I disagree. Video is such a large percentage of internet traffic and licensing fees are so high that it becomes possible for any number of companies to subsidize the development cost of a new codec on their own and still net a profit. Google certainly spends the most money, but they were hardly the only ones involved in AV1. At Mozilla we developed Daala from scratch and had reached performance competitive with H.265 when we stopped to contribute the technology to the AV1 process, and our team's entire budget was a fraction of what the annual licensing fees for H.264 would have been. Cisco developed Thor on their own with just a handful of people and contributed that, as well. Many other companies contributed technology on a royalty-free basis. Outside of AV1, you regularly see things like Samsung's EVC (or LC-EVC, or APV, or...), or the AVS series from the Chinese.... If the patent situation were more tenable, you would see a lot more of these.
The cost of developing the technology is not the limitation. I would argue the cost to get all parties to agree on a common standard and the cost to deploy it widely enough for people to rely on it is much higher, but people manage that on a royalty-free basis for many other standards.
Daala was never meant to be widely adopted in its original form — its complexity alone made that unlikely. There’s a reason why all widely deployed codecs end up using similar coding tools and partitioning schemes: they’re proven, practical, and compatible with real-world hardware.
As for H.265, it’s the result of countless engineering trade-offs. I’m sure if you cherry-picked all the most experimental ideas proposed during its development, you could create a codec that far outperforms H.265 on paper. But that kind of design would never be viable in a real-world product — it wouldn’t meet the constraints of hardware, licensing, or industry adoption.
Now the following is a more general comment, not directed at you.
There’s often a dismissive attitude toward the work done in the H.26x space. You can sometimes see this even in technical meetings when someone proposes a novel but impractical idea and gets frustrated when others don’t immediately embrace it. But there’s a good reason for the conservative approach: codecs aren’t just judged by their theoretical performance; they have to be implementable, efficient, and compatible with real-world constraints. They also have to somehow make financial sense and cannot be given a way without some form of compensation.
Until the new codec comes to together all those small optimizations aren’t really worth much, so it’s a long term research project with potentially zero return on investement.
And yes, most of the small optimizations are patented, something that I’ve come to understand isnt’t viewed very favorably by most.
(The answer is that most of the work would be done by companies who have an interest in video distribution - eg. Google - but don't profit directly by selling codecs. And universities for the more research side of things. Plus volunteers gluing it all together into the final system.)
People don’t develop video codecs for fun like they do with software. And the reason is that it’s almost impossible to do without support from the industry.
We'd be where we are. All the codec-equivalent aspects of their work are unencumbered by patents and there are very high quality free models available in the market that are just given away. If the multimedia world had followed the Google example it'd be quite hard to complain about the codecs.
The top AI companies use very restrictive licenses.
I think it’s actually the other way around and AI industry will actually end up following the video coding industry when it comes to patents, royalties, licenses etc.
And regarding ”royalty-free” codecs please read this https://ipeurope.org/blog/royalty-free-standards-are-not-fre...
Not to mention the computer clusters to run all the coding sims, thousands and thousands of CPUs are needed per research team.
People who are outside the video coding industry do not understand that it is an industry. It’s run by big companies with large R&D budgets. It’s like saying ”where would we be with AI if Google, OpenAI and Nvidia didn’t have an iron grip”.
MPEG and especially JVET are doing just fine. The same companies and engineers who worked on AVC, HEVC and VVC are still there with many new ones especially from Asia.
MPEG was reorganized because this Leonardo guy became an obstacle, and he’s been angry about ever since. Other than that I’d say business as usual in the video coding realm.
That makes the data much more fragile than metadata fields, though? Any kind of image alteration or re-encoding (which almost all sites do to ensure better compression — discord, imgur, et al) is going to trash the metadata or make it utterly useless.
I'll be honest, I don't see the need for synthesizing a "new image format" because "these formats are ancient (1995 and 1992) - it's about time we get an upgrade" and "metadata [...] gets stripped way too easily" when the replacement you are advocating not only is the exact same format as a PNG but the metadata embedding scheme is much more fragile in terms of metadata being stripped randomly when uploaded somewhere. This seems very bizarre to me and ill-thought-out.
Anyway, if you want a "new image format" because "the old ones were developed 30 years ago", there's a plethora of new image formats to choose from, that all support custom metadata. including: webp, jpeg 2000, HEIF, jpeg xl, farbfeld (the one the suckless guys made).
I'll be honest... this is one of the most irritating parts of the new AI trend. Everyone is an "ideas guy" when they start programming, it's fine and normal to come up with "new ideas" that "nobody else has ever thought of" when you're a green-eared beginner and utterly inexperienced. The irritating part is what happens after the ideas phase.
What used to happen was you'd talk about this cool idea in IRC and people would either help you make it, or they would explain why it wasn't necessarily a great idea, and either way you would learn something in the process. When I was 12 and new to programming, I had the "genius idea" that if we could only "reverse the hash algorithm output to it's input data" we would have the ultimate compression format... anyone with an inch of knowledge will smirk at this preposition! And so I learned from experts on why this was impossible, and not believing them, I did my own research, and learned some more :)
Nowadays, an AI will just run with whatever you say — "why yes if it were possible to reverse a hash algorithm to its input we would have the ultimate compression format", and then if you bully it further, it will even write (utterly useless!) code for you to do that, and no real learning is had in the process because there's nobody there to step in and explain why this is a bad idea. The AI will absolutely hype you up, and if it doesn't you learn to go to an AI that does. And now within a day or two you can go from having a useless idea, to advertising that useless idea to other people, and soon I imagine you'll be able to go from advertising that useless idea to other people, to manufacturing it IRL, and at no point are you learning or growing as a person or as a programmer. But you are wasting your own time and everyone else's time in the process (whereas before, no time was wasted because you would learn something before you invested a lot of time and effort, rather than after).
Overall, I think this is a positive ”problem” to have :-)
Muons are much nicer as you don't have to carry a neutron source around with you.
> However, if anyone is now thinking of standing under the bridge to get their body scanned, they shouldn't bother. First, they'd have to stand still for an hour, and second, the security patrol would be there within minutes.
Security patrol will come and bother you if you hand around the bridge for a few minutes?
There’s a land war in Europe. Hundreds of thousands have lost their lives during the past few years. There have been cases of sabotage against the Baltic states as well as the Nordic states. Things are pretty grim there and lurking around basic infrastructure pretty much guarantees a talk with the police.
Some of the gamification researchers are near the top 500 of that 2% list. Now ask yourself, is gamification something that should make you one of the top 500 scientist in the world? I doubt it, but modern science is a citation game. Nothing else.