RastaConverter https://github.com/ilmenit/RastaConverter is a graphics converter from modern computers to old 8bit Atari computers. In recent versions I added ability to generate two pictures blended together into a high-color output, leading to pictures with 800 or more unique perceived colors. The picture is displayed in graphics mode 15 (Antic Mode E) that has by default four unique colors.
The conversion process is optimization of the Kernel Program. It uses most of the Atari graphics capabilities including sprites, midline color changes and sprite multiplication.
Key capabilities:
- Extremely optimized emulator of subset of 6502 CPU and ANTIC to simulate execution on real machine.
- Optimization: Late Acceptance Hill Climbing (LAHC) and Diversified Late Acceptance Search (DLAS), with support for reproducible runs, evaluation limits, auto-save and resume.
- Dithering: chess, Floyd–Steinberg, random-Floyd, line,
line2, 2D, Jarvis, simple, and Knoll; tunable strength and randomness.
- Color distance: YUV (default), RGB Euclidean, CIEDE2000, and CIE94; independently selectable for preprocessing and optimization.
- Dual-frame mode: two alternating frames (A/B) with YUV or RGB blending, optional temporal luma/chroma penalties to reduce flicker, and export of both per-frame and blended outputs.
- Performance: multi-threaded execution with per-thread line caches and configurable cache size.
Considering that even simple neural networks are universal approximators, and that most of the intelligent tasks require prediction of the next state(s) according to previous state, aren't biological or artificial brains "just" universal approximators of extremely complex function of the world?
I did recently also a tool for prime numbers visualization:
https://ilmenit.github.io/prime-fold/
It's not only for visualization but also discovering of mathematical functions that generate or embed prime numbers using evolutionary algorithms and fitness functions. It has two modes:
PrimeFold Mode (2D Embedding): Enter or evolve two functions, f_x(n) and f_y(n), to map numbers to 2D points. Primes and composites are visualized differently. This mode helps you discover spatial patterns and structures unique to primes. Example: f_x(n) = n, f_y(n) = n^2 or simply n, n^2.
PrimeGen Mode (1D Generation): Enter or evolve a single function, f(n), to generate numbers. The app visualizes which outputs are prime and how many unique primes are produced. Example: f(n) = 2*n + 1.
Trying to stress-test LLM Agents on RetroArch codebase (quite complex, with a lot of conditional compilation) Gemini 2.5 Pro admitted lack of own capabilities. That's actually nice behavior that I'd expect to see more from other models that don't stop and make more and more mess.
Thank you for the feedback! I was thinking about the force forward mechanic and as it exists in mentioned game. In Pressure stepping back is defensive until reaching the edge of the board. The biggest problem with the current design I have with endgame when it's balanced to 1 token left on each side. This could be a draw, because it's in most of the cases is not possible to lead to surrounding the leftover token. With 2 to 1 left still (depending on a board setup) it's possible to dance around to avoid capture.
Do you have some proposal that would work in this game?