WEBVTT 00:00.000 --> 00:14.180 So, we're back, Energy Bites, episode two, Brad Dad is here, John Califian, got my co-host 00:14.180 --> 00:19.720 Bobby Nealon, and today we've also got Todd Bush from DeCarbonFuse, as well as just a 00:19.720 --> 00:25.080 man, I was trying to think about what year it was that I originally met you, and it's 00:25.080 --> 00:26.080 been a while. 00:26.080 --> 00:27.080 Yeah, it's been a long time, for sure. 00:27.400 --> 00:32.240 I had to look back on what the company has, I knew we even used the Energent, but I had 00:32.240 --> 00:33.240 to look back up what it was called. 00:33.240 --> 00:36.240 Yeah, I did too. 00:36.240 --> 00:41.160 We used it in a number of places, the API and stuff, when Bobby and I were working together, 00:41.160 --> 00:46.840 and then they got bought, and I also haven't worked at a company that needed it. 00:46.840 --> 00:50.400 But no, we've got Todd Bush, how's it, thanks for joining us. 00:50.400 --> 00:56.400 Yeah, thank you for the invitation, and definitely excited to talk about, we'll go back and forth 00:56.440 --> 01:01.160 on the data and AI side, and so interested to hear what you guys are up to, as well as 01:01.160 --> 01:03.760 sharing a little bit about what I'm doing. 01:03.760 --> 01:05.640 Awesome, absolutely. 01:05.640 --> 01:11.360 Go ahead and tell us a little bit about yourself, where are you from, how'd you end up here 01:11.360 --> 01:12.360 today? 01:12.360 --> 01:21.360 Yeah, so, let's see, so, born in Colorado, grew up mostly in Dallas, and was interested 01:21.840 --> 01:28.840 in technology and kind of information all along, went to Texas A&M undergrad, focused 01:28.840 --> 01:33.840 mostly on information and operations management, did a little bit of statistics, so that was 01:33.840 --> 01:37.840 kind of the, kind of piqued my interest a little bit in that. 01:37.840 --> 01:43.040 And then out of school, I actually worked for a small software company first, just really 01:43.040 --> 01:49.720 focused more on the financial and banking side, and then met some people and got recruited 01:49.720 --> 01:54.880 into a consulting firm that was working a lot with Chevron, and so I kind of found an 01:54.880 --> 02:00.960 inroad into Chevron and was a, kind of like a project manager, program manager, and one 02:00.960 --> 02:07.600 of the first projects there was a company-wide technical portal that included everything 02:07.600 --> 02:14.560 from the initial kind of regulatory planning, all the way to drilling and production, to 02:14.560 --> 02:18.400 what happens kind of on the work-over side afterwards, so that was kind of my first foray 02:18.680 --> 02:23.560 into, you know, all the information, kind of all the different workflows that are across 02:23.560 --> 02:30.280 different teams, and so from there, it's just been kind of expanded into a number of different 02:30.280 --> 02:33.440 products and projects, and so, good stuff. 02:33.440 --> 02:40.880 Todd's humble description of a successful software entrepreneur, I mean, that's how 02:40.960 --> 02:51.360 we met, I was, it had to be, I think, sometime around 13 or 14, 2012, 13, 14-ish, where I 02:51.360 --> 02:55.400 don't even, I think it was like a LinkedIn post or something, I came across Enerjet and 02:55.400 --> 03:01.280 I was working for a Frac company and we needed, you know, data about permits and completions 03:01.280 --> 03:07.360 and Frac focus had just kind of started back then, wasn't, you know, there was no requirements 03:07.360 --> 03:13.720 or anything around it back then, it was just a database, but yeah, and you know, what, 03:13.720 --> 03:16.560 you guys ended up selling that to? 03:16.560 --> 03:25.480 Yeah, to Westwood, yeah, so started Enerjet with a friend, Boyd Skelton, and we basically 03:25.480 --> 03:32.280 looked at all of the kind of Frac focus completion data, and at the time, the completion data 03:33.040 --> 03:40.200 just wasn't very good, right, this is 2013, right, so we had a little mobile app out there 03:40.200 --> 03:44.000 that was for kind of the field guys, and we just felt like the old field service side 03:44.000 --> 03:50.800 was underserved, really, and ended up doing a lot of work for FracSAN companies, logistics 03:50.800 --> 03:57.800 companies, financial institutions that were kind of looking at the, looking at activity 03:57.800 --> 04:02.680 and trying to understand what completion trends were happening, and so we ended up 04:02.680 --> 04:09.060 going from just the typical regulatory side and bringing in all that information to taking 04:09.060 --> 04:13.520 satellite data and trying to figure out, okay, could we actually observe when the rig is 04:13.520 --> 04:18.320 on site, when it leaves, what happens when a Frac crew is on site, can we detect kind 04:18.320 --> 04:22.720 of all that, and we had some pretty good success with that and launched another kind of product 04:22.800 --> 04:28.160 alongside Indigent, where it was really focused more on just activity and derived kind of 04:28.160 --> 04:32.520 information that we could send to a number of different people. 04:32.520 --> 04:38.080 So when you got onto that, was it ever the goal to, say, compete with the IHSs or Inverus 04:38.080 --> 04:43.280 of the world, or, I mean, because in a way it was, but then in other ways not, I mean... 04:43.280 --> 04:47.900 Right, right, yeah, we definitely wanted to not directly compete with them. I think one 04:48.020 --> 04:53.620 thing that we tried to do early on, and it was really trying to find the progressive 04:53.620 --> 04:59.020 companies that were, oh, we need an API, we need to integrate this into all of our systems, 04:59.020 --> 05:04.580 so we had what I thought was a very simple kind of well-headed API that didn't require 05:04.580 --> 05:09.620 you to download an entire database, it was restful, it was something that you could get 05:09.620 --> 05:14.540 by well name, by API number, by operator, kind of all the basic things that you would 05:14.580 --> 05:20.380 expect from what we thought a typical kind of oil and gas information company should 05:20.380 --> 05:27.380 provide. So we did that, and then that led to probably even more kind of visualization 05:27.540 --> 05:34.540 tools, I would say, on integrating with Tableau, integrating with kind of Spotfire, Salesforce, 05:34.620 --> 05:39.700 kind of all down that path, and there's so many different workflows that you can kind 05:39.700 --> 05:46.460 of tap into, and we ended up working really more with the drilling contractors, the logistics 05:46.460 --> 05:51.260 companies, and those firms that were really interested in kind of how they could get insights 05:51.260 --> 05:53.660 into what operators were doing. 05:53.660 --> 05:59.660 So Energent was your first startup, really? You were with Rigdata, I saw a little bit? 05:59.660 --> 06:06.660 Oh, yeah, so I kind of skipped over that for a bit. So I joined, let's see, I left Chevron 06:07.540 --> 06:12.260 because I kind of had like an entrepreneurial bug in just trying to do something. So I had, 06:12.260 --> 06:17.340 when I left Chevron, started a couple little side projects kind of on the software side, 06:17.340 --> 06:24.340 joined Rigdata, and really the emphasis at Rigdata was relaunching a mobile app and building 06:24.340 --> 06:30.740 out kind of, I'll say, kind of an enterprise data kind of product that they didn't have 06:30.780 --> 06:35.780 at the time, and so stayed there for a short period. I was hoping that I could actually 06:35.780 --> 06:42.780 at one point kind of take over or buy the company from the existing owners, and that 06:42.940 --> 06:46.540 didn't work out. They wanted to hold onto it, which I definitely understood, and that 06:46.540 --> 06:51.780 really spawned kind of Energent and really forced me to make a decision of, okay, I can 06:51.780 --> 06:56.820 stay here and work and help kind of build out the product landscape or kind of start 06:56.820 --> 07:02.100 Energent and go off on that, and so that's what I did. 07:02.100 --> 07:08.540 So with Energent then, so did you all start, so again, I think, as I understand it, Boyd 07:08.540 --> 07:12.940 was probably more fingers on the keyboard, and then you were driving the kind of direction 07:12.940 --> 07:14.140 of the product? 07:14.140 --> 07:21.140 Yeah, yeah, and then I would say I was trying to create some of the reports and the kind 07:21.940 --> 07:28.940 of visualizations that we were doing, so along the way we decided to pick up R as kind of 07:30.140 --> 07:36.540 a language for some analysis, some models, and really more probably in the way that I 07:36.540 --> 07:41.940 use it as really just a visualization tool, making it easy, and so we picked that up and 07:41.940 --> 07:48.940 ran with it and really improved kind of our ways of producing basically reproducible research, 07:49.940 --> 07:56.940 if you will, around oil and gas information, which at the time was probably, R wasn't very 07:58.180 --> 08:01.980 well known, but it was kind of coming into the scene. 