Hello everyone, my name is Phil Winder and I run a business called Winder.ai and we are AI consultants, we do development and consulting in the fields of machine learning, reinforcement learning and demo-lops as well. So it's the application and the operation of those AI applications. I'm also the author of O'Reilly's reinforcement learning so I know quite a lot about that. But today we're going to be talking a lot more about data engineering. So I'm here with my colleague Enrico and Enrico has done a load of really cool work investigating the ecosystem surrounding general purpose compute and whereas if you come from the Hadoop, well you might want to plug your ears in or something because there's going to be a bit of Hadoop bashing in this presentation. So in terms of the outline, I'm going to start digging into just some high level concepts about what data science is and specifically the life cycle of data engineering because it is relevant to this project and it is relevant to what Enrico is going to say but you do need a little bit of background information in order to understand it. Then Enrico is going to jump into a load of examples of how you do this in various frameworks and he'll sort of talk about the choice of frameworks that he's chosen to analyse a little bit later. But then he's going to talk about the pain and specifically we're going to try and highlight the fact, if you wanted to just get the 10 second version of this presentation and the main reason why we're so interested in this project is that most data engineering and most data science tooling is rubbish. It's really not very nice to use. It's really hard to use. So if we have an opportunity to build something that is nice to use, that's going to be great. Then I'm going to try and sort of map those solutions back to the portfolio that I've presented a little bit earlier and try and pull out some key themes and ideas that I think Baclau or the subsequent version of Baclau needs to adhere to. OK, so to begin with, I wanted to try and describe what data science is and the workflow and the life cycle, but specifically where the pain points emerge in this life cycle. A number of dimensions that you could use to try and describe this. I chose these two. I can't quite see the arrows that are going at the top there but it doesn't really matter. Basically we've got two axes yet. On the y axis up and down, we've got the traditional data science life cycle. So this is the thing that's taught in most data science courses. This is how you go from having some data to a serving usable product at the end and we'll go through those phases in a little bit. On the other axis, I've called it AI maturity but really it's just a normal engineering project maturity. You've got different phases in the development of your application that starts off with trying to prove the viability of something and you go through various different stages. Again, you may have more or less of these stages and phases but eventually you're trying to get to production. That's the ultimate aim. One of the hardest things to describe to non-data scientists about this process is that jump from proof of concept to MDP or that jump from MBP to production. There should be like a massive gulf, a big trench in between those two things and you've got to try and span that trench because it's a bit like with a projector today. All you want to do is just plug that cable in and you want the projector to work but the projector gods are just saying, no, no, your laptop's not good enough. It's not going to work and it's the same data science. You've got your code, you've got this pandas code that looks really simple and really nice and it's pre-processing your data. I just want to put it out there on the internet or I want to put it out there on a cluster or something and you've got to go through a complete translation process in order to do that and it's really horrible. On the left-hand side, we've got data working with the data. We've got feature engineering so that's working with raw data and turning it into something that's useful in the model itself. Important data engineering step. Then we've got modelling which is principally the role of a data scientist and they're responsible for investigating and analysing and deciding upon which algorithm and which implementation they're going to use to build this model. You go through some training process, the evaluation is trying to figure out how are you doing and then the deployment. This is like the traditional data science process. When you mix that with the AI maturity, you effectively get this pattern where when you're doing a POC, you're just trying to prove whether the whole idea is viable.  You're working on your laptop, you're working in notebooks, you're working with local data, it's all local. You're just trying to prove that it's even possible. When you make that jump to try and get something in front of a user, then you have a whole load of rework that needs to try and make these things more scripted, more declarative, more definitive basically so that a larger system can take over and run it. Finally, you get into the prods and you've got to be reactive. So there's three sort of key phases there. The other important dimension to get into this picture is that this isn't data science. Data science used to be like, in the past when you said you were a data scientist, you did all of this, but in fact that doesn't happen anymore. In most companies where there's more than one data scientist, this role has been split out into specific sub-domains. It's been split out into data engineers, into ML engineers, into DevOps obviously, into ML ops platform engineers, and so on and so forth. And so there's actually a real mix of people all working on this one so-called data science project. It's not just a data scientist. And I think when we're talking in the context of Black Law as it currently stands, we're not actually talking about data science at all. We're talking about data engineering. We're talking about we have the data in place. We need to do and operate upon that data to produce other data. And that is exactly the job description of a data engineer. So if I start focusing a bit more now on the specific role of a data engineer, then again, they have very different needs and very different tasks that they need to achieve at different points in the project life cycle. So when you're at a proof of concept phase, the whole goal there is to attempt to give the data scientist the data they need in order to do their job. But in order to do that, you need to find it. So it needs to be well-catalogged. It needs to be understandable. You need to mine it, which is kind of a way of describing sort of mixing data together in order to produce something useful. You've got access level control issues. And finally, that all needs to be locally accessible to the data scientist. When you get into some kind of almost production state, then we need to start turning these things into pipelines so that the feature engineer that's going on is encoded and is repeatable. We've got schemas that need to be defined because if you don't have schemas for your data, then it's very hard to test that your data conforms to that schema so on and so forth. And then finally, in production, you get sort of higher level governance related issues with regards to your data in terms of monitoring, making sure it's OK, testing, making sure it's good quality, scalable, guvernable, et cetera, et cetera. So I'm going to come back to that slide a little bit later on because I think Baklal does map on to some of these requirements. And so I'm going to sort of attempt to do that a little bit later. But for now, I'm going to pass you over to Enrico to talk about. Thank you, Phil. So here's an overview of some of the popular general computing frameworks. So I just want to run a little test here. Raise your hand if you've heard of use any of these tools before. I heard some good laughs before. Well, it's cool. OK, so just to recap quickly, we have Python, PyData kind of stack, top left corner. We have database systems in the top right corner and big data players at the bottom. Let's take a look at some of these. Well, now, so Pandas is a Python for data analysis. It's very popular because it's a data frame object. It's a table you can run lots of interesting data managing on it. It comes with utilities for managing and sampling, missing data, and so on, and so on. Very, very versatile syntax. Postgres is essentially a relational database. You can essentially use it in any language. It comes with lots of adapters. Popular syntax is a SQL declarative syntax. Now, these two. So when do you want to use the other two players on the list? Dashing a snowflake, essentially when your data set doesn't fit in your laptop, you may want to consider these other two players. But there, dashing a snowflake in terms of syntax or approach to data are quite similar to Pandas and Postgres respectively. Let's take a look at a couple of examples. Now, in this example, it's structured tabular data processing. The idea here is we have a real estate housing data set, and we just want to compute average aggregated per zip code, just an example. On the left-hand side, you have a Pandas example. So, as you can see, data importing a library and data parsing and reading is just a matter of one liner. And processing it, that's also very concise.  Now, on Postgres, it's slightly different. You first need to create a table which is a way to specify your data schema. And it's got to be very strict on that, and verify your data set complies. Data loading is also fast, and what's also highlighted by the red arrow is, yeah, it's a SQL query to compute that average aggregated, quite similar to Pandas, I would say. So, let's take a look at these, yeah, these two players have been making history in the big data world. Well, ADUP is essentially a distributed storage system, ACFS, and it also comes with a computing engine that implements and might produce paradigm to processing. It's mainly Java tool, quite famous for its very verbose, and also it has a clumsy API compared to modern tools. It scales out well, though its intermediate processing steps are going to be stored on these, and this makes the world computing a little bit slow. In part, it's the new successors trying to solve that problem essentially by running in-memory computation makes it faster. This is also the Scala Java kind of tool. What I want to highlight here, though, is that these tools are production-ready, right? So, it means they provide you stability, high availability, well-configured, and also an example later, the introduced concept of job and pipeline, and some try to have a more declarative syntax and scale out to very, very large data sets. Pandas, that's really hard to personalize on at the deployment phase, very, very good on large laptops. Let's take a look at an example of these two. Now, Spark. This is the same average house price example I showed before, and this is in Spark. That's the Scala code. As you see, it's a little bit more verbose than the previous options. You can really see that, essentially, you start by creating some context that allows you to communicate and connect to your remote cluster. Then there will be a session set up where you configure your parameters and maybe past credentials or whatever, or you find your job there. Then, Spark also comes with a data frame structure that somewhat reminds you to the Pandas data frame. Here, you can just change method calls, group buy, average, as I let everybody harrow. This stuff doesn't just run right away. You need a way to package this up into a jar file, which is essentially a package that ships your code along with the required dependencies and so on. A great possible way to run this is by using Spark Summit CLI, where in this case, you plan it to your cluster, local cluster in the example, can be remote, and you pass along your jar file as well. This creates a job and creates a DAG. This is essentially the first execution at a later stage when the cluster will be able to process that. You can really see it's quite different than the local kind of setup. How about Hadoop? Where does it all fit in all these? I say it's really hard to cage an elephant. In fact, as we said, a Hadoop example doesn't even fit on this slide, but let me show you something later. We don't really see the two axes here, but essentially the two errors, but we have data scale, scale on the X axis, and flexibility on the Y axis, and also other possible axes. The idea here is that there are different ways to look at these landscape analyses. As we said, it's really important to look at production readiness, for example. In that case, you will be looking at the right hand side of the screen, but if we look at essentially trade-off between flexibility, the tool gives you a data set scale, we see that as you grow in a way in the capability of managing large data sets, then your flexibility and complexity