1 00:00:03,040 --> 00:00:07,039 Speaker 1: Hey, everyone, Welcome to The Restless Ones. I'm Jonathan Strickland. 2 00:00:07,320 --> 00:00:10,719 Speaker 1: As always, my focus is on exploring the intersection of 3 00:00:10,720 --> 00:00:14,440 Speaker 1: technology and business by having conversations with the most forward 4 00:00:14,480 --> 00:00:19,200 Speaker 1: thinking leaders. Throughout my career, I've covered everything from massive 5 00:00:19,239 --> 00:00:24,319 Speaker 1: parallel processing to advanced robotics, but what truly inspires me 6 00:00:24,680 --> 00:00:31,040 Speaker 1: are the stories of innovation and transformation. I'd like to 7 00:00:31,040 --> 00:00:34,320 Speaker 1: think that every episode of The Restless Ones is a 8 00:00:34,320 --> 00:00:39,159 Speaker 1: special one, but today I've got something really special. I 9 00:00:39,200 --> 00:00:42,160 Speaker 1: got to sit down with Philippa Layton Jones, Senior Vice 10 00:00:42,159 --> 00:00:44,720 Speaker 1: president of the Trust with the Wall Street Journal, and 11 00:00:44,760 --> 00:00:47,879 Speaker 1: Matt Griffin, CEO of the Three to eleven Institute at 12 00:00:47,880 --> 00:00:51,599 Speaker 1: Mobile World Congress twenty twenty three in Las Vegas, Nevada. 13 00:00:52,080 --> 00:00:55,360 Speaker 1: Philippa and Matt both served as judges for the second 14 00:00:55,440 --> 00:00:59,520 Speaker 1: Team Mobile for Business Unconventional Awards, and both have a 15 00:00:59,560 --> 00:01:03,880 Speaker 1: lot of site into and passion about technology in general 16 00:01:04,200 --> 00:01:07,920 Speaker 1: and the power of connectivity in particular. The conversation was 17 00:01:08,040 --> 00:01:11,119 Speaker 1: a lively one, and as you'll hear, Philippa and Matt 18 00:01:11,280 --> 00:01:15,400 Speaker 1: are both generous with their time and expertise. So now 19 00:01:15,440 --> 00:01:19,319 Speaker 1: I'm going to throw it to Jonathan of the past 20 00:01:19,880 --> 00:01:24,280 Speaker 1: to lead us into a discussion about tech trends, connectivity, 21 00:01:24,640 --> 00:01:32,560 Speaker 1: and the restless leaders who are changing the world. Welcome 22 00:01:32,600 --> 00:01:36,200 Speaker 1: to the Restless Ones. I'm Jonathan Strickland. We're here at 23 00:01:36,240 --> 00:01:39,479 Speaker 1: Mobile World Congress twenty twenty three, and it's a very 24 00:01:39,480 --> 00:01:44,480 Speaker 1: special episode because my guests today are both amazing people. 25 00:01:44,920 --> 00:01:47,840 Speaker 1: With me, I've got Philippa Lighton Jones. Philippa, Welcome to 26 00:01:47,880 --> 00:01:48,639 Speaker 1: the Restless Times. 27 00:01:48,680 --> 00:01:50,040 Speaker 2: You very much for having me here. 28 00:01:50,240 --> 00:01:53,880 Speaker 1: We've already bonded over our shared love of English literature, 29 00:01:54,200 --> 00:01:56,200 Speaker 1: which we both slaved over when we were students. 30 00:01:56,280 --> 00:01:58,160 Speaker 3: Sent me did very long time ago, and for me 31 00:01:58,920 --> 00:02:02,640 Speaker 3: at least days when we read books and there was 32 00:02:02,680 --> 00:02:04,280 Speaker 3: no internet, pre Internet. 33 00:02:04,000 --> 00:02:07,040 Speaker 1: Days right shortly after literature itself had been invented. If 34 00:02:07,040 --> 00:02:10,040 Speaker 1: I'm not mistaken, and we have Matt Griffin here, we're 35 00:02:10,040 --> 00:02:12,280 Speaker 1: going to be talking with you a lot about the 36 00:02:12,400 --> 00:02:16,760 Speaker 1: far off future days because you're a prognosticator, so that's 37 00:02:16,800 --> 00:02:17,600 Speaker 1: really exciting. 38 00:02:17,840 --> 00:02:20,240 Speaker 4: Well, I say, I don't know about prognosticate to people 39 00:02:20,240 --> 00:02:23,160 Speaker 4: call me a procrastinator and a futurist. That's it, but 40 00:02:23,240 --> 00:02:24,440 Speaker 4: you know that'll be a new one on me. 41 00:02:24,919 --> 00:02:28,120 Speaker 1: Well, and before we jump in, I always love to 42 00:02:28,120 --> 00:02:30,880 Speaker 1: get to know my guests a little better. Philip, I 43 00:02:30,919 --> 00:02:34,359 Speaker 1: would love to hear more about your journey into covering 44 00:02:34,480 --> 00:02:37,160 Speaker 1: tech and whether or not that was something you had 45 00:02:37,160 --> 00:02:40,160 Speaker 1: a burning desire to do or you kind of followed 46 00:02:40,200 --> 00:02:43,519 Speaker 1: that path through other courses, and how it brought to 47 00:02:43,520 --> 00:02:44,520 Speaker 1: you to where you are today. 48 00:02:44,880 --> 00:02:45,520 Speaker 2: Great question. 49 00:02:45,760 --> 00:02:49,160 Speaker 3: The year was nineteen ninety seven, I think, and I 50 00:02:49,240 --> 00:02:51,640 Speaker 3: had just graduated in English literature and I knew I 51 00:02:51,680 --> 00:02:53,359 Speaker 3: wanted to be a journalist and. 52 00:02:53,480 --> 00:02:55,160 Speaker 2: That's very hard gig to get, right. 53 00:02:55,280 --> 00:02:58,760 Speaker 3: It was London, mid nineties, pre internet days, so there 54 00:02:58,760 --> 00:03:01,760 Speaker 3: were probably like fewer reporting jobs as well. 55 00:03:01,800 --> 00:03:02,799 Speaker 2: You had to fight pretty hard. 56 00:03:03,160 --> 00:03:06,000 Speaker 3: But I managed to get myself into an organization and 57 00:03:06,080 --> 00:03:10,360 Speaker 3: the gig was covering tech. Now I wasn't really a 58 00:03:10,400 --> 00:03:13,200 Speaker 3: technologist at heart, so that was a steep learning curve, 59 00:03:13,480 --> 00:03:15,919 Speaker 3: a kind of a critical juncture, I would say, in 60 00:03:16,200 --> 00:03:19,120 Speaker 3: a career, but also super interesting at the time, right 61 00:03:19,160 --> 00:03:22,000 Speaker 3: because it was when folks were grappling with what is 62 00:03:22,040 --> 00:03:22,480 Speaker 3: this thing? 63 00:03:22,680 --> 00:03:23,480 Speaker 2: Like what is tech? 64 00:03:23,560 --> 00:03:25,800 Speaker 3: First of all, on what is the Internet? We maybe 65 00:03:25,800 --> 00:03:29,000 Speaker 3: had one email address across our organization, and so that 66 00:03:29,200 --> 00:03:32,320 Speaker 3: was an interesting journey to see that kind of rapid adoption. 67 00:03:32,680 --> 00:03:37,240 Speaker 3: My beat specifically was technology in finance, so across investment, banking, 68 00:03:37,280 --> 00:03:40,720 Speaker 3: asset management, those kind of like arcane things which were 69 00:03:40,760 --> 00:03:42,760 Speaker 3: also not terribly well covered back in the day. 70 00:03:42,800 --> 00:03:44,200 Speaker 2: It was quite sort of a. 71 00:03:43,960 --> 00:03:49,160 Speaker 3: Trade and you saw really some big corporate names trying 72 00:03:49,160 --> 00:03:52,120 Speaker 3: to come to terms with how was this technology going 73 00:03:52,160 --> 00:03:55,760 Speaker 3: to reshape their business? And you saw the early adopters 74 00:03:55,800 --> 00:04:00,200 Speaker 3: who were kind of like visionary, and you saw the detractors, right, 75 00:04:00,320 --> 00:04:03,240 Speaker 3: I remember one won't name him, but one very notable 76 00:04:03,320 --> 00:04:06,400 Speaker 3: chief executive of one very big information company who said, 77 00:04:06,880 --> 00:04:08,720 Speaker 3: this isn't going to change the way we do things. 78 00:04:08,720 --> 00:04:10,720 Speaker 3: We carry on the way we're doing and they were 79 00:04:10,800 --> 00:04:13,840 Speaker 3: left scrambling to catch up for a long time. But 80 00:04:13,920 --> 00:04:17,320 Speaker 3: one thing that was kind of interesting in that beat 81 00:04:17,360 --> 00:04:20,400 Speaker 3: with the folks who were almost too visionary and had 82 00:04:20,440 --> 00:04:23,880 Speaker 3: ideas before the market was ready to kind of adopt 83 00:04:23,880 --> 00:04:27,359 Speaker 3: those ideas. And we saw that a lot with stock exchanges, 84 00:04:27,400 --> 00:04:30,520 Speaker 3: for example, and like the emergence of these electronic communications 85 00:04:30,560 --> 00:04:33,919 Speaker 3: networks and matching engines and like really quite kind of 86 00:04:34,000 --> 00:04:37,920 Speaker 3: forny stuff, but where ideas were excellent and now they're 87 00:04:38,000 --> 00:04:40,560 Speaker 3: kind of like old school, but at the time the 88 00:04:40,600 --> 00:04:43,000 Speaker 3: world just wasn't ready to adopt them. It was too much, 89 00:04:43,040 --> 00:04:46,360 Speaker 3: too soon because the pace was filtering, I guess, And 90 00:04:46,400 --> 00:04:48,400 Speaker 3: so that took me on a journey of covering tech, 91 00:04:48,800 --> 00:04:52,600 Speaker 3: which now obviously underpins everything we do. There is kind 92 00:04:52,600 --> 00:04:54,640 Speaker 3: of no beat that doesn't cover tech in a way. 93 00:04:54,720 --> 00:04:57,240 Speaker 3: So that's the sort of potted history. 94 00:04:57,520 --> 00:05:00,760 Speaker 1: Yeah, it's fascinating too, because you got in just a 95 00:05:00,800 --> 00:05:03,839 Speaker 1: couple of years before the infamous dot com crash, sure, 96 00:05:04,040 --> 00:05:07,839 Speaker 1: which was transformational in many many ways, and then we 97 00:05:08,160 --> 00:05:12,240 Speaker 1: saw the rebuilding process where we defined what later we 98 00:05:12,279 --> 00:05:15,040 Speaker 1: would come to call Web two point zero. You're also 99 00:05:15,360 --> 00:05:18,240 Speaker 1: starting right when Steve Jobs is coming back to Apple. 