Arrrghh. People are finishing up Rebirth and looking up the different localizations, and the inevitable wave of hate for the English version is starting to gain traction again just like with Remake. I guess I just get super defensive about it because I have worked on large translation projects before, and it's not as straightforward as players seem to think.
It's not like the good ol' days of "This Guy Are Sick." They don't write the JPN script first, and then just send it out for translation anymore. Nowadays the different language scripts are all written simultaneously, with the teams working back and forth together, to check over each ofher's work and make sure that no one sentence is under- or overshooting a goal. Like it or not— everything is checked over and approved.
There's a lot more being translated than just words. There's so much to take into account— tone of voice, the cultural context, the lip sync and corresponding length of each line (which isn't allowed to run over by more than 0.2 seconds which is CRAZY). It's a messy process and it's a lot of goddamn work.
And then there's the audience, too. Different languages' audiences are often going to have wildly different interpretations of a character. A really good example from FFVII would be Yuffie. In the JPN version of the OG, Yuffie is written to be a confident girl who's dead serious about her ninja training. The ENG translation didn't do that justice... she instead comes off as a silly annoying kid pretending to be a ninja. Remake's DLC was testing the waters to see if they could write Yuffie in a way that's still faithful to both of the strikingly different regional perceptions of her character. And they nailed it.
The same thing happened with Cloud, and continues to influence the way he's written in the Re-trilogy. It's much more subtle than with Yuffie, but it's still noticeable, and I think it's why a lot of people get up in arms about his dialogue.
Cloud has always been written as having a stark disconnect between his tone of voice and his choice of words. It's just that the two major languages get it swapped! JPN Cloud has a harsh, mean tone, but his choice of words is polite and easygoing. On the other hand, ENG Cloud says a LOT of nasty shit out loud, but his true feelings are betrayed by his soft voice and gentle body language.
The difference goes unnoticed by the average player who isn't so invested to give a damn. But if you're actively searching for "bad translations" to get mad at, then you'll find them where one version's Cloud comes off a bit too strong. It's only natural that English Cloud is the one that pisses people off more often— after all, he's literally saying stupid shit to to piss other characters off constantly. His character is so convincing that players want to reach into their screens and wring his neck, and I think that's glorious.
But that's why it upsets me to see people turn that frustration at the localization teams. They didn't "ruin" a character's dialogue— they were just barely able to make something work, all things considered. Character, line length, culture, story context, facial animations, voice acting, for MULTIPLE languages, like... holy shit. It's a miracle that most of it is really really good, and that the bad is only a little bit bad.
Idk where this rant is going. Just... c'mon people. Have some respect for such an insanely complicated art form.
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Reputation to Midnights and Final TPD Predictions
With 4 days until the Tortured Poets Department and two lines of lyrics we have so far, here are my thoughts on how we got here over the last 5 albums and final predictions for what's coming on Friday:
2016 changed the game - reputation era and long-term bearding
Many people might disagree, but I think the year 2016 changed a lot of things for Taylor. Without going into detail about snakegate, a possible failed coming out and scrapped album and the presidential election, her music has had a different tone ever since reputation (and I don't just mean sonically). As someone who writes a lot about love and relationships, the way she was writing about them changed from fairy tale love, pining and heartbreak to forever/long-term love, commitment/endame, 'us against the world' sort of love. And I do think she wanted to put that album out in 2016 but can't really do that when you're newly single and writing about wanting forever with someone... so in came Joe Alwyn who became the free pass for writing songs about long-term relationships, marriage and kids for the next six years. But LWYMMD (the song and the mv) made it pretty clear that this was not her first choice. Whatever happened, she had her agency taken from her, and she was mad about it. She may have made one hell of a comeback, but rep Taylor was on a revenge mission, and she has been ever since. Now, add to that the very same people foiled her coming out (possibly) a second time in 2019, I can well imagine the tortured poet that Taylor became during the pandemic with all that built up anger and misery pouring out into the folklore and evermore albums. And my guess is that with the plan to re-record the first 6 albums came an idea of how she could possibly get her revenge after all, which brings us to Midnights and TPD.
