India's AI Ambitions: Government Receives 67 Proposals for Indigenous Foundational Models

India's Push for Indigenous AI Models

In a significant move towards technological self-reliance, India has announced plans to develop its own AI foundational model within the next 10 months. This initiative comes in response to global advancements, particularly China's DeepSeek model, and aims to position India as a competitive force in the AI landscape 1

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Government Initiatives and Funding

The Indian government has demonstrated strong commitment to AI development through various initiatives:

1. The IndiaAI mission, approved in March 2023, with a budget of ₹10,372 crore 1

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2. An allocation of ₹2,000 crore in the Union Budget 2025 for the IndiaAI mission 1

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3. Plans to establish three AI Centres of Excellence in education 1

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Proposals and Evaluation Process

The Ministry of Electronics and Information Technology (MeitY) has received 67 proposals for building AI foundational models, including 20 for large language models (LLMs) 2

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. Notable applicants include Sarvam AI, CoRover.ai, and Ola 2

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. A high-level technical committee is being organized to evaluate these proposals within a month 2

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BharatGen: A Government-Funded AI Initiative

Among the various initiatives, BharatGen stands out as a government-funded project with an investment of ₹235 crores (approximately $27 million) . Led by Prof. Ganesh Ramakrishnan, BharatGen aims to create AI models that cater to India's diverse linguistic and economic landscape .

Challenges and Opportunities

Despite the ambitious plans, India faces several challenges in developing its AI ecosystem:

1. Limited access to high-quality data, especially in Indian languages 1

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2. Shortage of skilled professionals 1

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3. Privacy and security concerns 1

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4. Lack of clear regulatory frameworks 1

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5. A historically lagging AI research backbone compared to countries like China 4

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Future Outlook and Strategies

To overcome these challenges and boost AI development, experts suggest:

1. Increased collaboration between policymakers, academia, and the private sector 1

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2. Focus on building smaller, domain-specific language models 4

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3. Development of "trinity" models combining specific languages, domains, and tasks 4

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4. Leveraging government funding and projects like Bhashini for machine translation models 4

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As India progresses in its AI journey, the success of these initiatives will depend on balancing innovation, affordability, and ethical AI governance 1

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. The country's ability to address its unique challenges while fostering a robust AI ecosystem will be crucial in realizing its ambition of becoming a global AI powerhouse.