personalization that becomes important. We give cash 202 00:09:36,320 --> 00:09:39,839 Speaker 3: back to our consumers for shopping at our retailers. That 203 00:09:39,960 --> 00:09:44,040 Speaker 3: cash back is increasingly personalized to do things like incentivize 204 00:09:44,080 --> 00:09:46,320 Speaker 3: you to try stores that you've never tried before, to 205 00:09:46,400 --> 00:09:49,440 Speaker 3: incentivize you to make a second purchase at a retailer 206 00:09:49,480 --> 00:09:50,840 Speaker 3: that you've experienced before. 207 00:09:51,160 --> 00:09:52,480 Speaker 5: That level of value. 208 00:09:52,160 --> 00:09:54,680 Speaker 3: That we drive, not only is it valuable to our retailers, 209 00:09:54,679 --> 00:09:57,000 Speaker 3: but it's also really valuable to our consumers. 210 00:09:57,960 --> 00:10:00,280 Speaker 4: So when you say at the moment, you keep a 211 00:10:00,320 --> 00:10:04,320 Speaker 4: real loyal customer, in many ways, you say when a 212 00:10:04,520 --> 00:10:07,559 Speaker 4: retailer leaves, quite often the shopper remains on seventy five 213 00:10:07,559 --> 00:10:12,040 Speaker 4: percent of the time. Here, what is your dream new customer? 214 00:10:12,080 --> 00:10:15,000 Speaker 4: From a client perspective, From a retailer perspective, you're just 215 00:10:15,000 --> 00:10:16,800 Speaker 4: talking about Gucci there. Who do you want to lure 216 00:10:16,840 --> 00:10:18,960 Speaker 4: onto the platform that you haven't got yet? 217 00:10:19,640 --> 00:10:22,120 Speaker 3: Yeah, I think increasingly there is a younger consumer that 218 00:10:22,160 --> 00:10:24,839 Speaker 3: we're going after. The sort of younger millennial audience and 219 00:10:24,920 --> 00:10:27,840 Speaker 3: gen Z is really important to us. A lot of 220 00:10:27,880 --> 00:10:29,720 Speaker 3: what we've been doing over the last few years is 221 00:10:29,760 --> 00:10:32,520 Speaker 3: bringing on a lot of direct to consumer brands that 222 00:10:32,559 --> 00:10:36,280 Speaker 3: are more important to that audience and that generation, and 223 00:10:36,320 --> 00:10:40,120 Speaker 3: then to your point, expanding our luxury environment overall on 224 00:10:40,160 --> 00:10:43,600 Speaker 3: the platform. We have played really, really hard in luxury 225 00:10:43,640 --> 00:10:46,480 Speaker 3: department stores for a long time. Individual brands is the 226 00:10:46,520 --> 00:10:49,280 Speaker 3: next thing I'd love to tackle because that does actually 227 00:10:49,400 --> 00:10:51,480 Speaker 3: drive a lot of value for that younger millennial and 228 00:10:51,520 --> 00:10:51,920 Speaker 3: gen Z. 229 00:10:51,960 --> 00:10:55,120 Speaker 4: Consumer or someone who brings a lot of experience to 230 00:10:55,559 --> 00:10:58,160 Speaker 4: the role, having been well with Recuten as a general 231 00:10:58,200 --> 00:11:01,360 Speaker 4: manager since twenty eighteen, plenty of other places before that. 232 00:11:01,480 --> 00:11:03,600 Speaker 4: So Kris Single, we thank you so much for spending 233 00:11:03,600 --> 00:11:06,280 Speaker 4: some time with us with Q ten president there Now 234 00:11:06,360 --> 00:11:08,920 Speaker 4: from luxury spending to what's going on in the world 235 00:11:09,000 --> 00:11:12,360 Speaker 4: of Mountain View, California right now, ed and manner luxury. 236 00:11:12,480 --> 00:11:15,600 Speaker 5: You're covering Google though developers conference all day for us. 237 00:11:15,679 --> 00:11:16,600 Speaker 5: What's the key themes? 238 00:11:17,040 --> 00:11:20,160 Speaker 10: Yeah, Look, artificial intelligence just at the heart of everything here. 239 00:11:20,280 --> 00:11:23,360 Speaker 10: Thousands of people as Shoreline mountain View, two hundred and 240 00:11:23,400 --> 00:11:27,400 Speaker 10: thirty thousand union worldwide. And remember when Google introduced Barred 241 00:11:27,440 --> 00:11:30,680 Speaker 10: in February. It was always billed as a creative companion, 242 00:11:30,760 --> 00:11:33,680 Speaker 10: not a replacement for the core search product. So that's 243 00:11:33,679 --> 00:11:35,840 Speaker 10: the question. What are we going to find out today 244 00:11:36,160 --> 00:11:40,000 Speaker 10: about how you integrate the large Language Model the LM 245 00:11:40,600 --> 00:11:44,319 Speaker 10: into a next generation search engine. What does that functionality 246 00:11:44,320 --> 00:11:46,839 Speaker 10: look like? And what about Google's other software offerings. And 247 00:11:46,880 --> 00:11:48,200 Speaker 10: that's before we even get to hardware. 248 00:11:48,240 --> 00:11:52,040 Speaker 4: Caroline, Yeah, we'll address that a little bit later with you. 249 00:11:52,360 --> 00:11:53,800 Speaker 5: Brilliant to have you on the ground there. 250 00:11:53,840 --> 00:11:56,160 Speaker 4: You're going to be back with us and later in 251 00:11:56,200 --> 00:11:57,800 Speaker 4: the hour, but we're also going to be there throughout 252 00:11:57,840 --> 00:11:58,160 Speaker 4: the day. 253 00:11:58,240 --> 00:12:08,040 Speaker 5: We thank you so much. Let's go back to the earnings. 254 00:12:08,120 --> 00:12:11,240 Speaker 4: Let's look at Acamai Technologies shares actually having their best 255 00:12:11,320 --> 00:12:14,320 Speaker 4: day since twenty twenty after it reported first all results 256 00:12:14,320 --> 00:12:16,559 Speaker 4: that meat expectations. It gave a fullier forecast that was 257 00:12:16,600 --> 00:12:19,400 Speaker 4: ahead of the AMAS consensus. Let's talk about it all 258 00:12:19,600 --> 00:12:23,040 Speaker 4: with the CEO of Acami, Tom Nayton. Doctor Layton, it's 259 00:12:23,040 --> 00:12:26,160 Speaker 4: great to have some time with you. Strong given challenging 260 00:12:26,160 --> 00:12:29,880 Speaker 4: macroheadwinds and the pricing pressure, what do you make of 261 00:12:29,920 --> 00:12:32,760 Speaker 4: the economic environment which you're currently managing to weather better 262 00:12:32,800 --> 00:12:34,040 Speaker 4: than some had anticipated. 263 00:12:35,240 --> 00:12:38,560 Speaker 2: It is a challenging environment. You know, customers are trying 264 00:12:38,600 --> 00:12:41,360 Speaker 2: to cut back on costs. There are a couple of 265 00:12:41,400 --> 00:12:43,880 Speaker 2: ways that help us mitigate that though. 266 00:12:44,559 --> 00:12:44,760 Speaker 7: You know. 267 00:12:44,800 --> 00:12:46,679 Speaker 9: The first is folks are really. 268 00:12:46,440 --> 00:12:51,640 Speaker 2: Concerned about security and reliability, especially in the financial sector. Now, 269 00:12:51,679 --> 00:12:54,520 Speaker 2: the last thing a major bank wants is to have 270 00:12:54,559 --> 00:12:57,839 Speaker 2: an outage with the concern that people will think something's wrong, 271 00:12:57,880 --> 00:13:01,080 Speaker 2: you get a run and that's a big challenge and 272 00:13:01,160 --> 00:13:03,199 Speaker 2: we're the you know, the best provider when it comes 273 00:13:03,240 --> 00:13:04,640 Speaker 2: to reliability and security. 274 00:13:04,720 --> 00:13:07,120 Speaker 9: So that's been you know, helpful for us. 275 00:13:07,480 --> 00:13:12,720 Speaker 2: Also, as companies need to cut cost we can help them. 276 00:13:12,720 --> 00:13:14,240 Speaker 9: With our compute solution. 277 00:13:15,080 --> 00:13:19,120 Speaker 2: You know that's now integrated into our delivery platform. And 278 00:13:19,559 --> 00:13:21,480 Speaker 2: you know we are the biggest when it comes to 279 00:13:21,800 --> 00:13:25,920 Speaker 2: delivery and have a very economical platform for doing that, 280 00:13:26,040 --> 00:13:29,720 Speaker 2: and so we can help customers reduce their costs access 281 00:13:29,760 --> 00:13:32,320 Speaker 2: to cloud computing and delivery. 282 00:13:32,640 --> 00:13:35,640 Speaker 4: What about your buildout though, Tdcowen saying that they are 283 00:13:35,880 --> 00:13:38,000 Speaker 4: longer term a bit more cautious on your stock given 284 00:13:38,040 --> 00:13:41,600 Speaker 4: the capital expenditure intensity that's needed to build out the 285 00:13:41,679 --> 00:13:42,400 Speaker 4: compute part. 286 00:13:42,640 --> 00:13:44,199 Speaker 5: How are you managing those as a costs? 