increases. That's definitely a hurdle for data protectioners. Talking about hurdles, it's kind of intuitive, so simple tools have lots of pros. It's very easy to set up and maintain, easy to use, maybe friendly to your usual text stack or language, easy to debug, and here, for instance, when you need to debug a Doop job or PySpark job, that can be very, very painful. You also want to take a look at or consider community support. Some frameworks are doing very, very good in pushing that. However, when it comes to shareability and capability of sharing pipelines, artifacts, and being declarative in some way, then that's what most frameworks are struggling with. Another example we mentioned before is the headache in moving from a local setup to a cluster space with big data tools. Here's an example. You have pandas, this runs on your local, very concise syntax, but then you have a Doop on the right, and this is a map of these job runs on a large cluster. Problem is, that's not even the whole thing because there's much more behind that. First of all, you're going to need to connect and test that connection to your distributed storage, and there should be arrows pointing at those rectangles. When you press with a large data set, there's always that single data point that's going to fail your execution, so you want to introduce that exception handling code, of course, maybe add schema and validation. At some point, you need to distribute that. You need to allow your cluster nodes to take your application and run it. You may want to package it in a Docker container, distribute that, or maybe push it to a Docker registry, distribute that across your nodes, figure out notifications, and so on. Finally, you're able to do your Hadoop submit or Spark submit run. You'll have to configure resources such as CPU and so on, launch your job, again install CLI and so on, and then monitor it. If that fails, you'll have to go back to configuration or maybe even coding, and it's right there. It can be very painful. The thing is, it's not a one-man show. You'll probably need a world team next to you. Well, with that, I'll give it back to Phil. Thank you. Oh, Zapper Rooney. It's going to be the chair, it's like a static chair, my hair sticking up on end. Just coming back to some of these ideas as well, I think, just trying to sum all of this up. So firstly, in order to do data engineering and data sciences skill, you don't do it yourself, you do it as part of a really big team. It takes a lot of people to make this work. I think that's one big takeaway. Another big takeaway is that there is no debugability in any of these high-level orchestrators. If you want to test your data engineering code, you just try it, and you wait until it fails. When it fails, you then go through the horrible Java stack traces that are 600 lines long, and you figure out which little thing caused it to fail. Stack traces, if you're lucky, most of the time, it fails silently, or rots your output to someone you know that you have no idea where it is. That's right, yeah. Even in Spark, which is somewhat better in terms of above team usability and stuff, Spark excels in situations where it's doing analytics like workloads, and they have put a lot of effort into trying to optimise the performance of SQL-like jobs. One of the ways in which they do that is that they dynamically control the scale out, the fan out of the job. That's all the code that we had before. This code here, this code actually defines the DAG. This defines the pipeline that is going to run in Spark, but you as a person, you don't really know what that DAG looks like, because Spark doesn't know at this point. It doesn't know until you submit it. Then it figures out how it's going to run it, and that makes memory management incredibly difficult, because any one of those steps could be a little bit bigger than 64 gigabytes or however big your node is, and it'll fail. So it's really hard to do memory management in Spark. It's really hard to figure out what your pipeline and DAG is. It's just all of these things that sort of sound like little nits, but they add up to just being really painful. Why is my Spark cluster spending 80% of its time shoveling data between Spark clusters? Yeah, exactly. In fact, operating Spark clusters is a job now in big companies. There's people at Uber whose entire job is to optimise the Spark cluster. So I wanted to sort of come back to this slide again and just sort of try and place some of these tools into the lifecycle. As you can see, when you're doing your POC, everybody uses Pandas. If you wanted to try and scale that job, then you can use something like Dask, which is really nice to use, and it does allow you to scale, but it doesn't provide the production-level quality, declarativity, monitoring, all of the things that you need for intensive jobs. Finally, on the right-hand side, you get the schedulers of the world. They're okay, but they're not great. I think that this is really the landscape that we're competing with when we're talking about back-of-a-how. These are the things that we want to be comparing ourselves to. So going back to what we need from back-of-a-how as an ML engineer, then we go back to this picture again. This is an arbitrary picture. You speak to another data engineer, they pick another set of criteria, but I thought this was a pretty good representation of the day-to-day job. What I'm proposing is that we could possibly either build back-of-a-how to solve some of these problems or build tools on top of it to solve some of these problems. So, for example, on a data access level, companies need to have access controls in place to be able to control the use of data. For legal reasons, for regulatory reasons, for business reasons as well. They need that data to be exposed in a catalogue. It needs to be searchable, it needs to be observable for the people that need to see it. The data needs to work locally. When it comes to pipelines, in my opinion, I quite like specifying the DAG myself, specifying the pipeline myself, as opposed to letting the tool optimise it for me. It's only because, in my head, I've got a mental map of what the DAG is doing, and that helps me debug. You could argue that if you provide a better way of doing debugging, then maybe you can allow the framework to control the DAG a bit more. Schema, I don't know how you'd handle schema. We could talk quite a lot at length about what could we implement a lot of this? I think basically what I'm saying is that we need to present Baklau in this way in order to get data scientists on board. We need to be familiar, we need to talk in familiar terms. We can't use the Web3 terms, you can't use the words DHT, which I didn't know until about three hours ago, because I didn't know what that acronym meant. We need to talk in terms of data catalogs, not DHTs and so on and so forth. There's going to be some sort of interface that we're going to have to cross in order to talk in their language. Other things that have popped into my head over the day that I find really interesting, we've been talking about verification a lot in the morning, and we were talking about verification in the sense that we're trying to verify and prove that they did the work that they did. But because ML and pipelining and data is so uncertain in the first place, most of the time, I'm not going to get attacked. It's not going to be this guy that's pretending to do work, and that's going to cause my things to error. It's going to be my fault for the things of error. The data is crap and I haven't checked it and I haven't cleaned it properly, or my ML model is going to diverge and it doesn't actually learn. So I started to think about whether we could actually use the verification interface as a part of the testing and quality element of the lifecycle and the monitoring as well.  Things like that. Then we've got sort of governance. A big thing that I'm a big advocate of is lineage in data science and provenance, and the idea there is that it's really important to know how your models were built and where those models were built from. You need to know that this particular artifact was trained on that data. We've been doing some work with Ofcom, a UK regulator, that's about to start regulating social media platforms to prevent online harm. Part of their remit is that they want the platforms to be able to demonstrate that whenever they serve some content to some users, they don't want people to come to harm because of that content. If a regulator comes into that business, they're going to want to know what model was running at that time and what data was that model trained upon. The vast majority of businesses that we've spoken to, even really big ones, they can't do that because they don't know how to do it or they can't do it because they haven't got anything in place. Anyway, so I think that there's a big gap in the lineage market that I think we could also tackle basically chaining data together to verifiably prove that this data set originated from that other data set. That's a feature map. This is what you need to try and provide on a feature basis. There's then other dimensions that fit on top of that, in terms of how well you do that. The first one is familiarity and ease of use. It's the UX. We've been talking about that a lot already. Flexibility. This is a big one. So Spark and Hadoob are very locked down in terms of what you can use and what you can do. Trying to keep it as flexible as possible to allow the data scientists to use, the data engineers to use whatever libraries they want to use. That would be great. Scalability. That's when people talk about production ready. They're usually saying scalability underneath the scale. Declaritivity. That's how well the lineage and provenance and declaring your pipelines up front. Production readiness, of course. That's it from a data engineering point of view, but I did want to touch on the ML side as well. I think everyone talks about training ML as this big single step thing. People have been talking about it in the sense that we want to distribute our ML training. We just want to submit this one job that scales over massive numbers of nodes for performance reasons or something like that. But we've been talking to more and more people that are having to have local models in locations and localities, specific models for specific localities. And it's because of different languages, of different cultures, of different things that are deemed harmful and things like that. So some of the larger ML companies and tech companies out there, they're not just running one model for one thing. They're running hundreds of models for one thing. All of those models are completely different. So there's an idea here that locality is important and where the data resides is important because that specific model for that specific locality is based upon that specific data. The data doesn't need to go to a central location to actually do that training because generally the models that they use in these situations, the model architecture and the model definition is the same. It's just the data that's changing. So I can imagine a situation in a world where you have this distributed in the sense of many models, just all trained on different data, all the way down to local level. You've got data in your home and you're training models for your specific needs in your own home. That's certainly not possible at the moment. So bear that in mind. And there's a corolli there with business processes as well. And when we talk about business processes, they always follow this kind of plot where you're talking about the brewing process and it's just another process. But businesses have processes like this everywhere. And we've worked with a client at the moment who is trying to fully automate the paper manufacturer. So they're trying to automate going from wood pulp to bleached white paper. And it looks very much like this. They've got lots of tanks, they've got lots of steps and they have lots of models all powering each of those tanks. But again, the data is local to that one specific phase. The data is local to that one silo within the business. And it doesn't exist anywhere else. It doesn't need to exist anywhere else. So if we can have a distributed training for distributed data, that's really cool. And just to demonstrate that real home, I'm a big home brewer. And this is my cooling stage. I've just got a copper pipe that just cools it down. That's what home brewery is. And this is my bottling stage here. This is my packaging stage. So that's what it looks like in real life. A bit of both. Because it is home brew, any of those bottles can explode anytime. So it's a bit dangerous to open that safety door. OK. So, yeah, the future, we've talked about IPFS, IP... What did you call it, Luke? CS? IPCS. I'm going for IPAI. And it was totally accidental that the IPA and the beer thing all came together as well. But I'm going to take it. All right. That's it. Thank you very much.