Midnights and Tortured Poets Department - Reflection and melancholia
Midnights had a similar tone to me than what we have seen of TPD so far: introspective, sombre and looking back on happier times and missed opportunities (hence the whole '13 nights throughout my life' concept). There is a lot of wondering about what ifs and regrets and always with a sense of vengeance in the background, which shows how Taylor clearly holds a grudge and has a hard time letting things go that have hurt her. And this continues in the two lines we have seen from TPD so far. The 'full eclipse' gives me love blackout vibes and this line
is so similar to many folkmore and Midnights songs where she talks about not being able to move on from a traumatic event (failed coming out *cough cough*). So, this album clearly continues the theme of reflection, regrets and vengeance, but with an additional touch of reckoning or impending judgment. I've seen some people say it seems like Taylor is putting someone (else or herself) on trial, and both the evidence file esthetics and the legal language she has been using in the hidden words puzzle on Apple Music have been feeding that theory:
She told us back in February she'd be entering all of her defenses and her muses into evidence, so is she the one being trialed and we are the jury? Or is she presenting evidence in her defense and accusing someone else? I initially thought the former, but now I'm thinking it could be either or both.
The songs will tell the story of the most painful times of her life and we will be able to decide if she chose her suffering or if the context/industry is to blame. My favourite swifties pointed out this morning that the ‘un-recall’ lyric is a parallel to CIWYW “I recall late November”. So what is she trying to forget? The 2016 election. The start of the love blackout. Much like the ‘full eclipse’ lyric. They almost had it all but then her plans got foiled and Tr*mp was elected which forced them underground. And where did she run off to? London. And what’s track 5 called? So long, London…
So, a lot of this album so far gives 2016 vibes. And I’ve said in a previous post (here) that the visuals seem very rep-inverted. Black vs white and the half yin-yang ☯️ in the logo. It’s looking likely that this is going to be the reflection on that time where her vendetta originated before she goes for revenge. And I’m not trying to clown but the rep parallels haven’t stopped:
This QR code mural in Chicago is very rep-cover coded and leads to a website that has the same 321 error message as the TS website the night of the Grammys. The message then was red herring. And not to sound too crazy, but I've said from the start that something feels off with this album. The absence of proper promo or merch is still weird. And would an entire album as a red herring be too crazy? Probably. But is she a crazy woman? Definitely! 😉
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The conversation around AI is going to get away from us quickly because people lack the language to distinguish types of AI--and it's not their fault. Companies love to slap "AI" on anything they believe can pass for something "intelligent" a computer program is doing. And this muddies the waters when people want to talk about AI when the exact same word covers a wide umbrella and they themselves don't know how to qualify the distinctions within.
I'm a software engineer and not a data scientist, so I'm not exactly at the level of domain expert. But I work with data scientists, and I have at least rudimentary college-level knowledge of machine learning and linear algebra from my CS degree. So I want to give some quick guidance.
What is AI? And what is not AI?
So what's the difference between just a computer program, and an "AI" program? Computers can do a lot of smart things, and companies love the idea of calling anything that seems smart enough "AI", but industry-wise the question of "how smart" a program is has nothing to do with whether it is AI.
A regular, non-AI computer program is procedural, and rigidly defined. I could "program" traffic light behavior that essentially goes { if(light === green) { go(); } else { stop();} }. I've told it in simple and rigid terms what condition to check, and how to behave based on that check. (A better program would have a lot more to check for, like signs and road conditions and pedestrians in the street, and those things will still need to be spelled out.)
An AI traffic light behavior is generated by machine-learning, which simplistically is a huge cranking machine of linear algebra which you feed training data into and it "learns" from. By "learning" I mean it's developing a complex and opaque model of parameters to fit the training data (but not over-fit). In this case the training data probably includes thousands of videos of car behavior at traffic intersections. Through parameter tweaking and model adjustment, data scientists will turn this crank over and over adjusting it to create something which, in very opaque terms, has developed a model that will guess the right behavioral output for any future scenario.
