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MeitY unveils indigenous AI Models EKA-1, Dhīr 2B and 5B under IndiaAI mission

MeitY unveils indigenous AI Models EKA-1, Dhīr 2B and 5B under IndiaAI mission

New Delhi [India], November 3 (ANI): Ministry of Electronics and Information Technology (MeitY) has unveiled three indigenous artificial intelligence foundation models, EKA-1, Dhīr 2B and Dhīr 5B, developed by domestic companies with support under the IndiaAI Mission, with the government highlighting their potential for specialised applications and deployment in secure, offline environments.
MeitY Secretary S. Krishnan, while congratulating the teams behind the models, said the initiative would strengthen India's strategic autonomy in artificial intelligence and expand the availability of models suited to domestic requirements.
The models have been developed by Bengaluru-based Socket AI and ZenteiQ under the Foundation Model initiative of the IndiaAI Mission.
EKA-1, developed by Socket AI, is a 26-billion-parameter foundation model designed for mathematics, coding and reasoning. It has been trained on 7.5 trillion tokens and supports more than 100 Indian and international languages, as well as programming languages. The model is designed to handle multi-step tasks, execute code and operate in on-premises, private cloud and air-gapped environments.
Dhīr 2B and Dhīr 5B, developed by ZenteiQ, are mixture-of-experts foundation models trained from scratch using Google Cloud Tensor Processing Units (TPUs). The models support English and 10 Indian languages and can run directly on tested mobile hardware without an internet connection.
ZenteiQ said it was releasing the model weights under the Apache 2.0 licence, along with technical documentation and evaluation tools, through AIKosh.
Krishnan said the models had specific applications beyond general-purpose use, including mathematics, coding, scientific research and cybersecurity. He particularly highlighted their ability to operate in air-gapped environments, which could support wider adoption of enterprise artificial intelligence.
"These models can be deployed on air-gapped environments, which means enterprise-based artificial intelligence, which thus far hasn't really taken off, would be possible to do a lot more of that in the country using models like this," he said.
He added that smaller models could improve productivity and efficiency across different applications and that the government would continue supporting their refinement and development.
The models are accessible through AIKosh for researchers, students, innovators, enterprises and the general public, making them a wider national resource, Krishnan said. (ANI)

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