How Katana Video is Revolutionizing Podcast Editing: AI-Powered Solutions with Sam Bhattacharyya

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Welcome to Podcasting Tech, a podcast that equips busy entrepreneurs

 

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engaged in podcasting with proven and cost effective solutions

 

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Passe, your host and a 15 year veteran in the podcasting space.

 

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to subscribe to this show on YouTube or your favorite podcast platform and

 

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join us on this exciting journey to unlock the full potential of your

 

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podcast. Going to take you down to Houston. Today

 

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we are chatting with Sam Bhattacharya. He is the CEO of

 

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Katana Video. That is Katana, like the

 

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Blade video and currently the platform

 

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is here to auto edit zoom recordings to turn them

 

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into video podcasts. Something I'm sure that as people are hearing this,

 

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are thinking, oh yes please Sam, thank you for

 

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joining us here today. Thanks for inviting me. Before

 

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we talk specifically about how Katana works,

 

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just tell me a little bit like how did you get interested in

 

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streaming media? Like, you know, why are you working on

 

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content platforms? You formerly worked with Streamyard, but like

 

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what drew you to this industry specifically?

 

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Yeah, so let me start most recently and then get started with how I

 

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got into video in the first place. So most recently I used to work

 

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as the head of AI for Streamyard, which is a similar platform to Riverside that

 

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we're using, a little bit more focused on the streaming aspect.

 

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And there we got into kind of

 

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AI and editing features which is how we got into some of

 

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this world, how I got into Streamyard and how

 

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I got into this world of video streaming. I have an interesting story

 

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but I'll try to keep it short. So I originally started my

 

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career, I've never actually worked for a real company or I mean

 

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streaming is real. I didn't kind of like apply for real. Like I have a

 

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bit of a non traditional career path. So right out of grad school

 

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I started a company, my own company and the idea was to

 

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make an E learning app for students in Sub

 

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Saharan Africa, specifically in West Africa. And my

 

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co founder was from Nigeria. He had studied there and then gone to

 

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study in the US for grad school. And we both saw this problem of

 

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the Internet not being very accessible for taking things like online classes. So our

 

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idea was kind of like Khan Academy but for students in West Africa.

 

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Despite my parents hesitations, I moved to Ghana And

 

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Nigeria for a year. With my co founder, we built an app to help students

 

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study for exams, like a Khan Academy. We did the thing.

 

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We built an actual kind of exam preparation app with online

 

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courses. And a big part of what we had done was we had built some

 

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interesting video compression technology to make online

 

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courses very accessible on really, really slow Internet

 

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connection so that you could watch or use like an online video course on

 

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a 2G connection. And in those countries, I

 

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think still to this day, you pay per gigabyte. Right? Right. So thinking about,

 

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you know, like, or being paying per megabyte, like, if it costs you

 

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like $2 to watch an online course just in

 

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bandwidth, like, you're. That's. That's a barrier. Right. Especially for people

 

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in those countries and students, of all people.

 

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So that was a big thing that didn't work out as a business. We had

 

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users, we had actually about 50,000 students studying for our

 

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exams using our app. But it was hard to monetize and get anywhere near

 

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covering our costs. So we eventually shut that down and

 

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made the content free. And then we moved back to the US and tried to

 

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license our technology to other companies.

 

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We actually created this, like, patented video compression technology.

 

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Like, no joke, we got in front of the right

 

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people at YouTube and Netflix. Like, not without

 

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exaggeration. Like, we actually got in the doors with those people and quickly realized

 

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that while we had an interesting idea, it wasn't practical to deploy at scale at

 

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any real kind of video streaming

 

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platforms. A couple more pivots.

