Data Driven

In this episode of Data Driven, Frank and Andy chat with Philadelphia Microsoft Technology Center Data Architect Dave Wentzel on why you do not need a data warehouse.Also, Frank discusses leaving Microsoft, Frank and Andy talk about five seasons of Data Driven, and even BAILeY has a sentimental moment.Transcripts00:00:00 BAILey Hello and welcome to data driven, the podcast where we explore the emerging wait a tick. This is the premiere episode of Season Five. Can you believe it? Data driven started four years ago this month. 00:00:14 BAILey Up until last season, we had a human doing the voiceover work. That is until she was replaced by an AI. Yours truly. 00:00:23 BAILey In this episode, Frank and Andy speak to Dave Wensel about why you don't need a datawarehouse. We're starting off the new season with a bit of contrarian tone. 00:00:33 BAILey It's a lively back and forth conversation that runs contrary to prevailing wisdom. Don't say we didn't warn you? Now on with the show. 00:00:41 Frank Hello and welcome to data driven. The podcasts were we wait a minute. We've been saying this Andy for four years now. Can you believe it? 00:00:48 Andy Four years, that's crazy talk. 00:00:52 Frank That's just craziness. So I think when you and I first talked about this and that was that fateful, I think it was December was right after Thanksgiving. But before Christmas, I was thinking about starting a podcast and as a data scientist, I needed someone. 00:01:01 Andy Yeah, yeah. 00:01:09 Frank That was a data engineer that could kind of round out the talent there and and and and obviously I wanted someone I knew, liked, and trust. 00:01:11 Frank Found out. 00:01:11 Frank  00:01:22 Frank And so it was you. 00:01:25 Andy Well, I'm just glad all of the real smart data engineers you knew were busy. That's all I got to say. 00:01:25 Frank Much. 00:01:30 Frank Ah, no man. You were the first one. I reached out to and the only one I would have done it with it. So I was delighted when you said yes because starting a podcast can sound like a daunting thing, particularly if you haven't done it before. 00:01:44 Andy Yeah, neither one of us really had. And gosh, it's it's worked out. What are we up to? 180,000 downloads or something? I mean that's. 00:01:52 Frank Something. 00:01:53 Frank Like that about hundred 8000 downloads. I mean, we're not Joe Rogan, but that's OK, Yep. 00:01:55 Yeah. 00:01:57 Andy No. 00:01:59 Andy Yep, Yep. 00:01:59 Andy Yep. 00:02:01 Frank But you know what, we we we've impacted. I think the community in a significant way. We've we've done a number of things we've we've innovative how we podcast. 00:02:12 Frank Uh, we we've actually managed to keep a good cadence with some exceptions. 00:02:18 Andy Yeah, thanks. 00:02:19 Frank You know, we we finally did earlier this year or late last year, kind of fulfill our vision of it being data driven TV when we actually interviewed guests on. 00:02:27 Andy Yes. 00:02:32 Frank On video. 00:02:33 Frank And that was that actually delayed the launch of the show by about three months. 00:02:38 Andy It did but also uhm. Yeah, that was interesting, but you know it's typical software development, right? You release a feature and then you debug it. The I have this saying about that Frank. All software is tested some intentionally. 00:02:52 Frank Sometimes. 00:02:53 Andy Right? 00:02:56 Frank I love it, but I also like how, how, how both our careers have evolved over the last four years. And dumb, you know, this being the premiere episode of Season 5 and we have something special lined up, but I'll get to that in a minute. 00:02:58 Andy Hello. 00:03:03 Andy Oh gosh, itch. 00:03:11 Andy June. 00:03:12 Frank You've progressed in your career. We, you and I've worked on some some projects together or virtual Summit. What we're calling Ring Gate, which will announce very very soon and and but. But most of all, is been my kind of skilling up in transition into data engineering myself. 00:03:29 BAILey Ehm 00:03:31 Frank Which was something that when I joined, so this is just a job update about a year ago. I I left the role of Microsoft kind of field sales and I went into the Microsoft Technology Center stick with me. There's a point to this story and basically I was at the rest in MTC. 00:03:52 Frank And basically I was the AI guy on my my my field sales team, but I didn't really have deep knowledge of kind of the typical typical data engineering pipe work that goes into that role and basically my my. My then manager said you know he's like hey, you know, if you want this role, you've got a skill. 00:04:12 Frank And skill up I did. And with Andy's mentoring and a bunch of other folks that helped me kind of skill up on our the data engineering side. I looked at it this morning. I'm like 88 hours on Pluralsight. 00:04:25 Frank Wow, that was from mid may till we're recording this on April 30th. So just about a year 88 hours right now tracking on about 200 four 205 consecutive days of getting on LinkedIn. I'm not on LinkedIn on Pluralsight, LinkedIn learning. I also have a number of courses too. 00:04:31 Andy Yeah. 00:04:43 Frank Uh, that is something I'm proud of in terms of career evolution. 00:04:47 Andy Absolutely Frank, you should be. How many cirts are you up to now? 00:04:50 Frank I 87. 00:04:53 Andy Slacker. 00:04:54 Frank I know, I know. 00:04:54 Frank Know, I know. 00:04:54 Andy I think I've got 4. 00:04:56 Frank Ah, now I know you and I did the data engineering thing, so you have at least 11. 00:05:00 Andy That's true, that's true. We did that one and you know that was it's just. It's just been a nice journey and I'll take credit for this. 'cause 'cause I can I was. I was actually pestering you years ago. We've been friends since 2005 and we started doing. 00:05:20 Andy Code camps here in the Richmond area. 00:05:22 Andy Together and co-founded RE co-founded Richmond SQL Server Users Group and you know, worked with the net users group and stuff. And I told you as soon as I saw some of your graphic art and Frank would do a keynote for the Richmond code camps and every time he would make movie posters, the one that. 00:05:41 Frank Oh yeah. 00:05:42 Andy Still sticks out is 1 called devs on a plane. 00:05:45 Frank Ha ha ha. 00:05:49 Andy Oh yeah, I loved that one that was so so cool and. 00:05:49 Andy And that was. 00:05:49 Andy  00:05:54 Andy You know I saw the graphic arts part of it and I just knew I said you, you'd be really good in analytics and data visualization. You should get into by and you were busy doing other stuff which was cool. You were good at that too. It wasn't, you know you. I don't know of anything you've done that you haven't mastered. By thank you. You know you when. 00:06:14 Andy Things took a took, uh, started taking a turn for you in your first rodeo at Microsoft. You got into it and and took off with it. I don't. I won't tell the story well, but you just really turned around. You focused on data and. 00:06:32 Andy You know, I'll say this Frank. I was right. 00:06:35 Frank Well, with that he totally I. I think if anything I took away is I should have listened to Andy 10 years earlier. 00:06:36 Dave You aren't very good. 00:06:40 Frank Uhm? 00:06:41 Frank And that that that that is something that that that that's the big takeaway we'll talk about, kind of that journey. 'cause I think that's worth kind of talking about. And I think one of the things we you, and I've been bouncing around is kind of interviewing each other. 00:06:46 We 00:06:55 Frank Like in asking one of us those those those questions we have, so we definitely will do that, but not today kids. 00:06:55 Frank Yeah. 00:06:55 Frank  00:06:59 Dave We need to. 00:06:59 Dave Need to. 00:07:02 Andy Today, do we have Dave? 00:07:02 Andy Today do Dave. 00:07:03 Frank Today we have a special guest we have Dave Wentzel. Dave Wentzel is a was a peer of mine when I worked at the Microsoft MTC and that reminds me, I no longer work at Microsoft 2 weeks ago was my last day. I turned in my second blue badge. 00:07:05 Frank Yeah. 00:07:05 Frank  00:07:18 Frank And I joined a startup called electrify. We'll talk about them a later day, but I'm so excited to have Dave here. Dave is the data in AI architect out of the Philadelphia Microsoft Technology Center, and he's an awesome guy. Awesome, got to work with. I worked with him when I was in field sales and I worked with him when I was in the MTC organization. 00:07:38 Frank It is April. It was a privilege and honor Dave to have you as a colleague, and it's once again a privilege and an honor to have you here as a guest on data driven. 00:07:46 Dave Well, thank you so much, appreciate that. 00:07:47 Andy Welcome Dave. 00:07:49 Dave Thank you. 00:07:51 Frank So, uhm, so for folks that don't know what the MTC is. Shocking that there are actually people that don't know what that is, what? What is the MTC? 00:08:00 Dave So basically we're a free service to our customers and I'm a data and AI technology architect. We talked to customers about data and it could be anything from just, you know. Hey, here's what we're doing. State of the art in Azure with. 00:08:16 Dave With data, but it could also be architectural design sessions where we talk to customers. Our customers bring us their architectures, and then we kind of get it with them. Give them the pros and cons, alternative ways of thinking, and then what I really enjoy doing is hackathons with customers and workshops and just you know, helping them to learn without just. 00:08:37 Dave Taking a course somewhere so actually using their data and then I guess I'm roughly a data scientist, so we also do design thinking sessions and those are absolutely a lot of fun. 00:08:48 Dave We did one at the MTC with CSL Behring a couple years ago and it actually won a Forrester Award. So I'm very proud of that one. And yeah, it's it's a. It's a lot of fun and it's a good way to bring to have executives and business people understand the actual capabilities of data science. And then within two days be able to come up with a use case. 00:08:55 Andy Oh wow, wow. 00:09:08 Dave And actually build a prototype out a lot of fun. 00:09:11 Frank Yeah, the NPC's are definitely like Microsoft Secret weapon in terms of how 'cause you know. Although I will say and because we were in the DC and we dealt with a lot of government contracts, we could not say that they were a free service. They were and already included paid for service. 