Chucking a bunch of variables into a linear regression, getting an r^2 of 0.3 and calling it day is so far removed from Newtonian science that I'm not sure it should even be called science.
In reality chucking a bunch of variables into a linear regression is the easy part (well, with exceptions), getting ,or creating, good, interesting and important data that were not already analysed to death is a problem. Imho the revolution is the realising value in observational data and not using statistics. It's all about the data.
When discussing machine learning, data-mining or statistics with somebody far removed from the machinery (so for example from linguistics to biology), they always focus on what's possible with the tools but in reality the available data is what's constraining everything. Most tools (especially fancy ones like neural networks etc.) only work under certain constraints the are hard to achieve, it's not a hammer. You can always use a hammer and get results.