Firefighters have a truly noble job as their responsibilities often require putting one's own life on the line. A NASA researcher is using the Assistant for Understanding Data through Reasoning, Extraction, and sYnthesis (AUDREY), an artificial intelligence tool, to make a day's work a bit easier and safer for these heroes. The IoT-powered system will work with wearables that will track a firefighter's location via GPS and record heat and air quality in the specific points as they go around the site of the emergency. All this data is then tied-up with satellite imagery of the scene to build a game plan. AUDREY can lead a team of firefighters: artificial intelligence will determine which areas would likely collapse in an emergency and help any number of firefighters work together as efficiently as possible.

New estimates by the agriculture ministry show that the nation can raise its food self-sufficiency to 55 percent in 2050 from 39 percent now, sources said. The estimates are based on the assumption that Japan will maintain its current farm production while the population declines. The long-term estimates on food self-sufficiency are the first the ministry has ever made. According to the estimates, daily food demand will drop from 307 billion kilocalories in 2014 to 220 billion in 2050 due to the fall in population. To maintain the current output, the ministry believes it necessary to boost productivity, maintain the farming workforce and prevent farmland from being abandoned.

Call it artificial intelligence with a human touch. This week, two California universities separately announced new centers devoted to studying the ways in which AI can help humanity. USC's Viterbi School of Engineering and its School of Social Work said Wednesday that they had joined forces to launch the Center on Artificial Intelligence for Social Solutions. A day earlier, the University of California, Berkeley unveiled its newly minted Center for Human-Compatible Artificial Intelligence. Even as science and technology pundits (including Stephen Hawking, Bill Gates and Elon Musk) warn of the overthrow of humanity by advanced artificial intelligence - a prospect that appears nowhere on the horizon, experts say - scientists are increasingly looking ahead to the ways in which AI might actually aid human lives.

In 2014, Stanford University launched the One Hundred Year Study, a long-term look into the future of artificial intelligence set to publish a paper every five years. Just two years in, the team released its first report Sept. 1, Artificial Intelligence and Life in 2030. The document outlines the history of AI and where its being currently applied, like transportation for self-driving cars and healthcare with surgical robots. It's an important document not only for the research community, but for policymakers grappling to understand technology that existing laws could be unequipped to handle. The report says evil AI isn't what people need to anticipate--it's the unintended consequences of otherwise helpful things AI gives, like the erosion of privacy or displacement of labor.

A 100-year project conceived by Microsoft Research's Eric Horvitz to trace the impacts of artificial intelligence has issued its first report: a 28,000-word analysis looking at how AI technologies will affect urban life in 2030. Put away those "Terminator" nightmares of a robot uprising, at least for the next 15 years – but get ready for technological disruptions that will make life a lot easier for many of us while forcing some of us out of our current jobs. That assessment comes from Stanford University's One Hundred Year Study on Artificial Intelligence, or AI100, which is Horvitz's brainchild. Horvitz, a Stanford alumnus, is a former president of the Association for the Advancement of Artificial Intelligence and the managing director of Microsoft Research's Redmond lab. Horvitz and his wife, Mary, created the AI100 endowment with the aim of monitoring AI's development and effects over the coming century.

Dmitry Malioutov can't say much about what he built. As a research scientist at IBM, Malioutov spends part of his time building machine learning systems that solve difficult problems faced by IBM's corporate clients. One such program was meant for a large insurance corporation. It was a challenging assignment, requiring a sophisticated algorithm. When it came time to describe the results to his client, though, there was a wrinkle. "We couldn't explain the model to them because they didn't have the training in machine learning." In fact, it may not have helped even if they were machine learning experts. That's because the model was an artificial neural network, a program that takes in a given type of data--in this case, the insurance company's customer records--and finds patterns in them. These networks have been in practical use for over half a century, but lately they've seen a resurgence, powering breakthroughs in everything from speech recognition and language translation to Go-playing robots and self-driving cars.

The UC Berkeley-led center, directed by artificial intelligence researcher Stuart Russell, will seek to understand how human values can be built into AI's design, and create a mathematical framework that will help people build AI systems that are beneficial to humanity. Scientists might get around this communication problem by designing artificial intelligence that can watch humans and learn what their values are through their actions (though even that comes with some uncertainty, as humans don't always act in ways aligned with their values, Russell added). The USC center, co-directed by artificial intelligence researcher Milind Tambe and social work scientist Eric Rice, seems to operate in a mindset perpendicular to the one at UC Berkeley: It seeks to harness AI's existing capabilities to solve problems in messy, complicated human contexts. AI also includes a wide range of tools, including machine learning, computer vision, natural language processing and game theory (though some may consider game theory part of another discipline, Tambe said).

Clinton said she thought small classified markings were something else. When asked if she understood the "C" markings beside some paragraphs, Clinton told the FBI she assumed they indicated alphabetical ordering.

This article is featured in the new DZone Guide to Big Data Processing, Volume III. Get your free copy for more insightful articles, industry statistics, and more. In the past few decades, computer systems have achieved a whole lot. They have managed to organize and catalog the information produced by our civilization as a whole. They have relieved us from stringent cognitive tasks and increased our productivity significantly. One could say that where the industrial revolution automated labor, the digital revolution has automated cognitive labor. This statement isn't entirely correct however, if it was we would all be without a job.

A typical nightmare scenario goes something like this: Robots first replace autoworkers on the assembly line. Then they move into white-collar jobs, writing articles, drafting legal documents and reading X-rays. Finally, the robots, growing ever smarter through machine learning and Big Data, displace even the most highly trained workers. Another scenario: Robots become so intelligent that they not only can beat people in chess and on Jeopardy!, but they also think faster, better and more analytically than any of us. Milind Tambe thinks these dystopian visions, so popular these days, miss the mark.