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Within the next 18 months, the government plans to purchase 10,000 graphics processing units (GPUs) to strengthen the country’s computing infrastructure, according to Amitabh Kant, the former CEO of Niti Ayog and India’s G20 Sherpa.
Kant stated in a post on X that “this is expected to enhance India’s processing power, bringing its computational capabilities in line with its data generation.”
Twenty percent of the global data is produced in India. With 19% of all AI projects worldwide, India is also the country with the second-highest number of GitHub AI projects worldwide. This illustrates our dynamic and proactive involvement in AI research on a global basis,” Kant said in his essay.
“AI will be a game-changing opportunity for India to improve human development indices, transform learning and health outcomes,” he continued.
With a capacity of 950 MW, India has surpassed other major countries including Australia, Hong Kong SAR, Japan, Singapore, and Korea to become the largest country in the Asia Pacific area (excluding China) for data centre capacity, according to a recent research from CBRE South Asia Pvt Ltd.
Additionally, the analysis projects that India will have the most increase in data centre capacity in the area, adding 850 MW between 2024 and 2026.
Large collections of networked computers are called data centres, and they are used for distributing and storing data remotely. India’s data centre market is predicted to quadruple its capacity from around 0.9 GW in 2023 to 2 GW by 2026, according to a March research by CareEdge Ratings.
Over the following three years, it is anticipated that this increase will necessitate capital expenditures of Rs 50,000 crore.
There are already more than 100 generative AI businesses in India, but very little money has been invested in them. Between 2013 and 2022, the US saw approximately $250 billion in private investments in AI firms; by contrast, just $8 billion was invested in India.
Data from the AI Index 2023 Annual Report shows that within the same period, China saw investments totaling $95 billion, while the UK saw investments totaling $18 billion.
GPUs’ function in AI
These days, GPUs are crucial to AI since they offer the best performance possible for AI inference and training. They also have a lot to offer in a variety of applications that need for faster processing.
Elon Musk, the CEO of Tesla, stated during the firm’s first quarterly earnings for 2024 that the business presently has 35,000 H100 processors, the most potent and most costly graphics processing units intended for AI applications.
Mark Zuckerberg stated in January that Meta intends to have over 3.5 lakh H100 chips by the end of 2024, bringing the company’s total holdings to roughly 600,000 by then.
In 2023, Microsoft is expected to place an order for 1.5 lakh GPUs, as per Omdia, a technology research organisation. The article also stated that Oracle, Tencent, Google, and Amazon purportedly purchased 50,000 apiece.
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