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?
Learning languages is a great use case. I’m learning Mandarin right now, and being able to chat with a bot is really great practice for me. Another use case I’ve found handy is using it as a sounding board. The output it produces can stimulate new ideas in my own head, and it makes it a good exploration tool that let me pull on different threads of thought.
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.
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 competitions blind. 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.
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
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 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 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 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 hate questions like this due to 1 major issue.
A generative ai with “error free” Output, is very differently useful than one that isn’t.
Imagine an ai that would answer any questions objectively and unbiased, would that threaten job? Yeah. Would it be an huge improvement for human kind? Yeah.
Now imagine the same ai with a 10% bs rate, like how would you trust anything from it?
Currently generative ai is very very flawed. That is what we can evaluate and it is obvious. It is mostly useless as it produces mostly slop and consumes far more energy and water than you would expect.
A “better” one would be differently useful but just like killing half of the worlds population would help against climate change, the cost of getting there might not be what we want it to be, and it might not be worth it.
Current market practice, cost and results, lead me to say, it is effectively useless and probably a net negative for human kind. There is no legitimate usage as any usage legitimizes the market practice and cost given the results.
making roguelike content. Mazes, monsters etc
Making dynamic templates.
“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.
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.
Learning how to use Linux
Ha! I use it to write Ansible.
In my case, YAML is a tool of Satan and Ansible is its 2001-era minion of stupid, so when I need to write Ansible I let the robots do that for me and save my sanity.
I understand that will make me less likely to ever learn Ansible, if I use a bot to write the ‘code’ for me; and I consider that to be another benefit as I don’t need to develop a pot habit later, in the hopes of killing the brain cells that record my memory of learning Ansible.
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.