Rusty Kamori, and this is Beyond the Lines on Think Tech, Hawaii. I was the head coach of the Punahou Boys Varsity Tennis Team for 22 years, and we were fortunate to win 22 consecutive state championships. My books Beyond the Lines and Beyond the Game are about leadership, character, and creating a superior culture of excellence, which is what this show is all about. My special guest today is the owner and principal broker for Century 21 iProperties Hawaii, and he runs the very popular Abe Lee seminars for pre-licensing and continuing education. He is the highly respected Abe Lee, and today we are going beyond real estate. Hi Abe, how's everything? Hey, how are you? Thank you so much for having me. I feel so honored. Oh, it's so, you know, we have so much to talk about Abe, and you have so much wisdom, but I want to start at the beginning if you can tell me a bit about your background growing up. Sure, thank you. I actually came from Korea in 1956 when I was eight years old. My father had already come to Hawaii to go to the University of Hawaii and studied accounting in 1947, so he got my mother pregnant with me because I had an older brother and sister, so he wanted her to have a baby to watch over while he was in Hawaii going to grad school. So the Korean War broke out. I never signed for eight years, and then in 1956 we finally came to Hawaii. So that's the first time I saw my father. So I'm an immigrant, and my father said, if you go to Luna Lilo Elementary School, which I did, and anybody asked you any question, just say, I don't know. So those are my first three English words I knew. I don't know. And then I went to University High School and then went to University of Hawaii, got a Bachelor's Degree in Asian Studies, which I call a good for nothing degree. And then I got a Master's Degree in Education from the University of Utah and have come back to Hawaii and started my businesses. So Abe, what was the first job that you ever had that you got paid money for? He was actually delivering newspapers, just like a lot of other kids. So I had a newspaper route and delivered the Sunday paper, weekday paper. But the other funny thing was I saw newspapers at the old stadium on Eisenberg because I lived just a block away. I sold the newspapers just to get free entrance to the football games. Well, that's a good connection there. So Abe, you and your wife, Sally, have been married for a very long time. What's the secret to your longevity of marriage? I actually had to look up the date and not really. We've been married since March 24, 1973. So that makes it 47 years. We have six children and we have 10 wonderful grandchildren. And the two words I can teach you or teach anybody is yes, dear, secret, yes, dear. But I think, you know, overall, my wife is from Hilo, a wonderful young lady, and she just loves kids. And she's a social worker. And so she's very easy to work with, just compassionate, loving, and just a wonderful lady. So we always try not to argue. And I think I can honestly say I've never yelled at her. I've never sworn at her. And so she attested that. So I think that's part of it is just be humble and be teachable. And she's correcting me all the time. Even last night she's correcting me. But you got to take it. You didn't say the other words. I don't know, right? Yeah. So how did how did your real estate career begin? Okay, I'm going to give you the short version because this is kind of interesting. I went to graduate school. I'm sorry. I went to University of Hawaii. And while I was, by the way, this is an interesting story. I was a bellboy at Royal Hawaiian Hotel.  And there's a fellow named Cyrus Oda who is a bellboy with me. He's from Big Island. So Cyrus then became the CFO for Kyoya, which owns the Sheraton chain on Oahu. So I'm having lunch with Cyrus the other day. And I said, oh, I'm going to be interviewed by Rustic Komaramp. I'm so honored. He goes, hey, Nick Leong is my son-in-law. And Laurie is married to Nick. And then he says, Angela Oda and Ernie Shiraki has a son, who is Cyrus' grandson, taking lessons from you. Ernie Shiraki, the third, right? Then Tom Keabu, he's an agent with me, former UPS head for all of Hawaii.  And they're on the team. He said, I know Rusty for seven years at the Punauti. So Rusty, your fame is all over. So anyway, yeah, I won't say that because, you know, you are so famous. As soon as I mentioned Rusty Komar, I go, oh, I know him. He taught me whatever. And Chris Ma is another one, you know? And Ika Kajou, I know his mother. So I'm going to talk about a small world. So anyway, what I used to do in college was I would go to Kahala because I live in Kamiki. I put a little flyer in each mailbox and said I'll pick up your car, wash, wax, and vacuum and drop it off for 25 bucks. So I was doing that. I got some customers from Kahala. So then I thought, okay, what else can I do in Kahala, right? So I buy fire extinguishers, wholesale. I go door to door retail.  I go, who are you? Are you graduating from college? Yeah, I'm an agent studies major and good for nothing degree. I'm going into business, but I don't know where. She says, why don't you sell insurance for me? So I didn't work for him, but I worked for someone else in insurance. So that lady, I sold her three fire extinguishers and she actually propelled my insurance career. So then they had a draw back then. So you earn a thousand bucks to draw. As long as you sell enough, they keep you on the draw and they don't fire you. So in three months, I sold one year's worth of insurance.  He said, you can't do that. So I said, wait a minute, I'm an independent agent and I'm out nine months ahead of schedule. So he said you can't do that. So I resigned and I went to real estate and worked for a lady named Liz Baker. So it's fortuitous that I sold fire extinguishers. I got employed as an insurance agent, got a real estate license, and then as I said, the rest is fishery and I had my license in 1973. Wow, you're nine months ahead of schedule. I was very fortunate in sales. I wasn't afraid to talk to people. That's one thing, I'm okay. I don't mind knocking on doors and talking to strangers and just being friends with them. Yeah, that's interesting to see how it all began with you. And Abe, I want to ask you, why is your Century 21 IPH so successful? I think several things. One, most of the my agents are former students of mine. So they took my real estate class or some of them take my continuing education, even though they took the real estate class from someone else. So in my class, I was teach, be honest, be nice, have a good attitude, be serious about real estate, and embrace the ninja selling concepts.  So our whole culture is, like you do us, you give the biggest trophy I read to the kid that has the most best sportsmanship, not who is the best player. In our company, we don't show, but even announce who the top producers are and how much they made.  Because that one person will win the awards all tonight. So why do that? So we recognize people for other things. And so we have, I think, a really good training program. And that's part of the ninja selling ably seminars. I teach things that other companies don't teach. I actually have an MIT program called Millionaires in Training. And I teach agents how to become millionaires in real estate by investing wisely. So I think that's what we get. We have about 151 agents right now with us. And so we're very fortunate that we're one of the largest independent, I mean, not independent, but real estate companies on Oahu. Well, I like hearing what you said there. And that's why you definitely go beyond the lines, Abe. And I know you have my books, and I want to ask you what stood out to you in my books. I tell you what, Russ. By the way, Russ is so good. He wrote a personal note in the books. I don't know too many authors that do that. And by the way, his handwriting is beautiful. I could never do this. My handwriting is terrible. But really, when I read beyond the lines, and you have the keys, number one through eight, and I mean, they're all great. But to me, it was a character or a champion. Because that's what we teach. You teach that. You have to be a good character before you become a good winner. And so to me, that just resonates. Yeah, great book. Yeah, no, that's all that, you know, teaching character was my top priority. I wanted to develop champion athletes of character first, and then great tennis players second. And I think that's exactly what you're doing with your business is you're trying to really build the character of your team first, and then real estate second. Is that correct? That's absolutely correct. So when I met Rusty, I said, Hey, I'm going to buy these two books. I'm going to use this as an incentive. So I have a program right now with the agents keep a scorecard. It's not about production. It's about what did you do to help your clients? So they have a week long score sheet. And if they give me four score sheets, I don't give it zero or 100, because hundreds of max. As long as they kept journal of four weeks, then they get the first book. Then when they get the second four weeks, they get the second book. And so that's my incentive to them to say, Hey, look, I've got these books, Rusty's autograph them. You want the book, just give us a scorecard. And I don't care about your production. All I care about is activity. Did you do the activity and activities will produce the results? So that's I'm a firm believer of that. Well, it's all about personal growth. And by the way, thank you for purchasing a lot of books, Abe. And and I like, you know, the greatest leaders always provide incentives. And they always they're they always care about the the well-being and personal growth of their people. Talk to me, Abe, about how you created your superior culture of excellence and the principles that are very important to you. Well, you know, I you're going to ask me about ninja selling anyway, but this is the book by Larry Kendall. Again, I know you have read a little about him. But what Larry Kendall teaches is don't worry about the sales and the commissions. Create the value. And he says, stop selling. So a lot of real estate or any kind of sales, you know, techniques, always be closing, always be closing, make them do what they don't want to do. That's not what it's ninjas about. It says, how can I help you to get to where you need to go? And what can I do to help you? So it's a client-centric business, not agent-centric business. And we're not talking about commissions here. We're talking about what do you need to do to accomplish your goals. So to me, that's what I teach all the time to my agents. I said, forget the commission. You'll come. But you got to create that trusted advisory that people, you know, look to. So I've had some clients, they'll say, hey, tell me what to do. I'll do whatever you want. I go, no, no, no, you can't be that blind. I'll walk you through the process. You make the decision to help you with that process. So if we have time later, I'll talk about this one guy, then, you know, I just said, let's accept the offer. I said, no, you're leaving $30,000 on table. And then he finally realized that he should listen to me. So I'll bring that up later. But yeah, I mean, we try to create value for our clients and for our agents. Because in a real sense, our agents are my clients. Because if I don't service them, they can go somewhere else. Just like if my agents don't serve their clients, the clients couldn't use another router. And by the way, there's 18,000 real estate agents active in and active in the state of Hawaii. And about two thirds of them live on Oahu. So there's tons of competition. So how do you stand out? And that's what you got to do. Excellent. Like what you do, you know, it's to be the best. Yeah, I like hearing that. And wow, that's so many real estate agents. And Abe, let's talk about your super popular ably seminars. I mean, you've impacted thousands of people by helping them with their, you know, pre licensing and continuing education. Tell me more about your seminars. We, I don't want to brag, but I guess I think he reached the baseball player said, you didn't bragging if you've done it.  