08:01.980 --> 08:08.060 I think that's one area where we helped kind of bring, we'd bring analysts on, teach them 08:08.060 --> 08:13.940 R or hopefully they even had some kind of R skills, and then go to town on what we can 08:13.940 --> 08:20.940 do for completion metrics or kind of insights or anything around kind of the completion 08:22.060 --> 08:23.340 and production side. 08:23.340 --> 08:28.700 Yeah, so I guess I was thinking that, so I mean, was R kind of part of the Energent story 08:28.700 --> 08:32.340 like pretty early on, because I know I remember talking to you when you were at Westwood and 08:32.340 --> 08:36.100 you had some people working on, and you even had maybe an R library to help pull data out. 08:36.100 --> 08:41.020 Yes, yeah, so we ended up, I think there was a point in time when we talked about releasing 08:41.180 --> 08:46.060 kind of open sourcing some of the tools that we built around, because we had all kinds 08:46.060 --> 08:52.340 of R packages that were built specifically for the kind of well header information, specifically 08:52.340 --> 08:57.340 for some of the prop end data, even getting into some of the more detailed completion 08:57.340 --> 09:04.180 side where we had kind of pressures and ISIPs and a few other kind of metrics around kind 09:04.180 --> 09:08.540 of the completion data, and we didn't, but you know, I think there's, I'm sure those 09:08.620 --> 09:14.820 still exist, still being used, because they're a great kind of foundation for us to take 09:14.820 --> 09:17.820 the research and actually do something more with the information. 09:17.820 --> 09:22.820 For sure, so I mean at that point, I guess we can, yeah, I didn't know where we were 09:22.820 --> 09:27.180 going to go with some of the technologies, but I loved R. R was probably my first coding 09:27.180 --> 09:31.060 language, and I still love using it when I get the chance. So at the time, was R Markdown 09:31.060 --> 09:32.260 a thing? 09:32.260 --> 09:37.820 It was just, yeah, R Markdown was a thing, and we tried to do some of the, if you remember 09:37.900 --> 09:43.380 some of the PDFs and publish it with kind of Markdown. Some of that worked well, some 09:43.380 --> 09:49.380 of it was just okay, but we ended up taking all the ggplot and dplyr and kind of all of 09:49.380 --> 09:50.380 that. 09:50.380 --> 09:51.380 Daddyverse now, right? 09:51.380 --> 09:56.580 Yes, yeah, all the packages and using those in a way that we could kind of run through, 09:56.580 --> 10:03.220 oh, here's the updated information, here's, whether that's, say, taking some of the prop 10:03.780 --> 10:08.220 data that we had and creating some of the kind of quarterly reports around that, we 10:08.220 --> 10:12.820 could run through that pretty quickly and kept our, you know, the whole idea was, okay, 10:12.820 --> 10:18.380 we can do more with less and with R in the reproducible side and then our own data, then 10:18.380 --> 10:19.380 we could do a lot. 10:19.380 --> 10:27.380 Yeah, walk me through why y'all went with R over something else, just out of curiosity. 10:27.380 --> 10:36.900 So we started off with kind of a Ruby on Rails application. One thing, one of the decisions 10:36.900 --> 10:43.740 that we made early on was we wanted to do this with MongoDB and NoSQL instead of kind 10:43.740 --> 10:52.740 of a typical Postgres or Microsoft database or something like that, right? And that decision 10:52.860 --> 10:59.060 was a huge help in pushing us to be able to collect any type of information from any state 10:59.060 --> 11:07.060 regulatory body, from any, you know, EPA or even some of the FRAC focus information, we 11:07.060 --> 11:12.460 would basically collect through MongoDB first and then kind of rationalize it, if you will, 11:12.460 --> 11:21.460 a little bit and then pull that down into R for the analysis. And we started, I'm trying 11:21.860 --> 11:28.860 to remember exactly where we started, we had a, at the time we started doing a lot of kind 11:28.860 --> 11:35.860 of LinkedIn posts, articles, and having some key charts in there. One of the things that 11:35.860 --> 11:40.060 we found with R is we could kind of differentiate the chart, make it look a little different, 11:40.060 --> 11:46.060 kind of style it in a way that was unique to us. And so we continued doing that for 11:46.060 --> 11:49.780 marketing purposes and then pulled that into some of the research reports. 11:49.780 --> 11:55.100 So were you all just using it for just plotting or were you doing any kind of analysis and 11:55.100 --> 11:56.500 stats and stuff on the backside? 11:56.500 --> 12:02.340 On the backside, we did all the analysis in, I would say, some of the modeling. So we had 12:02.340 --> 12:08.140 kind of our quarterly forecast for drilling completions. We had part of that in R. We 12:08.140 --> 12:13.060 always wanted to move 100% into R, but there was just some things that were easy to do, 12:13.060 --> 12:17.500 you know, in Excel. Like if you want to tweak some of the, you know, growth factors or we 12:17.500 --> 12:22.700 believe, you know, the rig activity or drilling activities didn't go down in a particular 12:22.700 --> 12:27.460 quarter or a particular area, it was just easier to tweak some of that in Excel. But 12:27.460 --> 12:35.420 really the R gave us the front-end work of that to kind of really reduce how much effort 12:35.420 --> 12:36.420 we had to put into it. 12:36.420 --> 12:37.420 For sure. 12:37.420 --> 12:40.420 So you can use R in production. 12:40.420 --> 12:41.420 Proof. 12:41.420 --> 12:42.420 Yes. 12:42.420 --> 12:46.280 The other quick question I want to ask there, because you mentioned something that I think 12:46.280 --> 12:50.120 all of us kind of generally understand, but I want to make sure that for kind of just 12:50.120 --> 12:56.160 the average user that they understand, you're talking about your decision to go with a unstructured 12:56.160 --> 13:02.160 database versus a structured database. What kind of went into that and why? And like thinking 13:02.160 --> 13:07.680 about this from a generalist perspective of like, okay, I know that I need a database 13:07.680 --> 13:14.180 because I'm going to be doing some analytics analysis, whatever, basic stuff with our data. 13:14.180 --> 13:17.920 What do I need to think about and why do I need to be looking at unstructured versus 13:17.920 --> 13:18.920 structured? 13:18.920 --> 13:19.920 Yeah. 13:19.920 --> 13:20.920 Oh, interesting. 13:20.920 --> 13:21.920 That's a big question. 13:21.920 --> 13:22.920 Yeah. 13:22.920 --> 13:27.720 Let me rephrase it. What benefits did y'all find from going with an unstructured database 13:27.720 --> 13:31.120 versus a more traditional SQL structured type database? 13:31.120 --> 13:39.200 Yeah. Since we were thinking about a couple of different products, we had MongoDB on the 13:39.200 --> 13:46.200 back end so that we could pull in state regulatory information from any place. And so that would 13:46.200 --> 13:54.600 be everything from PDF documents to Excel spreadsheets to shape files going directly 13:54.600 --> 14:01.300 into an unstructured database allowed us to say, okay, at this state level, we don't care 14:01.300 --> 14:05.840 how you define your individual record. We're going to take all of that information and 14:06.080 --> 14:13.280 that if well names repeated and at least names repeated and you have kind of all this duplicate 14:13.280 --> 14:20.000 information, that's fine at one level. We'll pull that all into that kind of state, we'll 14:20.000 --> 14:24.840 call it state repository on the MongoDB side. And then once we normalize it, then we can 14:24.840 --> 14:29.520 actually get to a structure, kind of our standard well header. 14:29.520 --> 14:32.400 So it was almost like a staging layer, if you will, or almost like what a data lake 14:32.400 --> 14:33.400 would be. 14:34.240 --> 14:41.600 Yeah, it's kind of like our ETL layer, if you will. We just used that. So we had some 14:41.600 --> 14:48.880 Ruby programs that were all the gatherers that were basically pulling information and 14:48.880 --> 14:54.880 there were a couple of things where we connected directly to other sources, but essentially 14:54.880 --> 15:00.040 pulling that in and then within MongoDB that allowed us to say, okay, if you wanted to 15:00.040 --> 15:06.840 then show that information through an application, obviously we could do that or we could show 15:06.840 --> 15:14.960 the normalized view. And so that allowed us to basically not have to do, in Ruby and Rails 15:14.960 --> 15:20.680 it's called database migrations every time the relational database changes. So that allowed 15:20.680 --> 15:26.240 us to kind of prevent that whole step and just go directly to how we want to store the 15:26.280 --> 15:31.640 data and get access to it and then present it. And then from the R perspective, we could 15:31.640 --> 15:36.720 then use that normalized information or what often happened is like, oh, I want to dig 15:36.720 --> 15:43.120 into North Dakota. Show me what's happening in the Bakken or what's happening with some 15:43.120 --> 15:49.000 new minds or whatever it might be that we were able to then go deep into that state 15:49.000 --> 15:51.520 repository and have all that information at our fingertips. 15:51.520 --> 15:56.200 Yeah. So y'all started Energent when? What year? 15:56.920 --> 16:04.160 So officially, I think it was 2013. Did a little bit of consulting. I think we incorporated 16:04.160 --> 16:05.400 in 2013 or 2014. 16:05.400 --> 16:08.800 Okay. And then y'all exited when? 16:09.240 --> 16:16.640 In 2017. So I mean, that's a pretty quick turnaround for, in my opinion, in oil and 16:16.640 --> 16:23.760 gas. I'm sure in the trenches, especially when you've got almost two downturn or you 16:23.760 --> 16:24.800 got a downturn and a half. 16:24.800 --> 16:30.480 And a downturn and a half. Yeah, and so I'll never forget, Boyd and I always laugh about 16:30.480 --> 16:36.160 this, like some of our first customers, me driving through kind of Eagleford and talking 16:36.160 --> 16:41.280 to people that were using the mobile app because we had that out in the field and trying to 16:41.280 --> 16:45.640 figure out, okay, what steps do you really want to take? And some of those were large 16:45.640 --> 16:50.120 companies, but you know, had kind of their districts and others were really small companies. 16:50.120 --> 16:55.360 And so it was always an interesting kind of, you know, get a different view of that once 16:55.360 --> 16:56.800 you got in the field. 