WEBVTT 1 00:00:00.680 --> 00:00:05.320 So why not use your insurance to treat your addiction problem just like you would 2 00:00:05.320 --> 00:00:09.160 if you had a broken bone. And with a family medical ev act, 3 00:00:09.400 --> 00:00:14.080 you're allowed to take time off by law and your employer doesn't need to know 4 00:00:14.240 --> 00:00:18.920 the reason. So there are two good reasons. You've got insurance you can 5 00:00:19.039 --> 00:00:23.839 use for your addiction problem, and with a family medical evact, it's completely 6 00:00:23.920 --> 00:00:29.839 confidential. Call now eight hundred three nine eight seven four one four. That's 7 00:00:29.879 --> 00:00:39.399 eight hundred three nine eight seventy four fourteen. NBC News on CACAA Lomlada sponsored 8 00:00:39.399 --> 00:00:45.200 by Teamsters Local nineteen thirty two Protecting the Future of Working Families Teamsters nineteen thirty 9 00:00:45.240 --> 00:00:57.280 two, dot Org, NBC News Radio. I'm Tammy Trhio Israeli Prime Minister 10 00:00:57.320 --> 00:01:00.359 Benjamin Nettnaw who says he pulled out of ceasefire and otiations over the war in 11 00:01:00.399 --> 00:01:06.719 Gaza because of delusional demands by Hamas Netanya, who said Israel sent negotiators to 12 00:01:06.799 --> 00:01:10.719 Cairo last week as requested by President Biden, but added they won't be back 13 00:01:10.799 --> 00:01:15.519 until Hamas changes its demands. Hamas is calling for a permanency's fire and the 14 00:01:15.560 --> 00:01:19.480 release of more than fifteen hundred prisoners from Israeli jails. A South Carolina Democrat 15 00:01:19.519 --> 00:01:25.799 and longtime friend of President Biden says misinformation efforts are his biggest concern regarding the 16 00:01:25.840 --> 00:01:30.439 twenty twenty four presidential campaign. I've heard so much from people who seem to 17 00:01:30.480 --> 00:01:36.560 feel that everything they see or hear via the Internet has some substance to them. 18 00:01:36.680 --> 00:01:40.799 Speaking on CBS's Face the Nation, Congress, and James Cliburn said people 19 00:01:40.840 --> 00:01:45.079 believe a lot of negative information online about Biden that isn't true. Cliburn pointed 20 00:01:45.120 --> 00:01:49.120 to the recent incident of an AI generated message using the President's voice to send 21 00:01:49.159 --> 00:01:53.159 out false messages. He's concerned that type of false information will be very, 22 00:01:53.280 --> 00:01:57.519 very prevalent in this year's election. Two Minnesota police officers and a paramedic were 23 00:01:57.519 --> 00:02:01.079 shot and killed while responding to a domestic abuse early today in a Minneapolis suburb. 24 00:02:01.280 --> 00:02:05.439 Dylan Holls as he heard a few bangs a minute apart in his Burnsville 25 00:02:05.480 --> 00:02:08.199 neighborhood. I'm not sure that those were gunshots. They might have been tear 26 00:02:08.240 --> 00:02:13.520 gas or flash bangs or something. According to the Star Tribune, law enforcement 27 00:02:13.560 --> 00:02:17.199 sources confirmed the suspected gunman died of a self inflicted gunshot wound. Burnsville is 28 00:02:17.199 --> 00:02:22.680 about fifteen miles south of Minneapolis. Please are expected to provide more details at 29 00:02:22.680 --> 00:02:27.120 a news conference later today at Burnsville City Hall. A biopic about a reggae 30 00:02:27.159 --> 00:02:30.479 legend tops this weekend's box office. Bob Marley One Love took in an estimated 31 00:02:30.520 --> 00:02:35.599 twenty seven point seven million dollars in its opening weekend. The movie debuted on 32 00:02:35.639 --> 00:02:38.960 February fourteenth and set a record for the biggest MIDWEK Valentine's Day opening ever. 33 00:02:39.199 --> 00:02:44.400 Madam Webb opened in second place, while Argyle dropped a third. You're listening 34 00:02:44.479 --> 00:02:51.680 to the latest I'm Tammy Trhio and now the voices of KCAA was an exciting 35 00:02:51.719 --> 00:02:55.400 announcement. Want to hear NBC News or KCAA anywhere you go? Well, 36 00:02:55.439 --> 00:03:00.319 now there's a nap for that. 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Inside Analysis is your source of information and insight about how to make 77 00:06:35.199 --> 00:06:42.360 the most of this exciting new eraic Learn more at inside analysis dot comsideanalysis dot 78 00:06:42.399 --> 00:06:50.040 com. And now here's your host, Eric Kavanaugh. People. All right, 79 00:06:50.199 --> 00:06:54.800 folks, hello, and welcome back once again to the only coast to 80 00:06:54.879 --> 00:06:58.920 coast show all about the information economy. It's called Inside Analysis. Who is 81 00:06:58.959 --> 00:07:02.480 truly Eric Kavanaugh here with a very special guest, one of the most renowned 82 00:07:02.519 --> 00:07:06.160 cloud experts in the world, quite frankly, and a guy who I just 83 00:07:06.160 --> 00:07:13.439 found out moments ago coined the acronym EAI Enterprise Application Integration. I remember those 84 00:07:13.519 --> 00:07:16.759 Eddie days back in the nineties and the early aughts when we were really in 85 00:07:16.839 --> 00:07:24.160 the earlier days of trying to integrate enterprise applications like ERP, Enterprise resource planning, 86 00:07:24.240 --> 00:07:29.199 data warehouses, click, extreme analysis, all sorts of different systems, 87 00:07:29.360 --> 00:07:31.920 which of course used different data models, different types of data. The whole 88 00:07:31.959 --> 00:07:35.800 data warehousing world ben because we tried to get sense of what was really going 89 00:07:35.839 --> 00:07:41.120 on in all these different systems. And now that is bigger than ever. 90 00:07:41.800 --> 00:07:46.560 But Jennai is coming up and driving everything further in different directions, and we're 91 00:07:46.560 --> 00:07:49.439 all just trying to hang out for dear life to a certain extent. But 92 00:07:49.439 --> 00:07:54.120 we're going to talk today about the evolution of cloud computing. And David has 93 00:07:54.160 --> 00:07:57.959 a new book out in Insider's Guide to Cloud Computing at stron and Mechaman. 94 00:07:58.240 --> 00:08:01.720 You look that up and check it out, and I'll just give you my 95 00:08:01.160 --> 00:08:05.800 two cents here on what we'll talk about today. So what is the cloud 96 00:08:05.800 --> 00:08:09.319 today? Why are people going to the cloud? Why are people leaving the 97 00:08:09.360 --> 00:08:13.600 cloud? You had a joke before earlier today David about the cloud eviction. 98 00:08:13.839 --> 00:08:16.279 Notice, all right, and what's going on there? Sometimes it's too expensive, 99 00:08:16.360 --> 00:08:20.199 sometimes it's not what people thought. Sometimes they get locked in. Remember 100 00:08:20.240 --> 00:08:24.199 the concept of vendor lock in, but it's also the concept of cloud lock 101 00:08:24.279 --> 00:08:28.839 in. Although Google I heard just recently decided to kill all their egress fees, 102 00:08:28.879 --> 00:08:33.399 which was an interesting move. And just so people understand, when you 103 00:08:33.440 --> 00:08:35.200 put data in the cloud, obviously you payp for storage. A lot of 104 00:08:35.200 --> 00:08:41.639 people understand that now with their consumer lives of Apple and Microsoft selling you storage 105 00:08:41.679 --> 00:08:43.480 to keep all your stuff, all your videos, it's all your files, 106 00:08:43.519 --> 00:08:46.879 etc. But when you load it, of course you pay for storage. 107 00:08:48.000 --> 00:08:50.919 But then the big cloud vendors in the cloud computing world were charging you a 108 00:08:50.960 --> 00:08:52.799 lot of money to take the data out, so it was a penalty. 109 00:08:54.240 --> 00:08:56.639 I used to always use the joke Hotel California, you can check out any 110 00:08:56.639 --> 00:09:00.440 time you like, but you can never leave, at least without paying a 111 00:09:00.440 --> 00:09:03.759 whole lot of money. Then it was just painful, so they wanted to 112 00:09:03.799 --> 00:09:07.240 keep you there. And there are certainly some good arguments to be made for 113 00:09:07.519 --> 00:09:13.039 living within a cloud environment like Amazon Web Services has tons and tons of services. 114 00:09:13.279 --> 00:09:16.840 Microsoft of course is nipping at their heels. Google Cloud platform still in 115 00:09:16.879 --> 00:09:20.159 third place, I think a distant third at the moment, but they were 116 00:09:20.240 --> 00:09:22.919 certainly making a push, and there are others hero Coup, there's a bunch 117 00:09:22.919 --> 00:09:26.279 of others out there, rack Space, Oracle as a cloud. But with 118 00:09:26.360 --> 00:09:30.159 that long sort of intro, I throw it over to David Linthicum. David, 119 00:09:30.360 --> 00:09:33.600 tell us a bit about your new book and Insider's guide to Why are 120 00:09:33.600 --> 00:09:37.639 people going to the cloud today? Why are people leaving the cloud? Yeah? 121 00:09:37.840 --> 00:09:39.320 Thanks, Eric. I mean, ultimately it's a book that gives away 122 00:09:39.399 --> 00:09:43.320 the secrets that I learned in the last fifteen years of cloud computing and actually 123 00:09:43.320 --> 00:09:46.919 been inside the cloud world since the late nineties and got into it with the 124 00:09:46.960 --> 00:09:52.559 whole application delivery network thing, which is a predecessor to SASS, and got 125 00:09:52.600 --> 00:09:56.120 into SAS and got into integration as a service, and then got into the 126 00:09:56.159 --> 00:10:00.639 whole infrastructures of servicing and growth of cloud. And so I think there are 127 00:10:00.679 --> 00:10:05.519 a lot of misperceptions that people, quite frankly don't understand about cloud, and 128 00:10:05.559 --> 00:10:09.399 so I wrote a book which provides the realities of it in terms of what's 129 00:10:09.480 --> 00:10:13.759 cost justifiable and moving to cloud, what's not justifiable and moving to cloud, 130 00:10:15.240 --> 00:10:18.600 The fact that lock in is going to be around each and every time, 131 00:10:18.600 --> 00:10:20.440 you're never going to get away from it, and the ability to leverage the 132 00:10:20.480 --> 00:10:24.120 technology to kind of take everything to the next level. And what's occurring now 133 00:10:24.279 --> 00:10:31.000 is that people are looking for the justification of cloud computing as a business asset. 134 00:10:31.039 --> 00:10:33.639 So, in other words, it was all that in a bag of 135 00:10:33.720 --> 00:10:37.159 chips fifteen years ago. Everybody's moving into cloud was the destination of everything. 