WEBVTT 1 00:00:00.280 --> 00:00:04.360 NBC News Radio. I'm Chris Garagio. The Jacksonville County sheriff says the gunman 2 00:00:04.360 --> 00:00:08.359 who killed three people at a store in a predominantly black community yesterday had no 3 00:00:08.400 --> 00:00:12.720 criminal record and apparently purchased both of the weapons legally. The gunman took his 4 00:00:12.759 --> 00:00:16.359 own life minutes after carrying out the attack. President Biden has condemned it as 5 00:00:16.359 --> 00:00:20.000 a potential hate crime. A second victim has died following the mass shooting at 6 00:00:20.039 --> 00:00:23.280 a bar in Louisville early this morning. Four other people were shot and remain 7 00:00:23.399 --> 00:00:27.000 hospitalized. Police say there were two hundred three hundred people in the area during 8 00:00:27.039 --> 00:00:30.719 the shooting, which happened about three am. There are no suspects. Meantime, 9 00:00:30.719 --> 00:00:34.920 Mayor Craig Greenberg his calling for discussions on whether bars and Louisville should be 10 00:00:34.960 --> 00:00:39.520 allowed to stay open until four am. Former Arkansas Governor Asa Hutchinson says he's 11 00:00:39.560 --> 00:00:44.079 proud that he stood on his principles during Wednesday's Republican presidential debate. I'm proud 12 00:00:44.119 --> 00:00:47.439 of that decision and it was the right call, and I hope more people 13 00:00:48.240 --> 00:00:51.960 identify with what I said. Speaking on CNN State of the Union, the 14 00:00:52.000 --> 00:00:56.240 GOP presidential candidate, was referring to his refusal to raise his hand when the 15 00:00:56.280 --> 00:01:00.479 candidates were asked if they would support former President Trump as the Republican if he 16 00:01:00.520 --> 00:01:03.200 wins the nomination. Hutchinson said that he was surprised virtually that all of the 17 00:01:03.239 --> 00:01:07.159 other candidates said they would support Trump even if he's convicted. He added that 18 00:01:07.200 --> 00:01:11.359 he's not concerned that the audience booed him for opposing Trump. Vermont Senator Bernie 19 00:01:11.359 --> 00:01:15.719 Sanders is praising the Biden administration, but it is also quick to point out 20 00:01:15.719 --> 00:01:19.000 more needs to be done. We have to deal with the reality of life 21 00:01:19.040 --> 00:01:23.120 that we have massive levels of corporate greed in every part of society. Very 22 00:01:23.200 --> 00:01:26.200 rich are getting richer, working people are struggling. Speaking un seen in State 23 00:01:26.200 --> 00:01:30.920 of the Union, The Vermont Independent cited lower unemployment and inflation, along with 24 00:01:30.959 --> 00:01:34.519 clean energy investments and the rebuilding of the country's infrastructure as some of President Biden's 25 00:01:34.519 --> 00:01:38.519 accomplishments, but added that corporate greed is the reason sixty percent of Americans are 26 00:01:38.560 --> 00:01:42.120 living paycheck to paycheck, and Democrats need to have the guts to take on 27 00:01:42.200 --> 00:01:47.560 the large corporations. And Governor de Santis is urging Florida West Coast residence to 28 00:01:47.560 --> 00:01:51.599 get ready for tropical Stormy Dalia. He's placed thirty three counties under a state 29 00:01:51.599 --> 00:01:56.040 of emergency. Landfall is expected Tuesday. I'm Chris Garraggio, NBC News Radio. 30 00:01:56.760 --> 00:02:02.079 Now here's a new concept, digital work advertising for businesses. 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The 56 00:04:10.639 --> 00:04:14.800 complete website is to hibow Tea Club dot com or call us at eight one 57 00:04:14.919 --> 00:04:18.680 eight six one zero eight zero eight eight Monday through Saturday, nine am to 58 00:04:18.759 --> 00:04:25.519 five pm California time. That's eight one eight six one zero eight zero eight 59 00:04:25.600 --> 00:04:31.000 eight to hibow Tea Club dot Com. With sixty years of fascinating facts. 60 00:04:31.040 --> 00:04:36.800 This is the man from yesterday and back in time, this time to nineteen 61 00:04:36.879 --> 00:04:42.040 eighty seven. Bruce Willis is set to marry actress Demi More in the fall, 62 00:04:42.199 --> 00:04:45.720 probably in November. Here at nineteen eighty seven, Bruce Willis's career has 63 00:04:45.759 --> 00:04:49.920 excelled ever since Moonlighting debut on ABC TV just a few years ago. Bruce 64 00:04:49.959 --> 00:04:54.839 Willis is set to star in an action adventure movie, Diehard, and it 65 00:04:54.920 --> 00:04:57.800 should be out by next year. That's all right. We have plenty of 66 00:04:57.879 --> 00:05:00.199 dramamine for my first guest tonight, help ris guest, and I plays David 67 00:05:00.240 --> 00:05:03.639 Addison on the hit television series, of Course. The name of the show 68 00:05:03.680 --> 00:05:09.560 is Moonlighting. Please welcome Bruce Willis and from this time in nineteen sixty The 69 00:05:09.680 --> 00:05:14.040 surprise hit movie of the summer here in nineteen sixty is Psycho with Janet Lee 70 00:05:14.120 --> 00:05:18.360 and Anthony Perkins. It's another Alfred Hitchcock Winner. You have a vacacy. 71 00:05:19.600 --> 00:05:25.560 We have twelve vacancies, twelve Cavin's twelve vacancies. If you want anything, 72 00:05:25.600 --> 00:05:28.720 just just half on the wall. I'll be in the office. Thank you, 73 00:05:28.800 --> 00:05:33.160 Miss Norman Bass And from this time in nineteen seventy two, Matt Davis, 74 00:05:33.199 --> 00:05:36.759 known primarily as a songwriter who's written for the likes of Elvis Presley, 75 00:05:38.000 --> 00:05:42.000 may have a huge hit on his own as Baby Baby Don't Get Hooked on 76 00:05:42.040 --> 00:05:54.120 Me is beginning to get played on major market radio stations with Moore at Man 77 00:05:54.160 --> 00:06:01.720 from Yesterday dot Com, Miss Something Today, Yesterday last week. Check out 78 00:06:01.720 --> 00:06:06.839 our podcasts at www k c a a radio dot com. We leave no 79 00:06:08.000 --> 00:07:19.399 listener behind. It require or to kind of work together, but the beautiful 80 00:07:19.399 --> 00:07:21.439 thing. And I think open source has a lot to do with this, 81 00:07:21.560 --> 00:07:26.079 quite frankly, because the spirit of open source said, look, let's all 82 00:07:26.120 --> 00:07:30.920 collaborate on the foundations and then each of us can build out our unique characteristics 83 00:07:30.920 --> 00:07:35.439 and function out if it makes our company special. Right, yeah, I 84 00:07:35.480 --> 00:07:39.439 think you know. I would say that going back to the Gibson quote you 85 00:07:39.480 --> 00:07:42.040 started with, Right, the future is here, but it's not evenly distributed. 