Since the introduction of ChatGPT by OpenAI two years ago, the competition to develop its alternative has been fierce. Companies all over the world are racing to build generative AI models and LLMs to outdo each other. In India, there is a particular focus on building AI in Indic languages, including Bengali, Assamese, Tamil, Telugu, Sanskrit, and Hindi, among others, to cater to the needs of the entire population. This has led to the emergence of startups like Sarvam AI, Ola’s Krutrim, Wadhwani AI, and Tech Mahindra, as well as initiatives like Bhashini and AI4Bharat. The goal is to solve the Indic data and AI problem through research and initiatives.
In an interview with Tanuj Bhojwani, the head of People+ai, the importance of building Indic language models was emphasized. Bhojwani stated that the majority of the Indian population is yet to experience the convenience of using the internet due to the country’s low literacy rate. However, with the rise of multimodal internet access through voice and camera, it is crucial to develop AI models that can understand India’s linguistic nuances and cultural complexities.
One of the biggest challenges in developing AI for Indian languages is the scarcity of high-quality data. Unlike English, which has a vast amount of digital content available, Indian languages lack sufficient natural data to train AI models. This is a problem that even western AI companies are working on, with OpenAI showing some interest in working with Indic data. However, the moat for Indic AI companies lies in building AI use cases, as it is easier to go up the supply chain rather than down. This is where the concept of ‘Adbhut India’ or the ‘AI use case capital of the world’ comes into play.
In conclusion, the race to build AI in Indic languages is a crucial step towards India’s growth in the field of AI. It is essential to create models that can understand the linguistic and cultural complexities of the country to cater to the needs of the population. While the scarcity of high-quality data remains a challenge, the focus on building AI use cases can be the moat for Indic AI companies to stand out in the global market.
