I’m an independent AI systems developer, programmer, and technical researcher focused on the engineering behind modern computing systems.

My work spans artificial intelligence, machine learning, GPU computing, CUDA, quantum computing, automation, operating systems, cybersecurity, developer tooling, and high-performance software. I’m particularly interested in what happens beneath the abstractions: how systems actually execute, communicate, scale, fail, and can be engineered more efficiently.

I build and investigate practical systems rather than focusing exclusively on theory. This includes working with Python, C/C++, CUDA, Linux, AI infrastructure, local and distributed AI systems, GPU acceleration, quantum programming, automation frameworks, system administration, and security research.

My technical publishing is an extension of that work. I use Leanpub to document engineering knowledge, experiments, architectures, implementation techniques, and research-oriented material that can be useful to developers, engineers, researchers, and technically advanced readers.

I’m especially interested in emerging technologies where multiple disciplines meet — AI and systems engineering, GPU computing and machine learning, quantum computing and software development, automation and infrastructure, and cybersecurity and system architecture.

The goal is not simply to explain how a technology works, but to understand how to build with it, work around its limitations, examine its internals, and turn complex concepts into working systems.

I continuously develop, test, document, and refine these ideas through practical projects and technical research. My publications reflect that process: detailed engineering references created for people who want to go beyond the surface level and understand the technology they are working with.

https://businessofmachines.blogspot.com/

https://learn.microsoft.com/en-us/users/machinadeusex/

https://g.dev/machinadeusex

https://github.com/porucznikswext-source