Government Support for Indian LLM Development

Government support is vital for infrastructure such as GPU resources necessary for creating sovereign LLMs that deliver affordable AI solutions for the broader public. India boasts a robust emerging AI research ecosystem across both academia and industry, holding the third position globally in producing high-quality AI publications.

Support must encompass more than hardware; it should also involve well-curated local datasets, comprehensive AI governance frameworks, and a skilled workforce proficient in various roles from data annotation to AI leadership.

The Importance of Indian Government Support for LLMs

The pressing question today is how crucial government support from India is for the advancement of Indian LLMs and if local startups can effectively create LLMs without governmental backing. This contemplation extends to whether government assistance is essential for large-scale AI advancements.

Global Context and Examples

To understand this, it is useful to look at global examples. Major LLMs such as GPT-4o, Gemini, Llama, Claude, Mistral, and others are predominantly developed and funded by private enterprises and startups, often assisted by venture capital. Usually, substantial tech companies like Google or financially robust startups like OpenAI are behind the development and implementation of these models. For instance, OpenAI has substantial support from Microsoft, while Llama benefits from an extensive open-source ecosystem, partly funded by Meta.

This reality substantiates the notion that resourceful LLMs can be developed even without governmental support.

The Case for a Sovereign AI Approach

However, if a sovereign AI is needed from a governmental perspective to provide cost-efficient LLM resources for the public, it strongly recommends that the government supports the necessary infrastructure, like GPU resources, to create such LLMs.

A Balanced Approach to AI Development

The writer suggests a balanced approach, where a healthy mixture of sovereign and commercial models can be cultivated. Beyond merely supplying hardware, the support required for a thriving startup ecosystem to build LLMs extends to various components, including:

• Establishing a solid ecosystem for AI research.
• Creating well-curated localised data repositories.
• Implementing a strong AI governance structure to monitor and enhance models.
• Developing a robust human resource ecosystem that nurtures talent from data labelers to AI managers and chief AI officers.

India’s Emerging AI Research Ecosystem

India is witnessing an evolving AI research ecosystem, supported by institutions such as IITs, IIITs, NITs, and commercial labs like Google Research India, Microsoft Research India, and IBM Research India. Despite being third globally in high-quality AI research publications, as analysed by the research agency Itihaasa, it still trails behind China significantly.

Nonetheless, there are encouraging signs of growth in India’s AI research landscape.

Government Contributions to Data Repositories

The government can play a pivotal role through initiatives like AIKosh, which serves as a repository for Indian-centric datasets. This initiative has been well-received and is anticipated to greatly benefit the LLM development efforts of AI startups and other sector participants. Expanding the scope, variety, and reliability of datasets within AIKosh will immensely support Indian LLM initiatives.

AI Governance and Skills Development

On the governance side, the IndiaAI mission under MietY is set to introduce a framework tailored for AI governance in India, concentrating on ensuring safe and responsible AI while fostering innovation. Several MietY round tables have involved stakeholders from academia, government, and startups, aimed at shaping this framework in accordance with existing models from UNESCO and the EU AI Act.

Regarding skills, India holds great potential to become a global leader in AI talent development. This encompasses results from extensive AI/ML degree programmes offered by engineering and management institutes, as well as certification programmes for ongoing professional education. Furthermore, targeted CXO awareness initiatives on AI/ML will enhance India’s standing as the global hub for AI skills.

On these fronts, alongside infrastructure support, it is evident that government assistance could significantly accelerate innovations in AI and LLM technologies.

A comprehensive support strategy across the areas of data repositories, AI governance, AI research, and workforce development, complemented by infrastructure availability, is crucial for the growth of India’s LLMs. In an age where LLMs are increasingly becoming part of daily life, tailoring these technologies to fit India-specific data and use cases is of utmost importance.