287 00:13:45,240 --> 00:13:48,560 Speaker 2: Yeah, so We are investing this year to you know, 288 00:13:48,679 --> 00:13:52,319 Speaker 2: jumpstart the base platform, and that will largely be done 289 00:13:52,360 --> 00:13:55,120 Speaker 2: by the end of Q three, and then going forward 290 00:13:55,120 --> 00:13:59,920 Speaker 2: from there, the buildout expense is proportional to the revenue. 291 00:14:00,240 --> 00:14:02,199 Speaker 2: So if we get a lot of revenue growth, which 292 00:14:02,280 --> 00:14:04,160 Speaker 2: is what we're hoping and is a good news story, 293 00:14:04,200 --> 00:14:07,000 Speaker 2: then there'll be more capital expense. And you know, if 294 00:14:07,000 --> 00:14:09,280 Speaker 2: it's a more modest growth on revenue, then you know, 295 00:14:09,320 --> 00:14:11,840 Speaker 2: there won't be all that much capex to worry about, 296 00:14:11,920 --> 00:14:14,640 Speaker 2: so that'll be pretty much, you know, done with by 297 00:14:14,640 --> 00:14:16,840 Speaker 2: the end of Q three. We just turned on our 298 00:14:16,840 --> 00:14:19,280 Speaker 2: first new data center and we have fourteen more planned 299 00:14:19,280 --> 00:14:20,440 Speaker 2: over the next couple of quarters. 300 00:14:20,560 --> 00:14:21,040 Speaker 5: You really do. 301 00:14:21,080 --> 00:14:25,480 Speaker 4: Sound optimistic about the client still spending in this economic environment, 302 00:14:25,480 --> 00:14:28,960 Speaker 4: particularly on security. Just push back therefore on analysts over 303 00:14:28,960 --> 00:14:32,720 Speaker 4: at Guggenheim who are saying your low double digit guidance 304 00:14:32,920 --> 00:14:35,600 Speaker 4: in terms of security growth, they actually say it's somewhat 305 00:14:35,600 --> 00:14:39,720 Speaker 4: implausible because of this macro environment and the sharp acceleration 306 00:14:39,760 --> 00:14:42,320 Speaker 4: that's needed a new business. Why do you think that 307 00:14:42,400 --> 00:14:46,040 Speaker 4: this is plausible even though you've got some worrying about it. 308 00:14:46,920 --> 00:14:50,080 Speaker 2: Well, we have the market leading solutions for web at firewall, 309 00:14:50,160 --> 00:14:53,960 Speaker 2: you've got to have that market leading solution for bot management, 310 00:14:54,480 --> 00:14:59,560 Speaker 2: market leading solution for ransomware and defending against that, you know, 311 00:14:59,600 --> 00:15:02,520 Speaker 2: And and think about some of the older attacks that 312 00:15:02,560 --> 00:15:04,760 Speaker 2: are maybe you think of them as old news, like 313 00:15:04,840 --> 00:15:07,080 Speaker 2: denial of service. You know, we just in the last 314 00:15:07,120 --> 00:15:10,720 Speaker 2: few months you have the killnet coordinated d DOS attacks 315 00:15:10,760 --> 00:15:14,000 Speaker 2: against you know, the nation's leading medical centers for goodness sake, 316 00:15:14,880 --> 00:15:18,960 Speaker 2: and so security is still very much needed, and you know, 317 00:15:19,000 --> 00:15:21,800 Speaker 2: when you're the market leader in these solutions like akamie is, 318 00:15:22,120 --> 00:15:25,920 Speaker 2: I'm very optimistic about low double digit growth this year 319 00:15:25,920 --> 00:15:28,400 Speaker 2: for our security business. And of course now we're adding 320 00:15:28,760 --> 00:15:31,440 Speaker 2: API security, and as you know, that's very much in 321 00:15:31,480 --> 00:15:33,720 Speaker 2: the news with all the API attacks that have taken 322 00:15:33,760 --> 00:15:34,520 Speaker 2: place recently. 323 00:15:34,800 --> 00:15:39,280 Speaker 4: Yes, exactly, let's talk from API to AI as well 324 00:15:39,440 --> 00:15:42,080 Speaker 4: more broadly, doctor Layton, because I mean, you're a man 325 00:15:42,120 --> 00:15:44,080 Speaker 4: of fifty patents to your name in terms of content 326 00:15:44,080 --> 00:15:46,520 Speaker 4: delivery and Internet protocols. But I'm pretty sure you're thinking 327 00:15:46,560 --> 00:15:49,600 Speaker 4: the way in which artificial intelligence is increasing some of 328 00:15:49,640 --> 00:15:52,960 Speaker 4: those security attacks as we mentioned, but ultimately upending many 329 00:15:52,960 --> 00:15:54,840 Speaker 4: a business model. Right now, Is there anyway in which 330 00:15:54,880 --> 00:15:56,960 Speaker 4: you're thinking that you can harness that or that you're 331 00:15:57,000 --> 00:15:57,800 Speaker 4: worrying about it. 332 00:15:59,160 --> 00:16:02,120 Speaker 2: You know, we use a and a lot of our products, 333 00:16:02,160 --> 00:16:07,760 Speaker 2: particularly in security for anomaly detection, detecting attackers really you know, 334 00:16:07,920 --> 00:16:08,640 Speaker 2: very important. 335 00:16:08,880 --> 00:16:11,440 Speaker 9: We don't sell AI products per se. 336 00:16:12,280 --> 00:16:16,320 Speaker 2: Now, I think there's been some very interesting advances recently 337 00:16:16,320 --> 00:16:19,880 Speaker 2: an AI generative AI, and you know, one thing about 338 00:16:19,880 --> 00:16:22,760 Speaker 2: that is it's compute intensive, and so there is the 339 00:16:22,840 --> 00:16:26,760 Speaker 2: prospect of a lot more need for compute cycles and 340 00:16:26,800 --> 00:16:30,280 Speaker 2: that's something that you know, we could ultimately benefit us 341 00:16:30,680 --> 00:16:33,800 Speaker 2: with our compute platform. In fact, you know, there's early 342 00:16:33,840 --> 00:16:37,600 Speaker 2: work going on now that would you know, using algorithms 343 00:16:37,600 --> 00:16:42,160 Speaker 2: in scientific methods, uh, make it more affordable so that 344 00:16:42,200 --> 00:16:44,080 Speaker 2: you could do a lot of the work on inference 345 00:16:44,160 --> 00:16:47,600 Speaker 2: engines using CPUs instead of GPUs, which. 346 00:16:47,440 --> 00:16:48,440 Speaker 9: Is a lot more efficient. 347 00:16:49,040 --> 00:16:51,320 Speaker 2: So I think there's a lot of exciting results to 348 00:16:51,400 --> 00:16:53,880 Speaker 2: come there and ultimately, you know, good for business. 349 00:16:54,960 --> 00:16:57,240 Speaker 4: And it really is interesting that we've had from other 350 00:16:57,280 --> 00:17:00,680 Speaker 4: security software companies out there, thinking at ten with a 351 00:17:00,680 --> 00:17:03,520 Speaker 4: revenue forecast that was a bit lackluster cloud flair, we 352 00:17:04,000 --> 00:17:06,679 Speaker 4: have had this worry that people aren't going to invest 353 00:17:06,680 --> 00:17:10,160 Speaker 4: in much as much in securing themselves in this environment. 354 00:17:10,640 --> 00:17:14,120 Speaker 4: So is there any sign from any of your clients 355 00:17:14,480 --> 00:17:16,080 Speaker 4: that they're just going to have to pull back in 356 00:17:16,080 --> 00:17:17,639 Speaker 4: that area or none at all from you. 357 00:17:18,560 --> 00:17:21,760 Speaker 2: It does slow down sales cycle some you know, in 358 00:17:21,840 --> 00:17:24,639 Speaker 2: our growth rate, even in the low double digits, is 359 00:17:24,720 --> 00:17:27,000 Speaker 2: less than it was last year. That said, we had 360 00:17:27,000 --> 00:17:29,800 Speaker 2: a strong bookings quarter in security, and in fact, you know, 361 00:17:29,880 --> 00:17:32,600 Speaker 2: we ended up you know, taking business away from you know, 362 00:17:32,640 --> 00:17:35,359 Speaker 2: some of the companies that you mentioned, particularly in the 363 00:17:35,400 --> 00:17:39,800 Speaker 2: financial sector where you know, the leading financial institutions just 364 00:17:39,960 --> 00:17:43,280 Speaker 2: can't have an outage or an incident or have an 365 00:17:43,280 --> 00:17:46,800 Speaker 2: attack be successful in this environment. And so there's a 366 00:17:47,000 --> 00:17:49,640 Speaker 2: I think they turned to Akami more now so where 367 00:17:49,680 --> 00:17:53,080 Speaker 2: you might see some company struggling a bit, it's on 368 00:17:53,240 --> 00:17:55,040 Speaker 2: balance within this environment. 