Author: Chandra Khatri, Ashish Kulkarni, Rajkiran Panuganti, Sharath Adavanne, Kumar Ashish, Abhinav Ravi Description The plurality of Indian languages and culture poses unique challenges in building general purpose AI models for India. In the context of large language models, these include multilingual language understanding covering this linguistic diversity and the
Author: Chandra Khatri, Ashish Kulkarni, Rajkiran Panuganti, Sharath Adavanne, Kumar Ashish, Abhinav Ravi Introduction Tokenization is a crucial step in Natural Language Processing (NLP), as it directly impacts the performance of language models. Most existing tokenizers are optimized for high-resource languages like English, leaving Indian languages underrepresented. To address this
Author: Chandra Khatri, Abhinav Ravi, Rajkiran Panuganti, Sharath Adavanne, Kumar Ashish, Ashish Kulkarni Have you ever wondered if the AI you use every day truly understands India and its diverse culture? Most AI models are trained primarily on English, Chinese, or European languages, which means they might miss the nuances
Author: Bhavish Aggarwal Introducing India's First AI Frontier Research Lab Today, we proudly introduce कृत्रिम AI Lab—India’s first dedicated AI frontier research lab. This bold initiative is designed to drive cutting-edge AI innovation tailored for India's unique needs while contributing to