Sunday, February 13, 2022

Random thoughts on translation

How many books get carried over to another language only to suffer a cruel death by translation? I remember having read Catcher in the Rye in Russian when I was in college. It barely touched me, because the text wasn't alive, it was bland like semolina porridge. I heard similar accounts from English speaking people who tried reading Russian proze. I guess this becomes more if a problem when the context of the translated book is unfamiliar to the new readers. Anyways, Catcher in the Rye in English is well-written and engaging from the page one. 

Some English authors did shine even in translation. I could think of Wells, Conan Doyle, Vonnegut, Mark Twain and a few others. Or they were lucky to be about either historical times or about fictional setup. Pratchett has been ruined for me too, but Zelazny or Tolkien weren't. Perhaps because Pratchett was more satire than fantasy, and that sature was grounded in the context I had no clue about back then?

This seems to be less if an issue for some other languages/cultures; I rarely got annoyed at German, Polish or Czech translations I have read. Translated poetry is often terrible, but luckily, in Russia it wasn't uncommon when some great poet did it and produced if not a full match for the original, then at least an impressive remake in its own right - so some of the English poetry came across somehow, thanks to Boris Pasternak and others.

Will machine translation ever win over human translation? Could it become a perfect magic mirror? Do we even know how a perfect translation should look like? Till that time, getting access to the original works is one of the compelling reasons to learn about other languages and cultures. May be if more people did that, less people would get time and energy for violent conflicts of any kind. One can always dream.

Thursday, August 26, 2021

Выбор.

Созидающий башню сорвется,
Будет страшен стремительный лёт,
И на дне мирового колодца
Он безумье своё проклянёт.
Разрушающий будет раздавлен,
Опрокинут обломками плит,
И, Всевидящим Богом оставлен,
Он о муке своей возопит.
А ушедший в ночные пещеры
Или к заводям тихой реки
Повстречает свирепой пантеры
Наводящие ужас зрачки.
Не спасёшься от доли кровавой,
Что земным предназначила твердь.
Но молчи: несравненное право —
Самому выбирать свою смерть.

Автор этого стихотворения - Николай Гумилев. Ровно сто лет назад его не стало. По легенде, он отказался от предложения выйти из строя приговоренных к расстрелу. По другой легенде, пьесу Гумилева "Гондла" сняли с репертуара уже после его гибели, потому что восторженная публика хотела увидеть автора.

Thursday, August 19, 2021

A poet to a philosopher is like an engineer to a scientist.

For me, the analogy comes from the following perspective. Imagine we, as humanity, are moving forward into the hazy world of the unknown. Scientists distill that unknown into potentially useful materials. Engineers use these materials to cover more territory, so that the rest of the humanity (including scientists) could move forward.

Similarly, philosophers distill the unknown principles under which the reality (tangible or intangible) operates into clearly defined concepts. Poets use these concepts to extend our image of that reality, thus enabling the rest of humanity (including philosophers) move forward and look out for yet undiscovered aspects of life, universe and everything.

Monday, May 04, 2020

Thesis: the future is here, but it's not evenly distributed.
Ergo: buying a rare piece of future is only a good investment when you really need it right now.
Example: personal calculators.
Also, buying wrong future example: getting an early TV set that didn't become standard.

Wednesday, January 10, 2018

In a way, deep-learning systems could be seen as living in a Groundhog Day movie implemented: given (almost) unlimited chance to try out different choices and learn their consequences, as well as (almost) unlimited memory, design the most optimal policy for a given environment (which could be also seen as a very sophisticated set of reflexes).

Which makes one wonder:

1) whether conscious thinking, and the human civilization as a consequence of that, have developed as an evolutionary shortcut to mitigate the shortage of experience which could be obtained naturally by a single human being.

2) whether the "set of reflexes" approach can scale to emulate human conscience and not turn the Universe into paperclips in the process.

