Adrian Borucki is an AI programmer with 14 years of experience building and researching practical and unconventional intelligence systems, currently based in Warsaw. He implements deep learning solutions in PyTorch across NLP, recommendation, graph processing and lightweight computer vision, and pursues independent R&D into alternative AGI approaches such as OpenCog and Non-Axiomatic Reasoning (OpenNARS). Adrian has production experience shipping models and services at companies from startups to enterprises (User.com, Aperto, Samsung) and contributed to the well-known OpenCog AtomSpace by porting core components to Python 3. He favors correctness over speed, mentoring engineers and maintaining robust back-end foundations (Flask, Docker, AWS) when projects demand it. Notably, his AGI research led to a presentation at the 2022 AGI conference, reflecting a rare blend of applied ML engineering and deeper symbolic/graph-based AI experimentation.
15 years of coding experience
9 years of employment as a software developer
Matura General Education, Matura General Education at Stanislaw Staszic High School in Warsaw
Bachelor of Engineering - BE Computer Science, Bachelor of Engineering - BE Computer Science at Warsaw University of Life Sciences
The OpenCog (hyper-)graph database and graph rewriting system
Role in this project:
Back-end Developer
Contributions:10 commits, 3 PRs, 18 comments in 6 months
Contributions summary:Adrian's contributions primarily focused on porting the OpenCog Atomspace to Python 3, which involved updating the codebase to align with the new syntax. This includes modifications to Cython files (e.g., atomspace.pyx, exec.pyx), updating import statements, and fixing issues related to Python 3 compatibility. Furthermore, the user addressed import issues and refactored the TruthValue class.
Contributions:83 commits, 40 pushes, 3 branches in 4 months
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