 

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We eventually ended up creating AI for

 

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video streaming and video conferencing. So we

 

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had specialized in making features like virtual backgrounds and background noise

 

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removal. And then during the pandemic, we had gotten in touch with

 

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Streamyard who ended up using our technology for their own

 

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platform. And then they ended up acquiring us. And that's kind of how

 

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we got into Streamyard and like video streaming, it was just kind of an

 

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accident. But over the years, I'd built up experience around kind

 

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of video, video processing, especially AI as it

 

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relates to video. As someone who

 

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created a platform and then kind of like realized that the video compression was

 

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the big tool here and, you know, then was able to get in front of

 

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YouTube and Netflix and then go work for Streamyard. Like, do you do a lot

 

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of content creation yourself? Do you work with video or.

 

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Really it's just you figured out this problem and the coding itself

 

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is really where your passion lies. I think I'm much more on the

 

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coding side than the content side, though. We had actually,

 

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I Made some of our first online courses when we did that

 

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app. But we quickly realized that it was better to actually hire real

 

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teachers, especially from Ghana and Nigeria, to make those courses. So part of

 

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it was that was objectively better to have actual teachers

 

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making that content. And then more recently, you know,

 

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I just kind of been stringing along. I had started making

 

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content in when I was in Streamyard as a way to

 

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generate empathy for the people who are making content on Streamyard. Like, so I was

 

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like, you know, I was a product manager at the time, and I started

 

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making content to empathize with people who were using Streamyard to create

 

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content. But I actually kind of fell in. Like, I, I, I,

 

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I, I grew to like it the same way. I actually taught

 

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myself to code. So I figured, like, why can't I teach myself to make content?

 

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It's very different to put your code out on the stage than it is to

 

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put yourself out on the front stage and, you know, get that kind of feedback

 

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that is required. Yeah, well, you know what,

 

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that's true. And I am incorrigibly technical,

 

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if that makes sense. But one of the things that I realized that makes me

 

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kind of a bit different from most normal engineers is because I did a startup,

 

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because I did a lot of this stuff, that you're inherently putting yourself out there

 

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anyway. And so I had been no stranger to making pitches, to trying

 

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to convince people, you know, it was a different kind of use case. I was

 

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trying to convince people, hey, funder platform to help students and, you know,

 

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Ghana and E. Sorry for the exams. But at some point I was still making

 

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pitches, going on stages, trying to convince people, like, what we're doing is

 

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interesting. And that didn't seem that different from

 

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putting yourself out there online. It's just, you know, you have

 

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to, maybe when you're building a show, for example,

 

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treat it a bit more like an actual product. Like, who is your audience? Why

 

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are they interested? It's not like, so transactional as, like, you know, you

 

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donate to my company or invest in my company or whatever. But

 

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there's a sense in which I had gotten used to

 

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talking to people about what I was working on and trying to convince people to

 

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be excited about what I'm working on. That already kind of came into the door

 

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when I started making content. Gotcha. Okay, so

 

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tell us more about the actual Katana video platform.

 

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So how does it work? How do we sign up? You know, what can we

 

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expect? What problem is it solving for us? Yeah,

 

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so let's start with the problem that it's solving.

 

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So when I started working with

 

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Streamyard, I learned that many people make podcasts, obviously.

 

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But then the number one alternative that people used

 

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for recording podcasts on Streamyard

 

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was not Riverside, it was Zoom. Okay? So most

 

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people who start with podcasting start out recording

 

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on Zoom. And there's a reason that platforms like Riverside and

 

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Streamyard exist, because Zoom is not built for recording

 

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podcasts. And one of the main things that

 

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makes it hard to work with Zoom and turn that into a video podcast is

 

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that Riverside and

 

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similar platforms like Streamyard will give individual

 

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recordings, high quality recordings for each person

 

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doing the interview. And that's super important with editing to be able

 

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to do, for example, camera angle switching and knowing who's speaking

 

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when. And editors

 

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generally dislike working with zoom recordings because zoom

 

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doesn't give you that. Zoom just puts everything together. It's a nightmare to work with

 

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those zoom recordings and people work around it.

