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The Quest for a Foundational Large Language Model Tuned to Indian Languages

As the world embraces artificial intelligence (AI) and its transformative potential, a key challenge has emerged in the realm of language technology. Specifically, creating a foundational large language model that can effectively handle Indian languages has proven to be a daunting task.

The Data Dilemma

For programmers and tech enthusiasts, data is the fuel that powers AI models. However, the availability of Indian language content online, a crucial source of training data, remains minimal compared to well-represented languages. Vivekanand Pani, the co-founder of Reverie Language Technologies, notes that the "English data was entirely natural" in existing models. This disparity has hindered the development of monolingual AI models tailored to Indian languages.

Local Challenges in Local Languages

While the sheer volume of public user posts on the internet dwarfs user-generated content on the public web, the unique characteristics of Indian languages pose additional challenges. For instance, Indian languages like Odia utilize different registers for formal speech (such as newscasts) and informal speech in everyday life. This underrepresentation makes it challenging to develop models that can accurately capture nuances and contexts at scale.

Improved Translation, but Native Solutions Still Lag

Despite these constraints, translation quality has improved enormously for Indian languages on services like Google Translate. However, translation remains a transformative technology, with the challenge not extending to creating new text or solving problems natively in a given language.

Building Indic Language Datasets for a Homegrown Solution

To create a meaningful foundational AI model for Indian languages, better availability of Indian language data is paramount. With a growing amount of such text on social media, the challenge lies in amassing a critical mass of content to train the model effectively.

Harnessing the Potential of Non-English Speakers

The current scenario presents an opportunity for non-English speakers, who make up a significant portion of India's non-internet user base, to contribute meaningfully. By creating and sharing Indian language content online, these users can help drive the development of more sophisticated AI models.

Ongoing and Upcoming Efforts

Several initiatives are underway in India to compile and leverage Indian language datasets for AI model development:

• Karya, a Bengaluru-based firm, has garnered international attention by compensating Indian language speakers for contributing synthetic speech content.
• The IndiaAI Mission is planning a repository of Indian language datasets, IT Minister Ashwini Vaishnaw announced earlier this month.

These efforts represent key steps towards realizing the dream of a comprehensive large language model capable of engaging with Indian languages.

A Call to Action

The journey towards a robust foundational AI model for Indian languages is still in progress. As a programmer or tech enthusiast, it's essential to stay informed and contribute to the ongoing efforts to compile Indian language datasets. Together, we can help unlock the immense potential of AI in the Indian linguistic landscape.

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Published - February 14, 2025 12:18 pm IST

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Last updated on March 14, 2025