At Facebook's F8 developer conference in April, CEO Mark Zuckerberg announced his company's latest Messenger feature a personal shopping assistant and touted the app as being similar to shopping with a friend. There's just one key difference: The friend is a robot. More companies and organizations are turning to artificial intelligence (AI)-driven "chatbots", or conversational robots, as a new wave in customer service. The idea is to personalize each user's experience through advanced human-computer interactions. In the case of Facebook's e-commerce platform, the user will be able to interact with brands and companies that have opted to get involved with the app and order products and services without ever having to leave Messenger.

There have been an increasing number of reports about the rapidly developing world of AI, where computers can learn to use big data independently. Most recently, Google yesterday announced it would begin exploring whether automated machines are capable of creativity and producing original artwork and music. Many people's gut reaction to this is that nothing, not even the innately human ability to create, is safe from the machines. It makes me think of the "infinite monkey theorem": give a monkey a typewriter and an infinite amount of time and eventually, it will type something that makes sense. So, if we give computers (AI) huge amounts of big data and time, they will eventually develop creative ideas that can compete with the likes being dreamt up by skilled creatives and brilliant agencies all over the world?

Affectiva, a startup developing "emotion recognition technology" that can read people's moods from their facial expressions captured in digital videos, raised 14 million in a Series D round of funding led by Fenox Venture Capital. According to cofounder Rana el Kaliouby, the Waltham, Mass.-based company, wants its technology to become the de facto means of adding emotional intelligence and empathy to any interactive product, and the best way for organizations to attain unvarnished insights about customers, patients or constituents. She explained that Affectiva uses computer vision and deep learning technology to analyze facial expressions or non-verbal cues in visual content online, but not the content or conversations in a video. The company's technology ingests digital images--including video in chat applications, livestreamed or recorded videos, or even GIFs--through typically the simplest web cams. Its system first categorizes then maps the facial expressions to a number of emotional states, like happy, sad, nervous, interested or surprised.

Many people worry when they hear that organisations are using and sharing digital health data. What are they up to? Meanwhile, those organisations may worry that being more open could lead people to complain about the decisions they make. It's a vicious circle that can stop good things happening. A lack of transparency over the extent of data sharing by the UK National Health Service on 1.6 million patients with Google's artificial intelligence company DeepMind has been reported by New Scientist.

Instead of clicking around inside of Google Analytics to find the answer you want about your web traffic, wouldn't it be nice to just talk to Google to get what you want? That future is coming, Google demoed today, thanks to machine learning. Google's Babak Pahlavan, who heads measurement and analytics products for Google, showed the coming capability today during the Google Performance Summit. In one example, he asked by speaking, "How many users did we get from organic search in April?" and received the answer: In another, as you can see below, he spoke, "What were my best selling products for April?" and again, got a fast answer: Wow. Speak and get answers from Google Analytics.

"And then Hephaestus, Olympian god of fire, created a massive automaton out of bronze." Known as Talos, the giant creation was to protect the island of Crete. "On seeing strangers approach, he enveloped himself in fire and engulfed them." Or so the Greek myth goes. Our fascination with machines that can think is rooted in our collective histories.

Learn machine learning for free, because free is better than not-free. This website is inspired by the datasciencemasters/go and open-source-cs-degree github pages. This one is specifically for machine learning and features textbooks, textbook-length lecture notes, and similar materials found with a simple google search. This repository is meant as a general guide and resource for a free education. Note: Please report any broken links as an issue on the Github page.

On a spring afternoon in 2014, Brisha Borden was running late to pick up her god-sister from school when she spotted an unlocked kid's blue Huffy bicycle and a silver Razor scooter. Borden and a friend grabbed the bike and scooter and tried to ride them down the street in the Fort Lauderdale suburb of Coral Springs. Just as the 18-year-old girls were realizing they were too big for the tiny conveyances -- which belonged to a 6-year-old boy -- a woman came running after them saying, "That's my kid's stuff." Borden and her friend immediately dropped the bike and scooter and walked away. But it was too late -- a neighbor who witnessed the heist had already called the police. Borden and her friend were arrested and charged with burglary and petty theft for the items, which were valued at a total of 80. Compare their crime with a similar one: The previous summer, 41-year-old Vernon Prater was picked up for shoplifting 86.35 worth of tools from a nearby Home Depot store. Prater was the more seasoned criminal. He had already been convicted of armed robbery and attempted armed robbery, for which he served five years in prison, in addition to another armed robbery charge. Borden had a record, too, but it was for misdemeanors committed when she was a juvenile.

'The difference between men and boys will be the brains of their toys'. Developer conference season is well underway and the central theme that is emerging is a focus on making Digital Life services smarter and more intuitive. This has implications for both services to consumers created by the ecosystem itself but also the possibility to make it much easier for businesses to communicate and service their clients. This article was first published on Radio Free Mobile.

The supercomputer originally designed to win a game show is now learning how to fight crime. IBM announced on Tuesday that Watson, its artificial intelligence system, will be training to enhance cybersecurity. Watson already has some impressive accomplishments (for a supercomputer). Despite being a cookbook author,"Jeopardy!" winner, and health-care pioneer, it's still facing a steep learning curve when it comes to cybercrime, said IBM. "Even if the industry was able to fill the estimated 1.5 million open cyber security jobs by 2020, we'd still have a skills crisis in security," Marc van Zadelhoff, general manager at IBM Security, said in a press release. "The volume and velocity of data in security is one of our greatest challenges in dealing with cybercrime."