WEBVTT

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Did you make this year's PyCon event in the U.S.?

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There was a lot of excitement this time around in Salt Lake City.

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In this episode, I'll bring you a bunch of experiences we had this year.

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It starts where a frequent guest, Jay Miller, turns the tables and interviews me at the

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Microsoft booth on the Expo Hall floor in front of a live audience.

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And then you'll hear from Mario Munoz, Nick Moua, Chris Williams, Ray McClendon, and Sean

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Tibor about their time at the conference.

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This is Talk Python To Me, episode 413, recorded April 21st, 2023.

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Welcome to Talk Python To Me, a weekly podcast on Python.

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This is your host, Michael Kennedy.

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Follow me on Mastodon, where I'm @mkennedy and follow the podcast using @talkpython.

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Both on fosstodon.org.

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Be careful with impersonating accounts on other instances.

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There are many.

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Keep up with the show and listen to over seven years of past episodes at talkpython.fm.

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We've started streaming most of our episodes live on YouTube.

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Subscribe to our YouTube channel over at talkpython.fm/youtube to get notified about upcoming

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shows and be part of that episode.

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You can transform scripts, APIs, SQL queries, and more into internal UIs and frameworks in

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I want to welcome everybody to the Something Something 100th episode of Talk Python To Me.

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I am your host, Jay Miller.

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Our normal host, Michael Kennedy, apparently had some flight issues.

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Oh, no, he's here.

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I'm here.

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I'm here.

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Hello, everyone.

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We kind of talked about this.

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And I said, I have an idea.

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Trust me.

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And you said, okay.

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I trust you, Jay.

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This is going to be fun.

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I mean, I think a lot of people have made that mistake in the past.

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But I'm going to be interviewing you.

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And for those that don't know, I'm Jay Miller.

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I am a now six-time guest on the show.

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I think you get a jacket for that.

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You're in the 1%.

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You're a 1%.

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I am in the 1%.

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The top 1% of guests.

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The only person who's been on the show more times than me is my boss, which is annoying.

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Because he will rub it in after he hears this.

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But, yeah, Mike, we've been kind of working together for, what, four years now?

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Four or five years.

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Four or five years?

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For those that don't know, I do a little bit of marketing behind the scenes.

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So if you get that newsletter, if you're not subscribed to the Talk Python newsletter, you need to be.

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I work really hard on that.

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By the way, it may not come out this weekend because I'm here.

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Just so you know.

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But, yeah, so we've known each other for four or five years.

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And I think I was on, like, episode, like, 15 or something like that.

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Yeah, quite early.

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About developer productivity.

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Yeah.

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It was wonderful.

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So I wanted to take this time to kind of ask you questions similar to what you would do.

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And let's start with one of the easiest ones of why a podcast?

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Why a podcast?

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Well, I had done a lot of different things trying to teach people coding and evangelize coding.

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And that involved things like going to user group talks or doing trainings.

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And all these were like, hey, it's awesome.

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20 people showed up and are really engaged.

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But what if you leverage the Internet to reach more people, you know?

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Yeah.

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That was really one of the motivations is just how can you have a bigger impact?

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And when I got started with Talk Python, there were zero Python podcasts.

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I'm like, why are there zero Python podcasts?

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There have been some before, but they'd all shut down.

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And I'm like, that doesn't make any sense.

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Such a vibrant community and no one to interview and share the stories of it.

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So here we are, seven, eight years, eight years later.

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Yeah.

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And I mean, you've really trailblazed that industry.

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I think since your show, we've had Tobias started podcasting it.

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Dan has a real Python podcast.

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I think Chris is running.

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Hey, is that Chris right there?

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Yeah, that is Chris.

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He's getting a shout out right here.

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Speaking of the real Python podcast right there.

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I think Sean's here from Teaching Python.

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Sean and T-Borris here.

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And we've even seen it expand into kind of smaller niches like Django.

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And we have the Django Chats.

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Yeah, Django Chats.

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And some of those shows.

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And I mean, a little show, Python Community News on YouTube.

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Go check that out.

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But it's great that you started this thing because there wasn't a thing there.

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And then afterwards, a ton of shows showed up.

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And I see some other podcasters in the audience.

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I think I see Python Bytes and Tests and Code, Brian Okken here as well.

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How does it feel to see that, you know, now that you kind of kick-started things, the ecosystem is thriving?

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I think it's fantastic.

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Like I said, the goal was to share the stories of this community that weren't being told.

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And now I think so many people have taken up that torch.

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It's great.

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And I think there's room for all of us.

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We all have kind of our own special flavor.

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And people can gravitate to what they like.

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Yeah.

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Yeah.

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And you've interviewed a few hundred people.

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I think we're over 450 different guests so far on the show.

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Did you think there was that much to talk about in the Python space?

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I had a plan, Jay.

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I had a plan.

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And it involved five episodes.

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Okay.

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I'm like, okay, the first five.

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The first one was me announcing the show.

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So four.

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I'm like, okay, I know four people who I can interview about this.

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I talked about SeekWalkyMe.

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I talked about Pyramid, the web framework, and a couple of other things.

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And I'm like, all right, now what?

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But thankfully, so many people were really excited that, hey, there finally is a Python podcast.

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Like, that was a great show.

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You should talk to so-and-so.

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And this, have you considered this?

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And now it's just, you know, a snowball going downhill.

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It's great.

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But I had no idea I would make it this far, no.

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That's awesome.

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Yeah.

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So I know that just between, you know, you and I working together, we have developed things

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for the show to make the show easier to manage and maintain.

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Has there been any projects that you've developed that have kind of come out of inspiration from

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the show?

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Oh, yeah.

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There's tons of software behind the scenes that are all about automation and different kinds

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of things, both for the podcast itself and the courses.

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You know, it's amazing just how much these little tiny scripts or little things you can

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write in an afternoon that will just completely change your workday.

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You're like, you know what, this used to be such a pain and now it's completely automatic

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or it's almost automatic.

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You know, really great transcripts of some of the new AI stuff.

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Used to ship the files all over to different servers.

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Now I've got it set up differently.

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But, you know, just a ton of software that's constantly written.

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It's never ending fun.

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And it's also a really cool playground.

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Yeah.

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Like, I really want to learn FastAPI or I want to learn this thing.

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Let me just use that for this little small project I got.

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And now I have some experience with it.

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It's great.

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I have definitely gotten to witness like, oh, hey, just add this thing.

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And now it'll run and do all this stuff.

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And then usually I come in and I go, hey, I built something too.

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And you're like, I can't get it to work.

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And I go, oh, yeah, I broke it.

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I'm sorry.

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Your entire show is down.

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I'm kidding.

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I think I've done that yet.

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I haven't.

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I haven't.

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I've brought an entire networks down.

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I don't think I've brought in the podcast down yet.

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I think the thing that took the site down for the longest was the walrus operator.

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The walrus operator.

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The walrus operator.

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Shout out to the walrus operator.

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That's my favorite part of Python.

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Thank you, Emily.

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No, the walrus operator is awesome.

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But when the servers were running 3.7 and I was running 3.8 on my dev machine, I have these

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little management scripts for all this kind of stuff we're talking about, right?

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Yeah.

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And I'm like, well, that part's not part of the website.

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I'll do that.

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I'll write walrus operator code and all sorts of stuff.

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When I shipped it, the framework tried to scan to see if there was any routes in there and

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it couldn't parse it and it just couldn't start.

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I'm like, why won't there?

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I haven't even touched it.

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What's going on?

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Oh, the walrus operator took it down.

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That's funny.

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So you've interviewed a ton of people and I'm not going to ask you to say who's your favorite

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person to interview because we know the answer is me.

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Yes.

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But what were some of the most surprising interviews that you had?

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There's a whole set of categories of surprising, right?

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And your shows were very interesting and I really enjoyed talking to you about them.

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They're really inspiring because they're not just here's this API, but they were higher

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level, right?

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Like developer productivity and stuff.

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However, I would say the stuff that surprises me the most is where people are doing things

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you wouldn't have expected with Python.

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like, oh, hey, we're actually using machine learning in Python to find exoplanets in old kind of stale

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Kepler data.

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Yeah.

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And so there's this group in Oxford who found 50 exoplanets running machine learning across data they thought was already analyzed and done.

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And you would learn weird things like they said, we used to have grad students do it and that was okay, but it was really variable.

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Like the mood of the grad student matter.

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For example, at Oxford, they always had cookies and coffee at three.

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So more exoplanets were found after three than before three.

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There's no difference in the data.

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But, you know, if we could bring some automation, that might make science a little more scientific.

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Developer productivity tip, add cookies and coffee to your daily routine, right?

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Yeah, for sure.

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For sure.

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So I'm thinking about a particular episode that I was on where you had Rivers Cuomo from Weezer.

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That was one of the more notable ones, yes.

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That was, I just, I remember getting the message from you of like, hey, you're going to be on the show this week.

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And I was like, I can't, I've got it.

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He's like, no, no, no, no, no, no.

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You're, you are going to be on the show this week.

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You'll want to be here.

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Trust me.

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Yes.

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And then just being like, having to pick my jaw off the floor because like, you know, you had a rock star on the show.

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And I think that that, that is one of the beauties of podcasting is that just like Python is kind of stretched outside of,

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of, you know, developer community and is kind of branched into data science and branched into automation.

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And, you know, hopefully we'll see Python in more and more spaces.

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Like we're seeing it in places that no one would expect, like on stage, like with Rivers Cuomo.

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Like, what was that like?

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How did, how did that happen?

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So Rivers has an assistant who coordinates a bunch of stuff and sent me a message and said, the assistant sent me a message.

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Rivers would like to be on your show.

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I'm like, that is amazing.

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But you do understand it's a Python show.

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And I hadn't realized how much coding he had done.

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So I actually got to go out and spend some time with him when he was in Portland at a concert.

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Rub it in.

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Rub it in.

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Yeah.

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I like it.