00:09:26 That's. 00:09:26 Dave Much, much better said yes. 00:09:28 Frank I I 'cause I said free once and I got kind of slapped. 00:09:31 Frank On the hand, say that. 00:09:34 Frank But you know it, it really is something that if you do have a Microsoft account team and you are encountering any kind of questions or or whatever, and it's not strictly technical, there's also pretty good. You know, we basically wouldn't engage with the business development, business decision makers. 00:09:52 Frank Technical decision makers all the way from kind of like you know, hey, this is what Azure can do. This is what data can do for you all the way down to OK. What's your problem? Let's build something out, give you 3 days with one of the top Notch architects in the. 00:10:04 Frank Space and. 00:10:07 Frank You know, boom, you know we knock it out and and you know I I enjoyed it you know had this opportunity not come I would have I would have gladly stayed another. You know 5-10 years of the MTC. Like a lot of people do, and it's a fun organization. So with that in mind, today we're going to do something a little different. We're kind of doing the. 00:10:27 Frank A contrarian approach is that right, Dave. 00:10:29 Dave Yes, exactly. 00:10:31 Frank So this this has actually come up one of my last. This is one of the things that intrigued me about about your idea for the show was this came up when I was working with a we'll just call it a large governmental agency known for its. 00:10:42 Frank Birds. 00:10:42 Frank  00:10:43 Frank Tape. 00:10:44 Frank That that should keep it generic enough. They basically came to us and say we want Synapse. We want a data Lake. We want this. We want that. And I was like, OK, well how much data you're talking about. And like we have maybe you know 5 maybe 20 gigs of data. 00:11:02 Frank And I'm like, uh, OK, tell me what are you trying to do? And ultimately I kind of pitched the idea like look, you know you don't have that much data right to make data bricks. 00:11:14 Frank But you really want it so. 00:11:17 Frank If you really want it, I won't stop you, but I think it's kind of overkill. I think you're taking instead of using a steak knife to cut the steak using a chainsaw. 00:11:25 Frank And. 00:11:27 Frank You know they kind of came back and ultimately what won the day was they already they couldn't get approval for whatever we recommended 'cause it didn't get stamped by there. 00:11:37 Frank They're people for security usage yet, and things like that so they end up doing kind of the right thing because of their own bureaucracy, which. 00:11:44 Frank It's kind of weird. It's kind of like dividing by zero and seeing the universe fold in on itself. 00:11:50 Frank But UM, so the topic of today is kind of like no, you don't need a data warehouse. Did I get that right? 00:11:58 Dave Exactly, that's what I believe in, and I believed in it since I was in college and I first learned about data warehouses. I'm not saying data warehouses are always bad, they definitely have their. 00:12:10 Dave Use cases, but in 2021 when we're talking about advanced analytics and we're trying to tell customers you need to be more predictive than prescriptive. 00:12:19 Dave The data warehouse really doesn't deliver. 00:12:23 Frank Really, how so? 'cause? That's that's totally not the power. Certainly not the party line. I'm not going to say which party it was. You can figure it out but but why, why why would you say that? 00:12:33 Dave OK so take. 00:12:33 Dave A step back here, right? We're all data consultants, or we were at some point in our life and probably most of the listeners are. And if you've been doing this, I've been doing this since the mid 90s in college and when I first started I had an internship with a consumer package. Good company, they made candy. 00:12:52 Dave Hours and they said, hey, we wouldn't want to do an internship and take a look at our data and figure out where is the best spot to put candy on a shelf so that we sell more candy to kids, right? So we used data for that at the time that was known as business Intelligence in the industry. Nowadays business intelligence means something totally different. In reality, it's really closer to what? 00:13:12 Dave Today we would call data science right? So my tools of choice were SQL, although I didn't know what SQL was at the time and we had this goofy SQL engine and and essentially something called ESP's, which is roughly the equivalent of like our or stats package something. 00:13:28 Dave Like that and we kind of looked at data as just, you know I have data and let me find the Nuggets of gold and I'm not going to concern myself with schema and that is I think the biggest problem with data warehouses. But take a, you know a metal layer higher right? Talk to the average business executive like a you know a CTO or CEO. 00:13:48 Dave And tell them, as a consultant, you're going to go in and build them a data warehouse. 00:13:53 Dave Instantly,...

In this episode, Frank and Andy speak to Carlos Chacon about data community, family, and messy data in legacy CRM systems.Transcript00:00:00 BAILey Hello and welcome to data driven, the podcast where we explore the emerging wait a tick. This is the premiere episode of Season Five. Can you believe it? Data driven started four years ago this month. 00:00:14 BAILey Up until last season, we had a human doing the voiceover work. That is until she was replaced by an AI. Yours truly. 00:00:23 BAILey In this episode, Frank and Andy speak to Dave Wensel about why you don't need a datawarehouse. We're starting off the new season with a bit of contrarian tone. 00:00:33 BAILey It's a lively back and forth conversation that runs contrary to prevailing wisdom. Don't say we didn't warn you? Now on with the show. 00:00:41 Frank Hello and welcome to data driven. The podcasts were we wait a minute. We've been saying this Andy for four years now. Can you believe it? 00:00:48 Andy Four years, that's crazy talk. 00:00:52 Frank That's just craziness. So I think when you and I first talked about this and that was that fateful, I think it was December was right after Thanksgiving. But before Christmas, I was thinking about starting a podcast and as a data scientist, I needed someone. 00:01:01 Andy Yeah, yeah. 00:01:09 Frank That was a data engineer that could kind of round out the talent there and and and and obviously I wanted someone I knew, liked, and trust. 00:01:11 Frank Found out. 00:01:11 Frank  00:01:22 Frank And so it was you. 00:01:25 Andy Well, I'm just glad all of the real smart data engineers you knew were busy. That's all I got to say. 00:01:25 Frank Much. 00:01:30 Frank Ah, no man. You were the first one. I reached out to and the only one I would have done it with it. So I was delighted when you said yes because starting a podcast can sound like a daunting thing, particularly if you haven't done it before. 00:01:44 Andy Yeah, neither one of us really had. And gosh, it's it's worked out. What are we up to? 180,000 downloads or something? I mean that's. 00:01:52 Frank Something. 00:01:53 Frank Like that about hundred 8000 downloads. I mean, we're not Joe Rogan, but that's OK, Yep. 00:01:55 Yeah. 00:01:57 Andy No. 00:01:59 Andy Yep, Yep. 00:01:59 Andy Yep. 00:02:01 Frank But you know what, we we we've impacted. I think the community in a significant way. We've we've done a number of things we've we've innovative how we podcast. 00:02:12 Frank Uh, we we've actually managed to keep a good cadence with some exceptions. 00:02:18 Andy Yeah, thanks. 00:02:19 Frank You know, we we finally did earlier this year or late last year, kind of fulfill our vision of it being data driven TV when we actually interviewed guests on. 00:02:27 Andy Yes. 00:02:32 Frank On video. 00:02:33 Frank And that was that actually delayed the launch of the show by about three months. 00:02:38 Andy It did but also uhm. Yeah, that was interesting, but you know it's typical software development, right? You release a feature and then you debug it. The I have this saying about that Frank. All software is tested some intentionally. 00:02:52 Frank Sometimes. 00:02:53 Andy Right? 00:02:56 Frank I love it, but I also like how, how, how both our careers have evolved over the last four years. And dumb, you know, this being the premiere episode of Season 5 and we have something special lined up, but I'll get to that in a minute. 00:02:58 Andy Hello. 00:03:03 Andy Oh gosh, itch. 00:03:11 Andy June. 00:03:12 Frank You've progressed in your career. We, you and I've worked on some some projects together or virtual Summit. What we're calling Ring Gate, which will announce very very soon and and but. But most of all, is been my kind of skilling up in transition into data engineering myself. 00:03:29 BAILey Ehm 00:03:31 Frank Which was something that when I joined, so this is just a job update about a year ago. I I left the role of Microsoft kind of field sales and I went into the Microsoft Technology Center stick with me. There's a point to this story and basically I was at the rest in MTC. 00:03:52 Frank And basically I was the AI guy on my my my field sales team, but I didn't really have deep knowledge of kind of the typical typical data engineering pipe work that goes into that role and basically my my. My then manager said you know he's like hey, you know, if you want this role, you've got a skill. 00:04:12 Frank And skill up I did. And with Andy's mentoring and a bunch of other folks that helped me kind of skill up on our the data engineering side. I looked at it this morning. I'm like 88 hours on Pluralsight. 00:04:25 Frank Wow, that was from mid may till we're recording this on April 30th. So just about a year 88 hours right now tracking on about 200 four 205 consecutive days of getting on LinkedIn. I'm not on LinkedIn on Pluralsight, LinkedIn learning. I also have a number of courses too. 00:04:31 Andy Yeah. 00:04:43 Frank Uh, that is something I'm proud of in terms of career evolution. 00:04:47 Andy Absolutely Frank, you should be. How many cirts are you up to now? 00:04:50 Frank I 87. 00:04:53 Andy Slacker. 