This farm in Arkansas may soon be the most scientifically advanced farm in the world. There's a farm in Arkansas growing soybeans, corn, and rice that is aiming to be the most scientifically advanced farm in the world. Soil samples are run through powerful machines to have their microbes genetically sequenced, drones are flying overhead taking hyperspectral images of the crops, and soon supercomputers will be crunching the massive volumes of data collected. Scientists at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab), working with the University of Arkansas and Glennoe Farms, hope this project, which brings together molecular biology, biogeochemistry, environmental sensing technologies, and machine learning, will revolutionize agriculture and create sustainable farming practices that benefit both the environment and farms. If successful, they envision being able to reduce the need for chemical fertilizers and enhance soil carbon uptake, thus improving the long-term viability of the land, while at the same time increasing crop yields.
Health Catalyst introduced Touchstone at HIMSS18 and, in so doing, described it as a performance discovery, prioritization, benchmarking and recommendation tool. "Touchstone is built from the ground up on the latest AI and software from Silicon Valley," said Dale Sanders, President of Technology, Health Catalyst. "Touchstone's recommendation engine, which borrows from Amazon and Netflix, gives you not just comparative benchmarks but recommendations to improve your performance against benchmarks." The technology includes risk models based on artificial intelligence and anomaly detection algorithms that hospitals can use to pinpoint underperforming areas. Touchstone performs risk-adjusted benchmarking by culling data in claims, cost-accounting systems, EHRs, external benchmarks and operations to risk-adjust benchmarking, to "guide users to the data and analyses of greatest relevance to their work and to the organization's goals," the company said.
Future generations will likely look back at the development of machine learning as a turning point. It certainly is convenient to dispense with keyboards and touchscreens in favor of using ordinary speech to tell your iPhone, Android or Alexa device what you want it to do. But machine learning's far more consequential contributions to society will be found in the fields of agriculture.
And through all those millennia, farmers have literally battled the elements. They have read the seasons and bred new crop types largely through trial and error. By the late 20th century we had increased food production with mechanization, fertilizers, herbicides, pesticides, irrigation and a lot more. Today, humankind is growing more food than ever. But, here's a crucial question: How long can we keep farming like this?
"IoT helps cities to predict accidents and crime as well as gives doctors real-time insight into information from pacemakers or biochips," said Ahmed Banafa of San Jose State University at a recent webinar. "IoT optimizes productivity across industries through on equipment and machinery, creates truly smart homes with connected appliances, and provides critical communication between self-driving cars."
Artificial intelligence (AI) today is the new frontier in the digital transformation journey enterprises have already embarked on. But adoption to solve real problems and drive business outcomes has been slow. Driving up adoption is critical to unlock the real promise of AI and is going to depend on how we approach AI. And that opportunity is in front of us thanks to industry-optimized augmented intelligence.
These Indian subsistence farmers know just what to do: Pull out their smartphones and take their picture. The farmers then upload the images with GPS locations to a cloud-based artificial intelligence (AI) app named Plantix. The app identifies the crop type in the image and spits out a diagnosis of a disease, pest or nutrient deficiency. Plantix also aids farmers by recommending targeted biological or chemical treatments for ailing plants, reducing the volume of agrochemicals in groundwater and waterways that can result from overuse or incorrect application of herbicides and pesticides.
Marketing typically has the largest discretionary budget in any organization because of the variety of activities we do, but now it also has the largest discretionary technology budget. That shift of dollars away from IT has been causing tensions for some time, but marketers now must be at the head of the table when purchasing everything from CRM, to business intelligence and analytics tools, to ecommerce platforms, and of course the website. Just like technology, customer experience budget and planning will move more towards marketing--as will customer satisfaction KPIs. The entire customer journey from pre-sale to customer advocacy is part of the overall brand experience. "Predictive analytics driven by AI and machine learning are going to change the way we do just about everything" One of the biggest obstacles marketers still run into is resistance to change.
At a time when many people are concerned about the potentially negative impact of robotics on individuals' lives and livelihoods, researchers at the University of Missouri are relying on robots for a project that's decidedly pro-human: fighting world hunger. Robots are helping scientists track crops and how they grow in drought situations. Knowledge gained from the 3D images and data the robots create and collect could help agriculturists develop corn that is more drought resistant. An executive guide to the technology and market drivers behind the $135 billion robotics market. To develop 3D images of corn plants in the field, the research team developed a combination approach of a mobile sensor tower and autonomous robot vehicles equipped with three levels of sensors and an additional robotic arm.