analiza aiqbench

This article evaluates practical GPU acceleration for data preparation tasks using specific libraries like cuDF, cudf.pandas, and the Polars GPU Engine. It addresses a core infrastructure question regarding where to execute heavy data science workflows within modern AI pipelines. By focusing on hardware utilization for foundational ML steps rather than consumer electronics or general software updates, it remains central to machine learning engineering.