100 00:05:19,040 --> 00:05:22,120 Speaker 1: It was a truly pivotal moment in tech and in 101 00:05:22,240 --> 00:05:26,240 Speaker 1: business just as you were getting started. Matt. I'm curious, 102 00:05:26,279 --> 00:05:29,480 Speaker 1: how did you first get interested in technology? What drew 103 00:05:29,520 --> 00:05:31,159 Speaker 1: you to the world of tech? 104 00:05:31,560 --> 00:05:33,800 Speaker 4: So I kind of reversed into the world of tech. 105 00:05:33,960 --> 00:05:37,000 Speaker 4: My background is I'm a marine biologist and oceanographer by training. 106 00:05:37,520 --> 00:05:39,880 Speaker 4: I did a bunch of work with the UNHCR around 107 00:05:40,000 --> 00:05:42,479 Speaker 4: coral reef and coral reef preservation and so on and 108 00:05:42,480 --> 00:05:44,720 Speaker 4: so forth, but then ended up falling into a job 109 00:05:44,760 --> 00:05:48,520 Speaker 4: with e MC so then ran global sales specific organizations 110 00:05:48,560 --> 00:05:51,760 Speaker 4: like IBM and ATOS. I headed up IBM's what we 111 00:05:51,800 --> 00:05:55,480 Speaker 4: call PSNS business, so public safety and National Security business. 112 00:05:55,480 --> 00:05:57,000 Speaker 5: And when you're having a look at the five eyes, 113 00:05:57,400 --> 00:05:59,560 Speaker 5: which is typically you know, the GHQ's, the. 114 00:05:59,520 --> 00:06:02,479 Speaker 4: CIA and everything else, Yeah, they want to understand not 115 00:06:02,600 --> 00:06:05,680 Speaker 4: what's here now, not what's just coming, but they want 116 00:06:05,720 --> 00:06:08,520 Speaker 4: to understand technology from a kind of N plus two 117 00:06:08,760 --> 00:06:11,840 Speaker 4: N plus three perspective. So I set up a variety 118 00:06:11,920 --> 00:06:14,760 Speaker 4: of different sort of what we call blue sky forums, 119 00:06:14,839 --> 00:06:19,240 Speaker 4: especially within these organizations. In the two thousand and six 120 00:06:19,279 --> 00:06:21,520 Speaker 4: two thousand and seven, I saw over two hundred and 121 00:06:21,560 --> 00:06:25,120 Speaker 4: fifty thousand people in the technology industry then being made 122 00:06:25,160 --> 00:06:29,520 Speaker 4: redundant because you had the technology chance like IBM, who 123 00:06:29,520 --> 00:06:32,640 Speaker 4: had kind of seen this thing called cloud but didn't 124 00:06:32,640 --> 00:06:35,680 Speaker 4: really understand what it was. It was fundamentally disruptive to 125 00:06:35,720 --> 00:06:38,560 Speaker 4: their business, so they didn't really like it, so they 126 00:06:38,560 --> 00:06:40,680 Speaker 4: didn't really want to put their arms around in in the. 127 00:06:40,600 --> 00:06:42,719 Speaker 5: First place, which is a kind of a cultural thing. 128 00:06:43,400 --> 00:06:47,200 Speaker 4: And if you really want to actually understand how you 129 00:06:47,240 --> 00:06:52,040 Speaker 4: can protect people's jobs in the future, then you need 130 00:06:52,080 --> 00:06:55,520 Speaker 4: to understand technology. You need to understand what it is, 131 00:06:55,640 --> 00:06:57,720 Speaker 4: why it is, what it's capable of. You need to 132 00:06:57,800 --> 00:07:01,000 Speaker 4: understand what the trajectory looks like, and then you need 133 00:07:01,000 --> 00:07:02,400 Speaker 4: to be able to kind of try to plot all 134 00:07:02,440 --> 00:07:05,000 Speaker 4: of that out and say, in the future, we think 135 00:07:05,040 --> 00:07:08,240 Speaker 4: technology will be able to do X generative AI at 136 00:07:08,279 --> 00:07:10,160 Speaker 4: the moment as a superb example. 137 00:07:09,800 --> 00:07:12,480 Speaker 5: Of Armageddon going wrong, and then you. 138 00:07:12,440 --> 00:07:14,840 Speaker 4: Have to plot that back to say, well, if technology 139 00:07:14,840 --> 00:07:17,520 Speaker 4: in the future can do this, and these are the problems, 140 00:07:17,560 --> 00:07:20,720 Speaker 4: the societal and business issues that we actually see, here 141 00:07:20,720 --> 00:07:23,720 Speaker 4: are some of the solutions to that. So now I 142 00:07:23,800 --> 00:07:27,640 Speaker 4: cross over six hundred emerging technologies across every sector up 143 00:07:27,640 --> 00:07:31,040 Speaker 4: to fifty years out, and we do get crazy. 144 00:07:31,360 --> 00:07:34,960 Speaker 1: Yeah, When I used to do an episode at the 145 00:07:35,040 --> 00:07:37,000 Speaker 1: end of each year where I would do a predictions 146 00:07:37,040 --> 00:07:39,800 Speaker 1: episode of what happened the next year, I would hold 147 00:07:39,840 --> 00:07:42,800 Speaker 1: myself accountable, and at the end of that following year, 148 00:07:42,840 --> 00:07:44,400 Speaker 1: I would do a follow up to say, how did 149 00:07:44,440 --> 00:07:47,200 Speaker 1: I do? You would not hire me, Matt, I was 150 00:07:47,360 --> 00:07:50,240 Speaker 1: hit that. Oh gosh, if I were baseball, I would 151 00:07:50,240 --> 00:07:51,440 Speaker 1: have been benched years. 152 00:07:52,920 --> 00:07:54,720 Speaker 2: Everyone's hit rate bad on those things, though. 153 00:07:54,960 --> 00:07:57,280 Speaker 1: I think so, especially when you're looking at a near term, 154 00:07:57,320 --> 00:08:00,400 Speaker 1: just because you never really know what the next disruptive 155 00:08:00,400 --> 00:08:01,880 Speaker 1: thing is going to be which may not even be 156 00:08:01,920 --> 00:08:04,160 Speaker 1: tech related, right, It could just be a change in leadership, 157 00:08:04,200 --> 00:08:06,400 Speaker 1: It could be a change in strategy. Those are the 158 00:08:06,400 --> 00:08:08,680 Speaker 1: sort of things that can be really disruptive that are 159 00:08:08,800 --> 00:08:09,800 Speaker 1: very difficult to predict. 160 00:08:09,840 --> 00:08:11,960 Speaker 4: Well, I mean business models, geopolitics. If you have a 161 00:08:12,000 --> 00:08:14,320 Speaker 4: look at COVID. You know, we had COVID, then we 162 00:08:14,520 --> 00:08:16,560 Speaker 4: ended up with the Ukraine War. Then we ended up 163 00:08:16,600 --> 00:08:19,160 Speaker 4: with supply chain crunches, high rates of inflation and so 164 00:08:19,200 --> 00:08:22,040 Speaker 4: on and so forth, cost of living problems and issues. 165 00:08:22,560 --> 00:08:25,320 Speaker 4: And what we typically find is, ironically, when we have 166 00:08:25,360 --> 00:08:28,840 Speaker 4: a look against this backdrop of sort of geopolitics and 167 00:08:29,000 --> 00:08:33,280 Speaker 4: environmentalism and everything else, technology is actually quite straightforward to 168 00:08:33,320 --> 00:08:36,480 Speaker 4: predict because it follows common paths. So you can see 169 00:08:36,520 --> 00:08:40,000 Speaker 4: the ecosystems developing and building, you can see the problems 170 00:08:40,000 --> 00:08:41,800 Speaker 4: that people are trying to solve. You can see the 171 00:08:41,840 --> 00:08:45,839 Speaker 4: investor communities piling into particular things and so on and 172 00:08:45,880 --> 00:08:48,960 Speaker 4: so forth. So actually, ironically, it's the rest of the 173 00:08:49,000 --> 00:08:50,760 Speaker 4: stuff that starts confusing the world. 174 00:08:51,360 --> 00:08:54,120 Speaker 1: Let's talk a little bit about what we're seeing currently, 175 00:08:54,320 --> 00:08:56,480 Speaker 1: specifically in the mobile space, since we're here at Mobile 176 00:08:56,520 --> 00:08:59,200 Speaker 1: World Congress and one of the things I would love 177 00:08:59,240 --> 00:09:02,040 Speaker 1: to talk about are some of the things that people 178 00:09:02,080 --> 00:09:05,720 Speaker 1: are spotting right now. Is kind of an emerging directions trends, 179 00:09:05,720 --> 00:09:08,040 Speaker 1: so however you want to define it in the space, 180 00:09:08,160 --> 00:09:10,440 Speaker 1: and then Philip, I would love to get your opinion 181 00:09:10,440 --> 00:09:12,720 Speaker 1: about that, like sort of are we seeing the industry 182 00:09:12,760 --> 00:09:14,720 Speaker 1: coalesce around anything in particular? 183 00:09:15,080 --> 00:09:17,360 Speaker 3: I think there is a kind of coalescence of two 184 00:09:17,480 --> 00:09:19,360 Speaker 3: things that I think are super important and we should 185 00:09:19,360 --> 00:09:22,040 Speaker 3: spend some time talking about. One is obviously AI, right 186 00:09:22,200 --> 00:09:23,600 Speaker 3: is what's happening with genai? 187 00:09:23,760 --> 00:09:24,320 Speaker 2: Is it a real thing? 188 00:09:24,360 --> 00:09:26,200 Speaker 3: We were talking about this a little bit earlier, you know, 189 00:09:26,400 --> 00:09:28,400 Speaker 3: a couple of years ago, we were talking about NFTs. 190 00:09:28,440 --> 00:09:30,600 Speaker 2: We were all desperately trying to launch something with NFTs. 191 00:09:30,640 --> 00:09:33,160 Speaker 3: Then we were thinking about the metaverse, and then maybe 192 00:09:33,160 --> 00:09:35,679 Speaker 3: we're not thinking about the metaverse quite so much. We 193 00:09:35,720 --> 00:09:39,040 Speaker 3: were thinking about AR and VR, and maybe we've kind 194 00:09:39,040 --> 00:09:41,000 Speaker 3: of like scaled back a little bit on that now too. 195 00:09:41,440 --> 00:09:43,400 Speaker 3: Is it time to slow down on AI? One has 196 00:09:43,440 --> 00:09:46,720 Speaker 3: to be very measured about the consequences of AIJENAI obviously 197 00:09:46,800 --> 00:09:49,079 Speaker 3: is only one facet of it, and I think thinking 198 00:09:49,120 --> 00:09:52,680 Speaker 3: through the unintended consequences of technology, right, what is the 199 00:09:52,800 --> 00:09:56,000 Speaker 3: endgame for this even one year from now, five years 200 00:09:56,000 --> 00:09:58,320 Speaker 3: from now, ten years from now, there's chat, GPT and 201 00:09:58,440 --> 00:10:00,920 Speaker 3: open AI is sort of like really one of the scene. 