86 00:07:42.480 --> 00:07:45.920 I think the potential is here, but it's not evenly distributed. There's 87 00:07:45.920 --> 00:07:50.240 a there's a tendency where I find engineers are optimizers by nature, and so 88 00:07:50.279 --> 00:07:54.800 a lot of the times, even when they have the opportunity to say, 89 00:07:54.839 --> 00:07:58.920 forget about all that complexity underneath, just build what you want to build, 90 00:07:59.120 --> 00:08:01.759 they still like to tink current way with. You know, let's I think 91 00:08:01.800 --> 00:08:05.120 we can we can make that wheel spin a little bit faster. Let's reinvent 92 00:08:05.160 --> 00:08:07.720 that wheel one more time. So that's just to say that I think that 93 00:08:09.839 --> 00:08:11.879 one of the things that's really important in the in the world of cloud is 94 00:08:13.639 --> 00:08:18.319 constraints, and constraints come in different forms. So open sources is an interesting 95 00:08:18.439 --> 00:08:24.879 example there because open sources at the code level, it's very wide open in 96 00:08:24.959 --> 00:08:28.040 terms of what you can do. I find that can lead to a little 97 00:08:28.480 --> 00:08:33.840 of that tinkering I was describing. That may be superfluous, but APIs play 98 00:08:33.840 --> 00:08:35.600 a huge role in the cloud native space, and I think if you look 99 00:08:35.600 --> 00:08:39.480 at Kuberneties, if you look at Kuberneties, if you look at AWS, 100 00:08:39.519 --> 00:08:45.320 if you look at all these different cloud based services, APIs are usually the 101 00:08:45.360 --> 00:08:48.960 demarcation point between the consumer and the provider. And the place where you can 102 00:08:50.039 --> 00:08:54.960 hide all that you can abstract away all that complexity that's unnecessary for the consumer 103 00:08:56.000 --> 00:09:00.120 side. And I've been, you know, focusing on API design best do 104 00:09:00.279 --> 00:09:03.159 this for a long time. Again, there's ways to design good APIs that 105 00:09:03.200 --> 00:09:07.799 are durable and abstract things. S three and AWS is probably a great example 106 00:09:07.840 --> 00:09:11.960 of that, where it's they launch this API in two thousand and six and 107 00:09:11.000 --> 00:09:16.679 it's hardly changed in seventeen years. And then there's other examples where maybe the 108 00:09:16.960 --> 00:09:22.000 complexity bleeds through. But definitely for organizations I've seen really taking advantage of the 109 00:09:22.039 --> 00:09:26.600 cloud native opportunity. That's what they're doing. They're really using the demarcation points 110 00:09:26.600 --> 00:09:31.840 and the constraints and the abstractions to help people move at the fastest speed they 111 00:09:31.840 --> 00:09:33.279 can to get their job done. Well. Yeah, and you know, 112 00:09:33.600 --> 00:09:39.320 when the target stays the same, that allows you to practice and practice and 113 00:09:39.360 --> 00:09:43.480 get closer to perfection. But when the target keeps moving, you know, 114 00:09:43.480 --> 00:09:48.200 when the goal posts move, that really affects every last bit of the process. 115 00:09:48.240 --> 00:09:52.639 The planning, the roadmap, the execution, the maintenance. Everything becomes 116 00:09:52.720 --> 00:09:56.039 Lucy goosey if the goalposts keep moving. But if at least the target stays 117 00:09:56.080 --> 00:10:00.519 the same, then we can marshal resources it's necessary, and at least we 118 00:10:00.559 --> 00:10:03.679 can track our progress getting to where we want to go right exactly. And 119 00:10:03.720 --> 00:10:11.080 I think complexity is an interesting word here where I think a lot of times 120 00:10:11.080 --> 00:10:15.360 and this is you'll see in a lot of marketing materials in the industry treating 121 00:10:15.399 --> 00:10:18.799 complexity like it's the enemy. Right, complexity is bad. We're going to 122 00:10:18.840 --> 00:10:24.000 simplify everything. I think, like Fred Brookstead his paper in nineteen eighty five 123 00:10:24.120 --> 00:10:26.679 or something talking about different types of complexity, I think the reality is like, 124 00:10:28.279 --> 00:10:31.320 for the most part, look at what we can do with software, 125 00:10:31.399 --> 00:10:35.240 the complex problems that we can solve, and we're going to get into talking 126 00:10:35.240 --> 00:10:39.879 about ahi where it just takes it to all other levels. Right. It's 127 00:10:39.960 --> 00:10:45.360 really the organizations I've seen the work most effectively are the ones that understand that 128 00:10:45.679 --> 00:10:50.080 they have to make complexity of their friend and really learn how to tame complexity, 129 00:10:50.200 --> 00:10:54.759 right, take the wild beast and have it working for you as opposed 130 00:10:54.759 --> 00:10:58.279 to working against you. And a big part of that is delineating, like 131 00:10:58.720 --> 00:11:03.279 what's the complexity that we're solving for versus what's the complexity that we're introducing in 132 00:11:03.320 --> 00:11:07.960 the solution. And so I think with Cloud, that's why it's so powerful 133 00:11:09.080 --> 00:11:13.679 is we could never invent a single appliance that was going to hide all the 134 00:11:13.720 --> 00:11:16.080 complexity inside a box, right, But with with cloud and all the levels 135 00:11:16.120 --> 00:11:20.799 of abstraction that we have and the way that we can interconnect, you know, 136 00:11:20.840 --> 00:11:24.639 the things that we can do in an interconnected way allows us to dance 137 00:11:24.679 --> 00:11:28.679 with the right complexity and kind of and and not lead over too much of 138 00:11:28.679 --> 00:11:33.919 the complexity that we don't need. But to your point, like it's it's 139 00:11:33.960 --> 00:11:37.600 a potential, it's always a potential house of cards because if and that's why 140 00:11:37.600 --> 00:11:41.919 I think embracing complexity is an important thing for organizations to do, because if 141 00:11:41.919 --> 00:11:45.759 you pretend that it's gone right, this is like the fallacies of the network, 142 00:11:45.840 --> 00:11:48.120 right you like they will it will come back and bite you. That's 143 00:11:48.200 --> 00:11:52.159 right. I love what you said, dancing with the right level of complexity. 144 00:11:52.200 --> 00:11:56.080 That's pretty cool stuff. And you gave me a great segue to bring 145 00:11:56.120 --> 00:12:01.159 in Mike Bachman out of architecture and AI for booming Mike, So I'll bring 146 00:12:01.159 --> 00:12:03.840 you in. You know, the beautiful power of AI is again, if 147 00:12:03.840 --> 00:12:09.519 the target stays the same, then we can build our intelligent automation, our 148 00:12:09.600 --> 00:12:13.320 intelligent analysis around all that. Let's go to Mike Bachmann. Actually William mc 149 00:12:13.360 --> 00:12:15.919 knight is on the screen here. Just i'll get some quick thoughts from you. 150 00:12:16.000 --> 00:12:20.399 Go ahead me, well, yeah, yeah, go ahead, okay, 151 00:12:20.679 --> 00:12:26.200 okay, Well, I like what we'll said about cloud native. I 152 00:12:26.200 --> 00:12:28.720 do want to stress that it's more than just cloud computing. So it's more 153 00:12:28.759 --> 00:12:33.759 than just utilizing the cloud for all of the benefits that you get from the 154 00:12:33.759 --> 00:12:37.279 cloud where you don't have to have your own data center and the staff that 155 00:12:37.320 --> 00:12:39.519 goes along with that and all that sort of thing, but you get access 156 00:12:39.559 --> 00:12:43.519 to a wide variety of resources, which is great. But to be cloud 157 00:12:43.559 --> 00:12:48.879 data, you go beyond that, go beyond your lift and shift from your 158 00:12:48.879 --> 00:12:52.399 on prem to the cloud and you get into some of the things that we're 159 00:12:52.399 --> 00:12:58.200 talking about. Specifically, the broad term is micro services, and so to 160 00:12:58.279 --> 00:13:03.519 get there, you have to take your code, your historical code that is 161 00:13:03.559 --> 00:13:07.120 probably not in my pro services, but take that and shrink it down into 162 00:13:07.200 --> 00:13:13.399 manageable, bite sized pieces where each piece does a very finite function, orchestrate 163 00:13:13.440 --> 