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The following is a conversation all about FFMPEG and VLC with Jean Baptiste Kempf and Kieran Cunha. FFMPEG is an open source software system that is the invisible backbone behind YouTube, Netflix, Chrome, VLC, Discord and basically every platform that touches video or audio on the Internet. It can decode, encode, transcode, stream and play almost any video or audio format ever created. To me it is one of the most incredible software systems ever developed and it's all done by volunteers. VLC is also a legendary piece of software. It is an open source media player that plays basically anything you throw at it. Any format, any platform, no ads, no tracking. It has been downloaded over 6 billion times and again, for me it has been one of my favorite pieces of software ever with the most legendary logo, which I of course had to honor in this conversation by wearing the VLC traffic cone hat the whole time. So again, above all else, thank you to the incredible volunteer engineers who put their heart and soul into this code that has been used and loved by billions of people. Thank you. And about the two great engineers and human beings I'm talking to in this episode. Jean Baptiste is the President of Videolan and is a key figure behind VLC and FFmpeg. Kieran is a longtime codec engineer, FFMPEG contributor, and the man behind the now infamous FFMPEG account on Twitter X that I recommend everybody follow for the memes and for the unapologetic celebration of open source and great low level software engineering. Let me also say that it's inspiring and humbling that so much of modern civilization rests on software built by people who are not chasing fame or money, but are obsessed with the craft of engineering. We live in a world where billions of people consume video every day without ever thinking about the invisible machinery underneath it. But that machinery matters. Open source infrastructure matters. It is one of the great examples of human beings quietly collaborating across borders to build something useful, durable and elegant for the rest of us. And so this conversation is not just about codecs and media pipelines. It is also about the deeper spirit of engineering and generosity that makes projects like FFMPEG possible. Again, I can never say it enough. Thank you. And now a quick few second mention of a sponsor. Check them out in the description or@lexfriedman.com sponsors. It is in fact the best way to support this podcast. We got Laredin for understanding how AI is used in your business. Blitzy for code generation and large code bases. BetterHelp for mental health, Fin for customer service, AI Agents element for electrolytes and perplexity for curiosity driven knowledge exploration. Choose wisely my friends. And now onto the full lotteries. I try to make them interesting, but if you skip, please still check out the sponsors. I enjoy their stuff. Maybe you will too. To get in touch with me for whatever reason, go to lexfreeman.com contact all right, let's go. This episode is brought to you by Laradin, a platform that helps organizations understand how AI is being used across their business and what it's doing for productivity and performance. There really is a transformation happening at the individual developer level. Many people switch from writing, let's say 50%, 40%, 30% of their code, where the rest is written by AI, they switch to basically where it's 0% of code written by hand via so called agentic engineering. And so we could see that in the individual developers. Now the question is, when you scale that to 2, 3, 4, 5, 100 developers, what does that look like? 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When you have a huge number of agents, huge company, huge code base, how do you then seen at the big picture code base level, have the growth and development, the evolution of that code base, where a very large percentage of that code base is continuously worked on autonomously. The question is, when you have a large code base that already delivers value, that already sells stuff, that already has huge number of customers, how do you then use agentic engineering to continue adding features, continue improving, continuing the usual kind of development, with the testing, with the security, all that kind of stuff, how do you do that without messing stuff up, without filling up your code base with AI slop and nevertheless doing it? So for the most part autonomously, not fully autonomously, semi autonomously, but majority of the code is written autonomously. That's what Blitzy specializes in the future of autonomous software development is here. Learn more or speak to a member of their team@bitzy.com Lex that's blitzy.com Lex this episode is also brought to you by BetterHelp. Spelled H E L P help moving away from AI to the human the human mind is still to this day out of reach of our understanding. From the perspective of creating intelligence. There are so many intricate psychological complexities to the mind, which I think attributes to what makes humans incredibly special. But those complexities get all tangled up in ways that are counterproductive and so they need to be untangled. And I'm a big fan of talk therapy as a set of tools, as a methodology for untangling the complexities of the human mind. The easy, discreet, affordable way of doing that is betterhelp. That's why I keep recommending it. It's a really good way to take your first steps. If you haven't done talk therapy, get a licensed professional therapist in under 48 hours. BetterHelp makes it super easy. Check them out at betterhelp.com lex and save in your first month. That's betterhelp.com lex this episode is also brought to you by Fin, the number one AI agent for customer service. As I mentioned already about humans, humans are complicated and customer service is ultimately about looking at each individual human and really listening. So I try to do with the podcast to truly listen to each individual person, whether we're talking about a super technical topic or we're talking about the big questions of the human condition. And sometimes when you're talking about the details of the technical topic underneath there, you can feel the presence of the big picture questions of the human condition. All of those complexities peek out of the shallow surface interactions that at first glance you might think customer service interaction is, but really we're trying to solve the big problems of the human condition and specific to that individual person. So customer service is a really hard problem, but it's a really important one. And that's what Fin specializes in. How to leverage, how to use, how to utilize AI in the task of customer service. Go to Fin AI Lex to learn more about transforming your customer service and scaling your support team. That's Fin AI Lex. This episode is also brought to you by Element, my daily zero sugar and delicious electrolyte mix. I'm traveling to parts of the world that at first feel, at first experience are so foreign that they border on the uncomfortable. All new things can be uncomfortable and for me, Element on the health side, psychological side are a source of comfort. They're a reminder of home. It's a place where I'm healthiest. It's a place where I have everything sort of in line. I'm exercising, running every day, whether that's jiu jitsu or running or lifting. I am on a good diet. I'm fasting a lot. And for all of that, you need the electrolytes. That element provides sodium, potassium, magnesium. Really if you get the electrolytes right, everything else is a little bit easier. You don't get the headaches, you don't get just the weird iffy feeling when you're fasting. Favorite flavor, as always, I should mention, because I love it so much, is watermelon Salt. Get a free 8 Calm sample pack with any purchase. Try it@drinkelement.com Lex this is the Lex Friedman podcast to support it. Please check out our sponsors in the description where you can also find links to contact me, ask questions, give feedback and so on. And now dear friends, here's Jean Baptiste Kempf and Kieran Cunha. So the legend goes, VLC can open everything. What's the weirdest thing that you know that it can open?
B
You know there is a ton of people who are using VLC to record VHS videos, right? Like it's just like you plug it with a capture card and you can basically record VHS video.
A
Well, how does that work?
B
Basically it's in all those type of capture card where you can put a peritel in or RGA and you put that. And actually VLC can play those type of cards and there is a module which allows to control directly those VCR camcorders. We support DVD audios lately, right? We spent the summer working on DVD audio support and like there is no, no one's making any DVD audio support. There is a custom encryption schemes.
C
What about Lucasfilm?
B
Oh yeah. And there is of course all the weird codecs support game codecs supported by
C
ffmpeg1 Star wars video game. The first 10 second opening sequence, someone has gone and implemented that and make sure that's bit exact on one disc that existed at one time of one little sequence in the game.
B
And then funnily there was a. At one videoland conference we made a competition to make the weirdest and most horrible file ever and see if VLC could play it.
A
What did it end up being? What's the file?
B
It was an MKV file made by Derek which each of the frame was changing resolution, aspect ratio, rotation and it was like did it work? Yes. And there was Another one where the whole video was actually animated subtitles, right? Ssa. Right. So remember that? Yeah. This one was. So each frame was a black frame, but on top of that there was a subtitle that was animated.
C
For each frame there was a file that's a valid zip and a valid MP3 at the same time or something like that. So.
B
So yeah, we'd made a competition of
A
stupid files and it worked. It opened all of the stupid files.
B
Yes.
A
By the way, for people who are not familiar, I am wearing a hat. Would it be fair to say this is the best, worst logo of all time? The cone.
B
Yeah. By far. Right. The logo of VLC is so iconic, right? Like we are a team with a small number of people and the icon is known everywhere. I go to middle of nowhere in India or in China, people know the cone, right? And 25% of the website traffic that comes to our main website is cone player, right? So so many people don't know vlt, right? They know the cone player.
A
That's the thing that Google force. Cone player.
B
Yeah, they go on Google and they put cone player and they download vlc. Right? So that's iconic. And once we tried to change it as a joke, right? We said it was going to be a type of caterpillar construction and we said that during April 1st and we had around 10,000 emails saying, no, don't change the logo, and so on, right? So it's so iconic, right? It's so distinctive, right? If you want to do a video player, you're going to put a play button on a TV, right? And that's a YouTube. YouTube logo, right? It's an original. This one is orange, right? Very bright. And it's weird and it's ridiculous and
A
it's absurd and it's hilarious. It becomes meme and meme becomes culture
B
and you keep it and you know about it. And you know that in 20 years, like you still have going to have the Kuns and remember. Oh yeah, that was a video player.
A
Yeah. And we'll talk about, you know, the mission of FFmpeg being a kind of the archival aspect of it. So you can think about thousand years from now, we'll have all these videos that only VLC can open. Human civilization has already destroyed itself multiple times. And the only thing that will remain is this like, you know, the cockroaches will be crawling around and it'll be the VLC logo with some of the archival footage that VLC can open and the aliens will show up and they'll press Play and they'll get to see.
B
Really hope so. Right. But there is also so many memes where people say, well, I'm sure I can put a pancake inside my DVD drive and VLC will play it.
A
Can they?
B
No, we tried. It doesn't. But we actually have a video of us trying that didn't work.
A
A codec for physical reality. I don't know what that would even look like.
B
There was a guy who did that, right? He printed a small cone, right? Like the ones we distribute as goodies. And inside he put an RFID chip, which was his way of playing a movie, right? And so he put this on RFID player, and when he put that, it was playing like the last Star wars and so on. So instead of having, like, DVD boxes, he had like, VLC cones all around and he plugged that and there was like, physical objects.
A
So the thing that we're talking about is everything around video codecs, video encoding, video decoding, video streaming, video player, client that I'm wearing on my head, the entire ecosystem enabling free media. We'll talk about FFmpeg, we'll talk about Video Land, VLC and all the other incredible video technology that is used probably by billions of people. So, jb, you're the lead developer behind the legendary VLC player Kieran, amongst many other things, your lead developer behind the legendary FFMPEG handle on Twitter. And both of you have spicy opinions, I would say. So today I want to talk about FFMPEG and VLC for context, for people who are not aware, and I'm sure basically everybody listening to this have used these two technologies probably regularly without knowing it. So FFMPEG analyzed basically most video on the Internet, including YouTube, Netflix, Chrome, Firefox, of course, VLC and countless other video platforms. It is estimated that over 90% of video processing workflows online and offline involve FFmpeg. VLC has been downloaded at least 6.5 billion times, but likely that number, because it's impossible to really count. The number is much higher than that. Virtually any operating system supports virtually any media format. The limitation being it can't open pancakes. So can we just lay out some of the basics to help people understand what's involved in all of this? So when we press play on a video player like vlc, what happens? How does it go from the file or the stream to the pixels on the screen and the sound on the speaker? What are the big stages to be aware of?
B
So there are several stages, right? The first stage is to get from an address, right? Which is the CAB type of URL to give you a byte of streams. Right. So this would be, for example, HTTP file dvd. Right. You give the pass to the media and give you a stream of data.
C
The stream needs to be cut up by what's known as the container, the demultiplexer or demux. We'll try and keep the jargon light throughout this, but it needs to go and start demarcating video and audio frame. So it just gets data from the operating system blocks at the time and needs to start cutting these frames up into compressed data. It then needs to start doing simple parsing of the video frames, mainly to figure out whether that codec is GPU decodable or needs to fall back to software. We're very sort of used to assuming the GPU will play all of these things. There'll be hardware acceleration. I think it's up to 45% of files are not GPU decodable. So these need to be probed, they need to be detected. There can be variants of a given codec, some of which are decodable on the gpu. Different vendors of GPU might have different capabilities, so those need to be detected. So if it's GPU capable, you pass it through to the GPU black box. Now, if there's a software fallback, that means in the beginning is to first do de entropy coding, so removing the mathematical coding of the bitstream. So this uses capabilities such as Hoffman coding or arithmetic coding to actually decompress the mathematical layer of the bitstream. We then need to start reading the syntax elements for intra prediction. So intra prediction are like still images of the video. So your iframes. So this works and operates in the spatial domain. So you do your intra prediction, spatial domain, you have a residual because your prediction isn't quite matching that of reality. So you've made a prediction, but then there's a little bit left, and that's what's known as the residual. This is stored in the frequency domain and these are quantized to decompound their space. We then need to do the inverse transform to bring them back to the spatial domain and apply these residuals.
A
So a lot of the process of decoding is this thing is compressed.
C
Yes, yes.
A
And you have to predict the highest quality thing that's supposed to go there. Iframe is the best representation you have spatially, and then there's a lot of temporal compression that can happen depending on the codec. And then you're predicting, you're predicting what the reality that was captured in this Rawest form.
C
Yeah.
B
Because what people don't realize is that the compression on video and audio is 100 times, right? Like people don't realize how compressed we do, right? For audio you move, you compress by. When you go from normal audio to MP3, you compress by 10 times, right? When you move to video you need 100 times, 200 times, right? So you need to remove all the details, but that you don't care about because all the compressions that we do, and that's very important, people forget about that is to be viewed by humans, right? So all the codecs either for audio mimic basically how your ear works, right? And a lot of things about like the response on the ear and same for your eyes, right? And so for example, on video we don't work on rgb, right? Everyone expect to work in rgb, we don't, right. We move to yuv, which is basically one is luminance brightness and the other are colors. And this matches your eyes where inside your eyes you have the cones and the buttons, right? Some of them look on brightness and the other on colors, right? So we need to compress a lot. And so we need to degrade. But in order to degrade, we need to match the human perception. And this is why it's so difficult. And then we need to use the maximum power, mathematical power, very complex technologies. We move to the Frankie domain, as Kiran said, we do a ton of de quantizing and in order to get the best compression, but it still looks good.
A
You're trying to compress in order to maximize the highest quality thing for human perception.
B
That is correct. And that is correct. And this is very important, right? Compression is not like a zip, right? A zip. You have data in, you get data out, right? And you try with all the zip compression to arrive with the limit. Here we are degrading the signal, right? And so we need to degrade both the audio and the video signal in the best way possible. And we can do that, but it involves first a lot of theoretical knowledge about how it works, the eye works, but a lot of mathematical change, a lot of mathematical tricks, right? For example, when you move to RGB and you go to yuv, for example, what we do very often is that we scale down the resolution of the color compared to the brightness. And most of the time and just this, without compression, it divides the size by two. But most people don't see it, right? And so on and so on, right? And then you go to very complex mathematical change. So of course Fourier transform, which de Facto are not Fourier transformed. They are like discrete cosineus transform. But that's the same idea. So frequency domain, we split the video by blocks, right? So that's why when it's wrongly decoded, you see those blocks and badly encoded, you see those blocks and so on to arrive to compression state that are insanely high, right? And each generation of the codec is like 30% less for the same quality, right. And this requires amount of power, of computational power that are huge.
C
No, you should elaborate. It's 30% better, but an order of magnitude, perhaps even two orders of magnitude more compression power. That's the big difference.
A
What do you mean by compression power?
C
So CPU power to achieve that level of compression.
A
So you have to be able to leverage the CPU and sometimes gpu like you mentioned. And then we should mention that a lot of this programming is done at the lowest possible stack, whether it's C and of course, as the legendary Twitter handle re emphasizes over and over, a lot of assembly.
B
So what happens is globally is that you have an address, right? Which gives you with the operating system a stream of bytes, a stream of data, right? And this is the first step. And the second step arise with demuxing where you're going to separate audio, audio, video, subtitle in type of different tracks, and then on each of those tracks you're going to decompress them, decode them, either audio with an audio codec, video to video codec and subtitle to subtitle codec. And once you've decompressed those type of things, you have raw images, raw. And then you're going to talk with your graphic card in your screen and display that. And same for the audio. You're going to talk to your audio card, which then is going to go in analog to your audio, audio speakers
C
and everything we've just said in the past couple of minutes. Every sentence is someone's lifetime's work. There are books about every sentence. So the level of complexity in many cases is inordinate. You know, every sentence has thousands of people working on this in industry as a whole, books written about it. So there's a lot of detail, there's a lot of subtleties, there's a lot of both academic and practical realities, both of which matter.
A
We mentioned codecs, but I don't think you mentioned containers. So what's the actual containers for some of the stuff we're talking about? So people are familiar with MP4 mov, MKV. So anyway, what are containers versus the thing that goes inside?
B
So the Container is what we call also the muxer, right? When I say demuxing, it means decontanizing, right? So actually if you look, mux means multiplexer and demultiplexer, right? Mux and demux are those and same. A codec is actually coder decoder, right? And so containers are this collection of multiple tracks, right? So it's what normal people call the file format, but it's a bit more subtle than that. But the most known one of course is MP4. But when I started it was AVI, right? AVI was the video format from Microsoft and Moov Mov, which became MP4 was a format from Apple. In the open source community, one of the person that is still active on videoland is called Steve Lohm and started this Matroska format which is like a bit more complex and more feature proof and there are so many others.
A
So I mean it's a pretty common thing and maybe it'll even happen in this conversation that people confuse container and the codec, right? So confuse MP4 and H264 for example. Is that a horrible violation?
B
No, it's not. Because technically the name of H.264 is MPEG4 part 10. Because MPEG4 is actually a meta specification which has several things in it, right? There is the part two. So there is like audio codecs, right? AAC, de facto with MP4 audio something. There is actually several video codecs right inside the MPEG4 specification. One of them is MPEG4 part 10, called also AVC, called also H264, right? So it's completely the fault of the industry to, to. To. To make things difficult to understand. So that's very difficult. So that people then don't understand why sometimes you talk about MPEG4 part 10 where you mean H.264 and why it's not MP4.
A
So you can technically shove in all kinds of different codecs inside containers and horrible. So.
C
But broadly speaking, though MP4 is understood to generally be H264 plus AAC audio 99% of the time. That's that and that the rest are de minimis. The small effects, you know, edge effects really compared to that. So it's not the end of the world. There are people who do get annoyed by that. But also in reality, something like VLC, just to point out the file may say MP4, but it may be something completely different. And that's one of the challenges both FFMPEG and VLC have is the real world is a Completely different place to a three letter file format.
B
And this is very important to say, right? Like for example, In VLC and FFmpeg, we discard the file format, right? We look into the file to understand what's in it. Because so many people, like they say, oh, it's a video, which must be MP4, but technically it's an MOV, or maybe it's a MKV, right? So we analyze in real time everything that we have and we don't trust the format.
A
So what information does the fact that it's MP4 give you?
B
It helps, right? It gives you a hint, right? Just like, oh, it's finished by MP4. I will start first by opening, probing it with the MP4 container demuxer to see. Well, it should be that, but I don't trust it. And if I'm lost, I say, okay, maybe I'm going to try it. So it bumps the priority of the module.
A
So how do you get to. Just to take a bit of a tangent there. You know, the dumb thing is if you try the MP4, but it turns out it's a different codec than you would have expected. Most players just break there.
B
Yes, yes.
A
So how do you not break? There's just a. Philosophically, I'm sure there's a bunch of stumbling blocks along the way where you. It's easy to just break and stop, freak out. That's it. How does VLC not.
B
This is why VLC is popular, but the reason is because actually VLC is just a client of a streaming solution called VideoLAN from very long time ago, from the late 90s. And when you're playing video which are on UDP, right, in network, they might be damaged. So you don't trust your inputs. And this is very important in today's security is that you don't trust your inputs. So everything in VLC is prepared to work with broken files. And it's a philosophical idea from the beginning and everything is engineered into that and it's a culture, right? And so, for example, and VLC became very popular on that because a long time ago when people were pirating content, which they do a lot less today
A
and none of us ever have no,
B
of course not the metadata to play some files, like avi is a diagram at the end of the file, right? And when you're downloading you don't have that. Right. So VLC was just like, hey, this file is broken, but I'm still going to try to interpret it. And this was very useful.
A
We hinted at the awesomeness of the various different stages, we hinted at the awesomeness of codecs, the depth and the richness and the complexity of everything involved there. Let's try to define what is a video codec, what's involved there? What does it mean to compress something? You already started to hint at it, but can we elaborate a little bit more?
C
So there's a huge amount of redundancy in any video, both spatial and temporal. And the point of any video codec is to remove this redundant data, use mathematical properties as part of this reduction process. So more often than not, using several orders of magnitude more compute to compress, because that's more costly versus both costly both financially and in CPU resources versus the decompression. So it's asymmetric in that respect. Often the case, because compression is done once, but there could be lots of viewers of another file. So to take that information and Compress it by 100x200x, removing redundant information and using mathematical properties to make that small, but also have properties such as error resilience. So as JB suggested, VLC in the beginning was used to play UDP network feeds, and UDP network feeds lose packets. And so some of the design goals of a codec is also to be recoverable. You need to actually be able to join a stream. It's not necessarily a file you need to join. Get on the decoding process and start decoding.
B
And to give a more image to people who are not familiar, right? Like when you're going to see any type of movie, right? You're going to see the camera is going to pan, right? And travel. And you realize that, for example, all the background is the same for a minute, right? Or 30 seconds, right? So you can reuse the cloud that you see on the background. You can reuse that from a frame to another, right? And so it's gets. The more, the more memory you have, the more power, the more comparisons you can make, right? And so the more compressed you can be. And most of the modern codecs are basically doing that.
A
So just to make it even more explicit, so what is video? Video is a bunch of pixels off an RGB3 values. And you have a grid of pixels and you have, let's say 24 or 30 or 60 frames a second. And you just have all these pixels repeating and showing different stuff 30 times a second. And so the question, the philosophical, the technical question is how can I compress all of that?
B
Store all that at 100x or 1000x, right?
A
1000x.
B
The target is 1000x, right.
A
And the goal is, when you say redundancy, what is redundant? Meaning stuff at best that humans wouldn't notice if it was missing.
B
So for example, you have a picture of a cloud, right? And from the next frame they're still going to be the same cloud. So it's redundant. You could just put it once and not do it, right? Or you have a black background behind me, for example. The black is the same on the whole picture. So you can say, well, you know, in this picture, take the pixels that you have on the top left and the one on the top right. I'm not going to give the value, I'm just going to tell you it's the same at the top left. And then you can say for frame one, reuse something from the previous frame or the previous, previous frame and so on and so on, right? So you could basically it's unlimited, but then it's limited in terms of memory or in terms of compute power. Because for example, if you need to Compare pixels on 200 frames in the 4K resolutions, it's a huge amount of compute.
A
And then when you're showing it, you have to do the decompress of all of that. So is it the Kodak has the encoding and the decoding is a coupled process that you're developing?
B
Yes, exactly right. And those are two different trade offs, right? Are you going to compress more, but then it might be more difficult to decode? Are you going to make it a codec that is more complex to encode and easier to decode? Are you going to make a codec that is easier to encode? Because you need to be fast, but then the client side, the player is going to spend more time. That's why you have so many different types of codecs is that it's not always easy. And to make it even more complex, modern codecs like AV1, AV2 or VVC are actually not codecs. They are a collection of tools, right? There are multiple tools, multiple codecs in the same codec to depending on the image, get the more compression.
