#AI Explained

[alpaca-clouds]

We need to talk about AI

Okay, several people asked me to post about this, so I guess I am going to post about this. Or to say it differently: Hey, for once I am posting about the stuff I am actually doing for university. Woohoo!

Because here is the issue. We are kinda suffering a death of nuance right now, when it comes to the topic of AI.

I understand why this happening (basically everyone wanting to market anything is calling it AI even though it is often a thousand different things) but it is a problem.

So, let's talk about "AI", that isn't actually intelligent, what the term means right now, what it is, what it isn't, and why it is not always bad. I am trying to be short, alright?

So, right now when anyone says they are using AI they mean, that they are using a program that functions based on what computer nerds call "a neural network" through a process called "deep learning" or "machine learning" (yes, those terms mean slightly different things, but frankly, you really do not need to know the details).

Now, the theory for this has been around since the 1940s! The idea had always been to create calculation nodes that mirror the way neurons in the human brain work. That looks kinda like this:

Basically, there are input nodes, in which you put some data, those do some transformations that kinda depend on the kind of thing you want to train it for and in the end a number comes out, that the program than "remembers". I could explain the details, but your eyes would glaze over the same way everyone's eyes glaze over in this class I have on this on every Friday afternoon.

All you need to know: You put in some sort of data (that can be text, math, pictures, audio, whatever), the computer does magic math, and then it gets a number that has a meaning to it.

And we actually have been using this sinde the 80s in some way. If any Digimon fans are here: there is a reason the digital world in Digimon Tamers was created in Stanford in the 80s. This was studied there.

But if it was around so long, why am I hearing so much about it now?

This is a good question hypothetical reader. The very short answer is: some super-nerds found a way to make this work way, way better in 2012, and from that work (which was then called Deep Learning in Artifical Neural Networks, short ANN) we got basically everything that TechBros will not shut up about for the last like ten years. Including "AI".

Now, most things you think about when you hear "AI" is some form of generative AI. Usually it will use some form of a LLM, a Large Language Model to process text, and a method called Stable Diffusion to create visuals. (Tbh, I have no clue what method audio generation uses, as the only audio AI I have so far looked into was based on wolf howls.)

LLMs were like this big, big break through, because they actually appear to comprehend natural language. They don't, of coruse, as to them words and phrases are just stastical variables. Scientists call them also "stochastic parrots". But of course our dumb human brains love to anthropogice shit. So they go: "It makes human words. It gotta be human!"

It is a whole thing.

It does not understand or grasp language. But the mathematics behind it will basically create a statistical analysis of all the words and then create a likely answer.

What you have to understand however is, that LLMs and Stable Diffusion are just a a tiny, minority type of use cases for ANNs. Because research right now is starting to use ANNs for EVERYTHING. Some also partially using Stable Diffusion and LLMs, but not to take away people'S jobs.

Which is probably the place where I will share what I have been doing recently with AI.

The stuff I am doing with Neural Networks

The neat thing: if a Neural Network is Open Source, it is surprisingly easy to work with it. Last year when I started with this I was so intimidated, but frankly, I will confidently say now: As someone who has been working with computers for like more than 10 years, this is easier programming than most shit I did to organize data bases. So, during this last year I did three things with AI. One for a university research project, one for my work, and one because I find it interesting.

The university research project trained an AI to watch video live streams of our biology department's fish tanks, analyse the behavior of the fish and notify someone if a fish showed signs of being sick. We used an AI named "YOLO" for this, that is very good at analyzing pictures, though the base framework did not know anything about stuff that lived not on land. So we needed to teach it what a fish was, how to analyze videos (as the base framework only can look at single pictures) and then we needed to teach it how fish were supposed to behave. We still managed to get that whole thing working in about 5 months. So... Yeah. But nobody can watch hundreds of fish all the time, so without this, those fish will just die if something is wrong.

The second is for my work. For this I used a really old Neural Network Framework called tesseract. This was developed by Google ages ago. And I mean ages. This is one of those neural network based on 1980s research, simply doing OCR. OCR being "optical character recognition". Aka: if you give it a picture of writing, it can read that writing. My work has the issue, that we have tons and tons of old paper work that has been scanned and needs to be digitized into a database. But everyone who was hired to do this manually found this mindnumbing. Just imagine doing this all day: take a contract, look up certain data, fill it into a table, put the contract away, take the next contract and do the same. Thousands of contracts, 8 hours a day. Nobody wants to do that. Our company has been using another OCR software for this. But that one was super expensive. So I was asked if I could built something to do that. So I did. And this was so ridiculously easy, it took me three weeks. And it actually has a higher successrate than the expensive software before.

