Speaking with AgTechNavigator at the recent World Agri-Tech Innovation Summit in San Francisco, he explained: “Last year when I was here there was still a lot of priomise in the air. What I see today is a lot more concrete examples of company’s that are using AI for detecting the efficacy of droplets on leaves, for example, or using AI for summerising a drone flight and turning that into a conversation with the grower or the advisor.”
The focus over the next year, he believes, is to further explore the potential of machine to machine conversations.
If AI chatbots are merely summerising information for users, for example, it risks diluting the value of AI, says Sheikh. But if machine-to-machine learning can turn information into actionable recommendations for growers “that is when we start to see real change”.
