WEBVTT 1 00:00:00.680 --> 00:00:04.599 And with the Family Medical ev Act, you're allowed to take time off by 2 00:00:04.719 --> 00:00:09.880 law and your employer doesn't need to know the reason. So there are two 3 00:00:10.000 --> 00:00:14.439 good reasons. You've got insurance you can use for your addiction problem. And 4 00:00:14.599 --> 00:00:20.559 with the Family Medical Evact, it's completely confidential. Call now eight hundred three 5 00:00:20.640 --> 00:00:26.239 nine eight seven four one four. That's eight hundred three nine eight seventy four 6 00:00:26.559 --> 00:00:34.920 fourteen or on board kcaa's Inland Talk Express KCAA Homelinda ten fifty am, the 7 00:00:35.000 --> 00:00:45.640 station that needs noble your behind. The information economy has a rod. The 8 00:00:45.719 --> 00:00:51.600 world is teeming with innovation as new business models reinvent every industry industry. Inside 9 00:00:51.640 --> 00:00:56.640 Analysis is your source of information and insights about how to make the most of 10 00:00:56.679 --> 00:01:02.439 this exciting new era. Learn more and inside Analogs, dotside analysis dot com. 11 00:01:02.479 --> 00:01:11.239 And now here's your host, Eric Kavanaugh. Oh yes, indeed, 12 00:01:11.319 --> 00:01:15.840 folks, welcome to the future and yours truly. Eric Kavanaugh is here for 13 00:01:15.879 --> 00:01:19.040 the only coast to coast radio show all about the information economy Inside Analysis, 14 00:01:19.280 --> 00:01:23.599 and we're gonna be talking with an expert about one of the most important things 15 00:01:23.640 --> 00:01:26.519 in business today. The network, Yes, the network. We all know 16 00:01:26.560 --> 00:01:30.359 when the network is slow. Everyone knows when that happens, and that's no 17 00:01:30.480 --> 00:01:34.599 fun at all. I saw a great meme a while ago that said something 18 00:01:34.719 --> 00:01:38.400 like, if you want to find out who you're dealing with, put them 19 00:01:38.400 --> 00:01:42.840 on a really slow Internet connection for an hour and just see how they respond. 20 00:01:42.799 --> 00:01:48.079 That's gonna tell just how patient a person you are. You never go 21 00:01:48.280 --> 00:01:49.959 back right. Once you get things faster, you can't go back to having 22 00:01:51.000 --> 00:01:53.319 them slower. You know. I remember the old days with AOL friend of 23 00:01:53.359 --> 00:01:56.560 mine set oh, get on AOL. I really didn't want to do it. 24 00:01:56.920 --> 00:02:00.879 I did it anyway, and downloading images downloading image is and when I 25 00:02:00.920 --> 00:02:02.879 tried to get off of it, like six months later, they're like, 26 00:02:04.319 --> 00:02:07.640 what credit card did you use to log onto? I'm like, I don't 27 00:02:07.760 --> 00:02:10.560 remember, dude. I just want to get off that service. But that's 28 00:02:10.599 --> 00:02:14.919 the old days. Things are better now. And since we're gonna be talking 29 00:02:14.919 --> 00:02:19.680 about networking with Rob Tiffany from a very cool company called Red Bison, I 30 00:02:19.719 --> 00:02:23.560 figured I throw out my one bad, terrible networking story from the early days 31 00:02:23.560 --> 00:02:28.240 in Seattle at TDWY. They went out and they bought that VoIP stuff and 32 00:02:28.280 --> 00:02:31.680 it was just awful. And I noticed it would get worse throughout the call. 33 00:02:31.759 --> 00:02:35.159 So if you're on a call for like thirty minutes or forty minutes, 34 00:02:35.639 --> 00:02:38.759 like forty minutes in man, it's like, I mean, I like all 35 00:02:38.800 --> 00:02:43.199 that kind of stuff. You're just like I remember talking to management saying, 36 00:02:43.240 --> 00:02:46.719 guys, don't you think it's important that we be able to communicate to people 37 00:02:46.840 --> 00:02:52.319 outside the company kind of a critical component of information sharing. But anyway, 38 00:02:52.400 --> 00:02:54.879 things are so much better these days. And Rob Tiffany, you know a 39 00:02:54.960 --> 00:02:59.800 few things about networking, and you guys have a really interesting business model where 40 00:02:59.840 --> 00:03:02.479 you will build out the network for commercial office buildings and then you do all 41 00:03:02.560 --> 00:03:06.000 kinds of other things for them as well. So, first of all, 42 00:03:06.039 --> 00:03:09.879 tell us a bit about yourself and read Bison and why modern networking is so 43 00:03:10.000 --> 00:03:14.159 much better than it used to be. Sure, absolutely, thanks for having 44 00:03:14.159 --> 00:03:20.120 me. Yeah, so Red Bison. The bison is related to buffaloes and 45 00:03:20.159 --> 00:03:24.280 bisons in North Dakota, where our founder was originally from. Nice. But 46 00:03:24.360 --> 00:03:27.680 yeah, it's the company, you know, it's kind of a network as 47 00:03:27.719 --> 00:03:30.080 a service company. Is kind of the primary you know, backstory to the 48 00:03:30.120 --> 00:03:35.800 company. I'd say it's the intersection of high speed networks to commercial real estate, 49 00:03:36.439 --> 00:03:40.120 if that makes sense. And so whether it's skyscraper's, office buildings, 50 00:03:40.159 --> 00:03:45.680 office parks, multifamily, you know, it could be condos or apartments anyway. 51 00:03:45.879 --> 00:03:49.800 You know, bringing in high speed you know, dual fiber you know, 52 00:03:49.840 --> 00:03:53.840 like ten gigabit fiber into into buildings, then you kind of wire up 53 00:03:53.879 --> 00:03:58.479 the buildings. If anybody has walked into building, they saw those weird telecom 54 00:03:58.520 --> 00:04:02.599 closets or here weird strange terms like MDF or IDF or whatever. Anyway, 55 00:04:02.719 --> 00:04:06.680 there's some strange stuff in those closets. It's all about networking and building management, 56 00:04:06.840 --> 00:04:11.400 you know. You know, so you'll see stuff like from Honeywell and 57 00:04:11.479 --> 00:04:15.159 Johnson Controls or Siemens and all that kind of stuff that make these big buildings 58 00:04:15.240 --> 00:04:17.240 work. And so so yeah, we bring in the high speed networks in 59 00:04:17.279 --> 00:04:21.040 there, then fiber and Ethernet going up through all the way up through the 60 00:04:21.040 --> 00:04:24.560 building and out through you know, all the stuff you don't see that you 61 00:04:24.600 --> 00:04:27.920 take for granted that's in the walls, you know, like old stuff like 62 00:04:27.959 --> 00:04:31.759 ethernet right and Cat six cabling, you know, and then and then Wi 63 00:04:31.759 --> 00:04:35.519 Fi access points on the end of that. Everybody thinks we're all wireless, 64 00:04:35.519 --> 00:04:43.040 but it's actually wireless is made of wires. Yeah. My background, it's 65 00:04:43.079 --> 00:04:46.000 mostly software. Uh. You know, I spent most of my career at 66 00:04:46.000 --> 00:04:50.120 Microsoft. First half was doing Windows Mobile, Windows Phone, so I had 67 00:04:50.120 --> 00:04:54.759 to have really thick skin. You know. Things were okay when it was 68 00:04:54.800 --> 00:04:58.800 just us in BlackBerry battling it out, and then the iPhone came along and 69 00:04:58.879 --> 00:05:03.240 it started to get ugly and so and then the second half was building Azure 70 00:05:03.360 --> 00:05:08.279 and that was a lot of fun, building this global cloud thing and how 71 00:05:08.319 --> 00:05:13.560 you design that for availability, and then building Azure IoT. Most might have 72 00:05:13.639 --> 00:05:16.279 just so much background in the Internet of Things, industrial IoT and stuff like 73 00:05:16.319 --> 00:05:20.279 that, and so we built Azure IoT and that was a great building. 74 00:05:20.319 --> 00:05:26.959 You know, Global IoT platform got recruited out of there by Hitachi because they 75 00:05:27.000 --> 00:05:30.759 wanted to build an industrial IoT platform, and so I went and did that 76 00:05:31.199 --> 00:05:33.800 and got to design and build the whole thing from scratch. That was a 77 00:05:33.839 --> 00:05:39.360 great experience. I was living in Japanese factories and wow, you know, 78 00:05:39.639 --> 00:05:42.600 making it real. I think that's probably where I first got into that whole 79 00:05:42.639 --> 00:05:48.199 weird digital twin world. You know, modeling machines or bullet trains or all 80 00:05:48.279 --> 00:05:51.720 kinds of crazy stuff like that, And so you've got IoT and digital twins 81 00:05:51.800 --> 00:05:57.360 kind of together, and then of course you're playing analytics or machine learning AI, 82 00:05:58.519 --> 00:06:01.519 and then back to networks. More recently, I was a VP over 83 00:06:01.519 --> 00:06:05.519 at Erickson, which is one of the companies that makes all the cellular gear, 84 00:06:05.639 --> 00:06:10.040 the five gief stuff you always hear about in Sweden. So it's flying 85 00:06:10.040 --> 00:06:15.040 from Seattle to Sweden every month until COVID of course, and then I'm on 86 00:06:15.199 --> 00:06:18.439 phone calls and weird hours of the night, you know, the rest in 87 00:06:18.480 --> 00:06:23.480 Stockholm. But yeah, so we're pulling it all together here at Red Bison. 88 00:06:23.560 --> 00:06:26.560 So yeah, it's pretty interesting stuff for sure. Yeah, that is 89 00:06:26.600 --> 00:06:31.759 cool. And I totally see the alignment between IoT and building out the infrastructure 90 00:06:31.879 --> 00:06:36.240 for office towers because you have so many objects. You got all these different 91 00:06:36.279 --> 00:06:41.480 routers, you got all these lights, and of course smart cities and sustainability 92 00:06:41.480 --> 00:06:45.879 these are all big issues these days. Knowing what it really costs to have 93 00:06:45.959 --> 00:06:48.000 all these lights on, Knowing what it costs to have all this stuff running, 94 00:06:48.439 --> 00:06:53.480 Knowing how to be able to preen things or prune it down when you 95 00:06:53.600 --> 00:06:56.279 need to, and you know, knowing what the impact of all that is 96 00:06:56.360 --> 00:07:00.319 and you know that gets into these digital twins. And I'm a huge fan 97 00:07:00.480 --> 00:07:03.879 of the robust digital twin because you can really play around with ideas and you 98 00:07:03.879 --> 00:07:05.959 can say, well, what if we did this and what if we did 99 00:07:06.000 --> 00:07:10.240 that, and you do that in your digital twin environment and you get results 100 00:07:10.279 --> 00:07:12.600 and it says, Okay, this is how the costs will go up, 101 00:07:12.600 --> 00:07:15.680 this is how the usage will go You know. Those kinds of things are 102 00:07:15.680 --> 00:07:18.959 really important for planning, right absolutely, and lets you bring the whole thing 103 00:07:19.000 --> 00:07:21.800 to life, you know, makes it a living building. You know, 104 00:07:23.279 --> 00:07:25.759 you think, you know, because you're right, there's the whole bigger smart 105 00:07:25.759 --> 00:07:30.360 city thing. But mostly cities are made of buildings, is the primary thing. 