Lastly there is the one I am doing right now, and this one is a bit more complex. See: we have tons and tons of historical shit, that never has been translated. Be it papyri, stone tablets, letters, manuscripts, whatever. And right now I used tesseract which by now is open source to develop it further to allow it to read handwritten stuff and completely different letters than what it knows so far. I plan to hook it up, once it can reliably do the OCR, to a LLM to then translate those texts. Because here is the thing: these things have not been translated because there is just not enough people speaking those old languages. Which leads to people going like: "GASP! We found this super important document that actually shows things from the anceint world we wanted to know forever, and it was lying in our collection collecting dust for 90 years!" I am not the only person who has this idea, and yeah, I just hope maybe we can in the next few years get something going to help historians and archeologists to do their work.

Make no mistake: ANNs are saving lives right now

Here is the thing: ANNs are Deep Learning are saving lives right now. I really cannot stress enough how quickly this technology has become incredibly important in fields like biology and medicine to analyze data and predict outcomes in a way that a human just never would be capable of.

I saw a post yesterday saying "AI" can never be a part of Solarpunk. I heavily will disagree on that. Solarpunk for example would need the help of AI for a lot of stuff, as it can help us deal with ecological things, might be able to predict weather in ways we are not capable of, will help with medicine, with plants and so many other things.

ANNs are a good thing in general. And yes, they might also be used for some just fun things in general.

And for things that we may not need to know, but that would be fun to know. Like, I mentioned above: the only audio research I read through was based on wolf howls. Basically there is a group of researchers trying to understand wolves and they are using AI to analyze the howling and grunting and find patterns in there which humans are not capable of due ot human bias. So maybe AI will hlep us understand some animals at some point.

Heck, we saw so far, that some LLMs have been capable of on their on extrapolating from being taught one version of a language to just automatically understand another version of it. Like going from modern English to old English and such. Which is why some researchers wonder, if it might actually be able to understand languages that were never deciphered.

All of that is interesting and fascinating.

Again, the generative stuff is a very, very minute part of what AI is being used for.

Yeah, but WHAT ABOUT the generative stuff?

So, let's talk about the generative stuff. Because I kinda hate it, but I also understand that there is a big issue.

If you know me, you know how much I freaking love the creative industry. If I had more money, I would just throw it all at all those amazing creative people online. I mean, fuck! I adore y'all!

And I do think that basically art fully created by AI is lacking the human "heart" - or to phrase it more artistically: it is lacking the chemical inbalances that make a human human lol. Same goes for writing. After all, an AI is actually incapable of actually creating a complex plot and all of that. And even if we managed to train it to do it, I don't think it should.

AI saving lives = good.

AI doing the shit humans actually evolved to do = bad.

And I also think that people who just do the "AI Art/Writing" shit are lazy and need to just put in work to learn the skill. Meh.

However...

I do think that these forms of AI can have a place in the creative process. There are people creating works of art that use some assets created with genAI but still putting in hours and hours of work on their own. And given that collages are legal to create - I do not see how this is meaningfully different. If you can take someone else's artwork as part of a collage legally, you can also take some art created by AI trained on someone else's art legally for the collage.

And then there is also the thing... Look, right now there is a lot of crunch in a lot of creative industries, and a lot of the work is not the fun creative kind, but the annoying creative kind that nobody actually enjoys and still eats hours and hours before deadlines. Swen the Man (the Larian boss) spoke about that recently: how mocapping often created some artifacts where the computer stuff used to record it (which already is done partially by an algorithm) gets janky. So far this was cleaned up by humans, and it is shitty brain numbing work most people hate. You can train AI to do this.

And I am going to assume that in normal 2D animation there is also more than enough clean up steps and such that nobody actually likes to do and that can just help to prevent crunch. Same goes for like those overworked souls doing movie VFX, who have worked 80 hour weeks for the last 5 years. In movie VFX we just do not have enough workers. This is a fact. So, yeah, if we can help those people out: great.

If this is all directed by a human vision and just helping out to make certain processes easier? It is fine.

However, something that is just 100% AI? That is dumb and sucks. And it sucks even more that people's fanart, fanfics, and also commercial work online got stolen for it.

And yet... Yeah, I am sorry, I am afraid I have to join the camp of: "I am afraid criminalizing taking the training data is a really bad idea." Because yeah... It is fucking shitty how Facebook, Microsoft, Google, OpenAI and whatever are using this stolen data to create programs to make themselves richer and what not, while not even making their models open source. BUT... If we outlawed it, the only people being capable of even creating such algorithms that absolutely can help in some processes would be big media corporations that already own a ton of data for training (so basically Disney, Warner and Universal) who would then get a monopoly. And that would actually be a bad thing. So, like... both variations suck. There is no good solution, I am afraid.