369 00:17:55,200 --> 00:17:58,840 Speaker 4: Good for Akami, doctor Ayton, Tom Layton, Akam, I see 370 00:17:58,920 --> 00:18:01,120 Speaker 4: and we thank you for your winning us. We need 371 00:18:01,200 --> 00:18:04,840 Speaker 4: spelling out the environment in which we currently find ourselves. Meanwhile, 372 00:18:04,840 --> 00:18:08,000 Speaker 4: we're also watching other companies that actually are not performing 373 00:18:08,040 --> 00:18:09,960 Speaker 4: as well on the day as Zachameayas. Just check out 374 00:18:09,960 --> 00:18:14,760 Speaker 4: on internet infrastructure company Twilio falling in terms of sixteen percent. 375 00:18:14,440 --> 00:18:14,920 Speaker 5: On the day. 376 00:18:14,960 --> 00:18:17,480 Speaker 4: This is really is struggling to find its growth right now, 377 00:18:17,640 --> 00:18:21,240 Speaker 4: we overall see the company posting numbers that did show 378 00:18:21,960 --> 00:18:24,840 Speaker 4: a growth slowdown overall, and this is a business that's 379 00:18:25,000 --> 00:18:28,280 Speaker 4: trying to find it's footing amid the macro weak macro 380 00:18:28,400 --> 00:18:31,840 Speaker 4: that Jefferies are saying a small beat overall in this quarter, 381 00:18:31,920 --> 00:18:35,680 Speaker 4: but it really is the margin turnaround, and this particular 382 00:18:35,680 --> 00:18:38,800 Speaker 4: company is being overshadowed by a weak macro picture going forward. 383 00:18:38,840 --> 00:18:42,480 Speaker 4: So deterioration its net revenue retention rate in the outlook 384 00:18:42,520 --> 00:18:45,399 Speaker 4: for the second quarter points to more difficult days ahead 385 00:18:45,960 --> 00:18:48,080 Speaker 4: coming up. Look, let's talk about days ahead in the 386 00:18:48,160 --> 00:18:50,679 Speaker 4: race to compete with the likes of Chatchepete. More on 387 00:18:50,720 --> 00:18:53,320 Speaker 4: how Softbag s getting in on the action US next 388 00:18:53,400 --> 00:19:11,080 Speaker 4: as a bloomberg time now for Talking Tech and first 389 00:19:11,119 --> 00:19:14,520 Speaker 4: up monthly sales and Taiwan inconduct of Manufacturing TSMC fell 390 00:19:14,720 --> 00:19:17,600 Speaker 4: for a second month as his consumer demand for electronics 391 00:19:17,720 --> 00:19:19,040 Speaker 4: just slows sales. 392 00:19:18,680 --> 00:19:19,720 Speaker 5: And made to order chips. 393 00:19:19,880 --> 00:19:22,439 Speaker 4: They're down fourteen percent from a year earlier, signaling that 394 00:19:22,440 --> 00:19:26,240 Speaker 4: the chip sectors slump skeet to bottom. Meanwhile, also over 395 00:19:26,280 --> 00:19:28,960 Speaker 4: in Asia, soft Banks Mobile Unit is building a Japanese 396 00:19:29,080 --> 00:19:32,400 Speaker 4: version of You Guessed at Chatchipt, joining the already intense 397 00:19:32,480 --> 00:19:35,720 Speaker 4: race to create the next generation AI. The telecoms company 398 00:19:35,760 --> 00:19:38,280 Speaker 4: is actually setting up a new entity in March to 399 00:19:38,320 --> 00:19:41,240 Speaker 4: develop the technology. The CEO didn't elaborate on the project's 400 00:19:41,280 --> 00:19:44,800 Speaker 4: goals or progress so far. And let's look at content 401 00:19:44,880 --> 00:19:48,159 Speaker 4: right now, because Tucker Carlson says that he's turning to 402 00:19:48,240 --> 00:19:51,120 Speaker 4: Twitter to launch a new show as after, of course, 403 00:19:51,119 --> 00:19:53,919 Speaker 4: being fired from Fox News last month, Carlson posted a 404 00:19:54,040 --> 00:19:56,800 Speaker 4: three minute video online saying like he would bring a 405 00:19:56,840 --> 00:20:00,720 Speaker 4: new version of his Fox News program, although says. 406 00:20:00,520 --> 00:20:02,320 Speaker 5: He hasn't signed any sort of deal. 407 00:20:02,800 --> 00:20:05,919 Speaker 4: But let's dig into this with plans not send and Stone, 408 00:20:06,320 --> 00:20:08,720 Speaker 4: what would a program actually look like on a platform 409 00:20:08,760 --> 00:20:11,520 Speaker 4: like Twitter? And one of the concerns around content moderation, 410 00:20:11,680 --> 00:20:12,720 Speaker 4: Felix Jillett is with us. 411 00:20:12,840 --> 00:20:15,679 Speaker 5: Is flomby News interesting. 412 00:20:15,760 --> 00:20:18,879 Speaker 4: That many would say he left Fox or was pushed 413 00:20:18,880 --> 00:20:21,840 Speaker 4: out a Fox his advertisers were uncomfortable, So what makes 414 00:20:22,560 --> 00:20:24,879 Speaker 4: how does is it subscription based this time around? 415 00:20:25,160 --> 00:20:27,840 Speaker 11: It's kind of hard to say, because, yeah, advertisers were 416 00:20:27,920 --> 00:20:30,520 Speaker 11: uncomfortable with Tucker Carlson the show on Fox. They've been 417 00:20:30,640 --> 00:20:34,159 Speaker 11: uncomfortable with Elon Musk's version of Twitter. So do you 418 00:20:34,200 --> 00:20:36,440 Speaker 11: take two negatives, does it make a positive. It's hard 419 00:20:36,440 --> 00:20:39,880 Speaker 11: to imagine that happening. You know, Elon Musk has been 420 00:20:39,920 --> 00:20:43,960 Speaker 11: trying to get more subscription money for Twitter, getting people 421 00:20:43,960 --> 00:20:46,600 Speaker 11: to sign up for Twitter Blue. That's been a struggle. 422 00:20:47,000 --> 00:20:51,439 Speaker 11: So maybe getting some very die hard Tucker Carlson fans 423 00:20:51,440 --> 00:20:53,800 Speaker 11: to sign up and subscribe to a show. 424 00:20:54,560 --> 00:20:56,240 Speaker 1: It's all a little bit hard to imagine. 425 00:20:56,280 --> 00:20:58,560 Speaker 11: I mean, if you think about like video on Twitter. 426 00:20:58,840 --> 00:21:00,879 Speaker 11: I was thinking about what's the most successful video on 427 00:21:00,920 --> 00:21:03,080 Speaker 11: Twitter over the years, I would have to say it's Vine, 428 00:21:03,359 --> 00:21:06,440 Speaker 11: which was six second loops of comedians and people talking. 429 00:21:06,760 --> 00:21:09,000 Speaker 11: And you're going to take an hour long show and 430 00:21:09,040 --> 00:21:11,320 Speaker 11: somehow put it on this platform that has no real 431 00:21:11,440 --> 00:21:12,639 Speaker 11: history of TV shows. 432 00:21:13,760 --> 00:21:15,280 Speaker 5: This show used to stream on Twitter. 433 00:21:15,320 --> 00:21:20,359 Speaker 4: But there is an interesting viewpoint overall about just the 434 00:21:20,359 --> 00:21:23,280 Speaker 4: way in which we consume as well. I mean, how 435 00:21:23,359 --> 00:21:25,920 Speaker 4: much is there a vindication that people will want three 436 00:21:26,000 --> 00:21:30,000 Speaker 4: minute long pieces of information indeed shows anywhere you go, 437 00:21:30,040 --> 00:21:33,160 Speaker 4: Because is there anything that resembles another social media network 438 00:21:33,160 --> 00:21:36,480 Speaker 4: that's done content delivery, done shows like this in a 439 00:21:36,520 --> 00:21:37,240 Speaker 4: decent manner. 440 00:21:37,480 --> 00:21:41,679 Speaker 11: I mean, you know, Snapchat, YouTube, Facebook, like, people have 441 00:21:41,800 --> 00:21:44,720 Speaker 11: experimented with different links and different kinds of shows, political 442 00:21:44,800 --> 00:21:49,439 Speaker 11: shows on social media platforms. Yeah, and you know, Tucker, 443 00:21:49,680 --> 00:21:52,520 Speaker 11: he has these home studios that he built during the pandemic. 444 00:21:53,240 --> 00:21:58,160 Speaker 11: He's got a very robust and loyal audience. So you know, 445 00:21:58,840 --> 00:22:01,080 Speaker 11: how is that going to be monitored. It's hard to imagine, 446 00:22:01,080 --> 00:22:03,159 Speaker 11: but it does give him a voice in the platform 447 00:22:03,480 --> 00:22:07,000 Speaker 11: to keep himself relevant during the political campaign that's coming up, 448 00:22:07,200 --> 00:22:09,439 Speaker 11: as opposed to just being on the sidelines until he 449 00:22:09,480 --> 00:22:12,840 Speaker 11: finds a new cable network that would take. 450 00:22:12,760 --> 00:22:15,440 Speaker 4: Him rumble shares. On that note, we're on the down 451 00:22:15,520 --> 00:22:18,080 Speaker 4: side after the news. Felix Jenette always great to get 452 00:22:18,119 --> 00:22:27,520 Speaker 4: his take on all these things. We thank him. Welcome 453 00:22:27,520 --> 00:22:29,840 Speaker 4: back to BlueBag Technology. I'm Caroline Hide in New York. 454 00:22:29,880 --> 00:22:31,399 Speaker 4: Let's have a quick check on your markets because we've 455 00:22:31,400 --> 00:22:34,040 Speaker 4: actually seen a reprieve in tech stocks again on the 456 00:22:34,080 --> 00:22:36,959 Speaker 4: back of inflation data that shows maybe this pricing pressure 457 00:22:37,040 --> 00:22:39,800 Speaker 4: is cooling. Of course, interest rates sensitive tech stocks do well, 458 00:22:39,800 --> 00:22:41,439 Speaker 4: and then as like one hundred more than seven ten 459 00:22:41,680 --> 00:22:44,800 Speaker 4: percent as inflation comes in sub five percent year on year, 460 00:22:44,840 --> 00:22:46,920 Speaker 4: we're looking at ten year yield getting a bid. That's 461 00:22:47,000 --> 00:22:49,320 Speaker 4: as we maybe anticipate the Fed will maybe be able 462 00:22:49,359 --> 00:22:51,880 Speaker 4: to take that pause in its hiking cycle. We're down 463 00:22:51,920 --> 00:22:55,400 Speaker 4: seven basis points. Bitcoin does higher as the dollar goes lower. 