136 00:10:37.159 --> 00:10:39.720 We're going to shut everything, shut all the data centers down. And I 137 00:10:39.759 --> 00:10:43.879 think a lot of people believe that, and that's turning out not to be 138 00:10:43.000 --> 00:10:48.120 true, and so we're looking at cloud as a optional destination. We understand 139 00:10:48.120 --> 00:10:52.240 that everything's not going to be in cloud. We're moving to a ubiquitous computing 140 00:10:52.320 --> 00:10:56.879 environment where the STEP's going to run everywhere, including cloud. The cloud's just 141 00:10:56.919 --> 00:10:58.960 going to be an option, and really it should be an option that's justified 142 00:11:00.120 --> 00:11:03.799 in terms of its cost effectiveness and our ability to leverage it to take business 143 00:11:03.840 --> 00:11:07.240 to the next level. And I think that's a spotlight that they haven't been 144 00:11:07.320 --> 00:11:09.039 under yet, and I think it's a good thing that they are. Yeah, 145 00:11:09.200 --> 00:11:13.200 no, that's a good point, And I'm thinking to myself, there 146 00:11:13.240 --> 00:11:16.240 is so much innovation in the cloud. But as I've often said, the 147 00:11:16.320 --> 00:11:22.240 rumors of on prems demise are greatly exaggerated, if for no other reason than 148 00:11:22.279 --> 00:11:28.279 amortization. That's one stickiness. Data does have gravity. Data doesn't like to 149 00:11:28.320 --> 00:11:31.080 be moved, at least large amounts of data really don't like to be moved. 150 00:11:31.080 --> 00:11:33.320 There are all kinds of problems that happen. Records get truncated, records 151 00:11:33.360 --> 00:11:35.879 get lost, that's not put in the right place. All kinds of different 152 00:11:35.879 --> 00:11:39.960 things happen when you move stuff around. And let's face it, in the 153 00:11:39.960 --> 00:11:45.159 older days of data centers, even in the early two thousands, being able 154 00:11:45.240 --> 00:11:50.799 to realistically map what is where throughout that entire environment, even from a data 155 00:11:50.840 --> 00:11:54.879 perspective, it's pretty darn challenging. I mean, some companies came along, 156 00:11:54.039 --> 00:12:00.159 like Elation and some others in the data cataloging space that were our help being 157 00:12:00.440 --> 00:12:03.080 kind of get to the bottom of that and figure out where stuff is. 158 00:12:03.120 --> 00:12:07.159 And there's new technology for being able to scan environments and see look for metadata 159 00:12:07.200 --> 00:12:11.480 fields for example, to understand where your data is. But in most data 160 00:12:11.480 --> 00:12:13.600 centers, data is all over the place in lots of different formats. That's 161 00:12:13.639 --> 00:12:18.240 a very difficult challenge to try to sweep up and put up in the cloud. 162 00:12:18.360 --> 00:12:22.120 Right. Yeah, And now we have a new priority that the enterprises 163 00:12:22.159 --> 00:12:26.159 have. And this whole GENAI stuff, the genai needs data to train, 164 00:12:26.519 --> 00:12:31.080 and it needs existing data. Business data that's in mainframe systems, data that's 165 00:12:31.440 --> 00:12:35.440 scattered all over the place, including different cloud providers. Most enterprises leverage a 166 00:12:35.480 --> 00:12:39.600 multi cloud platform. They're leveraging more than one or two different cloud providers. 167 00:12:39.679 --> 00:12:43.519 Data datas in there in the basic, in the silos, and in the 168 00:12:43.600 --> 00:12:46.559 data centers. And to your point, it's a mess that we haven't solved 169 00:12:46.600 --> 00:12:50.919 yet. We've actually made things more complex over the last several years, adding 170 00:12:50.919 --> 00:12:56.360 additional data and additional databases and purpose built databases and object based databases and cloud 171 00:12:56.399 --> 00:12:58.360 based databases, things like that. And now we have this GENAI thing, 172 00:12:58.399 --> 00:13:01.720 and this thing eats data for breakfast, and we have to get relevant and 173 00:13:01.759 --> 00:13:05.320 correct data into these monsters in order to build the lms are going to be 174 00:13:05.320 --> 00:13:09.200 of use to us. And so suddenly everybody's scurrying around saying, we have 175 00:13:09.279 --> 00:13:13.240 no idea how we're going to find the data that we need to train these 176 00:13:13.279 --> 00:13:16.039 systems, how it's going to be cataloged, how it's going to be managed, 177 00:13:16.039 --> 00:13:18.080 how it's going to be secured, governed, and how we're going to 178 00:13:18.120 --> 00:13:22.000 deal with compliance, and so there's kind of a double priority out there right 179 00:13:22.000 --> 00:13:24.240 now. Number one, moving to generative AI. Everybody wants to do that, 180 00:13:24.679 --> 00:13:28.679 but understanding that generative AI is not going to be effective without data to 181 00:13:30.360 --> 00:13:33.720 data to support it, and they really have no way of dealing with their 182 00:13:33.759 --> 00:13:37.200 very complex and poorly deployed and poorly documented data systems that are in their environments. 183 00:13:37.840 --> 00:13:41.039 Right. Yeah, And I want to dive into the GENAI stuff, 184 00:13:41.240 --> 00:13:46.159 probably later in the show, but let's because it's just huge and I have 185 00:13:46.200 --> 00:13:48.679 some theories about it, and I think it's going to be a very interesting 186 00:13:48.799 --> 00:13:52.039 ride, but a very good ride quite frankly. But as I think about 187 00:13:52.039 --> 00:13:56.840 the cloud and for any listeners out there who maybe run a data center or 188 00:13:56.919 --> 00:14:01.120 are responsible for data and applications and functionality, when I look at what is 189 00:14:01.159 --> 00:14:05.679 happening in the cloud, by and large, there's a lot of net new 190 00:14:05.759 --> 00:14:09.399 stuff being developed, so net new workflows, cloud to cloud, kind of 191 00:14:09.399 --> 00:14:13.080 integrations, service providers B to B two C B two C, all that 192 00:14:13.159 --> 00:14:16.080 kind of stuff connectors, right, and it's getting so much better. I 193 00:14:16.080 --> 00:14:20.759 mean, just today I set up Stripe to work with Zoom and it took 194 00:14:20.799 --> 00:14:24.440 me like a second to enable the app. I'm like, wow, that's 195 00:14:24.440 --> 00:14:28.600 pretty cool. Like my friend Eve Molcher's was joking, Oh yeah, Like 196 00:14:28.720 --> 00:14:31.159 twenty years ago, I remember trying to connect two things in the banking system 197 00:14:31.159 --> 00:14:35.120 and it took me days days to figure that out. So things have changed 198 00:14:35.159 --> 00:14:39.480 a lot. But when I think about going up into the cloud with existing 199 00:14:39.639 --> 00:14:45.440 on prem applications, that's some pretty challenging stuff. And if you don't go 200 00:14:45.679 --> 00:14:48.159 all in when you do that, you're making matters worse for yourself because now 201 00:14:48.200 --> 00:14:52.039 you've got a whole another layer of complexity. I was talking to Mark Smith 202 00:14:52.080 --> 00:14:56.559 years ago who was talking about work day and how a bunch of companies looked 203 00:14:56.559 --> 00:14:58.960 to go into work day but they didn't get everything in there, so they 204 00:14:58.960 --> 00:15:01.440 had a fair amount of stuff PRAM with a whole bunch of stuff in work 205 00:15:01.480 --> 00:15:03.080 day and then you know, two years later, guess what, you have 206 00:15:03.120 --> 00:15:07.840 two different environments with tons of data. That's very hard to reconcile and that's 207 00:15:07.879 --> 00:15:11.559 just a nightmare. So what's your advice for companies looking to go into the 208 00:15:11.559 --> 00:15:18.799 cloud but want to do so responsibly and efficiently. Yeah, it's called planning, 209 00:15:18.720 --> 00:15:22.000 and we used to be pretty good at it. Back in the day, 210 00:15:22.039 --> 00:15:24.320 and I think everybody has a tendency to kind of move in random ways 211 00:15:24.399 --> 00:15:28.200 right now. One of the things I saw during the pandemic was a complete 212 00:15:28.200 --> 00:15:31.279 mad dash to cloud. So even though we were doing lift and shift and 213 00:15:31.440 --> 00:15:37.159 there was some refactoring going on and building that new applications using native technology which 214 00:15:37.200 --> 00:15:41.080 were fairly efficient in the cloud, suddenly we picked up a bunch of applications 215 00:15:41.080 --> 00:15:43.360 in data and we pushed it onto a public cloud provider. It compiled, 216 00:15:43.399 --> 00:15:46.240 the compile was clean, and we went ahead and ran it, and suddenly 217 00:15:46.279 --> 00:15:50.480 we figured out in twenty twenty two, and this is when a number of 218 00:15:50.519 --> 00:15:52.799 studies came out they were paying way more than we thought that we would be 219 00:15:52.840 --> 00:15:58.799 paying for the cloud. And that's because these unmodified, very inefficient applications that 220 00:15:58.879 --> 00:16:02.000 were running in the data center, we put them on cloud, and suddenly 221 00:16:02.000 --> 00:16:03.879 they were inefficient in the cloud as well. But only in the cloud. 222 00:16:03.919 --> 00:16:07.360 You have to pay for the resources that you're leveraging. Heavy use of memory, 223 00:16:07.360 --> 00:16:10.879 every use of IO, heavy use of the network, all those sorts 224 00:16:10.919 --> 00:16:14.720 of things you're going to get a bill for. So suddenly everybody realized that 225 00:16:14.720 --> 00:16:17.799 we made movements into the cloud we have half the stuff that runs in the 226 00:16:17.840 --> 00:16:19.080 data center, half the stuff that runs in clouds, some of the edge 227 00:16:19.080 --> 00:16:23.200 computing stuff, mobile computing platforms started to emerge as well. And now they're 228 00:16:23.200 --> 00:16:29.000 normalizing the systems and really kind of doing the things they needed to do after 229 00:16:29.039 --> 00:16:33.120 the fact. And so what's happening now is people are reactively planning and so 230 00:16:33.200 --> 00:16:37.000 that in other ways, they realized that we're paying about two point five times 231 00:16:37.039 --> 00:16:37.519 what we thought we were going to pay, and I wrote that. I 232 00:16:37.639 --> 00:16:41.679 wrote about that in my book and the Cloud. They can't afford it. 233 00:16:41.360 --> 00:16:45.679 They're looking to optimize the budgets, their ability to bring the most value back 234 00:16:45.679 --> 00:16:49.480 to the business. They have this GENAI mandate that's following them as well, 235 00:16:49.639 --> 00:16:55.080 and so they're running around quickly trying to normalize and pushing the systems onto the 236 00:16:55.200 --> 00:16:57.759 platforms they're going to be the most cost optimized for them, and in many 237 00:16:57.759 --> 00:17:00.559 instances that's going to be back on premise. So and since they're heading the 238 