John Deere has officially acquired Blue River Technology, the machine learning technology company that puts a large focus on agriculture. Blue River develops equipment that can be used by agricultural specialists and producers to optimize their daily work. "As a leader in precision agriculture, John Deere recognizes the importance of technology to our customers. "Blue River is advancing precision agriculture by moving farm management decisions from the field level to the plant level," said Jorge Heraud, co-founder and CEO of Blue River Technology.
Deere & Company (NYSE: DE) has signed a definitive agreement to acquire Blue River Technology, which is based in Sunnyvale, California and is a leader in applying machine learning to agriculture. As an innovation leader, Blue River Technology has successfully applied machine learning to agricultural spraying equipment and Deere is confident that similar technology can be used in the future on a wider range of products, May said. Blue River has designed and integrated computer vision and machine learning technology that will enable growers to reduce the use of herbicides by spraying only where weeds are present, optimising the use of inputs in farming – a key objective of precision agriculture. "Blue River is advancing precision agriculture by moving farm management decisions from the field level to the plant level," said Jorge Heraud, co-founder and CEO of Blue River Technology.
John Deere, the farm equipment company that's been chasing autonomous technology for more than 20 years, has agreed to buy Blue River Technology, a startup that uses AI to automatically identify and spray herbicide on weeds. Blue River Technology makes a number of farm tools: an automatic precision weed-sprayer, a device that trims lettuce at scale, and software for drones to analyze crops. John Deere's tractors have a level of autonomy today--some can steer themselves via help from GPS signals, while image sensors can determine the quality of grain during harvesting. But the company says Blue River's AI will allow future tractors to understand each individual plant in crops like lettuce and cotton, two areas Blue River has already showcased.
Farm equipment maker John Deere is banking on machine learning to change the way crops are grown, stumping up US$305 million (A$380 million) for a start-up in the space. Blue River Technology makes two "bots" armed with computer vision and machine learning that can be towed by a traditional tractor. A second bot is currently being tested for copper weeding; it similarly uses computer vision to recognise and remove weeds. John Deere hopes to take Blue River's technology and apply it to a broader range of agricultural scenarios.
John Deere is purchasing Blue River Technology, a Californian startup that makes machine learning tools for agriculture. Blue River's key technology is called "see and spray." The purchase of Blue River Technologies is a sign of increased interest in agriculture automation, but it's also a good example of just how complicated -- and difficult to automate -- the farming industry is. Blue River Technology is one of the companies that's bridging the gap between traditional agriculture and the fully automated farm of future, a future that may never come to pass.
Just ask Deere & Company. The John Deere brand owner just acquired Blue River Technology, which uses machine learning and computer vision to target herbicide spraying at just the weed-infested portions of a farm field. Blue River's team is staying in its Sunnyvale, California home. Machine learning is an "important capability for Deere's future," the company explains -- this is about making the technology an integral part of its equipment.
John Deere, established in 1837 to manufacture hand tools, announced it had acquired Blue River Technology, founded in 2011, late Wednesday. John Stone, an executive in the company's intelligent-solutions group, says Blue River's computer-vision technology will help Deere's equipment view and understand the crops it is working with. Stone says that Blue River's technology can make a larger impact on productivity because it makes decisions up close, on the ground. That system can target weeds with squirts of herbicide no larger than a postage stamp.
Data-driven management has risen sharply from a decade ago, when Thomas Davenport wrote Competing on Analytics.Data is now the critical tool for managing many corporate functions, including marketing, pricing, supply chain, operations, and more. Are managers relying excessively on data to guide their decisions, abdicating their own knowledge and experience? Data is now the critical tool for managing many corporate functions, including marketing, pricing, supply chain, operations, and more. As a practitioner and teacher of predictive analytics, my greatest concern is what I call the "big data, little brain" phenomenon: managers who rely excessively on data to guide their decisions, abdicating their knowledge and experience.
An Australian firm has revealed that construction giant Caterpillar has backed its Hadrian X giant truck mounted building robot that can lay 1,000 bricks an hour, glueing them into place as it goes. Mounted on the back of a truck, Hadrian X is simply driven onto a building site, and can put down 1,000 bricks an hour using a 30m boom, allowing it to stay in a single position while it builds. The bricks travel along the boom and are gripped by a clawlike device that lays them out methodically, directed by a laser guiding system. The bricks travel along the boom and are gripped by a clawlike device that lays them out methodically, directed by a laser guiding system.
One possible solution may be found in Agent-Based Simulation (ABS), a novel approach to solving complex business problems through computer simulations. One of the most appealing aspects of ABS is that it combines domain expertise and data. The domain expertise is used to define the structure of the simulation, which is unique to each business problem. With this approach, the manager's expertise regains the primary role, and the results of the simulation can be analyzed by the manager and data scientist together.