|
India's ambition is to establish a sustainable and competitive foundation for AI model capacity that can support long-term national requirements that will reduce the structural dependence on external providers, according to a government white paper.
The White Paper, prepared by the Office of the Principal Scientific Adviser to the Government of India, called for enabling inclusive and affordable adoption across Indian languages, regions, and sectors through a layered ecosystem of large models, multimodal systems, and small language models, and position India as a credible contributor to global innovation. Foundation models (FM) are a core enabling layer in modern AI systems because they can be adapted for many applications, reducing the need to train separate models from scratch for each task. The White Paper released this week also provided details on India's approach, which is centred on building indigenous capability across the foundation-model stack. Rather than relying on a single model, India is developing an ecosystem that combines shared compute access, India-centric data and model repositories, and multiple model-building efforts across text, speech, multimodal, and sectoral systems. The white paper essentially provides an understanding of India's approach to advancing indigenous foundation models through public-private collaboration and to governing these systems that support trust, accountability, and responsible adoption. The versatility of Foundation Models makes them a critical layer of today's AI ecosystem and a key area for innovation in India. Therefore, developing indigenous foundation models is a strategic priority. India's objective is to harness foundation models for inclusive growth and public good, while ensuring they are governed in a manner consistent with the country's values, legal framework, and security interests, the government has asserted. The global foundation-model landscape is no longer defined only by model performance or market adoption. The white paper said it is increasingly shaped by who can secure and scale the enabling infrastructure required to build models, high-end compute and data centre capacity, access to specialised chips, and large, high-quality datasets. Across countries, the strategic direction is to strengthen domestic capacity to train and deploy models at scale, while also shaping the supply chains and platforms that determine access. "Some jurisdictions are viewing advanced computing and chip supply chains as strategic assets by implementing stricter controls, while others are pairing rules with higher expectations for companies to be responsible and ready to follow regulations in the early stages of model development," the white paper read. Some countries are also scaling national computing capacity and directing AI deployment toward industrial integration. "These patterns reinforce a common insight: foundation models are increasingly being treated as a sovereign capability, anchored in infrastructure and ecosystem depth," it read. India's approach is centred on building indigenous capability across the foundation-model stack, rather than relying on a single model. The white paper has been prepared with inputs and feedback from domain experts, stakeholders, and others during various stages of its development. (ANI)
|
