1 00:00:01,480 --> 00:00:04,440 Speaker 1: Quite a lot of the technology used somewhere else, whether 2 00:00:04,640 --> 00:00:10,480 Speaker 1: it's hardware, sensors, WiFi, network to software, AI, all those things. 3 00:00:11,640 --> 00:00:16,120 Speaker 1: By using them right, this can transform how people live 4 00:00:16,160 --> 00:00:19,200 Speaker 1: at home. Lifestyle tech maybe is the right terminology for it. 5 00:00:19,560 --> 00:00:23,239 Speaker 1: I think that's the emerging area that I'm interested in pushing, 6 00:00:23,360 --> 00:00:25,639 Speaker 1: and I think it's gonna be you really excited for 7 00:00:25,680 --> 00:00:30,280 Speaker 1: the next couple of decades. Welcome to the Restless Ones. 8 00:00:30,560 --> 00:00:34,040 Speaker 1: I'm Jonathan Strickland. I've spent more than a decade really 9 00:00:34,120 --> 00:00:37,960 Speaker 1: learning about technology, what makes it tech, and then describing 10 00:00:37,960 --> 00:00:41,240 Speaker 1: and explaining that to my audience. But it's the conversations 11 00:00:41,280 --> 00:00:44,760 Speaker 1: with the world's most unconventional thinkers, the leaders at the 12 00:00:44,760 --> 00:00:48,160 Speaker 1: intersection of technology and business, that fascinate me the most. 13 00:00:48,640 --> 00:00:51,440 Speaker 1: In partnership with T Mobile for Business, I explore the 14 00:00:51,520 --> 00:00:53,760 Speaker 1: unique set of challenges that C T o s and 15 00:00:53,880 --> 00:00:56,800 Speaker 1: c I O s and other tech executives face from 16 00:00:56,840 --> 00:01:00,480 Speaker 1: advancements in cloud and edge computing, software is a service, 17 00:01:00,760 --> 00:01:04,959 Speaker 1: Internet of Things, and of course five G. We are 18 00:01:04,959 --> 00:01:08,480 Speaker 1: often left wondering how the leading minds in business continue 19 00:01:08,520 --> 00:01:15,520 Speaker 1: to thrive. Let's find out. Our guest today is Dr 20 00:01:15,600 --> 00:01:20,040 Speaker 1: Yoki Matsuoka, founder of the Johanna startup under Pana Sonic. 21 00:01:20,880 --> 00:01:25,759 Speaker 1: As you'll learn, Yoki has had an incredible career in technology, 22 00:01:26,000 --> 00:01:29,840 Speaker 1: and even her journey to choosing to study electrical engineering 23 00:01:29,840 --> 00:01:32,920 Speaker 1: and computer science began because her plans to become a 24 00:01:32,959 --> 00:01:37,440 Speaker 1: professional athlete didn't pan out. Yoki has dedicated her efforts 25 00:01:37,640 --> 00:01:42,200 Speaker 1: towards finding ways to benefit others directly using technology as 26 00:01:42,200 --> 00:01:46,240 Speaker 1: a facilitator. The focus isn't on the tech itself, but 27 00:01:46,560 --> 00:01:50,880 Speaker 1: how we can leverage tech to improve our lives. Yoki's 28 00:01:50,920 --> 00:01:54,160 Speaker 1: passion for helping others reminds me of another guest we've 29 00:01:54,160 --> 00:01:57,560 Speaker 1: had on the show, Mr Marty Paslick, ce IO of 30 00:01:57,720 --> 00:02:01,320 Speaker 1: h c A healthcare and are really inc This episode 31 00:02:01,600 --> 00:02:05,480 Speaker 1: is an interesting contrast to that one, as Yoki's approach 32 00:02:05,640 --> 00:02:09,280 Speaker 1: has frequently focused on ways to reach out to consumers directly, 33 00:02:09,600 --> 00:02:12,960 Speaker 1: while Marty's role is to enable a healthcare company to 34 00:02:13,040 --> 00:02:16,640 Speaker 1: serve the needs of patients. With Yoki, I wanted to 35 00:02:16,639 --> 00:02:20,960 Speaker 1: talk about her perspective and more importantly, what motivated her 36 00:02:21,040 --> 00:02:26,920 Speaker 1: to found a new startup in the healthcare and lifestyle space. Yoki, 37 00:02:27,080 --> 00:02:30,280 Speaker 1: thank you so much for joining us. I really appreciate 38 00:02:30,320 --> 00:02:32,840 Speaker 1: it and it's a genuine pleasure to get to speak 39 00:02:32,840 --> 00:02:36,040 Speaker 1: with you today. Oh, likewise, I've been very excited about this. 40 00:02:36,360 --> 00:02:38,840 Speaker 1: Thanks for the opportunity, And I always like to begin 41 00:02:38,960 --> 00:02:42,360 Speaker 1: any interview by learning more about the background of the 42 00:02:42,360 --> 00:02:45,400 Speaker 1: person I'm speaking with. So can you tell me about 43 00:02:45,639 --> 00:02:49,360 Speaker 1: when did you start getting interested in technology. I was 44 00:02:49,680 --> 00:02:53,120 Speaker 1: a late bloomer. I grew up in Japan. I moved 45 00:02:53,120 --> 00:02:55,280 Speaker 1: to the US thinking that I was going to become 46 00:02:55,280 --> 00:02:59,440 Speaker 1: a professional tennis player, so technology was not something that 47 00:02:59,560 --> 00:03:02,880 Speaker 1: was in my mind. I went to college again thinking 48 00:03:02,919 --> 00:03:04,840 Speaker 1: that I was going to be a professional tennis player, 49 00:03:05,240 --> 00:03:08,040 Speaker 1: and when that didn't work out, I started to think 50 00:03:08,080 --> 00:03:10,720 Speaker 1: about what else I can do, And that was almost 51 00:03:11,320 --> 00:03:14,400 Speaker 1: the first time I really thought technology could be in 52 00:03:14,480 --> 00:03:18,359 Speaker 1: my future. Oh, so you were literally at a crossroads. 53 00:03:18,440 --> 00:03:22,000 Speaker 1: Can you talk about how you explored your different opportunities 54 00:03:22,000 --> 00:03:26,000 Speaker 1: and what was it that had you gravitate towards electrical 55 00:03:26,080 --> 00:03:31,119 Speaker 1: engineering and computer science. Yeah. So, because all I knew 56 00:03:31,120 --> 00:03:35,680 Speaker 1: in my life really was tennis, what I, you know, realized, 57 00:03:35,680 --> 00:03:38,640 Speaker 1: is that, boy, if I want to do something interesting 58 00:03:38,680 --> 00:03:42,040 Speaker 1: with my life that doesn't involve me playing tennis, what 59 00:03:42,120 --> 00:03:44,880 Speaker 1: could it be. The first thing I thought about was 60 00:03:45,120 --> 00:03:47,960 Speaker 1: a tennis buddy robot that I could play tennis with 61 00:03:48,320 --> 00:03:50,520 Speaker 1: all my life. I started to read a little bit 62 00:03:50,520 --> 00:03:53,680 Speaker 1: of research and I realized that maybe I can build this. 63 00:03:54,600 --> 00:03:57,560 Speaker 1: As I thought about getting into robotics from that angle, 64 00:03:57,760 --> 00:04:00,920 Speaker 1: I explored different kinds of engineering. Luckily, I've always liked 65 00:04:01,160 --> 00:04:03,920 Speaker 1: science and math, and I was very fortunate to really 66 00:04:03,960 --> 00:04:06,720 Speaker 1: be able to pursue it further. But at the end 67 00:04:06,760 --> 00:04:08,920 Speaker 1: of the day, around then, when I was in college, 68 00:04:09,400 --> 00:04:13,000 Speaker 1: electrical engineering was a little bit of the future. It 69 00:04:13,120 --> 00:04:15,400 Speaker 1: felt like this was the thing that if I had 70 00:04:15,400 --> 00:04:18,440 Speaker 1: the right knowledge, it would really push me forward. Um, 71 00:04:18,480 --> 00:04:20,240 Speaker 1: I'll speak out a little bit. There's a thing of 72 00:04:20,360 --> 00:04:23,920 Speaker 1: control theory, which was a lot of math, but I 73 00:04:23,960 --> 00:04:26,480 Speaker 1: loved it. So I'm like, Okay, whatever allows me to 74 00:04:26,520 --> 00:04:28,400 Speaker 1: get deeper in control theory, I want to measure in that. 75 00:04:28,520 --> 00:04:30,440 Speaker 1: And then that's how I ended up doing electrical engineering. 76 00:04:30,839 --> 00:04:33,600 Speaker 1: I think what I realized is that I love problem solving. 