I would counter the fear. Data center engineering requires expert knowledge (network, civil engineering, material science, etc), and expert knowledge is a testi

I would counter the fear. Data center engineering requires expert knowledge (network, civil engineering, material science, etc), and expert knowledge is a testimony of experience, and experience is only proven to be good with data (track of records!)! While computers are very good at making prediction and decisions with enough data, humans are still integral in the decision such as actually building the blueprint and architecting the right system. That computer cannot do. Only human is capable of doing that today. Not to be too negative because I don't know how complicated the model is, but since they already have senors all the years (they use these senors to determine how much cool air need to be come in, how much of hot air need to be released and reused, etc), I am not sure how the learning model is different from a classical supervised ML algorithm. I can only think of simulation wasn't in the original equation and here they do some simulation?