Former United Kingdom Prime Minister Rishi Sunak Highlights India’s Unique Position in Global Technology Transformation at India AI Impact Summit 2026

Ganguli highlighted a striking paradox: while AI systems are advancing rapidly, we still lack a fundamental understanding of how they work. At the same time, the human brain, shaped by 500 million years of evolution, remains vastly more data- and energy-efficient than modern AI.He outlined three frontiers for advancing intelligence: data efficiency, energy efficiency, and the melding of brains and machines.On data efficiency, Ganguli presented new theoretical breakthroughs explaining neural scaling laws, long observed but poorly understood phenomena governing AI performance. His team’s recent work demonstrates how smarter data selection can dramatically accelerate learning, bending slow power laws into faster exponential gains.On energy efficiency, he contrasted the human brain’s 20-watt energy consumption with AI systems that can require millions of watts. By studying how biology matches computation to physics, Ganguli proposed a reimagining of the technology stack, from algorithms to quantum hardware, giving rise to what he calls “quantum neuromorphic computing.” Perhaps most striking was his vision for brain-machine integration. By building digital twins of neural circuits, researchers can decode perception, simulate disease states, and even write precise neural patterns back into the brain. From decoding visual perception in mice to controlling epileptic seizures, this fusion of AI and neuroscience signals a future where intelligence is both better understood and more therapeutically powerful.Together, the two addresses framed AI not as a distant abstraction, but as an immediate and transformative force. One speaker emphasized global governance, adoption, and human impact; the other laid the scientific foundations required to push beyond today’s models.