rtg

Road to Gramby's Save Format Explained: Roblox Build System Guide 2026

ProTracker 4.1 for Amiga - 8 channels, RTG graphics card screen/window, AHI sound cards, 68000 to 68060, Kickstart 2.04 up to AmigaOS 3.2.x

RTG (graphics card) software for AmigaOS 3.x, written from scratch: Workbench and programs in 256 colours, 16-bit and 24/32-bit on the MNT ZZ9000 and Cirrus-based Zorro II cards, with its own cybergraphics.library and Picasso96API.library.

Reader Translator Generator - NMT toolkit based on pytorch

An independent technical documentation of the Road to Gramby's (Roblox game) construction/save system.

Future Retro Fusion ProTracker 2.3F: CAMD USB MIDI, low-latency scheduling, Picasso96 RTG and Workbench enhancements for Amiga 68k

VirtIO GPU driver (virtiogpu.chip) for AmigaOS 4.1 on QEMU Pegasos2

ColorWheel and GrandientSlider replacement for Amiga OS

This parts addon provides several radial attached Radioisotope Thermoelectric Generators and fuel cells, for Kerbal Space Program.

Micropolis (SimCity) port to AmigaOS 3.2 with RTG

Raptor: Call of the Shadows — Amiga Port (68030/68060 & EC/LC, RTG/AGA, AHI/MHI/CAMD/WAVE). Runs on 68060 (FPU/no-FPU) and 68030 (FPU/no-FPU), RTG and AGA, A1200/A4000, PiStorm/Emu68 and WinUAE, using the original PC v1.2 game data.

Picasso96 RTG graphics card driver backed by a Raspberry Pi over the A314 clockport link

Extraction analysis of PixStory Social Media Dataset using language detection, language translation, tike geotopic parser, tika image object recognition/image caption generation, and PyTorch detoxify.

High-performance computing suite for subatomic materials manufacturing, field-guided atomic assembly, quantum transport, nuclear stability modeling, and multiscale portable power generation.

All of the power, none of the ugly. This electric charge parts addon adding several streamlined radial attached parts: one radioisotope thermoelectric generator (RTG) and one fuel cell, for Kerbal Space Program.

Dose 2 demo for Classic Amiga (Vampire accellerators)

A self-hosted platform for experimenting with AI-assisted analysis of radiology images (MRI, CT, X-ray, mammography, digital pathology) built on the open-source MONAI ecosystem. It wires together annotation, pretrained model inference, a DICOM store/viewer, and an LLM that drafts a human-readable report from the quantitative findings.