I for one am super excited for what my kids, and the other children they grow up with, will do in their future careers! I am so proud and cheer this future on, it can’t come soon enough! This is software’s true purpose.
Someone tried to generate a retro hip-hop album cover image with AI, but the text is all nonsense, and humans would have to be hired to clean that AI slop
In about two years we've gone from "AI just generates rubbish where the text should be" to "AI spells things pretty wrong." This is largely down to generating a whole image with a textual element. Using a model like SDXL with a LORA like FOOOCUS to do inpainting and input image with a very rough approximation of the right text (added via MS Paint) you can get a pretty much perfect result. Give it another couple of years and the text generation will be spot on.
So yes, right now we need a human to either use the AI well, or to fix it afterwards. That's how technology always goes - something is invented, it's not perfect, humans need to fix the outputs, but eventually the human input diminishes to nothing.
First thing that came to mind when I started seeing news about companies needing developers to clean up AI code, was the part of Charlie and the Chocolate Factory where Charlie's father is fired from the toothpaste factory because they bought this new machine to produce the toothpaste, but then they re-wire him for an higher salary because the machine keeps breaking and they need someone to fix it.
AI (at least this form of AI) is not going to take our jobs away and let us all idle and poor, just like the milling machine or the plough didn't take people's jobs away and make everyone poor. it will enable us to do even greater things.
> creating this garbage consumes staggering amounts of water and electricity, contributing to emissions that harm the planet
This is highly dependent on which model is being used and what hardware it's running on. In particular, some older article claimed that the energy used to generate an image was equivalent to charging a mobile phone, but the actual energy required for a single image generation (SDXL, 25 steps) is about 35 seconds of running a 80W GPU.
How is this ironic? Carelessly AI-generated output (what we call "slop") is precisely that mediocre average you get before investing more in refining it through iteration. The problem isn't that additional work is needed, but that in many cases it is assumed that no additional work is needed and the first generation from a vague prompt is good enough.
There are really two observations here: 1. AI hasn't commoditized skilled labor. 2. AI is diluting/degrading media culture.
For the first, I'm waiting for more data, e.g. from the BLS. For the second, I think a new category of media has emerged. It lands somewhere near chiptune and deep-fried memes.
It's not so strange that e-commerce is the first thing that AI has visibly altered. Most "buy this thing" sites really just have one proposition at their core. The presentation is incidental. You can't have a website looking like it's still 2003, but you also don't really care what your 2025 shop front looks like. Your ads are there to draw attention, not to be works of art.
What does AI do, at its heart? It is literally trained to make things that can pass for what's ordinary. What's the best way to do that, normally? Make a bland thing that is straight down the middle of the road. Boring music, boring pictures, boring writing.
Now there are still some issues with common sense, due to the models lacking certain qualities that I'm sure experts are working on. Things like people with 8 fingers, lack of a model of physics, and so on. But we're already at a place where you could easily not spot a fake, especially while not paying attention.
So where does that leave us? AI is great at producing scaffolding. Lorem Ipsum, but for everything.
Humans come in to add a bit of agency. You have to take some risk when you're producing something, decisions have to be made. Taste, one might call it. And someone needs to be responsible for the decisions. Part of that is cleaning up obvious errors, but also part of it is customizing the skeleton so that it does what you want.
Is that so ironic? Think of humans in factories fishing out faulty items, where formerly they would perhaps be the artisans that made the product in the first place.
"Think of humans in factories fishing out faulty items, where formerly they would perhaps be the artisans that made the product in the first place."
But according to this Indian service provider's website, the workers (Indians?) are hired to "clean up" not "fish out" the "faulty items"
Imagine a factory where the majority of items produced are faulty and are easily "fished out". But instead of discarding them,^1 workers have to fix each one
We have been doing this for decades. I was hired to correct and train speech recognition and OCR programs like 20 years ago. A friend of mine corrected geolocated tags.
