Globally, India has the second-largest number of residents who use AI (81%). Further, Asian countries tend to display greater subjective knowledge of AI, with South Korea, China, and India leading the way.
“India offers one of the most relevant and exciting contexts for AI, considering the readiness within the country to adopt various technologies, including IoT and AI, alongside other foundational technologies,” said Shekar Sivasubramanian, the CEO of Wadhwani AI, in an exclusive interview with AIM.
Further, he said that the country’s ability to skip extensive wired network development and move straight to wireless infrastructure demonstrates its readiness and adaptability.
Sivasubramanian also highlighted that for AI to succeed on a large scale, access to diverse data, which is abundantly available in India, is required.
While we are at the early stages of harnessing this data, the country’s multilingual and multicultural environment provides a unique opportunity to develop context-centric, powerful AI solutions.
“If AI works in India, it can work anywhere. This is because the diversity within the population acts as a natural protection against bias, allowing for more accurate and representative AI models,” added Sivasubramanian.
Sivasubramanian is an industry leader who brings 40 years of global applied technology and management experience towards creating positive and sustainable impact at scale.
He is currently driving non-profit organisation Wadhwani AI’s efforts toward establishing AI-driven solutions and ecosystems for the benefit of millions across the developing world.
Voice is the Future
“In the next 5-10 years, we would completely stop using the thumb and use only voice-based interfaces,” the Wadhwani AI CEO predicted.
He noted that to build meaningful voice-based interfaces, embracing the diversity of expression in India is crucial. And India’s varied linguistic and cultural landscape provides a unique testing ground for developing advanced voice AI technologies.
Along similar lines, Pramod Varma, former chief architect of Aadhaar, told AIM, “Indian entrepreneurs should really look at voice as a completely new human-computer interaction method. It could be very powerful, and I think it’s going to happen because voice is natural to humans.”
In a previous interaction with AIM, Sarvam AI also mentioned that it is currently working on a voice-based Indic LLM, which it plans to release this year.
Earlier, chief AI scientist at Meta, Yann LeCun had said that in the next 10-15 years we won’t have smartphones, and will be using augmented reality glasses and bracelets to interact with intelligent assistants.
“The last thing we might want is intelligent virtual assistants that help us in our daily lives. So today, all of us here are carrying a smartphone in our pockets; 10 years from now or 15 years from now, we’re not going to have smartphones anymore. We’re going to have augmented reality glasses,” said LeCun.
Even Meta CEO Mark Zuckerberg has repeatedly stressed that neural interfaces represent the inevitable next step beyond current methods like typing on screens.
Wadhwani AI Initiatives
India grows 26% of the world’s cotton and nearly 100 million farmers rely on cotton farming for their livelihood. However, cotton is highly vulnerable to pests, causing yield uncertainty and financial distress to farmers.
So, to help farmers protect their crops, Wadhwani AI has introduced CottonAce, an AI-powered early warning system available as an Android app.
Lead farmers, who work with welfare programs, use the app to upload photos of pests and the AI algorithm analyses the photos, determines infestation levels, and provides actionable advice, which is then shared with neighbouring farmers, even those without smartphones.
The app is available in nine languages, including English, Hindi, Marathi, Gujarati, Telugu, Kannada, Tamil, Odia, and Punjabi.
In the health industry, the non-profit institute developing AI solutions for social good is an official AI partner of the Central TB Division (CTD), and are developing multiple interventions across the TB care cascade and helping India’s National TB Elimination Programme become AI-ready.
They use AI to interpret the results of the LPA test to determine drug resistance to TB. Each LPA strip encodes the drug-resistance pattern of the patient via a series of activated (dark) and inactivated (light) bands corresponding to different regions of the genome of the Tuberculosis bacterium.
Further, it is developing multiple AI solutions to reduce morbidity and mortality for mothers and children in low-resource settings by improving the quality of primary care and strengthening the first 1,000 days of life.
