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Eva Winterschön
@winterschon@mastodon.bsd.cafe  ·  activity timestamp last week

Hello Anti-Ai, Anti-Tech, Anti-Fun Complainers,

Go ahead and keep being miserable while the rest of the world moves on without you; leveraging advanced technology to further the human race, engaging in complex scientific research with supercomputers, solving complex medical diagnoses, improving the success rate of invasive surgical procedures, and continuing efforts to create the world which you already benefit from — despite all of those misinformed views about this evolving technology you refuse to understand.

> "but.. the media told me that skynet.. and those evil chatbots.. something about hallucinations.. and our burning desire to anthropomorphize machine intelligence".

Anyway: https://zenodo.org/records/17196870 here's some recent fun with LLMs.

> [Kelsi Davis] decided to port the Macintosh System 7 OS to run on native x86 hardware, which would be challenging enough with full access to the source code. However, she instead performed this task by analyzing and reverse engineering the System 7 binaries with the aid of Ghidra and a large language model.
>
> Soon enough, she had the classic System 7 desktop running on QEMU with a fully-functional Finder and the GUI working as expected. [Kelsi] credits the LLM with helping her achieve this feat in just three days, versus what she would expect to be a multi-year effort if working unassisted.

#ai #llm #mac #qemu #reverseengineering

Zenodo

Leveraging Artificial Intelligence for Automated Reverse Engineering of Legacy Software Systems

We present an AI-assisted reverse engineering framework that achieves dramatic speedups—on the order of hundreds of times faster than traditional manual methods—by orchestrating specialized agents for evidence curation, struct recovery, and code drafting. Using this approach, we recreated a bootable prototype of Apple System 7.1 from binary analysis in just 3 days, a task that would normally require months or years. The framework enforces strict provenance tracking, tying each change to either disassembly bytes or runtime verification under QEMU. Rather than reporting abstract accuracy percentages, we emphasize artifact-based validation: screenshots, serial logs, and resource extractions that demonstrate Chicago font rendering, menu bar behavior, desktop patterns, and icon display. This work shows how carefully scoped AI assistance, coupled with human review and a structured verification loop, can transform reverse engineering from a slow artisanal process into a systematic, reproducible workflow for preserving computing history and modernizing legacy systems.
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