 

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So people will put like overlays on top of a zoom recording. But I

 

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had a pretty deep background in computer vision

 

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and kind of like old school AI

 

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and I figured, well, I mean, there's no reason you couldn't actually figure

 

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out like who's speaking when it just takes some upfront effort and work.

 

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And so the simple idea was, okay, well, let's

 

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actually take a zoom recording and then

 

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extract the video and audio and separate them as if they were

 

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local recordings. Okay? Then you could do things like multicam and

 

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camera angle switching and adding like name tags and all the stuff you would normally

 

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do. All the visuals you would normally put in a normal video

 

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podcast. It would be much easier once you knew who was speaking

 

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when, right? So that was very simple idea. Like, what if we just didn't

 

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fight this idea of people are going to use Zoom, get them to use Riverside

 

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or Streamyard or some other platform like that. What if we just met them where

 

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they were? You're using Zoom. Okay? Whatever reason you have to resume, there's still valid

 

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reasons for using Zoom. And so let's make

 

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it easy to make a zoom recording look like it was recorded and edited in

 

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a more professional platform like Riverside. And that was the high level.

 

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So when you go to Katana Video,

 

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the goal is to make it easy to turn

 

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your zoom recording into a video podcast. And a big aspect of that is

 

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automating those visuals of like the multi camera angle switching and whatnot

 

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so that within like five minutes you have something that looks like a

 

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professionally edited podcast with a lot of the

 

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visuals that would normally be done with

 

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tools. Like Riverside or Descript or whatnot. And then

 

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I'm also trying to make sure you can have a lot of the actual edits

 

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and cuts done. The basic ones, not like very, very artistic, but the basic

 

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ones, like making sure you cut off the recording before the interview actually

 

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starts and cut it off like after it actually ends. Because, you know,

 

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there's, there's one of you make a recording. There's like the, the pre

 

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interview stuff and the end of the interview stuff as well as like detecting the

 

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obvious like outtakes that you would find. Like, you know, can you cut this part

 

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out so that someone who's just getting started with podcasting can just get something

 

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that's out of the box, like is better

 

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than, better than what they started with for very little

 

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effort. It's not to the level of a professionally edited podcast by any

 

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means, but it's certainly better than what you started with.

 

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And the idea was to get something

 

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passable in five minutes. And so that's kind of like you just upload

 

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a zoom recording and you get like a

 

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good looking podcast in five minutes or 10 minutes. So what does it

 

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do? Like, what is the AI doing? What is it looking for? Are

 

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there things that we should be doing when we're recording

 

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to make the AI's job easier?

 

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Yeah, so. Well, one, everything's a work in progress, so I will be improving these

 

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algorithms as we go. But one is in terms

 

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of the core, who's talking when.

 

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The only thing that seems to mess up is when two people are talking exactly

 

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at the same time. And that kind of, I mean, can you really

 

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blame, you know, even as an editor you would have a hard time.

 

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So in that, in that, in those circumstances we just default to showing both people

 

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at the same time. Just like you don't highlight one of them when two people

 

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are talking at the same time. That's it.

 

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I think the idea is very much like you don't have to do anything specific

 

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to make the jobs easier. Like there's just like some edge cases that

 

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I'm finding that I need to handle

 

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for. So someone had an intro section that

 

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they recorded at the end of their podcast. We're like, oh, we forgot to do

 

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the intro, let's do it at the end and then we'll

 

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fix it in editing and post production. And that's like such a normal

 

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natural thing. But that kind of messed up my very simple algorithm that like assumes

 

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that the start happens before the end, if that makes sense. And that just

 

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kind of messed that, that whole thing up. And so, I mean those are edge

 

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cases that you'd want to handle gracefully in the future. But

 

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the idea is like you don't have to do anything special. Okay. And then

 

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once it's done, is it

 

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take it or leave it or can we take what you're

 

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creating and then, you know, bring it over to one of our editors and you

