The U.S. military has unveiled plans to use artificial intelligence (A.I.) on the battlefield; however, the military admits that they are struggling to keep up with commercial A.I. firms. The great challenge for A.I. researchers in 2016 will be to figure out how to enable machines to think for themselves; to make them autonomous. With this technology, the military hopes A.I. can control everything, from cyber soldiers to the targeting systems of the F-35.(1) According to Deputy Defense secretary Robert Work, "The Department of Defense is a follower. The commercial world has already made this leap.
Global competition to be the country with the most sophisticated AI will be the cause of the next world war, Musk predicts. His comment was responding to a story about Russian president Vladimir Putin predicting the country winning in artificial intelligence "will be the ruler of the world." Musk posted the warning with a photo of a poster that read "in the end, the machines will win." "I have exposure to the most cutting edge AI, and I think people should be really concerned by it," Musk said at the National Governors Association. "AI is a fundamental risk to the existence of human civilization in a way that car accidents, airplane crashes, faulty drugs or bad food were not -- they were harmful to a set of individuals within society, of course, but they were not harmful to society as a whole."
If you've been putting off your flu shot until the season really gets going, wait no longer. Influenza viruses quietly circulate year-round in the US, but every winter they go big, triggering a seasonal epidemic of sniffles, sweats, and sore throats. And this year it's come earlier than usual, just in time for a potential peak over the holidays. Normally, infections start to increase around the beginning of January, peak in February, and then come down by the end of March. But according to data released by the Centers for Disease Control and Prevention on Friday, the flu is already widespread in 12 states, including California and New York.
Much of the software now revolutionizing the financial services industry depends on algorithms that apply artificial intelligence (AI)--and increasingly, machine learning--to automate everything from simple, rote tasks to activities requiring sophisticated judgment. These algorithms and the analyses that undergird them have become progressively more sophisticated as the pool of potentially meaningful variables within the Big Data universe continues to proliferate. When properly implemented, algorithmic and AI systems increase processing speed, reduce mistakes due to human error and minimize labor costs, all while improving customer satisfaction rates. Creditscoring algorithms, for example, not only help financial institutions optimize default and prepayment rates, but also streamline the application process, allowing for leaner staffing and an enhanced customer experience. When effective, these algorithms enable lenders to tweak approval criteria quickly and continually, responding in real time to both market conditions and customer needs.
America's military budget, at $615 billion, dwarfs those of its closest competitors, China ($211 billion) and Russia ($69 billion). Even with that advantage, a new report finds that the U.S. is at risk of falling behind in the race to find and create AI for military applications. In 2014, U.S. Secretary of Defense Chuck Hagel announced that his department intended to lead the coming AI revolution with what he called the "Third Offset Strategy." For the uninitiated, the Second Offset Strategy was in response to the buildup of conventional forces along the Central European front by the Soviet Union and its satellite states ... which itself was a response to the First Offset Strategy that had the U.S. putting its own forces in the field. America didn't want to match the Soviets soldier for soldier, so new technology like long-range sensors and a new generation of guided munitions and submunitions was developed to give the U.S. an edge.
According to NASA, the discovery of Kepler-90i was the result of the work by researchers Christopher Shallue and Andrew Vanderburg, who used an artificial "neural network" to examine the 35,000 possible planetary signals returned by the unmanned Kepler spacecraft. Artificial intelligence has been used before to process the Kepler data, but by imitating the way neurons connect in the human brain, Shallue and Vandenberg were able to train the computer to seek out and identify weak transit signals that had previously been missed.
At the recent AWS re:Invent in Las Vegas, Andy Jassy, CEO of AWS, introduced 20 platforms on which Artificial Intelligence (AI) and Machine Learning (ML)-based services can be used. Everyone at the event – from Goldman Sachs to NASA to Expedia – showed the world how AWS can deploy infrastructure and heavy life data very quickly. But there's is a history why AWS is running on a $18 billion dollar run rate because they were the first to move to the cloud and they are constantly innovating by talking to customers. Simply put, it has thousands of engineers working on AI-based services. Dr Charles Elkan, Amazon Fellow, AI and Deep Learning, says, "We have worked on several technologies and with several businesses by understanding their problems.
Before scientists can effectively capture and deploy fusion energy, they must learn to predict major disruptions that can halt fusion reactions and damage the walls of doughnut-shaped fusion devices called tokamaks. Timely prediction of disruptions, the sudden loss of control of the hot, charged plasma that fuels the reactions, will be vital to triggering steps to avoid or mitigate such large-scale events. Today, researchers at the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL) and Princeton University are employing artificial intelligence to improve predictive capability. Researchers led by William Tang, a PPPL physicist and a lecturer with the rank of professor in astrophysical sciences at Princeton, are developing the code for predictions for ITER, the international experiment under construction in France to demonstrate the practicality of fusion energy. The new predictive software, called the Fusion Recurrent Neural Network (FRNN) code, is a form of "deep learning" -- a newer and more powerful version of modern machine learning software, an application of artificial intelligence.
On Thursday, NASA announced the discovery of an eighth exoplanet circling Kepler-90, a sun-like star with its own planetary system. The discovery tied Kepler-90 to our Solar System. RELATED: Could Mysterious Cigar-Shaped Comet Be Alien Spaceship? The discovery of Kepler-90i was possible using artificial intelligence technology from Google. "(It was) an approach to artificial intelligence in which computers'learn,'" NASA explained in a press release.