… enabling planetary scale analysis through artificial intelligence and machine learning. The company also supports a diverse set of federal …

Bright red cranberries are visible from space during the harvest season, which occurs from mid-September through mid-November in North America. These images show a sample of bog harvests in Wisconsin between 2015 and 2019 captured by the Landsat 8 and Sentinel-2 satellites. In 1959, a nationwide food panic erupted over a treasured Thanksgiving dish. Two weeks before the holiday, the federal government announced that cranberries had been contaminated by a cancer-causing chemical. Cranberry sales plummeted, schools tossed out cranberry products, restaurants eliminated the suspect fruit from menus.

Descartes Labs uses artificial intelligence to detect wildfires, and they can correctly spot one in a record-breaking time of nine minutes.

On Friday afternoons, Caitlin Kontgis and some of the other scientists at Descartes Labs convene in their Santa Fe, New Mexico, office and get down to work on a grassroots project that's not part of their jobs: watching hurricanes from above, and seeing if they can figure out what the storms will do.* They acquire data from GOES, the Geostationary Operational Environmental Satellite operated by NOAA and NASA, which records images of the Western Hemisphere every five minutes. That's about how long it takes the team to process each image through a deep learning algorithm that detects the eye of a hurricane and centers the image processor over that. Then, they incorporate synthetic aperture data, which uses long-wave radar to see through clouds, and can discern water beneath based on reflectivity. That, in turn, can show almost real-time flooding, tracked over days, of cities in the path of hurricanes.

With the popularization of Artificial Intelligence and its gradual emergence as the core technology that is impelling momentous developments in a large number of fields, there has been a spurt in the use of machine learning and deep learning as well. As per multiple surveys and studies, AI and Machine Learning would be among the highest-paid and most lucrative career streams in the years to come. AI and Machine Learning would revolutionize our existing technological frameworks and usher in a new industrial age by reorienting and transforming everything from the simplest of appliances to automobiles. The applications of Machine Learning are not only limited to the terrestrial zone but have reached for the sky too, both literally as well as figuratively. Just like all other domains that are constantly reimagining themselves and girding for the future, the domain of remote sensing is also undergoing profound changes and witnessing increasing use of specified algorithms when Big Data and Cloud have become almost ubiquitous.

Machine learning, combined with satellite imagery and Cloud computing, is enabling understanding of the world and making the food supply chain more efficient. There are more than 7 billion people on Earth now, and roughly one in eight people do not have enough to eat. According to the World Bank, the human population will hit an astounding 9 billion by 2050. With rapidly increasing population, the growing need for food is becoming a grave concern. The burden is now on technology to make up for the looming food crises in the coming decades.

Geospatial analytics, an industry where satellites are used to track everything from retail footfall to food production. Companies working on the technology have attracted big money. Orbital Insight raised $50 million in funding last year, while Descartes Labs attracted $30 million and SpaceKnow raised $4 million. One of the industry's pioneers is James Crawford, who worked for NASA and Google before founding Orbital Insight in 2013. "We were seeing an explosion in commercial satellites," said Crawford.

Geospatial analytics, an industry where satellites are used to track everything from retail footfall to food production. Companies working on the technology have attracted big money. Orbital Insight raised $50 million in funding last year, while Descartes Labs attracted $30 million and SpaceKnow raised $4 million. One of the industry's pioneers is James Crawford, who worked for NASA and Google before founding Orbital Insight in 2013. "We were seeing an explosion in commercial satellites," said Crawford.

Swarms of drones buzz overhead, while robotic vehicles crawl across the landscape. Orbiting satellites snap high-resolution images of the scene far below. Not one human being can be seen in the pre-dawn glow spreading across the land. This is a snapshot of the farm of the future. Every phase of the operation--from seed to harvest--may someday be automated, without the need to ever get one's fingernails dirty.

Say Machine Learning to someone, and if they recognize the term, they'll probably think, "tech company." But while the origin stories of transformative technologies like machine learning, deep learning, and artificial intelligence often seem to take root in Silicon Valley, the truth is these are industry-agnostic innovations. Their impact is being felt across countless fields you might never have thought of as being ripe for technological advancement. Think about it like this: If you were a farmer, and someone came to you and said, there's a technology out there that can accurately predict your crop yields, would you be interested? Well, this is exactly what Descartes Labs does.