Source: DDNEWS

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Context

India’s first Artificial Intelligence (AI) data bank was launched by the Ministry of Science and Technology. It was announced during the 7th Edition of the ASSOCHAM AI Leadership Meet 2024.

What is ASSOCHAM?

The Associated Chambers of Commerce and Industry of India (ASSOCHAM) is a non-governmental trade association and advocacy group based in New Delhi.

 The organisation represents the interests of trade and commerce in India and acts as an interface between issues and initiatives.

What is an AI Data Bank?

An AI Data Bank refers to a centralized repository or database that stores a wide variety of structured and unstructured data that can be used to train, test and develop Artificial Intelligence (AI) models.

These data banks are designed to offer diverse, high-quality datasets that support the development of AI algorithms for a range of applications such as predictive analytics, machine learning, natural language processing, computer vision and more.

Predictive analytics is the process of using data to forecast future outcomes. It uses statistical models, machine learning artificial intelligence and data analysis to find patterns that can predict future behavior. 

Machine learning is a subset of artificial intelligence that allows systems to learn and improve from data without being explicitly programmed. ML uses algorithms to analyze large amounts of data, learn from the insights, and then make informed decisions.

Features of an AI Data Bank

AI data banks contain varied datasets across different domains such as healthcare, finance, security, climate and public services.

Data banks are used to train AI systems by providing the vast amount of data necessary for algorithms to recognize patterns, make decisions and improve their predictions over time.

AI data banks enable real-time analysis by integrating data from different sources like satellites, IoT devices and drones, providing timely insights for applications such as national security, disaster management and public health.

AI data banks emphasize high-quality, clean and well-labeled datasets to ensure AI models are trained effectively. They also often include governance frameworks to address issues like data privacy, bias and ethical concerns.

These data repositories serve as a resource for startups, researchers and developers offering access to essential datasets that help in creating scalable and inclusive AI solutions.

Applications of AI Data Banks

AI data banks store data from surveillance, sensors and drones that can help in detecting threats and enhancing border security, real-time monitoring and predictive analytics for potential attacks.

By using satellite data, climate models and sensor inputs, AI data banks can help predict natural disasters, optimize evacuation plans and improve disaster response.

They can house medical records, clinical trials and genomic data to develop AI models for disease prediction, diagnostics and treatment.

Sources:

DDNEWS