00:04:54 Frank I know, I know. 00:04:54 Frank Know, I know. 00:04:54 Andy I think I've got 4. 00:04:56 Frank Ah, now I know you and I did the data engineering thing, so you have at least 11. 00:05:00 Andy That's true, that's true. We did that one and you know that was it's just. It's just been a nice journey and I'll take credit for this. 'cause 'cause I can I was. I was actually pestering you years ago. We've been friends since 2005 and we started doing. 00:05:20 Andy Code camps here in the Richmond area. 00:05:22 Andy Together and co-founded RE co-founded Richmond SQL Server Users Group and you know, worked with the net users group and stuff. And I told you as soon as I saw some of your graphic art and Frank would do a keynote for the Richmond code camps and every time he would make movie posters, the one that. 00:05:41 Frank Oh yeah. 00:05:42 Andy Still sticks out is 1 called devs on a plane. 00:05:45 Frank Ha ha ha. 00:05:49 Andy Oh yeah, I loved that one that was so so cool and. 00:05:49 Andy And that was. 00:05:49 Andy  00:05:54 Andy You know I saw the graphic arts part of it and I just knew I said you, you'd be really good in analytics and data visualization. You should get into by and you were busy doing other stuff which was cool. You were good at that too. It wasn't, you know you. I don't know of anything you've done that you haven't mastered. By thank you. You know you when. 00:06:14 Andy Things took a took, uh, started taking a turn for you in your first rodeo at Microsoft. You got into it and and took off with it. I don't. I won't tell the story well, but you just really turned around. You focused on data and. 00:06:32 Andy You know, I'll say this Frank. I was right. 00:06:35 Frank Well, with that he totally I. I think if anything I took away is I should have listened to Andy 10 years earlier. 00:06:36 Dave You aren't very good. 00:06:40 Frank Uhm? 00:06:41 Frank And that that that that is something that that that that's the big takeaway we'll talk about, kind of that journey. 'cause I think that's worth kind of talking about. And I think one of the things we you, and I've been bouncing around is kind of interviewing each other. 00:06:46 We 00:06:55 Frank Like in asking one of us those those those questions we have, so we definitely will do that, but not today kids. 00:06:55 Frank Yeah. 00:06:55 Frank  00:06:59 Dave We need to. 00:06:59 Dave Need to. 00:07:02 Andy Today, do we have Dave? 00:07:02 Andy Today do Dave. 00:07:03 Frank Today we have a special guest we have Dave Wentzel. Dave Wentzel is a was a peer of mine when I worked at the Microsoft MTC and that reminds me, I no longer work at Microsoft 2 weeks ago was my last day. I turned in my second blue badge. 00:07:05 Frank Yeah. 00:07:05 Frank  00:07:18 Frank And I joined a startup called electrify. We'll talk about them a later day, but I'm so excited to have Dave here. Dave is the data in AI architect out of the Philadelphia Microsoft Technology Center, and he's an awesome guy. Awesome, got to work with. I worked with him when I was in field sales and I worked with him when I was in the MTC organization. 00:07:38 Frank It is April. It was a privilege and honor Dave to have you as a colleague, and it's once again a privilege and an honor to have you here as a guest on data driven. 00:07:46 Dave Well, thank you so much, appreciate that. 00:07:47 Andy Welcome Dave. 00:07:49 Dave Thank you. 00:07:51 Frank So, uhm, so for folks that don't know what the MTC is. Shocking that there are actually people that don't know what that is, what? What is the MTC? 00:08:00 Dave So basically we're a free service to our customers and I'm a data and AI technology architect. We talked to customers about data and it could be anything from just, you know. Hey, here's what we're doing. State of the art in Azure with. 00:08:16 Dave With data, but it could also be architectural design sessions where we talk to customers. Our customers bring us their architectures, and then we kind of get it with them. Give them the pros and cons, alternative ways of thinking, and then what I really enjoy doing is hackathons with customers and workshops and just you know, helping them to learn without just. 00:08:37 Dave Taking a course somewhere so actually using their data and then I guess I'm roughly a data scientist, so we also do design thinking sessions and those are absolutely a lot of fun. 00:08:48 Dave We did one at the MTC with CSL Behring a couple years ago and it actually won a Forrester Award. So I'm very proud of that one. And yeah, it's it's a. It's a lot of fun and it's a good way to bring to have executives and business people understand the actual capabilities of data science. And then within two days be able to come up with a use case. 00:08:55 Andy Oh wow, wow. 00:09:08 Dave And actually build a prototype out a lot of fun. 00:09:11 Frank Yeah, the NPC's are definitely like Microsoft Secret weapon in terms of how 'cause you know. Although I will say and because we were in the DC and we dealt with a lot of government contracts, we could not say that they were a free service. They were and already included paid for service. 00:09:26 That's. 00:09:26 Dave Much, much better said yes. 00:09:28 Frank I I 'cause I said free once and I got kind of slapped. 00:09:31 Frank On the hand, say that. 00:09:34 Frank But you know it, it really is something that if you do have a Microsoft account team and you are encountering any kind of questions or or whatever, and it's not strictly technical, there's also pretty good. You know, we basically wouldn't engage with the business development, business decision makers. 00:09:52 Frank Technical decision makers all the way from kind of like you know, hey, this is what Azure can do. This is what data can do for you all the way down to OK. What's your problem? Let's build something out, give you 3 days with one of the top Notch architects in the. 00:10:04 Frank Space and. 00:10:07 Frank You know, boom, you know we knock it out and and you know I I enjoyed it you know had this opportunity not come I would have I would have gladly stayed another. You know 5-10 years of the MTC. Like a lot of people do, and it's a fun organization. So with that in mind, today we're going to do something a little different. We're kind of doing the. 00:10:27 Frank A contrarian approach is that right, Dave. 00:10:29 Dave Yes, exactly. 00:10:31 Frank So this this has actually come up one of my last. This is one of the things that intrigued me about about your idea for the show was this came up when I was working with a we'll just call it a large governmental agency known for its. 00:10:42 Frank Birds. 00:10:42 Frank  00:10:43 Frank Tape. 00:10:44 Frank That that should keep it generic enough. They basically came to us and say we want Synapse. We want a data Lake. We want this. We want that. And I was like, OK, well how much data you're talking about. And like we have maybe you know 5 maybe 20 gigs of data. 00:11:02 Frank And I'm like, uh, OK, tell me what are you trying to do? And ultimately I kind of pitched the idea like look, you know you don't have that much data right to make data bricks. 00:11:14 Frank But you really want it so. 00:11:17 Frank If you really want it, I won't stop you, but I think it's kind of overkill. I think you're taking instead of using a steak knife to cut the steak using a chainsaw. 00:11:25 Frank And. 00:11:27 Frank You know they kind of came back and ultimately what won the day was they already they couldn't get approval for whatever we recommended 'cause it didn't get stamped by there. 00:11:37 Frank They're people for security usage yet, and things like that so they end up doing kind of the right thing because of their own bureaucracy, which. 00:11:44 Frank It's kind of weird. It's kind of like dividing by zero and seeing the universe fold in on itself. 00:11:50 Frank But UM, so the topic of today is kind of like no, you don't need a data warehouse. Did I get that right? 00:11:58 Dave Exactly, that's what I believe in, and I believed in it since I was in college and I first learned about data warehouses. I'm not saying data warehouses are always bad, they definitely have their. 00:12:10 Dave Use cases, but in 2021 when we're talking about advanced analytics and we're trying to tell customers you need to be more predictive than prescriptive. 00:12:19 Dave The data warehouse really doesn't deliver. 00:12:23 Frank Really, how so? 'cause? That's that's totally not the power. Certainly not the party line. I'm not going to say which party it was. You can figure it out but but why, why why would you say that? 00:12:33 Dave OK so take. 00:12:33 Dave A step back here, right? We're all data consultants, or we were at some point in our life and probably most of the listeners are. And if you've been doing this, I've been doing this since the mid 90s in college and when I first started I had an internship with a consumer package. Good company, they made candy. 00:12:52 Dave Hours and they said, hey, we wouldn't want to do an internship and take a look at our data and figure out where is the best spot to put candy on a shelf so that we sell more candy to kids, right? So we used data for that at the time that was known as business Intelligence in the industry. Nowadays business intelligence means something totally different. In reality, it's really closer to what? 00:13:12 Dave Today we would call data science right? So my tools of choice were SQL, although I didn't know what SQL was at the time and we had this goofy SQL engine and and essentially something called ESP's, which is roughly the equivalent of like our or stats package something. 00:13:28 Dave Like that and we kind of looked at data as just, you know I have data and let me find the Nuggets of gold and I'm not going to concern myself with schema and that is I think the biggest problem with data warehouses. But take a, you know a metal layer higher right? Talk to the average business executive like a you know a CTO or CEO. 00:13:48 Dave And tell them, as a consultant, you're going to go in and build them a data warehouse. 00:13:53 Dave Instantly, that's a political statement you just made. Data warehouses have connotations of you, know risky projects over budget projects as far as time and money, and...