202 00:10:01,240 --> 00:10:02,760 Speaker 3: Where do we go next with that? What are the 203 00:10:02,880 --> 00:10:07,480 Speaker 3: real world examples? And then one other thing is there's sustainability, 204 00:10:07,520 --> 00:10:09,280 Speaker 3: which I think we have to be thinking about this 205 00:10:09,440 --> 00:10:10,720 Speaker 3: and I know we'll come onto this a little bit 206 00:10:10,760 --> 00:10:13,200 Speaker 3: when we talk about the awards maybe, but if we're 207 00:10:13,240 --> 00:10:16,480 Speaker 3: not putting mobile technology to work to help with things 208 00:10:16,559 --> 00:10:21,320 Speaker 3: like smart cities and dealing with the outcome of climate 209 00:10:21,400 --> 00:10:24,800 Speaker 3: change of climate disasters, we're missing a trick, right. I mean, 210 00:10:24,840 --> 00:10:27,360 Speaker 3: I know that the tech industry and the mobile industry 211 00:10:27,760 --> 00:10:31,880 Speaker 3: specifically has put sustainability really front and center of its considerations. 212 00:10:31,920 --> 00:10:34,040 Speaker 3: How big are our text acts, how much carbon are 213 00:10:34,080 --> 00:10:36,640 Speaker 3: we using to sort of keep our businesses afloat? But 214 00:10:36,720 --> 00:10:38,600 Speaker 3: I think it's much much more than that, and it's 215 00:10:38,640 --> 00:10:41,280 Speaker 3: about how do we create the solutions of the future 216 00:10:41,760 --> 00:10:44,320 Speaker 3: but also sell them in Like, we're seeing a lot 217 00:10:44,320 --> 00:10:47,160 Speaker 3: of rowing back of commitments at a government level, at 218 00:10:47,160 --> 00:10:50,040 Speaker 3: an organizational level, and I think that that is without 219 00:10:50,080 --> 00:10:51,600 Speaker 3: wanting to sort of get in the soap box here, 220 00:10:51,679 --> 00:10:53,920 Speaker 3: that is worrying, and I think that it is up 221 00:10:53,960 --> 00:10:56,240 Speaker 3: to the technologists of the world who have those solutions 222 00:10:56,280 --> 00:10:57,360 Speaker 3: to get on the front foot. 223 00:10:57,480 --> 00:11:00,360 Speaker 2: So those are the themes that are really emerging for me. 224 00:11:00,720 --> 00:11:04,400 Speaker 1: Well to your point about sustainability and climate change, conservation, 225 00:11:04,440 --> 00:11:06,800 Speaker 1: all of those things. I'm of two minds of the subject. 226 00:11:06,840 --> 00:11:08,240 Speaker 1: I know a lot of people who talk about us 227 00:11:08,280 --> 00:11:10,559 Speaker 1: engineering our way out of a problem, which I think. 228 00:11:10,440 --> 00:11:11,199 Speaker 2: Is part of it. 229 00:11:11,559 --> 00:11:13,280 Speaker 1: But to me, that's almost like saying this is a 230 00:11:13,280 --> 00:11:15,840 Speaker 1: future Jonathan problem, which I do in my personal life, 231 00:11:16,120 --> 00:11:19,439 Speaker 1: and future Jonathan hates Jonathan of today because Jonathan of 232 00:11:19,480 --> 00:11:20,439 Speaker 1: today could have taken. 233 00:11:20,280 --> 00:11:23,160 Speaker 2: Care of and you've already done the damage you remember, 234 00:11:23,240 --> 00:11:23,920 Speaker 2: right exactly. 235 00:11:24,160 --> 00:11:27,600 Speaker 1: But I think there's incredible potential. I mean, we're talking 236 00:11:27,600 --> 00:11:30,960 Speaker 1: about a global population where a massive number of us 237 00:11:31,160 --> 00:11:35,480 Speaker 1: are carrying around an incredibly powerful computer that's constantly connected, 238 00:11:35,880 --> 00:11:39,200 Speaker 1: and that there are ways of leveraging that that could 239 00:11:39,240 --> 00:11:43,559 Speaker 1: make a significant difference if we engineer the right approaches 240 00:11:43,600 --> 00:11:45,960 Speaker 1: to it. It's almost like it's an untapped resource, and 241 00:11:45,960 --> 00:11:48,360 Speaker 1: we're starting to see some businesses find ways to tap 242 00:11:48,400 --> 00:11:52,079 Speaker 1: into it in a very specific way that benefits their business, right. 243 00:11:52,200 --> 00:11:55,439 Speaker 1: But to me, that also means that there's the potential 244 00:11:55,960 --> 00:11:59,360 Speaker 1: of harnessing that power in ways that can have massive 245 00:11:59,679 --> 00:12:03,800 Speaker 1: pos of global impact. It just requires the right infrastructure, 246 00:12:03,840 --> 00:12:06,720 Speaker 1: the right approach, the right governance to make certain it's 247 00:12:06,800 --> 00:12:10,600 Speaker 1: run properly. Yeah, Matt, I'm also curious if you have 248 00:12:10,720 --> 00:12:13,360 Speaker 1: seen anything that is sparking your interest. 249 00:12:13,679 --> 00:12:15,120 Speaker 4: Well, I mean, if you have a look at MWC, 250 00:12:15,400 --> 00:12:19,040 Speaker 4: for example, there are no particular trends that actually stand out, 251 00:12:19,640 --> 00:12:21,040 Speaker 4: which I think is actually interesting. 252 00:12:21,080 --> 00:12:22,640 Speaker 5: So a lot of people still say, well, maybe that's 253 00:12:22,640 --> 00:12:23,120 Speaker 5: a cop out. 254 00:12:23,160 --> 00:12:26,000 Speaker 4: But we've got things like smart cities, we've got Internet 255 00:12:26,040 --> 00:12:28,680 Speaker 4: of Things trends, we've got the impact of five G 256 00:12:28,840 --> 00:12:31,880 Speaker 4: for example, basically on mobility. You know, there are conversations 257 00:12:31,880 --> 00:12:35,440 Speaker 4: about security and so on and so forth, deployment, network optimization. 258 00:12:36,040 --> 00:12:38,080 Speaker 4: But actually, for me, by see the fact that we 259 00:12:38,120 --> 00:12:41,200 Speaker 4: don't really have any trends that are particularly standing out 260 00:12:41,640 --> 00:12:44,600 Speaker 4: shows to me that you've actually got a very very 261 00:12:44,640 --> 00:12:47,400 Speaker 4: broad ecosystem. And actually, when you have a look at 262 00:12:47,480 --> 00:12:51,199 Speaker 4: fundamentally what five G is, five G is a general 263 00:12:51,240 --> 00:12:54,520 Speaker 4: purpose technology. It is a technology that can be used 264 00:12:54,640 --> 00:12:57,920 Speaker 4: very broadly and can be innovated on top of to 265 00:12:58,040 --> 00:13:01,480 Speaker 4: improve all kinds of different sectors for lots of different 266 00:13:01,520 --> 00:13:04,080 Speaker 4: kinds of use cases and everything else. And I think 267 00:13:04,160 --> 00:13:07,040 Speaker 4: when you actually have a look at the diversification of 268 00:13:07,080 --> 00:13:09,760 Speaker 4: all these different trends, it's really starting to show that 269 00:13:09,800 --> 00:13:12,360 Speaker 4: people have gone from the let's try to find the 270 00:13:12,440 --> 00:13:15,680 Speaker 4: specific killer applications for five G, you know, and we 271 00:13:15,720 --> 00:13:19,640 Speaker 4: had metaverse and AR and VR gaming for example, and 272 00:13:19,640 --> 00:13:21,959 Speaker 4: people are now starting to think, well, okay, now what. 273 00:13:21,920 --> 00:13:24,440 Speaker 5: Do we really do. How do we really start pushing 274 00:13:24,480 --> 00:13:26,680 Speaker 5: this into the enterprise, how do we start deploying this, 275 00:13:26,760 --> 00:13:28,560 Speaker 5: how do we actually practically do this? 276 00:13:28,960 --> 00:13:29,400 Speaker 2: But when we. 277 00:13:29,400 --> 00:13:32,760 Speaker 4: Actually look sort of further out, there's obviously conversations around 278 00:13:32,760 --> 00:13:36,040 Speaker 4: six G. We've already seen the US FCC starting to 279 00:13:36,080 --> 00:13:38,920 Speaker 4: sell seven G spectrum as well. We're already starting to 280 00:13:39,040 --> 00:13:42,840 Speaker 4: eye quantum communications. Then we've obviously got space based satellite 281 00:13:42,840 --> 00:13:45,040 Speaker 4: systems as well, and T Mobile have obviously teamed up 282 00:13:45,080 --> 00:13:45,840 Speaker 4: with SpaceX. 283 00:13:46,200 --> 00:13:47,280 Speaker 5: So there's actually a lot. 284 00:13:47,280 --> 00:13:50,720 Speaker 4: Happening just in that communications space. When we actually have 285 00:13:50,720 --> 00:13:52,760 Speaker 4: a look at five G today, we're topping out at 286 00:13:52,800 --> 00:13:55,600 Speaker 4: say what one point five maybe two point five gig 287 00:13:55,640 --> 00:13:58,120 Speaker 4: asecond But in the labs, when we have a look 288 00:13:58,120 --> 00:14:01,240 Speaker 4: at six G, we're already starting to talk about sixteen 289 00:14:01,280 --> 00:14:04,439 Speaker 4: gig a second. We're talking about pushing to terrabits per second. 290 00:14:05,240 --> 00:14:08,920 Speaker 4: So that's interesting. And then when we talk about quantum technologies, 291 00:14:08,960 --> 00:14:11,160 Speaker 4: we're talking about more unhackable sort. 292 00:14:11,040 --> 00:14:12,760 Speaker 5: Of systems and everything else you mentioned. 