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Towards Generative AI Excellence: Tackling India's Compute Infrastructure Gap
Towards Generative AI Excellence: Tackling India's Compute Infrastructure Gap

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In recent years, India has been striving to position itself as a global hub for technological innovation, particularly in the field of Generative AI. The Indian government has been vocal about its vision of leveraging AI to drive economic growth, foster innovation, and address societal challenges. However, lack of robust compute infrastructure continues to act as a major roadblock, hindering the progress in this direction. The challenges associated with procurement of compute hardware, either due to insufficient funding or due to lack of scaled OEMs which can effectively fulfil the demand, make it difficult for startups to train and run complex Gen AI models, which lie at the core of cutting-edge AI applications.

Recognizing this challenge, the Indian government has been taking decisive steps to bridge this infrastructure gap. In a significant move, the Cabinet recently approved and launched the IndiaAI Mission, allocating a substantial budget of Rs 10,372 crore ($1.2 billion) for a five-year period. This comprehensive national-level mission aims to boost AI development and supercomputing capacity within the country. One of the ways this plans on achieving this is by facilitating access to GPU infrastructure by establishing an AI computing base equipped with over 10,000 GPUs, which will be made available through a public-private partnership model. This infrastructure will not only support the development of AI models but also provide computing resources essential for AI startups looking to scale up. Since many Indian Generative AI startups have been struggling to attract enough funding, and compute infrastructure accounts for a fairly large share of their Generative AI budget, access to GPU clusters can be expected to fuel innovation, reduce dependency on foreign models, and attract more private investments into the sector.

The mission also aims to create an AI marketplace, offering AI-as-a-service and pre-trained models to innovators. This marketplace will serve as a centralized platform for accessing critical AI resources, thereby streamlining the development and deployment of AI solutions across various domains. Since the mission aligns with the nation's broader economic objectives, it has attracted significant interest and support from industry leaders and global tech giants. Companies like Nvidia, Microsoft, and Rackspace Technology have shown interest in collaborating with the Indian government to strengthen AI infrastructure and drive innovation. Nvidia's partnership with Indian conglomerate Reliance Industries to deploy AI-ready data centre infrastructure is an example of how the focus on AI infrastructure in India is growing.

 

Analyst’s Take:

 

Although these interventions can be seen as major steps towards addressing the challenges associated with Gen AI compute infrastructure in India, more focused efforts might be needed to fully address the challenges related to compute infrastructure. For instance, in addition to deploying GPU clusters, it can make sense for the government to establish mechanisms for startups to access GPU resources on-demand. This could involve facilitating the creation of multiple GPU-as-a-service platforms or cloud-based GPU instances that startups can provision as needed for Gen AI model training and inference tasks. Until this happens, the government can consider working towards streamlining customs procedures and regulatory approvals to facilitate the import of GPUs. Lastly, to reduce dependency on imported GPUs and boost domestic innovation, the government can explore ways to incentivize R&D in indigenous GPU technologies by means of grants, subsidies, and research collaborations with academic institutions and technology startups working on GPU design and fabrication.

While each of these suggested interventions will have its own merits and demerits, successful implementation of these approaches would require careful planning, and continuous monitoring and evaluation at all stages of execution. Additionally, the government would need to prioritize interventions based on their cost-effectiveness and alignment with broader economic and technological goals. This, coupled with support from all stakeholders in the ecosystem, can aid the industry in addressing these pressing challenges, and strengthen India’s position in AI-driven innovation globally.


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Dhiraj Sharma
Principal Analyst

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