Research fellow at @OxfordPhysics + @NCEOscience focusing on satellite data for weather and climate | Occasional Pilot | he/him | 
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Can DL tell you how to improve your next generation sensor? 
This was my first thought.
This is a huge part of what I always try to encourage when thinking about deep learning, it’s augmentation of human capability not replacement. Using DL to assist in data generation that indicate improvement pathways is valid, expecting to design new systems with it is not.
I also don’t think it’s valid to think of DL in a “train and forget” methodology, if it’s more accurate and captures new information/patterns then the questions to start asking are why, how can we understand that outside of an ML model, and can that be used to improve it?
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