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Till today I - as an AI layman - am confused by the promised and achieved improvements of automated translation.

My impression is: there is still a very, very far way to go. Or are there other explanations why the automated translations (offered and provided e.g. by Google) of quite simple Wikipedia articles still read and sound mainly silly, are hardly readable, and only very partially helpful and useful?

It may depend on personal preferences (concerning readability, helpfulness and usefulness), but my personal demands are disappointed very strongly.

Are the Google's translations nevertheless readable, helpful and useful for a majority of users?

Does Google have reasons to retain its greatest achievements (and not to show to the users the best they can show)?

Who claimed that machine translation is as good as a human translator? For me, as a professional translator who makes his living on translation for 35 years now, MT means that my daily production of human quality translation has grown by factor 3 to 5, depending on complexity of the source text.

I cannot agree that the quality of MT goes down with the length of the foreign language input. That used to be true for the old systems with semantic and grammatical analyses. I don't think that I know all of the old systems (I know Systran, a trashy tool from Siemens that was sold from one company to the next like a Danaer's gift, XL8, Personal Translator and Translate), but even a professional system in which I invested 28.000 DM (!!!!) failed miserably.

For example, the sentence:

On this hot summer day I had to work and it was a pain in the ass.

can be translated using several MT tools to German.

Personal Translator 20:

Auf diesem heißen Sommertag musste ich arbeiten, und es war ein Schmerz im Esel.

Prompt:

An diesem heißen Sommertag musste ich arbeiten, und es war ein Schmerz im Esel.

DeepL:

An diesem heißen Sommertag musste ich arbeiten und es war eine Qual.

Google:

An diesem heißen Sommertag musste ich arbeiten und es war ein Schmerz im Arsch.

Today, Google usually presents me with readable, nearly correct translations and DeepL is even better. Just this morning I translated 3500 words in 3 hours and the result is flawless although the source text was full of mistakes (written by Chinese).

Google's translations can be useful, especially if you know that the translations are not perfect and if you just want to have an initial idea of the meaning of the text (whose Google's translations can sometimes be quite misleading or incorrect). I wouldn't recommend Google's translate (or any other non-human translator) to perform a serious translation, unless it's possibly a common sentence or word, it does not involve very long texts and informal language (or slang), the translations involve the English language or you do not have access to a human translator.

Google Translate currently uses a neural machine translation system. To evaluate this model (and similar models), the BLEU metric (a scale from $0$ to $100$, where $100$ corresponds to the human gold-standard translation) and side-by-side evaluations (a human rates the translations) have been used. If you use only the BLUE metric, the machine traslations are quite poor (but the BLUE metric is also not a perfect evaluation metric, because there's often more than one translation of a given sentence). However, GNMT reduces the translation errors compared to phrase-based machine translation (PBMT).

In the paper Making AI Meaningful Again, the authors also discuss the difficulty of the task of translation (which is believed to be an AI-complete problem). They also mention the transformer (another state-of-the-art machine translation model), which achieves quite poor results (evaluated using the BLUE metric).

To conclude, machine translation is a hard problem and current machine translation systems definitely do not perform as well as a professional human translator.

Am I wrong and Google's translations are nevertheless readable, helpful and useful for a majority of users?

Yes, they are kind of helpful and allows to translate faster

Or does Google have reasons to retain its greatest achievements (and not to
show to the users the best they can show)?

Maybe, I don't know. If you search for info, Google does realy lost of horrible stupid stuff, like learning from what users do in internet, taking bullshit data as trusted datasets.