Why India Wants Sovereign AI Assets

Microsoft's withdrawal of services to Nayara last month exposed the risks of depending on foreign infrastructure

- Shadma Shaikh

Google's annual I/O Connect event in Bengaluru this July, the spotlight was on India's AI ambitions. With over 1,800 developers in attendance, the recurring theme echoing across various panel discussions, product announcements and workshops was that of building AI capability for India's linguistic diversity.

With 22 official languages and hundreds of spoken dialects, India faces a monumental challenge in building AI systems that can work across this multilingual landscape.

In the demo area of the event, this challenge was front and center, with startups showcasing how they're tackling it. Among those were Sarvam AI, demonstrating Sarvam-Translate, a multilingual model fine-tuned on Google's open-source large language model (LLM), Gemma.

Next to it, CoRover demonstrated BharatGPT, a chatbot for public services such as the one used by the Indian Railway Catering and Tourism Corporation (IRCTC).

At the event, Google announced that AI startups Sarvam, Soket AI, and Gnani are building the next generation of India AI models, fine-tuning them on Gemma.

At first glance, this might seem contradictory. Three of these startups are among the four selected to build India's sovereign large language models under the ₹10,300 crore India AI Mission, a government initiative to develop home-grown foundational models from scratch, trained on Indian data, languages, and values.

So, why Gemma?

Building competitive models from scratch is a resource-heavy task involving multiple challenges, and India does not have the luxury of building from scratch, in isolation. With limited high-quality training datasets, an evolving compute infrastructure, and urgent market demand, the more pragmatic path is to start with what is available.