I love this question. I have thought the exact same thing. The applications seem pretty obvious, given that agriculture is such a precision-based, sensor-driven industry now.
I think there are two ways to think about applications: (a) in terms of today’s value chain in the ag industry and (b) in terms of a new value chain or delivery framework that currently doesn’t exist but can be enabled by deep learning coupled with other nascent technologies in robotics, optics, and biotech.
i bet the biggest challenge is not technical but strategic. a lot of growers might be too risk averse to replace a key aspect of their supply chain with an ML-powered product or device. that said i bet “enthusiast” customers would be very interested, e.g. small hydroponic growers or individuals with large gardens. what do you think?
Another angle I’ve thought about is how ML can just change the entire supply chain in general. Could an ML-powered device or service (drone, app, whatever) enable much higher yield growing in people’s apartments or home gardens? Maybe an app with a camera that, scanned over my garden, can tell me which plants are getting too much water or too little, or whether fertilizer is needed, or that a certain bug or disease is starting to affect a particular plant.
Francisco, are you working in this space?