I'm studying about statistical learning theory and I bumped into the following statement in my study material:
Claim:
If a linear normed space $E_1$ contains bounded noncompact sets, then the inverse operator $A^{-1}$ for an absolutely continuous operator $A:E_1\rightarrow E_2$ ($E_2$ also linear normed space) need not be continuous.
Proof:
Consider a bounded noncompact set in linear normed space $E_1$. Select in this set an infinite sequence:
$$f_1, f_2, ...,\;(||f_j||_{E_1} \leq c \in \mathbb{R})\;\;\;\;\;\;\;\;\;\;\;\;(1)$$ such that no subsequence of it is convergent. An infinite sequence $$Af_1, Af_2, ...,\;\;\;\;\;\;\;\;\;\;\;\;(2)$$ from which convergent subsequence may be selected (since $A$ is absolutely continuous) corresponds in $E_2$ to this sequence. If the operator $A^{-1}$ were continuous, then a convergent subsequence
$$f_{k}, f_{k+1}, ...,\;\;\;\;\;\;\;\;\;\;\;\;(3)$$
could be extracted from $(1)$ in space $E_1$. This however contradicts the choice of sequence $(1)$.
The above was somewhat clear to me, but I wasn't 100% sure, so I wanted to try prove this claim myself and then verify here if I understood it or not.
UPDATE: I have added my own attempt as a possible answer.
My question was: is my proof valid? Or did I misunderstand something?