293 00:14:12,880 --> 00:14:15,400 Speaker 4: From a user perspective, people are looking for, you know, 294 00:14:15,400 --> 00:14:19,000 Speaker 4: what does this accessibility do for me? Right now, let's 295 00:14:19,040 --> 00:14:23,040 Speaker 4: say we bring generative artificial intelligence into it. Fundamentally, when 296 00:14:23,040 --> 00:14:25,200 Speaker 4: we have a look at things like five G they 297 00:14:25,240 --> 00:14:27,800 Speaker 4: give us access to stuff. One of the things that 298 00:14:27,880 --> 00:14:33,359 Speaker 4: excites me about accessibility using these different technologies is accessibility 299 00:14:33,400 --> 00:14:36,560 Speaker 4: to knowledge. Now that's different. So today Boally, we've got 300 00:14:36,560 --> 00:14:39,360 Speaker 4: about three point five billion people on the planet connected 301 00:14:39,720 --> 00:14:42,600 Speaker 4: in one way or another, so they have access to 302 00:14:42,640 --> 00:14:45,000 Speaker 4: the Internet, they have access to education and ed tech 303 00:14:45,040 --> 00:14:48,040 Speaker 4: systems and so on and so forth. However, when you 304 00:14:48,080 --> 00:14:49,800 Speaker 4: have a look at the Internet today, what we all 305 00:14:49,840 --> 00:14:53,640 Speaker 4: have access to is we have access to information. Now, 306 00:14:53,680 --> 00:14:57,120 Speaker 4: when you start overlaying these large language models, these systems 307 00:14:57,200 --> 00:14:59,960 Speaker 4: understand natural language to such a high degree that they 308 00:15:00,120 --> 00:15:03,440 Speaker 4: have an IQ of one hundred and fifty five. Now 309 00:15:03,760 --> 00:15:05,800 Speaker 4: what that means is they're able to take all of 310 00:15:05,840 --> 00:15:10,760 Speaker 4: this raw data. This information and start mixing the domains. 311 00:15:11,040 --> 00:15:16,080 Speaker 4: So now that we start generating knowledge. So now we're 312 00:15:16,120 --> 00:15:19,520 Speaker 4: starting to move from a global society that had access 313 00:15:19,560 --> 00:15:23,800 Speaker 4: to information across these networks to a global society that 314 00:15:23,920 --> 00:15:29,280 Speaker 4: has access to expertise and knowledge. And when you really 315 00:15:29,320 --> 00:15:33,040 Speaker 4: start thinking about how five G, for example, actually really 316 00:15:33,240 --> 00:15:37,880 Speaker 4: enables people to have access to these increasingly powerful cloud 317 00:15:37,920 --> 00:15:40,880 Speaker 4: based technologies, whatever they happen to be, that's one of 318 00:15:40,920 --> 00:15:43,480 Speaker 4: the most exciting things that I see as I travel around. 319 00:15:43,680 --> 00:15:46,840 Speaker 4: You know what happens when people have access to knowledge 320 00:15:47,280 --> 00:15:50,200 Speaker 4: and access to systems that can help them accelerate their 321 00:15:50,320 --> 00:15:55,800 Speaker 4: learning sixfold. When you can use generative artificial intelligence with 322 00:15:55,920 --> 00:16:00,160 Speaker 4: children to boost their grades by thirty percent for almost free. 323 00:16:00,720 --> 00:16:04,840 Speaker 4: When we have corporates that are taking juniors in a 324 00:16:04,880 --> 00:16:08,440 Speaker 4: whole variety of different domains and subjects and topics and 325 00:16:08,640 --> 00:16:12,200 Speaker 4: boosting them to a two h one level within three weeks. 326 00:16:13,000 --> 00:16:14,720 Speaker 4: So all of a sudden, what we have is we 327 00:16:14,840 --> 00:16:18,200 Speaker 4: have the network layer that gives us access to. 328 00:16:18,280 --> 00:16:21,520 Speaker 5: New things, to do new things, but from. 329 00:16:21,400 --> 00:16:25,800 Speaker 4: A societal perspective, access to knowledge, and then that's just 330 00:16:25,840 --> 00:16:28,240 Speaker 4: going to keep driving the five G ecosystem even more 331 00:16:28,240 --> 00:16:30,840 Speaker 4: because access to knowledge means that we now have access 332 00:16:31,160 --> 00:16:33,680 Speaker 4: to new ways to solve the problems that we actually have. 333 00:16:34,400 --> 00:16:36,040 Speaker 5: So it's that virtuous loop. 334 00:16:36,200 --> 00:16:39,560 Speaker 1: Which is nice to run into in tech. Yes, often 335 00:16:39,600 --> 00:16:42,720 Speaker 1: we're talking about the alternative, but I love that vision 336 00:16:42,760 --> 00:16:45,560 Speaker 1: of the future. I love the thought of using generative 337 00:16:45,560 --> 00:16:51,000 Speaker 1: AI to perhaps capture that long promised but never delivered 338 00:16:51,040 --> 00:16:57,040 Speaker 1: goal of being able to give students specific approaches to 339 00:16:57,120 --> 00:17:00,440 Speaker 1: learning that are catered to them. That's something that technology 340 00:17:00,440 --> 00:17:01,560 Speaker 1: has been promising for years. 341 00:17:01,880 --> 00:17:07,160 Speaker 4: So we are now at the point where every single person, 342 00:17:07,280 --> 00:17:11,520 Speaker 4: not just child, but every single adult has access to 343 00:17:11,640 --> 00:17:15,080 Speaker 4: a one on one tutor that has a thousand times 344 00:17:15,119 --> 00:17:17,960 Speaker 4: more general knowledge in its head than anyone on the planet, 345 00:17:18,720 --> 00:17:20,960 Speaker 4: where you can ask it anything. You can ask it 346 00:17:21,080 --> 00:17:24,359 Speaker 4: to teach you to become a five G network engineer, 347 00:17:24,760 --> 00:17:27,639 Speaker 4: or you can get it to teach you about, you know, 348 00:17:27,800 --> 00:17:30,840 Speaker 4: my daughter's case habitats and that sort of stuff. You've 349 00:17:30,840 --> 00:17:33,640 Speaker 4: now got access to a one on one tutor. 350 00:17:34,240 --> 00:17:37,000 Speaker 1: Both my parents are teachers, so I this speaks directly 351 00:17:37,040 --> 00:17:40,399 Speaker 1: to me because you're talking exactly the experience they would have, 352 00:17:40,440 --> 00:17:44,520 Speaker 1: where if they had the ability to focus on fewer students, 353 00:17:44,560 --> 00:17:48,600 Speaker 1: they could see those students flourish much more effectively. And 354 00:17:48,640 --> 00:17:50,879 Speaker 1: when you're looking at things like class size. Where I 355 00:17:50,920 --> 00:17:53,919 Speaker 1: come from in Georgia, class size could get quite large, 356 00:17:54,080 --> 00:17:58,360 Speaker 1: even in primary school. So that's a very powerful use case. 357 00:17:58,400 --> 00:18:00,720 Speaker 4: But it's also a combination of technol you know, everyone 358 00:18:00,760 --> 00:18:02,600 Speaker 4: looks at say generative AI and say, oh, well, we 359 00:18:02,640 --> 00:18:06,639 Speaker 4: can train children and adults in new ways using it. Fundamentally, 360 00:18:06,680 --> 00:18:08,960 Speaker 4: you need the connectivity beneath it, sure, which is where 361 00:18:09,000 --> 00:18:12,840 Speaker 4: that general purpose connectivity actually really makes sense. I mean, 362 00:18:12,880 --> 00:18:15,320 Speaker 4: without that connectivity layer, you haven't got it right. 363 00:18:15,680 --> 00:18:16,720 Speaker 2: I just want to interject you. 364 00:18:16,760 --> 00:18:18,440 Speaker 3: It's just as we're thinking about this in the news 365 00:18:18,440 --> 00:18:21,080 Speaker 3: industry obviously, and we at the Wall Street Channel and 366 00:18:21,160 --> 00:18:23,800 Speaker 3: Da Jones have been using AI for decades now in 367 00:18:23,880 --> 00:18:27,119 Speaker 3: terms of, you know, uncovering data points within company announcements 368 00:18:27,160 --> 00:18:29,320 Speaker 3: and to analyze large amounts of data. 369 00:18:29,480 --> 00:18:31,480 Speaker 2: But I think we are cautious. 370 00:18:31,560 --> 00:18:35,160 Speaker 3: I would say that the work our journalists do is 371 00:18:35,400 --> 00:18:36,840 Speaker 3: deeply researched. 372 00:18:36,400 --> 00:18:37,760 Speaker 2: On a very human level. 373 00:18:38,520 --> 00:18:43,280 Speaker 3: And if we've got AI reading vast amounts of data 374 00:18:43,359 --> 00:18:46,720 Speaker 3: that we know isn't research to the same degree, We've 375 00:18:46,720 --> 00:18:49,760 Speaker 3: got to be very very careful in the kinds of 376 00:18:49,840 --> 00:18:52,480 Speaker 3: news that emerges over the next few years and decades, 377 00:18:52,560 --> 00:18:54,640 Speaker 3: right that actually the data en it's all about data 378 00:18:54,680 --> 00:18:56,639 Speaker 3: and data out as we all know, and that we 379 00:18:56,800 --> 00:19:00,280 Speaker 3: preserve the governance over that data end. One thing I 380 00:19:00,320 --> 00:19:03,800 Speaker 3: think that will be a continuing theme for the news 381 00:19:03,800 --> 00:19:07,159 Speaker 3: industry is how is AI reshaping our business and our 382 00:19:07,200 --> 00:19:09,240 Speaker 3: world and the kinds of news that people are reading, 383 00:19:09,280 --> 00:19:12,320 Speaker 3: because we know that young people are kind of pretty 384 00:19:12,359 --> 00:19:14,960 Speaker 3: platform agnostic on where their news comes from, and we've 385 00:19:14,960 --> 00:19:18,359 Speaker 3: got to make sure that we kind of reinforce those 386 00:19:18,640 --> 00:19:22,240 Speaker 3: standards of journalism. That makes journalism journalism, right, not something 387 00:19:22,280 --> 00:19:25,000 Speaker 3: that can be created by a machine. So just to 388 00:19:25,040 --> 00:19:27,240 Speaker 3: put the kind of like Devil's Advocate hats on this. 389 00:19:27,400 --> 00:19:30,720 Speaker 1: Oh, certainly. The other thing, Matt that you mentioned, and Philippa, 390 00:19:30,800 --> 00:19:33,760 Speaker 1: I'm sure you have insight on this as well, the 391 00:19:34,000 --> 00:19:37,199 Speaker 1: concept of connectivity being sort of that underlying foundation that 392 00:19:37,640 --> 00:19:42,000 Speaker 1: facilitates innovation in other ways. That's really what this show 393 00:19:42,080 --> 00:19:43,879 Speaker 1: is all about. I mean, we talk about that a 394 00:19:43,920 --> 00:19:48,000 Speaker 1: lot on the Restless Ones, about the idea of how 395 00:19:48,000 --> 00:19:51,560 Speaker 1: we're in a realm of connectivity that is enabling specifically 396 00:19:51,600 --> 00:19:55,399 Speaker 1: business solutions on a level that was impossible before. To me, 397 00:19:55,480 --> 00:19:58,560 Speaker 1: that's really exciting. And again it really boils down to 398 00:19:58,640 --> 00:20:02,800 Speaker 1: the fact that we we have this connectivity technology that 399 00:20:02,960 --> 00:20:03,919 Speaker 1: is enabling that. 400 00:20:04,400 --> 00:20:06,440 Speaker 3: Yeah, and I think we see that moving at such pace, 401 00:20:06,480 --> 00:20:07,679 Speaker 3: and I hope we'll come on to this and talk 402 00:20:07,720 --> 00:20:09,720 Speaker 3: about some of the awards that we've been looking at recently. 