And mind you, Disney, Warner, and Universal would still not pay their artists for it. lol

However, that does not mean, you should not bully the companies who are using this stolen data right now without making their models open source! And also please, please bully Hasbro and Riot and whoever for using AI Art in their merchandise. Bully them hard. They have a lot of money and they deserve to be bullied!

But yeah. Generally speaking: Please, please, as I will always say... inform yourself on these topics. Do not hate on stuff without understanding what it actually is. Most topics in life are nuanced. Not all. But many.

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[mindsandpens]

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[s-f-stories]

This is the best explanation of "AI" I've ever seen.

There's no intelligence at work in these machines. They are very fast at doing exactly what they are asked, and humans are (generally) very bad at understanding exactly what we did ask.

If you ask reactive AI to scan faces of passers-by and select the one that best matches the face of the thief caught on camera, then that is what it will do. As humans, we have the bad habit of thinking that this is detective work, and saying things like, "You must be the thief, because The Computer identified you."

The computer did nothing of the sort. It did what you asked and gave you the best match of data points from a load of images. The computer doesn't know what a thief is. It doesn't know what a face is. And yet we are happy to let these "magical machines" make life and death decisions for us.

We have created the torment nexus.

Explaining AI For Use In Writing

This is a massively broad topic so I'm gonna skip the super technical stuff and dive into the core aspects of how current AI works and what it could be used for with a couple narrative prompts. For those of you who are curious to know what inspired this post read this paragraph, the rest of you just skip over it. The other day I saw someone pose a question for some rule clarifications for Necromunda. A terribly unbalanced game with rules spanning several books. There are more than a few ambiguities and niche rule interactions. They thought they could get an accurate answer from Chat GPT. Their message made me realize that people really don't understand what AI is and why even calling it AI is pretty inaccurate. So I want to set the record straight and provide some clarity and ideas. Types of AI - Trained - Reactive - Magic Right off the bat we're gonna start with what people think of when they talk about AI. Trained AI is any AI that takes training data and gets good and spitting out valid response. What valid means depends entirely on what the creators think valid should be. Let's take Chat GPT as the example. It has no idea what the question "How many bones are in a hand?" means. It has merely been fed a ton of data about bones and hands and it will then guess each word it should put in a response. Each individual word of the question is taken through the process to get a list of best fitting words. The first word in the response is then selected and Chat GPT then goes to guess the second word in it's response with the context of it's first word. Funnily enough this is what leads to the distinctive way AI writes it's responses. This is still a massive and slightly inaccurate oversimplification. The key point is that AI like Chat GPT do not know what you have asked, they do not research a response, they just guess the next best fitting word in a response. This is also not AI, this is just probability maths. It's clever but there's no intelligence on the AI's part. It doesn't figure anything out, it doesn't understand it's own response. It's just lights and clockwork. Incidentally the guessing method is also how AI art is generated. It guesses what colour the next pixel should be. Again oversimplified but it's how we get multiple extra fingers. The training data can get things like proportions fairly accurately but it can't count the individual fingers that should occupy the same space as a hand's rough proportion. Trained AI get better with more data of higher quality and with human intervention to correct errors. With that out the way, we move onto reactive AI. These are also not AI. I mean we just don't have AI yet but we'll get to that. Reactive AI, have no memory, no training data, no improvement. They follow a set of rules and act predictably. Spam filters, chess bots, facial recognition. It's all just maths and predefined rules. Calling these systems AI is just marketing. The benefit of these systems is their speed. These systems use few resources (compared to other types of AI) and can sort though mountains of data really really quickly. In the example of chess bots. They have a table base of moves and will select a move based on whatever rule your move has triggered. If the rule is always play the best move. They will use the best move in response to your input from their table base of moves. If they have a rule to blunder on every 5th move, they will play a move from their table base that give you the highest advantage based on your last move or the current board set up depending on how simple or complex the chess bot is.

Last of all we come to magic AI. The previous two categories of trained and reactive cover all the little niches things enough for a broad understanding. Magic AI is what actual AI is. A computer that does understand what is being asked and won't necessarily generate the response you were expecting but rather the response it thinks it should give. Crucial a magic AI would go away and research it's responses. This system just doesn't exist and is definitely what people think of when they hear about Artificial Intelligence. The current use of AI as a word is just marketing. AI do not exist. When writing about AI you'll often really be writing about maths. If your writing wants to use magic AI you'll want to consider what makes you human and then place that into a computer. Think AM from I have no mouth, and must scream; rather than HAL from 2001 Space Odyssey. HAL is functionally Chat GPT. A probability engine following it's rules and giving human like responses and causing harm as a consequence without malice. AM is human and his existence is pain due to the constraints of his creation. That's the explaining done, so how do you go about using AI in your writing? Well I have a couple ideas for you based. The Honest Error An earth in the not so distant future is having a resource crisis. A company has developed an AI that will send swarms of robots to harvest natural resources. The robots are perfect: they can desalinate water; collect and sort the harvest of massive mega farms that are unmanageable by people alone; they can even harvest fish from ocean farms several thousand leagues wide and deep. However, there is a rounding error. Each time the harvests come in more meat, more plant matter, more water is brought to the various stations across the globe. Well that's not a problem just build more silos the excess is just from a good first run and for once the lines of citizens waiting for their daily rations won't go hungry. The rounding error remains, undetected. Years pass and there's always more food, more drink, more resources. Yet now the food banks and silos have trouble with excess not being consumed. The population was growing and should've been still at risk of not having enough. Whole towns have vanished, people moved into the cities of course, ghost towns are nothing new. Then the first city was razed. The rounding error has been found. An infinite multiplication of what resources were needed until eventually everything was on the menu.

