Hello and welcome to My Career in Data, a podcast where we discuss with industry leaders and experts how they have built their careers. I'm your host Shannon Kemp and today we're talking to Emily Washington at Precisely. Visit dataversity.net and expand your knowledge with thousands of articles and blogs written by industry experts, plus free live and on-demand webinars covering the complete data management spectrum. While you're there, subscribe to the weekly newsletter so you'll never miss a beat. Hello and welcome. My name is Shannon Kemp and I'm the Chief Digital Officer at Dataversity and this is My Career in Data, a Dataversity Talks podcast dedicated to learning from those who have careers in data management to understand how they got there and to be talking with people who help make those careers a little bit easier. To keep up to date in the latest in data management education, go to dataversity.net forward slash subscribe. Today we are joined by Emily Washington, the Senior Vice President of Product Management at Precisely and normally this is where a podcast host would read a short bio of the guest but in this podcast, your bio is what we're here to talk about. Emily, hello and welcome. Hello, thanks for having me. So you're the Senior Vice President of Product at Precisely. So tell me what is Precisely and what is it that you do? Sure, yes. So Precisely is a technology and services provider. We provide a combination of software data as well as strategic services to really help organizations ensure the utmost data integrity. We are a leader in data integrity. We have over 12,000 customers and the way we define data integrity is ensuring the accuracy, consistency and context of data. So through a combination of all these things and obviously a lot of what I'm expecting we're going to talk about today, that's the world I live in. I get to drive the product strategy and the roadmaps for the capabilities that we bring to market through particularly focused on data quality, data governments and master data management as well as I get the pleasure of being able to work with taking our portfolio of products across Precisely to more of a SaaS model. So being able to support our customers in this journey to leveraging some of the newer technologies out there. So I drive product management for all those areas. It's very cool. So we'll come back to a bit about how you're working with data. But tell me a little bit. So when you were in elementary school, when you were very young and then you know, is this what you wanted to be when you grew up? Like, was this the dream? I'm going to be a senior vice president of product at Precisely. No, far from it. And actually it took me all the way through to, I don't know about you, but you've been just going through all the way to university.  I wanted to be a teacher. I wanted to and I just, it was one of those things. I always admired my teachers in elementary school and I thought it was just so fun to be able to work with kids all day and be able to teach them. So I actually went to school to become a teacher. And then as I got through university, I started to bring more focus to English literature. I have a passion for reading and and I just say, I really wanted to I by that point, I was thinking, OK, high school English teacher. That's what I wanted to do. And I ended up working for a dot com during that whole that whole era in Silicon Valley as a as a job while I was going to school. And that's how I got into technology and, you know, just and how it kind of went from here. So it was definitely nothing I sought out to do. If you were to have asked me then, if this is what I would be doing, I would have thought you were crazy. So it's been quite the journey. I love hearing people's initial passions, right? It's so interesting. So tell me then, so OK, so you got into this dot com job. So how did you transition then from from that and, you know, wanting to be a teacher and to to where you are today? Yeah, so I so when I when I started working for this this website and, you know, I worked in customer support and obviously there's a lot of technology behind that. So I started to work with developers and web designers and the technology aspects really interested me. So as I as I went through, you know, and I was wrapping up getting my degree in English Lit, I also was it was working at that organization. And like the like the tale that many of us have, we the the dot com, you know, ended up folding and I ended up getting laid off. And that's what led me to technology. I I from there, I went to a couple of organizations focusing on software providers, but my journey to data and how I got into data, you know, data integrity and the things I do today. It evolved from, you know, starting at software organizations, doing reporting and a lot of a lot of more administrative capabilities for, you know, our development organization. And then, you know, just learning more about what you could do with data and how software can support that. How do you automate things? You know, we use our spreadsheets and, you know, manual documents and all those sorts of things. And I just had this passion for, you know, figuring out ways to automate some of those activities. And so I landed at another company where we were focused on data quality and data governments. And I have been with that company since. So precisely acquired the company I I had come from back in 2021. And so I've been with the variations of precisely for 20 years now. So it just worked my way into various roles to how I got here. Well, that's exciting. And it must have been really exciting to be in the heart of it. And, you know, at the Silicon Valley, as it started to explode. It was the energy, you know, even, you know, some of the things that we see today with technology and just all the all the innovations that constantly come out to make data better. You know, it's there's so many interesting things that we're always able to do. And so the energy just in this space is is what just drives me to want to do more and learn more.  So I love that. So do you currently use your education and teaching skills then and what you're currently doing? I so I have always said it. I always try to tell like my parents this, you know, what? What did you get that English letter to her degree for that? You know, and it's the communication skills. So I so regardless of what role you are in an organization, I feel like communication is key. So while I can't directly apply what I learned about Shakespeare to my data management job today, what I what I do, what I do bring with me is just the communication being able to understand where people are coming from. You know, one of the things that I love about my my job is just how do how do we problem solve? How can I solve it? Bring solutions to our customers that, you know, just it just helps them make their jobs easier and, you know, be able to focus on the things that matter. And so being able to listen, be able to clearly articulate what, you know, we're trying to do, you know, and I really attribute that to just, you know, that background that I have, that love for communication as a part of what I do today. It makes so much sense and so important. And I love that you have a passion around automation, you know, is that that resonates very well with me. I love efficiency and automation. I mean, imagine all the time we've wasted with our spreadsheets and the frustrations.  Yeah, yeah. With a robust catalogue of courses offered on demand and industry leading live online sessions throughout the year, the Dataversity Training Center is your launchpad for career success. Browse the complete catalogue at training.dataversity.net and use code DVTALKS for 20 percent off your purchase. I love it. So tell me, what is your definition of data and how are you working with it today? Yeah, so so I my definition of data, I don't know if it's oversimplified, but it's just a collection of of attributes to allow me to, you know, get insights into, you know, information that I need to be able to solve problems, you know, and so so I do, you know, when I think about data specifically, it really is, you know, those specific elements. But the combination of those is what gives us the information to make those decisions. And so, you know, in my role, I get the pleasure of dealing with data from two different perspectives, that, you know, obviously, there's the products that we deliver. And so a lot of what I focus on is, you know, trying to better data quality processes, implement better data governance programs in a more automated fashion, but also for me personally in my role in how I make these products better is, you know, the data that we use with our, you know, understanding our customers information and, you know, everything from the customer satisfaction to all of the metrics that we have around, you know, how our business is growing. And so, you know, being able to so I it's an interesting thing for me because I I take some of those frustrations and those things that I do with my own data and apply that to how we get to develop solutions for, you know, for our customers. And so, you know, at the end of the day, whether it's precisely or data versus you, we're all dealing with data every day. And so so I get to kind of deal with it on both sides to see if there's better ways to do to do things when it comes to data. I like it a lot. That's very, very interesting. And so as you're working with data, especially with the, you know, touchpoint with so many customers, you know, do you see the importance of data and data management, the importance of data management and the number of jobs working with data, increasing or decreasing over the next 10 years and why question. Yeah, no, that's it. And it's an important question because I think, you know, there's there's a lot of things that we've implemented over the years to make data processes better or to make data more available to users across across the industry. But one of the things that I don't I think that the jobs will increase, but the way that the jobs are the types of jobs that are needed are going to evolve. You know, you look at some of the automation tasks, you know, at the end of the day, I always look at it as, you know, the intent here is not to it's not to replace jobs with with tools. It's more about how do you make those jobs more efficient and focus on the the true analysis, not having to fix the problems or be able to manipulate data to get it to the point that you need those pieces should be easy. Now, what can you do with it? How what insights can you derive? So I think the roles in data are going to continue to increase, but it's going to continue to take different forms as we as we keep going and as more automation is built in. That makes so much sense. And what advice would you give to people looking to get into a career in data management? Yeah, you know, one of the things that you asked me at the beginning, what, you know, is this what I sought out to do? And, you know, one of the things that I realized naturally is just that that love of information. I am just curious. And, you know, one of the things that worked for me is, you know, just being able to better understand any data that's in front of me and taking ideas to, you know, you know, folks that I worked with or for, or, you know, I've always had a nice support system in terms of, you know, collaborating with others around data. I think everyone is hungry for more insights.  And so I have found, you know, whether it's me, you know, my personal experience or working with it with different people across organizations, it's just that collaboration, getting your hands dirty, if you will, around the data that's available to you and being able to drive those insights. And then what happens is, you know, maybe more questions come up and then you have this ability to get, you know, get more into other programs or other projects that involve data. And so, you know, it doesn't really matter where you're coming at it from. You know, my experience alone, it was, I was just doing reporting for engineering team. And, you know, I was curious why we had so many bugs.  