00:13:20.679 them together with orchestration tools like Kubernetti's was mentioned make sure that everything is containerized, 164 00:13:20.279 --> 00:13:26.240 and this gives the code ability to be portable and manageable across all environments, 165 00:13:26.480 --> 00:13:31.240 as you have been stressing, Eric, but also I think take full 166 00:13:31.279 --> 00:13:33.039 advantage of the cloud and be cloud native. You have to be agile, 167 00:13:33.720 --> 00:13:39.080 and you have to code with CICD as we say, or continuous integration continuous 168 00:13:39.080 --> 00:13:45.080 delivery in mind, and that will help allow you to take full advantage of 169 00:13:45.120 --> 00:13:50.559 the cloud capabilities for your applications, and your DevOps should be more streamlined as 170 00:13:50.600 --> 00:13:56.200 well around this the ICD concept. So putting that all together, it's not 171 00:13:56.320 --> 00:14:03.399 for everything in most enterprises, but a lot of development is going that way, 172 00:14:03.559 --> 00:14:07.799 or it might be going to a place where you still got your on 173 00:14:07.919 --> 00:14:09.720 prem and you're adding on to it in the cloud. Is sort of a 174 00:14:09.840 --> 00:14:16.799 hybrid cloud fashion. So while I wouldn't call cloud native a current standard, 175 00:14:16.279 --> 00:14:22.519 I would say it's a great best practice and definite trend. M Yeah, 176 00:14:22.519 --> 00:14:24.960 and we'll bring Mike Bachman again into the next segment. I suppose I'll go 177 00:14:26.000 --> 00:14:28.759 back to you, William and kind of comments on what you just mentioned there, 178 00:14:28.759 --> 00:14:33.120 which is hybrid cloud. Right. So we have this very hybrid world 179 00:14:33.200 --> 00:14:35.720 right now because I you know, I think the rumors of on prem's demise 180 00:14:35.799 --> 00:14:39.320 have been greatly exaggerated. I think on prem data centers are going to stick 181 00:14:39.320 --> 00:14:43.559 around for a long time. They're gonna be a long tail at least for 182 00:14:43.639 --> 00:14:46.919 seven years, right. Isn't that the amorization schedule for those kinds of investments. 183 00:14:46.919 --> 00:14:50.240 So it's like the accountants and the senior executives are like, no, 184 00:14:50.120 --> 00:14:52.919 no, no, I'm amortizing that for another three or four years. You 185 00:14:52.960 --> 00:14:56.840 can't make it go away just yet. But I think you're going to start 186 00:14:56.879 --> 00:15:00.039 seeing it. We're already seeing this. In fact, before the PANDEM I 187 00:15:00.360 --> 00:15:03.960 went to a territated conference there was a company I can't remember what their name 188 00:15:03.039 --> 00:15:07.000 was, but what they do is they take your data center and they make 189 00:15:07.039 --> 00:15:09.399 it look like S three. So I think you're going to see some interesting 190 00:15:09.399 --> 00:15:13.039 innovations going on on the data center side to be able to leverage these things. 191 00:15:13.039 --> 00:15:18.200 And then things like personally Identifiable Information PII or you're the data you want 192 00:15:18.240 --> 00:15:22.480 to train your outgrams on, you probably want that data on prem. So 193 00:15:22.480 --> 00:15:24.559 they're going to be use cases to leverage on prem. It's not going to 194 00:15:24.600 --> 00:15:28.960 go away soon. So we really have to be careful about where we're going 195 00:15:28.000 --> 00:15:31.360 and how we're getting there, right William one minute, Yeah, that's right. 196 00:15:31.720 --> 00:15:35.200 As I mentioned, some newer parts of applications are going to the cloud, 197 00:15:35.639 --> 00:15:41.320 whereas it still has an on prem foundation to that application, but furthermore 198 00:15:41.000 --> 00:15:48.559 nonsensitive or less critical or you might say voluminous data that is data that's going 199 00:15:48.600 --> 00:15:52.519 into the cloud. And a lot of companies are still are still concerned about 200 00:15:52.559 --> 00:15:56.639 the cloud and exposing their data on the cloud. Some of them, though, 201 00:15:56.679 --> 00:16:00.759 are replicating data in both places, so they get it ask a recovery 202 00:16:00.799 --> 00:16:03.399 type of architecture going as well. So there's a lot of options in here 203 00:16:03.840 --> 00:16:08.240 with hybrid cloud. And you know, you might use the public cloud for 204 00:16:08.279 --> 00:16:14.320 your birsty type of workloads where in the month you've got some excess capacity that 205 00:16:14.879 --> 00:16:19.120 you're going to need, just use the cloud for that and avoid over provisioning. 206 00:16:21.320 --> 00:16:23.039 Yeah, I know, these are all factors that come into play. 207 00:16:23.080 --> 00:16:26.759 And I'm glad you brought that up because you do buy cloud in credits and 208 00:16:26.799 --> 00:16:32.039 if you have extra capacity and there's a wind time window on using it, 209 00:16:32.519 --> 00:16:34.320 and this is the job of a CIO these days, and a cdo and 210 00:16:34.360 --> 00:16:37.960 a CTO for these folks to talk to each other and understand where they're going. 211 00:16:38.360 --> 00:16:41.879 Plan these things out. Be as agile as possible, but don't lose 212 00:16:41.879 --> 00:16:45.480 your moorings. And then, of course we're talking about AI and training AI. 213 00:16:45.919 --> 00:16:48.480 Well, you're gonna want your own data to train that AI. Folks, 214 00:16:48.480 --> 00:16:52.600 you don't want to train your data on someone else's train your on someone 215 00:16:52.639 --> 00:16:55.240 else's data. But don't touch dot I'll be right back. You are listening 216 00:16:55.279 --> 00:17:06.519 to inside analysis. What if you could own a piece of the future. 217 00:17:07.079 --> 00:17:10.519 What if you could build your next castle not on sand, but on the 218 00:17:10.559 --> 00:17:15.079 bedrock of a modern blockchain ecosystem. The first Internet gold rush made millionaires, 219 00:17:15.119 --> 00:17:19.880 The second wave is minting billionaires, but the third wave is just gathering now 220 00:17:21.319 --> 00:17:26.400 and anyone can get in on the action. 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But we were talking about AI and 268 00:21:11.480 --> 00:21:15.759 your data and on prem data centers not going away and I'll throw this one 269 00:21:15.759 --> 00:21:18.720 over to Mike Bachman because you know, think or two about all this I 270 00:21:18.759 --> 00:21:23.240 mentioned you don't want your data training someone else's AI. Of course that's what 271 00:21:23.519 --> 00:21:27.079 chat GPT did. There are now some lawsuits out there and it's going to 272 00:21:27.119 --> 00:21:30.640 be interesting to see how that pans out. But you've got a lot of 273 00:21:30.680 --> 00:21:33.799 experience in the space at these are amazing times. What are your thoughts about 274 00:21:33.799 --> 00:21:37.480 this nexus of AI and cloud native. Yeah, so, first of all, 275 00:21:37.559 --> 00:21:41.880 Eric, thanks for having having me on today. This is a lot 276 00:21:41.920 --> 00:21:45.680 of fun. The conversation has been great where AI is going. You know, 277 00:21:47.160 --> 00:21:49.799 I loved where you left that off because I often say, do you 278 00:21:49.839 --> 00:21:59.319 want your IP training somebody else's IP? And interfacing with cloud based you know, 279 00:21:59.359 --> 00:22:03.799 machine and tell eligence services such as something like chet GPT, Barred Claude. 