Can artificial intelligence (AI) and machine learning help save the world's bees? That's the hope of scientists who are scrambling to reverse the dramatic declines in bee populations. Bees are in trouble, but we're not quite sure why. It could be the overuse of insecticides; air pollution; warming temperatures; the varroa destructor mite; or even interference from electromagnetic radiation. Or it could be a combination of all these factors.
Science hasn't been giving us a tremendous amount of good news these days. We've screwed up the environment so badly, it's hard to even call it an environment anymore. And that's coming back to bite (or sting) us: Bee populations, which we rely on to pollinate our crops, are plummeting. But science is also coming to the rescue, by gluing QR codes to bumblebees' backs and tracking their movements with a robotic camera. Researchers have created a system that tracks individual bees as well as the dynamics of whole colonies exposed to imidacloprid, a neurotoxin that belongs to the infamous neonicotinoid group of pesticides.
Google may soon tell you which restaurants could give you food poisoning. The tech giant is working with Harvard University to develop an algorithm that analyzes Google searches to spot which restaurants might have food safety issues. Researchers say it's capable of flagging possible offenders in'near real time.' They created a machine-learning based algorithm to identify unsafe restaurants, training it to look for specific search terms and location data. The model is called FINDER, or Foodborne Illness Detector in Real Time.
Worried your go-to hole-in-the-wall might not have a stellar food safety record? Google's new artificially intelligent (AI) system can help lay your fears to rest -- or confirm the worst of them. A study led by researchers at the Mountain View company and Harvard's T.H. Chan School of Public Health describes a machine learning model -- FINDER (Foodborne IllNess DEtector in Real time) -- that leverages search and location data to identify "potentially unsafe" restaurants. Their paper ("Machine-learned epidemiology: real-time detection of foodborne illness at scale") was published today in the journal npj Digital Medicine. "Foodborne illnesses are common, costly, and land thousands of Americans in emergency rooms every year. This new technique, developed by Google, can help restaurants and local health departments find problems more quickly, before they become bigger public health problems," Ashish Jha, K.T. Li Professor of Global Health at Harvard Chan School and director of the Harvard Global Health Institute, said.
Why data could be the deciding factor in Africa's agricultural transformation. The world has a palm oil problem. It's a global, billion-dollar industry and its end result is irreversible environmental damage, ranging from deforestation and fires, to the loss of species such as tigers, pygmy elephants and orangutans. Palm oil is used in 50% of the products we buy (think bread, shampoo, soaps and even chocolate) due to the fact that it is the highest-yielding vegetable oil crop. Yet, in a country like Uganda, where 80% of the population is involved in agriculture as a way of life, many Ugandans farm oil palm on small plots, barely making a living.
In a quiet corner of rural Hampshire, a robot called Rachel is pootling around an overgrown field. With bright orange casing and a smartphone clipped to her back end, she looks like a cross between an expensive toy and the kind of rover used on space missions. Up close, she has four USB ports, a disc-like GPS receiver, and the nuts and bolts of a system called Lidar, which enables her to orient herself using laser beams. She cost around £2,000 to make. Every three seconds, Rachel takes a closeup photograph of the plants and soil around her, which will build into a forensic map of the field and the wider farm beyond. After 20 minutes or so of this, she is momentarily disturbed by two of the farm's dogs, unsure what to make of her.
PlantVillage, a research and development project, based at Penn State University, is beginning to bring artificial intelligence to these smaller farms. Scientists at PlantVillage, in collaboration with international organizations, local farm extension programs and engineers at Google, is working to tailor A.I. technology for farmers in Tanzania who have inexpensive smartphones. The initial focus is on cassava, a hearty crop that can survive droughts and barren soil. But plant disease and pests can reduce crop yields by 40 percent or more. PlantVillage and International Institute of Tropical Agriculture have developed a simple A.I. assistant, called Nuru ("light" in Swahili).
KANSAS CITY, Kan. – Companies around the globe are leveraging innovative technologies and artificial intelligence to make more informed decisions and better run their businesses. This week, Dairy Farmers of America, a national cooperative owned by dairy farm families across the U.S., announced an investment in SomaDetect, a dairy technology startup that will help farmers utilize artificial intelligence to more closely monitor the health of their herd and improve milk quality. "This is a potentially game-changing technology for our farmers and the industry as it allows dairy farmers to know the health of each cow and quality of milk in real time," said David Darr, president, farm services at DFA. "With access to better data, our farmers can make more knowledgeable decisions, which is a huge value." With SomaDetect's technology, farmers can easily evaluate components of interest in raw milk, including fat, protein, somatic cells, progesterone and trace antibiotics. While the technology continues to be refined for commercialization, the platform provides cost-effective, instant analysis, which enables farmers to make rapid and proactive decisions related to the overall health and management of their cows.
Imagine one hundred years ago if farmers had access to huge volumes of information about the soil profile of their land, the varieties of crops they were growing, and even the fluctuations of their local climate. This kind of information could have prevented an environmental crisis like the Dust Bowl of the 1920s in the American Midwest. But even ten years ago, the idea that farmers could have access to this kind of information was unrealistic. For the team behind the CGIAR Platform for Big Data in Agriculture, farming is the next frontier for using artificial intelligence (AI) to efficiently solve complex problems. The team--which includes biologists, agronomists, nutritionists, and policy analysts working with data scientists--is using Big Data tools to create AI systems that can predict the potential outcomes of future scenarios for farmers.