C
So just to elaborate, codecs like AV1 VVC have a much wide, have a wide audience. It could be a screen, share content, it could be video, it could be animation. All of these require different coding tools. So what happens these days is a collection of tools are put in and called AV1 and called AV2, called EVC to allow for different use cases. So you may be on zoom and sharing your PowerPoint. And then you need to show the audience a video that codec needs to start changing its toolset depending on the content to compress in a different way.
A
And like you said, there's a bunch of incredible engineers behind each part of that. Each part of the tools that make up AV1, for example.
C
Sure.
A
So we've kind of danced around it. We talked about VLC, but the logo, the hat. Let's talk about FFmpeg. What is FFmpeg exactly?
B
FFMPEG is basically the low level libraries for codec. So compressions and decompression, muxers and demuxers and filters. It's the core is this. And then you have several tools which allow you to create a type of pipeline to process any type of video files. And it's used as a library. Absolutely. Inside everything from VLC to Chrome to your smart TVs to basically any video that you see online. You usually use FFMPEG and FFMPEG in it has all those type of tools and sometimes depend on other libraries like x264, libvpx and others. Right. So it's really now the de facto tool to process images.
C
From a philosophical level, I think it's incredible that your home videos, your grandmother's home videos and trillion dollar corporations effectively are on a level playing field using the same technology stack. It wouldn't be a surprise. You know, these big Companies just have 3000 line FFmpeg commands. There are some that use the API, but there are some that just have long command lines.
A
So yeah, there's a bunch of tools like literally command line tool, ffmpeg, of course, FF Probe, there's libraries, libavcodec, LIBAV format, LIBAV filter. But the FFMPEG on the command line is like legendary because you can cut, there's so many parameters, you can customize everything to help.
B
It's a language, it's an actual language.
A
It's an actual. Yeah, you could think of it as a programming language.
B
Yeah, of course, I'm sure because so most of the people, they're going to take FFMPEG file in, file out and specify the format. Right? But we've seen thousands of characters and we've seen also like people like doing programming generation of command lines to make FFmpeg. There is a ton of people who are using AI to generate command lines for FFmpeg because you have no idea what it is, but you can specify so many filters right on command line. Right. So FFMPEG is this collection of toolbox for multimedia processing that everyone, everyone uses and everyone that is watching your videos are Also using, right? You're on YouTube. Well, ffmpeg on the client side. Well, your server side. On the server side, the client side is polychrome. Well, you're using FFMPEG also and you're using obs to record. Well, it's FFmpeg, right? You're using a ton of important, like big box professional boxes. Well, it's very possible that inside some part of FFMPEG is run.
A
I mean, there's like so many. Just to give people an idea, like I use FFMPEG a lot on everything, just trivial stuff like take a video, add an intro video and an outro video and fade one into the other. Like what is it called? Dip to black. Like where it dips and then shows the next video and does the same thing with audio. There's like a cross dissolve of the audio. It's a quiet. It quiets the audio and makes it loud again. And then there's a bunch of stuff like showing the captions on screen hard, like baking the captions in. You can customize the font. You can do all kinds of layering of audio and video. There's a million things. And of course all of that works like magically with basically any codec, like anything you could shove in on the audio and the video side, it works.
B
But it's like if you, if you look at, for example, you can do things that you would do with Adobe After Effects in command line on ffmpeg. Right? And it's very interesting because, for example, for images there is not such tool. There is a few tools, but not with the breadth of FFmpeg.
A
So ImageMagick has a similar kind of.
B
Yes, but you will not do some filters, complex filters. You don't have the equivalent of Photoshop in command line, right? But for video you have FFMPEG in command line.
A
Yeah, it's incredible. I mean, it's like an example of a thing when a bunch of great people get together and they get a vision and they stick by that vision for many years, which is incredible.
B
And the vision behind and the same for VLC and FFMPEG is that we make everything that is very complex, easy to use for the normal people, for everyone, right? Our goal is to make something that is insanely complex technically and make it easy to use, right? And people, they use vlc, they drop a file, they don't realize how complex the file is, but they play it. Or people put any type of thing inside FFMPEG with complex filters and it just works like magically, right? And people. And this is our mission. Right. Make very complex things.
C
We wouldn't be here and you wouldn't be here if this required, you know, a traditional television studio setup. It's tools like FFMPEG that democratize this. The podcast and streaming revolution, the YouTube revolution was caused. You know, FFMPEG was a big player in that because it democratized this technology that was once in the. In the 90s, for example, you needed equipment that cost hundreds of thousands of dollars to do compression. It was the size of a car. And now everybody has that at almost an exact level playing field. And that's something that's so remarkable, it
A
gave voice to a lot of people. And just to clarify, we say you wouldn't be here. Not the human, but the podcast.
C
Sorry, you as the.
A
Sorry, VLC did not have anything to do on the biological Creating me as a human.
B
You realize also everything move from text to images and images to video. Right. Look at social networks. Video is everywhere. It's the most powerful medium there is. Right. And when you see shorts and in reels and TikTok. Right. It's amazingly powerful to give. Video is amazing for that. Right. But the complexity is important.
A
It's what people don't realize. I mean, this is really. It gave power to the individual all across the world. It's real freedom. And I think, I can't believe it. But we still haven't mentioned the actual obvious thing for people who are not familiar, which it's open source and there's a open source community of users and developers behind it. So it's really, it's a movement. So like, we'll talk a bunch, in a bunch of different ways about the community behind it, but can you speak to the open source element? So when we say, what is FFmpeg? It's an open source project.
B
Yeah. So FFmpeg, VLC x264 videoland. Everything we do is fully open source. And for the people who don't understand how open source is, my usual analogy is about a chocolate cheesecake. Usually when you want to buy your cheesecake, you go to a bakery, they give you the cheesecake. The other one way of having a cheesecake is have your grandma give you a recipe of how to make that. When we do open source, we give you the chocolate cake and we give you the recipe to actually remake the same cake, but at the same time tell you how to build the oven and also how you're allowed to modify the recipe and resell it to someone else. And this is because software is just a very long Recipe of small instruction Computers are not very clever. They go very, very fast. So a normal program has tens of billions of instructions instead of the tens when you have your chocolate recipe. So a lot of the software industry was about selling software where you just have the final cheesecake. In open source we give you everything and that managed to get a lot of people work together, right? Because then you decide that you're going to make the best program, the best recipe for video and you create communities in FFmpeg. Since the beginning of FFmpeg, probably 2,000 to 3,000 people have contributed from the beginning, right? And then it's exactly like the Linux kernel, right? The Linux kernel has probably 10,000 people contributing everywhere and they get together well, mostly online, right? So they virtually get together to create the best tool for something. And on FFmpeg and VLC it's just like, well, this codec doesn't work. So I'm going to work on the codec and I'm going to add the support for this file inside ffmpeg. So it will be beneficial to everyone because again, we work for the greater good. We work for everyone. And that is what open source is.
A
And we should mention depending on the licensing, you could probably build a billion dollar, maybe even a trillion dollar company around basically as a rapper.
C
Well, yes, people do.
B
People do, right? There was a lot of problems with mostly cloud provider are basically running some open source tools in the cloud and just give you the API to access to that. And there was a lot of databases like Mongo or Elastic who changed their license in order to avoid those type of scenarios.
C
This is a question we get a lot in FFMPEG is why don't you do that? And you can't. We have thousands of contributors, some of whom aren't even alive anymore. You would need all of their agreement to do that. And JB will go maybe a bit later and talk about how challenging that process was in VLC to do the relicensing.
B
The license is a social contract in terms of Rousseau de facto of the community. The community does not agree on much beside the license. People go around, discuss around because of the license and that also allow those license fork, right? Sometimes the community splits, but it's possible because of the license then to merge back. And we've seen that so many times, right? GCC and GC and EGC in the past we have seen for example all the web browsers, right? They started as khml which became webkit and then which became Blink, right? So open source license is like the Core of the community and people are coming from all over the world. Very different type of religion, political borders. They work in the same way on a project to solve a specific problem. And the specific problem we're working on is to make multimedia easy for everyone.
A
Looking it up on perplexity here, looking at the different open source licenses. Most major open source licenses fall into two buckets. Permissive, very few conditions and copy left share alike requirements for derivatives. Below is a brief practical summary of the main ones you'll see in the wild. MIT license, bsd, isc, Apache, GNU gpl, GNU agpl. Where's lgpl? Yeah, lgpl. Let's see, there's the Mozilla public license, there's Eclipse public license, it goes on. There's a lot of variety. I mean, I think, I think the really popular ones is mit, gpl, LGPLUS and bsd. Apache sometimes uses unlicensed. That's an option. Attempts to dedicate code to the public domain with a fallback permissive license.
B
There are many licenses for many different things. What people don't understand that public domain is something that doesn't exist worldwide, right? So all the open source licensing use the copyright law, right, the international copyright law, in order to give rights on how you use the software or how you modify. It's de facto a copyright license contract that you give to the end user or to the developer. And so you have like the first one, which are basically very permissive. MIT bsd, you give the code and basically you do whatever you want, right? You take it, you modify, you do what you want. And this is popular for JavaScript and the type of BSD operating system.
A
So some of them, one of the parameters is whether they require attribution, meaning if you use the code you have to say yes.
B
So in those type of permissive license, some you need to say if you use it, which is called attribution, and some you don't. And then there is the other part of license which are copy left where you need to give back to the community your modifications and with different string attached, some weak copy left license like the Mozilla public license to some which are a bit stronger like GPL or even very strong like agpl. So all of those are different type of licensing. That depends on what your goals are and how you want to structure your community. Which is why I spoke about social contract, because this is very important to understand. FFMPEG and VLC are mostly GPL or LGPL. The Linux kernel is GPL, but Android is Apache. A ton of JavaScript frameworks that are using mostly MIT, all the BSD kernels, OpenBSD, NetBSD are of course BSD. And so it's philosophical change on how you want people to contribute back, basically.
A
So there's, I think you talked about that you've moved at one point from GPL to LGPL on certain parts of the project. Can you describe the difference between the two? And what does it take to move to I guess, a more permissive. So that direction is more permissive. LGPL is more permissive than gpl.
B
Yeah. So you have to realize that you can always go from more permissive to less permissive. Right. Because of course those license are basically statement. So if you restrict, you can always restrict more. Right. So in a GPL project you can take MIT code, but you cannot do the opposite. Right. Because they are more constrained to match. Indeed. In fact, I changed the core of libvlc, which is the engine of vlc, from GPL to lgpl. And there were two reasons to do that. The first one is that so people can use the VLC engine libvlc into third party application. So a lot of applications which are playing video on your phone or on your tablet are actually VLC engine init, which is calling FFMPEG init.
A
Yeah.
B
So that was one of the way to create one of the company I created which is doing consulting and integration of those applications where you integrate VLC into third party solutions like inside game engines or stuff like that. With dpl, you couldn't do that because that means you needed to open source everything. Those are for a lot of like commercial companies who don't want that.
A
So you can create a company with lgbl, you can create a company around it, you can do a commercial thing. You don't have to open sources. So that's a big, big leap.
C
So you could play video in your game.
B
Yes.
C
The problem is I'm a game developer and I want to play some videos and I don't want to be forced to open source the entire game just to play those videos. So that's where the consulting business, the Lib VLC LGPL allows you to do that. The lgpl, the library GPL as it used to be known, allows you to do that.
B
And FFMPEG is exactly the the same LGPL forces you to give back what you change on this component, this library, which is why it's library gpl. And so you can use FFMPEG as LGPL into like Any type of application, even non open source. But you need to give back the modification you did on ffmpeg, same on libvlt.
A
Is it limiting from an open source perspective to go gpl? Because if you, if you're library, if your code is gpl, it means you're not. You're basically discouraging companies from building a business around it. Right? Is that fair to say?
B
It depends on the company. But the company whose business model requires the source, the application to be closed source. Yes, it's limited. So that's why for example, I moved to lgpl. The second reason is a bit more obscure is that the terms of condition of the App Store, the, the Apple app store for iOS makes it very complex to have GPL application on it, while it's easier to have LGPL applications on it. So VLC on Windows and on Mac and on Linux is GPL. The core is LGPL. But on iOS the iPhone version and the Apple TV version is a type of different license called the MPL. And yes, I went and changed the license and it was a long story.
A
Yeah, So I think basically to change the license you have to contact all the contributors.
B
Yes. It's very important to understand that open source projects are what we call in the US copyright law joint work or in civil law collective works or collaborative works, is that you work all together in terms of the same goal and then it creates one software which is one release. But. But the copyright is kept by all the individuals. Some open source projects don't do that, they force copyright assignment. But this is not what we do with communities. So everyone has basically copyright on what they changed and this copyright stays even if at the end your contribution was deleted because the new contribution was based on your previous one. Right. So if you want to properly relicense, you need to find all the contributors. And at that time I had to contact more than 350 people and sometimes, well, they're just. Just an email. Right. So you need to actually track down. I actually like traveled to some place to go somewhere that I was like, sorry that I had found online to see, to go to their job and say, well, you licensed that. Do you want to change from GPL to lgpl? Most of the times they don't even care. They wanted to help vlt. But also it brought me to very complex situation. I arrived to the work of a person who was a factory worker and I said, well, I need to you to sign that because it was his son who died who actually wrote the code. Right. So I had to explain all those type of open source meaning. And no, I was not a company trying to rip out the two lines or five lines that that guy did but was useful and the whole community agreed on that. And he had no idea I was a factory worker and I was a lot younger. Right. Like it was 14 years ago and I was almost in tears. Right. It's very difficult, right. We are talking about lives of people and he explaining and we went to talk about the photo of this guy. Right. So it's important to do it right and to do it correctly. But yes, that means tracking down everything because every contribution works. There are some projects who don't respect that and we do relicensing a bit like aggressively. But as I said, it destroyed the whole heart of the community because it's. We only agree on the license, so that's important.
C
I would emphasize the community is such a wide ranging group of people. There's people in a Syrian war zone with electricity part time. There's all people from all walks of life, rich, poor, young, old. So it's quite remarkable to get a group of people aligned on something now that's an achievement in itself.
A
Yeah, it's incredible. And a lot of them are introverts. So you coming, coming to find them and getting them and getting them to answer an email might be quite, quite difficult.
B
Most of us are introverts. Right. You need to be more precise. You have extremely introverts. Extremely, extremely introverts and introverts. Right. It's just like a whole spectrum of different people. It doesn't matter. The important is, is your code good? Is your code great? Is your technology great? We care about excellent code. We don't care who you are. Sorry. It's just like we have no idea to check. We cannot check. Right. Like maybe you're a dog. I don't care. Right. I don't care where you come from. I need to look at your code. And this is important because people don't understand that and they come to the community and send them some patches and they get rejected and they don't like that because you're just like, sorry, it's not up to our standards. Oh yeah. But I'm engineer at this very large company in Italy, in Germany, in the uk. We don't care. We care about the quality of your code because this is what defines our community. Which means that we have a lot of people who contribute who are some very different backgrounds and very introverts. Sure. But that's okay, right?
A
So one of the legends of the community is of course Linus Torvalds, who created Linux and is a longtime maintainer of the Linux kernel, as the legend goes. He can be pretty harsh on this meritocratic process of reviewing the code and saying it's not good enough. Can you just speak to the legend of Linus Torvalds?
B
Linus is one of a kind, right? And I would even go and say that what he did on Git is more interesting than what he did on the Linux kernel. He's very harsh. But what people don't see is usually when he's harsh to it's people who are maintainer of part of the kernel, right? So they know him, right? So he's not very harsh like that to everyone. The thing is, what he created in his room is basically powering every server online, right? Even at Microsoft cloud called Azure, I'm quite sure 70, 80% of the servers are running Linux. All your Android phones are running Linux. What he did with the power of a boot source sure is amazing. And yes, the quality of the Linux kernel is very high. And yes, it's difficult, but we cannot compromise on that. We cannot compromise on quality because in the end, and you have to understand that is the core community of VLC is five people. The core community of FFmpeg is 10 to 15. And we are the ones who are going to maintain your code, right? Because 1,000 contributors in the timeline and just 10 staying 1% chance that someone comes and stays 1%. So you will have change of job, change of wives, you have children, you have accident in life, you're going to change jobs, whatever, you're not going to come back. It's most likely. So we are the one going to maintain your code. It needs to be maintainable, it needs to be excellent. And yes, sometimes that means that you need to rework your work because it was good, but it's not excellent. And we need excellence because we have very few to maintain something that is critical for the whole.
A
But we should also mention that there's some spiciness, some harshness to the language that's sometimes used when you're keeping this high bar of excellence. Is there something to say to that?
B
It's true, right? It's also the fact that for example, what we're doing is low level, it's extremely technical. You get into this code community, the tone gets very like a type of. It's a subculture, right? So people who arrive from the external are basically not known to the subculture. Most of those people around FFMPEG and vlc we do videoland dev days VDD every year. They are so fun in real life and they love it. But it's true that you're online and sometimes like the tone. You don't realize how it is, but that's okay.
A
It's a culture. I mean you get this in the gaming culture. There's pretty harsh, intense the way people communic and everyone understands that the way you show love and respect just looks different in different communities. Sometimes people, it depends if it's a book club, usually people are going to be much sweeter if it's an open source project that's very high stakes and used by millions of people.
B
But it's very not often insults that you see for example in the gaming. Right. So Linux tone is a bit unusual even for the open source community. It's more like. It's more. More harsh on the resulting. No, this is not good, this is crap. Those type of things that you will see.
A
Try not to make it about the person, make it about the code.
C
Yes, it's very matter of fact. And I think you've got to look at it in terms of the famous FFmpeg is developed almost entirely by volunteers. And that's true. And you've got to imagine someone's done a hard day's work at their day job, they come home, terseness might be a thing. And that's not something to take personally. You're tired, you're busy, but you still care about this open source stuff. But you may not be able to explain and handhold someone on every subtle detail.
B
And also you have to realize that most people don't speak English as native language. And this is especially for open source projects like FFmpeg and VLC which are mostly centered out of Europe. Sometimes like people who are from the US or just are very not happy about the tone. But most of the time it's also like they don't know better. Right? It's difficult. English is a difficult language. There are so many subtilities and tones and so on that you don't have. Right. So often it's also difficult in those type of community about different cultures and languages.
A
So as the legend goes, jb, you repeatedly turned down millions of dollars to keep VLC open source free for everyone without ads. So take me through the reasoning behind that decision of leaving millions of dollars on the table.
B
Yeah, that's like almost a meme, right?
A
On Reddit there literally is a meme on Reddit 9gag.
B
And yeah, yeah, I see there's you
A
looking like a wizard in the VLC hat on Reddit. This is jb, the creator, VLC media player. He refused to of millions of dollars in order to keep VLC ads free. Thanks, Jean Baptiste Camp. You can even summon him on Reddit.
B
Yeah, and usually if you see, right, it's usually like people tag me, right? And then there is me. And like I say, good morning, I got 24k upvotes, which is great, right? My karma on Reddit is amazing, at least on that account. So the question needs to be answered first. What is a story about vlc, right? Because yes, this is true. I refuse dozens of millions of dollars. Yes, several times, yes, I could be a multimillionaire and be somewhere on the beach, but I did not do it because I thought it was not moral and it was not the right thing to do. And this is very important for myself is to be like, I work for the greater good, I work for people, and I don't want. It's not just by myself, but the reason is also because I did not feel that I'm completely legitimate to do that. And let me explain you why VLT story is a very weird story. In France, we have university and we have a type of top colleges. And those type of excellency schools are engineering school, business schools, and basically lawyers and medical, right? But they're outside of university. And in order to enter those, you spend two years working like crazy math, physics, to enter those best engineering schools.
A
School.
B
One of the schools is called the Ecole Central Paris. It has changed names since, but it was called the Ecole Central Paris. And because it was central, they had to move it because it was too small after the World War II. And they moved it, they wanted to move it to the central of France, in a place called Clermont Ferrand. And the alumni decided that this was not okay, right? It is the school that Eiffel, right, the one who did the Eiffel Tower attended to, right? So they said, no, no, we are amazing grade school, we cannot do that. And so they bought a piece of land south of Par, near Paris, and it was a campus managed by a nonprofit of the alumni, okay? Because of that, everything on the campus was managed by students. The university did nothing, right? So radio, tv, supermarket, library, defining who was going into which rooms. Everything was managed by the students.
A
That's amazing. That's an amazing experiment. It that it all didn't go to hell quickly, it somehow flourished, it worked great.
B
And I learned so much in my life doing those side Activities, right? Because you're 22 and you need to run your compass, else you don't have electricity. Right. So you care about that. Right. But Anyway, in the 80s, they did a full experiment of deploying a network mostly sponsored by IBM and 3Com, which was a token ring network. So token ring is something that, that probably almost no one knows about anymore. It's a networking technology where you don't have routers, right? Everyone is linked. It's really a ring. And when you want to send a message, you talk to your neighbor, who's going to put the message to the next one, who's going to put the things to the next one. In terms of ring, the issue with token ring is of course, that it's very slow because every computer on the network needs to open the message, see if it's okay. Is it for me? No, it's not. And then send it back like a token, which is traveling around, around the ring. In the 80s you're doing some telnet and sending mails as university. That's okay, right? But starts the 90s and the 90s and starts video games. And when you have high latency in video games, basically you die, right? So in 1994, 1995, around doom and Duke Nukem coming around, they want a faster network. So the students go and see the university and say, you know what? We want a faster network. We need to work, also play video games. And the university tells them that basically, oh, I'm sorry, we cannot help you because you understand the campus is not ours. You manage it, so do something. And you should see some basically partners of the university and basically go away and they go. And they actually go and see the CIO of buig, which is a large French company and who's doing some TVs in France. And he says, well, you know what the future of video is satellite. Well, today we know it's not, but at least it was a good idea in 1995, the first of satellite dish. And he says that instead of having like one satellite dish and a big decoder for each of the students, which are 1,500, what about you build like you put an enormous dish and only one decoder, and you send the video directly on the network. And that required a very fast network today, it's obvious, but at the time was like the first to do video streaming. So they built this project which was called Network 2000. Of course, we are in the 90s, right? Everything is futuristic. It's called 2000.
A
Yeah.
B
And so they do the Network 2000 project, it's completely hacked. It crashes after 45 seconds. That's okay. The demo is 40 seconds. It leaks memory. That's okay. They put 64 megabyte of RAM. It's instead of the eight or 16 you have. And the demo should have stopped there. And that was a Network 2000 project by the students.
A
What was the format of the video
B
that they had to work with MPEG2 because satellite is MPEG2TS for transport, MPEG2 video and MPEG2 audio at that time. And the project should have stopped there. Everyone was happy. They had like amazing ATM network at 155Mbps. They had probably one of the best network in Europe at that time time. And they stopped the project. Six months or a year later, two students arrive and say, well, you know what, maybe other people care about video streamed on a local network. And they create the videolan project, video lan. And one of them is called Christophe Massieux, that is a good friend of both Kieran and me. And they start the project. It's not even open source yet. And they spend around three years to get the school to agree to make it open source. Because the university wanted to get. Because of the IP and copyright of the students, wanted to basically monetize these MPEG2 decoders.
A
Just to be clear. So what was the main application? Streaming on a local network.
B
It was streaming on a local network.
A
By the way, that's just like to state the obvious, this is before YouTube.