16:57.560 --> 17:02.440 So from my infrastructure side, were y'all always on the cloud? Did you start off on 17:02.440 --> 17:03.040 the cloud? Yeah. 17:03.160 --> 17:08.160 Yeah, we started off with Heroku before they were acquired. 17:08.160 --> 17:08.440 Okay, yeah. 17:08.600 --> 17:13.720 Yep. And then MongoDB was an independent hosting. 17:13.720 --> 17:16.160 MongoDB Atlas, like the one that they host? 17:16.160 --> 17:21.080 So even before that, there was something called, oh shoot, I'm going to forget the name of 17:21.080 --> 17:27.640 it, not compose, but something that was acquired by IBM. 17:27.680 --> 17:27.960 Okay. 17:28.040 --> 17:32.680 And then we, like the MongoDB portion of that became the most expensive side of it. 17:33.040 --> 17:40.000 And so we believe at one point transferred over to, this probably after we were acquired, 17:40.000 --> 17:43.520 but transferred over to somebody else, probably Mongo Atlas. 17:43.640 --> 17:44.080 Yeah. 17:44.160 --> 17:47.720 To kind of reduce some of that cost, but that was years down the road. 17:47.720 --> 17:48.080 Right. 17:48.160 --> 17:48.400 Yeah. 17:48.400 --> 17:51.440 Who were you hosted on, or which cloud? 17:51.720 --> 17:52.880 Well, it was Heroku originally. 17:52.880 --> 17:53.800 Yeah, it was Heroku. 17:53.800 --> 17:55.360 And Heroku got bought by Salesforce, I believe. 17:55.360 --> 17:55.680 Yes. 17:55.680 --> 17:55.920 Yeah. 17:56.040 --> 17:56.240 Yeah. 17:56.720 --> 17:58.040 But I mean, it was a great platform. 17:58.040 --> 18:01.680 I mean, just from the, being like, yeah, you can, there's even some really great stuff 18:01.680 --> 18:06.240 now, even you're in API, Python, I'm going to just push it up and it works. 18:06.240 --> 18:10.800 Like, and again, really abstracting those layers of complexity. 18:11.200 --> 18:14.800 They handle all the hosting and even some of the CICD for you, if you want. 18:14.800 --> 18:15.600 Yes. 18:15.720 --> 18:15.920 Yeah. 18:15.920 --> 18:21.040 And so we would do things like, we had a little special project or something with 18:21.040 --> 18:26.480 Heroku, you could spin up a, say a Postgres database and then connect to that. 18:27.080 --> 18:33.720 We did some other things with AWS and connecting with some of the, once we got 18:33.720 --> 18:39.000 into production data, basically having kind of a direct connect to a public kind 18:39.000 --> 18:44.640 of production database on AWS, but primarily it was the core, I guess, was Heroku. 18:45.520 --> 18:49.840 Tell them, so you'll have your exit at Energent. 18:50.520 --> 18:51.280 What are you working on now? 18:51.760 --> 18:51.960 Yeah. 18:51.960 --> 18:57.960 So, so let's see the exit, stayed at Westwood for four or five years, four years, I 18:57.960 --> 19:04.080 guess, and then left and I knew I wanted to kind of go back and look at kind of 19:04.080 --> 19:05.880 some of the energy transition pieces. 19:06.720 --> 19:13.360 So one of my early projects at Chevron was a CO2 flood, it was kind of like 19:13.360 --> 19:14.720 water alternating gas. 19:14.880 --> 19:15.280 Wag. 19:15.400 --> 19:15.760 Yep. 19:15.800 --> 19:16.320 Wag. 19:16.480 --> 19:22.560 And so we had a reservoir engineer that basically dealing with all of the CO2 19:22.560 --> 19:25.880 buying and selling and trying to figure out how much water, how much CO2 they 19:25.880 --> 19:28.120 needed and figuring out kind of that life cycle. 19:28.120 --> 19:30.600 Logistics of that must be really fun. 19:30.720 --> 19:31.040 Yeah. 19:31.120 --> 19:35.040 And I'm like, if you have one guess, how do you think that was being managed? 19:35.040 --> 19:35.280 Right? 19:35.880 --> 19:38.320 It was, it was at Excel and access data. 19:38.320 --> 19:40.560 I was going to say access, but yeah, it's the same difference. 19:40.560 --> 19:41.080 So both of them. 19:41.280 --> 19:41.800 And so- 19:41.800 --> 19:44.360 I'm impressed that you had any kind of database involved. 19:44.360 --> 19:44.760 I know. 19:44.760 --> 19:45.280 Very true. 19:45.640 --> 19:45.880 Yep. 19:46.280 --> 19:46.640 Yeah, so- 19:46.640 --> 19:48.360 Not Excel as a database type. 19:48.920 --> 19:49.280 Yes. 19:49.360 --> 19:49.600 Yeah. 19:50.120 --> 19:54.200 So that was an interesting piece to me. 19:54.200 --> 19:58.040 And then obviously the, some of the other projects I've worked on, I was like, 19:58.040 --> 20:02.760 okay, there's got to be a little bit more on the CO2 side that's not very well 20:02.760 --> 20:09.040 known and so started digging into some of the other information that I knew 20:09.040 --> 20:13.200 about in different States for enhanced oil recovery and, and different CO2 20:13.200 --> 20:19.320 floods and started really doing more research around carbon capture and so 20:19.320 --> 20:22.040 started a decarbon fuse basically here. 20:22.040 --> 20:26.840 How can I provide some insights into the information around carbon capture, 20:26.840 --> 20:31.880 hydrogen and electrification because especially at Westwood did a lot with 20:31.880 --> 20:36.120 emissions and electrifications for different frac fleets and companies that 20:36.120 --> 20:40.440 were looking at, okay, how do we, how do we reduce emissions, clean, clean up 20:40.440 --> 20:41.360 operations, if you will. 20:42.000 --> 20:45.800 And so it took those kinds of three categories and really started digging 20:45.800 --> 20:52.280 into the market, like who the players, projects, and now trying to figure out 20:52.280 --> 20:57.760 if there's enough, enough kind of projects, enough spending to really 20:57.800 --> 21:04.080 warrant like a full-blown kind of tool around, around the screening of kind of 21:04.080 --> 21:06.280 carbon capture and hydrogen projects. 21:06.960 --> 21:17.960 So what kind of data workflow use cases is, is your like target customer 21:18.240 --> 21:20.040 we're looking for, right? 21:20.920 --> 21:25.000 And so a lot of it right now is screening, like all these projects that have been, 21:25.040 --> 21:28.840 been announced, most of them are in the screening and feasibility stage. 21:29.400 --> 21:32.720 And so with screening, it's mostly all public information, right? 21:32.840 --> 21:34.560 And you have all your emission data. 21:34.560 --> 21:40.240 You have some, some well logs, if you want to get into kind of the sequestration 21:40.800 --> 21:46.320 portion of it, with the kind of the offering that I have right now, it's 21:46.320 --> 21:50.920 really here, let me take a look at all the emission sources in an area where 21:50.920 --> 21:53.400 the proposed pipelines, what does that look like? 21:53.880 --> 21:57.960 And then what type of scenarios can you build off of that? 21:58.520 --> 22:01.960 And so the, I think the, go ahead. 22:02.120 --> 22:04.240 No, so I'm an operator. 22:04.280 --> 22:10.400 I want to get into sequestration because I just announced this giant carbon 22:10.400 --> 22:13.360 capture plant in the Permian per se. 22:14.400 --> 22:17.840 I con I'm trying to figure out how to logistically make that work. 22:17.880 --> 22:21.120 Once I capture the carbon, that's kind of essentially where you would come in as 22:21.120 --> 22:23.320 far as well, at least on the front end, right? 22:23.320 --> 22:24.760 When you're planning and doing all the logistics. 22:24.760 --> 22:25.000 Okay. 22:25.800 --> 22:32.640 And so is it, is it just, are people looking at, I'm, I'm fairly uneducated 22:32.640 --> 22:35.400 on this in the details. 22:35.400 --> 22:39.640 So I'm curious, is it people looking at using existing pipeline infrastructure? 22:39.640 --> 22:42.560 Are they trying to look at where they can build new pipeline infrastructure? 22:42.560 --> 22:44.960 What's the, all of the above? 22:45.000 --> 22:46.640 I think it's going to be pretty much all of the above. 22:47.480 --> 22:52.760 I think, let's see, Tallgrass in kind of outside of the DJ, they're going 22:52.760 --> 22:54.640 to repurpose an existing one. 22:55.240 --> 22:58.680 There's a couple of conversations happening in the Permian about repurposing 22:58.680 --> 23:02.800 and connecting into some of the existing CO2 pipeline that's already there. 23:02.800 --> 23:05.280 Cause there's thousands of miles already. 23:06.720 --> 23:09.600 It makes so much sense in the Permian just because of the fact that they've 23:09.600 --> 23:14.000 been doing it there forever and all the infrastructure is in place on top of the 23:14.000 --> 23:15.680 fact that it's one of the most prolific fields. 23:15.680 --> 23:17.800 So now you can increase your recoverable. 23:18.560 --> 23:22.080 So I don't think people understand how like oil and gas companies basically 23:22.080 --> 23:23.640 get to double dip on this, right? 23:24.160 --> 23:28.400 We get penalized for the emissions, but then we get the tax credits for pulling 23:28.400 --> 23:29.680 the emissions out of the air. 23:29.880 --> 23:34.000 And then we also get the upside of taking our recoverable reserves from 23:34.000 --> 23:37.520 whatever 20, 30% up to 40 to 50%. 23:38.200 --> 23:42.480 And so it's a, I think, I mean, it's a great idea in my perspective, if you 23:42.480 --> 23:47.640 can figure out the physical logistics, not just physically moving it around, 23:47.640 --> 23:51.080 but also the physics that go into capturing it and powering it and all that stuff. 23:52.440 --> 23:54.160 Some of it's come to mind for me. 23:54.200 --> 23:59.400 I mean, is it the same friction for like new pipelines if they're 23:59.800 --> 24:01.360 allocated towards CO2 as if they're- 24:01.360 --> 24:02.200 That's a good question. 24:02.360 --> 24:03.040 Oh yes. 24:03.120 --> 24:04.880 So yes, no pipelines. 24:04.920 --> 24:05.160 Right. 24:05.160 --> 24:06.720 It's yeah, no pipelines, period. 