403 00:20:09,760 --> 00:20:15,560 Speaker 3: But connectivity empowering and facilitating a whole new ways of 404 00:20:15,600 --> 00:20:20,360 Speaker 3: working has been so game changing, so powerful, taking things 405 00:20:20,400 --> 00:20:23,080 Speaker 3: to places you would never have been able to previously 406 00:20:23,119 --> 00:20:25,080 Speaker 3: do things. I used to be a reporter in Africa 407 00:20:25,600 --> 00:20:28,960 Speaker 3: and where we were promised that it had excellent connectivity, 408 00:20:29,200 --> 00:20:32,200 Speaker 3: it really didn't. It was kind of like cables that 409 00:20:32,240 --> 00:20:34,000 Speaker 3: would get soaked by the rain, and it was all 410 00:20:34,000 --> 00:20:37,360 Speaker 3: powered by a hydroelectric dam that wasn't always working. And 411 00:20:37,680 --> 00:20:40,960 Speaker 3: you see when you're stripped of that connectivity how disabling 412 00:20:41,000 --> 00:20:43,359 Speaker 3: it is, even on a personal level, but at a 413 00:20:43,359 --> 00:20:45,320 Speaker 3: business level. And all of the things that we've come 414 00:20:45,320 --> 00:20:48,520 Speaker 3: to rely on now you're hamstrung, right if it's not there. 415 00:20:48,560 --> 00:20:51,240 Speaker 3: We kind of do take it for granted, and we 416 00:20:51,280 --> 00:20:53,520 Speaker 3: are ever more ambitious than what we want to do, 417 00:20:53,800 --> 00:20:56,320 Speaker 3: and we're ever more geographically dispersed in what we want 418 00:20:56,359 --> 00:20:56,640 Speaker 3: to do. 419 00:20:56,880 --> 00:20:57,760 Speaker 2: And you only have to have. 420 00:20:58,040 --> 00:21:00,560 Speaker 3: I mean, at the simplest level, WHI fi not working 421 00:21:00,600 --> 00:21:03,640 Speaker 3: at your hotel before you realize your own personal work, 422 00:21:03,680 --> 00:21:05,280 Speaker 3: worlds comes crumbling down. 423 00:21:05,440 --> 00:21:06,800 Speaker 2: So I think you know a lot of what we 424 00:21:06,880 --> 00:21:07,760 Speaker 2: all come on to talk about. 425 00:21:07,800 --> 00:21:11,080 Speaker 3: I hope you'll see the underpinnings of connectivity. Even in 426 00:21:11,160 --> 00:21:14,840 Speaker 3: one year, it has changed the way businesses are doing 427 00:21:14,880 --> 00:21:22,160 Speaker 3: so many things. 428 00:21:24,800 --> 00:21:26,520 Speaker 1: I think that's a great way for us to kind 429 00:21:26,560 --> 00:21:29,159 Speaker 1: of talk a little bit about the Unconventional Awards. You 430 00:21:29,200 --> 00:21:33,040 Speaker 1: both are judges for this year's Unconventional Awards, and there 431 00:21:33,080 --> 00:21:35,840 Speaker 1: are various categories that we wanted to chat about. 432 00:21:36,160 --> 00:21:38,800 Speaker 3: Yeah, so this is the second year of the Unconventional Awards. 433 00:21:38,840 --> 00:21:40,679 Speaker 3: We were both judges last year as well, and the 434 00:21:41,040 --> 00:21:44,879 Speaker 3: quality of the entries this year was astonishingly high. There 435 00:21:44,920 --> 00:21:47,800 Speaker 3: was a huge surgeon entries as well. So I think 436 00:21:47,840 --> 00:21:52,280 Speaker 3: that is testament to corporations and individuals within those corporations 437 00:21:52,320 --> 00:21:55,159 Speaker 3: really condoning onto You can make a real change, you 438 00:21:55,240 --> 00:21:58,000 Speaker 3: can be innovative. But what we were seeing was real 439 00:21:58,400 --> 00:22:01,639 Speaker 3: change happening at an organization and an industry level. 440 00:22:01,960 --> 00:22:04,480 Speaker 1: An area that we were looking at was innovation in 441 00:22:04,560 --> 00:22:06,760 Speaker 1: community and I was wondering if there was anything that 442 00:22:06,840 --> 00:22:07,720 Speaker 1: kind of stood out to you. 443 00:22:08,000 --> 00:22:09,960 Speaker 4: So there were so I mean, we had three in 444 00:22:10,080 --> 00:22:11,960 Speaker 4: sort of going in no particular order. We had the 445 00:22:12,000 --> 00:22:15,240 Speaker 4: City of Bellevue who were using five G and V 446 00:22:15,359 --> 00:22:18,439 Speaker 4: two X so vehicle to X technology to try to 447 00:22:18,440 --> 00:22:21,080 Speaker 4: reduce road traffic accidents, which when you have a look 448 00:22:21,080 --> 00:22:22,719 Speaker 4: at the number of people that are killed on American 449 00:22:22,840 --> 00:22:25,480 Speaker 4: roads basically every year, I mean, there's what eight hundred thousand. 450 00:22:25,800 --> 00:22:28,520 Speaker 4: We still don't see cars at driving themselves yet we're 451 00:22:28,560 --> 00:22:31,679 Speaker 4: at category three. Category five is probably still two to 452 00:22:31,720 --> 00:22:34,600 Speaker 4: three years away. But actually, for me, when you have 453 00:22:34,640 --> 00:22:36,280 Speaker 4: a look at the City of Bellevue, was really good 454 00:22:36,280 --> 00:22:39,040 Speaker 4: to see a city that was actually moving from how 455 00:22:39,080 --> 00:22:42,280 Speaker 4: do we connect vehicles and transportation and things that are 456 00:22:42,359 --> 00:22:45,719 Speaker 4: mobile basically to city infrastructure to do X, Y and 457 00:22:45,840 --> 00:22:48,400 Speaker 4: Z to how do we actually bring this really down 458 00:22:48,440 --> 00:22:53,040 Speaker 4: to the ground to actually reduce fatalities typically pedestrian fatalities. 459 00:22:53,480 --> 00:22:54,879 Speaker 5: So that one really stood out. 460 00:22:55,160 --> 00:22:58,280 Speaker 4: Then we've had the Hampton Valley Ford's volunteer Fire Department. 461 00:22:58,680 --> 00:23:01,679 Speaker 4: You have this really hard working volunteer fire department, and 462 00:23:01,720 --> 00:23:04,520 Speaker 4: they said, what we've done is we've used five G 463 00:23:04,880 --> 00:23:08,600 Speaker 4: to really improve the reliability and the speed by seeing 464 00:23:08,640 --> 00:23:11,840 Speaker 4: of our networks and our network services and our communications, 465 00:23:12,520 --> 00:23:14,240 Speaker 4: and when you have a look at what they do, 466 00:23:14,320 --> 00:23:18,560 Speaker 4: they see they're in life saving situations incredibly regularly. And 467 00:23:19,400 --> 00:23:23,800 Speaker 4: just by having access to reliable and fast communications networks 468 00:23:23,800 --> 00:23:26,080 Speaker 4: and systems and everything else means that on the one hand, 469 00:23:26,080 --> 00:23:29,720 Speaker 4: they can get situational intelligence faster. So what's going on, 470 00:23:29,880 --> 00:23:32,200 Speaker 4: what's happening, who's in the building, what part of the 471 00:23:32,240 --> 00:23:34,280 Speaker 4: buildings are catching fire, how do we deal with it? 472 00:23:34,320 --> 00:23:37,160 Speaker 4: So in the heat of battle, they've got more information 473 00:23:37,240 --> 00:23:40,840 Speaker 4: that they can use very quickly to expedite people from 474 00:23:40,840 --> 00:23:42,920 Speaker 4: a building or whatever happens to be. But the reason 475 00:23:42,920 --> 00:23:44,600 Speaker 4: bey why I sort of felt a little bit guilty 476 00:23:44,600 --> 00:23:46,800 Speaker 4: is because actually the fire services should. 477 00:23:46,520 --> 00:23:50,399 Speaker 5: Have reliable networks. Anyway. I sort of felt like, on 478 00:23:50,440 --> 00:23:52,480 Speaker 5: the one hand, you know, they've done very very well. 479 00:23:53,160 --> 00:23:56,639 Speaker 4: Also they're thinking you should just have this stuff as standard, right, 480 00:23:56,960 --> 00:23:58,840 Speaker 4: But they took the ball by the horns, they ran 481 00:23:58,880 --> 00:24:00,879 Speaker 4: with it. They actually sort of picked the ball up 482 00:24:00,920 --> 00:24:03,840 Speaker 4: by themselves, and they actually did this by themselves as well, 483 00:24:04,400 --> 00:24:06,720 Speaker 4: And I think that's where they deserve around for applause. 484 00:24:07,080 --> 00:24:08,560 Speaker 4: But then the other one that sort of stood out 485 00:24:08,600 --> 00:24:12,120 Speaker 4: to me was Chicago Public Schools. Now in the UK, 486 00:24:12,240 --> 00:24:14,320 Speaker 4: I do a lot of work basically with homeless charities 487 00:24:14,359 --> 00:24:18,480 Speaker 4: and communities. And in Chicago schools case, they have about 488 00:24:18,480 --> 00:24:21,359 Speaker 4: thirteen thousand students at any one time, and about a 489 00:24:21,440 --> 00:24:25,480 Speaker 4: thousand of those students really are a truant. But some 490 00:24:25,560 --> 00:24:27,800 Speaker 4: of the problems that those students have go much deeper 491 00:24:27,840 --> 00:24:29,720 Speaker 4: than that. You know, there's a lot of absenteers and 492 00:24:29,760 --> 00:24:34,560 Speaker 4: because the parents basically are shall we say, unfit or 493 00:24:34,680 --> 00:24:37,320 Speaker 4: unwell to manage sort of particular situations and so on 494 00:24:37,400 --> 00:24:40,800 Speaker 4: and so forth. And with the public schools district in Chicago, 495 00:24:41,560 --> 00:24:46,280 Speaker 4: they ended up providing laptops and connectivity to a thousand 496 00:24:46,320 --> 00:24:47,400 Speaker 4: students that are truant. 