'AmiKit is a compilation of pre-installed and pre-configured Amiga programs running emulated on Windows, macOS, and Linux (as well as running on classic 68K Amigas expanded with a Vampire upgrade card). Besides original Workbench (Commodore's desktop environment/graphical filemanager), AmiKit provides Directory Opus Magellan and Scalos as desktop replacements and its "Rabbit Hole" feature allows you to launch Windows, Mac or Linux applications directly from your Amiga desktop! Anti-aliased fonts, Full HD 32-bit screen modes and DualPNG Icons support is included and this package comes with exclusive versions of the Master Control Program (MCP) and MUI 5 (Magic User Interface). The original AmigaOS (version 3.x) and Kickstart ROM (version 3.1) are required, also the recently released AmigaOS 3.2 is supported. You can also get the needed files from the Amiga Forever package(s). It even supports emulating AmigaOS 4.x (for PowerPC) easily through Flower Pot. Here's an extensive overview video by Dan Wood. An Amiga Future review of an earlier 2017 version can be read here. "Everything began in 1994 when my parents bought an Amiga 500 for me and my brother," explains AmiKit's developer. "I was 14 years old..." Fast forward to 2005, the AmiKit was born — an emulated environment including more than 350 programs. It fully replaced my old Amiga and it became a legend in the community over the years. Fast forward to 2017, a brand new AmiKit X is released, originally developed for A.L.I.C.E., followed by the XE version released in 2019, Vampire edition in 2020 and Raspberry Pi in 2021. The latest & greatest version was released in 2020. When someone, who has never heard about Amiga before, asks me why I would want to turn current modern computer into something retro and old fashioned, my short answer is: "Simply because I love Amiga!"' -- source: https://slashdot.org/story/22/05/29/2232204 Cheers, Peter -- Peter Reutemann Dept. of Computer Science University of Waikato, NZ +64 (7) 858-5174 (office) +64 (7) 577-5304 (home office) https://www.cs.waikato.ac.nz/~fracpete/ http://www.data-mining.co.nz/