Ola Founder Bhavish Aggarwal To Invest Rs 2,000 Crore In Krutrim, Launches AI Lab
Ola Founder Bhavish Aggarwal has announced an investment of Rs 2,000 crore into his artificial intelligence startup Krutrim, and has committed to invest Rs 10,000 crore more by next year.
In a post on social media platform X, Aggarwal announced that the company launched an AI lab on Tuesday. “Announcing the Krutrim AI lab today! While we've been working on AI for a year, today we're releasing our work to the open source community and also publishing a bunch of technical reports (sic).”
Krutrim's focus is on developing AI for India — to make AI better on Indian languages, data scarcity, and cultural context, he added.
This comes after Chinese startup DeepSeek shook the AI ecosystem with the launch of its new model, DeepSeek-R1, which is said to deliver performance on par with western AI giants but at a significantly lower cost.
Aggarwal also announced that the company, in partnership with Nvidia, will be deploying GB200 – a GPU card that is part of the Nvidia Blackwell platform. He expects the system to go live by March, and aims to make it the largest supercomputer in India by end of year.
“We're nowhere close to global benchmarks yet but have made good progress in one year. And by open sourcing our models, we hope the entire Indian AI community collaborates to create a world class Indian AI ecosystem. We're still learning to walk before we can run, hopefully within this year,” Aggarwal wrote in his X post.
Aggarwal, in his post, also mentioned that the company is launching an improved version of its large language model Krutrim 2. It launched its first LLM Krutrim 1 in January 2024.
Aggarwal also released other models built on Krutrim 1, which include Chitrarth 1, a vision language model capable of understanding images and documents, Dhwani 1, a speech language model capable of tasks like speech translations, Vyakhyarth 1, an Indic embedding model for use cases like Search and Retrieval-Augmented Generation, and Krutrim Translate 1 for text-to-text translation.
In addition, “BharatBench” global benchmark developed for Indic performance was also revealed, along with a bunch of technical reports and papers.
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