106 00:07:30.439 --> 00:07:32.879 And so if you think of digital twins and kind of zooming in, 107 00:07:33.000 --> 00:07:36.480 it's the it's kind of the overall property. Maybe it's a corporate campus and 108 00:07:36.519 --> 00:07:40.839 then one or more buildings, and then each building has one or more floors, 109 00:07:40.879 --> 00:07:44.879 and each floor has one or more A lot of people are just calling 110 00:07:44.920 --> 00:07:46.759 them spaces. Now there's you know, there was this smart city, a 111 00:07:46.839 --> 00:07:49.959 smart building. I'm hearing a lot of people kind of tver to smart spaces 112 00:07:50.399 --> 00:07:56.160 or sustainable spaces, maybe because they needed to genericize is it office, is 113 00:07:56.240 --> 00:08:00.399 a conference room, is it the lobby, is it whatever? So you 114 00:08:00.480 --> 00:08:05.000 kind of have these spaces, but they're all they're digital twins, and so 115 00:08:05.160 --> 00:08:07.319 each one of these spaces you can, you know, in the software you 116 00:08:07.800 --> 00:08:11.000 of digital twins, you set properties for them and bring them to life. 117 00:08:11.079 --> 00:08:18.199 And so you mentioned you know, just uh throttling things back based on you 118 00:08:18.240 --> 00:08:22.639 know, we can have occupancy sensors. You know, what did everybody discover 119 00:08:22.800 --> 00:08:26.040 during COVID. You had all these office buildings going full speed ahead with lighting 120 00:08:26.040 --> 00:08:30.959 and HVAC and just burning energy like there was no tomorrow, and there was 121 00:08:31.000 --> 00:08:33.159 nobody in them, right, you know, the buildings were empty, half 122 00:08:33.200 --> 00:08:37.360 empty, you know. Even well in today, you know, we've kind 123 00:08:37.360 --> 00:08:41.440 of this kind of in between hybrid back to work and so a lot of 124 00:08:41.480 --> 00:08:43.360 times most of the people you're seeing are kind of like Tuesday, Wednesday, 125 00:08:43.399 --> 00:08:48.639 Thursday ish, you know, right, And so you know, powering those 126 00:08:48.679 --> 00:08:54.000 buildings buildings are one of the biggest emitters you know of you know, greenhouse 127 00:08:54.039 --> 00:08:58.000 gas emissions, and so if there's nobody in there, even if there is, 128 00:08:58.039 --> 00:09:03.639 there's ways to be smart about it. And so that network software IoT 129 00:09:03.919 --> 00:09:09.519 digital twins analytics AI building altogether to make smarter buildings, but probably make sustainable 130 00:09:09.519 --> 00:09:13.559 buildings, you know. Well, yeah, and like the hidden challenge of 131 00:09:13.679 --> 00:09:18.919 IoT is that you have so many objects sometimes and so it's hard to even 132 00:09:20.519 --> 00:09:24.519 represent visually what's happening there. And of course, you know, you get 133 00:09:24.559 --> 00:09:28.080 devices that there are so many cool things happening in the IoT space. I 134 00:09:28.120 --> 00:09:30.840 mean, I can't remember the name, but I had a company on here 135 00:09:30.879 --> 00:09:37.960 that was working in low frequency IoT and basically it's I think it's blockchain underpin. 136 00:09:39.080 --> 00:09:41.360 You probably know who these guys are. I think they're based out of 137 00:09:41.360 --> 00:09:46.840 often somewhere, But basically it's like a low frequency network that can connect IoT 138 00:09:48.039 --> 00:09:52.799 devices with very little power to the home base. And so they're really interesting 139 00:09:52.799 --> 00:09:54.399 things that you can do for just kind of staying on top of things, 140 00:09:54.440 --> 00:09:58.600 where is the money going? Like what does it cost to air condition this 141 00:09:58.759 --> 00:10:03.320 building? And what if we play around with different options on different floors and 142 00:10:03.360 --> 00:10:05.440 things of this nature. Even the elevators, I mean, I have to 143 00:10:05.480 --> 00:10:11.759 think that for some buildings, strategic intelligent elevator management is a pretty good deal, 144 00:10:11.879 --> 00:10:16.039 right absolutely, Because you're right, most buildings it's still kind of mindless 145 00:10:16.320 --> 00:10:20.320 elevators are just doing like what they've done for the last fifty years. Right, 146 00:10:20.600 --> 00:10:24.799 of course that's an even bigger thing. The reality is most buildings are 147 00:10:24.799 --> 00:10:28.600 just old. You know. There's the world that we want, and we 148 00:10:28.639 --> 00:10:33.879 talk about futuristic cities and stuff like that, and we kind of joke about 149 00:10:33.879 --> 00:10:37.320 it. Let's say fifty years from now, when you think you're gonna have 150 00:10:37.399 --> 00:10:41.679 these futuristic logans run looking cities. But the reality is is all that old 151 00:10:41.720 --> 00:10:46.440 stuff that's one hundred and fifty years old will also still be there amongst it. 152 00:10:46.080 --> 00:10:50.039 And you know, unless they're going to demolish all the old buildings and 153 00:10:50.039 --> 00:10:52.320 we go to New York City, go anywhere, they're all still there. 154 00:10:52.679 --> 00:10:56.879 Right. People still use old buildings, and so how can you make them 155 00:10:56.919 --> 00:11:00.480 more efficient? Right? You know? And so it's just like my time 156 00:11:00.519 --> 00:11:03.720 in industrial IoT. You know, it's you're going to be retrofitting old stuff 157 00:11:03.840 --> 00:11:07.519 for a long time to get value. Lots of people dove into that IoT 158 00:11:07.679 --> 00:11:11.720 space thinking it was going to rip out all the old stuff and put in 159 00:11:11.799 --> 00:11:16.639 new, shiny, high tech things. And that's when the guy you're talking 160 00:11:16.639 --> 00:11:20.519 to is like, get out of my office. You know, tens of 161 00:11:20.519 --> 00:11:24.159 millions of dollars for all this stuff, and we're not throwing it out. 162 00:11:24.240 --> 00:11:26.600 You know, it's just not going to happen, you know. But yeah, 163 00:11:26.679 --> 00:11:30.039 it's a good point, you know. And so those sensors, those 164 00:11:30.039 --> 00:11:33.159 things, those objects, they're inside those spaces, and the space is kind 165 00:11:33.159 --> 00:11:37.159 of the twin and you know, you might be saying, well, gosh, 166 00:11:37.519 --> 00:11:43.639 this this conference room. When there's this X number of people in here, 167 00:11:43.879 --> 00:11:46.039 and you know, it gets too hot or there's too much CO two 168 00:11:46.120 --> 00:11:50.559 in the air or whatever it is you're looking for. You can start you 169 00:11:50.600 --> 00:11:52.679 know, there's that kind of real time streaming data where it's telling you what's 170 00:11:52.679 --> 00:11:58.519 happening now, and you've got occupancy sensors and temperature and emissions and stuff like 171 00:11:58.600 --> 00:12:03.279 that. And then so then you can take that same data and train models, 172 00:12:03.480 --> 00:12:07.080 you know, AI models or what we used to call last week mL, 173 00:12:09.039 --> 00:12:13.320 but machine learning's not cool enough, I guess anymore. And so to 174 00:12:13.360 --> 00:12:16.120 tell you what's going to happen down the road, you know, predict Oh 175 00:12:16.159 --> 00:12:20.240 gosh, I noticed every Thursday afternoon this conference room is packed full of people 176 00:12:20.879 --> 00:12:24.759 and they always complain about it being too hot or whatever, you know, 177 00:12:24.879 --> 00:12:28.080 And so you can start using those kind of analytics to predict the future and 178 00:12:28.159 --> 00:12:33.919 make things better for folks. But yeah, space for sure. Well, 179 00:12:33.960 --> 00:12:37.679 and you can learn all sorts of things about yourself, about your business, 180 00:12:37.799 --> 00:12:41.240 about the marketplace, and just by analyzing the data. By looking at the 181 00:12:41.320 --> 00:12:46.039 data and understanding the usage to your point, you can figure out, hey, 182 00:12:46.240 --> 00:12:48.440 for some reason, no one's ever here or very few people here Wednesday 183 00:12:48.480 --> 00:12:52.200 mornings, so we don't have to turn things on as much. You don't 184 00:12:52.240 --> 00:12:56.320 have to get the AC cranking as much. I mean, we really are 185 00:12:56.440 --> 00:13:00.840 an AC overkill kind of society here in America. Right, But my wife 186 00:13:00.840 --> 00:13:03.639 gets called all the time and walk into any corporate headquarters, it's like, 187 00:13:03.720 --> 00:13:07.039 oh my god, it's like sixty four degrees in here. Yeah, I 188 00:13:07.039 --> 00:13:09.840 mean I get the story about they're trying to kill the mold. Okay, 189 00:13:09.879 --> 00:13:13.120 I got that, we don't want mold everywhere, But still, does it 190 00:13:13.159 --> 00:13:16.519 have to be sixty four or going to be like seventy one seventy two? 191 00:13:16.200 --> 00:13:18.519 You know, it's a lot of money to get spent on that stuff. 