00:17:00.559 --> 00:17:04.119 reset button, I can't imagine having those conversations with my boss. And remember 239 00:17:04.160 --> 00:17:07.759 I removed that a app and that data sets to cloud and US is ten 240 00:17:07.799 --> 00:17:11.000 million dollars to make it happen. Well, oopsie, Daisy, we're going 241 00:17:11.079 --> 00:17:15.039 to have to put it back because it was way too expensive because we're unwilling 242 00:17:15.119 --> 00:17:18.119 to invest in the money to optimize it on the cloud platform. So there's 243 00:17:18.160 --> 00:17:22.039 no free lunch here. I think that's what it comes down to. And 244 00:17:22.079 --> 00:17:26.400 so we can certainly try to delude ourselves and the fact that moving to a 245 00:17:26.440 --> 00:17:29.880 new technology is going to solve all our problems. It's just going to create 246 00:17:29.920 --> 00:17:33.119 new problems. It is going to have opportunities, but we have to put 247 00:17:33.160 --> 00:17:37.839 the thinking ahead of making these opportunities viable for us. Yeah. I mean, 248 00:17:37.880 --> 00:17:40.440 if you're cloud first, if you're a new company, you can go 249 00:17:40.519 --> 00:17:44.279 cloud first, that's great news, right, But if you're an existing company 250 00:17:44.279 --> 00:17:47.200 with data centers all over the place, that's where you have to do that. 251 00:17:47.400 --> 00:17:49.440 I like the way you answer the question. It's called planning. If 252 00:17:49.440 --> 00:17:52.240 you guys heard of it, where you'd like sit down and map stuff out 253 00:17:52.759 --> 00:17:56.039 and you know, I wonder. I mean, attention spans are short of 254 00:17:56.079 --> 00:18:00.200 these days with TikTok. You now I hear my child on TikTok. It's 255 00:18:00.279 --> 00:18:06.519 affecting our attention span, our ability to focus on things. Boards are nervous 256 00:18:06.559 --> 00:18:08.759 about stuff. And now that we see the economy, even though it's not 257 00:18:08.799 --> 00:18:12.279 a recession, there's pressure everywhere. I mean, there's been a blood path 258 00:18:12.359 --> 00:18:17.119 in the tech space, and anytime that happens, you know that someone has 259 00:18:17.160 --> 00:18:18.359 to sit down and figure out, Okay, what were these people doing, 260 00:18:18.400 --> 00:18:22.000 what are you doing? Who's going to do this stuff now? And when 261 00:18:22.000 --> 00:18:25.839 you got this completely scattered world where twenty percent is in the cloud, eighty 262 00:18:25.839 --> 00:18:30.319 percent is still on prem that's I mean for an IT architect that it's going 263 00:18:30.359 --> 00:18:33.559 to leave you to pull your hair out, right. It is it is, 264 00:18:33.599 --> 00:18:34.880 and that's why we have to get a little smarter in how we're going 265 00:18:34.920 --> 00:18:41.119 to leverage technology layers, you know, abstraction, automation, the ability to 266 00:18:41.160 --> 00:18:44.519 do things smarter rather than harder. And I think that the complexity right now 267 00:18:44.559 --> 00:18:48.160 is killing us. We just have too many services that we're managing, too 268 00:18:48.240 --> 00:18:52.680 much heterogeneity. Certainly, the additional cloud is compounding that, as well as 269 00:18:53.039 --> 00:18:56.839 multi cloud environments and moving to edge computing and mobile computing things like that. 270 00:18:56.880 --> 00:19:02.799 There's reasons why we're moving in those directions and they do provide innovative differentiators for 271 00:19:02.920 --> 00:19:06.480 companies to do so and I think that's awesome. You want to leverage technology 272 00:19:06.839 --> 00:19:10.119 to build IP that's really going to create the value within your system, but 273 00:19:10.200 --> 00:19:12.000 you have to do so in a way that's going to be scalable and it's 274 00:19:12.000 --> 00:19:15.000 going to be optimized to bring the most value back to the business. And 275 00:19:15.079 --> 00:19:18.279 that seems to be a bummer, does you know? I always call myself 276 00:19:18.279 --> 00:19:22.319 the designated buzzkill in some of these meetings. But we're going to have to 277 00:19:22.319 --> 00:19:26.000 go through this at some point in time to make sure we can justify the 278 00:19:26.079 --> 00:19:30.240 utilization of the technology, cloud and everything else. And so it becomes an 279 00:19:30.319 --> 00:19:34.000 orchestration of many different platforms that we have to leverage that are going to get 280 00:19:34.079 --> 00:19:38.039 us to the end state that we're looking for, and that requires a tremendous 281 00:19:38.119 --> 00:19:42.559 amount of pre thinking, pre planning, proactive and proactive looking at data. 282 00:19:42.599 --> 00:19:45.519 You just mentioned the thing earlier, data normalization. The ability to get that 283 00:19:45.640 --> 00:19:49.599 under control huge issue, and we've got to start picking away at this now 284 00:19:49.680 --> 00:19:52.799 because it's not going to get any better. We're just making things more complex 285 00:19:52.839 --> 00:19:56.240 and hoping some technology will come along to fix it, and that's never going 286 00:19:56.279 --> 00:20:00.599 to happen. You know. I think somebody self that there are some cool 287 00:20:00.680 --> 00:20:04.160 technologies I've come across over the years, and I wonder if you've seen anything 288 00:20:04.599 --> 00:20:07.000 that is good. I mean, in the development world, use all kind 289 00:20:07.039 --> 00:20:11.640 of interesting things tracers to figure out to do your troubleshooting to understand what the 290 00:20:11.680 --> 00:20:15.359 heck's going on out there. So there are technologies that's a company Extra Hop 291 00:20:15.519 --> 00:20:19.079 I ran across gosh about ten years ago or so, that have a very 292 00:20:19.079 --> 00:20:23.759 interesting approach where and they're primarily for security, but there are other use cases 293 00:20:23.759 --> 00:20:27.960 as well where what they will do is they will siphon off your web i'm 294 00:20:29.000 --> 00:20:33.799 sorry, your network traffic and use it to create a digital twin of your 295 00:20:33.839 --> 00:20:37.960 existing environment so you can see all the databases where the applications are. You 296 00:20:37.960 --> 00:20:41.319 can kind of see data as it's flowing between them. That's an interesting one. 297 00:20:41.359 --> 00:20:45.079 But where I'm going with this question is is there any set of technologies 298 00:20:45.079 --> 00:20:53.119 that can really help understand map out and then render some cost efficiency models around 299 00:20:53.319 --> 00:20:59.680 what it really takes to move something from on prem to the cloud. How 300 00:20:59.799 --> 00:21:02.680 much money can we realistically expect to save. I mean, how do you 301 00:21:02.880 --> 00:21:06.880 get there? Is it just such a manual effort that you have to kind 302 00:21:06.880 --> 00:21:10.359 of build out spreadsheets to do it or how does that actually happen? Yeah, 303 00:21:10.359 --> 00:21:12.440 that's not going to work very well. We're doing Excel spreadsheets for everything. 304 00:21:14.160 --> 00:21:17.000 Some of the Finnops technology that's underway, and a lot of it's going 305 00:21:17.039 --> 00:21:19.799 to be driven by AI into itself, is promising because we're able to assess 306 00:21:19.920 --> 00:21:23.880 not only in efficiencies we have in our current configurations in the cloud, but 307 00:21:23.920 --> 00:21:29.279 also on the on premise systems as well and using the same technologies for BO. 308 00:21:29.480 --> 00:21:33.720 So anything that operates cross platform is going to be a huge help because 309 00:21:33.720 --> 00:21:37.920 we're not building additional silos on the particular platforms to solve a particular problem. 310 00:21:37.960 --> 00:21:41.920 Instance, We're solving a holistic problem that's going to go completely across the enterprise. 311 00:21:41.960 --> 00:21:45.960 And some of the phinnops tools and I'm seeing developed out there are starting 312 00:21:45.039 --> 00:21:48.440 to move in that direction, and that's going to be hugely beneficial because we're 313 00:21:48.440 --> 00:21:52.279 able to see usage patterns, we're able to do accountability, we're able to 314 00:21:52.279 --> 00:21:56.359 deal with security, and also we're able to understand what legacy and technical debt 315 00:21:56.400 --> 00:22:02.559 exists that we need to prioritize to fix, including data normalization. Yeah, 316 00:22:02.599 --> 00:22:07.200 I'm actually giving a talk at the Data Universe conference coming in April to New 317 00:22:07.279 --> 00:22:11.880 York City. A panel discussion that the word technical is in parentheses and the 318 00:22:11.920 --> 00:22:15.400 title is forever in your technical debt, right, because it's just everywhere. 319 00:22:15.440 --> 00:22:19.200 And I joked I heard a great definition of technical debt one day when one 320 00:22:19.240 --> 00:22:26.440 guy said the definition of a legacy system is any system in production, right, 321 00:22:26.680 --> 00:22:30.839 Yes, which I thought was pretty funny. But there are some more 322 00:22:30.039 --> 00:22:33.400 nuanced definitions that say, okay, after a certain number of years, or 323 00:22:33.400 --> 00:22:37.039 it's not well supported, there's not good documentation, you know. But to 324 00:22:37.079 --> 00:22:41.119 a certain extent, these lllms can help with a lot of that stuff. 325 00:22:41.160 --> 00:22:45.240 I mean, you look at the whole copilot concept and the ability now in 326 00:22:45.279 --> 00:22:48.200 some cases at least, to be able to feed code into an LM and 327 00:22:48.200 --> 00:22:52.400 say what does this do? Right? I mean, that's pretty powerful to 328 00:22:52.519 --> 00:22:56.319 help deconstruct and understand what's out there. But I mean, you know, 329 00:22:56.400 --> 00:22:59.960 the code base of some companies is like millions of lines, so you can't 330 00:23:00.039 --> 00:23:02.680 pump that into chat, GPT, at least not yet, right. But 331 00:23:02.799 --> 00:23:06.000 some of these tools I think are going to help us hack away and get 332 00:23:06.039 --> 00:23:08.799 closer to the goal that we're looking for. What do you think it's got 333 00:23:08.839 --> 00:23:12.480 to because we can't do this manually. So if we're going to have these 334 00:23:14.200 --> 00:23:18.400 this complete complex environment excuse me, yeah, holda go ahead. We're going 335 00:23:18.440 --> 00:23:22.680 to have this complete complex environment, we're going to have to understand how to 336 00:23:22.720 --> 00:23:26.480 normalize it, and we're going to need tools and talent to help us. 337 00:23:26.519 --> 00:23:30.039 And I think that's going to come from the AI stuff because it can take 338 00:23:30.240 --> 00:23:34.640 and make sense of a multitude of patterns in data and applications and API usages 339 00:23:34.680 --> 00:23:38.920 and different architectures and able to make sense of this stuff. And also the 340 00:23:40.000 --> 00:23:42.240 thing it's able to do is build a knowledge of these systems, what to 341 00:23:42.279 --> 00:23:47.119 do right and what not to do, to fix these issues and guide you 342 00:23:47.559 --> 00:23:49.519 in a way to get better, incrementally better over time. Get your data 343 00:23:49.559 --> 00:23:53.440 normalized, get your platforms normalized, get your APIs normalized, get your code 344 00:23:53.440 --> 00:23:59.200 normalized. It's going to allow us to be better people by leveraging this technology. 