We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. During CES 2022 in January, John Deere debuted a fully autonomous tractor, powered by artificial intelligence, that is ready for large-scale production. According to a press release, the tractor has six pairs of stereo cameras that capture images and pass them through a deep neural network – that then classifies each pixel in approximately 100 milliseconds and determines if the machine continues to move or stops, depending on if an obstacle is detected. And in March, the Iowa-based company launched See & Spray Ultimate, a precision-targeted herbicide spray technology designed by John Deere's fully owned subsidiary Blue River Technology. Cameras and processors use computer vision and machine learning to detect weeds from crop plants.

The future of computer vision and machine learning can be seen trundling at about 1 mile per hour at a lettuce field in the Salinas Valley of California. In certain fields, a tractor is pulling a highly specialized robot called the "lettuce bot." The robot, made by Blue River Technology, contains enough smarts to differentiate the weeds from the budding lettuce plants and then kill those weeds with an injection of fertilizer. The result is a weed-free field without the use of expensive and harmful pesticides -- making Blue River's robot a threat to the $31-billion pesticide business and a friend of organic farmers. The startup, founded in 2011, on Monday said it has raised $3.1 million in a Series A round led by Khosla Ventures.

A subcategory of machine learning, deep learning uses multi-layered neural networks to automate historically difficult machine tasks--such as image recognition, natural language processing (NLP), and machine translation--at scale. TensorFlow, which emerged out of Google in 2015, has been the most popular open source deep learning framework for both research and business. But PyTorch, which emerged out of Facebook in 2016, has quickly caught up, thanks to community-driven improvements in ease of use and deployment for a widening range of use cases. PyTorch is seeing particularly strong adoption in the automotive industry--where it can be applied to pilot autonomous driving systems from the likes of Tesla and Lyft Level 5. The framework also is being used for content classification and recommendation in media companies and to help support robots in industrial applications.

Novel artificial intelligence (AI)-based farming robots are being trained using the PyTorch framework. These enhanced tools are specially designed to support farmers and produce high-quality food with fewer resources. Blue River Technology's See and amp; Spray machine is utilizing the advanced ML (machine learning) framework called PyTorch and computer vision to train robotic crop sprayers to map and find weeds as they pass across a field. This enhanced technology uses a superior-resolution camera to instruct robots to spray herbicide and destroy weeds without harming crops. Thus, using Python-powered ML tools will help farmers increase yield and maintain food quality.

PyTorch is helping to power a new generation of AI-enhanced farming machines. For farmers, weeds pose a very real threat to the health of crops at a time when global population growth is raising food demand while also making resources such as land and water increasingly scarce. Seeking solutions to helping farmers produce more food with fewer resources, California-based Blue River Technology, a subsidiary of John Deere, has turned to artificial intelligence and robotics technology. The company's See & Spray robotic farming machine combines machine learning (ML) and computer vision to identify weeds among crops in real time and to treat weeds while leaving crops unharmed -- giving farmers a more consistent, precise, and efficient means of weeding crops. As the See & Spray machine moves through a field, it collects images of crops and weeds through the use of a high-resolution camera array.

How did farming affect your day today? If you live in a city, you might feel disconnected from the farms and fields that produce your food. Agriculture is a core piece of our lives, but we often take it for granted. The world's population is expected to grow to nearly 10 billion by 2050, increasing the global food demand by 50%. As this demand for food grows, land, water, and other resources will come under even more pressure. The variability inherent in farming, like changing weather conditions, and threats like weeds and pests also have consequential effects on a farmer's ability to produce food.

New AI-powered farming machines trained on the PyTorch framework are being developed to help farmers produce more food with fewer resources. Blue River Technology is using the PyTorch machine-learning framework to train robotic crop sprayers to identify and map weeds as they move through a field. Using a high-resolution camera array, the system instructs the machines exactly where to spray herbicide, killing weeds while leaving precious crops unharmed. Artificial intelligence in the real world: What can it actually do? What are the limits of AI?

Artificial intelligence allows farmers to spray weeds while keeping the crop untouched. With crop prices in the dumpster and the world's population growing among a changing climate, artificial intelligence is becoming a life-saving measure for many farmers. From automated planting and harvesting to unmanned vehicles for cultivation and soil sampling, AI has begun to make it more cost efficient for producers to do their job. One of the largest roadblocks is herbicides. According to a 2016 University of Illinois study, the chemical prices are on the rise and pose a big threat to a farmer's bottom line.

A prototype of See & Spray, Blue River Technology's precision weed control robot. How did farming affect your day today? If you live in a city, you might feel disconnected from the farms and fields that produce your food. Agriculture is a core piece of our lives, but we often take it for granted. The world's population is expected to grow to nearly 10 billion by 2050, increasing the global food demand by 50%.

Agricultural fields are no less than a battlefield. Irrespective of terrain, geography and type, crops have to compete against scores of different weeds, species of hungry insects, nematodes and a broad array of diseases. Weeds, or invasive plants, aggressively compete for soil nutrients, light and water, posing a serious threat to agricultural production and biodiversity. Weeds directly and indirectly result in tremendous losses to the farm sector, which convert to billions each year worldwide. To combat these challenges, the farm sector is looking at Artificial Intelligence (AI) based solutions.