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1901 points l2silver | 2 comments | | HN request time: 0.449s | source

Maybe you've created your own AR program for wearables that shows the definition of a word when you highlight it IRL, or you've built a personal calendar app for your family to display on a monitor in the kitchen. Whatever it is, I'd love to hear it.
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jonplackett ◴[] No.35738707[source]
I made a gender swapping algorithm for my own use only. You put in any text and it outputs the exact same thing with all the genders reversed. Man to woman, he to she, Prince to princess, witch to wizard.

Then got a book deal to create a series of gender swapped illustrated books ‘Gender Swapped Fairy Tales’ and ‘Gender swapped Greek myths’

It seems like a simple enough task but gets complicated in weird ways. For example - his can swap to her or hers depending on the context. And her can swap to his of him depending on context.

The idea is to show the biases in the original stories that you are blind to because you’ve been reading them forever.

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1. RunSet ◴[] No.35758007[source]
Years ago, after I noticed that most adverbs are redundant, I began to write an ebook processor that would strip the adverbs out of ebooks before I read them to save time.

It turned out to require rather more semantic parsing than I expected. Maybe its worth revisiting with the advent of large language models.

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2. jonplackett ◴[] No.35790248[source]
Yeah a bit of LLM help would have saved me sooooooo much time.

I had to create a bunch of very convoluted rules based on whether the preceding and following two words were verbs, nouns, adverbs, end of a sentence etc and with those I could be sure I was right about 95% of the time.

Eg before a noun it’s always his or her.

But some really do require a little intelligence beyond grammar rules.

Eg for ‘It is definitely his’

Both swaps make sense grammatically:

‘It is definitely hers’ or ‘It is definitely her’

You’d need to understand the context to get it right.