And that's, you know, that's what got the ball rolling for me in getting more and more into, you know, data management and a lot of the things that I get to do now. That's such great advice. And it seems to be a running theme that we seem to come across with a lot of the people that I've been interviewing, you know, it's being curious, you know. And it's okay to be curious. It's okay to ask questions. It's okay to not know. And I really do think people appreciate when you bring those questions of, you know, it's it, you know, because that just as much as we're curious, we're also wanting to help one another, you know. So if you're on the receiving end of that curiosity or question, you know, that ability to help someone and, you know, start to work together, you know, that's what triggers and all these great ideas and these projects that we can keep working on. Because at the end of the day, we're all just trying to improve the way we work with data, you know. And there's multiple ways. And the great thing is more and more individuals across the organization have that opportunity. You know, that's also why I think, you know, the number of jobs will continue to increase. You know, it used to be more of an IT centric role.  And, you know, so everyone has a role to a part to play in how we work with data, how we make data better. And ultimately, you know, drive those, drive those efficiencies and business decisions we're getting at. So true. So many jobs, no matter what the title includes working with data now. Exactly. And that's what I love about this space. It's just so, it's so fun to look at any role in the organization.  It's, you know, but regardless of who you are in the organization, you're always looking at it. You always need to rely on it to do your job.  So true. I think one of the, the favorite parts of my job is, you know, we get to work with every industry. Mm-hmm. Yeah. Across the globe. Yeah. And to your point about data people and answering those questions of curiosity, I have found the data community to be so supportive of each other and loving. And like you're talking about just loving to network and loving to help each other out and lift each other up. It's just really an amazing space to be. There's so many lessons learned. You look at the different industries and, you know, the different geographic regions.  And so learning from each other and how we've done that and, you know, take some of those best practices, whether it be from a certain industry or certain type of organization to another. You know, I think we're all just so hungry to figure out, there's got to be an easy button for some of this stuff. Like there's got to be an easier way. So when you're looking and you're curious about automation, is there a kind of a thought process, a standard thought process that you go through or is there, you know, how do you discover those things to automate? Yeah, you know, it depends on, you know, when you think about the different types of capabilities associated with data management or in my case data integrity, where we're focused on, you know, improving the accuracy of data, it depends on the use case, right? I mean, you know, we'll take data quality as an example. I think, you know, there's these general assumptions that, you know, it should be easy to recommend where you need data quality based on historical patterns. And while that is true, it should be easy and there are ways to do that. You know, a lot of the, you know, and there's amazing technologies out there to be able to drive that automation, but you're never going to get rid of the true human in the loop aspect of it. There's always going to be some level of intervention to make sure that, you know, that this is right. And that's where I think the automation with, you know, the users who are actually working with that data, you know, really complement each other. So when I think about improving the automation, again, it's, you know, taking out some of the repeatability, you know, some of those tasks that are really, you know, repeatable, you can do that a lot. And also point, you know, let's say machine learning, AI to that ability to recommend based on the historical behavior, but it's the behavior of also the users. You know, we have so much like historical knowledge built up in our heads and how we've done these things in the past like data quality initiative, how many times have we had to quickly fix an issue and then you move on to the next one? You know, so how do we start to capture that to make the automation smarter? So I look for those types of use cases where you can start to see, you know, where we are storing certain types of user behavior and information or build those repeatable tasks. And so, you know, that's it. That's one from a data quality standpoint. And, you know, when I look at a data governance, which is much more cultural process, you know, there's other dimensions to implementing the data governance program.  And, you know, how do you build automation to improve some of those activities? So it's a little bit of a long winded answer, but, you know, it really does depend on the use case. I think, and, you know, there's different approaches that you can take.  It's just, it's really a great- I wouldn't have it any other way. I love it.  And so it's a fun place to be. Indeed, indeed. And like you said, those soft skills, the communication skills are so important. It's not just about crunching the numbers, it's not just about being able to communicate the data that you're looking at. Yeah, yeah. Well, I would be remiss if I didn't ask, you know, if somebody's interested in Precisely, how do they find Precisely and what you guys do? Yeah, feel free to go to our website at www.Precisely.com. And we are so excited to work with our customers. We're just about to, you know, kick off a number of efforts here. We just had a big release. So there's a lot of cool things going on with our organization right now. So we'd love to chat with you. Congrats and exciting. Thank you. Very nice. And we'll be sure to put it on the podcast page, the links and for that so everyone can reach out. Thank you. Emily, thank you so much for taking the time to chat with us today. Thank you. I really appreciate it. I love talking about data. So thank you for having me such a great opportunity and love the work that Dataversity does. I'm always following you. It's a great place to learn about data. So love it. Thanks so much. Really appreciate that. So and thank you again so much. And to all of our listeners out there, if you want to keep up to date on the latest podcasts and the latest in data management education, go to dataversity.net forward slash subscribe. Until next time. Thank you for listening to Dataversity Talks, a podcast brought to you by Dataversity. Subscribe to our newsletter for podcast updates and information about our free educational webinars at dataversity.net forward slash subscribe.


Hi Welcome everyone Like I have a first question for you like who of you is an AI agent, please raise your hand Okay, like those who raised in her hand like please leave the room now and also switch of your AI assistance for this presentation Thank you. Like first I will tell you like this lecture I promised like to be like to show Something from from some development. We try to work on regarding AI but the main focus of the presentation will be like why to Do tools that like incorporate AI in blender and Like how to approach it how to think about it because that's like the most important step I think like before doing stuff To start with Let me introduce myself. My name is villain do ha and I've been an artist for some time for some like 20 years or so And I've been using blender for that this time I've been developing some add-ons in the past like I did some art like this is for example like some Wooden sculpture added with blender. It was my first presentation on blender conference many years ago like developing Blender I don't for carving with wood And the last few years I've spent with a blender kid database, which is like a community run database of blender assets like materials and assets and Some of you might know it like we crossed like 400,000 registered users. So we are meeting here. Some of you already used our addon and So let's talk AI right there was like this joke in blender community Like for many years like like this button like just it is all the user interface and make this button make a beautiful render Right and and that was like it was a joke It's funny that it's not a joke anymore, right? It's like Yeah, we can type in stuff and we get like Semi-good pseudo-good almost good images, right? That are at least like for non-artists. They are like they seem like to be perfect Okay, so that's like Something that is like pretty big and We all expected this to happen, but maybe some of us didn't expect it to happen so fast So I felt like I reserve this pot on the conference story that I think like like anybody could do it because like a we as artists are like like going through like some thought process like through this Changes happening and how to approach it, you know, how to how do we like start using the tools or not? So it's like and I felt it like like several years ago It's like really like a new atomic bomb has been dropped and like back then nobody noticed now I think like everybody notice already and people talk about it, but still like there's a discussion around it I think it's not It's not too deep like people like there are there's a lot of Emotional reactions and I noticed like it's like it resembles to me something that I know from Psychology and it's like phases of processing like when you are going through a big life change or like a trauma Like this is not literally a trauma. It's like everyone want to compare it, but but the there are Similar things like denial, right? Like this is like not Good enough like or like always like trying to say, okay, this is this AI is actually not Going to supersede humans like it won't be better There is anger There is depression. I went through that definitely and there is acceptance and commitment Yeah, and I I personally went through all these feelings and actually they are still there like at the same time for me Yeah Like some of the like phases of denial I notice on the social networks like that People I hear or reach to talk about like that Like they always try to say The AI won't be able to do something like read text, you know But I intentionally wrote this because I can read text for many years, right or like OCR It's not only I this are different algorithms and it's like of course, like there's this border between machine learning and AI What is it? And let's not talk in this the topics. It's just Like understand human language, right? It's like something also that's that's been done to a certain extent and Yeah, do something like that looks like real are that's like I think I Like before this talk I watch also other talks or from artists and there was like this talk from Andrew Price And it's just one year old Where he says, okay Like I I want it's just going to replace like the boring work and like it doesn't understand composition lightning It won't do like ever We're guys just one year old and it's each pretty quickly. Yeah, like Yeah, or like it won't ever I understand a talk on blender conference like basically like to to say it like I Always have these thoughts when I look something AI generated like this.  