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We hung out a little bit.

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He's like, let me show all the code I'm writing.

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And we just had a great time geeking out before the show.

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And after I saw him, I'm like, you have to be on the show.

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What you were doing is so awesome.

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So, yeah, he's doing legitimately cool stuff.

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I think now he's actually contributing to open source and Python as well.

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Yeah, I saw him and Brett Cannon going back forth on some work.

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Let's not talk about Brett Cannon.

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He's not here right now.

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He'll be back tomorrow.

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You can ask him questions about that at the Ask Me Anything.

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Anyway, it was really awesome to have him on the show.

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It was cool to have you there as well.

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That was a real popular one.

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That was in the vein of kind of what you opened this conversation with.

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It was a bunch of little automation tools that don't count as like, hey, I built Instagram.

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But they're like, this is a really amazing thing I built.

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Even if it only took a day, it was super powerful, right?

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Yeah.

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All right.

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So, we're about halfway through the interview.

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We understand that people want to get to talks.

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So, what we're going to do is we're going to go ahead and raffle off a pair of Surface earbuds.

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Also, if you're wanting to catch the talks, feel free to go do that.

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This will be on the podcast.

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Where can people find the podcast while you're looking for a number here?

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I don't want to be biased.

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You want to influence me?

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I'm not even looking.

00:12:40.620 --> 00:12:40.800
Yeah.

00:12:40.800 --> 00:12:42.240
Talkpython.fm.

00:12:42.240 --> 00:12:45.880
Or if you go to your any podcast player and just search for Talkpython.

00:12:45.880 --> 00:12:46.420
Okay.

00:12:46.420 --> 00:12:46.720
Okay.

00:12:46.720 --> 00:12:47.940
How do I read the number?

00:12:47.940 --> 00:12:48.280
Yeah.

00:12:48.280 --> 00:12:49.020
Just read the number.

00:12:49.020 --> 00:12:49.560
Read the number.

00:12:49.560 --> 00:12:49.960
All right.

00:12:49.960 --> 00:12:51.300
I wasn't paid that much for this.

00:12:51.300 --> 00:12:54.040
So, the last numbers are 548.

00:12:54.040 --> 00:12:55.120
Oh, wait.

00:12:55.120 --> 00:12:56.940
548.

00:12:57.660 --> 00:12:58.000
Congratulations.

00:12:58.000 --> 00:12:59.740
Thank you.

00:12:59.740 --> 00:13:00.080
Love it.

00:13:00.080 --> 00:13:00.620
Congratulations.

00:13:03.180 --> 00:13:03.800
This portion of Talkpython.fm.

00:13:03.800 --> 00:13:05.100
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00:13:05.100 --> 00:13:06.480
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00:14:17.040 --> 00:14:19.100
That link is in your podcast player show notes.

00:14:19.100 --> 00:14:22.500
Thank you to Airplane for keeping Talk Python flying high.

00:14:22.500 --> 00:14:36.780
Going back to that kind of that idea of like, hey, these are little tools, and now they're being used with like super amazing people in the Python space.

00:14:36.780 --> 00:14:41.280
Have you heard of anybody getting into Python because of your show?

00:14:41.960 --> 00:14:43.600
I've heard of a lot of people getting into there.

00:14:43.600 --> 00:14:55.000
You know, when I started the show, going back to the beginning a little bit, when I started the show, I expected, well, I tried to think, well, who will listen to a show about the people making these frameworks in these libraries?

00:14:55.200 --> 00:15:02.660
It's got to be the most hardcore developers, the people who maybe wrote that library or are really, really into it, right?

00:15:02.660 --> 00:15:03.060
Yeah.

00:15:03.840 --> 00:15:06.040
And sure, people like that listening.

00:15:06.040 --> 00:15:06.540
And it's great.

00:15:06.540 --> 00:15:15.360
But there's a bunch of people who listen and will say things like, I'm starting to understand what you all are talking about after six weeks.

00:15:15.360 --> 00:15:18.440
I'm like, why have you listened to six weeks and not known what I'm talking about?

00:15:19.000 --> 00:15:21.700
It's really kind of an honor, but like, why would you do that?

00:15:21.700 --> 00:15:26.040
That just, and what they do is they're using it as like language immersion.

00:15:26.040 --> 00:15:31.740
Like, if I just immerse myself in this community, soon enough, I will be a Python person.

00:15:31.740 --> 00:15:36.120
Like, if I move to Brazil, maybe I could learn Portuguese if I just force myself to it.

00:15:36.640 --> 00:15:39.180
And there's a lot of people like that.

00:15:39.180 --> 00:15:41.660
So there are a lot of people kind of on that journey, yeah.

00:15:41.660 --> 00:15:50.280
And then I guess in the same vein, has any of the feedback from the show that you've done kind of gone into some of the other things that you do, like Talk Python Training?

00:15:50.280 --> 00:15:51.940
Constantly.

00:15:51.940 --> 00:15:52.780
Constantly.

00:15:52.780 --> 00:15:55.340
I'll talk about something like, this might be interesting.

00:15:55.340 --> 00:15:58.560
And everybody's, this is so amazing, so interesting.

00:15:58.560 --> 00:15:59.660
I want to learn more.

00:15:59.660 --> 00:16:03.300
I'm like, okay, well, maybe I should put some more effort into it.

00:16:03.300 --> 00:16:06.560
Either have more shows or do a course or something like that.

00:16:06.620 --> 00:16:07.180
Yeah, absolutely.

00:16:07.180 --> 00:16:08.080
Very cool.

00:16:08.080 --> 00:16:13.420
So I guess I got one more question and then I'm going to go, I'm going to do the thing that you do at the end.

00:16:13.420 --> 00:16:13.920
All right.

00:16:13.920 --> 00:16:19.200
So you have, the show itself has kind of migrated.

00:16:19.200 --> 00:16:21.340
It started as a podcast only.

00:16:21.340 --> 00:16:23.740
And then I saw you start doing some videos.

00:16:23.740 --> 00:16:26.800
And then, of course, the courses were always kind of a big part of this.

00:16:26.800 --> 00:16:31.720
And now you've kind of integrated that live stream component to it as well.

00:16:32.180 --> 00:16:45.680
How was making that change from it being a, you know, pre-recorded, pre-talk, just you and the person you're interviewing, to now you have all of those things, but also a live audience listening over the internet?

00:16:45.680 --> 00:16:46.080
Yeah.

00:16:46.080 --> 00:16:47.660
So smash the bell on YouTube, right?

00:16:47.660 --> 00:16:48.020
Yeah.

00:16:48.020 --> 00:16:49.500
Like and subscribe.

00:16:49.500 --> 00:16:50.100
Ring the bell.

00:16:50.100 --> 00:16:50.600
Exactly.

00:16:50.600 --> 00:16:51.120
All that stuff.

00:16:51.120 --> 00:16:51.480
Yeah.

00:16:51.480 --> 00:16:56.620
So seriously, though, it was a big decision to make it a live show.

00:16:56.620 --> 00:16:59.880
And there were two things I was worried about.

00:16:59.880 --> 00:17:07.580
One is, will the guests who used to just sort of call up one-on-one and say, let's have a conversation and then you'll edit it right?

00:17:07.860 --> 00:17:14.120
Because if I say something, I'm really new to this and if you edit it, I think I can build up the confidence to be on there.

00:17:14.120 --> 00:17:14.820
Like, oh, guess what?

00:17:14.820 --> 00:17:18.180
We're live streaming it to the world and it'll be written in ink on YouTube.

00:17:18.180 --> 00:17:20.520
You know, like that's a different sort of deal.

00:17:20.520 --> 00:17:22.740
And for the most part, people haven't minded.

00:17:22.740 --> 00:17:23.660
Okay.

00:17:23.660 --> 00:17:24.900
At first, they're like, I'm a little nervous.

00:17:24.900 --> 00:17:27.700
I'm like, you know, it's fine, really.

00:17:27.700 --> 00:17:28.280
You'll be fine.

00:17:28.280 --> 00:17:30.420
It's all, it has been fine every time.

00:17:30.420 --> 00:17:33.740
It's always like the first time you go on a live stream, you're like, I don't, I don't know what to do.

00:17:33.740 --> 00:17:34.760
Do I stare at the camera?

00:17:34.880 --> 00:17:35.620
Do I look at the screen?

00:17:35.620 --> 00:17:41.200
Like, but then after that, they're like, oh, that was so fun engaging with the audience live and seeing the comments and doing all that stuff.

00:17:41.200 --> 00:17:42.240
Yeah, absolutely.

00:17:42.240 --> 00:17:47.400
And from a logistics perspective, it's taken the effort down a little bit.

00:17:47.400 --> 00:17:47.860
Okay.

00:17:47.860 --> 00:17:51.500
Ironically, like doing more, you'd think the live stream would add something.

00:17:51.500 --> 00:17:57.120
But we have people join the live stream and ask questions so we can kind of make the audience part of the show.

00:17:57.120 --> 00:17:58.540
I'm like, oh, I should have asked that question.

00:17:58.540 --> 00:18:01.660
But, you know, so-and-so in the live chat did.

00:18:01.660 --> 00:18:02.900
That helps.

00:18:03.320 --> 00:18:09.460
And then also, if it's already live, you don't have to edit it as much because it's kind of, you're a little more on focus.

00:18:09.460 --> 00:18:09.760
Yeah.

00:18:09.760 --> 00:18:13.380
Because you're like, instead of like, hey, can we do that again or can we talk or can we pause it?

00:18:13.380 --> 00:18:14.380
Like, you know, we're live stream.

00:18:14.380 --> 00:18:15.100
We're just going to go.

00:18:15.100 --> 00:18:15.380
Yeah.

00:18:15.380 --> 00:18:16.240
And it works out.

00:18:16.400 --> 00:18:19.980
But it kind of takes away some of the going back and fixing it up.

00:18:19.980 --> 00:18:20.780
Yeah.