464 00:22:55,400 --> 00:22:56,480 Speaker 4: We're up more than two percent. 465 00:22:56,680 --> 00:22:57,119 Speaker 5: Flick it on. 466 00:22:57,200 --> 00:22:59,000 Speaker 4: Let's go into some of the individual names, though, because 467 00:22:59,040 --> 00:23:01,640 Speaker 4: we've had mixtra amount of earning still to be digesting. 468 00:23:01,640 --> 00:23:03,720 Speaker 4: A firm on the higher side up more than four percent, 469 00:23:03,960 --> 00:23:06,600 Speaker 4: even there was some caution after the numbers dropped about 470 00:23:06,880 --> 00:23:10,520 Speaker 4: overall by now pay later the overall headwinds in this 471 00:23:10,600 --> 00:23:14,320 Speaker 4: macro environment of consumer but many an analyst thinking that 472 00:23:14,359 --> 00:23:16,040 Speaker 4: this is a stock that can weather. 473 00:23:15,920 --> 00:23:17,959 Speaker 5: Can perform at the moment. So we're up more than 474 00:23:17,960 --> 00:23:18,439 Speaker 5: four percent. 475 00:23:18,520 --> 00:23:21,080 Speaker 4: Data Dog, it's a local company, New York based up 476 00:23:21,160 --> 00:23:24,359 Speaker 4: six percent. Guess what's gone. An integration with open ai 477 00:23:24,480 --> 00:23:25,920 Speaker 4: and people like it, the fact that it's gonna be 478 00:23:26,000 --> 00:23:28,639 Speaker 4: checking in on how companies interact with chatchibt and like 479 00:23:28,680 --> 00:23:31,760 Speaker 4: product products. So Data Dog on the upside. Airbnb very 480 00:23:31,800 --> 00:23:34,119 Speaker 4: much on the downside, having its worse fall as a 481 00:23:34,119 --> 00:23:36,920 Speaker 4: publicly traded company after its forward looking guidance was a 482 00:23:36,960 --> 00:23:39,800 Speaker 4: little bit weak. Let's talk about other earnings, because there 483 00:23:39,800 --> 00:23:42,040 Speaker 4: are more they can fast in the EV space. In particular, 484 00:23:42,119 --> 00:23:45,000 Speaker 4: Blink Charging just reported revenue for the first quarter nook. 485 00:23:45,040 --> 00:23:47,439 Speaker 4: It missed some analystsessiments out there, but it's still more 486 00:23:47,440 --> 00:23:51,040 Speaker 4: than doubling revenues. The ev Charging Stations Company is really 487 00:23:51,040 --> 00:23:54,600 Speaker 4: continuing to transition to an in house manufacturing model. Gross 488 00:23:54,640 --> 00:23:57,320 Speaker 4: margin profile is expected to improve throughout twenty twenty three 489 00:23:57,359 --> 00:23:59,560 Speaker 4: and the next year. Let's talk about it all with 490 00:23:59,600 --> 00:24:02,280 Speaker 4: the relative we knew recently appointed CEO, Brendan Jones. 491 00:24:02,320 --> 00:24:03,880 Speaker 5: Of course you were other business. 492 00:24:03,560 --> 00:24:06,600 Speaker 4: Already and now taking the CEO mantel Brendan and just 493 00:24:06,640 --> 00:24:10,080 Speaker 4: talk to us about the revenue drivers here. Who is 494 00:24:10,119 --> 00:24:12,680 Speaker 4: wanting to get their hands on these charging stations across 495 00:24:12,680 --> 00:24:13,479 Speaker 4: the United States? 496 00:24:13,960 --> 00:24:16,640 Speaker 6: Absolutely so, this space is on fire. 497 00:24:17,359 --> 00:24:20,600 Speaker 8: As more and more states start to adopt provisions that 498 00:24:20,760 --> 00:24:24,000 Speaker 8: say that internal combustion engines can no longer be sold 499 00:24:24,000 --> 00:24:28,040 Speaker 8: past twenty thirty five, we're seeing an increasing emphasis on 500 00:24:28,280 --> 00:24:29,920 Speaker 8: charging and who's. 501 00:24:29,640 --> 00:24:30,359 Speaker 6: Asking for it. 502 00:24:30,440 --> 00:24:34,640 Speaker 8: You've got everything from municipalities to private ownerships, to big 503 00:24:34,680 --> 00:24:38,639 Speaker 8: real estate groups, to state parks that want to have 504 00:24:38,760 --> 00:24:42,280 Speaker 8: charging for new sport utility vehicles that are EVY, and. 505 00:24:42,200 --> 00:24:45,080 Speaker 6: Of course the federal government. We're very proud to have 506 00:24:45,160 --> 00:24:45,560 Speaker 6: been one. 507 00:24:45,640 --> 00:24:49,240 Speaker 8: The United States Post Office Service put out a bid 508 00:24:49,320 --> 00:24:53,879 Speaker 8: for four thousand for forty five thousand chargers. We won 509 00:24:54,000 --> 00:24:56,520 Speaker 8: part of that deal and we've already began to install 510 00:24:56,600 --> 00:25:00,399 Speaker 8: those chargers with USPS. So the goal right now is 511 00:25:00,440 --> 00:25:03,200 Speaker 8: to make sure that we can get as many chargers 512 00:25:03,240 --> 00:25:07,440 Speaker 8: out there to service the ED buying public and blink 513 00:25:07,520 --> 00:25:07,920 Speaker 8: right now. 514 00:25:07,960 --> 00:25:09,560 Speaker 6: As you saw, we're on digit. 515 00:25:09,440 --> 00:25:12,560 Speaker 8: Double digit growth between last year and this year, and 516 00:25:12,600 --> 00:25:15,879 Speaker 8: we see that trend continuing for the foreseeable future. 517 00:25:16,440 --> 00:25:19,240 Speaker 4: How does the US stack up versus Europe, Asia, Latin America. 518 00:25:19,320 --> 00:25:21,240 Speaker 4: I know these are all markets that you're analyzing and 519 00:25:21,640 --> 00:25:23,440 Speaker 4: in yes. 520 00:25:23,400 --> 00:25:25,640 Speaker 8: So what you see in Europe is a little bit 521 00:25:25,920 --> 00:25:29,040 Speaker 8: progression of the model. So they're much further ahead on 522 00:25:29,119 --> 00:25:32,679 Speaker 8: both the car sales and the penetration of chargers in 523 00:25:32,720 --> 00:25:36,560 Speaker 8: the public space. So US is following right behind that. 524 00:25:36,960 --> 00:25:39,280 Speaker 8: So while there a little ahead, we see ourselves as 525 00:25:39,359 --> 00:25:39,960 Speaker 8: catching up. 526 00:25:40,400 --> 00:25:40,640 Speaker 6: Now. 527 00:25:40,680 --> 00:25:44,399 Speaker 8: A lot in Europe is policy driven to mandate charging 528 00:25:44,440 --> 00:25:47,480 Speaker 8: and mandate the purchase of electric vehicles. We have some 529 00:25:47,640 --> 00:25:50,600 Speaker 8: policy initiatives that make it easy to adopt, and then 530 00:25:50,600 --> 00:25:52,920 Speaker 8: we have the federal funding for the Nevy program, the 531 00:25:52,960 --> 00:25:57,160 Speaker 8: two billion dollars from the Biden administration to accelerate infrastructure. 532 00:25:57,560 --> 00:25:59,719 Speaker 6: So the US is more show US. But I'll tell 533 00:25:59,760 --> 00:26:03,480 Speaker 6: you the autoims they are bringing out the cars today. 534 00:26:03,680 --> 00:26:09,280 Speaker 8: You have some of the most versatile, sexiest high speed 535 00:26:09,359 --> 00:26:10,840 Speaker 8: cars on the market. 536 00:26:10,520 --> 00:26:11,480 Speaker 6: That all drives. 537 00:26:11,640 --> 00:26:12,200 Speaker 5: What do you happen? 538 00:26:12,400 --> 00:26:16,320 Speaker 8: So I transitioned just recently out of Audietron, which is 539 00:26:16,320 --> 00:26:19,840 Speaker 8: a beautiful car, you know, full ev all the way, 540 00:26:19,880 --> 00:26:23,160 Speaker 8: but all everything you expected in a luxury car. Now 541 00:26:23,240 --> 00:26:25,680 Speaker 8: I'm looking at a couple of different models, some domestic 542 00:26:26,640 --> 00:26:29,560 Speaker 8: and some meat overseas as well. 543 00:26:30,400 --> 00:26:34,080 Speaker 6: So my goal in life was always on a Mustang. 