I promise this question is asked in good faith. I do not currently see the point of generative AI and I want to understand why there’s hype. There are ethical concerns but we’ll ignore ethics for the question.
In creative works like writing or art, it feels soulless and poor quality. In programming at best it’s a shortcut to avoid deeper learning, at worst it spits out garbage code that you spend more time debugging than if you had just written it by yourself.
When I see AI ads directed towards individuals the selling point is convenience. But I would feel robbed of the human experience using AI in place of human interaction.
So what’s the point of it all?
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In creative works like writing or art, it feels soulless and poor quality. In programming at best it’s a shortcut to avoid deeper learning, at worst it spits out garbage code that you spend more time debugging than if you had just written it by yourself.
I’d actually challenge both of these. The property of “soulessness” is very subjective, and AI art has won blind competitions. On programming, it’s empirically made faster by half again, even with the intrinsic requirement for debugging.
It’s good at generating things. There are some things we want to generate. Whether we actually should, like you said, is another issue, and one that doesn’t impact anyone’s bottom line directly.
To win a competition isn’t speaking to the purpose of art really, whose purpose is for communication. AI has nothing to communicate and approximates a mish mash of its dataset to mimic to great success the things it’s seen, but is ultimately meaningless in intention. It would be a disservice to muddy the art and writing out in the world created by and for human beings with a desire to communicate with algorithmic outputs with no discernible purpose.
I feel like the indistinguishability implied by this undercuts the communicative properties of the human art, no? I suppose AI might not be able to make a coherent Banksy, but not every artist is Banksy.
If you can’t tell if something was made by Unstable or Rutkowski, isn’t it fair to say either neither work has soul (or a message), or both must?
That is only if one assumes the purpose of art is its effect on the viewer which is only one purpose. Think of your favorite work of art, fiction, music, did it make you feel connected to something, another person? Imagine a lonely individual who connected with the loneliness in a musical artist’s lyrics, what would be the purpose of that artist turned out to be an algorithm?
Banksy, maybe Rutkowski, and other artists have created a distinct language (in this case visual) that an algorithm can only replicate. Consider the fact that generative AI cannot successfully generate an image of a full glass of wine, since they’re not commonly photographed.
I do think that the technology itself is interesting for those that use it in original works that are intended to be about algorithms themselves like those surreal videos, I find those really interesting. But in the case of passing off algorithmic output as original art, like that guy who won that competition with an AI generated image, or when Spotify creates algorithmically generated music, to me that’s not art.
That reminds me of the Matrix - “You know, I know this steak doesn’t exist. I know that when I put it in my mouth, the Matrix is telling my brain that it is juicy and delicious. After nine years, you know what I realise? Ignorance is bliss”
Okay, so does it matter if there’s no actual human you’re connecting to, if the connection seems just as real? We’re deep into philosophy there, and I can’t reasonably expect an answer.
If that’s the whole issue, though, I can be pretty confident it won’t change the commercial realities on the ground. The artist’s studio is then destined to be something that exists only on product labels, along with scenic mixed-animal barnyards. Cypher was unusually direct about it, but comforting lies never went out of style.
That’s kind of how I’ve interpreted OP’s original question here. You could say that’s not a “legitimate” use even if inevitable, I guess, but I basically doubt anyone wants to hear my internet rando opinion on the matter, since that’s all it would be.
Consider the fact that generative AI cannot successfully generate an image of a full glass of wine, since they’re not commonly photographed.
Okay, I have to try this. @[email protected] draw for me a glass of wine.
There was a legitimate use case in art to draw on generative AI for concepts and a stopgap for smaller tasks that don’t need to be perfect. While art is art, not every designer out there is putting work out for a gallery - sometimes it’s just an ad for a burger.
However, as time has gone on for the industry to react I think that the business reality of generative AI currently puts it out of reach as a useful tool for artists. Profit hungry people in charge will always look to cut corners and will lack the nuance of context that a worker would have when deciding when or not to use AI in the work.
But you could provide this argument about any tool given how fucked up capitalism is. So I guess that my 2c - generative AI is a promising tool but capitalism prevents it from being truly useful anytime soon.
I was asked to officiate my friend’s wedding a few months back, I’m no writer, and I wanted to do a bit better than just a generic wedding ceremony for them
So I fired up chatgpt, told it I needed a script for a wedding ceremony, described some of the things I wanted to mention, some of the things they requested, and it spit out a pretty damn good wedding ceremony. I gave it a little once over and tweaked a little bit of what it gave me but 99% of it was pretty much just straight chatgpt. I got a lot of compliments on it.