00:18:20.780 --> 00:18:22.020
But it's been really cool.

00:18:22.020 --> 00:18:23.040
I got into it.

00:18:23.040 --> 00:18:27.580
I think the real motivation to get into it was through a common friend of ours, Cecil Phillip.

00:18:27.580 --> 00:18:28.220
Okay.

00:18:28.220 --> 00:18:28.800
Yeah.

00:18:29.460 --> 00:18:36.600
And I interviewed him and Brian Clark about their live streaming, their developer stuff.

00:18:36.600 --> 00:18:37.000
Okay.

00:18:37.140 --> 00:18:39.000
And I was like, that's pretty cool what they're doing.

00:18:39.000 --> 00:18:39.980
How are you doing it?

00:18:39.980 --> 00:18:41.780
The stuff over at Stripe that they're doing?

00:18:41.780 --> 00:18:42.340
No, no.

00:18:42.340 --> 00:18:43.980
When he was at Microsoft.

00:18:43.980 --> 00:18:44.900
Oh, okay.

00:18:44.900 --> 00:18:45.380
Yeah.

00:18:45.380 --> 00:18:47.120
Some of the like Ask the Expert stuff that we do.

00:18:47.120 --> 00:18:47.480
Yeah.

00:18:47.480 --> 00:18:47.900
That kind of stuff.

00:18:47.900 --> 00:18:49.900
Well, now we're doing it on the Microsoft YouTube channel.

00:18:49.900 --> 00:18:53.120
I was like, so YouTube at Microsoft developer.

00:18:53.120 --> 00:18:53.880
Right on.

00:18:53.880 --> 00:18:54.660
Cool.

00:18:54.660 --> 00:18:58.940
So anyway, he got me inspired watching what they were doing and got me using things like

00:18:58.940 --> 00:18:59.520
StreamYard.

00:18:59.520 --> 00:19:00.420
And yeah, it's real good.

00:19:00.420 --> 00:19:01.560
Very awesome.

00:19:01.560 --> 00:19:01.940
I love it.

00:19:01.940 --> 00:19:02.200
All right.

00:19:02.200 --> 00:19:05.260
So normally you have some rapid fire questions at the end.

00:19:05.260 --> 00:19:07.060
So I have some rapid fire questions for you.

00:19:07.060 --> 00:19:08.960
We're at PyCon 2023.

00:19:08.960 --> 00:19:10.920
What was your first PyCon US?

00:19:10.920 --> 00:19:16.400
My first PyCon US, I think, was in Portland, my hometown.

00:19:16.400 --> 00:19:17.060
Okay.

00:19:17.060 --> 00:19:17.980
In 2015.

00:19:17.980 --> 00:19:18.900
In 2015.

00:19:18.900 --> 00:19:20.880
2015, 2016.

00:19:20.880 --> 00:19:24.140
The irony was for that one year I was living in Germany.

00:19:24.140 --> 00:19:30.240
So I had to fly back, rent a hotel, stay a mile from my house, who someone else lived in

00:19:30.240 --> 00:19:31.480
it at the time because I was renting it.

00:19:31.480 --> 00:19:31.860
Oh, wow.

00:19:31.860 --> 00:19:33.200
And then go to PyCon.

00:19:33.200 --> 00:19:36.600
So it was like a huge trip, even though it was only two miles, three miles from my house.

00:19:36.600 --> 00:19:37.780
But it was a great time.

00:19:37.780 --> 00:19:43.520
What is the one conference talk that you always go back and listen to or watch?

00:19:43.520 --> 00:19:45.500
Oh, the one conference talk.

00:19:45.500 --> 00:19:46.000
Oh, boy.

00:19:46.000 --> 00:19:57.680
It's, I would say, the birth and death of JavaScript by Gary Bernhardt, which is, have you seen this?

00:19:57.920 --> 00:19:59.680
I think I've seen it once.

00:19:59.680 --> 00:20:05.480
It's, whenever I got to do reference stuff with like low-level JavaScript and stuff.

00:20:05.480 --> 00:20:10.620
I mean, I know it's, this is Python and all, but I think he gave that at a Python conference

00:20:10.620 --> 00:20:12.740
as a, like a comedy thing.

00:20:12.800 --> 00:20:16.980
But it's also a really interesting history of JavaScript as both, you know, drama.

00:20:16.980 --> 00:20:18.220
I don't know.

00:20:18.220 --> 00:20:20.060
If you haven't seen it, it's worth checking out.

00:20:20.420 --> 00:20:20.760
All right.

00:20:20.760 --> 00:20:20.780
All right.

00:20:20.780 --> 00:20:21.980
Two more rapid fire questions.

00:20:21.980 --> 00:20:27.540
What is your favorite addition or update to Python since you've been using it?

00:20:30.900 --> 00:20:33.420
I thought I was going to, I almost started like, oh, that's easy.

00:20:33.420 --> 00:20:36.620
But then there's two, there's two things that are really, really, really.

00:20:36.620 --> 00:20:36.980
You can do two.

00:20:36.980 --> 00:20:37.360
All right.

00:20:37.360 --> 00:20:38.160
I'm going to do, I'm going to do two.

00:20:38.160 --> 00:20:38.740
I'm going to take two.

00:20:38.740 --> 00:20:39.940
Async and await.

00:20:39.940 --> 00:20:40.760
Type hints.

00:20:40.760 --> 00:20:42.060
Okay.

00:20:42.060 --> 00:20:42.960
Shout out to type hints.

00:20:42.960 --> 00:20:43.300
Type hints.

00:20:43.300 --> 00:20:43.600
Shout out.

00:20:43.600 --> 00:20:43.900
Yeah.

00:20:43.900 --> 00:20:46.000
f-strings are probably up there for me.

00:20:46.000 --> 00:20:48.040
f-strings are like in the top five.

00:20:48.040 --> 00:20:49.460
Type hints are definitely up there.

00:20:49.460 --> 00:20:49.940
Yeah.

00:20:49.940 --> 00:20:50.820
Walrus operator.

00:20:50.820 --> 00:20:51.360
Yeah.

00:20:51.360 --> 00:20:55.680
You can take a whole website down in a matter of seconds with that.

00:20:55.680 --> 00:20:56.860
No, the walrus operator is great.

00:20:56.860 --> 00:20:59.900
And then the last question is one that you normally ask.

00:20:59.900 --> 00:21:04.300
What is your favorite Python module or package?

00:21:04.300 --> 00:21:04.740
Yeah.

00:21:04.740 --> 00:21:04.960
Yeah.

00:21:04.960 --> 00:21:05.540
What one?

00:21:05.540 --> 00:21:10.880
There's a bunch of interesting ones I run across on Python bytes.

00:21:10.880 --> 00:21:12.260
It's like Brian Okken.

00:21:12.260 --> 00:21:14.120
We find a bunch there.

00:21:14.120 --> 00:21:19.660
The one that is really cool to me is unsync.

00:21:19.660 --> 00:21:20.060
Okay.

00:21:20.060 --> 00:21:26.060
It just kind of unifies threading, multiprocessing, and async and await in a nice, cool way.

00:21:26.060 --> 00:21:29.920
I haven't been able to use it as much as I'd like, but I really like that one.

00:21:29.920 --> 00:21:32.640
And I just want to give a shout out to Latexify.

00:21:32.640 --> 00:21:33.580
Okay.

00:21:33.580 --> 00:21:34.680
Latexify.

00:21:34.680 --> 00:21:35.680
You sure it's not Latexify?

00:21:35.680 --> 00:21:36.220
Yeah, yeah, yeah.

00:21:36.220 --> 00:21:38.060
You don't want the Latex people.

00:21:38.060 --> 00:21:38.540
Yeah, yeah, yeah.

00:21:38.540 --> 00:21:40.860
Sorry, LaTeX people coming after us.

00:21:40.860 --> 00:21:42.040
Let me re-say it.

00:21:42.040 --> 00:21:43.340
I meant Latexify.

00:21:43.340 --> 00:21:45.920
You can put a decorator onto a function.

00:21:45.920 --> 00:21:46.500
Okay.

00:21:46.500 --> 00:21:48.680
A Python function that does math inside.

00:21:48.820 --> 00:21:53.820
And we'll write the symbolic mathematical representation of the Python code you wrote.

00:21:53.820 --> 00:21:54.880
Oh, that's really cool.

00:21:54.880 --> 00:21:55.660
It's insane.

00:21:55.660 --> 00:21:56.480
That's really cool.

00:21:56.480 --> 00:22:00.720
It can't do everything, but it'll be like, okay, well, that's an infinite sum from zero to infinity of this.

00:22:00.720 --> 00:22:02.220
You know, how does it know?

00:22:02.220 --> 00:22:03.040
It's insane.

00:22:03.040 --> 00:22:03.860
Anyway.

00:22:03.860 --> 00:22:04.940
That's awesome.

00:22:05.100 --> 00:22:07.840
Well, Mike, again, thank you so much.

00:22:07.840 --> 00:22:10.800
Again, we've known each other for half a decade now.

00:22:10.800 --> 00:22:15.760
I hope we make it to a decade and more of working together and doing Talk Python stuff.

00:22:15.760 --> 00:22:19.880
And again, give people one more opportunity to know where they can learn more about the show.

00:22:19.880 --> 00:22:20.340
Yeah.

00:22:20.340 --> 00:22:25.760
If you're not subscribed, check it out, talkpython.fm or look for Talk Python in your podcast players.

00:22:25.760 --> 00:22:28.080
Really, really appreciate everyone.

00:22:28.340 --> 00:22:36.960
I mean, since I'm on this side of the microphone right now, I genuinely want to say thank you to everyone here, but everyone who listens to the show.

00:22:36.960 --> 00:22:41.580
It's been such an honor and it's so cool to be able to do that.

00:22:41.660 --> 00:22:44.020
You know, it's my full-time job now is running the podcast.

00:22:44.020 --> 00:22:44.720
That's awesome.