544 00:26:34,320 --> 00:26:36,479 Speaker 8: So I'm not hitting that it might be a monkey, 545 00:26:36,920 --> 00:26:38,520 Speaker 8: but I'm definitely leading that direction. 546 00:26:39,440 --> 00:26:43,240 Speaker 4: What about the inside focus on where you're buying? But 547 00:26:43,320 --> 00:26:45,720 Speaker 4: what about the innovation that blinks doing at the moment 548 00:26:45,760 --> 00:26:46,080 Speaker 4: as well? 549 00:26:46,119 --> 00:26:47,840 Speaker 5: Because yes, it would. 550 00:26:47,640 --> 00:26:49,359 Speaker 4: Be lovely, of course to have the infrastructure there that 551 00:26:49,359 --> 00:26:51,560 Speaker 4: we can all pull up and be able to speedily 552 00:26:51,960 --> 00:26:53,960 Speaker 4: charge our cars, But what about if you're on the move, 553 00:26:54,000 --> 00:26:56,520 Speaker 4: what about if you've been breaking down you're having I mean, 554 00:26:56,560 --> 00:26:58,320 Speaker 4: I know you had a whole host of different kind 555 00:26:58,320 --> 00:27:00,680 Speaker 4: of options on array at CS this one. 556 00:27:01,080 --> 00:27:03,919 Speaker 8: Yeah, and absolutely what we want to do is service 557 00:27:03,960 --> 00:27:07,520 Speaker 8: the pallethor of charging needs for the public. And that 558 00:27:07,560 --> 00:27:09,920 Speaker 8: means you've got to have fast chargers on the highway 559 00:27:10,119 --> 00:27:12,800 Speaker 8: that can fuel a vehicle in under thirty minutes or 560 00:27:12,840 --> 00:27:15,600 Speaker 8: in some cases under fifteen depending on the speed of 561 00:27:15,640 --> 00:27:16,160 Speaker 8: the battery. 562 00:27:16,720 --> 00:27:18,800 Speaker 6: Then you also have to havet home based charging. 563 00:27:18,840 --> 00:27:21,360 Speaker 8: When we look at McKinsey data, it tells us that 564 00:27:21,480 --> 00:27:23,880 Speaker 8: ninety percent of the charging that's going to take place 565 00:27:23,920 --> 00:27:27,320 Speaker 8: globally is what we call level two charging, and then 566 00:27:27,320 --> 00:27:29,600 Speaker 8: the other ten percent is going to be DC fast charging, 567 00:27:29,760 --> 00:27:32,960 Speaker 8: which is the faster must have charging. But also, as 568 00:27:33,000 --> 00:27:35,000 Speaker 8: you point it out, there's this need for what we 569 00:27:35,080 --> 00:27:38,920 Speaker 8: call a rescue charger. So if you run out of charge, 570 00:27:38,960 --> 00:27:41,280 Speaker 8: just like you run out of gas, we also have 571 00:27:41,359 --> 00:27:43,520 Speaker 8: products to satisfy that market, so. 572 00:27:43,440 --> 00:27:45,400 Speaker 6: We can charge you up on the go and get 573 00:27:45,440 --> 00:27:47,800 Speaker 6: you back to a charger as soon as possible. 574 00:27:47,920 --> 00:27:51,240 Speaker 8: So our job is to cover the home, to cover 575 00:27:51,280 --> 00:27:54,040 Speaker 8: the public, to cover the municipalities, and to cover the 576 00:27:54,119 --> 00:27:57,119 Speaker 8: highway with charging and make sure we have options and 577 00:27:57,200 --> 00:28:01,400 Speaker 8: innovative products to serve the general the general needs out there. 578 00:28:01,440 --> 00:28:04,359 Speaker 4: Are you growing that and innovating organically or I know 579 00:28:04,480 --> 00:28:06,639 Speaker 4: that you make quite a lot of acquisitions as well. 580 00:28:06,760 --> 00:28:08,119 Speaker 4: Do you want to do bolt on us to be 581 00:28:08,119 --> 00:28:09,679 Speaker 4: able to add that sort of level of offering. 582 00:28:10,359 --> 00:28:14,600 Speaker 8: Yeah, So we continue to be an inquisitive company. So 583 00:28:14,680 --> 00:28:18,560 Speaker 8: where acquisitions make sense, we will pursue them. We just 584 00:28:18,600 --> 00:28:25,400 Speaker 8: acquired a car sharing company called Envoy, who basically has 585 00:28:25,480 --> 00:28:28,400 Speaker 8: people engage with them on a car by car basis. 586 00:28:28,640 --> 00:28:30,520 Speaker 8: They get it, they're all evs, They get it for 587 00:28:30,560 --> 00:28:32,400 Speaker 8: a day, for an hour, etc. 588 00:28:32,840 --> 00:28:35,720 Speaker 6: They charge on our charging stations, and then we have. 589 00:28:35,680 --> 00:28:39,520 Speaker 8: Blue La, which is our mobility program in Los Angeles, 590 00:28:39,520 --> 00:28:42,760 Speaker 8: and under Blue La, we have two hundred stations that 591 00:28:42,800 --> 00:28:44,880 Speaker 8: have two to three cars on them and the general 592 00:28:44,920 --> 00:28:47,840 Speaker 8: public comes in there, takes a car for a day, 593 00:28:48,240 --> 00:28:50,400 Speaker 8: gets a chance to be in an EV and they 594 00:28:50,440 --> 00:28:54,360 Speaker 8: serve both the general public and the underserved communities simultaneously. 595 00:28:54,400 --> 00:28:56,560 Speaker 6: And we do both the cars and the charging. 596 00:28:57,120 --> 00:29:00,640 Speaker 4: Brendan, what's the regulatory environment for you thanking thesels of 597 00:29:00,640 --> 00:29:02,600 Speaker 4: acquisitions at the moment. I know you're not a big 598 00:29:02,680 --> 00:29:06,360 Speaker 4: cat player yet at the moment, but what are the 599 00:29:06,440 --> 00:29:08,760 Speaker 4: concerns about making acquisitions of other companies. 600 00:29:09,600 --> 00:29:12,000 Speaker 8: Well, you have to make sure that these acquisitions, when 601 00:29:12,000 --> 00:29:12,560 Speaker 8: we're looking at. 602 00:29:12,560 --> 00:29:14,080 Speaker 6: Them, you have a high degree of synergies. 603 00:29:14,480 --> 00:29:17,120 Speaker 8: If you don't, it doesn't make sense because the acquisition 604 00:29:17,240 --> 00:29:20,160 Speaker 8: of the in and of itself has to fit into 605 00:29:20,200 --> 00:29:23,040 Speaker 8: our business models. If it doesn't, we're going to pass 606 00:29:23,360 --> 00:29:26,560 Speaker 8: because the synergies of which makes that very valid. And 607 00:29:26,600 --> 00:29:29,840 Speaker 8: when you look at acquisitions in general and you benchmark 608 00:29:29,960 --> 00:29:32,880 Speaker 8: other companies, you see where they failed was they didn't 609 00:29:32,960 --> 00:29:35,800 Speaker 8: get the synergies. So we put a lot of money. 610 00:29:35,880 --> 00:29:39,640 Speaker 8: We work with McKenzie to outline, set a path, and 611 00:29:39,720 --> 00:29:44,680 Speaker 8: set a timeline associated to bid revenue sentergies, g anda sentergies, 612 00:29:44,840 --> 00:29:46,800 Speaker 8: and then product synergies across the board. 613 00:29:47,040 --> 00:29:50,000 Speaker 6: Without that, we're not going to do any acquisitions. 614 00:29:50,040 --> 00:29:52,400 Speaker 8: We need that to be efficient and to really get 615 00:29:52,400 --> 00:29:53,400 Speaker 8: to global scale. 616 00:29:54,400 --> 00:29:57,400 Speaker 4: Well, thank you giving us the global perspective link CEO 617 00:29:57,520 --> 00:30:00,880 Speaker 4: Friend and Jones. And look, let's just focus on M 618 00:30:00,920 --> 00:30:02,640 Speaker 4: and A a little bit more in the world of 619 00:30:02,680 --> 00:30:06,040 Speaker 4: tech because Bloomberg research has found that US government's current 620 00:30:06,120 --> 00:30:09,240 Speaker 4: aggressive stance on anti trust it's actually really chilling merger 621 00:30:09,280 --> 00:30:12,360 Speaker 4: activity among the country's biggest companies for some deals never 622 00:30:12,400 --> 00:30:14,920 Speaker 4: making it past the boardroom. Let's bring in and peace 623 00:30:14,960 --> 00:30:16,920 Speaker 4: to say right here in Neil Leah Nyland, who's over 624 00:30:16,920 --> 00:30:19,640 Speaker 4: from Washington to break it all down, and this story 625 00:30:19,720 --> 00:30:22,720 Speaker 4: really showing just how much of a chilling effect. Just 626 00:30:22,840 --> 00:30:25,160 Speaker 4: can you paint the picture of where we've been and 627 00:30:25,200 --> 00:30:27,440 Speaker 4: where we've come to because of the action of the administration. 