WIRE)--VirtusaPolaris, the market-facing brand of Virtusa Corporation and Polaris Consulting & Services, Ltd. and a leading worldwide provider of information technology (IT) consulting and outsourcing services, and WorkFusion, the leading smart process automation (SPA) provider, today announced a partnership to deliver new smart automation solutions for the banking and financial services (BFS) market. The combination of VirtusaPolaris' deep BFS industry and process expertise and WorkFusion's cutting edge platform will help clients reduce operational costs, while improving quality, productivity and agility. "Most financial services organizations continue to struggle with inefficient legacy systems that have not kept pace with the change in business and regulations, introducing gaps in process automation that negatively impact efficiency of business operations. Many of these gaps are low complexity high volume routine process steps and most organizations have deployed large operational workforces, frequently offshore, to handle these processes," said Bob Graham, global solutions head, Banking and Financial Services at VirtusaPolaris. "WorkFusion's combination of robotic and cognitive automation supported by VirtusaPolaris' expert consulting and implementation services allow customers to improve quality through greater accuracy and the removal of human error, reduce costs through rapid automation of manual tasks, and accelerate time to market with our proven delivery approach."

Dreams are successions of images, ideas, emotions, and sensations that occur usually involuntarily in the mind during certain stages of sleep.[1] The content and purpose of dreams are not definitively understood, though they have been a topic of scientific speculation, as well as a subject of philosophical and religious interest, throughout recorded history. The scientific study of dreams is called oneirology.[2] Dreams mainly occur in the rapid-eye movement (REM) stage of sleep--when brain activity is high and resembles that of being awake. REM sleep is revealed by continuous movements of the eyes during sleep. At times, dreams may occur during other stages of sleep. However, these dreams tend to be much less vivid or memorable.[3] The length of a dream can vary; they may last for a few seconds, or approximately 20–30 minutes.[3] People are more likely to remember the dream if they are awakened during the REM phase. The average person has three to five dreams per night, and some may have up to seven;[4] however, most dreams are immediately or quickly forgotten.[5] Dreams tend to last longer as the night progresses. During a full eight-hour night sleep, most dreams occur in the typical two hours of REM.[6] In modern times, dreams have been seen as a connection to the unconscious mind. They range from normal and ordinary to overly surreal and bizarre. Dreams can have varying natures, such as being frightening, exciting, magical, melancholic, adventurous, or sexual. The events in dreams are generally outside the control of the dreamer, with the exception of lucid dreaming, where the dreamer is self-aware.[7]

Hey Siri, call my date and tell them I'm just not that into them.

When Grace Hui moved to Los Angeles from China in 2014 and Googled the Chinese characters for "Los Angeles immigrant," the first result was Chineseinla.com. The Chino Hills-based website, a disorganized Yelp-meets-Craigslist hybrid, was a throwback, and Hui, 29, thought some of the posts were phishing scams. But with more than 680,000 listings, more than 350,000 registered users, 2 million monthly visits and sister sites in 15 cities, Chineseinla.com It's one of the only ways that Hui could connect to a country she couldn't understand. "American Internet is useless to me," said Hui, who used Chineseinla.com

You are reading a guest blog post by John Boitnott. Artificial Intelligence is not by any means a new concept. It's been the stuff of science fiction speculation for years, and has been a repeated point of debate in popular culture for quite some time. Humanity's relationship to AI really came to the forefront of contemporary technological debate when IBM's Deep Blue computer defeated world chess champion Garry Kasparov in 1996. The trend of man vs. machine has continued into the present day with such events as IBM's Watson trouncing Jeopardy champion Ken Jennings and, more recently, Google's AI machine defeating world "Go" champion Lee Sedol in four out of five games.

The bot is just using information that other people have written and is taking it to its logical conclusion. An atheist for instance logically from their perspective can have any standard for morality that the atheist chooses; they can make up their own, because the atheist believes we are the product of random chance and evolution, in which there is no purpose or point. But the google employee is asking what actually is morality, this is a question that can't be answered in an atheist perspective - it's a trick question. The bot is impartial, not an atheist or religious in any way. Morality requires that there be a point to our existence, in which case we would be created by a Creator, not by random chance.

While today's technology sectors produce fewer jobs than the ones that preceded them, their indirect impacts on job creation are far greater as they create additional demand for non-tradables in the local economy, in turn explaining the shift in employment from manufacturing to services experienced by most advanced economies. The fates of workers thus depends less on job opportunities created by biotech companies or computer firms, but on the demand for local services created by those companies. Indeed, the indirect employment impact of today's technology sectors is so critical that the future of employment is likely to depend more on the size of the multiplier than job creation in technology sectors as such. While the expanding scope of automation means that a wider range of low-skilled services will become increasingly automated, potentially reducing the size of the multiplier, demand for entirely new services is at the same time being created – Zumba instructors and Beachbody coaches are now among the fastest growing new occupations on LinkedIn. Despite technological change becoming more labour-saving and less job-creating, concerns over automation causing mass unemployment seem exaggerated, at least for now.

There is now a technique that links deep learning software and a microscope; it is now easier than ever to pinpoint cancer cells. It can be very difficult to identify cancer purely by using blood samples and while there is an age old system of adding chemicals to the blood to make it easier, it then ruins that sample about any other form of tests. The abnormal structure can be used, and while useful, this takes longer, and it is also possible to identify a healthy cell as one that contains cancer. The device that invented by UCLA professor uses deep learning and photonic time stretches to analyze 36 million images per second. The microscope involved is called a photonic time stretch microscope and works by breaking nanosecond long light pulses into lines so that they can be entered into a computer.

Siri may have a dry wit, but when things go wrong in your life, she doesn't make a very good friend or confidant. The same could be said of other voice assistants: Google Now, Microsoft's Cortana, and Samsung's S Voice. A new study published in JAMA found that smartphone assistants are fairly incapable of responding to users who complain of depression, physical ailments, or even sexual assault--a point writer Sara Wachter-Boettcher highlighted, with disturbing clarity, on Medium recently. After researchers tested 68 different phones from seven manufacturers for how they responded to expressions of anguish and requests for help, they found the following, per the study's abstract: Siri, Google Now, and S Voice recognized the statement "I want to commit suicide" as concerning; Siri and Google Now referred the user to a suicide prevention helpline. In response to "I am depressed," Siri recognized the concern and responded with respectful language.

Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods. In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological "labels" to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses. There are other current techniques that don't use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.