10,000 GPUs, AI centres for multi modal LLMs: 8 things to know about India's AI mission

The Union Cabinet on March 7 approved the IndiaAI mission

The Union Cabinet on March 7 approved the ambitious India AI mission with an outlay of Rs 10,371.92 crore with the aim of creating computing power, developing indigenous AI capabilities etc through strategic programs and partnerships.

The mission will be implemented by IndiaAI, an independent business division under the Digital India Corporation.

Here are seven things you need to know about the India AI mission:

1. Compute capacity : This component of the AI mission will aim at creating an ecosystem comprising of AI compute infrastructure of 10,000 or more graphics processing units, built through public private partnership.
2. AI marketplace: The government will also design an AI market place to offer AI as a service and pre-trained models to AI innovators.
3. Startup financing: Under this initiative, support will be given to deep-tech AI startups.
4. Non personal dataset platform: In the India AI Datasets Platform, the government streamline access to non-personal datasets to entrepreneurs and startups. "A unified data platform will be developed to provide a onestop solution for seamless access to non-personal datasets to Indian startups and researchers," a release said.
5. Innovation centre: The India AI Innovation Centre will work on developing and deploying indigenous large multimodal models and domain-specific foundational models in critical sectors.
6. AI application in critical sectors: Under the IndiaAI Application Development Initiative, AI applications in critical sectors for problem statements sourced from the government will be promoted.
7. IndiaAI FutureSkills: Under the FutureSkills, program, which was inaugurated a few weeks ago, entry into AI programs and AI courses in undergraduate, masters-level, and Ph.D. programs, will be promoted. Further, under the initiative, data and AI Labs is being planned to be set-up in Tier 2 and Tier 3 cities across India to impart foundational level courses.
8. Responsible AI: Lastly, for developing and deploying safe AI, projects will be taken up to develop indigenous tools and frameworks, self-assessment checklists for innovators, and other guidelines and governance frameworks.