280 00:22:04.559 --> 00:22:11.279 There are different ways that each of those different sas services uses their foundation 281 00:22:11.359 --> 00:22:18.079 models under the covers, but some you don't know exactly how your data is 282 00:22:18.119 --> 00:22:23.240 being used in spite of the fact that there are different governance tools that each 283 00:22:23.279 --> 00:22:30.119 one of these types of services offers. Still it's something that we're all impressed 284 00:22:30.119 --> 00:22:34.519 with. Chet GPT really changed a lot. It brought into the zeitgeist. 285 00:22:34.680 --> 00:22:41.319 You know, this concept of something that feels very anthropomorphic, something that feels 286 00:22:41.359 --> 00:22:47.559 like we can talk with a system of computation and get back something of value, 287 00:22:47.960 --> 00:22:52.240 and so it becomes seductive. I guess to want to interface with it. 288 00:22:52.599 --> 00:22:56.519 But I think if we use it as a system of production, or 289 00:22:56.559 --> 00:23:03.279 to put something like a generative, pre trained transform large language model in a 290 00:23:03.319 --> 00:23:07.400 typical data pipeline, we might want to think about how that use case really 291 00:23:07.400 --> 00:23:11.519 plays out, what type of governance needs to be thought through, and then 292 00:23:11.559 --> 00:23:18.480 what ultimately our desired outcome is from that particular use of this technology. Because 293 00:23:18.519 --> 00:23:26.200 it's really really neat stuff. However, it's just scratching the service. Yeah, 294 00:23:26.000 --> 00:23:29.880 you bring up an excellent point here, which is to remember what are 295 00:23:29.880 --> 00:23:33.559 we trying to accomplish? Right And I think one of the hurdles that organizations 296 00:23:33.559 --> 00:23:36.839 will have to get over here and it's happening and fits and starts right now, 297 00:23:37.400 --> 00:23:41.599 is how do we open our minds to the total recall open your mind, 298 00:23:41.720 --> 00:23:45.200 remember Arnold Shorten, But how do we open our minds to this new 299 00:23:45.279 --> 00:23:48.319 set of possibilities? Because there is a tendency to do things the old way 300 00:23:48.400 --> 00:23:52.519 and to get accustomed to our constraints that we have. Well, those constraints 301 00:23:52.519 --> 00:23:57.119 are now largely out the window. So you always want any focus you have 302 00:23:57.279 --> 00:24:03.599 about leveraging AI to be bordered and driven by some business need. What are 303 00:24:03.640 --> 00:24:07.480 we trying to accomplish? Do we want lower costs? Do we want a 304 00:24:07.480 --> 00:24:11.079 better conversion rate? Do we want to better understand the customer? And then 305 00:24:11.240 --> 00:24:15.960 let your team run wild in terms of coming up with how to leverage it. 306 00:24:15.200 --> 00:24:18.599 Give them a sandbox to play with to do something, but be careful 307 00:24:18.680 --> 00:24:22.920 have the guardrails. Do this in your on prime environment, for example, 308 00:24:22.920 --> 00:24:26.880 don't just throw it into one of these large language models. But focusing on 309 00:24:26.920 --> 00:24:32.640 the business outcome and then using these technologies to get there, that's the key 310 00:24:32.640 --> 00:24:36.599 to success. What do you think? Yeah, I agree with with all 311 00:24:36.599 --> 00:24:41.680 of that more or less. And I think you know the idea of being 312 00:24:42.319 --> 00:24:45.759 you know, at the nexus of where the art of the possible and the 313 00:24:45.799 --> 00:24:49.079 reality of the feasible meat is sort of where you know, both Matt and 314 00:24:49.079 --> 00:24:55.400 I have spent much of our career and with that comes you know, new 315 00:24:55.400 --> 00:25:03.599 and emergent technologies such as these really suffici sisticated sets of computation artificial intelligence, 316 00:25:03.640 --> 00:25:06.440 or I like to refer to it as machine intelligence, because I don't know 317 00:25:06.480 --> 00:25:10.839 what intelligence is, whether something's real or artificial. That's a philosophical conversation. 318 00:25:11.400 --> 00:25:15.039 But that said, fathom, you know, this is really powerful, and 319 00:25:15.079 --> 00:25:19.680 so before we use a powerful technology, we probably want to test it out 320 00:25:19.720 --> 00:25:23.200 in the sandbox environment. And one of the things that I love about how 321 00:25:23.279 --> 00:25:29.960 you're bringing together the conversation between cloud native and artificial intelligence is because they see 322 00:25:29.960 --> 00:25:33.880 them go hand at hand, you know, in terms of agile process, 323 00:25:33.960 --> 00:25:40.279 micro services, all of these things I think AI is today is really a 324 00:25:40.319 --> 00:25:44.359 lot of the and computation at scale. The ability to have memory systems and 325 00:25:44.480 --> 00:25:49.000 networks at scale as we do today happened iteratively for you know, really seven 326 00:25:49.079 --> 00:25:57.319 decades, and this was sort of the Turing's vision was what we're now realizing, 327 00:25:57.359 --> 00:26:03.720 where asian is actually capable of feeling and so how you know, data 328 00:26:03.799 --> 00:26:08.359 evolved with you know, with these different systems that we've built over the course 329 00:26:08.400 --> 00:26:11.799 of the last seven or so decades. We're at a point now where we 330 00:26:11.880 --> 00:26:21.319 get to see just the incipient phases of where AI or machine intelligences could take 331 00:26:21.440 --> 00:26:26.559 us, and so to use machine intelligence inside of our processes can be really, 332 00:26:26.599 --> 00:26:33.039 really seductive, and so it's important that we really think through all of 333 00:26:33.079 --> 00:26:37.519 the realm of possibilities that artificial intelligence can give an organization, look at our 334 00:26:37.599 --> 00:26:42.799 use cases and really become ready to receive AI in ways that we haven't. 335 00:26:42.839 --> 00:26:49.559 In fact, right now we're developing whole whole programs around AI readiness because this 336 00:26:49.960 --> 00:26:55.640 seems to be where folks want to know. Where can I use chat GPT? 337 00:26:56.240 --> 00:26:59.559 Is chat GPT the only thing I can use? Short answer, no, 338 00:27:00.000 --> 00:27:03.880 it's not. What are these models that I can take advantage of? 339 00:27:03.000 --> 00:27:06.720 Do I have to go through assas service to use them? Yes? Or 340 00:27:06.759 --> 00:27:11.680 no? How do I make sure that I can trust whatever this AI engine 341 00:27:11.720 --> 00:27:15.519 is giving me? Because I hear it it hallucinates? What does that mean? 342 00:27:15.880 --> 00:27:19.079 How is that relevant to my business? Right? These are just some 343 00:27:19.400 --> 00:27:23.559 of many concepts that we have to think through to become AI ready. And 344 00:27:23.640 --> 00:27:26.119 you know, I'm so glad you brought that up. That is a huge 345 00:27:26.200 --> 00:27:30.599 issue to tech. Maybe that's structured, it's probably more like ten, which 346 00:27:30.599 --> 00:27:36.920 means you've got ninety percent unstructured data. It's in documents, pdf, spreadsheets, 347 00:27:37.000 --> 00:27:40.079 emails, all sorts, of unstructured data. Well, guess what that's 348 00:27:40.079 --> 00:27:45.319 the context for your structured data now when the executives reports down and know the 349 00:27:45.400 --> 00:27:48.920 