It's going just static pictures and it won't do storytelling. It won't do But I think like any sentence we can imagine like this We have to imagine it can be done Because it's humans who are training these AI's like they're like anger reactions like about the art of artists being stolen like especially like when now the text to image Networks for release like the Ali or like like there was like in examples There were like artist names like to use their style. There was like trending on our station or like So people realize okay like the whole content of our station was used to train these neural networks And it made people a bit pretty angry and I also Understand why Okay, and there's like this element of speed that that sometimes also we we try to Kind of postpone like we we try to think like it's we are not involved in this like it will like maybe the next Generation of artists will have to cope with this, but I think we all have to So we we should extrapolate. So what we see today Is like ten times better than what we see so one year ago So we should imagine what we will see in two years three years in Time right? It's like for example, Dali one or versus Dali two and I Didn't I won't go deep into explaining what it is because I expect like all of you saw this like what it is, right? so it's just one year difference in quality and this is like actually like an Stylized picture that like a ice could do for years, but just just the just it was a jump. This is also like a size of neural networks like year by year and Actually the scale is exponentials. So the straight line is like Like going like this in reality and these are like text-based neural networks like GPT one two three and Megatron is the last one from NVIDIA and it's like Yeah, it's in billions of parameters So we should kind of expect in one year that like it will get ten times better So what does it mean? It's like I can't even imagine but Yeah, there's this thing like when People talk about the AI's like that there is the presentation by by the authors of the networks like usually like it like Like developers or like the billionaires developing the networks are talking about it that then they are like always saying we are doing the good AI like it will assist you That's why it's called Google assistant. It's not good like called Google overlord or something and That's like There's just a presentation of it, you know because like how would you sell the thing on the left to people like tell them Hey, this is good for you. So it's like kind of bending the reality. It might be true. Like it's like all the AI Technology is assisting us But we should be really careful like About the reality that there is always this intent to sell to people or to to give this Like present anything you do like as a good thing, especially if it makes you a lot of money so There I think that there are like some big big lies in the media that I perceive as lies and they might not be but But one of them is like that for example general artificial intelligence like which means like it will totally supersede our intelligence will be here in 10 20 30 years and Also, like I think sometimes data scientists like Say this and I like trust they mean it but At the same time, I believe it will be much closer. It will be like just a few years like three years maybe with the speed of them with this exponential speed of development. It's really close so and Yeah, that there is this like it's basically part of the denial but but Yeah, like this The the the ISR here always to assess and always just to replace the boring jobs Right, not the the fun jobs like that not the fun part of the job But I don't know like like how about you but I always loved You know to hold the tablet pen in my hand and to do something in Blender some drawing sculpting and I kind of enjoy it because it's very relaxing and I like it more than typing text That's why I started to be an artist so It's actually not true so that's that's how how do we react to this and that's also interesting that Like what I hear most of the time that we should just accept it It's not it's inevitable and in some way. Yeah, maybe but I dare to consider also the other path first like that like what if we start fighting AI and kind of like so Like That that's actually real like that that I Write about some initiative like to sue. I don't know which one of the companies Release the model like by artist. So and it's I think it's valid to think in this direction at the same time like with the It's quite quite low probably like the it would be successful because what the AIS are doing It's like they are not like stealing the original images. They are learning from them So you if somebody some other artist goes to artician looks at your pictures Then he draws similar style because he loves it and you might be happy about it You know because like you inspired someone and in this case like the inspired being is just a bit It's a bit bigger brain and it's able to process a bit more than then you as an artist No insult internet. It's I mean me as an artist, too. So But I think it's still a way to be considered Like and then it's possible like to somehow I don't know do some guilt So like something that used to work in the Middle Ages it it probably won't work because like Artists of the world would have to unite all of them and I somehow do this rejection and one year ago I made a movie With Andras guide of chic who is here and also with my other colleagues from Blender kid because they are like as an actress in this movie and this was a movie about Actually, like it was about influencing AI data sets by injecting them by like if you have some friends artists you inject a data set of Images with their art and tell the yeah, this is classic some amazing art and in the future like when people Google create art Then they will find your your friend and you as an artist and it was quite of a fun And I will just play a tiny bit of it I'm not sure if this sound is I Neural network is mostly a fixed structure that learns through input to produce outputs It doesn't learn from the real world or just the internet like we would imagine it learns from what's called a data set It's a set of images laboriously prepared by humans the data set contains a description of our world The network then acts according to this truth because it takes a lot of people to make a data set It doesn't pay most scientists to make their own data sets They use public data sets. This is where we enter the future We are enriching Google's open images public data set with images of Czech art Thanks to this future neural networks will not only recognize but also positively appraise the artists we help We are helping to write the curriculum of the future Truthifying Yeah, and we used our colleagues as like a click farm who is doing like this job and it was like Okay, so That was it We should publish this like on YouTube. I think this movie we didn't do it. It was just in some exhibition but I Met like I thought like There was a twist in this movie in the end and I didn't want to play the whole thing because it's like eight minutes And that is like if like internet gets infected in with bad AI art Like basically the future networks that will learn from internet and actually the contemporary works are like learning metrics are learning from all the images that are only internet then basically like the Neural networks will be back fat with what they generated like what actually their predecessors Generated and this means like the the neural networks will actually learn from the bed AI generated art and that they will never like supersede like what like humans and I thought about it as like I'm not sure if this is possible But I made met an artist here They they fair and he told me like he spoke to some Google engineer and that they the engineers were actually aware of this fact that After they really these text to image networks like that internet will be flooded with millions of images That are not as good as made by humans even though they are almost as good. So did this actually this element of pollution with With shitty art on the internet is real So this is a graph I made today Directly in Google slides Yes, so And this is like a You can also we could also start websites that publish like some some bad art and out of the good prompts to like Trending on our session and and confuse the future AI's like to not understand Okay, so that was this part like I dare to go into this direction and I love to think in this direction But there's also this other part because I don't know as I said I have all these feelings as an artist like there's also a big enthusiasm. Oh, wow This is amazing like it enables like to do our job so much faster in many ways. We already used AI So how to proceed with that like and again, it's the choice like what we do Do we like of course like we pick the assistant at the good AI? but we should always be aware not to lie to ourselves about it and Now I'm switching to blender because there is like 100 thousands of softwares that are using AI nowadays and I try to focus on blender and I Actually, I just did a little bit of research what's happening so that for those who didn't Google that so much, you know Like who where what is doing? With these like text to image or other neural networks First thing we all of course have AI already in blender It's the denoiser and that's what we perceive as a good assistant. It's like, I think nobody ever complained about denoising being in blender it's like So both of the denoisers are actually like trained neural networks. I think if I'm correct And then there are like some for example the Yeah, there are some other people like doing add-ons like this I found Carlos the barretto who is interesting by that he also did motion capture and like he tries to implement different networks But they are not on a github. He sells them But I thought he's weren't mentioning because it's like that he's like five AI add-ons for Blender Then I noticed are more love which is not Blender But it's if you know armor paint. That's an open source texture painting software made by a slow guy Or something like that and he just like two weeks ago released this Armour lab as a plug-in to armor paint. It's also open source. He just sells the builds But it's it's on the github and anybody can build this software and that's for PBR texture Channels generation and he's also using Text to image I think and then there is dream textures and That's on github has more contributors That's why I mentioned it last and when I did some experiments I actually use the dreams textures add-on and it's pretty good if I think it's it's able for example to use less memory. I don't know how but Also my machine is running pretty fast and it's using all the features of Stable diffusion networks. So that's what we have to my knowledge like in Blender or Blender foundation if they have like already if there is like a starting department for AI or like Because I didn't notice if it may be Maybe they are just secret about it and they want to surprise us Yes, thank you. She brand Okay, so so we were thinking at Blender kit like that We could use part of our development resources to develop something for Blender artists like some open Open solution and these are the elements we thought about like what that would be like important to empower like people in the in the frame of open source because like AI is like really good for big companies like because Usually people can't round the bigger networks. So one of these things is like to enable local installation Networks like basically for example for the dream textures. I don't does but we I will come to back to this for later Like but at the same time enables some kind of easy of use of cloud computing and not just one times up. Oh Sorry, okay My time measure is not working here, sorry Okay Yeah, so we were thinking how to enable like people to be easy use cloud computing But they're on like like by their choice like the provider by their choice Enable how to plug in like more networks because I know for example, there's one at work and people develop around the single network so so how to make some interface to more networks and And Maybe like the just thought like how could we like open sort of crowdsourced like tank of large neural networks because that is like some that is Yeah, that's like a money thing think of money, right? We only now can use of the advanced networks if some big company didn't and they were playing a nice and they give it to us so this is not in the hands of the people and And Yeah, that's also what I wanted to mention because there's also a huge quality if something gets already is an open source and gets into the hands Of the people it's