24:06.720 --> 24:06.960 Yeah. 24:07.080 --> 24:09.040 Well, I didn't know that was the thing because if you can say, well, this is 24:09.040 --> 24:12.000 for CO2 and then like five years online, you know what, this business isn't 24:12.000 --> 24:14.760 working for us, but you know, now we've got a good takeaway for natural gas. 24:14.760 --> 24:16.320 Infrastructure for anything else? 24:16.360 --> 24:16.560 Yeah. 24:17.000 --> 24:21.840 So if you, there's a company called Summit Carbon Solutions, they're running 24:21.840 --> 24:25.320 pipeline, they want to run pipeline through the Midwest all the way up to 24:25.320 --> 24:29.480 North Dakota, where they already have, I think they've already been permitted 24:29.480 --> 24:34.400 for the secret restoration well up there, but they're fighting all types of 24:34.400 --> 24:40.080 battles, counties, states, federal, everything to get all the approval. 24:40.080 --> 24:44.920 I think they have 2,200 miles of pipeline that they want to build. 24:45.240 --> 24:51.880 And it is, you know, it is a, a web of, um, infrastructure connecting ethanol 24:51.880 --> 24:55.640 facilities all the way through, you know, back to the sequestration side. 24:55.680 --> 25:01.400 So huge project and will be awesome if it's, they can get it all done, but they 25:01.400 --> 25:03.880 have a, they have an uphill battle from the community. 25:04.040 --> 25:04.400 Yeah. 25:04.480 --> 25:11.160 Well, I mean, that's, that's something to me that is just so under looked in 25:11.160 --> 25:14.520 the energy space is like, Oh, well, we need more refineries. 25:14.560 --> 25:18.040 Let's say it's going to take five years to do a study to figure out where, where 25:18.040 --> 25:23.120 and how, and all the environmental, all the, you know, NIMBY effect and political 25:23.120 --> 25:25.560 stuff, just to scope it out, right. 25:25.560 --> 25:27.320 And then it's like, and then it's going to take another five years. 25:27.320 --> 25:31.360 Once they do that, if they get the permits and approvals and all that to 25:31.360 --> 25:33.360 build it, and it's going to cost a billion dollars. 25:33.760 --> 25:38.000 And so it's like, people don't realize, you know, the time, effort and scope that 25:38.000 --> 25:40.320 goes in and just like the amount of logistics, right? 25:40.320 --> 25:46.120 Like getting local state and federal for 2200 miles sounds like a complete 25:46.120 --> 25:46.840 nightmare to me. 25:46.840 --> 25:48.040 I'm so glad I don't do that. 25:48.440 --> 25:50.000 Uh, completely, completely. 25:50.080 --> 25:53.440 And so we'll see if that happens, but you know, back to the Permian, there's 25:53.440 --> 25:57.840 this huge kind of wave of carbon capture projects that were announced around 25:57.840 --> 25:59.800 ethanol facilities, mostly in the Midwest. 26:00.080 --> 26:01.840 So that's all kind of moving forward. 26:02.400 --> 26:06.720 I think the Permian and natural gas either I'll say kind of midstream 26:06.720 --> 26:11.280 companies in general are kind of this next wave and there's, they kind of sit 26:11.560 --> 26:15.320 in a perfect situation where they have a lot of gathering facilities. 26:15.480 --> 26:20.560 Some might be, um, have sizable emissions and being able to capture that and then 26:20.600 --> 26:27.680 produce, you know, cleaner natural gas or even just take the credit or, uh, even 26:27.680 --> 26:32.280 better utilize it and go create kind of a sustainable aviation fuel or something 26:32.280 --> 26:32.600 else. 26:33.000 --> 26:36.520 There's some, there's some paths there that could be, uh, be really interesting. 26:36.640 --> 26:36.960 Yeah. 26:37.080 --> 26:41.520 No, I mean, if you could figure out the power source piece on the carbon capture 26:41.520 --> 26:46.600 side, the, you know, you could theoretically have zero in theory. 26:46.680 --> 26:50.480 I've never done the math on this and I won't because it's above my pay grade, 26:50.480 --> 26:56.720 but, uh, you know, you burn it, you capture the CO2 goes into the pipeline, 26:57.120 --> 27:01.120 goes back into the wealth that raises the reservoir pressure and aids in recovery. 27:01.120 --> 27:03.280 And it's just a closed loop system, right? 27:03.280 --> 27:06.800 Like there's potential that, that could exist someday, which is kind of 27:06.800 --> 27:07.400 wild machine. 27:10.560 --> 27:14.360 So to kind of steer it back a little more towards like the data and tech side, 27:14.360 --> 27:20.320 like, so, uh, at DeCarbonFuse, so are you aggregating data from all different kind 27:20.320 --> 27:24.320 of, you know, regulatory bodies on like a lot of public data and everything? 27:24.880 --> 27:30.920 Back to, uh, some of the, um, public information, that's all the EPA emissions 27:30.920 --> 27:34.680 data, essentially, which is, you know, there's a couple of different sources 27:34.680 --> 27:38.840 within the EPA, so we did a couple of things and publicly you can, most of 27:38.840 --> 27:41.400 this is available just, um, on the site, right? 27:41.480 --> 27:45.720 So you can see all the companies in energy and industrial in general, in 27:45.720 --> 27:50.800 those sectors, um, pulling in a lot of the, say sustainability reports. 27:50.800 --> 27:55.120 So what are they, you know, what are they doing from a scope one, scope two, 27:55.120 --> 27:59.800 scope three emissions, and do they have any sustainability targets and then 27:59.800 --> 28:01.720 going one layer down on the facility? 28:01.720 --> 28:03.480 So what type of facilities do they have? 28:04.040 --> 28:08.320 And kind of rated some of those facilities based on, oh, this is, uh, you 28:08.320 --> 28:10.440 know, this, the air quality is good. 28:10.440 --> 28:13.320 It's maybe high compared to others in the industry. 28:14.000 --> 28:18.280 And then really then pulled in all the emissions data for the facility so that 28:18.320 --> 28:23.320 you can basically say, okay, I only care about, um, natural gas facilities 28:23.320 --> 28:28.360 or, uh, fertilizer plants or cement plants or whatever, and I want to see 28:28.360 --> 28:35.080 what's available for CO2 infrastructure, what's available for, um, maybe other 28:35.320 --> 28:39.880 partners, so that's where the screening part comes in, especially with companies 28:39.880 --> 28:42.720 that are looking at, maybe they're only interested in Wyoming, right? 28:42.800 --> 28:47.560 So they can see kind of what that looks like and, um, and basically provide 28:47.560 --> 28:51.120 kind of a single source for kind of all that information. 28:51.440 --> 28:51.680 Okay. 28:51.680 --> 28:54.680 So you, you're just, are you just kind of aggregating all the time or are you 28:54.680 --> 28:57.040 doing it more project based for customers? 28:57.040 --> 29:00.320 And then like what, maybe what kind of tools are you using to get that? 29:00.360 --> 29:02.720 So surprised I'm still Ruby. 29:03.000 --> 29:07.960 So all Ruby on Rails on the kind of the, the website, uh, the scripts are, 29:08.320 --> 29:11.680 there's a couple kind of Python scripts in there. 29:11.720 --> 29:14.760 I'm trying to get like a little bit of Python experience. 29:14.800 --> 29:19.560 Like that's been a little bit of a headache, but this time around, um, I'm 29:19.560 --> 29:24.240 doing a little more of the kind of, I'll say development work myself, um, just to 29:24.240 --> 29:26.600 get familiar with some new information. 29:27.080 --> 29:34.920 And then, um, we're taking, let's see a handful of GIS tools and kind of 29:35.000 --> 29:37.600 relearning some of the kind of Mapbox functionality. 29:37.600 --> 29:43.520 So from the tool perspective, it is, uh, Ruby scripts, a couple of Python scripts 29:43.560 --> 29:51.160 pulling down data from most of it's actually in shape files or CSVs, some kind 29:51.160 --> 29:57.760 of like tab delimited data and then, um, aggregating that and this time around 29:57.760 --> 30:02.960 them using, trying to leverage Mapbox a little more and, and clean up the data 30:02.960 --> 30:05.560 and push it to Mapbox and then just visualize it on the front end. 30:06.440 --> 30:12.440 And so that's been a little bit easier to do, um, versus, uh, where Mapbox was, 30:12.520 --> 30:14.000 you know, when we started in an intergen. 30:14.400 --> 30:16.840 So that's kind of that process. 30:16.840 --> 30:21.000 And that goes, uh, we're basically doing that on a weekly basis. 30:21.040 --> 30:21.320 Okay. 30:21.720 --> 30:25.400 The most frequent, some of that is on a monthly basis. 30:25.440 --> 30:30.000 And then there's some of the, um, some of the EPA data is only updated once a year. 30:30.240 --> 30:32.200 So I kind of have to balance that out a little bit. 30:32.440 --> 30:37.320 And like the GIS data is, are you, are you winning that in like a Mongo 30:37.320 --> 30:38.680 or do you have like a QGIS? 30:38.680 --> 30:40.760 So I was going to ask you what DB you're on the. 30:41.160 --> 30:45.280 So this is where I've been getting some help on the QGIS side. 30:45.320 --> 30:45.560 Okay. 30:45.600 --> 30:51.000 If you kind of normalize some of it, um, can do some real simple kind of, um, 30:51.520 --> 30:53.320 aggregating there as well, right. 30:53.760 --> 30:56.520 Uh, before getting into getting into Mapbox. 30:56.600 --> 31:02.960 Um, and then what else on the, I'm thinking more on the kind of the 31:02.960 --> 31:04.720 data and the integration piece. 31:05.160 --> 31:10.120 So we're basically doing all of that locally now, most of it locally. 31:10.120 --> 31:15.120 There's some that's being hosted, uh, kind of just AWS S3. 31:15.160 --> 31:19.760 So pulling it down, I have the raw data available, keeping it as is, and 31:19.760 --> 31:25.360 then processing it, so kind of our ETL layers a little bit local, 31:25.360 --> 31:26.320 a little bit in the cloud. 