July 22, 2025

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

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

Are you frustrated with the headaches of editing Zoom podcast recordings? Wish you could turn raw footage into polished video podcasts—without hours of tedious work or a big budget? This episode is for you.

In this episode, host Mathew Passy sits down with Sam Bhattacharyya, CEO of Katana Video, to explore how AI is transforming video podcast editing—especially for creators working with Zoom recordings.

Whether you’re a seasoned podcaster or just starting out, you’ll learn how Katana Video’s AI-powered editing brings pro-quality video podcasts within anyone’s reach—no editing background required. Check out this episode to hear Sam’s story, understand common editing pitfalls, and get actionable strategies for making your next podcast sound and look its best, fast.


Episode Highlights:


Sam’s Journey to Video Tech Innovation: Sam recounts his unconventional career path, starting with building an e-learning platform for West African students, and how his early work in video compression and AI-powered streaming tech led to forming partnerships with Streamyard and eventually, the launch of Katana Video.  [00:01:11]


The Real Problem with Editing Zoom Podcasts: Why so many podcasters still use Zoom, despite its limitations, the challenges editors face with Zoom’s single-track recordings and how Katana Video bridges the gap: using AI to separate speakers, automate camera angle switching, add name tags, and create professional-grade visuals with minimal effort. [00:07:36]


The Future of AI in Video Editing: Sam’s perspective on the current state of AI tools like Opus and Descript, and why true “creative” edits are still a human domain, but automation can handle repetitive, standardized editing tasks. [00:17:53]

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Trends & Tech Wishlist for Podcasters: Sam encourages creators to focus less on terminology and more on making content accessible and valuable, and his wish for smarter AI quality control, so creators only get surfaced with high-value, relevant clips. [00:23:17]


Resources & Links:


Podcast Recommendations from Sam:


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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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for achieving a professional sound and appearance. I'm Matthew

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

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We'll help you cut through the noise and offer guidance on software and hardware

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that can elevate the quality of your show. Tune in weekly for

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insightful interviews with tech creators, behind the scenes studio tours and

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strategies for podcasting Success. Head to podcastingtech.com

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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

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fundamental way trained to predict what edits you would make in

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video content. And that comes from the fact that these

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large language model labs like OpenAI and

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

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editors to build the data sets. It goes back to

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

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like opus from using ChatGPT as a way of

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

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use a tool like OPUS Clips or even like,

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

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

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

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

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

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

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

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

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

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

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

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

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software tasks so people who are programmers can

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

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

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

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

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transitions and smart kind of layouts that'll predict

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

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think that's probably where most the most useful innovations

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

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

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

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

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

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

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

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

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very quickly. And so in the sense that Squarespace

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lets you get a website without necessarily hiring a programmer or

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learn to program yourself, the idea was can you build

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AI that can get you something that is

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

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

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reach the creative levels of an editor,

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

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So just the high level benchmark is if you

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gave the same thing to 10 humans to do and

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

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

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

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

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editors, and if you got like very different

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

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

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

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generically edited by an AI. But I

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think the argument here is that a lot of more

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

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

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

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

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

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

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

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then you could imagine automating that.

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

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of editing tasks that fit those cred that category of

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

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

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

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

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

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

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Katana Video. We've also got a LinkedIn

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

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

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

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

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

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

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

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to see improvement made or have somebody

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work on solving problems there?

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

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

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

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

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

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audio versus video, and at some point I kind

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

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

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

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

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

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

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

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

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I, I see opinions from people who are more

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

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

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

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

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

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

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

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it. What about, is there any tech on

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

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

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

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

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

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

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like Opus is that it, it doesn't

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

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

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to still go through and curate which ones are obviously

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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this. Are there other content creators that you are following

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religiously that you want to talk about?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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what is available. So the nerdier the better.

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

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

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

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

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

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

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

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

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people. So. I'm sure

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

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

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wants to check them out. Sam Bhattacharya, the CEO

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of Katana Video. Thank you for joining us.

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

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

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software that help power our guest customers. Content and podcasting

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tech available in the show notes and on our website at

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

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

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

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Podcasting Tech.