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FILE PHOTO: Perplexity CEO Aravind Srinivas has responded to Nandan Nilekani’s comments around India not needing to build its own models, saying he disagreed with the Infosys co-founder.
| Photo Credit: KSL
Perplexity CEO Aravind Srinivas said that Infosys co-founder Nandan Nilekani’s comment on India not needing to build its own AI models “is wrong.” Though Mr. Srinivas acknowledged Mr. Nilekani’s contributions to India’s tech industry, he noted that companies can train their own AI models while also building on top of existing models.
“To be clear: Nandan Nilekani is awesome, and he’s done far more for India than any of us can imagine through Infosys, UPI, etc. But he’s wrong on pushing Indians to ignore model training skills and just focus on building on top of existing models. Essential to do both,” Mr. Srinivas tweeted.
In October, Mr. Nilekani advised Indian AI startups to stay away from building large language models (LLMs) and make practical AI applications instead.
“Our goal should not be to build one more LLM. Let the big boys in the (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,” Mr. Nilekani said at the Meta AI Summit.
Mr. Nilekani said the focus must be on building infrastructure that can collect data to deploy and scale apps in a frugal manner. “Let other people build LLMs, we will make sure it works for people” he stated.
Other industry leaders in the country have echoed similar ideas when it comes to building new AI models.
“I don’t think there’s going to be a huge incremental advantage in building your own LLMs since there are so many already available. If you go by the existing heritage of most Indian organisations, we are more of system integrators. If you take a similar approach here, we are better off,” told TCS CEO K. Krithivasan to The Hindu’s Businessline a week ago.
Published – January 21, 2025 04:33 pm IST
In a recent interview, Perplexity CEO Arvind Srinivas shared his thoughts on Nandan Nilekani’s suggestion to prioritize model deployment over model training skills in India’s tech industry. Srinivas argued that Nilekani is wrong in his approach, emphasizing the importance of developing strong model training skills.
According to Srinivas, model training is the foundation of any successful AI project. Without proper training, models will not be able to accurately analyze and interpret data, leading to unreliable results. He believes that focusing solely on model deployment without adequate training skills will ultimately hinder India’s progress in AI technology.
Srinivas also highlighted the potential impact on job opportunities in the tech sector. By neglecting model training skills, India may miss out on valuable opportunities for growth and innovation in AI development. He stressed the need for a balanced approach, where both model training and deployment skills are given equal importance.
In conclusion, Srinivas expressed his disagreement with Nilekani’s viewpoint, advocating for a comprehensive strategy that prioritizes model training skills alongside deployment. He believes that this approach will better position India as a leader in AI technology and drive future advancements in the industry.
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