IndiaAI Mission: National Cloud Compute Capacity Crosses 34,000 GPUs to Boost Indigenous AI Innovation

PWOnlyIAS

June 03, 2025

IndiaAI Mission: National Cloud Compute Capacity Crosses 34,000 GPUs to Boost Indigenous AI Innovation

At the ‘IndiaAI – Make AI in India, Make AI work for India’ event, it was announced that India’s national common compute capacity on cloud has crossed 34000 GPUs.

  • The computing capacity added will boost the IndiaAI Mission by taking  a significant leap toward strengthening indigenous AI capabilities.

About IndiaAI Mission

  • IndiaAI Mission is India’s own Foundation Model launched in the year 2024, to strengthen AI capabilities.
  • Implementation Agency : IndiaAI, an Independent Business Division under Ministry of Electronics and Information Technology (MeitY), is the implementation agency for the IndiaAI Mission
  • Objective: To bolster India’s global leadership in AI, foster technological self-reliance, ensure ethical and responsible AI deployment, and democratize the benefits of AI across all strata of society.
  • Pillars: The Mission has 7 key pillars aimed at building a comprehensive AI ecosystem encompassing,
    • The IndiaAI Foundation Model: It aims to develop and deploy indigenous foundational models trained on India-specific data.
      • Sarvam AI: It will build India’s Sovereign LLM Ecosystem developing an open source 120 billion parameter AI model to enhance governance and public service access
      • Three new startups (Soket AI; Gnani AI; Gan AI) have been selected for building India’s own Foundation Model.
    • Compute Capacity: It includes establishing a state-of-the-art AI compute infrastructure with thousands of GPUs.
      • Significance: It is crucial to develop indigenous foundational models and AI solutions tailored to the Indian context.
    • Datasets: To create a platform for accessible and diverse Indian datasets to train AI models.
      • 367 datasets have been uploaded to AI Kosh.
    • IndiaAI Applications Development: It develop, scales, and promotes impactful AI solutions for various sectors, including healthcare, education, and agriculture.
      • Example: IndiaAI I4C CyberGuard AI Hackathon
    • Future Skills: It aims to advance AI education at all academic levels by establishing Data and AI Labs in Tier 2 and Tier 3 cities
    • Startup Financing: This pillar focuses on providing financial support and resources to AI startups, encouraging innovation and entrepreneurship in the AI space. 
    • IndiaAI Innovation Centre: It focuses on developing and deploying indigenous Large Multimodal Models and domain-specific foundational model

Terms Explained

Large Language Model (LLM)

  • It is a type of artificial intelligence (AI) that is trained on vast amounts of text data and is based on the Transformer model to generate natural language processing (NLP) tasks.
    • Applications: Natural Language Processing (To understand and generate human language); Translation; Content Generation; building chatbots; Summarization; Code Generation; Sentiment Analysis etc

Graphics Processing Unit (GPU)

  • It is a specialized electronic circuit designed for digital image processing and to accelerate computer graphics.
    • It is being present either as a discrete video card or embedded on motherboards, mobile phones, personal computers, workstations, and game consoles
    • Application: It is used in graphics and video rendering; gaming; creative production and artificial intelligence (AI).

AI Kosh

  • AI Kosh is IndiaAI’s flagship platform designed to democratize access to high-quality datasets by providing a repository of datasets, models and use cases to enable AI innovation.
    • It is a hub for AI resources (datasets, models, toolkits, use case library and development environment) to explore and share datasets, build applications and leverage the community.

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Quick Revise Now !
UDAAN PRELIMS WALLAH
Comprehensive coverage with a concise format
Integration of PYQ within the booklet
Designed as per recent trends of Prelims questions
हिंदी में भी उपलब्ध

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