I think that’s sort of the use case. For those of us who aren’t professional writers and public speakers, who have the general idea of what we need to say for a speech or presentation but can’t quite string the words together in a polished way.
Here’s pretty much what it spit out (Their wedding was in a cave)
Cell Phone Reminder
Officiant: Before we begin, I’d like to kindly remind everyone to silence your phones and put them away for the ceremony. Groom and Bride want this moment to be shared in person, free from distractions, so let’s focus on the love and beauty of this moment.
Giving Away the Bride
And before we move forward, we have a special moment. Tradition asks: Who gives this woman to be married to this man?
[Response from Bride’s dad]
Thank you.
Greeting
Welcome, everyone. We find ourselves here in this remarkable setting—surrounded by the quiet strength of these ancient walls, a fitting place for Groom and Bride to declare their love. The cave, much like marriage, is carved out over time—through patience, care, and sometimes a little hard work. And yet, what forms is something enduring, something that stands the test of time.
Today, we’re here to witness Groom and Bride join their lives together in marriage. In this moment, we’re reminded that love is not about perfection, but about commitment—choosing one another, day after day, even when things get messy, or difficult, or dark. And through it all, we trust in love to guide us, just as God’s love guides us through life’s journey.
Declaration of Intent
[Officiant turns toward Groom and Bride]
Groom, Bride, you are about to make promises to each other that will last a lifetime. Before we continue, I’ll ask each of you to answer a very important question.
Officiant: Groom, do you take Bride to be your lawfully wedded wife, to have and to hold, for better or for worse, in sickness and in health, for as long as you both shall live?
Groom: I do.
Officiant: Bride, do you take Groom to be your lawfully wedded husband, to have and to hold, for better or for worse, in sickness and in health, for as long as you both shall live?
Bride: I do.
Exchange of Vows
Officiant: Now, as a sign of this commitment, Groom and Bride will exchange their vows—promises made not just to each other, but before all of us here and in the sight of God.
[Groom and Bride share their vows]
Rings
Officiant: The rings you’re about to exchange are a symbol of eternity, a reminder that your love, too, is without end. May these rings be a constant reminder of the vows you have made today, and of the love that surrounds and holds you both.
[Groom and Bride exchange rings]
Officiant: And now, by the power vested in me, and with the blessing of God, I pronounce you husband and wife. Groom you may kiss your bride.
[Groom and Bride kiss]
Officiant: Friends and family, it is my great honor to introduce to you, for the first time, Mr. and Mrs. [Name].
I pretty much just tweaked the formatting, worked in a couple little friendly jabs at the groom, subbed their names in for Bride and Groom, and ad-libbed a little bit where appropriate
Idea generation.
E.g., I asked an LLM client for interactive lessons for teaching 4th graders about aerodynamics, esp related to how birds fly. It came back with 98% amazing suggestions that I had to modify only slightly.
A work colleague asked an LLM client for wedding vow ideas to break through writer’s block. The vows they ended up using were 100% theirs, but the AI spit out something on paper to get them started.
Those are just ideas that were previously “generated” by humans though, that the LLM learned
Those are just ideas that were previously “generated” by humans though, that the LLM learned
That’s not how modern generative AI works. It isn’t sifting through its training dataset to find something that matches your query like some kind of search engine. It’s taking your prompt and passing it through its massive statistical model to come to a result that meets your demand.
I feel like “passing it through a statistical model”, while absolutely true on a technical implementation level, doesn’t get to the heart of what it is doing so that people understand. It’s using the math terms, potentially deliberately to obfuscate and make it seem either simpler than it is. It’s like reducing it to “it just predicts the next word”. Technically true, but I could implement a black box next word predictor by sticking a real person in the black box and ask them to predict the next word, and it’d still meet that description.
The statistical model seems to be building some sort of conceptual grid of word relationships that approximates something very much like actually understanding what the words mean, and how the words are used semantically, with some random noise thrown into the mix at just the right amounts to generate some surprises that look very much like creativity.
Decades before LLMs were a thing, the Zompist wrote a nice essay on the Chinese room thought experiment that I think provides some useful conceptual models: http://zompist.com/searle.html
Searle’s own proposed rule (“Take a squiggle-squiggle sign from basket number one…”) depends for its effectiveness on xenophobia. Apparently computers are as baffled at Chinese characters as most Westerners are; the implication is that all they can do is shuffle them around as wholes, or put them in boxes, or replace one with another, or at best chop them up into smaller squiggles. But pointers change everything. Shouldn’t Searle’s confidence be shaken if he encountered this rule?
If you see 马, write down horse.
If the man in the CR encountered enough such rules, could it really be maintained that he didn’t understand any Chinese?