00:22:44.720 --> 00:22:48.440
And when I started, I thought, oh, this would be a cool hobby on the side.

00:22:48.440 --> 00:22:51.220
Like I said, five episodes and I've got to figure it out from there.

00:22:51.220 --> 00:22:56.040
And it's just been such a great response from everyone and thankful every day.

00:22:56.040 --> 00:22:57.320
And thank you for working.

00:22:57.320 --> 00:22:59.240
I also, 10 years.

00:22:59.240 --> 00:22:59.920
Let's do it.

00:22:59.920 --> 00:23:00.320
It'll be easy.

00:23:00.320 --> 00:23:01.580
Yeah, we'll make it happen.

00:23:01.580 --> 00:23:06.140
And thank you for letting us host this event at the Microsoft booth.

00:23:06.140 --> 00:23:08.780
And I think we actually have a gift for you as well.

00:23:08.780 --> 00:23:11.260
Aaron, do you have one of the?

00:23:11.460 --> 00:23:15.660
We have an extra pair of Surface earbuds.

00:23:15.660 --> 00:23:16.600
Oh, that's awesome.

00:23:16.600 --> 00:23:17.840
Especially for you.

00:23:17.840 --> 00:23:23.320
As a thank you one for doing this, but also a thank you for all that you do within the Python community.

00:23:23.320 --> 00:23:26.360
Everyone, this has been Michael Kennedy.

00:23:26.360 --> 00:23:27.040
I've been Jay Miller.

00:23:27.040 --> 00:23:28.340
This has been Talk Python Live.

00:23:28.340 --> 00:23:32.880
Let's give Michael a hand, wonderful hand for all that he's done for the past several years.

00:23:32.880 --> 00:23:34.760
Thank you, everyone.

00:23:41.260 --> 00:23:44.220
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00:25:22.840 --> 00:25:25.340
Hey, Mario.

00:25:25.340 --> 00:25:26.420
Hey, Mike.

00:25:26.420 --> 00:25:28.680
Great to see you here at the conference.

00:25:28.680 --> 00:25:29.800
I'm happy to meet you.

00:25:29.800 --> 00:25:30.940
Yeah, same here.

00:25:30.940 --> 00:25:34.520
First of all, before we get into it, just tell people quickly, who are you?

00:25:34.520 --> 00:25:34.860
Sure.

00:25:34.860 --> 00:25:35.320
Introduce yourself.

00:25:35.320 --> 00:25:36.440
My name's Mario.

00:25:36.440 --> 00:25:48.280
I live in Southern California, and I write a blog called Python by Night, which, you know, it's my hobby thing I do when the, you know, the kid's asleep, when my wife is asleep.

00:25:48.940 --> 00:25:50.720
That's what I do.

00:25:50.720 --> 00:25:51.360
Yeah.

00:25:51.360 --> 00:25:52.460
Some people play games.

00:25:52.460 --> 00:25:53.740
We write code.

00:25:53.740 --> 00:25:54.400
I write code.

00:25:54.400 --> 00:25:54.960
I write blogs or whatever.

00:25:54.960 --> 00:25:55.340
Awesome.

00:25:55.340 --> 00:25:57.560
So how's the conference going for you?

00:25:57.560 --> 00:25:58.360
Oh, man.

00:25:58.360 --> 00:25:59.340
I'm having a great time.

00:25:59.340 --> 00:25:59.600
Are you?

00:25:59.600 --> 00:26:01.320
It's my second PyCon.

00:26:01.680 --> 00:26:08.620
And this morning, I gave a lightning talk about being either a fly on the wall or a busy worker bee.

00:26:08.620 --> 00:26:10.780
And I've been a busy worker bee.

00:26:10.780 --> 00:26:14.600
Yeah, you said the first time you came here, we were speaking at lunch.

00:26:14.600 --> 00:26:16.820
You said the first time you came here, you kind of just held back.

00:26:16.820 --> 00:26:20.620
You're kind of just observing and watching from the outside.

00:26:20.780 --> 00:26:23.180
You kind of dove in with your feet first.

00:26:23.180 --> 00:26:28.040
You know, I tend to be in the background most of the time.

00:26:28.040 --> 00:26:35.280
But yeah, I saw a tweet, I think, asking for help over at the Python Software Foundation booth last year.

00:26:35.280 --> 00:26:36.820
It includes beanbags, by the way.

00:26:36.820 --> 00:26:38.220
It includes beanbags.

00:26:38.580 --> 00:26:41.660
Anyway, I went and helped out last year, met a lot of cool people.

00:26:41.660 --> 00:26:43.860
Then I just thought I should volunteer more.

00:26:43.860 --> 00:26:47.720
I got to meet a whole bunch of people I had only heard of or seen online.

00:26:47.720 --> 00:26:50.220
Like some, to me, Python heroes.

00:26:50.220 --> 00:26:51.820
And I thought this was excellent.

00:26:51.820 --> 00:26:56.540
So this year, I just dove in and tripled that or quadrupled that, I guess.

00:26:56.540 --> 00:26:56.920
Yeah.

00:26:56.920 --> 00:26:57.400
Awesome.

00:26:57.400 --> 00:26:58.820
Seems like you're having a great time.

00:26:58.820 --> 00:26:59.880
I'm having a great time.

00:26:59.880 --> 00:27:00.240
Awesome.

00:27:00.240 --> 00:27:02.060
What has your plan been?

00:27:02.060 --> 00:27:03.500
Some people try to go all the talks.

00:27:03.500 --> 00:27:05.060
Some people hallway track it.

00:27:05.060 --> 00:27:06.140
Some people just go to the parties.

00:27:06.140 --> 00:27:07.680
What's your plan?

00:27:07.680 --> 00:27:08.480
Let's see.

00:27:08.480 --> 00:27:14.460
So I guess I was so intent on getting my tutorial, which was on Wednesday, the very first tutorial,

00:27:14.460 --> 00:27:16.320
that I hadn't even made a plan.

00:27:16.320 --> 00:27:18.380
I just was so focused on that.

00:27:18.380 --> 00:27:21.920
Once I gave the tutorial, I was breathing easy.

00:27:21.920 --> 00:27:25.160
But I had already volunteered to help with the online platform.

00:27:25.160 --> 00:27:26.660
I was helping with the booth again.

00:27:26.660 --> 00:27:27.980
So that kind of kept me busy.

00:27:27.980 --> 00:27:30.840
I had planned to attend a couple talks.

00:27:30.840 --> 00:27:32.900
I've only been to two, maybe.

00:27:32.900 --> 00:27:34.040
Yeah, yeah, yeah.

00:27:34.040 --> 00:27:37.640
So the plan was survive the tutorial.

00:27:37.640 --> 00:27:38.840
I didn't figure it out for a minute.

00:27:38.840 --> 00:27:39.600
And then figure it out.

00:27:39.600 --> 00:27:40.180
How'd it go?

00:27:40.180 --> 00:27:41.120
It was HTMX, right?

00:27:41.120 --> 00:27:44.060
One of the fine technologies integrated with Python.

00:27:44.060 --> 00:27:44.680
Fantastic.

00:27:44.680 --> 00:27:46.800
I feel like I've been talking about it all conference.

00:27:47.480 --> 00:27:48.980
I've talked to people individually.

00:27:48.980 --> 00:27:50.760
I had an open space about it.

00:27:50.760 --> 00:27:52.220
I talked about it at lunch.

00:27:52.220 --> 00:27:59.420
There's a real kind of a very poppable energy that people feel when they see what it can do.

00:27:59.420 --> 00:28:00.280
It's pretty exciting.

00:28:00.280 --> 00:28:04.000
A bunch of people have been putting off learning JavaScript because they felt they have to.

00:28:04.000 --> 00:28:05.420
And you're like, wait, you don't actually have to do that.

00:28:05.420 --> 00:28:06.000
You don't have to.

00:28:06.000 --> 00:28:06.300
You don't have to.

00:28:06.300 --> 00:28:07.060
You really do.

00:28:07.060 --> 00:28:08.080
Keep it by thought.

00:28:08.200 --> 00:28:09.300
I haven't learned JavaScript.

00:28:09.300 --> 00:28:10.680
Yeah, exactly.

00:28:10.680 --> 00:28:13.260
Not knocking on people who have and they're welcome to.

00:28:13.260 --> 00:28:15.060
But if you don't want to, you shouldn't be made to.

00:28:15.060 --> 00:28:17.160
Yeah, it's not an either or.

00:28:17.160 --> 00:28:18.420
It's both and.

00:28:18.420 --> 00:28:20.560
But if you don't have to, you don't have to.

00:28:20.560 --> 00:28:24.280
Yeah, the irony is even Node.js JavaScript people like it.

00:28:24.280 --> 00:28:25.820
Because they don't have to write front end JavaScript.

00:28:25.820 --> 00:28:26.880
They can write back end JavaScript.

00:28:26.880 --> 00:28:27.300
Right.

00:28:27.300 --> 00:28:28.740
There's something in it for everyone.

00:28:28.740 --> 00:28:30.440
Yeah, so that's been mostly it.

00:28:30.520 --> 00:28:31.740
I love the hallway track.

00:28:31.740 --> 00:28:33.060
I love meeting people.

00:28:33.060 --> 00:28:38.340
I got a picture with Ned who, you know, he gave an awesome opening keynote.

00:28:38.340 --> 00:28:42.920
You know, all sorts of people that I'm meeting for the first time.

00:28:42.920 --> 00:28:44.120
Other people I met last year.

00:28:44.120 --> 00:28:44.840
It's fantastic.

00:28:44.840 --> 00:28:45.660
Yeah, awesome.

00:28:45.660 --> 00:28:46.980
What's your big takeaways?

00:28:46.980 --> 00:28:47.860
What has stood out for you?

00:28:47.860 --> 00:28:52.480
I mean, there's a bunch of cool stuff back here behind us at the expo hall and other things

00:28:52.480 --> 00:28:53.300
you probably saw at talks.