345 00:23:59.240 --> 00:24:00.599 I don't think we're there yet. I think people are putting too much 346 00:24:00.599 --> 00:24:03.960 emphasis on it, but we will be soon. Yeah, that's interesting stuff. 347 00:24:04.319 --> 00:24:07.480 I think that it is going to help hack away. But it's almost 348 00:24:07.519 --> 00:24:10.759 like you have to stop the world and get off for a minute to be 349 00:24:10.799 --> 00:24:14.319 able to rationalize all that stuff and reconcile it and understand where you're even going. 350 00:24:14.519 --> 00:24:17.119 But folks, don't touch that. Delb right back. You are listening 351 00:24:17.119 --> 00:24:27.839 to Inside Analysis. Welcome back to Inside Analysis. Here's your host, Eric 352 00:24:29.039 --> 00:24:34.920 Tabanaugh. All right, folks back here on Inside Analysis talking to the cloud 353 00:24:36.000 --> 00:24:40.279 duru himself, David Lintigham. He's got a new book out and Insider's Guide 354 00:24:40.359 --> 00:24:44.119 to Cloud Computing. We're talking about why go to the cloud? Why leave 355 00:24:44.200 --> 00:24:47.799 the cloud? That's kind of a fun conversation. I think that, you 356 00:24:47.839 --> 00:24:49.200 know, one of the funnier lines I've heard over the years was from someone 357 00:24:49.240 --> 00:24:55.319 who said that the most unpredictable line out of on your budget is the AWS 358 00:24:55.400 --> 00:24:59.079 bill because you don't know where it's going to be. Now you mentioned finnops 359 00:24:59.240 --> 00:25:03.599 and financial operations data. Basically that is really taking off, and I think 360 00:25:03.640 --> 00:25:07.920 for all sorts of great reasons, because it can kind of track and Observeability 361 00:25:07.039 --> 00:25:11.359 is a related technology and a sort of overlaying technology, if you will, 362 00:25:11.720 --> 00:25:15.720 being able to watch what comes in and let's face it, machine learning is 363 00:25:15.920 --> 00:25:21.720 very good at tackling vast amounts of data of otherwise really boring data that human 364 00:25:21.720 --> 00:25:26.000 beings don't want to look at, but noticing changes in patterns, noticing patterns 365 00:25:26.039 --> 00:25:30.599 themselves, noticing ups downs, something is different. Maybe take a look at 366 00:25:30.599 --> 00:25:34.680 this now. So it's the confluence of all those things that's creating this finops 367 00:25:34.759 --> 00:25:37.880 space, which I think is going to help us get a much better handle 368 00:25:37.960 --> 00:25:41.920 for how much cloud costs, what value are beginning from all that stuff. 369 00:25:41.960 --> 00:25:47.960 And this is what CTOs and CIOs need right in CFOs, they need some 370 00:25:48.319 --> 00:25:51.960 understanding of what it's really costing and then what it's doing for the business, 371 00:25:52.039 --> 00:25:59.000 right Yeah, And I think sometimes it's the finops system is going to tell 372 00:25:59.039 --> 00:26:03.559 you about all the inefficient is that that particular CIO or CTO built over the 373 00:26:03.640 --> 00:26:06.720 years, and so it's going to provide bad report cards, and I think 374 00:26:06.759 --> 00:26:08.680 that's going to come out in many in many instances. In other words, 375 00:26:08.680 --> 00:26:12.480 if I do take a finnop system and it's going to be trained with best 376 00:26:12.519 --> 00:26:18.519 practices from ten thousand experts and massive amounts of data, and it's able to 377 00:26:18.519 --> 00:26:21.960 look at my particular systems and look at the configuration of the systems, look 378 00:26:21.960 --> 00:26:23.839 at the optimization, look at the ability to solve the business problems, all 379 00:26:23.880 --> 00:26:27.079 those sorts of things. I suspect that a lot of them will provide them 380 00:26:27.079 --> 00:26:32.119 with the DNUS in terms of what was built and the technical debt that was 381 00:26:32.160 --> 00:26:36.480 built, and really lots of mistakes that have to be corrected. But I 382 00:26:36.519 --> 00:26:38.680 think it's okay to get a good, honest assessment as to where we are 383 00:26:38.720 --> 00:26:41.720 now in terms of our as a state, no matter how bad. Many 384 00:26:41.759 --> 00:26:48.279 of those instances are bad mistakes that are made and start progressing to more optimized 385 00:26:48.839 --> 00:26:52.599 it. You know, leveraging AI is the ability to direct it and it's 386 00:26:52.680 --> 00:26:55.599 kind of funny because it's also the destination of the systems that we're building. 387 00:26:56.720 --> 00:27:00.119 Yeah, this is what does get me very excited is thinking about the protect 388 00:27:00.359 --> 00:27:04.160 you mentioned checking configurations, right, so you can set up these algorithms to 389 00:27:04.160 --> 00:27:07.880 give them access to your environment. They check the data, they can go 390 00:27:07.960 --> 00:27:11.279 through and see what all the settings are, and if you have a baseline 391 00:27:11.640 --> 00:27:15.480 to understand what that means, then you can give really good advice. I 392 00:27:15.480 --> 00:27:18.039 mean Boomy we mentioned them, I think before the call, or maybe at 393 00:27:18.039 --> 00:27:22.319 the beginning. Boomy has a data lake of like two hundred million integration patterns 394 00:27:22.640 --> 00:27:29.319 that they've trained a large language large language model on That gets pretty interesting because 395 00:27:29.359 --> 00:27:32.599 you can see, Okay, I'm connected to my on premise, connected to 396 00:27:32.640 --> 00:27:36.480 this system and that system, this system over here, am I doing it 397 00:27:36.559 --> 00:27:38.720 correctly? And it can look and see well, actually, if you do 398 00:27:38.799 --> 00:27:42.200 it this way and that way, you can do something better. That's pretty 399 00:27:42.240 --> 00:27:45.759 interesting stuff. And I think that's where a lot of these LL and AI 400 00:27:45.799 --> 00:27:49.359 in general is going to come in very handy, is in making recommendations to 401 00:27:49.440 --> 00:27:55.559 the user based upon its training data and what it's determined so far. Right, 402 00:27:56.119 --> 00:27:59.559 absolutely, and the AIOps has grown up around that, the ability to 403 00:27:59.640 --> 00:28:03.640 leverage in a system to assist you in operating your environment in a much more 404 00:28:03.640 --> 00:28:06.839 effective and efficient way, which is very much like what Boomy's doing, it 405 00:28:06.880 --> 00:28:11.759 sounds like, And so it is going to be a layer of intelligence we're 406 00:28:11.759 --> 00:28:15.039 able to put between us as the human beings that are bad at making decisions 407 00:28:15.039 --> 00:28:18.559 in a real time way, and then having sets of automation that are driven 408 00:28:18.599 --> 00:28:21.519 by AI, they're going to be able to make better decisions. And I 409 00:28:21.559 --> 00:28:25.640 think we're going to have to throw the keys over to those sorts of mechanisms 410 00:28:25.880 --> 00:28:29.039 to allow it to continually improve itself. Can I remember it's not thinking about 411 00:28:29.039 --> 00:28:32.720 office politics, it's not thinking about the budget. It's just thinking about how 412 00:28:32.759 --> 00:28:37.440 to do something better and really kind of using the intelligence of ten thousand experts. 413 00:28:37.680 --> 00:28:41.960 And I think we're ripe and ready for some technology to come along to 414 00:28:41.000 --> 00:28:45.039 really assist us with that, and that seems to be a net positive thing. 415 00:28:45.480 --> 00:28:48.440 Yeah. I think we were talking on the break about the media and 416 00:28:48.480 --> 00:28:52.839 how a lot of media outlets are having real issues now, and I think 417 00:28:52.880 --> 00:28:56.559 that there is those are straws in the wind. And you look at how 418 00:28:56.559 --> 00:28:59.759 cloud computing changed all that, right, because we used to have newspapers that 419 00:28:59.839 --> 00:29:02.440 was tangible. Someone had to print. It costs a lot of money for 420 00:29:02.480 --> 00:29:03.799 the ink in the paper and you got to get it out there. And 421 00:29:03.839 --> 00:29:08.279 then everyone digital. And I remember it was like in the late nineties that 422 00:29:08.599 --> 00:29:11.359 I would read a story in the paper and be like, wasn't that like 423 00:29:11.440 --> 00:29:15.079 last week? And I realized, no, it was last night. I 424 00:29:15.119 --> 00:29:18.119 read it online. That's why it seemed old to me, because it's in 425 00:29:18.200 --> 00:29:23.119 the paper. And that sort of long tail is falling off pretty healthily now 426 00:29:23.160 --> 00:29:27.039 if you will, of print publications, like you don't see too many magazines 427 00:29:27.079 --> 00:29:30.960 anymore. You don't see too many printed publications, newspapers, et cetera. 428 00:29:32.279 --> 00:29:34.680 So they're all getting it from the web. But then there are downsides too 429 00:29:34.759 --> 00:29:38.480 because everything moves so fast and you don't really check things, and they're ever 430 00:29:38.519 --> 00:29:42.440 wants to get out there. And it gets back to planning and responsible behavior. 431 00:29:44.079 --> 00:29:45.759 And I guess that all maps to the cloud too. Right, You 432 00:29:45.839 --> 00:29:49.920 have to think through this stuff and don't just jump right in, but watch 433 00:29:51.000 --> 00:29:53.079 and see where it's going. But just to finish my point on the media 434 00:29:53.200 --> 00:30:00.720 and how the cloud is changing their world, it's huge, I mean information 435 00:30:00.799 --> 00:30:07.519 consumption. In my opinion is that no media organizational structure can live the old 436 00:30:07.599 --> 00:30:11.720 fashioned way in this new world because these large language models, and I think 437 00:30:11.759 --> 00:30:14.799 what's going to happen here it's going to be very interesting, is that up 438 00:30:14.799 --> 00:30:21.599 in the cloud you're going to have the ability to navigate through systems of record. 