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BT and Ticketmaster are more than just global leaders in their industries – they are example enterprise organisations already implementing artificial intelligence technology like Natural Language Process, Digital Assistants and Text Analytics into their strategies to improve customer support, experience and business growth. With the news of Google's DeepMind machine learning system and IBM's breakthrough artificial (AI) imitation of brain neurons, it's easy to assume that AI is still designated to hi-tech facilities with scientists in white lab coats and robots rolling past – and business leaders are not exempt from this belief that AI. Although common rebuffs about artificial intelligence claim'there aren't many use cases in the space', AI within enterprise businesses is already available and being implemented – perhaps just not on the same scale or format of what we see in media today (ie the all-robot staff at the Henn-na Hotel in Japan). "We've identified 191 discrete use cases where artificial intelligence is being used today, or will be used in the near future," notes Clint Wheelock, CEO, managing director of Tractica, a market intelligence firm focused on human interaction with technology. "These use cases span 27 different industries and range from well-known applications like algorithmic trading or static image recognition to more specialized emerging areas such as emotion recognition or processing of healthcare patient data."

This AI can tell if you're depressed by looking through your Instagram photos Sex doll makers "putting finishing touches" to artificial intelligence app so they can love you back

This article is a part of an evolving theme. Here, I explain the basics of Deep Learning and how Deep learning algorithms could apply to IoT and Smart city domains. Specifically, as I discuss below, I am interested in complementing Deep learning algorithms using IoT datasets. I elaborate these ideas in the Data Science for Internet of Things program which enables you to work towards being a Data Scientist for the Internet of Things (modelled on the course I teach at Oxford University and UPM – Madrid). Deep learning is often thought of as a set of algorithms that'mimics the brain'. A more accurate description would be an algorithm that'learns in layers'.

This AI can tell if you're depressed by looking through your Instagram photos Sex doll makers "putting finishing touches" to artificial intelligence app so they can love you back

Since it uses C 11 features, it requires a compiler with good C 11 support. Compilation is carried out using a Makefile, so you will need to have a working make. This will produce object files for all the classes as well as the main binary fasttext. If you do not plan on using the default system-wide compiler, update the two macros defined at the beginning of the Makefile (CC and INCLUDES). If you inted to build with Docker, a Docker file is available here fastText-Docker.

This AI can tell if you're depressed by looking through your Instagram photos

You know you shouldn't click on that article. There's no way the headline is going to live up to the promise. But the draw of finding out what happens next--crossing that curiosity gap--is just too much to resist. So you take the bait. And, sure enough, you're disappointed. Facebook wants to stop this from happening, and it's turning to artificial intelligence to help.

There was a time when doctors made house calls. That time is coming again, except now your doctor will be able to make 100 at once, while performing surgery at the same time. Dr. Leslie Saxon's USC Center for Body Computing and USC's Virtual Care Clinic leverage commercial tech innovations to advance medical care and delivery. "First thing we have to do is take your picture," says Dr. Leslie Saxon, Founder and Director of USC's Center for Body Computing, as she enthusiastically greets me at the Playa Vista campus location of the recently opened Virtual Care Clinic. I'm here to learn about the still nascent yet rapidly expanding field of digital medicine, and Dr. Saxon wants to show me what the face of the medical future that she envisions will look like--it turns out, just like an actual face, in fact.

There is no question about it: the real-time, on-demand economy is disrupting ecommerce. These days, you can order rides, buy groceries, rent a car, make a dinner reservation, and more with a single tap on your smartphone – and each service arrives in as little as minutes. Against this backdrop of speed, more consumers are expecting – and even demanding – a fast and frictionless user experience. The challenge for businesses is to meet these high expectations and stay competitive – all without increasing risk. All types of ecommerce companies struggle with payment fraud, but time-sensitive businesses that fulfill orders in real time face unique challenges.