From ChatGPT to weather forecasting, the applications of Artificial Intelligence (AI) continue to expand. London-based crop intelligence firm HSAT recently announced a “ground-breaking technology” capable of improving disease detection and crop prediction through the power of AI.

Known as “Inference”, HSAT’s development combines several established AI technologies into a single platform, including computer vision, machine learning, and large language models.

“Inference is a breakthrough because it yields a high degree of accuracy: typically 95% accuracy for crop prediction, and over 90% accuracy for disease detection,” the firm said in a release.

Easy to use, the platform offers predictive accuracy to help farmers and food producers identify and combat diseases. The platform can capture thousands of pictures of crops, taken with mobile devices. HSAT then analyzes these images to detect the risk of disease.

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Using geolocation, each image is mapped and associated with corresponding satellite and weather data.  With this information, HSAT can identify affected crops, build heat maps across entire countries, and create large-scale predictive models of national risks.  

HSAT can extend its analysis from individual plants to fields, farms, counties, and where useful for larger companies, to the national and global level.

“By leveraging AI for crop prediction and disease detection, farmers, producers, and traders can gain a global view of crop health, identify areas of poor irrigation, and create regional and national risk maps,” said HSAT Founder Rob Weston.

According to HSAT, Inference has already been deployed in 6 countries, across 4 continents, to assess “tens of thousands of farms.”