‘Sector-agnostic AI aimed at solving real problems’

Having built speech models for Indic languages, Gnani.AI has developed full-stack capabilities with its own platforms, applications, and proprietary technology. Bharath Shankar, Co-Founder & Chief Product and Engineering Officer, tells Ojasvi Gupta that large global models are limited because they are not optimised for local requirements. Excerpts:

- BHARATH SHANKAR , CO-FOUNDER & CHIEF PRODUCT AND ENGINEERING OFFICER, GNANI.AI

To address diversity, we have accumulated petabytes of audio data through proprietary and crowd-sourced channels.

How do you handle linguistic diversity in India?

To address diversity, we have accumulated petabytes of audio data through proprietary and crowd-sourced channels. This data includes a wide mix of accents, genders, and age groups, which helps in building more accurate and inclusive models.

What is your view on AI regulation versus innovation?

There needs to be a balance. Regulation is important to ensure responsible and explainable AI, but it should not restrict innovation. Instead of limiting applications, the focus should be on enabling access to quality datasets, compute infrastructure, and GPUs so that startups can build effectively.

What are your expectations from these models?