This is a really valuable list, specially because by reading journals and going to conferences one would not think these are the major problems (as most of thes

This is a really valuable list, specially because by reading journals and going to conferences one would not think these are the major problems (as most of these are too hard to be tackled directly and yet need simple solutions that would not translate to dozens of publications), but at the same time in talking to non-researchers there is too much clouding this clear picture. I'm trying to focus more on these problems in my research, but it is no accident that they are still unsolved. I think the main recent ideas to tackle these are: sampling instead of doing things exactly, random projections to compress information when needed, limiting the memory footpring of existing algorithms, and controlling shared state to increase distributedness. The hardest of these problems, how to act when what you do changes the world and the data you see, desperatly needs at least some guiding principles.