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Having poked at ChatGPT a bit, I'm not particularly surprised. If I think of a job it could potentially do that I understand, like graphic designer, Chat GPT (the only LLM/diffusion router I've personally tried) is about as good as a drunk college student, but much, much faster. There are some use cases for that -- the sort of project that's basically fake and nobody actually cares about or gets any value out of, but someone said it should be done. "I'll have GPT do that" basically means that it's considered meaningless drivel no matter who does it.
I suppose at some point it'll be able to make materials not only quickly, but also well -- but that day is not today.
"I would like an illustration for my fanfiction/roleplaying character. No, I'm not hiring an artist--I'm doing this for free, after all."
Sure. That's in the drunk college student, but way way faster realm. Nice to have, provides consumer surplus at free tier or $20/month, but probably not $200/month.
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How about proofreading a long document? You can get LLMs to go through page by page and check for errors like sate instead of state, pubic instead of public, dependent vs dependant...
That has to be most boring and obvious application. There are heaps more.
Or how about making making cartoons? These aren't too bad: https://x.com/emollick/status/1920700991298572682
Word processors already look for typos that are actual words, but don't make sense in the current context, without applying AI. More and better autocorrect is about in line with the original thesis -- they're good at spreadsheet scale tasks, which is useful but not a huge amount of a given person's job. I'm not completely sure what professional editors do, but I think it's probably a bit deeper than looking for typos.
Perhaps I was too flippant with the 'There are heaps more' applications for AI. I get this newsletter from alexander kruel almost daily where he gives a tonne of links about what people are using AI for. For example:
Interviewing people in the Phillipines (better than humans apparently). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5395709
62% of coders in this survey are using it: https://survey.stackoverflow.co/2024/ai
76% of doctors are using it: https://www.fiercehealthcare.com/special-reports/some-doctors-are-using-public-generative-ai-tools-chatgpt-clinical-decisions-it
It's thought that the US govt might've decided what tariffs to impose via AI: https://www.newsweek.com/donald-trump-tariffs-chatgpt-2055203
It goes on and on and on...
I personally used it for proofreading and indeed it can't do all of an editor's job. Editors do lots of highly visual tasks managing how words fit on the page in ways that AI isn't so good at. But it can do some of an editor's job. It can do much of a cartoonist's job (Ben Garrison is in the clear for now with his ultra-wordy cartoons?). I think it's more than fast drunk college student and more than meaningless drivel.
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Spellcheckers and grammar checkers have been a thing for ages in word processors, without throwing massive amounts of compute at it.
And none of them will fix errors like 'pubic law'. It won't notice when 'losses of profits' should be 'losses or profits'. It won't call out a date of 20008.
It does work but I think to do proper proofreading on an important document, you're going to need to supervise it, feed it your house style etc, and then check all its suggestions, or have someone competent who understands the subject matter do the same. Then you'll probably need to feed all the changes manually into InDesign (an LLM might be integrated into Adobe suite to be fair, I haven't used it lately).
By the time you've done that, maybe you'll have saved some time but I don't see it as that big a deal.
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If you put the sentence "Ohio law states that you may not loiter less than three get away from a pubic building." into Google docs, it will correct "get" to "feet", and "pubic" to "public". This has been the case for around 15 years.
OK, how about losses or profits? Or 20008? I cited pubic law because it's funny, the other two are actually real examples from what I was getting it to do.
I highly doubt Google docs could do tasks that require contextual understanding without some kind of LLM.
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Sure it is incrementally better on what we already have. The problem I'm trying to illuminate with it is that is the compute worth the provided value? It is hardly taking away a job from anyone doing the proof reading, it is an improved version of what we already have.
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Software spell check (on early computers at least) required a cute algorithm --- the Bloom filter --- to work reasonably efficiently. Actually checking each typed word against the whole dictionary wasn't (and likely isn't) practical, but a statistical guess of correctness is good enough.
Sir, you were in a coma and woke up in the future.
Checking the inclusion of an element in a hashtable is a constant-time operation, or at least constant-ish -- you still need to compare the elements so it's gonna be proportional to the size of the largest one. So the limiting factor here is memory. I suspect keeping a dictionary resident in RAM on a home PC shouldn't have been a big deal for at least 25 years if not more.
I think there should be an even longer period where it would be fine to keep the dictionary on disk and access it for every typed word, because no human could plausibly type fast enough to outpace the throughput of random reads from a hard disk. No idea how long into the past that era would stretch.
I still get surprised at how fast computers can do basic tasks.
A few weeks ago, I had to compare some entries in a .csv list to the filenames that were buried a few layers deep in some subfolders. It went through the thousands of items in an instant. I didn't even bother saving the output because I could regenerate it as fast as doubleclicking a file (or faster if it has to do something silly like opening Microsoft Word).
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Heh, I'm old enough to have owned a pocket electronic spell checker at one point. The hash table seems the right way to do it these days, but it will take up more memory (640K shakes fist at cloud). And sometimes you do want to scan faster than the user types, like opening a new large file.
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