1 00:00:01,520 --> 00:00:05,160 Speaker 1: From Mahart where Innovation of Money and Power Collie in 2 00:00:05,280 --> 00:00:06,800 Speaker 1: Silicon Valley, NBN. 3 00:00:07,120 --> 00:00:11,160 Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow. 4 00:00:25,360 --> 00:00:27,560 Speaker 1: I'm Caroline Heidel, Bloomberg's world headquarters in New York and 5 00:00:27,640 --> 00:00:30,760 Speaker 1: Ludlow He's off This is Bloomberg Technology coming up. Aren't 6 00:00:30,760 --> 00:00:33,440 Speaker 1: prepares to file for its IPO as soon as today 7 00:00:33,760 --> 00:00:35,440 Speaker 1: and what could be one of the biggest tech listings 8 00:00:35,440 --> 00:00:38,000 Speaker 1: ever on a US exchange. We will bring you the details. 9 00:00:38,280 --> 00:00:40,760 Speaker 1: Plus we'll sit down with venture capitalist and entrepreneur keithra 10 00:00:40,840 --> 00:00:44,000 Speaker 1: Boy to discuss how his company opens stores, helping small 11 00:00:44,000 --> 00:00:47,720 Speaker 1: businesses grow amid a pretty competitive e commerce landscape, and 12 00:00:47,760 --> 00:00:51,360 Speaker 1: Meta plans to launch a web version of its microbloggerging 13 00:00:51,560 --> 00:00:55,240 Speaker 1: app Threads early this week. We understand the newest challenge 14 00:00:55,320 --> 00:00:57,360 Speaker 1: is going to be taking on competitor x. I have 15 00:00:57,680 --> 00:00:59,720 Speaker 1: all of that and so much more throughout the appt 16 00:00:59,720 --> 00:01:02,400 Speaker 1: first with Sticking on Chips is sticking this time on 17 00:01:02,440 --> 00:01:05,280 Speaker 1: the designer of Chips expected to Cools to file paperwork 18 00:01:05,560 --> 00:01:07,920 Speaker 1: as seems today for its initial public offering, which is 19 00:01:07,959 --> 00:01:10,280 Speaker 1: expected to be the biggest of the year, most certainly 20 00:01:10,680 --> 00:01:13,120 Speaker 1: with US for the latest muggs Leanna Baker, who I 21 00:01:13,160 --> 00:01:15,800 Speaker 1: think perhaps doesn't have as RESTful weekends as she is 22 00:01:15,880 --> 00:01:19,600 Speaker 1: used to recently. So when we're looking towards these numbers, 23 00:01:19,600 --> 00:01:22,160 Speaker 1: how much clarity will we get on the actual amount 24 00:01:22,160 --> 00:01:24,280 Speaker 1: of the soft Bank is going to be selling here 25 00:01:24,520 --> 00:01:25,560 Speaker 1: and what valuation? 26 00:01:26,080 --> 00:01:28,320 Speaker 3: Those are all great questions. We're not actually going to 27 00:01:28,360 --> 00:01:31,120 Speaker 3: get those answers in the filing today. There's going to 28 00:01:31,160 --> 00:01:34,400 Speaker 3: be a lot of blank spots. For example, how much 29 00:01:34,400 --> 00:01:36,840 Speaker 3: are they trying to raise. We've reported it could be 30 00:01:36,880 --> 00:01:40,000 Speaker 3: somewhere around eight to ten billion, but we've also having 31 00:01:40,040 --> 00:01:42,680 Speaker 3: a story today that it could now be lower than 32 00:01:42,720 --> 00:01:45,440 Speaker 3: that because soft Bank is not selling as much as 33 00:01:45,480 --> 00:01:49,040 Speaker 3: they had originally liked. There was an insider transaction we've 34 00:01:49,040 --> 00:01:51,520 Speaker 3: reported on where the Vision Fund, which owns twenty five 35 00:01:51,560 --> 00:01:54,480 Speaker 3: percent of ARM, sold their stake back to SoftBank. 36 00:01:54,520 --> 00:01:56,920 Speaker 4: So the Vision Fund is no longer a seller in 37 00:01:56,960 --> 00:01:58,320 Speaker 4: this deal. So it's a little. 38 00:01:58,120 --> 00:02:00,480 Speaker 3: Complicated, but it does seem like they don't need as 39 00:02:00,560 --> 00:02:03,440 Speaker 3: much proceeds as before, so that's something we'll be trying 40 00:02:03,440 --> 00:02:06,160 Speaker 3: to figure out when the filing finally hits today. 41 00:02:06,240 --> 00:02:08,160 Speaker 1: What was interesting is a Vision Fund sort a bit 42 00:02:08,160 --> 00:02:10,560 Speaker 1: of an uplift Suddenly to the evaluation, what was it about? 43 00:02:10,600 --> 00:02:13,680 Speaker 3: Sixty four sixty four billion, which is an interesting number 44 00:02:13,800 --> 00:02:16,720 Speaker 3: because they bought that stake for around thirty two billions, 45 00:02:16,760 --> 00:02:19,440 Speaker 3: So the Vision Fund has doubled their money. So that's 46 00:02:19,480 --> 00:02:23,200 Speaker 3: great for their LP, Saudi Arabia, et cetera, whoever is 47 00:02:23,240 --> 00:02:25,560 Speaker 3: involved in the Vision Fund. But what does that mean 48 00:02:25,600 --> 00:02:28,200 Speaker 3: for arms valuation? Because to me it would seem to 49 00:02:28,240 --> 00:02:31,000 Speaker 3: be that they now need to get above sixty four 50 00:02:31,000 --> 00:02:34,800 Speaker 3: billion as a value, although that's just an insider mark 51 00:02:34,919 --> 00:02:35,240 Speaker 3: on it. 52 00:02:35,360 --> 00:02:37,400 Speaker 4: So there's really going to be a lot of questions. 53 00:02:37,520 --> 00:02:40,400 Speaker 3: How do you value this company? How's it valued against 54 00:02:40,440 --> 00:02:43,880 Speaker 3: its peers. We've already reported on some of the financials 55 00:02:44,360 --> 00:02:47,640 Speaker 3: the revenue Tiltal revenue is down one percent last year, 56 00:02:48,080 --> 00:02:50,480 Speaker 3: but there's going to be more to uncover and unpack. 57 00:02:50,520 --> 00:02:51,120 Speaker 4: In the filing. 58 00:02:51,200 --> 00:02:53,440 Speaker 3: We'll see more on margins and other things we haven't 59 00:02:53,440 --> 00:02:54,000 Speaker 3: reported yet. 60 00:02:54,040 --> 00:02:55,480 Speaker 1: And let's get to the nitty gritty O of the 61 00:02:55,480 --> 00:02:58,480 Speaker 1: business model, because this is a company that helps basically 62 00:02:59,440 --> 00:03:01,840 Speaker 1: define a blueprint for a chip then be able to 63 00:03:01,880 --> 00:03:04,520 Speaker 1: really understand how it's the most productive it can be. 64 00:03:04,880 --> 00:03:07,799 Speaker 1: It is so wedded to the mobile phone industry, and 65 00:03:07,840 --> 00:03:10,120 Speaker 1: of course that's one that's been slowing. So how is 66 00:03:10,160 --> 00:03:12,320 Speaker 1: this company trying to set itself up for success? 67 00:03:12,400 --> 00:03:14,680 Speaker 4: So it's right that mobile and ARM. 68 00:03:14,760 --> 00:03:17,880 Speaker 3: It's ubiquitous in mobile, but Rene has the CEO, has 69 00:03:17,880 --> 00:03:20,079 Speaker 3: been trying to diversify ARM away from mobile and some 70 00:03:20,200 --> 00:03:23,880 Speaker 3: more lucrative areas like the data center PC's servers. 71 00:03:24,240 --> 00:03:24,799 Speaker 4: So we'll be. 72 00:03:24,840 --> 00:03:28,320 Speaker 3: Trying to see how that's going, what the progress is. Remember, 73 00:03:28,360 --> 00:03:31,000 Speaker 3: an IPO filing is also backward looking, so it won't 74 00:03:31,000 --> 00:03:31,919 Speaker 3: have forecasts. 75 00:03:31,960 --> 00:03:32,880 Speaker 4: So there's going. 76 00:03:32,880 --> 00:03:35,320 Speaker 3: To be a lot that we see in this filing, 77 00:03:35,320 --> 00:03:37,840 Speaker 3: but we won't know, you know how what the future 78 00:03:37,840 --> 00:03:41,240 Speaker 3: holds for ARM. But we'll be trying to figure that out. 79 00:03:41,280 --> 00:03:43,120 Speaker 1: And can you try and get into the head a 80 00:03:43,160 --> 00:03:47,080 Speaker 1: little bit of Masayoshi's son here as to what SoftBank 81 00:03:47,240 --> 00:03:49,360 Speaker 1: would hold back a little bit for. Is it because 82 00:03:49,400 --> 00:03:52,160 Speaker 1: they think they could get better valuations they sold stakes later. 83 00:03:52,280 --> 00:03:54,160 Speaker 1: They therefore want to hold back in terms of putting 84 00:03:54,160 --> 00:03:57,600 Speaker 1: it all into the market, which is still a testing market. 85 00:03:57,800 --> 00:03:59,240 Speaker 1: To be polite, at the moment. 86 00:03:59,160 --> 00:04:01,560 Speaker 3: We've reported that soft Bank would look to float about 87 00:04:01,560 --> 00:04:03,680 Speaker 3: ten percent of the company, So by holding on to 88 00:04:03,840 --> 00:04:06,800 Speaker 3: ninety percent of ARM, that would indicate they're still bullish 89 00:04:06,880 --> 00:04:09,440 Speaker 3: on the future. They're not ready to part ways. They 90 00:04:09,480 --> 00:04:12,480 Speaker 3: have owned it since twenty sixteen. They do need a 91 00:04:12,520 --> 00:04:14,720 Speaker 3: win after a lot of their failed bets on STARTUS, 92 00:04:14,720 --> 00:04:16,600 Speaker 3: but they're not willing to just you know, get rid 93 00:04:16,600 --> 00:04:19,320 Speaker 3: of this. Although they did try to sell to Nvidia, 94 00:04:19,720 --> 00:04:22,240 Speaker 3: that deal was scuppered last. 95 00:04:22,080 --> 00:04:24,839 Speaker 1: Year the regulators a headache for many. We thank you 96 00:04:24,880 --> 00:04:26,840 Speaker 1: so much, Anabaka. I mean, of course going to be 97 00:04:26,920 --> 00:04:28,800 Speaker 1: all over this throughout the week when it comes to 98 00:04:28,920 --> 00:04:31,360 Speaker 1: arms IPO, but let's get you an update of really 99 00:04:31,360 --> 00:04:33,200 Speaker 1: what this says about the border IPO market in the 100 00:04:33,200 --> 00:04:35,360 Speaker 1: world of tech piller hazards with us some place of 101 00:04:35,360 --> 00:04:37,320 Speaker 1: say co found of equities, then it's a marketplace for 102 00:04:37,360 --> 00:04:40,479 Speaker 1: accessing pre IPO equity. Now, Phil, I don't think I 103 00:04:40,480 --> 00:04:43,440 Speaker 1: can access our equity here because I'm sure there haven't 104 00:04:43,440 --> 00:04:45,760 Speaker 1: been that many secretary market sales going on at the moment, 105 00:04:45,760 --> 00:04:48,400 Speaker 1: apart from seft Bank buying back from the Vision Fund. 106 00:04:48,400 --> 00:04:52,200 Speaker 1: But ultimately, what has desire been like to be buying 107 00:04:52,240 --> 00:04:55,120 Speaker 1: company equity at this moment in the private market. 