77 00:04:34,080 --> 00:04:36,560 Speaker 1: I love looking at problems, and I never wanted to 78 00:04:36,600 --> 00:04:38,400 Speaker 1: give up and I wanted to continue to solve it. 79 00:04:38,480 --> 00:04:41,080 Speaker 1: And then turns out the best way to go about 80 00:04:41,120 --> 00:04:43,720 Speaker 1: it is to, you know, do it through engineering. Well, 81 00:04:43,800 --> 00:04:46,400 Speaker 1: can you talk a little bit about what your path 82 00:04:46,560 --> 00:04:49,480 Speaker 1: was once your degree was complete, I mean you went 83 00:04:49,480 --> 00:04:52,880 Speaker 1: on to pursue post graduate studies and earn a PhD. 84 00:04:53,600 --> 00:04:57,440 Speaker 1: What happened along that pathway? Yeah. So when I was 85 00:04:57,440 --> 00:05:00,760 Speaker 1: an undergraduate at Berkeley, I was fortunate enough to have 86 00:05:00,960 --> 00:05:05,160 Speaker 1: professors who took me on to build robots. I learned 87 00:05:05,320 --> 00:05:08,720 Speaker 1: a lot. I wanted to continue with robotics, so I 88 00:05:08,760 --> 00:05:12,000 Speaker 1: applied to graduate schools, thinking that, yes, I will keep going. 89 00:05:12,040 --> 00:05:14,720 Speaker 1: I still want to build my tennis robot. That led 90 00:05:14,720 --> 00:05:16,640 Speaker 1: me to m I t That led me to a 91 00:05:16,680 --> 00:05:21,120 Speaker 1: group led by Professor Rodney Brooks, who was building a 92 00:05:21,200 --> 00:05:24,680 Speaker 1: humanoid robot. So I thought, perfect, I want to be 93 00:05:24,720 --> 00:05:27,160 Speaker 1: on that team, and I will make sure I has 94 00:05:27,360 --> 00:05:30,400 Speaker 1: arms and hands and legs and I could play tennis. 95 00:05:30,440 --> 00:05:33,840 Speaker 1: So that was really the beginning of my graduate school journey. 96 00:05:34,040 --> 00:05:37,320 Speaker 1: I love that tennis has become a through line for this. 97 00:05:37,680 --> 00:05:41,200 Speaker 1: That's fantastic. Then you went on and took a position 98 00:05:41,320 --> 00:05:46,039 Speaker 1: as a professor. Correct. So as as I got into robotics, 99 00:05:46,279 --> 00:05:50,120 Speaker 1: I've got fascinated with arms and hands again, still connected 100 00:05:50,120 --> 00:05:53,920 Speaker 1: to tennis. Then I, you know, machine everything, all the parts. 101 00:05:53,920 --> 00:05:57,320 Speaker 1: I built everything, and then I put you know, coating 102 00:05:57,360 --> 00:05:59,599 Speaker 1: on top and I put machine learning on top and 103 00:06:00,000 --> 00:06:03,200 Speaker 1: I and all of those things. Then I felt, why 104 00:06:03,240 --> 00:06:05,880 Speaker 1: isn't it playing tennis with me yet? And it was 105 00:06:06,040 --> 00:06:08,880 Speaker 1: nowhere near it. It could barely pick up objects in 106 00:06:09,200 --> 00:06:13,239 Speaker 1: the lab. And I felt this huge disconnect in AI 107 00:06:13,400 --> 00:06:15,880 Speaker 1: at that time, and I thought, Okay, in order to 108 00:06:15,920 --> 00:06:17,680 Speaker 1: get the robot to play tennis with me, I have 109 00:06:17,760 --> 00:06:21,240 Speaker 1: to learn neuroscience the human intelligence, because that's the only 110 00:06:21,279 --> 00:06:23,560 Speaker 1: way I can create enough artificial intelligence to get the 111 00:06:23,640 --> 00:06:26,000 Speaker 1: robot to do the right thing. So for the last 112 00:06:26,040 --> 00:06:29,560 Speaker 1: half of my PhD ended up studying neuroscience. That's really 113 00:06:29,640 --> 00:06:31,480 Speaker 1: I would say it was a turning point for me 114 00:06:32,000 --> 00:06:36,039 Speaker 1: to be exposed to learning about people who had neurological disorders, 115 00:06:36,080 --> 00:06:39,280 Speaker 1: who couldn't move the way they wanted. They wanted to, 116 00:06:39,839 --> 00:06:42,240 Speaker 1: but part of the brain wasn't working for them, And 117 00:06:42,279 --> 00:06:45,960 Speaker 1: I thought, wait a second, I've been selfish. I've been 118 00:06:46,000 --> 00:06:49,120 Speaker 1: trying to build this robot for myself. I could help 119 00:06:49,160 --> 00:06:53,760 Speaker 1: those people who need it for just getting by every day. 120 00:06:53,839 --> 00:06:56,720 Speaker 1: So that's why I retool myself towards the end of 121 00:06:56,760 --> 00:06:59,080 Speaker 1: my PhD and post doc into Harvard to say, you 122 00:06:59,080 --> 00:07:02,240 Speaker 1: know what, I'm dedicated to build technology to help people. 123 00:07:02,640 --> 00:07:05,479 Speaker 1: What was it that led to you deciding to leave 124 00:07:05,560 --> 00:07:09,880 Speaker 1: the world of academia and then to go into you know, 125 00:07:10,000 --> 00:07:14,680 Speaker 1: the private sector. Yeah. So I was a professor for 126 00:07:14,720 --> 00:07:17,960 Speaker 1: about a decade, but I realized that I was still 127 00:07:18,080 --> 00:07:21,160 Speaker 1: far away from helping people. I was writing papers, I 128 00:07:21,200 --> 00:07:23,880 Speaker 1: was graduating students, and I felt frustrated that distance that 129 00:07:23,960 --> 00:07:26,960 Speaker 1: I felt. So I started to get tickled by the 130 00:07:27,320 --> 00:07:30,960 Speaker 1: calling of the industrial side. How can I build something 131 00:07:31,000 --> 00:07:34,520 Speaker 1: that's closer to those people, you know, instead of contributing 132 00:07:34,560 --> 00:07:38,000 Speaker 1: pushing the envelope of science. It's not every day I 133 00:07:38,040 --> 00:07:40,520 Speaker 1: get to speak with someone who was present when the 134 00:07:40,720 --> 00:07:44,960 Speaker 1: famously secretive Google x got its start. So I wanted 135 00:07:45,000 --> 00:07:47,160 Speaker 1: to find out more from Yochi about her views on 136 00:07:47,280 --> 00:07:49,960 Speaker 1: emerging tech. Plus, I wanted to get her perspective on 137 00:07:50,000 --> 00:07:53,880 Speaker 1: how different technologies can work together to create incredible outcomes. 138 00:07:54,680 --> 00:07:56,800 Speaker 1: I was very lucky when I was a professor to 139 00:07:56,920 --> 00:07:59,240 Speaker 1: get a call from you know, the Google to say, Hey, 140 00:07:59,320 --> 00:08:00,880 Speaker 1: would you like to be one of the co founders 141 00:08:00,920 --> 00:08:04,960 Speaker 1: for this new concept, Google X. Google X was looking 142 00:08:05,000 --> 00:08:07,920 Speaker 1: at ten to fifteen years down the road for something 143 00:08:07,920 --> 00:08:12,640 Speaker 1: that's paradigm shifting, that's more hardware oriented, that can potentially 144 00:08:12,800 --> 00:08:16,000 Speaker 1: give birth to some of the future of Google, aligning 145 00:08:16,040 --> 00:08:18,080 Speaker 1: with what I've been thinking about what I wanted to 146 00:08:18,160 --> 00:08:21,760 Speaker 1: do and then be closer to customers. I thought, this 147 00:08:21,840 --> 00:08:24,240 Speaker 1: is it. I gotta ride this wave. It was just 148 00:08:24,320 --> 00:08:27,680 Speaker 1: a perfect fit given my research background. Of course, you know, 149 00:08:28,120 --> 00:08:31,360 Speaker 1: now everybody knows what Google X has given birth to, 150 00:08:32,200 --> 00:08:36,600 Speaker 1: you know, to Weymo, the autonomous driving cars two Verily, 151 00:08:36,920 --> 00:08:40,000 Speaker 1: which is a medical technology company that's you know, still 152 00:08:40,080 --> 00:08:43,560 Speaker 1: part of Alphabet. It's also giving birth to things like 153 00:08:43,600 --> 00:08:47,840 Speaker 1: Google Brain, which really became core of many of the 154 00:08:47,880 --> 00:08:51,440 Speaker 1: Google technology and an AI, so you know, but it 155 00:08:51,559 --> 00:08:54,480 Speaker 1: also was very important in an astro teller who continues 156 00:08:54,480 --> 00:08:57,880 Speaker 1: to run Google X and I respect highly. He makes 157 00:08:57,920 --> 00:09:00,360 Speaker 1: sure that a lot of projects fail as a our effect, 158 00:09:00,400 --> 