Smartest Machine on Earth

What is "machine learning"?
"Machine learning" is a branch of artificial intelligence that is concerned with the study of computer algorithms that improve automatically through experience. Watson by IBM uses "machine learning" in order to answer the Jeopardy questions without ever hearing the question before.

How did the IBM team employ that concept in the development of Watson's AI? What advantage did that provide over previous attempts at "intelligence"?
IBM employed the concept of "machine learning" in the development of Watson's AI by feeding Watson thousands of previous Jeopardy questions. They also fed Watson different forms of the same thing, for example the letter A. The letter can have many different forms and shapes.  Instead of letters, Watson is fed different forms of questions, Watson is better equipped to answer a question asked because it can reference the way something is worded, allowing Watson to imply things if needed. With all of the references that IBM has supplied Watson with, Watson is able to access all the information searching for information that relates to the question. It then "weeds out" the least likely, leaving the most likely answer choice. The Artificial Intelligence allows Watson to better find the most likely answer and learn from its mistakes. Watson is able to listen to the answers of his opponents and learn from the way they answered, whether it is right or wrong, and how they answered. In the video, a question is asked about what month a certain holiday is in. Watson answered that the holiday stated was a holiday. An opponent answered the question as a month, getting it correct. After hereing the same style of answer for times in a row, Watson was able to answer the next question, which was the same style, correctly. The "intellegence" that Watson has been given and allowed to build on makes Watson able to gain more information and intellegence the more it answers questions and hears questions answered. Watson has taken AI to the next level because up till now, no other technology could produce a machine anywhere near Watson.

I've often mentioned the term "Empirical Scepticism". What does that mean? How does that relate to the concept of Machine Learning? How does this relate to your life?
"Empirical Scepticism" is an attitude of doubt or a disposition to incredulity either in general or toward a particular object based on observation and/or experience. This relates to Machine Learning because Machine Learning is learning based off of previous information/experience. This relates to our lives because we live from experience, whether it is our own experience or other's.