3D ASCII rendering
Unusual rendering styles has become very popular lately. In this video, Acerola tries to write an ASCII based 3D rendering shader. Very interesting.
GPU programming chaos
GPU programming used to be just about rendering graphics. As we’ve moved into bitcoin mining and AI, eisfrosch goes over the current chaotic programming environments for GPUs.
Re-creating PS1 graphics with modern hardware
Acerola has a bunch of great graphics videos. In this one, he talks about why PS1 graphics looked the way it did.
I learned that PS1 actually had realtime camera distance tessellation – something that wasn’t available to desktop GPUs until the introduction of tessellation shaders.
Edge shading
Gamelogic does a decent intro to a few simple edge detection shaders used in toon-style rendering.
2.5D ASCII art concept
8 years ago Tenkai Games Dev Room made a cool ASCII nethack-like prototype, and has only gotten like 60k views. It’s amazing how things like this exist yet nobody has seen them.
Newbie vibe coded a top-ranked mobile game
Ron decided to learn to code in 2024. He proceed to use AI to vibe-code a game called Letterlike. It’s now one of the top ranked mobile games on Steam and the #1 paid word game on Android.
He tells his story on this reddit post.
Vibe coding is here. People are building viable commercial products with less than a year of coding experience. Sure this isn’t a solution that needs a lot of security like an online service, but here it is.
Best AI for coding
David Gewirtz reviews a bunch of AI tools for coding; and does some ranking.
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How to write kernel drivers with Rust
not-matthias has blogged his journey on writing a kernel driver with Rust.
He has a few other fun hacky posts about reverse engineering a digital jukebox in a bar to vote for his songs.
3D Math Primer for Game Development
The author’s of the 3D Math Primer for Graphics and Game Development book have provided their intro book for free online. It’s basic for those getting started, but nothing beats free and the author has done a number of GDC talks.
Google report on using AI for internal code migrations
Google published a report on it’s effort to migrate code to the latest dependencies – an often thankless task fraught with risk. Google’s code migrations involved: changing 32-bit IDs in the 500-plus-million-line codebase for Google Ads to 64-bit IDs; converting its old JUnit3 testing library to JUnit4; and replacing the Joda time library with Java’s standard java.time package. The 32-bit ID’s were particularly rough because they were often generically defined types that were not easily searchable.
They used a collection of AI tools as well as manual code reviews and touch-ups to achieve their goal. They emphasize that LLMs should be viewed as complementary to traditional migration techniques that rely on Abstract Syntax Trees (ASTs), grep-like searches, Kythe, and custom scripts because LLMs can be very expensive.
The results?
With LLM assistance, it took just three months to migrate 5,359 files and modify 149,000 lines of code to complete the JUnit3-JUnit4 transition. Approximately 87 percent of the code generated by AI ended up being committed with no changes. For the Joda-Java time framework switch, the authors estimate a time saving of 89 percent compared to the projected manual change time.
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