On August 31, 1993, noted science fiction author William Ford Gibson stated in an NPR interview "The future is already here, it is just not evenly distributed." In 2017, the cloud, machine learning, Big Data, and scalable distributed computing should all compel us to reflect about his declaration more than ever. As these capabilities mature, an oligarchy of technology companies has emerged (like Alphabet, Amazon, Apple, Facebook, and Microsoft) that is skewing the digitization of both our personal and work life. Thomas Friedman in his book, Thank You for Being late: An Optimist's Guide to Thriving in the Age of Accelerations, points out that the rate of change is not only accelerating within technology, but also in our markets and the environment. In this world, one can easily be overwhelmed by the rate of change, and many of us run the risk of being digitally disrupted.

Critics have aimed barbs at technology for solving short-term, high-payout problems. To be fair, the critiques aren't always distorted. While it's true urban dwellers can hail a ride and order take out more easily, we're still far from ending global hunger, realizing gender equality, or creating affordable, clean energy. Changes are underway, though, as these weighty concerns are finding much-needed aid from a set of smart, passionate technology leaders. Fortunately, efforts are underway to arm global leaders with smart technology.

The overarching term "artificial intelligence (AI)" is a hub with many spokes. One of the most exciting of these from a business perspective is machine learning. As I explained in my first blog in the series, at its most basic, machine learning involves'teaching' a computer to learn and change when given a vast amount of data. The computer is not necessarily explicitly programmed for these changes, but instead learns to spot patterns and make connections. Therefore, the machine learns (get it?)

The hype machinery is kicking into high gear with all types of vendors touting offerings, and even leadership, in the emerging markets for machine learning and Artificial Intelligence, or AI. The big vendors want in on the action too. Salesforce claims it's Einstein delivers'AI for Everyone' (does E AI2?!). IBM has been positioning Watson as the AI solution for business--accidentally leaving the door open for a more astute Sherlock to steal the show. Journalists, writers, filmmakers, and even the average "Joe blogger" have been sharing their visions of what a machine learning and AI future hold.