BharatGen

The BharatGen Vision

BharatGen is an initiative by BharatGen Consortium

BharatGen envisions becoming a pioneering suite of Generative AI Technology, crafting a soft digital AI infrastructure attuned to the needs of India’s unique socio-cultural landscape & diverse sectors. In the immediate term, it will foster grassroots innovation & knowledge generation, underpinning economic acceleration & technological self-reliance.

Strategically, the initiative is set to nurture an active AI ecosystem that amplifies India’s voice in the global arena, unlocking new potentials for all stakeholders in the long term. BharatGen strives for India’s leap into an AI-augmented future, where technology is inclusive, growth is sustainable, & innovation permeates every corner of our diverse nation.

BharatGen - Digital AI Infrastructure

BharatGen Consortium

BharatGen Initiatives

AI leadership

Generative AI leadership

Innovation

Grassroot Innovation

cultural preservation

Cultural Preservation

economic growth

Economic Growth

focus

India Centric Lens

AI ecosystem

Developing AI ecosystem

How? Key Activities

USPs of BharatGen

With a vision deeply integrated into the nation’s fabric, BharatGen paves the way for an inclusive AI future where innovation thrives, cultures are preserved, & the economy booms – all within a framework that is quintessentially Indian.

AI vision

Foundational & Strategic AI Vision

BharatGen is a vital part of India’s digital AI infrastructure, integrating AI into the nation’s digital development beyond just service offerings.

Cultural Integration

Deep Cultural Integration

A comprehensive approach integrates India’s cultural & linguistic nuances into AI, fostering a deeper understanding & interaction.

knowledge generation

State-of-the-Art Knowledge Generation

Led by top Indian institutes, a dedication to ongoing research & development is propelling India to the forefront of AI knowledge & leadership.

Ecosystem Development

Comprehensive Ecosystem Development

BharatGen’s Vision: A comprehensive AI ecosystem fostering grassroots innovation and global AI leadership.

True Technological Self-Reliance

A clarion call for technological independence, built on an indigenous framework that embodies the ethos of ‘Made in India’.

Holistic India Centricity

It seeks to align AI with India’s varied needs, aspirations, & values, excel language for strategic & meaningful integration with national priorities.

PPP

Public Private Academia Partnership

A coordinated PPP model aligns government, academia, & industry to promote fair & sustainable AI development.

Knowledge Generation for BharatGen

Fundamental Research Advances

  • Strategic endeavour to position India as a leader in the generative AI space.
  • Beyond replicating existing models, crafting a path tailored to India’s diverse linguistic, cultural, & societal fabric.
  • Dual focus on pushing AI technology boundaries & ensuring relevance to India’s context & use cases.

Strategic Research Pillars

  1. Data & Model Innovation: Enhancing data efficiency & model performance.
    • Subset Selection efficient training.
    • Knowledge Distillation to optimize model efficiency.
    • Curriculum Learning for progressive skill acquisition.
    • Efficient Model Composition to enhance capabilities with minimal resources.
  2.  Advanced Capabilities & Applications: Extending AI capabilities for broader societal impact.
      • Multimodal Fusion for comprehensive understanding across data types.
      • Advanced Reasoning for complex decision-making & problem-solving.
  3. Interactivity & User Experience: Personalizing AI interactions for enhanced user engagement.
    • Personalization Techniques for dynamic, context-aware conversations.
    • Explainability & Transparency to foster trust & ease of use.
4. Ethical AI & Privacy: Upholding ethical standards & user privacy in AI development.
  • Federated Learning for decentralized, privacy-preserving model training.
  • Bias Detection & Mitigation to ensure fairness & equity.
  • Grounding of Generated Text to maintain factual correctness.
5. Integration & Future Technologies: Merging AI with emerging technologies for innovative solutions.
  • Integration with other technologies such as IoT, & AR/VR for enhanced applications.
  • Neuro-symbolic AI & Continual Learning for next-generation AI capabilities.
6. Evaluation & Benchmarking
  • Setup robust evaluation frameworks (evaluation metrics & benchmarking standards) to measure progress & guide future research directions.

Bharat Data Sagar: Catalysing AI for India's Unique Needs

Establish a foundational data ecosystem to accelerate AI innovation across India’s diverse and unique landscape

Core Objectives

Core Objectives

Contextual Relevance: Ensure AI systems are trained on data that reflect the real-world complexities & nuances of Indian society & its diverse industries.

Data Diversity: Emphasize collecting not just linguistically & culturally significant data but also industry-specific, regional, & societal data to address India’s myriad use cases.

Strategic Importance

Bridging Data Gaps: Address the scarcity of India-centric datasets, in contrast to the abundance of Western-centric data, to foster AI solutions that are genuinely useful for Indian contexts.

Inclusive Development: Aim for AI applications that serve the entire spectrum of India’s demographic & geographic diversity, ensuring no community is left behind.

Collaboration & Incentives

Collaboration & Incentives

Community Engagement: Drive contributions from a broad spectrum of stakeholders, including individuals, academia, public entities, & private organizations.

Rewarding Participation: Offer compelling incentives such as early access to AI models, tools, & potential recognition or financial benefits to encourage & appreciate contributions.

Framework

Supportive Framework

Ease of Contribution: Provide a robust infrastructure that simplifies data contribution while upholding the highest st&ards of data privacy & security.

Reciprocal Benefits: Create a self-sustaining ecosystem where contributors not only enhance the dataset but also gain access to improved AI capabilities, fostering a cycle of innovation & progress.

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