31:26.320 --> 31:26.520 Yeah. 31:26.920 --> 31:33.800 Um, and then, uh, keeping kind of keeping all that together so I can move it into, 31:34.520 --> 31:39.280 move it into Mapbox and then eventually we'll have some of the announced projects. 31:39.280 --> 31:43.760 Um, so right now we're just focused on North America, but, uh, the announced 31:43.760 --> 31:48.280 projects are then in a Postgres database, which is updated essentially on, uh, 31:49.200 --> 31:54.160 uh, monitoring the news and announcements on a daily basis and then kind of confirm 31:54.160 --> 31:55.400 everything on a weekly basis. 31:55.440 --> 31:55.680 Okay. 31:56.080 --> 31:56.240 Yeah. 31:56.280 --> 31:57.080 So can you speak to that? 31:57.120 --> 32:00.800 Like, cause I'm assuming, I know a lot of people in the energy space are 32:00.800 --> 32:05.560 very familiar with Esri, like ArcGIS can speak about QGIS and benefits to it. 32:06.080 --> 32:12.440 Uh, only, I mean, I am a novice user on the, on the GIS side, but I think one 32:12.440 --> 32:18.120 thing that, that I can do very quickly is pull in shape files, do some editing, 32:18.160 --> 32:21.760 do some, um, kind of rationalizing of the data. 32:21.760 --> 32:26.360 So especially thinking of, you know, the, there's a lot of functionality. 32:26.400 --> 32:31.120 If you open up Esri as a first time user or even kind of, you know, intermediate, 32:31.200 --> 32:37.480 yeah, you're probably going into, you know, specific functions or specific 32:37.480 --> 32:40.400 things you do kind of every time, or maybe use some of the workflow tools. 32:40.920 --> 32:48.120 Um, but with, um, QGIS, basically I'm using it as here a little bit of data 32:48.120 --> 32:52.720 quality side, and then I also have another who I'd consider more kind of 32:52.760 --> 32:58.000 intermediate to advanced person that I know once I'm getting into some of the 32:58.000 --> 33:03.200 shape files, some of the different formats that then, uh, can get some 33:03.200 --> 33:05.520 help on visualization within GIS. 33:05.520 --> 33:06.440 And I passed that off. 33:06.960 --> 33:13.840 Um, but for me is kind of a, I'll say even beginner user, it's a, it's a simple 33:13.840 --> 33:17.360 way to kind of get access to the information you need and get it on a map. 33:17.560 --> 33:17.880 Yeah. 33:17.960 --> 33:19.400 And it's open source, right? 33:19.480 --> 33:23.400 Open source and free and, you know, runs on the Mac and like, I'm good. 33:23.640 --> 33:26.200 Yeah, no, I think it's important for people to understand. 33:26.200 --> 33:29.120 Cause I, again, you've, you just walk right into an operator your whole life 33:29.120 --> 33:31.960 and you just, oh, as we, but then you don't realize how much your company's 33:31.960 --> 33:32.800 paying for that license. 33:32.800 --> 33:35.920 And even having for us, you know, we have Esri, but we've actually got a 33:35.920 --> 33:39.360 couple of people engineered and stuff that, you know, know how to use QGIS and 33:39.360 --> 33:41.240 they can pull it in and do what they need to do. 33:41.240 --> 33:43.800 And we don't have to pay for another license of Esri, you know, to do 33:43.800 --> 33:44.880 those simple kind of things. 33:44.880 --> 33:45.280 Yes. 33:45.400 --> 33:46.040 Oh, exactly. 33:46.600 --> 33:50.880 And like, I still use some of the, um, Esri map kind of web services. 33:51.000 --> 33:55.840 Um, so still plug into a couple of those, but no, on a, I'd say on a, on a 33:55.840 --> 33:59.440 routine basis, it's all kind of, um, QGIS. 33:59.480 --> 34:02.760 And have you all looked at it or done anything with how to, or needed to do 34:02.760 --> 34:04.800 anything with say the, is Postgres just kind of a serving layer? 34:04.800 --> 34:07.600 Cause I know Postgres has PostGIS too, which is pretty powerful. 34:07.640 --> 34:07.920 Yeah. 34:07.920 --> 34:10.560 And I haven't used any of the PostGIS stuff yet. 34:10.680 --> 34:15.920 Um, I know, um, for a couple of people have recommended for building out kind 34:15.920 --> 34:19.360 of the scenarios and heat maps and different things, you can do some really 34:19.360 --> 34:24.080 kind of interesting things on the fly with, um, PostGIS, but I haven't done any 34:24.080 --> 34:26.880 of that right now, kind of that visualization piece I've, I've pushed 34:26.880 --> 34:30.440 in the map box and kind of recreated some of the analysis with new layers. 34:30.480 --> 34:30.720 Yeah. 34:30.880 --> 34:31.400 Effectively. 34:31.480 --> 34:31.720 Yeah. 34:31.960 --> 34:35.520 Um, I'm just being an R guy cause it's like, you know, we're here to nerd out 34:35.520 --> 34:39.480 on data and have you used any of the GIS stuff within R like the SF and all that? 34:39.520 --> 34:40.000 Yes. 34:40.040 --> 34:40.360 Yeah. 34:40.400 --> 34:45.400 Although I have a little bit of a hard time with, um, some of the more complex 34:45.400 --> 34:50.560 maps, I mean, I shouldn't say anything over kind of three or four layers and 34:50.800 --> 34:54.880 dealing with the scales within, um, within our feel like that breaks down a little 34:54.880 --> 34:59.920 bit, but, um, but overall, like there's some basic maps that I think that have 34:59.920 --> 35:04.200 been really good and like kind of who's doing what for primacy, for example, that 35:04.200 --> 35:10.000 was kind of nice, easy one to create an R and you know, simple there, um, being 35:10.000 --> 35:11.480 able to get points on the map. 35:11.720 --> 35:12.160 Yeah. 35:12.280 --> 35:17.720 So I mean, as a, as someone who's used Mapbox in a number of places for a 35:17.720 --> 35:21.160 number of reasons, I completely agree with you there. 35:21.160 --> 35:26.840 It's like, there's so many, especially with like the GIS and ArcGIS, uh, just 35:26.840 --> 35:31.040 like, Hey, there's this free thing over here or, you know, close to free of your 35:31.360 --> 35:36.640 beta prototyping stuff where it's like, Hey, you can go try this out very easily. 35:36.920 --> 35:38.200 Copy and paste API key. 35:38.200 --> 35:42.600 Now you have a Mapbox plot in your Power BI instance or in your website that you 35:42.600 --> 35:44.040 can just embed, right? 35:44.040 --> 35:47.600 It's a very, I think there's, there's, that's one of the reasons I wanted to do 35:47.600 --> 35:51.160 this podcast is because there's all these tools out there that everyone uses 35:51.160 --> 35:53.000 that it's like, Oh, I didn't know about that. 35:53.000 --> 35:54.240 And that's really nice. 35:54.240 --> 35:54.440 Right. 35:55.240 --> 36:02.000 But what, uh, what kind of, let me back up. 36:02.400 --> 36:06.760 What, I want to talk a little bit more about your satellite experience. 36:06.760 --> 36:09.560 Cause I think that's fascinating. 36:09.720 --> 36:15.000 Yeah, it's fascinating by itself, hard stop, but then also the industry is 36:15.000 --> 36:18.520 starting to use it more and more for a lot of really interesting things. 36:18.520 --> 36:22.240 I mean, there's a number of companies, Josh Adler's company. 36:22.920 --> 36:23.680 They changed their name. 36:23.680 --> 36:24.400 It was Sourcewater. 36:24.400 --> 36:25.240 It was Sourcewater. 36:25.240 --> 36:29.760 And I'm sorry that I'm forgetting the new name, but like, that's built off of that. 36:29.760 --> 36:29.960 Right. 36:29.960 --> 36:31.320 Like a lot of their stuff. 36:32.600 --> 36:33.360 Yeah, there's a lot of stuff. 36:33.360 --> 36:34.960 So talk a little bit more about that. 36:34.960 --> 36:37.880 Like, how do you, what are the limitations of it? 36:38.320 --> 36:42.560 How do you see it really making an impact on the industry now and 36:42.560 --> 36:43.960 moving kind of in the future? 36:44.560 --> 36:53.120 I think one of the, one thing that we saw that was incredible was the acceleration 36:53.160 --> 36:59.560 of the number of satellites that were covering the globe in between 20, call 36:59.560 --> 37:06.680 it 2017, when we were acquired to, you know, 20, 21, and even now, right? 37:07.040 --> 37:08.600 The number of satellites is crazy. 37:08.640 --> 37:08.800 Yeah. 37:08.800 --> 37:12.920 Walk people through just taking a step back, like, okay, what, what do we mean 37:12.920 --> 37:13.760 by satellite data? 37:13.800 --> 37:15.520 How is like, what does that look like? 37:15.560 --> 37:17.120 Who are you getting it from? 37:17.120 --> 37:18.920 How often, all of that kind of stuff. 37:19.440 --> 37:28.080 So there's a couple, I'll say open source, satellite ready kind of analysis 37:28.080 --> 37:31.520 ready, imagery companies out there. 37:31.640 --> 37:40.520 And so you have kind of Landsat would be one that would be, you get certain 37:40.520 --> 37:46.120 coverage, I think on a month, it's been a little while, but it's around a month 37:46.760 --> 37:52.520 type of view of probably 10 to 30 meter resolution. 37:52.520 --> 37:53.680 And this is where it's a, right. 37:53.680 --> 37:59.880 When you start getting into the, the frequency and the resolution is what's 37:59.920 --> 38:02.120 so important and that's where the cost is. 38:02.160 --> 38:08.880 But we ended up using, because there's a couple of different providers, right? 38:09.040 --> 38:09.240 Yeah. 38:09.320 --> 38:09.880 Who are they? 38:10.360 --> 38:15.680 So Sentinel is some of the data that you can acquire that has several 38:15.680 --> 38:17.200 different layers to it, right? 38:17.200 --> 38:23.440 So you could get the typical kind of RGB, which is your visualization or what 38:23.440 --> 38:26.160 you would probably see in most applications. 38:26.560 --> 38:30.560 Then they have some vegetation layers that kind of pre-built almost. 38:31.040 --> 38:34.640 And they also had some layers that were pre-built around 38:34.920 --> 38:36.440 detecting moisture and water. 38:37.080 --> 38:40.600 So those, we've got Sentinel-5P, which is the methane one, right? 