 

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know, make some finesse edits or you know, maybe tweak a few things here or

 

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there to get it where we want it to be. Well, so it's,

 

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it's got a built in Transcriptus editor

 

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built in. I, I consciously didn't make

 

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this a kind of. You can export this to Adobe and maybe I will in

 

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the future. But the use case that I was looking for

 

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was targeting a different segment. So there are plenty of

 

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very nice editor softwares out there like Descript and you

 

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know, Riverside, you can edit. But this was definitely designed for the

 

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people who wouldn't otherwise have

 

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or use those editor softwares or hire someone that does have those editor software.

 

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So I made sure, I spent a lot of effort just making sure that it

 

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works by itself. So I have like this own style of stack. So it's

 

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basically like you can tweak it, especially on the adjustments, like the branding, the look,

 

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the feel, the custom and you can, you can edit it based on transcript based

 

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editing and then it renders, you know, it

 

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has a full rendering stack and whatnot. But I haven't quite put in like you

 

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can export like the RAW project file as an Adobe Premiere

 

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profile or something like that. Maybe I will in the future, but I

 

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don't feel like I have enough like of the auto edit stuff yet that it

 

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makes sense to kind of do that. And I do want to improve the

 

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auto edit capabilities in the future. All right,

 

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so how does someone get started, right, like what are the pricing plans? Like what

 

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does it look like to work with it? Do we have to upload? Is there

 

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an integration with Zoom built into it? What does it look like for

 

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someone who's hearing this and wants to try it out? Yeah, well,

 

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so first it's Katana Video, that's the address

 

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and it's free right now. You couldn't pay me if you wanted to because I

 

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am still in beta and figuring things out. And the

 

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idea behind it was to have a free option that's always

 

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available. And the high level idea behind the free

 

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option was you can make your zoom recording look good

 

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and it'll have all of the camera angle switching and all of those like branding,

 

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customization, Options just out of the box for free forever. And

 

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there will be a play plan which has some additional auto edit capabilities.

 

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So in terms of auto edits, I think the idea is like

 

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to give you everything you need to get a

 

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raw recording to something you would happily upload on YouTube. Like

 

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there's a couple more things you'd need to do and one of them is like

 

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generating a really nice catchy intro, for example. That's one of the big things

 

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I'm focusing on right now. And so if you look at professionally edited

 

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podcasts on a video show on YouTube, they'll often

 

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have an intro section which is like a catchy

 

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back to back compilation of sound bites. Sometimes with effects.

 

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Like they'll zoom in on one of the speaker's faces, maybe they'll

 

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highlight some words in the background. At the most extreme end

 

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you'd see stuff like Diary of a CEO that's a bit extreme for what an

 

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automated tool could do at this point, but you have like less

 

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extreme versions of that where it's like, it's like a catching intro. So that's the

 

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kind of thing that would be on the paid plan. And so you would kind

 

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of generate one of these like intro teasers as part of the paid plan as

 

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well as like social media clips. Like the clips. So there's that

 

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functionality that would be on the paid plan primarily, but then the core

 

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just making your zoom recording look good. That's free

 

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forever. Forever. And yeah,

 

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I mean it's, it's also. Well, as long as Katana Video

 

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exists or whatever, like, you know, how am I supposed to know what, what

 

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things are going to look like in 20 years? But where do you think AI

 

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is going in terms of this stuff? Like, I love the idea that there

 

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are aspects of content

 

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creation and content editing that are

 

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monotonous and repeatable and you know,

 

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don't really require a lot of feel

 

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to get them right. Right. Like switching between two speakers. It's a

 

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fairly simplistic concept. But are you,

 

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do you think AI will ever really replace human

 

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editing and editors or ever be, you know, take it to the

 

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level that it will be capable of making something that

 

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is artistic or, you know, has emotion

 

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to it, or is it really just, you know,

 

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factual content editing and

 

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sharing and you know, quality control more than,

 

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you know, character control, let's say? Yeah, so I

 

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have, I do have some opinions and that may be interesting to the audience.

