My general impression is that it's fairly easy to get moderately accurate models with simple procedures on cheap hardware... linear regressions, say. Maybe tha

My general impression is that it's fairly easy to get moderately accurate models with simple procedures on cheap hardware... linear regressions, say. Maybe that'll get you 75% predictive accuracy. Then, you apply better techniques, that hit the limits of your PC, and you bring that up to maybe 80%. Then you bring in the PHDs, move your analysis to a cluster or into the cloud, and you gain another 2%. In other words, it's more often that 10000x the computing power gives you something like a 1.2x the model quality, not 10000x or even 100x. Still worth doing for a large enough company, though. Just my experience, and only a generalization. Some models just can't be built without a minimum amount of horsepower, etc.