And who else on earth has that record, right? So in that point of view, we actually have about 35% of the market. And there's about 20 schools. So if I take one 35%, then there's 65% to split up among 19 schools, which then is a really small percentage mathematically. So we've been very, very fortunate that our Yelp reviews, we've had hundreds of five-star Yelp reviews, and other schools haven't had those numbers. So they always say Abe cares about his students. And he gives us real life examples of what we should do in real estate. So I teach not just to pass a test, which is the main goal of the school, but there there is how do you prepare yourself to be a really good agent and to provide the services that other companies may not provide. Now we have some excellent realtors in town, and I teach a lot of them, but there are also some of them that you think, oh my goodness, they should not have a license. So you get the real spectrum, right? So anyway, but for us, we provide service. We provide value. Our school is one of the lowest priced schools for life tuition. And PJ Delanoza, who's my administrator, she came up with an idea one day. She goes, hey, boss, why don't we videotape the classes? I mean, kidding. You know how much it is to videotape? I had a really good friend, Abe Tasaka, who videotape for me, and I paid him an hourly rate. So we videotape all of our classes. No other school in the state, maybe in the country, videotapes all their classes. So all the pre licensing modules, we tape it in 15 minute modules so they can go back and forth and stuff. So we've had students go, I loved it because I can listen to it. I can rewind, and I can try and get what Abe was trying to say and follow in our textbook. So we provide services that I think most companies don't. And that's because we try to go beyond that line where we create that value service that no one else is doing. So I can say that I do not believe there's any other school that is videotape all of the continuing education classes and pre licensing courses. And the price is on the lower end. Well, all positives right there. And I know a lot. I have a lot of friends that took your classes and they all absolutely loved it. And they all speak very highly of you Abe. So I've known you before we met. I want to ask you about that big national organization, the Asian Real Estate Association of America. And there's the Hawaii chapter and you're part of it. Can you tell me more about that? I have to tell you first, Rusty has done his homework. I didn't even know that he knew about ARIA, the Asian Real Estate Association of America. I was a speaker at ARIA locally, like one actually twice for one or two of those events. Yeah. All right. Very good. But I joined because I felt that the Asian community and Pacific Islander community were not being well served. And so when I was introduced to ARIA, I said, okay, hit home to me because I'm Asian. I'm an immigrant. And I didn't know beans about how to buy a house. So I was very intrigued by the concept of ARIA. Now, the difficulty that ARIA has in Hawaii is that on the mainland, these Asian realtors are saying to the fellow Asians, hey, let's band together and be a political arm and a force because we're being discriminated against. But they come to Hawaii and they talk to the local Asian realtors and they go, what are you talking about? We're not minority. We're the majority. We rule. So it had a very old reception at the beginning. But as they saw what ARIA does for people, then our membership, I think grew to about 180. And we've gone down some because of COVID. But it's not a bad organization. And I just happened to be the president of ARIA for 2020 and for 2021. So they got stuck with me for two years. But yeah, it's a really good organization. And they have national and international reach. They work with developers from around the world. And they have junkets to Dubai, to China, to Korea, Mexico, Japan, looking at development projects and the network and internet, internet link. And also on the local chapter, our Meals on Wheels is part of ARIA service project. So before I met with you, I was driving around delivering meals to seniors in the Makali area. So fortunately, I finished on time and was able to come back, come on time to interview with you. So yeah, you know, ARIA is a wonderful organization. It's not just realtors. It's alone officers, CPAs, attorneys, anybody that wants to make an impact on the Asian community and Pacific Islanders, I think they should join. No, it's a fantastic organization and Abe, I want to ask you more about Larry Kendall and his ninja system. I know he's impacted you a whole lot and you teach the ninja system. What is it about Larry that impacted you so much? I gotta tell you, that picture, I don't know how Russi got it. He did some homework. I heard about Ninja through a student mind. And she tells me one day, you should come to this seminar all day at the Honolulu International Country Club, who's in Salt Lake here in Honolulu. And it's going to be the whole day. It's going to cost you 250 bucks. And you're here, this guy named Walt Frye talked about Ninja selling. He's kidding me. All day, 250 bucks, I went to so many seminars. And she says, I promise you, it'll be the best seminar you've been to. Okay, okay. So because I knew her and trusted her, I went. And Walt Frye is a disciple of Larry Kendall. And Walt's the one that did the heavy lifting that made Larry famous, actually. But Larry Kendall has a company called the Group Inc. out of Fort Collins, Colorado. Group Inc. is not a real original name here. I don't even know where Fort Collins was. All I knew was Denver. And that was it. So I fly up there to go to a four day session. It costs about 750 bucks back then. And playing for a hotel car the whole bit. And I'm sitting in there for four days. And I'm thinking, wow, this is amazing. What he's teaching us, we should be teaching to our fellow realtors. And that's when I walked up to Larry and I said, Hey, Larry, you don't know me, but I know Walt Frye took a classroom in Honolulu. And that's why I'm here. And I've been teaching for 40 years. Would you be willing to let me have your PowerPoint slides and kind of teach it to my agents? And what would you charge me? And Larry said, if you teach it to your agents at no cost, I'll give you my PowerPoint slides at no cost. 500 PowerPoint slides that nobody else has in Hawaii except me. And I'm thinking, Whoa, what a man. He didn't ask for any money. He just said, if you're going to help people, then be my guest. So I'm the one who certified Ninja instructor, Ninja selling instructor in Hawaii. And I'm blessed by Larry and also Walt Frye, because he created some continuing education classes on Ninja selling. And I got Walt's blessings to teach his classes and Larry's blessings to teach Larry's classes. So the system is not new.  That's what I do. Well, what Larry did was in his book, he put the whole thing into a system and a process. And he has what he calls Ninja line. Okay, it's five daily activities at four weekly activities.  That's his guarantee. Okay, just do the nine, just like your eight characters. Okay, with the eight, you know, steps. Same thing. Because if your tennis players and your business customers do the eight things, they'll succeed. Well, it's a Ninja nine now. Okay, so now if you add your eight to Ninja nine, what a wonderful system, right? So that's the reason I love Larry because he's not about the money. He's not out there to make a killing. And I've been to seminars where we pay seven hundred bucks for a two or three day seminar. And at the end, I don't know if you've been to those. See, they have people sitting in the back, and they're taking reservations for the next advanced class. And now they're going to ding you for 15, 20, 30 grand. Kendall has none of that. He says, once I teach you, the packet is complete. You don't need any more from me. So he doesn't upsell. And I've been upsold many times at different seminars across the country, but not Larry. That's why I love about him. He just straight up and says, this is what you do. And this will help you succeed. And that's why I tell my agents and students, and I teach this to all the students, not just my agents, because I believe the mission or the message is so powerful. So yeah, I love it. And I think he's a wonderful teacher, one of the best I've ever learned from. Well, I'm glad to hear all that. I'm glad that you're sharing all of that to so many people here in Hawaii. And Abe, I want to ask you about adversity.  Well, there's two. One is that my wife and I have six children, but we had two miscarriages. So she went three, four months on one of them. And I forgot how many months on the other. We lost two kids. And so that really hurt her physically as well as emotionally. But she's such a trooper. She just went ahead and had six kids. And I told her, four is enough for you, for me. And she just wanted eight or six, actually. And after we had the six, she said, okay, we're done. Our family's complete. I want to thank goodness. So that was one. But just a miscarriage. And, you know, how do you raise six kids in Hawaii? And all of them went to private schools. I don't know how on earth we did that. And when I look back, I go, it's a miracle. We just don't know how we're able to afford it. The other is in real estate, 1990 recession hit. And my business went under. And so we lost almost everything. So we had to start all over again. And that wasn't easy. But, you know, you got to persevere. And you got to just have faith that things will get better. So I'm very grateful to Sally for having stuck by it. Because she could have left me. She could have said, you lost everything. We're able to get it back. So we're very fortunate. Paul, thank you for sharing both of those adversities. And Abe, I want to ask you about you know, looking back, what's an important lesson you learned in life so far? You know what they say, your mother's advice is the best advice, right? My mother was a teacher in Korea. And she came to Hawaii, couldn't speak English. So she worked in a kitchen at Halakalane Hotel, shopping vegetables. And she had terrible arthritis. So she was in constant pain. But she always told me, be proud of what you have. And always help somebody. Even if they, if somebody helped you, but you can't pay them back, then pay it forward by doing it good to somebody else. Because you never know when that opportunity will arise. So I had a, my father was a CPA. And he kept books for people, Korean ladies. And a lady was a widow, and she almost lost her apartment building. My father helped her save it. So years later, the son calls me up and says, Hey, I'm the trustee for my mother's apartment buildings. Can you sell it for me?  He goes, no, I'm a trustee, so I don't want conflict. Besides that, your father saved my mother from financial ruin. So you list the problem. It's a three and a half million dollar deal. So my father helped the widow. The son now asked me to help him. Just exactly what my mother said. You may not be able to help the person that helped you, but you didn't always help somebody else. So I go with that or gratitude to my father, for being so honest in his work as an accountant, as a PhD. And he was a professor of accounting at New Age, by the way, and half the students at accounting school of accounting took classes from him. Dr. Samuel Lee. Well, Abe, I got to say, you know, it was such a great time having you on the show today and really appreciate you sharing those insights and wisdom with me on the show today. Thank you so much, Rossi. You're my hero. I want you to know. And I've talked about meeting you and, you know, having breakfast with you and sharing ideas. I hope I can sell a ton of more books for you because everybody should read it. And by the way, one more last shameless plug. I just bought the rights to this book. Our principles and practices are my real estate. And you notice that my name is there in the front. So I got the rights to this book because I've been teaching off of this for decades. And the author said, Abe, I'm retiring. You want to buy it? I go, okay. And she made me a good offer. So I'm very honored that I'm not the owner and the author of the book. Yeah. Oh, I love hearing that. Thank you for joining me. Thank you. My pleasure. And thank you so much. And thank you for watching Beyond the Lines on Think Tech Hawaii. For more information, please visit RustyKamori.com. And my books are available on Amazon and Barnes and Noble. I hope that Abe and I will inspire you to create your own superior culture of excellence and to find your greatness and help others find theirs. Aloha.