In this episode Frank and Andy have a chat with Chris Gherardini on the role of data in ERP and CRM Systems.Transcript00:00:00 BAILey Hello and welcome to data driven, the podcast where we explore the emerging fields of data science, machine learning and artificial intelligence. In this episode, Frank and Andy speak to Chris Gardini about the role data plays in ERP and CRM systems. 00:00:17 Frank Hello and welcome back to data driven. The podcast where we explore the emerging fields of data science, machine learning and artificial intelligence. If you like to think of data as the new oil, then you can think of us like Car Talk because we focus on where the rubber meets the road. Although there's not much of a road trip usually on this virtual road trip. 00:00:37 Frank Is Andy Leonard? How's it going, Andy? 00:00:40 Andy Hey Frank, it's going really well. How are you doing? 00:00:43 Frank I'm doing alright, you know, with the exception I might have to buy a new desktop computer. 00:00:48 Andy Ah, I have not. 00:00:49 Frank Possibly, or power supply. Literally. We were on this call and all of a sudden everything froze and I was like Oh well, blue screen. Big deal. 00:00:59 Frank And then when I went to power it back on. 00:01:03 Frank It just kept keeps beeping so I'm like oh, fee something something hard so I'm going to have to do some search engine work and possibly get a new power supply or something. 00:01:06 Andy Codes. 00:01:13 Frank Fortunately, micro center. 00:01:14 Andy Everything is. 00:01:17 Andy Go ahead. 00:01:17 Andy  00:01:17 Andy I've gotta say Frank, everything is figure out able right? 00:01:21 Frank Everything is figure out able because of my experience with clear DB and all sorts of other drama. I have multiple backups of just about everything it if if you know so it's it's. It'll be an inconvenience, not a tragedy. 00:01:32 Andy Outstanding. 00:01:37 Frank But every opportunity to come back from a complete backup failure is an opportunity to learn. 00:01:47 Frank And, uhm, Speaking of opportunity, it's really good timing that this guest is here because I as folks know I work at the Microsoft Technology Center in Reston and recently. 00:02:00 Frank There was a, uh, someone we were on this engagement and it was very heavy into dynamics and uh, dynamics is one of those things. I haven't really looked into Andy and I have been experimenting with power apps and power platform, mostly to kind of help automate a lot of our content. 00:02:21 Frank Production. 00:02:22 Chris This is crucial as we. 00:02:24 Frank Continue to put the final touches on our secret project, but this guest here is an expert in dynamics as well as various ERP solutions. 00:02:36 Frank And he's from Saint Louis, and his name is Christian. I'm really blowing this intro here. His name is Cristiano Gardeny. Did I pronounce that right? 00:02:48 Chris Cristiano Guardian yeah, he pulled our sounded out there so. 00:02:48 Frank OK good good. 00:02:51 Frank He did fine, got it. Sorry about that. He's the president and owner of Turnkey Technologies and they are a Microsoft partner. I did looking around on their website and they are basically they provide development, analytics, training and support services for Microsoft Dynamics. 00:03:09 Frank If you don't know what Microsoft Dynamics is, a lot of people don't. In the data world tend to just know it tangentially. It's basically Microsoft CRM system, so welcome to the show, Cristiano. 00:03:21 Chris Thank you very much. Thanks for having me. 00:03:25 Frank It's good to have you here, and so what's the weather like in Saint Louis right now? 00:03:30 Chris Ah, it's beautiful and sunny. Today it's about 64 degrees Sun index is just right around A5, so it's actually it's actually nice and better than the the ice. We had a couple weeks ago so. 00:03:38 Frank Knife. 00:03:42 Andy Yeah, it got bitterly cold out there for about a week, didn't it? 00:03:47 Chris That's right, I happen to be in Florida that entire week. Everybody couldn't believe I missed all the fun. So with the IT was good, it was a good week to be gone. We left Saturday. We came back Sunday was 52 when we got back and the 9 inches of snow had melted and. 00:03:51 Chris Unfelt 00:03:51 Chris  00:04:00 Chris So yeah, perfect timing. 00:04:02 Frank Nice, now you have excellent timing Sir. Not only in just the fact that dynamics is kind of coming up, coming up on my personal radar, but also in terms of avoiding bad weather. My first question is and I'm calm. Still a new bit dynamics. I learned a lot just by working on this. 00:04:23 Frank One engagement we had DMTC. 00:04:27 Frank Is Dinah. 00:04:28 BAILey Mix. 00:04:29 Chris So Dynamics Dynamics is the biz apps. I mean, you said CRM. It's more than CRM. But today dynamics represents a family of products. You know, the legacy on Prem products, Dynamics AX Dynamics, Navy Dynamics, GP, Dynamics, SL and then the current dynamics 365, which encompasses both you know financing. 00:04:49 Chris Operations, which was the dynamics AX and then Dynamics 365 business Central which was the Navy? So those are both ERP products. 00:04:57 Chris And then Dynamics customer engagement, which is the CRM platform so so dynamics is a collection of biz apps. It's a family of products and you know today we we focus on the two dynamics 365 ERP products and the CRM. The customer engagement product. So great solution, but it's a platform also it. 00:05:15 Frank That's what I noticed, and folks that are listening. They're like this is a data science kind of data engineering show. Why the heck are you talking about? 00:05:25 Frank Dynamics but dataverse the data models, which are one of the things that blew me away, was on this one demo is that there's a. There's a button where you just basically can dump out all your cream data. 00:05:38 Frank Or all your data and dynamics out to a data Lake. 00:05:42 Chris That's absolutely right, Azure. So if you think about the challenges where you move from a legacy system to the cloud, maybe all the data doesn't move and you need to combine it in an Azure data like a data warehouse, and certainly all those tools and all the analytics are all part of the platform. That's just it touches dynamics out of the box, so it's quite a quite a degree of efficiency. 00:06:02 Chris There. 00:06:03 Frank Interesting. 00:06:05 Frank So one question I have about dynamics is it's history now. You mentioned Dynamics AX and a couple of other letters next to the word dynamics. 00:06:17 Frank Once Upon a time when I worked when I lived in Richmond, there was a guy who used to do a lot of work with that technology. 00:06:24 Frank Back and it was Solomon in Great Plains is that is that the same thing is that the lineages from it. 00:06:30 Chris That's correct, that's correct, that's correct. And so the US based products was Great Plains software out of Fargo ND, and a gentleman named Doug Burgum owned that company privately and then his family. They bought the the Salomon product line as well and then in 2001 is when Microsoft bought Great Plains. 00:06:32 Silly. 00:06:46 Chris Software, so that's kind of how they consume the North American products and then a year later Microsoft went to Europe and bought Dynamics AX and Dynamics Navy. It was called Exapta in division so and that became a second big purchase and instantly at 2002 they had four ERP products and they're in the biz apps space like they've never been. 00:06:48 Chris OK, so. 00:06:48 Chris  00:07:06 Chris Before so. 00:07:09 Frank Ah OK, that's interesting. 'cause I I now I know why. There's a huge Microsoft campus in Fargo. 00:07:16 Chris Yes, yes. 00:07:18 Chris It's beautiful campus. 00:07:19 Frank Uhm? 00:07:21 Frank Yeah, I haven't been there, but I definitely maybe one day I'll end up going but the the other question I have for you. You keep saying biz apps when you say biz apps? What exactly do you mean like what? 00:07:32 Chris Sure, so I'm. I'm a technical guy. I'm engineering comp SCI math and there's two directions you go and even those curriculums you go **** **** or you or business applications and so business applications in our context is, you know, we're we're business process automation again, whether it starts in an ERP from a quote to cash or a procure to pay those. 00:07:33 Frank What what comic sub is that like? 00:07:52 Chris For business processes and the business applications support. 00:07:56 Chris Work, transactional processing or even non transactional if you think about context of a lead to opportunity to customer type of flow where you start even earlier in the process, but it is it's process automation and exception management and workflow and approvals and can go to the NTH degree of complexity. But but it's biz apps in that categorization. 00:08:16 Chris So as opposed to scientific apps or development tools or games, for example, right, we're focused on businesses, not on residential applications. 00:08:26 Chris That makes sense. 00:08:27 Andy It does, yeah. 00:08:28 Frank Do you have any questions Andy? 00:08:30 Frank This is so awkward being on on this recording, but not being live. So for those that are watching or listening or maybe watching. 00:08:35 Andy Yeah, I don't work. 00:08:40 Frank Go ahead. 00:08:42 Andy Yeah, I'd like to apologize to Chris, especially thank you for coming on here, but we're a little off because of the video. I I I never shaved but. 00:08:50 Chris No worries. 00:08:55 Andy I would have I. I have a face for radio. I think in audio, so that's what's throwing us just a bit. Although Frank and I do live streaming and stuff, can you tell us a little bit more about about what your company does, how how your team implements these biz apps? 00:09:14 Chris Sure, so so turnkey is a is a direct Microsoft distributor, so we distribute dynamics licensing and then we provide 100% of the professional services to to plan to implement, to convert, to customize, to integrate. So really, if you think about there's two parts of business, there's the licensing side and and then the services side, which we've got about 60 team members. 00:09:35 Chris These days, and as you think about, you know, delivering an implementation once the solutions been kind of articulated as project management methodology, really drive the success of the project, and so there's an intimate, detailed plan. 00:09:48 Chris Where we use Microsoft project and and we plan in very very low levels of detail for project execution. Everything from you know, the initial phases of analyzing and requirements and then through design and then through development and through deployment. And then we take people live, but it's a very predictable methodology that's used for project delivery. 00:10:08 Chris Around the ERP products, so that's that's the first spot, so. 00:10:12 Andy You know that sounds an awful lot like what what we do when we're doing data warehousing as well and and similar work I I would say. 00:10:22 Chris Absolutely the disciplines or you know, are kind of agnostic when you think about project methodology. 00:10:27 Andy So just curious, what is a typical engagement about how long does a typical engagement last? 00:10:34 Chris So and again, we sell 2 flavors Dynamics, 365 business Central. We talk about small, medium and those projects could. 00:10:41 Chris Maybe three months for somebody small coming off of a QuickBooks. It's just financials, but it could be six months for somebody that's implementing distribution and manufacturing, for example. So depending on complexity, three months is normally the least amount of time, and in 6 plus months for the business, central on the finance and supply chain, which was acts as a much larger applications targeted at, you know. 00:11:01 Chris Mid market enterprise organizations. Those projects are typically not being delivered in less than six months. Frankly, and I've got some that we see them take 12 to 18 months for example so. 00:11:13 Chris No, it's gonna save us the the project management requirement. Because of that duration and scope and girth. You really people get lost right? Anyway, I'm sorry please. 00:11:23 Frank Oh no no no no no so. 00:11:26 Frank The the, the ERM or the ERP systems like Dave require. So Once Upon a time I was working for a large German chemical company, right? And of course it's a German company, so they used SAP and they hired a bunch of consultants and consulting firms to build out the system. But when they. 00:11:46 Frank Rolled out SA P R2. I think it was. 00:11:49 Frank Is. 00:11:50 Frank Apparently there was not. 00:11:52 Frank A lot of project discipline now I'll just. I'll just leave it there. 00:11:57 Frank And it basically shut down some of their plants because there were just things were not coming in the way they were supposed to. So So what? 00:12:06 Frank How? 00:12:07 Frank How does ERP systems? How do our ERP systems? Kind of you know if they're done wrong? It sounds like they can create a big mess if they're done right, they could really optimize operations. 00:12:19 Frank Uhm? 00:12:21 Frank I mean is that, is that true? 'cause I I kind of saw, I mean. 00:12:23 Frank That was just a Horror Story. It's true. 00:12:24 Chris It's true, it's true. It's like me giving you lousy directions to drive from Florida to Washington, and it takes you six months and it should have taken you three days. There's a great example. I poor guidance and poor methodology, is it stretches it out. Things are missed, costs are out of control, but again, if it's done correctly through a thorough analysis. 00:12:34 Frank Point 00:12:45 Chris Then you really define scope. 00:12:46 Chris And you know you have good business process visualization. Then you drive to deliver those processes to that point and and it's. And again, if you do a good job and my team does a great job of of really articulating business process, you gain great efficiency and Moreover you get capacity to turn up the juice again, you can take more volume and you've you've articulated. 00:13:05 Andy Nice. 00:13:06 Chris And really gotten the inefficiency out of the process, and Even so, you don't touch every transaction you touch the exceptions so you get a lot of leverage. But then you're correct if it's done right, if it's done. 00:13:16 Chris Wrong, right? It maybe it's broken, maybe it falls off the table and somebody has to pick it up and has a manual step because they didn't think through it thoroughly. And and now you've got a bigger problem, right? And sometimes companies don't retire the old systems and they're working in two places, so there is a lot of negative that can come for people that don't manage and plan and and deliver these systems. And and again, we've been doing this. 00:13:37 Chris For 27 years, so we're pretty pretty good at it so. 00:13:38 Andy Will you? 00:13:40 Andy Wow. 00:13:42 Andy Well, you you mentioned Chris that you know when you were giving examples of the typical projects links that customers are are often migrating from other platforms. Other ERP ish. Perhaps they do some of the ERP work and then you're moving them into dynamics. And as you say. 00:14:02 Andy Once they get in there, they're going to be able to scale. It sounds like horizontally and and cover more territory than the system that they were using and also scale vertically. Like you said, turn up the juice and and just grow is that. Is that...

