Scientists at Stanford University have found a new method in predicting poverty through the use of machine learning and satellite images. The technique could make it easier for organizations to know where across the world their aid is needed most. Also, this could help governments develop a better policy to prevent or fight poverty. Using three data sources namely daytime images, night light images, and survey data, scientists built an algorithm to predict how wealthy or poor an area is. The results of the study have been published in the journal Science. "The idea is that if we train our models right, they help us predict poverty in areas where we don't have the surveys, which will help out aid orgs that are working on this issue," explained Neal Jean, co-author of the study and a doctoral candidate at Stanford.

Dataiku, the maker of the all-in-one predictive analytics software platform Dataiku Data Science Studio (DSS), has today announced the release of Dataiku DSS 3.1, which now enables transformations in Apache Spark's Scala, adds additional external integrations, an improved UX interface, and includes 5 machine learning engines in its visual analysis section. Dataiku DSS 3.1 introduces new visual machine learning engines that allow users to create incredibly powerful predictive applications within a code-free interface. Users of all skill levels can now leverage HPE Vertica machine learning, H2O Sparkling Water, MLlib, Scikit-Learn, and XGBoost directly from within the visual analysis section of Dataiku DSS 3.1 to apply powerful machine learning algorithms to their data science projects without having to write a single line of code. The blending of visual code-free and free-form code-based transformations is one of the main strengths of Dataiku DSS for the prototyping and production of data applications. In addition to Python, R, SQL, Hive, Impala, and Pig, Dataiku DSS 3.1 now enables Apache Spark users to write transformations and interactive notebooks in Scala, bringing the power of Spark's native and most performant language to the data teams using Dataiku DSS.

Until we open our mouths to speak, it is possible for most of us to keep our thoughts to ourselves. But computers could soon be able to predict what you are thinking by looking for distinct patterns of activity in your brain that relate to sentences. Researchers have developed a computer program that is able to search for the brain activity related to certain words and then use this to predict a sentence being thought even it hasn't seen it before. Scientists have created a computer model that can predict unspoken sentences by looking at the neural activity in the brain. They say the system is able to get the predictions right around 70 per cent of the time.

The World Economic Forum recently published its 2016 list of the Top Ten Emerging Technologies that will likely have the greatest impact on the world in the years to come. The list is compiled by the WEF Meta-Council on Emerging Technologies, a panel of global experts led by Dr. Bernard Meyerson, IBM Fellow and Chief Innovation Officer. "Horizon scanning for emerging technologies is crucial to staying abreast of developments that can radically transform our world, enabling timely expert analysis in preparation for these disruptors," said Dr. Meyerson. "The global community needs to come together and agree on common principles if our society is to reap the benefits and hedge the risks of these technologies." The technologies on the list are not new.

The number of CT scans hospitals perform is on the rise, but professionals who actually read these scans can't seem to keep up with increasing demand -- often just looking at images as they come in. But artificial intelligence may be able to help. Chicago startup Realize.ai is launching a pilot study of its AI that identifies certain problems often spotted on CT scans this fall at Northwestern University Medical Center. Many times, these scans can reveal deadly conditions that need immediate attention, which means reading scans efficiently can be a life-or-death situation. "Getting to a scan too late or misreading a scan can cause serious clinical problems and we are trying to alleviate that," said co-founder Alex Risman.

According to a recent Deloitte report, advances in medical science are leading to an increased life expectancy. In 2014, the average life expectancy globally was 72.3 years and that is expected to grow to 73.3 years by 2019. In 2019, 11% of the total population are expected to be aged more than 65 years. Analysts expect that out of the global health spend of nearly 7 trillion, nearly half of the funds are diverted to making sure that this aging population continues to live longer. La Jolla, California,-based Human Longevity (Private:HLONG) is one player that is successfully integrating genomics and technology to help create the world's largest and most comprehensive database of whole genome, phenotype and clinical data that can be used to increase human longevity.

A visualization of a convolutional neural network, which has a color scheme similar to OpenAI's. Since announced in December 2015, Elon Musk and Sam Altman's OpenAI has recruited some of the foremost names in modern artificial intelligence research. Its poached top talent from giants in the field--research director Ilya Sutskever cut his teeth at Google Brain after studying with A.I. veterans Geoff Hinton and Andrew Ng. In their latest round of hires, the company is starting to diversify its staff. OpenAI's newest recruits come from Google Brain (where they have previously tapped), but also from startups and a trading firm.

On Friday, one of China's leading tech companies, Cheetah Mobile, announced the 57 million acquisition of New Republic--a move that signals its "journey of a transformation," according to CTO Charles Fan, highlighting its investment in AI and transition into a mobile content company. Founded in 2010, Cheetah Mobile began as a mobile tools provider. Over the last six years, it has become a major player in China's tech scene--and made a big impact, globally. Fan told TechRepublic that the company has over 650,000,000 monthly active users, internationally, in Q1. Fan said he sees the company as a "bridge between China and the world." What makes Cheetah Mobile different, he said, is that 80% of their mobile users are outside of China.

China's next generation missiles to adapt to war situation according to Artificial Intelligence

China's next generation missiles to adapt to war situation according to Artificial Intelligence