Sarvam AI, based in Bengaluru, launched two open-source language models named Vikram at the AI Impact Summit on Wednesday.
The Vikram models include a 35-billion parameter model and a 105-billion parameter model.
These models aim to improve performance in Indian languages, addressing the scarcity of training data.
Sarvam AI received over $50 million in funding from investors like Peak XV and Khosla Ventures.
Detailed Insights:
The launch of Vikram is considered a significant milestone in AI development in India, aligning with the government's push for indigenous LLMs.
Training LLMs requires substantial computational resources, involving GPUs and significant investment.
The Ministry of Electronics and Information Technology (MeitY) is focusing on both inference and training of LLMs in India.
Sarvam AI utilized subsidized access to GPUs under the IndiaAI Mission’s common compute program.
The models' key objective is to enhance AI's proficiency in understanding and processing various Indian languages.
Key Concepts Involved:
Large Language Model (LLM): An AI model trained on vast amounts of text data to generate human-like text.
Inference: The process of using a trained AI model to make predictions or generate outputs based on new input data.
GPU (Graphics Processing Unit): A specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device.