628 00:30:27,760 --> 00:30:31,040 Speaker 12: Yeah, so the Biden administration really came in strong on 629 00:30:31,120 --> 00:30:34,280 Speaker 12: anti trust. They really felt that the past administrations were 630 00:30:34,280 --> 00:30:37,720 Speaker 12: a little too easy on mergers and letting big deals 631 00:30:37,760 --> 00:30:41,440 Speaker 12: go through with only settlements or maybe like challenging only 632 00:30:41,480 --> 00:30:43,760 Speaker 12: a couple of the bigger ones. But the Biden administration 633 00:30:43,840 --> 00:30:46,440 Speaker 12: has been really aggressive on this so far. Since the 634 00:30:46,520 --> 00:30:49,400 Speaker 12: anti trust enforcers came in in July of twenty twenty one, 635 00:30:49,880 --> 00:30:54,640 Speaker 12: they have challenged seventeen cases in court, but they've also 636 00:30:55,400 --> 00:30:58,880 Speaker 12: raised anti trust concerns about another twenty six. So those abandoned, 637 00:30:59,280 --> 00:31:01,800 Speaker 12: those deals were abandoned before they even made it to court. 638 00:31:02,120 --> 00:31:05,560 Speaker 12: So they have quite a record of, you know, killing 639 00:31:05,560 --> 00:31:06,480 Speaker 12: off deals so far. 640 00:31:07,040 --> 00:31:10,600 Speaker 5: How much are they ultimately tech savvy. 641 00:31:10,600 --> 00:31:13,000 Speaker 4: We know that the FTC that got a very much 642 00:31:13,040 --> 00:31:17,240 Speaker 4: a leaderly A Khan, who's focused on the world of technology, 643 00:31:17,280 --> 00:31:19,960 Speaker 4: did a lot of work within big tech. But there 644 00:31:20,000 --> 00:31:22,760 Speaker 4: is a talk now about AI being a new area 645 00:31:22,800 --> 00:31:28,320 Speaker 4: in which we get competitive overreach and monopolistic capabilities. How 646 00:31:28,400 --> 00:31:30,640 Speaker 4: much of those of the conversations you're having, is it 647 00:31:30,720 --> 00:31:32,960 Speaker 4: all about big tech and stifling there or just this 648 00:31:33,360 --> 00:31:34,280 Speaker 4: go cross industry. 649 00:31:34,320 --> 00:31:36,120 Speaker 12: It goes across industry, as if you look at a 650 00:31:36,120 --> 00:31:39,000 Speaker 12: lot of the deals that they have blocked, You've seen 651 00:31:39,040 --> 00:31:41,920 Speaker 12: a lot in the healthcare sector, you see some in 652 00:31:42,240 --> 00:31:46,280 Speaker 12: you know, brick and mortar industries like concrete and cement, 653 00:31:46,720 --> 00:31:48,960 Speaker 12: But the big tech ones are definitely ones that are 654 00:31:49,000 --> 00:31:50,280 Speaker 12: they're paying a lot of attention to. 655 00:31:50,320 --> 00:31:50,760 Speaker 5: You know. 656 00:31:50,840 --> 00:31:54,560 Speaker 12: The big case that the FTC challenged last year was 657 00:31:54,600 --> 00:31:58,880 Speaker 12: the one between meta platforms and Within, which was actually 658 00:31:58,960 --> 00:32:03,480 Speaker 12: just a small stirred up focused on virtual reality. One 659 00:32:03,480 --> 00:32:06,520 Speaker 12: of the anecdotes in our story was actually about Google 660 00:32:06,600 --> 00:32:09,960 Speaker 12: abandoning an acquisition because they had some concerns about the 661 00:32:10,000 --> 00:32:11,640 Speaker 12: antitrust problems. 662 00:32:11,240 --> 00:32:11,960 Speaker 5: That it could raise. 663 00:32:12,560 --> 00:32:15,400 Speaker 12: And both of the leaders of the antrus agencies right now, 664 00:32:15,440 --> 00:32:18,239 Speaker 12: that's Lena Khan at the FTC and Jonathan Kanter at 665 00:32:18,240 --> 00:32:21,200 Speaker 12: the Justice Department, have said that they're actually looking really 666 00:32:21,200 --> 00:32:24,120 Speaker 12: closely at AI because they're very concerned that some of 667 00:32:24,160 --> 00:32:28,320 Speaker 12: the biggest companies, the Microsofts, the Googles, the Amazons of 668 00:32:28,360 --> 00:32:31,880 Speaker 12: the world, really have the resources to devote to AI, 669 00:32:32,160 --> 00:32:34,680 Speaker 12: and they're really concerned that they might try, you know, 670 00:32:34,720 --> 00:32:37,120 Speaker 12: buying up a lot of the people who are really 671 00:32:37,160 --> 00:32:39,760 Speaker 12: focused on that and sort of dominating the AI market 672 00:32:39,800 --> 00:32:41,480 Speaker 12: and the way that they have really been able to 673 00:32:41,480 --> 00:32:42,240 Speaker 12: dominate the web. 674 00:32:42,960 --> 00:32:44,680 Speaker 5: What's interesting is some would say. 675 00:32:45,960 --> 00:32:49,680 Speaker 4: FTC Action, for example, hasn't actually been that successful. Yeah, 676 00:32:49,760 --> 00:32:53,320 Speaker 4: does that give companies speaking to a bit more resilience 677 00:32:53,360 --> 00:32:55,800 Speaker 4: and optimism they can get these deals through? Or they 678 00:32:55,800 --> 00:32:58,400 Speaker 4: look more what the UK's up to with Microsoft and 679 00:32:58,480 --> 00:32:59,200 Speaker 4: they think, okay. 680 00:32:59,040 --> 00:33:02,360 Speaker 12: No, it really depends. You know, companies that are more 681 00:33:02,920 --> 00:33:05,040 Speaker 12: risk averse aren't really going to want to put the 682 00:33:05,120 --> 00:33:07,840 Speaker 12: time and the money into this because so the increase 683 00:33:07,920 --> 00:33:10,520 Speaker 12: any trust really is dragging some of these things out. 684 00:33:11,280 --> 00:33:15,520 Speaker 12: But really big deals like Microsoft Activision, they're still going forward, 685 00:33:15,640 --> 00:33:18,320 Speaker 12: even in the face of regulatory scrutiny. So that one 686 00:33:18,400 --> 00:33:23,160 Speaker 12: the UK has blocked the FTC has brought litigation against 687 00:33:23,160 --> 00:33:25,200 Speaker 12: it that's supposed to go to trial later this year. 688 00:33:25,480 --> 00:33:27,600 Speaker 12: We're still waiting on the EU to make a decision. 689 00:33:27,640 --> 00:33:30,480 Speaker 12: It will later this month, but it's unclear if that 690 00:33:30,520 --> 00:33:33,200 Speaker 12: one's going to go through, just because when you get 691 00:33:33,240 --> 00:33:35,760 Speaker 12: that many lawsuits against a deal, it becomes really hard 692 00:33:35,800 --> 00:33:36,400 Speaker 12: to move forward. 693 00:33:36,960 --> 00:33:38,640 Speaker 4: Nana and it's great to have you right here in 694 00:33:38,720 --> 00:33:41,800 Speaker 4: New York. Appreciate it. We thank her for that great story. 695 00:33:41,840 --> 00:33:44,400 Speaker 4: And Ashley, we were just talking about the worries around 696 00:33:44,640 --> 00:33:47,200 Speaker 4: AI dominance. Well, coming up, we've got a great conversation 697 00:33:47,280 --> 00:33:49,560 Speaker 4: to have in the world degenerative AI with a leader. 698 00:33:49,800 --> 00:33:52,360 Speaker 4: Scale AI is deploying new tools to help its clients 699 00:33:52,400 --> 00:33:55,680 Speaker 4: safely and responsibly integrate the technology into their systems. We're 700 00:33:55,680 --> 00:33:57,480 Speaker 4: going to have a conversation with the founder, the CEO, 701 00:33:57,760 --> 00:33:58,680 Speaker 4: Alexandra Wang. 702 00:33:59,080 --> 00:34:00,240 Speaker 5: But let's talk about. 703 00:34:00,320 --> 00:34:03,520 Speaker 4: Potential monopolies building in the space, or want to be monopolies. 704 00:34:03,560 --> 00:34:07,480 Speaker 4: Because panenteer up another day after its earnings came out 705 00:34:07,480 --> 00:34:10,560 Speaker 4: and they talked about the unprecedented demand for its own 706 00:34:10,680 --> 00:34:14,239 Speaker 4: AI offering. The CEO alex cart get this saying that 707 00:34:14,280 --> 00:34:16,880 Speaker 4: they just want to take the whole market. 708 00:34:17,400 --> 00:34:20,680 Speaker 5: That's a strategy for AI apparently from New York. This 709 00:34:20,840 --> 00:34:21,400 Speaker 5: a Bloomberg. 710 00:34:36,880 --> 00:34:40,320 Speaker 4: Scale AI as a leader in creating generative AI systems 711 00:34:40,360 --> 00:34:43,520 Speaker 4: and it's launching two new platforms tell its customers apply 712 00:34:43,680 --> 00:34:47,800 Speaker 4: AI systems within their networks. Joining now is Alexander Wang, 713 00:34:47,840 --> 00:34:51,719 Speaker 4: the founder and CEO of Scale AI, and alex at 714 00:34:51,760 --> 00:34:54,319 Speaker 4: the moment, I'm trying to wade through Panenteer that was 715 00:34:54,360 --> 00:34:57,319 Speaker 4: to take the whole market. We had salesforce on interjecting 716 00:34:57,480 --> 00:35:01,400 Speaker 4: chat GPT within its offerings or Slack, and for Tableau 717 00:35:01,440 --> 00:35:04,360 Speaker 4: we've got IBM with Watson X. What exactly are you 718 00:35:04,440 --> 00:35:06,720 Speaker 4: offering that's kind of different from the others. 