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    Yule Monsters and Good Saint Nick
    2020-12-16 (duration 55m)
    [transcript]
    06:35 joy
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    Learning assertiveness from Germans, and growing to love a city (Jenna from Canada)
    2020-12-14 (duration 41m)
    [transcript]
    39:10 the website is called joy algo.
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    United States: Graduating into a Pandemic
    2020-10-18 (duration 29m)
    [transcript]
    10:06 Like, one of my favorite memories is like a Taylor Swift song was playing, and they were like people on tables singing along.
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    Episode 5
    2020-10-11 (duration 33m)
    [transcript]
    00:56 joy
    07:11 joy
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    Leading Your Church Through a Leadership Transition
    2020-10-01 (duration 28m)
    [transcript]
    26:20 Well, thank you so much, Pastor brown for taking the time with me, it's been a real joy to have you on this podcast, I just want to thank you for your years of service to the church. It's
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    Learning To Program By Building Tiny Python Projects
    2020-07-28 (duration 54m)
    [transcript]
    53:04 No, it's enchanting. I wasn't prepared for this. But I also have kids. And you know, I don't know when people will be listening to this. But right now we're still in the midst of pandemic in Arizona, we're still very much, at least my family trying to stay very close to home. And so we're pretty bored sometimes with but you know, for some reason, we've gone back and started rewatching, Parks and Rec. And even though I think that the kids have seen the episodes two or three times, and this is the second time for me, there's something comforting in kind of knowing the next punch line, or rediscovering it. And so I don't know, maybe that makes me sound pretty boring to say that I just want to rewatch old television shows. But that's been something that's actually brought me a little bit of comfort and joy during these these pre trying times.
     
    Dependency Management Improvements In Pip's Resolver
    2020-05-26 (duration 1h16m)
    [transcript]
    05:10 I do. Yes. I think it was about six years ago. Back when I was in school, high school, my dad gave me a book called python programming by Wesley j chin. And I had too much free time as a kid. And he basically handed me the book said, Hey, instead of playing that game, make one now it's like, oh, okay, cool, picked it up, built a game or two. I was like, hey, this, this is fun. And then I started diving deeper into the language itself, sort of seeing see fighting exists and trying to understand what that means and failing at that, because I didn't know see by then, obviously, Python was my first language and that's the only thing I knew. Then I realized I was using this tool called Pep. And well, then I dove into that and stuff happened since then. And now it will mean Taylor.
     
    Managing Distributed Teams In The Age Of Remote Work
    2020-05-11 (duration 48m)
    [transcript]
    37:35 going to be at, there's some other things around, you know, helping your family understand what it means to work from home, working from home is not hanging out at home. So being clear and communicating with your partners with, you know, your kids and so on. I have an 11 month old daughter so I'm not yet feeling the thing where you know she wants to come and knock on the door and hang out with me. If she does that right now, it seems amazing. And it seems like a ton of fun. But I know that it'll get in the way. And I don't know what to do with that. As with most things in parenting, I think I any plans that I have about how to deal with that now, I would have to throw out immediately. So I would defer to other people who have experienced that for how to deal with that kind of dynamic. I will say, though, that your team, they're all people. And if you have, you know, your kids in the room during a meeting, they're going to love that they're going to smile, and don't try to hide that from your team. They take joy and getting to work with other great people and your family is a part of that. So don't try to hide that.
     
    Illustrating The Landscape And Applications Of Deep Learning
    2019-10-22 (duration 56m)
    [transcript]
    14:13 Excellent question. So by running the deep learning study group that I run, and by teaching, say, at the New York City Data Science Academy, I developed a pretty good understanding of what topics needed to be covered in order to give somebody a wide ranging education and deep learning. So this is, you know, covering the fundamentals of how deep learning works, as well as the applications that people are most interested in, which are machine vision, natural language processing, these these technical generative adversarial networks that can create what appears to be artwork, and then as well as these game playing algorithms, deep reinforcement learning algorithms, so I yes So kind of I gradually became more and more familiar with his body of knowledge. And by teaching it to students, I started to understand where they were most easily able to understand the content and where things were tricky. And what I found was by using a whiteboard, and this was actually something something that I've always been doing is I love teaching on whiteboards. And so drawing figures that represent concepts. So So instead of trying to it for a lot of people, and equation can be a lot easier to understand if I can draw it kind of visually in terms of, you know, how the, the matrices of data are being used and transformed what how these operations are happening and kind of a visual way. So that's always been kind of a natural thing to me. And that and it became clear to me through teaching that this is something that works for a large number of students. It's a way that they really take to learning this relatively complex content. So At brunch one day, on a Sunday in New York, I was out with one of my best friends who has been at at alphabet at working at Google or YouTube for about 12 years. And at the time, his girlfriend now his wife, ugly Baskins. She is a professional artist. And I pitched her this idea over brunch of, you know, I think if we made this as, as a book, I think if we had an illustrated approach to learning about deep learning, this is something that a lot of people would really benefit from. What do you think about that? And perhaps because through her now husband being exposed so much to machine learning techniques at alphabet, she was immediately very interested and she was an absolute joy to work with over the entire process. So yeah, that's how it all came about.
     
