India’s largest cluster of graphics processing units (GPU) was about 2,000- 2,500 as compared with 20,000 plus in the US, said Shridhar Garge, Head, Strategy, Planning & Programs, NVIDIA, illustrating the relevant AI infrastructure gap that impedes growth potential for the biggest breakthrough technology in the world.
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The graphics processor and chipset major is the world’s sixth-most valuable company by market capitalization, at nearly $1.2 trillion, and the NVIDIA stock has surged nearly four times in a year as discussions around AI grab more column inches and dominate the air waves. The US chip giant’s products play a crucial role in AI systems.
Garge also said that for clusters that have about 1000 GPUs, India would have around four or five.
“There are certain things that are limiting the thought process of Indian startup founders – infrastructure being a very important one,” Garge said at the India Internet Day 2023 in New Delhi last week.
A GPU cluster is a group of computers that have a GPU on every node. Multiple GPUs provide accelerated computing power for specific computational tasks, such as image and video processing and training neural networks and other machine learning algorithms.
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Similarly, Rajan Anandan, MD, PeakXV Partners and Surge, said that for application-level companies like those involved in healthcare, education and customer support among others, not having this infrastructure in place is a real constraint. Thus, he said it boils down to how much capital the startups can raise but also the access that they can get.”One thing the government can do is to build a very large-scale (GPU cluster),” Anandan said. “Why shouldn’t India build a 100,000 GPU cluster and then we give it to Indian developers, Indian research institutions, Indian startups to build on it and make it very affordable?”
Costs & volumes
He said this would be playing on our strengths of doing population scale projects at ultra-low cost and high volumes.
As AI usage gains prominence, countries will need to work on building their own capabilities in large language models and computing infrastructure to support sovereign AI capabilities, IBM chairman and CEO Arvind Krishna had also said last week during his visit to India. The government could possibly consider investing in this area that will come at the cost “millions and not billions,” he had said.
NVIDIA President Jensen Huang and Google Cloud CEO Thomas Kurein are now in India, and these issues may come up for discussions with the government.
Industry body Nasscom, said in a report in June that the lack of high-quality training data, funding and compute infrastructure were three of the major challenges dogging startups.
As of May 2023, it said the Indian Generative AI landscape had more than 60 startups dedicated to offering solutions and services to their customers spread across various industry verticals. It said more than $590 million in funding has already flown into this space, with 2022 being the year with the heaviest funding inflow.
It added that the number of Gen AI startups in India more than doubled between 2021 and 2023 to date. Nearly 70% of all private investments into the Indian Gen AI space flowed in 2022. However, despite having the highest penetration of AI talent, the organisation said that India lags many of the major tech hubs in the world in the Gen AI race.
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