that's just not true. In a lot of cases in engineering, there are 10000000 possibilities, and deeplearning shows you 100 potentially more promising ones to doub

that's just not true. In a lot of cases in engineering, there are 10000000 possibilities, and deeplearning shows you 100 potentially more promising ones to double check, and that's worth huge amounts of money. In a lot of cases deep learning is able to simulate complex system at a precision that is more than precise enough, that otherwise would not be tracktable (like is the case with alphafold), and again this is especially valuable if you can double check the output. Ofc, in the field of language and vision and in a lot of other fields, deep learning is straight up the only solution.