China's plan for artificial intelligence (AI) development, issued by the State Council Thursday, is a major step for carrying out the innovation-driven development strategy and making the country a global leader in science and technology, said Wang Zhigang, vice minister of science and technology. Since the concept of AI was first proposed in 1956, it has been evolving rapidly with the development of the Internet, big data, super computers and neuroscience, ushering in "the new generation of AI," said Wang. "The new generation of AI" features deep learning, integration of multiple disciplines, human-machine collaboration and automatic operation, and is making various social and economic sectors smarter, said Wang. As a trigger for a new round of industrial reform, AI has been used by many countries to enhance international competitiveness and national security. However, China's move to propel AI development is not aimed at challenging the international status of certain countries, said Li Meng, another vice minister of science and technology. "The plan is based on our judgement and vision for the current and future development of Chinese science and technology, and it meets the demands of social and economic development," said Li.

A system by researchers at the Massachusetts Institute of Technology learns how to allocate data processing operations across thousands of servers most efficiently. Massachusetts Institute of Technology (MIT) researchers have created a system that automatically learns how to optimally allocate data processing workloads across thousands of servers as a means of boosting data center efficiency. The Decima scheduler leverages reinforcement learning to make scheduling decisions for specific workloads in specific server clusters. Decima tests multiple incoming workload allocation strategies across the servers to find the best trade-off between the use of computational resources and fast processing speeds. Decima's completion speed is about 20% to 30% faster than the best handwritten scheduling algorithms, the researchers say.

Artificial Intelligence (AI) is the cornerstone to driving food technology into the future and has the potential to grow revenue in the food industry by billions of dollars. It helps all sectors, from processing to manufacturing and safety to delivery. By studying previous dataset, machine learning can make predictions for the future. Learn how AI will revolutionize the food industry.

Fox News Flash top headlines for August 29 are here. Check out what's clicking on Foxnews.com A Pennsylvania court ruled Tuesday that making a "gunlike hand gesture" is a crime after a man made the hand motion during an argument with his neighbor -- an act which reportedly made several nearby residents nervous and prompted a call to police. Stephen Kirchner, 64, made the gesture toward his neighbor in Manor Township in June 2018, according to surveillance video. Kirchner, walking alongside a female neighbor, "stopped, made eye contact with [the male neighbor] and then made a hand gesture at him imitating the firing and recoiling of a gun," according to court documents.

At 3M, we apply science in collaborative ways to improve lives. With $33 billion in sales, our 93,000 employees connect with customers all around the world. We provide the freedom to explore and encourage curiosity and creativity. We gain new insight from diverse thinking, and take risks on new ideas. Here, you can apply your talent in bold ways that matter.

It arrived shortly after Bill Gates' comments to college kids in 2004. No coincidence, it showed up when the web took off, on the heels of terabytes of user-generated content from so-called web 2.0 companies like Google and Facebook. "Big data" entered the lexicon as volumes of unstructured (i.e., text and image) data-powered machine learning approaches to AI. AI itself was just then experiencing another of its notorious winters after the 2001 NASDAQ crash known as the "dot-com bubble." No one trusted the web after 2001 (almost no one), because it had failed to deliver on promises, tanked on Wall Street, and was still stuck in what we now snigger and sniff at, the "web 1.0" ideas that launched web sites for companies and tried to sell advertising--we are so different now!

You are free to share this article under the Attribution 4.0 International license. Machine learning analyzed 3.5 million books to find that adjectives ascribed to women tend to describe physical appearance, whereas words that refer to behavior go to men. "Beautiful" and "sexy" are two of the adjectives most frequently used to describe women. Commonly used descriptors for men include righteous, rational, and courageous. Researchers trawled through an enormous quantity of books in an effort to find out whether there is a difference between the types of words that describe men and women in literature.

The Defense Advanced Research Projects Agency awarded BAE Systems the second phase of an existing $12.8 million contract to develop digital tools to test and evaluate technologies for space command and control. The second phase focuses on the use of machine learning for space and situational awareness, the company announced Aug. 13. BAE Systems originally won the contract for the Hallmark Tools, Capabilities, and Evaluation Methodology (Hallmark-TCEM) program in November 2017. The program is to help operators improve their understanding of space events and their ability to take actions in response to situations that might affect U.S. satellites in space. The work is being performed by BAE Systems' Fast Labs research and development division.

Sarah.ai, from Cheetah, automatically analyzes photos taken on mobile phones to create stories. It does this by curating the photoset using state-of-the-art machine-learning computer vision algorithms to remove duplicates, to find the best photos, and to discard the bad ones. Users can edit their photobooks by adding/removing photos and write titles and captions on every page. They can also change the sequence and the colors of pages, delete and add pages (to a maximum of 96 pages). Find out more here: http://sarah-book.jp/pages/ai

Babies can cry because they're sick or in pain, but sometimes -- okay, a lot of the time -- they cry because they're hungry, cranky, or just feel like stretching their developing vocal cords. Now, researchers from Northern Illinois University have found a way to use artificial intelligence to decipher between the two types of vocalizations -- and not only could the AI save new parents from a lot of unnecessary worry, it could also save sick babies' lives. In a study published in IEEE/CAA Journal of Automatica Sinica, the researchers detail how they designed an algorithm based on automatic speech recognition technology that could distinguish between "normal" and "abnormal" cries, the latter being the kind often caused by a medical problem. They gathered their training data for the algorithm from 26 infants in a hospital's neonatal intensive care unit. Then they asked experienced nurses and caregivers to parse the probable reason for each cry -- "hungry," "diaper," "attention," "sleepy," or "discomfort" -- with the first four reasons considered "normal" and the fifth "abnormal."