Lana Bandoim explores these developments in a recent interview with Ofir Schlam, CEO and co-founder of Taranis, a leading precision agriculture intelligence platform.
Taranis is an AI-powered agriculture intelligence platform that was selected to be part of John Deere’s startup collaborator. It uses sophisticated computer vision, data science and deep learning algorithms to enable farmers to make informed decisions.
The platform is capable of monitoring fields and finding early symptoms of uneven emergence, weeds, nutrient deficiencies, disease or insect infestations, water damage and equipment issues. Overseeing millions of acres of farmland in the U.S., Argentina, Ukraine, Brazil and Russia, the company employs over 75 people worldwide and is headquartered in Tel Aviv with subsidiaries in Argentina, Brazil and the U.S.
Taranis relies on AI and machine learning. While Taranis’ imagery has enough resolution to scout an entire field, without automation it is of little use. That is why it employs deep-learning methods to “teach” the software what each problem looks like on a crop-to-crop basis. This is a very complex process, which requires an accurate data set of hundreds of thousands of symptoms, manually tagged by Taranis’ team of 120 expert agronomists.
Read the whole Forbes article here.
