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The World of Future Farming and Artificial Intelligence

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When you think of artificial intelligence (AI), chances are the first images that spring to mind are of gleaming tech headquarters populating the heart of Silicon Valley. Or perhaps you imagine state-of-the-art navigation and defense systems outfitting U.S. aircraft carriers and submarines. It's unlikely, though, that references to AI will conjure visions of sprawling fields replete with healthy crops, livestock grazing on emerald pastures, and expansive storehouses containing enormous yields of fresh fruit, vegetable, and dairy, all fresh from the farm. In fact, the marriage of AI and agriculture is real and it is promising. Now, more than ever, it appears that the future of farming may well lie in artificial intelligence technologies.


AI in agriculture could boost global food security, but there's risks - TechHQ

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As the global population has expanded over time, modernizing agriculture with the aid of innovations like AI has been humanity's prevailing approach to staving off famine. A variety of mechanical and chemical innovations delivered during the 1950s and 1960s represented the third agricultural revolution. The adoption of pesticides, fertilizers and high-yield crop breeds, among other measures, transformed agriculture and ensured a secure food supply for many millions of people over several decades. Concurrently, modern agriculture has emerged as a culprit of global warming, responsible for one-third of greenhouse gas emissions, namely carbon dioxide and methane. Meanwhile, inflation on the price of food is reaching an all-time high, while malnutrition is rising dramatically.


SwarmFarm Robotics Successfully Covers One Million Acres of Farming with Autonomous Robots

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SwarmFarm Robotics, the leader in Integrated Autonomy for agriculture, announced today that it crossed a significant milestone by successfully covering one million acres, 55,000 hours of operation, and has reduced pesticide inputs by an estimated 580 tons with its autonomous robots. These figures set SwarmFarm apart as the sole leader in a farmer-led movement that is happening whether operators are along for the ride - or not. A recent article published by Precision Farming Dealer stated that Raven Technologies had accumulated 8,000 hours of operational time, covering 69,000 acres. The same piece cited Blue-White Robotics as completing 10,000 hours of safe operation, and Monarch tractor with 1,300 operating hours. "We are excited to hear people talking more and more about the future of autonomy in agriculture - it's great for our category," said Andrew Bate, CEO of SwarmFarm Robotics.


Deep Learning and Its Use Cases

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Convolutional neural networks are one example of deep learning. Other examples of the use of deep learning include natural language processing and recommender systems. Deep learning applications are becoming more widespread, from improving worker safety around heavy machinery to speech translation and hearing assistance. CNNs are the brains behind home assistance devices. CNNs use tens or hundreds of layers of hidden layers to learn to recognize the different features of an image.


Artificial Intelligence In Agriculture – Another Place Where Medical Techniques Can Help

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As weird as it is to me to know that ranching is part of agriculture, I do find it interesting that the price points on medical technology means that new techniques can move into the industry. Artificial intelligence in medicine has been a big part of its growth. Now AI is also moving to help ranchers to better manage their herds. While much of the focus on AI in the field has been on vision and back-end analysis, the real world has a lot of another sense that matters – sound. In human medicine, of the first and easiest tools to use is the x-ray.


AI in Agriculture: Computer Vision, Robots, and Scales for Pigs

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Artificial intelligence is rapidly conquering agriculture and the food industry. To feed billions of people, you need a lot of lands. It is impossible to cultivate it manually these days. At the same time, plant diseases and insect invasions often lead to crop failures. With the modern scale of agriculture business, such invasions are difficult to identify and neutralize in the bud in time.


3 ways autonomous farming is driving a new era of agriculture

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Agricultural drones, self-driving tractors and seed-planting robots are among the innovations that could be key to future food supplies, as autonomous farming promises to produce more crops with less effort and less impact on the environment. Global farming shortages are affecting food chains globally. Last year the National Farmers' Union (NFU) in the UK wrote to Prime Minister Boris Johnson asking for the implementation of a'Covid Recovery Visa' to alleviate labour shortages across the supply chain. Seasonal worker visa scheme has been extended until end of 2024. The extension of the scheme was a key lobbying ask by the NFU There will be 30,000 visas available this year with potential to increase by 10,000 if necessary Find out more https://t.co/gsBU8Nca6W


Data and 3D Models in Agriculture

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Portfolio company AGERpoint has launched AGERpoint Capture, a mobile app for 3D data models about crops, trees, and forests. For those who have experience in applying machine learning and AI to agriculture or other complex use cases, one of the biggest problems in practice is high-quality data acquisition and data pipeline. Why is high-quality data acquisition important and difficult? Like anything in machine learning and AI, the quality of the raw data and labeled data (for supervised ML) is a key determinant of the quality of the results from the algorithms. In industries such as agriculture, chemicals, and industrials, it is generally the case that data are still "trapped" in the fields or factories.


Cereals Event - Technology: Dawn of a new reality? - cpm magazine %

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Has the fourth agricultural revolution arrived and does it have the capacity to solve the issues of farming and food production? Or is it too early to know just what impact robotics could have on agriculture? CPM found out more at Cereals. The fourth agricultural revolution can't simply be about automating the third one. A lot of the discussion centred around technology hails it as a revolution and something that could bring about transformational change, but speaking at the Cereals Event, Harry Henderson of AHDB asked if this would be the case.


Computer vision is primed for business value

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Over the past few years, computer vision applications have become ubiquitous. From phones that recognize the faces of their users, to cars that drive themselves, to satellites that track ship movements, the value of computer vision has never been clear. But hardware shortages and labor disruptions in the pandemic's wake are challenging companies' ability to make good on the promise of computer vision, even as the pandemic itself has accelerated the potential of its use cases. Following is a look at how companies across a range of industries are deploying computer vision to improve and optimize key business processes, from retail fulfillment to health-care diagnostics. Computer vision is a field of artificial intelligence that is focused on processing images and videos to extract meaningful information.