00:28:53.300 --> 00:28:54.200
Like what stood out?

00:28:54.200 --> 00:28:55.660
What stood out?

00:28:56.160 --> 00:29:05.020
I think, you know, part of it is just coming away from it from these past couple years that

00:29:05.020 --> 00:29:05.800
have been tough.

00:29:05.800 --> 00:29:08.740
Just not seeing a lot of people.

00:29:08.740 --> 00:29:12.260
And it is still kind of weird to see a lot of people.

00:29:12.260 --> 00:29:14.420
You feel that kind of hesitancy.

00:29:14.420 --> 00:29:15.860
People are still kind of feeling it out.

00:29:15.860 --> 00:29:23.300
But in spite of it all, I just think the Python community embraces people of all walks of life.

00:29:23.300 --> 00:29:30.060
No matter where you're coming from, even flies like myself who tend to be, you know, trying to

00:29:30.060 --> 00:29:31.020
masquerade as a bee.

00:29:31.020 --> 00:29:38.720
Even so, I feel like it's a safe space to be vulnerable, to learn a lot, and to teach a lot.

00:29:38.720 --> 00:29:40.020
Yeah, absolutely.

00:29:40.020 --> 00:29:41.700
It's a very welcoming space.

00:29:41.700 --> 00:29:42.620
And we're stronger together.

00:29:42.620 --> 00:29:45.160
That means we ought to take time to be together, right?

00:29:45.160 --> 00:29:45.820
Yeah, correct.

00:29:45.820 --> 00:29:46.280
Right.

00:29:46.280 --> 00:29:49.080
Well, thanks for taking the time to share your experience.

00:29:49.080 --> 00:29:49.880
Great to see you.

00:29:49.880 --> 00:29:50.300
All right.

00:29:50.300 --> 00:29:50.940
Awesome.

00:29:50.940 --> 00:29:51.480
Thank you.

00:29:51.480 --> 00:29:52.160
Yeah, thanks.

00:29:52.160 --> 00:29:52.560
Hey, Nick.

00:29:52.560 --> 00:29:53.040
How are you doing?

00:29:53.240 --> 00:29:54.140
Hey, Michael.

00:29:54.140 --> 00:29:55.220
Hey, it's good to see you.

00:29:55.220 --> 00:29:56.160
Good to see you, too.

00:29:56.160 --> 00:29:56.520
Yeah.

00:29:56.520 --> 00:29:57.900
In person this time.

00:29:57.900 --> 00:29:58.460
Yes.

00:29:58.460 --> 00:30:00.360
Last time it was on Python Bytes, right?

00:30:00.360 --> 00:30:00.740
Yes.

00:30:00.740 --> 00:30:02.000
Last time it was on Python Bytes.

00:30:02.000 --> 00:30:02.280
Yeah.

00:30:02.280 --> 00:30:03.800
But here on PyCon.

00:30:03.800 --> 00:30:04.580
Yes.

00:30:04.580 --> 00:30:04.840
Yeah.

00:30:04.840 --> 00:30:06.100
PyCon 2023.

00:30:06.100 --> 00:30:07.080
Yeah.

00:30:07.080 --> 00:30:10.520
So I just wanted to get together with a couple of folks, including you, and just ask, you know,

00:30:10.520 --> 00:30:11.920
what's your PyCon experience this year?

00:30:11.920 --> 00:30:12.320
How's it going?

00:30:12.320 --> 00:30:14.860
It has been actually quite amazing.

00:30:14.860 --> 00:30:19.300
This year was the first time I gave a talk at PyCon.

00:30:19.300 --> 00:30:19.660
Okay.

00:30:19.660 --> 00:30:20.460
My first ever talk.

00:30:20.460 --> 00:30:21.120
How did it go?

00:30:21.120 --> 00:30:22.400
It went really well.

00:30:22.560 --> 00:30:22.680
Yeah.

00:30:22.680 --> 00:30:28.400
I think I felt so encouraged by the Python community, people that came up to me and really appreciated

00:30:28.400 --> 00:30:30.240
what I had to say.

00:30:30.240 --> 00:30:34.460
And that made me feel more engaged and wanted me to do it again.

00:30:34.460 --> 00:30:34.940
Yeah.

00:30:34.940 --> 00:30:35.260
Yeah.

00:30:35.260 --> 00:30:35.480
Yeah.

00:30:35.480 --> 00:30:35.940
Fantastic.

00:30:36.080 --> 00:30:36.640
What was it on?

00:30:36.640 --> 00:30:41.560
It was on improving the transportation networks using Python.

00:30:41.560 --> 00:30:42.180
Mm-hmm.

00:30:42.180 --> 00:30:47.780
As a data scientist for Trimble Transportation, I work in the transportation industry.

00:30:48.140 --> 00:30:52.560
And they face a lot of problems in terms of reducing waste, optimizing their networks.

00:30:52.560 --> 00:30:55.480
And that's what my team at Trimble do day to day.

00:30:55.480 --> 00:30:55.880
Yeah.

00:30:55.880 --> 00:31:00.800
So I needed to share with the Python community.

00:31:00.800 --> 00:31:01.800
Yeah.

00:31:01.800 --> 00:31:04.880
And try to really get at the core of it.

00:31:04.880 --> 00:31:05.240
Yeah.

00:31:05.560 --> 00:31:08.480
And show that we use really a lot of Python to do it.

00:31:08.480 --> 00:31:10.520
That sounds awesome.

00:31:10.520 --> 00:31:14.280
I'm just kind of wondering, as you're telling me that, like, do you get extra frustrated at

00:31:14.280 --> 00:31:15.340
traffic jams and stuff?

00:31:15.340 --> 00:31:18.200
Because you know behind the scenes how much it could be better.

00:31:18.200 --> 00:31:22.180
I get frustrated at when my Amazon package doesn't come on time.

00:31:22.180 --> 00:31:22.400
Yeah.

00:31:22.400 --> 00:31:22.680
Okay.

00:31:22.680 --> 00:31:27.800
So, but then again, I also feel a lot of empathy too, because I know these drivers

00:31:27.800 --> 00:31:28.560
that are driving.

00:31:28.560 --> 00:31:28.880
Yeah.

00:31:28.880 --> 00:31:30.000
It's a lot.

00:31:30.000 --> 00:31:33.220
I think like half the traffic in the world might actually be Amazon drivers.

00:31:33.220 --> 00:31:38.220
But anyway, more, here, hold on, let me move this real quick.

00:31:38.220 --> 00:31:38.880
There we go.

00:31:38.880 --> 00:31:42.840
Tell me about what you thought this year.

00:31:42.840 --> 00:31:46.920
It seems like the conference people are really happy to be back, but you know, what stood out

00:31:46.920 --> 00:31:47.220
for you?

00:31:47.220 --> 00:31:52.020
I think what stood out for me is the number of new attendees we still got.

00:31:52.120 --> 00:31:52.780
Yeah, quite a few.

00:31:52.780 --> 00:31:52.980
Yeah.

00:31:52.980 --> 00:31:53.680
Quite a few.

00:31:53.680 --> 00:32:00.440
And it's pretty amazing because there were a lot of layoffs and economic struggles.

00:32:00.440 --> 00:32:04.440
And you know, the conferences, it's not like it's always, you're all free.

00:32:04.440 --> 00:32:06.880
But people still came.

00:32:06.880 --> 00:32:12.800
And I think that's partly due to the PSF and the great work they do with their, you know,

00:32:12.800 --> 00:32:14.280
financial program.

00:32:14.280 --> 00:32:14.560
Right.

00:32:14.560 --> 00:32:15.340
Some of the scholarships.

00:32:15.340 --> 00:32:15.640
Yeah.

00:32:15.640 --> 00:32:20.380
Companies that we see here in the booth, really understanding the importance of sending their

00:32:20.380 --> 00:32:21.100
people out here.

00:32:21.100 --> 00:32:23.140
So it's really great to see all those first time attendees.

00:32:23.140 --> 00:32:24.160
Yeah.

00:32:24.160 --> 00:32:24.840
Yeah.

00:32:24.840 --> 00:32:25.100
Excellent.

00:32:25.100 --> 00:32:29.120
And you said you're kind of trying the hallway track out this year?

00:32:29.120 --> 00:32:29.580
Yes.

00:32:29.580 --> 00:32:32.520
That is a secret feature of PyCon.

00:32:32.520 --> 00:32:33.820
The one thing not on YouTube.

00:32:33.820 --> 00:32:34.380
Yes.

00:32:34.380 --> 00:32:34.820
Live stream.

00:32:34.820 --> 00:32:35.320
None of that.

00:32:35.320 --> 00:32:36.000
None of that.

00:32:36.000 --> 00:32:36.020
None of that.

00:32:36.020 --> 00:32:36.020
None of that.

00:32:36.020 --> 00:32:36.020
None of that.

00:32:36.020 --> 00:32:36.020
None of that.

00:32:36.020 --> 00:32:36.520
None of that.

00:32:36.520 --> 00:32:40.240
And I was at the keynote with Ned Batch Elder.

00:32:40.240 --> 00:32:43.400
And he really talked about talking to people.

00:32:43.400 --> 00:32:50.000
Because we have, and also like Marietta, the chair of PyCon this year, talked about there's

00:32:50.000 --> 00:32:51.360
2,000 people here.

00:32:51.640 --> 00:32:52.960
Like over 2,000 people here.

00:32:52.960 --> 00:32:55.920
And this is only time you're going to get to talk to them.

00:32:55.920 --> 00:32:56.320
Yeah.

00:32:56.420 --> 00:32:59.120
So I opted, made a conscious effort.

00:32:59.120 --> 00:33:00.160
Yeah.

00:33:00.160 --> 00:33:00.340
Sorry.

00:33:00.340 --> 00:33:00.940
Got to cut off there.

00:33:00.940 --> 00:33:02.360
But the hallway track.

