We're just a couple of months into 2017, and you may already be sick of hearing about the latest overhyped marketing trend: artificial intelligence (AI). Before you sigh and think, "Really, another one?" AI can mean a lot of things, from self-driving cars to Siri and Spotify. But basically, AI is really about taking basic tasks that humans do and automating them. And since there are a lot of hands-on processes in B2B marketing, there's a big opportunity for AI to make an impact.

They give new tools to the powerful and their challengers. In the Syrian city of Aleppo, the struggle to frame the conflict for the international community ran parallel to the battle for control over the land itself. While drone footage from Russia Today showed videos of rebel-held and heavily-bombed eastern Aleppo, Syria's Ministry of Tourism published footage of the city's intact western half, complete with the soundtrack from HBO's hit show Game of Thrones. Life with the regime was normal. Life with the rebels was hell.

To predict the future, one must look at the past, says the old adage. To determine what to expect in 2017, we thought it was best to draw lessons from 2016 despite our industry's yearning for dramatic change. Sure, the tech giants are working on flashy AI projects, with projects on robotics, drones, and computers that surpass humans in certain tasks. However, what's more interesting -- and what we've been witnessing through our current work -- is that AI is nibbling away at IT, particularly with deep and supervised learning, as enterprises find more ways to apply them for business gain. Expect to see insights everywhere and "smart" everything (meaning things with machine learning components built in): smart data, smart objects, smart modules, smart processes, and smart applications.

Hitachi became an instant sensation when it displayed its first robot in an IT Fair in 1970. Ever since, this Japanese technology company has made great strides in Artificial Intelligence (AI), and more recently, in Machine Learning enabled AI research, as demonstrated through their successive applications in robotics. After 45 years of tireless AI research and product development, Hitachi again made the headlines across global media when it announced the arrival of a Robot Boss on the company's shop floor. This Artificial Intelligence story is changing the way enterprises understand AI in the modern data-evolved world. The Robot Boss is a powerful machine supervisor can allocate work to employees in the most efficient manner based on the employee's past performance.

Artificial intelligence (AI) is the stuff of the real world today. Your Google computer search, your Netflix movie choices, and your Amazon-supplied selection of buying options "made just for you" all employ AI based techniques. The application of AI pioneered by Cylance has transformed endpoint protection before our very eyes. Organizations are completely changing the way they operate, using greater security with fewer resources. Their staff was previously stretched thin, running around fixing problems, and trying to catch up with never-ceasing tickets.

We have received a request for a Business Justification letter from some of our attendees. Below is a letter template you can use to customize and present it along with this complete information pack to help convince why you should be at the MITCNC The Future of AI Conference. Just keep your validated parking ticket and use it to leave the parking garage. Press pass is provided only to full-time reporters / freelancers who work for established print, online, or broadcast news organizations. Industry analysts must be employed full time by a recognized research firm and consistently produce research reports.

In other words, AI is algorithm-based technology that mimics human cognition, meaning the technology is programmed to follow certain patterns or equations for a given input to produce an outcome. For example, you recently watched Breaking Bad on Netflix. The next time you sit down to watch Netflix you see a new queue of suggested shows to watch, "Because you watched Breaking Bad," that include Dexter, Making a Murderer, and Sons of Anarchy; not solely because they are similarly classified as crime series, but because millions of other users that have watched Breaking Bad have also watched the suggested titles. There are several differences between artificial intelligence and human cognition, the most obvious being that AI is, well, artificial. Beyond that, human cognition and AI differ in that AI has the unique advantage of being able to sort through a "database" of information, arguably instantaneously, to produce and output.

A three-headed alien is wandering around Central Park right now. If you believe that, you might be susceptible to a fake news story. Artificial Intelligence technology, however, could be a vital weapon in the war on fake news, according to cybersecurity companies. Popular during the last election but still prevalent on Facebook and other social media channels, fake news stories make wild claims, tend to exist only on a handful of minor news sites, and can be difficult to verify. Yet, artificial intelligence could help us all weed out the good from the bad.

Last March I wrote about an early experiment using Google's Cloud Vision API to perform deep learning-powered geocoding of 20 million global news images. In that experiment I compiled 20 million photographs that had appeared in online news articles worldwide as monitored by the open data GDELT Project over a period of two months and ran them through Google's Vision API service, which applies state-of-the-art deep learning algorithms to visually analyze an image much as a human would. The API returns a wealth of data about each image, including a list of objects and activities it depicts, recognizable logos, OCR text recognition in almost 80 languages, levels of violence, an estimate of how "happy" or "sad" people in the photograph appear to be and even the precise location on earth the image appears to depict. It is that last category that is so fascinating when it comes to trying to understand the visual geography of the world's news media. One year later the GDELT Project has now processed more than a quarter billion news photographs from news outlets in almost every corner of the world through Google's API – what can we learn through this deep learning powered "visual geocoding" of the world's news imagery?