It's official that Android will be rolling out dav1d to replace libgav1 as a system wide codec on Android 14 devices, though there is potential for it to be supported as far back as Android 10. Finally, libgav1 is no more!

As someone who spends time programming, I of course find myself in conversations with people who aren't as familiar with it. It doesn't happen all the time, but these discussions can lead to people coming up with some pretty wild misconceptions about what programming is and what programmers do.

• I'm sure many of you have had similar experiences. So, I thought it would be interesting to ask.

See title. For those who don’t know, the Mandela Effect is a phenomenon where a large group of people remember something differently than how it occurred. It’s named after Nelson Mandela because a significant number of people remembered him dying in prison in the 1980s, even though he actually passed away in 2013.

I’m curious to hear about your personal experiences with this phenomenon. Have you ever remembered an event, fact, or detail that turned out to be different from reality? What was it and how did you react when you found out your memory didn’t align with the facts? Does it happen often?

Some big changes have been introduced in SVT-AV1-PSY, courtesy of Clybius, the author of aom-av1-lavish! Here is the changelog:

Feature Additions

• Tune 3 A new tune based on Tune 2 (SSIM) called SSIM with Subjective Quality Tuning. Generally harms metric performance in exchange for better visual fidelity.
• --sharpness A parameter for modifying loopfilter deblock sharpness and rate distortion to improve visual fidelity. The default is 0 (no sharpness).

Modified Defaults

• Default 10-bit color depth. Might still produce 8-bit video when given an 8-bit input.
• Disable film grain denoising by default, as it often harms visual fidelity.
• Default to Tune 2 instead of Tune 1, as it reliably outperforms Tune 1 on most metrics.
• Enable quantization matrices by default.
• Set minimum QM level to 0 by default.

That's all, folks! Keep an eye on the master branch for more changes in the future!

From the landing page:

Tart is a virtualization toolset to build, run and manage macOS and Linux virtual machines on Apple Silicon.

Tart is using Apple’s native Virtualization.Framework that was developed along with architecting the first M1 chip. This seamless integration between hardware and software ensures smooth performance without any drawbacks.

Tart powers several continuous integration systems including on‑demand GitHub Actions Runners and Cirrus CI. Double the performance of your macOS actions with a couple lines of code.

With more than 36,000 installations to date, Tart has been adopted for various scenarios. Its applications range from powering CI/CD pipelines and reproducible local development environments, to helping in the testing of device management systems without actual physical devices.

I’ve been distrohopping for a while now, and eventually I landed on Arch. Part of the reason I have stuck with it is I think I had a balanced introduction, since I was exposed to both praise and criticism. We often discuss our favorite distros, but I think it’s equally important to talk about the ones that didn’t quite hit the mark for us because it can be very helpful.

So, I’d like to ask: What is your least favorite Linux distribution and why? Please remember, this is not about bashing or belittling any specific distribution. The aim is to have a constructive discussion where we can learn about each other’s experiences.

My personal least favorite is probably Manjaro.

Consider:

• What specific features/lack thereof made it less appealing?
• Did you face any specific challenges?
• How was your experience with the community?
• If given a chance, what improvements would you suggest?

In recent times, my opinion about self-hosting has changed. Instead of paying for multiple services, I am now renting a decently sized VPS on Scaleway, and hosting all my projects on them. It’s been three months, and it has been working out great for me.

Today, we have a very exciting development - Aviator, the Linux GUI for AV1 encoding, has switched to an in-house custom fork of SVT-AV1 dubbed SVT-AV1-PSY!

Featuring development efforts from BlueSwordM (author of the previous custom fork), myself (Gianni), and others, this change will enable us to have much more control over the encoder's development so that it aligns most effectively with Aviator's number one priority: visual quality.

So far, SVT-AV1-PSY's most noteworthy feature is a variance boost patch that appreciably improves intra- and inter-frame fidelity consistency across wide range of content. Visual fidelity per bit is estimated to have increased by up to 5% with this patch, which currently isn't present in mainline SVT-AV1.

Even though this patch should inevitably make it to mainline, the gains from having more direct control are already being realized as we can implement features like this flexibly at a pace we decide.

Aside from that, FFmpeg has been updated to version 6.1, the SCM toggle has been replaced with a more useful Open GOP toggle, and the README has been modified to reflect some of these more recent changes with regard to SVT-AV1-PSY.

Thank you for using Aviator, and happy encoding!

Aviator can be downloaded on Flathub, where 0.5.0 will be available soon.

This blog post on the Codec Wiki by encoder Trix presents extensive benchmarking of SVT-AV1 1.8.0 on animated content using both objective metrics and subjective image comparisons (the subjective part is coming soon). Short high-quality anime clips were encoded directly with SVT-AV1 across a range of settings. SSIMULACRA2 visual quality scores and encoding speeds were measured for each encode, along with bits per pixel to calculate encoding efficiency. The results are presented through graphs showing metric scores and speed, alongside comparison images enabling subjective evaluation of visual quality (again, comparison images coming soon for subjective analysis). This rigorous testing methodology provides insightful analysis of how SVT-AV1 performs when encoding animation.

This program generates an AV1 video encoding command for use with Av1an, a chunked AV1 encoding tool for use with aomenc, SVT-AV1, and rav1e.

This tool takes in the video resolution, frame rate, desired encoder, speed preset, and target bitrate range as command line arguments. Based on these parameters, it calculates settings like tile columns/rows, lag-in-frames, CRF, and encoder speed preset. Then, it injects these into a generated encoding command string.

The output is a full Av1an command that can be run to encode a video based on the specified settings.