108 00:04:56,360 --> 00:04:57,400 Speaker 5: Yeah, it's a great question. 109 00:04:57,520 --> 00:05:00,560 Speaker 6: You know, we've seen historically that trans actions on the 110 00:05:00,600 --> 00:05:03,760 Speaker 6: secondary market very much coincide what we see in the 111 00:05:03,760 --> 00:05:06,479 Speaker 6: IPO market, and so what that means is that over 112 00:05:06,480 --> 00:05:07,880 Speaker 6: the last year and a half things have been a 113 00:05:07,880 --> 00:05:11,400 Speaker 6: little bit slower. However, we have similar optimism kind of 114 00:05:11,440 --> 00:05:13,719 Speaker 6: posts this RM IPO that a number of other. 115 00:05:13,600 --> 00:05:14,920 Speaker 5: Companies will test the market. 116 00:05:15,320 --> 00:05:17,680 Speaker 6: But it's worth kind of saying that ARM is not 117 00:05:17,800 --> 00:05:20,560 Speaker 6: your classic venture backed company, going back to the or 118 00:05:20,600 --> 00:05:22,520 Speaker 6: company of the market. ARM is a company that was 119 00:05:22,520 --> 00:05:25,320 Speaker 6: public up until twenty sixteen, so investors are very familiar. 120 00:05:25,360 --> 00:05:27,720 Speaker 6: It's a very different kind of beast than you might 121 00:05:27,760 --> 00:05:29,400 Speaker 6: have a venture backed company coming out. 122 00:05:29,640 --> 00:05:31,920 Speaker 1: Yeah, well said one that I'm sure many are at 123 00:05:31,960 --> 00:05:34,760 Speaker 1: and prior analyst in the UK is rubbing their hands 124 00:05:34,800 --> 00:05:37,039 Speaker 1: and the beginning to get back into the financials of 125 00:05:37,040 --> 00:05:40,400 Speaker 1: this business. Phil, I'm interested for what we're hoping for 126 00:05:40,440 --> 00:05:44,240 Speaker 1: if this IPO goes well, go successfully. Who's there standing by? 127 00:05:44,320 --> 00:05:46,760 Speaker 1: We know Instacrat for example, eyeing the market as soon 128 00:05:46,800 --> 00:05:47,919 Speaker 1: as September for example. 129 00:05:49,080 --> 00:05:51,800 Speaker 6: Yeah, Unfortunately, I can't give specific names given that we 130 00:05:51,839 --> 00:05:53,560 Speaker 6: work with a lot of the companies that are hopefully 131 00:05:53,600 --> 00:05:55,200 Speaker 6: going to be coming public soon. 132 00:05:55,279 --> 00:05:58,080 Speaker 5: But I'd say that what investors will be looking at 133 00:05:58,160 --> 00:05:58,919 Speaker 5: is how successful. 134 00:05:58,960 --> 00:06:01,279 Speaker 6: Is this IPO and say September, does that mean we 135 00:06:01,320 --> 00:06:03,599 Speaker 6: have enough time to get our affairs in order and 136 00:06:03,640 --> 00:06:06,360 Speaker 6: maybe lifts before the end of the year. Historically these 137 00:06:06,400 --> 00:06:09,159 Speaker 6: two weeks leading up to Labor Day have been incredibly quiet. 138 00:06:09,200 --> 00:06:11,760 Speaker 6: I'm sure there's a lot of very frustrated investment bankers 139 00:06:11,760 --> 00:06:13,960 Speaker 6: all across the world galvanting and finding their way back 140 00:06:14,000 --> 00:06:15,120 Speaker 6: to New York or London. 141 00:06:14,920 --> 00:06:17,720 Speaker 5: Wherever to work on this. So I would imagine if 142 00:06:17,760 --> 00:06:19,000 Speaker 5: we do actually see. 143 00:06:18,800 --> 00:06:21,919 Speaker 6: A couple venture back tech IPOs, we'll see rumors of 144 00:06:21,960 --> 00:06:25,520 Speaker 6: filing and paperwork between now and Labor Day, because that's 145 00:06:25,560 --> 00:06:27,600 Speaker 6: the only way these companies are going to have are 146 00:06:27,640 --> 00:06:29,760 Speaker 6: going to be ready enough to actually list and start 147 00:06:29,760 --> 00:06:33,360 Speaker 6: trading by say October November, before you get to the 148 00:06:33,440 --> 00:06:35,880 Speaker 6: next quiet season, which is in December, and. 149 00:06:36,240 --> 00:06:38,880 Speaker 1: It's leading the tea leaves. There have been a couple 150 00:06:38,880 --> 00:06:42,560 Speaker 1: of relatively successful initial public offerings. Just remind us of 151 00:06:42,720 --> 00:06:46,200 Speaker 1: who's come and tapped and what the signal is there 152 00:06:46,240 --> 00:06:47,320 Speaker 1: for for the rest of the market. 153 00:06:48,320 --> 00:06:50,400 Speaker 6: Sure, I mean, in the last two years, it's been 154 00:06:50,560 --> 00:06:53,279 Speaker 6: incredibly quiet of a tech front, apart from probably just 155 00:06:53,320 --> 00:06:55,800 Speaker 6: some spinouts. You know, we saw Kenview come out from 156 00:06:56,680 --> 00:07:00,480 Speaker 6: Johnson Johnson, So we've seen some spinouts. Work is going 157 00:07:00,480 --> 00:07:03,040 Speaker 6: to be closer to tech, right, you know. I think 158 00:07:03,040 --> 00:07:05,160 Speaker 6: a fun fact is that Arn't was actually started by 159 00:07:05,160 --> 00:07:07,520 Speaker 6: a three million dollar investment from Apple, so it has 160 00:07:07,560 --> 00:07:12,040 Speaker 6: silicon value roots. And so I think it also serves 161 00:07:12,040 --> 00:07:14,080 Speaker 6: as a bit of a bell weather for how much 162 00:07:14,120 --> 00:07:16,800 Speaker 6: do people really think AI is worth and how valuable 163 00:07:16,880 --> 00:07:19,120 Speaker 6: is it to the people selling the picks and shovels 164 00:07:19,280 --> 00:07:22,360 Speaker 6: and videos certainly indicated that it's worth a lot, but 165 00:07:22,520 --> 00:07:24,480 Speaker 6: arm will be yet another bell weather and kind of 166 00:07:24,480 --> 00:07:26,720 Speaker 6: indicate if there are other companies that are building on 167 00:07:26,760 --> 00:07:30,040 Speaker 6: top of this new AI foundation, they can perform well 168 00:07:30,120 --> 00:07:32,559 Speaker 6: in this market as well, because we honestly haven't seen 169 00:07:33,000 --> 00:07:37,000 Speaker 6: a large tech IPO in the last say two plus years, 170 00:07:37,040 --> 00:07:39,320 Speaker 6: and you know, we had kind of this BAC pocalypse 171 00:07:39,360 --> 00:07:41,720 Speaker 6: that happened in twenty twenty one two twenty two, and 172 00:07:41,760 --> 00:07:44,560 Speaker 6: so that's not really available anymore. Growth fundings are down, 173 00:07:44,800 --> 00:07:46,360 Speaker 6: so I know that there's a lot of investors and 174 00:07:46,400 --> 00:07:48,800 Speaker 6: a lot of founders and CEOs that are eager to 175 00:07:48,840 --> 00:07:51,120 Speaker 6: see if this is a new channel for fundraising. 176 00:07:51,480 --> 00:07:54,120 Speaker 1: How frustrating has it been for those that need a 177 00:07:54,240 --> 00:07:57,640 Speaker 1: liquidity event right now who are working at some of 178 00:07:57,680 --> 00:08:01,040 Speaker 1: these startups and you know, need to manage their life, 179 00:08:01,120 --> 00:08:03,000 Speaker 1: need to buy a home, need to put kids through school. 180 00:08:04,040 --> 00:08:06,240 Speaker 6: Yeah, sometimes it's even worse and they're no longer working 181 00:08:06,240 --> 00:08:08,160 Speaker 6: at the company because they've been asked politely to no 182 00:08:08,240 --> 00:08:11,240 Speaker 6: longer come to the company, and that's even more frustrating. 183 00:08:11,280 --> 00:08:12,360 Speaker 5: You've got this combination of. 184 00:08:12,320 --> 00:08:14,720 Speaker 6: Layoffs and at equities, and we hear a lot about 185 00:08:15,440 --> 00:08:19,160 Speaker 6: employees current and former, desperately looking for liquidity. And I 186 00:08:19,160 --> 00:08:22,040 Speaker 6: think the most proactive founders that we've talked to equities 187 00:08:22,040 --> 00:08:24,320 Speaker 6: and are ones that are talking to their companies and 188 00:08:24,320 --> 00:08:28,200 Speaker 6: their shareholders about ways to address liquidity through maybe tender 189 00:08:28,240 --> 00:08:30,840 Speaker 6: offers or future IPOs. But it's something we hear about 190 00:08:30,840 --> 00:08:33,880 Speaker 6: a lot. There's still a disconnect on what management thinks 191 00:08:34,160 --> 00:08:36,720 Speaker 6: is not really an issue, and how employees are asking 192 00:08:36,800 --> 00:08:39,120 Speaker 6: all the time for places like equities and can we 193 00:08:39,160 --> 00:08:39,679 Speaker 6: sell shares? 194 00:08:39,720 --> 00:08:40,840 Speaker 5: I have downt painents on a house. 195 00:08:40,920 --> 00:08:43,240 Speaker 6: Interest rates have gotten higher, and so I think there's 196 00:08:43,240 --> 00:08:46,760 Speaker 6: a bit of a kind of a boiling sensation happening 197 00:08:46,760 --> 00:08:51,319 Speaker 6: amongst co founders or sorry amoungst employees and optimistic that 198 00:08:51,360 --> 00:08:53,200 Speaker 6: we'll see a bit of that release valve in the 199 00:08:53,200 --> 00:08:55,880 Speaker 6: IPO market, which will find its way down into the 200 00:08:55,920 --> 00:08:57,000 Speaker 6: pre IPO markets as well. 201 00:08:57,240 --> 00:09:00,520 Speaker 1: I mean, you're all about access to add ups to 202 00:09:00,559 --> 00:09:04,360 Speaker 1: private companies with accredited investors. What about sort of the 203 00:09:04,400 --> 00:09:06,840 Speaker 1: global nature of that investor. Now we are in a 204 00:09:06,880 --> 00:09:10,839 Speaker 1: time of geopolitical tension, to put it mildly, between the 205 00:09:10,960 --> 00:09:13,000 Speaker 1: US and China. How much do you think when these 206 00:09:13,040 --> 00:09:15,400 Speaker 1: companies are coming to market, we will see a global 207 00:09:15,520 --> 00:09:19,720 Speaker 1: abound interest in buying US companies or indeed UK companies 208 00:09:19,800 --> 00:09:20,240 Speaker 1: such as. 209 00:09:20,120 --> 00:09:23,840 Speaker 6: O't absolutely, We've actually seen it already. So we've worked 210 00:09:23,880 --> 00:09:28,480 Speaker 6: with individual investors and investment on the equities and platform from. 211 00:09:28,400 --> 00:09:29,439 Speaker 5: Ninety plus countries. 