00:09:03,280 Speaker 1: fail quick and then you know, then try a lot 159 00:09:03,320 --> 00:09:06,520 Speaker 1: of different things. There are lots of internal projects that 160 00:09:06,600 --> 00:09:08,760 Speaker 1: had to be killed, but thanks to them being killed, 161 00:09:08,760 --> 00:09:10,360 Speaker 1: there are a lot of good projects that were also 162 00:09:10,400 --> 00:09:13,920 Speaker 1: born to So that was really the idea of Google Acts. Yeah, 163 00:09:14,160 --> 00:09:16,640 Speaker 1: and and it's something that you actually saw carried out 164 00:09:16,800 --> 00:09:20,040 Speaker 1: through Google as a whole. I mean, on the tech 165 00:09:20,120 --> 00:09:24,040 Speaker 1: journalism side, there's this perception that Google releases a lot 166 00:09:24,080 --> 00:09:26,720 Speaker 1: of products and then some of those a few years 167 00:09:26,800 --> 00:09:30,160 Speaker 1: down the line might get retired. So in your experience, 168 00:09:30,200 --> 00:09:33,320 Speaker 1: there was that something that was really formative, this idea 169 00:09:33,480 --> 00:09:36,680 Speaker 1: of trying things quickly and finding things that work and 170 00:09:36,760 --> 00:09:41,600 Speaker 1: really exploring different possibilities. Yeah. I think there there are 171 00:09:41,600 --> 00:09:45,040 Speaker 1: two things right that I would say failure is the 172 00:09:45,080 --> 00:09:49,440 Speaker 1: only way to learn sometimes, so failing quick and learn 173 00:09:49,520 --> 00:09:51,960 Speaker 1: and get the essence out of it so that all 174 00:09:52,000 --> 00:09:54,840 Speaker 1: the you know, the future success can come. And then 175 00:09:54,880 --> 00:09:57,680 Speaker 1: there's this other part, which is that Google has a 176 00:09:57,720 --> 00:10:01,440 Speaker 1: culture a very bottom up They are incredibly intelligent people 177 00:10:01,480 --> 00:10:03,720 Speaker 1: and then then let them be creative. So there are 178 00:10:03,720 --> 00:10:06,320 Speaker 1: a lot of bottom up projects out even outside of 179 00:10:06,320 --> 00:10:09,480 Speaker 1: Google X. Yeah, and I get the feeling it's a 180 00:10:09,480 --> 00:10:12,800 Speaker 1: place that was founded by engineers and still has very 181 00:10:12,880 --> 00:10:18,319 Speaker 1: much an engineering spirit behind the development side. And that again, 182 00:10:18,360 --> 00:10:22,720 Speaker 1: if you aren't familiar with the approach to engineering, it 183 00:10:22,800 --> 00:10:28,800 Speaker 1: can seem haphazard or or chaotic even but once you 184 00:10:28,880 --> 00:10:31,960 Speaker 1: gain that that perspective, you realize, oh no, there's a 185 00:10:32,040 --> 00:10:36,880 Speaker 1: method to this apparent madness. And uh, that kind of 186 00:10:36,920 --> 00:10:40,160 Speaker 1: leads me to my next question, which is, so, so 187 00:10:40,360 --> 00:10:43,000 Speaker 1: you move on to Google X, what was it that 188 00:10:43,240 --> 00:10:47,760 Speaker 1: had you decided to go and join Nest. So Google 189 00:10:47,920 --> 00:10:50,360 Speaker 1: X was still looking at ten to fifteen years down 190 00:10:50,400 --> 00:10:54,680 Speaker 1: the road to be paradigm shifting in society. To be honest, 191 00:10:54,720 --> 00:10:56,600 Speaker 1: I felt like I was already doing that in research. 192 00:10:57,040 --> 00:11:00,679 Speaker 1: What I wanted was to help people now, and so 193 00:11:00,720 --> 00:11:03,600 Speaker 1: I was getting impatient. I was getting shortsighted a little bit. 194 00:11:03,920 --> 00:11:06,760 Speaker 1: And I happened to bump into my old student from 195 00:11:06,800 --> 00:11:10,800 Speaker 1: Carnie Mellen, who um was starting this secret startup called 196 00:11:10,840 --> 00:11:15,760 Speaker 1: Nest And while it wasn't about helping people with disabilities, 197 00:11:16,240 --> 00:11:19,679 Speaker 1: it still had the flavor of helping people achieve something 198 00:11:19,720 --> 00:11:24,200 Speaker 1: they couldn't, like save energy, and it was about learning 199 00:11:24,240 --> 00:11:28,200 Speaker 1: to build a consumer product in twelve months and put 200 00:11:28,200 --> 00:11:30,960 Speaker 1: it on the shelf. And I thought, boy, this is 201 00:11:31,080 --> 00:11:34,120 Speaker 1: a skill that I don't have at all. I must 202 00:11:34,200 --> 00:11:37,160 Speaker 1: learn how to do this and then find ways to 203 00:11:37,160 --> 00:11:39,840 Speaker 1: touch people now, learn about people? Now, how do I 204 00:11:39,920 --> 00:11:42,160 Speaker 1: work with them? How do I know what to build? Now? 205 00:11:42,200 --> 00:11:45,000 Speaker 1: How do I build millions of devices that everybody wants 206 00:11:45,000 --> 00:11:48,120 Speaker 1: to have? So I decided to jump and then give 207 00:11:48,160 --> 00:11:51,800 Speaker 1: that a try. Uh, Yukie, You're You're like, every answer 208 00:11:51,960 --> 00:11:55,120 Speaker 1: is just making me even happier. The impatience to get 209 00:11:55,160 --> 00:11:58,640 Speaker 1: to the point where you're helping people driving you is 210 00:11:58,679 --> 00:12:02,080 Speaker 1: really inspirational. Well, I have one less little question for 211 00:12:02,080 --> 00:12:05,040 Speaker 1: this segment before we move on, and it's just just 212 00:12:05,080 --> 00:12:08,559 Speaker 1: a little aside. What is your favorite piece of technology 213 00:12:08,600 --> 00:12:13,320 Speaker 1: that you own. I love my net thermostat. You know 214 00:12:13,400 --> 00:12:18,320 Speaker 1: why because it works with me when I want to 215 00:12:18,360 --> 00:12:22,640 Speaker 1: save energy. It learns about me and it helps me. 216 00:12:23,520 --> 00:12:25,960 Speaker 1: But what when I don't want to think about it? 217 00:12:25,960 --> 00:12:30,240 Speaker 1: It automatically changes temperature based on my activity if I'm home, 218 00:12:30,360 --> 00:12:32,720 Speaker 1: if I'm away, and I don't have to think about it. 219 00:12:32,679 --> 00:12:35,200 Speaker 1: It's a blends in with the background. And for me, 220 00:12:35,440 --> 00:12:42,600 Speaker 1: that's really the goal of what technology should be at 221 00:12:42,640 --> 00:12:46,440 Speaker 1: T Mobile. For business, unconventional thinking means we see things differently, 222 00:12:46,640 --> 00:12:49,400 Speaker 1: so you can focus on what matters most. Where some 223 00:12:49,520 --> 00:12:53,120 Speaker 1: see another small town, we see businesses in need of connectivity. 224 00:12:53,280 --> 00:12:56,760 Speaker 1: So we built the largest five G network to cover cities, towns, 225 00:12:56,880 --> 00:12:59,720 Speaker 1: and the most interstate miles in between. Where some see 226 00:12:59,720 --> 00:13:02,080 Speaker 1: all all are in a queue, we see an opportunity 227 00:13:02,120 --> 00:13:06,080 Speaker 1: for our experts to provide solutions without transfers. Where some 228 00:13:06,200 --> 00:13:09,880 Speaker 1: see another virtual meeting, we see five G enabling wireless 229 00:13:10,000 --> 00:13:13,880 Speaker 1: real time translations almost anywhere you do business. Our unique 230 00:13:13,880 --> 00:13:17,800 Speaker 1: approach built America's largest, fastest five G network and also 231 00:13:17,880 --> 00:13:21,880 Speaker 1: delivers exceptional customer support and five G included in every plan, 232 00:13:22,200 --> 00:13:25,880 Speaker 1: so you get it all without trade offs. Unconventional thinking 233 00:13:26,000 --> 00:13:29,920 Speaker 1: is better for business. T Mobile for Business fastest five 234 00:13:29,920 --> 00:13:32,760 Speaker 1: G based on average overall combined five G speeds according 235 00:13:32,760 --> 00:13:36,200 Speaker 1: to Open Signal Awards USA five G User Experience Report October. 