In this livestream, Frank and Andy talk about geothermal energy, solar power, and why you should never say not to Clippy.

In this episode of Data Driven, Frank and Andy speak with Peter Voss about Artificial General Intelligence, Personalizing Personal Assistants, and MotorcyclesSponsorSponsor: Audible.com - Get a free audio book and support DataDriven - visit thedatadrivenbook.com!Guest BioPeter Voss is the world’s foremost authority in Artificial General Intelligence.His company Aigo (https://www.aigo.ai/) has created the world’s first intelligent cognitive assistant.Aigo was funded with a personal investment of $10 million dollars. They currently manage millions of personalized customer service inquiries for household name-brandsNotable QuotesAigo is Peter's company. BAILeY's Introduction (00:00)The east coast has been blanketed with snow. (01:30)The Expanse books (03:00)Coding for curiosity? - Frank (11:50)"Models don't dynamically learn." - Peter (13:00)Three waves: Logic programming, Deep learning / neural networks, cognitive architecture / intelligence (14:00)Intelligence v. sentience? - Frank (15:50)What about bots being "led astray?" - Andy (18:30)On programming morality... (21:30)AI Safety is a better description - Peter (22:30)Asimov's three laws of robotics - Frank (23:15)On delimmas - Peter (24:15)"Morality should be about human flourishing." - Peter (25:15)Are we using digital means to do something analog? - Andy (27:55)Peter is trained as an electronics engineer. (28:05)"Context is always super-important." - Peter (28:30)"You need a feedback system." - Peter (30:00)AIGO is Peter's company. (31:00)The three meanings of personal. (34:00)"Exo-cortex" (33:50)On context switches (38:30)Did you find AI or did AI find you? (41:00)"I took five years off to study..." - Peter (43:00)What's your favorite part of your current gig? (44:10)When I'm not working, I enjoy ___. (45:00)I think the coolest thing in technology today is ___. (45:30)I look forward to the day when I can use technology to ___. (46:25)Something interesting or different about yourself (47:00)How Not to Die (48:00)Where can people learn more about Peter? (49:00)Book reading / listening recommendations? (49:00)The Mind's I (50:00)Peter's articles on Medium (52:00)Get a free audio book and support DataDriven - visit thedatadrivenbook.com! (00:00)TranscriptThe following transcript is AI generated.00:00:01 BAILeYHello and welcome to data driven.00:00:03 BAILeYThe podcast where we explore the emerging fields of data science, machine learning, and artificial intelligence.00:00:11 BAILeYIn this episode, Frank and Andy speak with Peter Voss, peterboat.00:00:15 BAILeYPeter Voss is the world's foremost authority, an artificial general intelligence or AGI.00:00:21 BAILeYIn fact, he is the one who coined the term in 2001 and published a book on the topic in 2002.00:00:28 BAILeYHe is a serial.00:00:29 BAILeYAI entrepreneur technology innovator who has for the past 20 years, then dedicated to advancing artificial general intelligence.00:00:38 BAILeYToday he is focused on his company, IGO, which is developing and selling increasingly advanced AGI systems for large enterprise customers.00:00:47 BAILeYPeter also has a keen interest in the interrelationship between philosophy, psychology, ethics, futurism and computer science.00:00:56 BAILeYI think you will find this interview a fascinating look at the future of AI.00:01:01 BAILeYNow on with the show.00:01:05 FrankHello and welcome to data driven, the podcast where we explore the emerging fields of data science, machine learning and artificial intelligence.00:01:13 FrankIf you like to think of data as the new oil, then you can think of us like well.00:01:18 FrankCar Talk because we focus on where the rubber meets the road and with me on this epic virtual road trip down the information highway because we're still locked in quarantine.00:01:29 FrankAs always, Andy Leonard.00:01:30 FrankHow's it going and?00:01:31 AndyGood Frank, how are you?00:01:33 FrankI'm doing well.00:01:34 FrankWe had a bit of snow.00:01:36 FrankWe're recording this on Monday, February 1st and the East Coast has been blanketed in some snow.00:01:37 Peter VossYes.00:01:45 AndyYeah, we got more than we've gotten, probably since 2018 or so. About four inches here in FarmVille and then almost an inch of ice on top of that, which always makes it fun, right?00:01:58 FrankYeah, the ice is worse than the snow on.00:02:00 FrankBasically so I went out, walk the dog today and one of the dogs and it was crunch, crunch, crunch.00:02:06 FrankSo there's a nice layer of ice over everything which is going to make driving later fun, but I do have.00:02:13 FrankI do have the an all wheel drive car which is fantastic.00:02:17 FrankI will never not own one of those again.00:02:19 AndyNice.00:02:21 FrankYeah, you've seen it's the CRV.00:02:23 AndyYes, yeah, it's nice you did well.00:02:26 FrankI dubbed it the Rocinante.00:02:31 AndyIn case our listeners are not familiar with that, with what Frank is referring to, it is not the old novel.00:02:40 AndyFrank is not tilting at windmills instead.00:02:44 AndyAnd if I got that reference wrong, correct me.00:02:46 AndyI'll just edit that out.00:02:47 FrankOh, you are right, it's from this AM Oh my God, I forgot new book on Cody.00:02:48 AndyNot sure.00:02:51 AndyDonkey Quixoti wasn't.00:02:53 FrankYeah yeah Cervantes I was gonna say from Cervantes book and I'm like oh what was the name of that?00:02:53 AndyYeah so.00:02:59 FrankWhich is the opposite of how most people think, but that's what I do.00:02:59 FrankOK, good.00:03:02 AndyThere we go, but it is actually a reference to both the books and a series, The expanse of which Frank and I are great fans, so.00:03:12 FrankAwesome, but you know who's not covered in snow today.00:03:13 AndyI like it.00:03:15 AndyWho is not covered in snow their guest.00:03:16 AndyOur guest.00:03:18 FrankWho lives in?00:03:18 FrankYeah.00:03:20 FrankI'm assuming sunny or Smokey I guess depending on the time of year California Peter Voss Peter welcome to the show.00:03:29 Peter VossThank you, yes, it's we've got snow on the mountains here, but it's very sunny.00:03:36 Peter VossIt's it's nice and we have a lot less smog these days.00:03:41 AndyVery good.00:03:41 FrankNice so you are the.00:03:46 FrankOne of the world's, or if not the world's foremost authority in AGI or artificially artificial general intelligence, and I believe you are the one that coined the term.00:03:58 Peter VossYes, correct and 2001 myself and two other people. We coined the term artificial general intelligence AGI to really distinguish the kind of work we were doing from, you know, specialized narrow AI which is.00:04:18 Peter VossPretty much what everybody else is doing.00:04:20 Peter VossThe original dream of artificial intelligence was of course, to have systems that can think and learn the way humans do, but that turned out to be a lot lot harder than people thought.00:04:31 Peter VossSo over the years, AI really turned into narrow AI using human ingenuity to figure out how to solve one particular problem, like playing chess or.00:04:41 Peter VossContainer optimization or medical diagnosis and then to write a program or to train data to do that to solve that particular problem.00:04:51 Peter VossBut it's really the external intelligence of the program or the data scientists that is then encoded.00:04:58 Peter VossTo solve that problem, whereas we wanted to get back to the original dream of having a thinking machine that it can figure out how to do these things and and learn more humans do so.00:05:09 Peter VossThat's why we felt we had to.00:05:12 Peter VossYou know, coin a separate term to distinguish it from narrow AI.00:05:16 FrankInteresting.00:05:18 FrankSo for years, AGI has been.00:05:21 FrankKind of thought the stuff of science fiction.00:05:24 FrankI think there was a lot of optimistic people like you said that thought we would have it by now.00:05:29 FrankI know this is kind of a loaded question, but one do you think we'll ever get there and two, what's the sort of time frame we're looking at?00:05:38 Peter VossYes, it's an interesting question, so absolutely, I believe it's it's.00:05:42 Peter VossPossible, and in fact the reason we got together. We wrote