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Nvidia’s Huang teams with Asia’s richest man on Blackwell AI hub

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Saritha Rai
Saritha Rai
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Bloomberg
Bloomberg
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By
Saritha Rai
Saritha Rai
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Bloomberg
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October 24, 2024, 1:03 PM ET
NVIDIA founder, President and CEO Jensen Huang.
Nvidia products have become a prized commodity among data center operators, which use the chips to develop AI software and services. The Santa Clara, California-based company acknowledged in August that Blackwell proved more difficult to produce than anticipated. Photo by Chip Somodevilla/Getty Images

Nvidia Corp.’s Jensen Huang struck a partnership with Asia’s richest man, Mukesh Ambani, to build out artificial intelligence infrastructure and spur the technology’s adoption in the world’s most populous country.

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The two executives shared the stage at Nvidia’s AI summit in Mumbai on Thursday and said a new major data center by Ambani’s Reliance Industries Ltd. in India is set to use the latest Blackwell chips from the US company. Nvidia also forged partnerships with Indian conglomerates including Infosys Ltd. and Tata Consultancy Services Ltd.

India has emerged as a potentially major AI arena, with the country of 1.4 billion adopting the technology in industries including agriculture, education and manufacturing to boost efficiency. While still a small part of their revenue, global tech companies from Nvidia to Microsoft Corp. and Meta Platforms Inc. are betting on the rapidly-growing economy as a growth market that can emerge as an alternative to China.

“India produced and exported software,” Huang said. “In the future, India will export AI.” 

A 1 gigawatt Reliance data center under construction in Gujarat state will use Nvidia’s Blackwell, making it among the first to deploy the powerful new chips. Nvidia’s customers such as Amazon Web Services are also in the process of starting to use the product, with AWS expecting them to be online next year. Dell Technologies Inc. also has said that Blackwell-based servers will be generally available at the beginning of 2025.

Nvidia products have become a prized commodity among data center operators, which use the chips to develop AI software and services. The Santa Clara, California-based company acknowledged in August that Blackwell proved more difficult to produce than anticipated. The company said that it was making changes to improve its manufacturing yield — the number of functioning chips that come out of factories.

Nvidia also said it’ll help India’s Tech Mahindra Ltd. to build a Hindi large language model, and work with e-commerce company Flipkart on its conversational customer-service systems. It’ll collaborate with India’s health-care companies to help them improve productivity in patient care and research.

The US company has emerged at the forefront of a global AI boom, supplying the chips tech leaders like Microsoft and Google use to develop artificial intelligence. Huang has toured the globe this year, pushing countries and enterprises to adopt AI technologies he’s dubbed a “new industrial revolution.”

Nvidia began its operations in Bangalore, southern India, two decades ago and also has development centers in three other cities in the country, with a total of about 4,000 engineers, its largest employee base after its home country.

About a year ago, it struck initial pacts to build AI data centers with local conglomerates including Ambani’s Reliance and the Tata Group. Reliance Industries is building a range of AI tools and applications called JioBrain, Ambani said at the company’s live-streamed shareholders meeting in August, during which he mentioned the term AI at least 80 times.

India has risen in prominence for global tech companies as the US’s tensions with China have escalated. Nvidia is among companies whose business with China has been curtailed by Washington’s restrictions. Huang described “India’s moment” after meeting Prime Minister Narendra Modi in the US last month.

While India boasts a burgeoning digital economy, its AI infrastructure is still developing. The government has set aside $1.2 billion under the IndiaAI Mission to build data centers vital to building AI systems and commercializing technologies.

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