In response to recent remarks by Google Research India director Manish Gupta, Infosys co-founder Nandan Nilekani has reiterated his position that India should prioritise investment in AI infrastructure and compute resources rather than building its own large language models (LLMs). Nilekani’s comments come amidst growing debate over India’s role in the global AI ecosystem.
Speaking to the press, Nilekani explained why he believes developing foundation models - large-scale AI systems like those from OpenAI or Meta - may not be the best allocation of resources for India.
“Foundation models are not the best use of your money. If India has $50 billion to spend, it should use that to build compute, infrastructure, and AI cloud. These are the raw materials and engines of this game,” he said.
Foundation models require significant financial and computational resources, often running into billions of dollars, as they depend on training vast datasets on expensive infrastructure.
Instead, Nilekani has consistently advocated for leveraging existing LLMs to build AI use cases tailored to India’s unique needs, such as healthcare, education, and governance.
Last month, Google Research India director Manish Gupta expressed a contrasting opinion at the Bengaluru Tech Summit, suggesting that India should not limit itself to building use cases. Gupta argued for the development of foundational AI systems, comparing them to Nilekani’s foundational work on Aadhaar.
“He is not preaching what he practised. He revolutionised India’s technology landscape by starting with the basics. With Aadhaar, he did not start with use cases; he started with building foundations. We too must, using our constraints as ingredients for innovation,” Gupta said.