I really like the idea that compression is intelligence, there are so many tricks an interesting ideas related to it. A bunch of them are described in the article, but you can imagine a long tail of many more inscrutable tricks chained together to get really incredible shrinkage in data.
Hutter prize (I think mentioned in a 3b1b video somewhere else in this thread) is a great example. Given this was written before advent of LLM, I would love to see someone throw openAI/Anthropic levels of compute at a similar problem to see what the swarm can produce.
The newest submissions to Hutter Prize made crazy jumps by just replacing the LSTM with a transformer and training it.
35'000$ for a prompt and some training is a nice chunk of cash.
Next steps are replacing the encoders and all the other human-biased compression parts by just raw data and training, probably another 20-30% is up for grabs.
H.264 High Profile is close to Patent Free. [1] I often wonder how much more efficiency could we get if we were to increase block size outside of spec.
Nvidia Shield is hardly the most popular anything. Roku has 43% of the market and Amazon has 35%.
Would be interesting to see if we could segment third-party from TV-embedded (see quote), but the metrics from the article seem to reflect actual consumer usage, as most consumers just use what comes in the TV they buy nowadays.
> This reflects a consolidated approach and eliminates yet another device in the home, and it’s catching on, as just 34% consider streaming media players as their primary viewing device. Meanwhile, 56% said the same for smart TVs.
Nvidia hasn't released a new model of the Shield since 2019. The current Apple TV model, Google TV model, Roku model, Fire TV, and Onn models support AV1.
AV1 decode works well enough even on quite old devices, and it has more favorable quality and size, individually or when considering both. I prefer it to h264 (or vp9 or even h265) at this point, and there isn't a particular need for hardware decode to benefit from it. On Youtube (probably the biggest and most accessible source of av1 video), when comparing size and quality on different codecs (h264/vp9/av1), av1 is either gonna have much smaller size while keeping some level of quality, or have better quality at similar size, or even have both be better.
There is no need to have a final one. It's no problem to keep supporting older codecs and add new ones in new products, as long as there's a "common ground" of widely supported codecs.
At any point in time there's only a couple video codecs you should be using. When we can repeatedly shave off 30% of video bandwidth, there's no reason to stop making one or two new ones every decade.
WebP stands on its own merits but it's profoundly annoying that as of Pop OS 22.04 I still have to open them up in Firefox instead of Eye of Gnome. Compatibility issues like this are littered everywhere. This laziness on the part of supporting WebP is a significant driver of continued use of PNG.
Yes, it's very disheartening. We're approaching two decades of WebP, after all. At this point it's not even worth implementing its support because JXL is superior in every use case.
Not really, lossless WEBP still decodes much faster than lossless JXL, so if you need to decode the images faster, you use WEBP. Yes, you could also speculatively decode the JXL images to hide the decode time.
For lossy, neither is not in a good place, since lossy AVIF beats both lossy JXL and lossy WEBP. Lossless AVIF is a joke and barely competes with PNG.
With JPEG XL finally being allowed into mainstream web browsers, we’ll hopefully see more native platform support and be able to slowly phase every older codec out, since JPEG XL does very well at more or less everything (except for animation, compared to video codecs).
This reminds me that I still haven't watched `part 2` of a very nice video from 3Blue1Brown - "Compression is Intelligence". YouTube suggestions, definitely failed me with this one.
For personal use, if those are your only two choices, then go with H.265 for higher efficiency, or H.264 for wider compatibility. If other codecs are an option, go with AV1 for higher efficiency. It’s currently the best and already pretty widely supported.
The main reason to use H.264 in 2026 is legacy device support. Some devices cannot play H.265, but H.264 is playable almost anywhere, as a 20+ year old codec.
I was surprised that Twitter only lets you upload H.264 still, in 2026.
It depends on how you want to play or share the media.
E.g. I remember having lots of issues sharing smaller video files encoded with H.265 via both WhatsApp and Messenger. iMessage doesn't support H.265 (or at least it didn't work for me at the time).
"The H.264 video, 300 frames long is 175KB. A single frame of that video in PNG is 1015KB. It looks like we're storing 300 times the amount of data in the video. But the file size is a fifth. So H.264 would seem to be 1500x as efficient as PNG. How is this even possible? All right, what's the trick?"
Mostly the trick is they're comparing lossy to lossless compression which doesn't even make any sense.
Actually I had the same thought, but this is obviously an article for people who don't know the difference between lossless and lossy compression. Ok, you might argue that it's not a good fit for HN, but going by the many times it seems to have been posted here, some people disagree.
It makes tons of sense to compare those numbers. It's a big part of how you benchmark lossy compression. I guess in some sense they should use BMP instead of PNG but it's arguable.
Hutter prize (I think mentioned in a 3b1b video somewhere else in this thread) is a great example. Given this was written before advent of LLM, I would love to see someone throw openAI/Anthropic levels of compute at a similar problem to see what the swarm can produce.
https://arxiv.org/html/2404.09937v1
35'000$ for a prompt and some training is a nice chunk of cash.
Next steps are replacing the encoders and all the other human-biased compression parts by just raw data and training, probably another 20-30% is up for grabs.
[1] https://meta.wikimedia.org/wiki/Have_the_patents_for_H.264_M...
https://engineering.fb.com/2026/06/22/video-engineering/adop...
And soon AV2
https://av2.aomedia.org/
Would be interesting to see if we could segment third-party from TV-embedded (see quote), but the metrics from the article seem to reflect actual consumer usage, as most consumers just use what comes in the TV they buy nowadays.
> This reflects a consolidated approach and eliminates yet another device in the home, and it’s catching on, as just 34% consider streaming media players as their primary viewing device. Meanwhile, 56% said the same for smart TVs.
https://www.cepro.com/news/roku-amazon-lead-streaming-media-...
And then we'll get AI-designed hardware codecs for them.
Otherwise we will have this:
https://xkcd.com/927/
PNG: 1039993 bytes - baseline
optimized*: 541539
WebP: 398974 - lossless mode, of course.
JPEG XL: 310778 - lossless, quick, and easy.
*after monumental compute effort; still probably some room for improvement but the effort is ridiculous.
For lossy, neither is not in a good place, since lossy AVIF beats both lossy JXL and lossy WEBP. Lossless AVIF is a joke and barely competes with PNG.
4.nov.2016 https://news.ycombinator.com/item?id=12871403 219 comments
17.mar.2022 https://news.ycombinator.com/item?id=30710574 219 comments
24.may.2019 https://news.ycombinator.com/item?id=19997813 180 comments
14.jun.2024 https://news.ycombinator.com/item?id=40681306 205 comments
Should I use H.264 or H.265?
I was surprised that Twitter only lets you upload H.264 still, in 2026.
How are you generating video?
How are you playing it back?
E.g. I remember having lots of issues sharing smaller video files encoded with H.265 via both WhatsApp and Messenger. iMessage doesn't support H.265 (or at least it didn't work for me at the time).
Mostly the trick is they're comparing lossy to lossless compression which doesn't even make any sense.
They're not actually confused here. It's a writing style, where you pose an interesting problem/scenario, then explain it.