B
This is before 10 years before YouTube. You have a Pentium 60 or 75, right? The main machine was 4886 DX at 33 MHz, right?
C
Bear in mind, television was the main form of video at the time. You could get new channels in the 90s, having even one new channel. When you grew up with four channels, having a fifth or a sixth was a big deal. And so having this satellite service with, you know, dozens, even hundreds of channels was so groundbreaking.
B
Especially because this is university where you had ton of different nationalities, right? So there was a ton of people who wanted. So in the end they had like several dishes on different type of satellite, right? Because for example, a lot of people were coming from the Maghreb or the middle and so they went to different type of satellites. Anyway, the solution worked great and they started the Videoland project. The Videoland project has several and some are completely crazy solutions, like one, how to create multicast on a unicast network. But let's not come to that. It's too complex. But Videoland client part is what became vlc. Actually they basically strong armed the university to force it to open source because the university did not understand that. And in 2001 it's still early, but basically yes, the University agreed early 2001 to make it open source. I joined the project in 2003 because that's when I joined the university. The first thing is I'm not the one who created VLC because actually no one did. Right.
A
Just kind of naturally emerged from the Videoland project. And we should mention that again. You said it just. But to make it clear, Vitalan as what it became was at the time is a set of technologies around video. The VLC, what you called the client. That's the thing that most normies.
B
That is correct.
A
Think of like as the thing which is like the thing that pops up when you click on video and you play it.
B
So I arrive in 2003 and then I will create the open source nonprofit organization called Videoland. And I took everything out of the university to create it. A non profit project and something sustainable. Yes, it's true that I spent more time than anyone on VLC and videoland that is sure. But it's a continuity of a previous project, Videoland, the student project, which is a continuity of the Network 2000 projects, which is a continuity of that.
A
And I'm sure there's moments along the way there you were thinking of like what is the future of this from an open source perspective? Because as. As the Internet is blowing up and there is companies, I mean for people who don't remember like there's companies making huge amounts of money.
B
And I can tell you that in 2005 the project should have died and I made it to continue the project at some point we were only two active developers and. And I thought it was great technology and was useful and it will be useful. And I made that my life and my time and I made that grow from a few hundreds of thousands of users, millions of users to what we have now, which is probably billions of versions of VLC around the world and used everywhere. So that's a bit the story of vlc. There is ton of very funny story around that many people from around the world working on it. Like you said in Syria or middle of nowhere in India. But along the way I got several offers which were either to bundle toolbars, right? You remember those horrible toolbars which were basically spyware or changing your web browser or your search engine or even like advertisement inside vlc. And I Didn't like that. Right. I. And people don't understand that I'm not against money. Right. I'm very happy to make money. I created several startups and one I hope that is going to work very well. It's the fact that I believe that you need to win money ethically. There is the right way of doing that. And doing sneaky advertisement or stealing data is not the correct way. Right. For example, if Netflix arrives at some point and say, well, we want to put Netflix inside vlc, probably the story would have been different. Right. But they didn't. The only people who came to us were shady ads company. And if I do that right, I would have a ton of money. Right. And then three years later, project is gone. Right. Someone forks it and something else happens.
A
So it's not even necessarily ads or any of that. It's the shadiness of the dishonesty of the. So you had a good radar, you had a good threshold of like, no, this compromises the spirit of what this is supposed to represent.
B
But also it's for me, right. Very selfishly, I need to go to bed at night and be happy about what I've done. Maybe it's my upbringing, maybe it's my parents fault or whatever, but I believe there is right and wrong and this was the right decision at the time. It still is. I want to be proud of what I've been doing and like if I had sold out, I would have betrayed so many other people. Work.
C
Yeah.
A
Well, I should say me and most of the Internet. Thank you for that decision. It's inspiring for others, I think, that are pushing the open source movement forward that it's okay to do these kinds of huge sacrifices if you believe it's right. And I think in that case it was right. And it was the reason that VLC became as successful as it was because it's an embodiment. It's a symbol of freedom and what the open source community can create. Yeah.
B
And be a service for so many people around the world. And this is important we should emphasize.
C
In the 2000s it was really normal to download a program and it secretly installed some spyware. It was buried in very faint text or in the license text box that nobody reads at the bottom. Oh, I will be installing this toolbar and changing all these things. And it was very common to have to, you know, you install a program to do something at the time of
A
any sort to put yourself in the mind of a developer at that time. I think it's very easy to everybody Listening to this, it's very easy at that time to convince yourself to take a few thousand dollars, a few thousand dollars to do it. To say no to much more money takes guts and takes vision.
B
The last offer I had was obscene. And they say, yeah, but imagine with all that money you could build something new open source. Right. It was like the mind trick was it was difficult but for me it was just like no, this doesn't work like that or this is not the right thing, so I don't do it. And again. Right. It's not that I don't like money or whatever, it's just like it wasn't. Right, Right.
A
Well, once again thank you from me and from the rest of the Internet. Let me talk a little bit more about the open source movement, about the fact that as you say over and over and over and over, FFMPEG is and many open source projects are built by volunteers. So there's a bit of drama recently Karen, on the interwebs on Twitter. You have a of spicy style on Twitter that I think articulates and celebrates all the incredible developers and development and the, the code, especially assembly that's involved in building some of these codecs and building some of this incredible technology. But that brings us to the a bit of a debacle that happened. Tell me the full saga of what happened with the Google security engineers.
C
Just to be clear, Google are one of the biggest supporters of open source out there. They have been for a long time. It's just I think some things kind of went a bit overboard this time. So FFMPEG itself, and this is not like a secret, it's on the homepage, you know the IT processes untrusted data. There can be security issues when you parse untrusted data. That's very normal. But recently what changed was Google started using AI to create security reports on an open source project. FEMPEG volunteers had to deal with that. They provided very limited funding and they even went to the media first announcing how good their AI was before the issues could be fixed.
A
And this is in the public forum.
C
Yeah.
A
So reporting an issue, using AI to find an issue in the code, which is a security vulnerability and then reporting that publicly before you're able to fix it.
C
Yeah, it's announcing how good their AI is that they provided a standard 90 day industry deadline without really understanding the nature of volunteer driven development. In addition, this vulnerability was on an obscure 1990s game codec the way. And let's look at it from their standpoint. To begin with, let's you know.
A
Yeah, can you steal me on their case?
C
Yeah, sure. They have substantial resources working on the security of open source projects, projects that are ubiquitous and they've used a lot of compute to do that and very expensive and very capable security researchers to do that. And that's their viewpoint is they are contributing by doing that. But I think that's where opinions differ. It opened up a lot of interesting fissures, I would say. It does seem that there's a portion of the security community that look at themselves a bit like building architects that never have to go to site. You know, going to site is something that is a little bit beneath them. The actual day to day construction. They're there to do their security things and it's someone else's problem. The security industry also kind of has a very aggressive tone towards things. The language they use is extremely aggressive. They use very strong language like you will get popular and to Joe public get popped. You know, it means something quite bad for them. It means to get hacked. The way I would look at it personally is a little bit like the padlock on your home. Not everyone the padlock on your home or you know, the lock on your home is there to protect against the capabilities of what it's there to protect. It's not there to protect nuclear secrets. It's not there to protect Fort Knox. And it could be looked at that they're using AI at a level of scale to go and pick those locks and then say hey, your lock's not secure, you need to deal with this. Whereas actually they're the ones with resources to be able to fix this. But that seems to not be something either they'll contribute to in terms of patches or in terms of financially. And the scale of AI is kind of the issue that the bug reports are very wordy, they're very, very. It's almost a denial of service by AI generated bug reports on very niche codecs. And the other issue the security community has is everything is marked high priority. You're going to, you know, this is the most important thing in the world and you need to deal with this high, high, high vulnerable. Scary, scary, scary. On a game codec used on one disc in 1993.
A
Yeah.
C
And that's where the dichotomy like going around telling everyone that their padlock's not safe. Well, that's a hobby project of somebody. The safety of that codec is consummate to what that person thinks. It's their hobby. It's good that they're security analyzing it but it doesn't need a big scary warning. This is a critical vulnerability. May recently also see that there was another quote unquote vulnerability. It wasn't a Google in this case but a filter could overflow and have an integer overflow and one of your pixels could be the wrong color and this was marked high 7.5 severity in red. And at some point the security industry needs to realize you can't keep crying wolf like this because this just leads to people, you know, the equivalent thereof of putting password stickers on their PC. You know, you can't just keep crying wolf every day. And I appreciate, you know, know that's their modus operandi is to create as much scared and fear. But from the Google standpoint, at the end of the day they need to contribute either financially or with patches. Google uses FFMPEG at a scale probably you or I couldn't even contemplate millions of CPU calls. And yes, they contribute in areas mostly regarding their own products. So VP9AV1 but in a wider sense there's a disproportionate level of contribution. Yes, they fund students, yes they fund summer of code and I think so. Alex Strange is a former FFMPEG developer, I think posting in a personal capacity.
A
So he posted about security engineers on Hacker News. His post reads, the problem with security reports in general is security people are rampant. Self promoters in parentheses. Linus once called them something worse. Imagine you're a humble volunteer open source developer. If a security researcher finds a bug in your code, they're going to make up a cute name for it, start a website with a logo. Google is going to give them a million dollar bounty. They're going to go to DEFCON and get a prize and I assume gonna sell kind of secret security people orgy where everyone is dressed like they're in the matrix. Nobody's going to do any of this for you when you fix it. Basically commenting on the sort of the incentives for the different people involved and
B
misaligned the problem here is the disproportion of means on discovery compared to patching it. Right? And this is the biggest issue, right? And after that debacle Google did some
C
changes, starting to send patches which is.
B
And they also now have reward tools for fixing issues. So it has changed a bit because of that debacle. So it's good, right? But we've seen and we talk about Google but we have seen like some, some other large companies saying oh, you need to fix this bug because it's critical in our product.
A
Can you explain XZ fiasco the FFmpeg tweet reads the EGGC fiasco has shown how a dependence on unpaid volunteers can cause major problems. Trillion dollar corporations expect free and urgent support from volunteers. Microsoft Microsoft Teams posted on a bug tracker full of volunteers that their issue is high priority. After politely requesting a support contract from Microsoft for long term maintenance, they offered a one time payment of a few thousand doll. This is unacceptable. We didn't make it up. This is what Microsoft Microsoft Teams actually did. And then they, you give the image and the details and all that kind of stuff showing that these trillion dollar companies are not giving much money, not giving much support.
C
They think an open source project is a traditional vendor, that they have an sla. They think a public bug tracker is actually, you know, a third party vendor's JIRA where you can do all of these things. It's not, it's there to report bugs. I think the thing that made this particularly heinous was the name dropping of Microsoft, the name dropping. This is a visible product. If this was just a general bug report, I think that would have made it a lot better.
A
Yeah. So they literally said like this is a big deal because a lot of people are using it in Microsoft. I wonder what happens psychologically. So I think what happens in these companies, maybe you can correct me, me is they, you're, you're right, they just think of FFMPEG as like a vendor that Microsoft surely is paying a huge amount of money to. They kind of assume that in their interaction and nobody anywhere on the stack is going like wait a minute, shouldn't we be giving like millions of dollars to FFmpeg?
B
And this is a very big problem in large, like we're talking about some companies but it's the same everywhere, right? A lot of those companies, when we talk to that person, he was just like a manager on one project in Microsoft Teams. He had never really discussed with open source community. He had no idea. But the problem is that usually there is what we call ospos, Open Source Program offices in those type of companies and they are the ones who are supposed to discuss with open source vendors or open source communities. But like they often don't explain that correctly internally.
A
Right.
B
And here it's just like we are not your supplier. If you want me to be a supplier, I'm very happy. Right. I will send you a contract and SLAs like I created five companies who are doing that around open source projects, so that's okay.
A
We should say that some of the spicy tweets that Kieran, you're behind. And some of the debacle produce results, positive results.
C
Donations have increased substantially. They're still not enough to cover even a single full time developer. But on both awareness level and a technical level there's substantially more technical awareness and sort of awareness of the importance of FFMPEG as a result of X and what's happened. I can say it solved its purpose. People realize the level of importance FFMPEG
B
has and on Videoland it's the same, right? Like for example, a very simple example. For more than a year we couldn't update VLC on Android because of a bug on the Play Store on Android. Play Store, right. The only way we got someone to answer was to put a very spicy as you say tweet saying that we were going to stop distributing VLC for Android. Right? And we have around 100 million people using it and now then someone from Android actually came and discussed to us, right? We had the same issue with Microsoft saying that we were going to stop distributing VLC on the Windows Store and unfortunately we are so small that the only very strong power we have to solve those issues is blaming on social network because, because it's snowballs and now they listen to us. But those large companies often have difficulty talking to us. Like for example, VLC is probably one of the top 10 software used on Windows. I am not part of Microsoft ISV programs. Right. I don't have a point of contact at Microsoft. Right. Well, I'm sure any other software, Adobe Spotify has a point of contact. I don't have that. So raising awareness works. It's sometimes very spicy. Lot of drama. X and Twitter are okay for that, but it's efficient.
A
So everybody listening to this should go follow FFMPEG on Twitter on x follow Videon on Twitter on X. Go donate, donate to FFMPEG and thank you Lex.
C
Over the years, several years you've been a supporter of of FFMPEG and videolan on X, giving us shout outs, appreciating what we do.
B
FFMPEG for life and for example Tim Sweeney, Carmack and a few others, very high level people have raised also the awareness on our X accounts and that helped a lot. Also Karpathy, Karpathy, Karpathy as well.
A
Yeah, I mean also outside of the fact that so many people use it, it's so impactful on the world. It's also a great representation of a great open source project like the value of assembly and C and making sure that like you take programming seriously for real world systems.
C
It's not just that we'll talk about assembly later, I'm sure, because that's this whole topic in itself, but it's also celebrating people like Andreas Reinhardt who do maintenance is I believe unpaid. I believe as a volunteer he's doing massive refactorings. Andreas Reinhardt and Anton Kurnov rewriting FFMPEG C with threading, celebrating those guys, celebrating the untold labor that's gone into this. That actually doesn't change anything from the user standpoint. The files are exactly the same, but wow, the airplane has been rebuilt whilst it's in the air.
A
Christian Garcia said as a teenager running this account, referring to the FFMPEG account and you responded, teenagers have written more assembly in FFMPEG than Google engineers. But also just pointing out that there's a lot of incredible contributors who are teenagers.
C
Like JB said, we don't care who you are, where you're from, what you do. Teenagers have written thousands of lines of assembly over the years. Give a shout out back in the days to Daniel Kang. So also highlighting the work of people like Ru Kai Peng. This is a 16 year old. Some of his first contributions to FFMP Peg actually doing and putting some of these quote unquote security researchers to shame by actually finding issues and fixing them and being 16. There's no barriers. There's no barriers to. You have to study at college under this person and understand these. If you can learn C and let's be honest, it's from the K and R book learn C, you can learn assembly. We'll talk about that maybe a bit later you can contribute to world class technology in vlc.
B
One of the oldest contributors is called Felix. He's the one doing everything on Mac and iOS. He's starting working on VLC. He was 16. We had a guy called Eduard Wong who used to be a Google Summer of Code student who stayed for three years around Videoland. He was 14, right? And part of Google Summer of Code and Google Coding, which were programs where basically we have students or high school. We wrote a ton of assembly for x264 and for VLC and a full ffmpeg. Right? So everyone can contribute.
C
And he also did a good job because he didn't play the alarmist CVE heist. Create a CVE which is like a public exposure of security and do these big scary red 7.5 priority. He just fixed an issue in git after 3 days and just fixed it. He didn't need to go and play a big security drama about it. And I think I posted, you know, the kids are all right. Where, whereas there's, there's, there's, you know, there is a. I'm not saying all security people do this, but there is a portion of the security community, as Alex said, that likes to hype themselves up by creating drama. They would have happily raised, this is a high priority CVE 8.0 or whatever on a, on an issue that actually was in git. It wasn't even in a release, it was in development and three days later was fixed.
A
Well, I just want to put a little bit of love out there, even to the bigger community. Much love and respect to Google engineers. Like you said, they're some of the best software engineers in the world and they do contribute a lot, even on the security front. And also, you know, I'm a big fan of Theo. Much love to Theo. He was part of this debacle and drama a little bit. I think when you just zoom out on the grand arc of human history, the drama contributed positively to everybody involved. Donations went up, it brought more attention to the topic, allowed everybody to bicker in a way that ultimately got them to figure out what FFMPEG is all about.
C
So the way, the way we looked at this is like it's a rap battle at the end of the day. No, but it is. We say stuff, we say stuff. Yeah, but we can, we can leave it on. The X is a perfect place for, you know, international rap battle. You say stuff, I say stuff about your mama, but it doesn't mean, you know, I'm having actual personal issue with her. Yeah, and that's what it looks like. The Theo situation, you know, JB can maybe expand, went a little bit too far and there was a little. But you know, it's just a bit of fun. It's just a bit of rap battle. It's a bit, it's wwe. You know, everyone's having a bit of fun on X. It doesn't need to be taken seriously. You know, the teenagers thing, you know that. So that, that guy was a Google employee saying, hey, you know, there are other ways to run an open source business. Go, go. And I was like, oh man, just have a bit of fun. You know, that's what the point of this account is. And, and furthermore, if you can teach people about the ways of open source projects, assembly, et cetera, by doing that, I think there's a lot to be offered here. It's not dunking on people for dunking sake. It's showing actually the story that I think X learned is these are not big corporate open source projects. This is not kubernetes where there's hundreds, maybe thousands of people paid to develop this stuff. These are just people in their basements in their spare time. And if you can address that topic in a fun and entertaining way, I think that's the good thing and that's the value of X and the reach we have.
B
And to be honest, even at Google, Google is one entity, but so many different people. And there is a ton of Google engineer we work with all the time. And even like Google, from YouTube to Chrome to Chrome Media to the rest of Google, those are very different type of entities. But what we do is efficient. And for example, for Theo, it went a bit too far. I had him, I called everyone down, I had him on the phone, we say, okay, this goes too far, and so on. But in the end, yeah, it's a hard battle, but it's positive for the project. The awareness we have on open source, and I mean true open source from communities, right, is increased dramatically in the last two years. And this is useful.
A
What do you think motivates all the incredible contributors that we've been talking about? What's the engine? It's so interesting to see, like you said, they're sitting in the basement. What's the driver? What's the engine there?
B
There are many drivers, but weirdly the main one is that what we do in multimedia plays videos and video is cool, right? And for example, we have so many people in the community who arrived because they loved watching anime, right? And, and this is like the advice when people ask me, what should I work on in open source? How do I start? And my answer is always the same. Work on something you love. I am working on VLC because I love movies, right? And I love watching the same movies over and over, even if my wife hates me when I do that, right? But because it's interesting, right? Because it's a topic that you like, right? That's the first thing where people come to, usually to VLC and FFmpeg. The second thing is that technically, because we search for excellent, this is the best school ever, right? This is the best school ever of programming. If you're good In C, in FFmpeg, if you know how to write assembly, are you sure you're going to be one of the best programmers ever? Even if you're working on writing Typescript? Because this is the most amazing thing to do and you will, like, have to get reviews by some of the most seasoned programmer ever who are Going to look at every part of your code and tell you why it's not great. It's like we are the best teachers that you've ever had in programming, right?
C
Andrew Kelly started Zig. He was an FFmpeg developer and started Zig after his FFmpeg school. I mean, it's the place to learn so many aspects of programming in the real world. In a thing used by billions of people, you have nowhere to hide. You have to be open and honest about your flaws and how you can learn and be better.
B
And what is also interesting in, in multimedia is that you have 16 milliseconds to display a frame. It's not like a game engine where you can basically slow down and wait a frame. So you need to be good, right? There is no choice, else you don't have your video. And because of how codecs if you miss a frame, you're going to destroy the look of the video, right? So you need to be good, you need to be perfect to have the right thing. But also is that it's not just pure programming in the mathematical sense, right? A lot of people don't understand, but in order to program correctly on the open source multimedia community, you need to understand how computer works. And when you write assembly, you need to understand about CPU pipelining, right? You need to understand how SIMD works, how the ILU works, right? You need to understand how I O works, right? And this is what I think that is missing to a lot of engineers and software engineers today is understanding what we call computer architecture. And seriously some of the debate is should we use this assembly call or this one? And people say, well no, it's going to be like three cycle on this type of CPU and this one and has massive impact on the output, right?
C
We should expand. FFMPEG is probably one of the biggest CPU users in the world. It's probably running as we speak easily order of magnitude 100 million, maybe even a billion CPUs as we speak. So every instruction matters. There's no, not the impact, at least in terms of CPU is massive for everything that we do.
B
So first you come because it's an interesting subject, then you stay because it's excellent and in the end you're very proud of it because it's on the end of everyone. Like so many people, like, oh, I'm working for whatever consulting company and I'm doing some portal to download invoices for your PG&E. Wow, great. Like so many jobs are like that. You're not going to tell that to your Grandma. But if you go to see your grandma and say, I do this so that you can play video on your laptop, they understand. And this is very important, right, because you're working on VLC, FFmpeg x264. It's in the end of hundreds of million of people and you have an impact and so you can be proud of yourself. And so I think that in addition to doing a great resume, all those things are why people contribute.
C
Yeah, those are side effects. My favorite quote on this topic is John Collinson. He said the world is a museum of passion projects. Everything out there is a passion project. And open source, multimedia and open source in general, you can just do that so much faster. There's such a faster network effect. I can open a cafe and that can be my passion project. But I have to get building codes, I have to build a building, I have to find a thing, find a location, I have to do all the, you know, all sorts of things. Well, in the software world, that passion project can be, can move quickly. It can be amplified by the network effect and that amplification can be more than the sum of the sum of the parts. You know, you can be, you can find people interested in extremely obscure things and have a network effect and make something that is truly amazing, Amazing.
A
And on that topic of passion projects, Tim Sweeney actually said in a reply to a tweet that was complimenting jb, he said, quote, many things in the world only happen because an awesome person decides to do it. This is the case with vlc. And that speaks to something interesting to me that it does seem that a small number of people, sometimes one person can create something incredible in the software world. Like you said this over and over and over. I think JavaScript is an incredible thing created by initially a single person. Some of the programming languages like Python and C and Java, like this one person has this vision, has this design and brings it sometimes over a weekend. Is the initial spark.
B
Yes. Linus built Git in two weeks. Wow.
A
It changed the world. I mean it really changed the world.
C
Linus passion project. Hey, I'm uploading this tarball to an FTP, like deal with it.
B
But for me it's not just in software, right. And I believe in individuals that are going to change the world. Right. And it's with a good, as you said, vision, right. I want to do that. It is useful, it will be useful. And whether it's going to like build train or cars or rockets or something like, I believe people who believe in themselves and have a Vision can have a huge impact for humanity.
A
Let's actually zoom out before we zoom back in. We'll just keep going up and down the stack. So we've been talking back and forth VLC and FFmpeg. Karen, you said that FFmpeg and Videoland VLC coexist and there's no central point of importance. It's what you call the binary star system. They succeed because of each other. Can you explain the difference, how they interact? What is the. Are they competitors?
C
I don't. I don't think they're competitors. I think. I think the simple answer is. The short answer before I go into detail is VLC is to FFMPEG as Android is to Linux. So they depend on each other, but they coexist because of each other. So they are a binary star system is the analogy I used.
