Union Cabinet approves IndiaAI Mission with Rs 10,372 crore outlay: How it could help private players

While still a blueprint, the approval could spur investments in this sector — with private companies setting up data centres in the country, and allowing startups access so they can test and build their generative AI models.

This is a benefit that startups such as Perplexity AI in the United States have enjoyed for some time now, since they can tap into the computing capacity offered by companies like Nvidia.

Computing capacity, or compute, is among the most important elements of building a large AI system, apart from algorithmic innovation and data sets. It is also one of the most difficult elements to procure for smaller businesses looking to train and build such AI systems, given the high costs.

For example, Nvidia’s A100 chip — considered to be the most cutting edge for AI applications — costs around $10,000, which means that a data centre of 10,000 such graphics processing units (GPUs) could cost at least $100 million (more than Rs 800 crore).

In an interview with The Indian Express earlier, Perplexity’s Aravind Srinivas had highlighted the hardware-related challenges that startups from India may face, compared with their counterparts in the West.

What is India’s plan for setting up AI computing capacity?

Under the IndiaAI Mission, the government will look to establish a computing capacity of more than 10,000 GPUs and also help develop foundational models with a capacity of more than 100 billion parameters trained on datasets covering major Indian languages for priority sectors like healthcare, agriculture, and governance.

While the infrastructure is being set up, priority will be placed on selecting the most advanced GPUs.

The implementation of this AI compute infrastructure will be done through a public-private partnership model with 50 per cent viability gap funding. If the compute prices come down, the private entity will have to add more compute capacity within the same budgeted amount to meet increased demand. Of the total outlay, Rs 4,564 crore has been earmarked for building computing infrastructure.

“Basically, there will be a tender inviting companies to set up data centres. When a company applies for, let’s say a centre which may cost Rs 10,000 crore, they can seek a viability gap funding from the government for a certain amount of that,” a senior government official said.

Are there proposals beyond hardware too?

The Cabinet has approved the financing by the government of deeptech startups at various levels of growth. Of the total outlay, roughly Rs 2,000 crore has been earmarked towards this.

As part of the programme, an IndiaAI Datasets Platform will be set up, which will look at leveraging the quality, access, and use of non-personal datasets for AI innovation. The platform will be tasked with hosting identified “high-quality” AI-ready datasets.

Together, these proposals cover two of the most crucial elements of building large language models: the hardware and access to high-quality datasets.

The government will also set up the IndiaAI Innovation Research Centre, which will undertake the development and deployment of large foundational models, with focus on indigenous Large Multimodal Models and domain-specific foundational models. Close to Rs 2,000 crore has been earmarked for this centre. There is a plan to financially support 4,000 BTech, 400 Mtech, and 600 PhD candidates who will focus on AI in premier educational institutions.

How does this announcement fit in with the government’s overall policy?

The IndiaAI Mission announcement came a week after the Cabinet cleared chip projects worth Rs 1.26 lakh crore, including what could be the country’s first commercial fabrication plant. India has identified electronics manufacturing as a key economic driver, and the government is willing to spend money in the initial phase to get production rolling.

This is a strategy that the European Union is following as well. To allay concerns over overregulation of AI, which could stifle innovation, the European Commission earlier this year released a set of rules to enable startups and other businesses to access hardware — such as supercomputers and computing capacity — to build large-scale AI models.

But what about AI regulations and aspects of safety?

Even as the private industry innovates rapidly, lawmakers around the world are grappling with setting up legislative guardrails around AI to contain some of its downsides.

In India, the IT Ministry recently issued an advisory to generative AI companies deploying “untested” systems to seek the government’s permission before doing so. However, the government’s move was criticised by stakeholders around the world, forcing it to clarify that the advisory was not applicable to startups. Questions have also been raised over the legal basis of the advisory.

Last year, the European Union reached a deal with member states on its AI Act, which includes safeguards on the use of AI within the EU, including clear guardrails on its adoption by law enforcement agencies. Consumers have been empowered to file complaints against any perceived violations.

In the United States, a White House Executive Order on AI is being offered as an elaborate template that could become a blueprint for other countries looking to regulate AI. A blueprint for an AI Bill of Rights released last October is seen as a building block for the subsequent executive order.