Now, this particular rule still is, in a sense, “symbol manipulation”; it’s exchanging a Chinese symbol for an English one. But it suggests the power of pointers, which allow the computer to switch levels. It can move from analyzing Chinese brushstrokes to analyzing English words… or to anything else the programmer specifies: a manual on horse training, perhaps.
Searle is arguing from a false picture of what computers do. Computers aren’t restricted to turning 马 into “horse”; they can also relate “horse” to pictures of horses, or a database of facts about horses, or code to allow a robot to ride a horse. We may or may not be willing to describe this as semantics, but it sure as hell isn’t “syntax”.
Never used it until recently. Now I use it to vent because I’m a crazy person.
It has value in natural language processing, like turning unstructured natural language data into structured data. Not suitable for all situations though, like situations that cannot tolerate hallucinations.
Its also good for reorganizing information and presenting it in a different format; and also classification of semantic meaning of text. It’s good for pretty much anything dealing with semantic meaning, really.
I see people often trying to use generative AI as a knowledge store, such as asking an AI assistant factual questions, but this is an invalid usecase.
I use it to sort days and create tables which is really helpful. And the other thing that really helped me and I would have never tried to figure out on my own:
I work with the open source GIS software qgis. I’m not a cartographer or a programmer but a designer. I had a world map and wanted to create geojson files for each country. So I asked chatgpt if there was a way to automate this within qgis and sure thing it recommend to create a Python script that could run in the software, to do just that and after a few tweaks it did work. that saved me a lot of time and annoyances. Would it be good to know Python? Sure but I know my brain has a really hard time with code and script. It never clicked and likely never will. So I’m very happy with this use case. Creative work could be supported in a drafting phase but I’m not so sure about this.
If you don’t know what you are doing and ask LLMs for code then you are gonna waste time debugging it without understanding but if you are just asking it for boiler plate stuff, or are asking it to add comments and print outs to console for existing code for debugging, it’s really great for that. Sometimes it needs chastising or corrections but so do humans.
I find it very useful but not worth the environmental cost or even the monetary cost. With how enshittified Google has become now though I find that ChatGPT has become a necessary evil to find reliable answers to simple queries.
I have had some decent experiences with Copilot and coding in C#. I’ve asked it to help me figure out what was wrong with a LINQ query I was doing with an XDocument and it pointed me in the right direction where I figured it out. It also occasionally has some super useful auto complete blocks of code that actually match the pattern of what I’m doing.
As for art and such, sometimes people just want to see some random bizarre thing realized visually that they don’t have the ability (or time/dedication) to realize themselves and it’s not something serious that they would be commissioning an artist for anyway. I used Bing image creator recently to generate a little character portrait for an online DND game I’m playing in since I couldn’t find quite what I was looking for with an image search (which is what I usually do for those).
I’ve seen managers at my job use it to generate fun, relevant imagery for slideshows that otherwise would’ve been random boring stock images (or just text).
It has actual helpful uses, but every major corporation that has a stake in it just added to or listened to the propaganda really hard, which has caused problems for some people; like the idiot who proudly fired all of his employees because he replaced all their jobs with automation and AI, then started hunting for actual employees to hire again a couple months later because everything was terrible and nothing worked right.
They’re just tools that can potentially aid people, but they’re terrible replacements for actual people. I write automated tests for a living, and companies will always need people for that. If they fired me and the other QAs tomorrow, things would be okay for a short while thanks to the automation we’ve built, but as more and more code changes go into our numerous and labyrinthine systems, more and more bugs would get through without someone to maintain the automation.
Documentation work, synthesis, sentiment analysis
Video generators are going to eat Hollywood alive. A desktop computer can render anything, just by feeding in a rough sketch and describing what it’s supposed to be. The input could be some kind of animatic, or yourself and a friend in dollar-store costumes, or literal white noise. And it’ll make that look like a Pixar movie. Or a photorealistic period piece starring a dead actor. Or, given enough examples, how you personally draw shapes using chalk. Anything. Anything you can describe to the point where the machine can say it’s more [thing] or less [thing], it can make every frame more [thing].
Boring people will use this to churn out boring fluff. Do you remember Terragen? It’s landscape rendering software, and it was great for evocative images of imaginary mountains against alien skies. Image sites banned it, by name, because a million dorks went ‘look what I made!’ and spammed their no-effort hey-neat renders. Technically unique - altogether dull. Infinite bowls of porridge.