 

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So one, I think there's a lot of misunderstanding of like how AI

 

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works and also even the people who, people who actually, like, do have an idea

 

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of, like what? Like, you know, there's no one's clear on what the future is

 

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going to be like. But I have a thesis of

 

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how AI is going to impact video editing. I think one of the

 

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things that you have to understand going off the boat is that there aren't really

 

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AI models that are trained to edit video. And

 

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I want to make sure and emphasize that point. There aren't really AI

 

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models that are in any deep or

 

Speaker:00:18:31

fundamental way trained to predict what edits you would make in

 

Speaker:00:18:35

video content. And that comes from the fact that these

 

Speaker:00:18:39

large language model labs like OpenAI and

 

Speaker:00:18:42

Google haven't actually sat down and hired hundreds of video

 

Speaker:00:18:45

editors to build the data sets. It goes back to

 

Speaker:00:18:49

the fundamental, like, they weren't built for this stuff. And that doesn't stop people

 

Speaker:00:18:53

like opus from using ChatGPT as a way of

 

Speaker:00:18:56

editing. But that's why the results are so mixed. If you

 

Speaker:00:19:00

use a tool like OPUS Clips or even like,

 

Speaker:00:19:04

you know, Riverside's clips, like, I don't think anyone would mistake those results

 

Speaker:00:19:08

for something that was created by a, you know, like a trained human editor.

 

Speaker:00:19:12

Like if, if you got like 30%, if, if, like a human editor gave

 

Speaker:00:19:16

you a clip that started in the middle of a sentence, you would say something's

 

Speaker:00:19:19

wrong with you. Right? But there's so many obviously wrong things,

 

Speaker:00:19:23

you know, with some of these clips. And I think that's why. So I think

 

Speaker:00:19:26

that people will start to address it. That's what I'm doing. But I really see

 

Speaker:00:19:29

as people kind of figure out, like, how to kind of actually

 

Speaker:00:19:33

get AI, not just to understand what's going on in a video, but also to

 

Speaker:00:19:37

decide what edits to make. I think you're going to see two

 

Speaker:00:19:40

distinct directions, and that's coming from my experience with software.

 

Speaker:00:19:44

So in software, you have tools that are being used to speed up

 

Speaker:00:19:48

software tasks so people who are programmers can

 

Speaker:00:19:52

now code faster because of these coding tools. And I think you're going to see

 

Speaker:00:19:54

the same thing with AI, sorry, editing tools. So those editing tools that blaze

 

Speaker:00:19:58

essentially have the equivalent of autocomplete or I think descript is probably

 

Speaker:00:20:02

the best example that I've seen of this so far, where they have, like, smart

 

Speaker:00:20:06

transitions and smart kind of layouts that'll predict

 

Speaker:00:20:09

what it is you're looking for and just kind of speed up that process. I

 

Speaker:00:20:13

think that's probably where most the most useful innovations

 

Speaker:00:20:17

are going to be in terms of AI editing. And in that sense, of all

 

Speaker:00:20:20

the companies that I've seen doing anything in this editing and creation space like

 

Speaker:00:20:24

Descript is probably way ahead of other companies on doing that.

 

Speaker:00:20:27

Like, I actually don't think that Opus is particularly interesting in

 

Speaker:00:20:31

that respect. And then what I'm trying to do, which is

 

Speaker:00:20:35

not build a tool for an editor, but rather kind of build something that's

 

Speaker:00:20:39

similar to Squarespace, where like someone who is not an editor

 

Speaker:00:20:42

and doesn't have the budget to hire an editor can still get something that's okay

 

Speaker:00:20:46

very quickly. And so in the sense that Squarespace

 

Speaker:00:20:50

lets you get a website without necessarily hiring a programmer or

 

Speaker:00:20:54

learn to program yourself, the idea was can you build

 

Speaker:00:20:58

AI that can get you something that is

 

Speaker:00:21:01

maybe not as good as what you get from a professional editor, but passable.

