The government plans to promote the development of artificial intelligence technology in cooperation with other entities for use in medical, manufacturing and other sectors to mitigate the expected labor shortages that will result from an aging society, officials said Friday. The public-private initiative will involve 20 firms and research institutions such as the government-backed Riken research institute, Toyota Motor Corp. and NEC Corp. The science ministry, which oversees Riken, is planning to seek 10 billion ( 99.7 million) in the fiscal 2017 budget for costs related to the project, which is expected to run for 10 years. In the medical field, AI technology is expected to be used in diagnosing the symptoms of patients and advising doctors on optimal treatments by analyzing electronic medical records and huge amounts of data on similar cases. In the manufacturing sector, for example, AI technologies could be used to detect signs of impending machinery glitches and failures at factories more efficiently than humans to reduce output disruptions.

On the day after Intel announced its acquisition of San Diego machine learning startup Nervana Systems, investor Steve Jurvetson told me he was feeling a sense of satisfaction about a call he made three years ago, and how it has been playing out. In a 2013 panel discussion at Silicon Valley's Churchill Club, the DFJ partner said "machine learning" was his pick as the most important tech trend to watch for the next three to five years. "Just about anything you've heard [about] at Google that sounds interesting and new is based on machine learning," Jurvetson said at the time. "Everywhere, technology is starting to percolate into an otherwise prosaic, non-tech industry--apply big data, apply machine learning--and revolutionize it." Just over a year later, Jurvetson led the Series A round of venture funding for Nervana Systems.

Organizations often conduct door-to-door surveys to identify people living in poverty, but the downside is that these surveys are often time-consuming and expensive. Indeed, locating impoverished environments is still a challenging process for researchers, and the availability of accurate information is still lacking. Now, in a new study, scientists from Stanford University propose a more reliable method to map poverty in areas previously void of data -- by combining satellite images and making use of machine learning. Led by Stanford computer science doctoral student Neal Jean, researchers sought to determine whether the combination of high-satellite imagery and machine learning -- the science of designing algorithms that learn from data -- could predict estimates of areas where impoverished people lived. Specifically, they extracted information about poverty from these satellite images, and built upon previous machine learning algorithms to detect impoverished areas across five countries in Africa.

Each time analyst group Gartner unveils a new edition of its Hype Cycle chart, it inspires either schadenfreude or a sinking feeling. Your competitor has banked on a technology that is mired in the Trough of Disillusionment, and you were wise enough to cash out on the Slope of Enlightenment -- or maybe it is the other way around. The most curious detail about the 2016 edition of the Hype Cycle is not where any one technology shows up. It is how multiple incarnations of one underlying technology -- machine intelligence -- are spread out across several points on the infamous trough-and-plateau chart. Perceptual smart machines Gartner's label for the rise of machine intelligence is "the perceptual smart machine age," and it predicts that such machines will be "the most disruptive class of technologies over the next 10 years." The benefits of what Gartner calls "radical computational power, near-endless amounts of data, and unprecedented advances in deep neural networks" are on the rise, but none has yet ripened to the point where it is boringly useful.

"The elimination of poverty worldwide is the first of 17 UN Sustainable Development Goals for the year 2030. To track progress towards this goal, we require more frequent and more reliable data on the distribution of poverty than traditional data collection methods can provide." Those are the opening words on the website of Stanford University's Sustainability and Artificial Intelligence Lab, and its researchers have come up with an unusual -- and effective -- way to map and predict the distribution of poverty; their method combines high-resolution satellite imagery with machine learning. The researchers explain their methodology, which they call "cheap and scalable," in a video. The study, titled "Combining satellite imagery and machine learning to predict poverty," was published in the journal Science.

Identity management professionals have seen significant changes in the industry in recent years, and the pace of change is only accelerating. In the past, workforce Identity and Access Management (IAM) evolved to keep up with a growing need for access to workforce systems. Now Customer Identity and Access Management (CIAM) is critically important as businesses undergo digital transformation and engage with customers across multiple apps and channels. Even before the dust has settled with CIAM, the Internet of Things (IoT) is entering the scene with a need to manage and connect human and device identities. Just on the horizon is Artificial Intelligence (AI), which could be the next big area where IAM plays a significant role.

Is AI Stealing Your Job? New Chinese Cruise Missiles to Have'High Level of Artificial Intelligence'

Wang's department is said to have developed a large family of cruise missiles for the Chinese military. He added that China was a global leader in the artificial intelligence field. In March, China announces 7.6 percent defense budget rise, lowest in six years, reaching 146 billion.

After receiving widespread criticism for their Teen Talk Barbie that lamented, "Math class is tough," Mattel is stepping up their game by releasing Hello Barbie, full name Barbara Millicent Roberts, the first Barbie with artificial intelligence. Their goal is to create a toy that seems more lifelike because of its ability to carry on a conversation with kids. Whereas Teen Talk Barbie, and other previous talking Barbies, simply selected a phrase at random from a small database of possible phrases, Hello Barbie knows 8,000 lines of dialogue. Even more impressive, she selects certain phrases based on what kids are saying to her or asking her. How it works The secret is in Barbie's belt buckle which actually doubles as a button that can activate speech recognition software.

A new technique using artificial intelligence to read satellite images could aid efforts to eradicate global poverty by indicating where help is needed most, a team of U.S. researchers said on Thursday. The method would assist governments and charities trying to fight poverty but lacking precise and reliable information on where poor people are living and what they need, the researchers based at Stanford University in California said. Eradicating extreme poverty, measured as people living on less than 1.25 U.S. a day, by 2030 is among the sustainable development goals adopted by United Nations member states last year. A team of computer scientists and satellite experts created a self-updating world map to locate poverty, said Marshall Burke, assistant professor in Stanford's Department of Earth System Science. It uses a computer algorithm that recognises signs of poverty through a process called machine learning, a type of artificial intelligence, he said.