A Cambridge AI model wants to make small farms visible to satellites for the first time

Satellite crop monitoring has always been built for the industrial mega farms of the US and Brazil, leaving the smallholder plots that feed much of the developing world essentially invisible to food security planners. Tessera's trick is turning imagery into compact seasonal summaries that can resolve messy field boundaries cheaply, which matters more for the UN and World Bank's grain forecasts than another benchmark topping model ever could. It is a reminder that some of the most consequential AI work looks nothing like a chatbot demo.