I don't think I understand the question. This is by far the best book about how the major research funding and community happened in the 60s (Parc was one of the outgrowths). I would say that our "age" (or any age) could be enriched by understanding this book. For example, the real issues are not "big data" but "big understanding", not "Machine Learning" but "Machine Thinking". Some of the "Dream Machine" is about how the funders were willing to put forth considerable resources for "problem finding" not just "problem solving" -- a lot more of that needs to be done today.
BTW, I did read the book about 10 years ago. Like what Alan commented below, I recognized some of the paragraphs and stories in the book with a kind of dream-like déjà vu. Very interesting feeling.
http://www.amazon.com/Dream-Machine-Licklider-Revolution-Com...
It was published in 2001. What do you think of its relevancy 15 years later in the context of our age of "big data" and "Machine Learning"?