Daijiworld Media Network - Bengaluru
Bengaluru, Jun 14: A startup founder has come to the defence of Infosys co-founders N. R. Narayana Murthy and Nandan Nilekani amid criticism over India's failure to develop a home-grown large language model (LLM), arguing that bureaucracy rather than industry leaders is the main obstacle to the country's artificial intelligence ambitions.
Chinmay Singh, founder of TeleVox Healthcare and AI firm iWish.ai, made the remarks on social media as debate intensified over India's AI strategy following reports that the United States had restricted access to some of Anthropic's advanced AI models.
Responding to criticism directed at Murthy and Nilekani, Singh said it was unfair to blame the Infosys founders for the absence of a domestic frontier AI model.
“Indians are blaming Infy/Murthy/Nandan for a lack of home-grown LLM. But that blame is misplaced,” Singh wrote, adding that while the industry veterans had the resources to fund projects, they were under no obligation to risk their personal wealth on such ventures.
Instead, Singh blamed what he described as India's entrenched bureaucratic culture. He specifically referred to former bureaucrat Amitabh Kant and other civil servants, claiming bureaucratic structures had contributed to talent migration from India.
The entrepreneur said he would refuse to establish an AI laboratory in India even if offered USD 10 billion in government funding, citing concerns over bureaucratic oversight.
“The real reason is Babu. Under no circumstance, I am going to report to a babu,” Singh wrote, while adding that he would be willing to work with elected representatives rather than career bureaucrats.
He further argued that excessive bureaucracy discourages non-resident Indians and global technology professionals from returning to India and investing their expertise in the country.
Singh also pointed to taxation policies affecting startups, claiming they increase operational costs and hamper productivity. As an example, he cited taxes on technology equipment used by engineers.
His comments come amid a wider debate on whether India should invest heavily in building foundational AI models or focus on developing applications using existing global AI platforms.
The discussion was reignited after criticism of Nilekani resurfaced over his long-held view that India should prioritise AI applications rather than compete with technology giants in developing expensive frontier models.
Speaking at Meta's “Build with AI” summit in Bengaluru in 2024, Nilekani had argued that India should become the “use-case capital of the world” rather than attempt to build another large language model.
“Our goal should not be to build one more LLM. Let the big boys in Silicon Valley do it, spending billions of dollars. We will use it to create synthetic data, build small language models quickly and train them using appropriate data,” Nilekani had said.
The debate has gained momentum as policymakers, entrepreneurs and technology experts continue to discuss the best path for achieving India's AI independence and strengthening its position in the rapidly evolving global artificial intelligence landscape.