The first build is always the slow one. MahaVISTAAR took about nine months. Ethiopia, learning from it, built something comparable in about three months. Amul's Sarlaben, drawing on both, launched in about three weeks. Nothing says every deployment will move this fast, but it
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- Silicon Valley is racing to build the most powerful model. India is asking a different question: how do you put AI into the hands of a billion people, in their own languages, on the devices they already own. The edge is not a bigger model. It is public digital infrastructure, the
- AI labs release a more capable model almost every week. That is not the hard part anymore. The hard part is adoption: getting AI into the institutions and services that actually touch people's lives. When capability races ahead and adoption lags, the people who stand to gain the
- A tribal language spoken by 10 million Indians couldn't be understood by AI. When a farming app in Nandurbar worked only in Marathi, the Bhili-speaking community built the data themselves. Recording words, translating textbooks, documenting oral stories. That's what AI diffusion
- An idea can travel from a conversation with the Prime Minister to a working app in millions of hands in 34 days. In India, it just did. On January 8, the idea was raised with PM Modi. By February 11, it was live. The Sarlaben app now serves the world's largest dairy cooperative:

