Meet Krutrim, ‘India’s own AI' developed by Ola CEO Bhavish Aggarwal-led venture
Krutrim is a large language model (LLM) which will be available in two classifications: the base Krutrim model, and Krutrim Pro, the more powerful one.
Krutrim Si Designs, the artificial intelligence (AI) venture led by Ola CEO Bhavish Aggarwal on Friday revealed ‘Krutrim,’ described by the startup as ‘India’s own AI’ model.
Krutrim is a Sanskrit word which means 'artificial' (Image courtesy: Ola)
Aggarwal unveiled the project at a launch event in Bengaluru, where both Ola and Krutrim Si Designs are headquartered. The project team is based in India and the Bay Area (United States).
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Launched in April 2023, Krutrim Si Designs was set up by Aggarwal along with Krishnamurthy Venugopala Tenneti, a board member at ANI Technologies Limited, the parent company of Ola Cabs and Ola Electric.
What is ‘Krutrim’?
With a name that means ‘artificial’ in Sanskrit, it is a large language model (LLM) which, as per Aggarwal, has been trained on more than 2 trillion ‘tokens’; these tokens are sub-words used in conversations.
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Krutrim, in fact, is to have two classifications. While the base Krutrim model was introduced today and will be available starting next month, the more power Krutrim Pro will come early next year with advanced capabilities for problem-solving and task execution.
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Krutrim, in fact, is to have two classifications. While the base Krutrim model was introduced today and will be available starting next month, the more power Krutrim Pro will come early next year with advanced capabilities for problem-solving and task execution.
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Users can express their interest in Krutrim with their mobile number and they will be informed when the technology is available for them.
Features of Krutrim
(1.) The model understands 20 Indian languages and can generate content in ten of these.
(2.) Hindi, Kannada, Marathi, Odiya, Telugu are among the languages it can generate content in.
(3.) The project team claims that Krutrim is larger than even GPT-4 in Indic language support.
(4.) This LLM uses a custom tokeniser to interpret the languages and scripts.
(5.) When compared to other open-source LLMs trained with similar data volumes, it outperformed those on a range of industry-standard benchmarks, the company claims.
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