439 00:30:21.680 --> 00:30:23.720 Think like for the federal government, the Federal Register. You connect an 440 00:30:23.799 --> 00:30:27.000 MLLM to the Federal Register, and all of a sudden you can have very 441 00:30:27.039 --> 00:30:33.480 interesting conversations about what is actually happening in your government in layman's terms, instead 442 00:30:33.519 --> 00:30:37.440 of trying to read legal lease or contracts or even think about the laws that 443 00:30:37.440 --> 00:30:41.279 we passed, fourteen hundred page laws just feeding into an LM and started asking 444 00:30:41.279 --> 00:30:45.519 you questions about what this stuff is that's going to I mean, that is 445 00:30:45.559 --> 00:30:49.319 a hugely game changing dynamic. Where I was talking about this a couple of 446 00:30:49.319 --> 00:30:56.279 weeks ago on the show. Even like in processes for lawyers, there's a 447 00:30:56.359 --> 00:31:02.079 law firm Morrison Forster that's eighteen hundred Pensylvania Avenue charge very large amounts of money 448 00:31:02.359 --> 00:31:04.079 for their services because they know a lot of stuff. They're very smart. 449 00:31:04.160 --> 00:31:10.920 But now these large language models trained on a corpus of legal documentation and legislation, 450 00:31:10.960 --> 00:31:14.480 et cetera, can answer all those questions for you, even simple process 451 00:31:14.599 --> 00:31:18.680 questions. So you know a lot of these AI white collar situations are going 452 00:31:18.720 --> 00:31:22.759 to be impactful for people going to take away jobs or ultamately change jobs. 453 00:31:23.160 --> 00:31:26.880 I mean, this is an incredibly disruptive time, right it is, And 454 00:31:26.960 --> 00:31:30.799 I think it's okay to start thinking about, you know, how to leverage 455 00:31:30.839 --> 00:31:33.920 this technology effectively. We also have to look at the ethics of it. 456 00:31:33.880 --> 00:31:38.759 But I probably would trust an AI lawyer than a single lawyer because they're going 457 00:31:38.839 --> 00:31:45.000 to have the knowledge of every case, every case law where a person can't 458 00:31:45.000 --> 00:31:48.680 think about everything. And so if I'm just researching something and getting advice, 459 00:31:48.240 --> 00:31:52.640 I'm going to get it directly from directly from the AI engine. And I 460 00:31:52.680 --> 00:31:56.319 think that's that's where things are going. So a lot of these information oriented 461 00:31:56.400 --> 00:32:00.079 jobs where you're just providing advice and recommendations, you're going to find that the 462 00:32:00.119 --> 00:32:04.359 aipath is going to be a much more fruitful way to do those things. 463 00:32:05.640 --> 00:32:08.960 I mean, that is such a mammoth transformation. It really, it's it's 464 00:32:09.119 --> 00:32:13.799 gobsmacking to think about it. Like terms of service. So We've got a 465 00:32:13.799 --> 00:32:16.480 little side project we're working on and I was talking to one of my partners 466 00:32:17.319 --> 00:32:22.519 and we were talking about well, like legal documentation like disclaimers and things of 467 00:32:22.519 --> 00:32:27.119 that nature for software applications, et cetera. I said, just go to 468 00:32:27.200 --> 00:32:30.559 chat GPT and tell it to write up a generic one. Boom, You're 469 00:32:30.559 --> 00:32:31.799 going to get it because it looks just like all the others. I mean, 470 00:32:31.920 --> 00:32:36.160 who actually reads these things anyway, right? I mean how many One 471 00:32:36.200 --> 00:32:37.960 thing that does annoy me is with software as a service, they'll say, 472 00:32:38.000 --> 00:32:43.119 okay, click here to say that you have read and understand the terms of 473 00:32:43.160 --> 00:32:46.240 service. I'm like, don't make me a liar like click here to get 474 00:32:46.279 --> 00:32:50.119 passes. I'll agree to it, but don't make me say I've read an 475 00:32:50.200 --> 00:32:55.079 understandable read it maybe a liar. That's when they do that. Yeah, 476 00:32:55.240 --> 00:32:59.759 it's it's going to change some of that. So in terms of service, 477 00:33:00.160 --> 00:33:02.079 we can tell the engine to read it for us and tell us what the 478 00:33:02.119 --> 00:33:07.240 exposures are, what it actually means. The ability to take legal documents. 479 00:33:07.279 --> 00:33:09.680 I sign them all the time. I'm not a lawyer. Some stuff to 480 00:33:09.720 --> 00:33:13.480 have them reviewed by a lawyer, but it would be so nice if I 481 00:33:13.559 --> 00:33:17.680 had some sort of a higher intelligence it's able to consume that and spit out 482 00:33:17.759 --> 00:33:21.799 the way I should consider it. And the thing is just kind of bringing 483 00:33:21.799 --> 00:33:24.240 everything back to technology decisions. The same thing with that, you know, 484 00:33:24.279 --> 00:33:28.920 the architectural decisions, the ability to look at the configuration of technology in some 485 00:33:28.960 --> 00:33:31.440 sort of an optimized way. Right now, we have so many biases and 486 00:33:31.480 --> 00:33:36.240 so many political decisions that are made that come into how people pick technology. 487 00:33:36.279 --> 00:33:38.640 That's how we're making the mistakes and building up the technical debt. So the 488 00:33:38.720 --> 00:33:44.000 assist us was that as well, and I think it's completely acceptable for people 489 00:33:44.079 --> 00:33:47.119 to leverage that technology to do things that we just don't have time to research. 490 00:33:49.319 --> 00:33:51.759 Yeah, and I think that's going to be a big new way of 491 00:33:51.839 --> 00:33:55.640 doing business, is to leverage these llms all day long, ask it stuff. 492 00:33:57.039 --> 00:34:00.880 I mean, what I've learned is that it's very good at describing basic 493 00:34:01.039 --> 00:34:07.239 technology patterns and usages, like understanding how do routers work? Or understanding how 494 00:34:07.239 --> 00:34:13.199 does Internet protocol work? What is HTTP all about? Things where there's enough 495 00:34:13.639 --> 00:34:17.400 published information that there are enough vectors that are similar enough that it can go 496 00:34:17.440 --> 00:34:21.679 out and find all that stuff, right, Because basically what they've done is 497 00:34:22.119 --> 00:34:25.320 they've vectorized text. And a vector, of course, is just it's a 498 00:34:25.360 --> 00:34:30.000 point and then a direction right, and then you It has lots and lots 499 00:34:30.000 --> 00:34:34.000 and lots of those like gajillions to use one of my mother's favorite words, 500 00:34:34.400 --> 00:34:37.599 and it can do very good pattern matching across those environments. And that's all 501 00:34:37.599 --> 00:34:40.599 it's really doing, right, It's just pattern matching based upon your prompt to 502 00:34:40.639 --> 00:34:45.239 give you something that it thinks you want, right, That's all it does. 503 00:34:45.440 --> 00:34:50.360 And so the ability to have an amalgamation of information that saves me from 504 00:34:50.400 --> 00:34:53.000 having to go collect it and find it and come up with my own opinions 505 00:34:53.000 --> 00:34:58.360 on it are come up my own disseminations of the information. So I'm going 506 00:34:58.400 --> 00:35:01.760 to be I'm going to be a bias by the information that I'm able to 507 00:35:01.800 --> 00:35:07.559 find. And so this puts a layer between all the information out there and 508 00:35:07.559 --> 00:35:10.280 the ability to aggregate it into some sort of a form where it's easier consumed 509 00:35:10.280 --> 00:35:14.239 by me, and I'm going to have less biases. I'm able to get 510 00:35:14.239 --> 00:35:16.880 to the essence of what the information means. And you know, I use 511 00:35:16.920 --> 00:35:21.119 AI for my research all the time and do that for just that purpose. 512 00:35:21.119 --> 00:35:23.079 In other words, I can certainly google something and go through all the documents 513 00:35:23.079 --> 00:35:27.440 out there and come up with a you know, basic understanding of what something 514 00:35:27.480 --> 00:35:30.519 means. Or I can you know, go to an AI search engine, 515 00:35:30.639 --> 00:35:34.679 well whatever, chat to EP versions that I'm using or barred and pull up 516 00:35:34.719 --> 00:35:37.920 and have it disseminate what all that information means, and not have it make 517 00:35:37.920 --> 00:35:42.760 a decision for me, but instruct me as to what's important, what are 518 00:35:42.760 --> 00:35:45.719 the attributes, what are the different patterns out there and the common patterns it's 519 00:35:45.760 --> 00:35:50.280 able to find. And as a researcher, that's absolutely an imperative to me. 520 00:35:50.960 --> 00:35:52.719 Yeah, and you know, to bring this back to a real focus 521 00:35:52.760 --> 00:35:57.239 on cloud. Let's think about Google. Like you said, I could google 522 00:35:57.320 --> 00:36:00.840 something. I Google is in the crosshairs of AI engines now, granted Gemini, 523 00:36:00.960 --> 00:36:04.599 that's Google's version, and that is the one I prefer. I use 524 00:36:04.960 --> 00:36:08.760 Bard all the time every day. And to your point to think about how 525 00:36:09.519 --> 00:36:15.320 Google's business model on search terms has been just so powerful, but is now 526 00:36:15.360 --> 00:36:17.719 holding it back in a lot of ways. Right, you go and Google 527 00:36:17.760 --> 00:36:21.880 something, and you've got to scroll down through all the sponsored links before you 528 00:36:21.920 --> 00:36:24.360 get to any real content. And someone actually told me, who's pretty well 529 00:36:24.400 --> 00:36:29.960 informed, that even the organic search results you're get in Google aren't entirely organic 530 00:36:29.960 --> 00:36:31.519 anymore. I thought that was kind of an interesting thought that he just threw 531 00:36:31.559 --> 00:36:35.039 out. There is a very very smart, very well connected guy, so 532 00:36:35.039 --> 00:36:38.920 I don't think he made that up. But now that whole model is byzantine 533 00:36:38.960 --> 00:36:43.239 compared to what these AI engines do, because to your point, you can 534 00:36:43.280 --> 00:36:46.199 ask it very specific questions and they'll give you the synthesis. It won't give 535 00:36:46.239 --> 00:36:49.599 you a bunch of links where you have to do the homework. Again. 536 00:36:49.960 --> 00:36:52.679 I mean, Google is now of course giving you short definitions of things and 537 00:36:52.719 --> 00:36:55.719 then pointing you to where you can find the rest, but that's not as 538 00:36:55.719 --> 00:36:59.679 good as what you get from BARD or chat GPT when you ask it these 539 00:36:59.760 --> 00:37:05.159 questions. So I think this is that is a huge transformation for how we're 540 00:37:05.159 --> 00:37:08.559 interacting with the web of information. And yes, hallucinations are a problem. 