Creative people will use this to film their pet projects without actors or sets or budgets or anyone else’s permission. It’ll be better with any of those - but they have become optional. You can do it from text alone, as a feral demo that people think is the whole point. The results are massively better from even clumsy effort to do things the hard way. Get the right shapes moving around the screen, and the robot will probably figure out which ones are which, and remove all the pixels that don’t look like your description.
The idiots in LA think they’re gonna fire all the people who write stories. But this gives those weirdos all the power they need to put the wild shit inside their heads onto a screen in front of your eyeballs. They’ve got drawers full of scripts they couldn’t hassle other people into making. Now a finished movie will be as hard to pull off as a decent webcomic. It’s gonna get wild.
And this’ll be great for actors, in ways they don’t know yet.
Audio tools mean every voice actor can be a Billy West. You don’t need to sound like anything, for your performance to be mapped to some character. Pointedly not: “mapped to some actor.” Why would an animated character have to sound like any specific person? Do they look like any specific person? Does a particular human being play Naruto, onscreen? No. So a game might star Nolan North, exclusively, without any two characters really sounding alike. And if the devs need to add a throwaway line later, then any schmuck can half-ass the tone Nolan picked for little Suzy, and the audience won’t know the difference. At no point will it be “licensing Nolan North’s voice.” You might have no idea what he sounds like. He just does a very convincing… everybody.
Video tools will work the same way for actors. You will not need to look like anything, to play a particular character. Stage actors already understand this - but it’ll come to movies and shows in the form of deep fakes for nonexistent faces. Again: why would a character have to look like any specific person? They might move like a particular actor, but what you’ll see is somewhere between motion-capture and rotoscoping. It’s CGI… ish. And it thinks perfect photorealism is just another artistic style.
What doesn’t exist yet, but is obviously possible, is automatic tweening. Human animators spend a lot of time drawing the drawings between other drawings. If they could just sketch out what’s going on, about once per second, they could probably do a minute in an hour. This bullshit makes that feasible.
We have the technology to fill in crisp motion at whatever framerate the creator wants. If they’re unhappy with the machine’s guesswork, they can insert another frame somewhere in-between, and the robot will reroute to include that instead.
We have the technology to let someone ink and color one sketch in a scribbly animatic, and fill that in throughout a whole shot. And then possibly do it automatically for all labeled appearances of the same character throughout the project.
We have the technology to animate any art style you could demonstrate, as easily as ink-on-celluloid outlines or Phong-shaded CGI.
Please ignore the idiot money robots who are rendering eye-contact-mouth-open crowd scenes in mundane settings in order to sell you branded commodities.
For the 99% of us who don’t know what tweening is and were scared to Google it in case it was perverted, it’s short for in-betweening and means the short frames of an animation in-between two main scenes
Have you seen this? There was another paper, but I can’t remember the name of it right now.
I had not. There’s a variety of demos for guessing what comes between frames, or what fills in between lines… because those are dead easy to train from. This technology will obviously be integrated into the process of animation, so anything predictable Just Works, and anything fucky is only as hard as it used to be.
I think this is the other one I remember seeing.
I think LLMs could be great if they were used for education, learning and trained on good data. The encyclopedia Britannica is building an AI exclusively trained on its data.
It also allows for room for writers to add more to the database, to provide broader knowledge for the AI, so people keep their jobs.
I’d say there are probably as many genuine use-cases for AI as there are people in denial that AI has genuine use-cases.
Top of my head:
- Text editing. Write something (e.g. e-mails, websites, novels, even code) and have an LLM rewrite it to suit a specific tone and identify errors.
- Creative art. You claim generative AI art is soulless and poor quality, to me, that indicates a lack of familiarity with what generative AI is capable of. There are tools to create entire songs from scratch, replace the voice of one artist with another, remove unwanted background noise from songs, improve the quality of old songs, separate/add vocal tracks to music, turn 2d models into 3d models, create images from text, convert simple images into complex images, fill in missing details from images, upscale and colourise images, separate foregrounds from backgrounds.
- Note taking and summarisation (e.g. summarising meeting minutes or summarising a conversation or events that occur).
- Video games. Imagine the replay value of a video game if every time you play there are different quests, maps, NPCs, unexpected twists, and different puzzles? The technology isn’t developed enough for this at the moment, but I think this is something we will see in the coming years. Some games (Skyrim and Fallout 4 come to mind) have a mod that gives each NPC AI generated dialogue that takes into account the NPC’s personality and history.
- Real time assistance for a variety of tasks. Consider a call centre environment as one example, a model can be optimised to evaluate calls based on language and empathy and correctness of information. A model could be set up with a call centre’s knowledge base that listens to the call and locates information based on a caller’s enquiry and tells an agent where the information is located (or even suggests what to say, though this is currently prone to hallucination).
