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Beyond the AI Garage: India's New Foundational Path for AI Innovation + Governance in 2025

Abhivardhan
Jan 22
21 min read

Updated: Nov 16

This is quite a long read.

India's artificial intelligence landscape stands at a pivotal moment, where critical decisions about model training capabilities and research directions will shape its technological future. The discourse was recently energised by Aravind Srinivas, CEO of Perplexity AI, who highlighted two crucial perspectives that challenge India's current AI trajectory.

The Wake-up Call

Figure 1: The two posts on X.com on Strategic Perspectives, by Aravind Srinivas.

Srinivas emphasises that India's AI community faces a critical choice: either develop model training capabilities or risk becoming perpetually dependent on others' models. His observation that "Indians cannot afford to ignore model training" stems from a deeper understanding of the AI value chain. The ability to train models represents not just technical capability, but technological sovereignty.

A significant revelation comes from DeepSeek's recent achievement. Their success in training competitive models with just 2,048 GPUs challenges the widespread belief that model development requires astronomical resources. This demonstrates that with strategic resource allocation and expertise, Indian organisations can realistically pursue model training initiatives.

India's AI ecosystem currently focuses heavily on application development and use cases. While this approach has yielded short-term benefits, it potentially undermines long-term technological independence. The emphasis on building applications atop existing models, while important, shouldn't overshadow the need for fundamental research and development capabilities.

In short, Srinivas attempts to highlight 3 key issues, through his posts, on the larger tech development and application layer debate in India:

Limited hardware infrastructure for AI model training
Concentration of model training expertise in select global companies
Over-reliance on foreign AI models and frameworks

This insight fixates itself on legal and policy perspectives around building necessary capabilities around innovating in core AI models, and also focusing on building use case capitals in India, including in Bengaluru and other places. In addition, this long insight covers recommendations to the Ministry of Electronics and Information Technology, Government of India on the Report on AI Governance Guidelines Development, in the concluding sections.

The Policy Imperative: Balancing Use Cases and Foundational AI Development

What is pointed out by Aravind Srinivas about AI development avenues in India's scenario is also backed by policy & industry realities. The recent repeal of the former Biden Administration (US Government)'s Executive Order on Artificial Intelligence by the Trump Administration hours ago demonstrated that the US Government's focus has pivoted on hard resource considerations around AI development, such as data centres, semiconductors, and talent. India has no choice but to keep both ideas - building use case capitals in India, and focus on foundational AI research alternatives, at the same time.