In the history of AI systems you basically had people inputing Prolog rules in "smart" systems or programmers hardcoding rules is programs like ELIZA or Generalised Problem Solvers.
I got shudders just re-reading it when I came across:
'“It’s too late to vid your wife,” the fasrad said. “There are
three emergency-rockets in the stern; if you want, I’ll fire them
off in the hope of attracting a passing military transport.”'
From the case that the article is presenting, I think LLMs are acting as a validation step – the average person who doesn't know how to code creates a minimal, LLM-spaghetti system (e.g. a restaurant menu website) with ChatGPT, validate if this is something that they need, iterate on it, create a specification, and then bring in an actual (costly) engineer that can fix and improve the system.
There's a lot of LLM byproducts that leave us in bad taste (hate all of the LLM slop on the internet), but I don't think this is one of them.
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[ 2.7 ms ] story [ 54.1 ms ] threadIn about two years we've gone from "AI just generates rubbish where the text should be" to "AI spells things pretty wrong." This is largely down to generating a whole image with a textual element. Using a model like SDXL with a LORA like FOOOCUS to do inpainting and input image with a very rough approximation of the right text (added via MS Paint) you can get a pretty much perfect result. Give it another couple of years and the text generation will be spot on.
So yes, right now we need a human to either use the AI well, or to fix it afterwards. That's how technology always goes - something is invented, it's not perfect, humans need to fix the outputs, but eventually the human input diminishes to nothing.
AI (at least this form of AI) is not going to take our jobs away and let us all idle and poor, just like the milling machine or the plough didn't take people's jobs away and make everyone poor. it will enable us to do even greater things.
This is highly dependent on which model is being used and what hardware it's running on. In particular, some older article claimed that the energy used to generate an image was equivalent to charging a mobile phone, but the actual energy required for a single image generation (SDXL, 25 steps) is about 35 seconds of running a 80W GPU.
There are really two observations here: 1. AI hasn't commoditized skilled labor. 2. AI is diluting/degrading media culture.
For the first, I'm waiting for more data, e.g. from the BLS. For the second, I think a new category of media has emerged. It lands somewhere near chiptune and deep-fried memes.
LLMs are not AI. Machine learning is more useful. Perhaps they will evolve or perhaps they will prove a dead end.
What does AI do, at its heart? It is literally trained to make things that can pass for what's ordinary. What's the best way to do that, normally? Make a bland thing that is straight down the middle of the road. Boring music, boring pictures, boring writing.
Now there are still some issues with common sense, due to the models lacking certain qualities that I'm sure experts are working on. Things like people with 8 fingers, lack of a model of physics, and so on. But we're already at a place where you could easily not spot a fake, especially while not paying attention.
So where does that leave us? AI is great at producing scaffolding. Lorem Ipsum, but for everything.
Humans come in to add a bit of agency. You have to take some risk when you're producing something, decisions have to be made. Taste, one might call it. And someone needs to be responsible for the decisions. Part of that is cleaning up obvious errors, but also part of it is customizing the skeleton so that it does what you want.
But according to this Indian service provider's website, the workers (Indians?) are hired to "clean up" not "fish out" the "faulty items"
Imagine a factory where the majority of items produced are faulty and are easily "fished out". But instead of discarding them,^1 workers have to fix each one
1. The energy costs of production are substantial
In the history of AI systems you basically had people inputing Prolog rules in "smart" systems or programmers hardcoding rules is programs like ELIZA or Generalised Problem Solvers.
... about when Tesla delivers full self driving.
https://en.wikipedia.org/wiki/Sales_Pitch_(short_story)
I got shudders just re-reading it when I came across:
'“It’s too late to vid your wife,” the fasrad said. “There are three emergency-rockets in the stern; if you want, I’ll fire them off in the hope of attracting a passing military transport.”'
...which sounds exactly like ChatGPT5.
Stopped reading there. The author is very biased and out of touch.
There's a lot of LLM byproducts that leave us in bad taste (hate all of the LLM slop on the internet), but I don't think this is one of them.