192 00:13:18.759 --> 00:13:22.799 There is a lot. And it's funny you talk about being over chilled and 193 00:13:22.840 --> 00:13:24.960 stuff like that. When I was with Hitachi and so I was a lot 194 00:13:26.080 --> 00:13:28.759 in Japan, a lot. I remember going all these office buildings skyscrapers in 195 00:13:28.759 --> 00:13:35.080 Tokyo and in the summertime, it's a little warm in there actually, and 196 00:13:35.120 --> 00:13:37.679 I'm like, what's that all about. It's that way everywhere. And it 197 00:13:37.720 --> 00:13:43.120 turns out they think of it in Japan as a shared sacrifice to reduce energy 198 00:13:43.200 --> 00:13:48.360 usage and therefore costs, right, and so it's the first thing you notice 199 00:13:48.440 --> 00:13:54.559 when you go into these beautiful skyscrapers in Tokyo in August and you're like wow, 200 00:13:54.799 --> 00:13:58.559 and it's like they're all on board. You know, the whole society's 201 00:13:58.600 --> 00:14:03.720 on board shared sacrifice to cut costs and energy usage. I was like, 202 00:14:03.759 --> 00:14:07.080 well, that's really interesting. I don't know if our country could get together 203 00:14:07.120 --> 00:14:09.679 here in the US just get on board with that or not. Well, 204 00:14:09.720 --> 00:14:11.279 you know, here's the interesting thing, right, I'm a data guy, 205 00:14:11.440 --> 00:14:15.360 and our show is focused heavily on the data side, because you want to 206 00:14:15.360 --> 00:14:16.360 see the data. What is the data tell you? You have your own 207 00:14:16.360 --> 00:14:20.559 opinions about things, but when you can see the data, then you really 208 00:14:20.639 --> 00:14:22.519 understand, oh, okay, that's what it's really costing. And with a 209 00:14:22.720 --> 00:14:28.240 situation like you're providing with a solution like this, you can see the data 210 00:14:28.279 --> 00:14:31.279 and review the data and talk to people about it and see, hey, 211 00:14:31.399 --> 00:14:35.919 let's just test this for five days. Let's change the temperature from you know, 212 00:14:35.960 --> 00:14:41.039 sixty nine to seventy two, and then watch the usage. I mean, 213 00:14:41.320 --> 00:14:45.120 what's cool is you're starting to see even power companies and end user facing 214 00:14:45.159 --> 00:14:48.960 companies embracing this. So you get your little email, here's your power usage 215 00:14:48.960 --> 00:14:52.120 from the last week. Here, saw compares to last year or last week 216 00:14:52.200 --> 00:14:54.879 or whatever, And so you kind of start to get a field for things. 217 00:14:54.200 --> 00:15:00.200 And the bottom line is what gets measured gets managed. And so when 218 00:15:00.240 --> 00:15:03.679 you can show the board and your team, hey guys, we would actually 219 00:15:03.679 --> 00:15:09.120 save twenty thousand dollars a month if we would just raise the temperature up three 220 00:15:09.200 --> 00:15:11.879 degrees. And then you know, we're going to give each of you a 221 00:15:11.919 --> 00:15:15.039 five hundred dollars bonus at the end of the year. How's that alright? 222 00:15:15.399 --> 00:15:18.960 Like, Okay, I love your comment, though. What gets measured gets 223 00:15:18.960 --> 00:15:24.120 managed, what gets managed gets measured or improved. I am so on that. 224 00:15:24.720 --> 00:15:28.200 And I always always when I talk about IoT, you know, without 225 00:15:28.240 --> 00:15:31.440 it, you're just guessing. You might be making educated guess, right, 226 00:15:31.480 --> 00:15:37.000 but with IoT, you're knowing you've got that realtime data feed and it's letting 227 00:15:37.039 --> 00:15:41.200 you know this is really what's going on. You're not imagining it or using 228 00:15:41.240 --> 00:15:46.639 a gut that's right, and it's so and so often I've noticed with these 229 00:15:46.720 --> 00:15:50.279 kinds of things, you will you will see things that surprise you. I 230 00:15:50.279 --> 00:15:54.080 mean, even though it's your office, it's your environment, you wouldn't think 231 00:15:54.080 --> 00:15:56.960 you should be surprised. But every time you look at some significant data set, 232 00:15:58.039 --> 00:16:00.120 I've found you're always surprised by something. Yeah, so you're going to 233 00:16:00.200 --> 00:16:03.679 see that outlier. It's like, well, what is that thing? Let's 234 00:16:03.720 --> 00:16:06.879 dig into that a bit more and understand what's going on there. And you 235 00:16:06.960 --> 00:16:08.159 know, to your point, you can save a lot of money, a 236 00:16:08.200 --> 00:16:11.360 lot of time, a lot of maintenance. You know. That's the other 237 00:16:11.399 --> 00:16:15.919 interesting thing about IoT is is predictive maintenance stuff. Absolutely. I've been a 238 00:16:17.000 --> 00:16:18.679 huge fan of this for years. As soon as I learned about I was 239 00:16:18.720 --> 00:16:22.799 like, oh, wow, that's cool, because the engineer who has to 240 00:16:22.840 --> 00:16:26.720 go around and check all the doors and check all the windows and all that 241 00:16:26.720 --> 00:16:32.200 stuff, that's a really boring job unless you've got some IoT solution where it's 242 00:16:32.360 --> 00:16:36.360 predicting, Hey, this heater is going to fail. We know because we 243 00:16:36.480 --> 00:16:40.120 recognize the pattern and usage. It goes up and it starts making a noise, 244 00:16:40.200 --> 00:16:41.120 And noises are a big part of that stuff too, right, like 245 00:16:41.159 --> 00:16:47.320 hearing the sound, noise, vibration. And it's like any industry with any 246 00:16:47.399 --> 00:16:51.360 kind of machines, whether you're in a skyscraper or a factory or a car, 247 00:16:51.720 --> 00:16:55.000 you know, and you always hear the deal that the folks have been 248 00:16:55.000 --> 00:16:57.559 working on those for years. When I put my hand on this machine, 249 00:16:57.600 --> 00:17:02.679 it vibrates a certain way. It's about to die next Thursday, right now. 250 00:17:03.200 --> 00:17:07.240 And the reality is is we can't rely on that forever. Those folks 251 00:17:07.279 --> 00:17:10.559 are going to retire. I mean, I'm up here in Seattle on it. 252 00:17:10.799 --> 00:17:12.799 Every year there's some deal in the news. We're like, wow, 253 00:17:12.880 --> 00:17:18.200 you know, all those aircraft engineers at Boeing they're about to retire. And 254 00:17:18.200 --> 00:17:21.359 no one knows how to build airplanes anymore, and we don't know how to 255 00:17:21.640 --> 00:17:23.599 monitor. And it's like you got to let the data tell you. You've 256 00:17:23.599 --> 00:17:27.720 got to start instrumenting everything and let the data be your guide, you know. 257 00:17:29.480 --> 00:17:33.680 In a way, that's it. It's the instrumentation and then it's the 258 00:17:33.799 --> 00:17:37.039 collection of all that data. And that's where maybe in the next segment we'll 259 00:17:37.039 --> 00:17:41.480 get more into the the the unwielding nature of IoT because you know, what 260 00:17:41.519 --> 00:17:48.880 you're typically measuring are simple things like temperature or amount of light or CO two 261 00:17:48.960 --> 00:17:52.240 levels or whatever it is. It's it's some particular thing that the sensor is 262 00:17:52.279 --> 00:17:59.279 designed to watch for. But then again, trying to aggregate all that stuff 263 00:17:59.319 --> 00:18:03.559 and manage and it requires some some sophisticated knowledge about how to look for things 264 00:18:03.599 --> 00:18:07.079 like what is the pattern I'm trying to find in here? Is it when 265 00:18:07.160 --> 00:18:10.240 it goes down? Is it when it goes up? Is it like a 266 00:18:10.319 --> 00:18:14.440 variety of different things. That's what experience will tell you, with the aid 267 00:18:14.480 --> 00:18:18.880 of course of machine learning in the background, because the machine learning algorithms don't 268 00:18:18.920 --> 00:18:21.839 tend to sleep. They just work all night long and they do their little 269 00:18:21.839 --> 00:18:22.519 thing, and you wake up in the morning and they go, oh, 270 00:18:22.519 --> 00:18:25.519 why don't you look at this? Why don't look at that? And I 271 00:18:25.640 --> 00:18:27.880 for one thing, that's how most AI solutions are going to provide value in 272 00:18:27.920 --> 00:18:34.359 the future is by suggesting things to you based upon the baseline and the pattern 273 00:18:34.359 --> 00:18:37.680 they're seeing right now at this moment, folks, don't touch that. Del'll 274 00:18:37.680 --> 00:18:47.799 be right back. You're listening to Inside Analysis. Welcome back to Inside Analysis. 275 00:18:48.319 --> 00:18:53.680 Here's your host, Eric Tavanaugh. All right, folks back here on 276 00:18:53.720 --> 00:19:00.200 Inside Analysis. You're truly Eric Kavanaugh with Rob Tiffany of Red Bison. He's 277 00:19:00.200 --> 00:19:02.920 been all around work for a bunch of big companies. Ericson. I think 278 00:19:02.960 --> 00:19:07.160 ATACI was talking about earlier, and of course Microsoft building Azure. That's not 279 00:19:07.240 --> 00:19:11.079 a small job building out this what is basically a cloud platform. And I 280 00:19:11.160 --> 00:19:18.640 often joke the irony strikes me that Microsoft saved us from the monopoly of Amazon 281 00:19:18.680 --> 00:19:25.759 Web Services, since Microsoft had the monopoly for years of operating systems and that 282 00:19:25.920 --> 00:19:29.880 caused a lot of trouble. I had a theory that Linux was born out 283 00:19:29.880 --> 00:19:32.960 of a desire to escape from that, and someone told me, no, 284 00:19:33.079 --> 00:19:37.200 not really, But it did serendipitously work out that way, that Linux thanks 285 00:19:37.240 --> 00:19:41.319 to IBM dropping a billion dollars into it to harden it to make it an 286 00:19:41.359 --> 00:19:48.200 operating system for enterprise solutions, and it won, and now Linux is the 287 00:19:48.240 --> 00:19:52.079 de facto standard, and open sources teetering a little bit these days, but 288 00:19:52.680 --> 00:19:56.880 we wanted to get a bit more into the IoT stuff, because I think 289 00:19:56.920 --> 00:20:03.039 you have to appreciate how on wieldy it is to have, like even in 290 00:20:03.039 --> 00:20:06.799 a large office tower, like how many phone systems are plugged into this thing, 291 00:20:06.880 --> 00:20:11.640 how many HVAC systems, All these different systems are plugged in. They're 292 00:20:11.680 --> 00:20:15.000 all pulling on the power. And that you want to talk about black magic 293 00:20:15.039 --> 00:20:18.960 man, like really getting into power. Like in these older homes, you 294 00:20:18.240 --> 00:20:22.480 can tell, like when the heater turns on, the lights dim, you 295 00:20:22.519 --> 00:20:26.640 know, it's because it's like pulling on that flow of energy. And to 296 00:20:26.880 --> 00:20:30.640 really understand that, and I'm guessing you guys got some great data and analytics 297 00:20:30.640 --> 00:20:34.920 on that kind of stuff can be very compelling in terms of knowing how to 298 00:20:34.960 --> 00:20:40.720 save money, knowing how to provision services more effectively. And that's all really 299 00:20:40.759 --> 00:20:45.119 important because when the network doesn't work, ain't nobody happy, right, right? 