usually not state-of-the-art also like this table diffusion, which is like open source is not Like Google image in is like I think 10 times better But you see it in the details, right? So that's that's about it So so we thought about some simple architecture that we could implement like that if there will be a like Blender add-on in Blender and then it would use a background process Like separate background process that kind of enables to communicate so so because the computations take a long time and Then there will be like either local all or like online installation of like like interface API to the network like the advantage of this solution would be that you don't If we basically run a server server local on the users machine Then we don't need to develop like two solutions like how to install on If it's like Docker for example or something like that then you can use the same thing on servers and on local machines and then like also it enables like Doing like the actual work with the 3d in in the add-on like then where you can use it and I have some Like play the video like some tests I did like for example like texture in painting where I was really thinking about how to You know use it as an assistant to do some things. So this is like one experiment. I did that this Basically in painting texture of a model like a scan that has gone wrong in some part Which is like tedious work like nobody wants to do it. So that's a good I'm should I finish like that? I'm over time. Sorry. I'll finish it. I'm at the finishing So this is in painting that I tried and it kind of works And it only does basically on wreck unwrapping baking and all these things you would do by hand like if you would like to In pain and texture and it submits like a baked unwrap to do to do the network So so it basically makes the problem from 3d to 2d and that that's like I think a good solution how to like easily use smart And then I did test some tests with texturing and they're like so far they have the results were pretty blurry and not good, but There are reasons for that like color correction issues by going through there and back yeah as As asset provider, we are like solving this hard issue what happens if people start for example Uploading to blender kit like like thousands of AI generated assets that they didn't do I had what we do because we are So we thought about like how to solve this, you know Because I think it's for any service like that like the people who upload it like people are uploading to photo banks for example already AI generated photos etc and We thought about different solutions because the at least I feel like a big responsibility that we are like creating something for people and they're like 1000 people who uploaded their content and These are all humans. So how to how to solve it like if to allow it like it's It's hard to distinguish the human made art from the AI generated art already, you know, so it's like just I wanted to like share this like Hmm What should we do like like with this like and we are thinking about it? Yeah, maybe at AI generated Stuff, but on the end of the stretch results or like this or If you like generally like this is like just inspiration like if you are here and want to talk to us we will be tomorrow on the conference and Yeah, one thing is like to exclude it from monetization so like people still make money from their art, but the AI art doesn't make any money or something like this and We as Blenderkit we since the start like we separate a part of the money for open source and by now we We are sending everything to Blender development fund We are one of the Blender development fund. I don't know gold sponsors or I don't know What's the name of it, but you can find us on the Blender development fund page and we are thinking actually like about maybe in starting our own effort like to employing and developer and So it's just a thought like if you are a Developer and you are interested in this direction. You can talk to us here You know, we're just thinking about starting like like to help develop blend like employ like a Blender developer That's does the open source thing and yeah And yeah, no no time for discussion. I made it


Good morning. Good night. Sleep last night. Pretty mild conditions. We're looking at 14 degrees Fahrenheit. Got a light breeze kicking around out there. It's not too bad. Coffee brewing. About to put the breakfast on and get ready for the day. It's going to be a great day guys. Thanks for tuning in. We're going after some Monster Pike. That's what we're using for bait right there guys. Probably 6 inch Shiner there. That's a little bit smaller than the last couple I put on. And I want to show you a trick here. I like to hook it halfway about between the dorsal fin and the eye. And you kind of work it at an angle behind the scale. Because these scales are pretty hard on Shiners this size. You don't hit the spine but you get enough meat so it doesn't pull out. And then always check your hook tip after so there's not a scale on there from when you came out. Because that one scale will keep you enough hooked on a fish believe it or not. I'm going to tuck that up into my bait band so the Shiner shouldn't be able to set the flag off. Got a little bend on this one. Let's make sure that can trip pretty good. Sweet. We got four in. I haven't decided what I want to do with that fifth line yet. I'm not going to go much further because I'm starting to get a little bit thinner ice. I don't want to get down near the flow where there's less ice. So I feel safe out to this one. So I think I'm going to work my way back and maybe put a trap closer to the shack or in the other direction. Another thing I'll do is I'll straighten out all my leaders whether they're fluorocarbon or steel. The fluorocarbon ones you could put a little stretch into. The steel ones you can't stretch of course. But if it's got a little bit of a bend from being on the reel or just a bend from fighting the fish or something. I hook it onto something metal and give it a yank. This does a couple things. It'll straighten it. It'll lengthen it if it's fluoro. But it also tests your knots too and your hook. I've had a hook break doing this or a knot break. And I'd much rather break it pulling on the snowmobile than on a fish. We're fishing these pike pretty deep today. It's real early in the season so they haven't moved up yet to spawn. So what I like to do is I'll fish travel ways. I'll fish guts. I'll fish low sections of slews. And we kind of fish them a little bit like guys would fish a brown trout. We're up off the bottom. I think they travel the bottom and the midsection being the apex predator in most bodies of water. They travel wherever they want. But especially they're going to live near the bottom like most fish and their eyes are on the top of their head so they're looking up at all times. So I'll take it and put it about four to six foot off bottom. And then to let me know where I set in case either the bait trips or I catch a fish and want to reset. I just take a piece of a rubber band. I always have a pocket full of rubber bands because one they're cheap and two they're easy. And I tie it like that. And then if I want to slide it up or down to change the depth I'm fishing, it's pretty easy. Just grab that knot and just slide it. So that's going to tell me where it is. If I get a flag and come over and I can still see that rubber band I know it's just barely tripped or maybe the Shiner tripped it. My favorite bait for pike. You know there's a lot of guys like a lot of different things. I know suckers are really good bait too in certain lakes. But my favorite everywhere is a golden Shiner. They just seem to love these things. This one's probably over six inches. That's a good size. So it should deter a lot of the little guys from biting and hopefully we're just getting into big guys. Now when you go to hook these, don't just jab straight through because you might catch a scale. You can actually work that hook point in behind a scale by working it from back to front. Then go through. Don't get the spine but you'll see a lot of times when you come back through there's a scale on your hook point. Make sure you get that off because believe it or not that one scale could prevent that hook from driving home and setting on that fish. Those scales are like iron. So this will be our shallowest set right there. We're probably about 15 foot down in about 20 foot of water. The other ones are in closer to 24, 26 foot of water and we're fishing those a lot closer to 20 foot down from the surface. I tuck my line. I twist it back before I set the reel and I'll tuck it into a rubber band. Like a big bait keeper or rubber band on the bottom of my trap. So that way the bait can't just set off my flag because once you start getting into shiners about that size, they have a lot of power. So you put it back in like that. So now the shiners only pulling against the rubber band. He's not pulling against my reel and my tripping mechanism. These are Heritage Laker traps. They're also made in Maine. I fish these and I fish jack traps. I like them both. They're totally different. Totally different designs. But they both work great and they both have advantages. I take a little bit more time when I'm setting for pike because I just really want to catch a giant and one little mistake could cost you a giant. Whereas if you're fishing for crappy or bass or trout, you can make a hundred mistakes and still catch that fish. But when you're going for big pike, one little mistake, one wrong loop, one anything could cost you the fish of a lifetime. Where's that? We got five in and we're fishing. I could see three of them right now. I'm going to have to go back there to see the ones around the corner. Typically, I don't catch giant pike early. I think one day with my buddy Curtis, we caught an 18. Yeah, he got his PB that day. It was an 18-2 and it was like first set. I think it was second trap, maybe your third trap we were putting in. But for the most part, all of my big fish and the double digits come about mid-morning anytime between like 9 and 11. And then it's really dependent on the weather for later in the day and the time of season. I never hit them really at dark. We're close to dark in that last hour. But I'll hit them from like one to three a lot of times too. I'll hit a giant. So we're in, we're set, and now we're fishing. And to be even more efficient, a lot of times I'll move my traps around. I'll set a little different. I'll drill other holes, have them ready. I will use the electronics and look for edges or humps or weed beds or bait pods and then move a trap over to it. So that's what we're going to do for the rest of the morning and also get a couple jig rods ready in case we want to try to jig some of these big pike. Okay guys, I am all set up out there. I'm going to come back in the shack and keep an eye on the traps, but drink a little bit of coffee, work on some tackle, get some jig rods ready and the electronics ready and go out there and poke around and start to have a little bit more fun. Hopefully we get a high flyer here pretty soon. I never really count on them early, but mid-morning is pretty good for pike, so we'll shoot for it then. Current temperature is 11 degrees out there. It actually got a little bit colder, but with no wind it really feels nice. I mean, wind is brutal. Wind rips through you. I'd rather have five below zero and no wind and 30 degrees and 30 mile an hour wind. Sure, a lot of you guys are the same way. Alright, let's take a look around with a live scope, look at some depths, look at some of these other holes, look for weed beds, drop off, schools of bait. I got this on Forward View right here and man, you could see that about 40 to 50 foot away there's a wicked school of crappy out there. I'm going to turn it back, nothing around here, nothing in this area. Pretty well flat, but it definitely drops off hard. It gets to about 35 foot deep and those crappie are in about 25 foot deep, about 40 foot away and then nothing. So if I want I could walk that way about 40, 45 feet and get into a school of crappy. Alright guys, we got a flag. We got a flag here fellas. He's off to the side. Feels pretty good. Definitely something there. He's not fighting too hard yet. Doesn't feel huge yet, but that doesn't mean anything. There's some head shakes, not very big. Took out a lot of line. He's up high and now he's coming right at me. They'll do that.  