Computational linguists at the Varanasi Institute of Advanced Studies have successfully used neural networks to decipher a collection of fragmentary 8th-century Sharada script manuscripts found in a high-altitude Himalayan cave. The texts, written in a technical form of Sanskrit, outline a surprisingly advanced system for classifying riparian bryophytes (mosses and liverworts) based on their ability to filter heavy metals and organic pollutants from mountain streams. This research suggests that ancient Indian scholars possessed a functional understanding of phytoremediation over a thousand years before the concept was formalized in modern science.
The AI model, which was trained on thousands of known Sharada inscriptions, identified recursive structural patterns that describe the chemical affinity of different moss species for specific mineral ores. These treatises provided protocols for the strategic planting of these species along pilgrimage routes to ensure the purity of drinking water. This discovery highlights the intersection of Vedic botanical knowledge and civil engineering in the early medieval period, offering new insights into ancient ecological management.