There are plenty of instances where technology of different forms have been in use that there was no real models around to explain, often the practical scientists/engineers/inventors could predict outcomes by looking up experimental data, interpolate from it and hammer out a few formulas by looking at patterns, without really making any models for why it worked.

It looks to me like this is just taking that method to the next level, throw more computing power, better algorithms and more data at the problem...

But often when data and knowledge had been amassed by practical experiments, the theoretical scientists could use this to make models, that was then fed back to the practical side and so help the engineers make better things, and suggest new experiments that would provide more data and so on.

I guess my point is that the theoretical and practical sides are complementary, sure you can do one whithout the other, but the best results is from having both...

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