212 00:09:29,600 --> 00:09:32,680 Speaker 6: Obviously there's a large concentration amongst the US and the UK, 213 00:09:34,080 --> 00:09:36,319 Speaker 6: but we're eager to see that more and more US 214 00:09:36,400 --> 00:09:40,079 Speaker 6: companies are breaking through and working on really hard technology problems. 215 00:09:40,160 --> 00:09:42,520 Speaker 6: I think what's really exciting what we've seen in the 216 00:09:42,600 --> 00:09:44,840 Speaker 6: last eighteen twenty four months is kind of the emergence 217 00:09:44,880 --> 00:09:49,400 Speaker 6: of hard tech, deep tech, really difficult problems that companies 218 00:09:49,400 --> 00:09:52,000 Speaker 6: are trying to solve, and that's really peaked the curiosity 219 00:09:52,000 --> 00:09:54,160 Speaker 6: of people around the world that we've seen so We 220 00:09:54,200 --> 00:09:57,040 Speaker 6: continue to see investor interests for US based companies in 221 00:09:57,320 --> 00:10:00,320 Speaker 6: cybersecurity and AI in particular, those are probably the most 222 00:10:00,360 --> 00:10:04,240 Speaker 6: common themes, which is unsurprising given the aforementioned geopolitical risks. 223 00:10:04,320 --> 00:10:06,600 Speaker 5: So we're excited to see that that trend can continue. 224 00:10:06,600 --> 00:10:08,480 Speaker 6: But ultimately, yes, our goal is to kind of bring 225 00:10:08,480 --> 00:10:11,960 Speaker 6: this market opportunity to not just the wealthier the one percent, 226 00:10:12,040 --> 00:10:13,720 Speaker 6: but everyone else that wants. 227 00:10:13,600 --> 00:10:14,120 Speaker 5: To be included. 228 00:10:14,520 --> 00:10:16,800 Speaker 1: Well, thanks so much for giving us your expertise today. 229 00:10:16,840 --> 00:10:20,240 Speaker 1: Phil has that it's course co founder of equity Zen. Meanwhile, 230 00:10:20,440 --> 00:10:22,360 Speaker 1: when we want to talk about something else that's affecting 231 00:10:22,640 --> 00:10:25,320 Speaker 1: potentially and a load of tech entrepreneurs and builders at 232 00:10:25,360 --> 00:10:28,400 Speaker 1: the moment. But following Tropical Storm Hillary, it's a weather event. 233 00:10:28,559 --> 00:10:32,480 Speaker 1: It's pummeling California, flooding rains today, disrupting flights, knocking out 234 00:10:32,520 --> 00:10:35,120 Speaker 1: power in fact across parts of the state, now across 235 00:10:35,120 --> 00:10:38,720 Speaker 1: the southwest region. The ongoing and historic amount of rainfall. 236 00:10:38,800 --> 00:10:42,400 Speaker 1: We understand it's expected to cause life threatening to catastrophic 237 00:10:42,440 --> 00:10:45,599 Speaker 1: floods along with landslides mudslides so well, according to the 238 00:10:45,679 --> 00:10:48,880 Speaker 1: National Hurricane Center. We'll continue to monitor storm for you 239 00:10:49,080 --> 00:11:01,319 Speaker 1: and bring you updates from New York. This is Brittemberg Technology. 240 00:11:03,679 --> 00:11:06,120 Speaker 1: Let's talk China for a moment. Search engine provide a 241 00:11:06,160 --> 00:11:08,560 Speaker 1: by Do. It's set to report second quarter earnings tomorrow. 242 00:11:08,559 --> 00:11:11,280 Speaker 1: The sluggish Chinese economy and for some setbacks from a 243 00:11:11,400 --> 00:11:14,480 Speaker 1: key segment of its business. It calls brokeers to lower 244 00:11:14,480 --> 00:11:17,160 Speaker 1: their earnings expectations to this particular company. For more, that's 245 00:11:17,200 --> 00:11:19,800 Speaker 1: bringing blue eggs Isabelle, who's going to be analyzing and 246 00:11:19,880 --> 00:11:22,080 Speaker 1: keeping a breasts of what's gonna happen with Bardo And 247 00:11:22,360 --> 00:11:24,280 Speaker 1: I mean it's had a big run out. What do 248 00:11:24,280 --> 00:11:26,560 Speaker 1: we expect in terms of numbers? So a couple of things. 249 00:11:26,559 --> 00:11:29,560 Speaker 7: You're right, brokers have really lower to expectations. In fact, 250 00:11:29,559 --> 00:11:32,440 Speaker 7: they expect a slowdown and that income growth. And this 251 00:11:32,520 --> 00:11:35,240 Speaker 7: is a combination of many things. So in the beginning, 252 00:11:35,520 --> 00:11:38,600 Speaker 7: Baydo was one of the first movers into the AI space, 253 00:11:38,640 --> 00:11:41,559 Speaker 7: and first mover is important. It created a chat GPT 254 00:11:41,840 --> 00:11:45,400 Speaker 7: like technology called erning Bot. But then disappointments are now 255 00:11:45,559 --> 00:11:48,560 Speaker 7: slowly piling up on earning Bot. Main key reason is 256 00:11:48,640 --> 00:11:51,679 Speaker 7: the lack of consumer consumption. I guess it's just getting 257 00:11:51,760 --> 00:11:54,000 Speaker 7: it hard. It's finding it hard for people to use 258 00:11:54,120 --> 00:11:57,160 Speaker 7: the machine and Because of that, analysts are saying, hmm, 259 00:11:57,200 --> 00:11:59,640 Speaker 7: maybe this isn't as promising as we imagine, and there's 260 00:11:59,720 --> 00:12:03,040 Speaker 7: slow really just lowering their expectations, and that's really what's 261 00:12:03,080 --> 00:12:05,520 Speaker 7: weighing the stock lower. And if you look at it, 262 00:12:05,600 --> 00:12:08,600 Speaker 7: options traders are also moving because they put call ratio, 263 00:12:09,000 --> 00:12:12,920 Speaker 7: which is a sign of bearish sentiment, is rising this month, 264 00:12:13,000 --> 00:12:16,120 Speaker 7: so people are kind of positioning against that tomorrow. So 265 00:12:16,800 --> 00:12:20,280 Speaker 7: we'll see, but who knows, maybe earnings will surprise those exactly. 266 00:12:20,320 --> 00:12:24,319 Speaker 1: I mean there have been nervous ahead of perhaps these 267 00:12:24,400 --> 00:12:26,880 Speaker 1: numbers because actually there's been a normal profit to take 268 00:12:26,920 --> 00:12:28,440 Speaker 1: off the table when it comes to party. It has 269 00:12:28,440 --> 00:12:30,360 Speaker 1: outperformed some of it. So all the competitors, right, it 270 00:12:30,360 --> 00:12:30,960 Speaker 1: definitely has. 271 00:12:31,000 --> 00:12:34,120 Speaker 7: It's up around thirty thirteen percent year todate and it's 272 00:12:34,120 --> 00:12:36,440 Speaker 7: the best performer to hang saying index which is down 273 00:12:36,520 --> 00:12:39,440 Speaker 7: kind of three percent. But we must remember that Bido 274 00:12:39,440 --> 00:12:43,120 Speaker 7: maybe a little bit ahead, but it's competitors. They're closely behind, 275 00:12:43,160 --> 00:12:46,320 Speaker 7: from Pencent to Alibaba and both of them those giants 276 00:12:46,320 --> 00:12:49,839 Speaker 7: are also now creating their own AI chat GPT like thing. 277 00:12:50,120 --> 00:12:51,880 Speaker 7: I mean, yes, you're the first mover, but you have 278 00:12:51,960 --> 00:12:54,679 Speaker 7: to maintain that because if a competitor is second or 279 00:12:54,760 --> 00:12:59,160 Speaker 7: third leaves over you, then that's going to spell trouble 280 00:12:59,160 --> 00:13:02,120 Speaker 7: for you. Are saying that the outlook remains cloudy at best. 281 00:13:02,120 --> 00:13:03,720 Speaker 7: So it's actually not looking that good. 282 00:13:03,840 --> 00:13:05,480 Speaker 1: I mean, it's such early days when it comes to 283 00:13:05,520 --> 00:13:08,200 Speaker 1: generatorve ai and any of that becoming revenue injuicing. But 284 00:13:08,280 --> 00:13:10,880 Speaker 1: what is revenue inducing for by Doo is well, local 285 00:13:10,960 --> 00:13:17,079 Speaker 1: governments and the actual Chinese economy spending on AUR related products. 286 00:13:17,120 --> 00:13:20,080 Speaker 1: At least, how have we seen that considering the macro economy. 287 00:13:20,160 --> 00:13:22,880 Speaker 7: Okay, that's true, A is just one arm. They also 288 00:13:22,920 --> 00:13:24,840 Speaker 7: have a cloud arm. But then overall it's just not 289 00:13:24,880 --> 00:13:27,439 Speaker 7: looking good for China. We have consumers spending down, prices 290 00:13:27,480 --> 00:13:31,400 Speaker 7: are down, the company's real estate sector is one of 291 00:13:31,440 --> 00:13:33,720 Speaker 7: the biggest companies is on the cusp of a default. 292 00:13:33,880 --> 00:13:36,439 Speaker 7: One in five young people there don't have jobs. It's 293 00:13:36,480 --> 00:13:39,240 Speaker 7: just not really looking that good overall, and the big 294 00:13:39,480 --> 00:13:42,480 Speaker 7: rebound that people were hoping to see just didn't pan out. 295 00:13:42,840 --> 00:13:44,640 Speaker 7: A lot of analysts are saying that the five percent 296 00:13:44,679 --> 00:13:47,960 Speaker 7: target that China is aiming for may not come true. 297 00:13:48,080 --> 00:13:50,240 Speaker 7: But then, you know, you don't also want to be 298 00:13:50,720 --> 00:13:53,320 Speaker 7: all this gloom and doom. Maybe too early, but for 299 00:13:53,360 --> 00:13:55,280 Speaker 7: now it's not looking good to China. In effect, it's 300 00:13:55,280 --> 00:13:58,480 Speaker 7: affecting its biggest sector, which is the tech sector. And 301 00:13:58,520 --> 00:14:01,040 Speaker 7: because this sector is very dom stick and like you're 302 00:14:01,040 --> 00:14:04,160 Speaker 7: in the US, a lot of international people use whatever 303 00:14:04,200 --> 00:14:07,240 Speaker 7: products the Wall Street here a Silicon Valley makes, but 304 00:14:07,640 --> 00:14:09,040 Speaker 7: it's not the same in China. A lot of the 305 00:14:09,040 --> 00:14:11,960 Speaker 7: products there are really used by domestic. 