The surge in demand for NVIDIA’s graphics processing units (GPUs) coupled with the supply shortage caused an uproar in the market last year. The situation got so dire that Chinese buyers had to resort to sourcing them from the black market as the US government prohibited NVIDIA from directly selling its high-end GPUs to China.

To make GPUs easily accessible in India, Tata Communications partnered with NVIDIA to build a large-scale AI infrastructure for its customers in the private as well as the public sector. The partnership will see both companies work together to develop an AI supercomputer utilising the next-generation NVIDIA GH200 Grace Hopper Superchip.

Tata’s partnership with NVIDIA extends beyond the infrastructure layer which entails adhering to their best practices, including the implementation of high-speed low-latency InfiniBand networks. 

Formerly known as Videsh Sanchar Nigam Limited (VSNL) – a government of India-owned entity – Tata Communications has undergone significant evolution over the years. It has expanded its service offerings from managed cloud services, microservices, connected solutions to content delivery networks and analytics. 

Presently, it aims to lead the AI revolution in India, positioning itself at the forefront of technological advancement.

AI marketplace

Going forward, Tata plans to create a marketplace where enterprises will be able to access a wide array of foundational models and AI tools thus simplifying the process of building and deploying generative AI applications. 

“Our partnership with NVIDIA is to create that AI cloud platform but we are not restricting ourselves only to the infrastructure layer,” Rajesh Awasthi, vice president & business head, cloud & hosting services at Tata Communications told AIM.

The marketplace is similar to Bedrock, a fully managed service by Amazon Web Services (AWS) that simplifies the creation and deployment of generative AI applications on the cloud.

“We will establish a platform that will facilitate the entire lifecycle process for customers, encompassing data pipeline creation. Additionally, we will offer managed databases as a service for inferencing deployment needs. 

“To manage this entire lifecycle, we will provide the MLOps and LLMOps platform, ensuring ease of use through APIs,” Awasthi added.

The platform, according to the company, could go live in the second half of this year. 

Tata’s AI strategy 

Going forward, Tata perceives hundreds of AI use cases to emerge both from the public sector as well as enterprises. Tata Communications operates 44 data centres in India and across the globe and many Point of Presence (PoP) as a part of its content delivery network.

Tata’s strategy is to have a centralised unit (AI Supercomputer), which can be leveraged by its customers for heavier tasks such as training large language models (LLMs) and fine-tuning.

“As a network provider, we believe this is advantageous because we can assist customers with data ingress, training the model, and subsequently egress and deployment near the desired location for inferencing,” Awasthi said.

The inferencing platform, however, could be segregated. According to Awasthi, inferencing will occur in proximity to the customer’s location, utilising Tata Communications’ existing PoP network in the country.

Another one following a similar approach is Akamai, a US-based company which is also transforming its PoPs into miniature data centres. This initiative aims to offer cloud solutions at the edge and compete with the hyperscalers.

“From our standpoint, the inference process is anticipated to be more decentralised, contingent upon the specific use cases. For instance, in scenarios such as smart factory projects, inferencing capabilities may be required within those environments,” Awasthi added.

Catering to the public sector 

Tata sees great demand for its AI platform and infrastructure not just from the private sector enterprises, but also from the government of India. 

Tata Communications does cater to a handful of public sector customers. Notably, it moved the Ministry of Electronics and Information Technology’s (MeitY) workload to the cloud.

“This was in line with what AWS did with the US Department of Defence, where they created a federal cloud. We were the first in India to develop a government community cloud, which currently hosts several mission-critical projects from various ministries and departments of the Government of India,” Awasthi said.

Moreover, projects such as Ayushman Bharat Digital Mission, formulated by the Ministry of Health and Family Welfare, were deployed on Tata Communications’ cloud platform. The Pradhan Mantri Jan Arogya Yojana 1.0, Awasthi points out, was also deployed on our platform four years ago.

Going forward, the Tata Communications AI platform can be leveraged by public sector initiatives like Bhashini, which focuses on the use of AI to break the existing language barrier within the country. 

Even though Tata serves a lot of customers in the BFSI sector, “the consumption from government’s critical projects surpasses that of several enterprises, considering the scale at which they deploy citizen services,” Awasthi said.

Part of IndiaAI Mission

In March, the Narendra Modi-led administration announced the IndiaAI Mission, allocating a budget of INR 10,371.92 crore to further the vision of Making AI in India and Making AI Work for India. 

As a part of the mission, the government is planning to develop an AI compute infrastructure of 10,000 or more GPUs, built through public-private partnerships.

Previously, NVIDIA CEO Jensen Huang met with the Prime Minister discussing AI and GPUs. According to Awasthi, Tata Communications is also in talks with the government to be part of the proposed public-private partnership.

“Yes, the government has announced that they would want to see the AI infrastructure enabled by NVIDIA because they are the market leader with clear technology advancement and ecosystem supporting them,” he concluded.

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