literally all of online “stan twitter” language is just aave that’s been popularized and generalized by nonblacks to the point where black people are the ones who look out of pocket for using words we came up with because funny internet persona #23904378 wants to use “deadass” and “finna” in every other sentence
can white people please reblog this because all i see in my notes are people of color and y’all need to own up to the fact that you overuse aave as well (looking @ u white gays)
Um honestly when I read the book The Body Keeps The Score it made me realize that abuse at a young age does in fact make you susceptible to abuse in relationships when you’re older because you’re conditioned to believe this is what’s supposed to happen to you, your self esteem and self worth is completely tarnished and at best that makes way for lazy and emotionally under achieving partners and at worst absolute demons who will spend every moment hurting you and further traumatizing you.
Look, I really want to be an advocate for abuse victims especially for those in the LGBT and black community because how many times have we been led to believe that us being treated like shit is because we ‘deserved it’ or they ‘loved us’? This isn’t acceptable! This isn’t what love is supposed to be! None of us deserved this kind of thing and now that I’ve learned what I have I refuse to let others suffer through the things I’ve suffered through! It’s within our right to be treated with kindness and those who failed us should never have been allowed to set the standard of the love that we receive and give in our lifetime.
do u ever wonder abt urself from an external pov??? bc like. everyone is p complicated and contradictory on the inside, but other ppl get a very simplified version of who u r based on ur interactions w them or what they see u doin
like if i was a cartoon character, what archetype would i be? if i was a design, if i was a DESIGNED person, what parts of me would be the most cohesive/emphasized, and which less significant traits would not be perceived at all???? its just bonkers to think abt i guess
Anonymous asked: 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
This is gonna produce some absolutely baffling pornography.
…. 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.
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.
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.