236 00:13:37,200 --> 00:13:39,360 Speaker 1: See five G device coverage and access details at T 237 00:13:39,480 --> 00:13:50,559 Speaker 1: mobile dot com. Well, I really, sincerely could have spent 238 00:13:50,720 --> 00:13:54,320 Speaker 1: hours talking with Yoki about her experiences at Google X 239 00:13:54,400 --> 00:13:57,480 Speaker 1: and Nest. I wanted to learn more about Johanna and 240 00:13:57,520 --> 00:14:01,839 Speaker 1: how it fits into Yoki's desire to help others. So 241 00:14:02,440 --> 00:14:05,680 Speaker 1: can you tell me about your your current project, because 242 00:14:05,800 --> 00:14:09,640 Speaker 1: it's it's brand new and it's really exciting. Yeah. I 243 00:14:09,720 --> 00:14:14,200 Speaker 1: have felt that I've learned how to build consumer products 244 00:14:14,280 --> 00:14:18,880 Speaker 1: and how to also build healthcare tech through working on 245 00:14:18,960 --> 00:14:23,120 Speaker 1: those at Apple, Google in different startups. I felt that 246 00:14:23,360 --> 00:14:28,520 Speaker 1: what I really wanted to do was to build technology 247 00:14:28,720 --> 00:14:34,720 Speaker 1: that helps people at home to live better, to be healthier, 248 00:14:35,400 --> 00:14:38,960 Speaker 1: to really care about their wellness. And I built this 249 00:14:39,000 --> 00:14:42,880 Speaker 1: company called Johanna, which is a wellness company that is 250 00:14:42,920 --> 00:14:46,240 Speaker 1: focused on healthy family find more balance, prioritized well being, 251 00:14:46,320 --> 00:14:48,440 Speaker 1: and be more present for each other. When you think 252 00:14:48,480 --> 00:14:51,240 Speaker 1: about the first offering that we are yeah, we just 253 00:14:51,320 --> 00:14:55,280 Speaker 1: announced it is a called it's called a Johanna Membership, 254 00:14:55,840 --> 00:15:00,320 Speaker 1: a personal assistance service design specifically for busy families. So 255 00:15:00,840 --> 00:15:05,040 Speaker 1: it is a tool that is a combination of an 256 00:15:05,080 --> 00:15:09,920 Speaker 1: app to a real person on the background who's assisted 257 00:15:09,960 --> 00:15:14,560 Speaker 1: by smart tools, data and also have researchers and pros 258 00:15:14,560 --> 00:15:17,800 Speaker 1: and a background. It is really a hybrid of real 259 00:15:17,840 --> 00:15:23,200 Speaker 1: people's intelligence and then the artificial intelligence of machines together 260 00:15:23,360 --> 00:15:27,040 Speaker 1: to help people's daily life. So this in a way 261 00:15:27,320 --> 00:15:29,960 Speaker 1: is kind of like that concept we were just talking 262 00:15:30,000 --> 00:15:33,440 Speaker 1: about with the nest Thermostat, but with a much broader 263 00:15:33,520 --> 00:15:37,080 Speaker 1: scope of looking at various needs that the average family 264 00:15:37,200 --> 00:15:41,280 Speaker 1: might encounter. That's right. So I'm a mother of four kids, 265 00:15:41,920 --> 00:15:45,880 Speaker 1: i have parents who are getting older. I'm the only child, 266 00:15:46,920 --> 00:15:51,160 Speaker 1: so there's a lot of family related responsibilities that you know, 267 00:15:51,200 --> 00:15:54,200 Speaker 1: follow me. I also want to be a good mom. 268 00:15:54,680 --> 00:15:56,920 Speaker 1: I want to be with my kids, and I want 269 00:15:56,960 --> 00:15:58,720 Speaker 1: to be a good daughter, and I want to be 270 00:15:58,760 --> 00:16:02,400 Speaker 1: a good wife too. So all of that together, while 271 00:16:02,640 --> 00:16:05,560 Speaker 1: I had my career, I had my mission to really 272 00:16:05,600 --> 00:16:08,800 Speaker 1: want to, you know, to deliver technology for others to 273 00:16:09,000 --> 00:16:12,880 Speaker 1: also be able to live happier and healthier life. Technology 274 00:16:12,880 --> 00:16:16,080 Speaker 1: hasn't been there to really help people. When you look 275 00:16:16,120 --> 00:16:19,720 Speaker 1: at those gaming technology or autonomous driving car technology, it's 276 00:16:19,920 --> 00:16:22,640 Speaker 1: mind blowing, right. The some of the advances that's been 277 00:16:22,640 --> 00:16:25,200 Speaker 1: made recently is amazing. But then when you look at 278 00:16:25,240 --> 00:16:27,760 Speaker 1: people's home after they work all those amazing things during 279 00:16:27,760 --> 00:16:29,320 Speaker 1: the day at a company, and then then when they 280 00:16:29,320 --> 00:16:33,400 Speaker 1: go home, the home life is still clunky, and then 281 00:16:33,400 --> 00:16:36,120 Speaker 1: it's like the daily things that pile up was never 282 00:16:36,160 --> 00:16:39,120 Speaker 1: taken care of. Ways to stay healthy well, you have 283 00:16:39,240 --> 00:16:41,280 Speaker 1: to do everything manual. You have to figure out what 284 00:16:41,320 --> 00:16:43,280 Speaker 1: to eat, you have to sleep on your own a 285 00:16:43,280 --> 00:16:46,720 Speaker 1: little bit better, you had to exercise. It felt like 286 00:16:46,880 --> 00:16:51,160 Speaker 1: it wasn't really pushing people to look out for themselves 287 00:16:51,560 --> 00:16:55,760 Speaker 1: in the right way using technology. This is absolutely fascinating 288 00:16:55,760 --> 00:16:58,280 Speaker 1: to me. You can look at certain areas of tech 289 00:16:58,360 --> 00:17:03,560 Speaker 1: where you see life years of advancement over the last decade, 290 00:17:03,600 --> 00:17:06,760 Speaker 1: and other areas which maybe it's one of those where 291 00:17:06,760 --> 00:17:09,439 Speaker 1: it wasn't seen as like a big engineering challenge, so 292 00:17:09,480 --> 00:17:11,919 Speaker 1: there wasn't a lot of attention devoted to it, or 293 00:17:11,960 --> 00:17:15,160 Speaker 1: maybe companies just had not hit upon that as being 294 00:17:15,720 --> 00:17:19,800 Speaker 1: a possible market to develop. It's kind of languished in 295 00:17:19,800 --> 00:17:23,960 Speaker 1: the background, and the thought of having a technology company 296 00:17:24,040 --> 00:17:29,160 Speaker 1: really focusing on ways to streamline lives, to do what 297 00:17:29,240 --> 00:17:32,000 Speaker 1: tech has always promised to do. The promise of tech, 298 00:17:32,040 --> 00:17:35,280 Speaker 1: I think ever since really the nineteen fifties, was that 299 00:17:35,359 --> 00:17:37,840 Speaker 1: technology was going to take over a lot of the 300 00:17:37,920 --> 00:17:42,720 Speaker 1: tasks that we find repetitive, that our time consuming, that 301 00:17:43,320 --> 00:17:45,240 Speaker 1: keep us from the stuff we really love to do. 302 00:17:45,960 --> 00:17:49,639 Speaker 1: But we've also seen a lot of technology not actually 303 00:17:50,280 --> 00:17:52,760 Speaker 1: solve those problems. We just end up doing more of 304 00:17:52,800 --> 00:17:54,960 Speaker 1: the stuff we we didn't want to do in the 305 00:17:55,000 --> 00:17:59,679 Speaker 1: first place. Yes, so in a way, technology needs change. 