GolDDranks

> language production and perception are quite separated in our heads

Do you have any evidence for this?

I am a former linguistics student (got my masters), and, after years of absenteeism in academia, interested in the current state of the affairs. So: "quite separated in our heads" Evidence for? against?

I think it's obvious that she means that it's something _like_ LLMs in some aspects. You are correct in that rhythm and intonation are very important in parsing language. (And also an important cue when learning how to parse language!) It's clear that the human language network is not like LLM in that sense. However, it _is_ a bit like an _early_ LLM (remember GPT2?) in the sense that it can produce and parse language, not that it makes much deeper sense in it.

"But for 90% of web browsing, lifting my hand to the mouse is unnecessary friction"

By this point, I realized that the OP uses a normal mouse. The MacBook trackpad is so good that I feel weird using a mouse these days. Also, the travel between the keyboard and trackpad is much smaller.

My e-mail is pyry.kontio@drasa.eu in case you happen to be around.

That's NEAT! I live in Japan myself, and I am a passionate Japanese learner (and used to be a teacher too) of multiple decades. Besides, I'm interested in natural language processing and language related technology, and used to study second language acquisition research back in the university. If you ever take part into any tech / language events or meetups, it would be nice to hang out and hear about the development of that app.

Note that the copyright is not about the source country of the work, but where do make/distribute the copy. Do you live in Japan, or are you interested in Japanese works? (Or both, possibly.)

Because that table is "Entering the public domain in countries with life + 80 years".

Calling people monkeys and losers doesn't particularly tickle my sense of humor. If anything, it reminds me of Linus Torvalds from his toxic ages. Fortunately, he has matured well. Andrew seems like a smart guy, I hope that he will have the emotional maturity to realize that you can be no-bullshit and straight to the point without the need to call people names.

What I usually do to share code, is send a link to GitHub or whatever VCS portal we are using. Of course, this doesn't work with local, new code, but that's why we also use liberally draft pull requests to share unfinished code.

I also grew up where 90% of TV was subtitled (Finland, where, incidentally, the author of the article is from too), but I find the "good" anime subtitles better – for the simple reason that they make it easier to see which translation corresponds to which text.

Note that anime has generally more text on the screen that many western shows, so I think subtitling practices of some subtitle-heavy western countries, while informed and proven by time, don't necessarily represent optimal practices for anime.

But I think you are correct about the subtitle preferences of anime fans. The "general wisdom" of audiovisual translations is that great translations manage to convey the important point very succinctly, and a professional translator knows how to shave off the fluff to achieve subtitles that are quick to read and "fade in the background" in the sense that you don't even realize that you are reading them.

However, many anime fans actually LIKE so-called foreignizing translations ( https://en.wikipedia.org/wiki/Domestication_and_foreignizati... ). I think this plays into the fancier subtitle preferences too.

The difference is that when there is text on the original video material, in the good examples the translations are positioned in the proximity of the original texts, and styled similarly, which makes it easier to understand what is translation of what, and generally improves immersion.

In the bad examples, the translations for the texts are mixed with the lines the characters are speaking, which makes it harder to follow.

Note that Turing test allows a lot leeway for the test settings, i.e. who interrogates it, how much they know about the weakness of current SOA models, are they allowed to use tools (I'm thinking of something like ARC-AGI but in a format that allows chat-based testing), and how long a chat is allowed etc. Therefore there can be multiple interpretations of whether the current models pass the test or not.

One could say that if there is maximally hard Turing test, and a "sloppy" Turing test, we are somewhere where the current models pass the sloppy version but not the maximally hard version.

Also, Rust is not going to have it for the long run that pointers can be, in fact, disguised as integers. There is this thing called pointer provenance, and some day, all pointers are required to have provenance (i.e. a proof where they did come from) OR they are required to admit that POOF this is a pointer out of thin air, you can't assume anything about the pointee. As long as there are no POOF magicians, the GC can assume that it knows every reference!

I agree specifically with regards to GC; I think that focusing on being an excellent language for low-level programming (linkable language-agnostic libraries, embedded systems, performance-sensitive systems, high-assurance systems etc.) should continue being the focus.

However, this is 3rd party research. Let all flowers bloom!

The mechanisms that Rust provide for memory management are various. Having a GC as a library for usecases with shared ownership / handles-to-resources is not out of question. The problem is that they have been hard to integrate with the language.

That depends on the intent of the sentence, and the intent was only a guess of the GP. But you can analyze だけに in two ways:

英語に吹き替える to dub in English (the base case of 吹き替える)

英語だけに吹き替える to dub just in English (だけ + に)

アメリカだけに吹き替える to dub, just because it's America / as you'd expect of America (だけに grammar https://tanosuke.com/n2-dakeni)

Those were the days.

Not the GP, but I watch all my anime raw (often enabling Japanese closed captions), and I struggle to understand the above...

There is something off with the explanation.

At first, there is 16 fetches per row x column, 1024 in total. Then, it is observed that an input row needs to be fetched only once per output row, reducing the amount to 8 fetches per row, plus 8 per row x column, 8 * 8 + 8 * 64 = 576 in total. This requires the same amount of 16 numbers to be kept in registers.

But then it is claimed that by doing one quadrant at a time, all that is needed is 64 fetches per quadrant or 256 fetches in total. But that assumes we can keep 4 rows and 4 columns, 8 numbers per row or column = 64 numbers in registers! If we can only keep 16 numbers like above, each row of the quadrant is going to take 40 fetches, and we get 160 fetches per quadrant or 640 fetches in total, a pessimization from 576 fetches!

It gets even worse, when the original mangaka typoes the name, and people follow a single typo like a religion. This happened with Kaoru Mori's "Emma", where a common English surname "Jones" was accidentally spelled "Jounse" by the author, and used in translations without questioning it too much, only later found to be written correctly "Jones" in a later chapter by the author herself.

However, that leaves you without any tools to check whether two things are equal or not, save for trivial, syntactic equality. It's like, in a programming sense equality declared to exist, but not actually defined.

The search within page functionality of my browser doesn't even find the word "tangential" in the document...

Okay, so number 8 got me...

Huh, Mr. Potato? Clearly that is a toy, not a vegetable?!

I made to the vegetable level. Tried various combinations but didn't managed to pass. Could someone tell the correct answer?

Which parts felt GPT'y to you? The list-happy style?

I wondered the same. Seems like it would just make a V-shaped loss around the zero, but abs has that property already!

Glad to know that I wasn't alone with my feeling!

Heh, I guess so. It's just an uneasy feeling I can't get rid of. Maybe I'm just being paranoid. Then again, I wonder if the said greentexts are AI-generated still. At least the contents are likely to be fakes.

Nice solution!

Out of curiosity to the OP, did you use an AI to tweak/refine the text? It contains a lot of similar writing patterns as some read-aloud 4chan greentext/copypaste YouTube channels, especially liberal use of whimsical similes: "like it's 2000 and I'm downloading a JPEG on dial-up" "starting to feel like cosmic punishment" "like it's protecting nuclear launch codes", and jocular asides: " -- exposed to British weather, coated in a mysterious film of protein shake and regret, probably being livestreamed to TikTok by someone's ring doorbell -- ".

So I started to wonder if my AI-radar was spot on, or is that style of writing something people naturally do – because I wouldn't bother, but then again, I don't run a blog that people actually read.