India's ambitious plans to become a global powerhouse in artificial intelligence (AI) are taking concrete shape, with significant strides made in building a robust computing infrastructure. The IndiaAI mission, launched with a budget of ₹10,372 crore, is focused on democratizing access to technology and empowering startups, researchers, and academics with scalable and affordable computing power. A key component of this mission is the establishment of a high-end common computing facility equipped with advanced Graphics Processing Units (GPUs).
Recent updates reveal that the IndiaAI mission has successfully onboarded a substantial number of GPUs, significantly boosting the nation's AI capabilities. Union Minister for Electronics and Information Technology Ashwini Vaishnaw announced that the country's national compute capacity has crossed 34,000 GPUs, bolstered by the addition of 15,916 new units to the existing 18,417. This expansion is a major leap forward in realizing the mission's goals.
Several cloud service providers (CSPs) and Indian firms are playing a crucial role in powering the IndiaAI Compute initiative with top-tier AI hardware. Companies such as Jio Platforms, NxtGen Data Centre, CtrlS Datacenters, Tata Communications, and E2E Networks are establishing a nationwide distributed AI infrastructure. In the second round of empanelment, Cyfuture India, Ishan Infotech, Netmagic, Sify, Vensysco, Locuz, and Yotta have joined the initiative, offering a mix of Nvidia GPUs (like H100, H200, B200), AMD chips (MI300X, MI325X), and Intel's Gaudi series.
The IndiaAI Compute Portal provides users with access to a vast pool of AI chips, including over 15,000 Nvidia H100 units, along with B200s, H200s, and other GPUs. The portal also includes AMD GPUs, AWS Inferentia 2 units, Intel Gaudi chips, and more, bringing scalable, affordable AI compute power to startups, researchers, and enterprises across India.
The expansion of GPU infrastructure is considered a critical enabler for India's AI ambitions. Vaishnaw emphasized the government's commitment to democratizing access to technology, stating that "Technology should not be left in the hands of a few. It is important that a larger section of society can access it, develop new solutions, and get better opportunities. That's the philosophy behind the IndiaAI Mission."
The IndiaAI mission is not just about hardware; it also focuses on developing indigenous AI models and datasets. Three new startups, Soket AI, Gnani AI, and Gan AI, have been selected to build foundational AI models tailored to India's linguistic diversity and specific needs. These startups join Sarvam AI, which was previously selected to build India's sovereign LLM ecosystem. As part of this effort, 367 datasets have already been uploaded to AI Kosh, India's AI-specific open data repository.
Looking ahead, India aims to develop its own GPU within the next three to five years, reducing reliance on imported technology. This ambition is supported by government initiatives such as the Semiconductor Mission and collaborations with global chip manufacturers. Full-scale production of indigenous GPUs is scheduled for 2029.
India's strategic location, cost advantages, and focus on renewable energy also position it as a potential global hub for data centers. However, to fully realize this potential, India needs to address challenges such as network connectivity, power infrastructure, and policy frameworks. Addressing these gaps through strategic investments and supportive policies will be crucial to enabling efficient data center growth and solidifying India's position as a global AI ecosystem leader.