Hello everybody, E here. Welcome back to another book review. Today we are talking about Joe Hill's second short story collection, Full Throttle. It's actually his third collection, but Strange Weather is a collection of novellas. His first short story collection was 20th Century Ghosts, which was his first published work that he released other than short stories that he released through PS Publishing and so on and so forth. Today we're talking about Full Throttle. Right off the bat, this is a very pretty book. It's got this snake, snake. Got a snake on there. I like what they did with it. They have these khaki endpapers. It's very nice. I appreciate it. I'm gonna go ahead and jump into it. I'm gonna go story by story. Overall, I thought this collection was okay. The main reason I thought it was okay is because I'd read much of what was in here. I think there was only two stories. At first, when I did the release day video, I thought I'd read all of them, but I hadn't. I hadn't read Fawn and there was another one. We'll get to that when we get into it, but I'd read all these before and several of them were underwhelming. We'll get to that in the collection itself, but one of the things that you will notice as you're reading this, and even Joe Hill mentions it in the outro or the intro, whatever it is. By the way, the introduction is the best part of this book, I feel. He tells a story about he actually throws Stephen King under the bus about driving drunk with him in the car without a seatbelt. So child neglect for the win, but he talks about how this book is pretty much just a cover album. He pretty much took other people's ideas and wrote his own stories based on those ideas, which is another thing that kind of doesn't sit well with me, but more on that in a minute. As we go through each and every one, of course you have, right off the bat, you have Throttle, the story that he wrote with his dad. There's two stories in here that he wrote with Stephen King. The first one is Throttle. This one, of course, is an ode to the Matheson story, Duel, and the Spielberg movie of the same name. I think they're of the same name. This is an okay story. You're going to be hearing that a lot from me throughout this review, and I didn't reread it this time.  I believe it is. I didn't care too much for it the first time. I think I gave it three stars on Goodreads. I can't remember. Then again, I have misremembered things before and given them like five glowing stars, but my memory does not fit those reviews. So please don't pay any attention to any of the reviews I might have for these stories up right now because my feelings have changed over the years. So that's Throttle. Next up we have Dark Carousel. Dark Carousel was first released. I was surprised to see it here. Dark Carousel was first released as an LP or as an EP. I think it's an LP as a vinyl, as a record. Some people don't like it being called vinyl, but as a record, an audiobook on vinyl. That was an odd decision. And the story itself, several times in the afterward and the forward or the introduction in the outro, he mentions how much his writing and his stuff is like his father, which boggles the mind, man, because for his first three published novels, I think it was, I think he was outed either during Horwitt Korn's release or shortly thereafter. It might have even been before. He worked so hard to put space between him and his father. He used a pen name. He didn't use his father's connections to get published. He did the work and all of a sudden now he's no longer his own man. He is Stephen King's son. For those of you that don't know, he actually made a name for himself before anybody knew that he was Stephen King's son, which is funny because the shining is dedicated to Joe Hill King when his actual name is Joseph Hillstrom King. I always find that funny. But Dark Carousel, he says, is a Stephen King story and I couldn't agree more. The story is definitely a Stephen King story about a group of teens or 20-somethings. I don't know how old they are who not pull a prank, but they deal with an old man in a carousel who might have done something to wrong one of the girls and then the carousel seeks revenge for how they treat him. It's very creep show-esque. I was shocked when I heard that the Silver Waters of Lake Champlain was going to be in creep show and not this one because this one just screams creep show. It feels very much like creep show, especially the Cigar Shop Indian story. Whatever one that was, I think it's creep show too. It might have been creep show one. But going on, Wolverton Station, the story goes nowhere. I don't see that it has a purpose. You might enjoy it. You might see that it has a purpose, but I was very underwhelmed by the story. And I'm going to go ahead and say it now. It's the same thing with Twittering from the Circus of the Dead. I remember enjoying it all right, but these are novelty stories that they don't feel like they serve any other purpose, but to put you in a mindset of maybe either nostalgia or something else completely. Like this whole book is an ode to other things, which is very weird to me. It's like when Metallica came out with their album Garage Days. I think it was. All the songs they used to practice and play when they were a garage band. While that album is good, it is not their album. It's them covering. Now they do change a lot of stuff, like Bob Cigar's Turn the Page. They do change it, make it their own, that kind of thing. Joe Hill does that here. But there wasn't one story that I felt had the originality of stories like Pop Art in 20th Century Ghost. Nothing in here felt like it stood alone. Next up you have, by the way, Silver Waters of Lake Champlain. I enjoy this story from when I understand the Shutter reboot of Creep Show. Completely changed it because not much happens in the story, but I do like the visuals. This is, of course, and going back to Dark Carousel also, these two stories and another one on top of that, which is another reason why I'm going to keep on bringing this up. It's an ode to Ray Bradbury. Dark Carousel, of course, something we could this way comes. Silver Waters of Lake Champlain. I think I'm saying that right. Is it Champlain? Champlain? Champlain? I don't know. But this is Ray Bradbury's short story, The Foghorn. I think that is about the Lighthouse. I love that story and I like this story. It just doesn't feel like much of Joe Hill there. It feels more like the source material and less like a Joe Hill story. I do like it, though. I do appreciate it, but it's one of three Bradbury stories in this collection. If this was like a Joe Hill marketed, Joe Hill reboots Ray Bradbury, I'd be all for it. But it's not. It's supposed to be a collection of his short stories. I don't get that. What I'm getting is, like I said, it's a cover album. It's what it feels. He goes into detail more along these lines later on. I think it's in the afterward when he discusses how, if you did the same thing that cover artists do when they cover a song, it would be considered plagiarism. You have to add your own stuff to it. You have to. You can't just rewrite the same story over again, which Hill does, but I don't think that the covers come anywhere near to being as good as the original source material in any of these stories. Next up is Fawn. Once again, we're back with Ray Bradbury. He even evokes the sound of thunder in the introduction to the book. He mentions a sound of thunder. He mentions in the outro, I want to say outro, afterword, whatever it is. He mentions there. He's harping on it. That's why I'm harping on it. How much these things came from other places. When you're reading Fawn, if you've read Bradbury's story or seen the, it's not atrocious. It's an okay direct to video movie of the sound of thunder. You will know what's going to happen. You know what's going to occur because you have the original source material balanced by Joe Hill's own writing and you know where he's going to go with the story. Just like you rewind back to Dark Carousel, you have the same issue. You have this story about a carousel that comes like magical carousel. You know where it's going. If another complaint I had just thought about this is Dark Carousel went on far too long. It just kept going and going and I remember having the same problem with his novella snapshot. It should have ended 30 pages before it did and this one could have easily ended 10 pages. That's Dark Carousel, by the way. Next up, Late Returns is the second one that I had not read. I enjoyed this story quite a bit. I liked it. If there is, if this is another cover story, I don't truly know what it's from, but I mean it's one of those age old stories. People, especially horror authors, fantasy authors period, whether it be dark or light fantasy, they love talking about libraries and this bookmobile story was cool. It just doesn't do anything new. I liked it, but it doesn't do anything new. You know exactly where it's going to go. You know it's going to become nostalgic. You know all this. You understand where it's going to go and that's the problem with these stories because you've read stories like them before.  I'm not trying to evoke needful things, but you've been here before and that's the problem pretty much with this entire story, this entire collection. All I care about is you. I don't like sci-fi and fantasy all that much. This is a, I don't know, cyberpunk. I don't know how you would, it's about machines and all that. I don't, I've read it and I forgot about it right after I read it and I still, it didn't stick with me whatsoever. And when you have a short story, I believe it's one of the longer stories in the collection. No, never mind. It's only 30 pages. It didn't stick with me. Another thing while we're talking about the short story structure, real quick, these short stories are not short stories. The vast majority of them are novelettes bordering on novellas. I don't think there's a single short story in here. I don't think there's a single one under 7,000 words. 