A well-trained model would be fed a green light and know to go, and a red light and know to stop, and 'green but there's a kid in the road' and know to stop. A very very well-trained model can probably do this better than my program above, because it has the capacity to be more adaptive than my rigidly-defined thing if the rigidly-defined program is missing some considerations. But if the AI model makes a wrong choice, it is significantly harder to trace down why exactly it did that.
Because again, the reason it's making this decision may be very opaque. It's like engineering a very specific plinko machine which gets tweaked to be very good at taking a road input and giving the right output. But like if that plinko machine contained millions of pegs and none of them necessarily correlated to anything to do with the road. There's possibly no "if green, go, else stop" to look for. (Maybe there is, for traffic light specifically as that is intentionally very simplistic. But a model trained to recognize written numbers for example likely contains no parameters at all that you could map to ideas a human has like "look for a rigid line in the number". The parameters may be all, to humans, meaningless.)
So, that's basics. Here are some categories of things which get called AI:
"AI" which is just genuinely not AI
There's plenty of software that follows a normal, procedural program defined rigidly, with no linear algebra model training, that companies would love to brand as "AI" because it sounds cool.
Something like motion detection/tracking might be sold as artificially intelligent. But under the covers that can be done as simply as "if some range of pixels changes color by a certain amount, flag as motion"
2. AI which IS genuinely AI, but is not the kind of AI everyone is talking about right now
"AI", by which I mean machine learning using linear algebra, is very good at being fed a lot of training data, and then coming up with an ability to go and categorize real information.
The AI technology that looks at cells and determines whether they're cancer or not, that is using this technology. OCR (Optical Character Recognition) is the technology that can take an image of hand-written text and transcribe it. Again, it's using linear algebra, so yes it's AI.
Many other such examples exist, and have been around for quite a good number of years. They share the genre of technology, which is machine learning models, but these are not the Large Language Model Generative AI that is all over the media. Criticizing these would be like criticizing airplanes when you're actually mad at military drones. It's the same "makes fly in the air" technology but their impact is very different.
3. The AI we ARE talking about. "Chat-gpt" type of Generative AI which uses LLMs ("Large Language Models")
If there was one word I wish people would know in all this, it's LLM (Large Language Model). This describes the KIND of machine learning model that Chat-GPT/midjourney/stablediffusion are fueled by. They're so extremely powerfully trained on human language that they can take an input of conversational language and create a predictive output that is human coherent. (I am less certain what additional technology fuels art-creation, specifically, but considering the AI art generation has risen hand-in-hand with the advent of powerful LLM, I'm at least confident in saying it is still corely LLM).
This technology isn't exactly brand new (predictive text has been using it, but more like the mostly innocent and much less successful older sibling of some celebrity, who no one really thinks about.) But the scale and power of LLM-based AI technology is what is new with Chat-GPT.
This is the generative AI, and even better, the large language model generative AI.
(Data scientists, feel free to add on or correct anything.)
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Sea Cryptic! Danny AU- Pt. 5
[Pt.1] [Pt.2] [Pt.3] [Pt.4] [Pt.6]
“So you’re that dead kid everyone’s talking about.”
Danny smacked a trash bag into the purple clad vigilante. “You can pick up the glass.”
“Wait, I’m just here to-”
“Bother me when I’m working? At least the litterer brings me cash. You can help clean or you can leave. Plastics go over there.”
Danny pointed at a pile of plastics, ignoring Spoiler’s bemused look. Hard to tell, really, considering her mask.
“I’ll help clean if you answer some questions!” Spoiler chirped, already moving to pick out the glass in the general trash pile Danny’s managed to gather. He nodded.
“Alright. At least you’re helping. The other one just bothers me and leaves his stuff on the beach.”
Spoiler snorted. “I’m Spoiler. Is the litterer Batman?”
