A.I. for Agriculture and the Insurance Implications as Explained by Adam Smith of Descartes Labs

A.I. for Agriculture and the Insurance Implications as Explained by Adam Smith of Descartes Labs

The technical team at Descartes Labs consists of a group of professionals who formerly worked for Los Alamos. They were artificial intelligence experts who formerly focused on machine learning for the U.S. government.

The artificial intelligence algorithms they created were used mostly on satellites, but also on drones performing aerial reconnaissance. One of the final projects they worked on during their time at Los Alamos was a joint project with European law enforcement attempting to predict the street value of heroin based on the supply of opium in Afghanistan.

This sparked the idea to apply data mining, artificial intelligence, and machine learning technology to the agricultural industry, leading the start up down an unexpected path.

The Transition to InsureTech

Using data mining in agriculture was a somewhat revolutionary approach, enabling them to base analytics and forecasts off of samples of corn, wheat, and cotton around the globe. While the application of this technology in agriculture is interesting in itself, it can also be highly beneficial to insurance companies- particularly those that insure large and small farms throughout the U.S.

It offers the ability to not only pinpoint individual farms for historic yields and production, but can also use analytics to calculate the damage or harm that came from a hail storm in corn fields, a late frost in wine country, or a deep freeze in citrus orchards without requiring an adjuster to go out and review the damage in person. This saves valuable time and money and provides highly accurate information that isn't quite as vulnerable to human error.

Other insurance benefits to consider, aside from virtual claims adjustments, is that insurance companies can engage in far more accurate loss forecasting and designation of funds as a result of the data mined from this service. It is even possible to create accurate fund designations based on the historic yields on a farm-by-farm basis.

Descartes Labs: Looking Forward

Descartes Labs is currently exploring new opportunities in insurance using this same satellite, data mining, and machine learning technology for other insurance applications, oil fracking, trading, and more. The applications are endless and can be beneficial to insurance companies interested in domestic and foreign agriculture today and in other areas over time and as machine learning technology evolves.

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