497 00:24:48,080 --> 00:24:49,240 Speaker 5: What it's doing is it. 498 00:24:49,160 --> 00:24:52,560 Speaker 4: Was enabling those people basically who were on the streets, 499 00:24:52,680 --> 00:24:56,240 Speaker 4: who had problems at home. It gave them a lifeline 500 00:24:56,280 --> 00:25:00,600 Speaker 4: into the Chicago Public schools community and seeing more than 501 00:25:00,600 --> 00:25:02,639 Speaker 4: actually going back to school, and when you have a 502 00:25:02,680 --> 00:25:06,480 Speaker 4: look at the importance of education on people's future lives, 503 00:25:07,160 --> 00:25:10,280 Speaker 4: it's life changing. So as an innovation, it might sound 504 00:25:10,320 --> 00:25:13,840 Speaker 4: fairly just straightforward, but actually it's probably one of the 505 00:25:13,880 --> 00:25:17,040 Speaker 4: most important kinds of innovation that we have because it 506 00:25:17,160 --> 00:25:20,959 Speaker 4: is changing people's lives as well as the lives of 507 00:25:21,000 --> 00:25:23,639 Speaker 4: any kids that they have. It's lifting them up in 508 00:25:23,680 --> 00:25:26,399 Speaker 4: a way basically that maybe a digital twin can't. 509 00:25:26,720 --> 00:25:28,720 Speaker 5: So this was obviously the Community. 510 00:25:28,240 --> 00:25:32,720 Speaker 4: Awards, but it was really good to see individuals within 511 00:25:32,760 --> 00:25:38,200 Speaker 4: the community identifying the problems to solve and then technology 512 00:25:38,440 --> 00:25:41,080 Speaker 4: is part of how they solved that, but obviously not 513 00:25:41,119 --> 00:25:43,440 Speaker 4: the whole picture, but it's part of how it was solved. 514 00:25:43,760 --> 00:25:45,760 Speaker 3: I think Matt makes excellent points there, and this is 515 00:25:45,840 --> 00:25:49,080 Speaker 3: a recurring common theme throughout these awards. A lot of 516 00:25:49,080 --> 00:25:51,720 Speaker 3: what we've seen with these awards has been and certainly 517 00:25:51,760 --> 00:25:54,120 Speaker 3: a big theme of last years was these are life 518 00:25:54,200 --> 00:25:57,320 Speaker 3: changing things that are happening. These are people who think, 519 00:25:57,440 --> 00:26:01,480 Speaker 3: how can we use connectivity to genuinely make the lives 520 00:26:01,560 --> 00:26:07,480 Speaker 3: better of you know, big recurring theme we see healthcare, cities, infrastructure, education, 521 00:26:08,000 --> 00:26:10,560 Speaker 3: and the digital divide, like so much of the digital divide, 522 00:26:10,560 --> 00:26:12,840 Speaker 3: which is so important and if we don't get that right, 523 00:26:12,920 --> 00:26:15,360 Speaker 3: what's the point because we're just kind of like creating 524 00:26:15,359 --> 00:26:16,160 Speaker 3: for creating's sake. 525 00:26:16,760 --> 00:26:21,360 Speaker 1: So innovation in employee enablement was one of the categories. 526 00:26:21,800 --> 00:26:25,080 Speaker 1: I was curious, Philip, was there any particular use case 527 00:26:25,080 --> 00:26:27,399 Speaker 1: that stood out to you as being particularly interesting in 528 00:26:27,400 --> 00:26:27,879 Speaker 1: that regard. 529 00:26:28,119 --> 00:26:30,720 Speaker 3: Yeah, one of the other entries we saw was Southland, 530 00:26:30,800 --> 00:26:34,200 Speaker 3: which is a construction firm. They had had huge growth 531 00:26:34,640 --> 00:26:38,040 Speaker 3: in their workforce and yet they couldn't tell when somebody 532 00:26:38,080 --> 00:26:40,920 Speaker 3: was injured on the job, and so they launched five 533 00:26:41,000 --> 00:26:44,160 Speaker 3: G enabled network to just figure out when they've gone 534 00:26:44,240 --> 00:26:46,520 Speaker 3: from a fifty to two hundred and fifty man team 535 00:26:46,560 --> 00:26:49,680 Speaker 3: to a two thousand man team or woman team, how 536 00:26:49,720 --> 00:26:51,760 Speaker 3: do you check people are checking in and checking out 537 00:26:51,760 --> 00:26:53,600 Speaker 3: a job so no one's got injured on that job. 538 00:26:53,720 --> 00:26:57,159 Speaker 3: Small thing, but it's how their business will survive. So 539 00:26:57,240 --> 00:26:58,639 Speaker 3: I just wanted to pick up on that point of 540 00:26:58,760 --> 00:27:00,879 Speaker 3: unconventional and we've I think we've always said this, we 541 00:27:00,880 --> 00:27:03,240 Speaker 3: don't want to see innovation for innovation's sake. We want 542 00:27:03,240 --> 00:27:05,119 Speaker 3: to see things that are actually moving the dial in 543 00:27:05,240 --> 00:27:07,480 Speaker 3: meaningful ways but also impact. 544 00:27:08,359 --> 00:27:11,280 Speaker 4: And I suppose by as judges, when we're actually evaluating 545 00:27:11,320 --> 00:27:13,879 Speaker 4: the entries that we have in one of the criteria 546 00:27:14,000 --> 00:27:17,119 Speaker 4: is impact. And when you have a look at the 547 00:27:17,280 --> 00:27:21,719 Speaker 4: impact that some of these initiatives actually have, in some 548 00:27:21,800 --> 00:27:25,280 Speaker 4: cases it's entire communities, it's staggering. I mean, you know, 549 00:27:25,359 --> 00:27:28,240 Speaker 4: what happens basically when you are able to use technology 550 00:27:28,320 --> 00:27:31,080 Speaker 4: to say level up, but actually to improve the lives 551 00:27:31,119 --> 00:27:34,359 Speaker 4: of an entire community. When we start feeding that through 552 00:27:34,359 --> 00:27:36,879 Speaker 4: to the local government perspective, you end up with people 553 00:27:36,920 --> 00:27:40,840 Speaker 4: being better educated, being able to get better jobs, getting richer, 554 00:27:40,880 --> 00:27:43,600 Speaker 4: which starts solving some of the wealth and poverty divides. 555 00:27:43,640 --> 00:27:46,160 Speaker 4: Basically that we actually see is they get better off. 556 00:27:46,200 --> 00:27:49,120 Speaker 4: They have access to better healthcare, better education, they've got 557 00:27:49,160 --> 00:27:51,199 Speaker 4: access to better food, you know, all these kinds of 558 00:27:51,200 --> 00:27:53,199 Speaker 4: different things. So when we actually have a look at 559 00:27:53,240 --> 00:27:56,840 Speaker 4: some of these entries basically from an impact perspective, certainly 560 00:27:56,840 --> 00:27:59,080 Speaker 4: one of the things I look at is how does 561 00:27:59,080 --> 00:28:04,040 Speaker 4: this fundamentally change somebody's future prospects? And then if you 562 00:28:04,160 --> 00:28:07,800 Speaker 4: change the prospects of one individual, they then start passing 563 00:28:07,840 --> 00:28:09,679 Speaker 4: it on as well. So when we have look at 564 00:28:09,720 --> 00:28:12,560 Speaker 4: Chicago public schools, for example, you haven't just got a 565 00:28:12,640 --> 00:28:15,480 Speaker 4: thousand children who are now being included in the community 566 00:28:15,480 --> 00:28:17,400 Speaker 4: in a new way to sort of lift them up. 567 00:28:17,920 --> 00:28:20,880 Speaker 4: But as they start getting older and older, no doubt 568 00:28:21,000 --> 00:28:23,720 Speaker 4: they will start passing that on to other people. So 569 00:28:23,800 --> 00:28:28,440 Speaker 4: now you have this massive network effect of people doing 570 00:28:28,560 --> 00:28:31,320 Speaker 4: good and say it, but it all stems really from 571 00:28:31,359 --> 00:28:35,520 Speaker 4: one or two individuals basically within an organization saying we've 572 00:28:35,520 --> 00:28:40,200 Speaker 4: got access to these tools and these support networks and 573 00:28:40,320 --> 00:28:43,080 Speaker 4: these resources. Should we do A or should we do B? 574 00:28:43,440 --> 00:28:45,920 Speaker 4: But actually then doing whatever that happens to be. 575 00:28:46,280 --> 00:28:46,400 Speaker 3: Now. 576 00:28:46,600 --> 00:28:50,440 Speaker 1: I love the insight into the judging process because I 577 00:28:50,520 --> 00:28:55,600 Speaker 1: often find myself guilty of focusing in on the micro 578 00:28:55,840 --> 00:28:58,080 Speaker 1: of an element and I have to remind myself to 579 00:28:58,120 --> 00:28:59,720 Speaker 1: step back and look at bigger pictures. 580 00:28:59,760 --> 00:29:02,200 Speaker 2: Yea, And the judging process is pretty robust, right. 581 00:29:02,240 --> 00:29:03,720 Speaker 3: We get into like a lot of debate and it 582 00:29:03,720 --> 00:29:05,520 Speaker 3: takes quite a while to get it when we do that. 583 00:29:05,520 --> 00:29:07,320 Speaker 2: Call, so like okay, who's the winner here? 584 00:29:07,920 --> 00:29:10,240 Speaker 3: And we all obviously have very different perspectives, but we 585 00:29:10,320 --> 00:29:12,520 Speaker 3: all kind of a guided by that principle of like 586 00:29:12,840 --> 00:29:15,200 Speaker 3: does it change lives at scale? 