The Internet connected us all--but what good is that if we can't understand each other? Skype's artificial-intelligence-based Translator is our digital Tower of Babel. It lets us talk to anyone, anywhere, regardless of mother tongue. Made available on Windows in late 2015, Translator uses layers of machine-learning algorithms. When a user speaks, the A.I., drawing on millions of speech examples, analyzes the words and transcribes them into text.

I've been trying to think of a way to describe how big Machine Learning is, and I think I finally have a decent one: Because Statistics is the primary mechanism we've had for decades for learning about the world. Machine Learning is similar, except its method of doing it is far more powerful. Machine learning is the subfield of computer science that gives computers the ability to learn without being explicitly programmed. Most importantly, Machine Learning can…well, learn. With traditional Statistics you can potentially extract additional insights with more (and better) data, but the model for doing the analysis itself doesn't improve.

Contact centers across Latin America are looking to transform their customer service solutions by implementing new channels, such as chat, social media, email, video, or updated voice services, which are still hugely relevant in the region. Within that scope, speech recognition technology is often seen as a means to cut costs, improve customer satisfaction, and increase productivity in the call center. But are these solutions worth it? Speech recognition is performed by a machine or program that can identify words or phrases in spoken language and convert them into a machine-readable format. Beyond interactive voice response (IVR) systems, some of the more popular call center speech recognition applications are call routing, speech-to-text, voice dialing, and voice search.

Advertisers must plan their entry into artificial intelligence. This was the rallying cry from SY Lau, SEVP of Tencent and President of Online Media Group (OMG). He was speaking at the 2016 Ninth Tencent MIND Conference where he laid out a three-step plan for brands looking to break past the A.I barrier in their marketing operations. His first piece of advice was reminiscent of advertising's ultimate promise -- be a trusted brand to people. He observed that rich user data is the fuel for the continuous growth of all brands in this period of digital sophistication.

A few years ago Eric Schadt met a woman who had cancer. It was an aggressive form of colon cancer that had come on quickly and metastasized to her liver. She was a young war widow from Mississippi, the mother of two girls she was raising alone, and she had only the health care that her husband's death benefits afforded her--an overburdened oncologist at a military hospital, the lowest rung on the health care ladder. To walk into such a facility with stage 4 metastatic disease is to walk back in time to the world of the unmapped human genome, when "colon cancer" was understood to have a single cause instead of millions of causes resulting in unique variations, when treatment was the same bag of poison, whether you were in Ocean Springs, Mississippi, or Timbuktu. A time without big data, machine learning, or hope.

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.