90% of the work in LHC physics is estimating the amplitude of backgrounds that look almost exactly like your signal process. Coming up with the "large booster"

90% of the work in LHC physics is estimating the amplitude of backgrounds that look almost exactly like your signal process. Coming up with the "large booster" for classification is only a small part of it. So yes, machine learning is used, but no, we don't use it blindly like you imply. As for throwing all the data away, the article you link to actually does a good job of explaining how this is done: we look at every collision with thousands of sensors before deciding whether to keep it. At this stage there is absolutely no machine learning anyway (just physics knowledge), so be careful blaming machine learning for any missed discoveries.