 

Speaker:00:21:05

Now, regarding the question of will you ever get something that'll

 

Speaker:00:21:09

reach the creative levels of an editor,

 

Speaker:00:21:13

I want to appeal to this meta sense of what is possible with AI.

 

Speaker:00:21:17

So just the high level benchmark is if you

 

Speaker:00:21:20

gave the same thing to 10 humans to do and

 

Speaker:00:21:24

they would all give you 10 different answers, then that's not a good kind

 

Speaker:00:21:28

of task to automate. And so if you're talking

 

Speaker:00:21:32

about like really fancy edits and you gave the same editing,

 

Speaker:00:21:35

you know, the same kind of like mandate to 10 different like high level

 

Speaker:00:21:39

editors, and if you got like very different

 

Speaker:00:21:42

responses back, that's probably not something you can edit. And that's why,

 

Speaker:00:21:46

you know, I struggle to see how you could create like edits of the level

 

Speaker:00:21:50

of like a Super bowl ad or like a Hollywood movie that's ever just

 

Speaker:00:21:53

generically edited by an AI. But I

 

Speaker:00:21:57

think the argument here is that a lot of more

 

Speaker:00:22:00

mundane kinds of content that people are making are not Hollywood edits. And

 

Speaker:00:22:04

the edits that you're making aren't like that creative. And so

 

Speaker:00:22:08

there's a lot of this kind of like mid level content for which

 

Speaker:00:22:12

there's an obvious like answer of like where does the recording start, where does it

 

Speaker:00:22:15

end? And those are tasks that are very, very much automatable.

 

Speaker:00:22:19

Because if it's like 10 people would all look at the same thing and say,

 

Speaker:00:22:22

yeah, the right thing to do is start here, start there, do this, do that,

 

Speaker:00:22:26

then you could imagine automating that.

 

Speaker:00:22:30

And the goal with what I was looking for is finding this subset

 

Speaker:00:22:33

of editing tasks that fit those cred that category of

 

Speaker:00:22:37

kind of things. So it's like, you know,

 

Speaker:00:22:41

I would never imagine an AI like just coming up with like a really great

 

Speaker:00:22:44

super bowl ad, but most people aren't creating super

 

Speaker:00:22:48

bowl ads, if that makes sense. That is very, very true.

 

Speaker:00:22:52

So, all right. We are chatting with Sam Bhattacharya. He

 

Speaker:00:22:56

is the CEO of Katana Video. You can learn more at

 

Speaker:00:22:59

Katana Video. We've also got a LinkedIn

 

Speaker:00:23:03

connection for Sam, so if you want to learn more about him and some of

 

Speaker:00:23:06

the other places he's worked and the things that he's up to, you can follow

 

Speaker:00:23:09

him there. Sam, before we let you go, we always like to ask folks a

 

Speaker:00:23:11

few questions about the space in general. Now, our show usually

 

Speaker:00:23:15

focuses more on podcasters. You're more of the content

 

Speaker:00:23:19

space where this isn't just limited to podcasters. But I'm still curious.

 

Speaker:00:23:23

Is there something else in the podcasting space where you would like

 

Speaker:00:23:26

to see improvement made or have somebody

 

Speaker:00:23:31

work on solving problems there?