300 00:20:45.680 --> 00:20:48.720 You know, the network is totally a trojan horse for us to get 301 00:20:48.720 --> 00:20:52.039 to do all those other great things. It really is like that, you're 302 00:20:52.079 --> 00:20:55.599 honest about that's fun it is, you know, you know, because I've 303 00:20:55.599 --> 00:21:00.319 seen other IoT players try to go after building management and do building IoT stuff 304 00:21:00.319 --> 00:21:03.279 because there's a lot of great use cases there and most of them just failed. 305 00:21:03.279 --> 00:21:07.480 They couldn't get into the building. They didn't know the right people, 306 00:21:07.599 --> 00:21:10.279 they didn't have the right you know. In the end, it's still about 307 00:21:10.279 --> 00:21:17.240 people and connections and what you're already doing there. And so since we go 308 00:21:17.319 --> 00:21:21.000 in, we're giving the building something they really really really want. People want 309 00:21:21.039 --> 00:21:22.839 fast internet and they want to be able to connect, and they needed to 310 00:21:22.839 --> 00:21:27.599 be reliable. And so because we do that, that gets us in there. 311 00:21:27.799 --> 00:21:32.039 And you can imagine if you own the network throughout the whole building, 312 00:21:32.400 --> 00:21:36.880 IoT needs a network to ride on, right, you know, and so 313 00:21:37.799 --> 00:21:41.200 like you mentioned earlier, you know the low low power, you know, 314 00:21:41.319 --> 00:21:45.039 low frequency stuff like Laura Wan and things like that. You know, people 315 00:21:45.160 --> 00:21:49.799 use outside where you have your IoT devices need to live for five or ten 316 00:21:49.880 --> 00:21:53.920 years on a battery. Luckily, in a building, we've got electricity to 317 00:21:53.920 --> 00:21:56.799 plug into, so we don't have to worry about that as much. But 318 00:21:56.880 --> 00:22:00.559 since we own the network, we've got the fastest, lowest latency network. 319 00:22:00.599 --> 00:22:06.920 You can imagine right there, all those IoT devices now it's easy for them 320 00:22:07.000 --> 00:22:11.880 to piggyback on that and for us to get to all that data. If 321 00:22:11.920 --> 00:22:15.839 you look think about like a pied chart of where the energy is being used 322 00:22:15.839 --> 00:22:19.119 in a building. You know, it's lighting an HVAC or your two biggest 323 00:22:19.319 --> 00:22:25.640 culprits. And then apparently then just everything that gets plugged in, all the 324 00:22:25.720 --> 00:22:30.240 extra stuff, whether it's a printer or your PC or whatever, a million 325 00:22:30.359 --> 00:22:33.960 things getting plugged in turns on, that turns out, that uses a huge 326 00:22:34.039 --> 00:22:40.559 chunk. And then of course there's that relationship between energy usage and emissions, 327 00:22:40.759 --> 00:22:45.039 right. It kind of goes hand in hand. And so you can monitor 328 00:22:47.039 --> 00:22:48.920 energy usage at a building level, you know, voltage, all that kind 329 00:22:48.960 --> 00:22:53.279 of stuff. But there's some great IoT sensors they have today where you can 330 00:22:53.839 --> 00:23:00.000 kind of do segmented monitoring of power usage in just certain parts of the building. 331 00:23:00.200 --> 00:23:04.240 They've got these little devices that you literally hook onto the cabling of the 332 00:23:04.279 --> 00:23:10.559 electricity. The power and the ambient energy coming off that cable is enough to 333 00:23:10.640 --> 00:23:14.440 power the IoT device. Wow. And then the IoT device a lot of 334 00:23:14.440 --> 00:23:18.480 times is using like that low low power, low uh frequency stuff like Laura 335 00:23:18.960 --> 00:23:22.519 to send because it's sending just little tiny bits and bites of data, nothing 336 00:23:22.559 --> 00:23:26.119 major, so you and it'll tell you how much. And so you can 337 00:23:26.160 --> 00:23:30.240 do something called sub metering where you can say, wow, this port, 338 00:23:30.359 --> 00:23:33.000 you know, this many floors or this part of the building is is really 339 00:23:33.160 --> 00:23:37.359 a culprit. It's using way more energy than all the other guys and stuff 340 00:23:37.400 --> 00:23:40.720 like that, And so you get a better granular view, you know, 341 00:23:40.759 --> 00:23:41.799 back to what we were talking about. You know, the data is going 342 00:23:41.839 --> 00:23:45.160 to tell you what's really happening. And so instead of saying, I know 343 00:23:45.200 --> 00:23:49.599 the power usage for this whole skyscraper, now I have a granular view of 344 00:23:49.640 --> 00:23:55.039 who's using what, and you can then make better decisions, and you can 345 00:23:55.079 --> 00:24:00.759 do management and you can improve the situation or anything that not just electrons but 346 00:24:02.160 --> 00:24:07.640 water, right you water and pipes and pumps all over the building to you 347 00:24:07.680 --> 00:24:10.160 know, people are like, how is it that you have a bathroom on 348 00:24:10.200 --> 00:24:11.440 the eightieth floor of the building. How does that work? You know, 349 00:24:11.880 --> 00:24:17.799 how's water coming out of the closet. There's this world of pumps that's pushing 350 00:24:17.960 --> 00:24:22.559 water and stuff up there to make that work. You know, I've done 351 00:24:22.559 --> 00:24:27.640 a lot of stuff kind of in the you know, reducing emissions that I 352 00:24:27.680 --> 00:24:33.000 don't know if you've ever heard of the United Nations Sustainable Development goals. Sure, 353 00:24:33.720 --> 00:24:36.640 so so I've built technology to you know, a lot of IoT to 354 00:24:36.680 --> 00:24:38.839 help that. Well, one of the big ones is water. It turns 355 00:24:38.839 --> 00:24:45.000 out where I forgot how many millions of gallons of water gets leaked and lost 356 00:24:45.039 --> 00:24:49.559 fresh water every day in our cities, in our buildings and so and then 357 00:24:49.680 --> 00:24:52.960 you know, at some point you start to realize that fresh water turns out 358 00:24:53.000 --> 00:24:57.519 to be one of the most important resources we have, and so being able 359 00:24:57.559 --> 00:25:02.559 to monitor and find leaked where there it's happening, and that whole matrix of 360 00:25:03.000 --> 00:25:07.200 plumbing going out throughout a building is kind of a thing. Oh yeah, 361 00:25:07.400 --> 00:25:10.000 yeah. I mean I spent the number of years living in New Orleans, 362 00:25:10.079 --> 00:25:15.960 and the data on the amount of water that is lost from the facility to 363 00:25:17.119 --> 00:25:19.440 the homes it's like, I want to say, it's like two thirds. 364 00:25:21.079 --> 00:25:25.079 It's it's a gobsmacking number which shows you how many holes there are in the 365 00:25:25.079 --> 00:25:29.000 system. I mean, my first job as a newspaper reporter, I interviewed 366 00:25:29.039 --> 00:25:32.359 a guy from in situ Form I think is the name of the company, 367 00:25:32.839 --> 00:25:37.559 and they would go in and use really which at the time was for cutting 368 00:25:37.640 --> 00:25:41.839 edge technology to go through pipes and like sense where the holes are, and 369 00:25:41.839 --> 00:25:45.119 they would actually line the pipes with like a synthetic material to prevent it from 370 00:25:45.160 --> 00:25:48.279 leaking and doing things like that. But you know, just ask anyone who 371 00:25:48.279 --> 00:25:52.240 had plumbing problems, man, Like, getting to the bottom of that is 372 00:25:52.279 --> 00:25:56.279 a huge issue, and that's something that IoT can help you do if you 373 00:25:56.359 --> 00:26:00.519 have the sensors in place, because you can sense the vibration and how much 374 00:26:00.519 --> 00:26:03.799 water is moving through here versus here, and you can use that to identify, 375 00:26:03.839 --> 00:26:07.000 Okay, well the problem must be here, So that's where we're going 376 00:26:07.079 --> 00:26:12.599 to drill through your wall. Like it's brutal. You made the comment earlier, 377 00:26:12.839 --> 00:26:18.119 just creating a baseline m h without even doing any crazy AI stuff. 378 00:26:18.400 --> 00:26:22.680 Just simple KPIs right, you say, I expect this, like you know, 379 00:26:22.720 --> 00:26:26.160 like KPI is green, yellow, red. Right, if you're in 380 00:26:26.160 --> 00:26:30.759 the green zone, I don't need to do anything. If I'm starting to 381 00:26:30.839 --> 00:26:34.720 lose water or electricity is going off or or whatever it is you're monitoring, 382 00:26:36.319 --> 00:26:37.799 you know, you get going to the yellow and you head towards the red 383 00:26:37.920 --> 00:26:41.920 zone. You can you do pattern matching on the data the packets that are 384 00:26:41.920 --> 00:26:47.720 coming in telling you what's going on right in those pipes in the electricity. 385 00:26:47.880 --> 00:26:51.000 You know, how many people are in the building all that kind of stuff, 386 00:26:51.039 --> 00:26:52.519 you know, and you say, I expect kind of like in New 387 00:26:52.559 --> 00:26:56.240 Orleans, I expect this much water to make it from here to here, 388 00:26:56.759 --> 00:26:59.920 right, And the reality is, well I lost two thirds of it. 389 00:27:00.480 --> 00:27:03.759 Maybe there's a problem, you know, and so you've got to, like 390 00:27:03.799 --> 00:27:07.400 you said, you've got to measure it or you can't absolutely can't manage these 391 00:27:07.440 --> 00:27:14.480 systems. And so IoT. You know, I often talk to folks they 392 00:27:14.519 --> 00:27:18.640 think they need the most advanced technology to do IoT to compete in factories or 393 00:27:18.680 --> 00:27:22.240 whatever. And I'm like, just remember, you're competing with a guy with 394 00:27:22.279 --> 00:27:26.279 a clipboard. That's really what it is. That's who your competition is. 395 00:27:26.319 --> 00:27:32.160 Some guy taking logs, monitor looking at gauges, you know, things like 396 00:27:32.200 --> 00:27:37.599 that to find out what's really going on. And so IoT is that person. 397 00:27:37.640 --> 00:27:42.880 It's that person taking logs except continuous monitoring. Right, that's brilliant. 