a book called Artificial General Intelligence. As I said in 2001 was because we believe the time is ripe to get back to this original dream that the technology had advanced enough. Both hardware and software technology and cognitive psychology. Cognitive science.00:06:02 Peter VossThat we now understood enough and had fundamentally had the tools in place to tackle this problem and to say.00:06:11 Peter VossSo I I absolutely believe that it can be solved soon, and in fact we will leave.00:06:18 Peter VossWe are on on the way of solving this problem now in terms of time frame.00:06:24 Peter VossNormally the way I answer this question is I don't measure it in time.00:06:28 Peter VossI measured in dollars.00:06:31 FrankI like that time is money, so I guess.00:06:34 FrankThat's a reasonable correlation.00:06:35 Peter VossYeah, and and the reason I do, I say that is because.00:06:39 Peter VossStill, today almost nobody is working on AGI. You know, 99% of all the effort in artificial intelligence is still on narrow AI, so if this continues, it will take a long long time for us to reach human level AGI. But if that changes.00:07:00 Peter VossAnd you know the kind of funding that's going into deep learning machine learning suddenly was applied to AGI.00:07:06 Peter VossThen I think it could easily happen at less than 10.00:07:09 BAILeYYes.00:07:10 FrankOh wow.00:07:11 AndyVery cool, so I'm curious is there any like lead in does?00:07:16 AndyDoes time and money invested in deep learning and narrow AI?00:07:23 AndyDoes any of that help move the cost?00:07:25 AndySay further the cause for AGI?00:07:29 Peter VossSlightly, I believe, you know.00:07:32 Peter VossObviously, any advances in languages and data collection in hardware development and the general experience.00:07:42 Peter VossIn that sense, it does help it.00:07:44 Peter VossBut in another sense, it's actually the opposite.00:07:46 Peter VossIt's actually hindering it because a whole generation of software engineers and data scientists are now coming into the field, believing that deep learning machine learning is a way to do it.00:08:00 Peter VossAnd all we need is more data, more horsepower and will solve this problem.00:08:05 Peter VossAnd that's I think barking up the wrong tree, and it's a it's a dead end.00:08:10 Peter VossSo in that sense, what's happening today with deep learning?00:08:12 Peter VossMachine learning is actually counter to achieving.00:08:16 AndyGI interesting very interesting.00:08:20 FrankWas it always that way or it's just the way the market kind of went frenzied over just narrowed AI?00:08:26 Peter VossWhy?00:08:26 Peter VossWell, we've had several windows of AI.00:08:30 Peter VossYou know the the disappointments over the decades.00:08:33 Peter VossYou know, when we had expert systems, people believe that you know they would really, you know, show real intelligence and then it kind of fizzled out.00:08:42 Peter VossAnd so we've had.00:08:43 Peter VossWe've had various windows, and but of course, deep learning machine learning has been so spectacularly successful in several areas.00:08:52 Peter VossYou know, image recognition, improving speech recognition, and you know various other fields that just, you know, it's the only game in town as it has been very, very successful.00:09:04 Peter VossBut people are also starting to realize what the limitations are of it.00:09:11 Peter VossSo yeah, it's it's kind of at the moment.00:09:14 Peter VossThe only game in town, and it has really been successful in many.00:09:17 AndyAreas, So what are those limitations?00:09:20 AndyAnd how does AGI addressing?00:09:23 Peter VossYeah, so fundamentally when you think about intelligence, you know if you think about just common sense.00:09:32 Peter VossIf we talk to a person and we judge them to be intelligent or to be totally non intelligent, the kind of things we expect is that they can learn.00:09:43 Peter VossImmediately that when you say something a, they understand what you're saying and they integrate that knowledge with their existing knowledge so you know if you say my sister's moving through Seattle next week or something.00:10:01 Peter VossThat knowledge needs to fit in somewhere.00:10:04 Peter VossYou know you know the person who's talking.00:10:06 Peter VossYou may know who the sister is, or you may not know who the sister is.00:10:10 Peter VossYou probably know what Seattle is.00:10:13 Peter VossYou may have images of, you know, rain pouring down all the time or whatever, but so you integrate that knowledge.00:10:21 Peter VossAnd if you're not cleared, my maybe the person has two sisters, so then you would ask her, do you mean your older sister you know your younger sister?00:10:30 Peter VossAnd so we expect an intelligent human to basically do.00:10:35 Peter VossYou know what's technically called one shot?00:10:37 Peter VossLearning?00:10:38 Peter VossYou hear something once you see an image.00:10:40 Peter VossOnce you learn that and you integrate it into your existing knowledge base.00:10:46 Peter VossAnd if you're not sure how to interpret it.00:10:49 Peter VossThen you ask clarifying.00:10:50 Peter VossQuestions until you know what it what it is.00:10:54 Peter VossSo you have deep understanding you have disambiguation.00:10:59 Peter VossYou have learning instant learning, one shot learning.00:11:03 Peter VossYou have long term memory.00:11:05 Peter VossYou remember that next week you you know if you paid attention, you will remember that and you have reasoning about.00:11:12 Peter Voss30 now deep learning machine learning as it's done today, really doesn't offer any of those.00:11:20 Peter VossSo if you if you had a human and you told them something and they didn't remember it, they didn't understand that they didn't ask for clarification.00:11:27 Peter VossYou wouldn't think of them as being very intelligent, would you?00:11:33 FrankNo, I mean, my kids are smart, but when I tell them to bring the trash cans back from the street, they'll conveniently forget.00:11:39 FrankBut I, I think I know where you're going with that, yes?00:11:42 BAILeYAll right?00:11:44 FrankBut the question I have, it sounds like you're trying to and I know this is going to be not really good analogy.00:11:50 FrankOr maybe it is you're trying to code for curiosity.00:11:54 Peter VossThat's very much part of it, but you know even deeper is understanding.00:11:59 Peter VossBasically, when you have some input, do you?00:12:02 Peter VossDo you understand you know what the implications are, how it fits in with the rest of the knowledge that you have?00:12:08 Peter VossAnd you know, even that, that's sort of more even more fundamental than curiosity.00:12:13 Peter VossBut yeah, curiosity is then wanting to gather more information, so this is inherently an interactive process.00:12:22 Peter VossYou know, an intelligent person would ask follow up questions you know they would want to kind of.00:12:29 Peter VossFill in the pieces of the puzzle and you know that they can be more.00:12:33 Peter VossIn fact effective in their communication on their or their job.00:12:37 FrankRight so.00:12:37 Peter VossSo yes, that's definitely part of it.00:12:40 FrankSo calling back to your example of someone's sister moving to Seattle you you would ask, you know, I didn't know you had a sister or how many sisters do you have or how many siblings do you have and.00:12:51 FrankWhere is she moving to?00:12:52 FrankWhy?00:12:53 FrankI guess that's kind of.00:12:55 FrankI guess it's all about building that knowledge map inside.00:12:58 FrankYour head or then your head being could be a program I guess.00:12:58 BAILeYExactly.00:12:59 BAILeYOK.00:13:02 Peter VossYeah, and deep learning machine learning really doesn't allow for that at all.00:13:07 Peter VossYou know you accumulate masses of data and you train a model, but that model is then static.00:13:14 Peter VossIt's a read only model.00:13:15 Peter VossYou know, it doesn't dynamically learn, so it may have a sort of a knowledge graph, but even that knowledge graph is.00:13:23 Peter VossIs very opaque, it's.00:13:26 Peter VossYeah, it's not scrutable you know and and this is this is such a big problem with deep learning machine learning that you don't know why it gives a certain response, which is a huge...