7,000 words I believe is about, I want to say 15 pages roughly in, not manuscript, but in this form. I could be wrong, but I'm just looking at some of the stuff that I have written that was over, you know, just around the 7,000 mark and none, none, all of these stories are longer than that. And novelette from what I think I remember it being from 7,000 to 14,000 words and then from 14,000 to 25,000 you have a novella territory, that kind of thing, 40,000 on. There's muddy area and there's also a lot of debate about what the industry standard is, but these aren't short stories. These are novelettes. These are big chunks. He, just like his father, he writes, when he gets involved in a story, he's going to give you a whole hunk of story. And these are more like either creep show episodes or they're definitely not a kiss in the dark from the stranger. That's Stephen King, that's a Stephen King quote by the way. They're definitely not that, they're definitely more, they're definitely meatier than your average short story. Thumbprint is another one. It's one of those things with Hill trying to be political and I think he completely misses the mark. I don't like the story at all. The more I think about it, the more I dislike it. It's another one of those gun violence war, war activists kind of things and I'm just not there for it. I think Loaded was a far better story and that's the novella from Strange Weather. Another note is their novellas, King and Hill, their novellas are about the size of, you know, Indie small press novel. It's about 50 to 60k words, 50 to 60,000 words. The thumbprint, it's whatever. The devil on the staircase is kind of like an odd one out. I read this in the, do I have the paperback sitting around here? Yeah, I do. Hang on. Okay, so this is the paperback version of horns and then you look back here and this is the devil on the staircase. It's formatted. Give you guys a second so you can see it. It's formatted like stairs and Hill talks about how the formatting was a pain in the ass because if they changed the font or anything it would screw up the stair structure which I think is cool just like from an industry standpoint. But the story itself, it evokes Italo Calvino, I think it is. On a winter's night a stranger, he wrote that short novel and it evokes that author which is something I never would have thought that Hill would have tackled. I just don't think that it's in his, I didn't think that it was in his wheelhouse. And while I don't care too much for the story, the story is very predictable once again. And Calvino was just a better all around author. I think Joe Hill is a good author. He's not as good as Calvino. But I mean we're talking about literary and we're talking about genre and Hill is far more genre than he is literary. There's a much deeper meaning when it comes to Calvino stuff whereas Hill is just trying to entertain you. He's like king. There is literary merit there more so for king than with Hill I feel. Another note on Hill said I'm going to keep on comparing him to his father because he compares himself to his father throughout this whole book. So I'm going to, I told myself back when I reviewed the fireman that I was going, before I reviewed the fireman that I was going to stop comparing these two because obviously he was his own man and doing his own thing. Nosferatu and all this stuff and they were hints in Nosferatu like the mention of Pennywise and so on and so forth. And then all of a sudden here comes the fireman and that entire book is just an, that entire book is an Easter egg for either Harry Potter or Stephen King's The Stand which was upsetting to me because I was hoping for something far more original. But it's a Harry Potter order of the phoenix by the way. But with, there's something, when I, when I read The Shining, here's what I'm getting at. When I read The Shining recently, there's a part in there where Stephen King says, and it really hit home for me, there comes a time in every author's career that he has to decide whether or not he's going to continue to do the same old thing or if he's going to strive to do better, to push farther. And I think Hill has hit that mark and he's decided he's not going to try any harder than what he's already doing. That is upsetting, that's bothersome. I am still a Joe Hill fan, but at this point in time, I've disliked almost as many of his books that I have fanboyed over. So I'm really, I'm on the fence here people. Twittering from the Circus of the Dead already talked about it. It's a short story written in tweets. I mean, about zombie apocalypse. It's whatever. Mums was an interesting story. I got a kick out of this one. It's probably my favorite story in the collection. So I also lied, because this is the third one that I hadn't read before, before picking up this book. But Mums was a good time. I think the less you know about the story, the better going into it. I did enjoy it. I mean, there's some politics in it, if I'm going to be honest, but I thought, well no, I didn't think it was well handled. I think that it was more satirical than you normally get from Hill, because Hill is usually far too on the nose. And while there's a lot of on the nose stuff in here, it's certainly not like King's Elevation. But Mums was an entertaining story. In the Tall Grass with Stephen King is another one. It's probably my second favorite in here. It has one of the most disturbing scenes I have ever read in it. It really bothered me for a long time. And no, I'm not going to do a review of the Netflix movie, because I'm going to leave Earl to that. But the reason I'm not going to is because I really don't have anything to say. The movie doesn't make any sense into the context of the story, especially not the scene that I like so much. And yes, the scene does disturb me. It did bother me. But that's why I like it, because it was so emotionally affecting. It bothered me a great deal. And it is one of my favorite Joe Hill stories, whatever you want to call it. In fact, I probably need to do my favorite Joe Hill stories and favorite novels and all that stuff. If you want to see that, let me know down there in the doobly-doo. And then last, certainly not least, you are released. This collection ends strongly. It starts strongly, middle of it. It's kind of, and then it ends strongly. I would give the whole collection of three, three stars. But another thing I'm going to throw out there, well, as far as you are released is concerned, the story is another one of those stories that kind of hides its politicality. It's not even a word. I don't know. It kind of hides its politics under overt messages about politics and society and that kind of thing. But there is a stronger undercurrent there, which I appreciated. King and Hill are much better when they allude to things. Every author is better when they allude to things. And when they don't just go, okay, here's my stance. Obviously, this is my stance. But there's also another thing to be said. If social media wasn't a thing. If we rewind back to like the, you know, the 80s and the 90s, early 90s, of course, if we rewind back to those days, knowing, not knowing their politics, and we read these stories, would we be having the same attitude and the same outrage that we have nowadays when the politics pops up in the book? That's an interesting thing. Without going into politics down there in the doobly-doo, I want to know if you guys think of it, is it because social media that we are like, oh my God, who mentioned so-and-so? Or is it because we're actually upset by these things? Because if you go back to like Dr. Sleep, Dr. Sleep mentions Bill Clinton, it mentions Nixon, it mentions Reagan, it mentions all these things, and none of the reviews mention those people. Yet you get to things like the Institute and that's all you hear about is how, oh my gosh, he evoked the current president. But like I said, without going into politics, without going into whose side you're on or any of that, cesspool nonsense, all I want to know is, do you guys think social media has the more to play than anything else when it comes to our outrage over breaking the fourth wall and throwing in like the most recent politician? I'd love to talk to you guys about that stuff. But you are released as a great story. It's one of my favorites in the collection. I enjoyed it immensely. But like I said, as far as the entire thing, I'm going to give it three stars. I think I liked it better than Strange Weather and I definitely liked it better than The Fireman. But it also, I had a lot of time in between these stories because I had read all of them previously as either Kindle exclusives or ebooks or Kindle singles, whatever they're called. So I might have liked some of these stories more or less either because I read them so long ago and I had a chance to digest them.  I think I'd get to that middle and I would completely stall out and then I'd go back to another story in the middle and then I'd stall out again. I think that's what would happen to me if I were to read this collection just sitting down. One final note on the audiobook. If you happen to get the audiobook, the best part of the audiobook too is the intro read by Joe Hill himself. I think he reads You Are Released also and of course he does the outro afterward, whatever it's called. I highly suggest you do not skip these things because like I said, the introduction is the strongest story, the strongest writing in here is that introduction. It is a hell of a lot of fun and it's a look into how he grew up and how his relationship with his father molded who he became as a writer. It also has a lot of insight on how he tried his best to make a name for himself without his father which is something I respected but now he's just kind of fallen away from that. But have you read Full Throttle or any of the short stories in there? You don't have to read the whole collection to chime in is what I'm getting at. Leave your comments down there in the doobly-doo. If you didn't like certain things please go into detail about why but also please give spoiler alerts if it's a if it's a plot point. Also if you didn't like it, I want to know why you didn't like it.  No I want to know why. I want the input to be able to say to be able to actually have a discussion with you about what you liked and what you didn't like or either or. But yeah leave all that stuff down there in the doobly-doo but until next time I have been E, you have been U, this has been another book review. I'll talk to you guys later. Bye bye!


Keeping soldiers safe is a top priority for vehicle engineers. Army researchers partnered with industry and academia to develop the next generation crash test dummy. Together, they designed a new device that will save lives. The mannequin reacts more like a human when an impact or blast comes from underneath the vehicle. Researchers from the U.S. Army Research Laboratory and the Tank Automotive Research Development and Engineering Center and industry partner DTS commemorated the delivery of four new mannequins in a ceremony July 19. Today is a significant day for Army Research Laboratories and U.S. Army Research Development Engineering Command because we are taking delivery of our first new generation of ATDs which are anthropomorphic test devices, human surrogate test devices that will be used in under blast testing. The Army's next generation crash test dummy has many advantages over past models developed by the automotive industry. Advanced sensors give high resolution data to open new insights into vehicle design. And so within our lab we use these crash test dummies or ATDs to give us a sense of what would actually happen if a person were in an under body blast type event in a simulated lab environment. What we do is evaluate vehicles and vehicle technologies for occupant protection. Following the ceremony the team along with university partners received hands-on training for the new devices all as part of the Warrior Injury Assessment Mannequin or We-A-Man program. The We-A-Man Engineering Office has done a really phenomenal job of really developing a science and technology initiative and really producing a prototype of a technology that soldiers really need. Officials said the delivery of the new test mannequin wouldn't have been possible without industry partners. So it's been significant for us. We have a history of working in safety research but for this now to expand into the military role and particularly the U.S. military it's been a significant honor and challenge and it's been very rewarding. The Army hopes to acquire at least 10 fieldable prototypes by next year. The system is going to allow us to really know what's going on inside those vehicles so we can bring our soldiers home safe. In Novi, Michigan, Joyce Conant, ARL TV.