00:33:02.360 --> 00:33:02.660
Yeah.

00:33:02.660 --> 00:33:03.320
The hallway track.

00:33:03.320 --> 00:33:04.300
And Ned talked about talking to people.

00:33:04.300 --> 00:33:04.500
Yeah.

00:33:04.500 --> 00:33:07.080
Ned and Marietta talked about talking to people.

00:33:07.080 --> 00:33:11.380
So I made a conscious effort to try and interact with the fellow people that are walking around

00:33:11.380 --> 00:33:13.180
this hallways and this expo booth.

00:33:13.180 --> 00:33:17.380
And I really got a lot of like really nice interactions.

00:33:17.380 --> 00:33:17.720
Yeah.

00:33:17.720 --> 00:33:20.720
I met up with old friends, people I met at PyCon.

00:33:20.720 --> 00:33:23.960
But we're going to do activities together and all that stuff.

00:33:23.960 --> 00:33:27.720
So it's been really, really, really like fruitful.

00:33:27.720 --> 00:33:28.240
Yeah.

00:33:28.240 --> 00:33:28.600
Awesome.

00:33:28.600 --> 00:33:30.980
Well, great to run into you.

00:33:30.980 --> 00:33:31.680
Same.

00:33:31.680 --> 00:33:32.220
Likewise.

00:33:32.220 --> 00:33:32.700
Yeah.

00:33:32.700 --> 00:33:32.900
Yeah.

00:33:32.900 --> 00:33:36.920
And thanks for taking the time to talk to everyone and sharing your experience.

00:33:37.320 --> 00:33:37.840
Bye, guys.

00:33:37.840 --> 00:33:38.180
Bye.

00:33:38.180 --> 00:33:38.520
Bye.

00:33:38.520 --> 00:33:39.440
Hey, Sean.

00:33:39.440 --> 00:33:40.240
Hey, Mike.

00:33:40.240 --> 00:33:40.620
How's it going?

00:33:40.620 --> 00:33:42.160
It's fantastic to see you again.

00:33:42.160 --> 00:33:42.900
And in person.

00:33:42.900 --> 00:33:43.420
I know.

00:33:43.420 --> 00:33:43.720
Imagine that.

00:33:43.720 --> 00:33:44.260
I know.

00:33:44.260 --> 00:33:45.160
First time in a few years.

00:33:45.160 --> 00:33:45.720
It's been great.

00:33:45.720 --> 00:33:46.220
It has.

00:33:46.220 --> 00:33:47.120
Since the before times.

00:33:47.120 --> 00:33:47.560
I know.

00:33:47.560 --> 00:33:49.060
Since the before times.

00:33:49.060 --> 00:33:51.680
But here we all are back together at PyCon.

00:33:51.680 --> 00:33:53.140
And yeah, it's great.

00:33:53.140 --> 00:33:55.380
Before we get into it, I would just tell people quickly about yourself.

00:33:55.380 --> 00:33:55.820
Sure.

00:33:55.820 --> 00:33:56.520
Fellow podcaster.

00:33:56.520 --> 00:33:57.080
Sure.

00:33:57.080 --> 00:33:58.160
So my name is Sean Tyber.

00:33:58.160 --> 00:34:04.100
I'm a senior cloud engineer at Mondelez International, which nobody knows except for we make all of the Oreos

00:34:04.100 --> 00:34:07.320
and the Nilla wafers and Cadbury chocolates, all the good stuff.

00:34:07.320 --> 00:34:10.260
And we also do a lot of really cool stuff in the cloud.

00:34:10.260 --> 00:34:14.280
So I'm also the co-host of the Teaching Python podcast.

00:34:14.280 --> 00:34:17.200
I feel like I'm missing my right arm because Kelly couldn't make it this time.

00:34:17.200 --> 00:34:17.820
Shout out to Kelly.

00:34:17.820 --> 00:34:18.920
Kelly, you should be here.

00:34:18.920 --> 00:34:19.320
We miss you.

00:34:19.320 --> 00:34:19.740
Yeah.

00:34:19.740 --> 00:34:20.840
Well, we'll get her next year, you know.

00:34:20.840 --> 00:34:21.480
Yes, exactly.

00:34:21.480 --> 00:34:22.060
Yeah.

00:34:22.060 --> 00:34:22.240
Awesome.

00:34:22.240 --> 00:34:29.800
And just here running the Education Summit on Thursday and attending the rest of the conference and enjoying it like any other Pythonista.

00:34:29.800 --> 00:34:31.220
How was the Education Summit?

00:34:31.580 --> 00:34:32.020
It's amazing.

00:34:32.020 --> 00:34:37.380
We had some wonderful speakers, educators coming from all over the country, from all over the world.

00:34:37.380 --> 00:34:41.700
We had people speaking from as far away as South Korea at the Education Summit.

00:34:41.700 --> 00:34:51.220
And it's the one time of year when people who are teaching computer science and teaching Python specifically get a chance to come together and talk about what they do with other people.

00:34:51.220 --> 00:34:53.040
It's just a unique experience.

00:34:53.040 --> 00:34:53.800
Yeah, it's excellent.

00:34:53.940 --> 00:34:58.020
And if you're teaching actual students, it's hard to get away, right?

00:34:58.020 --> 00:35:00.740
You've got the school year and you've got a structure on that.

00:35:00.740 --> 00:35:01.760
So it's a big deal.

00:35:01.760 --> 00:35:03.560
Yeah, it's been a great experience.

00:35:03.560 --> 00:35:09.040
We did some workshops talking about the impact of generative AI on education, some of the implications of that.

00:35:09.040 --> 00:35:12.000
And just, you know, trying to figure out what it's going to look like in the future.

00:35:12.000 --> 00:35:15.740
So what did you decide ChatGPT is going to do to our education system?

00:35:15.740 --> 00:35:23.320
Well, we still have way more questions than we have answers, but we also are looking at it from the lens of there have been other tools that have transformed education.

00:35:23.320 --> 00:35:27.500
Calculators were supposed to ruin the teaching of math, and yet we figured that out.

00:35:27.500 --> 00:35:29.400
So we're confident we can do the same here.

00:35:29.400 --> 00:35:31.300
Same thing for search.

00:35:31.300 --> 00:35:33.760
And the internet also kind of broke it, right?

00:35:33.880 --> 00:35:38.540
How are you going to test if people know history, if they can just type in, when was the War of 1812?

00:35:38.540 --> 00:35:39.000
Right.

00:35:39.000 --> 00:35:42.400
And what we found is that these are skills that we can teach.

00:35:42.400 --> 00:35:47.120
We can teach students how to search more effectively, how to find things, how to solve problems.

00:35:47.120 --> 00:35:55.840
And I think with generative AI, it's about how to evaluate what's happening, what you're asking for, and making sure that it is appropriate to the problem you're trying to solve.

00:35:55.840 --> 00:35:57.040
How do you ask good questions?

00:35:57.040 --> 00:35:59.220
And then how do you assess whether it's real, what it said?

00:35:59.220 --> 00:35:59.820
Exactly.

00:35:59.820 --> 00:36:00.160
Interesting.

00:36:00.160 --> 00:36:00.420
All right.

00:36:00.420 --> 00:36:02.240
Well, what stood out for you at the show so far?

00:36:02.240 --> 00:36:02.800
How's it been?

00:36:03.120 --> 00:36:04.300
I mean, it's the people.

00:36:04.300 --> 00:36:12.580
Like always, it's the people getting to see everyone, getting to have those great conversations, to sit down and have lunch together and talk about things.

00:36:12.580 --> 00:36:17.900
And just, I find myself looking at everyone's badges to figure out where they're coming from and what kind of cool work they're doing.

00:36:17.900 --> 00:36:24.940
And I'm just curious about how they're using Python and how I could connect with them and make something cool happen together.

00:36:24.940 --> 00:36:26.840
It's always surprising.

00:36:26.840 --> 00:36:28.680
You run into such cool people.

00:36:28.680 --> 00:36:30.120
And that is my favorite part as well.

00:36:30.120 --> 00:36:32.900
It's just kind of the, honestly, the hallway track.

00:36:32.980 --> 00:36:34.900
I know, not dissing the speakers.

00:36:34.900 --> 00:36:43.240
I'm looking forward to those talks on YouTube, but it's the parts that are not recorded and are spontaneous that really make it worth coming to, I think.

00:36:43.240 --> 00:36:43.740
That's true.

00:36:43.740 --> 00:36:45.320
And I've been enjoying the talks, too.

00:36:45.320 --> 00:36:48.620
There's been some really phenomenal talk tracks this year.

00:36:49.260 --> 00:36:54.640
We're just seeing, I think, a new wave of energy coming out of the pandemic.

00:36:54.640 --> 00:36:55.300
Yeah.

00:36:55.300 --> 00:36:58.900
And I can't wait to go to Pittsburgh next year and do this all again.

00:36:58.900 --> 00:36:59.360
I know.

00:36:59.360 --> 00:36:59.920
That'll be awesome.

00:36:59.920 --> 00:37:02.220
Well, thanks for taking the time to share your experience.

00:37:02.220 --> 00:37:03.100
It's my pleasure, Michael.

00:37:03.100 --> 00:37:03.380
Thanks.

00:37:03.380 --> 00:37:03.700
You bet.

00:37:03.700 --> 00:37:03.860
Bye.

00:37:03.860 --> 00:37:04.020
Bye.

00:37:04.020 --> 00:37:04.460
Hey, Chris.

00:37:04.940 --> 00:37:05.460
Hey, Mike.

00:37:05.460 --> 00:37:06.000
How are you doing today?

00:37:06.000 --> 00:37:06.980
Really good.

00:37:06.980 --> 00:37:07.400
Really good.

00:37:07.400 --> 00:37:08.200
Enjoying PyCon.

00:37:08.200 --> 00:37:08.660
How about you?

00:37:08.660 --> 00:37:10.420
I am having an absolute blast here.

