Our CEO Bill McDermott says, "Everything has to start with empathy for the end user." So, more precisely, what is empathy? It is "The quality of feeling and understanding another persons' situation in the present movement and communicating this to the person." A machine's ability to read the "emotion states" of a mind (body language, voice, and facial expression) is critical in the new paradigm of an autonomous system. Empathy changes the way we feel and more importantly, machines can be trained to recognize, express, and "have" emotions by reading those three emotion states.

We all see the term artificial intelligence (AI) thrown around in many contexts. AI is a buzzword in the tech industry in particular. However, many people (including those in IT) don't actually understand what AI is nor the challenges and opportunities it presents. Today, I'm beginning a series of blogs to share the basics of all things AI. As computer systems become ever more capable of performing the tasks that traditionally are staffed by human employees, the evolution will affect nearly every industry.

Our CEO Bill McDermott says, "Everything has to start with empathy for the end user." So, more precisely, what is empathy? It is "The quality of feeling and understanding another persons' situation in the present movement and communicating this to the person." A machine's ability to read the "emotion states" of a mind (body language, voice, and facial expression) is critical in the new paradigm of an autonomous system. Empathy changes the way we feel and more importantly, machines can be trained to recognize, express, and "have" emotions by reading those three emotion states.

Artificial intelligence is gaining traction faster than anybody imagined – quickly knocking down the dominoes of complex tasks that computers have long struggled with. For example, in April this year, Wired Magazine ran an article explaining why AI still sucked at transcribing speech. But just six months later, AI is now as good as humans at listening! And there have been similarly dramatic advances in other areas. Adding machine learning to Google Translate has improved error rates by up to 85% since it was introduced a month and a half ago! "It has improved more in one single leap than in 10 years combined" -- The list goes on: Google's AI can already lip read better than people, and the company's image service is now better than people at recognizing and tagging images.

In 2011, in an article in the Wall Street Journal, Marc Andreessen proclaimed that software is eating the world. He argued that a slew of technological innovations including advanced microprocessors and high-speed connectivity will revolutionize traditional business, and that every company should become a software company. Many pundits have subsequently argued that even traditional businesses will need to rethink their business models. Andreessen even went so far as to say that the entire retail vertical will eventually die due to the scalability of companies like Amazon. In short, if you aren't thinking about how you will disrupt your industry you can bet your competitors are already doing so.

Using algorithms to help make better decisions has been the "next big thing in analytics" for over 25 years. It has been used in key areas such as fraud the entire time. But it's now become a full-throated mainstream business meme that features in every enterprise software keynote -- although the industry is battling with what to call it. It appears that terms like Data Mining, Predictive Analytics, and Advanced Analytics are considered too geeky or old for industry marketers and headline writers. The term Cognitive Computing seemed to be poised to win, but IBM's strong association with the term may have backfired -- journalists and analysts want to use language that is independent of any particular company.