306 00:18:00,119 --> 00:18:03,720 Speaker 1: The society change, the societal pressure changed, All different things happen, 307 00:18:03,800 --> 00:18:06,800 Speaker 1: and in nineteen fifties. Actually, the reason why I'm partnering 308 00:18:06,800 --> 00:18:10,800 Speaker 1: with Panasonic is because Panasonic was one of the frontiers 309 00:18:10,840 --> 00:18:15,360 Speaker 1: of a company that built technology that east the chores 310 00:18:15,600 --> 00:18:20,119 Speaker 1: at home, washing machine, dryer, dishwashers, you know, name it. 311 00:18:20,480 --> 00:18:23,479 Speaker 1: Panasonic you know has owned them and then made it 312 00:18:23,520 --> 00:18:26,840 Speaker 1: better than anybody else for a long time. That's because 313 00:18:26,880 --> 00:18:30,200 Speaker 1: their founder was really focused on that he was in 314 00:18:30,359 --> 00:18:33,360 Speaker 1: this incredible emission driven guy started a company I think 315 00:18:34,720 --> 00:18:37,280 Speaker 1: in nineteen fifties as he was building washing and dryer, 316 00:18:37,720 --> 00:18:40,800 Speaker 1: he said, Hey, I'm doing this to free women so 317 00:18:40,840 --> 00:18:43,199 Speaker 1: that they have time to do something they want to do, 318 00:18:43,240 --> 00:18:45,399 Speaker 1: like read a block. Of course, that might be a 319 00:18:45,440 --> 00:18:47,600 Speaker 1: little bit offensive to say these days, but that was 320 00:18:47,640 --> 00:18:51,080 Speaker 1: the status the world around nineteen fifties, and we all 321 00:18:51,119 --> 00:18:56,000 Speaker 1: been in the fitter from those automated task specific technology 322 00:18:56,119 --> 00:18:58,879 Speaker 1: very much. You know, like I can't imagine living without 323 00:18:58,880 --> 00:19:01,760 Speaker 1: a dishwasher now. But now we live in the world 324 00:19:01,800 --> 00:19:05,720 Speaker 1: where those tax specific things are assisted by technology, and 325 00:19:05,880 --> 00:19:07,960 Speaker 1: we have tried to take on a lot more in 326 00:19:08,080 --> 00:19:11,160 Speaker 1: this world now, and you know, I think we're all 327 00:19:11,200 --> 00:19:14,080 Speaker 1: also getting mission driven and we want to contribute to society. 328 00:19:14,280 --> 00:19:17,439 Speaker 1: How do we even balance all of this has you know, 329 00:19:17,920 --> 00:19:20,679 Speaker 1: become quite a lot of um what people are thinking about. 330 00:19:20,960 --> 00:19:24,560 Speaker 1: On top of all of that, pandemic happened. I think 331 00:19:24,600 --> 00:19:28,320 Speaker 1: that pandemic has also highlighted some of the issues that 332 00:19:28,920 --> 00:19:32,480 Speaker 1: we're brewing brewing in the background. The pandemic of its 333 00:19:32,480 --> 00:19:37,480 Speaker 1: own was that home and work could not be balanced anymore. 334 00:19:38,359 --> 00:19:41,160 Speaker 1: Home and work blended in like you know, for me, 335 00:19:41,280 --> 00:19:43,879 Speaker 1: like four kids were doing zoom a how I was 336 00:19:43,960 --> 00:19:46,520 Speaker 1: doing zoom meetings at home and we're all in the 337 00:19:46,560 --> 00:19:50,639 Speaker 1: same space. That's when I thought, Okay, all the things 338 00:19:50,680 --> 00:19:53,280 Speaker 1: that has been a problem that has been amplified in 339 00:19:53,320 --> 00:19:55,879 Speaker 1: this time, is it just me? Did I go and staying? 340 00:19:56,800 --> 00:20:00,600 Speaker 1: But millions of people out there we're feeling the same thing. Women, 341 00:20:00,840 --> 00:20:06,399 Speaker 1: men just thanks for falling apart. Now women have quit 342 00:20:06,440 --> 00:20:09,680 Speaker 1: their job not by choice because they have to drop 343 00:20:09,720 --> 00:20:12,240 Speaker 1: something and they couldn't drop families, so they dropped work. 344 00:20:13,160 --> 00:20:16,040 Speaker 1: And technology has to be there to rescue all of 345 00:20:16,080 --> 00:20:18,639 Speaker 1: us somehow. Well to that point, can you tell us 346 00:20:18,640 --> 00:20:21,560 Speaker 1: a little bit about some of the technologies that you're 347 00:20:21,960 --> 00:20:25,600 Speaker 1: you're bringing to bear on this problem in the near future, 348 00:20:25,640 --> 00:20:29,200 Speaker 1: and maybe even some ideas about tech that might play 349 00:20:29,200 --> 00:20:33,280 Speaker 1: a larger role further down the line. Where I love 350 00:20:33,359 --> 00:20:40,000 Speaker 1: to go is a grandiest vision of putting hardware, software, AI, 351 00:20:40,320 --> 00:20:43,960 Speaker 1: humans all together in the end to end format to 352 00:20:44,080 --> 00:20:48,640 Speaker 1: help people in daily life, but especially things like elderly care. 353 00:20:49,119 --> 00:20:51,400 Speaker 1: You know, there are a lot of places where we 354 00:20:51,440 --> 00:20:54,360 Speaker 1: need to feel close to the family and then care 355 00:20:54,400 --> 00:20:56,960 Speaker 1: for family in a very different way from before. So 356 00:20:57,080 --> 00:20:59,080 Speaker 1: where do we start we start tackling on your to 357 00:20:59,160 --> 00:21:02,080 Speaker 1: do list, and when we look at the family to 358 00:21:02,119 --> 00:21:05,720 Speaker 1: do list, there are lots of different things. I put 359 00:21:05,760 --> 00:21:08,760 Speaker 1: them in three buckets. The first bucket is things that 360 00:21:09,000 --> 00:21:12,560 Speaker 1: just keep piling up, and that'd be nice if somebody 361 00:21:12,600 --> 00:21:16,080 Speaker 1: else who's on my shoulder and every day, who is saying, gotcha, 362 00:21:16,160 --> 00:21:18,679 Speaker 1: don't worry about it, I'll take care of it. You know. 363 00:21:18,840 --> 00:21:21,520 Speaker 1: That's something that we're starting to do. So that's one 364 00:21:21,680 --> 00:21:26,600 Speaker 1: type of two dousu mundane tasks. Second buckets have a 365 00:21:26,640 --> 00:21:28,879 Speaker 1: little more of the things that's probably in your to 366 00:21:29,000 --> 00:21:32,360 Speaker 1: do list for a long time that has never been cleared. 367 00:21:32,920 --> 00:21:36,200 Speaker 1: Maybe it is cleaning out the garage. Of course you 368 00:21:36,240 --> 00:21:38,080 Speaker 1: want to do it. You never somehow gets to the 369 00:21:38,119 --> 00:21:41,639 Speaker 1: point of clearing the garage, and that a team of 370 00:21:42,200 --> 00:21:48,040 Speaker 1: people who already know you can come and say, okay, well, 371 00:21:48,560 --> 00:21:51,680 Speaker 1: you know, let's decompose this problem to you know, easy ones. 372 00:21:52,280 --> 00:21:55,520 Speaker 1: Is it stinky? Is it you know? Is it on 373 00:21:55,560 --> 00:21:58,119 Speaker 1: the lit up? Really? Well, okay, so let's let me 374 00:21:58,160 --> 00:22:01,280 Speaker 1: send you a pro. Then, from my point of view, 375 00:22:01,280 --> 00:22:03,680 Speaker 1: I'll just get a very simple list of pros that 376 00:22:03,720 --> 00:22:07,600 Speaker 1: I can pick pick one. Schedule gets automatically made when 377 00:22:07,600 --> 00:22:09,880 Speaker 1: I have time, the pro shows up and then checks 378 00:22:09,880 --> 00:22:13,119 Speaker 1: out my garage and says, I has mildew eyes leaking 379 00:22:13,160 --> 00:22:16,000 Speaker 1: from here. Oh, you actually have termites. You gotta get 380 00:22:16,080 --> 00:22:18,840 Speaker 1: rid of all of those first pros come again at 381 00:22:18,880 --> 00:22:20,960 Speaker 1: a time that I can make it work. They come 382 00:22:20,960 --> 00:22:24,399 Speaker 1: and clean all those things. So those things, because I 383 00:22:24,480 --> 00:22:28,160 Speaker 1: have a partner who is just proactive reaching out, making 384 00:22:28,200 --> 00:22:30,000 Speaker 1: sure it's you know, in the form that I can 385 00:22:30,000 --> 00:22:32,320 Speaker 1: take care of, things are getting crossed off my to 386 00:22:32,400 --> 00:22:34,480 Speaker 1: do list because of it. So that's sort of the 387 00:22:34,520 --> 00:22:36,760 Speaker 1: second bucket of things that we can take care of. 388 00:22:37,119 --> 00:22:40,200 Speaker 1: But lastly, the most importantly, we are a well being 389 00:22:40,240 --> 00:22:43,760 Speaker 1: wellness company. We want to make sure that as you 390 00:22:43,840 --> 00:22:47,400 Speaker 1: manage your family, as you manage your life, that you're 391 00:22:47,440 --> 00:22:50,000 Speaker 1: taken care of, and often you don't put those things 392 00:22:50,000 --> 00:22:52,480 Speaker 1: there need to do list. What are those things? It 393 00:22:52,560 --> 00:22:55,160 Speaker 1: could be the day night with your husband just to 394 00:22:55,160 --> 00:22:57,400 Speaker 1: get a little bit of a break, or maybe even 395 00:22:57,520 --> 00:23:01,399 Speaker 1: descending flowers, gifting friends those things make you feel really happy. 