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?
Here’s some uses:
- skin cancer diagnoses with llms has a high success rate with a low cost. This is something that was starting to exist with older ai models, but llms do improve the success rate. source
- VLC recently unveiled a new feature of using ai to generate subtitles, i haven’t used it but if it delivers then it’s pretty nice
- for code generation, I agree it’s more harmful than useful for generating full programs or functions, but i find it quite useful as a predictive text generator, it saves a few keystrokes. Not a game changer but nice. It’s also pretty useful at generating test data so long as it’s hard to create but easy (for a human) to validate.
I have a friend with numerous mental issues who texts long barely comprehensible messages to update me on how they are doing, like no paragraphs, stream of consciousness style… and so i take those walls of text and tell chat gpt to summarize it for me, and it goes from a mess of words into an update i can actually understand and respond to.
Another use for me is getting quick access to answered id previously have to spend way more time reading and filtering over multiple forums and stack exchanges posts to answer.
Basically they are good at parsing information and reformatting it in a way that works better for me.
I have a very good friend who is brilliant and has slogged away slowly shifting the sometimes-shitty politics of a swing state’s drug and alcohol and youth corrections policies from within. She is amazing, but she has a reading disorder and is a bit neuroatypical. Social niceties and honest emails that don’t piss her bosses or colleagues off are difficult for her. She jumped on ChatGPT to write her emails as soon is it was available, and has never looked back. It’s been a complete game changer for her. She no longer spends hours every week trying to craft emails that strike that just-right balance. She uses that time to do her job, now.
I hope it pluralizes ‘email’ like it does ‘traffic’ and not like ‘failure’.
I need help getting started. I’m not an idea person. I can make anything you come up with but I can’t come up with the ideas on my own.
I’ve used it for an outline and then I rewrite it with my input.
Also, I used it to generate a basic UI for a project once. I struggle with the design part of programming so I generated a UI and then drew over the top of the images to make what I wanted.
I tried to use Figma but when you’re staring at a blank canvas it doesn’t feel any better.
I don’t think these things are worth the cost of AI ( ethically, financially, socially, environmentally, etc). Theoretically I could partner with someone who is good at that stuff or practice till I felt better about it.
i’ve written bots that filter things for me, or change something to machine-readable formats
the most successful thing i’ve done is have a bot that parses a web page and figures out the date/time in standard format, gets a location if it’s listed in the description and geocodes it, and a few other fields to make an ical for pretty much any page
i think the important thing is that gen ai is good at low risk tasks that reduce but don’t eliminate human effort - changing something from having to do a bunch of data entry to skimming for correctness
“at worst it spits out garbage code that you spend more time debugging than if you had just written it by yourself.”
I’ve not experienced this. Debugging for me is always faster than writing something entirely from scratch.
100% agree with this.
It is so much faster for me to give the ai the api/library documentation than it would be for me to figure out how that api works. Is it a perfect drop-in, finished piece of code? No. But that is not what I ask the ai for. I ask it for a simple example which I can then take, modify, and rework into my own code.
I generate D&D characters and NPCs with it, but that’s not really a strong argument.
For programming though it’s quite handy. Basically a smarter code completion that takes the already written stuff into account. From machine code through assembly up to higher languages, I think it’s a logical next step to be able to tell the computer, in human language, what you actually are trying to achieve. That doesn’t mean it is taking over while the programmer switches off their brain of course, but it already saved me quite some time.
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. @aihorde@lemmy.dbzer0.com draw for me a glass of wine.
I like using it to help get the ball rolling on stuff and organizing my thoughts. Then I do the finer tweaking on my own. Basically I kinda use a sliding scale of the longer it takes me to refine an AI output for smaller and smaller improvements is what determines when I switch to manual.
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.
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.
Fake frames. Nvidia double benefits.
Note: Tis a joke, personally I think DLSS frame generation is cool, as every frame is “fake” anyway.
AI saves time. There are few use cases for which AI is qualitatively better, perhaps none at all, but there are a great many use cases for which it is much quicker and even at times more efficient.
I’m sure the efficiency argument is one that could be debated, but it makes sense to me in this way: for production-level outputs AI is rarely good enough, but creates really useful efficiency for rapid, imperfect prototyping. If you have 8 different UX ideas for your app which you’d like to test, then you could rapidly build prototype interfaces with AI. Likely once you’ve picked the best one you’ll rewrite it from scratch to make sure it’s robust, but without AI then building the other 7 would use up too many man-hours to make it worthwhile.
I’m sure others will put forward legitimate arguments about how AI will inevitably creep into production environments etc, but logistically then speed and efficiency are undeniably helpful use cases.
As some witty folks have put it, LLMs can’t give you anything truly, interestingly new when all they’re capable of is some weighted average of what’s already there. And I’ll be clear in saying I hate with the force of a tsunami the way AI is being shoved at us by desperate CEOs, and how it’s being used to kill labor, destroy copyright law, increase income inequality, destroy the environment, and increase the power of huge corporations headed by assholes like Altman and Musk. But AI is getting pretty good at that weighted-average-of-what’s-out-there, and a lot of the work done in several industries can benefit from that. For me, one of the great perversities or tragedies of AI is that it could be a targeted, useful tool but, instead, it’s a hammer to further erode freedom. Even the coders, editors, advertisers, educators, etc. using it to do their jobs are participating in a short-term selloff of their profession to their CEOs, shareholders, etc. at the expense of large numbers of their colleagues or potential colleagues who will now never get jobs.
It’s like if someone invented the wheel and Sam Altman immediately patented it and sold it to Raytheon.
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).
making roguelike content. Mazes, monsters etc
