Co-Founder and CTO of Prospera Technologies, leading the company's vision to transform the way food is grown using data science and AI. The human race has come a long way in our ability to produce food at scale. Historian and author Yuval Noah Harari refers to it in his book Sapiens as "an agricultural revolution," using wheat as an example. Ten thousand years ago, wheat was a wild grass that grew in a relatively small region in the Middle East. Today, wheat can be considered one of the most successful plants in history, according to the evolutionary criteria of survival and reproduction. In regions where wheat never existed, such as the Great Plains of North America, you can drive for hundreds of miles without seeing anything else but wheat fields.
Agricultural equipment giant Deere & Co. next summer will debut in farm fields a solution that combines machine vision and machine learning, to distinguish weeds from plants. Agriculture giant Deere & Co. plans to roll out a system next summer that combines machine vision and machine learning to improve the identification of individual plants and weeds. Deere's Jahmy Hindman said neural network models could be trained to only spray weeds in crop fields, killing everything except genetically modified plants designed to survive chemical applications. Said Hindman, "We are interested in being able to manage each plant over the course of its life, minimizing inputs and maximizing productivity." The technology would take pictures of plants, and a machine cruising the field would make the decision to spray in just seconds.
One of the world's most endangered whales was spotted swimming with a newborn in the waters off South Carolina's Hilton Head island. A drone camera captured footage of a 50-ton North Atlantic right whale and her calf frolicking about four miles from shore. According to the boat captain who spotted the pair on Friday, the mother was 50 feet long and the calf was close to 15 feet. The North Atlantic right whale is among the rarest of marine mammals, with less than 400 left in the world. Collisions with boats and entanglement in lobster nets are the main reason they are critically endangered.
Agritech in India has seen a skyrocketing growth with numerous startups emerging with new technologies and advanced methods such as data analytics, machine learning and satellite imaging, among others to cater to the needs of Indian farmers and maximise their output. India with 118.7 million farmer households, accounting for more than half of the population is heavily dependent on agriculture as a primary source of income. But Indian agriculture is plagued by several problems both man made and natural such as; unavailability of seeds, small and fragmented land-holdings, problems with irrigation due to uncertain monsoon, shortage of finance among other necessities, leaving farmers helpless and with no option but to let their produce go at dirt cheap prices. Therefore, Agritech is clearly one of the most needed industries in India and here is a list of top 9 agritech startups helping Indian farmers by providing agronomic intelligence. Started in 2016 by Nishant Vats and Tauseef Khan, Gramophone is a one-stop e-commerce platform for farmers delivering agricultural inputs in more than 10,000 villages.
An inquiry into growing Australia's agriculture sector to AU$100 billion by 2030 has highlighted that digital technology will be key to driving growth in Australia's agriculture. The inquiry, conducted by the House of Representatives Standing Committee on Agriculture and Water Resources and chaired by Liberal MP Rick Wilson, estimated that digital agriculture could add AU$20 billion to the value of the sector. "A boost of this size would, by itself, cover the projected shortfall required to reach the AU$100 billion by 2030 target," the Growing Australia report [PDF] said. The inquiry was launched last September to investigate whether the National Farmers' Federation's goal to grow the country's agriculture sector to AU$100 billion by 2030 would be attainable. Read: CSIRO using artificial intelligence to map 1.7m Australian grain paddocks In releasing the findings, Wilson described the target as ambitious but achievable.
A spectrogram of the sound of a human voice, used by voice-recognition software. The idea of artificial intelligence (AI) -- systems so advanced they can mimic or outperform human cognition -- first came to prominence in 1950, when British computer scientist Alan Turing proposed an'imitation game' to assess whether a computer could fool humans into thinking they were communicating with another human. Soon after, researchers at Princeton University in New Jersey built MADALINE, the first artificial neural network applied to a real-world problem. Their system, modelled on the brain and nervous system, learnt to solve a maze through trial-and-error. Since then, the rise of AI has been enabled by exponentially faster and more powerful computers and large, complex data sets.
Despite a growing population, now predicted to reach 9.6 billion by 2050, the agriculture industry must rise to meet demand, regardless of environmental challenges like unfavorable weather conditions and climate change. To meet the needs of that growing population, the agriculture industry will have to adopt new technologies to gain a much-needed edge. New agricultural applications in smart farming and precision farming through IoT will enable the industry to increase operational efficiency, lower costs, reduce waste, and improve the quality of their yield. So, what is smart farming? Smart farming is a capital-intensive and hi-tech system of growing food cleanly and sustainable for the masses.
A behemoth of a worker, recently recognized by a national publication, that can meticulously and precisely remove weeds growing between sprouting crops is being employed on farms in California and Arizona. Time magazine recently placed the FarmWise Titan FT-35 on its list of Best Inventions of 2020. It is an automated mechanical weeder that can help substitute the pass of a hand-weeding crew, which usually has 10 to 15 people. FarmWise has its operations headquarters, or home base for its team and machines, in Salinas and an office in San Francisco that houses most of its engineers. The company works with farming operations in the Salinas Valley such as Dole and Braga Fresh, plus dozens of other customers.
Technology is everywhere in the 21st century, and America's food system is no exception. Scientists with the USDA Agricultural Research Service's (ARS) Western Human Nutrition Research Center (WHNRC), at the University of California (UC) – Davis, have joined forces with over 40 researchers from six organizations to form an institute that will use artificial intelligence (AI) to create the next-generation food system. The team, led by UC Davis, also includes UC Berkeley, Cornell University, and the University of Illinois at Urbana-Champaign. The project is funded by a $20 million grant from USDA's National Institute of Food and Agriculture. "The AI Institute for Next Generation Food Systems (AIFS) is dedicated to accelerating the use of artificial intelligence to optimally produce, process, and distribute safe and nutritious food," said Dr. Danielle Lemay, a USDA research molecular biologist at WHNRC.
Like humans, pigs have idiosyncratic faces, and new players in the Chinese pork market are taking notice, experimenting with increasingly sophisticated versions of facial recognition software for pigs. China is the world's largest exporter of pork, and is set to increase production next year by 9%. As the nation's pork farms grow in scale, more farmers are turning to AI systems like facial recognition technology – known as FRT – to continuously monitor, identify, and even feed their herds. This automated style of farming has the potential to be safer, cheaper and generally more effective: In 2018, pig farmers in China's Guangxi province trialling FRT found that it slashed costs, cut down on breeding time, and improved welfare outcomes for the pigs themselves. But it also has the potential to leave behind independent, small-scale farmers, who cannot afford to introduce this kind of technology to their operations.