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?
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.
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.
“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.
In the context of programming:
- Good for boilerplate code and variables naming when what you want is for the model to regurgitate things it has seen before.
- Short pieces of code where it’s much faster to verify that the code is correct than to write the code yourself.
- Sometimes, I know how to do something but I’ll wait for Copilot to give me a suggestion, and if it looks like what I had in mind, it gives me extra confidence in the correctness of my solution. If it looks different, then it’s a sign that I might want to rethink it.
- It sometimes gives me suggestions for APIs that I’m not familiar with, prompting me to look them up and learn something new (assuming they exist).
There’s also some very cool applications to game AI that I’ve seen, but this is still in the research realm and much more niche.
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.