In this episode, Frank and Andy speak with Dan Burcaw on Entrepreneurship, Using AI to Stop Customer Churn, and Deploying Code onto Nuclear Submarines.Show NotesTranscriptThe following transcript is AI generated.00:00:00 BAILeYHello and welcome to data driven.00:00:02 BAILeYThe podcast where we explore the emerging fields of data science, machine learning, and artificial intelligence.00:00:09 BAILeYIn this episode, Frank and Andy speak with Dan Burke or Dan is a serial entrepreneur who has founded four companies each on the forefront of a major technology wave, open source software, the smartphone.00:00:23 BAILeYCloud computing and now machine learning.00:00:26 BAILeYCurrently he leads Nam Eml, a company focused on helping app developers start and grow mobile subscription businesses.00:00:34 BAILeYIf you follow Frank and or Andy on social media, you certainly have heard them bang on about their secret project.00:00:41 BAILeYI will drop a one word hint here foreshadowing.00:00:45 BAILeYNow on with the show.00:00:48 FrankHello and welcome back to data driven.00:00:50 FrankThe podcast where we explore the emerging fields of data science machine learning, an artificial intelligence, and if you like to think of data as the new oil, then you could consider us Car Talk.00:01:02 FrankBecause we focus on where the rubber hits the road.00:01:05 FrankSo with that as my guest on this pandemic road trip, that hasn't happened.00:01:13Yeah.00:01:13 FrankBy my copilot here is Andy Leonard.00:01:16 FrankHow you doing Andy?00:01:17 AndyHey, I'm doing pretty good Frank how are you?00:01:20 FrankI'm doing well, I'm doing well.00:01:21 FrankI had a kind of an architecture session this morning, so that went really well.00:01:27 FrankIt was.00:01:28 FrankIt was an interesting conversation and I love doing those.00:01:31 FrankThose are always fun.00:01:32 FrankHow about?00:01:32 AndyYeah.00:01:33 AndyYeah, so I'm proofing the next book.00:01:36 AndyProofing is the absolute last chance to remove all of the typos I've left in.00:01:42 AndyAs I've gone through the last three full edit sessions and there's still some there.00:01:47 AndyFrank, I'm convinced that the next book is going to have, you know, have a fair share of those.00:01:52 AndyWhat I'm really concerned about.00:01:54 AndyIs making sure that the demos work an yeah that's you know it's it's tedious and it's the LastPass so you know it's like is this over yet? Yeah, I'm sick and tired of reading this guy's writing and it's me so.00:02:10 AndyYeah no.00:02:10 AndyBut yeah.00:02:12 FrankThat was the hardest part.00:02:13 FrankPeople asking.00:02:14 FrankLike when I wrote a book on Silverlight an aside from it being about Silverlight, the hardest thing wasn't so much writing, it was having to go back and re edit my own stuff and like.00:02:24 FrankYou know, and I would look at it and be like man like I'm a terrible or.00:02:28 AndyThat's I have said over and over again to my computer monitor who wrote this crap.00:02:33 AndyBy a friend if you live.00:02:33 AndyBut Fortunately for this is a second edition, so an it's one of those second editions where I kept the first 10 or 11 chapters.00:02:43 AndyI I changed from my writing language.00:02:46 AndyI wrote it like three years ago.00:02:48 AndyAnd I really this grew out of a series of blog posts that I wrote back in 2012. It was all in VB back then, Visual Basic. And so I wrote it that way in 2017 and for the 2nd edition I went back and updated all of that. That's really the only thing I changed was I went to C sharp.00:03:06 AndyAn I kind of needed to because the rest of the book was going to be in C sharp anyway.00:03:12 AndyAnd so yeah, that's that's kind of how it went.00:03:15 AndyAnd for anybody listen, it thinks wow, Andy is smart.00:03:18 AndyHe's written a book about C sharp.00:03:20 AndyHe must know C sharp really, really well.00:03:22 AndyI say throughout the book I am not a C sharp developer.00:03:26 AndyI feel like I'm working my way up to being a noob, but but.00:03:29 FrankDon't you work classes?00:03:31 AndyI do wear glasses.00:03:33 AndyYes, yeah.00:03:33 FrankSo you can see sharp.00:03:36 AndyI did.00:03:36 AndyThey took me awhile.00:03:37 AndyDo you have your sound effects running from I?00:03:39 FrankDo were back in Zend Caster.00:03:41 FrankSo for folks listening like I don't remember this being on the live stream.00:03:45 FrankIf it's not, we're doing this the old fashioned way right then, and don't worry, Andy and I've been live streaming a lot, which you probably noticed, but today we have a very special guest, don't we, Andy?00:03:48 FrankUm?00:03:56 AndyYeah yeah, Dan Burke all is awesome.00:04:00 AndyHe's a co-founder and CEO and I hope I say this right, is it?00:04:04 AndyIs it nami? Nami ML Dan.00:04:07 Dan BurcawYeah nami. Like tsunami.00:04:09 AndyAh OK, I got it right the first time NAMI AML and it's a really smart service for monetizing digital products with subscriptions.00:04:09 FrankWell.00:04:19 AndyAnd just he's had a whole ton of experience working in, you know, in marketing for the Oracle Marketing Cloud, working with the mobile product for that.00:04:31 AndySo pretty smart Guy joined joined Oracle back during the acquisition of Push IO and.00:04:39 AndyPush IO was a leading mobile messaging provider as well.00:04:44 AndyAnd he served there as a Co founder and CEO.00:04:47 AndyThere's a bunch more in here about Nan, an it all kind of boils down to super smart, successful guy.00:04:54 AndyWe've had a little bit of banner before we click the record button an I can attest to.00:04:59 AndyThat is really enjoyable conversation.00:05:01 AndyI look forward to this show.00:05:02 AndyThanks for being here, Dan.00:05:05 Speaker 1Really happy to be here.00:05:05 Speaker 1Really happy to be here.00:05:06 Speaker 1Thanks for having me.00:05:07 FrankAwesome, so you're a serial entrepreneur and you founded a bunch of companies.00:05:13 FrankUm, but my favorite part of the bio I read on you was that.00:05:18 FrankYou wrote software that ended up on a nuclear submarine.00:05:23 Speaker 1Yeah, that's right.00:05:26 Speaker 1It's it's hard.00:05:26 FrankThat that totally away I was like what?00:05:29 Speaker 1It it's it's hard to even tell that story sometimes because it's so unbelievable.00:05:35 Speaker 1I 17 years old at the time.00:05:38 Speaker 1The company that I cofounded was building a flavor of Linux.00:05:46 Speaker 1A flavor of Linux that was designed to run on Apple Macintosh hardware.00:05:52 Speaker 1And at the time.00:05:52 FrankInteresting.00:05:54 Speaker 1Then the the reason for that was that Apple was using the power PC chip power PC chip in that moment of time. You know, we're kind of talking in the late 90s. Early 2000s had fantastic price per performance per Watt, which is a metric that a lot of folks in the kind of high performance computing world look at when they're trying to figure out.00:06:11 AndyMe.00:06:18 Speaker 1How to build these kind of supercomputer clusters?00:06:21 Speaker 1And so it just happened at that moment in time, the Mac would had had the best price performance per Watt because of the chips that they.00:06:29 Speaker 1We're using and so we we ended up doing a deal with Lockheed Martin and the US Navy to build a cluster of Macs running Linux.00:06:45 Speaker 1That were deployed across the US Navy nuclear sub fleet for the purpose of doing sonar image processing, yeah.00:06:53 AndyWow.00:06:55 Speaker 1The the the software that I wrote was related to.00:07:00 Speaker 1You know how folks on the boat would have to manage these units if there was issues, how would you know?00:07:07 Speaker 1Kind of the maintainability repair ability was a big issue when you're actually out at sea and trying to have this stuff run in kind of a mission critical fashion so.00:07:17 Speaker 1We ended up.00:07:17 Speaker 1I mean it was this was such a crazy project because the hardware was modified hardware.00:07:22 Speaker 1It wasn't off the shelf Apple hardware, it was Apple Hardware and then we did a bunch of things to it and then it was Linux and then it was some custom software that made the whole thing operate an.00:07:35 Speaker 1So it's it was.00:07:37 Speaker 1It was a nutty project, an I'm.00:07:40 Speaker 1Looking back on it now, I'm surprised that it had ever shipped quite frankly.00:07:46 FrankSpoken like a true engineer, right?00:07:48 FrankYou're always you always look at your flaws and like Oh my God, that's actually running.00:07:56 FrankSo so you you where did you go after that?00:08:00 Frank'cause it says you know you're a serial entrepreneur and so how did you get into?00:08:05 FrankI don't want to steal.00:08:06 FrankKind of our pre canned questions Thunder but.00:08:11 FrankTell me how did you get into A&ML? Or were you doing ML on those on those retrofitted Max?00:08:18 Speaker 1No, we weren't.00:08:19 Speaker 1We weren't, but but you know, I think that part of the hype that world of high performance computing where a lot of our customers were, you know, national labs or defense oriented things.00:08:30 Speaker 1I mean, part of the appeal of what we were offering in that period of time was that they were running algorithms an doing some of this stuff.00:08:39 Speaker 1You know, obviously ahead ahead ahead of their time and they need it.00:08:43 Speaker 1There wasn't the cloud computing yet, so they were literally just trying to assemble the biggest.00:08:49 Speaker 1Supercomputers using off the shelf hardware that they possibly could so we weren't writing the algorithms.00:08:55 Speaker 1We were more enabling these algorithms to be run, but I would say the Fast forward is that in terms of my career, is that working on that led to?00:09:09 Speaker 1Being involved in sort of the mobile ecosystem from the launch of the App Store and the iPhone back in 2000, seven 2008 and in a way it was very very similar to what we did with the submarines. Because you were dealing with constrained hard.00:09:25 Speaker 1Where you always had to care about performance and battery life and battery life, less so on the Subs.00:09:31 Speaker 1But some of the same sort of constraints where you're trying to get the best performance you can out of these things and operating in that mobile landscape and building apps for some of the largest consumer brands.00:09:46 Speaker 1And then you guys mentioned in the in the intro about push IO.00:09:49 Speaker 1This mobile messaging company that we.00:09:51 Speaker 1Built, we ended up at Oracle building this mobile marketing engine is part of the Oracle Marketing Cloud an and one of the things that we saw there is that now.00:10:03 Speaker 1Fast forward to kind of more modern times and there's such a prevalent use out there of.00:10:11 Speaker 1Technology like email, you know email marketing systems and push notifications in the world of mobile in order to tackle kind of a fundamental problem that exists with some of these products, which is the user.00:10:28 Speaker 1Download your app, let's say, and they use it and then and then they churn, and then they abandon an and you as a publisher of a product like this, is one of the battles that you're trying to fight is how do I get them back into the experience and so are sort of observation is we were.00:10:44 AndyRight?00:10:48 Speaker 1You know, done our tenure there and we're looking to