Sunday, November 19, 2017

On pipelines and learning

Working with data processing pipelines made me see some analogies with the process of human learning. When a human being learns a new skill, they usually go through the state which could be called “snapshot reload” in the data processing pipelines lingo. That means, both a human and data pipeline have to spend some time accruing the “initial set of knowledge” based on which they will (hopefully) become useful in the future. Once this happens (e.g. you as a human finished a school or a professional course), in order to be fully useful one would also need to keep their knowledge current (get the recent information related to that set of skills by following the related events, reading articles, trying out the new tricks, etc etc). In pipeline world, this is called “catching up on the incrementals”. If this is not being done (or takes too much time) the pipeline (or a human) might need to do the new “snapshot reload” (go back to school) to stay in business.

What’s important to understand is that every such system is essentially useless and vulnerable while it’s doing those costly reloads. Almost everyone can relate to their student times as the periods of high uncertainty and remember the efforts it sometimes costed to stay on track, with no finish line in sight. The price of falling at that stage is also very high: dropping out is easier than restarting the process, and can result in hard compromises regarding the final state. Software, designed in a waterfall way and discontinued before completion, is useless (except for whatever could be scavenged for reuse in the next projects). A pipeline which failed to reload its state gets restarted from scratch, with no advantage from the incomplete work. And though a few school dropouts might become billionaires, the rest would eventually have to get their life back together and either return to that or other school or significantly lower their future expectations.

The traditional education was (and is) all about spending long (and costly) time in the “snapshot reload” phase (school, university, then perhaps more time in academia as a postgraduate) and because it’s recognized as being very time-consuming and costly, changing jobs or learning new skills as an adult is considered to be unlikely. (You can also draw an analogy with waterfall process here).

Ideally, though, both in the data processing world, in the software development in general and in the human world, one would prefer for things to become useful immediately, without going through that painful and costly (and often black-box) phase mentioned above. There are numerous papers describing large-scale incremental data flows. There is Agile methodology, which is about developing software in an incremental way, as opposed to phased Waterfall style. And nowadays, there is a pronounced tendency to try learning new skills incrementally: most of the online learning courses and the variety of learning apps are about splitting the information to be learned into piecemeal bites and feeding it to the students on a regular basis, assuming they would gradually become proficient in the given skill.

The big question is, is it always going to work or would the process in some cases be too slow to be useful? Could every child completely skip the hours in school and become the high-functioning adult just by incremental learning, interleaved with their daily life? Could every adult gradually shift to a new role, and if so, at which point of that shift can they actually become useful? Or are the “snapshot reload”, high-focus-on-the-problem-at-hand phases inevitable?

To me, these questions largely seem unanswered, and the second one might be a weak point of the online learning in general. It seems currently be well optimized for monetization via getting students to pay, but less so for monetization via helping the learners to refocus by steering them into using their acquired knowledge and connecting with the relevant communities. Udacity is making steps in that direction by trying to place their students into relevant job roles,  but this looks more like an exception than a rule so far.

I wonder whether there isn’t also some unconscious bias from the part of those who did go through the traditional “snapshot reload” phase regarding those who obviously didn’t, as incrementally acquired knowledge might appear “less valid” because it misses the hard proof of completing the “snapshot reload” phase and hence the credibility - which might be not ungrounded, on one side; on another side, the existence of scientific titles with the suffix “honoris causa”, “for the merit” proves that it was always posssible to do things differently.

The interview with Freeman Dyson, which mentions not obtaining the PhD due to not believing in the system, was my most recent reminder on that. In general, my hope is that the future becomes more fluid and "incremental" and will allow people to switch between different activities as they go through their lives, without discarding their ideas just because they arrived "too late" to be carried through a necessary snapshot reload phase before getting applied somewhere.

Monday, January 23, 2017

The real problem, in my humble opinion, is not Trump, or Putin, or Wilders, or Brexit. The real problem is what made lots of people believe that there was no better choice. And if we feel that the best answer to this question is blaming someone, then we might as well begin with ourselves, Dunning Kruger effect or not. It's us who make ivory towers whenever we have a chance, and then spend time devising elaborate mechanisms to keep these towers safe. Eventually people see through that, and that's, sadly, the point at which the unicorns fly away and the angry flock of bad-smelling rhinos breaks in. I only hope that eventually we learn how to break this ill samsara, and there will be no need to build ivory towers ever since.