AI-powered chatbots are the next big trend in emerging technology, with Venture Beat reporting there are currently 11,000 messenger chatbots live on Facebook. Several industries, from eCommerce to athletics to medicine, are looking for ways to implement artificial intelligence into their operations. While these chatbots are relatively new, they've already attracted a lot of attention in finance. Historically, banking has been among the most resistant industries to embrace digital transformation, but technology-driven customers want to interact with banks on their own terms. Calling in or waiting in teller lines is no longer a reasonable customer expectation, any online and mobile services have taken banks in the right direction.

A new study suggests the answer is ... kind of. Researchers from the University of Oregon in Eugene have replicated some of the same brain patterns exhibited by human meditators in the brains of mice -- no tiny meditation cushions or squeaky "oms" required. Still, experiments show that the "meditating mice" were more relaxed and less stressed than those with no rodent meditation training. The authors say the work, published Monday in PNAS, provides a proof of concept that will allow them to learn more about how meditation affects the brain. Previous research has shown that just one month of mindful meditation can have a significant impact on humans both physically and psychologically.

Step counting apps might be not only a waste of time but a dangerous one, according to one expert. The fitness apps might be doing more harm than good because they don't work but force people to focus on ambitious goals that they will never reach, according to a leading computer scientist. "Very few" of the roughly 165,000 healthcare apps are actually based on any scientific evidence, said Dr Greg Hager, from Johns Hopkins University in the US. But they have been downloaded more than a billion times by people looking to improve their health. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

Scientists know that the first signs of autism can appear in early childhood, but reliably predicting that at very young ages is difficult. A behavior questionnaire is a crapshoot at 12 months. However, artificial intelligence might just be the key to making an accurate call. University of North Carolina researchers have developed a deep learning algorithm that can predict autism in babies with a relatively high 81 percent accuracy and 88 percent sensitivity. The team trained the algorithm to recognize early hints of autism by feeding it brain scans and asking it to watch for three common factors: the brain's surface area, its volume and the child's gender (as boys are more likely to have autism).

"I was determined to do it precisely because I was told it was impossible." So says Yasuo Kuniyoshi, professor at the University of Tokyo's Graduate School of Information Science and Technology, in a quiet tone. However, the sharp glint in his eye betrays his grand ambition of developing a truly clever artificial intelligence to benefit humankind. Existing AI (Top) Self-driving cars most likely will one day be able to take people to their destination by recognizing simple instructions like, "Take me to the University of Tokyo." Because existing AI does not think the same way humans do, it cannot adapt to situations that are not in its playbook. Some current forms of artificial intelligence (AI), such as speech recognition and automated driving, are just as competent as humans--if not better--at carrying out their given tasks (figure 1).

The rise of chatbot technologies has not been the stunning success many people anticipated. The technology is now ubiquitous, but chatbots are more famous for their failures than successes. For instance, Microsoft's Tay faced a wave of media scorn after the internet trained it to become a misogynistic racist in the span of a day. Less snarky criticisms have been leveled at Google's Allo. Experts have called the tech giant out for failing to equip Allo with end-to-end encryption, thereby exposing chat conversations to third parties.

An algorithm that's able to accurately predict autism diagnoses in young kids could enable potental interventions to be made earlier. A team of researchers at the University of North Carolina at Chapel Hill have developed a deep learning algorithm that can accurately predict whether a child at high risk of autism is likely to be diagnosed with the disorder in early childhood. The algorithm was able to predict with 81 percent accuracy whether a diagnosis of autism would be made for a child with an autistic sibling,. The deep learning tool was developed in conjunction with computer scientists from the College of Charleston as part of the Infant Brain Imaging Study, which focuses on early brain development among children with autism. By scanning their brains at 6 months old, a year old, and 2 years old, they were able to make some interesting discoveries.

Credit ratings have long been the key measure of how likely a U.S. consumer is to repay any loan, from mortgages to credit cards. But the factors that FICO and other companies that create credit scores rely on--things like credit history and credit card balances--often depend on having credit already. In recent years, a crop of startup companies have launched on the premise that borrowers without such histories might still be quite likely to repay, and that their likelihood of doing so could be determined by analyzing large amounts of data, especially data that has traditionally not been part of the credit evaluation. These companies use algorithms and machine learning to find meaningful patterns in the data, alternative signs that a borrower is a good or bad credit risk. These companies are still young, but to date, there isn't clear evidence that these approaches have greatly expanded the credit available, and lenders using them often charge high interest rates, according to a report by the National Consumer Law Center, a consumer advocacy group.

Bono and The Edge are excited by Nuritas' potential for impact and profitability. Try to imagine walking into your local grocery store ten years from now. You head towards the back, as you've done countless times before, to snatch a handful of your favorite cereal bars. Only this time, the packaging looks a bit different. You notice that there are two new versions, each with a label below the brand name.

As Katy Franco waited for her morning coffee, passersby pulled out their phones and snapped photos and video of her barista. A man in his 20s did a double take, recorded the scene on his iPhone and posted it to Instagram. Another woman drifted toward the barista and asked no one in particular: "What's going on here?" Franco's barista was a robot. It's part of an automated coffee shop called Cafe X -- the latest example of the San Francisco's dual infatuations: artisanal coffee and automated technology.