A
By the way, I feel horrible that I just recently learned that Alpha Centauri, the closest star system to us, is a triple star system system.
B
And when you start doing the physics, it's a nightmare, right?
A
Yeah, hence the three body problem.
C
But anyway, so a lot of FFMPEG pipelines involve the X264 project, which is a Video Land project. I would put a finger in the air that say 80 plus percent of those pipelines are dependent on a videoland project. VLC, obviously, as we've discussed, a video land project uses FFmpeg, gives it reach exposure to weird files, historically used some donation money to fund FFMP FFMPEG development and we'll talk a bit maybe about some of the reverse engineering later. So it's a binary star system. They work and feed off each other. Many of the developers are shared, there's no central location. It's a virtuous cycle working together.
A
And we should mention that X264 is the encoder for H264 video standard. So H264 is the standard?
C
Yes, X264 is the implementation, open source implementation of the standard.
A
Standard that's used by basically everybody for everything. Yeah, that is the main driver of this. When you think of an MP4 file that has H264 Kodak in it, if
C
it came from a software environment like a data center or somewhere, the chances are it was created with X264 and
A
that's under the flag of Video Land.
C
That's a Video Land project. So in the Videoland graphic, it sits in the video LAN world and Video
A
Lance has a bunch of stuff in it. Go to the Videoland website. There's A bunch of icons.
B
Like if you look, there is so many libraries, right?
A
Lib, dvd, css, Lib dvd, nav, libdvd, psi, libvlc, of course, vlc, Unity, librewray. Yeah.
B
And there is so many more. Right. Lately the David project that we might talk about is the last project from videoland. It's everywhere. Right. And we have a Leap Spatial Audio lately that we announced Check ASM. Check ASM. An insane project, but amazing. And X264 is one of those Video Land projects. And my opinion, for example, is that x264 was the most amazing encoder ever designed. And this helped the adoption of FFmpeg. A lot of people and large companies went through FFMPEG because they to wanted. Wanted to use x264 and x264 increased the popularity on ffmpeg. But also VLC had its popularity because it's played so many files that were done by ffmpeg. Right. So it's many projects that are intertwined and work together.
C
Yeah. Unfortunately there's a thing on X where VLC is mentioned and there's people a quick reminder that it's FFMPEG inside doing their actual work. And that's, like I said, it's. That's not the case. We work together.
B
And to give you an idea, right. When I compiled VLC for Windows, I compiled around 16 million lines of code. Right. One million of those are inside the VLC repository and FFMPEG in total is probably two. Around two. Right. But that means that so many dependencies are outside. And if you also look at FFMPEG per se, FFMPEG also is integrating third party libraries like x264, but lib opus and so many others. Right. So we all depend on each other. Yeah.
A
That's why I was hoping to do this episode as we are doing that just kind of joins FFmpeg and VLC because it's really, it's. It's really two. Two of the same, like I said, binary star system and we're all just orbiting it. Can we give a shout out to some of the people along the way? We didn't really quite talk about the history of FFmpeg, so maybe can you tell me about Fabrice, can you tell me about Michael Nirmar? Can you tell me about some of
C
the key figures here, the eras of fmpeg? Because there's key eras and key people that made this possible. Fabrice, as you mentioned, creating the concept and then probably in the 2000s era I would call the era tour of FNPEG is. And the 2000s era was Michael Niedermeyer. So key things he got done was exhaustive support for DivX and XVID at the time and all sorts of weird variants of what's known as MPEG4 part 2. So this predates the MPEG4 part 10 that we used to. So this was 2000s era video codecs where there were flavor after flavor of weird, weird decoders. At the time in the 2000s you needed a new player to play every different type of file format. So there was Windows Media Player to play Windows Media formats. There was realplayer to play real media formats. And those were the other. The other key thing in FFMPEG at the time were native decoders for those. I actually remember being, being a teenager, I must have been figuring out there was this one player that could play, could decode these files without having separate bloated players. Because at the time when you downloaded RealPlayer there was a ton of other stuff in there, a ton of ads, a ton of other things. And just having a simple library that was fast led to that. And then I think 2008 was. 2008 onwards was a big challenge change because that's when H264 got its maturity. And I think something hopefully we'll talk about a bit more. This was the beginning of high definition video. So H264 was the key decoder of that. So I call that the late 2000s and 2010s. And that's when the big reverse engineers came along and really did astonishing work. The beginning was a single player that could play Xvid DivX, Windows Media. And Realplay was already a massive achievement in itself without codec packs, without weird stuff you had to download that had weird ads and weird spyware.
B
VLC 1.0 was out on those times 2000, 2009, 2010. And this is like where it exploded.
A
Yeah, without codec packs it just works across all these different.
B
De facto it's just like all the codecs packs are FFMPEG inside VLT plus we have other modules for all the type of codecs.
C
But at the time that wasn't. There were weird, weird. In the 2000s there were weird codec packs with DLLs coming from this place. With spyware, with you know what, it wasn't reliable, you didn't know. And having a single player that was open source or single playback module player that could do this, that was open source. But I think the thing to emphasize is this task in the 2000s that Michael did was Sisyphe. And it was really. The number of edge cases are poor beyond comprehension in terms of terms of. You could have a Chinese CCTV system that did one weird variant of MPEG4 part 2, what's known as MPEG4 ASP. And that was a weird variant and you had to fix that without breaking everybody else times a million.
A
So that's. So you said that that's where a lot of the reverse engineering was happening.
C
It started in the 2000s with the Windows media stuff, because that was proprietary. It started with the real media. So with Benjamin Larson, Kostya, Kostia Shizkov, that era, those were the key. That was the key groundwork. And then in the 2000 and tens was kind of the poor Mahal Kostya era doing some of the most difficult codex. JB, maybe can talk about GoToMeeting4 and GoToMeeting5 and what's the good.
B
So let's talk about this amazing Ukrainian guy called Kostyar, who was at that time living in Germany and who was in love with Sweden. Right. And the guy was the most. He's like, a lot of the people in the community are very clever. He's one of those who are like borderline geniuses. Right. He was able to reverse engineering extremely complex codecs. And he does that. And we do a bit of engineers with Kiran, but clearly not at this level. He reverse engineers engineered binary blobs, which are 20 megabytes. Yeah.
C
So just for reference, one megabyte binary blob to reverse engineer is probably order of magnitude a month of work, and this guy is doing 20, 30 megabyte blobs. Maybe we'll talk about that in a minute about the subtleties of how you do that. But this guy is doing it for very difficult and very obscure codecs and
B
did that for fun. Right. So GoToMeeting was a big problem with VLC because that was like the number one feature request for a long time. Put a bounty. And the guy at some point said, okay, jb, I'm going to do it. And in a matter of two months. And then he explained how he did it. He was just like, oh, I looked at the code like this looked like a DCT that I used to see on WMV and so on. He did that. And the funniest part is that the code he's written is a ton of jokes and there is a ton of jb, right. My name and Kempf and Kostya Jokes inside the code. The Cody's beautiful. Right?
A
So one of the things I want to comment is I've gotten a chance to speak to some of the developers, some of this assembly language level people, and they all always make everything sound like it's kind of easy. There's a kind of humility because maybe just the level of what's required to do this stuff is so high that everything else seems easy, I guess is the lesson to take away from that.
B
So in the community, like some of the most impressive people are the ones doing reverse engineering and the other ones doing the assembly force. Right. And both of those type of people are amazing. X264, for example, became amazing because of a guy called Lorraine Merritt, who was from the University of Washington I think at the time, and who was like, who made everything great and fast doing a ton of assembly. Yeah. So this is like the golden era, I guess, where so many things got on.
C
If you look at Kostya, for example, he looked at the world as a binary specification. He didn't need documentation or anything. I have a binary and I can figure all of this out. And he regularly used the phrase binary specification. Ah, you know, it's not a problem. And he went and he would go away and he would come back and he would do interesting stuff.
A
Can you actually speak to the details or any add color and texture to what it takes to reverse engineer a block?
C
Yeah. So let's look at GoToMeeting, for example, is a good one because I record a meeting on GoToMeeting, for example. How do I play it back without needing this GoToMeeting player? There may not even be a player. I may need to send a recording of a meeting to someone that doesn't have a player or whatever. So first of all, there's a ton of other stuff there. There's an actual video conferencing client you need to go and find. It may be easy. It may not be easy to find the actual module doing the decompression compression, you need a way to actually dump the YUV data from the module. So often it involves opening in a disassembler, trying to guess where the hooks are to incorporate that module and run that module natively to decode a sample file. So figure out where this module is doing the decoding process and find a way to hook in and output the raw YUV data. Because you will need that. That as a point of comparison for when you actually do the reverse engineering, because you'll need to be bit exact or in some cases close to bit exact. And then you open up your disassembler. Use a lot of intuition to go and figure out where the DCT is. Where's entropy coding. There is a kind of not a rule book, but there's always a pattern of some sort. For example, GoToMeeting, you know, it will be a lot of screen codec tools. There's also different variants. So often I think there's. What's GoToMeeting 45234.
B
I think 234- yeah.
A
So as you mentioned here, going to perplexity, GoToMeeting uses its own proprietary codec for older recorded sessions, historically stored in WMV files that require a special decoder to play properly on Windows. Without this decoder installed, Windows Media Player and some editors cannot decode the video track. So you may only hear audio or see a black screen. Boy, do I remember of that. But this is reverse engineering that.
B
This is key, right? Because the GoToMeeting is something that not many people know anymore, right? You know about zoom and teams and so on. But like now let's fast forward 10 years, 15 years and like this is a GoToMeeting EXE for Windows 32 bits, right? Which is like oh yeah, but I'm on Android, I'm on an iPad, I'm somewhere else. Right. How are you going to do that? I'm going to be on RISC V on arm. Those are blocked. But there are tons of files we need to support for the future and this is why those type of work
A
are
B
exceptionally useful for humanity.
A
I just have to say though, that reverse engineering process is mind blowing. It's crazy. It's like, it's a kind of like, you know, I've been reading a lot in the interview archaeologists. I mean you just have so little signal. Yes, yes. You need know over time you get so much experience, you understand the structure of the original code so you can kind of start inferring basics. But you're like archaeologists with a little brush trying to reconstruct the entire human solution.
B
Kiran is too humble. But Kiran has done some reverse engineering of Cineform.
C
Yeah, at the time.
A
Cineform, nice.
C
Yeah, at the time before actually led to the open sourcing of that work. So in parallel to doing the binary side, you obviously have some samples. In many cases you don't have many samples. So you have to figure out what all the different flavors are and you may have. So Cineform, for example, is actually a collection of different approaches and toolkits within that Codec because often it grows naturally. And the hard part is finding a sample that gets you kind of somewhere to start without having to implement 10 different other things. So start there. I think, thankfully at the time I found a sample by pure chance that had a lot of flat blocks. It was animation. So that really helped a lot because. Because it wasn't using particularly complex coding tools, et cetera. And you could kind of get somewhere and then build up and build up until you forget, hey, here's a few bits here. I missed this, I missed this. If branch that it does. And go, oh, so when we say
A
samples, you mean sample videos. And then you're tracking, trying to infer, like what is this codec doing? By observing the sample and then looking at what? At the, at the machine.
C
The machine code saying, this byte is 6. Take this branch, branch, and then a different sample.
B
Oh, it's nuts, man. That is nuts. So you see, this is nuts. Then you go to things like GoToMeeting.
C
It's like, mine was easy, right?
B
Imagine two order of magnitude of more complexity, a guy alone somewhere in Germany doing that. And for a long time you work, you're in a black box because a decoder for a long time, because there is so many steps from the entropy decoding, the intra prediction, the motion prediction, the IDCT, and so on. For a long time you don't see anything, right? So you're debugging purely in memory, debugging guesswork.
C
And you may have the buffer that the coefficients are stored in completely wrong. And so you may be going down a complete rabbit hole thinking it's this. And then, oh, damn, that's something else.
B
And you're doing that on binaries that are tens of megabytes, millions of instructions, right?
C
So you're stepping through the debugger, like one by one, you know, instruction by instruction, going, hey, this instruction changes this, this does this.
B
Pausing the program on the CPU level,
C
pausing it on the CPU level, watching what's going on, trying to figure out.
B
Sometimes you need to like be in a vm. So. Yeah, that you can pause the vm.
C
Yeah, pause the vm, dump the memory. Because some of the codecs could have encryption. There could be like a DRM on there. So you need to dump the memory from a virtual machine.
B
Like when I joined Decole Central Paris in 2003, John Lesh Johansson basically broke the DVD specification and created DC CSS showed us how he was breaking a DRM, which was MP4 Fairplay from Apple. What he did on his laptop and I was young, I was 21 was just like mind blowing because he was basically debugging windows inside a type of VM with like, wow, it's incredible.
A
It's mind blowing and inspiring. Does it get, like, from your experience and from what you've seen in the community, does it get discouraging? Does it get it.
C
People help you, people send you samples, people are keen. Sometimes you don't have access to an encoder, so this is even more difficult because you just ask and you have to ask for samples. I remember Videoland used to tweet for samples at one stage, Hey, I need this obscure sample.
B
And for a long time I was, oh, I need this codec. And I did this codec.
C
And if you were really lucky, you would find like. If you were unlucky, you'd get like one or two. You'd get nothing or you'd get one or two. And then sometimes you'd find a gold mine. Like, yeah, my company has 100,000 of these files because we depended on it for some reason. And so those are kind of the best if. Because then they can test bit exactness across the huge range of coding tools.
A
Can you explain bit exactness?
C
Bit exactness. So most, but not all video codecs, certainly from about the 2000s onwards, have a bit exact definitions. So every implementation must produce exactly the same bits, bit for bit in exactly the same data that comes out of
A
a decoder for like a large number
C
of samples for a given sample. So Lex's implementation, JB's implementation, and my implementation of H264 must match bit exactly. That wasn't the case in the 90s of MPEG2. Probably fair to say one of the biggest mistakes the video industry made. And I think people who were in the room in 92, I don't think most of both of us were in diapers, I suspect, but have acknowledged. I would give a shout out to Yuri Resnick, he's acknowledged that was one of the big mistakes of the era.
A
And you're saying the encoders needed to be able to run tests and then the bit exactness, I mean, that's a nice thing to guarantee. Like there's a parallel sort of development here on the way the web browser works, which takes HTML and displays it and there's no bit exactness there across the different engines.
C
I would point out, actually FFMPEG is unique in the sense that it's. It has been a winner takes all scenario. You have browsers is a good analogy because it has to parse A lot of different content and render it in a particular way, like a decoder. But there still are multiple browser engines. There's Firefox's one, there's Chrome's one, there's a few Japanese ones that are pretty decent. That's not been the case in multimedia in general. Across a wide range of codecs, FFMPEG has kind of won it all, I suppose, in a sense, because of the fact that you can. Can get every new codec added is actually worth more than the value of that codec itself, because it makes the whole thing better.
A
Man, this is really cool. Going to perplexity. Yuri Resnick is a multimedia and signal processing researcher. Got his PhD in computer science from Kyiv University with over 150 papers and more than 80 granted US patents. Contributor to major multimedia standards, including issues 64, MPEG4, AVC, H265, MPEG4, ALS, G718,
C
G718 is telco stuff.
A
And so he was more connected to comp.
B
Real audio, real video, right?
C
That was.
B
Oh, yeah, very important.
A
Zencoder, Bright Cove context. Man, I need to hang out with Yuri.
B
He's legit and he's like one of the most nice person ever, right? For example, for my startup that I'm doing right now called Kyber, right? I met Yuri because I met him every year at the Mile High Vision Video conference, which is in Denver. And he gave me like, so much good ideas and good things. He's like really amazing person.
C
He tells us how, how, you know, how great it is to be, you know, even know us. And you know, you look at that and it's. I think it's. I think it's the other way around.
A
Yuri, that reminds me of a thing that you mentioned to me about FATE testing and like the insanely rigorous process that's used to test everything that's incorporated into FFmpeg. Can you take me through the testing process?
C
Yeah. So FFMPEG has a system called fate. FFmpeg automated testing Environment. Because FFMPEG runs on so many different oss and can be compiled with so many different compilers, there's been a crazy number of configurations. So you can see the absurd combination of compiler variants, operating system variants, instruction set. You can see at the top. MacOS has tons of different variants because it has iOS, it has tvos.
A
I'm looking at a page f8ffmpeg.org 81 minutes ago 76 minutes ago Looking at the different architectures, the operating system, the different compilers, Apple Clang version, combinations of
C
the combination is saying these are all run by volunteers. So these are all volunteer systems. The ones at the top, for example, the Mac I host in my office, for example, host all sorts of different stuff. Other people host other things. So it's really there to make sure. Because FFMPEG does quite complex C code, for example, you do have miscompilations, so the compiler will sometimes compile C code incorrectly, for example. This happens once in a while.
A
There's a log of all the compilations.
C
Log of all the compilations, all the tests. I think one of the other ones will show all the tests passing.
B
If you click you can see all the tests test back, all test successfully in logs.
C
Test.
B
Yeah.
C
So you see all those tests are passing of all the different codecs, all the different filter transformations, all of them. The level of scale is quite crazy on all the combinations. It's not just a matrix at this point, it's like a pivot table of different combinations.
A
That's nuts.
C
And it's a key part of what we do because you may be able to test some thing locally, you make a change, but actually that breaks GCC version 11 on Mac or something like that, and you're able to then fix that. We also have miscompilation. So the C code, sometimes the compiler can have a bug in it where it creates the wrong output. And that can have quite a big effect sometimes on a video. On a video, because of the way frames have dependencies, even a small change in the output can cascade to actually quite big glitches.
B
You see poor PC, you see risk,
C
There was risk, there was weird stuff in the past, like DEC Alpha, see
B
Visual Studio, different Visual Studio, Intel Compiler,
C
Apple client, you name it.
A
What are some of the pain points? Like maybe do you have emotional triggers, maybe nightmares about a particular operating system, a particular container codec combination?
C
For me it's really easy because. So I have a day job, my company builds. The company I started builds equipment for broadcasting sports matches between TV stadiums and studios. For example, we have to work with 10 bit video and 10 bit video has a set of challenges that you can't process 10 bit data natively on a CPU. So that means you have to stick it in 16 bits, so that means you have 6 wasted bits. So there's different packing formats to actually pack the data more efficiently. Because when you send that over a network network, you lose because you need to save that 40%. For example, on PCI Express you may only have bus bandwidth to do that. And so I think internally we have about some are Industry ones and some are internal to our own hardware that we build. We have I think a 5 by 5 or 6 by 6 matrix of every single format to every single other format conversion. In fact, one of them I sent you, and they're all written in handwritten assembly and they're all written and they all support different CPU generations. So this is really traumatic, handling all these different combinations times a million.
A
By the way, the company you're talking about is Open Broadcast Systems.
C
Yes. No relation to the free OBS streaming service.
A
Yeah.
C
But JB and I have started companies, broadly speaking, around the FFMPEG VLC ethos. So that's really low level work. So in most companies this wouldn't be written in assembly. It would be accepted that C is fast. As you can see from that C is not fast.
A
So Here it says 62 times faster than C. Yeah.
C
So it's taking the ethos of doing low level programming, real time programming and using that for commercial applications. And JB and I have started companies around that that in many cases hiring developers from the open source community to use that ethos. And so that's a great example of some of the things we're doing in most companies it would be, I'll write this in C and it's fast and we're done. But actually you can get a lot better.
B
For me, some of the headaches we have is around some OS that are difficult to support. Right. Because if you look at VLC and thanks To Fate and FFmpeg, the last version of VLC runs on Windows XP and still runs there and runs on Windows 11. We work on macOS 10.7 to the latest macOS, whatever it is. Right. 26. We work on iOS since iOS 9, while we are actually iOS 26. Right. We support, we support many types of Linuxes, BSD, Solaris. The last version still runs on OS 2. Right. Like there is maybe 10 users of OS 2 in the world and one of them is maintaining VLC. Then you realize that this very small team around VLC and using ffmpeg, Codex and all the other ones support more oss than Microsoft or Google or Apple. And they have infinite amount of power and resources. But for example, the worst is, is iOS in order to build on iOS 9, we need to do some very clever mixing of several versions of the xcode, IDE and SDK from Apple, from several versions and do a type of Frankenstein version of that so that we can still support iOS9, which is not supported at all by the compiler of Apple, in order to still run iOS on ARM32, on iOS9. And you've seen on Fate that it was still supporting iOS9. Right. So my headaches are mostly related to the support of so many oss. And it's important because, like, we receive so many people saying, hey, thank you, I still have my iPad 2 to watch movies. And it still works on iOS 9. Right. And it's also an impact of, like, not forcing people to buy new hardware when it works, if you optimize it correctly. Which brings us to what we were saying about assembly. It's also fighting the fact that you need to buy something new nonstop, while you could optimize more, which is a lost art.
A
You gotta tell me about this lost art or this. The carriers of the flame of assembly. What is assembly? Why is it beautiful? Why is it challenging? How does it work?
C
So when you write assembly code, you write this using the instructions the actual processor is using directly. So most of the time you would write in a language. Let's take C is a good example. The compiler would use that to create assembly language and machine code instructions for you based off your C code. And there's a specific flavor of assembly that we use in FFmpeg that's called SIMD. SIMD single instruction, multiple data. So this means, for example, say I want to add five to a number in scalar assembly. So this is what's known as you work on an individual element. So I want to have a number of. I have a number 10 and I want to add 5, I use the add instruction and I add 5 to 10 and I get 15 with SIMD. With SIMD I can have a whole vector of 16 different numbers or could all be different. If I want to add five to that, I can run one instruction instruction, and that one instruction sums all 16 elements. And that, as you can imagine, lends itself very well to video, is a pixel grid. So I can perform operations on multiple pixels at the same time. The key thing that we do differently in FFMPEG is we don't use any abstractions or any major abstractions on top of that. So there's a part of the world that uses what's known as intrinsics. So these are C functions that behave very similarly, but not quite the same to writing assembly by hand. So the registers that data is stored in on the cpu, the compiler allocates those for you. And so the key thing to understand was when we write SIMD is we have a 10x not percentage 10x to 50x speed improvement. That function is 62x that's nuts. On the FFMPEG account, as you know, posts and tweets a lot about that to try and touch. Hey, we are doing this stuff.
A
You are a person who sees the beauty in assembly. But it's also extremely useful for these kinds of applications to actually significantly outperform even C, which is crazy.
B
It is necessary, right? Because like, one of the projects that we need to talk about is called David, right? So David is a decoder for the format that was done by Allianz for Open Media, which is a video decoder called AV1.
A
So for people who don't know, we've been talking about H264. AV1 is another hugely popular standard in Kodak that is increasingly taking over the Internet.
B
And when this format was launched, many people said, especially even from the alliance for Open Media, right? Which is Google, Netflix, Amazon, Mozilla say, well, this format is so complex, it must be done in hardware to do decoding, right? And, well, I arrived with a few other people, mostly Ronald, Henrik and Martin. And we said we need to have an extremely good software decoder because it's going to take time to have hardware. And so we wrote this project, which is beyond insane. We are talking, talking about 30,000 lines of C, but 240,000 lines of handwritten assembly, right?