 

Speaker:00:23:34

I don't know. I'm fundamentally, instead of prescriptive, I'm

 

Speaker:00:23:38

very descriptive in the sense that I don't like, imagine, like, this

 

Speaker:00:23:42

is how things should be done for how people are making content. I just accept

 

Speaker:00:23:45

that people are making content as how do you fix problems that

 

Speaker:00:23:48

exist? I see a lot of debate on, like,

 

Speaker:00:23:52

audio versus video, and at some point I kind

 

Speaker:00:23:56

of get that there's this mix and merge of media, and

 

Speaker:00:24:00

I see that there's a lot of people with opinions, and maybe this is just

 

Speaker:00:24:04

me coming with, you know, very little experience in the, in this

 

Speaker:00:24:07

industry up to date. So just let people make content like, you know,

 

Speaker:00:24:11

people. If there's like this mix between, like, show and podcast, like, I

 

Speaker:00:24:15

don't, I don't have strong opinions. Just, like, let people do what they want to

 

Speaker:00:24:18

do. You know, call it a podcast if you want. Don't call it a podcast

 

Speaker:00:24:21

if you don't want. Use the platforms you want to. I just, you know,

 

Speaker:00:24:25

I, I see opinions from people who are more

 

Speaker:00:24:28

experienced than I am in this space. And like, I, you know, it almost like

 

Speaker:00:24:32

I empathize in that I have my own crotchety opinions in the space of, like,

 

Speaker:00:24:36

programming and whatnot. But just, I don't, I don't get why people get so

 

Speaker:00:24:40

fussed about, like, you know, the direction of content giving. It's all kind of

 

Speaker:00:24:43

like mixing in this grab bag of, like, what does content even mean at this

 

Speaker:00:24:47

point? Yeah, if it's useful, if it's valuable, if somebody else enjoys it.

 

Speaker:00:24:51

Who cares what you call it? Just put it out there and let people access

 

Speaker:00:24:53

it. What about, is there any tech on

 

Speaker:00:24:57

your wish list, whether it's for content creation or for the,

 

Speaker:00:25:01

you know, editing process, something that either is out there that you want to get

 

Speaker:00:25:05

your hands on or something that has yet to be made that would be useful

 

Speaker:00:25:09

for you. Well, I mean, I, I'm kind of building the

 

Speaker:00:25:12

thing that I want to work, right? Like, so I think

 

Speaker:00:25:18

the, the. The thing that frustrates me most about tools

 

Speaker:00:25:21

like Opus is that it, it doesn't

 

Speaker:00:25:25

have, like, built in quality control. Right? Like, you'll give it

 

Speaker:00:25:29

a video and it'll give you back 30 clips, and you have

 

Speaker:00:25:33

to still go through and curate which ones are obviously

 

Speaker:00:25:37

good and obviously bad. And I kind of wish that you could have some kind

 

Speaker:00:25:39

of quality control where at this point, AI is smart enough, it should be

 

Speaker:00:25:43

smart enough. And that's what I'm working on to make sure that,

 

Speaker:00:25:46

okay, not Every show has 30 clips that are worth surfacing. So surface the

 

Speaker:00:25:50

ones that are actually with surfacing, even if it's not like 30, right. Like, if

 

Speaker:00:25:54

it's. If I only have like eight moments that are worth sharing, give me those

 

Speaker:00:25:57

eight moments, but make me make sure that those eight moments are actually like, you

 

Speaker:00:26:00

know, good or at least passable. Right? Like, I think we

 

Speaker:00:26:04

haven't even gotten past this basic filter of like, you know, like, there's

 

Speaker:00:26:08

like, artistic creativity. We can all disagree on, like, what constitutes good, but

 

Speaker:00:26:11

there's still a lot of things where people, the results are just obviously bad. And

 

Speaker:00:26:15

it's like, let's focus on filtering those out first,

 

Speaker:00:26:20

then we can have an argument on what's good. All right? And

 

Speaker:00:26:24

then lastly, are there any podcasts or. I'm going to expand

 

Speaker:00:26:27

this. Are there other content creators that you are following

 

Speaker:00:26:31

religiously that you want to talk about?