    Exploratory Data Analysis Made Easy At The Command Line
    2019-09-23 (duration 52m)
    [transcript]
    18:49 it's now just a bigger open source project. It's got a whole packaging release cycle. And I'm working with Anya, who has been very instrumental in some of the packaging and tech and documentation, stuff that we've been doing. And it's just kind of taken off and behind and gain more traction in that sense. And you asked about the libraries that I liked, and stuff, I'm actually one of the things I want to doing also to keep performance good is I think very few dependencies, I feel like layers is how things get messy. And so the fewer layers that you have, the better off, it'll be if you can wind up coating everything in between there. So the libraries that I use, obviously, curses is essential. But that's built into the Python standard library. Now Python standard library is really fantastic. And, and everything's included, which is super, super bonus. But then also the Pi Pi ecosystem in general is so broad that any format that I come across html5 or Excel or whatever, they have a library already for it. And it's a library, you can just use in Python and like you read a page of code and you've got the stuff in there. And then all the loaders really are just importing those libraries, and then condom and putting the rows of the return in there and having some columns around nice, pretty simple concept. One thing you mentioned. Other, you want to know other ways that keep this in a fast, I've been very focused on making sure that starts up very quickly. Like I think I feel like if it gets to be a half second of startup time, it just gets in the way it feels like a certain kind of friction. And so one thing that I do a lot of is lazy importing. So all these libraries, I have no idea how long they're going to take to load or sharp themselves. And I know that there are some pretty heavy ones, even in visited the physical use sometimes, but I don't use those unless I need to. And so when you open up an Excel Excel file, for instance, that's where it's an import the XLS library. And if you don't ever load an Excel file, didn't have to and have to spend the time doing that. So that's a other one of those tricks. And before we move on, I wanted to mention the Python date. util library is one of those, like, I don't take many dependencies, but that's one that I've been very happy to take. Because it parses any gate format that you can throw at it like if you can, if it can be parsed, I feel like it will parse it. And so it is it's amazing. It's the best in class detection and parsing parsing tool. And also, other feature that I have used a lot is Python decorators. I'm not sure. I mean, I think that's pretty standard thing. But I use them as just a way of tagging functions. For instance, I mentioned to a single thread decorator taking a pretty advanced concept sometimes and just making it just the essence of it so that I don't have to think or work hard to have those concepts work for me.
    40:02 Yeah. Well, you know, as as you're saying, I'm a solo developer, I've got a little bit of help. Now like I said, Anya has been instrumental in making me not being so alone with some of the decisions and discussions and stuff like that. There's also a pound visit data channel on fri know that several of us are hanging out. And there's people talking about things, people ask questions, and is it possible to do this, etc, maybe you could add this kind of feature. That's, I would prefer personally, chat system like that. Because I find myself doing a lot better with chat. I mean, I've been on chat for over over 20 years now than I do with email and emails, a lot heavier requires more intention and attention and chat, I can just kind of like toss off an answer. It's just done. So I'm, of course, the decider on those things. But I have to be honest, it kind of feels like I'm discovering visited a more than creating it at this point. Like, it's like a chunk of marble to a sculptor, it kind of tells me what it wants to become. And some things I didn't even consider. And then I look at it like, oh, why didn't I think of that already, you know, like the the road type down in the lower left corner where it shows you, you know, whatever, lines or columns, or whatever the current data type is, for the longest time, almost 1.0, that just said, Rose. And I didn't know why I even put the text there. If I was going to say the same thing every time. And yet I felt strongly that it should be there. And then once I realized that, that should just be the life, I was like, oh, like, I don't feel like that was my creation. That's that is just how it has to be. That makes sense. And so, so that, and then you mentioned about project sustainability. And the thing is, is that my energy is my most precious resource, my energy Blue Coat, I have a day job. And so I come home at night, and it's madness want to screw around the data. And there's, it's really hard to like some of the energy when I don't have like a very concrete use case for something that cares about something. And so I have the most energy when somebody is around, it is enthusiastic, and they have like a sample data set. And they're like, I just want to do this thing to it. It's like, Oh, right. And how can we do that? Is there like a, it's a kind of a little puzzle, you know, like, you kind of put together to kind of use existing commands to do this, you have to like a one liner that they put in their visited RC, or does this require like a different core piece of functionality to that now, not just that case, but 10 other cases can be solved too. And those are the things I enjoy the most, and I can, I actually do really enjoy solving those puzzles. But then sometimes we'll have people who asked for a generic feature. And like, it doesn't feel like it's it's not very immediate, it's more abstract, or I have a concept for something that I've been wanting for a while, and because nobody actually really, really wants it, I'm less motivated, I just kind of decide to do something else, you know.
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    Uniform Cycle Recap + What File Format Should I Upload To Buzzsprout?
    2019-10-25 (duration 39m)
    [transcript]
    03:11 joy.
    03:13 joy.
     
