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SIA is a self-improving AI framework designed to improve the performance of models or agents on benchmark tasks. It uses an iterative loop where a meta-agent creates or updates a task-specific target agent, while a feedback agent studies results and proposes improvements. The framework can refine both the harness around the task and the agent implementation itself. It is aimed at research and experimentation across tasks such as machine learning benchmarks, legal classification, code...

Adrix.NT Java Works :: Sources & Build Projects includes - Paged Lists of Object & Iterators Library for Java - Action / Entity Model for Java - VR Ax AWT Clock Java Component - VR Multi Dimensions Array Library - VR MDArray List Manager Library - VR Adjacency (List | Matrix) Direct Graph Lib - VRJMosaic cells sliding game with automatic resolver - VR RectsWorld Sample Applic - VR Free Chess 2D Applic also contains - Other Utils Libraries - Demo and Test Applications -...