The AI farm experiment

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Major companies are bringing together new machine learning algorithms, better and cheaper sensors, and increased computing power in hopes of addressing growing global demand for food and agriculture’s diminishing labor force.

The big picture: Alphabet’s X and John Deere, startups and universities are looking to AI-based agriculture to address these problems. But farming presents hard problems for AI that, if solved, could ultimately help it be deployed in more structured places (think: homes).

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The incredible ways John Deere is using artificial intelligence to transform farming

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Pesticides are currently an essential ingredient of big agriculture in order to ensure we can continue to feed the ever-growing global population of our planet.

However, pesticides also carry inherent risks, such as the damage they can do to the environment and local ecosystems, and the hazards that over-exposure can pose to human health. Their production and distribution also has environmental costs, as well as financial costs to the farmers. For this reason, when they must be used, there are a lot of good reasons that they should be used efficiently, and accurately.

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Internet of Things Innovations in Agriculture

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Venture capitalists invested a record amount in agriculture and food startups in the third quarter this year, totaling $269 million across 41 deals. Conservis, for example, raised $10 million to offer farmers a real-time view of operations. FarmLogs raised $4 million to deliver apps that help farmers increase their productivity and profitability by identifying the crops most likely to sell. In November, Eric Schmidt’s Innovation Endeavors and Flextronics Lab IX launched Farm2050, a collective to support “ag-tech” startups whose solutions boost global food production.

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