When will I be free, tell me

A Glambert, shameless TV addict, bookaholic, music lover.  Tumblr Theme: Magnusthemes' Daybreak

[animalsnaps]

More animal snaps

[bob-belcher]

Crazy Rich Asians (2018) dir. Jon M. Chu

[thcrin]

Crazy Rich Asians | dir. Jon Chu

[babyanimalgifs]

Animal snaps 

(#2 @ellietiny)

[babyanimalgifs]

Don’t even talk to me hooman!

[icryalittle]

Finally got hit with the tumblr adult content violation, on a fanart someone else did, that has two shirtless guys... Tumblr pls fix your broken as fuck system.

[chuuzus]

It’s the 10 year anniversary of 2009…

[manfuckyopride]

[veliseraptor]

okay but I did not know that there is a story about f. scott fitzgerald nervously showing ernest hemingway his penis because zelda said he couldn’t satisfy a woman with it and ernest hemingway was like “lol no dude you’re fine”

what are the modernists even

[seagodofmagic]

the best part of that story in context is that before they pull out their dicks, hemingway spends the better part of a chapter physically describing fitzgerald in great detail, claiming to be grossed out by him but obviously, obviously uncomfortably attracted

[veliseraptor]

oh my god, it got better. I just went to find an excerpt and

Scott was a man then who looked like a boy with a face between handsome and pretty. He had very fair wavy hair, a high forehead, excited and friendly eyes and a delicate long-lipped Irish mouth that, on a girl, would have been the mouth of a beauty. His chin was well built and he had good ears and a handsome, almost beautiful, unmarked nose. This should not have added up to a pretty face, but that came from the coloring, the very fair hair and the mouth. The mouth worried you until you knew him and then it worried you more.

ernest hemingway calm down and control your thirst a little

[flatluigi]

“The mouth worried you until you knew him and then it worried you more“ is a hell of a line 

[fozmeadows]

No Homo: A Literary Masterpiece

[rhapeseuhans]

Pokémon AU where Viktor (Beauty) and Yuuri (Cute) are Pokémon Coordinators, but they don’t compete against each other because they  aimed for different ribbons. 

They are already married, and always use coordinated outfits (Viktor’s idea obviously).

Viktor’s pokémon Shiny Altaria (♀), Smoochum (♀), Makkachin [Stoutland] (♂)

Yuuri’s pokémon Shiny Sylveon (♀), Vicchan [Lillipup] (♂), Gardevoir (♂)

((I gave them pokémon based over their personalities.))

[rhapeseuhans]

A Pokémon AU where Viktor and Yuuri are both Pikachu who met in the Pokémon Day Care, and Viktor is often confused with a female pikachu because of his heart-shaped tail, so people don’t understand why they haven’t had eggs if they spend so much time together x'DDD

Yuuri’s trainer and Viktor’s trainer tried to separed them when they realized they’re both were male (because no eggs) but they weren’t able to do it, so they abandoned them in the Day Care until Yurio adopted them…They are powerful but very usuless when get distrated to each other. Yurio sometimes regret it (not really x’D) <3

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[foodffs]

I’m dying over these ads 😹

[foodffs]

Wtf.

[foodffs]

Terminate innocent blogs ✅

Ban “adult” content ✅

Advertise pornographic production company ✅

Good job, Tumblr.

[foodffs]

Oh ffs.

[foodffs]

Omfg my post about search not working is now flagged as nsfw.

[linecrosser]

becoming undone

[surfacage]

blocked

[icryalittle]

So many ads wtf, it’s like there’s an ad every two/three posts.

[friendly-animals]

(Source)

[lauralot89]

Once, I encountered the funny story of an AI image descriptor with a sheep obsession. It had been trained on pictures of fields of sheep. Therefore, it tagged anything in a field as 'sheep', including an empty field, because they work on statistical probability. Therefore, it thinks "ah, a field! there's probably a sheep here." (It's a bit more complicated but basically that.) It also couldn't recognise sheep in places that weren't fields, such as petrol stations or barns. [cont]

Now, the alarming aspect of this story is that the very same technology is probably what tumblr is using to identify porn. Now, if it can’t tell that an empty field is not, in fact, full of sheep, what hope do we have that it can’t tell an empty room isn’t full of writing human forms engaged in passionate coitus?

this really does sound like an episode of black mirror

[architeuthism]

But wait, it’s even weirder than that!

[retroactivebakeries]

This is gonna produce some absolutely baffling pornography.

[crazy-pages]

…. oh my fucking god they actually are using open source software. They’re using a fucking one-layer unidirectional bicategory tag-trained neural network. This will never work. Literally, it will never work. There’s just not enough algorithmic complexity to do what they’re asking of it. I bet you I could prove on a mathematical level that this joke of a neural net fundamentally lacks the abstraction necessary to do its job.

This will never get better. Their algorithm will never stop fucking up, it will never actually flag porn reliably and it will always require a massive quantity of human hours to deal with the deluge of mistagged pictures. This isn’t just a case of an insufficiently trained algorithm, it’s just … this is the most basic neural network you can make. It probably hasa a lot of neurons and has loads of training data but like … you can’t just brute force this kind of stuff. One layer of neurons is just Not Enough.

[crazy-pages]

Also, just to make this clear, Tumblr lied. I mean, we already know this, but I mean they liiiieeeeed. All that stuff they promised about what would or would not be censored? That cannot be delivered on with a system this simple. Nude classical sculptures, political protests, male-presenting nipples (really Tumblr?), nude art outside the context of sex, all that? You cannot train a bicategory one-layer neural network to exclude those things. It cannot be done. Tumblr never intended for those things to actually be permitted, they were just lying. Because the system they have cannot actually do what they said it would and never will be able to.

Also, this kind of system is super vulnerable to counter-neural strategies. I bet you before the end of the month someone hooks up their own open source one layer bicategory neural network which puts an imperceptible (to humans) layer of patterned static over arbitrary images, and trains it by having it bot-post static-ed images to Tumblr and reinforcing based on whether the images are labeled nsfw or sfw. Seriously, within a month someone will have an input-output machine which can turn any image ‘sfw’ in Tumblr’s eyes.

This is genuinely pathetic. Like, I have real pity for whoever implemented this, because it’s clear Tumblr doesn’t actually have any engineers with any expertise with machine learning left at all and they foisted the job off on some poor bastard who has no idea what they’re doing and is going to get all kinds of flak for their (perfectly reasonable and predetermined) failure from management.

[garbage-empress]

As has been pointed out before, there are no humans behind this at all. The review process just reruns either the same algorithm or another algorithm, but people have posted screen shots showing obviously SFW pictures that were still deemed NSFW on review, despite the fact that any human, no matter how overworked / tired would have seen that these pictures were not porn.

[dancing-coyote]

And to think people actually believed staff when they said they were implementing “cutting edge technology” to root out the evil female nipples e.e

[bideogaymes]

me in a meme.