general context. But machines don't crawling around in your data, so you need 350 00:27:48.960 --> 00:27:52.119 to be ready to use AI. And you made another really interesting point here 351 00:27:52.119 --> 00:27:57.359 I'd like you to expand upon, which is we're not really gonna know until 352 00:27:57.400 --> 00:28:02.640 we play around how these things operate in what they do. And if folks 353 00:28:02.640 --> 00:28:04.440 WO haven't done it yet, you should definitely start playing around with these large 354 00:28:04.519 --> 00:28:07.759 language models. Just the different prompts you can get. We did all show 355 00:28:07.759 --> 00:28:14.519 on that last week about sequential prompts and strategically aligned prompts basically, and you 356 00:28:14.559 --> 00:28:17.680 can give lots of details. And then of course there's d MS into a 357 00:28:17.759 --> 00:28:21.200 vector dease of truth as Brian Raymond referred to it. A guy we had 358 00:28:21.200 --> 00:28:23.640 on the show last week. I love that concept anchors of truth. But 359 00:28:23.920 --> 00:28:27.519 you need a skunk works team to play around with this stuff, just to 360 00:28:27.599 --> 00:28:33.000 hash out the range of possibilities of what's going to be plausible to spend your 361 00:28:33.039 --> 00:28:36.480 time and effort on. And if you do that carefully, you know what 362 00:28:36.640 --> 00:28:40.640 was Eisenhower's line about planning I've always found that plans are useless, but planning. 363 00:28:40.880 --> 00:28:44.720 Planning is indispensable. You're going to learn a lot by playing around with 364 00:28:44.759 --> 00:28:49.079 this stuff, right, absolutely. And I do want to talk about something 365 00:28:49.119 --> 00:28:55.240 you just said, and that is I'm glad you had a conversation about embeddings 366 00:28:55.240 --> 00:29:00.519 and vector databases last week because really, you know, people off asked me, 367 00:29:00.160 --> 00:29:04.480 what changed? How did this thing come to be? Was it? 368 00:29:04.720 --> 00:29:08.319 Remember when chat GPT was introduced, it seemed to come out of nowhere. 369 00:29:08.400 --> 00:29:15.720 Well, if you've been in the space, theres that have happened the decades 370 00:29:15.799 --> 00:29:18.880 leading up to twenty seventeen. In December of twenty seventeen, there was a 371 00:29:18.920 --> 00:29:25.000 paper that came out that was sort of seminal for what where we're at today 372 00:29:25.759 --> 00:29:29.839 with something called Transformers. And since you had the conversation last week, we'll 373 00:29:29.880 --> 00:29:33.839 have your listeners go back to that. But really easily to distill what changed 374 00:29:34.559 --> 00:29:41.240 is humans no longer have to think like computers in order to retrieve information. 375 00:29:41.839 --> 00:29:45.799 Now the computer we can offload that function to the computer to do this, 376 00:29:45.359 --> 00:29:51.759 and so these anchors of truth that your previous guest had talked about is exactly 377 00:29:51.799 --> 00:29:56.720 that sort of thing wherein you know, instead of us having to think in 378 00:29:56.839 --> 00:30:03.039 terms of sequel statements or compute logic and in orgates, we can now ask 379 00:30:03.319 --> 00:30:08.119 in our own native languages, whether that's English, German, Russian, whatever, 380 00:30:10.160 --> 00:30:15.559 you can ask in your own native language a query question and you can 381 00:30:15.599 --> 00:30:21.640 get a response that really downs relevant to whatever the answer is going to be. 382 00:30:22.079 --> 00:30:25.160 And there's a you know, another thing to think about here too. 383 00:30:25.680 --> 00:30:33.599 The more that you provide context based data into that particular question, or you 384 00:30:33.720 --> 00:30:38.400 I view the machine intelligence with relevant data, the better your answers are going 385 00:30:38.440 --> 00:30:41.200 to be. And you brought something else up that I want to point out 386 00:30:41.240 --> 00:30:45.759 too, which is talking about different types of prompts. I like lazy prompting 387 00:30:47.480 --> 00:30:53.720 because what that means is that I can have conversations with the machine intelligent system 388 00:30:53.720 --> 00:31:00.000 that I'm talking to, whether it's Claude barred or chat GPT or something else, 389 00:31:00.839 --> 00:31:04.480 and be able to ask a very simple, root ammentary question about a 390 00:31:04.599 --> 00:31:11.680 particular topic and then riff with the computer until I come up with the answer 391 00:31:11.839 --> 00:31:17.160 that is sufficient for me, and so I don't need necessarily and certainly over 392 00:31:17.200 --> 00:31:21.920 time, I do not anticipate that these systems are going to require a well 393 00:31:22.039 --> 00:31:27.200 prompt engineered sort of input in order to achieve achieve a desired outcome. Instead, 394 00:31:27.240 --> 00:31:32.440 what it's going to require is domain efficiency with the kinds of questions that 395 00:31:32.480 --> 00:31:37.279 you're asking, and the ability to have two interlocutors, one human one machine, 396 00:31:37.000 --> 00:31:41.119 being able to rip off of each other until a defined answer is achieved. 397 00:31:42.039 --> 00:31:45.960 Yeah, lazy prompting, that's brilliant. It's like the open ended question. 398 00:31:47.039 --> 00:31:49.079 Right, maybe I'll bring let's see, I'll bring Matt mcclardy back into 399 00:31:49.079 --> 00:31:53.119 the conversation. The point is you have to play around with these things to 400 00:31:53.240 --> 00:31:56.440 understand how they work. It's like I got back into playing ping pong and 401 00:31:56.480 --> 00:32:00.839 reminding myself about spin, top spin, back spin. You have to do 402 00:32:00.880 --> 00:32:02.279 it a few times before you're oh, that's right. If he does backspen, 403 00:32:02.319 --> 00:32:05.079 I got to do backs. But if he does forcement, I got 404 00:32:05.079 --> 00:32:07.799 to do forcemen that kind of thing. That's what you're going to learn when 405 00:32:07.799 --> 00:32:09.759 you play around with these things. But there is so much to learn. 406 00:32:09.799 --> 00:32:15.200 We've only just begun, right. Yeah, you know, innovation in the 407 00:32:15.240 --> 00:32:21.319 technology space is a really it's a tricky. It's it's more art than science. 408 00:32:21.960 --> 00:32:24.720 I've been you know, I think it's The point was made earlier about 409 00:32:24.759 --> 00:32:29.920 really zoning in on the business need. But until you know what the range 410 00:32:29.920 --> 00:32:32.839 of possibilities are, it's hard to even figure out what business possibilities are going 411 00:32:32.960 --> 00:32:37.079 after And we've seen this. This isn't just a new thing for the AI 412 00:32:37.160 --> 00:32:40.319 space, but in any sort of technology domain, like how do you when 413 00:32:40.359 --> 00:32:45.480 a new technology comes along, where do you apply it? There can be 414 00:32:45.559 --> 00:32:51.000 a huge temptation to just you know, take the new hammer and everything is 415 00:32:51.039 --> 00:32:54.319 a nail. And at the other end of the spectrum you may be myoptically 416 00:32:54.400 --> 00:33:00.400 focused on some particular business needs. So I think the point about just having 417 00:33:00.400 --> 00:33:05.200 people get into that world and play around with it and get an understanding is 418 00:33:05.240 --> 00:33:08.920 important. But again I was talking earlier about the practical application and where there. 