India need not spend resources on large language model, says Nandan Nilekani
Nilekani advises against costly language models. He champions investment in core infrastructure like AI cloud computing. Gupta argues for building foundational models. He cites Aadhaar as an example of successful foundational projects.
Nilekani believes India shouldn't build its own large language model (LLM), a type of powerful AI, said the report (by Supriya Roy). Instead, he argues for investing in computing infrastructure and cloud technology.
“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.
These models, like those from OpenAI and Meta, require significant resources to develop. Nilekani suggests India utilise existing global LLMs and focus on creating applications.
Gupta, on the other hand, believes that India should build its own foundational models. He compared the situation to Nilekani's work on Aadhaar, India's biometric ID system, arguing that it began with building a foundation.
“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.
This difference of opinion highlights a key debate about how India can best position itself in the growing field of AI, the report said.
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