587 00:29:15,400 --> 00:29:17,000 Speaker 2: And is it a case study that can be used 588 00:29:17,040 --> 00:29:17,680 Speaker 2: at scale as well? 589 00:29:17,720 --> 00:29:20,320 Speaker 3: I think that that's so important is like does this 590 00:29:20,600 --> 00:29:24,160 Speaker 3: just work for this corporation or this industry or can 591 00:29:24,200 --> 00:29:27,080 Speaker 3: you scale it? Is it something that by being called out, 592 00:29:27,120 --> 00:29:29,640 Speaker 3: you've got other folks saying okay, we could use that. 593 00:29:29,840 --> 00:29:32,040 Speaker 3: You know, there's going to be other Vauntry fire services 594 00:29:32,080 --> 00:29:33,440 Speaker 3: that go, we could do that. 595 00:29:33,800 --> 00:29:36,320 Speaker 2: This is how we change the way we do our work. 596 00:29:36,440 --> 00:29:38,720 Speaker 3: So yeah, just to sort of give you a little 597 00:29:38,720 --> 00:29:41,080 Speaker 3: bit of extra insight there on that judging process and 598 00:29:41,120 --> 00:29:44,120 Speaker 3: how it all comes together and the underpinnings of it, 599 00:29:44,160 --> 00:29:46,000 Speaker 3: which is that it's going to be changing things and 600 00:29:46,000 --> 00:29:47,960 Speaker 3: potential to change things at huge scale. 601 00:29:48,040 --> 00:29:50,240 Speaker 4: But also, you know, to Philip's point, when we first 602 00:29:50,280 --> 00:29:52,160 Speaker 4: set about with the awards, one of the things that 603 00:29:52,200 --> 00:29:54,760 Speaker 4: we were actually thinking of is on the one hand, 604 00:29:54,840 --> 00:29:58,920 Speaker 4: we need to raise up and promote the good innovations, 605 00:29:58,960 --> 00:30:02,600 Speaker 4: say the good initial but actually by putting some of 606 00:30:02,640 --> 00:30:06,320 Speaker 4: these organizations on a pedestal quite rightly, like the Hampton 607 00:30:06,400 --> 00:30:09,760 Speaker 4: Valley Forge Volunteer Fire Department, it actually means that people 608 00:30:10,040 --> 00:30:13,360 Speaker 4: in other departments around the US can say, actually, if 609 00:30:13,360 --> 00:30:17,000 Speaker 4: they did it, we can do it. But also it 610 00:30:17,120 --> 00:30:19,640 Speaker 4: now means that these people could technically phone them up 611 00:30:19,680 --> 00:30:22,600 Speaker 4: and say, we've heard that you did this, what were 612 00:30:22,600 --> 00:30:24,920 Speaker 4: the benefits, what were the results? How did you do it? 613 00:30:25,200 --> 00:30:28,320 Speaker 4: So now but you have one innovation. It's essentially, you know, 614 00:30:28,520 --> 00:30:31,080 Speaker 4: using an analogy, the fire department can kind of hold 615 00:30:31,080 --> 00:30:34,520 Speaker 4: the tork job and then once they've actually completed these initiatives. 616 00:30:34,560 --> 00:30:36,200 Speaker 4: They can pass that torch on and say, right now, 617 00:30:36,200 --> 00:30:39,480 Speaker 4: it's your turn to use this to do X, Y 618 00:30:39,520 --> 00:30:42,000 Speaker 4: and z, to get better outcomes on whatever it happens to. 619 00:30:41,960 --> 00:30:44,960 Speaker 5: Be, to save more lives. So it's that ripple effect. 620 00:30:45,080 --> 00:30:47,920 Speaker 1: I like the torch analogy. I will remind you that 621 00:30:47,960 --> 00:30:49,760 Speaker 1: the firefighters are meant to put them out. 622 00:30:49,880 --> 00:30:53,200 Speaker 5: Well I didn't say it was lit, you know, that's it. 623 00:30:53,080 --> 00:30:55,400 Speaker 1: And you could be talking about a flashlight, which. 624 00:30:55,240 --> 00:30:58,080 Speaker 5: Is exactly yeah, that's it. Maybe that's the modern equivalent. 625 00:30:58,720 --> 00:31:02,160 Speaker 1: Well, we have two moregories of unconventional awards to kind 626 00:31:02,200 --> 00:31:04,760 Speaker 1: of chat about. The next one up is the innovation 627 00:31:04,840 --> 00:31:08,040 Speaker 1: and Customer Experience. I'm curious if there were any standouts 628 00:31:08,080 --> 00:31:09,280 Speaker 1: in that category as well. 629 00:31:09,600 --> 00:31:12,160 Speaker 5: So for me, actually Emphasis really stood up. 630 00:31:12,240 --> 00:31:15,520 Speaker 4: Now again this might sound slightly strange, but what Emphasis 631 00:31:15,520 --> 00:31:18,560 Speaker 4: were doing was they were using five G combined with 632 00:31:18,640 --> 00:31:22,920 Speaker 4: artificial intelligence to help improve tennis players play, improve their 633 00:31:22,920 --> 00:31:24,360 Speaker 4: form and everything else. So what they were doing is 634 00:31:24,360 --> 00:31:28,720 Speaker 4: they were using things like cameras, artificial intelligence, and biometrics 635 00:31:28,760 --> 00:31:33,960 Speaker 4: to automatically monitor a tennis player's form and then feedback 636 00:31:33,960 --> 00:31:34,760 Speaker 4: to that tennis player. 637 00:31:34,840 --> 00:31:36,280 Speaker 5: Say, if you did this, basically. 638 00:31:36,040 --> 00:31:39,120 Speaker 4: You'd actually be faster, you'd improve your scores, et cetera, 639 00:31:39,160 --> 00:31:41,280 Speaker 4: et cetera. Now again, you know, this is sort of 640 00:31:41,280 --> 00:31:42,720 Speaker 4: one of as on the surface, you look at it 641 00:31:42,760 --> 00:31:45,960 Speaker 4: and you think, okay, it's just applies to tennis players. However, 642 00:31:46,080 --> 00:31:48,080 Speaker 4: the way they actually created it means that it could 643 00:31:48,080 --> 00:31:50,400 Speaker 4: actually be scaled out to little. 644 00:31:50,200 --> 00:31:51,600 Speaker 5: Leagues everywhere and everything else. 645 00:31:51,640 --> 00:31:53,720 Speaker 4: It can be applied basically not just to tennis, but 646 00:31:53,800 --> 00:31:56,520 Speaker 4: to every single sport out there. And when we actually 647 00:31:56,560 --> 00:31:58,040 Speaker 4: have a look at the impact of these sort of 648 00:31:58,120 --> 00:32:01,320 Speaker 4: technologies on health and wellness, being able to, for example, 649 00:32:01,360 --> 00:32:05,880 Speaker 4: start putting equipment alongside an athletics track, where that equipment 650 00:32:05,960 --> 00:32:08,680 Speaker 4: now monitors how someone is running, and you can say, well, 651 00:32:08,680 --> 00:32:12,000 Speaker 4: actually you're running slightly skewed with your gate is slightly off, 652 00:32:12,000 --> 00:32:14,440 Speaker 4: which means your hips going to be out and you're 653 00:32:14,480 --> 00:32:15,200 Speaker 4: going to end up with. 654 00:32:15,120 --> 00:32:15,760 Speaker 5: A bad back. 655 00:32:15,800 --> 00:32:19,400 Speaker 4: So if you start adjusting your running posture to this, 656 00:32:19,960 --> 00:32:22,200 Speaker 4: you can not only get faster, but you can avoid injury. 657 00:32:22,680 --> 00:32:24,840 Speaker 4: Is actually important, and especially you know, when we have 658 00:32:24,880 --> 00:32:26,760 Speaker 4: a look at the importance of health and wellness in 659 00:32:26,760 --> 00:32:30,000 Speaker 4: today's society, we could have a podcast on that alone. 660 00:32:30,040 --> 00:32:32,880 Speaker 1: Sure, yeah, it's very similar to their education status too, 661 00:32:32,920 --> 00:32:37,040 Speaker 1: where you're talking about using technology to give personalized health 662 00:32:37,080 --> 00:32:41,880 Speaker 1: and wellness information to the individual. Well, that's a fantastic example. 663 00:32:41,920 --> 00:32:43,960 Speaker 1: And then our last one, of course, is the innovation 664 00:32:44,080 --> 00:32:47,200 Speaker 1: in industry. Philippa Lee, you wanted to have a talk 665 00:32:47,240 --> 00:32:47,720 Speaker 1: about that. 666 00:32:47,960 --> 00:32:51,000 Speaker 3: This was such a strong category. We saw some amazing 667 00:32:51,280 --> 00:32:53,960 Speaker 3: endeavors here. One that I would call out in particular 668 00:32:53,960 --> 00:32:57,240 Speaker 3: as bosson Children's Hospital. So this is an absolute clinical 669 00:32:57,320 --> 00:33:01,600 Speaker 3: leader in pediatric care, recognize global leader doing some of 670 00:33:01,600 --> 00:33:04,360 Speaker 3: the most important work in the industry. However, the hospital's 671 00:33:04,400 --> 00:33:08,120 Speaker 3: Wi Fi network was causing significant challenges. So you are 672 00:33:08,160 --> 00:33:09,880 Speaker 3: trying to take care of your patients and you can 673 00:33:09,960 --> 00:33:14,000 Speaker 3: only enter their clinical information in a fixed desktop in 674 00:33:14,040 --> 00:33:17,719 Speaker 3: the patient's room. Clinicians want to be able to connect 675 00:33:17,720 --> 00:33:20,000 Speaker 3: with each other, use their mobile devices, connect their own 676 00:33:20,040 --> 00:33:23,160 Speaker 3: devices into the hospital network, and so that's what they did. 677 00:33:23,240 --> 00:33:26,280 Speaker 3: They implemented gain using t mobile technology. They put in 678 00:33:26,320 --> 00:33:29,560 Speaker 3: a layer of connectivity that meant they were now able 679 00:33:29,600 --> 00:33:32,800 Speaker 3: to enter clinical information on the fly. They were able 680 00:33:32,840 --> 00:33:34,560 Speaker 3: to connect with more kind of like bring your own 681 00:33:34,560 --> 00:33:38,720 Speaker 3: devices and really make a game changing impact on the 682 00:33:38,720 --> 00:33:41,280 Speaker 3: way they were caring for their patients. And also recording 683 00:33:41,360 --> 00:33:44,960 Speaker 3: data and that again, now we have a case study 684 00:33:45,000 --> 00:33:47,400 Speaker 3: that can be rolled out at scale to other hospitals, 685 00:33:47,440 --> 00:33:49,640 Speaker 3: which we kind of know a lot of these hospitals 686 00:33:49,720 --> 00:33:54,160 Speaker 3: are based on this kind of legacy it infrastructure that 687 00:33:54,320 --> 00:33:57,040 Speaker 3: is holding a lot of clinical work back. You've got 688 00:33:57,080 --> 00:34:00,120 Speaker 3: the real talent and the real science and our d 689 00:34:00,320 --> 00:34:03,040 Speaker 3: happening at that clinical level, and the technology is holding 690 00:34:03,040 --> 00:34:05,240 Speaker 3: them back. So Boston Children's Hostile is one that I 691 00:34:05,240 --> 00:34:07,720 Speaker 3: would really call out there as something that is again 692 00:34:07,880 --> 00:34:10,080 Speaker 3: changing lives at a kind of life or death level. 