396 00:23:01,560 --> 00:23:04,160 Speaker 1: We'll make sure that we are proactively thinking about you 397 00:23:04,280 --> 00:23:07,160 Speaker 1: and then your well being and maybe even community outreach 398 00:23:07,560 --> 00:23:10,400 Speaker 1: that maybe you've been wanting to feel part of the community. 399 00:23:10,480 --> 00:23:12,840 Speaker 1: So there are with different ways that we try to 400 00:23:12,880 --> 00:23:16,560 Speaker 1: make sure that you're you're preserved, you feel good, and 401 00:23:16,600 --> 00:23:19,600 Speaker 1: then you have time in those moments to contribute to 402 00:23:19,680 --> 00:23:23,200 Speaker 1: your family and to society. So I imagine in order 403 00:23:23,240 --> 00:23:27,160 Speaker 1: to get that level of understanding, you're depending both upon 404 00:23:28,080 --> 00:23:33,399 Speaker 1: the human beings who are working on behalf of these subscribers, 405 00:23:33,560 --> 00:23:38,199 Speaker 1: as well as probably some data analysis and machine learning 406 00:23:38,240 --> 00:23:42,560 Speaker 1: to start to anticipate things before they even become to 407 00:23:42,640 --> 00:23:44,760 Speaker 1: the level of a problem so that you can address 408 00:23:44,800 --> 00:23:47,440 Speaker 1: it and it never even takes up that mind space 409 00:23:47,520 --> 00:23:50,199 Speaker 1: that just weighs down on people day after day. Is 410 00:23:50,200 --> 00:23:52,520 Speaker 1: that more or less where you're you're kind of aiming 411 00:23:52,560 --> 00:23:54,719 Speaker 1: at with this this adventure. Yeah, So let me tell 412 00:23:54,760 --> 00:23:56,800 Speaker 1: you a little bit about what this product will feel like. 413 00:23:57,040 --> 00:24:00,199 Speaker 1: When you become a subscription member, what you get is 414 00:24:00,240 --> 00:24:04,280 Speaker 1: an onboarding call with a person who is going to 415 00:24:04,280 --> 00:24:06,919 Speaker 1: tell you a little bit about what the program is about, 416 00:24:07,160 --> 00:24:09,880 Speaker 1: and then also start to learn about who you are, 417 00:24:10,200 --> 00:24:12,040 Speaker 1: how can we work with you, what kind of things 418 00:24:12,040 --> 00:24:14,840 Speaker 1: are wine down on you. They will start taking on 419 00:24:14,960 --> 00:24:18,000 Speaker 1: some of the first tasks. You get an app where 420 00:24:18,080 --> 00:24:21,520 Speaker 1: you can chat, you can track tasks, and that then 421 00:24:21,640 --> 00:24:25,240 Speaker 1: you can move forward with a dedicated assistant, name your 422 00:24:25,280 --> 00:24:29,040 Speaker 1: assistant who you will know by first name basis that 423 00:24:29,160 --> 00:24:32,120 Speaker 1: you can start to chat with and then start to delegate. Now, 424 00:24:32,160 --> 00:24:33,879 Speaker 1: of course that person will start to get to know 425 00:24:33,960 --> 00:24:36,080 Speaker 1: you that you know, then you get to know them 426 00:24:36,440 --> 00:24:39,640 Speaker 1: and then learn this each other's style to start tackling 427 00:24:39,640 --> 00:24:42,359 Speaker 1: on different tasks that I mentioned. Um, so this is 428 00:24:42,400 --> 00:24:45,280 Speaker 1: pretty much how it works in terms of the nutshell 429 00:24:45,600 --> 00:24:49,040 Speaker 1: of the product. As you know, you may have lots 430 00:24:49,040 --> 00:24:52,480 Speaker 1: of things to offload to people and sometimes they're a 431 00:24:52,560 --> 00:24:54,080 Speaker 1: little bit of a nudge, a little bit of a 432 00:24:54,080 --> 00:24:59,800 Speaker 1: proactive reach that's required. Definitely sounds like a great go 433 00:25:00,000 --> 00:25:02,639 Speaker 1: old to have. Well, before we move on, I have 434 00:25:02,760 --> 00:25:06,560 Speaker 1: one another quick question, which is what is the best 435 00:25:06,680 --> 00:25:12,320 Speaker 1: piece of advice that you have ever received in your career? Okay, 436 00:25:12,560 --> 00:25:15,480 Speaker 1: so I keep revealing myself way too much, but here 437 00:25:15,520 --> 00:25:21,879 Speaker 1: I go. Um, I'm um introvert, I'm you know, often 438 00:25:21,960 --> 00:25:27,440 Speaker 1: not super confident by myself sometimes and so when I 439 00:25:27,480 --> 00:25:31,719 Speaker 1: was younger, I used to pretend to be dumb because 440 00:25:31,760 --> 00:25:33,840 Speaker 1: I wanted to be accepted as a girl. When I 441 00:25:33,880 --> 00:25:36,639 Speaker 1: was at m TEA in grad school, I used to 442 00:25:36,680 --> 00:25:38,760 Speaker 1: wear the hello my name is signed that you know, 443 00:25:38,800 --> 00:25:41,040 Speaker 1: you put as a sticker sometimes and I used to 444 00:25:41,080 --> 00:25:42,880 Speaker 1: say hello, my name is and I put air head. 445 00:25:43,640 --> 00:25:45,840 Speaker 1: This is second year in grad school at M I 446 00:25:45,920 --> 00:25:48,480 Speaker 1: T and then one of the most amazing institutions in 447 00:25:48,520 --> 00:25:53,159 Speaker 1: the world. And my professor pulled me on the side, Yoki, 448 00:25:54,000 --> 00:25:56,479 Speaker 1: I need to give you an advice because you wouldn't 449 00:25:56,520 --> 00:25:59,920 Speaker 1: go any further unless you change right now, he said, 450 00:26:01,080 --> 00:26:04,680 Speaker 1: snap out, You're not an airhead. You're at M I T. 451 00:26:05,240 --> 00:26:09,000 Speaker 1: Everybody already ceased through you, so stop it. That was 452 00:26:09,040 --> 00:26:11,400 Speaker 1: probably like twenty three years old. It took that long 453 00:26:11,520 --> 00:26:14,800 Speaker 1: for me to try to stop pretending trying to actually 454 00:26:15,400 --> 00:26:19,520 Speaker 1: hide behind something, and that was one of the best 455 00:26:19,560 --> 00:26:23,280 Speaker 1: advices that I've ever gotten. Since then, I have been trying. 456 00:26:23,720 --> 00:26:26,080 Speaker 1: I have been also a little bit more vulnerable. I've 457 00:26:26,080 --> 00:26:28,840 Speaker 1: been showing when I fail a little bit more. That 458 00:26:28,920 --> 00:26:30,880 Speaker 1: was something that I was scared to do too. As 459 00:26:30,880 --> 00:26:32,679 Speaker 1: long as I knew that, you know, I pretended to 460 00:26:33,040 --> 00:26:36,160 Speaker 1: not face it. I didn't have to because I didn't try, 461 00:26:36,200 --> 00:26:38,960 Speaker 1: so no big deal. But now suddenly I started trying 462 00:26:39,000 --> 00:26:42,399 Speaker 1: that The consequence was really scary. But at the same time, 463 00:26:42,440 --> 00:26:44,480 Speaker 1: the world suddenly opened up. And then that was by 464 00:26:44,520 --> 00:26:48,919 Speaker 1: far the best advice I've got. What a fantastic story. 465 00:26:49,400 --> 00:26:53,760 Speaker 1: I love that answer. Well, let's let's talk a bit 466 00:26:53,800 --> 00:26:58,800 Speaker 1: about emerging technology, something that you've been around for quite 467 00:26:58,840 --> 00:27:02,600 Speaker 1: some time. You've seen tons of different projects that are 468 00:27:02,640 --> 00:27:06,560 Speaker 1: all dedicated around technologies that are either emerging or maturing. 469 00:27:07,440 --> 00:27:11,760 Speaker 1: Which ones do you feel have the potential to to 470 00:27:12,000 --> 00:27:16,760 Speaker 1: provide the largest benefit in the in the fairly near future. 471 00:27:17,359 --> 00:27:19,879 Speaker 1: Even though I'm a technologist, I don't think technology first. 