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Alphabet’s Mineral: Harnessing Data Analytics for Agriculture Innovation

AgTech company, Mineral Ai becomes part of Alphabet

Mineral strives to supply enterprises in the food, agricultural, and technology sectors with fundamental and useful data and insights. Since 2017, Alphabet, the parent company of Google, has been quietly incubating projects at its X “moonshot factory.” Using a camera-equipped rover that can gather enormous image datasets, Mineral combines unique sensor technologies with machine learning algorithms. Effective machine learning and artificial intelligence (AI/ML) require large and trustworthy datasets.

X is a division of Alphabet (formerly Google) that was created in 2010 to incubate “moonshot” projects or technologies that have the potential to solve major global problems. The division is led by Astro Teller, who has referred to it as the “moonshot factory.” X’s purpose is to develop new technologies and spin them off as independent companies, such as Waymo, the self-driving car company that emerged from the Google self-driving car project. X’s projects are highly experimental and use a variety of technologies, such as artificial intelligence, robotics, and machine learning to solve large and complex problems. is an agtech company that has been incubated by Alphabet’s X division since 2017 and yesterday it was publicly announced by Alphabet for the first time. The company is working on providing foundational and actionable data and analytics for companies across the food, agriculture, and technology to better understand the natural systems driving our food supply and find new and improved ways to manage the industry in the face of climate change.  With a focus on three areas, Mineral is utilizing autonomous artificial intelligence, machine learning, and edge computation power to accomplish these aims.

“Why agriculture?  Why now?  Agriculture is increasingly believed to be a major contributor to the climate crisis – but it is also a victim of a changing climate.  There is no time to waste to find more climate-resilient crop varieties, transition to less chemical- and fossil-fuel-intensive practices, improve soil health, and restore biodiversity.  We are confident the foundational technology (such as generative artificial intelligence, machine learning, and edge computing power) has matured to the point where we can solve problems at the scale needed for production agriculture and with the accuracy and speed demanded by farmers.” Commented Elliott Grant, Mineral CEO on X announcement.

  • Creating sensor technologies that can produce rich plant data sets
  • Gathering agricultural data from many sources, organizing it for machine learning (ML), and creating strong software algorithms
  • Doing studies that can significantly improve our knowledge about plants in general.

Image provided by Mineral.Ai

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