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​Which IIT supported the launch of India’s ‘BharatGen’ initiative under the NM-ICPS on 30 September 2024 to make generative AI available in Indian lan
Question

​Which IIT supported the launch of India’s ‘BharatGen’ initiative under the NM-ICPS on 30 September 2024 to make generative AI available in Indian languages?

A.

​Indian Institute of Technology (IIT) Kharagpur

B.

​Indian Institute of Technology (IIT) Bhubaneswar

C.

​Indian Institute of Technology (IIT) Madras

D.

Indian Institute of Technology (IIT) Bombay

Correct option is D

​The correct answer is (d) Indian Institute of Technology (IIT) Bombay

Explanation:

  • The BharatGen initiative, launched on September 30, 2024, is India's first government-funded multimodal large language model (LLM) project aimed at creating inclusive and efficient AI solutions in Indian languages.
  • The project is led by IIT Bombay under the National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS) of the Department of Science and Technology (DST).

Information Booster:

BharatGen Initiative:

Features of BharatGen:

  • Multilingual and Multimodal Models: It incorporates both multiple languages and various modes of content (text, images, etc.).
  • Bhartiya Data Set: The models will be built and trained using data relevant to India.
  • Open-Source Platform: It aims to create an open-source ecosystem for generative AI research in India.
  • Expected Impact: The project is expected to benefit government, private, educational, and research institutions, with a two-year completion plan.

What is a Multimodal Large Language Model?

  • Definition: A multimodal large language model processes and generates multiple types of content, including text, images, and sometimes audio and video.
  • Training: These models are trained on vast datasets containing both text and image data, enabling them to understand the relationships between these different types of content.
  • Applications:
    • Image Captioning: Generating textual descriptions for images.
    • Visual Question Answering: Answering questions about images based on text and visual content.
    • Content Recommendations: Systems that use both text and images to provide personalized content recommendations.

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