38:40.640 --> 38:41.560 Methane, yes. 38:41.560 --> 38:42.480 So that's coming. 38:42.560 --> 38:46.400 And I know there's a couple of companies that are trying to, to use that as well. 38:47.040 --> 38:53.080 I think the, where we started was a concept of can we see, you know, 38:53.840 --> 38:55.880 that was very futuristic five years ago, right? 38:55.880 --> 38:58.160 Like that was like, can we see permits? 38:58.200 --> 39:01.200 It's like, can I detect pads before the permit is there? 39:01.360 --> 39:06.640 We knew, we knew for a fact there were companies that were developing and 39:06.680 --> 39:13.240 clearing the pads before, before any notification or regulatory report was 39:13.240 --> 39:14.560 out, right, knew that for a fact. 39:14.560 --> 39:18.080 And we knew we could kind of try and identify those visually. 39:18.080 --> 39:20.720 It's like, okay, this would be, that would be stellar. 39:20.720 --> 39:23.400 And then you start going down that kind of value chain and it's like, oh, well, 39:23.520 --> 39:26.480 if I can confirm the rig onsite, right? 39:26.520 --> 39:33.480 If I can confirm the frac crew and looking at the frac activity and then even 39:33.480 --> 39:39.000 afterwards, can I tell when the frac, you know, when the frac crew leaves and maybe 39:39.000 --> 39:45.240 there's flow back, maybe you can tell something's happening, but when, when, 39:45.480 --> 39:47.080 when we'll actually get to production. 39:47.600 --> 39:53.160 And so that kind of value stream or kind of chain of events, I would say, we tried 39:53.160 --> 39:59.120 to automate pieces of that and really be, begin detecting kind of the permit side. 39:59.560 --> 40:03.560 So this is, this is a funny thing where I think there were a lot of companies 40:03.640 --> 40:06.840 talking about this at the same time and doing different things. 40:07.360 --> 40:13.240 And you should look at some of the like, and Boyd and I sat down one day and 40:13.240 --> 40:16.880 started kind of making up stuff about, well, like what, what if we could detect 40:16.880 --> 40:21.960 kind of the, the permit date beforehand and, you know, the drilling dates and 40:22.160 --> 40:25.840 rig dates and frac dates and everything else, and started kind of putting a 40:25.840 --> 40:26.600 process to it. 40:27.160 --> 40:34.720 And so we set out, of course, started with the Permian and he was able to do 40:34.720 --> 40:41.760 some pretty good, I'll say machine learning around detecting the imagery, 40:41.800 --> 40:47.160 processing the imagery, looking at certain areas and being able to see at 40:47.160 --> 40:49.520 least, okay, here's a pad, here's what it looks like. 40:50.040 --> 40:56.960 And then built a whole kind of processing slide to this that we would essentially 40:56.960 --> 41:03.240 download the images, only the ones that we needed, and then do some automated 41:03.240 --> 41:09.120 work upfront, but then it became a manual effort and we ended up using some of our 41:09.120 --> 41:13.120 analysts to basically detect, detect kind of what the rig looks like, what the 41:13.120 --> 41:14.560 frac crew looks like, and so forth. 41:14.720 --> 41:17.800 Did you use them to train a model as you went? 41:17.840 --> 41:18.160 Yep. 41:19.080 --> 41:20.600 It's probably serving two purposes. 41:20.600 --> 41:24.440 Like you're augmenting it, you know, for your customers, but then also then you 41:24.440 --> 41:26.600 can take what they've kind of confirmed. 41:26.600 --> 41:31.600 And when we were able to kind of scale that from the Permian to Eagleford to 41:31.600 --> 41:39.480 Haynesville to Bakken, and I think the DJ, and I don't think, I'm trying to 41:39.480 --> 41:46.920 think if we ever got to Guahoma and majority, we covered majority of the 41:47.280 --> 41:50.920 cell basins, but one of the things that we saw early on was it wasn't frequent 41:50.920 --> 41:51.360 enough, right? 41:51.360 --> 41:52.960 There was not enough imagery. 41:53.560 --> 41:59.760 And then all of a sudden kind of year in, we moved from once per like 10 days to 41:59.760 --> 42:05.040 once every two days, three days, and sometimes daily, which that was, that was 42:05.040 --> 42:05.520 huge. 42:05.520 --> 42:05.680 Yeah. 42:06.520 --> 42:07.920 Well, but then that comes with a cost, right? 42:07.920 --> 42:11.920 Like, so that's my next question for you is for people that are looking at or 42:11.920 --> 42:16.160 interested in satellite data, kind of talk about, you know, the knobs that you 42:16.160 --> 42:18.280 can turn from the different providers, right? 42:18.280 --> 42:22.640 Cause if my understanding is it boils down to basically resolution and 42:22.640 --> 42:23.800 frequency, right? 42:23.960 --> 42:24.440 Exactly. 42:24.480 --> 42:28.480 So if you, if you're looking for something like a pad being built that can be done 42:28.480 --> 42:33.000 in a short period or a rig moving on location or whatever, you need much 42:33.000 --> 42:37.400 higher frequency data than, you know, if you're monitoring the completion of a 42:37.560 --> 42:39.840 refinery or something like that, it's going to take years. 42:40.000 --> 42:40.520 Yes. 42:40.600 --> 42:40.800 Yeah. 42:40.880 --> 42:45.600 And so seeing the resolution, you know, there's obviously what's available 42:45.600 --> 42:50.680 publicly, which is what 10 meter and then goes all the way down to what I've 42:50.680 --> 42:55.320 seen, I think is three centimeter resolution, which you can basically see 42:55.320 --> 42:56.440 the logo on the side of the truck. 42:56.600 --> 42:56.760 Yeah. 42:56.760 --> 42:58.560 Like it's amazing. 42:58.640 --> 43:01.560 Um, also super expensive, right? 43:01.560 --> 43:06.240 And so we ended up, uh, talking to a handful of companies that were already 43:06.360 --> 43:12.240 like in that space, I think what, what we saw is a lot of the imagery providers 43:12.280 --> 43:17.760 wanted to become, wanted to deliver some of the analytics and wanted to be the 43:17.760 --> 43:22.680 source for that, but didn't really understand the nuances between, you know, 43:22.720 --> 43:27.600 a, well, that's actually a frat group, maybe, but it's just trucks parked. 43:27.960 --> 43:28.240 Yeah. 43:28.560 --> 43:29.480 That's staging ground. 43:29.480 --> 43:34.760 Like, so we, we had some, um, we're able to kind of combine some information that 43:34.920 --> 43:40.520 others weren't or actually others weren't doing at the time, but just buying the 43:40.520 --> 43:45.400 satellite imagery, we went and got quotes from everyone to do the Permian. 43:45.440 --> 43:47.120 And it was ridiculous. 43:47.360 --> 43:51.440 You know, this is obviously it's the pricing has come down, but at the time it 43:51.440 --> 43:55.240 was, you know, several million just to do the Permian and then just consider 43:55.320 --> 43:56.920 what's going to cost me to put a satellite in orbit. 43:57.000 --> 43:57.280 Yeah. 43:57.520 --> 43:58.160 Yeah, exactly. 43:58.480 --> 44:02.960 Which is, I think what some of the, uh, you know, companies are doing now, but 44:02.960 --> 44:06.480 it's like, wow, that's a, yeah, that's taken it to another level. 44:06.600 --> 44:11.400 Um, and, um, so yeah, we saw the, we saw the value in it. 44:11.400 --> 44:13.800 We could, we could produce some insights from it. 44:14.400 --> 44:17.960 We could see kind of the, the pad detection and some of that kind of work 44:17.960 --> 44:23.880 come in, um, but really the, I would say the true value of, of what we were 44:23.880 --> 44:27.960 producing was then all the way down the value stream of saying, okay, here's 44:27.960 --> 44:34.120 a frat, frat crew, we can say, here's a frat crew that's consuming, call it, you 44:34.120 --> 44:40.840 know, what, 2,500 tons a month type of deal and then forecast out what the 44:40.840 --> 44:46.640 activity, um, would be based on that frat crew and then even further down the road. 44:47.120 --> 44:51.840 Um, can you, can you say that well is going to come online and be producing, 44:52.280 --> 44:55.800 um, with, with better, more granular information kind of. 44:56.400 --> 44:58.200 I was trying to get university lands on that. 44:59.080 --> 44:59.360 Yeah. 44:59.640 --> 44:59.960 Yeah. 45:00.880 --> 45:03.640 I mean, cause I mean, you know, just like you're saying from the people doing work 45:03.640 --> 45:07.280 on the land before, you know, they're permitted to, I mean, would, 45:07.280 --> 45:08.000 would have been a big deal. 45:08.520 --> 45:08.920 Oh yeah. 45:08.960 --> 45:09.200 Yeah. 45:09.320 --> 45:10.560 And just also knowing, right. 45:10.960 --> 45:16.200 Cause again, you know, you got the, say the invariant, the rig data stuff, you 45:16.200 --> 45:19.400 know, but the drilling does not mean production, you know, you know, you've 45:19.400 --> 45:21.040 got ducks now for a year or two years. 45:21.040 --> 45:24.480 I mean, like, when someone's tracking, you know, like I should expect, you 45:24.480 --> 45:29.200 know, um, you know, money coming in the door within, you know, a month or 45:29.200 --> 45:30.720 so, you know, like give or take. 45:30.720 --> 45:36.160 So even, even back then we were, we wanted to be able to buy based on 45:36.160 --> 45:38.040 smaller kind of smaller areas. 45:38.040 --> 45:38.280 Right. 45:38.560 --> 45:42.760 And I think there's, I know there's a startup now out of, I think out of Austin 45:42.760 --> 45:47.480 or maybe Denver Albedo that is doing smaller areas and they're like, they're 45:47.480 --> 45:49.240 focused on the commercial side. 45:49.640 --> 45:53.360 And I think that's like, I think that could be a winner because serve me the 45:53.360 --> 45:57.360 data that I need also don't try and build the analytics on top of it because I 45:57.360 --> 46:01.560 have a very custom nuance app use case or application for it. 46:01.560 --> 46:03.160 Yeah, just keep that data. 46:03.400 --> 46:04.800 Now that's, that's interesting. 