no offense but I look forward to having a healthy way of thinking and coping and living
its true that crying wont solve things but we dont cry to solve. we cry to release
Taking the lid off a pot that’s boiling too much wont solve the problem of the heat being too high, but it will release the pressure so you’ll have time to get the heat under control before everything inside the pot explodes
i love redemption arcs so much when they’re done right.
i love the concept of “i can never be forgiven this, i can never make this right, but i will spend the rest of my life trying to heal the world as much as i have hurt it.” when the characters don’t move past their mistakes or cruelty but use it as the driving force for kindness.
because i have harmed i will heal. because i have been cruel i will be kind. because i have hated needlessly i will love recklessly.
you’ve gotta stat romanticizing your life. you gotta start believing that your morning commute is cute and fun, that every cup of coffee is the best you’ve ever had, that even the smallest and most mundane things are exciting and new. you have to, because that’s when you start truly living. that’s when you look forward to every day.
live your life like a ghibli movie where literally everything is charming and beautiful
AI fears you have: Sentient and autonomous robots waging war against humans
AI fears you should have: We are literally automating systems of oppression which is amplifying systemic racism and making it more efficient. Using algorithms that target marginalized people for longer sentencing in prison, perpetuate invisible redlining, and neglect to identify people of color and disabled people as human in facial recognition software, allows people to avoid even the most basic ethical consideration or self interrogation about their role because they can allow themselves to believe programs and algorithms are “objective.”
hi I’m a therapist
some people come to me to break down severe childhood trauma
some people come to me because their job is super stressful
some people come to me because they’re worried all the time about stuff that they know they shouldn’t be worried about but they worry anyway
some people come to me because they’re bad at focusing
some people come to me because their mom said they should but they’re enjoying the experience anyway
what i’m saying is there is no wrong time, reason, or explanation to come see a therapist. we’re ready for you.
Reblogging because someone probably needs to hear this.
THIS. Please take care of yourself. You deserve it.
“I saw the sunrise for the first time in years” moves me way more than it has any right to
Oh my God this is so fucking wholesome
I got 1 task done today. I emptied the big trash can in my bedroom. That’s one less fork to deal with.
I have severe executive dysfunction. I’ve been dealing with it by having myself do one small task a day. So far it’s helped a lot. By doing it this way my brain doesn’t freak out trying to tackle everything at once.
I got my inspiration for it from this Donald Duck comic:
“It is by no means obvious that in order to be intelligent human beings have solved or needed to solve the large data base problem” - Hubert Dreyfus
In the late 60s, AI had failed to meet many of the predictions made a decade before. There were no programs discovering new mathematical theorems, or playing chess at more than a dopey amateur level, or processing more than the most rudimentary natural language – most importantly, it had not become self-learning. AI researchers remained enthusiastic, blaming the slow growth on hardware. Hubert Dreyfus, however, predicted that AI, as it was conceived then, had already hit its limits, that it was grounded in a flawed model of intelligence.
According to Dreyfus, computer scientists had unwittingly adopted a Rationalistic view of the mind dating back to Plato. A key strategy of “Good Old fashioned AI” (GOFAI), as Dreyfus called it, was to build trees of information and use search algorithms to scan across the tree to collect information: a dog is a mammal, a mammal is an animal, etc. This mimics the concept of mind that Plato had put forth: the mind holding a map of the world as we understand it, which we use to rationalize and come to an understanding of a given situation.
In Dreyfus’s “What Computers Can’t Do” (1972), he encouraged AI researchers to consider other models of the mind, including Heidegger’s concept of “thrownness.” When we want to hammer a nail, we don’t recall data about hammers, analyzing their history or associated facts; instead, we pick up an object that we barely register in a linguistic form, thinking of it only in terms of its current utility (a “driver-of-nails”). This is the difference between cognition and reasoning. Likewise, when playing a game of chess, we don’t mentally run through the 20,000 possible outcomes from a given scenario. Instead, we focus on parts of the board that feel wrong, based on our experience of playing the game – expertise lets us hone in on what’s important, rather than considering every possibility. While his critique was seen as ungenerous at the time, he was more of less proven correct: Connectionism, the statistically-based competing model of AI (then in early stages), now dominates the field.