541 00:37:08.960 --> 00:37:15.199 Everyone's working on that with these RAG models, retrieval augmented generation. I think 542 00:37:15.239 --> 00:37:16.679 that's where all the action is going to be in the future, and I 543 00:37:16.719 --> 00:37:22.079 think that's going to be the future interface for senior executives working with their enterprise 544 00:37:22.159 --> 00:37:27.079 data. It's going to be some AI, large language model that has access 545 00:37:27.159 --> 00:37:30.519 to all these different information systems and can help you figure out what's happening in 546 00:37:30.559 --> 00:37:34.679 your business right now and what you can do about it right You're right. 547 00:37:34.760 --> 00:37:37.880 It will be personalized how they want to consume information. You know. It'll 548 00:37:37.920 --> 00:37:42.360 even sing them a song about sales results, you know, And I think 549 00:37:42.360 --> 00:37:46.079 that's perfectly fine. I think the ability of personalization and the ability to find 550 00:37:46.079 --> 00:37:50.480 information in much more effective ways, and the ability to get to the essence 551 00:37:50.480 --> 00:37:53.320 of what that information means is something that we don't do well today, and 552 00:37:53.519 --> 00:37:59.440 a lot of bad decisions are made based on misinformation coming in from something and 553 00:37:59.599 --> 00:38:04.440 miss understandings and not having all of the information in front of them making technology 554 00:38:04.440 --> 00:38:07.960 decisions for instance. Keep coming back to that, So the ability to have 555 00:38:07.000 --> 00:38:13.119 a personalized view of how we're making decisions and then put it in the context 556 00:38:13.199 --> 00:38:15.519 of how I understand it, and also put it in how I learn in 557 00:38:15.559 --> 00:38:21.559 other words, either a video or audio or text or whatever. It's just 558 00:38:21.599 --> 00:38:22.920 going to be much more effective. People are going to have a much more 559 00:38:22.920 --> 00:38:28.039 effective day. Maybe it won't not work as much as we do, and 560 00:38:28.079 --> 00:38:31.639 the ability to get to decisions that are going to be much more balanced and 561 00:38:31.800 --> 00:38:36.239 much more directed at the outcome of the business. Well in the ability to 562 00:38:36.320 --> 00:38:39.079 track things too, and to audit things right. That's the other really cool 563 00:38:39.199 --> 00:38:46.480 side of machine learning in general is that machines don't sleep, machines don't lie. 564 00:38:47.039 --> 00:38:50.719 Machines are working all the time. But if you set it up properly, 565 00:38:51.159 --> 00:38:53.559 you can have an audit trail for who is using the recommendation. So 566 00:38:53.599 --> 00:38:58.840 I mentioned I think most of the benefit that AI will bring will come through 567 00:38:58.880 --> 00:39:02.079 recommendations suggestions that come from the system. This could be in healthcare, it 568 00:39:02.079 --> 00:39:05.440 could be in banking, it could be in retail, it could be anywhere. 569 00:39:05.920 --> 00:39:08.000 But you'll make a kind of like use the analogy the other day of 570 00:39:08.159 --> 00:39:13.400 in baseball, when the pitcher shakes off the catcher, I always go, 571 00:39:13.440 --> 00:39:15.320 oh, no, here we go. We get a comfort ball because listen 572 00:39:15.360 --> 00:39:17.719 to the catcher. The catcher knows man. The catcher is probably the best 573 00:39:17.719 --> 00:39:21.559 person. It's like your mother on the field there to listen to your catcher. 574 00:39:22.119 --> 00:39:25.239 But we'll be able to track how often Bob or Susan or Fred or 575 00:39:25.239 --> 00:39:29.719 whatever went with the recommendation, how often they did not, and if they 576 00:39:29.719 --> 00:39:31.400 do better without going with the recommendation. Okay, well we need to learn 577 00:39:31.400 --> 00:39:36.199 from them. If they don't do very well by not going with the recommendation, 578 00:39:36.280 --> 00:39:37.400 we have a conversation with them. Why are you not going with the 579 00:39:37.400 --> 00:39:42.239 recommendations? Like you're not making sales, you're not listening to the recommendations. 580 00:39:42.320 --> 00:39:45.760 The point is that's another thing you can track. It's another form of instrumentation 581 00:39:45.960 --> 00:39:50.199 in your enterprise and environments. I know the break's coming up quickly here, 582 00:39:50.239 --> 00:39:52.840 so I'll just flesh us out for this one. But that's a very, 583 00:39:52.960 --> 00:39:58.679 very big deal because hitherto you've just kind of relied on people telling you what 584 00:39:58.679 --> 00:40:01.119 they've been doing all day and shaking their word forward and then looking at the 585 00:40:01.159 --> 00:40:05.079 results. But in the future, you're going to have many more metrics to 586 00:40:05.199 --> 00:40:08.599 understand. You know, how much time did they spend working on these projects, 587 00:40:08.679 --> 00:40:12.920 how often did they listen to the recommendations of this engine, how long 588 00:40:13.079 --> 00:40:15.519 did they engage with this engine? All that stuff that can be tracked, 589 00:40:15.559 --> 00:40:17.480 and that's a big deal. But don't touch up to folks, and be 590 00:40:17.559 --> 00:40:28.199 right back. You're listening to Inside Analysis. Expect now welcome back to Inside 591 00:40:28.239 --> 00:40:35.360 Analysis. Here's your host, Eric Tabanac. All right, folks, back 592 00:40:35.360 --> 00:40:39.000 here on Inside Analysis talking about the evolution of cloud computing. And I've got 593 00:40:39.039 --> 00:40:43.400 David Linthikom. He's got a new book out there and Insider's Guide to Cloud 594 00:40:43.760 --> 00:40:47.079 Computing. Let's let's get back to some advice. You've been in this business 595 00:40:47.079 --> 00:40:52.599 for so long, so you've seen and you understand that that AI is very 596 00:40:52.639 --> 00:40:55.800 powerful, and to our point in these conversations we're having here, it doesn't. 597 00:40:55.840 --> 00:40:58.679 I mean, it has a little bit of bias just from what it's 598 00:40:58.719 --> 00:41:01.400 picked up by absorbing all as content, but it doesn't have a whole lot 599 00:41:01.440 --> 00:41:06.360 of bias. And I think that it's going to be really interesting to see 600 00:41:06.719 --> 00:41:09.360 that getting humans out of the loop is a big part of the success story 601 00:41:09.400 --> 00:41:13.800 going forward. You always want humans in the loop, curating these engines, 602 00:41:13.920 --> 00:41:16.400 watching them, monitoring them. You can't just turn it on and walk away. 603 00:41:17.039 --> 00:41:21.519 But I think it's going to be the case that we're going to learn 604 00:41:21.719 --> 00:41:25.440 that the AI make better decisions in a lot of cases about what to do 605 00:41:25.800 --> 00:41:30.840 because it can consider all these factors that are hard for human beings to consider, 606 00:41:30.880 --> 00:41:35.039 and it can absorb so much information and process it so quickly. So 607 00:41:35.159 --> 00:41:37.639 I think we're going to go through a period of time of learning to let 608 00:41:37.760 --> 00:41:42.719 go of control and learning to let these AI things, kind of like we 609 00:41:42.760 --> 00:41:45.840 do when you follow your phone on a map quest through a Google Maps to 610 00:41:45.880 --> 00:41:49.840 take you somewhere right. What do you think? No, absolutely, I 611 00:41:49.880 --> 00:41:53.360 think that the AI is going to take over a lot of the mundane information 612 00:41:53.480 --> 00:41:58.480 oriented tasks that are going to be rising up to more strategic decisions, which 613 00:41:58.519 --> 00:42:01.480 I think is perfectly fine. So we make most of the decisions we make 614 00:42:01.800 --> 00:42:07.159 is based on our own knowledge of information that we and normally it's an impression 615 00:42:07.199 --> 00:42:10.320 that we have. It's not normally accurate because we're human beings. We can't 616 00:42:10.400 --> 00:42:15.639 understand everything to the degree of accuracy, and the ability to turn that over 617 00:42:15.679 --> 00:42:17.559 to an AI engine, I think is going to be a productive is going 618 00:42:17.639 --> 00:42:21.840 to be a productive instate. I certainly don't like making those decisions. I'd 619 00:42:21.920 --> 00:42:24.639 rather have you know, somebody, certainly the mundane stuff. How I feel 620 00:42:24.639 --> 00:42:30.400 at fill out a time card? Are you know, looking at you know, 621 00:42:30.000 --> 00:42:34.119 doing a security audit, which is just a matter of running numbers. 622 00:42:34.239 --> 00:42:37.079 And we have people who do that. And if I can turn it over 623 00:42:37.119 --> 00:42:38.400 to an AI engine and they're going to be able to do that thing is 624 00:42:38.440 --> 00:42:40.760 going to be able to give you much more of an accurate response. And 625 00:42:40.800 --> 00:42:45.440 that's going to be a tool that's going to go to not only my productivity, 626 00:42:45.440 --> 00:42:47.679 but also go to the ability to optimize the value that's coming back to 627 00:42:47.719 --> 00:42:52.960 the business because they're getting the right answers cheaper price. We don't have to 628 00:42:52.039 --> 00:42:55.199 hire and fire people to do that kind of stuff. Then people do what 629 00:42:55.239 --> 00:43:00.320 people do. We're good innovative creatures. We're good at making decisions and looking 630 00:43:00.360 --> 00:43:02.880 at the innovation of the technology and how to use it. And that's the 631 00:43:02.960 --> 00:43:06.119 role we're going to play, which I think is a much better role than 632 00:43:06.159 --> 00:43:09.920 we're playing today having everybody involved with the mundane stuff. So I welcome that 633 00:43:09.960 --> 00:43:14.679 world. I guess I welcome my robot overlords. You know, that's what 634 00:43:14.679 --> 00:43:16.440 some people say, but you know, at the end of the day, 635 00:43:16.480 --> 00:43:20.440 it's going to make us better humans if we use the technology in the right 636 00:43:20.480 --> 00:43:22.599 way. Yeah. I think that's a really good way to put it. 637 00:43:22.960 --> 00:43:27.599 And it's kind of the point I'm trying to make about learning to ride this 638 00:43:27.719 --> 00:43:31.159 wave and to use these tools. And I also think that we'll see, 639 00:43:31.519 --> 00:43:37.119 thanks to the power of AI delivered mostly via the cloud. Quite frankly, 640 00:43:37.599 --> 00:43:42.239 we're going to see more of a flattening again of organizational hierarchies. I think 641 00:43:42.320 --> 00:43:45.000 it's going to become much more collegial, and that's what everybody wants anyway. 