306 00:14:11,920 --> 00:14:14,520 Speaker 1: I think, I mean really to the point that some 307 00:14:14,559 --> 00:14:17,840 Speaker 1: of these GDP figures a city, for example, economists downgrading 308 00:14:17,840 --> 00:14:19,760 Speaker 1: where they think overall China is going to go. Some 309 00:14:19,840 --> 00:14:21,800 Speaker 1: analysts starting to figure that into bider and the rest 310 00:14:21,800 --> 00:14:24,600 Speaker 1: of the tech sector. Brilliant to get Isabelle ahead of those, 311 00:14:24,640 --> 00:14:26,720 Speaker 1: of course, keep an eye on how by do performs 312 00:14:26,760 --> 00:14:29,920 Speaker 1: isabella LEI there. Meanwhile, let's stick with AI and chatbots, 313 00:14:30,000 --> 00:14:33,440 Speaker 1: because well, neither who is line messaging app and search 314 00:14:33,440 --> 00:14:36,880 Speaker 1: engine dominates Japan and South Korea's internet landscape. It's got 315 00:14:37,000 --> 00:14:39,440 Speaker 1: a mail guess what its own answer to chatshetpt as 316 00:14:39,440 --> 00:14:42,360 Speaker 1: it joins a race and is global to tap potentially 317 00:14:42,360 --> 00:14:45,480 Speaker 1: transformative AI technology. Now, the company is expected to take 318 00:14:45,480 --> 00:14:48,480 Speaker 1: the lid off several generative AI services. It's been working 319 00:14:48,480 --> 00:14:59,800 Speaker 1: on latest and soon as this week. We understand time 320 00:14:59,840 --> 00:15:03,040 Speaker 1: now for talking tech first up. After plunging following its 321 00:15:03,080 --> 00:15:06,080 Speaker 1: earning support last week, addi End's most bearish analyst predicts 322 00:15:06,360 --> 00:15:08,640 Speaker 1: even further declines that The City Group analyst said in 323 00:15:08,680 --> 00:15:11,400 Speaker 1: a note he remained skeptical of adiends reaching its long 324 00:15:11,520 --> 00:15:15,720 Speaker 1: term margin target, maintaining his Cell rating on the stock. Meanwhile, 325 00:15:15,800 --> 00:15:19,160 Speaker 1: Broadcom's sixty one billion dollar takeover of VMware was cleared 326 00:15:19,160 --> 00:15:21,320 Speaker 1: by the UK's anti trust watchdog, paving the wave for 327 00:15:21,400 --> 00:15:23,880 Speaker 1: the one of the largest ever tech deals, and the 328 00:15:23,920 --> 00:15:27,040 Speaker 1: CMA confirmed its provisional decision to clear the deal after 329 00:15:27,080 --> 00:15:30,080 Speaker 1: finding that it wouldn't substantially reduce competition in the supply 330 00:15:30,160 --> 00:15:34,080 Speaker 1: of key computer server products. Plus, let's talk about the 331 00:15:34,120 --> 00:15:36,720 Speaker 1: Tesla data breach that was back in May. Impacted more 332 00:15:36,720 --> 00:15:40,520 Speaker 1: than seventy five thousand people and included employee related records. Now, 333 00:15:40,560 --> 00:15:42,960 Speaker 1: according to a notice posted by the Office of the 334 00:15:43,040 --> 00:15:47,080 Speaker 1: main Attorney General, the breach was a result of insider wrongdoing. 335 00:15:47,480 --> 00:15:51,400 Speaker 1: Tesla says two former employees shared information with a foreign 336 00:15:51,480 --> 00:15:54,040 Speaker 1: media outlet. So let's get the details on that story. 337 00:15:54,080 --> 00:15:56,960 Speaker 1: For most Anna Halla's with us and Dena I mean 338 00:15:57,000 --> 00:15:59,280 Speaker 1: it was Hannelds. Black was a German publication that we 339 00:15:59,360 --> 00:16:03,080 Speaker 1: understand got the information contacted Tesla. What do you think 340 00:16:03,080 --> 00:16:05,160 Speaker 1: that was being shared here? Shared here by who? 341 00:16:05,920 --> 00:16:08,760 Speaker 8: Well, it sounds like it was internal employee information, things 342 00:16:08,800 --> 00:16:12,600 Speaker 8: like names, addresses, social Security numbers, and you know. The 343 00:16:12,680 --> 00:16:14,960 Speaker 8: details that we learned on Friday are thanks to the 344 00:16:14,960 --> 00:16:16,720 Speaker 8: fact that the state of Maine is one of the 345 00:16:16,720 --> 00:16:19,160 Speaker 8: few states in the United States that kind of regularly 346 00:16:19,240 --> 00:16:26,320 Speaker 8: posts data breach information. So Tesla is now informing former 347 00:16:26,440 --> 00:16:28,479 Speaker 8: and current employees if they were impacted. 348 00:16:28,720 --> 00:16:30,920 Speaker 5: Apparently nine of them live in the state of Maine. 349 00:16:31,000 --> 00:16:35,040 Speaker 8: So the state of Maine got this notification, and they're 350 00:16:35,040 --> 00:16:37,760 Speaker 8: saying that two former employees basically shared this data with 351 00:16:37,800 --> 00:16:41,840 Speaker 8: handles Plot and that Tesla has taken legal action against them. 352 00:16:42,280 --> 00:16:42,960 Speaker 5: The one thing that. 353 00:16:42,880 --> 00:16:45,840 Speaker 8: I don't know is where exactly these former employees live. 354 00:16:45,960 --> 00:16:48,960 Speaker 8: I'm assuming that it's in Europe. I'm guessing that it 355 00:16:49,000 --> 00:16:51,600 Speaker 8: could be in Germany, given that handles Plot was the 356 00:16:52,240 --> 00:16:54,520 Speaker 8: was a publication that originally got this information. But it 357 00:16:54,560 --> 00:16:57,400 Speaker 8: does not appear that these folks are in the United States. 358 00:16:57,440 --> 00:16:59,560 Speaker 8: I can't find any record of a lawsuit being filed 359 00:16:59,560 --> 00:17:02,320 Speaker 8: here in the U. So in terms of next steps, 360 00:17:02,360 --> 00:17:05,200 Speaker 8: we're just sort of wondering, well, okay, where is this lawsuit, 361 00:17:05,320 --> 00:17:07,439 Speaker 8: who are the employees and is there any kind of 362 00:17:07,480 --> 00:17:11,560 Speaker 8: EU gdpr sinction coming given. 363 00:17:11,280 --> 00:17:12,000 Speaker 9: This data breach? 364 00:17:12,280 --> 00:17:16,399 Speaker 1: Interesting? I mean, Tesla's said that they've cooperated with law enforcement, 365 00:17:16,480 --> 00:17:20,760 Speaker 1: but is there any well ramification of what they should 366 00:17:20,760 --> 00:17:22,760 Speaker 1: have been doing could have been doing, because when it's 367 00:17:22,840 --> 00:17:28,440 Speaker 1: internal wrongdoing, that must be pretty hard to prevent, right, Well, 368 00:17:28,480 --> 00:17:29,280 Speaker 1: it sounds. 369 00:17:29,000 --> 00:17:33,400 Speaker 8: Like, you know, internal wrongdoing and two employees basically sharing 370 00:17:33,680 --> 00:17:37,320 Speaker 8: employee data. So to be clear, no consumers were impacted 371 00:17:37,359 --> 00:17:39,199 Speaker 8: by this that we know of. This really seems to 372 00:17:39,240 --> 00:17:43,360 Speaker 8: be impacting Tesla employees. But why there were more controls 373 00:17:43,760 --> 00:17:46,920 Speaker 8: how these internal employees had access to this database, I'm 374 00:17:46,920 --> 00:17:50,320 Speaker 8: not entirely clear. And you know, the Tesla statement on 375 00:17:50,359 --> 00:17:53,640 Speaker 8: this main website is pretty vague, like cooperating with law enforcement, 376 00:17:53,680 --> 00:17:56,040 Speaker 8: but like which law enforcement? Like are we talking like 377 00:17:56,119 --> 00:18:00,119 Speaker 8: the Dutch regulatory authorities, the EU Germany? Like It's that's 378 00:18:00,160 --> 00:18:02,920 Speaker 8: that entirely clear where within Europe this is all happening. 379 00:18:03,560 --> 00:18:07,119 Speaker 1: And Autopilot, the driver assistance product, that was something that 380 00:18:07,359 --> 00:18:09,479 Speaker 1: seemed to be flagged in some of the data that 381 00:18:09,640 --> 00:18:11,639 Speaker 1: was at least leaked to Handles Black. Why is that 382 00:18:11,680 --> 00:18:13,600 Speaker 1: so important to Tesla? 383 00:18:13,800 --> 00:18:16,480 Speaker 8: Well, autopilot is just a big part of Tesla's valuation, 384 00:18:16,680 --> 00:18:18,919 Speaker 8: you know, Elon Musk himself has said that, you know, 385 00:18:18,960 --> 00:18:22,200 Speaker 8: the promise of future self driving is like a big 386 00:18:22,240 --> 00:18:25,439 Speaker 8: part of why investors believe in the company. And this 387 00:18:25,560 --> 00:18:28,520 Speaker 8: data breach covered all kinds of things. What we learned 388 00:18:28,520 --> 00:18:31,680 Speaker 8: on Friday is really more just about the employee information. 389 00:18:32,400 --> 00:18:35,199 Speaker 8: But yeah, I mean autopilot is a fugiturist to investors 390 00:18:35,359 --> 00:18:39,040 Speaker 8: and it's a big differentiator, right, Like you know, electric 391 00:18:39,119 --> 00:18:42,359 Speaker 8: vehicles are now becoming more common, but Tesla's autopilot is 392 00:18:42,880 --> 00:18:45,840 Speaker 8: something that Tesla still markets as being something that sets 393 00:18:45,840 --> 00:18:46,640 Speaker 8: that apart from. 394 00:18:46,480 --> 00:18:50,480 Speaker 1: Their evs one to watch considering also just how global 395 00:18:50,560 --> 00:18:52,800 Speaker 1: teslra is and I know that that was something Handles 396 00:18:52,840 --> 00:18:55,880 Speaker 1: Abount was shining light on the fact of access perhaps 397 00:18:56,240 --> 00:18:58,800 Speaker 1: by China as well. Anaha, we thank you so much 398 00:18:58,920 --> 00:19:02,879 Speaker 1: coming to us on that data breach, well the nuances 399 00:19:02,880 --> 00:19:13,680 Speaker 1: within it. Welcome back to Blombo Technology. I'm Karen Hide 400 00:19:13,680 --> 00:19:16,440 Speaker 1: in New York. What about payments, premissessing and the world 401 00:19:16,440 --> 00:19:18,960 Speaker 1: of e commerce more generally, what about e commerce in 402 00:19:19,040 --> 00:19:21,120 Speaker 1: terms of our enthusiasm around it and pleased to say 403 00:19:21,119 --> 00:19:23,480 Speaker 1: we could get a really close look at it via 404 00:19:23,520 --> 00:19:26,760 Speaker 1: open Stores, the largest operator of Shopify brands in the world. 