419 00:33:09.000 --> 00:33:13.920 So I think that AI has for the most part the world of out 420 00:33:13.960 --> 00:33:17.880 of the world of analytics right in data and analytics. It's it's essentially this 421 00:33:17.960 --> 00:33:22.319 is a massive oversimplification, but it's like code written by data, right. 422 00:33:22.400 --> 00:33:25.799 This is this is kind of if we if we were to classify all the 423 00:33:25.880 --> 00:33:30.720 all the AI stuff that's out there, and so garbage in, garbage out. 424 00:33:30.839 --> 00:33:35.519 It's putting the focus on the data is extremely important, but it's easy 425 00:33:35.559 --> 00:33:39.480 because of all the complexity in that world to get lost and forget about if 426 00:33:39.519 --> 00:33:45.119 you're a business evaluating the usage of this technology, how is it actually moving 427 00:33:45.160 --> 00:33:47.119 the needle from my business? Where am I going to realize value? And 428 00:33:47.200 --> 00:33:52.799 so, you know, I think for companies that are pure play building new 429 00:33:52.880 --> 00:33:55.240 models, you know, doing all the innovation on the AI side, fundamentally 430 00:33:55.279 --> 00:34:00.880 important where we sit and boomy is we we have a ten to span those 431 00:34:00.920 --> 00:34:05.319 worlds just by virtue where a platform resides, right, we're going from the 432 00:34:05.400 --> 00:34:09.719 data bringing that to the surface where it's used in by customers, for companies, 433 00:34:09.760 --> 00:34:16.000 by other user interactions, by automated process that drive the business. So 434 00:34:16.039 --> 00:34:21.400 I think this is where we've been able to observe, even pre AI other 435 00:34:21.440 --> 00:34:25.920 technologies, like where the value gets realized in all of this isn't so much 436 00:34:27.000 --> 00:34:30.880 in the latest and greatest model that gets invented, But how does the insights 437 00:34:30.920 --> 00:34:36.880 coming out of the models, how do they actually get leveraged in the flow 438 00:34:36.920 --> 00:34:42.639 of business to drive the business model for companies. So and I've seen a 439 00:34:42.639 --> 00:34:45.719 lot of companies sort of approach this from the data side, from the supply 440 00:34:45.840 --> 00:34:49.760 side, almost like hey, get our data or in order to get our 441 00:34:49.800 --> 00:34:52.199 AI strategy in order we need to look at the data, think about all 442 00:34:52.239 --> 00:34:57.159 the types of data that we have. I think it's actually quite useful to 443 00:34:58.159 --> 00:35:01.800 invert that and look at things from the consumer side and think of Okay, 444 00:35:02.800 --> 00:35:07.400 if if we know the place that the value is going to be realized is 445 00:35:07.440 --> 00:35:12.679 going to be in the execution of our business model, whether that's how seamlessly 446 00:35:12.719 --> 00:35:16.960 we integrate or how seamlessly we interact with our customers, how we support our 447 00:35:17.000 --> 00:35:22.039 customer channels through you know, assisted channels right, like you can see it 448 00:35:22.039 --> 00:35:24.760 becomes make it more bite size and you can, you know, taking the 449 00:35:24.800 --> 00:35:29.519 principles of cloud native and micro services, you can you can right anyway, 450 00:35:29.880 --> 00:35:30.800 Yeah, that's an excellent point. Well, folks, don't touch it. 451 00:35:30.840 --> 00:35:36.800 I'll be right back. You are listening to inside analysis. 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Call eight hundred 483 00:37:55.280 --> 00:38:00.840 seven one oh three seven three nine, eight hundred seven three seven three nine, 484 00:38:01.039 --> 00:38:06.480 eight hundred seven one h three seven three nine. That's eight hundred seven 485 00:38:06.559 --> 00:38:10.960 one h thirty seven thirty nine n MLS sixty six ZH six www dot MLS, 486 00:38:12.079 --> 00:38:15.119 consumer XS dot org. This is not an offer or commitment to end 487 00:38:15.199 --> 00:38:17.920 subject to borrow or improperty qualifications. Not all borrowers will qualify. Terms and 488 00:38:17.920 --> 00:38:22.679 conditions apply equal housing opportunity. Do you need to get your hands on some 489 00:38:22.760 --> 00:38:27.000 extra money right now? Maybe twenty five thousand or more If you're a homeowner, 490 00:38:27.079 --> 00:38:30.039 Now is a perfect time to get cash out while homes in many neighborhoods 491 00:38:30.039 --> 00:38:34.679 like yours have gone up in value. 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This 501 00:39:12.880 --> 00:39:15.320 is not an offer or commitment to end subject to borrow We're improperty qualifications. 502 00:39:15.400 --> 00:39:23.079 Not all borrowers will qualify. Terms and conditions apply equal housing, opportunity expression. 503 00:39:23.320 --> 00:39:31.880 Welcome back to Inside Analysis. Here's your host, Eric Kavanaugh. All 504 00:39:32.000 --> 00:39:37.360 right, ladies and gentlemen, back here on Inside Analysis, your host Eric 505 00:39:37.440 --> 00:39:39.880 Kavanaugh with an all star cast. Here we've got Matt McCarty CTO, and 506 00:39:39.920 --> 00:39:44.920 Mike Bachmann, head of AI and architecture over at Boomy, and William McKnight 507 00:39:45.360 --> 00:39:49.199 number one cloud analysts in the world according to some sources, and I'm fine 508 00:39:49.239 --> 00:39:52.760 with that. And William, you've made a couple of really good points about 509 00:39:52.920 --> 00:39:59.159 cloud native as a concept and about principles of engineering and software development and design 510 00:39:59.199 --> 00:40:02.159 and program management. I mean, that's really what a CIO needs to be 511 00:40:02.199 --> 00:40:07.039 doing, is program management, understanding where to allocate resources, what to put 512 00:40:07.079 --> 00:40:10.760 in the cloud, what to do on prem's it's a fun time, but 513 00:40:10.840 --> 00:40:15.480 it's a bit of a dizzying time. What's your advice for how to navigate 514 00:40:15.519 --> 00:40:20.360 through these waters. Well, you're going to get a typical enterprise. It's 515 00:40:20.360 --> 00:40:23.239 not going to get there all at once. So I take an inventory of 516 00:40:23.280 --> 00:40:30.079 your on prem assets that could move to the cloud. The better architecture they 517 00:40:30.119 --> 00:40:35.719 are today, the easier they will be to migrate to the cloud. And 518 00:40:36.039 --> 00:40:38.440 there's there's a host of things that need to be done. Obviously, you 519 00:40:38.440 --> 00:40:44.280 need to select a cloud provider, adapt a micro services architecture. That's a 520 00:40:44.320 --> 00:40:46.880 big one there. If you really want a cloud native. Now some things 521 00:40:46.920 --> 00:40:52.239 you're just going to move, lock and load cloud computing. Okay, we 522 00:40:52.320 --> 00:40:54.719 get some of those benefits like I mentioned before, but to get the cloud 523 00:40:54.800 --> 00:40:59.880 native, which is that next level of value, next level of value that 524 00:41:00.039 --> 00:41:04.559 the application portfolio is going to be delivering back to the business, you want 525 00:41:04.599 --> 00:41:09.559 to adopt the micro services architecture and understand that when you do this and move 526 00:41:09.599 --> 00:41:14.440 to the cloud, you're now in for the most parked serverless computing. So 527 00:41:14.519 --> 00:41:17.719 you don't have to worry about things like provisioning and managing servers, trying to 528 00:41:19.119 --> 00:41:23.320 guestimate how scalable this needs to be where it's going to go. That's all 529 00:41:23.360 --> 00:41:28.280 taken care of, as well as backup recovery, all your kind of operational 530 00:41:28.320 --> 00:41:30.800 things as well. So there's a lot of good things in moving to the 531 00:41:30.800 --> 00:41:37.000 cloud and getting to cloud native. You've got to containerize and package your applications, 532 00:41:37.320 --> 00:41:40.440 you got to choose an orchestration platform and implements the ICD. But I 533 00:41:40.480 --> 00:41:47.039 will also add that what the cloud allows is much more visibility in two operations, 534 00:41:47.519 --> 00:41:54.119 and so you can use tools like Prometheus or Grafana to monitor your applications 535 00:41:54.199 --> 00:41:59.920 at a much lower level than you ever did before. You can also selective 536 00:42:00.079 --> 00:42:07.519 move to manage services in the cloud in order to minimize your overall operational overhead. 