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Nvidia CEO Jensen Huang says India's crucial to shape AI market

  • India's plan for a 10,000 GPU cluster for AI grabs Nvidia CEO Jensen Huang's attention.
  • Nvidia recently received a market capitalization worth over $2 trillion.
  • On 23 February, Nvidia’s shares surpassed more than 300% within a year.

India's plan to launch a 10,000 GPU processing cluster for indigenous AI computing needs piques Nvidia CEO Jensen Huang’s interest.

Nvidia’s offer

Jensen Huang, on Tuesday, mentioned that this plan would aid him in entering India’s growing market, along with enabling the Indian government to enhance the nation’s tech force - startups, academic institutions, and researchers in the industry.

He is more than willing to provide India with the opportunity to expand its AI capabilities with Nvidia’s technology, such as Graphics Processing Units (GPUs), and his consultation. Apart from this, Huang also offers Blackwell, his most recent processor design, which is famous for its incredible speed in processing AI models.

The potential of Nvidia chips

Nvidia’s chips are vital for AI development; OpenAI's ChatGPT, Microsoft Corp.'s GitHub Copilot, and other such power applications depend on Nvidia’s tech for training large language models.

Nvidia recently received a market capitalization worth over $2 trillion, becoming the first chipmaker to do so, closely behind Microsoft and Apple. On 23 February, Nvidia’s shares surpassed more than 300% within a year, crossing over $2 trillion.

The global share of AI markets is seeing a constant exponential growth from $168.5 billion in 2022 and will reach over $2 trillion by 2032. Several Indian companies such as Tata Communications and Hiranandani Group’s Yotta Infrastructure have partnered with Nvidia to utilize its AI-specific GPUs.

The Indian government’s contribution

The government aims to position India as the hub of value creation rather than merely serving as "the back room for global firms". The Union Cabinet’s India AI Mission just approved India’s promise to develop the country’s AI using domestic resources only.


With a budget of $1.2 billion over a period of five years for various vital programs such as the development of regional AI models, and starting and maintaining an open-source dataset covering all 22 official Indian languages.