Suppose you are sitting in front of a screen with white noise. There are all these black and white pixels coming with equal probability at you, conveying maximum traditional Shannon information or Boltzmann information. And still this stream of inputs is totally boring again because, yes, it's very uncompressible. You cannot find a short pattern and you cannot improve your current description of the signal, which again means that there is no compression progress, so this is also boring.
He is contradicting himself. For most purposes the term "white noise" is all you need to know to predict the features that actually matter.
What if it was encrypted interesting data? What if you find the key later, but you only remember the original data as "white noise", you'd kick yourself.
Basically, calling it "white noise" is lossy compression, which may not be a good idea.
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