46:04.920 --> 46:11.040 What will someone roll your machine learning comments from that into the 46:11.040 --> 46:19.480 next question, which is what, you know, how do you see ML, AI, GPTs of the 46:19.480 --> 46:24.320 world playing into the, you know, the energy space today and in the future? 46:24.320 --> 46:26.640 Like, where do you see that being kind of the most impactful? 46:27.120 --> 46:33.160 We can, we can just pick, we can pick GPT or insert your favorite ML kind of 46:33.160 --> 46:35.200 tool or platform just to narrow it down. 46:35.200 --> 46:40.960 But yeah, no, uh, I mean, everyone seems to be talking about GPT so I'll start 46:40.960 --> 46:42.240 with that and then we can work backwards. 46:42.280 --> 46:48.960 But, um, there's so many interesting little use cases that are probably being 46:49.000 --> 46:56.360 tested and piloted right now on, um, and with, uh, chat GPT that I think you 46:56.360 --> 47:03.520 could, if you can get back, if you can get by some of the privacy concerns, um, 47:03.560 --> 47:08.600 I'll put that to the side, but just some of the use cases, um, like, like being 47:08.600 --> 47:13.680 able to pull in, um, drilling docs and answer questions around kind of the 47:13.680 --> 47:18.480 drilling process without having access to WellView or without having access to 47:18.480 --> 47:20.120 whatever drilling tool you're using. 47:20.440 --> 47:25.560 I think that is a unique, um, kind of, uh, kind of deal. 47:25.600 --> 47:31.400 And then especially, um, talk to a company this week that is really developed a 47:31.400 --> 47:37.400 lot of, I'll say kind of AI toolbox, if you will, uh, targeted oil and gas, maybe 47:37.400 --> 47:40.480 some healthcare, and they're just doing data discovery, right? 47:40.520 --> 47:43.080 So where, what do I have? 47:43.120 --> 47:43.400 Right. 47:43.480 --> 47:45.280 What do I, you know, what do I need? 47:45.400 --> 47:47.520 And then can I monetize any of that? 47:47.920 --> 47:52.120 You know, can I go sell some old kind of well information or logs or, you 47:52.120 --> 47:53.600 know, defects or whatever? 47:53.600 --> 47:54.400 Do I even have it? 47:54.560 --> 47:54.840 Yes. 47:55.560 --> 47:55.920 Yeah. 47:56.240 --> 48:00.240 And so seeing that kind of that data discovery angle, um, I think there's 48:00.240 --> 48:05.080 been so much talk about kind of data as an asset within, within oil and gas, but 48:05.520 --> 48:11.840 it is, um, it's hard to do and, and you have so many different source kind of 48:11.840 --> 48:14.360 projects and different kinds of workflows that are needed. 48:14.840 --> 48:21.680 Um, but the AI side, I think if there's an, what I like about, um, chat GPT and 48:21.680 --> 48:24.960 open AI is basically the API component to it. 48:25.280 --> 48:29.400 So if I can use your kind of intelligence, combine it with my own 48:29.400 --> 48:34.400 data and I can keep the data on my little vector database or whatever type 48:34.400 --> 48:37.440 of database, then I think that could be fascinating. 48:37.560 --> 48:38.040 Absolutely. 48:38.080 --> 48:38.320 Yeah. 48:38.360 --> 48:40.280 Do you all have any kind of discovery? 48:40.280 --> 48:44.480 You have some kind of discoverability engine or something on your platform? 48:44.480 --> 48:44.680 Yeah. 48:44.880 --> 48:49.920 A little bit, but not, not something you could kind of plug into, uh, yeah, not, 48:50.080 --> 48:56.000 not yet plugging into scanning, I would say kind of scanning, um, uh, sources 48:56.000 --> 49:02.160 and, and crawling different things, but internally I could see somebody creating 49:02.160 --> 49:06.160 something and then pulling that into their own little database to then say, 49:06.200 --> 49:08.440 Oh, here, this is what I need. 49:08.800 --> 49:10.280 I don't want to pay for this data again. 49:10.800 --> 49:12.560 Um, or I want to sell some information. 49:12.920 --> 49:13.640 Oh, that's perfect. 49:13.760 --> 49:14.080 Yeah. 49:14.240 --> 49:17.920 Well, I mean, like even just, I say it's a basic use case. 49:17.920 --> 49:20.600 It's not a basic use case, but like discoverability, right? 49:20.600 --> 49:24.560 Like whether it's within a company of your own documents or on a, on 49:24.560 --> 49:26.840 Reddit or on a mess, like whatever, right? 49:26.840 --> 49:31.040 Like discoverability historically has been a very hard problem that, you know, 49:31.240 --> 49:37.000 all the social media companies have figured out ways to, to, I guess you 49:37.000 --> 49:40.920 could say solve, but their real intention is just your keeping your time, 49:40.920 --> 49:42.760 not necessarily what you care about. 49:42.920 --> 49:43.120 Yeah. 49:43.240 --> 49:45.880 Um, but I mean, that's a big thing, right? 49:45.880 --> 49:49.400 Like even with when you're talking about the evolution of the internet, right? 49:49.400 --> 49:53.600 Like we went from forums or chat to forums and now we, I mean, we're still 49:53.600 --> 49:57.600 using forums because Reddit is still huge, but even in that, in that, like 49:57.600 --> 50:01.680 the discoverability part of it is such a key component, right? 50:01.680 --> 50:05.520 Because you want to serve the person that is using it exactly what they want. 50:05.520 --> 50:10.720 But if it's not the old way of having to tag, you know, put in tags or hashtags 50:10.720 --> 50:12.560 is basically the modern version of that now, right? 50:13.160 --> 50:16.640 But being able to do that with AI in the future, where it's just like, it just 50:16.640 --> 50:21.000 knows, it knows everything that's in there so it can find all of the 50:21.000 --> 50:23.280 missing pieces for you is pretty crazy. 50:23.320 --> 50:23.440 Yeah. 50:23.440 --> 50:26.240 I mean, I think someone saw someone talking about just how it's really 50:26.240 --> 50:28.560 going to stir up like the elastic searches and some of those are real too. 50:28.560 --> 50:31.760 Like if they haven't bought into this, I mean, like it's going to wipe them out. 50:32.360 --> 50:36.640 Cause now you can just run these LLMs like on, you know, internal things and 50:36.640 --> 50:39.360 it's going to be so much more powerful and better than, you know, what people 50:39.360 --> 50:41.280 were already using those tools for. 50:41.280 --> 50:41.600 For sure. 50:42.440 --> 50:44.120 We've got like five more minutes. 50:45.840 --> 50:47.120 Just jump into the speed round. 50:47.640 --> 50:48.400 You can expand on. 50:48.400 --> 50:49.320 Let's do one. 50:49.560 --> 50:53.840 What's one piece of advice you'd give people either getting into the energy 50:53.840 --> 50:57.920 tech space or that are, are new to it. 50:58.440 --> 51:01.320 That I'm new to it. 51:01.400 --> 51:03.840 Um, yeah, don't do free pilots. 51:05.000 --> 51:08.480 No, that's a free pilot. 51:08.560 --> 51:10.840 Well, you say that, but I mean, I think it's also controversial. 51:10.840 --> 51:13.280 I mean, like there's plenty of people, I think that see the other way too. 51:13.280 --> 51:17.800 So, yes, yeah, says the guy, says the guy at the operator. 51:17.800 --> 51:18.720 I just want to point that out. 51:18.760 --> 51:22.480 No, no, I'm talking, I'm like, I know somebody's on the software side that 51:22.880 --> 51:27.040 or on their side having decent luck with it, but at the same time, definitely 51:27.040 --> 51:27.840 want to hear your thoughts on it. 51:28.040 --> 51:28.240 Yeah. 51:28.280 --> 51:28.520 Yeah. 51:28.520 --> 51:33.600 So, um, I've just seen so many companies get stuck in this pilot mode. 51:33.680 --> 51:33.920 Yeah. 51:34.160 --> 51:37.720 And if you don't have a way to monetize that, then you're, you know, you're 51:37.720 --> 51:39.040 running your. 51:39.760 --> 51:40.320 Takes resources. 51:40.320 --> 51:43.600 So you're just running your opportunity kind of into the ground. 51:43.600 --> 51:45.320 So you're just burning that cash, right? 51:45.320 --> 51:51.840 There's so many, um, there's so many, I would say smart and unique things that 51:51.840 --> 51:57.440 you can do within, um, within oil and gas and especially oil field that will 51:58.360 --> 51:59.840 pay for solutions. 52:00.120 --> 52:05.600 So find that, find that willingness to pay and then move, move that direction. 52:05.840 --> 52:10.440 So go, go work for the smaller operator that's willing to pay for the pilot 52:10.440 --> 52:17.160 instead of going to work for the big, uh, NLC or IOC that, yeah, it's going to 52:17.160 --> 52:20.400 take three years and lots of time and handholding. 52:20.600 --> 52:20.880 Yes. 52:21.240 --> 52:21.360 Yeah. 52:21.360 --> 52:22.840 Those sales cycles are very slow. 52:23.080 --> 52:26.920 That's, that's still one of the biggest misconceptions of that. 52:26.920 --> 52:31.200 I see software companies coming from outside of the industry into the industry. 52:31.400 --> 52:34.160 Like, well, if we can get shell, we're a billion dollar company. 52:34.160 --> 52:38.840 It's like, it's going to take you three years and a long time if you get in 52:39.080 --> 52:43.320 lots of gatekeeping, lots of interviews, lots of hoop jumping, all of the 52:43.320 --> 52:48.000 insurance, all of the documentation, all of the security, like, or you could go 52:48.000 --> 52:51.440 talk to a smaller operator that doesn't have all that stuff that is also willing 52:51.440 --> 52:55.800 to potentially pay for it because they're not going to be able to duplicate it 52:55.800 --> 52:58.400 themselves, another big risk that you have. 52:58.440 --> 53:01.360 But all right, Bobby, let's, let's do the speed round. 53:01.760 --> 53:02.040 Yeah. 53:02.080 --> 53:06.160 So, um, what's, uh, your favorite cloud that you've used? 53:07.080 --> 53:07.920 Favorite cloud. 