Big problems on Computer Science and Machine Learning

One of the most intriguing questions that Richard Hamming raised in his talk : "You and your research" (which I'm sure most of you've red) is : What are the most important problems in your area?
In one hand it is obvious that one can only focus on single well defined thing to do "great" stuff but in the other, and as Feynman states:

"... You have to keep a dozen of your favorite problems constantly present in your mind, although by and large they will lay in a dormant state. Every time you hear or read a new trick or a new result, test it against each of your twelve problems to see whether it helps. ..."

 So I decided to do a quick search about this and found a Wikipedia entry, a StackOverflow entry and a very interesting blog from Andreas Zwinkau, who describes an experiment : "Fantasy Research Lab" proposed by Philip Greenspun.
The Fantasy Research Lab consists of

 " ... [you] pretending that you are the lab director for computer science at a brand-new research university and to come up with a plan for how you'd populate your lab with projects."

 I thought it was an interesting experiment so I asked prof. Fabio to try it out, he rapidly came up with the interesting problem of Automatic Programming.
Now I'm interested in knowing the point of view of some very bright people like you,  but not only regarding the entire Computer Science field (which by itself could extend to Operating Systems, Software Engineering, Security, Databases, Hardware and so on as Microsoft Academic Search unveils) but also the more specific Machine Learning, Information Retrieval and HPC view which is central to this blog.

Thanks for reading ;)