405 00:19:27,000 --> 00:19:29,200 Speaker 1: It's announced ways to actually support some of the smaller 406 00:19:29,240 --> 00:19:32,320 Speaker 1: players on the platform using open Store Boost to help 407 00:19:32,359 --> 00:19:35,199 Speaker 1: the businesses grow. Joining us now as of course the 408 00:19:35,240 --> 00:19:37,720 Speaker 1: even still CEO and well Home VC Keith through a 409 00:19:37,720 --> 00:19:39,359 Speaker 1: boy Keith. It is great to have some time with you, 410 00:19:39,440 --> 00:19:41,880 Speaker 1: And what we loved about some of the announcements coming 411 00:19:41,880 --> 00:19:44,879 Speaker 1: out is actually the intricate detail you're giving of just 412 00:19:44,920 --> 00:19:47,520 Speaker 1: who's on there selling via Shopify and how small some 413 00:19:47,560 --> 00:19:50,159 Speaker 1: of them are. Was it a surprise of how small 414 00:19:50,240 --> 00:19:52,120 Speaker 1: some of these online commerce players are. 415 00:19:53,040 --> 00:19:55,400 Speaker 10: Well, we always knew that of the two million Shopify 416 00:19:55,560 --> 00:19:58,359 Speaker 10: stores that many of them would be long stile businesses. 417 00:19:58,560 --> 00:20:00,840 Speaker 10: The whole premise of open s Store is that we 418 00:20:00,920 --> 00:20:04,640 Speaker 10: will offer to buy a long tail Shopify store or 419 00:20:04,840 --> 00:20:07,200 Speaker 10: allow the owner to turn it into pass cash flow 420 00:20:07,240 --> 00:20:09,760 Speaker 10: and take a break. And we're always targeting one to 421 00:20:09,800 --> 00:20:12,560 Speaker 10: ten million dollar GMB stores, so pretty small. 422 00:20:13,040 --> 00:20:14,480 Speaker 9: But in studying the market. 423 00:20:14,240 --> 00:20:15,960 Speaker 10: Over the last few years that we've been in business, 424 00:20:15,960 --> 00:20:18,560 Speaker 10: we realize that eighty five percent of Shopifi stores are 425 00:20:18,720 --> 00:20:20,800 Speaker 10: very small and they don't have the tools and the 426 00:20:20,880 --> 00:20:24,520 Speaker 10: opportunities to grow into that scale. So eighty five percent 427 00:20:24,560 --> 00:20:27,280 Speaker 10: of business on Shopify earn less than fifty thousand dollars 428 00:20:27,320 --> 00:20:29,600 Speaker 10: a year, and so we're going to fix that. Anybody 429 00:20:29,640 --> 00:20:33,240 Speaker 10: who's earning fifty eighty to five hundred K will allow 430 00:20:33,280 --> 00:20:35,439 Speaker 10: them to apply, and we'll give them access to all 431 00:20:35,480 --> 00:20:37,440 Speaker 10: of our tools and expertise and try to grow them 432 00:20:37,480 --> 00:20:39,159 Speaker 10: ten x in a few months. 433 00:20:39,400 --> 00:20:42,239 Speaker 1: Okay, and then they get into the remint of your 434 00:20:42,280 --> 00:20:44,520 Speaker 1: sweet spot. So does your sweet spot change at all? 435 00:20:44,600 --> 00:20:47,160 Speaker 1: Or do you continue to want to be looking at 436 00:20:47,320 --> 00:20:50,040 Speaker 1: buying and running companies that are about a million to 437 00:20:50,440 --> 00:20:52,119 Speaker 1: the likes of ten million in terms of GMV. 438 00:20:52,960 --> 00:20:55,840 Speaker 10: I think the biggest market opportunity for us where people 439 00:20:55,920 --> 00:20:58,520 Speaker 10: don't have access to brand owners, don't have access to capital, 440 00:20:58,840 --> 00:21:00,159 Speaker 10: and where they really don't have a lot lot of 441 00:21:00,200 --> 00:21:04,720 Speaker 10: equity options and they're confronting a really challenging choice, which 442 00:21:04,760 --> 00:21:06,960 Speaker 10: is to run a business twenty four to seven sweat 443 00:21:06,960 --> 00:21:10,200 Speaker 10: twenty four to seven forever, or they can allow us 444 00:21:10,200 --> 00:21:11,000 Speaker 10: to drive the business. 445 00:21:11,000 --> 00:21:12,440 Speaker 9: It will guarantee them the cash. 446 00:21:12,240 --> 00:21:14,760 Speaker 10: Flow, or they can sell the business and walk away 447 00:21:14,800 --> 00:21:17,359 Speaker 10: and do whatever's next and whatever's important in their life. 448 00:21:17,520 --> 00:21:20,560 Speaker 10: This area has never had opportunities before. I think, as 449 00:21:20,560 --> 00:21:23,439 Speaker 10: you grow a business into fifty one hundred million dollars sales, 450 00:21:23,600 --> 00:21:26,399 Speaker 10: there's other options, but most people don't have those options, 451 00:21:26,400 --> 00:21:27,359 Speaker 10: and that's why we exist. 452 00:21:27,840 --> 00:21:31,840 Speaker 1: Of course, you exist to mainly help US based companies, 453 00:21:31,920 --> 00:21:33,600 Speaker 1: right but would you go global? Would you look at 454 00:21:33,600 --> 00:21:37,320 Speaker 1: companies that perhaps are international in them in their perspective 455 00:21:37,359 --> 00:21:39,520 Speaker 1: or at least where they build to be selling vibe 456 00:21:39,680 --> 00:21:40,880 Speaker 1: into the US? 457 00:21:41,320 --> 00:21:46,000 Speaker 10: Absolutely, We already will price to acquire or drive a 458 00:21:46,040 --> 00:21:49,159 Speaker 10: business that targets US customers wherever in the globe the 459 00:21:49,160 --> 00:21:52,280 Speaker 10: business is located. For now, though, our focus is building 460 00:21:52,280 --> 00:21:55,200 Speaker 10: a value proposition for US consumers and at some point 461 00:21:55,240 --> 00:21:55,680 Speaker 10: in the future. 462 00:21:55,720 --> 00:21:59,160 Speaker 1: Works found that US consumers have got quite a lot 463 00:21:59,160 --> 00:22:00,920 Speaker 1: of choice right now, and in fact, they're getting a 464 00:22:00,960 --> 00:22:03,200 Speaker 1: lot of choice from abroad. I'm just thinking of how 465 00:22:03,320 --> 00:22:06,320 Speaker 1: Sheen has really managed to dominate capture attention in the 466 00:22:06,359 --> 00:22:09,400 Speaker 1: lower end price point of garments. You're thinking about TikTok 467 00:22:09,480 --> 00:22:13,520 Speaker 1: that's potentially going to start adding shopping to its remit Like, 468 00:22:13,800 --> 00:22:16,320 Speaker 1: how is the world of e commerce in the US 469 00:22:16,359 --> 00:22:18,320 Speaker 1: from real perspective well. 470 00:22:18,280 --> 00:22:22,520 Speaker 10: Most digitalization of commerce hasn't been very successful. So we're 471 00:22:22,560 --> 00:22:25,800 Speaker 10: thirty years into e commerce and roughly e commerce ac 472 00:22:25,800 --> 00:22:29,000 Speaker 10: counselor at twelve thirteen, maybe fourteen percent of e commerce. 473 00:22:29,040 --> 00:22:31,560 Speaker 10: And there's fundamental reasons why that's true. Why there's a 474 00:22:31,560 --> 00:22:34,399 Speaker 10: big blocker is that nobody has a way of discovering 475 00:22:35,119 --> 00:22:39,480 Speaker 10: inspired purchases. Products that you serendipitously discover when you're in 476 00:22:39,520 --> 00:22:41,639 Speaker 10: the real world, if you're at a shopping mall or if 477 00:22:41,640 --> 00:22:44,600 Speaker 10: you're at a department store back in the day, you 478 00:22:44,680 --> 00:22:47,120 Speaker 10: see things that inspire you. And really the only way 479 00:22:47,119 --> 00:22:51,639 Speaker 10: that works online today is through Instagram ads to shopify stores, 480 00:22:51,760 --> 00:22:54,199 Speaker 10: which is a very inefficient way of discovering products. Most 481 00:22:54,240 --> 00:22:55,640 Speaker 10: of the time when you're on Instagram, you really want 482 00:22:55,640 --> 00:22:57,680 Speaker 10: to see your friend's content. You don't really want to 483 00:22:57,720 --> 00:23:00,359 Speaker 10: be shopping, but you get interrupted by adds to one 484 00:23:00,400 --> 00:23:02,840 Speaker 10: percent of those people click on those ads and buy something, 485 00:23:03,440 --> 00:23:05,879 Speaker 10: and that's, you know, not the best way to substitute 486 00:23:05,960 --> 00:23:07,960 Speaker 10: to go to the design district in Miami or a 487 00:23:07,960 --> 00:23:10,199 Speaker 10: shopping mall in New Jersey when I was growing up. 488 00:23:10,359 --> 00:23:14,120 Speaker 10: But that's what we're building, is aggregation that inspires purchases 489 00:23:14,320 --> 00:23:17,040 Speaker 10: and nobody in the West has ever done that before successfully. 