398 00:27:44.039 --> 00:27:47.200 I'm going to quote that and post it here shortly, Like you're competing with 399 00:27:47.240 --> 00:27:49.359 a guy with the clipboard. That's right, Well, as you suggest, 400 00:27:49.480 --> 00:27:55.319 until you take those baselines and let's think about it. Flow applies to water, 401 00:27:55.440 --> 00:27:59.759 Flow applies to electricity, flow applies to data, to information packets going 402 00:27:59.759 --> 00:28:03.880 around on your network right and getting that baseline you talk about security, getting 403 00:28:03.920 --> 00:28:08.640 a baseline of network traffic and what happens every day. There's a company and 404 00:28:08.759 --> 00:28:14.319 a dot I think they're based in Israel and they can't remember how they started, 405 00:28:14.359 --> 00:28:18.160 but they're all about anomalies. Basically, they're looking for strange things like 406 00:28:18.240 --> 00:28:21.480 what is different from yesterday? Well, you don't know until you have a 407 00:28:21.480 --> 00:28:25.160 baseline. Once you get a baseline, then you can start analyzing and understanding 408 00:28:25.319 --> 00:28:27.039 all right, now, why why did things slow down for this period of 409 00:28:27.039 --> 00:28:32.119 time? And you know, there's a guy I interviewed gosh fifty fourteen years 410 00:28:32.119 --> 00:28:33.599 ago in the show I Love this name, Zohargi Lot. He was with 411 00:28:33.680 --> 00:28:37.680 a company called Precise. They got bought by who were they? They got 412 00:28:37.680 --> 00:28:44.200 bought by Idea I think. And it's basically it's it's troubleshooting for systems, 413 00:28:44.640 --> 00:28:47.920 and you know, these days it's even more complex than that, with Kubernetes 414 00:28:47.920 --> 00:28:49.440 and containers and all this stuff. It's like, oh my god, yeah, 415 00:28:49.559 --> 00:28:53.079 once might have all this observability stuff these days, right, but now 416 00:28:53.119 --> 00:28:56.799 you have to like collate all that observability data and figure that out. So 417 00:28:56.880 --> 00:29:00.680 it's like, you know, this stuff comes just but again the point is 418 00:29:00.839 --> 00:29:06.039 understanding what's normal and then what's not normal, and so hard. We were 419 00:29:06.079 --> 00:29:08.599 joking about stuff because I was saying, even if you have all this great 420 00:29:10.000 --> 00:29:14.079 technology, you're still looking at histograms. You know, CPU usage went up, 421 00:29:14.359 --> 00:29:17.279 network went down. Well, how do we correlate these things? And 422 00:29:17.319 --> 00:29:19.079 of course that's where time series comes into play. It's like, well, 423 00:29:19.359 --> 00:29:22.640 let's look at the time series and see what was leading up. There's a 424 00:29:22.720 --> 00:29:29.400 slow rise here and then a big fall there. It's probably related, you 425 00:29:29.440 --> 00:29:34.119 know, absolutely absolutely, and then go ahead. Another thing I thought of 426 00:29:34.160 --> 00:29:38.880 that flows through a building and underneath everybuilding in a city is natural gas, 427 00:29:40.880 --> 00:29:45.880 right right, And so that continuous monitoring is so critical, so you know 428 00:29:47.000 --> 00:29:48.960 in real time and you can react to it even if you're not doing predictive 429 00:29:49.200 --> 00:29:53.440 maintenance. Right, you can nip it in the bud super fast because you 430 00:29:53.519 --> 00:29:56.839 don't want to find out too late that there's a natural gas leak, right 431 00:29:57.000 --> 00:30:00.480 right, right? I saw some and it was a house just exploded in 432 00:30:00.519 --> 00:30:03.799 something. Right, Oh, it's so bad. Well, and there there 433 00:30:03.839 --> 00:30:07.480 are sensors for everything. I mean, that's the thing about IoT, right, 434 00:30:07.559 --> 00:30:11.079 is you get all these new kinds of sensors coming out, and they're 435 00:30:11.079 --> 00:30:15.000 getting better and better and cheaper and cheaper, right, because a lot of 436 00:30:15.000 --> 00:30:18.400 these things are very inexpensive and their whole job is just to go hello when 437 00:30:18.400 --> 00:30:22.920 something changes. Right. But then once you get that all in line, 438 00:30:22.759 --> 00:30:26.680 then if you have a good IoT solution, you can save I mean, 439 00:30:26.880 --> 00:30:30.680 you know, the cost of being able to troubleshoot quickly versus over a long 440 00:30:30.680 --> 00:30:34.640 period of time is massive in terms of disparity, like and the you know, 441 00:30:34.680 --> 00:30:38.119 the reputational harm, the damage to human beings and the buildings. I 442 00:30:38.119 --> 00:30:41.440 mean, good god, water in particular, I'm sure you know being in 443 00:30:41.480 --> 00:30:45.119 the industry, like you get water leaks that go for a while. Man, 444 00:30:45.319 --> 00:30:49.000 oh no, exactly exactly. So you're right, you know, make 445 00:30:49.000 --> 00:30:56.000 sure you've got these little slow cost leak detection sensors in the bathrooms, right 446 00:30:56.000 --> 00:30:59.039 in the room. If there's a restaurant, there's a kitchen, there's a 447 00:30:59.200 --> 00:31:03.920 you know whatever, so many simple things. Temperature, you know, worked 448 00:31:03.960 --> 00:31:08.720 with restaurants that are in buildings and just having temperature sensors in the walk in 449 00:31:08.839 --> 00:31:14.319 cooler and the freezer. You know. I remember having a guy said, 450 00:31:14.400 --> 00:31:15.519 yeah, you know, one of the you know, and we're not talking 451 00:31:15.599 --> 00:31:21.839 rocket science here, but one of the employees left opened the door for the 452 00:31:21.880 --> 00:31:23.240 freezer as he left for the weekend, and it was going to be this 453 00:31:23.319 --> 00:31:27.480 closed down three day weekend. But luckily that sensor told them. And we're 454 00:31:27.519 --> 00:31:32.079 not even talking about some cool dashboards. It was just a text message. 455 00:31:33.240 --> 00:31:34.640 And the guys like, yeah, it saved us, Like we would have 456 00:31:34.680 --> 00:31:38.680 lost thirteen thousand dollars worth of food that would have gone bad just because of 457 00:31:38.680 --> 00:31:41.400 that. Wow. And then and then the leak stuff. You're right, 458 00:31:41.559 --> 00:31:47.960 is just horrible. In fact, you know that's one of the biggest insurance 459 00:31:47.960 --> 00:31:52.039 companies When they have to do payouts. You assume it's a fire is the 460 00:31:52.119 --> 00:31:55.200 number one, but turns out flooding is number one. I'm sure it's neck 461 00:31:55.359 --> 00:32:00.759 deck with fire. I knew some guys at an IoT company and their way 462 00:32:00.799 --> 00:32:06.000 to instead of charging customers to put in sensors for leak detection in their homes 463 00:32:06.119 --> 00:32:10.839 or buildings. It turns out when the insurance companies looked at their actuarial tables, 464 00:32:10.920 --> 00:32:15.119 they came to the conclusion that they the insurance company would pay for the 465 00:32:15.160 --> 00:32:22.240 sensors for free and everything because the loss when it happens is so horrific. 466 00:32:22.559 --> 00:32:25.799 Wow. So that's cool. Yeah, it is cool. And so a 467 00:32:25.839 --> 00:32:30.799 lot of times it comes back to money and insurance and figuring stuff out like 468 00:32:30.839 --> 00:32:32.839 that. Well, but it makes a lot of sense. And that's why 469 00:32:32.880 --> 00:32:36.640 you want actuaries there, right. It's because they're saying, all right, 470 00:32:36.680 --> 00:32:39.720 well, if we just go ahead and incentivize people to get these sensors in 471 00:32:39.799 --> 00:32:45.079 place, we're going to save on the back end millions of dollars, which 472 00:32:45.119 --> 00:32:50.160 is probably true because all it takes is one bad apple to just screw the 473 00:32:50.160 --> 00:32:54.359 whole bunch, right, absolutely, absolutely, Yeah, So yeah, it's 474 00:32:54.359 --> 00:32:59.440 great having that network in there. I was surprised to find out that a 475 00:32:59.440 --> 00:33:01.240 lot of theseuildings, you know, you put in different systems, like you 476 00:33:01.319 --> 00:33:07.440 mentioned elevators or HVAC or lighting. There's all kinds of systems put in by 477 00:33:07.440 --> 00:33:12.119 different companies. And what we've discovered over time is each one of those has 478 00:33:12.200 --> 00:33:19.839 the building owner install a completely separate high speed network circuit interesting for each individual 479 00:33:19.920 --> 00:33:22.839 thing. So you might come to a building and find out that this building's 480 00:33:22.839 --> 00:33:30.960 got five or six separate networks all to cater to these different vendors and stuff 481 00:33:30.000 --> 00:33:35.359 like that, and so a lot of times we help save money for buildings 482 00:33:35.720 --> 00:33:39.319 by consolidating those down too, you know, lower cost but faster, bigger 483 00:33:39.319 --> 00:33:44.559 pipes that way, which is kind of interesting. Yeah, and I'll bet 484 00:33:44.839 --> 00:33:46.960 that. And granted just takes some analysis, and this takes some time to 485 00:33:47.039 --> 00:33:52.880 kind of dig into. But because you do host command and control for all 486 00:33:52.920 --> 00:33:59.319 these different systems, you can do time series analysis across different scenarios. So 487 00:33:59.400 --> 00:34:02.480 when something happens or when a bill comes into high or whatever. It's very 488 00:34:02.519 --> 00:34:06.680 frustrating if you have to look at five or six different systems. But if 489 00:34:06.680 --> 00:34:09.679 you can go to one master's system that has control over all of them, 490 00:34:10.079 --> 00:34:14.079 that's where you get that single source of truth and can really kind of dig 491 00:34:14.119 --> 00:34:15.719 into it. And I you know, again, I have to believe that 492 00:34:15.760 --> 00:34:21.960 there's a lot of money to be saved by not freezing all of your denizens 493 00:34:22.000 --> 00:34:24.360 every day it's sixty four degrees fahrenheit. You know, it's like, okay, 494 00:34:24.360 --> 00:34:27.079 I know we want to be cool, but does it have to be 495 00:34:27.119 --> 00:34:30.199 that cool? Like can we just maybe ease off a little bit and just 496 00:34:30.679 --> 00:34:32.599 and see what it is? When you see the numbers, you'll find out 497 00:34:32.599 --> 00:34:36.039 what the deal is. But folks, don't touch that. That will be 498 00:34:36.119 --> 00:34:39.800 right back talking to Rob Tiffany of Red Bison, all about IoT and fun 499 00:34:39.840 --> 00:34:51.519 stuff. We'll be right back to Welcome back to Inside Analysis. Here's your 500 00:34:51.599 --> 00:34:58.440 host, Eric Tavanaugh. All right, folks back here on Inside Analysis. 