693 00:34:10,200 --> 00:34:13,600 Speaker 1: And a huge challenge as well from a technological standpoint, 694 00:34:13,640 --> 00:34:17,799 Speaker 1: because you're talking specifically about healthcare. Obviously you're type of 695 00:34:17,920 --> 00:34:20,279 Speaker 1: very sensitive information as the security, right, I think, so 696 00:34:20,760 --> 00:34:23,239 Speaker 1: designing your system so that you have this ability to 697 00:34:23,239 --> 00:34:27,319 Speaker 1: connect in and have that interconnectivity while also ensuring that 698 00:34:27,400 --> 00:34:30,080 Speaker 1: safety it is not a trivial matter. So I see 699 00:34:30,080 --> 00:34:34,080 Speaker 1: how that's a huge endeavor. And to see an organization 700 00:34:35,000 --> 00:34:37,840 Speaker 1: go through and start to idate and solve those problems 701 00:34:38,160 --> 00:34:41,120 Speaker 1: that can then be ported to other organizations. 702 00:34:40,840 --> 00:34:43,840 Speaker 4: Well, it is it's like this osmosis effect. You know, 703 00:34:43,960 --> 00:34:47,280 Speaker 4: something happens basically within one organization and all the benefits 704 00:34:47,280 --> 00:34:50,480 Speaker 4: start leaking out all the other organizations in the ecosystem, 705 00:34:50,480 --> 00:34:51,560 Speaker 4: in the industry. 706 00:34:51,160 --> 00:34:53,799 Speaker 5: Whatever it happens to be. And I think bas with 707 00:34:53,800 --> 00:34:54,640 Speaker 5: all of the. 708 00:34:54,400 --> 00:34:57,279 Speaker 4: Awards that we've actually awarded, all of the innovations and 709 00:34:57,320 --> 00:35:00,280 Speaker 4: initiatives we actually looked at. When you actually really starts 710 00:35:00,320 --> 00:35:05,000 Speaker 4: scaling this up, the improvement to people's lives is staggering. 711 00:35:05,160 --> 00:35:07,719 Speaker 4: But then also you know, impacts on the environment from 712 00:35:07,760 --> 00:35:11,120 Speaker 4: the sustainability perspective. I applaud everybody that actually put their 713 00:35:11,160 --> 00:35:16,200 Speaker 4: ideas forward because they all made a massive herculean effort 714 00:35:16,400 --> 00:35:19,000 Speaker 4: not just to do something, but to actually implement it 715 00:35:19,320 --> 00:35:20,439 Speaker 4: and really carry through. 716 00:35:20,600 --> 00:35:23,040 Speaker 3: Yeah. Look, these are important towards I think because it 717 00:35:23,160 --> 00:35:27,239 Speaker 3: just shows possibility. It really helps drive that knowledge and 718 00:35:27,280 --> 00:35:30,080 Speaker 3: awareness of what's being done at this sort of innovative 719 00:35:30,120 --> 00:35:32,759 Speaker 3: level and shows that like you put something in a 720 00:35:32,800 --> 00:35:35,840 Speaker 3: soundbox and real change can happen, the possible. 721 00:35:36,440 --> 00:35:38,799 Speaker 1: So before I can let you go, I do have 722 00:35:38,840 --> 00:35:41,279 Speaker 1: to ask you one more thing. It is just the 723 00:35:41,320 --> 00:35:44,200 Speaker 1: simple question, and Philippa, I'll start with you. Our show 724 00:35:44,280 --> 00:35:48,160 Speaker 1: is called The Restless Ones. So what does restless mean 725 00:35:48,239 --> 00:35:48,560 Speaker 1: to you? 726 00:35:49,320 --> 00:35:53,080 Speaker 3: I think it is do not be afraid of calling 727 00:35:53,120 --> 00:35:54,839 Speaker 3: things out when you think that something can be done 728 00:35:54,840 --> 00:35:58,279 Speaker 3: better right and making the change that will actually have 729 00:35:58,360 --> 00:36:01,480 Speaker 3: this sort of far reaching effect. Think through the long 730 00:36:01,600 --> 00:36:04,440 Speaker 3: term consequences. Is this idea actually going to change the 731 00:36:04,480 --> 00:36:08,360 Speaker 3: course of our company, of lives, of society, of news 732 00:36:08,440 --> 00:36:11,120 Speaker 3: or whatever it might be? Right, Because you've got to 733 00:36:11,160 --> 00:36:14,759 Speaker 3: have that long term view. You've got to have good governance, 734 00:36:15,000 --> 00:36:17,800 Speaker 3: whether that's at an individual level or like the people 735 00:36:17,800 --> 00:36:20,040 Speaker 3: you're bringing along with you, and you've got to think 736 00:36:20,040 --> 00:36:22,879 Speaker 3: through the unintended consequences. But I think if you keep 737 00:36:22,920 --> 00:36:25,879 Speaker 3: that long term view and you are restless and curious, 738 00:36:26,360 --> 00:36:29,960 Speaker 3: and you think about the wider impact of what you're doing, 739 00:36:30,320 --> 00:36:31,920 Speaker 3: that will make your idea successful. 740 00:36:32,200 --> 00:36:34,759 Speaker 4: That's a great answer, Matt for me, by Sally being 741 00:36:34,840 --> 00:36:37,399 Speaker 4: restless is all about never stopping to try to find 742 00:36:37,440 --> 00:36:41,120 Speaker 4: problems and never stopping to try and find solutions. And 743 00:36:41,120 --> 00:36:43,080 Speaker 4: that's exactly by say what a lot of the people 744 00:36:43,080 --> 00:36:45,879 Speaker 4: who've entered have actually done. They've looked for problems, they've 745 00:36:45,920 --> 00:36:48,480 Speaker 4: looked for solutions. Generally they've found solutions. 746 00:36:48,880 --> 00:36:51,040 Speaker 1: Carry On, a lot of the people I've had on 747 00:36:51,080 --> 00:36:54,160 Speaker 1: the show, their background is an engineering and I love 748 00:36:54,440 --> 00:36:57,759 Speaker 1: talking to engineers because they just see the world as 749 00:36:57,800 --> 00:37:00,680 Speaker 1: a series of problems waiting to be solved, and they're 750 00:37:00,719 --> 00:37:02,600 Speaker 1: constantly thinking of the solutions. 751 00:37:02,760 --> 00:37:04,960 Speaker 3: Yeah, Barack Obama has a great line on that, right 752 00:37:04,960 --> 00:37:07,240 Speaker 3: he Because there are like hundreds people in your organization, 753 00:37:07,320 --> 00:37:09,520 Speaker 3: you will find the problems and it's then ages diagnosing 754 00:37:09,560 --> 00:37:12,040 Speaker 3: the problems to people who fix the problems are the 755 00:37:12,080 --> 00:37:13,719 Speaker 3: ones that you want to hang on to. And I 756 00:37:13,760 --> 00:37:15,600 Speaker 3: think that that is a lot of being restless, is 757 00:37:15,600 --> 00:37:17,680 Speaker 3: spotting something and then going and fixing it. 758 00:37:18,160 --> 00:37:22,040 Speaker 1: Fantastic, Philip and Matt, thank you for joining the Restless Ones. 759 00:37:22,120 --> 00:37:23,759 Speaker 1: This has been a great conversation. 760 00:37:24,040 --> 00:37:25,000 Speaker 2: Thank you for having us. 761 00:37:30,239 --> 00:37:33,000 Speaker 1: Thanks again to Philippa Layton Jones and Matt Griffin for 762 00:37:33,080 --> 00:37:36,200 Speaker 1: joining me on the Restless Ones. I'm so glad we 763 00:37:36,200 --> 00:37:39,240 Speaker 1: were able to sit down and talk about technology's capacity 764 00:37:39,320 --> 00:37:44,040 Speaker 1: to make real substantial change in business, in communities, and 765 00:37:44,080 --> 00:37:47,240 Speaker 1: in people's lives. And it was also good to remind 766 00:37:47,239 --> 00:37:50,399 Speaker 1: ourselves that it's beneficial sometimes to step back and ask 767 00:37:50,560 --> 00:37:53,920 Speaker 1: really big questions and to consider all the possibilities and 768 00:37:53,960 --> 00:37:57,759 Speaker 1: potential consequences of our decisions, the stuff that you know 769 00:37:57,840 --> 00:38:01,319 Speaker 1: leaders do every single day. There's a lot going on 770 00:38:01,400 --> 00:38:04,880 Speaker 1: this year at Mobile World Congress. The use cases that 771 00:38:04,920 --> 00:38:07,600 Speaker 1: we talk about are just a small slice of the 772 00:38:07,600 --> 00:38:10,600 Speaker 1: innovation going on all over the world, all made possible 773 00:38:10,640 --> 00:38:14,359 Speaker 1: by connectivity. And while we've been having some conversations about 774 00:38:14,400 --> 00:38:17,400 Speaker 1: business and technology for four seasons on The Restless Ones, 775 00:38:17,840 --> 00:38:20,520 Speaker 1: I can't help but think that we're just on the 776 00:38:20,560 --> 00:38:25,160 Speaker 1: precipice of an astonishing future where we see potential become reality. 777 00:38:29,719 --> 00:38:32,399 Speaker 1: Thanks for listening to The Restless Ones. We've got more 778 00:38:32,400 --> 00:38:35,680 Speaker 1: than fifty episodes focusing on business leaders and tech in 779 00:38:35,719 --> 00:38:38,359 Speaker 1: the archives, so be sure to check those out and 780 00:38:38,480 --> 00:38:41,320 Speaker 1: tune in for more conversations this season about how leaders 781 00:38:41,400 --> 00:38:46,040 Speaker 1: are leveraging tech to create amazing new opportunities. Until next time, 782 00:38:46,239 --> 00:38:48,840 Speaker 1: I'm Jonathan Strickland.