490 00:23:17,720 --> 00:23:21,359 Speaker 1: So how like when you've got you know, door dash engineers, 491 00:23:22,400 --> 00:23:24,360 Speaker 1: some of the early ones really thinking about the way 492 00:23:24,359 --> 00:23:26,280 Speaker 1: in which we engage in shop, like what are the 493 00:23:26,280 --> 00:23:28,640 Speaker 1: innovations that we can't see around the corner of yet. 494 00:23:29,359 --> 00:23:32,399 Speaker 10: Well, we're going to ship some products to the next quarter, 495 00:23:32,520 --> 00:23:34,720 Speaker 10: so it's the starting in September that will show some 496 00:23:34,840 --> 00:23:37,760 Speaker 10: inspired purchases. The first thing we needed to do was 497 00:23:37,800 --> 00:23:40,320 Speaker 10: acquire brands, products, Scus and a customer base. 498 00:23:40,600 --> 00:23:41,160 Speaker 9: You really need. 499 00:23:41,200 --> 00:23:42,880 Speaker 10: You know, you have a kind of a proverbial chicken 500 00:23:42,960 --> 00:23:45,640 Speaker 10: leg problem, So we needed to start with products and SKUs. 501 00:23:45,880 --> 00:23:47,720 Speaker 10: Now that we have a supply of over one hundred 502 00:23:47,720 --> 00:23:51,359 Speaker 10: thousand scues and over two million consumers that bought something from. 503 00:23:51,280 --> 00:23:53,360 Speaker 9: Us, we can stitch them together into. 504 00:23:53,200 --> 00:23:56,119 Speaker 10: Compelling value or proposition that is a standalone app that 505 00:23:56,119 --> 00:23:57,679 Speaker 10: people are going to want on the phone screen on 506 00:23:57,720 --> 00:23:58,520 Speaker 10: their phone. 507 00:23:58,760 --> 00:24:01,160 Speaker 1: What's interesting about your business course, is it where you're 508 00:24:01,160 --> 00:24:05,200 Speaker 1: buying other businesses? Sometimes that right, sometimes just managing what's 509 00:24:05,240 --> 00:24:09,439 Speaker 1: that like? From a valuation perspective? Have those lifestyle CEOs 510 00:24:10,040 --> 00:24:12,720 Speaker 1: are they willing to sell the business when perhaps things 511 00:24:12,760 --> 00:24:15,240 Speaker 1: don't look as pretty from a valuation perspective for them. 512 00:24:15,800 --> 00:24:18,639 Speaker 10: Well, we've study this empirically and a seven percent of 513 00:24:18,720 --> 00:24:21,400 Speaker 10: brand owners on Shalpifi wants to sell their business right 514 00:24:21,400 --> 00:24:24,040 Speaker 10: now and seventy four percent want to sell at some 515 00:24:24,200 --> 00:24:27,360 Speaker 10: time in future. So the acquisition process works really well 516 00:24:27,400 --> 00:24:29,439 Speaker 10: for the seven percent who want to sell, will make 517 00:24:29,480 --> 00:24:31,760 Speaker 10: them an offer it's very attractive. 518 00:24:31,480 --> 00:24:33,240 Speaker 9: And then they can go on invest the money however 519 00:24:33,280 --> 00:24:33,639 Speaker 9: they like. 520 00:24:34,280 --> 00:24:36,159 Speaker 10: For people who are in the seventy four percent, they 521 00:24:36,200 --> 00:24:38,640 Speaker 10: may opportunistically want to sell, but they can just get 522 00:24:38,640 --> 00:24:40,840 Speaker 10: the cash flow and have the passive income with none 523 00:24:40,880 --> 00:24:43,200 Speaker 10: of the stress. So we've kind of created a product 524 00:24:43,200 --> 00:24:46,080 Speaker 10: suite that appeals to a very wide set of brand owners. 525 00:24:46,080 --> 00:24:48,959 Speaker 1: On Shopify, you've got a one hundred and thirty there 526 00:24:48,960 --> 00:24:51,960 Speaker 1: are thereabout some employees. What's the market like for talent 527 00:24:52,200 --> 00:24:53,120 Speaker 1: at the moment, Keith. 528 00:24:53,480 --> 00:24:56,200 Speaker 10: It's a great question. I think the talent's widely available 529 00:24:56,280 --> 00:24:58,520 Speaker 10: right now. I think people are frustrated at large company 530 00:24:58,600 --> 00:25:02,240 Speaker 10: bureaucracy in a real to join new companies and trying 531 00:25:02,240 --> 00:25:04,639 Speaker 10: to transform parts of the world or all the world 532 00:25:04,720 --> 00:25:08,119 Speaker 10: or industries, so that's become easier. I think there's a 533 00:25:08,160 --> 00:25:11,560 Speaker 10: lot of less sort of vanity metrics and fake fundings 534 00:25:11,760 --> 00:25:13,879 Speaker 10: where companies are getting funded that they shouldn't to be 535 00:25:14,720 --> 00:25:17,480 Speaker 10: sort of migrating to create a critical density of talent 536 00:25:17,520 --> 00:25:19,000 Speaker 10: around companies that have high potential. 537 00:25:19,960 --> 00:25:21,920 Speaker 1: You can show off your high potential, of course, because 538 00:25:21,920 --> 00:25:24,240 Speaker 1: of the money that you were able to raise was 539 00:25:24,320 --> 00:25:26,359 Speaker 1: more than one hundred and fifty million, inequity you've valued 540 00:25:26,359 --> 00:25:29,400 Speaker 1: at about a billion dollars. You're a man who also 541 00:25:29,440 --> 00:25:31,639 Speaker 1: sits on the other side of the table and often 542 00:25:31,920 --> 00:25:35,440 Speaker 1: is writing these checks in this environment. How are evaluations 543 00:25:35,560 --> 00:25:37,240 Speaker 1: big tech startups right now? 544 00:25:38,160 --> 00:25:40,680 Speaker 10: We've been very disciplined at Founders Fund. I think we've 545 00:25:40,720 --> 00:25:44,119 Speaker 10: been consistently disciplined, maybe even before the market change, but 546 00:25:44,240 --> 00:25:47,600 Speaker 10: fundamentally there's been a massive transformation in Series A, Series 547 00:25:47,640 --> 00:25:51,440 Speaker 10: B and late stage growth company valuations. And so we're 548 00:25:51,480 --> 00:25:55,119 Speaker 10: investing with very soluctively the right founders who are the 549 00:25:55,560 --> 00:25:59,040 Speaker 10: extraordinary founders within a compelling vision. But we have to 550 00:25:59,080 --> 00:26:02,520 Speaker 10: pay prices valuations that reflect reality. So we went through 551 00:26:02,560 --> 00:26:06,000 Speaker 10: about a two or three year window when valuations were 552 00:26:06,000 --> 00:26:07,720 Speaker 10: really divorced from reality. 553 00:26:07,960 --> 00:26:09,200 Speaker 9: That occasionally happens in. 554 00:26:09,200 --> 00:26:11,600 Speaker 10: Tech about every twenty thirty years, Like this happened in 555 00:26:11,640 --> 00:26:13,320 Speaker 10: ninety ninety six, ninety seven, ninety eight. 556 00:26:13,560 --> 00:26:15,640 Speaker 9: With ninety ninety to two thousand. 557 00:26:15,520 --> 00:26:18,040 Speaker 10: You know that three to four year window was totally 558 00:26:18,040 --> 00:26:19,240 Speaker 10: gone and things were back to normal. 559 00:26:19,440 --> 00:26:22,359 Speaker 9: So if you take arc of forty years, if you pay, if. 560 00:26:22,280 --> 00:26:24,640 Speaker 10: You invest at the right prices, things work out well 561 00:26:24,640 --> 00:26:27,280 Speaker 10: on technology. But there's blips of two to three years 562 00:26:27,280 --> 00:26:29,480 Speaker 10: when you could feel good with just momentum investing. 563 00:26:30,160 --> 00:26:33,600 Speaker 1: Is that just momentum investing around AI at the moment right? 564 00:26:34,040 --> 00:26:37,440 Speaker 9: We think? So? I don't believe in AI companies. 565 00:26:36,960 --> 00:26:39,480 Speaker 10: As a good place for a VCS to be spending 566 00:26:39,520 --> 00:26:41,400 Speaker 10: their time, but I'm glad like competitors want to waste 567 00:26:41,400 --> 00:26:42,080 Speaker 10: their money there. 568 00:26:42,480 --> 00:26:46,640 Speaker 1: Really, like what makes you reticent because you don't think 569 00:26:46,640 --> 00:26:49,359 Speaker 1: that a lot of them are actually integrally AI at 570 00:26:49,400 --> 00:26:50,000 Speaker 1: their core? 571 00:26:50,840 --> 00:26:54,680 Speaker 10: Well, no, I think that there's a classic structural advantage 572 00:26:54,680 --> 00:26:57,960 Speaker 10: in new technologies, and some of these technologies are disruptive 573 00:26:57,960 --> 00:27:00,639 Speaker 10: and they disrupt incumbents in their powers, and some actually 574 00:27:00,720 --> 00:27:04,360 Speaker 10: enabling combents to get stronger. AI is most likely going 575 00:27:04,400 --> 00:27:07,880 Speaker 10: to generate more power for large tech large market cap 576 00:27:07,960 --> 00:27:10,840 Speaker 10: tech companies not really be a substitute. And if there 577 00:27:10,880 --> 00:27:13,040 Speaker 10: is a substitute, it's probably going to be open AI, 578 00:27:13,080 --> 00:27:14,639 Speaker 10: which we've investigated unfortunately. 579 00:27:16,440 --> 00:27:21,720 Speaker 1: And so how you seeing the global nature of AI 580 00:27:21,960 --> 00:27:24,000 Speaker 1: and the face competition there is do you think that 581 00:27:24,040 --> 00:27:26,000 Speaker 1: the US giants are going to be the ones stealing 582 00:27:26,040 --> 00:27:27,359 Speaker 1: the funder hair or do you think it will be 583 00:27:27,359 --> 00:27:27,760 Speaker 1: in China? 584 00:27:27,800 --> 00:27:32,520 Speaker 10: For example, I'm seriously concerned about China's progress in AI. 585 00:27:32,680 --> 00:27:36,879 Speaker 10: I think it's been under reported and under uh you know, 586 00:27:37,560 --> 00:27:40,600 Speaker 10: and uh policy makers and regulators haven't paid enough attention. 587 00:27:41,000 --> 00:27:44,200 Speaker 10: That's starting to change. But there's a lot of advantages 588 00:27:44,320 --> 00:27:46,960 Speaker 10: China has an AI. There's less privacy, there's more people. 589 00:27:47,160 --> 00:27:51,360 Speaker 10: More data usually makes AI better. Their organizational top down 590 00:27:51,440 --> 00:27:53,960 Speaker 10: hierarchy may work better for AI building. 591 00:27:54,840 --> 00:27:57,359 Speaker 9: So in the and their computing power and their chips 592 00:27:57,400 --> 00:27:59,919 Speaker 9: are actually pretty first rate. I think people underestimated that 593 00:28:00,080 --> 00:28:00,520 Speaker 9: as well. 594 00:28:00,800 --> 00:28:04,159 Speaker 10: So the combination is very scary and this is a 595 00:28:04,320 --> 00:28:07,640 Speaker 10: major threat to the United States. The future geopolitical future 596 00:28:07,640 --> 00:28:09,880 Speaker 10: of the United States is whoever Wednesday AI race. 597 00:28:09,720 --> 00:28:11,040 Speaker 9: Well major advantages. 