501 00:34:58.440 --> 00:35:05.039 A fascinating conversation about networks and electricity and gas and things that flow. Right. 502 00:35:05.079 --> 00:35:07.519 You want things that flow like cash flow right, You got to watch 503 00:35:07.559 --> 00:35:10.239 out and you get a big pool of cash like that's when trouble starts. 504 00:35:10.239 --> 00:35:14.679 You want it to be flowing. You want everything to flow through your organization, 505 00:35:14.960 --> 00:35:17.280 energy, food, fuel, all that kind of fun stuff. And 506 00:35:17.320 --> 00:35:21.679 we've been talking about the networking side of that, which is a foundation of 507 00:35:21.760 --> 00:35:24.960 the information economy. You could argue is networking right. It's the ability to 508 00:35:25.039 --> 00:35:29.840 move information from one place to another, to enable functionality, to enable people 509 00:35:29.880 --> 00:35:34.719 to do cool things. And Rob Tiffany of Red Bison knows a lot about 510 00:35:34.719 --> 00:35:37.039 all that. We wanted to get in a bit more to the I guess 511 00:35:37.039 --> 00:35:43.760 to the edge stuff, and just to people understand edge basically, your cell 512 00:35:43.760 --> 00:35:47.000 phone is at the edge. A computer can be at the edge. It's 513 00:35:47.039 --> 00:35:52.599 an edge device basically. And we went through this interesting period of time client 514 00:35:52.639 --> 00:35:55.400 server, because we started a mainframe, you do client server, and then 515 00:35:55.440 --> 00:35:59.559 the cloud came along, and then you get hybrid cloud and multi cloud and 516 00:35:59.559 --> 00:36:02.199 all that stuff, and then the edge comes along. The edge is very 517 00:36:02.320 --> 00:36:07.760 very interesting because it's it's not the data center per se. It's not like 518 00:36:07.800 --> 00:36:12.199 the big corporate data center. It's not the cloud. It's not just one 519 00:36:12.239 --> 00:36:15.239 device. It's all these devices that are out on the periphery basically, but 520 00:36:15.280 --> 00:36:17.920 you could do interesting things there. And you were talking about this earlier, 521 00:36:19.360 --> 00:36:22.480 rob where you know, you come in, you build a network for the 522 00:36:22.519 --> 00:36:25.119 office tower. And by the way, we now have servers on every other 523 00:36:25.159 --> 00:36:29.679 floor, so we can do a little mini cloud for you. We don't 524 00:36:29.679 --> 00:36:31.880 have to send stuff up to the cloud, because what happens when you're sending 525 00:36:31.880 --> 00:36:35.519 everything up to the cloud. You got to go through the network. Right. 526 00:36:36.239 --> 00:36:37.719 I was in the had Dupe space, which was a big deal. 527 00:36:37.719 --> 00:36:43.599 You may remember had Dupe, But the network was the achilles heel because you 528 00:36:43.599 --> 00:36:45.840 had to move all this stuff around the network, and so all of a 529 00:36:45.880 --> 00:36:51.000 sudden that becomes the bottleneck. And anyone knows in business as in life, 530 00:36:51.039 --> 00:36:53.480 bottlenecks are where you have to figure out what to do, and you guys 531 00:36:53.519 --> 00:36:57.440 have done some interesting things on that, So tell us about how you're able 532 00:36:57.480 --> 00:37:01.519 to enable all sorts of interesting service for your clients. Yeah. Well, 533 00:37:01.559 --> 00:37:06.639 since we don't just install the network and walk away, we kind of do 534 00:37:06.679 --> 00:37:10.039 this network as a service, so we're actively managing it. We have hardcore 535 00:37:10.119 --> 00:37:15.880 firewalls all over the place, We've got AI built in our networking gear, 536 00:37:15.119 --> 00:37:20.320 and so we actively manage and so that's an ongoing thing that we do to 537 00:37:20.360 --> 00:37:23.079 make sure performance is always there to nip things in the bud. Like we 538 00:37:23.199 --> 00:37:28.519 talked about with other things. Security is the huge deal, but just make 539 00:37:28.559 --> 00:37:30.639 sure you know a customer's paying for this much bandwidth, we have to make 540 00:37:30.679 --> 00:37:36.079 sure that they're getting it. And so actively doing a network as service then 541 00:37:36.239 --> 00:37:39.039 gives us the ability to go in and provide other services and have that confidence 542 00:37:39.039 --> 00:37:43.719 because you're right, you talked about hadoop and the network bottleneck being an achilles 543 00:37:43.760 --> 00:37:45.960 heel for a lot of that stuff. So, since we have this crazy 544 00:37:46.000 --> 00:37:52.440 network that we're managing actively. So you walk into a skyscraper and every floor 545 00:37:52.559 --> 00:37:55.960 there's this weird door that's like a closets. Do you remember the good old 546 00:37:57.039 --> 00:38:00.679 days when companies used to put their IT stuff in a closet kind of yeah, 547 00:38:00.039 --> 00:38:04.239 servers literally in the closet. Yeah, and the closet, you know, 548 00:38:04.679 --> 00:38:07.800 before data centers got big or anything like that, there's the IT closet 549 00:38:07.880 --> 00:38:12.000 or whatever. Okay, that still is kind of here today, believe it 550 00:38:12.079 --> 00:38:16.199 or not. And so the bottom floor, don't remember what the acronyms stand 551 00:38:16.239 --> 00:38:21.000 for. The bottom floor is called an MDF and that's where the fiber optics 552 00:38:21.079 --> 00:38:23.559 comes in, and that's where all the building management stuff is. And then 553 00:38:23.639 --> 00:38:29.239 on the subsequent floors you have, they're called IDFs and they're smaller. So 554 00:38:29.920 --> 00:38:32.079 since we get space, since we own the network, we get space rack 555 00:38:32.199 --> 00:38:37.639 server space on every other one of those floors to put compute in there. 556 00:38:37.679 --> 00:38:40.199 And so you kind of asked the questions, well, gosh, you know, 557 00:38:40.239 --> 00:38:44.519 so we have cooling, we've got electricity, we've got compute. It's 558 00:38:44.599 --> 00:38:50.440 right there. It's inside the security envelope that we've created. Like you're inside 559 00:38:50.480 --> 00:38:53.280 the building and you're protected by our firewall and we're actively managing it with AI 560 00:38:53.400 --> 00:39:00.960 systems. And so you've got an interesting scenario where into your point there's all 561 00:39:00.039 --> 00:39:04.519 kinds of edges. I used to think I knew what edge computing was in 562 00:39:04.559 --> 00:39:07.960 the early days of IoT used to be like a rugged PC talking to machines 563 00:39:08.000 --> 00:39:14.280 in a factory. And then the sensors and devices themselves got powerful enough that 564 00:39:14.360 --> 00:39:17.480 we did compute there right at the very very end, right at the endpoint 565 00:39:17.679 --> 00:39:22.840 almost, and so what we're able to do and then gosh, there's companies 566 00:39:22.840 --> 00:39:29.159 that are doing edge computing like literally taking shipping containers like cargo shipping containers and 567 00:39:29.199 --> 00:39:32.320 packing them full of servers and dropping them in someplace in a city and hooking 568 00:39:32.320 --> 00:39:37.119 them up. And so the edge thing is super disruptive to the cloud. 569 00:39:37.679 --> 00:39:44.039 It's also probably collaborative as well, and so lower latency because it's closer to 570 00:39:44.119 --> 00:39:46.360 the source of the data or the people who need to use that stuff. 571 00:39:47.559 --> 00:39:53.320 So since we put this edge compute, we are users of it, and 572 00:39:53.360 --> 00:39:58.519 then tenants in the building or the building owners are also can use that. 573 00:39:58.679 --> 00:40:02.159 And so I'd say our first product offering around that, that was a real 574 00:40:02.239 --> 00:40:07.719 no brainer. With security cameras, turns out, lots of buildings, lots 575 00:40:07.760 --> 00:40:12.480 of people are into having you know, different security cameras around their thing. 576 00:40:12.840 --> 00:40:15.840 It's kind of a thing these days, especially actually it's booming these days. 577 00:40:15.920 --> 00:40:19.519 I hate to say it, right, it's good for business, but it's 578 00:40:19.639 --> 00:40:24.880 it's bad for society that we need more security cameras. And so normally you'd 579 00:40:24.880 --> 00:40:30.000 have all these you know that the rise years ago is of IP cameras, 580 00:40:30.239 --> 00:40:34.840 you know, and all these standards to stream HD video and record it and 581 00:40:34.880 --> 00:40:37.239 do playback. And so a lot of folks are just streaming it off to 582 00:40:38.679 --> 00:40:43.400 AWS or Azure or GC, you know, some cloud and they're paying whatever 583 00:40:43.440 --> 00:40:46.440 for storage up there. So since we have this edge compute, we're like, 584 00:40:46.480 --> 00:40:51.320 well, you're in the building, you could just stream all those HD 585 00:40:51.440 --> 00:40:54.920 streams to us. And we have massive, you know, hundreds of terabytes 586 00:40:54.920 --> 00:41:00.119 of storage locally on site with our edge compute, and so it's a low 587 00:41:00.239 --> 00:41:05.519 latency, high speed way to get that stuff saved and recorded and then playback 588 00:41:05.599 --> 00:41:08.880 really quickly. And then if you want to tie in all this crazy AI 589 00:41:09.000 --> 00:41:13.159 stuff to it. You know, you're seeing more and more computer vision where 590 00:41:13.199 --> 00:41:16.519 it can actually recognize what's going on or is this a person or if that's 591 00:41:16.559 --> 00:41:21.159 a cat, or this person went from this place to this place or whatever, 592 00:41:21.280 --> 00:41:23.159 you know, and so folks are interested in that. So that's a 593 00:41:23.159 --> 00:41:29.280 good use case the same kind of business workloads you might run in the cloud, 594 00:41:29.800 --> 00:41:32.480 you know, like there's the standard I need to spin up a VM 595 00:41:34.119 --> 00:41:37.760 and I need much storage business workload. Sure, we do that at the 596 00:41:37.920 --> 00:41:44.559 edge, as it turns out without having to buy the edge versions of Azure 597 00:41:44.719 --> 00:41:47.760 or AWS. They'll have special fund names for those kind of things and having 598 00:41:47.760 --> 00:41:52.920 to pay them for that. Turns out there's lots of great open source solutions. 