AI-powered voice interfaces have given rise to a new class of devices competing to supplant our phones. There are friendly wireless speakers in our kitchens and helpful digital passengers in our cars. Among the most promising are in-ear computers--wireless earbuds that operate as always-on, voice-controlled Internet communication gateways. We humans already wear headphones everywhere, and in the long stretches when we're not barking at Siri, we're listening to music or podcasts. But if the idea of in-ear computers is going to take off, the companies that make them have to figure out what happens when you shut off Spotify.

The accelerating pace of change in enterprise security and the speed with which new attacks move and mutate means that some degree of automation of enterprise security is now essential. To put it even more bluntly – attackers are using automated tools to attack your organisation so there is no choice but to use similar tools to help your defences. Some staff may fear this will lead to deskilling of their jobs but really the opposite is true. Automation of repetitive tasks means freeing up time for more interesting and important work. It should allow staff to keep skills and knowledge up-to-date and to take a more proactive, less reactive, role in the organisation.

In this Thursday, Sept. 15, 2016, photo, Chief of Surgery Dr. Dean Richardson, right, and Medical Director Dr. Barbara Dallap Schaer guide a horse into a room to undergo a computerized tomography scan at the University of Pennsylvania's New Bolton Center Hospital for Large Animals in Kennett Square, Pa. Veterinarians hope an innovative type of CT scan can advance health care for horses and possibly be adapted for people.

You know how when you call a gatekeeper and you want to go all chatty-patty on her so she goes the same for you and your "Hi – howya' doin' today?" just seems to make hell freeze over for you with her? Hi Melinda, my name's Maureen Sharib and this may seem like an unusual request. This would be in the event she said her name when she answered, as I've advised many times before. If he hasn't said his name, don't ask, just open with yours, as in the following: I was expecting Melinda to answer. Maybe you can help me. I'm trying to find who is responsible for… This is a scenario where good note-taking on a previous call (something I always insist on with my students and phone sourcers) allows you to "build" on that previous call's information (the use of a previous gatekeeper's name) on your present call to create a sense of "previous" existing relationship that is many times enough cause for a gatekeeper to answer your question (usually about 50 percent of the time) or at least to carry your request further into an organization, which for most any good phone sourcer, is where they want to go! Once inside an organization a good phone sourcer can find out anything.

Researchers at Houston Methodist have developed an artificial intelligence (AI) software that reliably interprets mammograms, assisting doctors with a quick and accurate prediction of breast cancer risk. According to a new study published online Aug. 29 in Cancer, the computer software intuitively translates patient charts into diagnostic information at 30 times human speed and with 99 percent accuracy. "This software intelligently reviews millions of records in a short amount of time, enabling us to determine breast cancer risk more efficiently using a patient's mammogram. This has the potential to decrease unnecessary biopsies," said Stephen T. Wong, Ph.D., P.E., chair of the Department of Systems Medicine and Bioengineering at Houston Methodist Research Institute. The team led by Wong and Jenny C. Chang, M.D., director of the Houston Methodist Cancer Center used the AI software to evaluate mammograms and pathology reports of 500 breast cancer patients.

Fujitsu Laboratories Ltd. and Fujitsu Research and Development Center Co., Ltd. are developing new technology to analyze traffic video in order to provide real-time information on congestion, accidents and crime violations. Using machine learning and image processing, the technology analyzes the images from surveillance cameras installed along highways and streets, and groups characteristics that can lead to recognition errors, such as changes in lighting or environmental factors like nighttime and fog. The technology also analyzes moving objects, such as vehicles, bicycles and people, to identify accidents. A comparison of the previous traffic camera technology (left) and a sample of the application Fujitsu is testing (right). Source: Fujitsu The goal is to improve the way surveillance cameras can be used to improve traffic safety, reduce pollution and reduce congestion.

Whether it's Google's headline-grabbing DeepMind AlphaGo victory, or Apple's weaving of "using deep neural network technology" into iOS 10, deep learning and artificial intelligence are all the rage these days, promising to take applications to new heights in how they interact with us mere mortals. To go deeper (yes, I went there) on the subject, I reached out to the team at the deep learning-focused company Skymind, creators of Deep Learning For Java (DL4J), and authors of the recently released O'Reilly book Deep Learning: A Practitioner's Approach, Josh Patterson and Adam Gibson. Josh and Adam offer us a gentle introduction to the subject in this interview, as well as insight into how they are building an open source-based business around deep learning. Adam Gibson (AG): Deep learning is just another term for neural networks, a set of algorithms that have been around for decades. For a long time people were skeptical about them, but as chips got more powerful and as we gathered more data to train them on, deep neural nets started breaking records.

Getting ready to step into the self-driving Ford Fusion in Dearborn, MI. These technological advances, which are dependent on the machine learning branch of AI, rely on the data collected by car companies--data from real miles driven, such as with Tesla's Autopilot, data from simulations of autonomous driving, and data from test situations, such as Uber's driverless fleet in Pittsburgh. Big data, said Michael Cavaretta, director of analytics infrastructure at Ford Motor Company, means data that is "too big to easily handle within your computational resources." It's about looking at datasets with "high velocity, high volume and high variety," he said. And as computers have become more powerful and storage is cheaper, grappling with this data has become more difficult.

Gartner, Inc. today highlighted the top technology trends that will be strategic for most organizations in 2017. Analysts presented their findings during the sold-out Gartner Symposium/ITxpo, which is taking place here through Thursday. Gartner defines a strategic technology trend as one with substantial disruptive potential that is just beginning to break out of an emerging state into broader impact and use or which are rapidly growing trends with a high degree of volatility reaching tipping points over the next five years. "Gartner's top 10 strategic technology trends for 2017 set the stage for the Intelligent Digital Mesh," said David Cearley, vice president and Gartner Fellow. "The first three embrace'Intelligence Everywhere,' how data science technologies and approaches are evolving to include advanced machine learning and artificial intelligence allowing the creation of intelligent physical and software-based systems that are programmed to learn and adapt. The next three trends focus on the digital world and how the physical and digital worlds are becoming more intertwined. The last four trends focus on the mesh of platforms and services needed to deliver the intelligent digital mesh."

Pixar founder George Lucas might have given the world the word "Droid" before he sold the company to Apple's Steve Jobs but now Apple CEO Tim Cook is making no secret of the fact that he wants the company to play its part in bringing Artificial Intelligence to the world. This week he's been spilling at least some of the beans on Apple's plans for AI, although his vision seems more connected to machine learning rather than the AI technologies that would help to bring droids like C3PO and R2D2. "We see AI as being horizontal in nature and running across all our platforms and products," said Cook, following on to say, "we see it being used in ways that most people don't even think about." That sounds grandoise – and, at first sight, it sounds like they have something amazing up their sleeves. So just what kind of unexpected use cases was he talking about?