A
Handwritten assembly, 240,000 lines. That's incredible. I mean, some of the stuff we're talking about is probably the biggest assembly code bases.
B
To give you an idea, and Kieran can correct me, but I think The FFmpeg has 100,000 lines of assembly for all the codecs.
C
All codecs.
B
And just this one has 240. It's a videoland project, of course, and it is optimized at the maximum because the motto when we're starting the project is every cycle matters, right? Every cycle matters. Because David is used in VLC and in some software, AV1 playback stacks. We are talking about probably 3 billion devices which are going to decode video nonstop, because, for example, 30% of the video from Netflix are now in AV1, 50% of YouTube. Right? So. And you often don't have a hardware decoder because not many devices have a hardware decoder. And with David, we realized that in one or two calls you were able to decode 720p correctly. So it is like literally incredible, Right, David?
C
Look at that.
A
Yeah. So this is another spicy tweet from you. This is what peak video codecs should look like. Like 79.9% assembly, 19.6% C and 0.5% other.
B
And what's incredible is with those tweets, which is factual, people get crazy. They are unhappy, right?
C
They say, yeah, for the last two years. They go crazy. No, intrinsics is fine, the compiler is.
B
Oh, they go, you can optimize your compiler auto vectorization. It's your fault, you don't understand. And we've tried that forever for two
C
years and two years later, showing hundreds of examples of handwritten assembly. No, no, no, you're doing it wrong. The compiler can do this.
A
So we should actually just articulate a little clearer. So the intuition there from the software engineering folks. When you have code like, okay, let's just take an example. C, there's a compiler that's doing a lot of the optimization. Yes. And the assumption is if you have a good enough compiler, if you continue to improve the compiler, you going to generate code that can perform like optimal performance. You cannot possibly beat it and you're consistently challenging that thought that if you.
C
By orders of magnitude, by orders of
A
magnitude, handcrafted assembly can outperform C. The
B
two things that they tell us is, yeah, but modern compilers have auto vectorization, right? Because SIMD that we're doing is vectorization. And like it's not even close, right? It's not even close, right? It's not like 5%, 10% slower, it's multiple times slower.
A
So can we. I don't know if you can say something philosophically because there's a lot of, there's a lot of great software engineers, great engineers, great machine learning people. Karpathy will listen to this and it's like, what's the intuition he's supposed to get from this? What are we supposed to.
C
Karpathi learned assembly because of the tweets, by the way. He's like, oh, I think this is,
A
let me figure out.
C
And you know, the way he documents his work.
B
And so philosophically, what's important to realize is, is that we passed the time where hardware was going so much faster, right? We at the end of the more low. We have limitation for AI, for memory, you need to go down in the stack and optimize more to get more power from what you have. Because our requests for power, CPU power, GPU power are exploding while the hardware is not exploding in spite of speed, right? So what people do is that they add more calls, right? But that's basically like at some point you can add 250 cores, right? So what we do is to take every inch of the machine.
C
Not just that, not just that, we abuse the Machine we go and use, we use the machine in ways that the creator didn't expect. Sometimes we use an instruction that's completely unrelated to what we do. We use a cryptography instruction in video processing to do nothing.
B
And one of other things that we do, for example, in David, which is a bit crazy, is that we don't use the function calling convention from the operating system. We should explain that that is extremely complex. But basically, usually when you do move from one function in code to another, there is a way to save the registry, the state of the cpu, to enter another function. And this is like standard.
C
It's a bit complex. I would simplify this a bit. So David does things to abuse the calling convention. You could define the calling convention as I've written a function and I want to call another function. How is the data shared between the functions? Because there's a convention, what's known as a calling convention. And what David does for optimal reasons is create its own calling convention sometimes. So if I want to call Lex Friedman's library, we've got to agree on a convention so that I can share data with you in the assembly language space. And one of the challenges in assembly is every operating. Well, not every operating system, but there are at least four that I can think of on x86, Linux 32 bit Windows 32 bit, Windows 64, Linux 64, they all have their own calling conventions. And so one of the amazing things Lauren Merritt did, who we talked about before, was create a very lightweight abstraction layer so you could write your assembly code once. And it handled all the calling convention stuff for you, which was always a problem because you had to manage four different variants. But David takes this even further for speed reasons. It does its own calling convention within itself to bypass the kind of rules, the rules of the rules of sort of functions, and say, okay, actually I'm going to call a function this way because I know it's within my library.
A
Does it have to be special to every single operating system?
C
Well, if it's custom, no. But the challenge is, is in general, yes. And in terms of each instruction set. So the thing to also emphasize is we do this on every instruction set. So every instruction set has its own handwritten assembly, which is even more crazy. And that matrix has got bigger in recent years because of RISC v, because of ARM64, because of the new SVE. There's SME, x86, has AVX512AVX. So we do runtime processor detection. We see what the machine FFMPEG is running on or David's running on. On is capable of. Because you could be on a laptop from 2008 where this isn't there. Runtime detection, we set function pointers accordingly and then from then on, off you go.
A
Or you could be on a machine
B
with RISC V. Yes. And in all that we don't even respect the calling convention of the operating system in order to be faster because we know that we are going to be called from within our binary so we can share data without saving all the registry in the common way because that can lead to. To loading and saving registry on the L1 and L2 CPU and gets us faster. So that's why I said that understanding CPU architecture, computer architecture is key and this is also why it's handwritten. I don't know anyone, I've never heard any other project than Devin doing that. This is what Kiran calls it an art, right? It is an art.
C
I think in a mass world there isn't something on billions of devices. I know there are some specialist industries. I know in high frequency trading they take this really seriously where they're receiving feeds from a market and they need to react within X number of microseconds and so the instructions matter. But that's not a mass, you know, a mass produced thing that's on a billion devices that's hyper specialized running on hyper specialized hardware. We're running on all hardware from.
A
Sorry to linger on it but like that's a really counterintuitive, almost like revolutionary idea here that there is a huge amount of value to us assembly. Like what are we supposed to take away from that? Like what? You know, there's a bunch of people listening to this. They're basically like, sorry from myself included, you know, I programmed for many, many years in C C going up the standards of C, fell in love with C, even metaprogramming and so on. And then transition more and more because of machine learning about 15 years ago to Python. And so like for me in this Python world, JavaScript world world, now Vibe coding where I'm just using natural language, sitting in my jacuzzi, drinking a drink and just talking to the computer record stops. Why is the value to go back all the way down to the low level?
B
Because you can get more power per dollar invested, right? And sometimes it's going to be a problem that is limited by your hardware. A good analogy is what you see in Quantum quantization in LLMs, right? And people are doing, oh, I'm going to do that in FP8 or FP4 or some crazy things like Microsoft Fear who did in 1.5, because you're constrained by memory, because you're constrained by the machine you can run. Because at some point we are doing real time. And I believe this is going to happen on AI inference also is that at some point you need to get faster and you cannot always get harder, more powerful hardware. Right? So you need to understand, analyze code and see where, like where is the mission critical, where is the things that are called non stops. And for example, David is a good example. It's going to be run billions of hours per day. That makes sense. It doesn't make sense to be on the glue of FFmpeg CLI. It makes sense over there.
A
Yeah. And this has to do also. We'll talk about it more. But your new effort, your new company kind of fiber, is doing that kind of thing for ultra low latency. So the slogan being every millisecond count. So when you actually extremely highly constrained
B
in some dimension, we are also arriving at a point where we've done so many great things, but the hardware is getting back to us, right? Because cost is increasing, because we need more power. And so you're limited by either either your cpu, your RAM or your networking and you need to optimize. And this is where value is going to be. Especially because doing AI is going to help do the programming of business. Right. And so the core thing that you will not be able to vibe code are optimization for the hardware to be as fast as is possible.
A
I'd love to talk to you about who and how how should learn assembly. But first I think we need a bathroom break. Quick 10 second thank you to our sponsors. Check them out in the description. It really is the best way to support this podcast. Go to lexfreedman.com sponsors and now back to the episode. All right, and we're back. There's this nice repo with the assembly lessons. First of all, do you think developers should learn how to program an assembly and how would you go about learning it? What is this? ASM lessons?
C
So I personally wasn't happy with the way assembly is taught in books and online because it's very grammar focused and you don't in general learn a language from learning the grammar and the structure. You learn a language by asking someone what their name is and you start from there and you go and solve real problems, problems that you have when you want to communicate. You don't learn sentence structure. This is the interrogative and the adverb and all the assembly books seem to be doing, going through every instruction, even ones that aren't really relevant. Explaining what they all do and how they actually doesn't really change much. And the other problem that we have in our community is assembly is taught sort of hand to hand, person to person blacksmithing one by one. That's the only logical analogy. And that doesn't really scale online. It doesn't do other things. So this. I started a set of assembly lessons in the way it's done in FFmpeg, which is a little bit different to the way assembly in general for. I don't know, I'm trying to think. The other good big use case of assembly is in embedded devices, in really, really low power cheap devices. And that's completely different to what we're doing here. I think it would be good if you could highlight the requirements which are quite simple. It's high school mathematics and see and actually not even see. Really. Really. It's pointers to emphasize. Yes, we've talked about how brilliant this stuff is, but high schoolers like Daniel Kang have written assembly and ffmpeg. I think there's been contributions because of these lessons. So it's really about trying to get this dying art to continue because we've shown it's possible with David to produce something amazing. There's still a lot of codex in FFMPEG that are only maybe partially assembled. Assembly, assembly optimized. And so it really, it really starts with basics and continues explains a lot of the jargon, a lot of the syntax. It doesn't really try and explain to you, you know, interrupt handlers and interrupt instructions and all of these different jump targets. It actually makes this really vector focused
A
and describes all kinds of registers, general purpose registers, vector registers, really nice examples. This is cool.
C
It's a classic example of Fanbake. But some of this assembly language is really beautiful. And I think it's beautiful because it's kind of like flying a Spitfire. It's really aviation at its purest, but also pushing the aircraft beyond what the designer thought was possible. So we're abusing for example, sometimes cryptography instructions to do certain things. And there's a level of beauty in art where it's really you and the processor. There's nothing in between. It's you and the joystick of the cockpit. And you move that joystick and it's physically connected to the ailerons and you can push that plane beyond what it can normally do. And there's a level of beauty and amazingness to go that. But I don't think the sort of person by person assembly that is. But someone taught me and I've taught multiple people is going to work long run because of the particular flavor and the way that we do it.
A
It's literally no, I should. I was gonna say wizards handing it down. I realized I look like a wizard wearing this hat. But you're basically just like the sages, the wise sages handing down the craft. Can I ask about LLMs? Can they help?
C
They had more of an understanding than I expected, but they are still. I've asked it questions and it still goes and starts hallucinating. Not hallucinating, but making modifications. And then I go is it bit exact? No, fix it. And then it just goes and does the same thing and it's going. There isn't the corpus of information like stack overflow to work on.
B
There is not enough data to train on. And this is the biggest issue. I started my career actually doing some assembly for Itanium. Right? So the Itanium is a dead processor type, right? Which was done by intel in HTTP a long time ago when they wanted to do 64 bits. Well, they lost and then we got AMD who did it, AMD 64 which became Executive 4. But Itanium was extremely interesting in the sense that those were processors who had a ton of computing power to do floats, FMAs, which is similar to what we need now for LLMs, right? And you could pack three operations per line that could be loaded. So basically you had an output of basically 6 billion of operation per second. But the bus, the memory bus only allowed 1.5, right? So your CPU was four times faster. So you had to do crazy things to pack things in memory, reuse the registered and those type of semantics. No language could do that, right? So um, like I have the Italian programming book because intel did amazing books. But that's exactly what Kiran says. If you don't know what you you're going to do, it's impossible to read, right? It's a ton of jargon and so on. While those lessons are amazing because they are targeted to a real problem and you can do it yourself.
C
And people have, people have. There are patches and they said oh, I studied your lessons and here's my first changes.
B
That's amazing. And part of that in the lessons is a framework called X86 Inc, written by Lorraine when he was working on X264. And it allows you to do more things about that to create a type of like not caring too much about different coding convention. And we had A lot of students who gave code to x264 using that a long time ago. Right. So it's really doable and I believe it's necessarily to understand assembly language, even if you don't do it much to understand what's going on inside your computer. And that will make you a better programmer. And I assure you that because doing that you will understand some of the architecture of the memory inside your computer. Right. Understanding register L1, L2, L3, RAMS, SSDs disk and so on, which are very important. Important because then you have a good programming culture that will make you a better programmer.
A
What do you think about the Rust programming language? Because that's a bit of a meme.
B
We have very different opinions with Kiran.
C
I think it's valuable what they're doing in terms of memory safety as a concept.
A
Can it achieve some of the speed up that assembly achieves?
C
Not assembly by hand? No. I think that that's a given C potentially. But I see it very. It has a very big Esperanto vibe about it. It's like we're going to solve this and we're doing this in a particular way.
A
Meaning it's a bit too utopian.
C
There's a lot of focus on the self importance rather than solving real world problems. It reminds me of the Sinclair C5. Sir Clive Sinclair of Sinclair Computers built a car and he said, oh, everyone will be traveling around in one of these electric cars. And it was Frost reminds me of that where I think the community doesn't. The community doesn't quite understand that in order to get people to move, you have to build something that's as good as, if not better than what you have now. Yes, people are doing Rust rewrites, but if they only do 85, 90% of the feature set of what we need, like things like core utils that last 1% takes 99% of the time. To use Elon's famous quote, prototypes are easy. Like this kind of stuff is easy. But this. To get a real electric car, you have to make a car as good as, if not better than what we have now. And Rust isn't in that stage yet. I think we. I don't think anyone would object to seeing rust code in FFmpeg. But it needs to work as well and support the same unit testing as everything else. It needs to be flawless. It can't just randomly break. They can't just randomly break ABI when they want to. It needs to. It needs to have, I think more. I think it still has only one compiler implementation, so it's got to be as good as, if not better. And saying, hey, here's my utopia of memory safety isn't enough, even though we probably all agree that that's the goal.
B
So I've done a ton of Rust and the two major topics I had was adding Rust modules inside vlc. One of the reasons VLC got popular and which was one of the main architecture decision is that VLC is a very small core and a ton of modules, right? And so you can write modul in C, in C, in Objective C and anything that is basically interoperable with C. And so we did some Rust modules and so I have experience on that and I wrote some of it. And also my new startup called Kyber is an open source project mainly done in Rust. Rust is extremely good in the sense that it's a better C that cares about memory and allows you to do things about memory ownership that no one else can do. So far, however, it's great when you start a new project from scratch and you do everything in Rust, but it's very not good when you interrupt with existing part. And some part of the Rust community believes that they need to rewrite everything and everything will be better with Rust. And the answer is like, no, I'm almost always. And all my years of being engineer, manager, CTO of startup and so on, don't rewrite, right?
A
That's the initial instinct for a lot of people when they show up to a code base, probably before LLMs, is like, probably because they don't understand the wisdom of the way things have been done in the past. They say, well, we need to rewrite it, hence why there's a thousand JavaScript frameworks.
B
But the reason is the following, and this is very important to understand. It is an order of magnitude easier to write code than read code. And you see that also with LLM they can wipe code. Analyzing is a lot more difficult. And so when you arrive and when you arrive to a very complex piece of code, right, you don't understand it, right? Because it's so much more effort to understand the code from someone else because you don't have the source thought process. And often I joke about some languages, mostly Perl, for example, which has very complex syntax. And imagine I am at my maximum intellectual efficiency in programming and I write the best code ever. I will not be able to understand myself six months later, right? Because reading code is more difficult. So very often you arrive, you don't understand all the wisdom, all the business logic, the reasons that were done, that is maybe not documented. And you say, well, I'm going to rewrite it. And the thing is. No, you don't. Right, because that's, as Kiran said, I'm going to rewrite coreutils in Rust. And then of course you arrive very quickly at 80%, then 90% takes a bit more time. And then you got the last ones right on the other side. So for new projects, it's great. Everything related to parsing files, networking, because of the memory checker, borrow checker. It's amazing. And there is is nothing else to answer A bit differently for us. Imagine I take a piece of software like David or x264, which has a ton of runtime in assembly, right? I rewrite the C part in Rust, right? So it's more secure. Yes, but then you arrive into the assembly and you can jump anywhere in the memory because we are doing handwritten assembly. So even if I rewrite the CPART in. In Rust for security reason, you break all the security when you write handwritten assembly. Because we can jump anywhere. So in my opinion we need to do something that is secure assembly, right? So which is compile time, check the assembly, which is similar to the check assembly projects that we're doing on David and x364 with Videoland, is to start instrumenting your assembly at compile time to check that it's not jumping anywhere in the memory. Because else you might rewrite a part of C in Rust. But if you want to have the same performances, you're going to have inline assembly. And so you destroy your whole security model. So that's a bit what I think about Rust.
C
I just want to. I would say on a personal level, I'm so in awe about assembly. I actually once it never gets old, the speed improvements to show 62x. There are months. On a personal level, I run our internal test suite at work and just see I'm still in awe of the gains we have.
A
There's a source of joy and happiness programming for different reasons, but I think one of the greatest happinesses is in the optimization of code. And it sounds like you're like at
B
the cutting edge of that was cool in the community. I want to speak about two people who are wizards of assembly, right. The two of them are actually working, living in north of Europe, Sweden and Finland. And Henrik Gramner knows so much about intel x86 assembly that when we ask questions at intel about things, they tell like, why are you asking us Intel? You have Henrik. Henrik knows better. He knows all the cycles of almost all the SIMD instruction by all the CPU generation. Oh yes, this is a P4, this is a nehalem, this is a core two, et cetera. That person is like the best person on assembly in the world. And he's the nicest person that you've seen. Like very. He arrives, you don't see. He's amazing. And the other one is called Martin, Martin Storcio. And he's doing mostly the same on arm, right? So neon, right? And iPhones and Androids and so on. And he codes in assembly on his phone, editing it with the crappy keyboard, like virtual keyboard you have while watching his kids play in the playground. Right? Like this is just like wizard level. So those two people are like.
A
Yeah, so apart. When you're programming assembly at that high level, a part of that is knowing the architecture that you're programming on x86.
C
On arm in particular.
A
Yes, ARM in particular. But these are complicated architectures, right?
C
Yeah, but in some ways more x86 with out of order execution, it's not so bad. Arm, you really need to understand all the different generations of ARM processor because they're all different. There's a 72, et cetera, et cetera. And there's the Apple variant, there's this variant and you need to write code that works efficiently on all of them. X86. Well, broadly speaking, you have Intel AMD, you have sub variants, but generally speaking there's something fast is going to remain fast on all of the variants. Whereas in ARM it's a completely much more complicated ballgame.
A
We're taking a nonlinear journey through history here, but we were talking about Michael Niedermaier. I wanted to ask about this. For a time there was a split in FFmpeg and Libav.
B
Yes. So in open source projects sometimes you disagree, right? You have such a nice way of putting it.
A
Yeah.
B
And the good thing is because of the license you're allowed to basically do your own, right? And this is normal. And this has happened all the time, Right. At the point, there was GCC at the time of GCC2 and EGCs, which became then GCC3. Right. There is what we told KHTML with WebKit, with Blink, it is a sane process. And also like when I want to do a new feature today in vlc, I fork, I do my thing on my own and then I merge back to the community. So there was a split in the open source community on FFmpeg, which became Libevin and FFmpeg. And after a Few years. Well, the community merged back and people moved on. It's a bit drama that is normal in open source community, but folks are even they're important because they change the statue quo of a community. Not talking about FFMPEG and EBEV here, but the GCC fork made GCC a ton better because some people wanted to change the architecture fundamentally to make it faster. And of course it's always question of people and so on. But in the end you realize that FFMPEG today is better than it was was before the fork. And now, well, we are back all together, right? And I spent a lot of time and Kian Gense in the community. It's not often, to be honest, very well explained because a ton of the reasons are not very public. But I think that's normal and that's good.
A
Yeah, I mean you're making it sound really nice, but there's pretty heated battles inside open source projects. I mean it is a very passionate community and you are kind of in a distributed way, have to define the direction of things. So here looking at perplexity, FFMPEG and libav split in 2011 mainly over project governance, leadership style and development processes, not because of a fundamental technical disagreement. FFMPEG effectively absorbed Libav's work while Libav withered. Most distributions and developers moved back to FFmpeg. Yeah, those are a weird. From a user's perspective, that was a weird experience because, you know, I'm a Linux user, so you know, whether it's Ubuntu and so on, all of a sudden I think for, for, for a little bit Ubuntu, I feel like, am I remembering correctly?
C
Switched to Libav 12, 14, something like that?
A
Yeah, something like that. And then they switched back. I was like, what is happening? So on the sort of you. You get to feel the ripple of effects of the different internal debates that are happening.
C
To be fair, on Apple, when you type gcc you get clang like they did something like that as well.
B
So yeah, so to me it's like the fork was like heated drama. But most of the development from Libev was merged back into FFmpeg. Right? So de facto FFMPEG got a superset around Libev. And so that gave the user, because in the end we work the user for the users, a larger set of features and a ton of things that were discussed. For example, the debate on reviews, on how we push are something that now is completely settled in FFMPEG and is following mostly what everyone in the community Agrees. Right. So de facto everyone who was active on Dybav came back in work on FFmpeg because the disagreements were fixed and in the end FFMPEG is stronger than it was before. Right. And I know people love drama, but.
A
Well, my, my main concern, I, I understand and I think looking at the, the long history, it's all for the good. But I do, I am concerned because there's so few humans that are critical to the success of open source projects that I have seen it be a psychological toll on folks and sometimes leads to burnout. So you have these incredible people that are at the core of open source projects. There's a moment that happens because what is the motivation of doing it? Ultimately it's because you're passionate about it and it makes you happy. And at a certain point you wake up and it's like this been a bit too much heat from the drama. So like at the project level the project continues and often flourishes, but sometimes there's these individual huge humans, they're just like, I've had enough.
B
Yeah, but it's not just about forks, right? So it's very. What you are referring to is one of the most challenging and most interesting part of open source today is maintenance burnout, right? And AI is a problem because of that. And Daniel Steinberg, which is the maintainer of Curl, who's probably one of the best promoters of open source in the world, he's by the way, a member of the European Open Source Academy with me. So I'm very humbled to be on the same community as him. Right. He's against what he called AI slop, right? Because it gives a ton of fake reports or bad reports, bad patches, and then a lot of maintainers have a lot of burden to maintain the software and this is straining the mind of open source developers much more than folks. And for example, the XZ fiasco was because there was one guy maintaining it and he got basically hammered by two attackants who were asking him questions nonstop, at weird times, at night to block him. And at some point he got fed up and said okay, I can't do that, and gave the comment access to the attackant. So burnout in open source community is something that exists, but mostly it's about maintaining things, right?
A
No, for sure. I wonder how do we help that? Because those people are so important, the human beings are so important, the core of these projects.
B
So for example, now I am maintaining a ton of multimedia and non multimedia library as maintainer because the maintainers got fed up, right? Some on videoland, some outside of videolan. Because it's some. Sometimes you need tough skins, right? Because you get like it's not really attacks, but oh, this is not working, this is not working. And you feel it personally. And this is also why Resources or the Google fiasco was a problem, right. They don't realize that in the end you have, you know, it's like the same graph where you see like everything and it's just like one random open source project that is maintaining the Internet. You see the one, right?
