Indian AI Model Expected in 6 Months: Union Minister for Electronics & Information Technology

Indian AI Model Expected in 6 Months: Union Minister for Electronics & Information Technology

The Union Minister for Electronics and Information Technology has announced that an indigenous Indian AI model is expected to be launched within the next six months. Alongside this, a call for proposals under the India AI Mission has been issued, inviting startups, researchers, and entrepreneurs to contribute to the development of AI models using Indian datasets.

Features of the Indian AI Model:

• Graphics Processing Units (GPUs): The model will initially be launched with 10,000 GPUs, with plans to expand to 18,693 GPUs. GPUs are specialized processors capable of processing large amounts of data simultaneously, making them ideal for tasks like machine learning and video editing.

• Cost-Effective: The computation cost for India’s AI model will be under 100 rupees per hour after a 40% government subsidy. In comparison, global AI models currently cost between 2.5 to 3 dollars per hour.

• Multidimensional Applications: The AI model will be designed to create scalable and impactful solutions across various sectors such as healthcare, education, agriculture, climate, and governance.

Need for Indigenous AI Models:

• Boosting Innovation and Research: Developing AI models within India will help meet global standards while addressing the unique challenges and opportunities specific to the country.

• Focus on Ethical AI: The initiative will prioritize ethical AI practices, with a focus on inclusivity, fairness, and the elimination of biases, while taking into account India’s diverse cultural and societal context.

• Strengthening Digital Sovereignty: By developing indigenous AI, India aims to enhance its control over digital infrastructure, including the entire AI supply chain—covering everything from data to hardware and software.

• Security and Data Protection: The AI model will implement safety measures, such as AI bias mitigation, explainable AI frameworks, and AI privacy strategies, to safeguard data from foreign models.

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