One of the early successes of AI (in the GOFAI era) was Terry Winograd’s SHRDLU, a program where one orders an mechanical arm to manipulate differently shaped blocks in an artificial space (all of this simulated through text). SHRDLU could understand what blocks you mean by what you were saying previously, despite the fact that many blocks are identical – in other words, it could understand context. However, like many of the other early AI successes, it would not scale; adding new elements to that contained world quickly ran into a database too large to manage on hardware of the time.
By the 1980s, Winograd was one of the AI pioneers turning away from GOFAI, and he (along with fellow Stanford engineer Fernando Flores) wrote "Understanding Computers and Cognition.” A key point of Winograd and Flores is a lesson from the Speech Act Theory of Austin and Searle: language is not only (or perhaps even primarily) about the exchange of information; we speak for many reasons other than to trade data with other nodes. While this may sound obvious, it was not clear to computer scientists in the 1970s.
The classic example from Austin is the performative utterance: we can can make a promise, name a ship, etc.: make something occur in the world, rather than state something with a truth value. While this seems friendly to code (we’ve looked at Speech Act Theory previously on this blog, in terms of the performativity of the text of code), it also pushes the “exchange of information” quality of text to a secondary attribute. Drawing from Habermas, he shows how most statements are not true or false but rather felicitous or misleading, depending on the shared context of speaker and listener in terms of culture, personal history, and other factors that are not so easy to represent or evaluate in AI.
This problem of context is still relevant in AI: an “intelligent” personal assistant like Alexa can understand phrases in many different voices (a problem more easily solvable through statistical techniques) but is worse than a four-year-old child in understanding what it is we’re talking about. We have learned to speak in an absurdly specific (and often patronizing) way to get such a system to respond appropriately. If we could get Alexa to understand context better, it would perhaps overly humanize her, creating a creepy, a verbal uncanny valley.
So how is this relevant to esolangs?
As designers of programming languages, we’re building interfaces between person and machine at much more raw level than an Alexa. Here, we are even more squarely on the machine’s turf, translating our intent into discreet, logical steps. Looking at the missteps of designers working the other way, we can see the implicit assumptions about language – how we use it, why we use it, where its ambiguities lie – and it could give great material for exploring that chasm of understanding in languages that mediate between person and machine.
I hate this idea people have that if a parent walks in and turns off the tv while their kids are watching or playing something it’s evidence of some unhealthy attachment or addiction to technology if they get pissed off. If you walk up and slap a book out of my hand while I’m reading I’m going to have the same reaction, fuck off you’re not making some great social commentary you’re just being an ass hole.
If you slap a sandwich out of my hands and I get pissed it doesn’t mean I’m addicted to eating it just means I was enjoying something and then you had to be an asshole lmao
It always blows my mind how adults expect children to have more emotionally maturity than they demand of themselves.
The other day I watched a little boy get knocked to the ground by an older kid who was running by. He burst into tears as his mother hurried over.
“Here’s a bandaid for ya,” I said, producing one from my vest pocket.
“Oh, he’s not bleeding, thank you though!”
I lowered my voice and leaned in. “Kids think bandaids are health magic,” I said. “Ask him where it hurts and exploit that placebo effect.”
She did just that, and instantly the kid stopped crying and thanked her. “I’ll have to remember that,” she said.
Also if you have a crying kid give them a cup of water. You can’t cry and drink at the same time and it gives them a chance to calm down.
Tell them their going to run out of tears so they drink the water.
My mom does this at her preschool after awhile the other children start offering the crying child little cups of water.
Stuff like this is also a great test to see if the kid is actually seriously injured! Because with how much some kids cry over tiny bumps and scrapes, it can be hard to tell. But if you slap a Band-Aid on it or give them a cup of water or a piece of candy and they stop crying, they’re fine. If they keep crying despite whatever little placebo or distraction you’ve given them, you might wanna look a little closer at that injury or seek medical attention.
With my two’s class we ask them “more hurt or more scary?” It takes a bit of practice but after a few times they can answer without more prompting. More scary gets a hug and more hurt gets a look over.
That last one is so important because it validates the child’s feelings and tells them it’s okay to have these feelings and lets them learn how to deal with them, rather than just distracting them from them. I also helps teach the child to both communicate their feelings more readily and communicate when they’re hurt more clearly. All really important skills for a child to develop young.