CAS 2010 DISTILLATION:  (not in time order):

We've Got More!!  LSST, SDO, MACHO, LIGO/LISA, ...

More is hard to handle:  I/O is toughest. Distributed ... bases and computation

More is Different.
"This problem is not just in astronomy. It is in National Challenge areas."   aip.org/fya"
"How do you take an algorithm to beyond RAM; or beyond 1 disk?"
"We have to degrade the (space/time) resolution for our methods to work."

Physics Modeling/Simulations are crucial -- take a long time to run well.  OR:
* "How do you exctract information from all this cacaphony."
* Interpolating grids of results; evaluating model mis-specification/uncertainty

There are Challenges AND there are New Tools (mostly non-parametric):
* There are now good, robust --fast --algorithms available; not in textbooks. 
   See designers!
* Careful validation at the Math end --- from wavelets to diffusion maps to trees
* Useful to do blind analysis -- HEP "opening the box" 
    don't bias yourself by assuming too much ahead of time -- is it more a 'frequency' method?
* Dimension reduction to get clean input:
* Tradeoff of computation time / clean input versus statistical rigor for messiness
* + Characterize first;  classify via physics experts later  versus
   + Based on underlying physics/statistics:
      Careful conservative filtering first; intensive statistics only when needed
* Careful validation on known data

To Get Real Science Out:
* Science Data Quality Assessment of methods
*  Crucial to understand messy efficiency/response of whole process, as
* LARGE effects of systematic bias of instrument model mis-specification
* How to include measurement error? Limited: modifying method with weights
  + missing data problem
* Inject probability modeling into the right places - how to find these?

 Many results are very promising!
* Fitting large populations statistically,rather than bright-source by bright-source
* Well-tailored tools for specific problems - on older data.

Many still have challenges:

And finally:
"...discussions are not important. What is important are collaborations that comes out of it."
"Collaborations take months to years... Not as simple as answering an email question."

How do we move on from here?

Three ideas for building collaborations:  The ISI that David van Dyk mentioned; the SCMA summer 2011;
 and the working group that Kirk Borne mentioned.  So there are problems to work on.

Would writing more proposals be helpful?
Proposal pressure.  And younger astronomers can be more receptive.
A lot of people won't be receptive until they see for themselves that there is a payoff from doing this kind of analysis... We need to have scientific return ... agressively advertised ... Right now many astrostatistics/ astroinformatics can be published in machine learning journals, or ADASS, or not in ApJ or AJ or MNRAS or..
Making the code available can really help  --- even though people misuse the code all the time.

Are there any private funding sources?