A
Yeah, this is the meme. I mean it applies to a lot of projects, but this is the all modern digital multimedia infrastructure. And then that thing at the very bottom that everything relies on is FFmpeg. It's true. And then there's usually, you know, a handful of folks that are maintaining that
B
and ffmpeg or vlc, right? You have a community of 10, 15 core developers are not the worst open source project. XZ, which is even in more installations, is one person, right? There is one guy.
C
Libxml is.
B
Yeah, libxml right. There was big stop. No one is maintaining XML anymore. Which is like the only library that is able to parse XML everywhere.
C
All the crazy edge cases of XML under ridiculous circumstances and they get attacked by security researchers because there's one other crazy edge case that they haven't thought of and say, yeah, but the body of knowledge to actually resolve that is massive.
B
There is one guy maintaining all the time zones for everyone who is in the middle of, I think, was it Nebraska or South Dakota? Like the mental health of the open source maintainers is something that large corporations don't care or don't see. Right. It's just like, oh yeah, I'm just doing an open source report and so on.
A
Some of it is financial, but some of it. And people should definitely support open source financially all across the board. But some of it is also like spiritual on a basic human level. There's something that happens like with this image of a Fempeg and so much of the Internet depending on it were people almost like talk down to the folks who are carrying these projects forward and maintaining them in the security community.
C
They certainly did. That was one of the things I think that argument came out is there was a portion of the security community. No, these guys write crap code. They need to fix their crap code. I'm like, no, no, no, no. This is a guy's hobby project. You have a security bot that's gone and found some AI generator stuff. That guy didn't Write crap code. It's just an edge case to the 99th. 99999 percentile he didn't think about because it's his hobby project decoding Star wars games.
A
I get the hobby project aspect of it. It's just hard work and it's beautiful. And the right approach there is to celebrate people for doing incredible, incredible work. It's just incredible that humans step up not getting really paid at first or maybe ever and then they doing it out of the love of it. And we need to like human civilization runs on people like that. We need to celebrate them.
B
To give you an idea, I received death threats on Video Land, right?
A
You mentioned that to me. What is behind that?
B
So that must be what 2009, 2010, right? Apple is moving from PowerPC to Core Duo that probably in 2006. And by 2009 or 2010 I decided that we are not going to do new versions of VLC for Power PC. At that time, like VLC, we were close to the number 1.0 release. We were four of us, right? Just like, no, this is not possible. So I receive a death threat with some powder in it, right? Remember there was some anthrax threats at that time, right? And it was because I had taken the decision to not maintain the PowerPC port anymore. And of course it wasn't anthrax, of course it was some type of flaw and so on. But I received that as with the letter of like, you're a piece of shit, you should die, borrow a PC forever and so on. And was 2009 or 2010, right? I was young, I was just like, why? What did I do?
A
Right? Yeah, they can break yourself spirit.
B
It's like why my mother freaked out, right? We had to go see the police and so on. And now like I'm going to say that I'm quite happy that this happened at that time. It, it fooled me a lot, right? I am, I, I can see I can take a lot of, of hate on me. I'm. I'm okay with it, right?
A
It sucks that that's part of reality because all the people that love VLC, all the people that love FFmpeg like me, me, you know, I, I legitimately hundred, probably thousands of times in my life had a smile on my face because FFMPEG made me happy, period. And how many times did I get a chance to say that? Zero. Until I realized there's a Twitter account and every once in a while I'm like messaging it.
B
One of the things I like on the Reddit meme about me, which I don't like this meme for a lot of reasons. But.
A
But.
B
And someone says, oh, JB is on. Is on Reddit, which I am. Right? And I say. And say hello, right? And then I got so many people who say, oh, thank you for vlc. And like I take pictures. And then I shared that to the signal to irc. Yes, we use IRC on.
A
I saw as a quick tangent you mentioned IRC is like Slack for old people. So you still use irc?
B
Of course.
C
Yeah, I have it on my phone as well.
B
Of course.
C
Every day works fine.
A
Wow, it works fine. You have to power with the crank.
C
No, but there's no, there's no tracking. There's nothing.
B
The biggest issue, to be honest, right, compared to Slack is that it doesn't have threads. That's annoying. It doesn't have emojis for reaction. Sometimes it would be nice.
C
V3 has.
B
Yes, V3, but no one does it. And you cannot edit your messages. Right. And the rest it works perfectly fine for.
A
How do you communicate with auto emojis?
B
Well, that's why I said it's for old people.
A
Old people.
B
And we do emojis with like, you know, columns and that.
A
Yeah, exactly. So anyway, you're communicating irc. What were we even talking about?
B
Yeah, we are talking about death threats and. But having people thanking you and sometimes they got people who sent me a message and oh, thank you for vlc. And I always answer because I want to validate the fact that you need to thank the open source community.
A
Yeah, please, everybody listening to this. Celebrate. Celebrate FFMpegs. Celebrate VLC. Celebrate all the incredible open source projects, Linux, everything. There's so many. There's so many. And you know what I mean? Even outside of open source, just celebrate companies that create software that you use a lot and love.
C
Celebrate human endeavor. Celebrate the human effort to not just build something that's okay. Build something that is damn good.
B
Yeah, this is important, right? Like, because as we said, right, we work for technique. We do something very complex for the normal people. Like we want our excellence in tech to be useful for everyone. And this is why, like, this is why we work, right? This is why I wake up in the morning, is because I want people to use our stuff because it's making everyone's life easier.
C
I want to solve hard problems, work on something interesting. Work on some interesting technical challenges.
B
We are engineers. We love to build things. When I was young, very early, I knew I wanted to be an engineer. I wanted to do Cars. Maybe at some point I will go back to cars, right? But this is like we want to build things that are cool and useful and they need to be challenging, right? Because you want your brain to turn on.
A
When did two of you first fall in love with programming, with building, with engineering?
B
When is the first time you programmed Kiran Microsoft Cubasic?
C
As I was on Windows 3.1 and Windows 95. Microsoft Cubasic.
A
Well, what'd you build?
C
Like a multiplication? Just counting loops, like 10, 20, 30, 40.
A
Nice.
C
Then I thought I could do everything. After that I jumped from doing that to I want to create a soccer, football, soccer video game. And I drew everything out. It's like I want to do it. And I didn't quite grasp that actually. I think Grass actually is a massive piece of work to jump from BASIC and drawings and pictures to a video game. But there we go.
B
I think I did also Basics and then Turbo Pascal when I was end of elementary school. But mostly the first time I actually did some serious programming was the first year of. You call that middle school when you're 11. I lived in Italy for a year in France, Florence and it was amazing year. And the math teacher told us to work in a programming language called Logo where you had a turtle that was designing things on the screen and you would turn left and right. And in the end we used that to do very complex programming because of course you could do things. And this changed. Like I knew I wanted to do things with computers and program.
A
I don't think we quite talked about x264 properly. We talked about. David, can we return backtrack a little bit to x264 this thing that powers basically all of the video on the Internet. So can you tell me the story of x264 and Kieran? You're actually a contributor to x64.
C
So x264 is a video encoder for the H264 video standard. It dominates Internet video, but also other areas such as Blu Ray discs. And Blu Ray discs are interesting because the people that make them really want the highest quality. And there's some really cool high end films that have been encoded, broadcasting and all sorts of other areas. X264 was a big step change
B
because
C
it kind of happened at the right time as well. A lot of the development took place when HD video was coming out. Intel Core 2 and Nihil M CPUs were getting fast. You could do real time video. But the most important thing was a key sort of focus on visual metrics so industry and academia for 20 years before was obsessed with mathematical metrics. So what's known as peak signal to noise ratio. So mean squared error, logarithm of mean squared error. And that led to tons of issues because mean squared error leads to blurring, because you actually want to add a little bit of error to everything to reduce the mean squared error as opposed to having a big error. And that led to loads and loads of blurring. So hobbyists bucked that trend. It was for their own personal videos, most mostly anime. So there were two things they did differently. And there's a big iterative feedback loop with the community. They did some stuff differently. Two big things. Psycho visual rate distortion. So using block energy, trying to compensate for human perception when making decisions.
A
So the psycho visual distortion, that's the critical thing. That's the thing. I mean, it's kind of revolutionary like that. We can like rethink. Don't make it like this kind of theoretic thing of compression. Make it all about being pleasing visually to the eye. Yeah, yeah. So compressing in a way that loses the least amount of information for the stuff that matters for us humans.
C
Yes, exactly. As opposed to what? Industry. Some parts of industry are still obsessed by this, which is mathematical numbers that don't look good in reality. And then adaptive quantization was the other big one, one where it was biasing bits against complex areas and redistributing them to less complex areas, like grass. Grass has some high frequencies, but it's kind of. It's less complex overall compared to more complicated things. And this came around by Park Joy. So Park Joy was really the canonical sample that was running around in the pot. Yeah. So this guy was really the. So this. This was created by Swedish television in the beginning of HD and it was done on film and it was no expense spared in terms of production quality. And it was given away for free. This was really. And this is the sample, really, that sorts the men from the boys in terms of. It has so many challenges with the trees, with the water, with the grass, with the motion, with the. I don't think there's. There's still been any. Any public test sequence as good as that these days.
A
So for people who are just listening, we're looking at a bunch of humans running along a river. As you have the reflection, a lot of really high information. Textures everywhere. The leaves and the lighting playing with the leaves and all of this, you
C
could show clearly that encoders with high PSNR will blur everything. Will blur everything. And you could see actually I could turn on psycho visual stuff. I could turnover adaptive quantization and it would just look so much better. But your metrics and these metrics are at the time. At the time were considered so holy. These are the holy metrics that are untouchable. PSNR is the most important thing.
A
Can you speak to how do you measure psycho visual stuff like how do you turn how pleasing a compression is for a human eye into a number? Is that even possible?
C
That's what Netflix have been trying to do with vmaf. They said they've used a machine learning model.
A
That's a more recent thing. But back in when X36 was being developed. That's by eye.
C
It was by eye. It was developers on their laptops. So it's not like even with big companies with professional screens or anything. And that was actually one of the goals which was. I don't. The developers at the time, Lauren Merritt in particular is. I don't want to test this on a $30,000 screen. I want this to look good on someone's laptop at home.
A
Yeah, brilliant.
B
And there is another sample which is a sample that is Planet Earth's keyless SA that I absolutely love. And you are going to see why. It's a ton of birds, right, Flying and the more it goes, the more there are birds. And at the end, right, it's almost like you have millions of birds. It's the most complex thing ever to encode, right? And well, you're watching it on YouTube and you see how bad the YouTube encoding is. Is actually right? And this is like phenomenal to optimize and get perfect quality in a constant bitrate. There was a lot of optimization, mostly by Lauren also on anime, right. For a long time anime was very badly encoded because there was a ton of bending, right? And so you see those issues and there was a ton of things. So x264 is like. And today it's still the reference to any encoder, new encoder, AV1, AV2, VVC, HEVC. Everyone compares to X264.
C
One of my favorite films, Cinema Paradiso. I know the engineer who created the Blu ray and he showed me the comparisons of x264 versus others and it's completely different. And I think a bunch of guys in the Blu ray world started using x264. I think the big one was Chris Henderson from Warner Brothers. He did the whole French orange box set with. That's a quite like a thing a person on the street actually watches and wants to look good. And so they kind of took a risk in their jobs doing that because they're in a big company, that big company can buy whatever they want. And they said, no, no, no. I want to use this free and open source thing so that things look good for my, my customers and build the best. And to this day I personally still try and avoid watching the most cinematic films on streaming services and buy the physical discs because they look good without even having to buy an expensive TV. I think that's the key thing.
B
And X364 is yet another example of open source project. It was started by Laurent Aimard when he was at Die Cole Central Paris where VLC was born. And then you got a generation of people like Lorraine, like Jason, like Mance, like so many.
C
Henry, Henrik, Henrik, Anton.
B
And this is Anton. And this is where the assembly thing that we use now on ffmpeg, David and so on was born. Right. So X264 is like amazing project with people who were really all over the world and I think most of them never met each other.
A
But all of them, according to Kieran, are large percentage love anime. There's several things I've never got into and one of them is anime. And I need you.
B
I watch anime so much, especially at the time. Like at the time it was, it was like a lot of anime content doesn't exist commercially, Right. We are before Crunchyroll, right. So what happens is usually people who love anime who take some DVDs in Japan and rip them because there is no commercial offering. And some of the people who are what we call fan subbers are basically translating themselves to make subtitles. Right. And at that time you download completely illegally. It was the only way to do that. Right. And so all of that was handcrafted and it fits the open source community, right. Because they needed tools to encode to do fan subbing. Right. One of the most amazing open source projects for subtitles is called AEG Sub and it's a subtitle. It's known for anime for South Asian in Japanese languages.
C
There are weird textures in anime that I don't think you get in real life content. I think that was a key one which was optimizing these weird textures that you get. Because anime is not done in a normal.
B
Yeah, the way you produce it is not. You mostly produce it like on screens, right. Since a bit of time. And you have all those gradients in colors because they are very easy to produce digitally, very complex to produce in real life. And the subtitles also are very complex because you need to have often the Japanese and then you need to have the diacritics, what we call the ribi, which is the hiragana and the katakana for the kanji. And then because often course, so that you have the official subtitling, but you also need the English subtitles or the French subtitles, because you want to learn that, right? And there is so many things crazy on subtitles and we had like crazy samples on subtitles that we've seen all around. So this is an important part of the culture. But also because there was no official offering, there was no way of doing that.
A
Can you speak to the difference between H264 and AV1 and then X264 and David, this is this big step. Can you help people understand? Are some of the streaming sites moving more towards that direction of AV1?
B
Let's be honest, all of those codecs, since MPEG2 video are the same concepts. The same concept about inverse transform, about intra prediction motion, compulsory on tropic coding, all of them. However, each generation gives you a bump between 25 and 50% more compression for the same quality. And so you had the MPEG2, you had the Divix area, you have H264, which was like changing, right? H264 improved so much and then you had more, right? You had HEVC, you had VP9 at the same time of HEVC. VP is a bit similar to HEVC in terms of quality compression, but it's royalty free. Because in multimedia there is ton of patents and the licensing after H264 became out of hand, right? And could cost hundreds of millions of dollars per year. So it made no sense. So Google did this VP9 and the alliance for Open Media did this new codec called AV1. So you can imagine that AV1 saves between 40 and 60% less bandwidth than H264 for the same quality, visual quality
C
at a given bitrate.
B
At a given bitrate, right? So that's really like you increase the quality. Either you set the bit rate and you increase the quality, or you set the quality and you decrease your bitrate. But because now you move from SD to HD and HD to 4k and 4k to 4k HD. Like you increasing the size by like 2 factor 2, 3, 4, right? So you need to have better compression to keep it in terms of something that is manageable.
C
It's more coding tools, more bigger blocks, lots more sub partitions in each block. It's just Exponentially more complex.
B
It's more complex because the encoder needs to search more possibilities, right? So you, for example, one of the things that is easy to understand is to predict a block, a color block to another. You have directions, right? You can go left, right, bottom up, and then in terms of the other quadrants, northeast, northwest and so on, right? But that's eight directions. Then you can do more direction. You can do 16 or 69 or 128, right? You can. And every time your encoder is going to spend more time to see, oh well, this block is exactly this one. And those type of tools that you can bring and the encoder needs to check which of the tools are going to compress you better. And so I guess that AV1 encoding is 2 order of magnitude more than H.264 in terms of CPU cycle, right? Order of magnitude, right.
C
And as we discussed, CPUs are not getting faster, you're just throwing more cores at the problem.
B
But also it's the fact that you encode once and you have hundreds of millions of users, right? So for example, YouTube, a very good example. YouTube encodes almost everything in H264, but the popular video gets re encoded in AV1 because it costs more of course, to encode. But you encode once and you send that to millions, right? So it's a trade off between encoding time and complexity and CPU usage on the server side and on the client side. Because. Because at the end, if you're distributing a video to hundreds of thousands of people and the size is half of the other, then it's better. It's better for your battery, it's better for your modem, et cetera, et cetera.
A
So we can lay out, let's say the top five codec container combos would be H.264 inside MP4 containers, AV1 inside MP4 WebM container containers. ProRes for nonlinear editing inside MOV containers. So for people who don't know, I guess ProRes is.
C
It's Apple's codec for editing originally for Final Cut Pro. And it's designed to be faster decode, fast to seek because an editor will need to move very quickly. So it's a different use case to the distribution element.
A
There's no or very minimal temporal compression.
B
There's none yet.
C
There's no non inverse. So you can cut. So you can do cuts.
B
This is what we call intra only codecs. Right. So I'm going to explain quickly what is IPB frames?
A
Yes, please.
B
So I frames Often keyframes but is complete frames. It's like an image. It's a jpeg, right? You have. You can start, you see everything, right? And then the next image can be a P frame which is a predicted frame. So you take some part of the previous image saying well, I need the block 5 and 7 and 42 and you replace it and then you just give the extra information. Right? But that means that in order to decode this P frame you need to have access to previous I frame. Right? And then of course you have more complex ones which are B frames, which are B predicted frames which can be depend on different type of frames, some in the past, some in the future. And so Prores is an intra only codec for the people who can see. This is a very good one. Right. So iframes are complete frames. P frames basically depend only on iframe. And B frames can depend on in
A
front and this GOP group of pictures. I think the default for actually FFMP peg for H264 is like 250 frames. Something like this.
B
Yes.
A
And to me it's just. It's like magic like that you could predict that you can have a complete
B
frame every several seconds. That means several seconds.
A
And then you could still. You could have this chain of predictions you make. And the fact that you can. The fact that somebody like me can use FFMPEG to compress something and not notice that the result still plays back smoothly. It's like magic.
B
You can even have. And we use that in tons on Kyber is what we call intra refresh where basically it's. There is no iframe.
C
You have one at the beginning and you never send an iframe to that.
A
How does that work?
C
You build up an iframe gradually across as the stream continues.
A
So you refresh certain parts of the
B
image, but so you never have an iframe. This is intra refresh that we use. Right. But for me the biggest mind blown when I started was the B frames. B frames means B predicted frames can depend on frames that are coming in the future. That means that in order to decode this B frame you need to wait for the next frame that is dependent buffer that decode that one so that you can decode the B frame. Right. So the way you decode the frame, the decoding order is not the same as the display order. Right. That means the encoder needs to be very clever and decide that well, you know, I'm going to depend on things like in the future. So this is like mind blowing.
A
Yeah.
C
The fact it works so smoothly every day is kind of miraculous in some ways it works. So you can have a stream that works across the world on their decoder versus one in the US versus one here of different manufacturers and they produce bit for bit exactly the same material. That's quite remarkable. And do quite complex things and getting more and more complex and still be bit exact. There's a lot of work that goes into that.
A
There's a lot of knobs you can control in this whole process. There's a lot of really fascinating parameters that I've gotten to know more and more over the years that FFMPEG gives you complete access to. Maybe you can speak to some of them. So first of all, like obviously we can lower the resolution, we can lower the frame rate, we can use different kinds of codecs as we mentioned, from H264 to AV1. There's ways to tune the trade off between bitrate and quality. As we've kind of spoken to. You know, you could do constant bitrate, you can do constant quality. Sarah, cq, qp, you can do the longer or shorter group of pictures GOP that we mentioned. I mean all that kind of stuff. It's crazy. Number of B frames.
B
Yeah. What is crazy is that a ton of people's job is to optimize those parameters. A ton of people that you see at YouTube, at Netflix, at Meta and so on, they're not writing codecs, they're just like finding the right parameters for the file they have for the format they have. Right. Because like something that is for a movie or something that is user generated content from your phone or a screen recording or something that you're going to video edit, you don't want the same things. And there are thousands of people whose job is just to optimize all that.
A
Yeah, they're wizards, hats off to them. YouTube like to deliver all the streaming sites actually to deliver at scale and like YouTube is, is really magical because it's not just doing like what Netflix it does which is one way bro, like broadcasting type thing. It's also has to upload videos from all the places. So they're also doing encoding at scale for videos. They're going to be watched by like five people and it still has to deliver them re like on a moment's notice. No, no delivery delay, nothing. No latency, very minimal latency. And also serve it in all different resolutions. Like YouTube is basically the web version of VLC.
B
Well actually it's funny because like Google Video which was something they did before they acquired YouTube was actually using the VLC plugin so that you could run VLC inside the web browser using the ActiveX plugging. And so it worked in Internet Explorer and you were actually running VLC inside your browser. Which is funny because today we have the opposite. Where we have VLC webassembly, where we compile all VLC nffmpeg to decode to run VLC inside the JavaScript virtual machine with webassembly.
A
Okay, there's this legendary story that you pointed to me too, that it was discovered via WikiLeaks release of Vault 7 documents the CIA was using a modified version of VLC to basically try and trick people. What, to steal their data?
B
Yes, exactly.
A
So can you explain what the heck happened?
B
So this was a surprise, right? Because at some point WikiLeaks mentioned some documents. There were a few more ones with something related to blu rays and VLC. But the most interesting one was the CIA Vault 7, which if I understand correctly was the CIA had like a custom version of VLC where they had a specific plugin. Yeah, exactly. This is like we had to write a press release on that.
A
Videoland wrote a press release saying the only safe source for getting VLC media player is the official Videoland website. I mean, I suppose that's a security vulnerability for basically any piece of open source software somebody can trick you to
B
download in a fake website or targeted advertisement. That was a targeted advertisement. To watch a specific file you need to watch with this custom version of vlc. And it was the normal binaries of vlc except they added one dll, I think it was PSAPI DLL which was basically reading your document folder, encrypting that and sending that. And the thing is, this is very clever to be honest, because once you're watching a movie, right, you're going to do that for two hours and you're not going to touch your computer. And sometimes it's normal because it's HD that your fans are going up and say, and there is ton of CPU usage because you're using vlc, right? That's normal. But the thing is what you don't see is that actually, actually a powered version of VLC that is used by CIA. We had exactly the same problem with Chinese hackers that were targeting Indian people and that got VLC banned from India. Until I had to fight in courts in India, the Indian government to unban vlc, they didn't use vlc, they took just one DLL because we signed the DLL correctly and they used that DLL to do another program. So you had the VLC exe and was calling libvlc, but it was calling it into a fake one and they used that to target. There is not much we can do actually to block those type of hacks.
A
Yeah. And I think people should, for all open source software, for all software in general, people should pay attention where they download the thing.
B
Yes, because. Because that means that they were not downloading it from our website.
A
Do the search engines help you?
B
No, they don't.
A
Just to clarify, because you can, you know, to prevent threats from people manipulating SEO to get up there on the link.
B
Absolutely not. Right. We have a big issue for like more than 10 years is that there is a fake version of VLC in Germany that was reported for now for 12 years. And Google basically decides to not they know what's in it, but the binary is too big for, for their virus analyzer to analyze it. And so. Well, if you're in Germany, you can go to a website that is a fake version of VLC with a custom installer. And it's very popular in Germany because their website is in German and Google mentioned that before Videoland. And the weirdest thing is that it doesn't do anything on your machine for three weeks because that's how they do the detection. And after three weeks there is a small program that is a service that installed at the same time that wakes up after three weeks and installation start downloading spyware and adware. And Google knows about it. They've decided not to do anything. The guys use DOC SEO in Germany to do that at some point. And this is very damaging. Right. Because one of the things that they're downloading is actually something that is replacing your ads inside your machine. Right.