00:37:10.420 --> 00:37:11.820
It's always fun, isn't it?

00:37:11.820 --> 00:37:13.240
Oh, it's, it's, it is.

00:37:13.240 --> 00:37:14.700
This is my favorite conference.

00:37:15.980 --> 00:37:24.040
The, the energy, the vibe, the people, the willingness to share is bar none, the

00:37:24.040 --> 00:37:25.760
best conference that I've ever attended.

00:37:25.760 --> 00:37:25.980
Yeah.

00:37:25.980 --> 00:37:27.060
And I've been to a lot.

00:37:27.060 --> 00:37:27.400
Yeah.

00:37:27.400 --> 00:37:28.000
I know you have.

00:37:28.000 --> 00:37:30.180
It really is unique in that regard.

00:37:30.180 --> 00:37:32.380
Tell people quickly about yourself.

00:37:32.380 --> 00:37:33.500
Hey, everybody.

00:37:33.500 --> 00:37:34.820
My name is Chris Williams.

00:37:34.820 --> 00:37:37.760
I am the host of the V Brown Bag podcast.

00:37:37.760 --> 00:37:42.500
I'm a DevRel manager for HashiCorp and I'm an AWS hero.

00:37:42.500 --> 00:37:43.240
Yeah.

00:37:43.240 --> 00:37:43.780
Awesome.

00:37:44.400 --> 00:37:47.380
And I've been on your Brown Bag a few times.

00:37:47.380 --> 00:37:48.060
That's been very fun.

00:37:48.060 --> 00:37:49.400
You're a friend of the V Brown Bag show.

00:37:49.400 --> 00:37:50.340
I am a friend of the V Brown Bag.

00:37:50.340 --> 00:37:51.260
I am a friend of Talk Python.

00:37:51.260 --> 00:37:52.640
That is right.

00:37:52.640 --> 00:37:52.880
Yeah.

00:37:52.880 --> 00:37:53.560
We're all friends here.

00:37:53.560 --> 00:37:53.940
It's amazing.

00:37:53.940 --> 00:37:54.260
Yay.

00:37:54.260 --> 00:37:58.280
So, you know, how's this conference going for you?

00:37:58.280 --> 00:37:59.220
How is it in 2023?

00:37:59.220 --> 00:38:01.100
It's been going really well.

00:38:01.100 --> 00:38:05.300
I'm glad that, that there's a bit more energy than, than last year.

00:38:05.300 --> 00:38:07.700
It's there's, there's more and more interest.

00:38:07.700 --> 00:38:14.000
It's, it's been, I think people are just exuberant to be out of the house and meeting new

00:38:14.000 --> 00:38:18.740
folks and getting back into the vibe of the before times.

00:38:18.740 --> 00:38:19.080
Yeah.

00:38:19.080 --> 00:38:20.160
What do we miss people?

00:38:20.160 --> 00:38:20.520
Yeah.

00:38:20.520 --> 00:38:21.140
Yeah, exactly.

00:38:21.140 --> 00:38:22.080
Zoom is fine.

00:38:22.080 --> 00:38:24.940
But it's not a patch on actually hanging out with folks.

00:38:24.940 --> 00:38:25.740
It's not a replacement.

00:38:25.740 --> 00:38:26.300
That's right.

00:38:26.300 --> 00:38:26.560
Yeah.

00:38:26.560 --> 00:38:26.900
That's right.

00:38:26.900 --> 00:38:30.720
So what's your game plan here?

00:38:30.720 --> 00:38:32.980
Are you on hit all of the talks?

00:38:32.980 --> 00:38:34.300
Are you on hallway track?

00:38:34.300 --> 00:38:36.080
Are you trying to get all the swag?

00:38:36.080 --> 00:38:36.820
What's going on here?

00:38:37.040 --> 00:38:39.080
So I'm actually changing it up a little bit this year.

00:38:39.080 --> 00:38:39.280
Okay.

00:38:39.280 --> 00:38:43.140
I love the hallway track and, and meeting folks.

00:38:43.140 --> 00:38:48.260
So I found an entire contingent of people in Boston that I didn't even know were out there.

00:38:48.260 --> 00:38:48.620
Yeah.

00:38:48.620 --> 00:38:56.100
The keynotes have been, I am now trying to find ways to improve my public speaking.

00:38:56.280 --> 00:39:03.120
So paying attention to truly good folks like James and Ned and their keynotes were master

00:39:03.120 --> 00:39:07.380
classes and presentation and humorous pauses and things like that.

00:39:07.380 --> 00:39:11.200
And, and so I'm furiously scribbling down notes like, Oh, that sounded great.

00:39:11.200 --> 00:39:11.560
I'm going to try.

00:39:11.560 --> 00:39:12.200
I'm going to crib that.

00:39:12.200 --> 00:39:13.080
Yeah.

00:39:13.080 --> 00:39:17.060
You can, you can watch the talks or you can attend the talks or you can study the talks.

00:39:17.060 --> 00:39:20.340
And I, whenever I go there, as somebody who's done a ton of public speaking, I'm like,

00:39:20.340 --> 00:39:21.420
that was nice.

00:39:21.420 --> 00:39:23.380
I don't know if people caught that, but they appreciated that.

00:39:23.380 --> 00:39:23.600
Yes.

00:39:23.600 --> 00:39:23.840
If they didn't.

00:39:23.840 --> 00:39:24.260
Yeah.

00:39:24.260 --> 00:39:25.820
So yeah, that's.

00:39:25.820 --> 00:39:29.460
So I'm doing, I'm doing the keynotes as a, as a study session.

00:39:29.460 --> 00:39:31.760
I am doing the hallway track.

00:39:31.760 --> 00:39:36.740
I, if generally, if something is going to be recorded, I will catch it after the fact.

00:39:36.740 --> 00:39:41.320
So, so I tend to not do them unless there's something that I want to talk to the presenter

00:39:41.320 --> 00:39:44.200
about, like on the spot, then, then I will, then I will attend that.

00:39:44.200 --> 00:39:46.700
But I'm just, I'm just trying to catch up with some friends.

00:39:46.700 --> 00:39:52.500
A good friend of mine spent an inordinate amount of time teaching me new things in Python

00:39:52.500 --> 00:39:53.740
over the past couple of days.

00:39:53.740 --> 00:39:55.540
He's a, he's a contributor.

00:39:55.540 --> 00:39:56.140
Mm-hmm.

00:39:56.140 --> 00:40:01.300
And he was, he was showing me some stuff that as a, as a newbie developer, I've, I've just,

00:40:01.300 --> 00:40:03.940
I'm kind of too dumb to know the right questions to ask.

00:40:03.940 --> 00:40:06.980
And, and I know that people don't, don't like saying you're too dumb.

00:40:06.980 --> 00:40:07.780
Nobody's too dumb.

00:40:07.780 --> 00:40:08.660
There's no dumb questions.

00:40:08.660 --> 00:40:11.180
But well, you do need to sort of find your way.

00:40:11.180 --> 00:40:11.500
Right.

00:40:11.500 --> 00:40:11.860
Right.

00:40:11.960 --> 00:40:14.500
So the questions that I don't know I need to ask yet.

00:40:14.500 --> 00:40:14.880
Yeah.

00:40:14.880 --> 00:40:15.220
Sure.

00:40:15.220 --> 00:40:20.340
So, so yeah, it's, it's just been really, really good to catch up with folks, learn new things

00:40:20.340 --> 00:40:23.080
and, and absorb as much as humanly possible in three days.

00:40:23.080 --> 00:40:23.720
Oh yeah.

00:40:23.720 --> 00:40:26.540
It's, it is tiring, but it's fun.

00:40:26.540 --> 00:40:27.740
Commerce is fun.

00:40:27.740 --> 00:40:28.740
After parties are fun.

00:40:28.740 --> 00:40:28.980
Yep.

00:40:28.980 --> 00:40:29.320
Yep.

00:40:29.560 --> 00:40:29.760
Yeah.

00:40:29.760 --> 00:40:30.740
Really, really good stuff.

00:40:30.740 --> 00:40:33.500
So thanks for the chat here.

00:40:33.500 --> 00:40:35.600
Like what, what in Python are you excited about right now?

00:40:35.600 --> 00:40:39.180
So I'm going to be checking out the new releases in 3.12.

00:40:39.180 --> 00:40:42.640
They were, they were making some announcements on f-strings that, that I need to dig into.

00:40:42.640 --> 00:40:43.920
Like that we're making f-strings better.

00:40:43.920 --> 00:40:44.860
I'm like, okay, how?

00:40:44.860 --> 00:40:49.100
So, so I'm going to, I'm going to be doing a lot of Googling after everything is said and

00:40:49.100 --> 00:40:50.360
done to figure it out.

00:40:50.560 --> 00:40:55.380
And, and as a content creator myself, I will be spending a lot of time parsing through the

00:40:55.380 --> 00:41:01.940
stuff that I've been making and, and you know, just finding new ways to reach out to

00:41:01.940 --> 00:41:02.920
people, get content.

00:41:02.920 --> 00:41:06.560
I mean, I don't know about you, but for me, this whole experience is a great way to find

00:41:06.560 --> 00:41:07.840
interesting people to talk to.

00:41:07.840 --> 00:41:10.440
Like you could have people on V Brown Bag, right?

00:41:10.440 --> 00:41:12.420
There's a, there's a bunch of resumes.

00:41:12.420 --> 00:41:14.040
They didn't know they submitted to you.

00:41:14.040 --> 00:41:14.680
Oh yeah, absolutely.

00:41:14.680 --> 00:41:15.140
Yeah.

00:41:15.140 --> 00:41:19.340
I have been, I've been scribbling down names and my, my little, my little notepad on my

00:41:19.340 --> 00:41:23.400
phone is filling up furiously as, as I find people to pester after this.

00:41:23.400 --> 00:41:23.820
Awesome.

00:41:23.820 --> 00:41:26.040
Well, thanks for taking the time to share your thoughts.