472 00:27:20,480 --> 00:27:22,959 Speaker 1: The way I think about it is there's no technology 473 00:27:23,000 --> 00:27:26,240 Speaker 1: around to help me as a mom, help me as 474 00:27:26,600 --> 00:27:29,440 Speaker 1: a family member, help me as a daughter, to be 475 00:27:29,440 --> 00:27:33,120 Speaker 1: better for my aging family and parents. I think that's 476 00:27:33,119 --> 00:27:35,880 Speaker 1: going to be the low hanging fruits. Quite a lot 477 00:27:35,880 --> 00:27:40,840 Speaker 1: of the technology used somewhere else, whether it's hardware, sensors, WiFi, 478 00:27:40,960 --> 00:27:46,680 Speaker 1: network to software AI, all those things. By using them right, 479 00:27:47,280 --> 00:27:51,120 Speaker 1: this can transform how people live at home. Lifestyle tech 480 00:27:51,240 --> 00:27:54,280 Speaker 1: maybe is the right terminology for it. I think that's 481 00:27:54,320 --> 00:27:57,520 Speaker 1: the emerging area that I'm interested in pushing, and I 482 00:27:57,560 --> 00:28:00,520 Speaker 1: think it's gonna be really exciting for the next cup decades. 483 00:28:00,840 --> 00:28:04,120 Speaker 1: I think what you're talking about, where we have these 484 00:28:04,200 --> 00:28:10,520 Speaker 1: various independent disciplines of technology starting to converge in specific areas. 485 00:28:10,920 --> 00:28:14,280 Speaker 1: And if we see that converge in say the lifestyle space, 486 00:28:14,720 --> 00:28:17,160 Speaker 1: I have a feeling like it will seem maybe five 487 00:28:17,240 --> 00:28:19,680 Speaker 1: years down the road, I'll look back at this and 488 00:28:19,760 --> 00:28:22,159 Speaker 1: think I was just on the precipice of living in 489 00:28:22,200 --> 00:28:25,199 Speaker 1: the future, just as I felt when smartphones started to 490 00:28:25,240 --> 00:28:28,000 Speaker 1: become a thing that now I had a computer in 491 00:28:28,080 --> 00:28:29,959 Speaker 1: my hand that got thit in my pocket, and I 492 00:28:30,000 --> 00:28:32,760 Speaker 1: lived in the future. Yeah, and let me even add 493 00:28:32,800 --> 00:28:34,720 Speaker 1: one more things, like I just want to I can 494 00:28:34,800 --> 00:28:38,280 Speaker 1: make it kind of more concrete. How we get older 495 00:28:38,920 --> 00:28:43,080 Speaker 1: and how we live after retirement, let's say, and how 496 00:28:43,120 --> 00:28:46,520 Speaker 1: we die. This all need to change. Then then a technology, 497 00:28:46,920 --> 00:28:49,800 Speaker 1: you know what I'm calling life type lifestyle tech should 498 00:28:49,840 --> 00:28:53,719 Speaker 1: be able to detect as you age, predict and make 499 00:28:53,760 --> 00:28:56,720 Speaker 1: things a little bit better, maybe have the right medication 500 00:28:56,800 --> 00:29:00,880 Speaker 1: to start earlier, to really live your life in better way. 501 00:29:00,920 --> 00:29:04,080 Speaker 1: But when it comes to caring instead of how from 502 00:29:04,080 --> 00:29:07,040 Speaker 1: the hospital, can we do that from home with technologies assistance, 503 00:29:07,320 --> 00:29:10,560 Speaker 1: where people in technology and hardware and an AI altogether 504 00:29:11,120 --> 00:29:13,440 Speaker 1: is caring for you in the right way so that 505 00:29:13,680 --> 00:29:16,840 Speaker 1: you can have that last ten through thirty years of 506 00:29:16,840 --> 00:29:19,600 Speaker 1: your life in the best way possible without worrying about 507 00:29:19,600 --> 00:29:22,000 Speaker 1: the kind of things that we currently have to worry about. Right, 508 00:29:22,560 --> 00:29:26,720 Speaker 1: being able to lean on technology to give people independence 509 00:29:26,960 --> 00:29:32,240 Speaker 1: and allow them that sense of agency and dignity. I 510 00:29:32,280 --> 00:29:35,800 Speaker 1: think that's a really worthy goal to strive for the 511 00:29:35,840 --> 00:29:39,040 Speaker 1: Internet of Things concept. I mean, I'm sure when you 512 00:29:39,080 --> 00:29:44,120 Speaker 1: were first getting into college, that was probably a buzz 513 00:29:44,160 --> 00:29:47,200 Speaker 1: word that maybe was being talked about a little bit, 514 00:29:47,200 --> 00:29:50,600 Speaker 1: But now it's reality. Do you see IoT playing a 515 00:29:50,680 --> 00:29:53,760 Speaker 1: larger role in our home lives and being part of 516 00:29:53,800 --> 00:29:59,160 Speaker 1: this system that helps us maintain our lives longer and 517 00:29:59,320 --> 00:30:03,080 Speaker 1: more comfortably within the home. Absolutely, I mean that's the 518 00:30:03,200 --> 00:30:05,800 Speaker 1: future that I want to be part of building and 519 00:30:06,040 --> 00:30:08,560 Speaker 1: living in. And you know, of course, as five G 520 00:30:08,720 --> 00:30:12,040 Speaker 1: technology comes in, I imagine the world to be a 521 00:30:12,120 --> 00:30:17,640 Speaker 1: lot more sensor oriented and also more privacy oriented. We 522 00:30:17,680 --> 00:30:19,920 Speaker 1: are able to do those things. As the network gets 523 00:30:20,000 --> 00:30:22,400 Speaker 1: faster and as the technology gets more enabled, we can 524 00:30:22,480 --> 00:30:25,440 Speaker 1: have edge computing thanks that can stay within your home 525 00:30:25,520 --> 00:30:28,400 Speaker 1: so that doesn't have to travel across for security reasons. 526 00:30:28,960 --> 00:30:31,480 Speaker 1: I think those things are within the reach now. You know, 527 00:30:31,640 --> 00:30:34,480 Speaker 1: from even from the health care perspective, it shouldn't be 528 00:30:34,560 --> 00:30:37,400 Speaker 1: this instant when you happen to being a doctor, and 529 00:30:37,400 --> 00:30:39,240 Speaker 1: then you happen to be reporting to a doctor about 530 00:30:39,280 --> 00:30:42,640 Speaker 1: what's wrong. But it should be that all the data 531 00:30:42,800 --> 00:30:45,760 Speaker 1: of your daily life, really that's the predictor of how 532 00:30:45,880 --> 00:30:48,080 Speaker 1: you're going to be. What you might you know, feel 533 00:30:48,080 --> 00:30:51,000 Speaker 1: bad about moving forward, what kind of illness you might get. 534 00:30:51,040 --> 00:30:53,600 Speaker 1: Those informations should be available to yourself, and then then 535 00:30:53,640 --> 00:30:56,400 Speaker 1: you should be, you know, deciding whether you want to 536 00:30:56,400 --> 00:30:59,120 Speaker 1: share that for you know, some value benefits that you 537 00:30:59,200 --> 00:31:02,840 Speaker 1: might get. But all those choices, all those possibilities are 538 00:31:02,920 --> 00:31:07,040 Speaker 1: coming because of the technology moving forward, and it's exciting 539 00:31:07,080 --> 00:31:09,920 Speaker 1: to see that all those technologies, even though they are 540 00:31:09,920 --> 00:31:13,520 Speaker 1: in different disciplines, are all maturing so quickly that we're 541 00:31:13,640 --> 00:31:17,360 Speaker 1: lucky that it's converging at this point. That to me, 542 00:31:18,400 --> 00:31:21,240 Speaker 1: as you were saying earlier in this episode about you know, 543 00:31:21,280 --> 00:31:23,560 Speaker 1: the technology being in the background, it's almost as if 544 00:31:23,600 --> 00:31:26,400 Speaker 1: you live in a magical house at that point that 545 00:31:26,520 --> 00:31:30,040 Speaker 1: is anticipating things, and it's working on your behalf and 546 00:31:30,080 --> 00:31:33,640 Speaker 1: solving problems, possibly before you even realize that there was 547 00:31:33,680 --> 00:31:37,160 Speaker 1: a problem to solve. Yes, yes, I love it. And 548 00:31:37,200 --> 00:31:41,280 Speaker 1: then I've been always imagining that house is not just 549 00:31:41,440 --> 00:31:45,160 Speaker 1: a roof in wall that shields you from the outside harshness. 