599 00:41:52.039 --> 00:41:55.559 Back to you were talking about Linux based on Linux, you know, 600 00:41:58.199 --> 00:42:01.199 me being spending so much time in the time world. You know, all 601 00:42:01.280 --> 00:42:05.480 the telcos, a lot of them are using what is it open shift, 602 00:42:05.880 --> 00:42:10.719 which is red hat the open stack, you know, Canonical, Ubutu, 603 00:42:12.039 --> 00:42:15.719 those guys. Yeah, they even have a smaller version that we've utilized. 604 00:42:15.800 --> 00:42:19.360 It's literally, i think it's just called micro cloud. And so you can 605 00:42:19.400 --> 00:42:23.159 imagine having being able to take a few nodes. It works with as few 606 00:42:23.159 --> 00:42:28.559 as three nodes three servers basically, and it'll create a cloud instance and it 607 00:42:28.599 --> 00:42:31.360 will cluster together storage and everything dynamic. It's so much easier than it used 608 00:42:31.400 --> 00:42:35.519 to be when we had to really do this by hand. Yeah, and 609 00:42:35.599 --> 00:42:38.760 then providing kind of that web interface and now we're providing it just to people 610 00:42:38.800 --> 00:42:43.159 in the local, you know, building, and then they can click and 611 00:42:43.199 --> 00:42:45.360 say, yeah, I want to spin up a VM that's using two virtual 612 00:42:45.400 --> 00:42:50.400 CPUs and this much RAM, and I'm going to run my workload right here 613 00:42:50.559 --> 00:42:52.920 in the building and it's going to be cheaper, it's going to be lower 614 00:42:53.000 --> 00:42:57.679 latency, it'll be more responsive that kind of thing, uh, or just 615 00:42:57.760 --> 00:43:00.079 or I just want to do storing data back data like you might do the 616 00:43:00.119 --> 00:43:07.039 cloud or obviously there's no shortage of cloud based backup data services out there, 617 00:43:07.360 --> 00:43:10.280 right, they can do stuff like that as well, and so they can 618 00:43:10.360 --> 00:43:15.800 run workloads we'll run our IoT stuff is running at the edge in the building 619 00:43:16.000 --> 00:43:21.400 and talking to all those sensors and all those building systems at high speed and 620 00:43:21.440 --> 00:43:23.800 load latency, and so it's kind of a win win for both of us. 621 00:43:25.159 --> 00:43:28.800 And yeah, customers are als, you know, a lot of I'm 622 00:43:28.840 --> 00:43:35.000 surprised there's still people doing it closets today and they're like, can you be 623 00:43:35.199 --> 00:43:40.760 yourn right? Well, And I mean I'm guessing that you have enough analytics 624 00:43:40.800 --> 00:43:46.119 from some of the instances that you have to be able to do some consulting 625 00:43:46.159 --> 00:43:49.559 on this stuff to be able to say, hey, you should put this 626 00:43:49.599 --> 00:43:52.599 here, put that there. I mean data centers, you know, for 627 00:43:52.639 --> 00:43:55.000 example, knowing where to put stuff in the room is pretty important, and 628 00:43:55.079 --> 00:44:00.480 being able to track where the airflow goes you have your hottest machine means right 629 00:44:00.519 --> 00:44:04.159 underneath this particular area, doctor, I mean, there are specific things that 630 00:44:04.239 --> 00:44:07.199 you can do that take a lot of attention and take a lot of effort 631 00:44:07.519 --> 00:44:13.320 to focus on. And it's so important because it's very expensive to run these 632 00:44:13.320 --> 00:44:16.119 big buildings, and it really helps to be able to know what is this 633 00:44:16.280 --> 00:44:21.719 cost, what are our options for being able to achieve this in some different 634 00:44:21.800 --> 00:44:27.840 way, And just having another competitor to the existing cloud service providers is also 635 00:44:28.400 --> 00:44:31.760 good stuff, like just because you'll see there's certain use cases where you really 636 00:44:31.800 --> 00:44:35.480 want that very very low latency, you know, if you're doing a data 637 00:44:35.519 --> 00:44:39.360 science project for example, or experimentation PII. They are all these different use 638 00:44:39.360 --> 00:44:43.519 cases where it makes sense to not go up into the cloud, and you 639 00:44:43.599 --> 00:44:45.760 guys are giving an option for doing all that, right, it's just another 640 00:44:45.800 --> 00:44:49.039 option, you know. There was that notion. I think a lot of 641 00:44:49.119 --> 00:44:53.280 us felt like with the growth of the hyperscale clouds that the data center business 642 00:44:53.360 --> 00:44:57.719 was going to go away, and it turns out the inverse has been true. 643 00:44:57.840 --> 00:45:00.599 They're building those centers like there's no tomorrow, and as soon as they 644 00:45:00.639 --> 00:45:05.760 open they're being sold out, packed full of servers. Five years ago they 645 00:45:05.760 --> 00:45:09.840 were doing bitcoin mining. Now they're all AI training factories. Wow. And 646 00:45:09.880 --> 00:45:15.000 by the way, Helium was the company I was feeling of the guys from 647 00:45:15.079 --> 00:45:16.880 Helium. They're the ones that do the low frequency I mean, that's just 648 00:45:16.960 --> 00:45:23.079 so fascinating to me, using low radio frequency to communicate an IoT devices. 649 00:45:23.119 --> 00:45:28.440 Well, folks, look this gentleman up online, Rob Tiffany from Red Bison. 650 00:45:28.480 --> 00:45:30.119 If you're in the commercial property space, you want to be talking to 651 00:45:30.159 --> 00:45:37.719 these guys. Folks, you've been listening to Inside Analysis. Okay, folks, 652 00:45:37.719 --> 00:45:39.800 time for the podcast bonus segment here on Inside Analysis. A great show 653 00:45:39.840 --> 00:45:45.480 with Rob Tiffany from Red Bison, and you threw out that great segue at 654 00:45:45.480 --> 00:45:49.719 the end of the segment talking about training AI. And there's a company called 655 00:45:49.800 --> 00:45:52.639 Hammer Space. I was on The Girl's Show a few weeks ago. They're 656 00:45:52.639 --> 00:45:57.519 actually training Lama too right now, so that's pretty interesting. And she was 657 00:45:57.559 --> 00:46:01.639 talking about how there are shortages of like you can't even get the processors because 658 00:46:01.719 --> 00:46:06.760 everyone wants them, because all these companies are trying to train AI. And 659 00:46:06.840 --> 00:46:10.239 you know, frankly, I know for sure that these AI models are going 660 00:46:10.320 --> 00:46:14.960 to fundamentally change computing. You know, it's I look at you know, 661 00:46:15.000 --> 00:46:19.719 like for example, when chat GBT was unveiled like in April or something or 662 00:46:19.760 --> 00:46:22.519 May, I started playing around it. Within five minutes, I was like, 663 00:46:22.599 --> 00:46:24.719 Oh, if it can do all these languages, I bet it can 664 00:46:24.800 --> 00:46:30.400 do code too. Yes it can, Yes it can, right, And 665 00:46:30.440 --> 00:46:34.280 it's like they all we had to show last week on this and they're just 666 00:46:34.320 --> 00:46:37.559 talking about Usama Fayad, who is the chief data officer for Yahoo, was 667 00:46:37.559 --> 00:46:39.800 saying, Yeah, really, scientifically, it's not that much that interesting about 668 00:46:39.840 --> 00:46:44.159 these They're just weights. They're just weights, and it's a predictive engine, 669 00:46:44.639 --> 00:46:50.079 but it has so much information that it is absorbed. And yes they do 670 00:46:50.159 --> 00:46:52.039 hallucinate. Yes there are these issues, but I think they're going to figure 671 00:46:52.039 --> 00:46:54.679 out a way around all that. And I think what you're going to see 672 00:46:54.760 --> 00:47:00.360 is a whole new generation of software applications built on top of these things. 673 00:47:00.400 --> 00:47:05.519 And guess what a company like red Bison, because you are running the network 674 00:47:05.559 --> 00:47:09.679 as a service you're very well positioned to do these sorts of add ons and 675 00:47:09.719 --> 00:47:13.159 to basically come in and say, hey, guess what, we have this 676 00:47:13.239 --> 00:47:17.599 new service where we can help you train your own private instance by using all 677 00:47:17.599 --> 00:47:22.280 this data of your usage of what you've done over the years. I mean, 678 00:47:22.320 --> 00:47:23.800 there's all these things you can do if you have the data right. 679 00:47:24.199 --> 00:47:31.639 Absolutely absolutely, you know you're right. Nobody can find those in video GPUs 680 00:47:31.760 --> 00:47:35.960 that everybody wants. I mean, I guess in video was the biggest number 681 00:47:36.000 --> 00:47:40.079 one stock performer in twenty twenty three. Yeah, because everybody wants what They've 682 00:47:40.079 --> 00:47:45.360 got to train AI models and it's going crazy, and so you know, 683 00:47:45.880 --> 00:47:51.800 being able to but I think you're also seeing AMD is starting to get some 684 00:47:51.960 --> 00:47:54.400 love. Intel had to recognize that they need to get in that game. 685 00:47:54.440 --> 00:48:00.400 And there's been a lot of talk in the last few weeks about aipcs and 686 00:48:00.760 --> 00:48:07.719 neural processing units in just kind of desktop or laptop class devices, and so 687 00:48:07.719 --> 00:48:10.599 so we'll be we take advantage of GPUs, you know, in our edge 688 00:48:10.599 --> 00:48:15.320 compute, so that we can we're training models ourselves. And you know, 689 00:48:15.360 --> 00:48:17.400 and actually to your point about writing code, as I've been building a lot 690 00:48:17.440 --> 00:48:22.960 of technology, I've been using it as an assistant. You know, I've 691 00:48:23.039 --> 00:48:28.920 used chat GBT and I've used a Microsoft's Copilot and they've integrated Copilot in with 692 00:48:28.960 --> 00:48:32.400 GitHub and so you know, when I have to if there's some tough problem 693 00:48:32.440 --> 00:48:37.079 you're trying to solve, you'd be amazed of how good it is at figuring 694 00:48:37.119 --> 00:48:42.519 out you know, complicated scenarios or algorithms and stuff like that. And so 695 00:48:43.039 --> 00:48:47.719 it's helped me to build software that does AI. Your ability to not just 696 00:48:47.800 --> 00:48:52.239 have to use AI training software that's in the hyperscale clouds. There's a lot 697 00:48:52.280 --> 00:48:55.559 of stuff you can do locally. You know, you can use Python. 