719 00:35:07,239 --> 00:35:10,400 Speaker 13: Yeah, So at Scale we've been in the AI industry 720 00:35:10,480 --> 00:35:13,240 Speaker 13: for more than seven years now. We've been quietly powering 721 00:35:13,360 --> 00:35:16,480 Speaker 13: much of the modern revolution in generative AI. And what 722 00:35:16,480 --> 00:35:19,840 Speaker 13: we're seeing today is a lot of AI tourists pretending 723 00:35:19,840 --> 00:35:21,400 Speaker 13: to be AI natives. You know, there's a lot of 724 00:35:21,440 --> 00:35:24,680 Speaker 13: companies who are not selling solutions. They're ultimately just selling 725 00:35:24,719 --> 00:35:28,319 Speaker 13: vaporware and our products, you know, they aren't coming soon. 726 00:35:28,440 --> 00:35:31,560 Speaker 13: They're in the hands of customers today, from the Fortune 727 00:35:31,600 --> 00:35:33,880 Speaker 13: five hundred to the US Department of Defense, and we 728 00:35:33,920 --> 00:35:36,120 Speaker 13: don't see many other platforms that can say that. 729 00:35:36,560 --> 00:35:38,440 Speaker 1: So today we're proud. 730 00:35:38,239 --> 00:35:41,880 Speaker 13: To introduce our two new generative AI platforms, Scale Donovan 731 00:35:42,080 --> 00:35:45,239 Speaker 13: and Scale EGP to unlock the power of AI for 732 00:35:45,600 --> 00:35:50,520 Speaker 13: every industry, from the US government to global enterprise. Our 733 00:35:50,640 --> 00:35:55,359 Speaker 13: Donovan product is our platform, which is the first large 734 00:35:55,440 --> 00:35:58,640 Speaker 13: language model deployed on a classified network for the US 735 00:35:58,719 --> 00:36:03,440 Speaker 13: government and with our war fighters connect in minutes instead 736 00:36:03,440 --> 00:36:06,560 Speaker 13: of weeks. And our customers today include the US Army's 737 00:36:06,560 --> 00:36:11,120 Speaker 13: eighteen Airborne Corps, the DoD's CDAO and the Joint All 738 00:36:11,120 --> 00:36:13,760 Speaker 13: Demand Command and Control Effort in particular, and the Marine 739 00:36:13,760 --> 00:36:15,719 Speaker 13: Corps University School of Advanced Warfighting. 740 00:36:15,920 --> 00:36:18,440 Speaker 4: So just to go back, are you saying that palenteer 741 00:36:19,239 --> 00:36:24,080 Speaker 4: with its machine learning and it's already integration with the 742 00:36:24,120 --> 00:36:26,760 Speaker 4: Defense Partment, for example, that's an AI tourist. 743 00:36:27,360 --> 00:36:29,319 Speaker 13: So, you know, I think the key thing to look 744 00:36:29,360 --> 00:36:31,960 Speaker 13: at with any one of these platforms is whether or 745 00:36:32,040 --> 00:36:35,360 Speaker 13: not they have customers that are live with the technology. 746 00:36:34,880 --> 00:36:36,640 Speaker 1: Today or are using it actively. 747 00:36:36,920 --> 00:36:39,400 Speaker 13: And you know, I think there are plenty of platforms 748 00:36:39,400 --> 00:36:41,719 Speaker 13: that are touting huge announcements but that do not have 749 00:36:41,760 --> 00:36:45,480 Speaker 13: any live customers and any activity today, and they have 750 00:36:45,719 --> 00:36:51,040 Speaker 13: oftentimes coming soon as sort of the headline on their homepages. 751 00:36:51,239 --> 00:36:52,920 Speaker 13: So I think that's one of the key things to 752 00:36:52,960 --> 00:36:55,040 Speaker 13: look at. You know, we at scale we've worked with 753 00:36:55,120 --> 00:36:57,440 Speaker 13: open AI since twenty nineteen, or you have much of 754 00:36:57,480 --> 00:37:01,120 Speaker 13: the technology that's undergirded chat, GPT and other technologies work 755 00:37:01,160 --> 00:37:03,920 Speaker 13: with much of the rest of the ecosystems such as Microsoft, 756 00:37:04,040 --> 00:37:09,920 Speaker 13: meta working folks like Stability, adept, carper cohere, and so 757 00:37:10,200 --> 00:37:12,880 Speaker 13: this is you know, we've been in this industry. We 758 00:37:12,920 --> 00:37:15,280 Speaker 13: have we're one of the companies with the greatest amount 759 00:37:15,280 --> 00:37:17,480 Speaker 13: of experience in generative AI, and we're excited to actually 760 00:37:17,520 --> 00:37:20,920 Speaker 13: bring that expertise to the enterprise, EMPTO government customers. 761 00:37:20,560 --> 00:37:23,440 Speaker 4: And to the White House in terms of evaluating platforms. 762 00:37:23,520 --> 00:37:24,879 Speaker 5: Right, just remind us. 763 00:37:24,880 --> 00:37:26,839 Speaker 4: That is it going to be your platform that they're 764 00:37:26,880 --> 00:37:29,440 Speaker 4: using at Defcon thirty one to be able to basically 765 00:37:29,560 --> 00:37:33,839 Speaker 4: test and understand how hugging Face and topic Google actually work. 766 00:37:34,320 --> 00:37:35,120 Speaker 1: Yeah, exactly. 767 00:37:35,200 --> 00:37:38,799 Speaker 13: So we are Switzerland, we are not behold into any 768 00:37:38,800 --> 00:37:41,960 Speaker 13: one platform, and in fact, we've been quietly partnering with 769 00:37:42,080 --> 00:37:44,360 Speaker 13: most of the AI industry. As a result, we're the 770 00:37:44,400 --> 00:37:48,000 Speaker 13: perfect partner to work with the White House and with 771 00:37:48,080 --> 00:37:51,400 Speaker 13: Defcon in using our platform to actually evaluate all of 772 00:37:51,400 --> 00:37:53,840 Speaker 13: these models that are being built and understand what the 773 00:37:53,880 --> 00:37:57,040 Speaker 13: implications and safety implications of these models are. You know, 774 00:37:57,160 --> 00:38:00,080 Speaker 13: we believe that progress and foundation models needs to have 775 00:38:00,120 --> 00:38:04,160 Speaker 13: been hand in hand and alongside progress and model evaluation 776 00:38:04,239 --> 00:38:06,600 Speaker 13: and safety, and that's really what we've built our platform 777 00:38:06,640 --> 00:38:09,279 Speaker 13: to help enable and why our platform is going to 778 00:38:09,320 --> 00:38:11,960 Speaker 13: be the one that's used again in partnership with White House, 779 00:38:12,000 --> 00:38:14,960 Speaker 13: in partnership with Defcon to help understand these models. 780 00:38:15,040 --> 00:38:18,359 Speaker 4: What do you think you'll find, Alex, Do you think 781 00:38:18,400 --> 00:38:23,560 Speaker 4: you'll find safe and solid space is being crafted for 782 00:38:24,120 --> 00:38:28,000 Speaker 4: new models or you're a little bit more worried, you know. 783 00:38:27,960 --> 00:38:30,359 Speaker 13: I think broadly within the industry. One of the things 784 00:38:30,360 --> 00:38:32,279 Speaker 13: that's happened. One of the things that's happened is these 785 00:38:32,320 --> 00:38:34,960 Speaker 13: models have all been released and have have been released 786 00:38:35,000 --> 00:38:38,239 Speaker 13: down with the world before much of this testing has 787 00:38:38,239 --> 00:38:40,520 Speaker 13: taken place out in the public, and so you know, 788 00:38:40,600 --> 00:38:43,040 Speaker 13: I think invariably we're going to find some things that 789 00:38:43,080 --> 00:38:44,759 Speaker 13: are that are going to be concerning. But I think 790 00:38:44,800 --> 00:38:47,080 Speaker 13: we're also going to find that many of the builders 791 00:38:47,080 --> 00:38:49,880 Speaker 13: of these models have actually put a huge amount of 792 00:38:49,880 --> 00:38:52,040 Speaker 13: thought into the systems that they're developing, and so I 793 00:38:52,040 --> 00:38:53,560 Speaker 13: think we'll see a range. You know, there will be 794 00:38:53,600 --> 00:38:55,879 Speaker 13: some models that are significantly safer than others, and even 795 00:38:55,920 --> 00:38:57,640 Speaker 13: the models that are safe, I think we'll continue to 796 00:38:57,680 --> 00:38:59,239 Speaker 13: find things that you know, we need to work on, 797 00:38:59,280 --> 00:39:01,560 Speaker 13: we need to improve, you know, our goal with this 798 00:39:02,520 --> 00:39:04,239 Speaker 13: with this or in our work with the White Houns 799 00:39:04,280 --> 00:39:07,160 Speaker 13: with defcon is really in releasing a platform that and 800 00:39:07,560 --> 00:39:11,200 Speaker 13: a framework that can be used across for the rest 801 00:39:11,200 --> 00:39:13,320 Speaker 13: of for the in perpetuity by the industry. 