The Equitable Life Assurance Society presents, this is your FBI. This is your FBI. The official broadcast from the files of the Federal Bureau of Investigation. Transcribed and presented as a public service by the Equitable Life Assurance Society of the United States. And the Equitable Society is representative in your community. Did you ever hear of getting an invitation to hear a radio commercial? Well, that's what has happened today. Thousands of people receive postcard invitations from representatives of the Equitable Life Assurance Society. Postcards inviting them to hear tonight's middle commercial. Tonight's commercial is an important one. Something everyone should hear. It concerns the Equitable Society's independent sixties plan. A practical, workable plan for people who want to look forward to complete independence in their sixties. I'll be back in approximately 14 minutes to give you full information on this special plan offered by the Equitable Life Assurance Society of the United States. Tonight's FBI file, The Larsonous Bride. Despite its popularity in the public frames and in private speech, a million is still a large number. So large, in fact, that it is impossible for the human mind to picture a million of anything. Yet the word has become so much a part of our pattern of living that it has almost lost its meaning. Therefore, some new approach must be found to tell you that in the last six-month period analyzed by the Federal Bureau of Investigation, the value of property stolen in the United States amounted to more than 57 million dollars. That means that the total for the year, since the next six-month period saw an increase, was well over 100 million dollars. Perhaps you will get some idea of how much that amount of money really is when you look at it comparatively. It means that almost a dollar per person was stolen for every man, woman and child in the country. It also means that in one year the criminals of this nation stole property valued at more money than it cost the original 13 states to fight an eight-year war of independence. In fewer words, freedom from tyranny was less expensive for the American people than freedom from crime. The night's file opens in the hallway of an apartment house located in a large eastern city. A young couple has just gotten out of the elevator. They walk to the door of an apartment and open it. Wait first. Hmm? Aren't you forgetting something, dear? What? You're supposed to carry me over the threshold. Oh, sure. Come on, honey. How do you like the place? You're beautiful. Oh, honey. Well, where have you been? Mother! Hello, Mrs. Carson. Yeah, where have you been? We stepped off at our house to get my bags, Mother. We just came back to get mine. Milted, where are your bags? In the lobby. Go get them. But Mrs. Carson, our train, it leaves in an hour. I canceled your reservation. What? Mother, this is our honeymoon. That can wait. I've arranged for your husband to get some work. What kind of work? You'll serve as an apprentice to a man I've known for years. We're meeting him tomorrow. Where? In Boston at his hotel. We'll all get down the midnight train. Oh, Mother. These are my orders. Bert? Yes, ma'am. If you listen to what this man tells you and watch him closely when he works inside of a year, I predict you'll be the best young thief in town. Coming. Hello, Colonel. Well, Martha Carson. Enter. Enter all of you.  Okay. Colonel Anderson, this is my daughter Milted and her husband, Bert Johnson. I am delighted to meet you both. How do you do, sir? Martha, I never would have believed that you had a daughter this old. Stop the con. Is he a real Colonel? Oh, of course not. But he's wearing a real Colonel's uniform. I have a collection of uniforms, my dear. And when we get some time, I'll show you my wardrobe. Why, Eisenhower himself... Let's get down to business, Colonel. Oh, yes, of course, of course. Well, when you called me, Martha, and said that you were bringing this pair of young lovebirds into my bar, I thought of an enterprise into which they will fit admirably. Again. But before I agree to take them on, I'll have to ask them a few questions. Go ahead. You first, young man. Now tell me, have you any kind of a record at all? Well, I deserted from the Army. That's not bad. Have you ever done any legitimate stealing? Nothing very big, sir. I've done a kid stuff. I see. But he's willing to work hard. That touching devotion. You'll do, young man. Thank you, sir. Now, how about you, Mildred? Have you any record? Oh, Colonel, she's too young. Too young? I'm surprised that any child of yours wasn't born with a record. Look, do you want to use them or don't you? Of course, Martha. Of course I use both of them. There is one rather important thing that I thus far have omitted mentioning. What's that? This operation of mine requires an investment of an original stake which I unfortunately do not possess. However, since you're interested in the welfare of these children... How much? About $4,000. Well, all right. For the sake of their marriage, I'll let you have it to give them a start. Splendid. Just write out a check. We'll get some lunch. And then we'll see you back to the railroad station. What for? What didn't you say these young people were just married yesterday? I thought you brought them here so they could start their honeymoon. Colonel, it's not that I don't trust you, but with that much money invested, I'm staying on this honeymoon with them. Several weeks later, at an FBI field office, Special Agent Jim Taylor approaches the desk of Agent Andy Nelson. Morning, Andy. Hi, Jim. You were a long way from your desk, aren't you? I came over to see you. Oh, about what? A new case. What guard? Impersonation. Here? Not yet. Well, here's the fill-in on it. The young man and a woman go to the outskirts of a city and find a large parcel of available vacant land. They pose as honeymooners. They claim they want to buy the property to build a range for themselves. However, the young man says that his money is being transferred from a bank in another city and he has only six or seven thousand dollars in cash with him. I see. Well, being anxious to sell the property owner gives the young couple an option for 90 days and return for, say, oh, five thousand dollars. So far, this is all very legal? All right. Well, about a week later, however, a man wearing a Colonel's uniform calls on the property owner and says that he is interested in purchasing the property for use by the government as an airfield. Then what happens? Well, then the man posing as a Colonel offers twice the price that the young couple offers. Well, if the property owner is already given the couple an option. And that's this window. After the fake Colonel leaves, the owner gets a hold of the couple and buys back the option. Had a nice profit to the couple. Then, of course, the Colonel never reappears. Well, I'll come worrying on it. You mean this office? A local police at the last place they pulled this window. I think the trio is headed here. Have you sent out any local alarm? Not yet, Andy. I'm having flyers printed up on all three of them. As soon as they're ready, we'll start distribution. Listen to this. Ten days of restful ocean cruising. Two gala nights and two full days for sightseeing. Participate in the colorful life of this great South American city. I guess it's in South America. What are you reading? It's a travel folder. What's the point in reading if we're not going any place? Well, maybe someday Mother will let us take a honeymoon by ourselves. No, sir. Yes, Mother. I want to talk to both of you. We're through working with the Colonel. Good. What happened, Mother? He just insulted me. Where? Down in the lobby. I met him as I was coming in. What'd he say? He had some out-of-town newspapers. They were from the cities we've been working. There were stories about the jobs we pulled, and they all said we stole more than we actually did. Oh. He accused me of stealing the difference. Mother. What? Did you? Did I what? Steal from the Colonel, too, on each job? Sure, but he has no right to accuse me of it. How about the job in this town, Mrs. Carson? Are we going through with it? Yeah, but when it's finished, the Colonel gets nothing. We'll take all the money and leave. Andy, anything coming on the swindlers? Only one thing, Jim, and that's no help. Oh, it's that. I'll check to see if the Colonel had any arrest record in the town he's already worked. And did he? Yes. He was arrested six years ago. For what? Suspicion of swindling an elderly woman. He got out on bail. Jumped a bond. Who's bond with it? His own. He put up $5,000 in cash. Must have hurt. Well, it didn't really cost him a dime, Jim. Oh, how come? While he was being held, he convinced a dozen of his prison mates that he'd buried a box containing $100,000. He then sold them copies of a map showing where the loot was buried. Oh, no. The maps turned out to be worthless, of course, but by that time he was out of prison and out of the state. Sounds like there are a lot of people looking for him. Including the clerk at every hotel and roaming house here. I circularized him this morning through the local police. Fine, I just finished alerting the list of real estate agents. Well, how about the owners of large pieces of property? Jim, do you think we ought to warn them? Well, the real estate board said it would take care of that. Oh, good. Landy, let's run over what we know about the Colonel. All right. We know he's a glib talker. We know he eats in expensive restaurants. We know that he had uniforms tailored by one of the best shops in New York. We know... Hey, Landy, why didn't we think of this before? The Colonel eats and wears nothing but the best. How does that help? That means he probably lives in a place that's just as exclusive, like a private club. Yeah. Landy, I'm going to check every good club in town. Mildred. Yes, dear? I want to talk to you. What is it? Well, I kind of hate to say this against your own flesh and blood, your mother, I mean. But I'd sort of like it better if we could go off on our own. Mother's only trying to help you, Bert. I know. She's just launching your career. I've got a right to launch my own career. Bert. I mean it. She's got no right to run things like this. Look, Mildred, for all she knows, I might even want to take an honest job someplace. Oh, Bert, you don't mean that. I do. I'm going to have a talk with your mother about this whole thing. I'm just going to... Yes, mother. Did the colonel call here this morning? No, mother. Mrs. Carson? How about the man you bought the option from? Mr. William? Yeah, did he call? No. Mrs. Carson, I want to talk to you. Please, Bert, we've got business to tend to. You paid that Mr. Williams the $8,000 for the option, didn't you? Yes. I better call the colonel. Mrs. Carson, this is a very important matter I wish to discuss. Bert, this is a very important matter I'm going to take care of. Now, I want to find out... Oh, Colonel Anderson, please. Mrs. Carson, I wish you'd listen to me for just a minute. I've got a matter to discuss with you. Hello? This is Martha. Oh, good morning, Martha. I sound as if you just got up. On the contrary, my dear, you caught me just as I was leaving. On your way to see Mr. Williams? Oh, no, I've already seen him. Oh, he hasn't called here yet. I know that, and he won't. Why not? Oh, look, you're not going to bring that up again. Well, that day... The $8,000 of my money for an option... In just a minute to tonight's exciting FBI file. Tonight, I have an invitation from the Equitable Society for men and women in their 30s and 40s. It's a brief but very important message concerning the Equitable Society's famous Independent 60s plan. Now, there's nothing complicated about Independent 60s. It means just what it says. Freedom and independence beginning at the age of 60. Freedom