YouTube captioning in English works surprisingly well, the improvement over the last few years is huge. It still chokes on proper nouns but in general it mostly works.

I think it's a bit like self-driving cars in the sense that it's good enough to be impressive but not good enough to be actually usable everywhere. Of course self-driving is worse because people seldom die of bad captions.

Google's captioning works well when people speak clearly and in English. Google translate works well when you translate well written straightforward text into English. It's impressive but it's got a long way to go to reach human grade transcription and translation.

I think when evaluating these things people underestimate how long the tail of these problems is. It's always those pesky diminishing returns. I think it's true for many AI problems today, for instance it looks like current self-driving car tech manages to handle, say, 95% of situations just fine. Thing is, in order to be actually usable you want something that critical to reach something like 99.999% success rate and bridging these last few percent might prove very difficult, maybe even impossible with current tech.

What's important to remember, I think, is that we should not compare YouTube auto captions to human made captions, because auto captions were not created as a substitute for human made captions - if it wasn't for auto captioning, all these videos wouldn't get any captions at all. They may never be perfect, but they're not designed to be, they're creating new value on their own. And IMO they crossed the threshold of being usable, at least for English.

Mh no it does not. It is just a source of hilarity apart from a few very specific cases (political speeches mostly, because of their slow pace, good english and prononciation I guess).

Every time I activate it I am in for a good laugh more than anything actually useful.

It works for general purpose videos. Transcripts of any kind appear to stop working whenever there's domain knowledge involved. That doesn't matter for most youtube videos but is crucial if you want to have a multi purpose translator/encoder.

A. Cooper had a nice example of this kind: a dancing bear. Sure, the fact that bear dances is very amusing, but let it not distract us from the fact that it dances very very badly.

Google Translate is way, way better than it used to be (at least German > English which I suppose is probably an easier task than many languages).

Google Translate of Goethe:

    Have now, ah! Philosophy,
    Law and medicine,
    And unfortunately also theology
    Thoroughly studied, with great effort.
    Here I am, I poor gate!
    And I'm as smart as before

word for word not completely bad, but then it breaks when we have to translate 'Tor'. Google Translate is clueless because it is unable to derive that here the 'fool' is meant.

It's unable to 'understand' that 'I poor gate' makes no sense at all.

Google Translate is the 'poor gate'.

On the other hand Deepl gives translations for news articles that are of such quality that it allows me to read international news as if it were local. Definitely useful.

DeepL is better, but it basically has the same problems. I understand both German and English - and I can easily detect where DeepL also shifts the meaning of sentences, sometimes even to mean the opposite. DeepL like Google Translate has no concept for 'is the meaning preserved?'.

You may think that you can now read German news, but in fact you would not know if the sentence meaning has been preserved in the English translation. The words itself might look as if the sentence makes sense - but the meaning is actually shifted - slight differences, but also possibly the complete opposite.

The translation also does not give you any indication where this might be and where the translation is based on weak training material or where there is some inference needed for a successful translation.

Not sure if I agree. If you have some knowledge of the language is still mostly easier to translate the words you don't understand. Easy texts work, anything more complicated (e.g. science articles) not really.