Google-backed AI startup Cropin wants to predict future of food


A worker picks navel oranges during a harvest at a farm in Leeton, Australia. As the world’s population explodes and food security concerns increase, generative AI and large language models have the potential to transform modern agriculture in a climate-impacted world. — Bloomberg

Food and agriculture AI startup Cropin Technology Solutions has unveiled a real-time intelligence solution to forecast future yields for 13 vital crops as artificial intelligence helps overcome bottlenecks in the farming industry.

The Bangalore-headquartered company unveiled Sage, powered by Alphabet Inc’s Google Gemini AI model, which converts the world’s agricultural landscape into a proprietary grid-based map and then delivers precise predictive intelligence based on historical data. Decision-makers can ask questions about crop performance and life cycle in their native language and get information on productivity, climate, farm practices and soil for the 13 crops that account for 80% of global food demand.

“To predict the future of a particular crop is a major leap, and we see entire industries go into turbulence on account of shortfall in say, cocoa or orange crop,” said Krishna Kumar, Cropin’s founder and chief executive officer.

As the world’s population explodes and food security concerns increase, generative AI and large language models have the potential to transform modern agriculture in a climate-impacted world. That can help a whole range of customers from consumer packaged goods makers and seed manufacturers to financial institutions and governments plan crop production and make informed decisions on cultivation.

The world’s agricultural land spans 4.8 billion hectares, according to Cropin.

The company’s technology fuses generative AI with four decades of climate data, earth data and knowledge graphs to decode each crop country-by-country and predict how a certain crop will behave this season, next year or over the next five years.

"We have the technology to predict, for example, which variety of potato will yield optimally in certain grids in Idaho or in Kenya, helping a prominent chipmaker customer to plan their supply chain,” Kumar said over a video call. – Bloomberg

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