An AI-powered robotic system, Polybot, has successfully automated the complex process of creating highly conductive and defect-free electronic polymer films, paving the way for faster material discovery and manufacturing.

Scientists use computer models to find the best places to gather weather data, aiming to improve predictions for India's vital summer monsoon.

A new study suggests that widespread, regular chest X-rays, powered by AI, could significantly reduce tuberculosis cases and deaths in India.

New research examined how a specific type of AI, known as ANFIS, could help predict the yield of several important crops grown in the Nashik region of Maharashtra, India.

IIT Kharagpur researchers have developed a new framework using blockchain-based technology and token-based incentivisation to securely and fairly share data to train an AI model.

A new study analyses some of the most widely used databases and applications or algorithms available for protein mutations and predicting disease-causing mutations among them.

Imagine if we could predict the properties of materials without having to test them in a lab. This would save a lot of time and money, and it could help scientists discover new materials with amazing properties, like super-strong metals or super-efficient semiconductors. This is exactly what researchers at the Indian Institute of Science (IISc) and University College London are working on. They are using machine learning tools to predict material properties, even when there is limited data available.