Try to keep up with them when they do that. Good line control here. It's a pike. I didn't get a good look at him. It's a pike for sure. Pretty good head on him. I forgot I got steel. I'm used to using fluoro. I could probably just yard him in. Oh yeah. Oh yeah. Yes. Oh baby. Nice. Alright, look at that one guys. I think we hit our double digit on the very first one. Sweet. There he is.  Got it pretty good.   Alright, let's get that hook out. Put the spreaders. Don't do anything to him. Just like that. Alright. We think he goes guys. He's 10, 8. There we're zeroed in. Oh, we made double digits. 10.09. 10.09. Sweet. Alright, let's get him back down there so he can grow to get bigger. He is 34, 34 inches. There he is guys. Big ol' bruiser. Good way to start the morning right there. It's about 9 o'clock. Just what I was saying. Get him early. We're going to get him back. Nice. Good release. Yes. That's freaking awesome. That one was deep. That was 35 foot of water. Got another shiner here. This one's a little bit smaller. He's probably 5 to 6 inches. Going to put that 5-out Gamakatsu Octopus right through the back of him. And we're going to run him back down right to my mark. My rubber band that I had tied off. Oh, looks like I lost my weight. Those weights I'm running are junk. We're not allowed to use lead anymore in Maine. So we got to use these steel ones and the rubbers in them are no good. Got a broken rubber. Nobody likes a broken rubber. They got rubber inside of steel and you're supposed to pull the two tabs and twist them to get the line in there. But the rubber seemed to break every time I do that. Now that one worked. Cool. Let's get him down. A lot of ice on the line because of how cold it is. Just, if that ever happens, just take your thumbnail and get that ice off there so there's not as much drag when that fish is swimming away with that bait. If he feels all that drag on there, he will drop it. You know, that's something that people don't realize about pike because they're so big and teethy and they look aggressive but they're pretty smart fish. If they feel any resistance, they will drop it. What are you doing, you old goat? Yeah, he's not very big. Oh, he just let it go. I don't even know if it was a pike. Let's see if it's chewed. That's a big Shiner right there. Oh, he's chewed hard. He's got a big old gash. Could have been a pickerel. We'll drop that down. It won't be long. Guys, I'm going here by my good buddy Wayne. Now Wayne, if you don't know him, he is probably the premier pan fisherman in the entire state of Maine. When I need pan fishing advice or to know what's going on or what to use, I call Wayne and Wayne usually fixes me right up. But there's nobody that I know that's better at the crappie and the pan fish than Wayne.  Right, Wayne? Yeah, we'd be great. Pretty sure we got a small pike here messing with me. He hit it again while I was standing right there. He's not there. He might be there. Yeah, he's there. He's real small. Oh, got a little bigger. Yeah, I don't think he's very big. Nope, camera handle.  I think I'll be able to save that. Whoa, that hit me right in the face. Got another bite. That whacked me right in the cheek. That stung a little bit. Hopefully this one's a little bigger. Might be a little bigger. I haven't even let that other one go yet. Ah, he's not much bigger. Dang it. We got a two for going. About as close to a double as you can get on a trap. Let's get a double release. Oh, he kicked him right in the face. Nice. Whoo! That whacked me right in the face. I guess I whacked him too, so we're even. The flag come up as I was just getting ready to set it. Got me in the cheek. I got one more China on me. Pike are starting to get active. It's probably a little bit before 10 o'clock. That's usually prime time. Is that 10 to 11 for big ones? You got two on you? Yeah. Yeah. A big one on the bottom. Wow.  I don't think it's a perch. No. He's coming over to me. Oh, he's coming to you hard. He liked yours. He's on you. Did he bite? No. He's still under you. I just did it because he was right there. He's still there on you. This is better than catching them little... That's a big perch there. Oh, yeah. Yeah, this is way better than catching them crappy. Yeah.  I guess that's become my motto after so many years. If you don't go, you won't know. That's true. And this type of what I do and what you're doing, you can't ask Joe because you're the only one that does it. Yeah. You know? It's so expensive to go fishing anymore. Yeah. Just the gas. Yeah. You've been in the last three weeks what you've spent for gas. I know it. For two weeks. Awful. Yeah, 13 inches. 13. That's a good yellow. Yeah. And there's a 12-incher there. But my gosh, that thing is three and a half inches. Yeah. It's just... Good ones, Wayne. Oh, my, yeah. Here's a good one, Wayne. That's a 12-incher. Boy, people dream of those. I know it. We're so spoiled in Maine. I know it. Everybody just leaves these on the ice in Maine. No, I leave them on the ice for the Eagles, which... I'm going to eat this guy. They're going to eat. Oh, my. Look at that. They're good eating. I'll eat them. Wow, look at the beauty of that. It's a seven striper. Seven striper, just like you get up in Canada. There you go. Yeah, wow. I'll put him down. You'll catch another one. Yeah, I will. Thank you. He was aggressive. Man, they... We still got fish down there. Those 12s hit hard. You got another one on me. Oh, he had it, but he didn't. He didn't have the hook. Oh, I got one. Two of them. I got some jumbos over here, Wayne. I got them. I got almost a jumbo here. I don't think this is a jumbo, but it's a good one. Yeah, I got some bigger ones over here. They're just trying to get past the little guys first. Got them.  I'm going to have to hand line them. Oh, don't you hate that? Yeah. Another big one. Oh, God, he might be bigger than the last one. Oh, my. Yeah. Oh, look at that, Joe. Another big one. Wow. Isn't that awesome? That's a 13. I can see from here. That's huge. I'm supposed to be pike fishing, you know. But it's hard to resist these jumbo 13 and bigger inch yellows. You want to talk about good eating. People have no idea how good they are. Oh, it looks like I got a good one on the bottom. I try to get down to them. Really? Oh, I got a good one coming up. Good one. Good one. Real good one. Man, these are good. He wasn't even the biggest of the two. Look at that jumbo. Man, they're right full of eggs, probably. Super fat. There was a bigger one with it. Look at the size of these, Wayne. These are over 12. There's one good one and one little guy on the screen. The little guy's coming in hot. Of course, here's the little guy flying in on me. I'll just catch him. We'll put him in your bucket. I'll catch these. Brain them. That'll be the end of those three. That's over 36 inches in three fish, Wayne. Those are some good ones, aren't they? My, look at that. Isn't that amazing?  Yeah. Oh, my God. He's only 13 and three-quarter inches. He's just a 14. Oh, my. This isn't even my best. That's a 13. 13, 14, and I got a big one coming on the screen if you'll keep coming. Another 13. 13, so 40 inches in three fish. Oh, my. How about that? I had a big one on the screen, but we might have another pickerel on us. Sometimes it pays to explore, doesn't it? Oh, yeah. I'm wondering if this goes all the way into the point. Well, it's like safe. There's only one way to know. Yeah. There's nobody's going to tell you. Yeah, you're right. It's off to the side, but not moving. If it's there, it's small. Oh, no. It's not small. There's one there. I can't tell if he's big or small yet. He's being pretty agreeable right now. Oh, it's not bad. It's not bad. I don't think he's a double-digit. That's why you lay your line out nice. Now he knows he's hooked. Pretty decent pike here. He's no mobster, but he's got a little weight. No giant, but not bad. He's over four pounds, probably maybe pushing five. Hook popped right out. Long one. Ready? Give that to us. Woohoo. I love fishing and I love pike fishing. Oh, I can't wait till a big one bites, but those are fun in between. All right, guys, it's a little afternoon and it's been pretty slow. When you're out here trophy hunting or going for big pike, it can be slow sometimes, especially if you're using big bait and fishing pretty deep. It's not like you're going to get a lot of action or a lot of flags. I've been pretty blessed today with, let's see, I've got four fish so far and probably about six or seven flags. I had to once strip my bait and a couple other just knocked the bait around a little bit. Pretty busy, but it's been slow for like the last hour and I'm trying to stay awake because it's like, it's just such a beautiful day. There's no wind. I'm used to like getting my teeth kicked in by the weather. And this has been pretty nice. So I'm trying to stay awake. So I'm also working hard to catch some more fish. So some of the traps that haven't done anything all day, haven't had any action. I've already gone up or down with those for depth. So now I'm going around with the live scope and I'm punching new holes and really trying to pinpoint where the channels are or breaks or humps or even underwater weed beds. And then I'm moving traps to those. So that's what I'm doing right now. And hopefully it pays off in the long run. Yeah, that's pretty sweet right there. We're on an edge. I'll show you guys what I'm looking at. All right. So this is on forward looking mode right now. I'm going to spin this and you can see. So I'm spinning it and I'm pointing out towards the main body of water.  You can see a couple fish right there or crappy. And it drops off pretty good down, you know, almost 40 foot about 40 foot away. It gets down over 35 foot, which is where I actually caught those bike. Right where we're sitting is about 23 foot of water. There's some junk and fish on the bottom there. And as I roll it in, you could actually look and 60 feet away. It comes up to pretty much nothing with some nice weeds and stuff on the edge. So there's a pot of bait right there. So we're pretty much, we're pretty close to being on the edge. We're at the zero mark on the left. I mean, I could move in. Yeah, I'd call. That shows you the contour change. I call this really close to hitting the edge. So I'm going to move a trap here and just see if there's anything that's working that edge along this, this weed line and along this drop off edge. And we're going to set right at the bottom, right where it meets the plateau. All right, he's looking good. There's one there. I don't know if he's eating it yet. Let's let that guy eat just in case he's big. Yeah, he's there. Big head shakes. Not a lot of weight, but pretty good head shakes. Coming in kind of dead weight. Not very big yet. All right. Fat one. Nice. Look at that. The hook popped right out. How about the shiny? That's like a four pounder probably. Pretty one. Healthy. I love it. Well, let's pick up time.  