Propelled by the rapid development of innovative technologies and agribusiness-tech partnerships, modern farming is on the verge of the kind of digital transformation process seen across many other industries. In fact, research predicts that by 2026, the AI in agriculture market will grow at over 25% per year to reach a value of $4 billion. According to the same study, this impressive acceleration in the adoption of AI is due to the "increasing implementation of data generation through sensors and aerial images for crops, increasing crop productivity through deep learning technology, and government support for the adoption of modern agricultural techniques." But where is this tech-led innovation being focused? Smart farming, for example, is an autonomous end-to-end system that can gather and process key datasets to give actionable insights.

The five international teams participating in the final rounds of the 3rd Autonomous Greenhouse Challenge have completed the first try-out experiment. The teams tested their algorithms and gained experience during a first crop cycle with lettuce. The goal of the 3rd Autonomous Greenhouse Challenge is to grow lettuces in two crop cycli fully autonomously with an AI algorithm on a cloud platform with good quality and little resource and energy use and without any human interference in the experimental greenhouses of Wageningen University & Research (WUR) in Bleiswijk. The first crop cycle of the 3rd Autonomous Greenhouse Challenge started on February 2nd with the planting of cultivar Salanova. Five teams (Team CVA, Team digital_cucumber, Team MondayLettuce, Team VeggieMight, Team Koala) participated in the first try-out experiment to test their algorithms and gain experience.

Agile development, rapid learning, granular instrumentation, a large-scale compute and data infrastructure, cutting-edge machine learning -- these are the ingredients that give innovative companies their edge. But to date, this mindset and approach have been largely confined to the world of software and Internet-based services. Look outside of that space and you'll find a wide range of industries -- some hundreds of billions of dollars in value -- that are slow-moving and starved of rapid iteration and learning. Think aerospace, transportation, manufacturing, logistics, material sciences, life sciences, and agriculture. These industries are ripe with opportunities for transformative startups, and are seeing a new wave of entrepreneurs capitalize on them by unlocking the agility and speed of learning we take for granted in the software world.