53:08.160 --> 53:13.960 I think just some of the simplicity of AWS and S3, I still use it today. 53:13.960 --> 53:14.880 I've been using it forever. 53:14.880 --> 53:16.400 It's like, it's just easy. 53:16.520 --> 53:17.080 Yeah. 53:17.320 --> 53:21.360 I mean, S3 is probably the, one of the best cloud offerings that there's been 53:21.360 --> 53:22.880 in it, it's to the test of time. 53:23.240 --> 53:24.280 I probably have three accounts. 53:24.280 --> 53:26.440 I'm still getting billed, but it's like a dollar 25. 53:26.440 --> 53:28.800 Oh yeah, no, I've got to, I don't even know what that is. 53:28.800 --> 53:30.200 That could be something, I don't even know. 53:30.280 --> 53:31.640 Yeah, that's not something I'm saying. 53:31.680 --> 53:33.880 Um, let's go down. 53:33.880 --> 53:35.560 What's your favorite managed service? 53:35.560 --> 53:37.080 I mean, you mentioned Heroku previously. 53:38.160 --> 53:43.320 Yeah, I mean, I've, uh, I've just been using Heroku for so long. 53:43.320 --> 53:48.200 I would say that's probably still the one, um, there's several coming out 53:48.200 --> 53:51.440 that I'm kind of watching kind of more on the, on the rail side. 53:51.520 --> 53:56.120 And then I still think there's this little gap with some of the, um, R and R 53:56.160 --> 53:57.320 studio stuff. 53:57.320 --> 54:01.880 That's kind of fascinating for kind of deploying, um, you know, deploying 54:01.880 --> 54:03.960 some dashboards and different things like that. 54:04.040 --> 54:04.760 I just don't know if they're 54:04.760 --> 54:08.520 shiny, sir, or the, you know, like, yeah, some of that hasn't been great, but 54:08.640 --> 54:12.200 yeah, that didn't work out so well, but I'm still kind of keeping an eye on 54:12.200 --> 54:15.160 that to see what else, what else you can do there, Freddie Drennan. 54:15.160 --> 54:17.360 I don't know if you follow him on LinkedIn or not, but he's got some 54:17.360 --> 54:19.840 like indexer thing where it's supposed to be really helped like push your 54:19.840 --> 54:22.040 R projects up to the cloud, the cloud. 54:22.120 --> 54:22.440 Yeah. 54:23.000 --> 54:25.000 Um, about security. 54:26.960 --> 54:27.760 Oh man. 54:28.480 --> 54:30.120 Well, um, security tool. 54:30.520 --> 54:33.760 This was written by someone who has never dealt with IT security 54:33.840 --> 54:34.720 in his entire life. 54:34.720 --> 54:38.280 So you don't have to answer that because I just threw that on there because 54:38.280 --> 54:41.760 I was like, ah, maybe I don't even, I don't even know it like, uh, I guess 54:41.760 --> 54:43.440 last, I don't know. 54:43.560 --> 54:43.840 Yeah. 54:43.840 --> 54:44.200 Yeah. 54:44.840 --> 54:47.400 Like, um, yeah, I would be like some like off zero that 54:47.400 --> 54:51.000 makes authentication easier, but let's do visualization tool. 54:52.000 --> 54:52.520 Oh yeah. 54:52.600 --> 54:58.760 I definitely go with R and then I still go back to, uh, some of the, I guess 54:58.760 --> 55:03.680 JavaScript JavaScript components like, um, D three to do some kind of unique 55:03.680 --> 55:04.240 things. 55:04.320 --> 55:11.760 Um, I think that's, well, that's what libraries and R DG plot, uh, GD 55:11.760 --> 55:14.880 plots, doing a little more with SF for sure. 55:15.120 --> 55:17.760 And then now I'm gonna have to come at speed on kind of the tidy 55:17.760 --> 55:19.040 verse piece of that as well. 55:19.600 --> 55:23.840 No, I mean, GD plots, but pretty core component, but I mean, one that if 55:23.840 --> 55:28.200 you're talking about the D three and you'd like GD plot is plotly and then, 55:28.360 --> 55:29.960 uh, cause they have GD plotly. 55:29.960 --> 55:30.840 So it was basically a wrapper. 55:30.840 --> 55:34.640 So you just wrap that around your GD plot code and it makes it interactive. 55:34.920 --> 55:35.080 Yeah. 55:35.080 --> 55:38.360 That would be fantastic. 55:38.480 --> 55:42.320 I haven't used plotly in a long, I remember seeing it when, um, we would do 55:42.320 --> 55:45.840 some kind of visualizations, but I haven't, I've haven't personally used it. 55:45.840 --> 55:46.160 Yeah. 55:46.360 --> 55:49.000 But I mean, if you're using any R, like, I mean, literally it's just simply 55:49.240 --> 55:51.600 just, you know, install the plotly library, but then like they have the 55:51.600 --> 55:55.800 GD plotly calling, just wrap your GD plot in GD plotly and it makes it 55:55.960 --> 55:59.320 interactive and it brings in all the same formatting and yeah, the 55:59.320 --> 56:03.280 formatting piece is like, it keeps it like your GD plot formatting, however 56:03.280 --> 56:06.160 you've made it, but then it makes those pieces interactive and markable 56:06.160 --> 56:06.800 and all that kind of stuff. 56:06.880 --> 56:07.120 Cool. 56:07.480 --> 56:11.960 This is why I love coding because it's like, Hey, you used to have to do all 56:11.960 --> 56:15.040 these really hard, monotonous, boring things and another wrap. 56:15.680 --> 56:16.920 Polly's built on top of D3. 56:16.920 --> 56:17.560 So, okay. 56:20.560 --> 56:20.960 Awesome. 56:21.040 --> 56:22.040 Um, one more. 56:22.560 --> 56:22.720 Yeah. 56:22.720 --> 56:23.040 One more. 56:23.040 --> 56:23.600 Let's go. 56:25.360 --> 56:28.520 What's the most interesting, like emerging bleeding edge tech 56:28.520 --> 56:29.360 that you're excited about? 56:30.560 --> 56:34.440 I'm trying to wrap my head around all the, I mentioned a little bit, all 56:34.440 --> 56:38.800 the new vector databases and that's just fascinating to me that like 56:39.040 --> 56:43.680 just in the last four months, there's probably five or six new ones that are 56:43.680 --> 56:50.760 out there that, um, that, so it's kind of use case that I'm trying to look at 56:50.760 --> 56:55.640 is, all right, can I take, um, any type of policy documents or, or research 56:55.640 --> 57:00.360 reports or anything like that, create embeddings within kind of the pine cone 57:00.360 --> 57:02.080 or try, uh, what's the other one? 57:02.080 --> 57:03.520 Chroma that I was kind of looking at. 57:04.120 --> 57:10.000 Um, and then you use that with open aid, open AI API and create something. 57:10.280 --> 57:10.680 Okay, cool. 57:10.680 --> 57:14.480 So that's going to be like, that's fascinating to me right now. 57:14.560 --> 57:18.680 And getting it to work has been, um, a little bit of a challenge. 57:18.760 --> 57:21.720 Like, imagine that even like give it a year and you are going to make 57:21.720 --> 57:23.360 that so much easier, right? 57:23.360 --> 57:23.720 Better. 57:23.720 --> 57:27.080 Like easier, but doing it now, like where the, while the barriers, your 57:27.080 --> 57:29.840 entry is higher, it provides more opportunity, right? 57:30.120 --> 57:30.440 Right. 57:30.440 --> 57:34.160 And just seeing, you know, just trying to understand the technology side of it. 57:34.200 --> 57:38.160 Kind of my, I don't know, it blows my mind a little bit on the whole, like 57:38.200 --> 57:42.280 how it's turning it into vector and what that means and how the interpretation 57:42.280 --> 57:43.280 is happening and all that. 57:43.320 --> 57:44.520 But no, I mean, I've got some homework. 57:45.000 --> 57:45.240 Yeah. 57:47.200 --> 57:50.400 I'll be Wikipedia-ing that after we're done. 57:50.520 --> 57:51.440 It's the first time I've heard it. 57:51.440 --> 57:52.520 So I'm excited. 57:52.600 --> 57:57.160 That's, uh, yeah, no, I mean, at the end of the day, everything is basically 57:57.160 --> 57:59.280 built on or around some kind of database. 57:59.280 --> 57:59.520 Right. 57:59.520 --> 58:02.240 And I don't feel like a lot of people respect that. 58:03.440 --> 58:08.000 And he all know Corey Quinn, he he's a cloud economist, the guy 58:08.080 --> 58:10.200 he's got some really good stuff on AWS. 58:10.240 --> 58:12.960 He's pretty active on Twitter, but like, he's just points out like, 58:13.160 --> 58:14.240 Oh, that's a database. 58:14.240 --> 58:17.680 That's a bit, you know, route 53 is a database, you know, everything, you 58:17.680 --> 58:19.040 know, cloud front as a database. 58:19.520 --> 58:23.760 The internet is literally just a giant assortment of databases that have 58:23.760 --> 58:28.040 relationships to each other with gooey on top of it is really like, if you 58:28.040 --> 58:29.440 really distill a lot of it down, 58:30.080 --> 58:31.880 what we were at that UT blockchain thing. 58:31.880 --> 58:35.800 And that one guy, Jimmy, something like he was like, it's a bleeping 58:36.400 --> 58:37.480 database with rules. 58:37.480 --> 58:40.240 It's like, yeah, it just turned inside out. 58:40.520 --> 58:40.760 Yeah. 58:41.200 --> 58:45.680 And it's just exposed to the, yeah, it's like, well, every, every company 58:45.680 --> 58:48.120 should be a data business when it comes down to it. 58:48.120 --> 58:48.320 Right. 58:48.360 --> 58:49.200 Yeah, absolutely. 58:49.520 --> 58:53.160 You know, depending on your, your Wells, your real-time information coming from 58:53.160 --> 58:55.840 that side, you know, what you can do with it, what you want to do with it. 58:56.160 --> 58:57.640 There's so many opportunities right there. 58:57.800 --> 59:01.080 And Excel is not a database just for the record, just for clear. 59:01.200 --> 59:01.400 Yeah. 59:02.760 --> 59:03.320 Well, awesome. 59:03.360 --> 59:04.080 Well, not Todd. 59:04.080 --> 59:05.480 It's always a pleasure talking to you, man. 59:05.480 --> 59:05.880 So really. 59:05.880 --> 59:06.200 Thanks. 59:06.200 --> 59:06.720 Appreciate it. 59:07.120 --> 59:07.520 Enjoyed it. 59:08.040 --> 59:08.560 Thanks, man. 59:09.040 --> 59:09.560 Yeah, you bet. 59:10.360 --> 59:18.200 While some may see them as the crazy ones, we see genius because the people who 59:18.200 --> 59:24.000 are crazy enough to think they can change the world are the ones who do. 59:25.080 --> 59:25.640 Goodbye.