from money worries. Freedom from job worries. The Independent 60s plan. You're self-supporting and self-respecting. You can live as you like and where you like. Let me tell you what I've done under the plan, Mr. Keating. Down on the Florida Gulf, I'm building my own home. A complete five-room house. The kind of place I always wanted. You mean you're actually doing the construction work yourself? Practically all of it, Mr. Keating. And when it's finished, my wife and I are going to settle down and really enjoy life. Fishing, swimming, sunbathing. There's everything you could ask for in Florida. You know, Tom, when I talk to a man like you, I wonder why everybody doesn't join the Equitable Society's Independent 60s plan. I think I know the reason, Mr. Keating. People think it takes a small fortune to get in on a plan like this. I know I did. Who gave you the facts? I talked with an Equitable Society representative. He showed me I practically had Independent 60s already. Thanks to Social Security and the life insurance I already own. That's often the case, Tom. It takes only a small amount of additional insurance to enable a man to look forward with complete confidence to Independent 60s. A few extra dollars a week did it for me. So why not see your Equitable Representative with our delay? Phone him soon, or send a postcard care of this station to the Equitable Society. That's E-Q-U-I-T-A-B-L-E. Equitable Life Assurance Society of the United States. Now back to the FBI file, The Larsenous Bride. So long as men and women like the ones in tonight's case from the files of your FBI are at liberty, and in your community, you are a potential victim. There is no way in which you, the citizen, can apprehend them. But there is a way you can aid in seeing to it that they do not visit your city. That simple method of self-protection is to have the very best local police force that is within your power to get. Criminals are everywhere, in every city. But there are fewer of them in those fortunate cities where there is a strong local force. The basic reason for mentioning this on tonight's program is that you do have it within your power to strengthen your city law enforcement agency. As a voter, you have in your possession a deadly weapon. Deadly to the criminal. Because if you live in a city where the police are woefully underpaid, as is the case in almost every section of the nation, you can do something about it. With higher pay, you will get not only more protection from a force with better morale, but you will also get a larger force. And just as it is a fact that many policemen are underpaid, so it is an accompanying fact that many staffs are under-manned. Give your local police your support, and they will repay that confidence the way you want it repaid with more protection from the criminal for you, the decent citizen. Tonight's file continues at the local FBI field office. Andy, we got a tough break. What's that, Jim? We were right in our theory that the Colonel might be staying at a private club. He was at the Hudson Club, but he checked out a little while before I got there. That is tough. And he lead on where he went. The only thing at the club, the switchboard, is checking the one that he called the most often. That might help. Yeah, but that's all I got. How about his room? No, it had just been cleaned. I checked at the transportation desk at the club, but he didn't buy any tickets from them. Maybe he's still in town. Could be, Andy, but I doubt it. Have you sent flyers to the railroad station? Yeah, to the airport, the bus station, and car rental agencies. The only other thing we know is that he visited someone here in town. He asked at the club one day for directions to Emory Street. This is Mr. Taylor. This is Ms. Hopkins at the switchboard, Mr. Taylor. Oh, yes, Ms. Hopkins. That number you gave me doesn't answer. Have you found out where it is? Yes, sir. No. Thank you, Ms. Hopkins. Yes, sir. Come on, Eddie. Where are we going? To 21 Emory Street and say we can locate the honeymooners. Shouldn't I be mad? That dirty crook stealing all my money. Imagine him accusing me and then stealing himself. But Mrs. Carson, you were going to steal from him, weren't you?  To the railroad station. I heard you say that to the cab driver. Then you shouldn't have asked. I mean, from there, Mother. Back to your husband's apartment. Back in Madison? Yes. Mother? What? Are you going to let the colonel just take all our money? In the first place, it's my money, not ours. And in the second place, he's not going to get away with it. How are you going to stop him? We'll meet him. Where? At your apartment. Mother, how do you know he's in Madison? I saw a list of cities in his room one day. I didn't know what they were, but I copied them down just in case. What kind of a list of cities, Mother? Just plain cities. That's the list he's using for his trip. So far he's stuck to the list and Madison is next. But Mrs. Carson? What? Madison is a big place. How are we ever going to find him? I've got that all figured out. Landy, judging by the superintendent's description, there's not much doubt that this is the couple we watched. No. I wonder who the older woman with them was. Does she appear any place on the record? Not in any of the swindles, no. Jim, maybe. Got that key the super gave you? Yeah, yeah, right. Go ahead. Oh, thanks, Jim. There's plenty there. Yeah. You know, we really seem to have the just missed them on this case. I'll take a look in this closet. Okay. I'll see if we're any luck with prints around it. Yeah. Real empty, Jim. Find anything? Yeah. Yeah, the number prints on this glass top here. Looks like Goodwin's, too. Let's work them up, Andy. They might tell us a lot about our missing couple. I always thought Madison was a smaller town than this, Andy. It mustroom during the war. Wait a minute, Jim. Here's the address coming up. Number 216. 214. 212. And a vacant lot. 210 is a vacant lot. Andy, where's that data we got from the draft board on the young man? Right here. Is 210 the right number? Yes. We get a set of fingerprints. Washington identifies them as belonging to an army deserter. The army deserter is our young honeymooner, and now the address he gave his draft board is a vacant lot.  Hey, wait a minute. You know, we still might, Andy. How? Take a look at that store there across the street. What about it? You see the lettering across the window? Sure. Now look at the number. It's painted a different color. I don't see what you're driving at, Andy. It's just a theory, Andy. Let's get on the city hall. In the bedroom, he just got back. I know. I went out a little while after you did. Where? To answer an ad. An ad in the papers? Mother, he didn't take a job, did he? Of course not. Well, then what kind of an ad was it? The Colonel's ad. The Colonel? Yeah, I put an ad in the local paper looking for property, so I had Bert answer it. Oh. The Colonel's hired a new pair of honeymooners. They came and gave Bert money for an option on some property. Well, we don't own any. Bert showed them a fake deed. Hi, honey. Hello, dear. Mother was just telling me about the money from the Colonel. Yeah, $2,000. $2,000? But that's less than the Colonel stole from us. $6,000 less, but we'll get the rest. How? This should answer that. Yeah, Colonel, we're home. Huh? Bert is the one who answered your ad this morning. That's right, Colonel. Well, that was quite right of you, Martha. I thought you'd like it. I want that other $6,000 you stole. Oh, that. I'm afraid that's rather a lost cause. What? You see, in the Army, such a thing is referred to as a calculated risk. You send out so many men in order to gain such and such an objective. What's that got to do with our $6,000? I sent out $2,000 this morning in an effort to gain perhaps another five. I took my calculated risk and lost. So? That I regard as an operation which failed, and I no longer let it disturb me. And I suggest that you do the same regarding the other $6,000. Oh, no. I'm afraid you have no choice. They have fallen on the field of battle, and so far as you're concerned, they are my prisoners of war. Drop all the army talk. We want that money, and we want it now. Martha, I see that I have failed to instill in you an appreciation of sound military maneuvering. Therefore, I shall take my leave. Wait a minute. Just a minute, Colonel. Huh? Hey, Andy, we've got all of them. Oh, good. You're all under arrest. Huh? Martha, exactly who are your borish visitors? I don't know. We're special agents of the FBI. Oh, fellow government employees, eh? I'll save it, Anderson. You can all tell your stories when we get to headquarters. The criminals in tonight's case were tried and convicted. Howard Anderson, alias the Colonel, received a sentence of ten years. Bert Johnson was sentenced to serve seven years, and both his wife and mother-in-law were imprisoned for terms of five years. The problem which faced the two special agents, having an address and finding a vacant lot at that number, was resolved by Special Agent Taylor's observation that the store across the street had the number painted in a different color than the name of the store. A visit to City Hall and the Bureau of Records substantiated his theory that the district had been rezoned, and that the vacant lot, which was 210, had only just come by that number. It then developed that the building which was formerly 210 North Adams Street was now, after the rezoning, 2055 North Adams. A visit to that address revealed that it was an apartment house in which Bert Johnson was a tenant. And so, because of hard work on the part of two special agents, plus diligent investigation and keen observation, your FBI was able to close four criminal careers, and in that manner further to protect you, the American people. In just a moment, we will tell you about next week's exciting case from the files of your FBI. Now, two final questions on the Equitable Society's Independent 60s plan. Mr. Keating, suppose I start a plan now, and then my income goes up in the next few years. Can I increase the amount of my Independent 60s plan? An excellent idea. Your Equitable Society representative will be glad to lay out a plan like that for you. For what sort of an income will this plan give me in my 60s? The exact figure depends on your present income and your future needs. In any case, the sooner you investigate, the better. Ask your Equitable representative to drop around for a friendly visit. Call him soon, or write care of this station, to the Equitable Life Assurance Society of the United States. Next week, we will dramatize another case from the files of the Federal Bureau of Investigation. An exciting account of the exploits of a gang of professional criminals. It's subject. Robbery. It's title. The Big Buildup. The incidents used in tonight's Equitable Life Assurance Society's broadcast are adapted from the files of the Federal Bureau of Investigation. However, all names used are fictitious, and any similarity thereof with the names of persons living or dead is accidental. Tonight's program was transcribed, and the music was composed and conducted by Frederick Steiner. The author was Jerry D. Lowes. Your narrator was William Woodson, and special agent Taylor was played by Stacey Harris. Others in the cast were B. Benaderit, Patty Chapman, Roland Morris, Herb Rawlinson, Theodore Von Elts, and Betty White. This is Your FBI is a gerrydivine production. This is Larry Keating speaking for the Equitable Life Assurance Society of the United States and the Equitable Society's representative in your community. And inviting you to tune in again next week at this same time when the Equitable Life Assurance Society will bring you another thrilling story from the files of the Federal Bureau of Investigation. The Big Buildup on This Is Your FBI. This is ABC, the American Broadcasting Company.