642 00:43:45.039 --> 00:43:49.880 I mean, not too many people really enjoy telling other people what to do, 643 00:43:49.960 --> 00:43:52.599 and those people are probably not the people who you'd be telling other people 644 00:43:52.599 --> 00:43:55.079 what to do, because what you want are what do they call it, 645 00:43:55.880 --> 00:43:59.800 servant leaders, right, that's really what you're looking for as someone who will 646 00:43:59.800 --> 00:44:02.440 help help you as a leader, not just telling not to boss you around. 647 00:44:02.480 --> 00:44:06.519 Basically, I think there is going to be more of a flattening like 648 00:44:06.559 --> 00:44:08.639 we saw in the eighties. I remember when a lot of middle management went 649 00:44:08.639 --> 00:44:12.880 away in the nineteen eighties when there was a recession, and we're probably going 650 00:44:12.880 --> 00:44:15.960 to see something like that again, because it's at the coal face, as 651 00:44:15.960 --> 00:44:20.039 they say, where work gets done, and way up high where its strategic 652 00:44:20.039 --> 00:44:23.000 decisions get made. Those are the most important places, and I think in 653 00:44:23.000 --> 00:44:27.480 the middle it's all going to flatten out a little bit, especially because the 654 00:44:27.559 --> 00:44:30.400 nature of what we're doing so much of it is going to change because it's 655 00:44:30.440 --> 00:44:32.199 going to be automated, it's going to be AI fueled, AI driven. 656 00:44:32.599 --> 00:44:37.760 So it's going to be an interesting period of time now as we adapt to 657 00:44:37.239 --> 00:44:42.559 this confluence of technologies coming together. What do you think? No, I 658 00:44:42.559 --> 00:44:45.920 couldn't agree more. I think that it is going to be a revolution. 659 00:44:46.119 --> 00:44:51.079 It's an industrial revolution in essence. It's going to occur in twenty twenty five 660 00:44:51.079 --> 00:44:53.840 to twenty twenty six, and we're going to have to rethink and reevaluate how 661 00:44:53.880 --> 00:44:58.320 we're leveraging this technology and how the human beings need to interact with it, 662 00:44:58.360 --> 00:45:00.400 and where it's going to have value, where it's going to be and I 663 00:45:00.480 --> 00:45:05.639 think organizations are preparing to make those decisions. Now there's whole future work that's 664 00:45:05.679 --> 00:45:07.639 going on, or people are rethinking the role of human beings at work and 665 00:45:07.679 --> 00:45:12.000 the ability to look at we have a declining you know, declining birth rates 666 00:45:12.000 --> 00:45:15.840 in some countries and you have to have people who fill into that. And 667 00:45:15.880 --> 00:45:20.679 so it's a matter about doing things in smarter ways with the technology when we 668 00:45:20.719 --> 00:45:23.440 have an opportunity, since this technology is a huge weapon that's in front of 669 00:45:23.480 --> 00:45:28.679 us now to do a tremendous amount of good. And I think that information 670 00:45:28.880 --> 00:45:31.679 jobs people who you know, do some of the mundane stuff in some of 671 00:45:31.719 --> 00:45:35.519 these organizations, they're going to be displaced, they're going to go away, 672 00:45:35.599 --> 00:45:38.159 but I think they're going to rise up and do things that are more rewarding 673 00:45:38.239 --> 00:45:43.119 and also compensated better. And also the ability to automate the training of them 674 00:45:43.480 --> 00:45:47.199 and the ability to have them learn how to run the prompts is going to 675 00:45:47.199 --> 00:45:50.559 be the next generation of this stuff, and I think people are going to 676 00:45:50.679 --> 00:45:53.280 desire to do that more so than sitting in front of an Excel spreadsheet for 677 00:45:53.280 --> 00:45:57.480 ten hours a day. Right, that's a good point. Let me ask 678 00:45:57.480 --> 00:46:00.519 you one question about and we talked about finops, about cost, and you 679 00:46:00.559 --> 00:46:05.559 think about how much money has already gone into training these models, for example, 680 00:46:05.599 --> 00:46:08.320 the training Chat GPT. I've heard some stories about how many GPUs it 681 00:46:08.400 --> 00:46:12.760 took and how long it took to train that stuff, but then to actually 682 00:46:12.920 --> 00:46:15.679 run them, I mean, right now it's very inexpensive. Is there another 683 00:46:15.679 --> 00:46:19.239 shoot that's going to drop in two, three, four years? Do you 684 00:46:19.239 --> 00:46:23.519 think in terms of cost of these things as companies like Microsoft, like Google 685 00:46:23.960 --> 00:46:27.760 try to pull the string and make more money from that stuff, is that 686 00:46:27.760 --> 00:46:30.000 what's going to happen? What do you think? It's not going to be 687 00:46:30.079 --> 00:46:32.679 cheap And I think whether you run in the cloud or on premise. Also, 688 00:46:32.679 --> 00:46:37.960 the specialized processes you just mentioned in GPUs, and there's processes in development 689 00:46:37.119 --> 00:46:40.440 right now or lower power and are going to be more expensive. So it's 690 00:46:42.159 --> 00:46:45.320 takes a tremendous amount of processing. And so if you're going to process your 691 00:46:45.360 --> 00:46:46.679 own data, you're going to have to store that data someplace. You're going 692 00:46:46.679 --> 00:46:51.079 to have to process that data on a specialized process is typically a GPU. 693 00:46:51.480 --> 00:46:53.079 You're going to have to pay for that infrastructure, and people, I don't 694 00:46:53.079 --> 00:46:57.400 think understand how much that's going to cost. And it's going to be hugely 695 00:46:57.480 --> 00:47:00.159 cost prohibitive in many instances, and so we have to figure out to put 696 00:47:00.159 --> 00:47:05.960 those justifications in now. Yeah, and I guess the Microsofts of the world 697 00:47:06.039 --> 00:47:09.880 are banking on the size of the audience, the size of the customer base, 698 00:47:09.960 --> 00:47:14.480 because what was sucked in to Della talking about we're building things for billions 699 00:47:14.559 --> 00:47:17.039 of people to use. So if you spread that out over billions of people, 700 00:47:17.079 --> 00:47:20.599 yeah, you can make your money back. That's probably why Microsoft is 701 00:47:20.599 --> 00:47:24.119 doing so well right now. I'm just thinking to myself, when is that 702 00:47:24.159 --> 00:47:27.719 shoe going to drop? Is it going to be? Because I mean, 703 00:47:27.719 --> 00:47:30.880 we see this all the time with the freemium model, right. I use 704 00:47:30.920 --> 00:47:34.719 a service called Bitley, which has been very useful for me. In the 705 00:47:34.760 --> 00:47:37.400 early days, you could only buy an enterprise license or the free version, 706 00:47:37.400 --> 00:47:38.920 and I leaned on them have a cheap version, and I said, oh, 707 00:47:38.960 --> 00:47:42.119 we just can't do it right now, and now they do. Now 708 00:47:42.119 --> 00:47:45.039 you can do eight bucks a month or twenty eight bucks a month or something, 709 00:47:45.039 --> 00:47:49.639 and that is it's a very established standard. But I did get addicted 710 00:47:49.679 --> 00:47:51.639 to it. And now if you want to have X number, you have 711 00:47:51.679 --> 00:47:52.920 to pay like thirty or forty bucks a month. Or something like that. 712 00:47:53.519 --> 00:47:59.000 So it's an established model. We understand that product led growth is one way 713 00:47:59.000 --> 00:48:02.559 to describe all that stuff, but really knowing where the costs are going to 714 00:48:02.639 --> 00:48:07.320 bend is part of the ballgame, right and understanding it's hard to figure out 715 00:48:07.360 --> 00:48:12.400 exactly how that's going to happen, right, Yeah, I think the majority 716 00:48:12.400 --> 00:48:15.559 of the AI is going to happen in the cloud because it's more convenient to 717 00:48:15.559 --> 00:48:17.760 do there. It's actually a more expensive model. It's more expensive to use 718 00:48:17.800 --> 00:48:21.400 the resources in the cloud being on premise, and I think a lot of 719 00:48:21.519 --> 00:48:23.440 organizations, just like we did on the pattern of the last ten years, 720 00:48:23.480 --> 00:48:29.000 are going to start out in building their initial prototypes and systems in the cloud 721 00:48:29.159 --> 00:48:31.639 and then look at the expense and look at the opportunities for pulling it back 722 00:48:31.679 --> 00:48:36.199 on premise, or even looking at the micro clouds that are being developed these 723 00:48:36.280 --> 00:48:38.440 days, anything with the dot AI, their GPUs as a service, things 724 00:48:38.480 --> 00:48:42.760 like that. In other words, specialized microclouds that are just doing AI. 725 00:48:42.920 --> 00:48:45.280 I think that's going to be an option, but everything is going to be 726 00:48:45.280 --> 00:48:47.719 more expensive than people think it is right now, based on what I have, 727 00:48:47.760 --> 00:48:52.280 like conversations, and then I do the back of the mac back of 728 00:48:52.320 --> 00:48:55.360 the Napkin calculations. It's going to be to get to where people want to 729 00:48:55.400 --> 00:48:58.559 be, they're going to be spending a lot more money in the r right 730 00:48:58.559 --> 00:49:02.719 now. Yeah, that's my thinking is that there's so much investment in getting 731 00:49:02.760 --> 00:49:07.079 people onto the systems, you know, getting client acquisition basically, and you're 732 00:49:07.079 --> 00:49:08.880 going to get addicted to it. You're going to want to use it all 733 00:49:08.880 --> 00:49:10.639 the time, and the cost they are going to go up, up, 734 00:49:10.719 --> 00:49:13.639 up, up up, and you're going to have to figure out how to 735 00:49:14.159 --> 00:49:16.519 deal with that. And you know, maybe some of these smaller models are 736 00:49:16.519 --> 00:49:22.119 coming out too, which aren't so extravagant, small language models people are talking 737 00:49:22.119 --> 00:49:24.960 about, for example, Mistral's got this mixture of experts they talk about, 738 00:49:25.000 --> 00:49:29.519 So there are going to be ways to make it more sustainable. But even 739 00:49:29.559 --> 00:49:34.920 a small language model is an incredibly intense initiative to build and to run. 740 00:49:35.079 --> 00:49:37.079 It just takes a lot of money and there are a lot of sunk costs 741 00:49:37.119 --> 00:49:39.559 baked in there, right, so it is going to be a little bit 742 00:49:39.679 --> 00:49:44.360 dicey, I think. Closing