    The Best Podcast Microphones + Where Are My Spotify Stats?!?
    2019-09-13 (duration 40m)
    [transcript]
    32:09 joy
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    Open Source Object Storage For All Of Your Data
    2019-09-23 (duration 1h8m)
    [transcript]
    04:02 this time. While I mean, I always an object storage, most people think that I am doing this because I became a storage guy. And because of my past experience with the file system, that's actually not the real story. I was at Red Hat for a while after the acquisition to make your the transition went smooth, and they are able to take take care without me. But what actually happened was, I was thinking about doing something more fun. We were working on me and a small team, we were working on bionics like ability to see through skin, you can close your eyes and see things like I wanted to do something more fun. But then when it came to actually doing a startup moment, you have VCs involved, and you want to do something that makes an impact the next six months, next 12 months, you want to show progress, right? And I went back to a asked you a very simple question laid in and in the object storage was an accident of that. The real question I asked was that 10 years from now, what problem if you pick today will still stay relevant, not only stay relevant, it has to compound and grow. And don't pick something that is trendy and short term a where every where I looked, the direction was simply the world will produce more and more data. And it was never about storage, right? Gloucester Fs was about building a storage system. This time around what I saw, the problem was it's about data. And data will be the heart of every modern enterprise, and how you build a powerful brand of trust and low. And then I saw that everyone was traveling with just managing vast amount of data, the closest thing they saw was HDFS and some distributed file systems like Lester Fs, and in 2008, it became quite clear even while I was doing the after that Amazon will convince the rest of the world that if you are willing to let go all the legacy interfaces like file and block, you can build a significantly better data storage system. And I knew that Amazon will convince the rest of the world. So I saw that building an object storage was a good starting point, my simple thesis was that if the data sits on a technology that we built, we can do many powerful things on top. And, and a good starting point would be to build an object storage. Everyone else thought object storage is a hard problem to go attack. And I thought that object storage is simply a distributed set of web servers, right. And we started out with object storage. And the idea being if you are inside AWS, you should use Amazon s3. But if you are outside AWS, what joy is you got? And that's the part that mean, I will should address in a my, my calculation is and it's also a bet right is the world will produce so much data, what percentage of that world's data will be sitting on Amazon s3, compared to the rest, I thought that bulk of the world's data will be outside of Amazon s3. And I wanted to go get the rest of the world and a powerful open source better alternative to Amazon s3. And it turned out to be great in the last four years, it really picked up widely.
     
    Building A Reliable And Performant Router For Observability Data
    2019-09-10 (duration 55m)
    [transcript]
    42:55 Yeah. So in terms of like a one point release, where we would recommend it to for like, very stringent production use cases. I think what Luke just talked about internal metrics, I think it's really important that we improve vectors own internal observer ability, and provide operators the tools necessary to monitor performance, set up alarms and make sure that they have confidence in factor internally, the stress testing is also something that would raise our confidence, and that we have a lot of interesting stress testing use cases that we want to run vector through. And I think that'll expose some problems. But I think getting that done would definitely raise our confidence. And then I think there's just some like, General house cleanup that I think would be helpful for one point or release. Like, you know, the initial stages of this project have been inherently a little more messy, because we are building out the foundation and moving pretty quickly with our integrations. I would like to see that settle down more when we get to 1.0. So that we have smaller increment releases, and we take breaking changes incredibly seriously factors reliability, and sort of least surprise, philosophy definitely plays into like how we're releasing the software and making sure that we aren't releasing a minor update that actually has breaking changes in it, for example. So I would say those are the main things missing. Before we can officially call it one point O outside of that, the one other thing that we want to do is provide more education on some high level use cases around vector. I think right now, it's like the documentation is is very good. And that it, like dives deep into all the different components like sources, sinks and transforms and all the options available. But I think we're lacking in more guidance around like how you deploy vector and an AWS environment or a GCC environment. And that's, that's certainly not needed for 1.0. But I think it is one of the big missing pieces that will make Dr. More of a joy to us
     