A
It's actually quite surprisingly effective. Whoever is doing it with Twitter and X with X I'll get emails about your X account has been hacked and however they phrase it, it gets me to like at least click on the email, not to follow the thing. And then you're like, man, whatever they're doing with the psychology to try to trick you, they're quite good.
B
There is a security version of vlc, right? You received an email saying, hey, there is a security version update on vlc. Think about updating right now because it can hack your computer. You come, it's a website that looks decent and and you download it's a new version of vlc. Great. You don't know, a month later you're hacked. You have no idea you're part of a botnet.
A
Yeah. So make sure wherever you're downloading stuff, it's legitimate part of the botnet. Speaking of which, so you've mentioned that VLC sandboxing is something you're working on, and it's actually something quite challenging. Why is it important? Why is it hard?
B
So VLC is a core with around 500 plugins, right? One of them is ffmpeg, but we support so many other formats. We support new protocols, we support new filters, we support weird architectures. And in this release of vlc, you have modules that are going to call your drivers, right? Mostly the hardware decoders which are going to call your intel, your Nvidia, your AMD driver, or calling FFmpeg, right? And there might be a security issue. There might be a security issue in the shader, there might be a security issue in VLC, in FFmpeg that is going to basically crash. The issue is that you're running VLC like every other program, like Adobe, right? You're running it on your machine and it has access to all your documents, right? So the idea is to be sure that you do a sandbox so that we can protect from ourselves, because inside the VLC process is running some code that is not even ours. Either it's open source, the other projects that we integrate in vlc, or it's your GPU driver or something that is provided by someone else inside. And so when we crash, we want to not allow people to do bad things, right? Because one of the common way of hacking people is to crash a program. Very often done with a web browser, are very often done with PDF files, less often with multimedia, but that could happen. And when you crash, you launch something on the machine of the person. Could be a ransomware, could be a botnet, right? So security of desktop application is important. On mobile, it's a bit different because most of the mobile applications are running inside their own sandbox. But for vlc, we could run it inside one sandbox. But the problem is that we need access to so many things that it's basically we would have all the permissions, right? And so if you have a sandbox and you put some holes everywhere, it defeats a purpose, right? So what we are trying to do and we're actually doing is splitting VLC into several processes. One is decoding, one is demuxing, one is filters, and all of them run into their own sandbox. The so that the whole vlc, a part of VLC crash, like Chrome, crashes on some tab, right? It crashes crash, but it did not crash the whole program. And this is what we are trying to do. And it's difficult because it's a sandbox that needs to sustain gigabits per second of memcpies. Now, it's not a website which is 5 megabytes or 10 megabytes. We're talking about hundreds of megabits per second. So this is why it is quite challenging. And this is a research topic that we, we are working on in order to have multimedia player that is secure.
A
This is all the kind of stuff you have to think about when millions of people are using. You've mentioned something somewhere where like all the different features of vlc, when you have that many people using it, somebody will use every single feature and they will tell you about it.
B
Best feature in VLT is called the puzzle filter, right? So you click the puzzle filter and it transforms your video into a jigsaw puzzle, right? And you can click and move the pieces, right?
A
Yeah.
B
It's very, very useful when you're watching a French movie, right? You're bored because it's like very long things or love triangle, right? We've seen that so many times, right? But you need to watch it because someone, your wife told you to do that or your boyfriend told you to do that. So you're doing that, right? And you can click and move the pieces around. It's absolutely useless, right? Like, who cares about that? First it was done by a math teacher in high school in south of France to teach his students about bezier curves, which is something that everyone should know about, right? It's very useful. But the code was clean, so it got in VLC, it was merged in 2010. Five years later I received an email saying, hello, JB, I have a problem with VLC. The puzzle is too simple. And I was just like, what? And yes, the puzzle was in the UI maximus by 16 by 16, right? Only 256 pieces. And he says, I'm sorry, but in a movie I love puzzles. This is too simple, right? So there is a commit of me. You can check it online, which is JB changing that the dimensions are 256 by 256. My point is, so many use features are used by a few people, right? There is a way to watch VLC movies in command line without any ui, right?
A
I saw that you can do ascii.
B
ASCII art. Is it useful? Very useful. Imagine you're debugging. Imagine you're debugging a multicast network, right? You have thousands, very complex, very Complex networking stack. Right. You can SSH to all of the routers and put VLC on it with no ui and you're going to see whether it's black or it's not black. Right. So you. Or it's all green or not all green. Right. So you can see. Right. People don't realize there is so many things in VLC that are useful and they have users because once you have hundreds of millions of users, you have people who use every feature.
A
I would love to sort of zoom in and talk a little bit more about the distinction between kind of downloading a file and watching it offline versus streaming. So the, the complexities, the challenges of streaming. Is there something we could say about what it takes to stream files? Because we've been talking about codecs and I think a lot of that implies encoding and decoding without the having to communicate over the network.
B
Sure, sure.
A
So can you elaborate what's required to do over the network stuff?
B
Yeah, but it is less complex than it seems compared to everything that we've talked about. Especially because the most complex thing is not about streaming in terms of streaming services, but it was what was done to actually broadcast through satellites. Because in most of the modern broadcasting services you can pause and you can go on, but when you're sending live streaming, whether it's broadcast or live, for streaming services which are live, this is much more difficult because you need to encode in real time. When you go on a satellite, you have a specific size of the link. Right. You cannot have a burst of bandwidth even for a second. Right. Because you don't have the space for that in your total file. However, there is different types of choice challenges, which are interesting challenges, but I think they are less complex than the one we've seen with late 90s and early 2000s about broadcasting and streaming through satellite.
C
They're different. There are control systems challenges, whereas some are more mathematical. I think that's a difference.
B
In the streaming world, what you have is called what we call adaptive streaming, because the difficulty, and it's not really a video problem, it's mostly a CDN problem, is that you might have too many people watching the same thing at the same time. And it's a congestion of the network.
C
Right.
B
So your player has difficulty downloading things fast enough to play them. So what happens is that locally the player is going to read a lower resolution of it. But there are some very clever algorithms to do that. But most of it is quite basic, to be honest.
A
Even on the buffering side is pretty basic.
B
Yeah, you start with that, download a segment, what we call a segment, and then you time, right. And if it takes more than 50% of the time to download the segment, you go down to right. And the difficulty is more about when do you go up in bandwidth in quality. But this is not very complex to do. When you encode, you're going to encode seven resolutions, right? And you're going to give the bit rate. The difficulties to have your encoder give the same bit rate, but it's not as strict as it used to be.
A
So probably YouTube has to figure out how the human psychology side of that, like how pissed off do you get when it's like very low bit rate and how long should it wait before it increases the bit rate, even though the connection is better? Because maybe the changes in the bit rate is what like affects you psychologically.
C
I think actually the interesting one is the audio that's true that you can kind of notice when they move from full fat AAC to the. There are compressed versions of AAC that use spectral band replication. You can kind of see it goes a bit tinny. And that up and down is very jarring. The video side is a lot smoother and there's less notice. It's really the audio you can, you can definitely, you can definitely feel it from when it's moved you from a different audio profile to one or the other. I don't know. We're surprisingly tolerant at skipping audio glitches. I'm surprised people are know who are not video engineers, how tolerant they are, how tolerant they are to watching sports at 30fps for example, whereas it should really be 60. The world is a lot more tolerant to that. But audio people are very. It's an immediate feedback mechanism of all.
B
If you hear a glitch, you realize it directly.
A
Yeah, I get to fully realize that. I suppose one of the things I'm afraid of when I listen to audio more and more that I get to notice every single tiny detail. And that you can over apply obsessed. When people, people in general are able to kind of, kind of blur their consumption, they can look past certain imperfections.
B
But then when you combine like an event that is for example a sport event that is probably going through satellite or somewhere else and goes to a central place for encoding and then you need to encode this older resolution in real time. You don't have time for QA. You need to push that to CDNs. You need to add probably DRM or protection. You need to have that over a ton of different devices then yes, it is complex and also like you're in the web browser or in very much different devices that you use for television where you had like a defined set top box or cable box that you know where you control end to end. So it's a challenge, but it's less. I think the networking part, while you agree to have 10, 20 seconds of latency, I don't think this is very difficult.
A
Speaking of networking and latency, so your new effort as we mentioned, is Kyber, which is aimed at ultra low latency. As you say, every millisecond counts. And you're applying that to remote control machines like robots, drones, computers, keyboards. Tell me about it.
B
Sure. If you start from where we used to be, right. You used to use FFMPEG to encode files, right. And then we used FFMPEG and VLC to encode in streaming services. Right. And then you need to go lower and lower and the question was where up to where can we go? And this question is very important because there are many use cases where you need to be fast and it's when you have feedback interaction, right. We are not just listening to something, you're actually controlling it. Right. Because. And that's the biggest difference that compared to what we've done so far is that I need video to have a feedback on something that is happening live, whether it's a drone flying, whether it's controlling humanoid robots from distance, whether it's controlling a rover, whether it's playing a video game in the cloud gaming. Because this is what I did on a previous job, right. I was CTO of a cloud gaming startup. And this is a very interesting topic because you push to the limit the network you need to be to care not about the quality like we've done on video and we've Talked about with x264. You care about latency because a milliseconds is meaningful when you're controlling a car, right. Well, you've seen, you've used way more, right. When waymos don't work. And that happens even if 1% of the time there is someone that is basically remote controlling that. And this is exactly the stuff that we're building. It's really an SDK platform to do end to end control of machines.
A
So this comes up quite a lot in a lot of different contexts in robotics. So obviously teleoperation, teleop is becoming more and more important, including for training robots via machine learning.
B
Yes. And what we do is a bit different from everyone else, is that we take only One socket, one connection, which is a QUIC protocol based on udp, which is interesting because it's done for low latency. It doesn't have two of the what we call the TCP end offline problem and HTTP end of line problem. It's sifu by default, but on the same wire we send multiple streams, like multiple track, we send audio, we send video, but we also send the commands, right mouse, keyboard, gamepad and so on. And we do that while maintaining coherence, right Synchronization. Because what people don't realize is that all the clocks actually drift. And when you're controlling a robot, a robot is going to have like two cameras, five cameras, 10 cameras, a ton of captors, GPS and so on. And if you want to train correctly, your robotic AI model, you need to have all those that are in sync and current. And what we've done, and it's all the stuff that we learn on VLC in broadcast in real time and MPEG ts that Kirants know well is that we account for clock drifting. And so when I record a Kyber stream a robot, I am sure that it's going to be predictive in the way you play it back. And so when you're going to do recording and training of your AI model, you need to be sure that every time you retrain based on the data, the data is going to stay coherent and clocks actually drift. Like the existing Solution works with one camera. Once you're going to a 5 or seg, it's more complex.
A
So you want to make sure that the visual snapshot perfectly matches the time it actually happened.
B
Exactly. And also if you're going to control, right. I do something on robot, I need to be sure that it is actually happening at that precise time. Right. And so, so we have on the server, which would be a robot, a time of retime stamping mechanism accounting for clock drift for that. Right. So that's one of the use case of Kyber to control robots. I also think like remote drones, remote, whether it's defense or non defense, remote cars, remote submarines. There is many places in industry or remote surgery where the expert can not go everywhere the machine is because either dangerous or it's too costly. Right? So you allow people to have machines next to you, right. The goal of Kyber is to make distance disappear because it's either projection of skills or projection of power. Right. So imagine we are all like you've seen the Meta Reba and everyone else, right. You need to stream there, right? Because you're not going to run anything over there, right. So you need GPU power that's on the cloud, on the phone to stream that. And so all of these use cases needs to be not about extremely low latency, but real time latency for video. And so that means you need, we're toying with the encoders so that the encoders encode a frame in 4 milliseconds. And Kiran with his company also goes under those type of latency because you need to understand, optimize at max the local latency, right? Because it's the decoder, the encoder and so on. Because this time is going to be added to your networking time. And it's not just about low latency, it's also about reliability. We do clever things like forward error correction, right? So forward error correction is you over transmit a bit bit of data, right? A few percent. And while over transmit you're allowed to lose some packets because all of that is very difficult over an Internet network where you're going to do things very far away. And if you check that all packets are delivered, you add a ton of latency. If you don't want latency, what we do is that we over transmit some data that you can reconstruct on the client side when there is things that are broken. Right. We a few days weeks ago we were doing the demo around Las Vegas for the CES about we had a Rover that is fully 3D printed. It's very simple. It's a car, right? It's a small car with a telescopic arm and it was actually controlled from France. Right. And the video was with a webcam and a very small server. Right. A small PCB was basically running and send that to someone that is on the hand other other side of the planet. And so there is so many use cases. You can also think about having AI who are going to control many drones and so on. And the technically we need to be amazing in video, we need to be amazing at networking. We need to care about any milliseconds in networking, in encoding time, in decoding time. And also you need to integrate very
A
low level, so sync everything together well. But what kind of latency can you get to when you say mill milliseconds? What's the goal?
B
So My goal is 4 milliseconds Glass to glass latency.
A
What's glass to glass mean?
B
So it's easy, right? You have a computer which is running a program, right? Probably a video game and this one is actually running, right? It could be, it's an example of a robot, right? And you have the replicate that is done through the network and you want, if you take a 1000 camera, you can take a picture and you want that to be at 4 milliseconds. 4 milliseconds means 240 hertz, right?
A
Yes.
B
Not so far. We achieve 7 milliseconds from windows to Windows or Windows to Mac. And if you look in the timing most There is around 3.5 milliseconds inside the Nvidia hardware encoder and around 2 milliseconds on the intel decoder, right? So like the encoder plus the decoder is already 6 milliseconds, right? So in order to go down we'll need either to have some other type of codecs or some better encoder that are faster. But 4 milliseconds would be the gral.
A
That's pretty nuts. I love it though. I don't think anyone's ever achieved that, right. That's fast.
B
You can achieve that with custom hardware, with sdi, with professional hardware, but I want that to work over the Internet. I want to work with any robots where you're going to have a small Jetson Nano in it or N150, right? I want that because there is going to be millions of robots or drones are just rolling robots or flying robots or swimming robots, right? It's just you, a machine that you control. And in order either you need to teleoperate them or when everything will be fully autonomous, you need to tele observe them, right? You need to check what's happening. And in my view in the future all those remote cars will be tele observed by an AI model which is just going to say, well, everything is good. And when it's not good, say hey, there is a problem. And then you have an operator, right? And this is going to be about safety, right? When you have your humanoid taking care of your ground grandma or my grandma, I want to be sure that everything goes well. And I'm not in those type of horrible scenarios where the robot is dangerous or when I'm driving, I want the car to stop when it should stop and if needed, someone takes care of that, right? And so there is so many cases, scenarios about real time. And so the goal of Kyber is to make real time control of machine distance disappear.
A
It's incredible. And some of the same technology, some of the same ideas we've been talking about is connected to what you're doing.
B
And for me it's amazingly challenging, right? Because I would say that on video, I'm doing okay, but networking, I have so much more to learn, right? It's about like congestion protocols, bit rate adaptation in real time. But it's quite funny. So I created this project and, and we have foundries in the us of course, but it's open source, right? This is a boardroom, right? Like we've not said that. Right. But everything on Kyber is open source.
A
So how do you make money?
B
It's a dual license, commercial and agpl, right? You remember what you said about licenses? Basically, if you want to use Kyber in your product, you must have your full product open source. If you want to use this amazing technology, but not, not open source, you pay the commercial license, right? So the small people or the hobbyists and the very small guys who want to do that, they can use the technology. They build something that is open source and cool. And if you're a large company, you're going to have the support, all the ip, the right modification and so on. So yeah, it's really cool. And also I'm building robots and I love that, right. The robot we have is 3D printed. We are finishing a demo where it's an actual wing, right? Like a type of drone wing that is also fully 3D printed. We are trying to do a sailboat that is 3D printed. And we'll work on some humanoids. Of course, they are not going to be very good robots. Right? It's not our job, but we're here for everyone to make robots. Cool.
A
You're talking to the right guy. I love robots. There's a bunch of them upstairs. And teleop is going to be really, really important, especially as the number of robots scales across the world. So 100%. Let's talk about the future of multimedia, FFmpeg, VLC. But some of the codecs, we didn't really mention AV2. So can we just lay out what is AV2? What is the hope for it? What is H265, H266?
B
So AV1 is this codec that is done by the alliance for Open Media, right? Where there is Google, Netflix, Amazon, Apple Videoland, where we try to make a royalty free, very good codec, right? And now it's being deployed. But actually the codec was finished in 2018. But a codec takes years to be used in wide scenarios, right? So AV2 is the next generation of this codec. It's 30% better, right? So if you keep the same quality, you got 30% bandwidth reduction compared to AV1.
A
What's the connection with the David and AV2.
B
We are going to do a David 2, right. That I called David because de is 2 in French. And you have to know that David is an actual, what we call recursive acronym. Right. Because it means D. David is an AV1 decoder. Right. So.
A
Oh, nice, nice, nice. I didn't even think of that. And people should know that David spelled with a 1.
B
Yes, it's. And so David 2 is going to
A
be spelled with a 2 pretty soon
B
it's going to be day AV2D. Sorry, I don't know how you pronounce that. And again, we did a demo at the CES of VLC running the first demo of AV2.
A
So can you clarify to me the specification of AV2 and then the encoding and the decoding?
B
Sure. So the specification is like the document to explain how the codec is supposed to work. Right.
A
And that's really AV2.
B
That is AV2 like H264. Right. Then you have an encoder. The current encoder is called avm. And there will probably be other encoders, probably one called SVTAV2 and those are the encoder. The same way x264 is an encoder to H264, the same way that x265 is an encoder for the H265 codec and the decoders for AV1 is David. The decoder for AV2 is David 2. The decoder for H264 is FF H264 inside FFmpeg. The decoder for HVC is FF HVC inside FFmpeg. And there is a next generation codec from the MPEG World After H264, H265, there is one that is called H266, also known as VVC.
A
So HEVC is H265, VVC is H266. Why is H266 super sexy? So much better.
B
So the question often we have is why are they two names? Because most of the time it is a conjunct work from the ISO world and the itu, which is the International Telecommunication Union.
A
These are these two regulatory bodies.
C
One is a private entity and one is the United Nations.
A
Which one is the private?
C
ISO is private in theory.
B
H264 is MPEG4 part 10, H260AVC. And this is the full name.
A
Nice.
C
So it's the concatenation of the ISO name and the ITU name.
A
Yeah.
C
Even though they work together, this is, this is politics, historical, you know.
B
And for HVC it's MPEG H H265HCVC.
A
Got it.
B
And there is H266, which is also named VVC.
A
Is there a high level thing to say about the improvement?
B
30% each and every generation is the best summary.
A
This is true Both for the AV Codex and the H26456.
B
So the professional who are listening to us are going to kill us because they say no, it's 35%, 25%. But globally you need to know that HEVC is 30% better than H264, H260 is 30% better than H265 because there is so many cases and so many scenarios. For example, there are cases especially for screen recording where the gains are humongous because you arrive, you have the right tool that is done for that. And so for a specific video, a new generation is going to give you 70% gain or 80% gain. But there used to be a ton more codecs, but now the two main codecs for transmission are the H264, H265, H266 and the other is AV1, AV2.
A
And I guess the major difference would be the cost of encoding. Yes.
B
And the royalty of the patents. And this is the reasons why you see the AV version of Codex is because they try to be as royalty free, which means no cost for the patents as much as possible. Because what you need to know, and we've not talked about that so far, is that multimedia is what we call a patent minefield. There is two places where, where you have the most patents. It's everything related to 3G, 4G, 5G RF and multimedia because it's very mathematical and you can get great gains and so on. So Google and Meta and Netflix wanted something where it was royalty free. There are people who say that they have patents outside, but they are fringe patents, right? So it's mostly true that it's patent free.
C
We should extend patent. Patent checking was done as part of the standardization process in AV1, AV2, whereas patents are not even discussed in the MPEG world. Patents are off topic completely.
A
Can you educate me at the patents side?
B
So usually so MPEG does a format, right? And then there is. Everyone comes around and says, well I have all those patents, all formats. And they do. Usually a union union was called MPEG la MPEG Licensing Association. And you put all the, all your patents in and then you ask everyone who's using this format to pay for it.
A
Wait, can you elaborate? What does it mean to have a patent of a Kodak? Why is there many patents?
B
Imagine I'm doing something where I'm going to. Instead of doing blocks which are square, I'm going to do rectangles. Right.
A
Also every idea somebody patents.
B
Yes,
A
oh man.
B
Yes.
A
Oh man. People and their. How many lawyers are.
C
I mean it pays for a lot of lawyers.
B
Right. The biggest issue is not the following. Right. Because at time of h264 the patents were, let's call it like sane. But there was so much money in that that for hevc a lot. There were a ton of things that were pushed inside the specification which are not useful in 9.9.9 of the time. But just one could add a patent on it. And so it became that for HEVC licensing there was MPEG LA plus another patent pool called HEVC Advance Plus I think was. Nokia was outside of the patent pool.
C
Yeah, a few of them are outside. And some other one.
B
And so it was impossible to license. Right. And I think that several months ago HP decided that they were going to remove support from hevc in their Windows laptops because the cost was increasing of those patents. And it arrived where a point where. And there was uncapped pad. And so for YouTube or Netflix, we could talk about hundreds of millions of dollars of licensing for patents per year. And they said, you know what? At 100 million per year I could create my own codec. And this is what they did. And so that's why we have the Open Media alliance, alliance for Open Media, where we are part studies that created AV1 and creates AV2. We create also audio codecs. But yes. So the main difference would be that. And because you need to work around the patents or go do some things that are not patented. A lot of things are different. Right. The basic things that were done in MPEG2 30 years ago are caught out of patents. But so for example, there is things like Golden Frame S Franklin Frame or different type.
A
These are all patented ideas.
C
Yeah. No, I can't believe it's not butter. I can't believe it's not a B frame. I mean it's kind of what it is in some ways it's like a.
A
Oh, so it's a different variant of a B frame.
C
Yeah, that's to try and sidestep things like that.
B
And so you need to have double creativity. Right? Creativity in terms of being more efficient, but creativity of being sure that you don't infringe existing patents. And so for example, VVC has all the patents of each EVC plus new ones, right? While AV2 tries to be as royalty free as possible.
A
To what degree does FFMPEG and VLC have to think about this kind of stuff?
B
We don't. And one of the reasons why VLC was in France is that France rejects software patents. So most of those patents are illegal in France because I once made the calculus that if I had to pay all the licensing fee for VLC I needed to pay more than €200 per user. Right? It's the same in dollars. But most of those patents are invalid in Europe because those are called. It's basically mathematical patents or idea patents and they are not valid in Europe.
A
Let me just high level, just out of curiosity. So the meme online and the interwebs on X and Twitter and so on and my own, I have friends in Europe. The sense is that Europe is not friendly to entrepreneurship. They over regulate, there's too much bureaucracy and so on. Is there any, anything positive to say? Is there hope for entrepreneurship in the future of Europe? Is Europe over from a tech perspective?