598 00:28:11,320 --> 00:28:14,640 Speaker 10: So this is something that everybody United States, from entrepreneur, 599 00:28:14,680 --> 00:28:17,360 Speaker 10: from the entrepreneur level to the presidential level, you need 600 00:28:17,359 --> 00:28:18,440 Speaker 10: to pay attention. 601 00:28:18,119 --> 00:28:18,920 Speaker 9: To every day. 602 00:28:19,640 --> 00:28:21,800 Speaker 1: Wow, thanks for making us pay attention to it. Thanks 603 00:28:21,800 --> 00:28:24,200 Speaker 1: for shining alout and some of the Chinese competition coming 604 00:28:24,240 --> 00:28:27,200 Speaker 1: in in commerce stretch as well, and just the whole 605 00:28:27,320 --> 00:28:29,040 Speaker 1: world lens that you get from an open store and 606 00:28:29,119 --> 00:28:31,040 Speaker 1: and you've found us fund. We appreciate it so much. 607 00:28:31,280 --> 00:28:34,400 Speaker 1: CEO of Open Store, Keith boy there. Meanwhile, coming up, 608 00:28:34,600 --> 00:28:36,240 Speaker 1: we've got to talk a little bit about social media. 609 00:28:36,800 --> 00:28:39,600 Speaker 1: Talk to TikTok a moment ago. Let's talk threads, Let's 610 00:28:39,640 --> 00:28:42,240 Speaker 1: talk X. Let's talk about threads coming on too desktop 611 00:28:42,360 --> 00:28:45,000 Speaker 1: and what X is doing to disable your blocks. I'll 612 00:28:45,040 --> 00:28:55,360 Speaker 1: discuss at all and going viral. This is bluemog technology. 613 00:28:57,720 --> 00:28:59,960 Speaker 1: Time for going viral and look at what the Internet 614 00:29:00,120 --> 00:29:02,720 Speaker 1: is talking about. According to reports, Meta is planning to 615 00:29:02,760 --> 00:29:05,680 Speaker 1: launch a web version of its app Threads early this week. 616 00:29:05,960 --> 00:29:06,080 Speaker 7: Now. 617 00:29:06,160 --> 00:29:09,000 Speaker 1: The web version is already been tested internally at the company. 618 00:29:09,440 --> 00:29:12,320 Speaker 1: We've also got some updates on XO. Meg's Max Chaffkin 619 00:29:12,480 --> 00:29:14,560 Speaker 1: is here with more. And I mean there was a 620 00:29:14,600 --> 00:29:17,360 Speaker 1: lot of hype and actually, you know, reinforced hype when 621 00:29:17,360 --> 00:29:19,120 Speaker 1: it came to Threads, and then it's kind of just 622 00:29:19,720 --> 00:29:20,800 Speaker 1: pulled away a little bit. 623 00:29:21,080 --> 00:29:24,080 Speaker 11: Yeah, you know, back when Meta, you know, the company 624 00:29:24,080 --> 00:29:27,080 Speaker 11: formerly known as Facebook, launch Threads, the kind of criticism 625 00:29:27,240 --> 00:29:29,800 Speaker 11: was they're just taking the audience from Instagram, which is 626 00:29:29,800 --> 00:29:32,680 Speaker 11: a huge platform, you know, obviously with billions of users, 627 00:29:32,880 --> 00:29:35,720 Speaker 11: and sort of grafting it onto this new social network. 628 00:29:36,080 --> 00:29:39,280 Speaker 11: Critics were questioning whether that audience would stay. We saw 629 00:29:39,280 --> 00:29:42,760 Speaker 11: a hundred million people download the app, and what's happened 630 00:29:42,840 --> 00:29:45,920 Speaker 11: is is kind of what I'd say critics were worried about, 631 00:29:45,920 --> 00:29:47,760 Speaker 11: which is that the audience has kind of fallen off. 632 00:29:48,680 --> 00:29:51,000 Speaker 1: We're seeing, you know, it's still getting used. 633 00:29:51,480 --> 00:29:54,360 Speaker 11: It's still if it weren't a Facebook product, I think 634 00:29:54,960 --> 00:29:57,160 Speaker 11: people will be really impressed by it, but now they're 635 00:29:57,240 --> 00:30:00,400 Speaker 11: back down sort of more in startup territory. We're seeing 636 00:30:00,400 --> 00:30:02,760 Speaker 11: the company kind of start to do these normal things. 637 00:30:02,760 --> 00:30:05,080 Speaker 11: You know, a web interface doesn't sound that exciting, it does. 638 00:30:05,200 --> 00:30:06,640 Speaker 11: There is a little bit of a you know what, 639 00:30:06,760 --> 00:30:10,040 Speaker 11: like you know, two thousand called and it's it's it's 640 00:30:10,400 --> 00:30:12,360 Speaker 11: not what you would normally think of as a product update. 641 00:30:12,520 --> 00:30:14,080 Speaker 11: But this is the kind of thing that is important 642 00:30:14,120 --> 00:30:17,200 Speaker 11: for marketers, social media people if they want to have 643 00:30:17,680 --> 00:30:20,240 Speaker 11: kind of like brands using the service, having having a 644 00:30:20,240 --> 00:30:21,480 Speaker 11: web interface will help. 645 00:30:21,880 --> 00:30:24,800 Speaker 1: And I think therein lies the issue is that brands 646 00:30:24,840 --> 00:30:27,440 Speaker 1: wanted to save a space, but we, as the user, 647 00:30:27,560 --> 00:30:30,440 Speaker 1: wanted things that we were familiar with that Twitter now 648 00:30:30,440 --> 00:30:34,560 Speaker 1: known as X makes Interestingly, X is taking away things 649 00:30:34,600 --> 00:30:36,600 Speaker 1: that we quite like using on x Y. 650 00:30:37,360 --> 00:30:40,680 Speaker 11: Elon Musk kind of showing up on X formerly Twitter 651 00:30:40,800 --> 00:30:42,280 Speaker 11: last week saying he's going to get rid of the 652 00:30:42,280 --> 00:30:45,960 Speaker 11: block feature. That's the feature that allows you to essentially 653 00:30:45,960 --> 00:30:49,680 Speaker 11: prevent people from reading your tweets while while you're logged 654 00:30:49,720 --> 00:30:53,400 Speaker 11: into the account. Also means you don't see messages from 655 00:30:53,440 --> 00:30:56,320 Speaker 11: trolls and so on. A lot of people like this, 656 00:30:56,400 --> 00:30:58,800 Speaker 11: people on sort of both sides of publical aisle brands 657 00:30:58,880 --> 00:31:01,400 Speaker 11: like it. It's it's a little bit surprising to see 658 00:31:01,440 --> 00:31:03,640 Speaker 11: Elon Musk doing this. The one thing I'll say is, 659 00:31:04,040 --> 00:31:06,040 Speaker 11: you know, Musk has seemed to be trying to do 660 00:31:06,120 --> 00:31:09,800 Speaker 11: whatever he can to kind of goose engagement to you know. 661 00:31:10,440 --> 00:31:13,719 Speaker 11: We've seen reports about you know, and it's disputed to 662 00:31:13,760 --> 00:31:17,360 Speaker 11: what extent has Twitter's traffic gone up or down, And 663 00:31:17,440 --> 00:31:19,640 Speaker 11: it seems like this would be an effort to get 664 00:31:19,640 --> 00:31:21,840 Speaker 11: more people logging in more of the time, because if 665 00:31:21,880 --> 00:31:25,000 Speaker 11: you're getting trolled, if you're getting into fights, then you're 666 00:31:25,080 --> 00:31:28,760 Speaker 11: using the platform and it's all gold as far as 667 00:31:28,760 --> 00:31:32,120 Speaker 11: Elon Musk concerned. The point the response to that is 668 00:31:32,120 --> 00:31:34,560 Speaker 11: that brands, of course do not like having their ads 669 00:31:34,560 --> 00:31:36,360 Speaker 11: appear next to trolls, and that's kind of been one 670 00:31:36,360 --> 00:31:40,920 Speaker 11: of the central criticisms from Madison Avenue of Twitter now 671 00:31:41,120 --> 00:31:42,800 Speaker 11: X in the Elon Musk era has been. 672 00:31:42,680 --> 00:31:45,640 Speaker 1: One of the central focuses of the new CEO. In 673 00:31:45,680 --> 00:31:48,960 Speaker 1: the yak Areina, I mean de facto, whether she's not 674 00:31:49,920 --> 00:31:52,400 Speaker 1: in control or is trying to drive real change, but 675 00:31:52,440 --> 00:31:54,840 Speaker 1: it's something about brand safety from their perspective. 676 00:31:55,120 --> 00:31:57,840 Speaker 11: Well, she's certainly talking a lot about brand safety because 677 00:31:57,840 --> 00:32:01,280 Speaker 11: it's something that the brands care about. But on the 678 00:32:01,320 --> 00:32:04,440 Speaker 11: other hand, there hasn't been a lot of necessarily action 679 00:32:04,600 --> 00:32:07,480 Speaker 11: around that besides statements by Linda Yakarino. I think a 680 00:32:07,480 --> 00:32:10,440 Speaker 11: lot of advertising people are sort of taking a wait 681 00:32:10,480 --> 00:32:12,880 Speaker 11: and see approach. They like what she's saying, they like her, 682 00:32:13,000 --> 00:32:16,320 Speaker 11: they know her track record, but they're not seeing steps 683 00:32:16,320 --> 00:32:19,320 Speaker 11: towards brand safety, or they might question whether there's been 684 00:32:19,360 --> 00:32:21,960 Speaker 11: real effort in terms of brand safety. And this is 685 00:32:21,960 --> 00:32:24,160 Speaker 11: not going to help. This is not going to assure 686 00:32:24,160 --> 00:32:26,640 Speaker 11: those concerns in any way, although it may add a 687 00:32:26,680 --> 00:32:29,200 Speaker 11: little bit more traffic. A little bit more engagement, which 688 00:32:29,240 --> 00:32:32,400 Speaker 11: of course social networks need, and you know, Thread's engagement 689 00:32:32,480 --> 00:32:35,720 Speaker 11: seems to be falling, and of course Elon Musk certainly 690 00:32:35,760 --> 00:32:36,800 Speaker 11: craves that attention. 