    Digging Into Data Replication At Fivetran
    2019-08-12 (duration 44m)
    [transcript]
    02:50 Well, I'll start with the story of how it got started. So in late 2012, when we started the company, Taylor and I, and then Mel, who's now our VP of engineering, who joined early in 2013, five turn was originally a vertically integrated data analysis tool. So it had user interface that was sort of a super powered spreadsheets slash BI tool, it had a data warehouse on the inside, and it had a data pipeline that was feeding the data warehouse. And through many iterations of that idea, we discovered that the really valuable thing we had invented was actually the data pipeline that was part of that. And so we threw everything else away, and the data pipeline became the product. And the problem that five trans solves, is the problem of getting all your company's data in one place. So companies today use all kinds of tools to manage their business. You use CRM systems, like Salesforce, you use payment systems, like stripe support systems like Zendesk finance systems like QuickBooks, or Zora, you have a production database somewhere, maybe you have 20 production databases. And if you want to know what is happening in your business, the first step is usually to synchronize all of this data into a single database, where an analyst can query it, and where you can build dashboards and BI tools on top of it. So that's the primary problem that five trend solves people use by trying to do other things. Sometimes they use the data warehouse that We're sinking to as a production system. But the most common use case is they're just trying to understand what's going on in their business. And the first step in that is to sync all of that data into a single database.
     
    Apache Zookeeper As A Building Block For Distributed Systems with Patrick Hunt
    2018-12-03 (duration 54m)
    [transcript]
    07:30 like Bill, Joy Deutsch, Peter Deutsch, and those guys, I think came up with the initial three or four. It was added to you by Gosling and a few other folks, but you know, things like, you know, people assume that network latency is 00. They assume that bandwidth is infinite, they assume that the network is reliable and secure. Those are some of the main fallacies of distributed computing. And zookeeper puts that right in your face, it requires you to consider those issues. One thing I also usually have to mention to people is that zookeeper doesn't really solve all these problems for you, right? It provides you a framework to address them, but it's not like, you know, magic pixie dust that we sprinkle on your system and everything is addressed. You still have to worry about these all these issues. But zookeeper provides a framework for you to do so.
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    Urlaub
    2021-03-30 (duration 1h51m)
    [transcript]
    21:34 so einer Partnerstadt in Frankreich, also auch wieder über die Schule äh Joy Nee hieß die.
     
    Craft Comedy Bremen
    2020-10-27 (duration 1h6m)
    [transcript]
    24:35 irgendwie, ich weiß nicht, ob ihr Taylor, Tom Linsen kennt, von Netflix hat ein ziemlich gutes Special rausgebracht, die irgendwie auch Videos hat von sechs Jahren, vor vier Jahren, vor zwei Jahren, wo man sieht,
     
    Wie Lush nur mit Käse
    2019-06-25 (duration 1h53m)
    [transcript]
    1:37:44 also ist wirklich wie reingegangen weil das kann man dann da sehen wenn der sogar dann auf facebook landet weil irgendein radio joy ja radio enjoy hat mein gepostet,
     
    Kevin allein in der Dusche
    2019-04-30 (duration 1h51m)
    [transcript]
    50:14 Der arbeitet also da der Liebe diesen Dingen ist es auch speziell nur da das gibt's nur da dass es wirklich so groß ist aber so keine Ahnung in den Alpen hast du halt immer irgendwo bisschen Schieflage und es gibt halt manchmal Taylor Taylor verstehe ich ringsrum Berge und ein Tal Menschen siedeln sich an,
     
    Zwischen Bremen und München
    2019-04-16 (duration 1h37m)
    [transcript]
    1:17:15 weil du mit diesen mit diesen joy-con also mit diesem Griff den du dann von der Nintendo hast die hat ja zwei Kilos abnehmen kannst und jeder Griff ist ein Spieler und die hat auch so ein Bewegungssensor,
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