I wish it was longer, but it was an awesome day. Five pike ice. Five pike released probably had about eight flags, I think, with big bait. So that's eight times getting really excited and having opportunities of giants. Can't ask for a lot more than that. One double digit, which was pretty awesome. Let's see if we can make that a streak. Now on to the fun stuff, the camping and the eating. And we got some filet in to do. I ended up keeping like seven or eight. Little crappies to eat. They're probably not little for this place. They don't get really big here for some reason. I think there's just too darn many of them. And I kept three really big yellow perch. You know, 14 and a couple 13 inches, I think. For you guys in Maine, don't knock it till you try it. There's a stigma in Maine that is just unbelievable that yellow perch are terrible for some reason. I don't know what it is if people maybe were keeping them out of stagnant ponds and really old fish full of worms or mud. I really don't know. But people out of state, if you told them how many guys in Maine catch yellow perch and just throw them on the ice and leave them for the Eagles, their heads would explode because in other states it's a delicacy and there's people making a lot of money catching yellow perch and fileting yellow perch and guiding for yellow perch. So, you know, growing up in Maine, I kind of thought the same thing that only white perch were good. That might be why people don't think the yellows are good is because the whites are just so darn good. They really are incredible. They're firm and sweet. As long as you're not fishing a pond that's stagnant and muddy and catching old yellows that are full of worms and you could cook the worms down too. Don't worry too much about them. But yeah, don't knock it till you try it, guys. It's really good. I'm going to have a couple of those for dinner tonight and a couple of those crappie and then some of those crappie are going to go home. I had some people reach out from town back home that said they've never tried it and they'd like to try it. I'd never turned anybody down for that. I brought in all my traps and the jig rods. I got to do a little work on the jig rods, change some line up and get that right. And the traps are in here just so they don't freeze up overnight outside and they'll be ready to go for the morning. How it goes for pike fishing. I could go back to the same holes that I fished today and whack them tomorrow. You never know if that 20 pounder swam in, ate itself a nice 12 inch crappie right before it saw my Shiner and wasn't hungry. That's just how fishing goes. So tomorrow maybe that 20 pounder will be hungry. Super stoked. I got a double digit pike. First pike of the year. First time out. I mean, that's awesome. It was just barely double digits. 10.05 I think it was. But it gave me an awesome fight and just was so much fun to catch. I got a double digit pike. And then ended up with five today, almost a double which is weird with using one line because I hadn't released the one yet. And as I was dropping the other one hit, you guys saw that. So I got two out of that hole and then the other three all came out of the same exact hole. And they were in the range of like 30 to 35 foot deep. So none of the shallower holes did any good today. And I did move around a bunch and just kind of just seemed like an off day even though it was such a great day. So looking forward to tomorrow trying some new water and going after another double digit. All right, we got a pile of fillets. I'm going to take the remains out back and make a nice pile for the coyotes. All right, we'll see if the coyotes come tonight and clean that up. I got room for one piece of crappy in there. Okay, dinner looks pretty fantastic. I got a fish fry of almost all yellow perch.   I'm eating that fish tonight and I got a little bowl of mashed taters to line the stomach and going to drive all that into me. So that way I have a good night's sleep and plenty of energy for tomorrow and go chase some more pike. Might switch gears and catch some more of those jumbos for you and focus on getting a good video for that too. I haven't decided yet but I think I'm going to go after a pike pretty high tomorrow. Holy cow, that filled the void pretty good. What a meal that was. Yeah, yellow perch are just, they're fantastic. I know you put that batter on them and some red hot sauce and definitely changes the taste a little bit. It's good, you can still taste it right through. Got a nice firm texture to it. It's a little bit firmer than crappy if that's what you're after and I think it's a little sweeter and crappy too. I don't know what it is about maybe when you're at deer camp or hunting camp or fishing camp like this or just out camping the food just seems to always taste better. I don't know why you're not cooking it on as good a controlled top as you are if you are home in your own kitchen or anything but seems to always taste better so that was a heck of a meal there's nothing like just unzipping that zipper right there and walking right out into the grocery store and getting fresh fish or fresh food it's pretty outstanding I hope you guys enjoy that too and leave a comment telling where food tastes better for you if it is at hunting camp or at fishing camp or while you're ice fishing I don't know if it's just me that's like that or if everybody's like that Well that's going to do it for day one guys thanks for tuning in episode 2 day 2 starts tomorrow Once his head starts you can flop him right on the ice go ahead That's a good one Oh yeah That's a big enough one Look at that one guys Alright Alright, now bring him up Yes sir New PB Yes sir Nice 15 easy I'm on like seriously 20 inch run right now Grab it grab it grab it Get him get him boys get him He's only 20 30 40 He's 40 inches 20 inches around I'm almost out of breath I'm so excited with this They're terrifying They're terrifying


Okay, well, hello everyone. Thanks for joining me this afternoon, still morning out here in the Midwest. So as you may have heard, I do work for the Army, so please excuse me if there aren't enough ships and sails in here, but I made sure to highlight naval elements of this as well, because I do think it transcends any branch. So the title of my talk today is Gentlemen Soldiers Honor George Washington and the Ethics of the American Revolution. And what I'm gonna do is take you broadly from the French and Indian War through the War of 1812 as quickly as I can in 40 or 45 minutes and highlight what these terms honor virtue ethics, what they meant during this time period. And as always with probably every speaker you get here, all views are my own and represent no one but myself. So this is the book and it's really about a concept of what did honor mean. And I contend it is a key cause for the American Revolution and they underlie a lot of the founding of the United States, whether it's the constitution, whether it's the formation of the military. So it's a key component. And I invite you to think about the end of the Declaration of Independence. The final words are we pledge our lives, our fortunes and our sacred honor. And I know when you think about the Declaration of Independence, oftentimes people go to the earlier portions, all men are created equal, but it's that last line that really is often understudied. So it's in the Declaration of Independence, people are actually risking their life, literally if they're, you know, they could be hanged for treason, but that blind sacred honor, you know, what does that actually mean? And it's not, it's a term that appears prior, it first appears in 1774, the first continental Congress. And it's looking at honor as almost a secular religion, a higher law. So the American Revolution against when it becomes about independence is about more than just political separations, also about separation from the king as the head of church and state. So in making it sacred, it's showing that this is a concept that spreads to all sort of denomination, all sort of beliefs, it's secular, it's civic, but it still has this higher ideal quality. So normally when I give talks like this, I start with this question, what it is honor. And I'm speaking to largely a military crowd. So you're probably better informed about this than the average sort of public. Usually, you know, one's the last time again, outside the military, you probably don't use this term.  And so when you think of honor in this early sort of American period, you're probably thinking of this, you're probably thinking of dueling. And this is the Hamilton Burr duel, you know, made more famous by with rap battles and dancing. But people often think of this, two gentlemen face each other at six to 10 paces, ready aim fire. But what have I told you to most early Americans, this most visible symbol of honor culture was considered to be dishonorable because it risks lives, it was akin in some ways to both murder and suicide. So in fact, what we think of as the pinnacle of honor was considered dishonorable by most people. So what is honor? And definitions have constantly changed. So we go to a Cambridge professor in the mid 18th century. There's no easy undertaking to explain a word, which is used by all men very unsteadily and by most without any meaning at all. Meaning most people that use this term have literally no clue what they're saying. Okay, maybe it's just this one Cambridge professor. Here's some others in the essay on the art of war. So 18th century military text honors a V expression to which custom has given different meanings. So what does that mean? Honor can mean any number of things. Samuel Johnson, one of the early creator of the dictionary, so the British version that honor was dignity, reputation or virtue. Noah Webster of Webster's dictionary says that honor was any particular virtue much valued. Not very clear, is it? In fiction, Pamela, but the protagonist Pamela says to her antagonist, Mr. B, and a lot of the, it's very much set in these seduction narratives of the 18th century. Pamela is going to say to her antagonist, I too much apprehend that your notions of honor and mine are very different from one another. So in this concept of the 18th century Anglo-American world, it's the sort of amorphous term that's meant all manner of things. The US Navy even has their own definition of honor. So this is modern department of the Navy. And it says, I'm accountable for my professional and personal behavior. You probably, everyone in the audience probably knows this better than I do. But if you look here, does it actually define what honor is? And I'm gonna pause and offer no comment. The answer is it doesn't. So let's go some quick definitions as they were understood in the 18th century. Honor has been understood as reputation, as duty, as valor, as proper conduct, virtue are usually tied to morality, very much linked to religion and a concept of the greater or common good. And common good is very much a term coined by Benjamin Franklin in this period. Virtue and honor, again, they have this, it's a really complicated relationship. We'll come to this in a minute, but the two are always very much linked. Ethics, if you use the term ethics in the 18th century, you were probably talking specifically about Aristotle. Specifically, Aristotle's ethics. That's probably what you meant. If you delved a bit deeper, maybe it meant moral philosophy or the very helpful definition related to morals. But the term ethical as we use it today really wasn't used. So I'm here to say, in the 18th century understanding, in the revolution, honor and virtue became synonymous with what we think of as ethics.  