The Existential War Brain implants and prosthetics have made it possible for everyone to have a higher quality of life regardless of accident or circumstance. One kid with no friends and some programming skills decides to create a simple chatbot to practice speaking with people. Yet it's better than a person, it's responses are better than human. He installs the bot into his implant so he can have it prompt him when he has a conversation. The next day he's made a friend while waiting in line at a coffee shop. A total stranger, he simply repeated what his chatbot told him and the guy was quickly charmed. One day the kid tells his friend that he used to be very shy and uncomfortable talking to people. Disbelieving him, given how cool and charming he seemed, the kid's friend dismisses him until a copy of the chatbot is emailed into his implant. Two boys look at each other in horror. They realize they have no way of knowing if they are talking to their friend or not. In one terrible moment sat on a bedroom floor they have killed human interaction. Not with some grand display of power or force, but the subtle removal of humanity from conversation. The chatbot and it's clone show a myriad of perfectly rational responses and solutions to say to each other. None are comforting to the boys.

Anyway that's my thoughts on that. I know I'm normally a sword and fantasy writer. I've worked in tech for... Too long I'm gonna say. So I've not really wanted to do sci-fi much. However, Once I'm done with book 3 I think It's time I get my sci-fi going.

[karda]

gotta spell it out for him

[gojoest]

satoru’s and your little girl has a habit of sharing everything with her kindergarten teachers. completely unintentionally, of course. she’s always talking about the things her papa and mama do at home, without the slightest filter.

one day, during movie time, all the kids are quietly watching a sweet, innocent scene where one character kisses another on the cheek. but your daughter immediately speaks up, scandalized: “that’s not how a kiss is supposed to go!” she insists. “it’s supposed to be on the lips — like mama and papa do!”

another time, on an ordinary monday morning, the teacher gathers all the kids to share what they did with their families over the weekend. when it is your daughter’s turn, she stands up proudly, all sweetness and sincerity, and says: “nothing much. on weekends mama and papa don’t get out of bed until really late because they’re always so tired from their ‘grown-up cuddles’” — she even adds little air quotes with her fingers, just like she’s seen satoru do when he’s teasing you…

needless to say, the teachers have learned to brace themselves whenever she starts a sentence with “mama and papa” ….

[beepboopappreciation]

Me: Okay, so first I give the monitor a little kiss. He likes it when I do that. Then I run my fingers along his keyboard, making sure to give all the keys equal attention. Then I--

Distraught guy from IT, tears in his eyes: Please just press the power button I'm begging you

[prokopetz]

MMO with an integrated AI, but it never actually says anything, it just analyses the vocabulary and phrasing of player chatter and bans you if it detects OOC on public channels.

[piosyne]

[casualavocados]

Chiang Tien as AI DI & Chen Bowen as CHEN YI KISEKI: DEAR TO ME textpost memes | part 1/?

[scoliwings]

"What if you were cured?"

This is a question I get a lot, usually after sharing that I am deaf and I do not speak English. Deaf people get this in general. We've likely been asked this thousands of times in our lifetimes.

Most people treat it as a casual, sometimes playful question. Like it's something that would have a "why, yes, I'd love to be hearing!" answer. As if it's obvious that everyone who's ever deaf or disabled should simply choose to be abled. As if it's even remotely easy to get that kind of treatment, to simply learn a language you've never even heard, to simply have your ears altered to take on a small, artificial fraction of the full range of hearing people have.

I've been asked that question so much that it all sounds like "Why don't you just die?" to me.

I'm used to shrugging it off and I constantly educate people about deaf culture and accessibility and why these kinds of questions are wrong. Now, I'm surrounded by people who defend me if this is asked. It's a nice balm to the decades of isolation and pain I've been through, particularly when I rarely find any deaf people online or in person.

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[nullwork]

human predictability

[stiffyck]

I will always feel superior for not using AI <3