691 00:32:37,480 --> 00:32:39,959 Speaker 1: Meanwhile, he says there isn't a good social media network 692 00:32:39,960 --> 00:32:42,959 Speaker 1: out there at the moment, sort of self flagellation. At 693 00:32:42,960 --> 00:32:45,479 Speaker 1: the same time, Max always great to catch up with him. 694 00:32:45,520 --> 00:32:47,280 Speaker 1: You've got to go and meet him all across Boomberg, 695 00:32:47,640 --> 00:32:57,600 Speaker 1: of course, whether it be on BusinessWeek or him like. 696 00:32:57,680 --> 00:33:00,360 Speaker 1: This year continues to mark a kind of gradual turn 697 00:33:00,520 --> 00:33:03,320 Speaker 1: to a five day in office work week, as more 698 00:33:03,360 --> 00:33:05,680 Speaker 1: company requires after we return to the office at least 699 00:33:05,720 --> 00:33:09,680 Speaker 1: four days at least. However, some argue that limiting work 700 00:33:09,680 --> 00:33:11,880 Speaker 1: from home will hit women that took advantage of the 701 00:33:11,920 --> 00:33:14,960 Speaker 1: flexibility horder than men. So how are this trend impact 702 00:33:15,320 --> 00:33:18,440 Speaker 1: what diversity looks like on the executive level going forward. 703 00:33:18,840 --> 00:33:20,600 Speaker 1: Place to say that someone's putting a lot of thought 704 00:33:20,640 --> 00:33:22,840 Speaker 1: into this is the Chief People Officer of Service now, 705 00:33:22,920 --> 00:33:25,080 Speaker 1: Jackie Canny, and it's great to have some time with you, Jackie. 706 00:33:25,120 --> 00:33:28,600 Speaker 1: And just at the moment, you're trying to think about talent, 707 00:33:28,680 --> 00:33:32,480 Speaker 1: about retainment, about ensuring that people can work most effectively 708 00:33:32,520 --> 00:33:35,560 Speaker 1: from wherever they are. Are you asking people to come 709 00:33:35,560 --> 00:33:37,920 Speaker 1: back to the office to ensure that it's that serendipity 710 00:33:38,320 --> 00:33:40,440 Speaker 1: you keeping a flexibility around Service Now? 711 00:33:41,520 --> 00:33:43,920 Speaker 2: Well, first, thank you for having us here. It's such 712 00:33:43,920 --> 00:33:46,280 Speaker 2: a great opportunity to talk about what I care so 713 00:33:46,360 --> 00:33:48,880 Speaker 2: much about, which is talent strategy and people and how 714 00:33:48,920 --> 00:33:52,000 Speaker 2: they can thrive and here at Service Now, we've been 715 00:33:52,120 --> 00:33:55,600 Speaker 2: always leading with flexibility and trust for our people, even 716 00:33:55,640 --> 00:33:59,280 Speaker 2: before COVID and then certainly during COVID, and now we 717 00:33:59,320 --> 00:34:01,880 Speaker 2: still lean on we have the opportunity where are people 718 00:34:02,160 --> 00:34:04,680 Speaker 2: with their managers can pick what persona they want to 719 00:34:04,680 --> 00:34:07,040 Speaker 2: be in. Is it to be a remote person meaning 720 00:34:07,040 --> 00:34:08,960 Speaker 2: you're not in the office at all? Is it to 721 00:34:08,960 --> 00:34:11,840 Speaker 2: be a flexible person where you're one to three days 722 00:34:11,880 --> 00:34:14,560 Speaker 2: in the office per week, and then are you in 723 00:34:14,600 --> 00:34:17,239 Speaker 2: the office all the time? And we continue to you know, 724 00:34:17,360 --> 00:34:19,760 Speaker 2: let our people let that unfold, and it's been working 725 00:34:19,800 --> 00:34:20,840 Speaker 2: really great for us. 726 00:34:21,200 --> 00:34:24,239 Speaker 1: Does that I was talking to someone who works another 727 00:34:24,320 --> 00:34:26,959 Speaker 1: key tech companies having to make that decision right now 728 00:34:27,000 --> 00:34:29,040 Speaker 1: as to whether they sign up to be fully remote 729 00:34:29,160 --> 00:34:32,000 Speaker 1: or not, and well, they're mainly worried about what the 730 00:34:32,000 --> 00:34:34,480 Speaker 1: winter looks like, how they will then feel in months 731 00:34:34,520 --> 00:34:37,720 Speaker 1: to come. How that ultimately unfolds. How do you ensure 732 00:34:37,719 --> 00:34:40,480 Speaker 1: that flexibility remains flexible to help in and opt out of. 733 00:34:41,520 --> 00:34:44,480 Speaker 2: It's for sure, this conversation between a manager and a 734 00:34:44,520 --> 00:34:48,040 Speaker 2: person here, it's we have flexibility in that conversation too, 735 00:34:48,080 --> 00:34:51,600 Speaker 2: and we're continually, you know, adding these requests and trying 736 00:34:51,640 --> 00:34:53,520 Speaker 2: to manage them all so that people get to put 737 00:34:53,560 --> 00:34:55,319 Speaker 2: their point of view out there and then if we 738 00:34:55,320 --> 00:34:57,160 Speaker 2: can make it happen, they can pick the persona that 739 00:34:57,200 --> 00:34:58,960 Speaker 2: they want to they want to be in. So I 740 00:34:59,040 --> 00:35:03,080 Speaker 2: expect the winter could create a different environment. There's summer 741 00:35:03,120 --> 00:35:05,560 Speaker 2: here in the US. That also, you know, people need 742 00:35:05,600 --> 00:35:08,520 Speaker 2: more flexibility and we've been able to keep those promises. 743 00:35:09,239 --> 00:35:13,480 Speaker 1: So without a mandatory office attendance, are you kind of 744 00:35:13,520 --> 00:35:18,040 Speaker 1: like the biggest flexible distributed workforce. 745 00:35:19,320 --> 00:35:21,560 Speaker 2: I'd like to think so. I haven't really checked on that, 746 00:35:21,640 --> 00:35:24,920 Speaker 2: but we certainly are amongst the biggest, and you know, 747 00:35:25,000 --> 00:35:27,880 Speaker 2: I think the people being able to have a covenant 748 00:35:27,880 --> 00:35:29,279 Speaker 2: with each other on I'm going to be in the 749 00:35:29,320 --> 00:35:31,600 Speaker 2: office one to three days as flexible is really important. 750 00:35:31,640 --> 00:35:33,160 Speaker 2: And if if you're not going to be in one 751 00:35:33,160 --> 00:35:34,480 Speaker 2: to three days, then you have to talk to your 752 00:35:34,520 --> 00:35:36,160 Speaker 2: manager about why you're not going to be there. So 753 00:35:36,360 --> 00:35:40,200 Speaker 2: I think we can continue with flexibility and accountability in 754 00:35:40,200 --> 00:35:42,400 Speaker 2: the same way, so we can get the growth, the innovation, 755 00:35:43,000 --> 00:35:45,480 Speaker 2: the shoulder to shoulder camaraderie where we can and certainly 756 00:35:46,040 --> 00:35:48,840 Speaker 2: really dial it into moments that matter. So I'm in 757 00:35:48,880 --> 00:35:50,759 Speaker 2: the New York office today. One of the jobs I 758 00:35:50,800 --> 00:35:53,399 Speaker 2: take seriously is to represent this workforce in New York. 759 00:35:53,800 --> 00:35:55,799 Speaker 2: Whether it's about coming in because there's a great learning 760 00:35:55,840 --> 00:35:59,480 Speaker 2: and development opportunity, or you know, we have other visitors 761 00:35:59,520 --> 00:36:01,560 Speaker 2: coming in that you can learn from, or there's a 762 00:36:02,320 --> 00:36:05,200 Speaker 2: community social event where we're helping give back in New York. 763 00:36:05,239 --> 00:36:07,160 Speaker 2: And I think that is actually what's bringing people into 764 00:36:07,160 --> 00:36:09,840 Speaker 2: the office more than a mandate or you know, sort. 765 00:36:09,719 --> 00:36:11,239 Speaker 1: Of being specific. 766 00:36:11,440 --> 00:36:13,920 Speaker 2: And I think that those moments that matter will continue 767 00:36:14,000 --> 00:36:16,399 Speaker 2: to like have us earn the commute for our people 768 00:36:16,480 --> 00:36:16,880 Speaker 2: to come in. 769 00:36:17,080 --> 00:36:19,000 Speaker 1: I'm sure they're coming in to talk about the technology 770 00:36:19,040 --> 00:36:22,359 Speaker 1: they're building. How much are they worried, particularly in your 771 00:36:22,400 --> 00:36:26,480 Speaker 1: area of focusing on reducing bias and ensuring equality. When 772 00:36:26,480 --> 00:36:28,480 Speaker 1: we think about generator of AI and AI, how much 773 00:36:28,600 --> 00:36:30,920 Speaker 1: is there thought about that in the moment the way 774 00:36:30,920 --> 00:36:32,719 Speaker 1: in which you deploy it at Service Now. 775 00:36:33,280 --> 00:36:35,480 Speaker 2: We are such an optimistic company. You know, we have 776 00:36:35,560 --> 00:36:39,000 Speaker 2: great ambitions. You've probably heard Bill McDermott talk about us 777 00:36:39,000 --> 00:36:42,680 Speaker 2: becoming the DESCO twenty one C, which is the you know, 778 00:36:42,760 --> 00:36:45,799 Speaker 2: defining enterprise software company of the twenty first century. So 779 00:36:46,360 --> 00:36:50,319 Speaker 2: innovation technology generative AI are always at the top of 780 00:36:50,360 --> 00:36:54,040 Speaker 2: everyone's mind and it's an exciting optimistic place to be 781 00:36:54,200 --> 00:36:57,279 Speaker 2: to talk about those things, specific around bias and the 782 00:36:57,320 --> 00:36:58,880 Speaker 2: things that you just asked me about. You know, I 783 00:36:58,920 --> 00:37:01,280 Speaker 2: believe that the technology can help us take that out. 784 00:37:01,680 --> 00:37:04,120 Speaker 2: So you have a job description, you can use generative 785 00:37:04,120 --> 00:37:06,520 Speaker 2: AI to review that job description and say these are 786 00:37:06,560 --> 00:37:08,760 Speaker 2: the things that come out because it is creating bias 787 00:37:08,920 --> 00:37:12,560 Speaker 2: versus the negative, darker side of AI, and we take 788 00:37:12,560 --> 00:37:15,360 Speaker 2: it very seriously in how we build governance and trust. 789 00:37:15,960 --> 00:37:18,799 Speaker 1: We're here for the optimism. Jackie Kenney, thank you so much. 790 00:37:18,840 --> 00:37:22,040 Speaker 1: Service Now CPO. Great to have some time. But then 791 00:37:22,200 --> 00:37:25,040 Speaker 1: and ultimately that does it for this edition of Bloomberg Technology. 792 00:37:25,239 --> 00:37:27,200 Speaker 1: Don't forget to check out our podcast. You can find 793 00:37:27,239 --> 00:37:30,440 Speaker 1: it on the Terminal, online on Apple, Spotify, iHeart from 794 00:37:30,520 --> 00:37:34,000 Speaker 1: New York. This is Bloomberg Technology.