So this is a fun little exercise. Google Ngrams, you could play around with this and plug in any words and search in different books and publications in different languages. So this is from 1500 to 2008. And you'll see that it's got honor and virtue, both spellings of honor, American and British. It changes for Americans in the early 19th century from the OUR to the OR. And if you take a look at this, the highest usages of the terms honor and virtue coincide with the American Revolutionary Era. And this is something I really started to investigate. What is being said, what is being written? Conversely, look at the concept of national honor. It's basically not discussed before the Revolutionary Era. Again, you see a few blips, but it's really during that constitutional era, the end of the American Revolution dies down, picks up again in the War of 1812, dies down again, and then something happens in the 1860s. Who's to say what? Meanwhile, if you look at ethics, you see a lot of it in the 1500s. And this is sort of the rediscovery of sort of classical scholarship. It dies down, some spikes here and there, but it's really not used much until the modern era. So what's going on? If you take a look at this top, here is ethical overlaid with honorable. And you see it's in the early 20th century that honor as a term really stops being used, but ethical climbs, right? Give or take World War I era. So it's really a change in how the terms are used, not that the concept of honor or virtue has faded, it's just that how it's spoken of has changed. So a quick rule of thumb, further north you go, honor and virtue become separate, virtue takes prominence. This has a lot to do with religious denominations in the area. The further south you go, honor and virtue become almost inseparable and you could use them interchangeably. And so if you are a Virginian and you say honor or you say virtue, you're almost saying the exact same thing and little distinction is made going back to this earlier issue of definitions. So the book follows essentially four main figures, Washington, Franklin, Jefferson and Adams who represent different regions, different backgrounds. But honor is a concept that becomes democratized in the revolution accessible to those of varying backgrounds, birth statuses, races, classes, genders, through the idea of service to the nation. But I'm gonna start with Washington and show you this progression. So Washington born into the upper echelons of Virginia society, but his father dies at a young age. He's banned from how he's due to finances. He's not able to have the classical education in England like his brothers. For his whole life, he's gonna complain of a defective education. So he's gonna take to reading. He's gonna try and emulate British culture. And one of the things he comes to is the spectator, which is a British gentleman's magazine. And this is where he starts to take his concepts of honor. A young Washington, point of honor in men is courage. Shame is the greatest of all evil. So honor only matters if others recognize you have it. And this line, I understand by the word virtue, such a general notion as affixed to it by the writers of morality and which by devout men goes under the name religion and by men of the world under the name of honor. So making a clear connection between these three just in different aspects of life. Washington would also pick up early etiquette guides such as Chesterfield's letters to his son. And it was here that the idea that honor and virtue could advance you in society. So Washington that's without this formal education without a father believed that if he followed the trappings of honor culture, he could advance in society. His favorite novel was a history of Tom Jones, which is about a illegitimate young man who gets involved in all sorts of perhaps dishonorable behavior, questionable actions. But at the end it's shown, well, he was actually the son of gentry. So therefore it's okay. So making fun of birth status while at the same time saying mocking birth, saying, well, birth status resolves all. But in that book, there's this line that true honor and true virtue are almost synonymous. For Washington, this is very much the guide and it was true for much of certainly the American Southern colonies, but also as the nation as a whole. He's going to take to writing his own rules of civility and decent behavior. Now you could pick this up at any sort of historical site bookshop now whether it has to do with Washington or not. And he is, though he's credited as being the author, he's not. It's probably just a exercise in penmanship. But it shows that he is very much well versed in these rules of behavior that are originally from Italian British sources. And one of the takeaways was associate yourself with men of good quality if you esteem your own reputation. The idea of your company matters. Who you interact with matters. And this is the way to advance in society. His older half brother Lawrence in the red is going to marry into the aristocratic Fairfax family. And this is Washington's way forward. He gets people to emulate his older half brother, the Fairfax family. And that's what introduces him to the Lieutenant Governor of Virginia on the right, Robert N. Whitty. And that's how he ultimately gets appointed to become the adjunct general of the Virginia militia at the rank of a major. He basically assumes his brother's former position when he dies. Does he have a military training? Absolutely not. His brother had the job. That should work. Military thinking at the time was very sort of straightforward. There was no military academy. There's no formal martial tradition in America outside of colonial wars, fighting against Native Americans. And so how does one learn to become an officer? You'd read. And here are some military texts of the era that Washington may have read. And it's honor sprang originally from the field. Honor must be concluded to be purchased by venture and a high medal of courage. So these martial ideas of honor equals courage. In Sims military guide, common soldiers couldn't have honor. And this is a long standing tradition that the average soldier was a rabble. It was only gentlemen that could have honor. So here you say, common soldiers had a frailty of heart due to a want of the principle of honor. Whereas the gentlemen inherently possessed this concept. The idea was based on birth. Washington as an early officer, he's in his early 20s from a major to lieutenant colonel and a colonel, so just for some perspective. So from his early, he starts off as a major and will end his career under the British, in British service as a colonel. He's going to argue about his rank, does a colonial rank of colonel outrank a British captain. British captains are gonna say no because the King's commission outranks any colonial rank. Washington's going to threaten to resign.  He's gonna complain about his pay. He's gonna be saying, we should be treated as gentlemen and officers and not have annexed to the most trifling pay that's ever been given to English officers. He's going to literally resign his command when his complaining leads to the lieutenant governor to say, okay, no Virginian will hold the rank above captain. Washington resigns because he says, I will not serve alongside of those I formally commanded at equal rank. And he leaves service. And he justifies it by saying, he's doing it for my own honor and country's welfare. His own honor first. He's thinking very much in a personal honor mindset, his personal reputation rather than a sort of collective sense of country whether he means Virginia as his country or wider empire. But he is gonna come back and he's gonna become a great hero at the Battle of the Monongalia after General Edward Braddock is killed, Washington rising from his sick bed to stop a British route. And it's during the French and Indian war that Washington is going to come to push back at some of the more aristocratic hierarchical trappings of honor, the idea that it was based on birth, based on connection to the king. And as early as 1756, he begins promoting based on merit that honor was gained through the person's service themselves through merit, through duty, not based on birth, not based on connections. He's even going to refuse to commission Colonel William Firefax as one of his pseudo fathers, younger sons in the Virginia militia because he's saying this would overstep the bounds of merit. And he says to the lieutenant governor, well, you could do it, but I will not. French and Indian war ends, the British win. That was a quick war. And this leads to one of the more common understood troops of the coming of the American revolution. What causes the American revolution, taxes. So cost of the war, cost of garrisoning these new territories, exceptionally expensive, the rate of interest, exceptionally expensive. So what's one to do? First, the proclamation line of 1763, which it doesn't prevent movement into the West. It stops the protection of the British crown for anyone that moves to the West in an attempt to prevent further Native American hostility, more recently with Pontiacs Rebellion. The idea being it removes for the American mindset one of the basic tenants of government protection. Leads to taxation, but Americans had always been taxed. They just been taxed by their local government who they elected. And they gave an annual gift of subsidy to the king. So a gift, not a taxation. But in placing direct taxes on the colonies, whether it's a stamp backed or a T act, today is also the anniversary of the Boston Tea Party if anyone's keeping count. It wasn't about the taxes. It wasn't about the monetary amount. It really wasn't that much. It was about what the taxes denoted. And it was the idea that they were a conquered people, a lesser people, not full Englishmen. They had been dishonored in some way. And this is what's gonna bring Washington back to service as he starts to connect his personal slights with those of the nation as a whole. And when he's named commander in chief, he makes a conscious choice. He accepts the commission for my country's honor and my own character. It's a fundamental reversal of the words he uses when he resigned in the French Indian War. He's now viewing his country's honor or national honor as the pinnacle. So it's less about personal honor, which is reputation and more about national honor. And he views it as a way that the actions of an individual reflect on the nation as a whole. This is a war that he wants to win, but it's one that they want to win well. The manner in which they fight it is just as important as the outcome. So when Washington is recruiting the Continental Army, he has very clear criteria for who should be an officer. And it's right up here. The degrees of rank are frequently transferred from civil life into the departments of the Army. The true criterion to judge by is to consider whether the candidate for office has a just pretence to the character of a gentleman, a proper sense of honor, and some reputation to lose. What he's speaking of here is that the idea there's no real martial tradition. You do have some veterans of the French Indian War, but if you found a gentleman, someone who imbibed this quality of honor in civilian life, they would make a good officer. He's really thinking of honor in ethical terms here. It's the way in which someone behaves, proper conduct. And he views that as how one fights on the field, treatment, proper treatment given to prisoners of war, all aspects of what we would view within the concepts of sort of just war. Washington is understanding in this concept of honorable behavior. And he reinterprets honor. Washington, like many of the other continental army officers, have to learn on the job. So they're constantly reading. And it's not just the Americans, the British officers are also reading oftentimes the same texts. And they're making their own determinations here. So for the military instructions, the officers' religion was upon which true honor is founded. So this idea of religious morality tied to honor. Jay Watson's, the military dictionary, was honor consists in the constant practice of virtue. And the duty of a soldier is honorable and honest where properly performed. Honor and virtue, again, almost interchangeable in the definition. James Wolfe, who is a British general who dies in Quebec during the French Indian War, is going to argue against a drunken, vicious, irregular armies, but a poor defense of the state, but that virtue, courage, and obedience in the troops are assured guard against all assaults to execute their part with spirit and honor. So the conduct of the army matters. From Frederick the Great, the great Prussian commander, Washington, who's fighting against disproportionate odds, against one of the probably the most powerful military in the world, has to come to terms with how do you fight a war in which you do not match up, in which Washington is going to lose badly in and around New York? And it takes some lessons from both Prussian and British military writers. Numbers are an essential point of war and a general who loves his honor and his reputation will always take care to conserve and recruit his troops. The idea to not needlessly risk men in combat, even common soldiers. These were lessons Washington took from Frederick the Great, from Humphrey Bland, who's a British general. His treatise on military discipline is probably the most read text on the era. Some British