Agricultural businesses usually have a massive number of trackable assets (plants, livestock, and machinery), often operate in wide geographic areas in which these assets are located, and are subject to operational factors often beyond their control, such as the amount of sunlight or rainfall they receive, or temperature fluctuations. As such, agriculture is ripe for the adoption of new technologies to help monitor and manage assets on a granular level, and everything from Internet of Things (IoT) sensors, robots, and drones are being used by farms around the globe. The U.S. Department of Agriculture's National Institute of Food and Agriculture notes that the farms of today are avid users of agriculture technologies such as robots, temperature and moisture sensors, aerial imaging, and GPS technology, which are more precise and efficient than humans alone, and allow for safer, more efficient, and more profitable operations. One example of how technology enables new farming techniques is the use of robotic harvesting on indoor farms, which today account for a tiny fraction of the 900 million acres of traditional farmland in the U.S. However, these indoor farms are well suited to the growth of vegetables such as tomatoes, lettuce, and other leafy greens, are highly sustainable, generally feature an average yield per acre more than 10 times higher than that of outdoor farms, and represent a continuation of the agricultural sector's trend toward incorporating precision agriculture techniques to improve yields and become more sustainable.
A Bill Gates-funded startup is seeking permission to test a new kind of drone detector at Sunday's Super Bowl game between the Los Angeles Rams and the New England Patriots in Atlanta, Georgia. Echodyne, a Seattle-based company, filed an application with the Federal Communications Commission (FCC) on Sunday to operate two experimental radars "in the immediate vicinity" of Mercedes-Benz Stadium to "alert security personnel, including Federal officers, of any unidentified drone activity during Super Bowl LIII". The drone tests would be conducted under the guidance and direction of the FBI. Atlanta police have said there will be a zero tolerance policy for drones near the Super Bowl stadium, with hundreds of local, state and federal law enforcement officers watching for illegal flights. Reports of rogue drones grounded flights at Newark Liberty International Airport in New Jersey last week, and forced the closure of Gatwick, Britain's second-busiest airport, for several days in December.
A hitchhiking robot was beheaded in Philadelphia. A security robot was punched to the ground in Silicon Valley. Another security bot, in San Francisco, was covered in a tarp and smeared with barbecue sauce. Why do people lash out at robots, particularly those built to resemble humans? It is a global phenomenon. In a mall in Osaka, Japan, three boys beat a humanoid robot with all their strength. In Moscow, a man attacked a teaching robot named Alantim with a baseball bat, kicking it to the ground, while the robot pleaded for help.
The model is a neural network utilising HTM neurons  which resemble biological pyramidal neurons. These neurons are more complex than conventional artificial neural network neurons, with multiple groups and types of input connections (dendrites) with different functions. There are dendrites that are stimulators, and those that are modulatory, and predict activations. There is an input and output layer (resembling two of the cortical pyramidal cell layers) with feedback and lateral input connections. Neurons are arranged into columns that cover a subset of the input space.
The first time Azim Shariff met Iyad Rahwan--the first real time, after communicating with him by phone and e-mail--was in a driverless car. It was November, 2012, and Rahwan, a thirty-four-year-old professor of computing and information science, was researching artificial intelligence at the Masdar Institute of Science and Technology, a university in Abu Dhabi. He was eager to explore how concepts within psychology--including social networks and collective reasoning--might inform machine learning, but there were few psychologists working in the U.A.E. Shariff, a thirty-one-year-old with wild hair and expressive eyebrows, was teaching psychology at New York University's campus in Abu Dhabi; he guesses that he was one of four research psychologists in the region at the time, an estimate that Rahwan told me "doesn't sound like an exaggeration." Rahwan cold-e-mailed Shariff and invited him to visit his research group.
This is a visualization of global internet attacks, seen during the 4th China Internet Security Conference in Beijing. Microsoft's Bing search engine is no longer accessible in China, the company reports. This is a visualization of global internet attacks, seen during the 4th China Internet Security Conference in Beijing. Microsoft's Bing search engine is no longer accessible in China, the company reports. The Microsoft search engine, Bing, appears to have been blocked in China since Wednesday.
Every day, researchers use the NI platform to push the boundaries of discovery. They are driven by the grand challenges humanity faces and the economic and technical trends that are revolutionizing wireless communications, transportation, and energy. The ideas, theories, and prototypes that start in academic research labs scale to ever more complex applications and eventually impact all our lives in the form of commercial technology. As varied as their research focus areas might be, academics face similar challenges regardless of domain. The goal of NI has always been to help scientists and engineers spend their time on the novel and the innovative by providing a platform with the accuracy, repeatability, and scalability they need to validate and prototype research.
The question may seem basic, but the answer is kind of complicated. In the broadest sense, AI refers to machines that can learn, reason, and act for themselves. They can make their own decisions when faced with new situations, in the same way that humans and animals can. As it currently stands, the vast majority of the AI advancements and applications you hear about refer to a category of algorithms known as machine learning. These algorithms use statistics to find patterns in massive amounts of data.
Eat too much and there won't be grass for anyone. In an essay written in 1833, the British economist William Forster Lloyd made a profound observation using the example of cattle grazing. Lloyd described a hypothetical scenario involving herders who share a pasture, and individually decide how many of their animals would graze there. If few herders exercised restraint, overgrazing would occur, reducing the pasture's future usefulness and eventually hurting everybody. The sinister beauty of this example is that the rational course of action is to behave selfishly.