C
Just look at the two of us, right? It's notable that there's two people from the European continent on this podcast talking about video. It's fair to say the community's weighted heavily.
B
What you probably don't see yet is that there is a new generation of entrepreneurs in Europe and mostly in France, UK has done it since a long time because well, it's more Anglo Saxon type of business, look at business, but especially like what happened in France and of course sometimes a bit overdone with everything called French tech. But today most of the people who come on the market want to create a startups. 15 years ago it wasn't the case. Everyone wanted to work on big companies because when you failed in France, for example, 20 years ago, 15 years ago, and you destroy your company, which is normal for startup, right, you were not allowed to create a new company, right? There was a lot of stigma. This stigma is gone. There is so many things happening on AI in France and so on, right? So there is sure. Over regulations. I know that, right. I'm an entrepreneur. But it has some good things also.
A
I mean, is there some paralyzing aspects? If I look at the case of somebody I've become close with, Paul Durov, you know, he was blamed directly by the French government for the kind of things his quote platform was hosting. I could see the same kind of stuff basically just as an example, VLC being blamed for the kind of videos that people are watching.
B
That's right.
A
Right.
B
Like, we had, we, like, we. We had issues. Like, we.
A
Like. I mean, that's the pressure that people worry about. Because if you have to think about that kind of stuff when you're kind of just obsessed about.
B
No, you don't think about it. And that's. That's okay. Right.
A
Like, but what if they come in when.
B
What if they show up and there is no office? Finland doesn't have office.
A
I mean, this. What happened with Pablo, they arrested him. Right, so arrested them for particular videos or, Or. Or particular content that's being shared on the platform.
B
Sure. I don't have any platform. Everything is on the client side.
A
Yeah, but they're. They still arrest you.
B
On what ground? I'm not sharing anything. I'm not. The content doesn't go through my. My stuff for sure.
A
But it's still lawyer fees. That's the problem.
B
Yes, that's correct.
A
Paperwork. So, like, actually, if you had infinite trillions of dollars, you would win easily because you're on the right side. But the thing is, there is a degree to which they suffocate you with paperwork. That's. That's the downside. Bureaucracy through paperwork, through process. You know, it's the Kafkaesque thing.
B
You have to realize that one of the good things, for example, in France or most of Europe, is that answering to a court order does not make you bankrupt. Right. It's not like in the US where it can actually bankrupt you. Right. The way the law system work is that, like, I receive lawyers years later every week. Right. And I can tell you that the cost of lawyer fees for Vidaland is less than $10,000 per year. Right, Right. So that's not really scary.
A
I mean, similar with Pavel, the intelligence agencies tried to, like, say, can you put a back door on vlc?
B
Yes. Two of them. What?
A
What do you say?
B
No, I was a lot less polite.
A
I. I see you.
B
Yeah, yeah, yeah.
A
You're basically saying, hell no.
B
Like, if we had to compromise our software, we would shut it down. This is clear.
A
And what's the definition of compromise? Like allowing a government to do a backdoor.
B
There is no code that gets into VLC that we don't control. And the way we compile vlc, you would call me completely paranoid. Like, we compile on boxes that are offline, where we start by compiling the compiler. We do everything offline on places that have never been connected to the Internet. The way we do signing there is double signature. Especially because, for example, we've Seen and we believe it's a governmental agency that is not from the Western world who try to push a fake binary into our own servers. And that scared us a lot. And videoland is open source. How can you kill it? Like, I moved to where, right? I moved to Malta, I moved to, I don't know, Cayman, Idaho, Lens. And I change the domain name and I start again, right? Like, VLC is a tool. It's a tool that is going to help people doing things. We are not a platform. And for patents. Well, I'm sorry, but most of the patents, like you shouldn't be able to patent math and matrixes like, this is wrong.
A
Does VLC ever censor the kind of videos it can play and not based on the content of the video?
B
No, never. We never do that because like a VLC is completely offline, doesn't talk to any server, so we don't know anything that you're using the software for.
A
So again, there's no government that can say, you know, like the French government come in and say, we don't want, I think anime is destructive to society. We don't want any anime. Not allowed to be.
B
No, they cannot, they cannot do that. And also what they trust is to say, hey, I want to know if that person watched that type of video. And the answer is like, no idea.
A
So no on that. So for surveillance. No, no, no.
B
Because the only infrastructure we have is a downloading infrastructure. There is no telemetry in vlc, right?
C
It would be difficult because of the international nature. It would be difficult for you to incorporate that code because there would be someone in the UK and someone in Germany and somewhere in the US as part of video and who'd be able to see that. It would be extremely difficult.
B
The only thing that we can do which is happen is like we had the issue, we had the case with some police in the US who said, we have a murder case, right? And the file is destructed or doesn't play in that version of vlc. Could you help us? Right. We never have access to the video. It's like a normal support, right?
A
Oh, it's really about playing the file.
B
Yes. And like I remember in the middle of the Afghan war, right, I received an email from someone in the army, right. I don't remember the grades, right. It was just like, we have a big issue with the latest version of Vladimir VLC because it doesn't play correctly. The file on an RTSP server that we have where there is all the movies. And he says, VLC is very important for the moral on the troop, on the ground. Right. Because at night I think it might be boring. Right. So they have a collection of videos to watch or movies over there. Right. And of course, I did an update and I broke some support of rtsp. Right. So I gave them another version just for them. Right. Because it was important. And because VLC is completely open source, I think it is allowed on the US army laptops. Right. Because I guess someone in the US Military actually looked at it and said, well, okay, this is okay. Right. And the way we document how we process that was okay. Right. So the only way we work with authorities is to help them doing support.
A
That's amazing. That's really, that's an amazing story. Yeah.
B
We don't see anything happening on how people use vlc. And this is strong.
A
Do you feel the stress of this? So first of all, millions of people using it. Second of all, the military using it. Maybe sometimes pressure from governments does that. Does that. That's a, that's a small team, right? Yeah. How big is vlc? Like the core contributor. How many?
B
Six, eight. But, and, and, and everything legally is only me. Everything that is legal is only me.
A
You're not stressed about this?
B
I used to stress about that a lot.
A
Yeah.
B
But the thing is, we're doing what we can for everyone, for the greater good. We work that we make some extremely complex technology easy for everyone. We a tool. And every tool is going to be used for great things and for bad things. Right. You cannot blame a tool. I think, and this is very important for us. I used to be in a lot of stress. I'm not anymore. Right.
A
What's the secret to your Zen? I mean, over and over in the chats I've had with you in the conversation today about every even tense topic. You're very Zen. What's the source of Zen?
B
I have a way of thinking about what is the worst case scenario. Always. Right. And the answer is at the end, if I take a chess player, in the end, am I dead? Yes or no? Right. And I do that nonstop. Right. And that's also how I do my startups. Right? Is that I'm here to get something great. What is the worst case? It goes bankrupts. That's life. A company lives, a company dies. That's okay. Right. And so my moral way is always like, am I dying in the end? Am I hurt? Hurting someone? If the answer is no, then too bad. Right? Like, oh, some lawyers are going to be unhappy. What are they going to do? Take all the money off Video Land. Wow. They're going to earn 50 grand. Amazing.
C
Right?
B
What are they going to do with that? The source code is out there. It's not stoppable also, because what we do is good and it's done for everyone.
A
That's beautiful. Karen, you said that there's an active archiving preservation generation community. I think that's super fascinating. You wrote that they're stretching budget, but they see the extreme importance of FFMPEG as a Rosetta Stone so that multimedia can be played a thousand years from now. I mean, that's a beautiful way to see FFMPEG VLC as a tool for preserving visual knowledge. Yeah.
C
So one of the coolest communities in open source multimedia, mainly led by someone called Dave Rice, I'll give him a shout out, I think, from City University of New York, is the archiving community. They've done so much stuff that they value that they value open source. One, because, yes, they lack budgets, but two, they see the fact that archiving video is important for the world and. But being able to play that is a big problem. Famously, in the uk there was something called the new Doomsday Book and they archived lots of stuff on BBC microcomputers and within 10 to 15 years, no one had the rights to software to play that. I think it was 20 years or something like that and someone had to go and reverse engineer this and that was 20 years. Imagine that in a thousand years. I think one of the great things about FFMPEG is it's written in C. C is the closest to mathematics you're probably going to get. The closest to logic is.
B
Do you think in 1,000 years we'd still have C compilers? Yes.
C
We have languages that exist that haven't changed too much. We have mathematical notation that exists. It will be like Latin, C will be like Latin. It will be a thing, thing that you learn from the past, but it will still be usable in certain contexts. So the archiving community are really great. Practically, again, limited funds, they funded the development of the FFV1 codec. So that's a lossless codex. So the archiving community is really scared about the act of compression, losing things. And they have a fair point in this. If they compress too hard, it could change the view of the material. There could be something slightly different here and there. So they're really concerned about things need to be not just compressed well, but lossless and be fast. And so they worked with FFMPEG to develop a whole new codec designed for fast software based Encoding, they're really concerned about resilience. So if they're storing on tapes or other hard disks, I lose some bits I need to recover quickly. I can't lose a whole GOP because I've lost a bit. Something like that. So they're a really great bunch of people. They funded GPU encoding in FFmpeg to make FFV1 encode faster. And it's really about preserving the world's multimedia heritage in a way that's usable. And there's a lot of great teams and a lot of archival groups across the world who've chosen FFmpeg and FFV1 as their archiving solution. And they can really provide us also super specialist advice. They can explain, ah, in the 1950s colorimetry was done like this on this certain type of tape. And so there is this special case that you need to handle and you'll never get this anywhere else.
B
They know things on video that we don't. Yes, like every time I talk to,
C
with a Dave, Dave Rice or the
B
people from the British film, it's just like every time I just learn something new and I've been doing video for 20 years. They, they have, especially on color, colorimetry and, and colors, storage, these other things.
A
I mean they have a deep, deep appreciation of the content itself, of the video itself. And like, especially when you're thinking lossless, they're terrified of losing something essential about the thing. And in so doing they're deeply understanding the thing that is to be preserved, which you sometimes might not be thinking about when you're obsessing about the actual technology of the encoding and so on.
B
And when you enter the habit hole of film scanners, right. So you take those, those things to make to digital, it's like a huge topic that like would take another five hours of podcast just on that topic.
C
And there's a lot of film that needs to be archived. Film is degrading. It's maybe not stored in the right environment. The other thing is they can, what they also do is because it's open source, they give this away, their workflows to countries who can't afford to have archiving institutions where archiving is done by volunteers. It's done by other things. They go and teach, you know, in India they teach children to do, to do FFmpeg commands. They're really great. They're really, they're really the model community, the model ethos of what we're trying to achieve. They are such a great bunch of people, so interested in participating and being Part of something much bigger because they realize the world work they're doing in a thousand years is going to tell a lot. You know, in a thousand years we may be drowning in AI slop. This stuff needs to be important and archived. Well, what was life like?
A
Yeah. It feels like Capturing the 20th century and the 21st century is essential because it feels like a transition point where we went from scarcity of data to a slob ocean of slop. And that transition point is good to archive.
B
People don't realize we are losing today a ton of films. There is a ton of things from the 30s, from the 40s and the 50s that where there is no value and tape.
C
70s and 80s, there's tape. And there's not enough tape heads in
B
the world to read all the tapes.
C
So they have to decide what they want to archive and throw away the rest of the tapes. This huge moral hazard, I guess for want of a better phrase around this topic because this is a digital record of human history and they have to make decisions and there's digital stewardship, I suppose for want to. I made that phrase up.
B
That's not a real phrase.
C
To make sure the world can have this information in something that's playable by everybody. Not playable on some device that doesn't exist anymore.
A
And then there's like, realistically speaking, there's a needle in the haystack where there's a lot of. Of value in. In archiving all that footage and then over time finding the gems that we don't know are there.
C
Hey, there was something in that corner that we just didn't.
A
Yeah.
C
And that would have been compressed away because some little thing. Oh wow, there's something there. And that's. They've made sure that it's lossless. They can prove mathematically that it's lossless. They can run different trade offs for if there's bit frot. They lose a bit. A single bit flips. I can make sure that I only lose a portion of. Of a given frame. We can do error recovery. They can do error recovery on previous frames. They can do all sorts of different things.
A
Do you think VLC and FFmpeg will be here 100 years from now?
B
FFmpeg? Yes. VLC maybe.
A
What's the future of where is FFMPEG going? Where is VLC going? Like in the next. If you think about like 5 years, 10 years, 20 years?
B
5 years, 10 years is easy. The question is after that. Right. The question is, do we arrive at something called holograms? Right.
A
Yeah. So will VLC and FFmpeg expand to whatever multimedia.
B
Yes.
A
So multimedia might become. Sorry for the pothead expansion of topic. But if you look at something like neuralink with brain computer interfaces, it's very possible that we start to consume. What multimedia means is what? Whatever codec, whatever data that our brain wants to consume through the brain computer interfaces. That's one. Then virtual reality.
B
Of course you will have VLC for
C
neural link and you'll have FFmpeg I input format human brain.
A
Yeah, there's going to be codecs for the brain.
B
Yes, sure, 100%. Of course.
C
I mean compress neural information.
B
Today there is like there are new codecs for, for example, what we call point cloud. Right. Or volumetric videos.
C
Right.
B
There is a ton of research on what we call rgbd. Right. So codecs for depth, that is useful for robotics and for 3D things. The return of codecs for compression of 3D elements, compression for astronomy, for example, on VLC we also have already a VR and XR version of VLC. And also on Kyber, right? We talk about Kyber. On Kyber, we also like do streaming of XR content for the glasses who cannot have enough power or inside the Apple Vision or the Quest. So we already work on streaming 3D XR interactive low latency. There is something called volumetric video point cloud videos. So it's not stopping. And yes, at some point they will manage 3D data inside VLT and FFmpeg. Right? It's obvious.
A
So that's where it is moving. Like the community is open.
B
Not everyone in the community sees that. But like as Kiran and I, we entrepreneurs, we know where it's going. We see that. Right?
A
So I suppose that there is a tension probably inside. FFMPEG is like, hey listen folks, we're really good at doing video and audio, so like, why expand? Like let's do the thing we're really good at doing.
B
In order to answer that question, we need to answer the definition of what is multimedia?
A
Yeah.
B
And multimedia. Multimedia is a digital representation of several streams for the human senses. And we will do that. Right? So imagine there is now a way to not have a mic, but have a odor sensor and a diffuser of others. It will get into ffmpeg.
A
So your Demuxer.
B
Yes, yes, of course. Your Demuxer has a new track type that is basically others, right? And you also smell, touch.
C
It's like audio. You love a left and right nose track. You have a left and right audio pair. It's easy.
B
Yes, of course.
A
The stereo smell.
C
Stereo smell yeah.
B
So in vlc, for example, we already have a plugin for haptic. It's mostly for what we call 4D cinemas. Right. You know those ones on hydraulic. I don't know how you say that.
C
Hydraulic arms. Hydraulic.
B
And where everything is moving like you have in theme parks. Right. And there is a data feed synchronized, which is basically transporting this information.
A
Is there yet a standard for that?
B
There are many standards. Right.
A
You make me so happy.
B
And so of course we have a plugin which is not in the normal version of VLC that is basically transporting those type of movements, which is physical movements, which is haptic movements. Right. It is a human sense. So it will. Will get in.
A
That's such an exciting future. Was it? I mean, it's a small community of developers. How do you pull that off? Like, if you're a contributor At FFmpeg or VLC, it feels stressful. Like just looking at Twitter, it's like it's a huge amount of work to make it work on all these different operating systems. An incredible effort.
B
No, see it in the other direction. We are not the contributors, we are the maintainers. Right. So we maintain for everyone. Meaning that, for example, every year there is around 150 people who contribute to VLC and maybe 300 on FFmpeg. Right. Our goal as a small team is to get all the contribution in. So if there is more usage, there will be more contributions and those people will do the right modules, the new format and so on. We care about the architecture, the architecture of FFmpeg. Right now we're doing things in VLC, which is a spatial audio.
C
Right.
B
We did the demo not long ago. There was changes needed on the architecture and we did the first spatial audio module. When it's going to add the second one, it's going to be easy. Or the third one is going to be easy. Right. Our goal is going to be the same for others or haptic. Right. We need to work on the architecture so that modules can be added to add future capabilities. So, yes, we are going. We have multimedia frameworks, so that's not just audio and video. It's everything that is timed and represents something that you can sense. And if it's brainwaves, it's going to be brainwaves.
C
I think that's inevitable. Sorry.
A
I love this on so many fronts because so FFMPEG and VLC are pushing companies and pushing the world to standardize. So for example, to standardize brainwaves. So standardize. It would push. Like, I hope Neuralink comes up with a Standard for multimedia via brain computer interfaces or for robots with haptic by experience.
B
What happens is always the same, right. You start, it's a new topic. There is like five different standards. Because everyone starts to do this, the hype goes down. Because every time the hype goes down, then people start say, well, you know what, we need to do a standard, people. Because two or three companies, usually not the leader, but the two or three followers do a standard and then we implement the standard and then it's the end of the curve, it starts shoving
A
more paper and then the leaders kind of pressured into it because it's better to do a standard.
B
Example 3D audio, right?
A
Yeah.
B
Six or seven years ago, it was everything about 3D. You had the cardboard on Android, you had two audio formats. They're all dead. Right. And now it's coming back with actual use cases and we learn from the mistakes of the past standard. So it will be the same everywhere
A
and not try to avoid closed. I saw somewhere you didn't have too many nice things to say about Dolby.
B
No, I don't.
A
What is. Can you educate me on why? Where they went? What did they do bad that made you mad?
B
It used to be an amazing company doing tons of great things with amazing engineers. They defined what sound was and now it's mostly lawyers and licensing things.
A
Oh, so they're. Yeah, they're closing stuff off. They're trying to.
B
It's just like they don't innovate as much as they did and so on. It's a bit like, I'm sorry to say. Right. Like HP race.
A
Oh. Since we talked about Twitter a bunch in a bunch of different contexts. Do you have a. Do you have a favorite and least favorite, most embarrassing tweet on either video and ffmpeg? Twitter's.
C
My two favorites are talk is cheap Zen patches, I think that embodies a lot of the stuff doesn't get. As we've talked about, stuff doesn't get built unless someone does it. It doesn't just appear from the ether. The other one that I like is ffmpeg. Nothing is beyond our reach. I think that comes from a US military satellite patch where I think they invented some kind of monitoring system that could see the whole world. And this was released.
B
Wasn't there something where FFMPEG was running on a rover on Mars or something?
C
Yeah. So FFMPEG is used by the Mars rover, the Mars 2020 rover, to compress pictures. They wrote a paper about it and they really wanted to use as much commercial off the Shelf technology as possible FFMPEG runs. So we are a multi planetary open source library.
A
Nice.
B
Very often we've seen tweets for people using VLC in weird places. A lot of the people doing formula ones in all the paddocks, they use VLC to play the live feed. We've seen the European Space agency, we've seen SpaceX monitoring the launches with Vladimir VLC. And like, it's like fills you with joy, right?
A
I've seen Particle Accelerator.
B
Oh yeah, yeah, we had. One of the most amazing things that I went for was to go to the SAN at the LHC because they were using VLC to monitor all the captures on the ring, because the ring is 27km and so they had some analog cameras and they were using some of the capture cards to go to analog to vlc. So VLC could stream on their multicast network network for the whole CERN to access to that. And I visited that in 2010 with Laurent and we fixed their issue in an hour or something like that because with some parameters maybe not well documented at that time. And he said, okay, for the whole day, what do you want to do? And we visited everything like things were with antimatter and colliders and so on. And that was like one of the most amazing day of my. My physic background.
A
Yeah, it's used like everywhere. Any, any tweets, Karen, you regret tweets of regret or is it like that? Well, how's the French song go? Regret nothing.
B
Yes. That's very important for me. Right. Don't regret anything. No, it's because regrets are attacks on your mind. Right. So learn from your mistakes, but don't regret because you've done it. So except if you have a time machine to go back in time, don't regret. Right. It's going to just tax your brain. Learn from your mistake. Sure. Don't regret.
A
It's like, it reminds me. It's beautiful. It's a tax in your brain. Reminds me of the Johnny Depp quote I saw where he was saying hate. You know, I don't hate. Hate is a very expensive emotion.
B
Are you comparing me to Johnny Depp? Because that would be your first one.
A
Well, gentlemen, like I said, I'm eternally grateful for the software that the two of you and the bigger community have been part of building with FFMPEG and VLC and everything else. I'm eternally grateful for the spicy tweets. Never stop. And I'm grateful that you would talk with me today and give me this sexy hat. I feel like a wizard. I feel spoiled special. And I feel special to get a chance to talk and celebrate the piece of software that brought me so much joy over the years. So thank you for everything and thank you for talking today.
C
Thank you for having me.
B
Thank you so much.
A
Thanks for listening to this conversation with John Baptiste Kempf and Kieran Cunha. To support this podcast, please check out our sponsors in the description where you can also find links to contact me, ask questions, give feedback, and so on. And now let me leave you with some words. Words from the legendary Linus Torvalds. Most good programmers do programming not because they expect to get paid or get adulation by the public, but because it is fun to program. Thank you for listening and hope to see you next time.
Guests: Jean-Baptiste Kempf (President of VideoLAN, lead VLC and FFmpeg engineer), Kieran Cunha (longtime codec engineer, FFmpeg contributor, known for the FFmpeg Twitter/X account)
Aired: May 6, 2026
This episode is a celebration and deep dive into FFmpeg and VLC, the two open-source powerhouses forming the “invisible backbone” of the world’s video infrastructure. Lex talks with two leading figures from these projects, exploring not just the technical brilliance and wild stories behind decoding, streaming, and achieving bit-exact playback—but also the deeper, human spirit of volunteer-powered, open-source engineering. The episode moves fluidly among war stories, technical breakdowns, software licensing, the joy and pain of open source, and the future of media itself.
On open source lasting millennia:
“FFmpeg will be here in 100 years. VLC, maybe.” ([251:10], B)
Archiving as preservation of knowledge:
“The world is a museum of passion projects. Everything out there is a passion project.” ([98:54], C)
Why assembly, even now?
“Because you can get more power per dollar invested. ... At some point, we are doing real time, and I believe this is going to happen on AI inference also…” ([141:44], B)
On declining fortunes for “software as math”:
“France rejects software patents... most of those patents are illegal in France because I once made the calculus that if I had to pay all the licensing fee for VLC I needed to pay more than €200 per user.” ([233:37], B)
| Technology | Purpose | Notable Use | Key quote / note | |------------------|--------------------------------------------------|----------------------|-----------------------------------------| | FFmpeg | Low-level media toolkit, encoding/decoding | YouTube, Netflix, Discord, Chrome | “FFmpeg is this collection of toolbox for multimedia processing that everyone, everyone uses” | | VLC | Universal open source media player | 6+ billion downloads | Iconic traffic cone logo | | x264 | H.264 encoder (VideoLAN project) | Video encoded everywhere | “x264 was the most amazing encoder ever designed”| | DAV1D (David) | AV1 decoder, 240k lines assembly (Videolan) | Netflix, YouTube streaming | “Every cycle matters.” |
Thank you for celebrating the engineers and open-source ethic at the heart of the digital media world.