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?
My last three usages of it:
- A translation
- Looking up what actors from Mars Attacks had shared work on another movie. I recognized that Pierce Brosnan and John Doe Baker had done Goldeneye and wondered if there were more.
- Name suggestions for a black and white cat - I got some funny suggestions like Oreo and a kick-ass suggestion for Domino
I just use it for fun. Like, my own personal iPhone backgrounds and stuff. Sometimes I’ll share them with friends or on Mastodon or whatever, but that’s about it.
Gemini is fun to dink around with. When it works…
I think genAI would be pretty neat for bit banging tests, aka. Throwing semi-random requests and/or signals at some device in the hopes of finding obscure edge-cases or security holes.
Fuzzing.
It’s kinda handy if you don’t want to take the time to write a boring email to your insurance or whatever.
Yeah that’s how I use it, essentially as an office intern. I get it to write cover letters and all the other mindless piddly crap I don’t want to do so I can free up some time to do creative things or read a book or whatever. I think it has some legit utility in that regard.
I sorta disagree though, based on my experience with llms.
The email it generates will need to be read carefully and probably edited to make sure it conveys your point accurately. Especially if it’s related to something as serious as insurance.
If you already have to specifically create the prompt, then scrutinize and edit the output, you might as well have just written the damn email yourself.
It seems only useful to write slop that doesn’t matter that only gets consumed by other machines and dutifully logged away in a slop container.
It does sort of solve the ‘blank page problem’ though IMO. It sometimes takes me ages to start something like a boring insurance letter because I open up LibreOffice and the blank page just makes me want to give up. If I have AI just fart out a letter and then I start to edit it, I’m already mid-project so it actually does save me some time in that way.
I agree. By the time I’m done, I’ve written most of the document. It gets me past the part where I procrastinate because I don’t know how to begin.
For us who are bad at writing though that’s exactly why we use it. I’m bad with greetings, structure, things that people expect and I’ve had people get offended at my emails because they come off as rude. I don’t notice those things. For that llms have been a godsend. Yes, I of course have to validate it, but it conveys the message I’m trying to usually
I get the point here but I think it’s the wrong approach. If you feel the email needs too much business fluff, just write it more casual and get to the point quicker.
Money. It’s always about money. But more seriously, I also wonder what’s the point since all my interactions with GenAI have been disappointment after disappointment. But I read Dev saying that it’s great at creating drafts
So what’s the point of it all?
To reduce wages.
Instead of using tech to reduce work and allow humans to thrive and make art, we use tech to make art and force humans into long hours of drudgery and repetitive bitch work just because CEOs like to watch other people suffer I guess.
For coding it works really well if you give it examples like “i have code that looked like this … And i made it to look like this … If i give you another piece of code that’s similar to the first can you convert it to the second for me”. Been great to reduce the amount of boring grunt work so I can focus on the more fun stuff
In C#, when programming save/load in video games, it can be super tedious. I am self taught and i didnt have the best resources, so the only way i could find to ensure its saving the correct variables was to manually input every single variable into a text file. I dont care if its plaintext, if people want to edit their save then more power to them. The issue is that there are potentially tens of hundreds of different variables that need to be saved for the gamestate to be accurately recreated.
So its really nice that i can just copy/paste my classes into gpt and give it the syntax for a single variable to be saved, then have it do the rest. I do have to browse through and ensure its actually getting all the variables, but it turns a potentially mindnumbing 4 hour long process into maybe a 20 minute one thats relatively engaging.
Also if you know a better way lmk. I read that you can simply hash the object into a text file and then unhash it, but afaik unhashing something is next to impossible and i could never figure it out anyways.
You could encrypt and decrypt it with keys.
Or you can do something simple like scramble the letters like a cypher, still able to edit manually but it wouldn’t be as readable and obvious what everything does.
Or you can can encode it, same issue as the last but they’ll have to know what it was encoded with to decode it before editing.
Or you can just turn it into bytes so the file is more awkward to work with.
You could probably mix a bunch of these together if you care enough. U don’t think any are THE standard and foolproof but they’re options
The goal isnt to encrypt the data, i dont care if its plaintext. The goal is to find a way to save an object in c# without having to save each individual variable.
Oh, in that case serialise it into json. Just use the json serialiser in system.text. it can turn any object in c# into a json object and you can deserialise them back into objects too.
Sorry i misinterpreted what you were asking for.
Yeah, that sounds a lot easier. Thanks
People keep meaning different things when they say “Generative AI”. Do you mean the tech in general, or the corporate AI that companies overhype and try to sell to everyone?
The tech itself is pretty cool. GenAI is already being used for quick subtitling and translating any form of media quickly. Image AI is really good at upscaling low-res images and making them clearer by filling in the gaps. Chatbots are fallible but they’re still really good for specific things like generating testing data or quickly helping you in basic tasks that might have you searching for 5 minutes. AI is huge in video games for upscaling tech like DLSS which can boost performance by running the game at a low resolution then upscaling it, the result is genuinely great. It’s also used to de-noise raytracing and show cleaner reflections.
Also people are missing the point on why AI is being invested in so much. No, I don’t think “AGI” is coming any time soon, but the reason they’re sucking in so much money is because of what it could be in 5 years. Saying AI is a waste of effort is like saying 3D video games are a waste of time because they looked bad in 1995. It will improve.
AI is huge in video games for upscaling tech like DLSS which can boost performance by running the game at a low resolution then upscaling it, the result is genuinely great
frame gen is blurry af and eats shit on any fast motion. rendering games at 640x480 and then scaling them to sensible resolutions is horrible artistic practice.
rendering games at 640x480 and then scaling them to sensible resolutions is horrible artistic practice.
Is that a reason a lot of pixel art games are looking like shit? I remember the era of 320x240 and 640x480 and the modern pixel art are looking noticeably worse.
that’s probably more to do with a lack of dithering and not using tubes anymore. lots of those older games looked better on crt than they do on digital
a good example is dracula’s eyes in symphony of the night, on crt the red bleeds over giving a really good red eyes effect
on lcd they are just single red pixels and look awful
I use it for parsing through legalese or terms and conditions. IT IS NOT PERFECT. I wouldn’t trust it ever over a lawyer. But it’s great for things like “Is there anything here that is extra unusual or weirdly anti-consumer or very bad for privacy?”. I think it’s great for that.
People here are just “it will take jobs it’s inherently evil”. They said the same about Photoshop, and computers before. I think there are evil uses for it sure, but that doesn’t mean that it has no valid usages
Great use for it!
I don’t use it for anything. I have had no involvement and it will stay that way.
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”.
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.
I have personally found it fantastic as a programming aid, and as a writing aid to write song lyrics. The art it creates lacks soul and any sense of being actually good but it’s great as a “oh I could do this cool thing” inspiration machine
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.