550 00:31:45,520 --> 00:31:48,080 Speaker 1: It's going to have to protect you in a very 551 00:31:48,120 --> 00:31:51,920 Speaker 1: different way moving forward. Yes, agreed. And even as you 552 00:31:51,960 --> 00:31:55,280 Speaker 1: said before, like the idea of especially in the pandemic, 553 00:31:55,440 --> 00:31:59,640 Speaker 1: of trying to separate home and work, and how difficult 554 00:31:59,640 --> 00:32:02,280 Speaker 1: that was even before we were all staying at home. 555 00:32:02,400 --> 00:32:05,680 Speaker 1: It was hard. Now it's it feels like it's impossible. 556 00:32:06,080 --> 00:32:08,440 Speaker 1: It's going to be really important for us to have 557 00:32:08,840 --> 00:32:11,880 Speaker 1: the technologies that allow us to set up those boundaries 558 00:32:12,320 --> 00:32:16,720 Speaker 1: so that we can have both a satisfying work life 559 00:32:17,040 --> 00:32:22,520 Speaker 1: and a rich and valuable home life at the same time. Exactly, 560 00:32:23,840 --> 00:32:26,480 Speaker 1: I wasn't about to let Yoki go without asking her 561 00:32:26,880 --> 00:32:30,880 Speaker 1: one more thing. In your opinion, what do you think 562 00:32:30,960 --> 00:32:37,640 Speaker 1: is the most misunderstood technology. I actually think that AI 563 00:32:39,160 --> 00:32:44,480 Speaker 1: is misunderstood, and you know, there's a lot of advancement 564 00:32:44,680 --> 00:32:49,280 Speaker 1: and excitement, but incredible fear of what it could be. 565 00:32:49,360 --> 00:32:52,720 Speaker 1: It's going to take over human you know, intelligence, it's 566 00:32:52,760 --> 00:32:55,640 Speaker 1: going to rule the world. It made an incredible progress 567 00:32:55,680 --> 00:32:58,040 Speaker 1: of course since that, you know, the eighties and the nineties, 568 00:32:58,080 --> 00:33:01,560 Speaker 1: when you know the speed of things limited, ability to 569 00:33:01,600 --> 00:33:04,520 Speaker 1: collect data was limited, and now we look at and 570 00:33:04,560 --> 00:33:06,640 Speaker 1: put a massive amount of data to be able to 571 00:33:06,680 --> 00:33:09,680 Speaker 1: do a lot of you know, inference that we couldn't 572 00:33:09,680 --> 00:33:13,640 Speaker 1: do before. So it's true, it's make advancements. It's not 573 00:33:14,040 --> 00:33:18,680 Speaker 1: the fearful thing. It's just not there yet. So no 574 00:33:18,760 --> 00:33:20,800 Speaker 1: offense to anybody who's working on a machine learning and 575 00:33:20,800 --> 00:33:23,280 Speaker 1: an amazing advancement. And I know there's a lot of 576 00:33:23,400 --> 00:33:26,760 Speaker 1: effort of course to you know, surpass human intelligence, and 577 00:33:26,800 --> 00:33:29,400 Speaker 1: those things will push a lot of technology forward, but 578 00:33:29,480 --> 00:33:31,640 Speaker 1: I don't want people to be scared of it or 579 00:33:31,680 --> 00:33:35,920 Speaker 1: avoid it to the point that they're not benefiting. It's 580 00:33:35,920 --> 00:33:38,880 Speaker 1: not that time, Yogi. That was a great answer because 581 00:33:39,280 --> 00:33:41,560 Speaker 1: it reminds me of a couple of things. One is that, 582 00:33:41,680 --> 00:33:46,600 Speaker 1: like as you say, in very specific implementations, under very 583 00:33:46,640 --> 00:33:50,880 Speaker 1: specific circumstances, computers do phenomenal things at a level that 584 00:33:50,920 --> 00:33:54,600 Speaker 1: we humans just cannot do. But those are very specific 585 00:33:55,040 --> 00:33:57,320 Speaker 1: and humans the one of the amazing things about us 586 00:33:57,360 --> 00:34:00,280 Speaker 1: is that we are general purpose machines. We and do 587 00:34:00,520 --> 00:34:04,920 Speaker 1: lots of stuff, and computers typically, or machines or robots 588 00:34:04,960 --> 00:34:08,160 Speaker 1: typically can only do a subset of those things, and 589 00:34:08,239 --> 00:34:12,320 Speaker 1: sometimes not nearly as well as a human could. Yoki. 590 00:34:12,400 --> 00:34:16,560 Speaker 1: This has been a really inspiring conversation, and I am 591 00:34:16,640 --> 00:34:19,600 Speaker 1: so thankful to have had the opportunity to speak with 592 00:34:19,640 --> 00:34:22,360 Speaker 1: you today. Thank you for joining us. Oh my gosh, 593 00:34:22,400 --> 00:34:24,480 Speaker 1: it was so fun. Thank you. Let's do it again. 594 00:34:28,040 --> 00:34:31,240 Speaker 1: Yoki brought this up in our conversation, but it really 595 00:34:31,520 --> 00:34:35,600 Speaker 1: is worth driving home. We are currently in an environment 596 00:34:35,680 --> 00:34:39,080 Speaker 1: in which multiple technologies have matured in such a way 597 00:34:39,239 --> 00:34:43,239 Speaker 1: as to present incredible opportunities. And while Yoki and I 598 00:34:43,320 --> 00:34:46,320 Speaker 1: focused on ways that it will affect users and people 599 00:34:46,400 --> 00:34:50,640 Speaker 1: on an individual or maybe family unit basis, the same 600 00:34:50,680 --> 00:34:54,799 Speaker 1: can be said of businesses. The development of effective, powerful 601 00:34:54,960 --> 00:34:59,000 Speaker 1: and affordable sensors, the pairing of those sensors with transmitters, 602 00:34:59,040 --> 00:35:01,880 Speaker 1: and the underlying can nications networks that we have with 603 00:35:01,960 --> 00:35:06,799 Speaker 1: five G are going to enable world changing solutions. I 604 00:35:06,840 --> 00:35:10,359 Speaker 1: expect every major company in the world is looking at 605 00:35:10,400 --> 00:35:13,719 Speaker 1: how to leverage these technologies to deliver more value to 606 00:35:13,800 --> 00:35:16,920 Speaker 1: customers and to drive down costs of business and to 607 00:35:17,000 --> 00:35:22,279 Speaker 1: increase efficiency and productivity two untold levels. It's truly amazing 608 00:35:22,600 --> 00:35:25,959 Speaker 1: to see how the Internet of things, the speed of communication, 609 00:35:26,360 --> 00:35:29,880 Speaker 1: and our ability to collect and analyze data have all 610 00:35:29,920 --> 00:35:34,399 Speaker 1: reached incredible sophisticated levels. And have the potential for those 611 00:35:34,440 --> 00:35:37,640 Speaker 1: technologies to make a positive impact. I mean, it's impossible 612 00:35:37,719 --> 00:35:41,759 Speaker 1: to overstate how phenomenal this is. I can't wait to 613 00:35:41,840 --> 00:35:45,280 Speaker 1: hear how Johanna evolves over time and rolls out various 614 00:35:45,280 --> 00:35:47,839 Speaker 1: products in an effort to give us back the most 615 00:35:47,880 --> 00:35:51,880 Speaker 1: precious resource we have time. Please be sure to come 616 00:35:51,920 --> 00:35:54,360 Speaker 1: back and listen as we talk with more leaders in 617 00:35:54,400 --> 00:35:57,840 Speaker 1: the tech space to get their insight on future episodes 618 00:35:57,920 --> 00:36:06,760 Speaker 1: of The Restless Ones. I'm Oathan Strickland at T Mobile. 619 00:36:06,760 --> 00:36:10,359 Speaker 1: For business, unconventional thinking means we see things differently so 620 00:36:10,440 --> 00:36:13,200 Speaker 1: you can focus on what matters most. That's why we've 621 00:36:13,239 --> 00:36:16,840 Speaker 1: built America's largest, fastest five G network while remaining a 622 00:36:16,880 --> 00:36:20,560 Speaker 1: partner who delivers exceptional customer support and five G included 623 00:36:20,600 --> 00:36:24,160 Speaker 1: in every plan so you get it all. Unconventional thinking 624 00:36:24,239 --> 00:36:27,000 Speaker 1: is better for business. Fastest five G based on average 625 00:36:27,040 --> 00:36:29,480 Speaker 1: overall combined five G speeds according to Open Signal Awards 626 00:36:29,520 --> 00:36:32,520 Speaker 1: USA five G User Experience Report October one. See five 627 00:36:32,560 --> 00:36:36,360 Speaker 1: D device coverage and access details at T mobile dot com.