 

Speaker:00:26:37

I have come to realize that I have a very different information

 

Speaker:00:26:41

diet from a lot of people. I was at a podcasting conference called

 

Speaker:00:26:45

podfests earlier this year, and they mentioned four different shows and

 

Speaker:00:26:49

podcasts. And two of them, everyone raised their hand except me. And

 

Speaker:00:26:52

then the third, I was the only who raised my hand. Okay.

 

Speaker:00:26:56

Just some random stuff that I like. So one is,

 

Speaker:00:27:00

I follow a lot of AI stuff. So there's one podcaster called Dwarkesh

 

Speaker:00:27:04

Patel. He's, you know, some very smart CS

 

Speaker:00:27:07

guy that decided, I'm going to go into podcasting and interviews, like the CEO of

 

Speaker:00:27:11

Microsoft, and they're talking about the future of AI. And you listen to that

 

Speaker:00:27:15

stuff and it's just a very, very different kind of view of the world of

 

Speaker:00:27:18

like, assuming that the whole world is going to be automated. They're talking about, like,

 

Speaker:00:27:22

you. Are we going to have AI only companies, it's

 

Speaker:00:27:26

like. And then like the actual conversations from like real world people

 

Speaker:00:27:30

is very different. Or, you know, AI is just like a tool. Like,

 

Speaker:00:27:34

AI just means chat, GPT. I don't know, it's just very different information diets.

 

Speaker:00:27:38

And I'm sitting in the middle, I'm like, I don't know, like, just people have

 

Speaker:00:27:42

different information diets. That, that kind of feeds into their

 

Speaker:00:27:46

worldview, I guess, but just trying to make sense of that. But,

 

Speaker:00:27:49

you know, those are some of the things I like. I also just have like

 

Speaker:00:27:53

a hodgepodge of like, I like history. So I have some very random, like, history

 

Speaker:00:27:56

podcasts that I listen to, but it's all very nerdy, if that

 

Speaker:00:28:00

makes sense. That's okay. That's. I mean, I think that's part of what makes podcasts

 

Speaker:00:28:04

great, is that it allows people to really get as nerdy as they want to

 

Speaker:00:28:06

on a topic that interests them. And, you know, they're not just forced to consume

 

Speaker:00:28:10

what is available. So the nerdier the better.

 

Speaker:00:28:15

Yeah, exactly. You know, it's like some retired professor

 

Speaker:00:28:19

who has some time and has decided, you know, I'm going to do a podcast

 

Speaker:00:28:21

instead of doing lectures. Like, that's great and it's free and I love it.

 

Speaker:00:28:25

So thank you for making those podcasts. Even if it has, like,

 

Speaker:00:28:29

even if I'm one of the only, like 3K subscribers they have. I mean, 3K

 

Speaker:00:28:32

is not a, you know, number to sneeze at, but still, it's not like when

 

Speaker:00:28:36

I'm talking About like Darius E.O. kind of

 

Speaker:00:28:40

popularity, but there's, there's people who listen to those things and I'm one of those

 

Speaker:00:28:43

people. So. I'm sure

 

Speaker:00:28:46

the creators are happy to hear that. And we'll try to put links to all

 

Speaker:00:28:50

the ones that you did mention here in the show notes for anybody else who

 

Speaker:00:28:53

wants to check them out. Sam Bhattacharya, the CEO

 

Speaker:00:28:56

of Katana Video. Thank you for joining us.

 

Speaker:00:29:00

Thank you for inviting me. Thanks for joining us. Today

 

Speaker:00:29:04

on Podcasting Tech, there are links to all the hardware and

 

Speaker:00:29:07

software that help power our guest customers. Content and podcasting

 

Speaker:00:29:11

tech available in the show notes and on our website at

 

Speaker:00:29:14

podcastingtech. Com. You can also subscribe to the show on your

 

Speaker:00:29:18

favorite platform, connect with us on social media, and even leave a rating and review

 

Speaker:00:29:21

while you're there. Thanks and we'll see you next time on

 

Speaker:00:29:25

Podcasting Tech.