I was trying to do a memory test to see how far back 3.5 could recall information from previous prompts, but it really doesn't seem to like making pseudorandom seeds. 😆
this post was submitted on 10 Dec 2023
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I regularly use ChatGPT to generate questions for junior high worksheets. You would be surprised how easily it fucks up "generate 20 multiple choice and 10 short answer questions". Most frequently at about 12-13 multiple choice it gives up and moves on. When I point out its flaw and ask it to finish generating the multiple choice, it continues to find new and unique ways to fuck up coming up with the remaining questions.
I would say it gives me simple count and recall errors in about 60% of my attempts to use it.
Consider keeping school the one place in a child's life where they aren't bombarded with AI-generated content.
I use it as a brainstorming tool. I haven't had a single question make it as-is to a student's worksheet. If the tool can't even count to 20 successfully, I'm not sure how anyone could trust it to generate meaningful questions for an ELA program.
Yet people claim it writes all their programming code...
I haven't had much luck with it writing stuff from scratch, but it does a great job of helping with debugging and figuring out why complex equations are doing what they're doing.
I put together a pretty complex shader recently, and gpt 3.5 did a great job of helping me figure out why it wasn't doing quite what I wanted.
I wouldn't trust it to code anything without my input, but it's great for advice and explanations and certain kinds of problem solving. Just don't assume it has the right answer, you still have to do the work
I've tried it with languages I don't know, and it managed to write simple working functions by just iterating over:
It seems to lose context easily, like if you ask it to fix one error, then another, it might revert the first fix, but asking it to fix both at once, tends to work.
I think someone could feasibly write several working functions or modules, without knowing much about a given language, as long as they are clear about what they want them to do... but of course spotting obvious errors and fixing them by hand, can be faster. Fixing integration problems is where I think it might get harder (haven't tried though, could be interesting).
Well, it's terrible at factual things and counting, and even when it comes to writing code it will often hallucinate APIs and libraries that don't exist - But when given very limited-scope, specific-domain problems with enough detail and direction, I've found it to be fairly competent as a rubber ducky for programming.
So far I've found ChatGPT to be most useful for: