Infosys co-founder Nandan Nilekani recently criticised the trend of developing increasingly complex AI models, suggesting that such efforts are yielding diminishing returns, The Economic Times reported.
Speaking at the People+AI Mela in Bengaluru, Nilekani remarked, “They keep doing more of that, but it is not that it is going to get any better. They are all typically kept within the four walls of a company. It is like a black box for the rest of us.” He emphasised that the lack of transparency and accessibility hampers broader innovation and progress.
In contrast, Nilekani praised China's innovative approach to AI model-building, noting their success in creating efficient models with fewer resources. He highlighted China's transparency, stating, “They have done the world a service. So that goes back to commoditisation.” Nilekani believes China’s openness in sharing techniques has significantly contributed to the commoditisation of AI knowledge, which can benefit global AI development.
Nilekani has always considered AI models as commodities and stated, “This is proving to be true. Hundreds of models are getting built. China’s DeepSeek demystified model-building. Last week they tweeted all their open-source practices. The knowledge to build models is getting rapidly commoditised.” This commoditisation, according to him, is key to fostering innovation and accessibility in AI technologies.
Highlighting the role of computing power and data, Nilekani stressed the importance of high-quality datasets, particularly in Indian languages, to accelerate AI development.
He mentioned AI4Bharat, an initiative of IIT Madras focusing on open-source language AI for Indic languages, as a model for leveraging local data to boost AI advancements. “The hard part is uses. How do we use this to deliver value for people? That is where we can lead. We can always replace the model.”
AI4Bharat, supported by Nilekani for the past three to four years, is committed to further expanding its activities over the next three years. This initiative underlines the importance of making AI resources accessible and beneficial for diverse linguistic contexts in India.
The entrepreneurial landscape in India has witnessed substantial growth, with startups increasing from 1,000 in 2016 to 150,000 in recent years. Nilekani foresees continued expansion driven by the adoption of mass-scale technologies and the influx of capital. “They will use mass scale technologies that we have deployed in interesting use cases. There is also going to be a lot of capital coming in,” he noted.
Nilekani believes practical applications of AI are crucial for delivering real value to people. While models may evolve, the focus should remain on finding effective ways to utilise AI in solving practical problems and enhancing people's lives.