“Sure. I don’t really care what his name is,” which was a complete lie, Danny was a fan. It’s just that messing with Batman (especially after he couldn’t clean up after himself, honestly!) overrode his fan behavior. “But if I catch him leaving shit in the waters again…”
Danny frowned, eyes glowing. He could feel- even with his partial tangibility, the muck of Gotham's waters seeping into his boots. It was not giving 'Live, Laugh, Love' to Danny, and he needed it gone.
“Whatever. They dropped a lot of guns down here. You can deal with those too, yeah?”
“I'm pretty sure that's evidence?!”
“If you could call it that.” Danny plucked away the Styrofoam and the hazardous (more than regular, anyways) materials away from the trash pile so Spoiler could dig through with her gloves without contracting sixteen different sorts of illnesses.
“So, what brings you to Gotham?”
Danny pointed at the water. “Came for school. Stayed because you losers polluted the water with dead bodies and gross chemicals.”
“You go to school?”
“Hey, that’s discriminatory.”
“Oops! No, sorry! I meant-”
Danny waved her off, irritably separating a bottle cap from the crushed bottle. Seriously, what’s the point of putting the cap back on if you were going to throw it in the bay anyways?
“It’s fine. How else am I supposed to learn about the advancements made in the scientific industry otherwise?”
Even if Danny wasn’t too sure that science could sure stupidity, but a halfa could dream, right?
"So... do you just... listen in on lectures?"
Danny stared at her. "What else would I do in a class??"
"Oh. I just thought since you're dead and all, you'd do something more... fun?"
"I mean, I could terrorize the local villains for kicks, if that's what you meant."
Spoiler brightened. "Actually, yeah! That would be helpful! If Mr. Freeze keeps bringing the cold during my latte Thursdays, I'm gonna snap and wring his cold little chicken neck."
Danny snorted. "Alright. I will keep an eye out for this Mr. Freeze." Danny paused. "Hey, tell your friend to come down and help us."
"What- oh. Black Bat!" Stephanie waved her partner down. Black Bat gracefully slipped down towards the bay, casually knocking out two goons gunning for Spoiler.
'Careful,' Black Bat signed.
"Thanks!" Spoiler bounced on the heels of her feet. She swept an arm out. "Wanna help?"
Black Bat tilted her head and, after placing Danny under quick but thorough scrutiny, nodded.
'You can get the salvageable stuff. Anything you can't lift, leave to me.' Danny signed clumsily, placing emphasis on can't.
"You know sign language?"
"I'm not too good at it, I just learned this version."
He knew ghost-sign first, after all.
"Chop, chop. I don't have all night."
----
Danny learned that Black Bat had the skill to knock cans into their designated piles if he threw them in the air so she could kick at them.
"You two can come back anytime."
Spoiler whooped while Black Bat leaned back, smug.
"Wait, tell the litterer he owes me $200. He was short last time."
"...Are you telling me Batman owes you money?"
"Yeah. He might be in financial straights, so I gave him some lee-way."
Black Bat and Spoiler looked at each other.
----
"Hey, so guess what I learned about sea boy!"
Bruce's head swiveled to her with startling intensity. The rest of the clan tuned in.
"He knows sign language! Maybe he even knows ancient sign language! And goes to school, but since he's like, dead, he could only listen to the lectures."
"Bruce, Bruce, do not start a ghost-education plan. Stop. We don't even know if he even-" Dick tackled Bruce, who was already writing a petition as Bruce Wayne to give partial credit to students that diligently goes to class.
"Oh, yeah!" Stephanie shouted over the unraveling chaos. "He promised to fuck with our Rogues for a bit so we can get a break! And we also got a bunch of guns!"
"Where? Gimme!" Jason demanded.
"Do not give Todd more firearms!" Damian cut in.
"Also!" Stephanie grinned as Cass shook with laughter. "Batman's a debtor! He owes Phantom $200!"
"Ain't no fucking way." Tim cackled. "Hear that Bruce? That's karma! For not defending me when he called me broke!"
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