Oh, my toosh, no.  I don&#x27;t agree with everything Matt said, but on this, you&#x27;re totally off.  I try pretty hard to do research that is (a) potentially industry-relevant (key word:  potentially); and that (b) industry won&#x27;t do for various reasons.  Thus far, it&#x27;s seemed to work pretty well.  Using my favorite example of the week, take some of our work on cuckoo hashing -- it&#x27;s contributed quite a bit to the literature of how to implement fast cuckoo hashes, contributed a new and fairly intriguing data structure for approximate set membership, and produced a design that I know to be in use in two Very Large Companies(tm).<p>The companies wouldn&#x27;t have done this work, at least outside of their research labs, because the solution&#x27;s theory is too far from the need of any one problem.  But the result -- a more memory-efficient hash table design -- turns out to be broadly useful.<p>And yes, I do consider this to be &quot;industry-relevant&quot; research.  I&#x27;m not going to solve their problems for them -- but there can be great synergies between industry and academia for having broad impact through adoption.<p>(full disclosure:  I&#x27;m an academic on sabbatical at Google for the year.  It&#x27;s likely I&#x27;m a little biased in my belief that both have value.  But this isn&#x27;t a bias unique to me;  systems as a general area is close to industry, and most of my colleagues rotate in and out of industry periodically via sabbaticals or startups.)