537 00:42:07.960 --> 00:42:10.920 Beyond that, you're just going to have to iterate and improve until your 538 00:42:12.239 --> 00:42:16.320 environment visaly the cloud is where you want it to be, and you're never 539 00:42:16.360 --> 00:42:20.599 going to get there because there's mings coming in the door all the time. 540 00:42:20.920 --> 00:42:23.760 Maybe you push those to the cloud and by the time you think you might 541 00:42:23.800 --> 00:42:29.199 get there or something else will come in play, and you'll just keep moving. 542 00:42:29.239 --> 00:42:32.559 But keep moving, keep going forward. Remember holp to make how to 543 00:42:32.559 --> 00:42:36.880 do priversation, to want to do things that are easy to do, that 544 00:42:36.920 --> 00:42:40.559 you can do low risk. We've been talking about kind of reading the same 545 00:42:40.599 --> 00:42:45.599 thing for cloud. You want to set yourself up for the future by doing 546 00:42:45.639 --> 00:42:51.960 things now or immediately that help you do bigger and better things in the future. 547 00:42:52.360 --> 00:42:58.559 And so some ways that you divide up your applications inside of your enterprise 548 00:42:58.599 --> 00:43:00.920 can help you do that. Finally, and most importantly, is you want 549 00:43:00.960 --> 00:43:05.800 to add value back to the enterprise. We've been talking a lot about ROI, 550 00:43:05.880 --> 00:43:10.519 and I'm all about ROI when it comes to AI, though, yes, 551 00:43:10.800 --> 00:43:16.000 we do need to explore how can we ever project and we really don't 552 00:43:16.039 --> 00:43:19.760 know what we're doing. We don't know what possibilities are, we don't know 553 00:43:19.760 --> 00:43:22.800 how long it's going to take or what resources. Organizations really need to be 554 00:43:22.880 --> 00:43:27.360 learning a lot now and where to apply it. Let's see, I'll throw 555 00:43:27.400 --> 00:43:29.840 it over to I guess Mike Bachmann. I see you nodding your head. 556 00:43:30.719 --> 00:43:34.320 A lot of great stuff from William there. It's a lot to digest and 557 00:43:34.400 --> 00:43:37.920 understand. Again. Prioritization, I mean to me, this is one of 558 00:43:37.960 --> 00:43:40.800 the most important things in any organization these days. How do you prioritize what 559 00:43:40.880 --> 00:43:46.159 you're working on now? How investment ling future innovation versus keeping the train running 560 00:43:46.159 --> 00:43:49.760 on time and all that stuff. You got to make sure that stuff works. 561 00:43:50.000 --> 00:43:54.440 But it's about intelligent automation and integration. And you begin to learn from 562 00:43:54.440 --> 00:44:00.119 these models how to optimize. Me possibly more than the generative AI stuff is 563 00:44:00.280 --> 00:44:07.960 learning to optimize these incredibly complex architectures to save time, improve performance, and 564 00:44:07.039 --> 00:44:09.760 by the way, if you do it right, you're also improving security. 565 00:44:09.800 --> 00:44:14.440 What do you think, Michael, Yeah, I think that the three often 566 00:44:14.559 --> 00:44:19.679 stated rules of value are day out of jail, you know there's risk, 567 00:44:20.320 --> 00:44:23.760 and so as long as you can tie technical value to one of those three 568 00:44:24.039 --> 00:44:28.719 areas, I think you have a good case to make about how you can 569 00:44:28.760 --> 00:44:32.480 go about prioritizing. In fact, what William just said sounds an awful lot 570 00:44:32.519 --> 00:44:37.880 like how you determine whether your principles is a little bit of a heavy word 571 00:44:37.920 --> 00:44:42.719 for me, but we could say a list of six and growing things to 572 00:44:42.800 --> 00:44:47.360 think about when being AI ready, having clear goals, Having great documentation one 573 00:44:47.360 --> 00:44:53.280 of the biggest inhibitors to whether you're talking about breaking up an application into smaller 574 00:44:53.320 --> 00:44:59.280 pieces, or whether you talk intelligence or machine intelligence. A dearth of a 575 00:44:59.320 --> 00:45:04.760 documentation creates a lengthy road for you to get to your destination. So documentation 576 00:45:04.880 --> 00:45:10.440 is key account This isn't artificial intelligence isn't just about stuff that makes your bow 577 00:45:10.480 --> 00:45:15.719 tie spin for you know, for tech geeks like myself, but it's it's 578 00:45:15.719 --> 00:45:20.760 about bringing the line of business together with the technology in order to have a 579 00:45:20.760 --> 00:45:23.920 way to make money, save money or reduce risk as important and we go 580 00:45:24.039 --> 00:45:30.400 through in our workshop, needs to be had by all of the stakeholders involved 581 00:45:30.639 --> 00:45:35.679 in these coprocesses, which should be documented. And then one of the biggest 582 00:45:35.679 --> 00:45:39.880 things in the area is automating manual processes. AI works at SPET. We 583 00:45:40.760 --> 00:45:45.639 be able to, you know, sort of get our heads wrapped around a 584 00:45:45.639 --> 00:45:51.559 lot of manual prospated processes are dependent upon and so I implore our enterprise organizations 585 00:45:51.599 --> 00:45:54.719 with which we work to automate those manual processes. And the last thing is 586 00:45:55.400 --> 00:46:00.480 really getting good understanding our data, data quality, data governance, data lineage, 587 00:46:00.559 --> 00:46:04.239 line of data that you know, we call the context is the stuff 588 00:46:04.440 --> 00:46:09.199 the AI for data that's going to be sore to your orgation in some particular 589 00:46:09.239 --> 00:46:14.280 way. And so the idea is if you can create a good context pipeline 590 00:46:14.760 --> 00:46:20.920 to ground the teenager to which I read before, this hallucinogenic precosition as an 591 00:46:20.920 --> 00:46:23.800 advisor to your business, well, that's one pipeline that we can serve today. 