Sammy Selim strode through the dense, shiny green bushes on the slopes of his coffee farm in Sorwot village in Kericho, Kenya, accompanied by a younger farmer called Kennedy Kirui. They paused at each corner to input the farm's coordinates into a WhatsApp conversation. The conversation was with Virtual Agronomist, a tool that uses artificial intelligence to provide fertiliser application advice using chat prompts. The chatbot asked some further questions before producing a report saying that Selim should target a yield of 7.9 tonnes and use three types of fertiliser in specific quantities to achieve that goal. "My God!" Selim said upon receipt of the report.

Climate change is the most horrific threat our species has ever known: No matter how powerful you are or how much money you have, our transforming planet is a reckoning for every one of us. But there are degrees to this misery. If you're perched in a Manhattan penthouse, the effects might not be immediately apparent (because you don't care or aren't paying attention, or both). If you're a subsistence farmer in Kenya, the situation is already much more dire. There's an equalizer, though, that is helping small farmers adapt to a changing planet: smartphones.

PlantVillage, a research and development project, based at Penn State University, is beginning to bring artificial intelligence to these smaller farms. Scientists at PlantVillage, in collaboration with international organizations, local farm extension programs and engineers at Google, is working to tailor A.I. technology for farmers in Tanzania who have inexpensive smartphones. The initial focus is on cassava, a hearty crop that can survive droughts and barren soil. But plant disease and pests can reduce crop yields by 40 percent or more. PlantVillage and International Institute of Tropical Agriculture have developed a simple A.I. assistant, called Nuru ("light" in Swahili). Wave the phone over a plant leaf, and the software diagnoses the disease or pest blight and suggests low-tech treatments.

Among the various companies, non-profits and researchers using tech company Google's TensorFlow platform, one application that has caught the attention of developers at the internet giant is PlantMD. Created by high school students Shaza Mehdi and Nile Ravenell, the app can detect diseases in plants. The duo, who showcased the app at Google's I/O annual developer conference this year, built it based on the Internet company's open-source machine learning library for data programming--TensorFlow. "PlantMD's machine learning model was inspired by a dataset from PlantVillage, a research and development unit at Penn State University. PlantVillage created an app called Nuru, Swahili for'light', to assist farmers to grow better cassava, a crop in Africa that provides food for over half a billion people daily," Fred Alcober, a member of Google's TensorFlow team, wrote in a blog post. Cassava plants, wrote Alcober, though very tolerant of harsh weather conditions, is susceptible to pests and diseases.

You're working in the garden when you notice your tomato plant is stunted and wrinkled. What is your next step? A team of researchers from Penn State University and the Swiss Federal Institute of Technology in Lausanne (EPFL) believes you should reach for your phone. They are building a free app called PlantVillage that can recognize plant disease from a mobile phone photo. Behind the app, expected to be available in early 2017, is a database of 150,000 photographs of diseased plants--a number the team intends to grow to three million.