Gallup polling says 1% of people in the US didn't believe in god in 1967, 17% in 2022. Of those 17% i'd imagine many believed at some point (or went to church/temple/...), these people don't really behave like a 'pure' atheist would. They're very much still influenced by the religious ideas they grew up in. So yes it's a rather new thing if you're thinking about society.
I think your problem is you don't seem to be aware of history before 1967 or society outside of the US. Your local community college might offer some courses in history and sociology.
That’s fair — and I agree if enough context exists.
The key limitation is that a raw bank transaction usually contains very little semantic information: amount, merchant name, date. From that alone, an LLM can only guess based on patterns or prior behavior, not actually know what the expense was for.
“$100 at a supermarket” could be groceries, pet food, a household item, or something work-related. An LLM can infer probabilities once it has enough historical data and feedback, but that still means the user has to correct or confirm things at some point.
So I see LLMs as very helpful for assisting categorization (suggestions, defaults, learning over time), but they can’t fully replace intent unless the underlying data becomes richer than what bank statements provide today.
Is there any chance it could become richer? What governs the content of credit card and bank statements? Is there anyone pushing for them to be more useful?
I think (granted, this is from a quick bit of research so I could be wildly wrong) - the message you see in your credit card app with a transaction is usually mainly the merchant name and location which is part of ISO 8583, so it may be a bit hard to extend it to include an arbitrary message in a way that works without merchants having to replace card reader/POS systems en-masse.
No, no one has ever known anything, and every day people are born knowing even less. This is a strangely aggressive way to share this interesting information, especially for MacOS programming, a platform requiring such byzantine arcane knowledge I'm amazed people write anything for it at all. At least for Win32 people wrote books you could buy and not blog posts.
Anyway, thank you for the introduction to the very cool SwiftScripting project [0], extracting programmable interfaces directly from app bundles. It's just like COM, right? nice to see MacOS catching up (/ragebait)
Also, FYI the interesting part about the post is getting the extracted code in type-safe Swift code. Getting the extracted code for ObjC is trivial and any seasoned macOS developer should already know how to do it.
It is trivial to append to files without reading them. Also, no AI provider even wants your secrets, they are a liability. Do whatever you want though, I'm not here to convince you of anything.
This is probably different between startups and enterprises. My background is purely startups, and I can't imagine not having access to 100% of the code for the company I work.
> Among children whose parents read to them frequently at age three, the link between infant screen time and altered brain development was significantly weakened.
It sounds a bit like the problem might not be so much "heavy screen time" as "heavy screen time, plus no alternative stimulation". Not defending heavy screen time at all, just thought it was an interesting tidbit.
I would tend to agree with that. I can even see in my own kids changes in behavior when external factors affect my own ability to be attentive to my kids.
reply