592 00:46:23.920 --> 00:46:30.400 Okay, now fonds that you're getting from this new advisor to your business, 593 00:46:30.639 --> 00:46:34.400 what do you do with that okay's great, we should have we should 594 00:46:34.840 --> 00:46:37.239 act in certain way. But if you don't have an automated way to do 595 00:46:37.320 --> 00:46:40.559 that sort of thing, well, that makes sure keep you in a place 596 00:46:40.599 --> 00:46:45.039 of being moored on the side of the ocean, so the on the shore, 597 00:46:45.280 --> 00:46:47.199 off the shore. And so the idea is you want to have a 598 00:46:47.239 --> 00:46:52.920 context pipeline as input feeding the AI action pipeline as a response to what the 599 00:46:52.960 --> 00:46:58.880 AI is suggesting from a predictive state statement and whether that's predicting you know, 600 00:46:58.960 --> 00:47:06.039 how how to restock your inventory payments on time to your veil under a different 601 00:47:07.199 --> 00:47:09.760 So there's a whole panel plate of different options that we have of use cases 602 00:47:10.079 --> 00:47:15.159 where that action pipeline needs to be automated as well. So, yeah, 603 00:47:15.239 --> 00:47:19.000 those are all excellent points. And you use that term suggest and I'll throw 604 00:47:19.039 --> 00:47:22.320 this over guests to mep here before the live section in our podcast put a 605 00:47:22.400 --> 00:47:27.679 segment comes up. But I believe that by and large the power of AI 606 00:47:27.719 --> 00:47:31.320 will manifesttions, and so the key is to be open to those suggestions and 607 00:47:31.360 --> 00:47:36.760 then track when the suggestion helped and when the suggested didn't help, And over 608 00:47:36.840 --> 00:47:38.960 time you're going to get better and better suggestions. From your AI real quick, 609 00:47:38.960 --> 00:47:42.840 what do you think completely? I think this is all about it. 610 00:47:42.880 --> 00:47:45.400 As we've heard, it's all about learning. We don't intelligence. It's all 611 00:47:45.440 --> 00:47:51.360 about learning. So those suggestions, so data creates data. When we put 612 00:47:51.360 --> 00:47:53.519 those insights into action, we get more insights and we can put those into 613 00:47:53.559 --> 00:47:59.039 action and you create these feedback loops here and everything that Williams is describing around 614 00:47:59.079 --> 00:48:02.239 the principles of native and the practices that come along with that. Breaking things 615 00:48:02.239 --> 00:48:08.760 down, frequent change, smaller, more inventable bits is fundamental to even more 616 00:48:08.840 --> 00:48:13.599 so for AI, and this is something as a company actually with Boomy we 617 00:48:13.800 --> 00:48:16.480 we actually have a feature called Boomy Suggestment around for a while our own AI 618 00:48:16.559 --> 00:48:22.280 journey. All those learnings that we've gone through you integrate automated, we've put 619 00:48:22.320 --> 00:48:27.360 them. So it's definitely probably that when it comes to AI. That's that 620 00:48:27.480 --> 00:48:30.280 is such an excellent point. You know what, I don't think I've heard 621 00:48:30.320 --> 00:48:34.280 someone say that per se, which is interesting because you're right, even though 622 00:48:34.280 --> 00:48:37.639 we're talking about this artificial intelligence, I have folks who talk about authentic intelligence, 623 00:48:37.679 --> 00:48:42.760 which I like even more. But really it's all about learning and learning 624 00:48:42.800 --> 00:48:45.760 from this reflection that we see from AI because it was built upon or as 625 00:48:45.840 --> 00:49:20.360 upon US. Lifestyle expert Megan Murphy has more try Airborne NBC News Radio. 626 00:49:20.400 --> 00:49:23.239 I'm Chris Garagio. The Jacksonville County sheriff says the gunman who killed three people 627 00:49:23.280 --> 00:49:28.920 at a store in a predominantly black community yesterday had no criminal record and apparently 628 00:49:28.960 --> 00:49:31.599 purchased both of the weapons legally. 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I'm proud of that decision, 637 00:50:02.920 --> 00:50:07.199 and it was the right call, and I hope more people identify with 638 00:50:07.519 --> 00:50:10.960 what I said. Speaking on Scenen State of the Union, the GOP presidential 639 00:50:12.000 --> 00:50:15.079 candidate was referring to his refusal to raise his hand when the candidates were asked 640 00:50:15.079 --> 00:50:19.840 if they would support former President Trump as the Republican nominee if he wins the 641 00:50:19.880 --> 00:50:22.840 nomination. Hutchinson said that he was surprised virtually that all of the other candidates 642 00:50:22.840 --> 00:50:27.519 said they would support Trump even if he's convicted. He added that he's not 643 00:50:27.559 --> 00:50:30.920 concerned that the audience booed him for opposing Trump. Vermont Senator Bernie Sanders is 644 00:50:30.920 --> 00:50:35.320 praising the Biden administration, but it's also quick to point out more needs to 645 00:50:35.360 --> 00:50:37.360 be done. 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That can be a convenience for many workers, but a new 716 00:56:15.159 --> 00:56:21.199 corporate policy, first imposed in March on thousands of its workers in Columbia is 717 00:56:21.280 --> 00:56:27.280 an Orwellian nightmare. Teleperformance is pressuring them to sign an eight page addendum to 718 00:56:27.360 --> 00:56:32.960 their employee contracts allowing corporate controlled video cameras, electronic audio devices, and data 719 00:56:34.000 --> 00:56:38.039 collection tools to be put in their homes to monitor their actions. I work 720 00:56:38.119 --> 00:56:42.559 in my bedroom, one employee noted, I don't want to have a camera 721 00:56:42.679 --> 00:56:46.599 in my bedroom. Neither would I, and I doubt that teleperformances twenty million 722 00:56:46.639 --> 00:56:52.079 dollars a year, CEO would allow one in his mention uglier. Yet the 723 00:56:52.199 --> 00:56:58.800 privacy obliterating contract requires that even the children of employees can be spied on at 724 00:56:58.840 --> 00:57:04.639 home. The list the Colombian workers signed because her supervisors said she could lose 725 00:57:04.719 --> 00:57:08.039 her job if she refused, of course, tell her performance Ain't assures us 726 00:57:08.119 --> 00:57:13.280 that the data it collects on children is not shared elsewhere. But how do 727 00:57:13.360 --> 00:57:16.199 we know that? Trust us? They say? This is Jim high Tower 728 00:57:16.320 --> 00:57:22.360 saying, do you? This segment is sponsored by press Print, Southern California's 729 00:57:22.360 --> 00:57:27.440 best full service union printer and mailhouse. They offer their lowest prices around with 730 00:57:27.599 --> 00:57:31.079 unmatched service and reliability and free delivery throughout so Calle. 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That's 756 00:59:24.119 --> 00:59:29.480 eight one eight six one zero eight zero eight eight to ebot club dot com. 757 00:59:30.960 --> 00:59:34.719 Did you know here at KCA eight ten fifty a m that we developed 758 00:59:34.760 --> 00:59:38.079 an app for all your Android devices. We're talking about your smartphone, your 759 00:59:38.199 --> 00:59:42.800 tablets, you name it. You have an Android format. You can take 760 00:59:42.920 --> 00:59:46.920 KCAA with you everywhere you go. We're talking about our audio stream, our 761 00:59:47.000 --> 00:59:52.159 video stream, and even our podcast. Go to KCAA express dot com. 762 00:59:52.599 --> 01:00:00.159 That's KCAA express dot com, KCAA express dot com. Del Walmsley here. 763 01:00:00.320 --> 01:00:04.079 The first thing you're going to have to learn is that until you stop expecting 764 01:00:04.199 --> 01:00:07.880 our politicians or anyone else to change your life, your life isn't going to 765 01:00:07.000 --> 01:00:08.400 change. The only person who can