thoughts, we've got about sixty seconds before the 743 00:49:44.400 --> 00:49:46.880 live show closes out. Where do people get your book? I'm sure online 744 00:49:46.880 --> 00:49:51.159 where should they find out more about you? Amazon? Look, look me 745 00:49:51.239 --> 00:49:55.360 up on LinkedIn. I have seventy two classes out on LinkedIn Learning and also 746 00:49:55.400 --> 00:49:59.320 teach at LSU, so you can find me in all those places. So 747 00:49:59.360 --> 00:50:00.960 you went, did you go the LSU? No, never been on the 748 00:50:00.960 --> 00:50:04.920 campus. Oh no, kidding, that's too funny because I lived in New 749 00:50:05.000 --> 00:50:07.000 Orleans for a number of years, and of course LSU is a you know, 750 00:50:07.159 --> 00:50:10.559 very well known. I heard that. Yeah, the people love their 751 00:50:10.760 --> 00:50:15.880 LSU in Baton Rouge obviously, but cool stuff. So that new book is 752 00:50:17.280 --> 00:50:22.280 remind me again. It's an Any's Got to Cloud Insider's Got to Cloud Computing 753 00:50:22.800 --> 00:50:27.159 and published by Pearson's and you can find it anywhere finer books are sold. 754 00:50:27.400 --> 00:50:30.360 And you've got some several books out there, right, seventeen books. I 755 00:50:30.360 --> 00:50:35.960 wrote the book on Enterprise Application Integration B to B application Integrations, so at 756 00:50:35.960 --> 00:50:40.440 a cloud convergence. Even wrote a book called Killer Doss Utilities twenty years ago. 757 00:50:40.480 --> 00:50:43.840 It's I think the coolest book I've ever wrote, as big as a 758 00:50:43.880 --> 00:50:47.519 doorstop. Hiller Dos Utilities looking has a shark on the has a shark on 759 00:50:47.559 --> 00:50:51.440 the cover, and came with the it came with a three point five inch 760 00:50:51.440 --> 00:50:54.559 floppy. Wow, that's pretty impressive. I remember the free point five inch 761 00:50:54.599 --> 00:51:00.719 floppies. Man, I remember my first portable portable compact computer. It was 762 00:51:00.800 --> 00:51:05.480 like forty five pounds. Good break your back lifting that thing up. They 763 00:51:05.519 --> 00:51:08.199 go for thousands of dollars on eBay now, so it's if you held on 764 00:51:08.199 --> 00:51:10.800 to it, it'd be worth some money. Wow. While folks, you've 765 00:51:10.840 --> 00:51:19.000 been listening to Inside Analysis inciting thank you missed something today, yesterday, last 766 00:51:19.000 --> 00:51:23.239 week. Check out our podcasts at www. KCAA radio dot com. We 767 00:51:23.360 --> 00:51:30.280 leave no listener behind and now the voices of KCAA was an exciting announcement. 768 00:51:30.480 --> 00:51:35.760 Want to hear NBC News or KCAA anywhere you go? Well, now there's 769 00:51:35.760 --> 00:51:38.599 an app for that. 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That number again eight hundred ninety eight two 808 00:54:37.760 --> 00:54:45.360 three one ninety seven, and old political truism notes that where there's a will, 809 00:54:45.679 --> 00:54:50.119 there are a thousand won'ts. And what a hurricane of wonts swirled out 810 00:54:50.119 --> 00:54:54.400 of Washington's power centers and march to pummel Joe Biden. Corporate lobbyists in their 811 00:54:54.440 --> 00:55:00.280 congressional hirelings howled at him for declaring that he would seek a tax increa on 812 00:55:00.320 --> 00:55:05.920 corporations to pay for the essential, overdue job of repairing and expanding our nation's 813 00:55:05.960 --> 00:55:12.519 and equated dilapidated infrastructure. Blowhard Mitch McConnell, the GOP Senate leader, blustered 814 00:55:12.559 --> 00:55:16.360 that poor corporate America should not be singled out to bear this burden. But 815 00:55:16.440 --> 00:55:22.119 wait, Mitch singled out the corporate giants in twenty seventeen to receive a massive 816 00:55:22.199 --> 00:55:25.519 cut in their tax rate, so even with a slight increase now they'll pay 817 00:55:25.639 --> 00:55:30.840 much less than regular people. Also, the giants worm loopholes in the law 818 00:55:30.960 --> 00:55:36.639 to cut their taxes further. Indeed, fifty five of the biggest most profitable 819 00:55:36.679 --> 00:55:42.360 corporations paid zero in US income taxes last year. As Bernie Sanders points out, 820 00:55:42.480 --> 00:55:45.679 if you paid one hundred and twenty dollars for a pair of Nike shoes, 821 00:55:45.960 --> 00:55:50.239 you paid more to Nike than it paid in federal income taxes over the 822 00:55:50.280 --> 00:55:54.360 past three years while it made four billion dollars in profits. Mitch and his 823 00:55:54.480 --> 00:56:00.280 fellow hypocrites cynically profess that they support restoring America's infrastructure, but he says, 824 00:56:00.639 --> 00:56:06.199 asking our corporate political funders to pay more is not going to get support from 825 00:56:06.239 --> 00:56:08.679 our side. So who do they want to pay for it? You, 826 00:56:09.440 --> 00:56:15.159 working people and the poor. Senator Roy Blunt, a Missouri Republican and a 827 00:56:15.280 --> 00:56:20.519 leader of Mitch's team, points to putting more user fees on drivers and adding 828 00:56:20.559 --> 00:56:23.960 taxes on consumers as the way to go. This is Jim Hitler saying, 829 00:56:24.280 --> 00:56:29.719 to see a list of other major corporate scott Laws who have been pocketing billions 830 00:56:29.719 --> 00:56:34.679 in profits yet paying zilch for the upkeep of America. Go to the Institute 831 00:56:34.800 --> 00:56:44.960 on Taxation and Economic Policy ITEP dot org. The election is March fifth. 832 00:56:45.000 --> 00:56:49.280 There's a new Marshal in town. Vote Derek Marshall for twenty third Congress by 833 00:56:49.360 --> 00:56:52.599 March fifth. We all know we need to change Congress. The current Congress 834 00:56:52.599 --> 00:56:54.599 has nothing but fight with each other. He've forgotten why we sent them there 835 00:56:54.800 --> 00:56:59.599 to work. Let's marshal and fix our problems at the border, a comprehensive 836 00:56:59.639 --> 00:57:04.119 plan, not political rhetoric and infighting. Yes, there's a new Marshall in 837 00:57:04.159 --> 00:57:07.079 town. The rent is two darn high. Let's marshal an affordable housing and 838 00:57:07.199 --> 00:57:13.639 real affordable universal healthcare. Let's marshal better union jobs. The current congress member. 839 00:57:13.800 --> 00:57:17.039 But here's party first. Our incumbent party politician voted no on the recently 840 00:57:17.079 --> 00:57:22.239 passed bipartisan infrastructure bill. He voted no to three billion dollars in new funds 841 00:57:22.239 --> 00:57:27.639 for our district and no to thirty five thousand new jobs right here at home. 842 00:57:27.840 --> 00:57:30.880 He said we need a secure border, but now he's rolled it back 843 00:57:30.920 --> 00:57:36.159 to play politics. We need to marshal real solutions. Derek Marshall for twenty 844 00:57:36.199 --> 00:57:40.920 third Congressional district. That's DEREKMARSHALLCA dot Com paid for Derek Marshall for Congress. 845 00:57:42.119 --> 00:57:50.760 My name is Derek Marshall and I approved this message NBC News Radio. I'm 846 00:57:50.800 --> 00:57:54.320 Chris Garagio. GOP presidential hopeful. Nikki Haley is slamming former President Trump for 847 00:57:54.320 --> 00:57:59.679 his silence on last week's death of Russian opposition leader Alexi Navalni. Speaking of 848 00:57:59.679 --> 00:58:01.960 the name Sees this week, she called it both concerning and a problem that 849 00:58:02.000 --> 00:58:07.679 Trump has not responded to Navali's unexpected death in prison. She noted President Biden 850 00:58:07.679 --> 00:58:12.079 and other world leaders lay the blame directly on Russian President Putin. Haley said 851 00:58:12.119 --> 00:58:15.320 either Trump believes it's cool for Putin to have one of his opponents killed, 852 00:58:15.599 --> 00:58:20.000 or Trump doesn't consider Navalne's death that important. And a Nikki Hally surrogate says 853 00:58:20.039 --> 00:58:23.159 he believes former President Trump's legal battles will cause him to run out of campaign 854 00:58:23.280 --> 00:58:29.159 resources. The errantcy itself has a record low amount of cash on hand because 855 00:58:29.159 --> 00:58:31.239 of his leadership and his type of message. Speaking on Fox News Sunday, 856 00:58:31.280 --> 00:58:36.760 New Hampshire Governor Chris Sanunu noted a recent campaign finance filing that showed Trump had 857 00:58:36.760 --> 00:58:39.360 spent fifty million dollars on legal fees. In addition to legal fees, a 858 00:58:39.440 --> 00:58:44.039 judge on Friday ordered Trump to pay more than three hundred and fifty million dollars 859 00:58:44.039 --> 00:58:46.719 in fines in his civil fraud case. That came just three weeks after a 860 00:58:46.800 --> 00:58:52.880 jury awarded e Gen Carrol eighty three million dollars in her defamation case against Trump. 861 00:58:52.119 --> 00:58:57.119 Israeli Prime Minister of Benjamin net Yahoo says he pulled out of ceasefire negotiations 862 00:58:57.159 --> 00:59:01.039 over the war in Gaza because of delusional demands by Hamas. Netanyahu said Israel 863 00:59:01.079 --> 00:59:06.559 sent negotiators to Cairo last week, as requested by President Biden, but he 864 00:59:06.599 --> 00:59:09.679 added they won't be going back until Hamas changes its demands. Hamas is calling 865 00:59:09.719 --> 00:59:14.920 for a permanent ceasefire and the release of more than fifteen hundred prisoners from Israeli 866 00:59:14.960 --> 00:59:19.440 jails. Netnah who also said Israeli forces will continue their offensive in the southern 867 00:59:19.519 --> 00:59:22.719 border town of Rafa, where more than a million Palestinians are seeking refuge. 868 00:59:23.079 --> 00:59:28.119 California is bracing for more possible flooding over the next few days. Santa Barbara 869 00:59:28.199 --> 00:59:31.400 County along the central coast is once again expected to be among the hardest hit 870 00:59:31.440 --> 00:59:37.599 areas. Emergency officials are issuing evacuation warnings for some areas because of possible flash 871 00:59:37.599 --> 00:59:40.920 flooding and landslides, possibly through Wednesday. Heavy mountain snow was also predicted, 872 00:59:42.000 --> 00:59:47.360 along with gusty winds. I'm Chris Karagio, NBC News Radio, NBC News 873 00:59:47.400 --> 00:59:52.880 on CACAA Lomalinda, sponsored by Teamsters Local nineteen thirty two, Protecting the Future 874 00:59:52.960 --> 01:00:02.400 of Working Families, Teamsters nineteen thirty two dot org. K CIA Radio has 875 01:00:02.440 --> 01:00:07.000 openings for one hour talk shows. If you want to host a radio show, 876 01:00:07.159 --> 01:00:08.440 now is the time. Make k CIA your