802 00:39:13,440 --> 00:39:16,000 Speaker 1: We want to create an evaluation system that we can 803 00:39:16,120 --> 00:39:17,080 Speaker 1: always use to. 804 00:39:17,040 --> 00:39:19,600 Speaker 13: Evaluate the quality and performance of these models going forward. 805 00:39:19,760 --> 00:39:22,400 Speaker 4: But does it matter if we put regulation on the 806 00:39:22,560 --> 00:39:26,799 Speaker 4: United States or developed nations do when others many would 807 00:39:26,800 --> 00:39:30,000 Speaker 4: say China, Russia don't. And what does that look like 808 00:39:30,120 --> 00:39:33,200 Speaker 4: because technology doesn't have that many boundaries. 809 00:39:34,520 --> 00:39:36,640 Speaker 13: Yeah, I think this is this is a really really 810 00:39:36,640 --> 00:39:39,520 Speaker 13: important question, you know. I think that the topic of 811 00:39:39,560 --> 00:39:43,879 Speaker 13: AI regulation is certainly an important one, and as we've 812 00:39:43,920 --> 00:39:47,480 Speaker 13: seen with AI to date, the key to human centric 813 00:39:47,520 --> 00:39:51,719 Speaker 13: responsible AI is really a solid data foundation, you know. 814 00:39:51,719 --> 00:39:53,160 Speaker 1: For technology is transformed to this. 815 00:39:53,239 --> 00:39:55,440 Speaker 13: I think it's very important to consider the questions on 816 00:39:55,520 --> 00:39:59,040 Speaker 13: AI regulation and are what are the consumer impacts of 817 00:39:59,080 --> 00:40:01,520 Speaker 13: this technology? One of the reasons why we're so excited 818 00:40:01,520 --> 00:40:03,359 Speaker 13: about the work that we're doing with the White House 819 00:40:03,400 --> 00:40:06,880 Speaker 13: and others. That being said, like you mentioned, our adversaries, 820 00:40:06,880 --> 00:40:09,360 Speaker 13: our near peer competitors like Russia and China will not 821 00:40:09,480 --> 00:40:11,759 Speaker 13: let regulation get in the way of their ambitions, and 822 00:40:11,800 --> 00:40:13,680 Speaker 13: in fact, I think it's quite the opposite, they will 823 00:40:13,760 --> 00:40:17,040 Speaker 13: use these tools to tighten their grip on you know, 824 00:40:17,160 --> 00:40:19,640 Speaker 13: domestic social and political control. 825 00:40:20,320 --> 00:40:24,080 Speaker 5: So you know, now we'll finish that thought. 826 00:40:24,920 --> 00:40:25,160 Speaker 1: Yeah. 827 00:40:25,200 --> 00:40:28,120 Speaker 13: So you know in China, you know, the the the 828 00:40:28,120 --> 00:40:30,799 Speaker 13: content of their AI systems, you know, will need to 829 00:40:30,800 --> 00:40:35,200 Speaker 13: reflect their socialist core values and avoid information that that 830 00:40:35,280 --> 00:40:38,120 Speaker 13: undermines their state power, national unity. And so you know, 831 00:40:38,160 --> 00:40:43,080 Speaker 13: you see intent from our near peer competitors to to use. 832 00:40:42,880 --> 00:40:45,120 Speaker 1: This technology to for their ambitions. 833 00:40:45,120 --> 00:40:48,800 Speaker 13: And again they won't, they won't overregulate to prevent the 834 00:40:50,000 --> 00:40:51,680 Speaker 13: proliferation in spread of the technology. 835 00:40:52,360 --> 00:40:56,520 Speaker 5: Very briefly, open source versus not? Where do you come 836 00:40:56,560 --> 00:40:57,279 Speaker 5: down on order that? 837 00:40:58,600 --> 00:41:03,320 Speaker 13: So our belief is that enterprises and government customers need as. 838 00:41:03,120 --> 00:41:04,240 Speaker 1: Many options as possible. 839 00:41:04,320 --> 00:41:06,520 Speaker 13: And so our view again as I mentioned we're Switzerland, 840 00:41:06,680 --> 00:41:08,200 Speaker 13: we want to enable our customers to be able to 841 00:41:08,239 --> 00:41:10,359 Speaker 13: use open source models as well as the best closed 842 00:41:10,360 --> 00:41:14,279 Speaker 13: source models from nthropic, opening iico here, et cetera, to 843 00:41:14,320 --> 00:41:17,239 Speaker 13: be able to achieve their ambitions. So I think it's 844 00:41:17,280 --> 00:41:20,080 Speaker 13: really a question of choice, you know, I think the 845 00:41:20,160 --> 00:41:22,239 Speaker 13: more options that there are in the ecosyst the better, 846 00:41:22,800 --> 00:41:25,200 Speaker 13: and argles to enable as many of them as possible. 847 00:41:25,480 --> 00:41:27,720 Speaker 4: Alex Wang, go to spend some time with your founder 848 00:41:27,760 --> 00:41:38,000 Speaker 4: and CEO the scale AI. We've got to go back 849 00:41:38,040 --> 00:41:40,040 Speaker 4: to our one on only andenel adlone mountain view at 850 00:41:40,040 --> 00:41:43,160 Speaker 4: Google Io, which is about officially kick off, and I 851 00:41:43,160 --> 00:41:47,680 Speaker 4: imagine a high host of conversation around barred and ultificial intelligence. 852 00:41:49,600 --> 00:41:52,120 Speaker 10: Yeah, look, this is the developers conference, but it's all 853 00:41:52,160 --> 00:41:54,600 Speaker 10: about AI, and really what we want to know is 854 00:41:54,600 --> 00:41:58,239 Speaker 10: about a more conversational version of Google Search. So much 855 00:41:58,280 --> 00:42:00,560 Speaker 10: emphasis on bard when it was released in February, but 856 00:42:00,560 --> 00:42:03,239 Speaker 10: it was always meant to be a creative companion. So 857 00:42:03,360 --> 00:42:05,880 Speaker 10: how have they taken their work on the large language 858 00:42:05,880 --> 00:42:08,960 Speaker 10: models and moving the needle forward in terms of that 859 00:42:09,040 --> 00:42:12,320 Speaker 10: core search product. That's the big question for the thousands 860 00:42:12,320 --> 00:42:15,000 Speaker 10: of developers that are here but also worldwide virtually. 861 00:42:15,480 --> 00:42:18,359 Speaker 4: What about the developers that want to be building on 862 00:42:18,480 --> 00:42:20,880 Speaker 4: pieces of a hardware kit, the Google mans. Where are 863 00:42:20,920 --> 00:42:22,320 Speaker 4: we seeing the iteration of the pixel? 864 00:42:24,400 --> 00:42:27,759 Speaker 10: Yeah, so we expect them to unveil pixel fold, a 865 00:42:27,840 --> 00:42:30,759 Speaker 10: large form factor folding smartphone and you ask, well, how 866 00:42:30,760 --> 00:42:33,040 Speaker 10: does that relate to AI? But if you speak to 867 00:42:33,120 --> 00:42:35,640 Speaker 10: developers or analysts, they say, well, look how big it is? 868 00:42:35,840 --> 00:42:38,799 Speaker 10: Think about the processing power. What are the future on 869 00:42:38,800 --> 00:42:41,560 Speaker 10: the inference side of AI use cases that you can 870 00:42:41,600 --> 00:42:44,000 Speaker 10: do with a phone like that. Google has one percent 871 00:42:44,040 --> 00:42:47,680 Speaker 10: of the smartphone market. Flip phones or folding phones are 872 00:42:47,760 --> 00:42:51,080 Speaker 10: one percent of that market in itself. It's tiny, So 873 00:42:51,120 --> 00:42:52,719 Speaker 10: how are they going to move the needle forward here? 874 00:42:52,800 --> 00:42:56,120 Speaker 10: Grow their business and deeply integrate AI throughout all of 875 00:42:56,160 --> 00:42:57,560 Speaker 10: their software and hardware offerings. 876 00:42:57,600 --> 00:43:00,959 Speaker 4: Karrot ed great to have what's happening on the ground. 877 00:43:01,080 --> 00:43:03,040 Speaker 4: Go run off to that next speech that you'll be 878 00:43:03,080 --> 00:43:04,160 Speaker 4: listening to Ed Ludlow. 879 00:43:04,280 --> 00:43:05,040 Speaker 5: We thank him. 880 00:43:05,160 --> 00:43:07,120 Speaker 4: He's going to have so much more for you throughout 881 00:43:07,200 --> 00:43:09,640 Speaker 4: the day on Bloomberg TV from Google Io. But that 882 00:43:09,640 --> 00:43:12,120 Speaker 4: does it for this addition on Bloomberg Technology, Stay with 883 00:43:12,239 --> 00:43:14,440 Speaker 4: us for an exclusive conversation from. 884 00:43:14,320 --> 00:43:17,239 Speaker 5: Google Io, the head of Google Devices and Services. They 885 00:43:17,320 --> 00:43:19,040 Speaker 5: want to miss it. This is a Bloomberg