It would not surprise me if high-tech companies are inventing new, useful things in this field.
In my career as first a scientist and then an engineer, I've found very few practical users of highly technical experimental design theory, and all of them were in industry. These algorithms move about intelligently along all dimensions of some search space, whereas in the lab we prefered to turn just one knob at a time.
One reason is that the algorithms are optimally seraching for "known unknowns" -- that is they assume they roughly understand the problem. The lab is a world of unkown unknowns where the more plodding, understandable protocols tend to be safer.
But in industry, some problems are of the known-unknowns type. And experiment runs can burn up seriously expensive hardware time. So it makes sense for fusion researchers and cloud-computing giants a like to invent new practical ways to optimise searches.
Besides, optimising searches is what Googlers are for.
In my career as first a scientist and then an engineer, I've found very few practical users of highly technical experimental design theory, and all of them were in industry. These algorithms move about intelligently along all dimensions of some search space, whereas in the lab we prefered to turn just one knob at a time.
One reason is that the algorithms are optimally seraching for "known unknowns" -- that is they assume they roughly understand the problem. The lab is a world of unkown unknowns where the more plodding, understandable protocols tend to be safer.
But in industry, some problems are of the known-unknowns type. And experiment runs can burn up seriously expensive hardware time. So it makes sense for fusion researchers and cloud-computing giants a like to invent new practical ways to optimise searches.
Besides, optimising searches is what Googlers are for.