Opinion | AI Needs A Ramanujan Moment: Why India Must Think Beyond The West
The next Ramanujan of AI will not emerge from research that mimics the West but from minds that rethink intelligence with India’s unique strengths—frugality, adaptability, and a refusal to accept intellectual colonisation
A century ago, when India was shackled by political and economic colonisation, a band of extraordinary scientists defied their circumstances to revolutionise physics, mathematics, and chemistry. They lacked institutional support, suffered racial discrimination, and often worked without pay. And yet, their intellectual independence led to path breaking contributions that shaped global science.
Today, while India is politically and economically free, it faces a subtler yet equally insidious challenge: mental colonisation. As the global AI race accelerates, India needs researchers who embody the spirit of Jagadish Chandra Bose, Satyendra Nath Bose, C.V. Raman, and Srinivasa Ramanujan—scientists who created with little but thought freely and acted boldly.
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Breaking Free from Mental Colonisation
The irony is striking. A hundred years ago, despite systemic oppression, Indian scientists thought independently and pioneered new fields. Jagadish Chandra Bose refused to patent his work on wireless communication, prioritising knowledge over personal gain. Satyendra Nath Bose reimagined quantum statistics with a single letter to Einstein, fundamentally shaping quantum mechanics. These scientists were not constrained by the West’s intellectual hegemony; they built their own paradigms.
Contrast that with today: Indian research institutions remain fixated on Western benchmarks—be it publishing in elite journals, securing grants from Western funding agencies, or replicating Silicon Valley’s technological models. The result? A lack of originality, over-dependence on Western validation, and an AI industry that consumes rather than creates. But what if we approached AI research the way our forefathers approached science—unbound by conventional constraints?
The DeepSeek Wake-Up Call
China is already demonstrating how a nation can break free from Silicon Valley’s technological hegemony. DeepSeek, China’s homegrown AI research lab, has produced models that rival OpenAI and Google DeepMind. The Chinese approach is clear: resource efficiency, alternative methodologies, and independent innovation. Instead of chasing the American paradigm, they are crafting their own.
India must take note. Our research mindset cannot be constrained by resource limitations, nor should it be enslaved to Western frameworks of technological progress. There are novel ways to build frontier technologies with fewer resources. Consider how Meghnad Saha, without access to a modern laboratory, formulated the Saha Ionization Equation, which transformed astrophysics. Or how Ramanujan, armed with nothing but self-taught mathematics and a notebook, sent shockwaves through Cambridge with his theorems. Their constraint was economic, but their ideas were limitless.
An Indic Alternative to AI Research
The world does not need another OpenAI or Google; it needs an alternative way of thinking about AI. What alternative framework can India offer to the AI revolution? Prof. Gopinath of Rishihood University has inspired a crucial insight—perhaps India’s intellectual traditions hold the key to new AI models.
Imagine a way of thinking that combines what you see with your eyes and what you figure out with numbers. That’s what “computational positivism"—or Drigganitaikya in Sanskrit—means. It’s about blending observation (like watching the stars) with math (like calculating their paths). This idea comes from ancient India, where brilliant minds like Aryabhata and Bhaskara watched the world closely and created math to explain it—think of them as early scientists and coders rolled into one. This tradition emphasized empirical validation—cross-checking calculations against observable data—and iterative refinement, creating a robust framework. For instance, Aryabhata’s computation of Earth’s circumference (within 1 per cent of the modern value) relied on both geometric theory and astronomical measurements, showcasing this synthesis.
How can this method help AI and machine learning? Today, AI and machine learning (ML) are like super-smart calculators that learn from data—like teaching a computer to recognise cats in photos by showing it thousands of pictures. But sometimes, AI gets stuck: it might overthink the data, miss the big picture, or use too much power. India’s computational positivism offers a fresh approach. Just like ancient Indians checked star positions against their calculations, AI could combine real-life observations with math rules to make smarter, more reliable predictions.
For instance, while current ML might predict stock prices from historical data alone, a Drigganitaikya-inspired model could incorporate real-time economic indicators and mathematical priors (e.g., market equilibrium equations), refining predictions dynamically. This could lead to more robust, efficient, and explainable AI systems—critical for applications like climate modeling, autonomous vehicles, or personalised medicine.
In short, India’s old-school wisdom could give AI a new edge: smarter, simpler, and more in tune with reality. It’s like teaching a computer to think like a Rishi—watching, calculating, and adapting all at once.
A New Breed of Indian Researchers
India must cultivate a new generation of researchers who combine intellectual audacity with strategic pragmatism. This means moving beyond the obsession with Western benchmarks and embracing indigenous, disruptive models of innovation. It means recognising that AI is not just about GPUs and billion-dollar datasets but about reimagining intelligence itself.
The scientists of 100 years ago built their legacies not through imitation but through fearless originality. India must do the same in AI and frontier technologies. The next Ramanujan of AI will not emerge from research that mimics the West but from minds that rethink intelligence with India’s unique strengths—frugality, adaptability, and a refusal to accept intellectual colonisation.
The global AI race is wide open. The question is: Will India enter it as an independent creator, or as a follower of preordained paths? History shows us the answer. It is time to remember it.
Shobhit Mathur is the Co-founder and Vice-Chancellor of Rishihood University, Haryana. Views expressed in the above piece are personal and solely those of the author. They do not necessarily reflect News18’s views.
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