4 min readNew DelhiJul 25, 2024 04:51 AM IST
First published on: Jul 25, 2024 at 04:21 AM IST
After receiving its first budgetary allocation for the ambitious IndiaAI Mission, the IT Ministry is looking at soon releasing a tender to procure between 300 to 500 graphics processing units (GPUs) to help the private sector build domestic computing capacity for building and testing artificial intelligence (AI) systems, The Indian Express has learnt. In the Union Budget 2024, the Ministry of Electronics and IT has been allocated Rs 551.75 crore for the IndiaAI Mission for 2024-25.
In March, the Union Cabinet had cleared the Rs 10,372 crore IndiaAI Mission 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. The idea is that if such an infrastructure exists in the country, start-ups could plug into it for developing AI systems.
As a first step though, the ministry is taking a more moderated approach. “With the allocation, we will look at AI compute, skilling, data sets and some other applications… the funds outlay for now, we will aim at procuring 300 to 500 GPUs. We will release a tender in due course,” a senior government official said on condition of anonymity.
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. It is also likely to be a weak point in India’s AI strides as no major domestic company currently controls the crucial hardware needed to build large scale datasets. In that, Nvidia has a near virtual monopoly, with its A100 chip — considered to be the most cutting edge for AI applications — costing as much as $10,000.
This is why the government has decided to step in and help procure some GPUs to allow Indian start-ups access to such computing needs early on.
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.
Of India’s Rs 10,370 crore plan, the implementation of computing 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.
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.
Of India’s Rs 10,370 crore plan, the implementation of computing infrastructure will be done through a public-private partnership model with 50 per cent viability gap funding. 
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