The Sunnyvale, California-based company makes farming machines. Blue River's machines are robots that help farmers manage their fields more efficiently. The jury is still out on whether this will be a fruitful sector for venture capitalists like those backing Blue River Technology, since large exits have been thin on the ground since Monsanto's 2013 acquisition of the Climate Corporation for more than $1 billion. Lawyer Roger Royse, whose California law firm specializes in representing agtech companies, tells Inc. that he thinks Blue River is a prime acquisition target, especially as the industry consolidates.
The controversial corporation will use Atomwise's artificial intelligence expertise to discover molecules that could protect crops quicker. Atomwise uses deep learning algorithms to discover molecules that might have the desired effect, rather than look at every individual molecule. "Each growing season, farmers around the world are challenged with yield-robbing pests and diseases, yet the average crop protection product takes up to 11 years and more than $250 million to commercialize," said Jeremy Williams, Monsanto's agricultural productivity innovations lead. "Discovering new solutions is critical, and this collaboration will help bring much-needed crop protection solutions to farmers faster."
The process of developing and getting new crop protection technologies to market can stretch for more than a decade and require hundreds of millions of dollars. To home in on new ones in more timely and efficient ways, Monsanto is turning to artificial intelligence through a collaborative research agreement announced Wednesday. The biotech giant's partnership with Atomwise, a San Francisco-based company that uses artificial intelligence to accelerate the discovery and development of medicines, will look for crop science applications of the company's AtomNet technology, which a press release said uses "algorithms and supercomputers to analyze millions of molecules for potential crop protection products." "Instead of the traditional trial-and-error and process of elimination to analyze tens of thousands of molecules, the AtomNet technology aims to streamline the initial phase of discovery by analyzing how different molecules interact with one another," the release stated.
Drought-damaged corn on an Ohio farm, 2012.In 2012 heat and drought in the United States slashed national corn, soybean and other crop yields by up to 27 percent Famines are extreme events in which large populations lack adequate access to food, leading to malnutrition and death. In the past several decades, many of the world's major breadbaskets have experienced shocks – events that caused large, rapid drops in food production. It is clear that rising demand, growing international trade in agricultural products, and the potential for weather-, climate- and soil-related shocks are making the world food production system less resilient. We have developed scenarios in which small shocks (10 percent crop loss) and large shocks (50 percent crop loss), averaged over five years, are applied to corn, wheat or rice in their major production regions, and then to all the combinations of one, two or all three crops in one, two or the top three production regions.
Deep learning models, trained by using a large set of labeled data and neural network architectures that contain many layers, routinely achieve impressive accuracy. The article explains how Neurala's technology will assist Air Shepherd's analysts in identifying animals, poachers, and vehicles from the terabytes of data created by the drones' video feeds. BeeScanning is a smartphone app that uses deep learning to analyze images of bee colonies to determine if they are infected by varroa mites. The Nature Conservancy's Indonesia Fisheries program is working with 2 technology companies that use machine learning to sort and recycle cell phones to develop a prototype, called Fishface, that applies this same technology to species identification for fish.
For example, vertical farming, a technique allowing farmers to grow and harvest crops in controlled environments, often indoors and in vertical stacks, has exploded in both popularity and potential. Finally, augmented reality (AR), where informative images overlay or augment everyday objects, can help both farmers and gardeners to monitor and manage crop health. A remote server dedicated to machine learning analyses growth and growth conditions and anticipates future plant needs. This idea is at the heart of Plant.IO: a fun, workable solution for an agriculture-based scenario where digital information can overlay a physical object or area without losing context.
FORTALEZA, BRAZIL – Researchers in Brazil are experimenting with a new treatment for severe burns using the skin of tilapia fish, an unorthodox procedure they say can ease the pain of victims and cut medical costs. Related Image Doctors wrap a child's burnt skin with sterilized tilapia fish skin at Dr. Jose Frota Institute in the northeastern costal city of Fortaleza, Brazil, May 3, 2017. A tilapia fish and tilapia fish skins are displayed in Jaguaribara, Brazil, April 26, 2017. After about 10 days, doctors remove the bandage.
Google partnered with nonprofits to found Global Fishing Watch to detect illegal fishing activity using satellite data in near real time. The algorithm for detecting apparent fishing activity uses AIS data from roughly 35,000 fishing vessels worldwide (out of the roughly 200,000 vessels on the seas in the course of a year). The system captures the navigation pattern information of these 35,000 vessels with 22 million data points per day allowing deep learning algorithms to learn and then detect patterns that indicate fishing. Satellite intelligence startup Orbital Insight partnered with Global Forest Watch to detect illegal logging and other causes of global forest degradation.
In a departure from using AI and machine learning tools for tasks such as automating customer service, some companies are applying the technologies to grow better corn crops and exterminate bugs and vermin. The researcher defines machine learning (ML), a sub-field of AI, as algorithms leveraging technologies that operate based on existing information and are used in both unsupervised and supervised learning. Some of the company's 5,000 pest control technicians are using an Android mobile app developed by Accenture to identify bugs. The picture calls home to Google's image classification and machine learning software to sift through a number of pest images and identify the intruder, according to Nisha Sharma, a managing director in Accenture's mobility group.
Researchers have pioneered an autonomous tractor which can be steered by a farmer from a control room to carry out the drilling, seeding and spraying of the land. Researchers have pioneered an autonomous tractor which can be steered by a farmer from a control room to carry out the drilling, seeding and spraying of the land. Drilling of the spring crop of barley has already taken place on the land and over the coming months the crop will be cultivated before harvest in August and September. Drilling of the spring crop of barley has already taken place on the land and over the coming months the crop will be cultivated before harvest in August and September.