In our increasingly digital society, the efficient management of data is essential for everything from everyday communication to complex scientific research. Central to this efficiency are two fundamental concepts: redundancy and compression—silent architects of speed, clarity, and resilience in the digital fabric of modern life. Compression algorithms function not merely as space-savers but as **cognitive filters**, selectively shaping what data remains visible by prioritizing relevance over raw volume. Machine learning