698 00:48:57.599 --> 00:49:02.519 I've been using a technology for Microsoft called mL dot net, the dot Net 699 00:49:02.679 --> 00:49:07.320 framework and c sharp and all that stuff. In that world. They've they've 700 00:49:07.360 --> 00:49:13.519 built a AI training system that's like Microsoft Times to make things easy, which 701 00:49:13.559 --> 00:49:17.920 is great helpful to train models using a dot Net and c sharp versus Python 702 00:49:19.079 --> 00:49:22.320 or R or something else. So and you can do it locally. And 703 00:49:22.400 --> 00:49:28.239 so we can have that technology to train models right there locally at the edge 704 00:49:28.880 --> 00:49:30.599 for folks. We can do it for ourselves. We can do it for 705 00:49:30.639 --> 00:49:35.400 tenants, but you can imagine doing it for third parties who aren't even in 706 00:49:35.440 --> 00:49:38.559 the building. Right, Like, when I think about how I'm designing our 707 00:49:38.760 --> 00:49:44.840 edge cloud, basically is taking a lot of the ideas we had at Azure 708 00:49:44.920 --> 00:49:47.840 and at AWS head this notion of availability zones. You know, you always 709 00:49:47.840 --> 00:49:52.800 want to have uptime and availability. So you can imagine now that MDF on 710 00:49:52.840 --> 00:49:58.199 the first floor might be the main place, but those other closets above there, 711 00:49:58.679 --> 00:50:04.079 those are availability, these zones where we replicate data right across so that 712 00:50:04.280 --> 00:50:08.239 different things can go down because the cloud's designed for failure. You know, 713 00:50:08.280 --> 00:50:12.960 servers are failing continuously, but the software keeps it going. Yeah, so 714 00:50:13.239 --> 00:50:15.679 we start there with availabilities one that way, the next step for us will 715 00:50:15.719 --> 00:50:20.760 then be in the same city where we have other buildings replicating across that and 716 00:50:20.800 --> 00:50:24.199 then so just like you know, just like you so yes, I'm sure 717 00:50:24.199 --> 00:50:27.559 you'll say, yeah. I remember when I talked to some guy at read 718 00:50:27.599 --> 00:50:30.920 Bison and they ended up taking down all the hyper scale clouds just quietly as 719 00:50:31.000 --> 00:50:36.039 the thing just came to life, and it was in every building on every 720 00:50:36.119 --> 00:50:39.719 city in every country. That's wild. It is wild, but there's a 721 00:50:39.760 --> 00:50:45.400 demand. There's a demand to train AI models by people and people are looking 722 00:50:45.440 --> 00:50:47.800 for compute wherever they can get it, and so data centers are being built 723 00:50:47.800 --> 00:50:51.519 as fasts they can and so uh, that's kind of how I think of 724 00:50:51.559 --> 00:50:53.800 our our edge cloud. You know, it'll do that edge IoT stuff, 725 00:50:53.840 --> 00:50:58.440 but it'll will use it for other things as well well. And you hit 726 00:50:58.440 --> 00:51:00.960 the nail on the head when you mentioned how they're just filling up immediately, 727 00:51:01.519 --> 00:51:05.559 so you know, I remember just I'll close on this, but I remember 728 00:51:05.559 --> 00:51:08.679 interviewing a guy from the Illinois Department of Transportation like thirty odd years ago in 729 00:51:08.719 --> 00:51:12.599 my first job, and he made a really interesting point. He said, 730 00:51:13.039 --> 00:51:16.239 the law does not allow you to plan the size of a highway based on 731 00:51:16.320 --> 00:51:22.559 projections of future traffic. You have to look at existing traffic as your baseline 732 00:51:22.840 --> 00:51:25.000 and then build the highways. And he said it's a bit of an issue 733 00:51:25.039 --> 00:51:29.880 for us because as soon as we build these big three four lane interstates, 734 00:51:30.280 --> 00:51:32.960 boom, they're filled. And they did that in Illinois with I three fifty 735 00:51:32.960 --> 00:51:36.639 five, because you've got fifty five, which is a major highway and just 736 00:51:36.679 --> 00:51:39.440 gets clogged as heck getting into Chicago. But they built three fifty five, 737 00:51:39.480 --> 00:51:44.559 and I mean within days, it was just packed with cars, because now 738 00:51:44.599 --> 00:51:46.360 you can go all the way up to the North Suburbs in like thirty two 739 00:51:46.360 --> 00:51:50.000 minutes when he used to take you an hour and a half. So you 740 00:51:50.119 --> 00:51:53.280 go see your friend up in the North Suburbs. You go shopping to different 741 00:51:53.280 --> 00:51:57.719 malls and things like that. So people use stuff when you make it available. 742 00:51:58.039 --> 00:52:00.440 Then you got to And the other thing with the data center is that 743 00:52:00.960 --> 00:52:04.320 you reach the end of the data center, you cannot get one more box 744 00:52:04.320 --> 00:52:07.719 in that data center. That's where the edge comes into play. Because if 745 00:52:07.719 --> 00:52:09.119 you've got a bunch of these little edge nodes, then guess what, you 746 00:52:09.159 --> 00:52:15.000 can very quickly absorb the demand and take their money and make good things happen. 747 00:52:15.079 --> 00:52:19.719 Right, that's the plan. That's the I love it. Well, 748 00:52:19.760 --> 00:52:22.239 look these guys up online. What a fun conversation with Rob Tiffany of Red 749 00:52:22.280 --> 00:52:24.639 Bison. Send me email if you want to be in the show. Info 750 00:52:24.639 --> 00:52:28.280 at inside analysis dot com. We'll talk to you next time you've been listening 751 00:52:28.480 --> 00:52:37.480 to Inside Analysis. Southern California is Inland Talk Express is kcaa open for takeout 752 00:52:37.559 --> 00:52:43.440 and delivery. 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And from this time 787 00:55:13.119 --> 00:55:17.280 in nineteen sixty three, Tony Curtis who's thirty seven, and German actress Christine 788 00:55:17.320 --> 00:55:22.480 Kaufman, she's eighteen, they marry for many years. Tony Curtis was narried 789 00:55:22.480 --> 00:55:25.760 to Janet Lee. Which one of your pictures would you say was the you 790 00:55:25.760 --> 00:55:29.400 felt the most uncomfortable? You just said, oh what am I doing in 791 00:55:29.440 --> 00:55:34.360 this? There was I actually call the Purple Mask, which was a rip 792 00:55:34.400 --> 00:55:37.920 off of the Scarlet Pimpernel. And from this time in nineteen sixty six, 793 00:55:38.199 --> 00:55:44.400 John Carridy will once again portray mister Gateman, Herman's boss at the Mockingbird Heights 794 00:55:44.639 --> 00:55:47.880 Funeral Parlor, on an Upcoming Monsters. In the episode, Eddie takes a 795 00:55:47.880 --> 00:56:00.920 pill from Grandpa and becomes a jazz trumpet player with more at me from yesterday 796 00:56:00.039 --> 00:56:07.400 dot com. It's that time of year again, No, not the holidays. 797 00:56:07.599 --> 00:56:12.960 Medicare open enrollment and if you have questions about Medicare, you should talk 798 00:56:13.000 --> 00:56:16.079 to the local experts. Paul Barratte and Associates. All of his agents are 799 00:56:16.079 --> 00:56:21.239 certified with plans that are accepted by most of the medical groups in our area. 800 00:56:21.239 --> 00:56:24.679 Call nine oh nine seven nine three oh three eighty five. Their service 801 00:56:24.760 --> 00:56:29.639 is free and after forty two years of the business, their agents are trained 802 00:56:29.639 --> 00:56:35.320 to help you pick the plan that's right for you. Bobyla here with my 803 00:56:35.400 --> 00:56:38.199 home improvement tip of the day. 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The Faran 821 00:58:02.039 --> 00:58:09.280 do Zih Show on KCAA Radio on all available streaming platforms and full six point 822 00:58:09.280 --> 00:58:15.519 five am and ten fifty am. The Ferano Zi Show on KCAA Radio. 823 00:58:27.760 --> 00:58:31.079 KCAA Radio has openings for one hour talk shows. If you want to host 824 00:58:31.119 --> 00:58:36.639 a radio show now is the time. Make KCIA your flangship station. Our 825 00:58:36.760 --> 00:58:39.679 rates are affordable and our services are second to none. We broadcast to a 826 00:58:39.760 --> 00:58:45.559 population of five million people plus. We stream and podcast on all major online 827 00:58:45.599 --> 00:58:50.519 audio and video systems. If you've been thinking about broadcasting a weekly radio program 828 00:58:50.559 --> 00:58:54.599 on real radio plus the Internet, contact our CEO at two eight one five 829 00:58:54.800 --> 00:59:00.400 nine ninety eight hundred two eight one five nine. You can skype your show 830 00:59:00.440 --> 00:59:05.360 from your home to our Redlands, California studio, where our live producers and 831 00:59:05.400 --> 00:59:09.440 engineers are ready to work with you personally. A radio program on KCAA is 832 00:59:09.480 --> 00:59:15.639 the perfect work from home avocation in these stressful times. Just type KCAA Radio 833 00:59:15.760 --> 00:59:19.519 dot com into your browser to learn more about hosting a show on the best 834 00:59:19.519 --> 00:59:22.400 station in the nation, or call our CEO for details. Two eight one 835 00:59:22.599 --> 00:59:29.119 five nine nine ninety eight hundred Listina KCAA Low Melinda at one O six point 836 00:59:29.159 --> 00:59:36.280 five FM, K two ninety three CF, Burrito Valley, NBC News Radio. 837 00:59:36.559 --> 00:59:39.400 I'm Brad Siegel. Another surge of Arctic air will bring hazardous cold weather 838 00:59:39.480 --> 00:59:43.440 to much of the country by next week, and to alert from the National 839 00:59:43.440 --> 00:59:47.159 Weather Service today warns of dangerously low temperatures and wind chills reaching into the south 840 00:59:47.199 --> 00:59:52.119 by next week. Meanwhile, freezing rain in the Northwest is blamed for more 841 00:59:52.119 --> 00:59:55.480 than one hundred and fifty thousand power outages today in Oregon. Former President Trump 842 00:59:55.519 --> 00:59:59.960 is maintaining a nearly thirty point lead in the Iowa polls. In the final 843 01:00:00.159 --> 01:00:04.639 poll before Monday's GOP caucuses, Trump had support from forty eight percent of likely 844 01:00:04.679 --> 01:00:08.360 Republican caucus goers. Former UN Ambassador Nikki Helly narrowly edging Florida