In a post at Less Wrong, Vladimr_M is asking about how we know if an area of academia is a good place to look for current and relevant information on a particular subject. He notes one way to do this is to see if there is a lot of “low hanging fruit” available that allows a lot of viable and reasonably cost effective research. If the only things left to be discovered are obtuse and expensive to research, then much of the research will be pointless and obtuse themselves. He notes that modern physics has this problem.
But then he brings up the current technology that was the latest (possibly excepting lasers) to reach mainstream: computers.
Somewhat surprisingly, another example is presented by some subfields of computer science. With all the new computer gadgets everywhere, one would think that no other field could be further from a stale dead end. In some of its subfields this is definitely true, but in others, much of what is studied is based on decades old major breakthroughs, and the known viable directions from there have long since been explored all until they hit against some fundamentally intractable problem. (Or alternatively, further progress is a matter of hands-on engineering practice that doesn't lend itself to the way academia operates.) This has led to a situation where a lot of the published CS research is increasingly distant from reality, because to keep the illusion of progress, it must pretend to solve problems that are basically known to be impossible. 
 Moldbug’s "What’s wrong with CS research" is a witty and essentially accurate overview of this situation. He mostly limits himself to the discussion of programming language research, but a similar scenario can be seen in some other related fields too.
So I went over to the linked article and came up with this amusing anecdote.
So here's the first thing that's wrong with CS research: there's no such thing as CS research. First, there is no such thing as "computer science." Except for a few performance tests and the occasional usability study, nothing any CS researcher does has anything to do with the Scientific Method. Second, there is no such thing as "research." Any activity which is not obviously productive can be described as "research." The word is entirely meaningless. All just semantics, of course, but it's hardly a good sign that even the name is fraudulent.
If you go through both postings, what you get a sense of is that academia in most areas is too convoluted, to entrenched within their existing belief structures to likely be of much use. Accidents, like Google, do happen. But even Google is not exactly an earth-shaking revelation. So your best hopes from major advances are likely to be in very young fields of endeavor. However, if your scenario postulates a relatively narrow time frame for success the 50 year introductory period for new technology to go from experimental introduction to mainstream wide application is a problem.