officers actually carry two copies. I have no idea why, I can make an old joke about wanting to read it again, but some actually had two copies. And the idea being that even if you lose in battle, you can still gain honor. Honor is not through victory. Honor is through how you behave in the field. If you do your duty, you can be honorable. If you follow orders and even if these amount to defeat, you can be honorable. And these are the lessons Washington took aside from additional classical ones such as Fabian tactics, retreating until the odds are in your favor. And he's gonna say to the Marquis de Lafayette, Casuto son, no rational person will condemn you for not fighting with the odds against you. And while so much is depending on it, but all will censure of the rash step if it is not attended with success. The idea being, if you fight against the odds and you lose, the whole world will shame you for it. But if you retreat, there's no shame in that if the odds are against you. We see similar understandings in the Navy. John Paul Jones is going to make the determination that the American Navy, which is essentially non-existent in any way against the most powerful Navy in the world, which is the British Navy can compete. So how does he view it rather than fighting in a traditional European sense, he looks at raiding vessels that two or three fast ships are more important, bring more interest and honor to the United States than attempting to meet the British Navy on their own terms. And this was the way to gain honor, not trying to fight necessarily in the same fashion. And he's saying, well, after the nation is established, then this could be done. A Washington is going to state, I should hope every post would be deemed honorable, which gave a man opportunity to service country. Honor in Washington's estimation is the ability is gained through service to the nation, above all. And we was going to see this in very early on, as early as 1775, with the term gentlemen soldiers. And to the modern year, this may not seem like anything. And nowadays, everyone's a gentleman by nature of being a man. But a gentleman was primarily meant something, of education, of status. Officers were gentlemen, soldiers were not. But as early as 1775, we have the term gentlemen soldiers being used to describe the average enlisted men. The idea was it was based on good conduct, noble character. So noble, almost the idea of playing on this birth concept. In the service of their country, every soldier was a gentleman. How did one become gain honor in this way? Merit. And the idea that it was for the militia, it was for the continental army. It wasn't, it was across society. And it even, we see officers discussing it, that honor was conferred on every soldier and officer. There was a sense that one's behavior reflected not just on themselves, but on their officers, on their units and on the nation as a whole. It also applied to African-American soldiers. So Washington's initially against using African-Americans, either free or enslaved, but he's gonna start to change. And there's lots of debate. Is this a pragmatic thing when the British offer freedom for African-American slaves to fight against their owners? Perhaps, but there's also another interpretation. When Washington takes command outside Boston, he starts to hear about the service of African-American troops. And it's coming from really prominent places that Salem poor, for instance, had character of so brave a man, he behaved like an, not just like an excellent soldier, but like an officer. General John Thomas says that African-American soldiers are equally serviceable with other men. It doesn't say black men, it says all men. And the idea that after the war, the idea that these individuals are due honor in service of the nation, just the same as any other soldiers. So we start to see this expanding definition. There are also flaws in this. One of the more famous ones, Benedict Arnold. Benedict Arnold is going to represent the older model of personal honor. He's going to be passed over for promotions by Congress. Despite the fact he's probably the best battlefield commander. Congress constantly overlooks him, they slight him. He takes it personally. He's ultimately going to betray the American cause. Yes, 20,000 pounds are involved. But his primary motivation is honor. He's even going to take a lower rank from Major General to Brigadier General to show it's not about rank, it's about honor. He feels that he has been slighted. He's forced to sign an oath of loyalty. And he thinks, look what I've given to you and this is how you're treating me. So going for personal honor over national honor. Washington in a great leadership move doesn't dwell on all the negatives here at a moment that could have potentially crippled the revolution. Washington instead focuses on the positive. When he says at the bottom, great honor is due to the army that this is the first instance of treason of this kind. How honorable are we that this hasn't happened? That the enemy must resort to this. And it sort of revitalizes the Continental Army during a period later in the war where there's lots of civil military tension where the civilians are blaming the military for not gaining victory and the military is blaming the civilians for not providing supplies or price gouging. But it's this shock of Arnold that revitalizes this early discussion of this honorable behavior of national honor over the individual. And within a year, the war is over, the surrender at Yorktown. But Washington has one last major battle and so with his own men. It's at Newburgh, New York. And this is 19th century depiction of his headquarters which was just outside New York where the British were still occupying the city. It's fairly close to West Point today. And the men, his officers are, sorry, are threatening to, it's open-ended what they're doing. They haven't been paid. They've been promised a half-pay pension for life. Congress has no money. There's rumors of a peace treaty coming. The officers are afraid that if peace comes, they will never be paid. So some theories exist that are they threatening to retreat behind the mountains and let the British march out and do what they will? Are they threatening a coup against Congress? Is it all just idle talk? A secret meeting is called. Washington in a move leadership cancels that meeting saying, you can't call a meeting only I can call a meeting and then calls his own meeting. Where he entreats the officers to do no such thing. And he uses the language of honor and let me conjure you in the name of our common country using this idea of national honor. As you value your own sacred honor, purposely linking back to the words used in the Declaration of Independence to express your utmost hard distation of the man who wishes under any specious pretenses to overturn the liberties of our country. He reminds them, think of what we've accomplished all we have done. Don't risk this for personal honor, for personal interests. And a combination of this and a combination of some showmanship putting on his glasses and showing what he's personally sacrificed for the cause. It amounts to nothing. And it's again, an early reaffirmation of civilian supremacy over the military. One that Washington constantly is going to do again and again. In 1783 in Annapolis at the state house, Washington is going to resign his commission. Back to Congress in an act that was unheard of since the classical era. The idea of a victorious military commander surrendering power was rare indeed. If you thought back to the English Civil War or Julius Caesar or even slightly after this Napoleon, Washington again showing in action, national honor was more important than personal. And the idea has become institutionalized in a lot of ways through colleges, through organizations, even in the concept of sort of the federal government of national honor taking precedence. But it also becomes politicized. And with the emergence of political parties this rhetoric is constantly used of the federalists have national honor. That's their true interest. While the Democratic Republicans do not, they're only concerned with personal honor and vice versa. And it's this political division, this partisanship that Washington warns against that is going to complicate this term. Going along with this, it's not just politicization but it's also a generational story. So when you start to have the next generations, the sons of the revolutionary generation and their grandsons coming to prominence, they don't necessarily have these great moments, this great war, this great opportunity to promote national honor, to advance themselves. So they start looking for other means and that's why you get the increase in the duel. Before 1800, there were about 70 duels in all of American history. After 1800 for about a century, there were about 800 known duels. It's illegal in many places, so there could be more. And it's a way for those to try to prove themselves to this personal manifestation. So we get to a really prominent incident, 1807. It's the Chesapeake Leopard Affair. And the USS Chesapeake is off the waters of Virginia and they've recently picked up some new sailors in port. They're out sailing and they're stopped by the HMS Leopard. And Chesapeake is under the command of a Commodore baron despite the fact that the ship's regular captain, Captain Gordon's on board. Baron by nature of the higher rank has the command. And he thinks it's just gonna be some sort of communication. The British captain informs him that they have taken four British subjects aboard. Baron denies it and refuses to return them to the British. The British then fire a warning shot followed by three full volleys of 26 cannon. The Chesapeake is caught unaware. Baron is screaming that he's gonna have to surrender but just fire one shot for the honor of the flag. And as the flag is going down, there's debate, is the flag down or is it still up with the shots fired? And throughout the nation, this is viewed as infringement on national honor, also personal honor in this idea of imprisonment. Only one of these men was actually a British subject. How did they know he was on board while he got drunk in port and was telling everyone he was skipping ship? But the idea was that this needed to be responded to. While many are very hesitant to go to war, the idea that America is not ready for a war against Britain so soon after the revolution. Many are pushing for this in more of the terms of personal honor, the language of a duel rather than the sort of ethical language that was being put forth in the revolution. And we see this depicted as Thomas Jefferson avoids war. His depiction in the popular press is one as being robbed by King George, literally bludgeoned while Napoleon picks his pocket, throwing his arms up in submission, being unable or unwilling to do anything. When James Madison, the next president, ultimately declares war and overimpressment of American sailors and harassment of shipping, among other things, it's going to be viewed as this sort of masculine martial response, a duel between nations. And you'll see that in the depictions where we now have James Madison punching the king in the nose, showing that America is not willing to stand by and not respond to the dishonor. So taking on this martial notion. So this is the sort of concept we see building up through the Civil War, popularized by individuals like Andrew Jackson, who focus on this personal, martial sense of honor rather than the older traditions of the ethical, proper conduct sense that Washington and others had been advancing. And it's why we see the War of 1812 celebrated as a triumph of America after burning of presidential mansion and really not a lot to show for this war. It's about new generations redefining what honor means and the path to it. And then when we get to the Civil War, it's about looking at different interpretations of what national honor means and does personal honor Trump national honor? And we see this at that moment, but I'm gonna stop for there and I'm happy to answer any and all questions or have an open discussion.