p. 5-6 :

While supervised learning relies on labeled or structured data (think rows in a database), unsupervised learning trains on unlabeled or unstructured data (the text of a book). These algorithms explore the data and try to find structure. Here, widely used unsupervised learning algorithms are clusters analysis and market basket analysis. Naturally, this tends to be more difficult, as the data has no preexisting labels to assist the algorithms in understanding the data. While more challenging to process, as we’ll discuss later, unstructured data makes up the vast majority of data that enterprises need to process today.

p. 11 :

Strikingly, 90% of the world’s data was created in the past two years, and 80% of that data is unstructured.

p. 18 :

Interestingly, while one may think this leads to a reduction in jobs (particularly for the relatively lower-cost paralegals and legal assistants), it has in fact improved their efficiency instead, allowing them to spend their time doing more/higher-rate billable work.

Big Blue is watching you, p. 52 :

The industry the company [VideoRecon] plans to focus on first is law enforcement. Ryan explains: “Imagine you work in law enforcement, and you knew there was a traffic camera on a street where a burglary occurred last night. You could use VideoRecon to review the footage from that camera and create a tag whenever it detected a person going into the burgled house. Within a few minutes, you would be able to review all the sections of the video that had been tagged and find the footage of the break-in, instead of having to watch hours of footage yourself.” Once a video is uploaded, IBM Watson’s Visual Recognition is used to analyze the video footage and identify vehicles, weapons, and other objects of interest.