do something next.00:10:52 Speaker 1And new was a couple of things.00:10:55 Speaker 1The first thing we saw was that with the iPhone 10, I think it was.00:11:01 Speaker 1Apple released.00:11:02 Speaker 1Face ID.00:11:03 Speaker 1And that was using algorithms running on the device, so the benefit was you could unlock the phone very, very fast, but also it had some privacy characteristics where Apple doesn't need your face and the kind of the point cloud representation of your face to be up on their servers somewhere.00:11:21 Speaker 1That was really intriguing to us.00:11:23 Speaker 1The other thing was that we saw that the app economy, so to speak, was in transition from kind of the early days of where it was paid downloads.00:11:33 Speaker 1Transitioning to kind of in app purchases, which the game ecosystem has really been been focused on to trying to create more durable, sustainable revenue models through subscription.00:11:35 Speaker 1Which is right?00:11:46 Speaker 1And so how we sort of arrived at focusing a lot on data at NAMI.00:11:53 Speaker 1Is that it?00:11:54 Speaker 1It seemed to us like there was.00:11:56 Speaker 1If we we would, we really were excited about an idea that if we could.00:12:02 Speaker 1Help the guy.00:12:04 Speaker 1Is.00:12:04 Speaker 1App publishers a mechanism to send way fewer push notifications.00:12:10 Speaker 1An email messages because they had a technology stack that could allow them to detect in the experience, right directly on the device that somebody was showing signs of churn, or that somebody was showing some.00:12:25 Speaker 1Early intent that they might be a a candidate to be a subscriber, and so just that idea that maybe there's a way that we could be part of cutting down the messaging load by making the actual experiences smarter and more intelligent about what users are doing was where we.00:12:42 Speaker 1Started.00:12:43 FrankThat's interesting.00:12:43 FrankThat's it.00:12:44 FrankWhat sorts of signals?00:12:47 FrankThat you can collect given specially with Apple's kind of enhanced privacy policies that they've been been doing.00:12:55 FrankAn what?00:12:56 FrankWhat sorts of signals kind of indicate churn?00:13:00 Speaker 1So you know it is.00:13:01 Speaker 1It's a great question.00:13:02 Speaker 1When we started out we were thing.00:13:04 Speaker 1Gain, we're going to collect all this crazy stuff.00:13:07 Speaker 1I mean, we were even thinking at one point in the early prototyping that you know, maybe maybe, what carrier the user is on is some signal.00:13:16 Speaker 1Maybe the device form factor, whether it's the really expensive version of the phone or the lower you know there's all these things that we were thinking about, but.00:13:24 Speaker 1When when?00:13:27 Speaker 1And we're not my cofounder and I are not experts in this field, so one of the things that we did was we recruited our CTO who has a PhD in applied math and had been building data science animal models, kind of in production at, you know, in the real world.00:13:46 Speaker 1Applications of places like the Los Angeles Times and Tribune Publishing and one of the first things he told us when he came in was guys like, wait, you're trying to?00:13:55 Speaker 1You don't need all these days.00:13:56 Speaker 1Points a lot of what you're trying to collect just isn't isn't going to move the needle, and So what.00:13:57 Speaker 1Huh?00:14:03 Speaker 1It really gets to both on the so we look at, you know from subscriptions we're looking at.00:14:07 Speaker 1Kind of two things.00:14:08 Speaker 1One is what are signals that show that somebody might be have a propensity to purchase.00:14:17 Speaker 1And then, secondarily, that early turn detection, or kind of likelihood to churn.00:14:23 Speaker 1And it turns out it's it's pretty simple on some level, because it's really about the behavioral signals around engagement.00:14:34 FrankInteresting soon.00:14:34 Speaker 1So are they using the app or are they using the app a lot?00:14:38 Speaker 1Or they did they used to use it a lot and now they're not using it as much so those are kind of the key?00:14:44 AndySignals, so you're not popping up little boxes and saying, do you want to keep using the app?00:14:51 AndyCheck yes or no.00:14:54 Speaker 1No, I mean it's it's.00:14:55 Speaker 1It's funny, you know.00:14:57 Speaker 1I have a friend that has that has a company that that powers some of that around the ratings right?00:15:05 Speaker 1Do you want?00:15:05 AndyYeah, yeah.00:15:05 Speaker 1To make this.00:15:06 Speaker 1Yep, and you know they have a really fascinating take on it, which is that.00:15:11 Speaker 1Because whenever I see one of those, I hit no, I don't.00:15:14 Speaker 1I you know, I just like want to dismiss it an.00:15:17 AndyYeah, yeah.00:15:18 Speaker 1Yeah, he's got a strong viewpoint that by by asking a user a binary question it provides them better data for what they're trying to do around kind of customer sentiment an so I just thought I was fascinated by that because whenever I see one of those ratings popped up so I just wanted to like.00:15:34 AndyInteresting.00:15:41 Speaker 1I want to say no, even if I like the experience on some level, I have a visceral reaction that's just like I leave me.00:15:47 FrankNo.00:15:48 FrankRight, right?00:15:48 AndyWell, I wonder if that's00:15:48 FrankWell, it's always when you're sorry, ID.00:15:50 AndyThat's OK, go ahead.00:15:52 FrankIt's always when you're trying to do something or the kids are screaming like do you want to write this?00:15:52 FrankIt's always when you're.00:15:56 FrankLike no, I want to use this stupid app like even if I like it.00:15:58 FrankBut what I find myself doing and I've as I'll say not now like like remind me

In this episode, Frank and Andy talk about staying motivated in the new year, answer questions from the audience, and share a little about their secret project.This episode was originally recorded on an impromptu livestream and  in a delightful surprise Andy was able to join.

In this episode, Frank offers some encouragement for people hoping for a better year in 2021.This episode was originally recorded on an impromptu livestream and <break time="0.3s" /> in a delightful surprise Andy was able to join.Links:Get a free Audible book on us at https://www.audible.com/ep/creator?source_code=PDTGBPD060314004RTranscript Coming Soon

In this episode, Frank interview Baby Supriya about her journey from student to professional data scientist.Transcript coming soon.

In this Thanksgiving Data Point, Frank sends a special message of thanks to you, the best audience in the world!Show NotesDid AT&T Predict the Future?http://franksworld.com/2020/11/26/did-att-predict-the-future/Transcript 00:00:00 Frank Hey, what's up is Frank here from data driven? Just wanted to take a moment here. It's Thanksgiving here in the US. I'm actually sitting by the by the ocean on the beach. 00:00:15 Frank And it's a beautiful day. 00:00:19 Frank And God. 00:00:21 Frank Some interesting interesting email the other day from website called Pod Stats or Pod Status. You'll see I have my other production assistant with me, but I just wanted to say thank you to all the listeners who helped made data driven successful over the years. Can't believe that tomorrow. 00:00:42 Frank It's been four years since I had the idea for data driven. Next week will probably be. It'll be about four years since I asked Andy to be the cohost we've been rocking it pretty well. We're at about 160,000 downloads. 00:00:55 Frank 265 or 266 shows an. 00:01:03 Frank Just wanted to say thank you. 00:01:05 Frank Actually got an interesting email the other day from a website called Pod Stats Pod status. 00:01:11 Frank And apparently we are very highly ranked where the 29th ranked podcast in technology in Italy. So I want to say gratze. We also rank very high and definitely in the top 50. In Sweden, Thailand, Norway in Brazil. 00:01:30 Frank So thank you, I only know how to say thank you in. 00:01:35 Frank Italian sorry, but I would have to go back and figure out how to say it in those other languages. 00:01:46 Frank I'm sorry about that, but I will go back and figure out how to say it in the other language is another thing. If you've been very eagle eyed in terms of our show notes and the transcriptions. 00:01:57 Frank Uh. 00:01:58 Frank We have we have a name now for the AI voice over Lady probably do more formal show on it. But you know what? 00:02:07 Frank Not gonna do it, figured I would just get the information out. Right now we call her Bailey which is an acronym for British AI Lady. You can look in the transcripts. You'll see her kind of listed as there is a name. 00:02:23 Frank Interestingly enough, we changed up how we do our transcripts. I used to use video indexer but now word online you can actually upload the audio file, the MP3 file and it will actually not only do the transcription and the timestamp, but actually the speaker identification too. So we actually test this out. 00:02:45 Frank And it's pretty accurate, so you'll so hopefully now are. 00:02:52 Frank Hopefully now are. 00:02:55 Frank Our transcripts are much more accessible. That's something we've been meaning to do and. 00:03:01 Frank Yeah, oh, I see Andy's on hey what's up? Andy yeah we I shared that email with you and yeah, we are we're we're we're reaching the top 30 this is pretty good I'm I'm excited I'm happy about the show. Happy I'm thankful Thanksgiving right? 00:03:18 Frank So I'm thankful for having Andy as a good friend and a cohost on this journey on this epic road trip down the information superhighway. As we say in our standard intro and but he was basically talking about all the things that look very futuristic in those commercials and. 00:03:39 Frank The my dog is about to pull my arm off. I can feel it. 00:03:43 Frank And. 00:03:46 Frank So. 00:03:47 Frank Yeah, so it's interesting that how how that you know. So he kind of goes through. It's interesting from a language point of view, 'cause I was alive in 1993. I was in the middle of college and all that stuff seemed I wouldn't say in pop. 00:04:00 Frank Possible seems a little far fetched in a little improbable, but it's interesting how that video predicted touch screens. The widespread use of touch screens so it held up pretty well, except for the fact it wasn't really a T&T that was a major player in that, and if memory serves the AT&T we know today is actually a rebranding of singular, which was another company entirely so. 00:04:24 Frank I'm sure someone will call me on the comments if I'm wrong. 00:04:28 Frank But just wanna say I love you too man. 00:04:32 Frank See Andy's comment. Yeah man, I'm just thankful to have good people in my life. Like Andy. I'm happy to have a great audience that I have happen. Will be happy to be able to, you know, spend some time and I'm unplugged by the ocean. 00:04:48 Frank So happy Thanksgiving to everyone. I'm going to sign off now and might do another quantum show. Probably tomorrow, maybe not today because I had a mental breakthrough in terms of what I was able to figure out by watching this video. And I might even scored a new guest for that show. So with all of that. 00:05:10 Frank From all of us to all of you. 00:05:13 Frank You have a great Thanksgiving if you don't celebrate Thanksgiving. I hope you have a wonderful Thursday.