Not OP, but I'd start with a one-click way to "install" the PWA apps using an API, e.g. with a banner (like on Android) instead of an item in the share menu.
A single file with a few functions, it seemed a good test to convert it to some other languages with GPT-4 (I tried Python and Ruby). Unfortunately, my access to GPT-4 is limited to the 2k version, and the first function is 4,500 tokens (800 minified, but losing names, comments, and probably the quality of the conversion).
With some language-independent tests in such a repository, you might be able to semi-automatically convert the code into different languages, and continue with code scanning and optimizations.
Your tl;dr shows how text+reader_context can generate the best summaries. Those 5 words are perfect if you know what they did for ChatGPT.
This makes me think that to get high quality summaries:
1) they have to be generated for each individual reader
2) the AI should know what the reader knows
You achieved 2 by imagining what HN people may already know, but the ultimate goal would be to know what the individual reader knows.
And this chain of thought leads to
- Perhaps all AI output should be generated on the fly for the end user with full (relevant and compressed) context.
- Giving AI what we know is extremely dangerous if someone wants to use it for something bad (so we really, really need local AI).
Sure, these are all things people in the industry already know, but there must be a lot of people like me who are just now thinking about it.
A note: "^2" added humor to make the reading light with very few bytes. Perhaps the machine would do this too, if the reader wants.
Only few things make me very very excited and sometimes very very sad like some AI developments. But the exciting part wins for now!