00:41:26.040 --> 00:41:26.640
Thanks, Mike.

00:41:26.640 --> 00:41:27.080
Appreciate it.

00:41:27.080 --> 00:41:27.480
Yeah, you bet.

00:41:27.480 --> 00:41:27.680
Bye.

00:41:27.680 --> 00:41:28.280
Hey Ray.

00:41:28.280 --> 00:41:29.620
Hey, how are you doing?

00:41:29.620 --> 00:41:30.660
I'm doing wonderful.

00:41:30.660 --> 00:41:31.940
Great to meet you.

00:41:31.940 --> 00:41:32.820
You as well.

00:41:32.820 --> 00:41:33.040
Yes.

00:41:33.040 --> 00:41:33.860
Thank you.

00:41:33.860 --> 00:41:37.060
Tell people quick, quick who you are, a bit about yourself.

00:41:37.060 --> 00:41:37.760
Let's see.

00:41:37.760 --> 00:41:39.000
So I'm Ray McLendon.

00:41:39.000 --> 00:41:42.080
I'm actually a data scientist at the Kansas city fed.

00:41:42.080 --> 00:41:46.360
I'm mostly working natural language processing, that kind of fun stuff.

00:41:46.360 --> 00:41:46.760
Yeah.

00:41:46.760 --> 00:41:47.940
Oh, that sounds really awesome.

00:41:47.940 --> 00:41:48.060
Awesome.

00:41:48.060 --> 00:41:49.580
Yeah.

00:41:49.580 --> 00:41:54.740
So just talking to people about their PyCon experience and you know, how many times you've

00:41:54.740 --> 00:41:54.980
been here?

00:41:54.980 --> 00:41:57.180
So this is my second PyCon.

00:41:57.180 --> 00:41:57.560
Okay.

00:41:57.560 --> 00:41:59.280
My first one was last year.

00:41:59.280 --> 00:41:59.660
Yeah.

00:41:59.660 --> 00:42:03.100
Sort of like right on the back of everybody getting back together from the pandemic.

00:42:03.100 --> 00:42:03.780
Yeah.

00:42:03.840 --> 00:42:07.380
So I'm not sure how representative your experience was last time.

00:42:07.380 --> 00:42:10.160
It was a little different, but how was it this year?

00:42:10.160 --> 00:42:12.500
Oh, I'm really enjoying it.

00:42:12.500 --> 00:42:14.960
I actually gave a tutorial this year.

00:42:14.960 --> 00:42:15.280
Oh, you did?

00:42:15.280 --> 00:42:15.880
What was on?

00:42:15.880 --> 00:42:18.700
Feature engineering is for everyone.

00:42:18.700 --> 00:42:19.220
Uh-huh.

00:42:19.600 --> 00:42:22.960
So trying to just kind of share our knowledge of feature engineering.

00:42:22.960 --> 00:42:25.840
I co-presented that with a, with a coworker of mine, Leah.

00:42:25.840 --> 00:42:28.100
And yeah, it was fantastic.

00:42:28.100 --> 00:42:28.860
We had a great time.

00:42:28.860 --> 00:42:29.100
Yeah.

00:42:29.100 --> 00:42:30.260
You had a good experience doing it?

00:42:30.260 --> 00:42:31.040
Absolutely.

00:42:31.040 --> 00:42:32.240
Looking forward to doing it again.

00:42:32.240 --> 00:42:32.700
Cool.

00:42:32.700 --> 00:42:34.800
And what library was that like?

00:42:34.800 --> 00:42:35.940
PyTorch or what was it?

00:42:35.940 --> 00:42:37.220
Oh, that's really interesting.

00:42:37.380 --> 00:42:38.760
So it was a mix.

00:42:38.760 --> 00:42:43.320
There was some exploration with Y Data Profiler.

00:42:43.320 --> 00:42:44.140
Okay.

00:42:44.140 --> 00:42:47.540
And then there was building various features.

00:42:47.540 --> 00:42:54.160
Some of it was kind of just using Pandas or NumPy and scikit-learn.

00:42:54.160 --> 00:42:58.620
We use some of the libraries for feature engineering that are built into that.

00:42:58.620 --> 00:43:00.160
So it was a mix of libraries.

00:43:00.160 --> 00:43:00.500
Yeah.

00:43:00.500 --> 00:43:01.280
Cool.

00:43:01.280 --> 00:43:03.480
Well, what stood out to you so far this year?

00:43:04.980 --> 00:43:10.720
Well, I guess the interesting part that I did was I went to open spaces.

00:43:10.720 --> 00:43:12.320
I didn't do that the previous year.

00:43:12.320 --> 00:43:12.520
Yeah.

00:43:12.520 --> 00:43:14.960
And I went to one this year around civic data.

00:43:14.960 --> 00:43:16.920
So that was really fascinating.

00:43:16.920 --> 00:43:17.240
Yeah.

00:43:17.240 --> 00:43:17.580
Yeah.

00:43:17.580 --> 00:43:25.000
Enjoyed the real community vibe and learning about, I guess, honestly, how difficult it is

00:43:25.000 --> 00:43:27.060
to get your hands on civic data, quite frankly.

00:43:27.060 --> 00:43:27.280
Yeah.

00:43:27.280 --> 00:43:32.980
I can imagine that it is, but you know, we can complain a lot about the government and, and

00:43:32.980 --> 00:43:37.200
systems and that's easy to do, but at the same time, like we have all this technology

00:43:37.200 --> 00:43:41.120
and all this data and people, people can really put in, you know, make a difference.

00:43:41.120 --> 00:43:44.960
You know, I see actually the U S digital services have a booth over there.

00:43:44.960 --> 00:43:45.240
Right.

00:43:45.240 --> 00:43:50.580
And that's kind of like trying to bring people in from industry to say like, look, you built

00:43:50.580 --> 00:43:51.020
Instagram.

00:43:51.020 --> 00:43:55.160
Now, could you help us build something else for the government that we could, so people

00:43:55.160 --> 00:43:55.560
won't come.

00:43:55.560 --> 00:43:56.840
It's kind of cool actually.

00:43:57.200 --> 00:43:57.320
Yeah.

00:43:57.320 --> 00:43:59.100
So they were at the civic data group.

00:43:59.100 --> 00:43:59.500
Oh, they were.

00:43:59.500 --> 00:44:00.800
And I hate to say it.

00:44:00.800 --> 00:44:03.700
I had never heard of the U S digital service before.

00:44:03.700 --> 00:44:07.940
So I was really excited to hear about the efforts and the work that they're doing, including some

00:44:07.940 --> 00:44:12.040
of the like best practices guides around UX and UI that they even provide.

00:44:12.040 --> 00:44:13.900
So it's, they're a cool, cool service.

00:44:13.900 --> 00:44:20.980
I interviewed David on talk Python years ago, but maybe I should talk to them again, but

00:44:20.980 --> 00:44:22.000
anyway, it's, it's a cool service.

00:44:22.140 --> 00:44:23.460
So what stood out to you this year?

00:44:23.460 --> 00:44:27.620
Strangely enough, I come to Python.

00:44:27.620 --> 00:44:30.260
I expect some really technical talks to be honest.

00:44:30.260 --> 00:44:31.480
That's an expectation.

00:44:31.480 --> 00:44:37.120
It was really the keynote from the first day with Ted where he kind of broke down like communication.

00:44:37.120 --> 00:44:37.940
Yeah.

00:44:37.940 --> 00:44:41.840
That strangely, that was the thing that stood out the most to me.

00:44:41.840 --> 00:44:46.900
I've heard so many good things from his keynote and, and I was doing preparing for a live event

00:44:46.900 --> 00:44:48.160
that started the minute it ended.

00:44:48.280 --> 00:44:52.240
So I couldn't be there like, but I'm going to watch it on YouTube and I'll, I'll check it out.

00:44:52.240 --> 00:44:52.840
So cool.

00:44:52.840 --> 00:44:53.320
Absolutely.

00:44:53.320 --> 00:44:53.980
Yeah.

00:44:53.980 --> 00:44:57.900
And you've been walking around doing the hallway track a little bit as well and joins me and people.

00:44:57.900 --> 00:44:58.580
That's right.

00:44:58.580 --> 00:44:59.480
Yeah, I sure have.

00:44:59.480 --> 00:45:07.800
I bumped into a few folks and we've been throwing ideas around, you know, I'm really big into the

00:45:07.800 --> 00:45:09.060
whole GPT thing.

00:45:09.060 --> 00:45:09.980
Oh, it's crazy.

00:45:09.980 --> 00:45:10.220
Yeah.

00:45:10.220 --> 00:45:10.960
It's pretty wild.

00:45:10.960 --> 00:45:11.300
Yeah.

00:45:11.480 --> 00:45:14.960
So it's been interesting to see some folks that are really thinking deeply about ethics

00:45:14.960 --> 00:45:19.500
and security in that space and giving me new ideas to bring back.

00:45:19.500 --> 00:45:20.020
Yeah.

00:45:20.020 --> 00:45:20.320
Cool.

00:45:20.320 --> 00:45:23.360
There's a lot of ML and a lot of AI stuff around here this year.

00:45:23.360 --> 00:45:24.380
So, all right.

00:45:24.380 --> 00:45:25.680
Well, thanks for being on the show.

00:45:25.680 --> 00:45:26.740
Thanks for taking time.

00:45:26.740 --> 00:45:27.520
Appreciate it.

00:45:27.600 --> 00:45:27.700
Yeah.

00:45:27.700 --> 00:45:31.840
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00:46:52.320 --> 00:46:54.160
This is your host, Michael Kennedy.

00:46:54.160 --> 00:46:55.460
Thanks so much for listening.

00:46:55.460 --> 00:46:56.640
I really appreciate it.

00:46:56.640 --> 00:46:58.540
Now get out there and write some Python code.

00:46:58.540 --> 00:47:19.440
I'll see you next time.